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Sample records for based diagnostic model

  1. Overcoming limitations of model-based diagnostic reasoning systems

    Science.gov (United States)

    Holtzblatt, Lester J.; Marcotte, Richard A.; Piazza, Richard L.

    1989-01-01

    The development of a model-based diagnostic system to overcome the limitations of model-based reasoning systems is discussed. It is noted that model-based reasoning techniques can be used to analyze the failure behavior and diagnosability of system and circuit designs as part of the system process itself. One goal of current research is the development of a diagnostic algorithm which can reason efficiently about large numbers of diagnostic suspects and can handle both combinational and sequential circuits. A second goal is to address the model-creation problem by developing an approach for using design models to construct the GMODS model in an automated fashion.

  2. DIAGNOSTIC TEST FOR GARCH MODELS BASED ON ABSOLUTE RESIDUAL AUTOCORRELATIONS

    Directory of Open Access Journals (Sweden)

    Farhat Iqbal

    2013-10-01

    Full Text Available In this paper the asymptotic distribution of the absolute residual autocorrelations from generalized autoregressive conditional heteroscedastic (GARCH models is derived. The correct asymptotic standard errors for the absolute residual autocorrelations are also obtained and based on these results, a diagnostic test for checking the adequacy of GARCH-type models are developed. Our results do not depend on the existence of higher moments and is therefore robust under heavy-tailed distributions.

  3. A Probabilistic Rain Diagnostic Model Based on Cyclone Statistical Analysis

    OpenAIRE

    Iordanidou, V.; A. G. Koutroulis; I. K. Tsanis

    2014-01-01

    Data from a dense network of 69 daily precipitation gauges over the island of Crete and cyclone climatological analysis over middle-eastern Mediterranean are combined in a statistical approach to develop a rain diagnostic model. Regarding the dataset, 0.5 × 0.5, 33-year (1979–2011) European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA-Interim) is used. The cyclone tracks and their characteristics are identified with the aid of Melbourne University algorithm (MS scheme). T...

  4. Diagnostic markers based on a computational model of lipoprotein metabolism

    NARCIS (Netherlands)

    Schalkwijk, D.B. van; Ommen, B. van; Freidig, A.P.; Greef, J. van der; Graaf, A.A. de

    2011-01-01

    Abstract Background: Dyslipidemia is an important risk factor for cardiovascular disease and type II diabetes. Lipoprotein diagnostics, such as LDL cholesterol and HDL cholesterol, help to diagnose these diseases. Lipoprotein profile measurements could improve lipoprotein diagnostics, but interpreta

  5. Developing computational model-based diagnostics to analyse clinical chemistry data

    NARCIS (Netherlands)

    Schalkwijk, D.B. van; Bochove, K. van; Ommen, B. van; Freidig, A.P.; Someren, E.P. van; Greef, J. van der; Graaf, A.A. de

    2010-01-01

    This article provides methodological and technical considerations to researchers starting to develop computational model-based diagnostics using clinical chemistry data.These models are of increasing importance, since novel metabolomics and proteomics measuring technologies are able to produce large

  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 that...

  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. 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

  9. 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.

  10. 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

  11. Bayesian modeling and inference for diagnostic accuracy and probability of disease based on multiple diagnostic biomarkers with and without a perfect reference standard.

    Science.gov (United States)

    Jafarzadeh, S Reza; Johnson, Wesley O; Gardner, Ian A

    2016-03-15

    The area under the receiver operating characteristic (ROC) curve (AUC) is used as a performance metric for quantitative tests. Although multiple biomarkers may be available for diagnostic or screening purposes, diagnostic accuracy is often assessed individually rather than in combination. In this paper, we consider the interesting problem of combining multiple biomarkers for use in a single diagnostic criterion with the goal of improving the diagnostic accuracy above that of an individual biomarker. The diagnostic criterion created from multiple biomarkers is based on the predictive probability of disease, conditional on given multiple biomarker outcomes. If the computed predictive probability exceeds a specified cutoff, the corresponding subject is allocated as 'diseased'. This defines a standard diagnostic criterion that has its own ROC curve, namely, the combined ROC (cROC). The AUC metric for cROC, namely, the combined AUC (cAUC), is used to compare the predictive criterion based on multiple biomarkers to one based on fewer biomarkers. A multivariate random-effects model is proposed for modeling multiple normally distributed dependent scores. Bayesian methods for estimating ROC curves and corresponding (marginal) AUCs are developed when a perfect reference standard is not available. In addition, cAUCs are computed to compare the accuracy of different combinations of biomarkers for diagnosis. The methods are evaluated using simulations and are applied to data for Johne's disease (paratuberculosis) in cattle.

  12. 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...

  13. 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.

  14. 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.

  15. Development of class model based on blood biochemical parameters as a diagnostic tool of PSE meat.

    Science.gov (United States)

    Qu, Daofeng; Zhou, Xu; Yang, Feng; Tian, Shiyi; Zhang, Xiaojun; Ma, Lin; Han, Jianzhong

    2017-06-01

    A fast, sensitive and effective method based on the blood biochemical parameters for the detection of PSE meat was developed in this study. A total of 200 pigs were slaughtered in the same slaughterhouse. Meat quality was evaluated by measuring pH, electrical conductivity and color at 45min, 2h and 24h after slaughtering in M. longissimus thoracis et lumborum (LD). Blood biochemical parameters were determined in blood samples collected during carcass bleeding. Principal component analysis (PCA) biplot showed that high levels of exsanguination Creatine Kinase, Lactate Dehydrogenase, Aspertate aminotransferase, blood glucose and lactate were associated with the PSE meat, and the five biochemical parameters were found to be good indicators of PSE meat Discriminant function analysis (DFA) was able to clearly identify PSE meat using the five biochemical parameters as input data, and the class model is an effective diagnostic tool in pigs which can be used to detect the PSE meat and reduce economic loss for the company.

  16. Modeling Diagnostic Assessments with Bayesian Networks

    Science.gov (United States)

    Almond, Russell G.; DiBello, Louis V.; Moulder, Brad; Zapata-Rivera, Juan-Diego

    2007-01-01

    This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…

  17. 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…

  18. Learning Item-Attribute Relationship in Q-Matrix Based Diagnostic Classification Models

    CERN Document Server

    Liu, Jingchen; Ying, Zhiliang

    2011-01-01

    Recent surge of interests in cognitive assessment has led to the developments of novel statistical models for diagnostic classification. Central to many such models is the well-known Q-matrix, which specifies the item-attribute relationship. This paper proposes a principled estimation procedure for the Q-matrix and related model parameters. Desirable theoretic properties are established through large sample analysis. The proposed method also provides a platform under which important statistical issues, such as hypothesis testing and model selection, can be addressed.

  19. Testing Expert-Based versus Student-Based Cognitive Models for a Grade 3 Diagnostic Mathematics Assessment

    Science.gov (United States)

    Roduta Roberts, Mary; Alves, Cecilia B.; Chu, Man-Wai; Thompson, Margaret; Bahry, Louise M.; Gotzmann, Andrea

    2014-01-01

    The purpose of this study was to evaluate the adequacy of three cognitive models, one developed by content experts and two generated from student verbal reports for explaining examinee performance on a grade 3 diagnostic mathematics test. For this study, the items were developed to directly measure the attributes in the cognitive model. The…

  20. Diagnostic evaluation of distributed physically based model at the REW scale (THREW) using rainfall-runoff event analysis

    Science.gov (United States)

    Tian, F.; Sivapalan, M.; Li, H.; Hu, H.

    2007-12-01

    The importance of diagnostic analysis of hydrological models is increasingly recognized by the scientific community (M. Sivapalan, et al., 2003; H. V. Gupta, et al., 2007). Model diagnosis refers to model structures and parameters being identified not only by statistical comparison of system state variables and outputs but also by process understanding in a specific watershed. Process understanding can be gained by the analysis of observational data and model results at the specific watershed as well as through regionalization. Although remote sensing technology can provide valuable data about the inputs, state variables, and outputs of the hydrological system, observational rainfall-runoff data still constitute the most accurate, reliable, direct, and thus a basic component of hydrology related database. One critical question in model diagnostic analysis is, therefore, what signature characteristic can we extract from rainfall and runoff data. To this date only a few studies have focused on this question, such as Merz et al. (2006) and Lana-Renault et al. (2007), still none of these studies related event analysis with model diagnosis in an explicit, rigorous, and systematic manner. Our work focuses on the identification of the dominant runoff generation mechanisms from event analysis of rainfall-runoff data, including correlation analysis and analysis of timing pattern. The correlation analysis involves the identification of the complex relationship among rainfall depth, intensity, runoff coefficient, and antecedent conditions, and the timing pattern analysis aims to identify the clustering pattern of runoff events in relation to the patterns of rainfall events. Our diagnostic analysis illustrates the changing pattern of runoff generation mechanisms in the DMIP2 test watersheds located in Oklahoma region, which is also well recognized by numerical simulations based on TsingHua Representative Elementary Watershed (THREW) model. The result suggests the usefulness of

  1. Operational modelling to guide implementation and scale-up of diagnostic tests within the health system: exploring opportunities for parasitic disease diagnostics based on example application for tuberculosis.

    Science.gov (United States)

    Langley, Ivor; Adams, Emily; Doulla, Basra; Squire, S Bertel

    2014-12-01

    Research and innovation in the diagnosis of infectious and parasitic diseases has led to the development of several promising diagnostic tools, for example in malaria there is extensive literature concerning the use of rapid diagnostic tests. This means policymakers in many low and middle income countries need to make difficult decisions about which of the recommended tools and approaches to implement and scale-up. The test characteristics (e.g. sensitivity and specificity) of the tools alone are not a sufficient basis on which to make these decisions as policymakers need to also consider the best combination of tools, whether the new tools should complement or replace existing diagnostics and who should be tested. Diagnostic strategies need dovetailing to different epidemiology and structural resource constraints (e.g. existing diagnostic pathways, human resources and laboratory capacity). We propose operational modelling to assist with these complex decisions. Projections of patient, health system and cost impacts are essential and operational modelling of the relevant elements of the health system could provide these projections and support rational decisions. We demonstrate how the technique of operational modelling applied in the developing world to support decisions on diagnostics for tuberculosis, could in a parallel way, provide useful insights to support implementation of appropriate diagnostic innovations for parasitic diseases.

  2. A diagnostic interface for the ICOsahedral Non-hydrostatic (ICON) modelling framework based on the Modular Earth Submodel System (MESSy v2.50)

    Science.gov (United States)

    Kern, Bastian; Jöckel, Patrick

    2016-10-01

    Numerical climate and weather models have advanced to finer scales, accompanied by large amounts of output data. The model systems hit the input and output (I/O) bottleneck of modern high-performance computing (HPC) systems. We aim to apply diagnostic methods online during the model simulation instead of applying them as a post-processing step to written output data, to reduce the amount of I/O. To include diagnostic tools into the model system, we implemented a standardised, easy-to-use interface based on the Modular Earth Submodel System (MESSy) into the ICOsahedral Non-hydrostatic (ICON) modelling framework. The integration of the diagnostic interface into the model system is briefly described. Furthermore, we present a prototype implementation of an advanced online diagnostic tool for the aggregation of model data onto a user-defined regular coarse grid. This diagnostic tool will be used to reduce the amount of model output in future simulations. Performance tests of the interface and of two different diagnostic tools show, that the interface itself introduces no overhead in form of additional runtime to the model system. The diagnostic tools, however, have significant impact on the model system's runtime. This overhead strongly depends on the characteristics and implementation of the diagnostic tool. A diagnostic tool with high inter-process communication introduces large overhead, whereas the additional runtime of a diagnostic tool without inter-process communication is low. We briefly describe our efforts to reduce the additional runtime from the diagnostic tools, and present a brief analysis of memory consumption. Future work will focus on optimisation of the memory footprint and the I/O operations of the diagnostic interface.

  3. Development of a Diagnostic and Remedial Learning System Based on an Enhanced Concept--Effect Model

    Science.gov (United States)

    Panjaburees, Patcharin; Triampo, Wannapong; Hwang, Gwo-Jen; Chuedoung, Meechoke; Triampo, Darapond

    2013-01-01

    With the rapid advances in computer technology during recent years, researchers have demonstrated the pivotal influences of computer-assisted diagnostic systems on student learning performance improvement. This research aims to develop a Diagnostic and Remedial Learning System (DRLS) for an algebra course in a Thai lower secondary school context…

  4. The Meta-Ontology Model of the Fishdisease Diagnostic Knowledge Based on Owl

    Science.gov (United States)

    Shi, Yongchang; Gao, Wen; Hu, Liang; Fu, Zetian

    For improving available and reusable of knowledge in fish disease diagnosis (FDD) domain and facilitating knowledge acquisition, an ontology model of FDD knowledge was developed based on owl according to FDD knowledge model. It includes terminology of terms in FDD knowledge and hierarchies of their class.

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

    Directory of Open Access Journals (Sweden)

    Jang-Han Bae

    2013-01-01

    Full Text Available 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 evolving tonometric mechanism at a constant velocity and defined the pulse depth index as the optimal SD where the largest pulse amplitude was observed. By calculating the pulse depth index for 18 volunteers, we showed that the pulse was deepest at Cheok (significance level: P<0.01, while no significant difference was found between Chon and Gwan. In contrast, the two CP-based models estimated that the pulse was shallowest at Gwan (P<0.05. For the repeated measures, the new SD-based model showed a smaller coefficient of variation (CV≈7.6% than the two CP-based models (CV≈13.5% and 12.3%, resp.. The SD-based pulse depth assessment is not sensitive to the complex geometry around the palpation locations and temperature variation of contact sensors, which allows cost-effective sensor technology.

  6. The role of residence time in diagnostic models of global carbon storage capacity: model decomposition based on a traceable scheme.

    Science.gov (United States)

    Yizhao, Chen; Jianyang, Xia; Zhengguo, Sun; Jianlong, Li; Yiqi, Luo; Chengcheng, Gang; Zhaoqi, Wang

    2015-11-06

    As a key factor that determines carbon storage capacity, residence time (τE) is not well constrained in terrestrial biosphere models. This factor is recognized as an important source of model uncertainty. In this study, to understand how τE influences terrestrial carbon storage prediction in diagnostic models, we introduced a model decomposition scheme in the Boreal Ecosystem Productivity Simulator (BEPS) and then compared it with a prognostic model. The result showed that τE ranged from 32.7 to 158.2 years. The baseline residence time (τ'E) was stable for each biome, ranging from 12 to 53.7 years for forest biomes and 4.2 to 5.3 years for non-forest biomes. The spatiotemporal variations in τE were mainly determined by the environmental scalar (ξ). By comparing models, we found that the BEPS uses a more detailed pool construction but rougher parameterization for carbon allocation and decomposition. With respect to ξ comparison, the global difference in the temperature scalar (ξt) averaged 0.045, whereas the moisture scalar (ξw) had a much larger variation, with an average of 0.312. We propose that further evaluations and improvements in τ'E and ξw predictions are essential to reduce the uncertainties in predicting carbon storage by the BEPS and similar diagnostic models.

  7. The diagnostics of diabetes mellitus based on ensemble modeling and hair/urine element level analysis.

    Science.gov (United States)

    Chen, Hui; Tan, Chao; Lin, Zan; Wu, Tong

    2014-07-01

    The aim of the present work focuses on exploring the feasibility of analyzing the relationship between diabetes mellitus and several element levels in hair/urine specimens by chemometrics. A dataset involving 211 specimens and eight element concentrations was used. The control group was divided into three age subsets in order to analyze the influence of age. It was found that the most obvious difference was the effect of age on the level of zinc and iron. The decline of iron concentration with age in hair was exactly consistent with the opposite trend in urine. Principal component analysis (PCA) was used as a tool for a preliminary evaluation of the data. Both ensemble and single support vector machine (SVM) algorithms were used as the classification tools. On average, the accuracy, sensitivity and specificity of ensemble SVM models were 99%, 100%, 99% and 97%, 89%, 99% for hair and urine samples, respectively. The findings indicate that hair samples are superior to urine samples. Even so, it can provide more valuable information for prevention, diagnostics, treatment and research of diabetes by simultaneously analyzing the hair and urine samples.

  8. Cognitive Diagnostic Modeling Using R

    Science.gov (United States)

    Ravand, Hamdollah

    2015-01-01

    Cognitive diagnostic models (CDM) have been around for more than a decade but their application is far from widespread for mainly two reasons: (1) CDMs are novel, as compared to traditional IRT models. Consequently, many researchers lack familiarity with them and their properties, and (2) Software programs doing CDMs have been expensive and not…

  9. 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.

  10. 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.

  11. Diagnostic X-ray shielding design based on an empirical model of photon attenuation

    Energy Technology Data Exchange (ETDEWEB)

    Archer, B.R.; Thornby, J.I.; Bushong, S.C.

    1983-05-01

    A series of nomograms that simplify determination of diagnostic X-ray shielding requirements with lead are presented. All recommendations of the NCRP, except that to ''add one half value layer'' in determining secondary barriers, were followed in the production of these curves. For secondary barriers, the shielding required to reduce the weekly exposure to the applicable MPD has been determined. This eliminates the over-shielding inherent in the ''add one HVL'' approximation and allows a variety of more cost effective materials to be considered for secondary barriers.

  12. Diagnostic x-ray shielding design based on an empirical model of photon attenuation

    Energy Technology Data Exchange (ETDEWEB)

    Archer, B.R. (Radiation Safety Office, Houston, TX); Thornby, J.I.; Bushong, S.C.

    1983-05-01

    A series of nomograms that simplify determination of diagnostic X-ray shielding requirements with lead are presented. All recommendations of the NCRP, except that to ''add one half value layer'' in determining secondary barriers, were followed in the production of these curves. For secondary barriers, the shielding required to reduce the weekly exposure to the applicable MPD has been determined. This eliminates the over-shielding inherent in the ''add one HVL'' approximation and allows a variety of more cost effective materials to be considered for secondary barriers.

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. A support vector machine model provides an accurate transcript-level-based diagnostic for major depressive disorder

    Science.gov (United States)

    Yu, J S; Xue, A Y; Redei, E E; Bagheri, N

    2016-01-01

    Major depressive disorder (MDD) is a critical cause of morbidity and disability with an economic cost of hundreds of billions of dollars each year, necessitating more effective treatment strategies and novel approaches to translational research. A notable barrier in addressing this public health threat involves reliable identification of the disorder, as many affected individuals remain undiagnosed or misdiagnosed. An objective blood-based diagnostic test using transcript levels of a panel of markers would provide an invaluable tool for MDD as the infrastructure—including equipment, trained personnel, billing, and governmental approval—for similar tests is well established in clinics worldwide. Here we present a supervised classification model utilizing support vector machines (SVMs) for the analysis of transcriptomic data readily obtained from a peripheral blood specimen. The model was trained on data from subjects with MDD (n=32) and age- and gender-matched controls (n=32). This SVM model provides a cross-validated sensitivity and specificity of 90.6% for the diagnosis of MDD using a panel of 10 transcripts. We applied a logistic equation on the SVM model and quantified a likelihood of depression score. This score gives the probability of a MDD diagnosis and allows the tuning of specificity and sensitivity for individual patients to bring personalized medicine closer in psychiatry. PMID:27779627

  18. 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.

  19. Toward theory-based diagnostic categories.

    Science.gov (United States)

    Gordon, M

    1990-01-01

    As a social institution, nursing has a responsibility to society for the development of knowledge in the areas described by nursing diagnoses. This article focuses on the need for developing the theoretical basis of each diagnostic category. Diagnoses are viewed as summarizations of underlying conceptual models for interpreting observations, and as such, they provide a perspective for understanding and thinking about a set of clinical observations. At present many diagnostic concepts do not meet this standard and suggest primitive, pretheoretical ideas with a minimal knowledge base. The importance of having valid and reliable diagnostic categories for use in making clinical judgements and as a focus for care planning is discussed. A cycle of development is outlined in three phases: diagnostic concept identification, concept analysis-model development, and construction/reconstruction of diagnostic categories. It is suggested that a useful category captures the conceptual understanding and state of knowledge development about a phenomena in its (a) name, (b) definition, and (c) cluster of defining characteristics.

  20. Accuracy of Reaction Cross Section for Exotic Nuclei in Glauber Model Based on MCMC Diagnostics

    Science.gov (United States)

    Rueter, Keiti; Novikov, Ivan

    2017-01-01

    Parameters of a nuclear density distribution for an exotic nuclei with halo or skin structures can be determined from the experimentally measured reaction cross-section. In the presented work, to extract parameters such as nuclear size information for a halo and core, we compare experimental data on reaction cross-sections with values obtained using expressions of the Glauber Model. These calculations are performed using a Markov Chain Monte Carlo algorithm. We discuss the accuracy of the Monte Carlo approach and its dependence on k*, the power law turnover point in the discreet power spectrum of the random number sequence and on the lag-1 autocorrelation time of the random number sequence.

  1. 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

  2. Clinically based diagnostic wax-up for optimal esthetics: the diagnostic mock-up.

    Science.gov (United States)

    Simon, Harel; Magne, Pascal

    2008-05-01

    A diagnostic wax-up can enhance the predictability of treatment by modeling the desired result in wax prior to treatment. It is critical to correlate the wax-up to the patient to avoid a result that appears optimal on the casts but does not correspond to the patient's smile. This article reviews the applications and techniques for clinically based diagnostic wax-up, and focuses on the diagnostic mock-up philosophy as a means to obtain predictable esthetics and function.

  3. AI-Based Diagnostic Shell

    Directory of Open Access Journals (Sweden)

    R. L. Verma

    1989-01-01

    Full Text Available This paper datails the design and implementation of an AI-based diagnostic shell. The shell has a user-interface which takes in the complaint and aids the user throughout the consultation. The 'expert knowledge' is acquired and encoded in the form of 'IF-THEN' rules, The control mechanism routes through the rules chaining first backwards to identify a fault and then forwards to confirm it.Explanation facilities have been provided to enable the user query the reason for any question asked, a facility to go back and re-answer any previous question, and a trace and explanation of the path of reasoning.This shell was developed and first used for the diagnosis of a digital exchange. It was then applied for the fault-finding of the moving target indicator used in the radar.

  4. An Evaluation of Diagnostic Atmospheric Dispersion Models for ’Cold Spill’ Applications at Vandenberg Air Force Base, California

    Science.gov (United States)

    1992-12-30

    tandem with ADPIC , RIMPUFF, or CALPUIF diffusion may provide the most robust diagnostic modeling suite. A cost/benefit analysis of computer hardware and...LINCOM/RIMPUFF 43 H. GENERAL DENSE GAS DISCUSSION 51 I. HEAVYPUFF 52 J. MATHEW/ ADPIC TICQUALYf 54 V. SUMMARY COMMENTS Accesion For 65 VI. REFERENCES...serious contenders: NUATMOS/CITPUFF, CALMET/CALPUFF, PGEMS, WOCSS/MACHWIND/Adaptive plume, LINCOM/ RIMPUFF/HEAVYPUFF, MATHEW/ ADPIC . The following

  5. Integrated Case-Based Applied Pathology (ICAP): a diagnostic-approach model for the learning and teaching of veterinary pathology.

    Science.gov (United States)

    Krockenberger, Mark B; Bosward, Katrina L; Canfield, Paul J

    2007-01-01

    Integrative Case-Based Applied Pathology (ICAP) cases form one component of learning and understanding the role of pathology in the veterinary diagnostic process at the Faculty of Veterinary Science, University of Sydney. It is a strategy that focuses on student-centered learning in a problem-solving context in the year 3 curriculum. Learning exercises use real case material and are primarily delivered online, providing flexibility for students with differing learning needs, who are supported by online, peer, and tutor support. The strategy relies heavily on the integration of pre-clinical and para-clinical information with the introduction of clinical material for the purposes of a logical three-level, problem-oriented approach to the diagnosis of disease. The focus is on logical diagnostic problem solving, primarily using gross pathology and histopathological material, with the inclusion of microbiological, parasitological, and clinical pathological data. The ICAP approach is linked to and congruent with the problem-oriented approach adopted in veterinary medicine and the case-based format used by one of the authors (PJC) for the teaching and learning of veterinary clinical pathology in year 4. Additionally, final-year students have the opportunity, during a diagnostic pathology rotation, to assist in the development and refinement of further ICAPs, which reinforces the importance of pathology in the veterinary diagnostic process. Evidence of the impact of the ICAP approach, based primarily on student surveys and staff peer feedback collected over five years, shows that discipline-specific learning, vertical and horizontal integration, alignment of learning outcomes and assessment, and both veterinary and generic graduate attributes were enhanced. Areas for improvement were identified in the approach, most specifically related to assistance in the development of generic teamwork skills.

  6. 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.

  7. Vibration diagnostics of weak base embankments

    Institute of Scientific and Technical Information of China (English)

    Evgenij Ashpiz; Vladimir Kapustin; Svetlana Klepikova; Maxim Shirobokov

    2013-01-01

    In this paper the theoretical background was analyzed for vibration diagnostics method and experience in its application for weak base embankments. General schemes of survey and recommendations on hardware systems and further prospective development are outlined.

  8. A Multi-Expert Approach for Developing Testing and Diagnostic Systems Based on the Concept-Effect Model

    Science.gov (United States)

    Panjaburee, Patcharin; Hwang, Gwo-Jen; Triampo, Wannapong; Shih, Bo-Ying

    2010-01-01

    With the popularization of computer and communication technologies, researchers have attempted to develop computer-assisted testing and diagnostic systems to help students improve their learning performance on the Internet. In developing a diagnostic system for detecting students' learning problems, it is difficult for individual teachers to…

  9. Obtaining Diagnostic Classification Model Estimates Using Mplus

    Science.gov (United States)

    Templin, Jonathan; Hoffman, Lesa

    2013-01-01

    Diagnostic classification models (aka cognitive or skills diagnosis models) have shown great promise for evaluating mastery on a multidimensional profile of skills as assessed through examinee responses, but continued development and application of these models has been hindered by a lack of readily available software. In this article we…

  10. 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)

  11. ELECTRIC MOTOR DIAGNOSTICS OF SWITCHES BASED ON THE NEURAL NETWORK DATA MODELING THE SPECTRAL DECOMPOSITION OF THE CURRENTS

    Directory of Open Access Journals (Sweden)

    O. M. Shvets

    2009-07-01

    Full Text Available The method of automated diagnostics of electric motors is offered. It uses a neural network revealing the electric motor faults on the basis of analysis of frequency spectrum of current flowing through the motor.

  12. 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

  13. Model Diagnostics for Bayesian Networks

    Science.gov (United States)

    Sinharay, Sandip

    2006-01-01

    Bayesian networks are frequently used in educational assessments primarily for learning about students' knowledge and skills. There is a lack of works on assessing fit of Bayesian networks. This article employs the posterior predictive model checking method, a popular Bayesian model checking tool, to assess fit of simple Bayesian networks. A…

  14. 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.

  15. Vehicle diagnostics based on decision trees

    OpenAIRE

    Gofman, Yevgeniy

    2012-01-01

    In this article the method of diagnosing of T-150 model car lanos is designed for enterprise CJSC "ZAZ". This method is implemented to improve the quality of the process of diagnostics and increasing the rate of automation in the enterprise as a whole.

  16. Facial-paralysis diagnostic system based on 3D reconstruction

    Science.gov (United States)

    Khairunnisaa, Aida; Basah, Shafriza Nisha; Yazid, Haniza; Basri, Hassrizal Hassan; Yaacob, Sazali; Chin, Lim Chee

    2015-05-01

    The diagnostic process of facial paralysis requires qualitative assessment for the classification and treatment planning. This result is inconsistent assessment that potential affect treatment planning. We developed a facial-paralysis diagnostic system based on 3D reconstruction of RGB and depth data using a standard structured-light camera - Kinect 360 - and implementation of Active Appearance Models (AAM). We also proposed a quantitative assessment for facial paralysis based on triangular model. In this paper, we report on the design and development process, including preliminary experimental results. Our preliminary experimental results demonstrate the feasibility of our quantitative assessment system to diagnose facial paralysis.

  17. Diagnostic indicators for integrated assessment models of climate policy

    Energy Technology Data Exchange (ETDEWEB)

    Kriegler, Elmar; Petermann, Nils; Krey, Volker; Schwanitz, Jana; Luderer, Gunnar; Ashina, Shuichi; Bosetti, Valentina; Eom, Jiyong; Kitous, Alban; Mejean, Aurelie; Paroussos, Leonidas; Sano, Fuminori; Turton, Hal; Wilson, Charlie; Van Vuuren, Detlef

    2015-01-01

    Integrated assessments of how climate policy interacts with energy-economic systems can be performed by a variety of models with different functional structures. This article proposes a diagnostic scheme that can be applied to a wide range of integrated assessment models to classify differences among models based on their carbon price responses. Model diagnostics can uncover patterns and provide insights into why, under a given scenario, certain types of models behave in observed ways. Such insights are informative since model behavior can have a significant impact on projections of climate change mitigation costs and other policy-relevant information. The authors propose diagnostic indicators to characterize model responses to carbon price signals and test these in a diagnostic study with 11 global models. Indicators describe the magnitude of emission abatement and the associated costs relative to a harmonized baseline, the relative changes in carbon intensity and energy intensity and the extent of transformation in the energy system. This study shows a correlation among indicators suggesting that models can be classified into groups based on common patterns of behavior in response to carbon pricing. Such a classification can help to more easily explain variations among policy-relevant model results.

  18. Diagnostic Measures for Nonlinear Regression Models Based on Empirical Likelihood Method%非线性回归模型的经验似然诊断

    Institute of Scientific and Technical Information of China (English)

    丁先文; 徐亮; 林金官

    2012-01-01

    经验似然方法已经被广泛用于线性模型和广义线性模型.本文基于经验似然方法对非线性回归模型进行统计诊断.首先得到模型参数的极大经验似然估计;其次基于经验似然研究了三种不同的影响曲率度量;最后通过一个实际例子,说明了诊断方法的有效性.%The empirical likelihood method has been extensively applied to linear regression and generalized linear regression models. In this paper, the diagnostic measures for nonlinear regression models are studied based on the empirical likelihood method. First, the maximum empirical likelihood estimate of the parameters are obtained. Then, three different measures of influence curvatures are studied. Last, real data analysis are given to illustrate the validity of statistical diagnostic measures.

  19. 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...

  20. 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...

  1. 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

  2. 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.

  3. Case-Deletion Diagnostics for Nonlinear Structural Equation Models

    Science.gov (United States)

    Lee, Sik-Yum; Lu, Bin

    2003-01-01

    In this article, a case-deletion procedure is proposed to detect influential observations in a nonlinear structural equation model. The key idea is to develop the diagnostic measures based on the conditional expectation of the complete-data log-likelihood function in the EM algorithm. An one-step pseudo approximation is proposed to reduce the…

  4. 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.

  5. 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

  6. Training Educational Psychologists: A Model of Working with Diagnostic Case

    Directory of Open Access Journals (Sweden)

    Shubina A.S.,

    2016-12-01

    Full Text Available The paper describes a model of working with a diagnostic case in educational psychological practice and analyses its compliance with the requirements of the professional standard for educational psychologists as well as with the theoretical bases of psychological assessment as a form of professional activity of a psychologist. The paper reviews the possibilities for making the requirements of the professional standard more specific by means of relating its components to the stages of the diagnostic process. As it is shown, a number of aspects in the diagnostic activity are deficient and require to be specially developed during professional and advanced training. The paper analyses the necessity of designing the content of psychodiagnostic disciplines so that they involve working with diagnostic hypotheses. It also outlines the tasks of mastering psychodiagnostic disciplines which, if solved successfully, would prevent students from making typical diagnostic mistakes. Finally, the paper discusses the difficulties with the development of the gnostic component of diagnostic activity in graduate students with bachelor degrees in a non-psychology field.

  7. 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.

  8. 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.

  9. 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.

  10. A universal model of diagnostic reasoning.

    Science.gov (United States)

    Croskerry, Pat

    2009-08-01

    Clinical judgment is a critical aspect of physician performance in medicine. It is essential in the formulation of a diagnosis and key to the effective and safe management of patients. Yet, the overall diagnostic error rate remains unacceptably high. In more than four decades of research, a variety of approaches have been taken, but a consensus approach toward diagnostic decision making has not emerged. In the last 20 years, important gains have been made in psychological research on human judgment. Dual-process theory has emerged as the predominant approach, positing two systems of decision making, System 1 (heuristic, intuitive) and System 2 (systematic, analytical). The author proposes a schematic model that uses the theory to develop a universal approach toward clinical decision making. Properties of the model explain many of the observed characteristics of physicians' performance. Yet the author cautions that not all medical reasoning and decision making falls neatly into one or the other of the model's systems, even though they provide a basic framework incorporating the recognized diverse approaches. He also emphasizes the complexity of decision making in actual clinical situations and the urgent need for more research to help clinicians gain additional insight and understanding regarding their decision making.

  11. Hierarchical mixture of experts and diagnostic modeling approach to reduce hydrologic model structural uncertainty: STRUCTURAL UNCERTAINTY DIAGNOSTICS

    Energy Technology Data Exchange (ETDEWEB)

    Moges, Edom [Civil and Environmental Engineering Department, Washington State University, Richland Washington USA; Demissie, Yonas [Civil and Environmental Engineering Department, Washington State University, Richland Washington USA; Li, Hong-Yi [Hydrology Group, Pacific Northwest National Laboratory, Richland Washington USA

    2016-04-01

    In most water resources applications, a single model structure might be inadequate to capture the dynamic multi-scale interactions among different hydrological processes. Calibrating single models for dynamic catchments, where multiple dominant processes exist, can result in displacement of errors from structure to parameters, which in turn leads to over-correction and biased predictions. An alternative to a single model structure is to develop local expert structures that are effective in representing the dominant components of the hydrologic process and adaptively integrate them based on an indicator variable. In this study, the Hierarchical Mixture of Experts (HME) framework is applied to integrate expert model structures representing the different components of the hydrologic process. Various signature diagnostic analyses are used to assess the presence of multiple dominant processes and the adequacy of a single model, as well as to identify the structures of the expert models. The approaches are applied for two distinct catchments, the Guadalupe River (Texas) and the French Broad River (North Carolina) from the Model Parameter Estimation Experiment (MOPEX), using different structures of the HBV model. The results show that the HME approach has a better performance over the single model for the Guadalupe catchment, where multiple dominant processes are witnessed through diagnostic measures. Whereas, the diagnostics and aggregated performance measures prove that French Broad has a homogeneous catchment response, making the single model adequate to capture the response.

  12. Modelling the Spoon IRS diagnostic diagram

    CERN Document Server

    Rowan-Robinson, Michael

    2009-01-01

    We explore whether our models for starbursts, quiescent star-forming galaxies and for AGN dust tori are able to model the full range of IRS spectra measured with Spitzer. The diagnostic plot of 9.7 mu silicate optical depth versus 6.2 mu PAH equivalent width, introduced by Spoon and coworkers in 2007, gives a good indication of the age and optical depth of a starburst, and of the contribution of an AGN dust torus. However there is aliasing between age and optical depth at later times in the evolution of a starburst, and between age and the presence of an AGN dust torus. Modeling the full IRS spectra and using broad-band 25-850 mu fluxes can help to resolve these aliases. The observed spectral energy distributions require starbursts of a range of ages with initial dust optical depth ranging from 50-200, optically thin dust emission ('cirrus') illuminated by a range of surface brightnesses of the interstellar radiation field, and AGN dust tori with a range of viewing angles.

  13. Defining Characteristics of Diagnostic Classification Models and the Problem of Retrofitting in Cognitive Diagnostic Assessment

    Science.gov (United States)

    Gierl, Mark J.; Cui, Ying

    2008-01-01

    One promising application of diagnostic classification models (DCM) is in the area of cognitive diagnostic assessment in education. However, the successful application of DCM in educational testing will likely come with a price--and this price may be in the form of new test development procedures and practices required to yield data that satisfy…

  14. 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...

  15. Modeling and Diagnostic Software for Liquefying-Fuel Rockets

    Science.gov (United States)

    Poll, Scott; Iverson, David; Ou, Jeremy; Sanderfer, Dwight; Patterson-Hine, Ann

    2005-01-01

    A report presents a study of five modeling and diagnostic computer programs considered for use in an integrated vehicle health management (IVHM) system during testing of liquefying-fuel hybrid rocket engines in the Hybrid Combustion Facility (HCF) at NASA Ames Research Center. Three of the programs -- TEAMS, L2, and RODON -- are model-based reasoning (or diagnostic) programs. The other two programs -- ICS and IMS -- do not attempt to isolate the causes of failures but can be used for detecting faults. In the study, qualitative models (in TEAMS and L2) and quantitative models (in RODON) having varying scope and completeness were created. Each of the models captured the structure and behavior of the HCF as a physical system. It was noted that in the cases of the qualitative models, the temporal aspects of the behavior of the HCF and the abstraction of sensor data are handled outside of the models, and it is necessary to develop additional code for this purpose. A need for additional code was also noted in the case of the quantitative model, though the amount of development effort needed was found to be less than that for the qualitative models.

  16. Diagnostics and future evolution analysis of the two parametric models

    CERN Document Server

    Yang, Guang; Meng, Xinhe

    2016-01-01

    In this paper, we apply three diagnostics including $Om$, Statefinder hierarchy and the growth rate of perturbations into discriminating the two parametric models for the effective pressure with the $\\Lambda$CDM model. By using the $Om$ diagnostic, we find that both the model 1 and the model 2 can be hardly distinguished from each other as well as the $\\Lambda$CDM model in terms of 68\\% confidence level. As a supplement, by using the Statefinder hierarchy diagnostics and the growth rate of perturbations, we discover that not only can our two parametric models be well distinguished from $\\Lambda$CDM model, but also, by comparing with $Om$ diagnostic, the model 1 and the model 2 can be distinguished better from each other. In addition, we also explore the fate of universe evolution of our two models by means of the rip analysis.

  17. Toward Validation of the Diagnostic-Prescriptive Model

    Science.gov (United States)

    Ysseldyke, James E.; Sabatino, David A.

    1973-01-01

    Criticized are recent research efforts to validate the diagnostic prescriptive model of remediating learning disabilities, and proposed is a 6-step psychoeducational model designed to ascertain links between behavioral differences and instructional outcomes. (DB)

  18. Beam Loss Diagnostics Based on Pressure Measurements

    CERN Document Server

    Weinrich, U

    2003-01-01

    The GSI is operating a heavy ion synchrotron, which is currently undergoing an upgrade towards higher beam intensities. It was discovered that beam losses induce a significant pressure increase in the vacuum system. In order to detect the time constants of the pressure increase and decrease, fast total pressure measurements were put into operation. With the recently installed partial pressure diagnostics it is also possible to follow up which types of molecules are released. The presentation will focus on the different techniques applied as well as on some measurement results. The potential and difficulties of this diagnostic tool will also be discussed.

  19. 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...

  20. 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.

  1. Atmospheric Pressure Plasma Based Flame Control and Diagnostics

    Science.gov (United States)

    2015-01-01

    TYPE 3. DATES COVERED 00-00-2015 to 00-00-2015 4. TITLE AND SUBTITLE Atmospheric Pressure Plasma Based Flame Control and Diagnostics 5a...to 10%)  Flame speed enhancement (>20%)  Extension of lean limit (factor of two)  Distributed ignition  Development of new diagnostics

  2. Advances in paper-based point-of-care diagnostics.

    Science.gov (United States)

    Hu, Jie; Wang, ShuQi; Wang, Lin; Li, Fei; Pingguan-Murphy, Belinda; Lu, Tian Jian; Xu, Feng

    2014-04-15

    Advanced diagnostic technologies, such as polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELISA), have been widely used in well-equipped laboratories. However, they are not affordable or accessible in resource-limited settings due to the lack of basic infrastructure and/or trained operators. Paper-based diagnostic technologies are affordable, user-friendly, rapid, robust, and scalable for manufacturing, thus holding great potential to deliver point-of-care (POC) diagnostics to resource-limited settings. In this review, we present the working principles and reaction mechanism of paper-based diagnostics, including dipstick assays, lateral flow assays (LFAs), and microfluidic paper-based analytical devices (μPADs), as well as the selection of substrates and fabrication methods. Further, we report the advances in improving detection sensitivity, quantification readout, procedure simplification and multi-functionalization of paper-based diagnostics, and discuss the disadvantages of paper-based diagnostics. We envision that miniaturized and integrated paper-based diagnostic devices with the sample-in-answer-out capability will meet the diverse requirements for diagnosis and treatment monitoring at the POC.

  3. [Culture based diagnostic methods for tuberculosis].

    Science.gov (United States)

    Baylan, Orhan

    2005-01-01

    Culture methods providing isolates for identification and drug susceptibility testing, still represent the gold standard for the definitive diagnosis of tuberculosis, although the delay in obtaining results still remains a problem. Traditional solid media are recommended for use along with liquid media in primary isolation of mycobacteria. At present, a number of elaborate culture systems are available commercially. They range from simple bottles and tubes such as MGIT (BD Diagnostic Systems, USA), Septi-Chek AFB (BD, USA) and MB Redox (Biotest Diagnostics, USA) to semiautomated system (BACTEC 460TB, BD, USA) and fully automated systems (BACTEC 9000 MB [BD, USA], BACTEC MGIT 960 [BD, USA], ESP Culture System II [Trek Diagnostics, USA], MB/BacT ALERT 3D System [BioMérieux, NC], TK Culture System [Salubris Inc, Turkey]). Culture methods available today are sufficient to permit laboratories to develop an algoritm that is optimal for patients and administrative needs. In this review article, the culture systems used for the diagnosis of tuberculosis, their mechanisms, advantages and disadvantages have been discussed under the light of recent literature.

  4. Technical Note: The Simple Diagnostic Photosynthesis and Respiration Model (SDPRM

    Directory of Open Access Journals (Sweden)

    B. Badawy

    2012-10-01

    Full Text Available We present a Simple Diagnostic Photosynthesis and Respiration Model (SDPRM that has been developed based on pre-existing formulations. The photosynthesis model is based on the light use efficiency logic, suggested by Monteith1977, for calculating the Gross Primary Production (GPP while the ecosystem respiration (Reco model is based on the formulations introduced by Lloyd1994 and modified by Reichstein2003. SDPRM is driven by satellite-derived fAPAR (fraction of Absorbed Photosynthetically Active Radiation and climate data from NCEP/NCAR. The model estimates 3-hourly values of GPP for seven major biomes and daily Reco. The motivation is to provide a-priori fields of surface CO2 fluxes with fine temporal and spatial scales, and their derivatives with respect to adjustable model parameters, for atmospheric CO2 inversions. The estimated fluxes from SDPRM showed that the model is capable of producing flux estimates consistent with the ones inferred from atmospheric CO2 inversion or simulated from process-based models. In this Technical Note, different analyses were carried out to test the sensitivity of the estimated fluxes of GPP and Reco to their driving forces. The spatial patterns of the climatic controls (temperature, precipitation, water on the interannual variability of GPP are consistent with previous studies even though SDPRM has a very simple structure and few adjustable parameters, and hence it is much easier to modify than more sophisticated process-based models used in these previous studies. According to SDPRM, the results show that temperature is a limiting factor for the interannual variability of Reco over the cold boreal forest, while precipitation is the main limiting factor of Reco over the tropics and the southern hemisphere, consistent with previous regional studies.

  5. 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.

  6. Assessing Fit of Cognitive Diagnostic Models: A Case Study

    Science.gov (United States)

    Sinharay, Sandip; Almond, Russell G.

    2007-01-01

    A cognitive diagnostic model uses information from educational experts to describe the relationships between item performances and posited proficiencies. When the cognitive relationships can be described using a fully Bayesian model, Bayesian model checking procedures become available. Checking models tied to cognitive theory of the domains…

  7. 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.

  8. Optically-Based Diagnostics for Gas-Phase Laser Development

    Science.gov (United States)

    2010-08-01

    Phase Laser Development Acknowledgement of Support and Disclaimer This material is based upon work supported by Air Force Office of Scientific...00-2010 4. TITLE AND SUBTITLE Optically-Based Diagnostics for Gas-Phase Laser Development 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM...Sciences Inc. Role of Optical Diagnostics in High Energy Gas Laser Development  Chemically rich, energetic, reacting flow with competing phenomena

  9. 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.

  10. Paper-based sample-to-answer molecular diagnostic platform for point-of-care diagnostics.

    Science.gov (United States)

    Choi, Jane Ru; Tang, Ruihua; Wang, ShuQi; Wan Abas, Wan Abu Bakar; Pingguan-Murphy, Belinda; Xu, Feng

    2015-12-15

    Nucleic acid testing (NAT), as a molecular diagnostic technique, including nucleic acid extraction, amplification and detection, plays a fundamental role in medical diagnosis for timely medical treatment. However, current NAT technologies require relatively high-end instrumentation, skilled personnel, and are time-consuming. These drawbacks mean conventional NAT becomes impractical in many resource-limited disease-endemic settings, leading to an urgent need to develop a fast and portable NAT diagnostic tool. Paper-based devices are typically robust, cost-effective and user-friendly, holding a great potential for NAT at the point of care. In view of the escalating demand for the low cost diagnostic devices, we highlight the beneficial use of paper as a platform for NAT, the current state of its development, and the existing challenges preventing its widespread use. We suggest a strategy involving integrating all three steps of NAT into one single paper-based sample-to-answer diagnostic device for rapid medical diagnostics in the near future.

  11. Mental Disorder Diagnostic System Based on Logical-Combinatorial Methods of Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Anna Yankovskaya

    2013-11-01

    Full Text Available The authors describe mental disorder diagnostic system based on logical-combinatorial methods of pattern recognition called as the intelligent system DIAPROD-LOG. The system is designed for diagnostics and prevention of depression. The mathematical apparatus for creation of the proposed system based on a matrix model of data and knowledge representation, as well as various kinds of regularities in data and knowledge are presented. The description of the system is given.

  12. Current development of saliva/oral fluid-based diagnostics.

    Science.gov (United States)

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

    2010-07-01

    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 diagnostics. In this review, we discuss the current consensus on development of saliva/oral fluid-based diagnostics and provide a summary of recent research advancements of the Texas-Kentucky Saliva Diagnostics Consortium. In the foreseeable future, current research on saliva based diagnostic methods could revolutionize health care.

  13. Structural Equation Modeling Diagnostics Using R Package Semdiag and EQS

    Science.gov (United States)

    Yuan, Ke-Hai; Zhang, Zhiyong

    2012-01-01

    Yuan and Hayashi (2010) introduced 2 scatter plots for model and data diagnostics in structural equation modeling (SEM). However, the generation of the plots requires in-depth understanding of their underlying technical details. This article develops and introduces an R package semdiag for easily drawing the 2 plots. With a model specified in EQS…

  14. 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.

  15. System Modeling and Diagnostics for Liquefying-Fuel Hybrid Rockets

    Science.gov (United States)

    Poll, Scott; Iverson, David; Ou, Jeremy; Sanderfer, Dwight; Patterson-Hine, Ann

    2003-01-01

    A Hybrid Combustion Facility (HCF) was recently built at NASA Ames Research Center to study the combustion properties of a new fuel formulation that burns approximately three times faster than conventional hybrid fuels. Researchers at Ames working in the area of Integrated Vehicle Health Management recognized a good opportunity to apply IVHM techniques to a candidate technology for next generation launch systems. Five tools were selected to examine various IVHM techniques for the HCF. Three of the tools, TEAMS (Testability Engineering and Maintenance System), L2 (Livingstone2), and RODON, are model-based reasoning (or diagnostic) systems. Two other tools in this study, ICS (Interval Constraint Simulator) and IMS (Inductive Monitoring System) do not attempt to isolate the cause of the failure but may be used for fault detection. Models of varying scope and completeness were created, both qualitative and quantitative. In each of the models, the structure and behavior of the physical system are captured. In the qualitative models, the temporal aspects of the system behavior and the abstraction of sensor data are handled outside of the model and require the development of additional code. In the quantitative model, less extensive processing code is also necessary. Examples of fault diagnoses are given.

  16. Technical Note: The Simple Diagnostic Photosynthesis and Respiration Model (SDPRM

    Directory of Open Access Journals (Sweden)

    B. Badawy

    2013-10-01

    Full Text Available We present a Simple Diagnostic Photosynthesis and Respiration Model (SDPRM that has been developed based on pre-existing formulations. The photosynthesis model is based on the light use efficiency logic for calculating the gross primary production (GPP, while the ecosystem respiration (Reco is a modified version of an Arrhenius-type equation. SDPRM is driven by satellite-derived fAPAR (fraction of Absorbed Photosynthetically Active Radiation and climate data from the National Center for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NCEP/NCAR. The model estimates 3-hourly values of GPP for seven major biomes and daily Reco. The motivation is to provide a priori fields of surface CO2 fluxes with fine temporal and spatial scales for atmospheric CO2 inversions. The estimated fluxes from SDPRM showed that the model is capable of producing flux estimates consistent with the ones inferred from atmospheric CO2 inversion or simulated from process-based models. In this Technical Note, different analyses were carried out to test the sensitivity of the estimated fluxes of GPP and CO2 to their driving forces. The spatial patterns of the climatic controls (temperature, precipitation, water on the interannual variability of GPP are consistent with previous studies, even though SDPRM has a very simple structure and few adjustable parameters and hence it is much easier to modify in an inversion than more sophisticated process-based models. In SDPRM, temperature is a limiting factor for the interannual variability of Reco over cold boreal forest, while precipitation is the main limiting factor of Reco over the tropics and the southern hemisphere, consistent with previous regional studies.

  17. Towards Accreditation of Diagnostic Models for Improved Performance

    Science.gov (United States)

    2004-10-02

    analysis. Secondly, while performing testability, the diagnostic algorithm is not included to assess Anuradha Kodali et al. This is an open-access...to assess the diagnosis (Sheppard, & Simpson, 1998). Considering these factors, Interactive Diagnostic Modeling Evaluator (i-DME) ( Kodali , Robinson...requirements set before to suit practical compulsions. This may lead to changing the basic principles and to refine the existing methods continuously

  18. Comparison of the utility of the classic model (the Henderson-Hasselbach equation) and the Stewart model (Strong Ion Approach) for the diagnostics of acid-base balance disorders in dogs with right sided heart failure.

    Science.gov (United States)

    Sławuta, P; Glińska-Suchocka, K

    2012-01-01

    Classically, the acid-base balance (ABB) is described by the Henderson-Hasselbach equation, where the blood pH is a result of a metabolic components--the HCO3(-) concentration and a respiratory component--pCO2. The Stewart model assumes that the proper understanding of the organisms ABB is based on an analysis of: pCO2, Strong Ion difference (SID)--the difference strong cation and anion concentrations in the blood serum, and the Acid total (Atot)--the total concentration of nonvolatile weak acids. Right sided heart failure in dogs causes serious haemodynamic disorders in the form of peripheral stasis leading to formation of transudates in body cavities, which in turn causes ABB respiratory and metabolic disorders. The study was aimed at analysing the ABB parameters with the use of the classic method and the Stewart model in dogs with the right sided heart failure and a comparison of both methods for the purpose of their diagnostic and therapeutic utility. The study was conducted on 10 dogs with diagnosed right sided heart failure. Arterial and venous blood was drawn from the animals. Analysis of pH, pCO2 and HCO3(-) was performed from samples of arterial blood. Concentrations of Na+, K+, Cl(-), P(inorganic), albumins and lactate were determined from venous blood samples and values of Strong Ion difference of Na+, K+ and Cl(-) (SID3), Strong Ion difference of Na+, K+, Cl(-) and lactate (SID4), Atot, Strong Ion difference effective (SIDe) and Strong Ion Gap (SIG4) were calculated. The conclusions are as follows: 1) diagnosis of ABB disorders on the basis of the Stewart model showed metabolic alkalosis in all dogs examined, 2) in cases of circulatory system diseases, methodology based on the Stewart model should be applied for ABB disorder diagnosis, 3) if a diagnosis of ABB disorders is necessary, determination of pH, pCO2 and HCO3(-) as well as concentrations of albumins and P(inorganic) should be determined on a routine basis, 4) for ABB disorder diagnosis, the

  19. 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

    2016-06-17

    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."

  20. 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

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

    Directory of Open Access Journals (Sweden)

    Ewert Linder

    2016-06-01

    Full Text Available 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.”

  2. Diagnostic indicators for integrated assessment models of climate policy

    NARCIS (Netherlands)

    Kriegler, Elmar; Petermann, Nils; Krey, Volker; Schwanitz, Valeria Jana; Luderer, Gunnar; Ashina, Shuichi; Bosetti, Valentina; Eom, Jiyong; Kitous, Alban; Méjean, Aurélie; Paroussos, Leonidas; Sano, Fuminori; Turton, Hal; Wilson, Charlie; Van Vuuren, Detlef P.

    2015-01-01

    Integrated assessments of how climate policy interacts with energy-economy systems can be performed by a variety of models with different functional structures. In order to provide insights into why results differ between models, this article proposes a diagnostic scheme that can be applied to a wid

  3. Using Diagnostic Text Information to Constrain Situation Models

    NARCIS (Netherlands)

    Dutke, S.; Baadte, C.; Hähnel, A.; Hecker, U. von; Rinck, M.

    2010-01-01

    During reading, the model of the situation described by the text is continuously accommodated to new text input. The hypothesis was tested that readers are particularly sensitive to diagnostic text information that can be used to constrain their existing situation model. In 3 experiments, adult part

  4. $Om$ diagnostic applied to scalar field models and slowing down of cosmic acceleration

    CERN Document Server

    Shahalam, M; Agarwal, Abhineet

    2015-01-01

    We apply the $Om$ diagnostic to models for dark energy based on scalar fields. In case of the power law potentials, we demonstrate the possibility of slowing down the expansion of the Universe around the present epoch for a specific range in the parameter space. For these models, we also examine the issues concerning the age of Universe. We use the $Om$ diagnostic to distinguish the $\\Lambda$CDM model from non minimally coupled scalar field, phantom field and generic quintessence models. Our study shows that the $Om$ has zero, positive and negative curvatures for $\\Lambda$CDM, phantom and quintessence models respectively. We use an integrated data base (SN+Hubble+BAO+CMB) for bservational analysis and demonstrate that $Om$ is a useful diagnostic to apply to observational data.

  5. 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.

  6. 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.

  7. 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

    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......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...

  8. 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…

  9. A Mixed Model Approach to Meta-Analysis of Diagnostic Studies with Binary Test Outcome

    Science.gov (United States)

    Doebler, Philipp; Holling, Heinz; Bohning, Dankmar

    2012-01-01

    We propose 2 related models for the meta-analysis of diagnostic tests. Both models are based on the bivariate normal distribution for transformed sensitivities and false-positive rates. Instead of using the logit as a transformation for these proportions, we employ the "t"[subscript alpha] family of transformations that contains the log, logit,…

  10. Recombinant protein-based viral disease diagnostics in veterinary medicine.

    Science.gov (United States)

    Balamurugan, Vinayagamurthy; Venkatesan, Gnanavel; Sen, Arnab; Annamalai, Lakshmanan; Bhanuprakash, Veerakyathappa; Singh, Raj Kumar

    2010-09-01

    Identification of pathogens or antibody response to pathogens in human and animals modulates the treatment strategies for naive population and subsequent infections. Diseases can be controlled and even eradicated based on the epidemiology and effective prophylaxis, which often depends on development of efficient diagnostics. In addition, combating newly emerging diseases in human as well as animal healthcare is challenging and is dependent on developing safe and efficient diagnostics. Detection of antibodies directed against specific antigens has been the method of choice for documenting prior infection. Other than zoonosis, development of inexpensive vaccines and diagnostics is a unique problem in animal healthcare. The advent of recombinant DNA technology and its application in the biotechnology industry has revolutionized animal healthcare. The use of recombinant DNA technology in animal disease diagnosis has improved the rapidity, specificity and sensitivity of various diagnostic assays. This is because of the absence of host cellular proteins in the recombinant derived antigen preparations that dramatically decrease the rate of false-positive reactions. Various recombinant products are used for disease diagnosis in veterinary medicine and this article discusses recombinant-based viral disease diagnostics currently used for detection of pathogens in livestock and poultry.

  11. 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.

  12. Managing evidence-based health care: a diagnostic framework.

    Science.gov (United States)

    Newman, K; Pyne, T; Cowling, A

    1998-01-01

    This paper proposes a diagnostic framework useful to Trust managers who are faced with the task of devising and implementing strategies for improvements in clinical effectiveness, and is based on a recent study incorporating clinicians, managers, and professional staff in four NHS Trusts in the North Thames Region. The gap framework is inspired by the gap model developed by Zeithaml, Parasuraman and Berry from their research into service quality and incorporates Dave Sackett's schema as well as a personal competency profile needed for the practice of evidence based health-care (EBHC). The paper highlights the four organisational and personal failures (gaps) which contribute to the fifth gap, namely the discrepancy between clinically relevant research evidence and its implementation in health care. To close the gaps, Trusts need to set the goal and tackle the cultural, organisational, attitudinal and more material aspects such as investment in the information infrastructure, education and training of doctors. Doctors need to go through a process from awareness to action facilitated through a combination of personal and organisational incentives and rewards as well as training in the requisite skills. Researchers should take steps to improve the quality of the evidence and its accessibility and purchasers should reinforce the use of EBHC by withdrawing funding for care which has proved to be ineffective, inappropriate or inferior.

  13. [Practical diagnostics of acid-base disorders: part I: differentiation between respiratory and metabolic disturbances].

    Science.gov (United States)

    Deetjen, P; Lichtwarck-Aschoff, M

    2012-11-01

    The first part of this overview on diagnostic tools for acid-base disorders focuses on basic knowledge for distinguishing between respiratory and metabolic causes of a particular disturbance. Rather than taking sides in the great transatlantic or traditional-modern debate on the best theoretical model for understanding acid-base physiology, this article tries to extract what is most relevant for everyday clinical practice from the three schools involved in these keen debates: the Copenhagen, the Boston and the Stewart schools. Each school is particularly strong in a specific diagnostic or therapeutic field. Appreciating these various strengths a unifying, simplified algorithm together with an acid-base calculator will be discussed.

  14. 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.

  15. Internet gaming disorder: Inadequate diagnostic criteria wrapped in a constraining conceptual model.

    Science.gov (United States)

    Starcevic, Vladan

    2017-03-17

    Background and aims The paper "Chaos and confusion in DSM-5 diagnosis of Internet Gaming Disorder: Issues, concerns, and recommendations for clarity in the field" by Kuss, Griffiths, and Pontes (in press) critically examines the DSM-5 diagnostic criteria for Internet gaming disorder (IGD) and addresses the issue of whether IGD should be reconceptualized as gaming disorder, regardless of whether video games are played online or offline. This commentary provides additional critical perspectives on the concept of IGD. Methods The focus of this commentary is on the addiction model on which the concept of IGD is based, the nature of the DSM-5 criteria for IGD, and the inclusion of withdrawal symptoms and tolerance as the diagnostic criteria for IGD. Results The addiction framework on which the DSM-5 concept of IGD is based is not without problems and represents only one of multiple theoretical approaches to problematic gaming. The polythetic, non-hierarchical DSM-5 diagnostic criteria for IGD make the concept of IGD unacceptably heterogeneous. There is no support for maintaining withdrawal symptoms and tolerance as the diagnostic criteria for IGD without their substantial revision. Conclusions The addiction model of IGD is constraining and does not contribute to a better understanding of the various patterns of problematic gaming. The corresponding diagnostic criteria need a thorough overhaul, which should be based on a model of problematic gaming that can accommodate its disparate aspects.

  16. Statefinder Diagnostic for Born-Infeld Type Dark Energy Model

    Institute of Scientific and Technical Information of China (English)

    HUANG Zeng-Guang; LU Hui-Qing

    2008-01-01

    Using a new method called the statefinder diagnostics which can make one dark energy model differ from the others, we investigate the dynamics of Born-Infeld (B-I) type dark energy model. The evolution trajectory of B-I type dark energy with Mexican hat potential model with respect to e-folding time N is shown in the r (s) diagram, When the parameter of noncanonical kinetic energy term η→0 or kinetic energy ψ2→0, the B-I type dark energy (K-essence) model reduces to the quintessence model or the ACDM model corresponding to the statefinder pair {r, s}={1, 0} respectively. As a result, the evolution trajectory of our model in the r (s) diagram in Mexican hat potential is quite different from those of other dark energy models. The current values of parameters Ω,ψ and ω,ψ in this model meet the latest observations WMAP5 well.

  17. Using Enstrophy-Based Diagnostics in an Ensemble for Two Blocking Events

    Directory of Open Access Journals (Sweden)

    Andrew D. Jensen

    2013-01-01

    Full Text Available Recent research has used enstrophy-based diagnostics to identify the development and dissipation stages of blocking events. These previous studies made use of reanalysis data sets in the calculations of the enstrophy-based diagnostics, such as the NCEP-NCAR reanalysis (2.5° × 2.5° of geopotential height and horizontal winds. However, none of these studies has explored the use of the enstrophy-based diagnostics in weather or climate models with higher horizontal resolution. In this paper, the enstrophy-based diagnostics are used to analyze two blocking events, using data from the ERA-Interim reanalysis data set (0.75° × 0.75° and also the Global Ensemble Forecast System (GEFS (1° × 1°. The results of this work indicate that using an ensemble may be more effective than a single dynamical control forecast in evaluating the enstrophy-based diagnostic quantities, and that the results are similar to those obtained with coarser resolution.

  18. 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.

  19. Validation of a Cognitive Diagnostic Model across Multiple Forms of a Reading Comprehension Assessment

    Science.gov (United States)

    Clark, Amy K.

    2013-01-01

    The present study sought to fit a cognitive diagnostic model (CDM) across multiple forms of a passage-based reading comprehension assessment using the attribute hierarchy method. Previous research on CDMs for reading comprehension assessments served as a basis for the attributes in the hierarchy. The two attribute hierarchies were fit to data from…

  20. Finite Elements Modeling in Diagnostics of Small Closed Pneumothorax.

    Science.gov (United States)

    Lorkowski, J; Mrzygłód, M; Grzegorowska, O

    2015-01-01

    Posttraumatic pneumothorax still remains to be a serious clinical problem and requires a comprehensive diagnostic and monitoring during treatment. The aim of this paper is to present a computer method of modeling of small closed pneumothorax. Radiological images of 34 patients of both sexes with small closed pneumothorax were taken into consideration. The control group consisted of X-rays of 22 patients treated because of tension pneumothorax. In every single case the model was correlated with the clinical manifestations. The procedure of computational rapid analysis (CRA) for in silico analysis of surgical intervention was introduced. It included implementation of computerize tomography images and their automatic conversion into 3D finite elements model (FEM). In order to segmentize the 3D model, an intelligent procedure of domain recognition was used. In the final step, a computer simulation project of fluid-structure interaction was built, using the ANSYS\\Workbench environment of multi-physics analysis. The FEM model and computer simulation project were employed in the analysis in order to optimize surgical intervention. The model worked out well and was compatible with the clinical manifestations of pneumothorax. We conclude that the created FEM model is a promising tool for facilitation of diagnostic procedures and prognosis of treatment in the case of small closed pneumothorax.

  1. Electron Beam Diagnostic Based on a Short Seeded FEL

    CERN Document Server

    Graves, W; Kaertner, Franz X; Zwart, T

    2005-01-01

    The optical properties of an FEL amplifier are sensitively dependent on the electron beam current profile, energy spread, and transverse emittance. In this paper we consider using a short FEL amplifier operating on a low harmonic of a visible-IR input seed as a mildly destructive electron beam diagnostic able to measure these properties for sub-ps time slices. The optical methods are described as well as a planned implementation of the device for the FERMI@Elettra XUV FEL under construction at Sincrotrone Trieste, including its fiber-based seed laser closely coupled with the facility timing system, undulator parameters, and requirements on the electron and FEL pulses. This diagnostic is conveniently integrated with a "laser heater" designed to increase the very low electron beam energy spread produced by a photoinjector in order to avoid space charge and coherent synchrotron radiation instabilities.

  2. 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.

  3. 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.

  4. 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).

  5. Peptide based diagnostics: are random-sequence peptides more useful than tiling proteome sequences?

    Science.gov (United States)

    Navalkar, Krupa Arun; Johnston, Stephan Albert; Stafford, Phillip

    2015-02-01

    Diagnostics using peptide ligands have been available for decades. However, their adoption in diagnostics has been limited, not because of poor sensitivity but in many cases due to diminished specificity. Numerous reports suggest that protein-based rather than peptide-based disease detection is more specific. We examined two different approaches to peptide-based diagnostics using Coccidioides (aka Valley Fever) as the disease model. Although the pathogen was discovered more than a century ago, a highly sensitive diagnostic remains unavailable. We present a case study where two different approaches to diagnosing Valley Fever were used: first, overlapping Valley Fever epitopes representing immunodominant Coccidioides antigens were tiled using a microarray format of presynthesized peptides. Second, a set of random sequence peptides identified using a 10,000 peptide immunosignaturing microarray was compared for sensitivity and specificity. The scientific hypothesis tested was that actual epitope peptides from Coccidioides would provide sufficient sensitivity and specificity as a diagnostic. Results demonstrated that random sequence peptides exhibited higher accuracy when classifying different stages of Valley Fever infection vs. epitope peptides. The epitope peptide array did provide better performance than the existing immunodiffusion array, but when directly compared to the random sequence peptides, reported lower overall accuracy. This study suggests that there are competing aspects of antibody recognition that involve conservation of pathogen sequence and aspects of mimotope recognition and amino acid substitutions. These factors may prove critical when developing the next generation of high-performance immunodiagnostics.

  6. Modeling and Measurement Constraints in Fault Diagnostics for HVAC Systems

    Energy Technology Data Exchange (ETDEWEB)

    Najafi, Massieh; Auslander, David M.; Bartlett, Peter L.; Haves, Philip; Sohn, Michael D.

    2010-05-30

    Many studies have shown that energy savings of five to fifteen percent are achievable in commercial buildings by detecting and correcting building faults, and optimizing building control systems. However, in spite of good progress in developing tools for determining HVAC diagnostics, methods to detect faults in HVAC systems are still generally undeveloped. Most approaches use numerical filtering or parameter estimation methods to compare data from energy meters and building sensors to predictions from mathematical or statistical models. They are effective when models are relatively accurate and data contain few errors. In this paper, we address the case where models are imperfect and data are variable, uncertain, and can contain error. We apply a Bayesian updating approach that is systematic in managing and accounting for most forms of model and data errors. The proposed method uses both knowledge of first principle modeling and empirical results to analyze the system performance within the boundaries defined by practical constraints. We demonstrate the approach by detecting faults in commercial building air handling units. We find that the limitations that exist in air handling unit diagnostics due to practical constraints can generally be effectively addressed through the proposed approach.

  7. About the Big Graphs Arising when Forming the Diagnostic Models in a Reconfigurable Computing Field of Functional Monitoring and Diagnostics System of the Spacecraft Onboard Control Complex

    Directory of Open Access Journals (Sweden)

    L. V. Savkin

    2015-01-01

    Full Text Available One of the problems in implementation of the multipurpose complete systems based on the reconfigurable computing fields (RCF is the problem of optimum redistribution of logicalarithmetic resources in growing scope of functional tasks. Irrespective of complexity, all of them are transformed into an orgraph, which functional and topological structure is appropriately imposed on the RCF based, as a rule, on the field programmable gate array (FPGA.Due to limitation of the hardware configurations and functions realized by means of the switched logical blocks (SLB, the abovementioned problem becomes even more critical when there is a need, within the strictly allocated RCF fragment, to realize even more complex challenge in comparison with the problem which was solved during the previous computing step. In such cases it is possible to speak about graphs of big dimensions with respect to allocated RCF fragment.The article considers this problem through development of diagnostic algorithms to implement diagnostics and control of an onboard control complex of the spacecraft using RCF. It gives examples of big graphs arising with respect to allocated RCF fragment when forming the hardware levels of a diagnostic model, which, in this case, is any hardware-based algorithm of diagnostics in RCF.The article reviews examples of arising big graphs when forming the complicated diagnostic models due to drastic difference in formation of hardware levels on closely located RCF fragments. It also pays attention to big graphs emerging when the multichannel diagnostic models are formed.Three main ways to solve the problem of big graphs with respect to allocated RCF fragment are given. These are: splitting the graph into fragments, use of pop-up windows with relocating and memorizing intermediate values of functions of high hardware levels of diagnostic models, and deep adaptive update of diagnostic model.It is shown that the last of three ways is the most efficient

  8. 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

  9. Diagnostic imaging advances in murine models of colitis.

    Science.gov (United States)

    Brückner, Markus; Lenz, Philipp; Mücke, Marcus M; Gohar, Faekah; Willeke, Peter; Domagk, Dirk; Bettenworth, Dominik

    2016-01-21

    Inflammatory bowel diseases (IBD) such as Crohn's disease and ulcerative colitis are chronic-remittent inflammatory disorders of the gastrointestinal tract still evoking challenging clinical diagnostic and therapeutic situations. Murine models of experimental colitis are a vital component of research into human IBD concerning questions of its complex pathogenesis or the evaluation of potential new drugs. To monitor the course of colitis, to the present day, classical parameters like histological tissue alterations or analysis of mucosal cytokine/chemokine expression often require euthanasia of animals. Recent advances mean revolutionary non-invasive imaging techniques for in vivo murine colitis diagnostics are increasingly available. These novel and emerging imaging techniques not only allow direct visualization of intestinal inflammation, but also enable molecular imaging and targeting of specific alterations of the inflamed murine mucosa. For the first time, in vivo imaging techniques allow for longitudinal examinations and evaluation of intra-individual therapeutic response. This review discusses the latest developments in the different fields of ultrasound, molecularly targeted contrast agent ultrasound, fluorescence endoscopy, confocal laser endomicroscopy as well as tomographic imaging with magnetic resonance imaging, computed tomography and fluorescence-mediated tomography, discussing their individual limitations and potential future diagnostic applications in the management of human patients with IBD.

  10. 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.

  11. Locating eating pathology within an empirical diagnostic taxonomy: evidence from a community-based sample.

    Science.gov (United States)

    Forbush, Kelsie T; South, Susan C; Krueger, Robert F; Iacono, William G; Clark, Lee Anna; Keel, Pamela K; Legrand, Lisa N; Watson, David

    2010-05-01

    Existing structural models of psychopathology need to be expanded to include additional diagnostic constructs beyond mood, anxiety, substance use, and antisocial behavior disorders. The goal of this study was to locate eating disorders within a hierarchical structural model of psychopathology that is anchored by broad Internalizing and Externalizing factors. Participants were female adolescent twins (N = 1,434) from the Minnesota Twin Family Study. The authors compared the fit of 4 models in which eating disorders (a) defined their own diagnostic class, (b) represented a subclass within Internalizing, (c) formed a subclass within Externalizing, and (d) were allowed to cross-load on both Internalizing and Externalizing. In the best fitting model, eating disorders formed a subfactor within Internalizing. These findings underscore the value of developing more comprehensive empirically based models of psychopathology to increase researchers' understanding of diverse mental disorders.

  12. 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.

  13. Using Transport Diagnostics to Understand Chemistry Climate Model Ozone Simulations

    Science.gov (United States)

    Strahan, S. E.; Douglass, A. R.; Stolarski, R. S.; Akiyoshi, H.; Bekki, S.; Braesicke, P.; Butchart, N.; Chipperfield, M. P.; Cugnet, D.; Dhomse, S.; Frith, S. M.; Gettleman, A.; Hardiman, S. C.; Kinnison, D. E.; Lamarque, J.-F.; Mancini, E.; Marchand, M.; Michou, M.; Morgenstern, O.; Nakamura, T.; Olivie, D.; Pawson, S.; Pitari, G.; Plummer, D. A.; Pyle, J. A.

    2010-01-01

    We demonstrate how observations of N2O and mean age in the tropical and midlatitude lower stratosphere (LS) can be used to identify realistic transport in models. The results are applied to 15 Chemistry Climate Models (CCMs) participating in the 2010 WMO assessment. Comparison of the observed and simulated N2O/mean age relationship identifies models with fast or slow circulations and reveals details of model ascent and tropical isolation. The use of this process-oriented N2O/mean age diagnostic identifies models with compensating transport deficiencies that produce fortuitous agreement with mean age. We compare the diagnosed model transport behavior with a model's ability to produce realistic LS O3 profiles in the tropics and midlatitudes. Models with the greatest tropical transport problems show the poorest agreement with observations. Models with the most realistic LS transport agree more closely with LS observations and each other. We incorporate the results of the chemistry evaluations in the SPARC CCMVal Report (2010) to explain the range of CCM predictions for the return-to-1980 dates for global (60 S-60 N) and Antarctic column ozone. Later (earlier) Antarctic return dates are generally correlated to higher (lower) vortex Cl(sub y) levels in the LS, and vortex Cl(sub y) is generally correlated with the model's circulation although model Cl(sub y) chemistry or Cl(sub y) conservation can have a significant effect. In both regions, models that have good LS transport produce a smaller range of predictions for the return-to-1980 ozone values. This study suggests that the current range of predicted return dates is unnecessarily large due to identifiable model transport deficiencies.

  14. 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.

  15. A Chinese literature overview on ultra-weak photon emission as promising technology for studying system-based diagnostics.

    Science.gov (United States)

    He, Min; Sun, Mengmeng; van Wijk, Eduard; van Wietmarschen, Herman; van Wijk, Roeland; Wang, Zhihong; Wang, Mei; Hankemeier, Thomas; van der Greef, Jan

    2016-04-01

    To present the possibilities pertaining to linking ultra-weak photon emission (UPE) with Chinese medicine-based diagnostics principles, we conducted a review of Chinese literature regarding UPE with respect to a systems view of diagnostics. Data were summarized from human clinical studies and animal models published from 1979 through 1998. The research fields can be categorized as follows: (1) human physiological states measured using UPE; (2) characteristics of human UPE in relation to various pathological states; and (3) the relationship between diagnosis (e.g., Chinese syndromes) and the dynamics of UPE in animal models. We conclude that UPE has clear potential in terms of understanding the systems view on health and disease as described using Chinese medicine-based diagnostics, particularly from a biochemistry-based regulatory perspective. Linking UPE with metabolomics can further bridge biochemistry-based Western diagnostics with the phenomenology-based Chinese diagnostics, thus opening new avenues for studying systems diagnostics in the early stage of disease, for prevention-based strategies, as well as for systems-based intervention in chronic disease.

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

    Science.gov (United States)

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

    2017-03-01

    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.

  17. 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.

  18. Molecular diagnostics based on clustering dynamics of magnetic nanobeads

    DEFF Research Database (Denmark)

    Donolato, Marco; Bejhed, Rebecca S.; de la Torre, Teresa Zardán Gómez;

    2014-01-01

    The detection of specific DNA sequences has facilitated the diagnosis and targeted treatment of several human diseases. Although great advances have been made in the last few years, the detection of certain pathogenic bacteria is still based on bacterial culture and colony counts or on the polyme......The detection of specific DNA sequences has facilitated the diagnosis and targeted treatment of several human diseases. Although great advances have been made in the last few years, the detection of certain pathogenic bacteria is still based on bacterial culture and colony counts...... transmission modulation caused by the AC magnetic field-stimulated reversible formation and disruption of elongated MNB supra-structures during a cycle of the uniaxial applied magnetic field. As a specific clinically relevant diagnostic case, we detect DNA coils formed via padlock probe recognition...

  19. 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

  20. 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

  1. 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

  2. Diagnostic Modeling of PAMS VOC Observation on Regional Scale Environment

    Science.gov (United States)

    Chen, S.; Liu, T.; Chen, T.; Ou Yang, C.; Wang, J.; Chang, J. S.

    2008-12-01

    While a number of gas-phase chemical mechanisms, such as CBM-Z, RADM2, SAPRC-07 had been successful in studying gas-phase atmospheric chemical processes they all used some lumped organic species to varying degrees. Photochemical Assessment Monitoring Stations (PAMS) has been in use for over ten years and yet it is not clear how the detailed organic species measured by PAMS compare to the lumped model species under regional-scale transport and chemistry interactions. By developing a detailed mechanism specifically for the PAMS organics and embedding this diagnostic model within a regional-scale transport and chemistry model we can then directly compare PAMS observation with regional-scale model simulations. We modify one regional-scale chemical transport model (Taiwan Air Quality Model, TAQM) by adding a submodel with chemical mechanism for interactions of the 56 species observed by PAMS. This submodel then calculates the time evolution of these 56 PAMS species within the environment established by TAQM. It is assumed that TAQM can simulate the overall regional-scale environment including impact of regional-scale transport and time evolution of oxidants and radicals. Therefore we can scale these influences to the PAMS organic species and study their time evolution with their species-specific source functions, meteorological transport, and chemical interactions. Model simulations of each species are compared with PAMS hourly surface measurements. A case study located in a metropolitan area in central Taiwan showed that with wind speeds lower than 3 m/s, when meteorological simulation is comparable with observation, the diurnal pattern of each species performs well with PAMS data. It is found that for many observations meteorological transport is an influence and that local emissions of specific species must be represented correctly. At this time there are still species that cannot be modeled properly. We suspect this is mostly due to lack of information on local

  3. Paper-Origami-Based Multiplexed Malaria Diagnostics from Whole Blood.

    Science.gov (United States)

    Xu, Gaolian; Nolder, Debbie; Reboud, Julien; Oguike, Mary C; van Schalkwyk, Donelly A; Sutherland, Colin J; Cooper, Jonathan M

    2016-12-05

    We demonstrate, for the first time, the multiplexed determination of microbial species from whole blood using the paper-folding technique of origami to enable the sequential steps of DNA extraction, loop-mediated isothermal amplification (LAMP), and array-based fluorescence detection. A low-cost handheld flashlight reveals the presence of the final DNA amplicon to the naked eye, providing a "sample-to-answer" diagnosis from a finger-prick volume of human blood, within 45 min, with minimal user intervention. To demonstrate the method, we showed the identification of three species of Plasmodium, analyzing 80 patient samples benchmarked against the gold-standard polymerase chain reaction (PCR) assay in an operator-blinded study. We also show that the test retains its diagnostic accuracy when using stored or fixed reference samples.

  4. On Diagnostic Checking of Vector ARMA-GARCH Models with Gaussian and Student-t Innovations

    Directory of Open Access Journals (Sweden)

    Yongning Wang

    2013-04-01

    Full Text Available This paper focuses on the diagnostic checking of vector ARMA (VARMA models with multivariate GARCH errors. For a fitted VARMA-GARCH model with Gaussian or Student-t innovations, we derive the asymptotic distributions of autocorrelation matrices of the cross-product vector of standardized residuals. This is different from the traditional approach that employs only the squared series of standardized residuals. We then study two portmanteau statistics, called Q1(M and Q2(M, for model checking. A residual-based bootstrap method is provided and demonstrated as an effective way to approximate the diagnostic checking statistics. Simulations are used to compare the performance of the proposed statistics with other methods available in the literature. In addition, we also investigate the effect of GARCH shocks on checking a fitted VARMA model. Empirical sizes and powers of the proposed statistics are investigated and the results suggest a procedure of using jointly Q1(M and Q2(M in diagnostic checking. The bivariate time series of FTSE 100 and DAX index returns is used to illustrate the performance of the proposed portmanteau statistics. The results show that it is important to consider the cross-product series of standardized residuals and GARCH effects in model checking.

  5. 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.

  6. Ewing sarcoma family of tumors: a model for the new era of integrated laboratory diagnostics.

    Science.gov (United States)

    Khoury, Joseph D

    2008-01-01

    The Ewing sarcoma family of tumors (ESFT) represents one of the best models illustrating the multifaceted approach to the diagnosis of cancer that has evolved over the past decade. ESFT encompasses tumors that arise in bone or soft tissues and may have disparate histologic features. As a result, it was not until the discovery that these tumors share a common underlying molecular pathogenesis (chromosomal translocations involving the EWS gene and one of several members of the ETS family of transcription factors) that significant advances in the diagnosis and therapy of ESFT became possible. As a result, ESFT has come to embody the amalgamation of classical diagnostic tools, such as histology and routine microscopy, with newer techniques, such as immunohistochemistry and molecular techniques; the latter include PCR-based methods and fluorescence in situ hybridization. This review will address the features of ESFT and how it has emerged as a model for the new era of integrated diagnostics.

  7. A mathematical model of penile vascular dysfunction and its application to a new diagnostic technique.

    Science.gov (United States)

    Barnea, Ofer; Hayun, Shimon; Gillon, Gabriel

    2007-04-01

    A noninvasive diagnostic device was developed to assess the vascular origin and severity of penile dysfunction. It was designed and studied using both a mathematical model of penile hemodynamics and preliminary experiments on healthy young volunteers. The device is based on the application of an external pressure (or vacuum) perturbation to the penis following the induction of erection. The rate of volume change while the penis returns to its natural condition is measured using a noninvasive system that includes a volume measurement mechanism that has very low friction, thereby not affecting the measured system. The rate of volume change (net flow) is obtained and analyzed. Simulations using a mathematical model show that the device is capable of differentiating between arterial insufficiency and venous leak and indicate the severity of each. In preliminary measurements on young healthy volunteers, the feasibility of the measurement has been demonstrated. More studies are required to confirm the diagnostic value of the measurements.

  8. Comparison of prognostic and diagnostic surface flux modeling approaches over the Nile River basin

    Science.gov (United States)

    Yilmaz, M. Tugrul; Anderson, Martha C.; Zaitchik, Ben; Hain, Chris R.; Crow, Wade T.; Ozdogan, Mutlu; Chun, Jong Ahn; Evans, Jason

    2014-01-01

    Regional evapotranspiration (ET) can be estimated using diagnostic remote sensing models, generally based on principles of energy balance closure, or with spatially distributed prognostic models that simultaneously balance both energy and water budgets over landscapes using predictive equations for land surface temperature and moisture states. Each modeling approach has complementary advantages and disadvantages, and in combination they can be used to obtain more accurate ET estimates over a variety of land and climate conditions, particularly for areas with limited ground truth data. In this study, energy and water flux estimates from diagnostic Atmosphere-Land Exchange (ALEXI) and prognostic Noah land surface models are compared over the Nile River basin between 2007 and 2011. A second remote sensing data set, generated with Penman-Monteith approach as implemented in the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD16 ET product, is also included as a comparative technique. In general, spatial and temporal distributions of flux estimates from ALEXI and Noah are similar in regions where the climate is temperate and local rainfall is the primary source of water available for ET. However, the diagnostic ALEXI model is better able to retrieve ET signals not directly coupled with the local precipitation rates, for example, over irrigated agricultural areas or regions influenced by shallow water tables. These hydrologic features are not well represented by either Noah or MOD16. Evaluation of consistency between diagnostic and prognostic model estimates can provide useful information about relative product skill, particularly over regions where ground data are limited or nonexistent as in the Nile basin.

  9. Medical diagnostics by laser-based analysis of exhaled breath

    Science.gov (United States)

    Giubileo, Gianfranco

    2002-08-01

    IMany trace gases can be found in the exhaled breath, some of them giving the possibility of a non invasive diagnosis of related diseases or allowing the monitoring of the disease in the course of its therapy. In the present lecture the principle of medical diagnosis based on the breath analysis will be introduced and the detection of trace gases in exhaled breath by high- resolution molecular spectroscopy in the IR spectral region will be discussed. A number of substrates and the optical systems for their laser detection will be reported. The following laser based experimental systems has been realised in the Molecular Spectroscopy Laboratory in ENEA in Frascati for the analysis of specific substances in the exhaled breath. A tuneable diode laser absorption spectroscopy (TDLAS) appartus for the measurement of 13C/12C isotopic ratio in carbon dioxide, a TDLAS apparatus for the detection of CH4 and a CO2 laser based photoacoustic system to detect trace ethylene at atmospheric pressure. The experimental set-up for each one of the a.m. optical systems will be shown and the related medical applications will be illustrated. The concluding remarks will be focuses on chemical species that are of major interest for medical people today and their diagnostic ability.

  10. Diagnostic calibration of a hydrological model in an alpine area by hydrograph partitioning

    Directory of Open Access Journals (Sweden)

    Z. H. He

    2014-12-01

    Full Text Available Hydrological modeling can exploit informative signatures extracted from long time sequences of observed streamflow for parameter calibration and model diagnosis. In this study we explore the diagnostic potential of hydrograph partitioning for model calibration in alpine areas, where meltwater from snow and glaciers are important sources for river runoff (in addition to rainwater. We propose an index-based method to partition the hydrograph according to dominant runoff water sources, and a diagnostic approach to calibrate an alpine hydrological model. First, by accounting for the seasonal variability of precipitation and the altitudinal variability of temperature and snow/glacier coverage, we develop a set of indices to indicate the daily status of runoff generation from each type of water source (i.e. glacier meltwater, snow meltwater, rainwater, and groundwater. Second, these indices are used to partition a hydrograph into four parts associated with four different combinations of dominant water sources (i.e. groundwater, groundwater + snow meltwater, groundwater + snow meltwater + glacier meltwater, groundwater + snow meltwater + glacier meltwater + rainwater. Third, the hydrological model parameters are grouped by the associated runoff generation mechanism, and each group is calibrated to match the corresponding hydrograph partition in a stepwise and iterative manner. Similar to use of the regime curve to diagnose seasonality of streamflow, the hydrograph partitioning curve based on a dominant runoff water source (more briefly called the partitioning curve, not necessarily continuous can serve as a diagnostic signature that helps relate model performance to model components. The proposed methods are demonstrated via application of a semi-distributed hydrological model (THREW to the Tailan River basin (1324 km2 in the Tianshan Mountain of China.

  11. Ontology-Oriented Diagnostic System for Traditional Chinese Medicine Based on Relation Refinement

    Directory of Open Access Journals (Sweden)

    Peiqin Gu

    2013-01-01

    Full Text Available 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.

  12. 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.

  13. 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...

  14. 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

  15. 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.

  16. 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...

  17. A stochastic model to determine the economic value of changing diagnostic test characteristics for identification of cattle for treatment of bovine respiratory disease.

    Science.gov (United States)

    Theurer, M E; White, B J; Larson, R L; Schroeder, T C

    2015-03-01

    Bovine respiratory disease is an economically important syndrome in the beef industry, and diagnostic accuracy is important for optimal disease management. The objective of this study was to determine whether improving diagnostic sensitivity or specificity was of greater economic value at varied levels of respiratory disease prevalence by using Monte Carlo simulation. Existing literature was used to populate model distributions of published sensitivity, specificity, and performance (ADG, carcass weight, yield grade, quality grade, and mortality risk) differences among calves based on clinical respiratory disease status. Data from multiple cattle feeding operations were used to generate true ranges of respiratory disease prevalence and associated mortality. Input variables were combined into a single model that calculated estimated net returns for animals by diagnostic category (true positive, false positive, false negative, and true negative) based on the prevalence, sensitivity, and specificity for each iteration. Net returns for each diagnostic category were multiplied by the proportion of animals in each diagnostic category to determine group profitability. Apparent prevalence was categorized into low (diagnostic specificity, perhaps through a confirmatory test interpreted in series or pen-level diagnostics, can increase diagnostic value more than improving sensitivity. Mortality risk was the primary driver for net returns. The results from this study are important for determining future research priorities to analyze diagnostic techniques for bovine respiratory disease and provide a novel way for modeling diagnostic tests.

  18. [SCAN system--semi-structured interview based on diagnostic criteria].

    Science.gov (United States)

    Adamowski, Tomasz; Kiejna, Andrzej; Hadryś, Tomasz

    2006-01-01

    This paper presents the main features of contemporary diagnostic systems which are implemented into the SCAN--modern and semi-structured diagnostic interview. The concepts of further development of the classifications, rationale for operationalized diagnostic criteria and for the divisional approach to mental diagnoses will be in focus. The structure and components of SCAN ver. 2.1 (WHO), i.e. Present State Examination--10th edition, Item Group Checklist, Clinical History Schedule, Glossary of Definitions and computer software with the diagnostic algorithm: I-Shell, as well as rules for a reliable use of diagnostic rating scales, will be discussed within the scope of this paper. The materials and training sets necessary for the learning of proper use of the SCAN, especially training sets for SCAN Training Centers and the Reference Manual--a form of guidebook for SCAN shall be introduced. Finally the paper will present evidence that SCAN is an instrument feasible in different cultural settings. Reliability and validity data of SCAN will also be dealt with indicating that SCAN could be widely used in research studies as well as in everyday clinical practice facilitating more detailed diagnostic approach to a patient.

  19. Diagnostic Method of Diabetes Based on Support Vector Machine and Tongue Images

    Science.gov (United States)

    Hu, Xiaojuan; Chen, Qingguang; Tu, Liping; Huang, Jingbin; Cui, Ji

    2017-01-01

    Objective. The purpose of this research is to develop a diagnostic method of diabetes based on standardized tongue image using support vector machine (SVM). Methods. Tongue images of 296 diabetic subjects and 531 nondiabetic subjects were collected by the TDA-1 digital tongue instrument. Tongue body and tongue coating were separated by the division-merging method and chrominance-threshold method. With extracted color and texture features of the tongue image as input variables, the diagnostic model of diabetes with SVM was trained. After optimizing the combination of SVM kernel parameters and input variables, the influences of the combinations on the model were analyzed. Results. After normalizing parameters of tongue images, the accuracy rate of diabetes predication was increased from 77.83% to 78.77%. The accuracy rate and area under curve (AUC) were not reduced after reducing the dimensions of tongue features with principal component analysis (PCA), while substantially saving the training time. During the training for selecting SVM parameters by genetic algorithm (GA), the accuracy rate of cross-validation was grown from 72% or so to 83.06%. Finally, we compare with several state-of-the-art algorithms, and experimental results show that our algorithm has the best predictive accuracy. Conclusions. The diagnostic method of diabetes on the basis of tongue images in Traditional Chinese Medicine (TCM) is of great value, indicating the feasibility of digitalized tongue diagnosis. PMID:28133611

  20. Diagnostic Method of Diabetes Based on Support Vector Machine and Tongue Images

    Directory of Open Access Journals (Sweden)

    Jianfeng Zhang

    2017-01-01

    Full Text Available Objective. The purpose of this research is to develop a diagnostic method of diabetes based on standardized tongue image using support vector machine (SVM. Methods. Tongue images of 296 diabetic subjects and 531 nondiabetic subjects were collected by the TDA-1 digital tongue instrument. Tongue body and tongue coating were separated by the division-merging method and chrominance-threshold method. With extracted color and texture features of the tongue image as input variables, the diagnostic model of diabetes with SVM was trained. After optimizing the combination of SVM kernel parameters and input variables, the influences of the combinations on the model were analyzed. Results. After normalizing parameters of tongue images, the accuracy rate of diabetes predication was increased from 77.83% to 78.77%. The accuracy rate and area under curve (AUC were not reduced after reducing the dimensions of tongue features with principal component analysis (PCA, while substantially saving the training time. During the training for selecting SVM parameters by genetic algorithm (GA, the accuracy rate of cross-validation was grown from 72% or so to 83.06%. Finally, we compare with several state-of-the-art algorithms, and experimental results show that our algorithm has the best predictive accuracy. Conclusions. The diagnostic method of diabetes on the basis of tongue images in Traditional Chinese Medicine (TCM is of great value, indicating the feasibility of digitalized tongue diagnosis.

  1. Diagnostic Method of Diabetes Based on Support Vector Machine and Tongue Images.

    Science.gov (United States)

    Zhang, Jianfeng; Xu, Jiatuo; Hu, Xiaojuan; Chen, Qingguang; Tu, Liping; Huang, Jingbin; Cui, Ji

    2017-01-01

    Objective. The purpose of this research is to develop a diagnostic method of diabetes based on standardized tongue image using support vector machine (SVM). Methods. Tongue images of 296 diabetic subjects and 531 nondiabetic subjects were collected by the TDA-1 digital tongue instrument. Tongue body and tongue coating were separated by the division-merging method and chrominance-threshold method. With extracted color and texture features of the tongue image as input variables, the diagnostic model of diabetes with SVM was trained. After optimizing the combination of SVM kernel parameters and input variables, the influences of the combinations on the model were analyzed. Results. After normalizing parameters of tongue images, the accuracy rate of diabetes predication was increased from 77.83% to 78.77%. The accuracy rate and area under curve (AUC) were not reduced after reducing the dimensions of tongue features with principal component analysis (PCA), while substantially saving the training time. During the training for selecting SVM parameters by genetic algorithm (GA), the accuracy rate of cross-validation was grown from 72% or so to 83.06%. Finally, we compare with several state-of-the-art algorithms, and experimental results show that our algorithm has the best predictive accuracy. Conclusions. The diagnostic method of diabetes on the basis of tongue images in Traditional Chinese Medicine (TCM) is of great value, indicating the feasibility of digitalized tongue diagnosis.

  2. How to make DNA count: DNA-based diagnostic tools in veterinary parasitology.

    Science.gov (United States)

    Hunt, P W; Lello, J

    2012-05-04

    Traditional methods for the diagnosis of parasitic helminth infections of livestock have a number of limitations, such as the inability to distinguish mixed-species infections, a heavy reliance on technical experience and also sub-sampling errors. Some of these limitations may be overcome through the development of rapid and accurate DNA-based tests. For example, DNA-based tests can specifically detect individual species in a mixed infection at either the larval or egg stages, in the absence of morphological differences among species. Even so, some diagnostic problems remain the same, irrespective of whether a DNA-based or traditional method is used. For example, sub-sampling errors from an aggregated distribution are likely to persist. It is proposed, however, that DNA-based diagnostic technologies offer an opportunity to expand diagnostic capabilities, and are discussed in the current review. The future introduction of DNA-based diagnostic technologies into routine diagnostic settings will also be discussed.

  3. 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.

  4. 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...

  5. Modeling Mid-infrared Diagnostics of Obscured Quasars and Starbursts

    Science.gov (United States)

    Snyder, Gregory F.; Hayward, Christopher C.; Sajina, Anna; Jonsson, Patrik; Cox, Thomas J.; Hernquist, Lars; Hopkins, Philip F.; Yan, Lin

    2013-05-01

    We analyze the link between active galactic nuclei (AGNs) and mid-infrared flux using dust radiative transfer calculations of starbursts realized in hydrodynamical simulations. Focusing on the effects of galaxy dust, we evaluate diagnostics commonly used to disentangle AGN and star formation in ultraluminous infrared galaxies (ULIRGs). We examine these quantities as a function of time, viewing angle, dust model, AGN spectrum, and AGN strength in merger simulations representing two possible extremes of the ULIRG population: one is a typical gas-rich merger at z ~ 0, and the other is characteristic of extremely obscured starbursts at z ~ 2-4. This highly obscured burst begins star-formation-dominated with significant polycyclic aromatic hydrocarbon (PAH) emission, and ends with a ~109 yr period of red near-IR colors. At coalescence, when the AGN is most luminous, dust obscures the near-infrared AGN signature, reduces the relative emission from PAHs, and enhances the 9.7 μm absorption by silicate grains. Although generally consistent with previous interpretations, our results imply none of these indicators can unambiguously estimate the AGN luminosity fraction in all cases. Motivated by the simulations, we show that a combination of the extinction feature at 9.7 μm, the PAH strength, and a near-infrared slope can simultaneously constrain the AGN fraction and dust grain distribution for a wide range of obscuration. We find that this indicator, accessible to the James Webb Space Telescope, may estimate the AGN power as tightly as the hard X-ray flux alone, thereby providing a valuable future cross-check and constraint for large samples of distant ULIRGs.

  6. MODELING MID-INFRARED DIAGNOSTICS OF OBSCURED QUASARS AND STARBURSTS

    Energy Technology Data Exchange (ETDEWEB)

    Snyder, Gregory F.; Jonsson, Patrik; Hernquist, Lars [Harvard-Smithsonian Center for Astrophysics, 60 Garden Street, Cambridge, MA 02138 (United States); Hayward, Christopher C. [Heidelberger Institut fuer Theoretische Studien, Schloss-Wolfsbrunnenweg 35, D-69118 Heidelberg (Germany); Sajina, Anna [Department of Physics and Astronomy, Tufts University, 4 Colby Street, Medford, MA 02155 (United States); Cox, Thomas J. [Carnegie Observatories, 813 Santa Barbara Street, Pasadena, CA 91101 (United States); Hopkins, Philip F. [Department of Astronomy, University of California at Berkeley, C-208 Hearst Field Annex, Berkeley, CA 94720 (United States); Yan Lin, E-mail: gsnyder@cfa.harvard.edu [Infrared Processing and Analysis Center, California Institute of Technology, Pasadena, CA 91125 (United States)

    2013-05-10

    We analyze the link between active galactic nuclei (AGNs) and mid-infrared flux using dust radiative transfer calculations of starbursts realized in hydrodynamical simulations. Focusing on the effects of galaxy dust, we evaluate diagnostics commonly used to disentangle AGN and star formation in ultraluminous infrared galaxies (ULIRGs). We examine these quantities as a function of time, viewing angle, dust model, AGN spectrum, and AGN strength in merger simulations representing two possible extremes of the ULIRG population: one is a typical gas-rich merger at z {approx} 0, and the other is characteristic of extremely obscured starbursts at z {approx} 2-4. This highly obscured burst begins star-formation-dominated with significant polycyclic aromatic hydrocarbon (PAH) emission, and ends with a {approx}10{sup 9} yr period of red near-IR colors. At coalescence, when the AGN is most luminous, dust obscures the near-infrared AGN signature, reduces the relative emission from PAHs, and enhances the 9.7 {mu}m absorption by silicate grains. Although generally consistent with previous interpretations, our results imply none of these indicators can unambiguously estimate the AGN luminosity fraction in all cases. Motivated by the simulations, we show that a combination of the extinction feature at 9.7 {mu}m, the PAH strength, and a near-infrared slope can simultaneously constrain the AGN fraction and dust grain distribution for a wide range of obscuration. We find that this indicator, accessible to the James Webb Space Telescope, may estimate the AGN power as tightly as the hard X-ray flux alone, thereby providing a valuable future cross-check and constraint for large samples of distant ULIRGs.

  7. Integrating molecular diagnostics into histopathology training: the Belfast model.

    Science.gov (United States)

    Flynn, C; James, J; Maxwell, P; McQuaid, S; Ervine, A; Catherwood, M; Loughrey, M B; McGibben, D; Somerville, J; McManus, D T; Gray, M; Herron, B; Salto-Tellez, M

    2014-07-01

    Molecular medicine is transforming modern clinical practice, from diagnostics to therapeutics. Discoveries in research are being incorporated into the clinical setting with increasing rapidity. This transformation is also deeply changing the way we practise pathology. The great advances in cell and molecular biology which have accelerated our understanding of the pathogenesis of solid tumours have been embraced with variable degrees of enthusiasm by diverse medical professional specialties. While histopathologists have not been prompt to adopt molecular diagnostics to date, the need to incorporate molecular pathology into the training of future histopathologists is imperative. Our goal is to create, within an existing 5-year histopathology training curriculum, the structure for formal substantial teaching of molecular diagnostics. This specialist training has two main goals: (1) to equip future practising histopathologists with basic knowledge of molecular diagnostics and (2) to create the option for those interested in a subspecialty experience in tissue molecular diagnostics to pursue this training. It is our belief that this training will help to maintain in future the role of the pathologist at the centre of patient care as the integrator of clinical, morphological and molecular information.

  8. Exponential quadruplex priming amplification for DNA-based isothermal diagnostics.

    Science.gov (United States)

    Partskhaladze, Tamar; Taylor, Adam; Lomidze, Levan; Gvarjaladze, David; Kankia, Besik

    2015-02-01

    Polymerase chain reaction (PCR) is a method of choice for molecular diagnostics. However, PCR relies on thermal cycling, which is not compatible with the goals of point-of-care diagnostics. A simple strategy to turn PCR into an isothermal method would be to use specific primers, which upon polymerase elongation can self-dissociate from the primer-binding sites. We recently demonstrated that a monomolecular DNA quadruplex, GGGTGGGTGGGTGGG, meets these requirements, which led to the development of the linear versions of quadruplex priming amplification (QPA). Here we demonstrate exponential version of isothermal QPA, which allows an unprecedented 10(10)-fold amplification of DNA signal in less than 40 min.

  9. 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.

  10. Intraoral fiber-optic-based diagnostic for periodontal disease

    Science.gov (United States)

    Colston, Bill W., Jr.; Gutierrez, Dora M.; Everett, Matthew J.; Brown, Steve B.; Langry, Kevin C.; Cox, Weldon R.; Johnson, Paul W.; Roe, Jeffrey N.

    2000-05-01

    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 senor. 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 too.

  11. OIL MONITORING DIAGNOSTIC CRITERIONS BASED ON MAXIMUM ENTROPY PRINCIPLE

    Institute of Scientific and Technical Information of China (English)

    Huo Hua; Li Zhuguo; Xia Yanchun

    2005-01-01

    A method of applying maximum entropy probability density estimation approach to constituting diagnostic criterions of oil monitoring data is presented. The method promotes the precision of diagnostic criterions for evaluating the wear state of mechanical facilities, and judging abnormal data. According to the critical boundary points defined, a new measure on monitoring wear state and identifying probable wear faults can be got. The method can be applied to spectrometric analysis and direct reading ferrographic analysis. On the basis of the analysis and discussion of two examples of 8NVD48A-2U diesel engines, the practicality is proved to be an effective method in oil monitoring.

  12. Early diagnostic method for sepsis based on neutrophil MR imaging

    Directory of Open Access Journals (Sweden)

    Shanhua Han

    2015-06-01

    Conclusion: Mouse and human neutrophils could be more effectively labelled by Mannan-coated SPION in vitro than Feridex. Sepsis analog neutrophils labelled by Mannan-coated SPIONs could be efficiently detected on MR images, which may serve as an early diagnostic method for sepsis.

  13. A reduced model for the ICF gamma-ray reaction history diagnostic

    Energy Technology Data Exchange (ETDEWEB)

    Schmitt, Mark J [Los Alamos National Laboratory; Wilson, Douglas C [Los Alamos National Laboratory; Hoffman, Nelson M [Los Alamos National Laboratory; Langenbrunner, Jamie R [Los Alamos National Laboratory; Hermann, H W [Los Alamos National Laboratory; Kim, Y H [Los Alamos National Laboratory; Young, C S [Los Alamos National Laboratory; Evans, S C [Los Alamos National Laboratory; Cerjan, C J [LLNL; Stoeffl, Wolfgang [LLNL; Munro, D H [LLNL; Dauffy, L S [LLNL; Miller, K M [LIVERMORE; Horsfield, C J [AWE; Rubery, M S [AWE

    2009-01-01

    An analytic model for the gamma reaction history (GRH) diagnostic to be fielded on the National Ignition Facility is described. The application of the GRH diagnostic for the measurement of capsule rho-R during burn using 4.4 MeV carbon gamma rays is demonstrated by simulation.

  14. A reduced model for the ICF Gamma-Ray reaction history diagnostic

    Science.gov (United States)

    Schmitt, M. J.; Wilson, D. C.; Hoffman, N. M.; Langenbrunner, J. R.; Herrmann, H. W.; Kim, Y. H.; Young, C. S.; Evans, S. C.; Cerjan, C. J.; Stoeffl, Wolfgang; Munro, D. H.; Dauffy, L. S.; Miller, K. M.; Horsfield, C. J.; Rubery, M. S.

    2010-08-01

    An analytic model for the gamma reaction history (GRH) diagnostic to be fielded on the National Ignition Facility is described. The application of the GRH diagnostic for the measurement of capsule rho-R during burn using 4.4 MeV carbon gamma rays is demonstrated by simulation.

  15. Have Cognitive Diagnostic Models Delivered Their Goods? Some Substantial and Methodological Concerns

    Science.gov (United States)

    Wilhelm, Oliver; Robitzsch, Alexander

    2009-01-01

    The paper by Rupp and Templin (2008) is an excellent work on the characteristics and features of cognitive diagnostic models (CDM). In this article, the authors comment on some substantial and methodological aspects of this focus paper. They organize their comments by going through issues associated with the terms "cognitive," "diagnostic" and…

  16. Flexible Substrate-Based Devices for Point-of-Care Diagnostics.

    Science.gov (United States)

    Wang, ShuQi; Chinnasamy, Thiruppathiraja; Lifson, Mark A; Inci, Fatih; Demirci, Utkan

    2016-11-01

    Point-of-care (POC) diagnostics play an important role in delivering healthcare, particularly for clinical management and disease surveillance in both developed and developing countries. Currently, the majority of POC diagnostics utilize paper substrates owing to affordability, disposability, and mass production capability. Recently, flexible polymer substrates have been investigated due to their enhanced physicochemical properties, potential to be integrated into wearable devices with wireless communications for personalized health monitoring, and ability to be customized for POC diagnostics. Here, we focus on the latest advances in developing flexible substrate-based diagnostic devices, including paper and polymers, and their clinical applications.

  17. 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 study…

  18. Cost-effectiveness modelling in diagnostic imaging: a stepwise approach

    NARCIS (Netherlands)

    Sailer, A.M.; Zwam, W.H. van; Wildberger, J.E.; Grutters, J.P.C.

    2015-01-01

    Diagnostic imaging (DI) is the fastest growing sector in medical expenditures and takes a central role in medical decision-making. The increasing number of various and new imaging technologies induces a growing demand for cost-effectiveness analysis (CEA) in imaging technology assessment. In this ar

  19. The Feasibility of a Diagnostic Media Test System Model.

    Science.gov (United States)

    Rapp, Alfred V.

    Research investigated the feasibility of a diagnostic media test system. Two distinct tests were developed for sixth grade and university populations, each having: 1) a main phase with three specific teaching sequences, one for each media form; 2) test items for each teaching sequence; and 3) a validation phase with one teaching sequence…

  20. New Developments in Structural Health Monitoring Based on Diagnostic Lamb Wave

    Institute of Scientific and Technical Information of China (English)

    Shenfang YUAN; Yingdi XU; Ge PENG

    2004-01-01

    Structure health monitoring based on diagnostic Lamb waves has been found to be one of the most promising techniques recently. This paper has a brief review of the new developments on this method including the basic novel of the method, fundamentals and mathematics of Lamb wave propagation, narrowband and wideband Lamb wave excitation methods, optimization of excitation factors and diagnostic Lamb wave interpretation methods.

  1. Design, modeling, and diagnostics of microplasma generation at microwave frequency

    Science.gov (United States)

    Miura, Naoto

    Plasmas are partially ionized gases that find wide utility in the processing of materials, especially in integrated circuit fabrication. Most industrial applications of plasma occur in near-vacuum where the electrons are hot (>10,000 K) but the gas remains near room temperature. Typical atmospheric plasmas, such as arcs, are hot and destructive to sensitive materials. Recently the emerging field of microplasmas has demonstrated that atmospheric ionization of cold gases is possible if the plasma is microscopic. This dissertation investigates the fundamental physical properties of two classes of microplasma, both driven by microwave electric fields. The extension of point-source microplasmas into a line-shaped plasma is also described. The line-shape plasma is important for atmospheric processing of materials using roll-coating. Microplasma generators driven near 1 GHz were designed using microstrip transmission lines and characterized using argon near atmospheric pressure. The electrical characteristics of the microplasma including the discharge voltage, current and resistance were estimated by comparing the experimental power reflection coefficient to that of an electromagnetic simulation. The gas temperature, argon metastable density and electron density were obtained by optical absorption and emission spectroscopy. The microscopic internal plasma structure was probed using spatially-resolved diode laser absorption spectroscopy of excited argon states. The spatially resolved diagnostics revealed that argon metastable atoms were depleted within the 200mum core of the microplasma where the electron density was maximum. Two microplasma generators, the split-ring resonator (SRR) and the transmission line (T-line) generator, were compared. The SRR ran efficiently with a high impedance plasma (>1000 O) and was stabilized by the self-limiting of absorbed power (<1W) as a lower impedance plasma caused an impedance mismatch. Gas temperatures were <1000 K and electron

  2. Knowledge-based diagnostic system with probabilistic approach

    Directory of Open Access Journals (Sweden)

    Adina COCU

    2007-12-01

    Full Text Available This paper presents a knowledge learning diagnostic approach implemented in an educational system. Probabilistic inference is used here to diagnose knowledge understanding level and to reason about probable cause of learner’s misconceptions. When one learner takes an assessment, the system use probabilistic reasoning and will advice the learner about the most appropriate error cause and will also provide, the conforming part of theory which treats errors related to his misconceptions.

  3. 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...

  4. Absolute calibration of a multilayer-based XUV diagnostic

    CERN Document Server

    Stuik, R; Tümmler, J; Bijkerk, F

    2002-01-01

    A portable, universal narrowband XUV diagnostic suitable for calibration of various XUV light sources, was built, tested and fully calibrated. The diagnostic allows measurement of the absolute XUV energy and average power in two selected wavelength bands, at 11.4 and 13.4 nm. In addition, the pulse-to-pulse and long-term XUV stability of the source can be assessed, as well as the contamination of multilayer XUV optics exposed to the source. This paper describes the full calibration procedure: all optical elements were calibrated at the wavelength of operation by Physikalisch-Technische Bundesanstalt at the storage ring Bessy II, a full analysis of geometrical factors was done, and the influence of the spectral emissivity of the source on the calibration was analyzed in detail. The calibration was performed both for the centroid wavelength as for the full bandwidth of the diagnostic. The total uncertainty in the absolute calibration allowed measurement of source characteristics with an uncertainty of less than...

  5. An intelligent diagnostic aid (ida) based upon the simulated and operational experience

    Energy Technology Data Exchange (ETDEWEB)

    Zuenkov, M.; Poletykin, A. [Institute of Control Sciences Moscow (Russian Federation); Marsiletti, M. [Ansaldo - Nuclear Division (Italy)

    1999-07-01

    A diagnostic system has been developed addressed to timely trouble shooting in process plants during all operational modes. The theory of this diagnostic system is related with the usage of learning methods for automatic generation of knowledge bases. This approach enables the conversion of 'cause to effect' relations into 'effect to possible causes' ones. As applied to technical diagnosis, this allows one to generate troubleshooting rules of the kind 'symptoms to possible diagnosis' through 'failure to symptoms' relations. The problem of diagnostic rule generation is, thus, reduced to obtaining samples of the symptoms, that is the well known problem of failure modelling. The diagnostic rules are derived from the operation of a simulator according to the following procedure: (a) identification of all initiating events and of the corresponding operational modes; (b) simulation of all the selected transients for a time sufficient to identify the uniqueness of the plant response under each of the initiating event; (c) automatic generation of the set of diagnostic rules that, through the use of temporal logic and a filtering Expert System, associate the evolution of the process parameters and their derivatives to the initial perturbation. The plant model running under the simulator is built-up by means of the LEGO code. The LEGO code is a modular package developed at the Research and Development Department of the Italian National Electricity Board (CRA-ENEL) to facilitate modelling of the dynamics of fossil-fuelled and nuclear power plants. The LEGO code consists of a library of pre-programmed, pre-tested and pre-validated modules, that represent power plant components and a master program which allows the user to build-up a model by automatically interconnecting the modules in the arrangement determined by the modeler. The reference plant is Sampierdarena power station, that is a combined cycle plant dedicated to produce both

  6. 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...

  7. 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.

  8. 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...

  9. 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.)

  10. Bearing diagnostics: A method based on differential geometry

    Science.gov (United States)

    Tian, Ye; Wang, Zili; Lu, Chen; Wang, Zhipeng

    2016-12-01

    The structures around bearings are complex, and the working environment is variable. These conditions cause the collected vibration signals to become nonlinear, non-stationary, and chaotic characteristics that make noise reduction, feature extraction, fault diagnosis, and health assessment significantly challenging. Thus, a set of differential geometry-based methods with superiorities in nonlinear analysis is presented in this study. For noise reduction, the Local Projection method is modified by both selecting the neighborhood radius based on empirical mode decomposition and determining noise subspace constrained by neighborhood distribution information. For feature extraction, Hessian locally linear embedding is introduced to acquire manifold features from the manifold topological structures, and singular values of eigenmatrices as well as several specific frequency amplitudes in spectrograms are extracted subsequently to reduce the complexity of the manifold features. For fault diagnosis, information geometry-based support vector machine is applied to classify the fault states. For health assessment, the manifold distance is employed to represent the health information; the Gaussian mixture model is utilized to calculate the confidence values, which directly reflect the health status. Case studies on Lorenz signals and vibration datasets of bearings demonstrate the effectiveness of the proposed methods.

  11. 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.

  12. 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.

  13. A Comparison of General Diagnostic Models (GDM) and Bayesian Networks Using a Middle School Mathematics Test

    Science.gov (United States)

    Wu, Haiyan

    2013-01-01

    General diagnostic models (GDMs) and Bayesian networks are mathematical frameworks that cover a wide variety of psychometric models. Both extend latent class models, and while GDMs also extend item response theory (IRT) models, Bayesian networks can be parameterized using discretized IRT. The purpose of this study is to examine similarities and…

  14. 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…

  15. Thymic epithelial turnours : A population-based study of the incidence, diagnostic procedures and therapy

    NARCIS (Netherlands)

    de Jong, Wouter K.; Blaauwgeers, Johannes L. G.; Schaapveld, Michael; Timens, Wim; Klinkenberg, Theo J.; Groen, Harry J. M.

    2008-01-01

    The population-based incidence, diagnostic procedures, therapy and survival of thymic epithelial tumours were determined using the Netherlands National Pathological Archives and the Netherlands Cancer Registry. Excess mortality compared to the Netherlands standard population was estimated by relativ

  16. 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....

  17. Saliva-based biosensors: noninvasive monitoring tool for clinical diagnostics.

    Science.gov (United States)

    Malon, Radha S P; Sadir, Sahba; Balakrishnan, Malarvili; Córcoles, Emma P

    2014-01-01

    Saliva is increasingly recognised as an attractive diagnostic fluid. The presence of various disease signalling salivary biomarkers that accurately reflect normal and disease states in humans and the sampling benefits compared to blood sampling are some of the reasons for this recognition. This explains the burgeoning research field in assay developments and technological advancements for the detection of various salivary biomarkers to improve clinical diagnosis, management, and treatment. This paper reviews the significance of salivary biomarkers for clinical diagnosis and therapeutic applications, with focus on the technologies and biosensing platforms that have been reported for screening these biomarkers.

  18. Saliva-Based Biosensors: Noninvasive Monitoring Tool for Clinical Diagnostics

    Directory of Open Access Journals (Sweden)

    Radha S. P. Malon

    2014-01-01

    Full Text Available Saliva is increasingly recognised as an attractive diagnostic fluid. The presence of various disease signalling salivary biomarkers that accurately reflect normal and disease states in humans and the sampling benefits compared to blood sampling are some of the reasons for this recognition. This explains the burgeoning research field in assay developments and technological advancements for the detection of various salivary biomarkers to improve clinical diagnosis, management, and treatment. This paper reviews the significance of salivary biomarkers for clinical diagnosis and therapeutic applications, with focus on the technologies and biosensing platforms that have been reported for screening these biomarkers.

  19. Goodness-of-fit tests and model diagnostics for negative binomial regression of RNA sequencing data.

    Directory of Open Access Journals (Sweden)

    Gu Mi

    Full Text Available This work is about assessing model adequacy for negative binomial (NB regression, particularly (1 assessing the adequacy of the NB assumption, and (2 assessing the appropriateness of models for NB dispersion parameters. Tools for the first are appropriate for NB regression generally; those for the second are primarily intended for RNA sequencing (RNA-Seq data analysis. The typically small number of biological samples and large number of genes in RNA-Seq analysis motivate us to address the trade-offs between robustness and statistical power using NB regression models. One widely-used power-saving strategy, for example, is to assume some commonalities of NB dispersion parameters across genes via simple models relating them to mean expression rates, and many such models have been proposed. As RNA-Seq analysis is becoming ever more popular, it is appropriate to make more thorough investigations into power and robustness of the resulting methods, and into practical tools for model assessment. In this article, we propose simulation-based statistical tests and diagnostic graphics to address model adequacy. We provide simulated and real data examples to illustrate that our proposed methods are effective for detecting the misspecification of the NB mean-variance relationship as well as judging the adequacy of fit of several NB dispersion models.

  20. Goodness-of-fit tests and model diagnostics for negative binomial regression of RNA sequencing data.

    Science.gov (United States)

    Mi, Gu; Di, Yanming; Schafer, Daniel W

    2015-01-01

    This work is about assessing model adequacy for negative binomial (NB) regression, particularly (1) assessing the adequacy of the NB assumption, and (2) assessing the appropriateness of models for NB dispersion parameters. Tools for the first are appropriate for NB regression generally; those for the second are primarily intended for RNA sequencing (RNA-Seq) data analysis. The typically small number of biological samples and large number of genes in RNA-Seq analysis motivate us to address the trade-offs between robustness and statistical power using NB regression models. One widely-used power-saving strategy, for example, is to assume some commonalities of NB dispersion parameters across genes via simple models relating them to mean expression rates, and many such models have been proposed. As RNA-Seq analysis is becoming ever more popular, it is appropriate to make more thorough investigations into power and robustness of the resulting methods, and into practical tools for model assessment. In this article, we propose simulation-based statistical tests and diagnostic graphics to address model adequacy. We provide simulated and real data examples to illustrate that our proposed methods are effective for detecting the misspecification of the NB mean-variance relationship as well as judging the adequacy of fit of several NB dispersion models.

  1. Study of a high power hydrogen beam diagnostic based on secondary electron emission

    Science.gov (United States)

    Sartori, E.; Panasenkov, A.; Veltri, P.; Serianni, G.; Pasqualotto, R.

    2016-11-01

    In high power neutral beams for fusion, beam uniformity is an important figure of merit. Knowing the transverse power profile is essential during the initial phases of beam source operation, such as those expected for the ITER heating neutral beam (HNB) test facility. To measure it a diagnostic technique is proposed, based on the collection of secondary electrons generated by beam-surface and beam-gas interactions, by an array of positively biased collectors placed behind the calorimeter tubes. This measurement showed in the IREK test stand good proportionality to the primary beam current. To investigate the diagnostic performances in different conditions, we developed a numerical model of secondary electron emission, induced by beam particle impact on the copper tubes, and reproducing the cascade of secondary emission caused by successive electron impacts. The model is first validated against IREK measurements. It is then applied to the HNB case, to assess the locality of the measurement, the proportionality to the beam current density, and the influence of beam plasma.

  2. A Robust Automated Cataract Detection Algorithm Using Diagnostic Opinion Based Parameter Thresholding for Telemedicine Application

    Directory of Open Access Journals (Sweden)

    Shashwat Pathak

    2016-09-01

    Full Text Available This paper proposes and evaluates an algorithm to automatically detect the cataracts from color images in adult human subjects. Currently, methods available for cataract detection are based on the use of either fundus camera or Digital Single-Lens Reflex (DSLR camera; both are very expensive. The main motive behind this work is to develop an inexpensive, robust and convenient algorithm which in conjugation with suitable devices will be able to diagnose the presence of cataract from the true color images of an eye. An algorithm is proposed for cataract screening based on texture features: uniformity, intensity and standard deviation. These features are first computed and mapped with diagnostic opinion by the eye expert to define the basic threshold of screening system and later tested on real subjects in an eye clinic. Finally, a tele-ophthamology model using our proposed system has been suggested, which confirms the telemedicine application of the proposed system.

  3. Evolvable Smartphone-Based Platforms for Point-Of-Care In-Vitro Diagnostics Applications

    DEFF Research Database (Denmark)

    Patou, François; Al Atraktchi, Fatima Al-Zahraa; Kjærgaard, Claus

    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......-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......-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...

  4. Validation of a Novel Traditional Chinese Medicine Pulse Diagnostic Model Using an Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Anson Chui Yan Tang

    2012-01-01

    Full Text Available In view of lacking a quantifiable traditional Chinese medicine (TCM pulse diagnostic model, a novel TCM pulse diagnostic model was introduced to quantify the pulse diagnosis. Content validation was performed with a panel of TCM doctors. Criterion validation was tested with essential hypertension. The gold standard was brachial blood pressure measured by a sphygmomanometer. Two hundred and sixty subjects were recruited (139 in the normotensive group and 121 in the hypertensive group. A TCM doctor palpated pulses at left and right cun, guan, and chi points, and quantified pulse qualities according to eight elements (depth, rate, regularity, width, length, smoothness, stiffness, and strength on a visual analog scale. An artificial neural network was used to develop a pulse diagnostic model differentiating essential hypertension from normotension. Accuracy, specificity, and sensitivity were compared among various diagnostic models. About 80% accuracy was attained among all models. Their specificity and sensitivity varied, ranging from 70% to nearly 90%. It suggested that the novel TCM pulse diagnostic model was valid in terms of its content and diagnostic ability.

  5. Diagnostics for stochastic genome-scale modeling via model slicing and debugging.

    Directory of Open Access Journals (Sweden)

    Kevin J Tsai

    Full Text Available Modeling of biological behavior has evolved from simple gene expression plots represented by mathematical equations to genome-scale systems biology networks. However, due to obstacles in complexity and scalability of creating genome-scale models, several biological modelers have turned to programming or scripting languages and away from modeling fundamentals. In doing so, they have traded the ability to have exchangeable, standardized model representation formats, while those that remain true to standardized model representation are faced with challenges in model complexity and analysis. We have developed a model diagnostic methodology inspired by program slicing and debugging and demonstrate the effectiveness of the methodology on a genome-scale metabolic network model published in the BioModels database. The computer-aided identification revealed specific points of interest such as reversibility of reactions, initialization of species amounts, and parameter estimation that improved a candidate cell's adenosine triphosphate production. We then compared the advantages of our methodology over other modeling techniques such as model checking and model reduction. A software application that implements the methodology is available at http://gel.ym.edu.tw/gcs/.

  6. Diagnostics for stochastic genome-scale modeling via model slicing and debugging.

    Science.gov (United States)

    Tsai, Kevin J; Chang, Chuan-Hsiung

    2014-01-01

    Modeling of biological behavior has evolved from simple gene expression plots represented by mathematical equations to genome-scale systems biology networks. However, due to obstacles in complexity and scalability of creating genome-scale models, several biological modelers have turned to programming or scripting languages and away from modeling fundamentals. In doing so, they have traded the ability to have exchangeable, standardized model representation formats, while those that remain true to standardized model representation are faced with challenges in model complexity and analysis. We have developed a model diagnostic methodology inspired by program slicing and debugging and demonstrate the effectiveness of the methodology on a genome-scale metabolic network model published in the BioModels database. The computer-aided identification revealed specific points of interest such as reversibility of reactions, initialization of species amounts, and parameter estimation that improved a candidate cell's adenosine triphosphate production. We then compared the advantages of our methodology over other modeling techniques such as model checking and model reduction. A software application that implements the methodology is available at http://gel.ym.edu.tw/gcs/.

  7. 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

  8. 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.

  9. Accelerating the Development and Validation of New Value-Based Diagnostics by Leveraging Biobanks.

    Science.gov (United States)

    Schneider, Daniel; Riegman, Peter H J; Cronin, Maureen; Negrouk, Anastassia; Moch, Holger; Balling, Rudi; Penault-Llorca, Frederiques; Zatloukal, Kurt; Horgan, Denis

    The challenges faced in developing value-based diagnostics has resulted in few of these tests reaching the clinic, leaving many treatment modalities without matching diagnostics to select patients for particular therapies. Many patients receive therapies from which they are unlikely to benefit, resulting in worse outcomes and wasted health care resources. The paucity of value-based diagnostics is a result of the scientific challenges in developing predictive markers, specifically: (1) complex biology, (2) a limited research infrastructure supporting diagnostic development, and (3) the lack of incentives for diagnostic developers to invest the necessary resources. Better access to biospecimens can address some of these challenges. Methodologies developed to evaluate biomarkers from biospecimens archived from patients enrolled in randomized clinical trials offer the greatest opportunity to develop and validate high-value molecular diagnostics. An alternative opportunity is to access high-quality biospecimens collected from large public and private longitudinal observational cohorts such as the UK Biobank, the US Million Veteran Program, the UK 100,000 Genomes Project, or the French E3N cohort. Value-based diagnostics can be developed to work in a range of samples including blood, serum, plasma, urine, and tumour tissue, and better access to these high-quality biospecimens with clinical data can facilitate biomarker research.

  10. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Shelton, R T; O' Brien, D W; Kamperschroer, J H; Nelson, J R

    2007-10-03

    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.

  12. 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).

  13. Modeling of oil spreading in a problem of radar multiangle diagnostics of Sea surface pollutions

    Science.gov (United States)

    Matveev, A. Ya.; Kubryakov, A. A.; Boev, A. G.; Bychkov, D. M.; Ivanov, V. K.; Stanichny, S. V.; Tsymbal, V. N.

    2016-12-01

    The possibilities of a multiangle method of radar diagnostics to determine thickness of an oil film on a sea surface by comparing the radar data with the quantitative modeling results obtained using the model of oil spreading dynamics are analyzed. The experimental results of the remote sensing of the Caspian Sea water area near the Neftyanye Kamni oil field by the Envisat-1 synthetic aperture radar (SAR) and the new Floating Objects Tracking System (FOTS) model of oil spreading are used for the analysis. The model allows to calculate the dynamics and change in the mass and size of an oil slick basing only on the available data of satellite measurements and atmospheric reanalysis.The model takes into account the main processes that influence the slick formation (gravity spreading, advective transport, dispersion, emulsification, turbulent mixing, and evaporation). This model is used to calculate the thickness evolution and dynamics of the displacement of oil slicks in the period between two consecutive radar images of this region (0.5-4 days) and to estimate the volumes of oil spilled in the field. The good consistence of the height of the oil film calculated using radar measurements and the modeling results confirms the method's reliability.

  14. [Internet- and mobile-based approaches : Psycho-social diagnostics and treatment in medical rehabilitation].

    Science.gov (United States)

    Baumeister, Harald; Lin, Jiaxi; Ebert, David Daniel

    2017-02-21

    Technology-based approaches for psychosocial diagnostics and interventions provide an attractive opportunity to optimize medical rehabilitation. Based on an Internet- and mobile-based assessment of existing functional health impairments, appropriate planning, implementation of corresponding courses of action as well as outcome assessment can take place. This can be implemented in the form of Internet- and mobile-based interventions (IMI).The present article provides an overview of the basic knowledge of IMI and their evidence base both in general and in particular for their use in medical rehabilitation. Important aspects of internet and mobile-based psycho-social diagnostics are discussed subsequently. Finally, an outlook for the use of Internet- and mobile-based diagnostics and interventions in medical rehabilitation is given.

  15. Kernel model-based diagnosis

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The methods for computing the kemel consistency-based diagnoses and the kernel abductive diagnoses are only suited for the situation where part of the fault behavioral modes of the components are known. The characterization of the kernel model-based diagnosis based on the general causal theory is proposed, which can break through the limitation of the above methods when all behavioral modes of each component are known. Using this method, when observation subsets deduced logically are respectively assigned to the empty or the whole observation set, the kernel consistency-based diagnoses and the kernel abductive diagnoses can deal with all situations. The direct relationship between this diagnostic procedure and the prime implicants/implicates is proved, thus linking theoretical result with implementation.

  16. 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.

  17. 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...

  18. Autofluorescence-based diagnostic UV imaging of tissues and cells

    Science.gov (United States)

    Renkoski, Timothy E.

    Cancer is the second leading cause of death in the United States, and its early diagnosis is critical to improving treatment options and patient outcomes. In autofluorescence (AF) imaging, light of controlled wavelengths is projected onto tissue, absorbed by specific molecules, and re-emitted at longer wavelengths. Images of re-emitted light are used together with spectral information to infer tissue functional information and diagnosis. This dissertation describes AF imaging studies of three different organs using data collected from fresh human surgical specimens. In the ovary study, illumination was at 365 nm, and images were captured at 8 emission wavelengths. Measurements from a multispectral imaging system and fiber optic probe were used to map tissue diagnosis at every image pixel. For the colon and pancreas studies, instrumentation was developed extending AF imaging capability to sub-300 nm excitation. Images excited in the deep UV revealed tryptophan and protein content which are believed to change with disease state. Several excitation wavelength bands from 280 nm to 440 nm were investigated. Microscopic AF images collected in the pancreas study included both cultured and primary cells. Several findings are reported. A method of transforming fiber optic probe spectra for direct comparison with imager spectra was devised. Normalization of AF data by green reflectance data was found useful in correcting hemoglobin absorption. Ratio images, both AF and reflectance, were formulated to highlight growths in the colon. Novel tryptophan AF images were found less useful for colon diagnostics than the new ratio techniques. Microscopic tryptophan AF images produce useful visualization of cellular protein content, but their diagnostic value requires further study.

  19. 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.

  20. FPGA based implementation of hardware diagnostic layer for local trigger of BAC calorimeter for ZEUS detector

    Science.gov (United States)

    Pozniak, Krzysztof T.

    2004-07-01

    The paper describes design and construction of hardware diagnostics layer dedicated to the local trigger of the Backing Calorimeter (BAC). The BAC is a part of the ZEUS experiment in DESY, Hamburg. A general characteristic of the hardware of BAC trigger was presented. The design of hardware diagnostic and calibration sub-systems for BAC trigger bases on the continuous monitoring of consecutive electronic and photonic blocks. The monitoring process is performed via the specialized tests. The standardized diagnostic components were realized in the algorithmic and parameterized description in AHDL. There were presented the implementation results in ALTERA ACEX chips.

  1. Diagnostic test of predicted height model in Indonesian elderly: a study in an urban area

    Directory of Open Access Journals (Sweden)

    Fatmah Fatmah

    2010-08-01

    Full Text Available Aim In an anthropometric assessment, elderly are frequently unable to measure their height due to mobility and skeletal deformities. An alternative is to use a surrogate value of stature from arm span, knee height, and sitting height. The equations developed for predicting height in Indonesian elderly using these three predictors. The equations put in the nutritional assessment card (NSA of older people. Before the card which is the first new technology in Indonesia will be applied in the community, it should be tested. The study aimed was to conduct diagnostic test of predicted height model in the card compared to actual height.Methods Model validation towards 400 healthy elderly conducted in Jakarta City with cross-sectional design. The study was the second validation test of the model besides Depok City representing semi urban area which was undertaken as the first study.Result Male elderly had higher mean age, height, weight, arm span, knee height, and sitting height as compared to female elderly. The highest correlation between knee height and standing height was similar in women (r = 0.80; P < 0.001 and men (r = 0.78; P < 0.001, and followed by arm span and sitting height. Knee height had the lowest difference with standing height in men (3.13 cm and women (2.79 cm. Knee height had the biggest sensitivity (92.2%, and the highest specificity on sitting height (91.2%.Conclusion Stature prediction equation based on knee-height, arm span, and sitting height are applicable for nutritional status assessment in Indonesian elderly. (Med J Indones 2010;19:199-204Key words: diagnostic test, elderly, predicted height model

  2. Development of -omics research in Schistosoma spp. and omics-based new diagnostic tools for schistosomiasis

    Directory of Open Access Journals (Sweden)

    Wei eHu

    2014-06-01

    Full Text Available Schistosomiasis, caused by dioecious flatworms in the genus Schistosoma, is torturing people from many developing countries nowadays and frequently leads to severe morbidity and mortality of the patients. Praziquantel (PZQ based chemotherapy and morbidity control for this disease adopted currently necessitate viable and efficient diagnostic technologies. Fortunately, those -omics researches, which rely on high-throughput experimental technologies to produce massive amounts of informative data, have substantially contributed to the exploitation and innovation of diagnostic tools of schistosomiasis. In its first section, this review provides a concise conclusion on the progresses pertaining to schistosomal omics researches to date, followed by a comprehensive section on the diagnostic methods of schistosomiasis, especially those innovative ones based on the detection of antibodies, antigens, nucleic acids, and metabolites with a focus on those achievements inspired by omics researches. Finally, suggestions about the design of future diagnostic tools of schistosomiasis are proposed, in order to better harness those data produced by omics studies.

  3. 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.

  4. 非线性再生散度模型的诊断%SOME DIAGNOSTICS IN NONLINEAR REPRODUCTIVE DISPERSION MODELS

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This article discusses the problem of the detection of influential cases in nonlinear reproductive dispersion models (NRDM). A diagnostic based on case-deletion approach in estimating equations is proposed. The relationships between the generalized leverage defined by Wei et al. in 1998, statistical curvature, and the local influence of the response vector perturbations are investigated in NRDM. Two numerical examples are given to illustrate the results.

  5. How Preclinical Models Evolved to Resemble the Diagnostic Criteria of Drug Addiction.

    Science.gov (United States)

    Belin-Rauscent, Aude; Fouyssac, Maxime; Bonci, Antonello; Belin, David

    2016-01-01

    Drug addiction is a complex neuropsychiatric disorder that affects a subset of the individuals who take drugs. It is characterized by maladaptive drug-seeking habits that are maintained despite adverse consequences and intense drug craving. The pathophysiology and etiology of addiction is only partially understood despite extensive research because of the gap between current preclinical models of addiction and the clinical criteria of the disorder. This review presents a brief overview, based on selected methodologies, of how behavioral models have evolved over the last 50 years to the development of recent preclinical models of addiction that more closely mimic diagnostic criteria of addiction. It is hoped that these new models will increase our understanding of the complex neurobiological mechanisms whereby some individuals switch from controlled drug use to compulsive drug-seeking habits and relapse to these maladaptive habits. Additionally, by paving the way to bridge the gap that exists between biobehavioral research on addiction and the human situation, these models may provide new perspectives for the development of novel and effective therapeutic strategies for drug addiction.

  6. Using Principal Component Analysis And Choqet Integral To Establish A Diagnostic Model of Parkinson Disease

    Science.gov (United States)

    cao, Xiuming; Song, Jinjie; Zhang, Caipo

    This work focused on principal component analysis and Choquet integral to structure a model of diagnose Parkinson disease. The proper value of Sugeno measure is vital to a diagnostic model. This paper aims at providing a method of using principal component analysis to obtain the sugeno measure. In this diagnostic model, there are two key elements. One is the goodness of fit that the degrees of evidential support for attribute. The other is the importance of attribute itself. The instances of Parkinson disease illuminate that the method is effective.

  7. 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.

  8. Diagnostic tests for influenza and other respiratory viruses: determining performance specifications based on clinical setting.

    Science.gov (United States)

    Takahashi, Hiroshi; Otsuka, Yoshihito; Patterson, Bruce K

    2010-06-01

    The lack of sensitivity of rapid immunoassays in detecting the novel 2009 H1N1 influenza virus infection has led to recommendations on influenza diagnostic testing for clinicians treating patients as well as advising clinicians on testing decisions. Studies have also shown that rapid immunoassays for seasonal influenza virus show considerable variability in performance characteristics, based on age of patient, prevalence of disease, course of infection, and the quality of the kit used. While public health authorities are currently focused on influenza virus diagnostics, a lack of sensitivity of rapid immunoassays for other viral respiratory pathogens has been widely reported, such as the very limited value of rapid immunoassays for the detection of respiratory syncytial virus in adults. In light of the lack of sensitivity of diagnostic tests for suspected 2009 H1N1 influenza virus infection, as well as their variable performance characteristics for seasonal influenza virus, a number of recommendations have been made by public health authorities advising clinicians on the need for clinical judgment as an important part of testing and treatment decisions as well as reliance on local epidemiologic and surveillance data. With the availability of new molecular methodologies that are user-friendly and allow the front-line physician as well as hospital infection control programs to significantly improve respiratory viral diagnostics, there is a need to carefully determine the most optimal diagnostic testing methodology based on the clinical setting. This review will describe the historical, current, and changing dynamics of respiratory virus infection diagnostics.

  9. Behavior of gadolinium-based diagnostics in water treatment

    Energy Technology Data Exchange (ETDEWEB)

    Cyris, Maike

    2013-04-25

    determined, however, it is strongly assumed that the anthropogenic gadolinium fraction is present as chelate. Adsorption characteristics were evaluated by bottle point isotherm experiments on different activated carbon types and activated polymer based sorbents. The Freundlich coefficients vary between 0.013 and 2.83 (μmol kg{sup -1})(L μmol{sup -1}){sup 1/n} for Gd-BT-DO3A, on Chemviron RD 90 {sup registered} and on the best synthetic adsorbent, respectively. Lab scale experiments with small adsorber columns in a drinking water matrix gave insight in the behavior during fixed-bed adsorption processes. The breakthrough was described successfully by the Linear Driving Force model. Modeling has shown that a description of experimental results is only possible by including dissolved organic carbon isotherm results from drinking water in the model, to describe an additional competitive adsorption effect within the fixed-bed adsorber, different from direct competition. First investigations in a wastewater treatment plant proved a poor adsorption of gadolinium similar to iodinated X-ray contrast media such as iopamidole. Therefore, gadolinium will hardly be removed from wastewater by implementation of a further adsorptive treatment step. However, gadolinium may be utilized as indicator substance for breakthrough. Rate constants of the chelates with ozone and hydroxyl radicals have been determined under pseudo-first-order conditions. Rate constants for the ozone reaction were determined to be < 50 M{sup -1}s{sup -1} for all tested chelates. Hence, the chelates may be considered ozone refractory. For determination of hydroxyl radical rate constants different methods were applied. Radicals were generated either by pulse radiolysis, in this case rate constant were determined directly and by competition with thiocyanate, or by the peroxone process, where only competition kinetics were applied (para-chlorobenzoic acid and tert-butanol as competitors). From pulse radiolysis

  10. 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.

  11. Towards diagnostic model calibration and evaluation: Approximate Bayesian computation

    NARCIS (Netherlands)

    Vrugt, J.A.; Sadegh, M.

    2013-01-01

    The ever increasing pace of computational power, along with continued advances in measurement technologies and improvements in process understanding has stimulated the development of increasingly complex hydrologic models that simulate soil moisture flow, groundwater recharge, surface runoff, root w

  12. Influence Diagnostics in Partially Varying-Coefficient Models

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    When a real-world data set is fitted to a specific type of models, it is often encountered that one or a set of observations have undue influence on the model fitting, which may lead to misleading conclusions. Therefore, it is necessary for data analysts to identify these influential observations and assess their impact on various aspects of model fitting. In this paper, one type of modified Cook's distances is defined to gauge the influence of one or a set observations on the estimate of the constant coefficient part in partially varying-coefficient models, and the Cook's distances are expressed as functions of the corresponding residuals and leverages. Meanwhile, a bootstrap procedure is suggested to derive the reference values for the proposed Cook's distances. Some simulations are conducted, and a real-world data set is further analyzed to examine the performance of the proposed method. The experimental results are satisfactory.

  13. 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.

  14. 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...

  15. 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.

  16. 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.

  17. A temporally and spatially resolved electron density diagnostic method for the edge plasma based on Stark broadening

    Science.gov (United States)

    Zafar, A.; Martin, E. H.; Shannon, S. C.; Isler, R. C.; Caughman, J. B. O.

    2016-11-01

    An electron density diagnostic (≥1010 cm-3) capable of high temporal (ms) and spatial (mm) resolution is currently under development at Oak Ridge National Laboratory. The diagnostic is based on measuring the Stark broadened, Doppler-free spectral line profile of the n = 6-2 hydrogen Balmer series transition. The profile is then fit to a fully quantum mechanical model including the appropriate electric and magnetic field operators. The quasi-static approach used to calculate the Doppler-free spectral line profile is outlined here and the results from the model are presented for H-δ spectra for electron densities of 1010-1013 cm-3. The profile shows complex behavior due to the interaction between the magnetic substates of the atom.

  18. Predicting population coverage of T-cell epitope-based diagnostics and vaccines

    Directory of Open Access Journals (Sweden)

    Newman Mark J

    2006-03-01

    Full Text Available Abstract Background T cells recognize a complex between a specific major histocompatibility complex (MHC molecule and a particular pathogen-derived epitope. A given epitope will elicit a response only in individuals that express an MHC molecule capable of binding that particular epitope. MHC molecules are extremely polymorphic and over a thousand different human MHC (HLA alleles are known. A disproportionate amount of MHC polymorphism occurs in positions constituting the peptide-binding region, and as a result, MHC molecules exhibit a widely varying binding specificity. In the design of peptide-based vaccines and diagnostics, the issue of population coverage in relation to MHC polymorphism is further complicated by the fact that different HLA types are expressed at dramatically different frequencies in different ethnicities. Thus, without careful consideration, a vaccine or diagnostic with ethnically biased population coverage could result. Results To address this issue, an algorithm was developed to calculate, on the basis of HLA genotypic frequencies, the fraction of individuals expected to respond to a given epitope set, diagnostic or vaccine. The population coverage estimates are based on MHC binding and/or T cell restriction data, although the tool can be utilized in a more general fashion. The algorithm was implemented as a web-application available at http://epitope.liai.org:8080/tools/population. Conclusion We have developed a web-based tool to predict population coverage of T-cell epitope-based diagnostics and vaccines based on MHC binding and/or T cell restriction data. Accordingly, epitope-based vaccines or diagnostics can be designed to maximize population coverage, while minimizing complexity (that is, the number of different epitopes included in the diagnostic or vaccine, and also minimizing the variability of coverage obtained or projected in different ethnic groups.

  19. 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.

  20. Flow diagnostics downstream of a tribladed rotor model

    DEFF Research Database (Denmark)

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

    2012-01-01

    This paper presents results of a study of vortex wake structures and measurements of instantaneous 3D velocity fields downstream of a triblade turbine model. Two operation modes of flow around the rotor with different tip speed ratios were tested. Initially the wake structures were visualized and...

  1. 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…

  2. 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.

  3. First Steps Toward Incorporating Image Based Diagnostics Into Particle Accelerator Control Systems Using Convolutional Neural Networks

    Energy Technology Data Exchange (ETDEWEB)

    Edelen, A. L.; Biedron, S. G.; Milton, S. V.; Edelen, J. P.

    2016-12-16

    At present, a variety of image-based diagnostics are used in particle accelerator systems. Often times, these are viewed by a human operator who then makes appropriate adjustments to the machine. Given recent advances in using convolutional neural networks (CNNs) for image processing, it should be possible to use image diagnostics directly in control routines (NN-based or otherwise). This is especially appealing for non-intercepting diagnostics that could run continuously during beam operation. Here, we show results of a first step toward implementing such a controller: our trained CNN can predict multiple simulated downstream beam parameters at the Fermilab Accelerator Science and Technology (FAST) facility's low energy beamline using simulated virtual cathode laser images, gun phases, and solenoid strengths.

  4. 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.

  5. 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.

  6. 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.

  7. Plasma Channel Diagnostic Based on Laser Centroid Oscillations

    Energy Technology Data Exchange (ETDEWEB)

    Gonsalves, Anthony; Nakamura, Kei; Lin, Chen; Osterhoff, Jens; Shiraishi, Satomi; Schroeder, Carl; Geddes, Cameron; Toth, Csaba; Esarey, Eric; Leemans, Wim

    2010-09-09

    A technique has been developed for measuring the properties of discharge-based plasma channels by monitoring the centroid location of a laser beam exiting the channel as a function of input alignment offset between the laser and the channel. The centroid position of low-intensity (<10{sup 14}Wcm{sup -2}) laser pulses focused at the input of a hydrogen-filled capillary discharge waveguide was scanned and the exit positions recorded to determine the channel shape and depth with an accuracy of a few %. In addition, accurate alignment of the laser beam through the plasma channel can be provided by minimizing laser centroid motion at the channel exit as the channel depth is scanned either by scanning the plasma density or the discharge timing. The improvement in alignment accuracy provided by this technique will be crucial for minimizing electron beam pointing errors in laser plasma accelerators.

  8. Cognitive Diagnostic Models for Tests with Multiple-Choice and Constructed-Response Items

    Science.gov (United States)

    Kuo, Bor-Chen; Chen, Chun-Hua; Yang, Chih-Wei; Mok, Magdalena Mo Ching

    2016-01-01

    Traditionally, teachers evaluate students' abilities via their total test scores. Recently, cognitive diagnostic models (CDMs) have begun to provide information about the presence or absence of students' skills or misconceptions. Nevertheless, CDMs are typically applied to tests with multiple-choice (MC) items, which provide less diagnostic…

  9. 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…

  10. Vibration-based monitoring and diagnostics using compressive sensing

    Science.gov (United States)

    Ganesan, Vaahini; Das, Tuhin; Rahnavard, Nazanin; Kauffman, Jeffrey L.

    2017-04-01

    Vibration data from mechanical systems carry important information that is useful for characterization and diagnosis. Standard approaches rely on continually streaming data at a fixed sampling frequency. For applications involving continuous monitoring, such as Structural Health Monitoring (SHM), such approaches result in high volume data and rely on sensors being powered for prolonged durations. Furthermore, for spatial resolution, structures are instrumented with a large array of sensors. This paper shows that both volume of data and number of sensors can be reduced significantly by applying Compressive Sensing (CS) in vibration monitoring applications. The reduction is achieved by using random sampling and capitalizing on the sparsity of vibration signals in the frequency domain. Preliminary experimental results validating CS-based frequency recovery are also provided. By exploiting the sparsity of mode shapes, CS can also enable efficient spatial reconstruction using fewer spatially distributed sensors. CS can thereby reduce the cost and power requirement of sensing as well as streamline data storage and processing in monitoring applications. In well-instrumented structures, CS can enable continued monitoring in case of sensor or computational failures.

  11. A WAO - ARIA - GA²LEN consensus document on molecular-based allergy diagnostics.

    Science.gov (United States)

    Canonica, Giorgio Walter; Ansotegui, Ignacio J; Pawankar, Ruby; Schmid-Grendelmeier, Peter; van Hage, Marianne; Baena-Cagnani, Carlos E; Melioli, Giovanni; Nunes, Carlos; Passalacqua, Giovanni; Rosenwasser, Lanny; Sampson, Hugh; Sastre, Joaquin; Bousquet, Jean; Zuberbier, Torsten

    2013-10-03

    Molecular-based allergy (MA) diagnostics is an approach used to map the allergen sensitization of a patient at a molecular level, using purified natural or recombinant allergenic molecules (allergen components) instead of allergen extracts. Since its introduction, MA diagnostics has increasingly entered routine care, with currently more than 130 allergenic molecules commercially available for in vitro specific IgE (sIgE) testing.MA diagnostics allows for an increased accuracy in allergy diagnosis and prognosis and plays an important role in three key aspects of allergy diagnosis: (1) resolving genuine versus cross-reactive sensitization in poly-sensitized patients, thereby improving the understanding of triggering allergens; (2) assessing, in selected cases, the risk of severe, systemic versus mild, local reactions in food allergy, thereby reducing unnecessary anxiety for the patient and the need for food challenge testing; and (3) identifying patients and triggering allergens for specific immunotherapy (SIT).Singleplex and multiplex measurement platforms are available for MA diagnostics. The Immuno-Solid phase Allergen Chip (ISAC) is the most comprehensive platform currently available, which involves a biochip technology to measure sIgE antibodies against more than one hundred allergenic molecules in a single assay. As the field of MA diagnostics advances, future work needs to focus on large-scale, population-based studies involving practical applications, elucidation and expansion of additional allergenic molecules, and support for appropriate test interpretation. With the rapidly expanding evidence-base for MA diagnosis, there is a need for allergists to keep abreast of the latest information. The aim of this consensus document is to provide a practical guide for the indications, determination, and interpretation of MA diagnostics for clinicians trained in allergology.

  12. 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.

  13. 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.

  14. Diagnostic parameters in liquid-based cervical cytology using a coagulant suspension fixative

    NARCIS (Netherlands)

    Boon, ME; Ouwerkerk-Noordam, E; Suurmeijer, AH; Kok, LP

    2005-01-01

    Objective To evaluate in detail the morphology of cervical cell samples suspended in the coagulant fixative BoonFix (R) (Finetec, Tokyo, Japan) in liquid-based Papspin (R) slides (Thermo Shandon, Pittsburgh, Pennsylvania, U.S.A) to detect shifts in diagnostic parameters for infections and neoplasia.

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

    Energy Technology Data Exchange (ETDEWEB)

    Reifman, J.; Wei, T.Y.C.; Vitela, J.E. [Argonne National Lab., IL (United States); Applequist, C. A. [Commonwealth Research Corp., Chicago, IL (United States); Chasensky, T.M. [Commonwealth Edison Co., Chicago, IL (United States)

    1996-03-01

    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.

  16. Web-Based Two-Tier Diagnostic Test and Remedial Learning Experiment

    Science.gov (United States)

    Lai, Ah-Fur; Chen, Deng-Jyi

    2010-01-01

    Offering a series of diagnosis and individual remedial learning activities for a general class by means of web and multimedia technology can overcome the dilemma of conventional diagnosis and remedial instruction. The study proposes a three-layer conceptual framework and adopts a two-tier diagnostic test theory to develop a web-based two-tier…

  17. 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 obtaine...

  18. microRNA-based diagnostics and therapy in cardiovascular disease-Summing up the facts.

    Science.gov (United States)

    Schulte, Christian; Zeller, Tanja

    2015-02-01

    Circulating microRNAs (miRNAs) are discussed as potential disease-specific biomarkers in cardiovascular disease. Their diagnostic value has been examined in numerous studies and animal models with respect to coronary artery disease (CAD) and myocardial infarction (MI) and the prognostic abilities of circulating miRNAs in risk stratification of future disease have been evaluated. Various miRNAs are described to complement protein-based biomarkers or classical risk factors in the diagnosis of CAD or MI and even represent potential new biomarkers in the discrimination of unstable angina pectoris (UAP). Signatures consisting of sets of multiple miRNAs seem to improve the predictive power compared to single miRNAs. Furthermore, the emerging field of miRNA-based therapeutics has reached cardiovascular research. The first promising in vitro results are raising hope for future clinical application. However, methods and material used for RNA isolation, miRNA detection and normalization steps still lack ways of standardization and need to be considered carefully. This article reviews the current knowledge of miRNAs in cardiovascular disease focusing on CAD and MI and will provide an overview regarding the use of circulating miRNAs as biomarkers and potential therapeutic targets in the field of CAD.

  19. 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.

  20. 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.

  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. a Diagnostic System Measuring Orthogonal Factors of Sound Fields in a Scale Model of Auditorium

    Science.gov (United States)

    SAKURAI, M.; AIZAWA, S.; SUZUMURA, Y.; ANDO, Y.

    2000-04-01

    Based on the model of auditory-brain system which consists of the autocorrelation mechanism, the interaural cross-correlation mechanism between both the auditory pathways, and the specialization of human cerebral hemispheres (Y. Ando 1998 Architectural Acoustics, Blending Sound Sources, Sound Fields, and Listeners New York: AIP Press/Springer-Verlag), a new diagnostic system was developed. After obtaining the binaural impulse response, four orthogonal factors including the SPL, the initial time-delay gap between the direct sound and the first reflection, the subsequent reverberation time and the IACC can be analyzed for the calculation of the scale values of both global and individual subjective preferences. In addition, two more factors extracted from the interaural cross-correlation functionτIACC and WIACC, can be figured out. Also, the sound energy,Φ (0), the effective duration, τe, and fine structures of autocorrelation function of sound signals including the magnitude of first maximum, φ1, and its delay time,τ1 , can be analyzed. As an example of the measurement, effects of reflectors' array above the stage in a 1/10 scale model of auditorium at each seat are discussed here.

  3. Development of a diagnostic technique based on Cherenkov effect for measurements of fast electrons in fusion devices

    Energy Technology Data Exchange (ETDEWEB)

    Plyusnin, V. V.; Duarte, P.; Fernandes, H.; Silva, C. [Association Euratom/IST, Instituto de Plasmas e Fusao Nuclear, Instituto Superior Tecnico, Universidade Tecnica de Lisboa, Av. Rovisco Pais, 1049-001 Lisboa (Portugal); Jakubowski, L.; Zebrowski, J.; Malinowski, K.; Rabinski, M.; Sadowski, M. J. [National Centre for Nuclear Research (NCBJ), 7 Andrzeja Soltana Str., 05-400 Otwock (Poland)

    2012-08-15

    A diagnostic technique based on the Cherenkov effect is proposed for detection and characterization of fast (super-thermal and runaway) electrons in fusion devices. The detectors of Cherenkov radiation have been specially designed for measurements in the ISTTOK tokamak. Properties of several materials have been studied to determine the most appropriate one to be used as a radiator of Cherenkov emission in the detector. This technique has enabled the detection of energetic electrons (70 keV and higher) and the determination of their spatial and temporal variations in the ISTTOK discharges. Measurement of hard x-ray emission has also been carried out in experiments for validation of the measuring capabilities of the Cherenkov-type detector and a high correlation was found between the data of both diagnostics. A reasonable agreement was found between experimental data and the results of numerical modeling of the runaway electron generation in ISTTOK.

  4. Mixing in the Extratropical Stratosphere: Model-measurements Comparisons using MLM Diagnostics

    Science.gov (United States)

    Ma, Jun; Waugh, Darryn W.; Douglass, Anne R.; Kawa, Stephan R.; Bhartia, P. K. (Technical Monitor)

    2001-01-01

    We evaluate transport processes in the extratropical lower stratosphere for both models and measurements with the help of equivalent length diagnostic from the modified Lagrangian-mean (MLM) analysis. This diagnostic is used to compare measurements of long-lived tracers made by the Cryogenic Limb Array Etalon Spectrometer (CLAES) on the Upper Atmosphere Research Satellite (UARS) with simulated tracers. Simulations are produced in Chemical and Transport Models (CTMs), in which meteorological fields are taken from the Goddard Earth Observing System Data Assimilation System (GEOS DAS), the Middle Atmosphere Community Climate Model (MACCM2), and the Geophysical Fluid Dynamics Laboratory (GFDL) "SKYHI" model, respectively. Time series of isentropic equivalent length show that these models are able to capture major mixing and transport properties observed by CLAES, such as the formation and destruction of polar barriers, the presence of surf zones in both hemispheres. Differences between each model simulation and the observation are examined in light of model performance. Among these differences, only the simulation driven by GEOS DAS shows one case of the "top-down" destruction of the Antarctic polar vortex, as observed in the CLAES data. Additional experiments of isentropic advection of artificial tracer by GEOS DAS winds suggest that diabatic movement might have considerable contribution to the equivalent length field in the 3D CTM diagnostics.

  5. Synthetic Biology-Based Point-of-Care Diagnostics for Infectious Disease.

    Science.gov (United States)

    Wei, Ting-Yen; Cheng, Chao-Min

    2016-09-22

    Infectious diseases outpace all other causes of death in low-income countries, posing global health risks, laying stress on healthcare systems and societies, and taking an avoidable human toll. One solution to this crisis is early diagnosis of infectious disease, which represents a powerful way to optimize treatment, increase patient survival rate, and decrease healthcare costs. However, conventional early diagnosis methods take a long time to generate results, lack accuracy, and are known to seriously underperform with regard to fungal and viral infections. Synthetic biology offers a fast and highly accurate alternative to conventional infectious disease diagnosis. In this review, we outline obstacles to infectious disease diagnostics and discuss two emerging alternatives: synthetic viral diagnostic systems and biosensors. We argue that these synthetic biology-based approaches may overcome diagnostic obstacles in infectious disease and improve health outcomes.

  6. Evidence-Based Point-of-Care Diagnostics: Current Status and Emerging Technologies

    Science.gov (United States)

    Chan, Cangel Pui Yee; Mak, Wing Cheung; Cheung, Kwan Yee; Sin, King Keung; Yu, Cheuk Man; Rainer, Timothy H.; Renneberg, Reinhard

    2013-06-01

    Point-of-care (POC) diagnostics brings tests nearer to the site of patient care. The turnaround time is short, and minimal manual interference enables quick clinical management decisions. Growth in POC diagnostics is being continuously fueled by the global burden of cardiovascular and infectious diseases. Early diagnosis and rapid initiation of treatment are crucial in the management of such patients. This review provides the rationale for the use of POC tests in acute coronary syndrome, heart failure, human immunodeficiency virus, and tuberculosis. We also consider emerging technologies that are based on advanced nanomaterials and microfluidics, improved assay sensitivity, miniaturization in device design, reduced costs, and high-throughput multiplex detection, all of which may shape the future development of POC diagnostics.

  7. Score, pseudo-score and residual diagnostics for goodness-of-fit of spatial point process models

    DEFF Research Database (Denmark)

    Baddeley, Adrian; Rubak, Ege Holger; Møller, Jesper

    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 compensator of the K-function for testing other fitted models. The results also support localisation methods...... such as the scan statistic and smoothed residual plots. Software for computing the diagnostics is provided....

  8. Advanced Laser-Based Techniques for Gas-Phase Diagnostics in Combustion and Aerospace Engineering.

    Science.gov (United States)

    Ehn, Andreas; Zhu, Jiajian; Li, Xuesong; Kiefer, Johannes

    2017-03-01

    Gaining information of species, temperature, and velocity distributions in turbulent combustion and high-speed reactive flows is challenging, particularly for conducting measurements without influencing the experimental object itself. The use of optical and spectroscopic techniques, and in particular laser-based diagnostics, has shown outstanding abilities for performing non-intrusive in situ diagnostics. The development of instrumentation, such as robust lasers with high pulse energy, ultra-short pulse duration, and high repetition rate along with digitized cameras exhibiting high sensitivity, large dynamic range, and frame rates on the order of MHz, has opened up for temporally and spatially resolved volumetric measurements of extreme dynamics and complexities. The aim of this article is to present selected important laser-based techniques for gas-phase diagnostics focusing on their applications in combustion and aerospace engineering. Applicable laser-based techniques for investigations of turbulent flows and combustion such as planar laser-induced fluorescence, Raman and Rayleigh scattering, coherent anti-Stokes Raman scattering, laser-induced grating scattering, particle image velocimetry, laser Doppler anemometry, and tomographic imaging are reviewed and described with some background physics. In addition, demands on instrumentation are further discussed to give insight in the possibilities that are offered by laser flow diagnostics.

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

    OpenAIRE

    2003-01-01

    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 deter...

  10. Mountain Waves in High Resolution Forecast Models: Automated Diagnostics of Wave Severity and Impact on Surface Winds

    Directory of Open Access Journals (Sweden)

    Peter Sheridan

    2017-01-01

    Full Text Available An automated method producing a diagnostic of the severity of lee waves and their impacts on surface winds as represented in output from a high resolution linear numerical model (3D velocities over mountains (3DVOM covering several areas of the U.K. is discussed. Lee waves involving turbulent rotor activity or downslope windstorms represent a hazard to aviation and ground transport, and summary information of this kind is highly valuable as an efficient ‘heads-up’ for forecasters, for automated products or to feed into impact models. Automated diagnosis of lee wave surface effects presents a particular challenge due to the complexity of turbulent zones in the lee of irregular terrain. The method proposed quantifies modelled wind perturbations relative to those that would occur in the absence of lee waves for a given background wind, and diagnoses using it are found to be quite consistent between cases and for different ranges of U.K. hills. A recent upgrade of the operational U.K. limited area model, the U.K. Variable Resolution Model (UKV used for general forecasting at the Met Office means that it now resolves lee waves, and its performance is here demonstrated using comparisons with aircraft- and surface-based observations and the linear model. In the future, automated diagnostics may be adapted to use its output to routinely produce contiguous mesoscale maps of lee wave activity and surface impacts over the whole U.K.

  11. MRI-based diagnostic biomarkers for early onset pediatric multiple sclerosis

    Directory of Open Access Journals (Sweden)

    Martin Weygandt

    2015-01-01

    Full Text Available Currently, it is unclear whether pediatric multiple sclerosis (PMS is a pathoetiologically homogeneous disease phenotype due to clinical and epidemiological differences between early and late onset PMS (EOPMS and LOPMS. Consequently, the question was raised whether diagnostic guidelines need to be complemented by specific EOPMS markers. To search for such markers, we analyzed cerebral MRI images acquired with standard protocols using computer-based classification techniques. Specifically, we applied classification algorithms to gray (GM and white matter (WM tissue probability parameters of small brain regions derived from T2-weighted MRI images of EOPMS patients (onset <12 years, LOPMS patients (onset ≥12 years, and healthy controls (HC. This was done for PMS subgroups matched for disease duration and participant age independently. As expected, maximal diagnostic information for distinguishing PMS patients and HC was found in a periventricular WM area containing lesions (87.1% accuracy, p < 2.2 × 10−5. MRI-based biomarkers specific for EOPMS were identified in prefrontal cortex. Specifically, a coordinate in middle frontal gyrus contained maximal diagnostic information (77.3%, p = 1.8 × 10−4. Taken together, we were able to identify biomarkers reflecting pathognomonic processes specific for MS patients with very early onset. Especially GM involvement in the separation between PMS subgroups suggests that conventional MRI contains a richer set of diagnostically informative features than previously assumed.

  12. Semi-empirical model for fluorescence lines evaluation in diagnostic x-ray beams.

    Science.gov (United States)

    Bontempi, Marco; Andreani, Lucia; Labanti, Claudio; Costa, Paulo Roberto; Rossi, Pier Luca; Baldazzi, Giuseppe

    2016-01-01

    Diagnostic x-ray beams are composed of bremsstrahlung and discrete fluorescence lines. The aim of this study is the development of an efficient model for the evaluation of the fluorescence lines. The most important electron ionization models are analyzed and implemented. The model results were compared with experimental data and with other independent spectra presented in the literature. The implemented peak models allow the discrimination between direct and indirect radiation emitted from tungsten anodes. The comparison with the independent literature spectra indicated a good agreement.

  13. Sparse Modeling Reveals miRNA Signatures for Diagnostics of Inflammatory Bowel Disease.

    Science.gov (United States)

    Hübenthal, Matthias; Hemmrich-Stanisak, Georg; Degenhardt, Frauke; Szymczak, Silke; Du, Zhipei; Elsharawy, Abdou; Keller, Andreas; Schreiber, Stefan; Franke, Andre

    2015-01-01

    The diagnosis of inflammatory bowel disease (IBD) still remains a clinical challenge and the most accurate diagnostic procedure is a combination of clinical tests including invasive endoscopy. In this study we evaluated whether systematic miRNA expression profiling, in conjunction with machine learning techniques, is suitable as a non-invasive test for the major IBD phenotypes (Crohn's disease (CD) and ulcerative colitis (UC)). Based on microarray technology, expression levels of 863 miRNAs were determined for whole blood samples from 40 CD and 36 UC patients and compared to data from 38 healthy controls (HC). To further discriminate between disease-specific and general inflammation we included miRNA expression data from other inflammatory diseases (inflammation controls (IC): 24 chronic obstructive pulmonary disease (COPD), 23 multiple sclerosis, 38 pancreatitis and 45 sarcoidosis cases) as well as 70 healthy controls from previous studies. Classification problems considering 2, 3 or 4 groups were solved using different types of penalized support vector machines (SVMs). The resulting models were assessed regarding sparsity and performance and a subset was selected for further investigation. Measured by the area under the ROC curve (AUC) the corresponding median holdout-validated accuracy was estimated as ranging from 0.75 to 1.00 (including IC) and 0.89 to 0.98 (excluding IC), respectively. In combination, the corresponding models provide tools for the distinction of CD and UC as well as CD, UC and HC with expected classification error rates of 3.1 and 3.3%, respectively. These results were obtained by incorporating not more than 16 distinct miRNAs. Validated target genes of these miRNAs have been previously described as being related to IBD. For others we observed significant enrichment for IBD susceptibility loci identified in earlier GWAS. These results suggest that the proposed miRNA signature is of relevance for the etiology of IBD. Its diagnostic value

  14. Convergence between DSM-IV-TR and DSM-5 diagnostic models for personality disorder: evaluation of strategies for establishing diagnostic thresholds.

    Science.gov (United States)

    Morey, Leslie C; Skodol, Andrew E

    2013-05-01

    The Personality and Personality Disorders Work Group for the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) recommended substantial revisions to the personality disorders (PDs) section of DSM-IV-TR, proposing a hybrid categorical-dimensional model that represented PDs as combinations of core personality dysfunctions and various configurations of maladaptive personality traits. Although the DSM-5 Task Force endorsed the proposal, the Board of Trustees of the American Psychiatric Association (APA) did not, placing the Work Group's model in DSM-5 Section III ("Emerging Measures and Models") with other concepts thought to be in need of additional research. This paper documents the impact of using this alternative model in a national sample of 337 patients as described by clinicians familiar with their cases. In particular, the analyses focus on alternative strategies considered by the Work Group for deriving decision rules, or diagnostic thresholds, with which to assign categorical diagnoses. Results demonstrate that diagnostic rules could be derived that yielded appreciable correspondence between DSM-IV-TR and proposed DSM-5 PD diagnoses-correspondence greater than that observed in the transition between DSM-III and DSM-III-R PDs. The approach also represents the most comprehensive attempt to date to provide conceptual and empirical justification for diagnostic thresholds utilized within the DSM PDs.

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

    Energy Technology Data Exchange (ETDEWEB)

    Morman, J.A.; Reifman, J.; Wei, T.Y.C. [Argonne National Lab., IL (United States)] [and others

    1997-12-31

    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&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&D goals should contribute to the acceptance of knowledge-based digital systems for transient diagnostics and management.

  16. Cellulose-based diagnostic devices for diagnosing serotype-2 dengue fever in human serum.

    Science.gov (United States)

    Wang, Hsi-Kai; Tsai, Cheng-Han; Chen, Kuan-Hung; Tang, Chung-Tao; Leou, Jiun-Shyang; Li, Pi-Chun; Tang, Yin-Liang; Hsieh, Hsyue-Jen; Wu, Han-Chung; Cheng, Chao-Min

    2014-02-01

    Here, two types of cellulose-based in vitro diagnostic devices are demonstrated for the diagnosis of dengue virus infection in both buffer system and human serum: 1) paper-based ELISA for providing the semiquantitative information of the disease activity of serotype-2 dengue fever to healthcare persons (i.e., monitoring the disease activity with a specific serotype in single patients); 2) lateral flow immunoassays to screen for infection with serotype-2 dengue fever (i.e., rapid YES or NO diagnosis prepared for large populations, in terms of global public health). Paper-based ELISA (specific to serotype-2 dengue fever), which builds off of our previous studies and a revised previous ELISA procedure, owns multiple advantages: 1) high sensitivity (about 40 times higher than the current ELISA-based approaches, due to our therapeutic-based monoclonal antibody) and specificity (specific to dengue virus serotype-2 nonstructural protein-1 antigens); 2) tiny amount of sample and reagent used for single tests; 3) short operating duration (i.e., rapid diagnostic device); and, 4) inexpensiveness (appropriate for use in all developing and underdeveloped nations of the world). Due to the higher sensitivity and shorter operating duration of paper-based ELISA (compared with conventional ELISA, and lateral flow immunoassays also performed in this study), this study has not only been able to perform the diagnosis of dengue virus serotype-2 nonstructural protein-1 antigens in both buffer system and human serum but also to evaluate dengue virus serotype-2 envelope proteins in the buffer system, thus successfully achieving the first such use of these proteins as the target antigen for the development of diagnostic tools. These results provide a more comprehensive understanding for the genesis of dengue fever diagnostic tools (through antibody-antigen recognition).

  17. 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...

  18. 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

    2016-09-03

    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.

  19. 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.

  20. 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

  1. Web Based VRML Modelling

    NARCIS (Netherlands)

    Kiss, S.

    2001-01-01

    Presents a method to connect VRML (Virtual Reality Modeling Language) and Java components in a Web page using EAI (External Authoring Interface), which makes it possible to interactively generate and edit VRML meshes. The meshes used are based on regular grids, to provide an interaction and modeling

  2. UK-based real-time lymphoproliferative disorder diagnostic service to improve the management of patients in Ghana.

    Science.gov (United States)

    Parkins, Elizabeth; Owen, Roger G; Bedu-Addo, George; Sem, Ohene Opare; Ekem, Ivy; Adomakoh, Yvonne; Bates, Imelda

    2009-07-09

    The objective of the study was to evaluate the feasibility of a UK-based real-time service to improve the diagnosis and management of lymphoproliferative disorders (LPDs) in Ghana. Adult patients reporting to hospital with a suspected LPD, during a 1 year period, were prospectively enrolled. Bone marrow and/or lymph node biopsies were posted to the Haematology Malignancy Diagnostic Service (HMDS), Leeds, UK and underwent morphological analysis and immunophenotyping. Results were returned by e-mail. The initial diagnoses made in Ghana were compared with the final HMDS diagnoses to assess the contribution of the HMDS diagnosis to management decisions. The study was conducted at the two teaching hospitals in Ghana-Komfo Anokye, Kumasi and Korle Bu, Accra. Participants comprised 150 adult patients (>/=12 years old), 79 women, median age 46 years. Bone marrow and lymph node biopsy samples from all adults presenting with features suggestive of a LPD, at the two teaching hospitals in Ghana, over 1 year were posted to a UK LPD diagnostic centre, where immunophenotyping was performed by immunohistochemistry. Molecular analysis was performed where indicated. Diagnostic classifications were made according to international criteria. Final diagnosis was compared to the initial Ghanaian diagnosis to evaluate discrepancies; implications for alterations in treatment decisions were evaluated. Median time between taking samples and receiving e-mail results in Ghana was 15 days. Concordance between initial and final diagnoses was 32% (48 of 150). The HMDS diagnosis would have changed management in 31% (46 of 150) of patients. It is feasible to provide a UK-based service for LPD diagnosis in Africa using postal services and e-mail. This study confirmed findings from wealthy countries that a specialised haematopathology service can improve LPD diagnosis. This model of Ghana-UK collaboration provides a platform on which to build local capacity to operate an international quality

  3. [Mobile phone based data acquisition and evaluation system for the alternative four diagnostic methods of traditional Chinese medicine].

    Science.gov (United States)

    Yang, Jun; Liu, Jing; Liu, Ran

    2013-01-01

    This study is dedicated to integrate the theories of the four diagnostic methods of TCM and the methods of mobile healthcare so as to achieve the goal of the four diagnostic functions of TCM on mobile phone. An Android smartphone based data acquisition system has been developed and experimentally demonstrated. It was shown that the prototype could successfully achieve the fundamental function of the four diagnostic methods of TCM and thus help preliminarily interpret the symptoms of human diseases.

  4. 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.

  5. Microarray-based genomic profiling as a diagnostic tool in acute lymphoblastic leukemia.

    Science.gov (United States)

    Simons, Annet; Stevens-Kroef, Marian; El Idrissi-Zaynoun, Najat; van Gessel, Sabine; Weghuis, Daniel Olde; van den Berg, Eva; Waanders, Esmé; Hoogerbrugge, Peter; Kuiper, Roland; van Kessel, Ad Geurts

    2011-12-01

    In acute lymphoblastic leukemia (ALL) specific genomic abnormalities provide important clinical information. In most routine clinical diagnostic laboratories conventional karyotyping, in conjunction with targeted screens using e.g., fluorescence in situ hybridization (FISH), is currently considered as the gold standard to detect such aberrations. Conventional karyotyping, however, is limited in its resolution and yield, thus hampering the genetic diagnosis of ALL. We explored whether microarray-based genomic profiling would be feasible as an alternative strategy in a routine clinical diagnostic setting. To this end, we compared conventional karyotypes with microarray-deduced copy number aberration (CNA) karyotypes in 60 ALL cases. Microarray-based genomic profiling resulted in a CNA detection rate of 90%, whereas for conventional karyotyping this was 61%. In addition, many small (< 5 Mb) genetic lesions were encountered, frequently harboring clinically relevant ALL-related genes such as CDKN2A/B, ETV6, PAX5, and IKZF1. From our data we conclude that microarray-based genomic profiling serves as a robust tool in the genetic diagnosis of ALL, outreaching conventional karyotyping in CNA detection both in terms of sensitivity and specificity. We also propose a practical workflow for a comprehensive and objective interpretation of CNAs obtained through microarray-based genomic profiling, thereby facilitating its application in a routine clinical diagnostic setting.

  6. 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.

  7. Network analysis-based approach for exploring the potential diagnostic biomarkers of acute myocardial infarction.

    Directory of Open Access Journals (Sweden)

    Jiaqi Chen

    2016-12-01

    Full Text Available Acute myocardial infarction (AMI is a severe cardiovascular disease that is a serious threat to human life. However, the specific diagnostic biomarkers have not been fully clarified and candidate regulatory targets for AMI have not been identified. In order to explore the potential diagnostic biomarkers and possible regulatory targets of AMI, we used a network analysis-based approach to analyze microarray expression profiling of peripheral blood in patients with AMI. The significant differentially-expressed genes (DEGs were screened by Limma and constructed a gene function regulatory network (GO-Tree to obtain the inherent affiliation of significant function terms. The pathway action network was constructed, and the signal transfer relationship between pathway terms was mined in order to investigate the impact of core pathway terms in AMI. Subsequently, constructed the transcription regulatory network of DEGs. Weighted gene co-expression network analysis (WGCNA was employed to identify significantly altered gene modules and hub genes in two groups. Subsequently, the transcription regulation network of DEGs was constructed. We found that specific gene modules may provide a better insight into the potential diagnostic biomarkers of AMI. Our findings revealed and verified that NCF4, AQP9, NFIL3, DYSF, GZMA, TBX21, PRF1 and PTGDR genes by RT-qPCR. TBX21 and PRF1 may be potential candidates for diagnostic biomarker and possible regulatory targets in AMI.

  8. 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.

  9. 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.

  10. New model for light propagation in highly inhomogeneous polydisperse turbid media with applications in spray diagnostics

    OpenAIRE

    Berrocal, Edouard; Meglinski, I. V.; Jermy, Mark C.

    2005-01-01

    Modern optical diagnostics for quantitative characterization of polydisperse sprays and other aerosols which contain a wide range of droplet size encounter difficulties in the dense regions due to the multiple scattering of laser radiation with the surrounding droplets. The accuracy and efficiency of optical measurements can only be improved if the radiative transfer within such polydisperse turbid media is understood. A novel Monte Carlo code has been developed for modeling...

  11. Diagnostic of the temperature and differential emission measure (DEM based on Hinode/XRT data

    Directory of Open Access Journals (Sweden)

    P. Rudawy

    2008-10-01

    Full Text Available We discuss here various methodologies and an optimal strategy of the temperature and emission measure diagnostics based on Hinode X-Ray Telescope data. As an example of our results we present the determination of the temperature distribution of the X-rays emitting plasma using a filters ratio method and three various methods of the calculation of the differential emission measure (DEM. We have found that all these methods give results similar to the two filters ratio method. Additionally, all methods of the DEM calculation gave similar solutions. We can state that the majority of the pairs of the Hinode filters allows one to derive the temperature and emission measure in the isothermal plasma approximation using standard diagnostics based on the two filters ratio method. In cases of strong flares one can also expect good conformity of the results obtained using a Withbroe – Sylwester, genetic algorithm and least-squares methods of the DEM evaluation.

  12. 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%.

  13. Electrical-Based Diagnostic Techniques for Assessing Insulation Condition in Aged Transformers

    Directory of Open Access Journals (Sweden)

    Issouf Fofana

    2016-08-01

    Full Text Available The condition of the internal cellulosic paper and oil insulation are of concern for the performance of power transformers. Over the years, a number of methods have been developed to diagnose and monitor the degradation/aging of the transformer internal insulation system. Some of this degradation/aging can be assessed from electrical responses. Currently there are a variety of electrical-based diagnostic techniques available for insulation condition monitoring of power transformers. In most cases, the electrical signals being monitored are due to mechanical or electric changes caused by physical changes in resistivity, inductance or capacitance, moisture, contamination or aging by-products in the insulation. This paper presents a description of commonly used and modern electrical-based diagnostic techniques along with their interpretation schemes.

  14. USXR Based MHD, Transport, Equilibria and Current Profile Diagnostics for NSTX. Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Finkenthal, Michael

    2009-06-01

    The present report resumes the research activities of the Plasma Spectroscopy/Diagnostics Group at Johns Hopkins University performed on the NSTX tokamak at PPPL during the period 1999-2009. During this period we have designed and implemented XUV based diagnostics for a large number of tasks: study of impurity content and particle transport, MHD activity, time-resolved electron temperature measeurements, ELM research, etc. Both line emission and continuum were used in the XUV range. New technics and novel methods have been devised within the framework of the present research. Graduate and post-graduate students have been involved at all times in addition to the senior research personnel. Several tens of papers have been published and lectures have been given based on the obtained results at conferences and various research institutions (lists of these activities were attached both in each proposal and in the annual reports submitted to our supervisors at OFES).

  15. An Overview of Models of Speaking Performance and Its Implications for the Development of Procedural Framework for Diagnostic Speaking Tests

    Science.gov (United States)

    Zhao, Zhongbao

    2013-01-01

    This paper aims at developing a procedural framework for the development and validation of diagnostic speaking tests. The researcher reviews the current available models of speaking performance, analyzes the distinctive features and then points out the implications for the development of a procedural framework for diagnostic speaking tests. On…

  16. 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.

  17. 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

  18. Next-generation sequencing-based genome diagnostics across clinical genetics centers : implementation choices and their effects

    NARCIS (Netherlands)

    Vrijenhoek, Terry; Kraaijeveld, Ken; Elferink, Martin; de Ligt, Joep; Kranendonk, Elcke; Santen, Gijs; Nijman, Isaac J.; Butler, Derek; Claes, Godelieve; Costessi, Adalberto; Dorlijn, Wim; van Eyndhoven, Winfried; Halley, Dicky J. J.; van den Hout, Mirjam C. G. N.; van Hove, Steven; Johansson, Lennart F.; Jongbloed, Jan D. H.; Kamps, Rick; Kockx, Christel E. M.; de Koning, Bart; Kriek, Marjolein; Deprez, Ronald Lekanne Dit; Lunstroo, Hans; Mannens, Marcel; Mook, Olaf R.; Nelen, Marcel; Ploem, Corrette; Rijnen, Marco; Saris, Jasper J.; Sinke, Richard; Sistermans, Erik; van Slegtenhorst, Marjon; Sleutels, Frank; van der Stoep, Nienke; van Tienhoven, Marianne; Vermaat, Martijn; Vogel, Maartje; Waisfisz, Quinten; Weiss, Janneke Marjan; van den Wijngaard, Arthur; van Workum, Wilbert; Ijntema, Helger; van der Zwaag, Bert; van IJcken, Wilfred F. J.; den Dunnen, Johan T.; Veltman, Joris A.; Hennekam, Raoul; Cuppen, Edwin

    2015-01-01

    Implementation of next-generation DNA sequencing (NGS) technology into routine diagnostic genome care requires strategic choices. Instead of theoretical discussions on the consequences of such choices, we compared NGS-based diagnostic practices in eight clinical genetic centers in the Netherlands, b

  19. A Chinese literature overview on ultra-weak photon emission as promising technology for studying system-based diagnostics

    NARCIS (Netherlands)

    He, M.; Sun, M.; Wijk, E. van; Wietmarschen, H. van; Wijk, R. van; Wang, Z.; Wang, M.; Hankemeier, T.; Greef, J. van der

    2016-01-01

    To present the possibilities pertaining to linking ultra-weak photon emission (UPE) with Chinese medicine-based diagnostics principles, we conducted a review of Chinese literature regarding UPE with respect to a systems view of diagnostics. Data were summarized from human clinical studies and animal

  20. 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.

  1. 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.

  2. Computer modeling and design of diagnostic workstations and radiology reading rooms

    Science.gov (United States)

    Ratib, Osman M.; Amato, Carlos L.; Balbona, Joseph A.; Boots, Kevin; Valentino, Daniel J.

    2000-05-01

    We used 3D modeling techniques to design and evaluate the ergonomics of diagnostic workstation and radiology reading room in the planning phase of building a new hospital at UCLA. Given serious space limitations, the challenge was to provide more optimal working environment for radiologists in a crowded and busy environment. A particular attention was given to flexibility, lighting condition and noise reduction in rooms shared by multiple users performing diagnostic tasks as well as regular clinical conferences. Re-engineering workspace ergonomics rely on the integration of new technologies, custom designed cabinets, indirect lighting, sound-absorbent partitioning and geometric arrangement of workstations to allow better privacy while optimizing space occupation. Innovations included adjustable flat monitors, integration of videoconferencing and voice recognition, control monitor and retractable keyboard for optimal space utilization. An overhead compartment protecting the monitors from ambient light is also used as accessory lightbox and rear-view projection screen for conferences.

  3. NIR-camera-based online diagnostics of laser beam welding processes

    Science.gov (United States)

    Dorsch, Friedhelm; Braun, Holger; Keßler, Steffen; Pfitzner, Dieter; Rominger, Volker

    2012-03-01

    We have developed an on-axis camera-based online sensor system for laser beam welding diagnostics that detects the thermal radiation in the near-infrared (NIR) spectral range between 1200 and 1700 nm. In addition to a sensor in the visible (VIS) range, our camera detects the thermal radiation of the weld pool more clearly, and it is also sensible to the radiation of the solidified weld seam. The NIR images are analyzed by real-time image processing. Features are extracted from the images and evaluated to characterize the welding process. Keyhole and weld pool analysis complement VIS diagnostics, whereas the observation of the weld seam and heat affected zone with an NIR camera allows online heat flux thermography. By this means we are able to detect bad joints in overlap weldings ("false friends") online during the welding process.

  4. Scintillator based energetic ion loss diagnostic for the National Spherical Torus Experiment.

    Science.gov (United States)

    Darrow, D S

    2008-02-01

    A scintillator based energetic ion loss detector has been built and installed on the National Spherical Torus Experiment (NSTX) [Synakowski et al., Nucl. Fusion 43, 1653 (2000)] to measure the loss of neutral beam ions. The detector is able to resolve the pitch angle and gyroradius of the lost energetic ions. It has a wide acceptance range in pitch angle and energy, and is able to resolve the full, one-half, and one-third energy components of the 80 keV D neutral beams up to the maximum toroidal magnetic field of NSTX. Multiple Faraday cups have been embedded behind the scintillator to allow easy absolute calibration of the diagnostic and to measure the energetic ion loss in several ranges of pitch angle with good time resolution. Several small, vacuum compatible lamps allow simple calibration of the scintillator position within the field of view of the diagnostic's video camera.

  5. Diagnostics on LALR(k) conflicts based on a method for LR(k) testing

    DEFF Research Database (Denmark)

    Kristensen, Bent Bruun; Madsen, Ole Lehrmann

    1981-01-01

    A user of an LALR(k) parser generator system may have difficulties in understanding how a given LALR(k) conflict is generated. This is especially difficult if the conflict does not correspond to an LR(k) conflict. A practical method for giving informative diagnostics on LALR(k) conflicts...... is presented. The diagnostics distinguish between those LALR(k) conflicts that correspond to LR(k) conflicts and those that do not. As a side effect the user is thus informed whether or not his grammar is in fact LR(k) despite not being LALR(k). The method is based on an algorithm for testing LR(k)-ness using...

  6. Mobile phone-based biosensing: An emerging "diagnostic and communication" technology.

    Science.gov (United States)

    Quesada-González, Daniel; Merkoçi, Arben

    2017-06-15

    In this review we discuss recent developments on the use of mobile phones and similar devices for biosensing applications in which diagnostics and communications are coupled. Owing to the capabilities of mobile phones (their cameras, connectivity, portability, etc.) and to advances in biosensing, the coupling of these two technologies is enabling portable and user-friendly analytical devices. Any user can now perform quick, robust and easy (bio)assays anywhere and at any time. Among the most widely reported of such devices are paper-based platforms. Herein we provide an overview of a broad range of biosensing possibilities, from optical to electrochemical measurements; explore the various reported designs for adapters; and consider future opportunities for this technology in fields such as health diagnostics, safety & security, and environment monitoring.

  7. 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.

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

    Directory of Open Access Journals (Sweden)

    Jieyao Cheng

    Full Text Available 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.The diagnostic performance of ten noninvasive models (HALF index, FibroScan, S index, Zeng model, Youyi model, Hui model, APAG, APRI, FIB-4 and FibroTest was assessed against the liver histology by ROC curve analysis in CHB patients. The reproducibility of the ten models were evaluated by recalculating the diagnostic values at the given cut-off values defined by the original studies.Six models (HALF index, FibroScan, Zeng model, Youyi model, S index and FibroTest had AUROCs higher than 0.70 in predicting any fibrosis stage and 2 of them had best diagnostic performance with AUROCs to predict F≥2, F≥3 and F4 being 0.83, 0.89 and 0.89 for HALF index, 0.82, 0.87 and 0.87 for FibroScan, respectively. Four models (HALF index, FibroScan, Zeng model and Youyi model showed good diagnostic values at given cut-offs.HALF index, FibroScan, Zeng model, Youyi model, S index and FibroTest show a good diagnostic performance and all of them, except S index and FibroTest, have good reproducibility for evaluating liver fibrosis in CHB patients.ChiCTR-DCS-07000039.

  9. Is a biomarker-based diagnostic strategy for invasive aspergillosis cost effective in high-risk haematology patients?

    Science.gov (United States)

    Macesic, N; Morrissey, C O; Liew, D; Bohensky, M A; Chen, S C-A; Gilroy, N M; Milliken, S T; Szer, J; Slavin, M A

    2017-01-27

    Empirical antifungal therapy is frequently used in hematology patients at high risk of invasive aspergillosis (IA), with substantial cost and toxicity. Biomarkers for IA aim for earlier and more accurate diagnosis and targeted treatment. However, data on the cost-effectiveness of a biomarker-based diagnostic strategy (BDS) are limited. We evaluated the cost effectiveness of BDS using results from a randomized controlled trial (RCT) and individual patient costing data. Data inputs derived from a published RCT were used to construct a decision-analytic model to compare BDS (Aspergillus galactomannan and PCR on blood) with standard diagnostic strategy (SDS) of culture and histology in terms of total costs, length of stay, IA incidence, mortality, and years of life saved. Costs were estimated for each patient using hospital costing data to day 180 and follow-up for survival was modeled to five years using a Gompertz survival model. Treatment costs were determined for 137 adults undergoing allogeneic hematopoietic stem cell transplant or receiving chemotherapy for acute leukemia in four Australian centers (2005-2009). Median total costs at 180 days were similar between groups (US[Formula: see text] for SDS [IQR US[Formula: see text

  10. 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.

  11. 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.

  12. Quantitative diagnostics of soft tissue through viscoelastic characterization using time-based instrumented palpation.

    Science.gov (United States)

    Palacio-Torralba, Javier; Hammer, Steven; Good, Daniel W; Alan McNeill, S; Stewart, Grant D; Reuben, Robert L; Chen, Yuhang

    2015-01-01

    Although palpation has been successfully employed for centuries to assess soft tissue quality, it is a subjective test, and is therefore qualitative and depends on the experience of the practitioner. To reproduce what the medical practitioner feels needs more than a simple quasi-static stiffness measurement. This paper assesses the capacity of dynamic mechanical palpation to measure the changes in viscoelastic properties that soft tissue can exhibit under certain pathological conditions. A diagnostic framework is proposed to measure elastic and viscous behaviors simultaneously using a reduced set of viscoelastic parameters, giving a reliable index for quantitative assessment of tissue quality. The approach is illustrated on prostate models reconstructed from prostate MRI scans. The examples show that the change in viscoelastic time constant between healthy and cancerous tissue is a key index for quantitative diagnostics using point probing. The method is not limited to any particular tissue or material and is therefore useful for tissue where defining a unique time constant is not trivial. The proposed framework of quantitative assessment could become a useful tool in clinical diagnostics for soft tissue.

  13. 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

  14. Clinical prediction model to aid emergency doctors managing febrile children at risk of serious bacterial infections: Diagnostic study

    NARCIS (Netherlands)

    R.G. Nijman (Ruud); Y. Vergouwe (Yvonne); M.J. Thompson (Matthew); M.V. Veen (Mirjam Van); A.H.J. van Meurs (Alfred); J. van der Lei (Johan); E.W. Steyerberg (Ewout); H.A. Moll (Henriëtte); R. Oostenbrink (Rianne)

    2013-01-01

    textabstractObjective: To derive, cross validate, and externally validate a clinical prediction model that assesses the risks of different serious bacterial infections in children with fever at the emergency department. Design: Prospective observational diagnostic study. Setting: Three paediatric em

  15. Smartphone-Based Accurate Analysis of Retinal Vasculature towards Point-of-Care Diagnostics

    Science.gov (United States)

    Xu, Xiayu; Ding, Wenxiang; Wang, Xuemin; Cao, Ruofan; Zhang, Maiye; Lv, Peilin; Xu, Feng

    2016-01-01

    Retinal vasculature analysis is important for the early diagnostics of various eye and systemic diseases, making it a potentially useful biomarker, especially for resource-limited regions and countries. Here we developed a smartphone-based retinal image analysis system for point-of-care diagnostics that is able to load a fundus image, segment retinal vessels, analyze individual vessel width, and store or uplink results. The proposed system was not only evaluated on widely used public databases and compared with the state-of-the-art methods, but also validated on clinical images directly acquired with a smartphone. An Android app is also developed to facilitate on-site application of the proposed methods. Both visual assessment and quantitative assessment showed that the proposed methods achieved comparable results to the state-of-the-art methods that require high-standard workstations. The proposed system holds great potential for the early diagnostics of various diseases, such as diabetic retinopathy, for resource-limited regions and countries. PMID:27698369

  16. 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

  17. Observational constraints and diagnostics for time-dependent dark energy models

    CERN Document Server

    Wang, Deng

    2016-01-01

    In this paper, we constrain four time-dependent dark energy (TDDE) models by using the Type Ia supernovae (SNe Ia), baryonic acoustic oscillations (BAO), observational Hubble parameter (OHD) data-sets as well as the single data point from the newest event GW150914. Subsequently, adopting the best fitting values of the model parameters, we apply the original statefinder, statefinder hierarchy, the growth rate of matter perturbations and $Om(z)$ diagnostics to distinguish the TDDE scenarios and the $\\Lambda$CDM scenario from each other. We discover that all the TDDE models and $\\Lambda$CDM model can be distinguished better at the present epoch by using the statefinder hierarchy than using the original statefinder, the growth rate of matter perturbations and $Om(z)$ diagnostics, especially, in the planes of $\\{S_3^{(1)},S_4^{(1)}\\}$, $\\{S_3^{(2)},S_4^{(2)}\\}$, $\\{S_5^{(1)},S_5^{(2)}\\}$ and $\\{S_4^{(2)},S_5^{(2)}\\}$.

  18. 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

  19. Diagnosing Appendicitis: Evidence-Based Review of the Diagnostic Approach in 2014

    Directory of Open Access Journals (Sweden)

    Daniel J. Shogilev

    2014-11-01

    Full Text Available Introduction: Acute appendicitis is the most common abdominal emergency requiring emergency surgery. However, the diagnosis is often challenging and the decision to operate, observe or further work-up a patient is often unclear. The utility of clinical scoring systems (namely the Alvarado score, laboratory markers, and the development of novel markers in the diagnosis of appendicitis remains controversial. This article presents an update on the diagnostic approach to appendicitis through an evidence-based review. Methods: We performed a broad Medline search of radiological imaging, the Alvarado score, common laboratory markers, and novel markers in patients with suspected appendicitis. Results: Computed tomography (CT is the most accurate mode of imaging for suspected cases of appendicitis, but the associated increase in radiation exposure is problematic. The Alvarado score is a clinical scoring system that is used to predict the likelihood of appendicitis based on signs, symptoms and laboratory data. It can help risk stratify patients with suspected appendicitis and potentially decrease the use of CT imaging in patients with certain Alvarado scores. White blood cell (WBC, C-reactive protein (CRP, granulocyte count and proportion of polymorphonuclear (PMN cells are frequently elevated in patients with appendicitis, but are insufficient on their own as a diagnostic modality. When multiple markers are used in combination their diagnostic utility is greatly increased. Several novel markers have been proposed to aid in the diagnosis of appendicitis; however, while promising, most are only in the preliminary stages of being studied. Conclusion: While CT is the most accurate mode of imaging in suspected appendicitis, the accompanying radiation is a concern. Ultrasound may help in the diagnosis while decreasing the need for CT in certain circumstances. The Alvarado Score has good diagnostic utility at specific cutoff points. Laboratory markers have

  20. 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.

  1. 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

  2. Oligonucleotide-based biosensors for in vitro diagnostics and environmental hazard detection.

    Science.gov (United States)

    Jung, Il Young; Lee, Eun Hee; Suh, Ah Young; Lee, Seung Jin; Lee, Hyukjin

    2016-04-01

    Oligonucleotide-based biosensors have drawn much attention because of their broad applications in in vitro diagnostics and environmental hazard detection. They are particularly of interest to many researchers because of their high specificity as well as excellent sensitivity. Recently, oligonucleotide-based biosensors have been used to achieve not only genetic detection of targets but also the detection of small molecules, peptides, and proteins. This has further broadened the applications of these sensors in the medical and health care industry. In this review, we highlight various examples of oligonucleotide-based biosensors for the detection of diseases, drugs, and environmentally hazardous chemicals. Each example is provided with detailed schematics of the detection mechanism in addition to the supporting experimental results. Furthermore, future perspectives and new challenges in oligonucleotide-based biosensors are discussed.

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

    Directory of Open Access Journals (Sweden)

    Luis Alberto Corona Martínez

    2007-04-01

    Full Text Available 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, and also allows the establishment of some of the regularities whose knowledge by the student is of great importance for the learning and application of the method by our Medicine students.

  4. Preliminary investigation into application of problem-based learning in the practical teaching of diagnostics

    Directory of Open Access Journals (Sweden)

    Rui Z

    2015-03-01

    Full Text Available Zeng Rui,1,* Yue Rong-Zheng,2,* Qiu Hong-Yu,2 Zeng Jing,3 Wan Xue-Hong,3 Zuo Chuan41Department of Cardiovascular Diseases, 2Department of Nephrology, 3Department of Internal Medicine, 4Department of Rheumatology and Immunology, West China Hospital, School of Clinical Medicine, Sichuan University, Chengdu, People's Republic of China*These author contributed equally to this work and should both be considered first authorsBackground: Problem-based learning (PBL is a pedagogical approach based on problems. Specifically, it is a student-centered, problem-oriented teaching method that is conducted through group discussions. The aim of our study is to explore the effects of PBL in diagnostic teaching for Chinese medical students.Methods: A prospective, randomized controlled trial was conducted. Eighty junior clinical medical students were randomly divided into two groups. Forty students were allocated to a PBL group and another 40 students were allocated to a control group using the traditional teaching method. Their scores in the practice skills examination, ability to write and analyze medical records, and results on the stage test and behavior observation scale were compared. A questionnaire was administered in the PBL group after class.Results: There were no significant differences in scores for writing medical records, content of interviewing, physical examination skills, and stage test between the two groups. However, compared with the control group, the PBL group had significantly higher scores on case analysis, interviewing skills, and behavioral observation scales.Conclusion: The questionnaire survey revealed that PBL could improve interest in learning, cultivate an ability to study independently, improve communication and analytical skills, and good team cooperation spirit. However, there were some shortcomings in systematization of imparting knowledge. PBL has an obvious advantage in teaching with regard to diagnostic practice

  5. Implementation of erythroid lineage analysis by flow cytometry in diagnostic models for myelodysplastic syndromes

    Science.gov (United States)

    Cremers, Eline M.P.; Westers, Theresia M.; Alhan, Canan; Cali, Claudia; Visser-Wisselaar, Heleen A.; Chitu, Dana A.; van der Velden, Vincent H.J.; te Marvelde, Jeroen G.; Klein, Saskia K.; Muus, Petra; Vellenga, Edo; de Greef, Georgina E.; Legdeur, Marie-Cecile C.J.C.; Wijermans, Pierre W.; Stevens-Kroef, Marian J.P.L.; da Silva-Coelho, Pedro; Jansen, Joop H.; Ossenkoppele, Gert J.; van de Loosdrecht, Arjan A.

    2017-01-01

    Flow cytometric analysis is a recommended tool in the diagnosis of myelodysplastic syndromes. Current flow cytometric approaches evaluate the (im)mature myelo-/monocytic lineage with a median sensitivity and specificity of ~71% and ~93%, respectively. We hypothesized that the addition of erythroid lineage analysis could increase the sensitivity of flow cytometry. Hereto, we validated the analysis of erythroid lineage parameters recommended by the International/European LeukemiaNet Working Group for Flow Cytometry in Myelodysplastic Syndromes, and incorporated this evaluation in currently applied flow cytometric models. One hundred and sixty-seven bone marrow aspirates were analyzed; 106 patients with myelodysplastic syndromes, and 61 cytopenic controls. There was a strong correlation between presence of erythroid aberrancies assessed by flow cytometry and the diagnosis of myelodysplastic syndromes when validating the previously described erythroid evaluation. Furthermore, addition of erythroid aberrancies to two different flow cytometric models led to an increased sensitivity in detecting myelodysplastic syndromes: from 74% to 86% for the addition to the diagnostic score designed by Ogata and colleagues, and from 69% to 80% for the addition to the integrated flow cytometric score for myelodysplastic syndromes, designed by our group. In both models the specificity was unaffected. The high sensitivity and specificity of flow cytometry in the detection of myelodysplastic syndromes illustrates the important value of flow cytometry in a standardized diagnostic approach. The trial is registered at www.trialregister.nl as NTR1825; EudraCT n.: 2008-002195-10 PMID:27658438

  6. 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.

  7. A nondestructive diagnostic method based on swept-frequency ultrasound transmission-reflection measurements

    Science.gov (United States)

    Bramanti, Mauro

    1992-08-01

    A nondestructive diagnostic technique is proposed to measure depth and thickness of unwanted inclusions inside laminate-type materials (gaps, delaminations, and cracks, for example). The method is based on the frequency-domain analysis of transmission and reflection coefficient measured on the material under test when it is irradiated by a CW ultrasound beam whose frequency varies over a suitable frequency range. By measuring the frequency distance between two adjacent minima in the attenuation and reflection coefficients the thickness and depth of the inclusion can be obtained. A practical implementation of the technique is suggested, and the first experimental results obtained by a laboratory setup are reported.

  8. A memory-based model of posttraumatic stress disorder

    DEFF Research Database (Denmark)

    Rubin, David C.; Berntsen, Dorthe; Johansen, Marlene Klindt

    2008-01-01

    In the mnemonic model of posttraumatic stress disorder (PTSD), the current memory of a negative event, not the event itself, determines symptoms. The model is an alternative to the current event-based etiology of PTSD represented in the Diagnostic and Statistical Manual of Mental Disorders (4th ed......., text rev.; American Psychiatric Association, 2000). The model accounts for important and reliable findings that are often inconsistent with the current diagnostic view and that have been neglected by theoretical accounts of the disorder, including the following observations. The diagnosis needs...

  9. The clinical inadequacy of the DSM-5 classification of somatic symptom and related disorders: an alternative trans-diagnostic model.

    Science.gov (United States)

    Cosci, Fiammetta; Fava, Giovanni A

    2016-08-01

    The Diagnostic and Statistical of Mental Disorders, Fifth Edition (DSM-5) somatic symptom and related disorders chapter has a limited clinical utility. In addition to the problems that the single diagnostic rubrics and the deletion of the diagnosis of hypochondriasis entail, there are 2 major ambiguities: (1) the use of the term "somatic symptoms" reflects an ill-defined concept of somatization and (2) abnormal illness behavior is included in all diagnostic rubrics, but it is never conceptually defined. In the present review of the literature, we will attempt to approach the clinical issue from a different angle, by introducing the trans-diagnostic viewpoint of illness behavior and propose an alternative clinimetric classification system, based on the Diagnostic Criteria for Psychosomatic Research.

  10. 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

  11. 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.

  12. The Biplot as a diagnostic tool of local dependence in latent class models. A medical application.

    Science.gov (United States)

    Sepúlveda, R; Vicente-Villardón, J L; Galindo, M P

    2008-05-20

    Latent class models (LCMs) can be used to assess diagnostic test performance when no reference test (a gold standard) is available, considering two latent classes representing disease or non-disease status. One of the basic assumptions in such models is that of local or conditional independence: all indicator variables (tests) are statistically independent within each latent class. However, in practice this assumption is often violated; hence, the two-LCM fits the data poorly. In this paper, we propose the use of Biplot methods to identify the conditional dependence between pairs of manifest variables within each latent class. Additionally, we propose incorporating such dependence in the corresponding latent class using the log-linear formulation of the model.

  13. 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.

  14. Realization of process improvement at a diagnostic radiology department with aid of simulation modeling.

    Science.gov (United States)

    Oh, Hong-Choon; Toh, Hong-Guan; Giap Cheong, Eddy Seng

    2011-11-01

    Using the classical process improvement framework of Plan-Do-Study-Act (PDSA), the diagnostic radiology department of a tertiary hospital identified several patient cycle time reduction strategies. Experimentation of these strategies (which included procurement of new machines, hiring of new staff, redesign of queue system, etc.) through pilot scale implementation was impractical because it might incur substantial expenditure or be operationally disruptive. With this in mind, simulation modeling was used to test these strategies via performance of "what if" analyses. Using the output generated by the simulation model, the team was able to identify a cost-free cycle time reduction strategy, which subsequently led to a reduction of patient cycle time and achievement of a management-defined performance target. As healthcare professionals work continually to improve healthcare operational efficiency in response to rising healthcare costs and patient expectation, simulation modeling offers an effective scientific framework that can complement established process improvement framework like PDSA to realize healthcare process enhancement.

  15. Stage Separation Failure: Model Based Diagnostics and Prognostics

    Science.gov (United States)

    2010-10-01

    estimate the characteristic time of the heating of the nozzle wall analytically we use Bartz’ approximation (Bartz, 1965; Incropera and DeWitt, 2002...Publishing Company, Inc. New York. F.P. Incropera and D. P. DeWitt (2002), Introduction to Heat Transfer, John Wiley & Sons, NY, D.G. Luchinsky, V.V

  16. 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...

  17. Rotorcraft Diagnostics

    Science.gov (United States)

    Haste, Deepak; Azam, Mohammad; Ghoshal, Sudipto; Monte, James

    2012-01-01

    Health management (HM) in any engineering systems requires adequate understanding about the system s functioning; a sufficient amount of monitored data; the capability to extract, analyze, and collate information; and the capability to combine understanding and information for HM-related estimation and decision-making. Rotorcraft systems are, in general, highly complex. Obtaining adequate understanding about functioning of such systems is quite difficult, because of the proprietary (restricted access) nature of their designs and dynamic models. Development of an EIM (exact inverse map) solution for rotorcraft requires a process that can overcome the abovementioned difficulties and maximally utilize monitored information for HM facilitation via employing advanced analytic techniques. The goal was to develop a versatile HM solution for rotorcraft for facilitation of the Condition Based Maintenance Plus (CBM+) capabilities. The effort was geared towards developing analytic and reasoning techniques, and proving the ability to embed the required capabilities on a rotorcraft platform, paving the way for implementing the solution on an aircraft-level system for consolidation and reporting. The solution for rotorcraft can he used offboard or embedded directly onto a rotorcraft system. The envisioned solution utilizes available monitored and archived data for real-time fault detection and identification, failure precursor identification, and offline fault detection and diagnostics, health condition forecasting, optimal guided troubleshooting, and maintenance decision support. A variant of the onboard version is a self-contained hardware and software (HW+SW) package that can be embedded on rotorcraft systems. The HM solution comprises components that gather/ingest data and information, perform information/feature extraction, analyze information in conjunction with the dependency/diagnostic model of the target system, facilitate optimal guided troubleshooting, and offer

  18. Optical diagnostics based on elastic scattering: Recent clinical demonstrations with the Los Alamos Optical Biopsy System

    Energy Technology Data Exchange (ETDEWEB)

    Bigio, I.J.; Loree, T.R.; Mourant, J.; Shimada, T. [Los Alamos National Lab., NM (United States); Story-Held, K.; Glickman, R.D. [Texas Univ. Health Science Center, San Antonio, TX (United States). Dept. of Ophthalmology; Conn, R. [Lovelace Medical Center, Albuquerque, NM (United States). Dept. of Urology

    1993-08-01

    A non-invasive diagnostic tool that could identify malignancy in situ and in real time would have a major impact on the detection and treatment of cancer. We have developed and are testing early prototypes of an optical biopsy system (OBS) for detection of cancer and other tissue pathologies. The OBS invokes a unique approach to optical diagnosis of tissue pathologies based on the elastic scattering properties, over a wide range of wavelengths, of the microscopic structure of the tissue. The use of elastic scattering as the key to optical tissue diagnostics in the OBS is based on the fact that many tissue pathologies, including a majority of cancer forms, manifest significant architectural changes at the cellular and sub-cellular level. Since the cellular components that cause elastic scattering have dimensions typically on the order of visible to near-IR wavelengths, the elastic (Mie) scattering properties will be strongly wavelength dependent. Thus, morphology and size changes can be expected to cause significant changes in an optical signature that is derived from the wavelength dependence of elastic scattering. The data acquisition and storage/display time with the OBS instrument is {approximately}1 second. Thus, in addition to the reduced invasiveness of this technique compared with current state-of-the-art methods (surgical biopsy and pathology analysis), the OBS offers the possibility of impressively faster diagnostic assessment. The OBS employs a small fiber-optic probe that is amenable to use with any endoscope, catheter or hypodermic, or to direct surface examination (e.g. as in skin cancer or cervical cancer). It has been tested in vitro on animal and human tissue samples, and clinical testing in vivo is currently in progress.

  19. 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.

  20. 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

  1. 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.

  2. A damage diagnostic imaging algorithm based on the quantitative comparison of Lamb wave signals

    Science.gov (United States)

    Wang, Dong; Ye, Lin; Lu, Ye; Li, Fucai

    2010-06-01

    With the objective of improving the temperature stability of the quantitative comparison of Lamb wave signals captured in different states, a damage diagnostic imaging algorithm integrated with Shannon-entropy-based interrogation was proposed. It was evaluated experimentally by identifying surface damage in a stiffener-reinforced CF/EP quasi-isotropic woven laminate. The variations in Shannon entropy of the reference (without damage) and present (with damage) signals from individual sensing paths were calibrated as damage signatures and utilized to estimate the probability of the presence of damage in the monitoring area enclosed by an active sensor network. The effects of temperature change on calibration of the damage signatures and estimation of the probability values for the presence of damage were investigated using a set of desynchronized signals. The results demonstrate that the Shannon-entropy-based damage diagnostic imaging algorithm with improved robustness in the presence of temperature change has the capability of providing accurate identification of damage in actual environments.

  3. Single-use paper-based hydrogen fuel cells for point-of-care diagnostic applications

    Science.gov (United States)

    Esquivel, J. P.; Buser, J. R.; Lim, C. W.; Domínguez, C.; Rojas, S.; Yager, P.; Sabaté, N.

    2017-02-01

    This work demonstrates a stand-alone power source that integrates a paper-based hydrogen fuel cell with a customized chemical heater that produces hydrogen in-situ upon the addition of a liquid. The presented approach operates by capillary action and takes advantage of the hydrogen released as a by-product of an exothermic reaction used in point-of-care diagnostics. The paper-based fuel cell produces a maximum power of 25.8 mW (103.2 mW cm-2), which is suitable for powering a diversity of electrical devices such as commercially available digital pregnancy tests and glucometers. While device shape and dimensions can be customized, here it is shown that the fuel cell can be designed in a compact form factor and footprint comparable to a lateral flow test while providing a remarkable power output. This approach holds great promise for powering portable diagnostics, as the generated electric power could enable device functionalities required for advanced assays, such as device timing, actuation, and signal quantification. Part of the same liquid sample that is to be analyzed (urine, saliva, water, etc) could be used to trigger the hydrogen generation and start the fuel cell operation.

  4. 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.

  5. Synergism between particle-based multiplexing and microfluidics technologies may bring diagnostics closer to the patient.

    Science.gov (United States)

    Derveaux, S; Stubbe, B G; Braeckmans, K; Roelant, C; Sato, K; Demeester, J; De Smedt, S C

    2008-08-01

    In the field of medical diagnostics there is a growing need for inexpensive, accurate, and quick high-throughput assays. On the one hand, recent progress in microfluidics technologies is expected to strongly support the development of miniaturized analytical devices, which will speed up (bio)analytical assays. On the other hand, a higher throughput can be obtained by the simultaneous screening of one sample for multiple targets (multiplexing) by means of encoded particle-based assays. Multiplexing at the macro level is now common in research labs and is expected to become part of clinical diagnostics. This review aims to debate on the "added value" we can expect from (bio)analysis with particles in microfluidic devices. Technologies to (a) decode, (b) analyze, and (c) manipulate the particles are described. Special emphasis is placed on the challenges of integrating currently existing detection platforms for encoded microparticles into microdevices and on promising microtechnologies that could be used to down-scale the detection units in order to obtain compact miniaturized particle-based multiplexing platforms.

  6. Static Digital Telepathology: A Model for Diagnostic and Educational Support to Pathologists in the Developing World

    Science.gov (United States)

    Sohani, Aliyah R.; Sohani, Moez A.

    2012-01-01

    Background: The practice of pathology in the developing world presents challenges in terms of limited resources, shortages of trained personnel, and lack of continuing education programs. Telepathology holds promise as a means of diagnostic and educational support. Methods: We donated multiheaded teaching microscopes equipped with digital cameras to four hospitals in Eastern Africa and trained local pathologists on their use. Static images of challenging cases were posted on a web-based telepathology platform. A U.S.-based pathologist reviewed images in consultation with subspecialist colleagues. Results: Over a period of 40 months, 109 cases were submitted for second opinion consultation, including 29 dermatopathology cases (26.6%), 14 hematopathology cases (12.8%), and 13 cases each (11.9%) in cytopathology and bone and soft tissue pathology. Static images enabled a complete or partial diagnosis in 100/109 cases (91.7%). Factors precluding a definitive diagnosis included absence of confirmatory immunophenotyping, technical issues, or lack of clinical history. Case responses included a diagnosis and discussion, including differential diagnosis, references, and treatment recommendations. Conclusion: Static digital telepathology is a simple, cost-effective, reliable and efficient means to provide diagnostic and educational support to pathologists in the developing world. Additional training may help overcome technical factors precluding a definitive diagnosis in certain cases. PMID:22233701

  7. 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

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

    Science.gov (United States)

    Moores, B M; Charnock, P; Ward, M

    2010-01-01

    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

  9. Appropriate targeting of artemisinin-based combination therapy by community health workers using malaria rapid diagnostic tests

    DEFF Research Database (Denmark)

    Ndyomugyenyi, Richard; Magnussen, Pascal; Lal, Sham;

    2016-01-01

    OBJECTIVE: To compare the impact of malaria rapid diagnostic tests (mRDTs), used by community health workers (CHWs), on the proportion of children ... sensitivity of current mRDTs in patients with low parasite density are a concern. For community-based treatment in areas of low transmission and/or non-immune populations, presumptive treatment of all fevers as malaria may be advisable, until more sensitive diagnostic assays, suitable for routine use by CHWs...

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

    OpenAIRE

    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...

  11. Comparing Multiple-Group Multinomial Log-Linear Models for Multidimensional Skill Distributions in the General Diagnostic Model. Research Report. ETS RR-08-35

    Science.gov (United States)

    Xu, Xueli; von Davier, Matthias

    2008-01-01

    The general diagnostic model (GDM) utilizes located latent classes for modeling a multidimensional proficiency variable. In this paper, the GDM is extended by employing a log-linear model for multiple populations that assumes constraints on parameters across multiple groups. This constrained model is compared to log-linear models that assume…

  12. Size-based molecular diagnostics using plasma DNA for noninvasive prenatal testing.

    Science.gov (United States)

    Yu, Stephanie C Y; Chan, K C Allen; Zheng, Yama W L; Jiang, Peiyong; Liao, Gary J W; Sun, Hao; Akolekar, Ranjit; Leung, Tak Y; Go, Attie T J I; van Vugt, John M G; Minekawa, Ryoko; Oudejans, Cees B M; Nicolaides, Kypros H; Chiu, Rossa W K; Lo, Y M Dennis

    2014-06-10

    Noninvasive prenatal testing using fetal DNA in maternal plasma is an actively researched area. The current generation of tests using massively parallel sequencing is based on counting plasma DNA sequences originating from different genomic regions. In this study, we explored a different approach that is based on the use of DNA fragment size as a diagnostic parameter. This approach is dependent on the fact that circulating fetal DNA molecules are generally shorter than the corresponding maternal DNA molecules. First, we performed plasma DNA size analysis using paired-end massively parallel sequencing and microchip-based capillary electrophoresis. We demonstrated that the fetal DNA fraction in maternal plasma could be deduced from the overall size distribution of maternal plasma DNA. The fetal DNA fraction is a critical parameter affecting the accuracy of noninvasive prenatal testing using maternal plasma DNA. Second, we showed that fetal chromosomal aneuploidy could be detected by observing an aberrant proportion of short fragments from an aneuploid chromosome in the paired-end sequencing data. Using this approach, we detected fetal trisomy 21 and trisomy 18 with 100% sensitivity (T21: 36/36; T18: 27/27) and 100% specificity (non-T21: 88/88; non-T18: 97/97). For trisomy 13, the sensitivity and specificity were 95.2% (20/21) and 99% (102/103), respectively. For monosomy X, the sensitivity and specificity were both 100% (10/10 and 8/8). Thus, this study establishes the principle of size-based molecular diagnostics using plasma DNA. This approach has potential applications beyond noninvasive prenatal testing to areas such as oncology and transplantation monitoring.

  13. A starch-based microparticulate system dedicated to diagnostic and therapeutic nuclear medicine applications.

    Science.gov (United States)

    Lacoeuille, F; Hindré, F; Venier-Julienne, M C; Sergent, M; Bouchet, F; Jouaneton, S; Denizot, B; Askienazy, S; Benoit, J P; Couturier, O F; Le Jeune, J J

    2011-11-01

    The aim of this work was to develop a new microparticulate system able to form a complex with radionuclides with a high yield of purity for diagnostic or therapeutic applications. Owing to its properties potato starch was chosen as starting material and modified by oxidization and coupling of a ligand (polyamine) enabling modified starch to chelate radionuclides. The choice of suitable experiments was based on a combination of a Rechtschaffner experimental design and a surface response design to determine the influence of experimental parameters and to optimize the final product. Starch-based microparticle formulations from the experimental plans were compared and characterized through particle size analysis, scanning electron microscopy, elemental analysis and, for the most promising formulations, by in vitro labeling stability studies and determination of free polyamine content or in vivo imaging studies. The mechanism of starch-based microparticle degradation was identified by means of size measurements. The results of the Rechtschaffner design showed the positive qualitative effect of the temperature and the duration of coupling reaction whereas surface response analysis clearly showed that, by increasing the oxidization level and starch concentration, the nitrogen content in the final product is increased. In vitro and in vivo characterization led to identification of the best formulation. With a size around 30 μm, high radiochemical purity (over 95%) and a high signal-to-noise ratio (over 600), the new starch-based microparticulate system could be prepared as ready-to-use kits and sterilized without modification of its characteristics, and thus meet the requirement for in vivo diagnostic and therapeutic applications.

  14. New model for light propagation in highly inhomogeneous polydisperse turbid media with applications in spray diagnostics

    Science.gov (United States)

    Berrocal, Edouard; Meglinski, Igor; Jermy, Mark

    2005-11-01

    Modern optical diagnostics for quantitative characterization of polydisperse sprays and other aerosols which contain a wide range of droplet size encounter difficulties in the dense regions due to the multiple scattering of laser radiation with the surrounding droplets. The accuracy and efficiency of optical measurements can only be improved if the radiative transfer within such polydisperse turbid media is understood. A novel Monte Carlo code has been developed for modeling of optical radiation propagation in inhomogeneous polydisperse scattering media with typical drop size ranging from 2 μm to 200 μm in diameter. We show how strong variations of both particle size distribution and particle concentration within a 3D scattering medium can be taken into account via the Monte Carlo approach. A new approximation which reduces ~20 times the computational memory space required to determine the phase function is described. The approximation is verified by considering four log-normal drop size distributions. It is found valid for particle sizes in the range of 10-200 μm with increasing errors, due to additional photons scattered at large angles, as the number of particles below than 10 μm increases. The technique is applied to the simulation of typical planar Mie imaging of a hollow cone spray. Simulated and experimental images are compared and shown to agree well. The code has application in developing and testing new optical diagnostics for complex scattering media such as dense sprays.

  15. 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

  16. Development of diagnostic SPR based biosensor for the detection of pharmaceutical compounds in saliva

    Science.gov (United States)

    Sonny, Susanna; Sesay, Adama M.; Virtanen, Vesa

    2010-11-01

    The aim of the study is to develop diagnostic tests for the detection of pharmaceutical compounds in saliva. Oral fluid is increasingly being considered as an ideal sample matrix. It can be collected non-invasively and causes less stress to the person being tested. The detection of pharmaceutical compounds and drugs in saliva can give valuable information on individual bases on dose response, usage, characterization and clinical diagnostics. Surface plasmon resonance (SPR) is a highly sensitive, fast and label free analytical technique for the detection of molecular interactions. The specific binding of measured analyte onto the active gold sensing surface of the SPR device induces a refractive index change that can be monitored. To monitor these pharmaceutical compounds in saliva the immunoassays were developed using a SPR instrument. The instrument is equipped with a 670nm laser diode and has two sensing channels. Monoclonal antibodies against the pharmaceutical compounds were used to specifically recognise and capture the compounds which intern will have an effect of the refractive index monitored. Preliminary results show that the immunoassays for cocaine and MDMA (3,4-methylenedioxymethamphetamine) are very sensitive and have linear ranges of 0.01 pg/ml - 1 ng/ml and 0.1 pg/ml - 100 ng/ml, respectively.

  17. A smartphone-based diagnostic platform for rapid detection of Zika, chikungunya, and dengue viruses

    Science.gov (United States)

    Priye, Aashish; Bird, Sara W.; Light, Yooli K.; Ball, Cameron S.; Negrete, Oscar A.; Meagher, Robert J.

    2017-01-01

    Current multiplexed diagnostics for Zika, dengue, and chikungunya viruses are situated outside the intersection of affordability, high performance, and suitability for use at the point-of-care in resource-limited settings. Consequently, insufficient diagnostic capabilities are a key limitation facing current Zika outbreak management strategies. Here we demonstrate highly sensitive and specific detection of Zika, chikungunya, and dengue viruses by coupling reverse-transcription loop-mediated isothermal amplification (RT-LAMP) with our recently developed quenching of unincorporated amplification signal reporters (QUASR) technique. We conduct reactions in a simple, inexpensive and portable “LAMP box” supplemented with a consumer class smartphone. The entire assembly can be powered by a 5 V USB source such as a USB power bank or solar panel. Our smartphone employs a novel algorithm utilizing chromaticity to analyze fluorescence signals, which improves the discrimination of positive/negative signals by 5-fold when compared to detection with traditional RGB intensity sensors or the naked eye. The ability to detect ZIKV directly from crude human sample matrices (blood, urine, and saliva) demonstrates our device’s utility for widespread clinical deployment. Together, these advances enable our system to host the key components necessary to expand the use of nucleic acid amplification-based detection assays towards point-of-care settings where they are needed most. PMID:28317856

  18. Method for assessing the reliability of molecular diagnostics based on multiplexed SERS-coded nanoparticles.

    Directory of Open Access Journals (Sweden)

    Steven Y Leigh

    Full Text Available Surface-enhanced Raman scattering (SERS nanoparticles have been engineered to generate unique fingerprint spectra and are potentially useful as bright contrast agents for molecular diagnostics. One promising strategy for biomedical diagnostics and imaging is to functionalize various particle types ("flavors", each emitting a unique spectral signature, to target a large multiplexed panel of molecular biomarkers. While SERS particles emit narrow spectral features that allow them to be easily separable under ideal conditions, the presence of competing noise sources and background signals such as detector noise, laser background, and autofluorescence confounds the reliability of demultiplexing algorithms. Results obtained during time-constrained in vivo imaging experiments may not be reproducible or accurate. Therefore, our goal is to provide experimentalists with a metric that may be monitored to enforce a desired bound on accuracy within a user-defined confidence level. We have defined a spectral reliability index (SRI, based on the output of a direct classical least-squares (DCLS demultiplexing routine, which provides a measure of the reliability of the computed nanoparticle concentrations and ratios. We present simulations and experiments to demonstrate the feasibility of this strategy, which can potentially be utilized for a range of instruments and biomedical applications involving multiplexed SERS nanoparticles.

  19. Model-Independent Evaluation of Tumor Markers and a Logistic-Tree Approach to Diagnostic Decision Support

    Directory of Open Access Journals (Sweden)

    Weizeng Ni

    2014-01-01

    Full Text Available Sensitivity and specificity of using individual tumor markers hardly meet the clinical requirement. This challenge gave rise to many efforts, e.g., combing multiple tumor markers and employing machine learning algorithms. However, results from different studies are often inconsistent, which are partially attributed to the use of different evaluation criteria. Also, the wide use of model-dependent validation leads to high possibility of data overfitting when complex models are used for diagnosis. We propose two model-independent criteria, namely, area under the curve (AUC and Relief to evaluate the diagnostic values of individual and multiple tumor markers, respectively. For diagnostic decision support, we propose the use of logistic-tree which combines decision tree and logistic regression. Application on a colorectal cancer dataset shows that the proposed evaluation criteria produce results that are consistent with current knowledge. Furthermore, the simple and highly interpretable logistic-tree has diagnostic performance that is competitive with other complex models.

  20. Dielectric characterization of PCL-based thermoplastic materials for microwave diagnostic and therapeutic applications.

    Science.gov (United States)

    Aguilar, Suzette M; Shea, Jacob D; Al-Joumayly, Mudar A; Van Veen, Barry D; Behdad, Nader; Hagness, Susan C

    2012-03-01

    We propose the use of a polycaprolactone (PCL)-based thermoplastic mesh as a tissue-immobilization interface for microwave imaging and microwave hyperthermia treatment. An investigation of the dielectric properties of two PCL-based thermoplastic materials in the frequency range of 0.5-3.5 GHz is presented. The frequency-dependent dielectric constant and effective conductivity of the PCL-based thermoplastics are characterized using measurements of microstrip transmission lines fabricated on substrates comprised of the thermoplastic meshes. We also examine the impact of the presence of a PCL-based thermoplastic mesh on microwave breast imaging. We use a numerical test bed comprised of a previously reported 3-D anatomically realistic breast phantom and a multi-frequency microwave inverse scattering algorithm. We demonstrate that the PCL-based thermoplastic material and the assumed biocompatible medium of vegetable oil are sufficiently well matched such that the PCL layer may be neglected by the imaging solution without sacrificing imaging quality. Our results suggest that PCL-based thermoplastics are promising materials as tissue immobilization structures for microwave diagnostic and therapeutic applications.

  1. Diagnostics of a crack in a load coupling of a gas turbine using the machine model and the analysis of the shaft vibrations

    Science.gov (United States)

    Pennacchi, Paolo; Vania, Andrea

    2008-07-01

    The diagnostics of malfunctions that can cause catastrophic failures has to be made in early stage in the industrial environment. Often flexible couplings are employed in industrial rotating machines when gearboxes and heavy thermal gradients are present. The hot and cold alignment of these couplings can be very different. Severe misalignments can generate cracks in the stub shafts, which can propagate in operating condition. Owing to the flexural flexibility of the load coupling, the shaft vibrations may be not noticeably affected by some typical symptoms that usually point out the presence of a crack, like twice per revolution harmonics in the vibration spectrum. Anyhow, suitable diagnostic strategies can detect clear fault symptoms, while model-based methods can confirm the occurrence of the shaft bow induced by the progressive yielding of a load coupling due to a crack. This paper shows as a model-based diagnostic methodology would have allowed a crack in a load coupling of a gas turbine to be identified before a serious failure happened by means of the shaft vibration analysis under operating conditions and rated speed. Finally, the vibrations caused by the shaft bow due to the propagation of a crack in the stub shaft of the coupling have been simulated using suitable equivalent excitations, the magnitude and phase of which have been estimated by means of a model-based identification method.

  2. The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP): Overview and Description of Models, Simulations and Climate Diagnostics

    Science.gov (United States)

    Lamarque, J.-F.; Shindell, D. T.; Naik, V.; Plummer, D.; Josse, B.; Righi, M.; Rumbold, S. T.; Schulz, M.; Skeie, R. B.; Strode, S.; Young, P. J.; Cionni, I.; Dalsoren, S.; Eyring, V.; Bergmann, D.; Cameron-Smith, P.; Collins, W. J.; Doherty, R.; Faluvegi, G.; Folberth, G.; Ghan, S. J.; Horowitz, L. W.; Lee, Y. H.; MacKenzie, I. A.; Nagashima, T.

    2013-01-01

    The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) consists of a series of time slice experiments targeting the long-term changes in atmospheric composition between 1850 and 2100, with the goal of documenting composition changes and the associated radiative forcing. In this overview paper, we introduce the ACCMIP activity, the various simulations performed (with a requested set of 14) and the associated model output. The 16 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 are responsible for a significant range across models, mostly in the case of 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. However, models that are clear outliers are different enough from the other models to significantly affect their simulation of atmospheric chemistry.

  3. 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.

  4. The diagnostic and prognostic role of liquid-based cytology: are we ready to monitor therapy and resistance?

    Science.gov (United States)

    Rossi, Esther Diana; Bizzarro, Tommaso; Longatto-Filho, Adhemar; Gerhard, Rene; Schmitt, Fernando

    2015-01-01

    Here, we evaluate the diagnostic and prognostic role of liquid-based cytology (LBC) in different body lesions, including thyroid, lung, effusions and malignant breast lesions. LBC has gained consensus after being applied to both non-gynecologic and fine-needle aspiration cytology. Although some remain sceptical regarding the diagnostic efficacy of LBC, mainly when used alone, in recent years, good results have been obtained as long as it showed a high diagnostic accuracy. Here, we discuss the additional possibility of storing material for the application of ancillary techniques (immunocytochemistry-molecular analysis) with several diagnostic and prognostic advantages, which may pave the way for the challenging evaluation of both monitoring responses to treatment and resistance to targeted therapies in thyroid, lung, breast carcinoma or malignant effusions. Furthermore, it provides the use of several molecular spots as specific targets for personalized therapy.

  5. 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

  6. 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...

  7. 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.

  8. 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.

  9. Novel peptidoglycan-based diagnostic devices for detection of wound infection.

    Science.gov (United States)

    Hasmann, Andrea; Wehrschuetz-Sigl, Eva; Kanzler, Gertraud; Gewessler, Ulrike; Hulla, Elisabeth; Schneider, Konstantin P; Binder, Barbara; Schintler, Michael; Guebitz, Georg M

    2011-09-01

    Detection of wound infection is based on evaluation of the well-known signs of inflammation like rubor (redness), calor (heat), tumor (swelling), and dolor (pain) by medical doctors and/or time-consuming procedures requiring special machinery. There is currently no rapid diagnostic device available for the indication of wound infection, which would especially be helpful in home care of chronic ulcer patients. In this study, a new concept for a fast diagnostic tool for wound infection based on lysozyme and elastase triggered release of dye from a peptidoglycan matrix was investigated. The matrix consisted of alginate/agarose and peptidoglycan covalently labeled with Remazol brilliant blue. Lysozyme activity in postoperative wounds and decubitus wound fluids was significantly elevated upon infection (4830 ± 1848 U mL(-1)) compared to noninfected wounds (376 ± 240 U mL(-1)). Consequently, incubation of 8% (w/v) labeled agarose/peptidoglycan blend layers with infected wound fluid samples for 2 h at 37 °C resulted in a 4-fold higher amount of dye released than measured for noninfected wounds. For alginate/peptidoglycan beads, a 7-fold higher amount of dye was released in case of infected wound fluid samples compared to noninfected ones. Apart from lysozyme, proteases [i.e., gelatinase matrix metalloproteinase MMP-2 and MMP-9 and elastase] were detected in wound fluids (e.g., using Western blotting). When dosed in ratios typical for wounds, a slight synergistic effect was measured for peptidoglycan hydrolysis (i.e., dye release) between lysozyme and these proteases. Incubation of a double-layer system consisting of stained and nonstained peptidoglycan with infected wound fluids resulted in a color change from yellow to blue, thus allowing simple visual detection of wound infection.

  10. Same-day diagnosis based on histology for women suspected of breast cancer: high diagnostic accuracy and favorable impact on the patient.

    Directory of Open Access Journals (Sweden)

    Maarten W Barentsz

    Full Text Available Same-day diagnosis based on histology is increasingly being offered to patients suspected of breast cancer. We evaluated to which extent same-day diagnosis affected diagnostic accuracy and patients' anxiety levels during the diagnostic phase.All 759 women referred for same-day evaluation of suspicious breast lesions between November 2011-March 2013 were included. Diagnostic accuracy was assessed by linking all patients to the national pathology database to identify diagnostic discrepancies, in which case slides were reviewed. Patients' anxiety was measured in 127 patients by the State Trait and Anxiety Inventory on six moments during the diagnostic workup and changes over time (< = 1 week were analyzed by mixed effect models.Core-needle biopsy was indicated in 374/759 patients (49.3% and in 205/759 (27% patients, invasive or in situ cancer was found. Final diagnosis on the same day was provided for 606/759 (79.8% patients. Overall, 3/759 (0.4% discordant findings were identified. Anxiety levels decreased significantly over time from 45.2 to 30.0 (P = <0.001. Anxiety levels decreased from 44.4 to 25.9 (P = <0.001 for patients with benign disease, and remained unchanged for patients diagnosed with malignancies (48.6 to 46.7, P = 0.933. Time trends in anxiety were not affected by other patient or disease characteristics like age, education level or (family history of breast cancer.Same-day histological diagnosis is feasible in the vast majority of patients, without impairing diagnostic accuracy. Patients' anxiety rapidly decreased in patients with a benign diagnosis and remained constant in patients with malignancy.

  11. 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...

  12. Summary receiver operating characteristics (SROC) and hierarchical SROC models for analysis of diagnostic test evaluations of antibody ELISAs for paratuberculosis.

    Science.gov (United States)

    Toft, Nils; Nielsen, Søren S

    2009-11-15

    Critical, systematic reviews of available diagnostic test evaluations are a meticulous approach to synthesize evidence about a diagnostic test. However, often the review finds that data quality is poor due to deficiencies in design and reporting of the test evaluations and formal statistical comparisons are discouraged. Even when only simple summary measures are appropriate, the strong correlation between sensitivity and specificity and their dependence on differences in diagnostic threshold across studies, creates the need for tools to summarise properties of the diagnostic test under investigation. This study presents summary receiver operating characteristics (SROC) analysis as a means to synthesize information from diagnostic test evaluation studies. Using data from a review of diagnostic tests for ante mortem diagnosis of paratuberculosis as an illustration, SROC and hierarchical SROC (HSROC) analysis were used to estimate overall diagnostic accuracies of antibody ELISAs for bovine paratuberculosis while accounting for covariates: the target condition (infectious or infected) used in the test evaluation (one for the evaluation of Se and one for Sp); and the type of test (serum vs. milk). The methods gave comparable results (regarding the estimated diagnostic log odds ratio), considering the small sample size and the quality of data. The SROC analysis found a difference in the performance of tests when the target condition for evaluation of Se was infected rather than infectious, suggesting that ELISAs are not suitable for detecting infected cattle. However, the SROC model does not take differences in sample size between study units into account, whereas the HSROC allows for both between and within study variation. Considering the small sample size, more credibility should be given to the results of the HSROC. For both methods the area under the (H)SROC curve was calculated and results were comparable. The conclusion is that while the SROC is simpler and easier

  13. Towards a public, standardized, diagnostic benchmarking system for land surface models

    Directory of Open Access Journals (Sweden)

    G. Abramowitz

    2012-02-01

    Full Text Available We examine different conceptions of land surface model benchmarking and illustrate the importance of internationally standardized evaluation experiments that specify data sets, variables, metrics and model resolutions. We additionally show how essential the definition of a priori expectations of model performance can be, based on the complexity of a model and the amount of information being provided to it, and give an example of how these expectations might be quantified. Finally, we introduce the Protocol for the Analysis of Land Surface models (PALS, a free, online land surface model benchmarking application, and show how it is structured to meet both of these goals.

  14. Towards a public, standardized, diagnostic benchmarking system for land surface models

    Directory of Open Access Journals (Sweden)

    G. Abramowitz

    2012-06-01

    Full Text Available This work examines different conceptions of land surface model benchmarking and the importance of internationally standardized evaluation experiments that specify data sets, variables, metrics and model resolutions. It additionally demonstrates how essential the definition of a priori expectations of model performance can be, based on the complexity of a model and the amount of information being provided to it, and gives an example of how these expectations might be quantified. Finally, the Protocol for the Analysis of Land Surface models (PALS is introduced – a free, online land surface model benchmarking application that is structured to meet both of these goals.

  15. Gamma-ray diagnostics of Type Ia supernovae: Predictions of observables from three-dimensional modeling

    CERN Document Server

    Summa, A; Kromer, M; Boyer, S; Roepke, F K; Sim, S A; Seitenzahl, I R; Fink, M; Mannheim, K; Pakmor, R; Ciaraldi-Schoolmann, F; Diehl, R; Maeda, K; Hillebrandt, W

    2013-01-01

    Besides the fact that the gamma-ray emission due to radioactive decays is responsible for powering the light curves of Type Ia supernovae (SNe Ia), gamma rays themselves are of particular interest as a diagnostic tool because they provide a direct way to obtain deeper insights into the nucleosynthesis and the kinematics of these explosion events. Focusing on two of the most broadly discussed SN Ia progenitor scenarios - a delayed detonation in a Chandrasekhar-mass white dwarf (WD) and a violent merger of two WDs - we use three-dimensional explosion models and perform radiative transfer simulations to obtain synthetic gamma-ray spectra. Both chosen models produce the same mass of 56Ni and have similar optical properties that are in reasonable agreement with the recently observed supernova SN 2011fe. In contrast to the optical regime, the gamma-ray emission of our two chosen models proves to be rather different. The almost direct connection of the emission of gamma rays to fundamental physical processes occurin...

  16. Hybrid-structure atomic models for HED laboratory plasma diagnostics and simulations

    Science.gov (United States)

    Hansen, Stephanie

    2010-03-01

    While theoretical atomic physics calculations are well developed for isolated atoms and have been thoroughly benchmarked against low-density laboratory sources such as electron beam ion traps and tokamak plasmas, the high energy density (HED) regime offers significant challenges for atomic physics and spectroscopic modeling. High plasma densities lead to collective effects such as continuum lowering, line broadening, and significant populations in multiply excited atomic states. These effects change the plasma equation of state and the character of emission and absorption spectra and must be accounted for in order to accurately simulate radiative transfer in and apply spectroscopic diagnostics to HED plasmas. Modeling complex mid- and high-Z ions in the HED regime is a particular challenge because exponential growth in accessible configuration space overwhelms the reduction of the Rydberg levels through continuum lowering. This talk will discuss one approach to generating a tractable spectroscopic-quality atomic kinetics model and describe its application to HED laboratory plasmas produced on Sandia's Z facility. [4pt] Sandia is a multi-program laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

  17. The calculation of the circulation in South China Sea by a diagnostic model

    Institute of Scientific and Technical Information of China (English)

    ZHOU Weidong; YANG Yang; DONG Danpeng

    2008-01-01

    A high resolved two - dimensional linear global diagnostic model combining with the dynamical calculation is used to calculate ve- locity field in the South China Sea(SCS). The study of model results shows that eddy diffusion does not change basic structure of circulation in the SCS and does not change the direction of invasive water, but changes the value of transport considerably espe- cially in straits. The velocity field is not changed whether the wind stress is considered or not. This result shows the circulation is largely determined by a density field which well records most of the important contribution of the wind stress effect. Potential vor- ticity is calculated to testify the dynamics of the model results. The result shows that a good conservation of the nonlinear PV. This indicates most effects of the important nonlinear processes are well recorded in density and the nonlinear term is negligible so that the simplified model is reliable. The model results show the water exchanges between the SCS and open ocean or surrounding seas. Cold deep water invades through Luzon Strait and Warm shallow water is pushed out mainly through Karimata Straits. The model results also reveal the structure of the circulation in the SCS basin. In two circulations of upper and middle layers, a cyclon- ic one in the north and an anti-cyclonic one in the south, reflect the climatologic average of the circulation driven by monsoon. In the deep or bottom layer, these two circulations reflect the topography of the basin. Above the middle layer, invasive water enters westward in the north but the way of invasion of Kuroshio is not clear. Below the deep layer, a current goes down south near the east basin , and invasive water enters in the basin from the west Pacific.

  18. DIAGNOSTIC PROFILE IN CHILDREN PRESENTING WITH POOR SCHOLASTIC PERFORMANCE—A CLINIC BASED STUDY

    Directory of Open Access Journals (Sweden)

    Jayaprakash

    2013-02-01

    Full Text Available ABSTRACT: BACKGROUND: Learning is not a unitary process involving teacher and student. It also depends on the relationship and interplay of fami lial, psychological, educational, social and economical atmosphere in and around the child. AIM: The present study was done to formulate a diagnostic profile and compare the co-morbidity sta tus in children presenting with poor scholastic performance in a Child Guidance Clinic s et up. SETTINGS AND DESIGN: A sample of 100 children from the age of 4 years to 12 years at tending the Child Guidance Clinic under the department of Paediatrics in a medical college set u p with history of poor scholastic performance was collected. The study design was case study method. METHODS AND MATERIALS: Detailed psychological analysis was done and diagno sis was made by using the ICD – 10 diagnostic guidelines and multi axial diag nostic system. The study population was divided in to failure (group II and non failure (gr oup I groups based on the repetition of grade and the psychiatric morbidity was compared. STATISTICAL ANALYSIS: Statistical analysis was done by SPSS (Statistical Package for the Social Sc iences and chi square test. RESULTS AND CONCLUSIONS: Psychiatric morbidity was present in 42%, developmen tal disorders in 34%, Non psychiatric medical diagnosis in 25% and abnorma l psychosocial situation in 31% of the sample population. Multiple diagnoses were present in 1 6%. Comparison shows that Prevalence of psychiatric co morbidity was more in the failure group than the non failure group. Scholastic backwardness in children is a complex issue, having various causes. Each child’s problem is unique in nature. So a multi disciplinary interventi on is needed at Paediatric level itself.

  19. 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.

  20. 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

    2016-01-08

    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.

  1. 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.

  2. Self-Diagnostic Model and Modeling Method of Computing System%计算系统自诊断模型与建模方法的研究

    Institute of Scientific and Technical Information of China (English)

    李瑞贤; 朱怡安; 陆伟

    2012-01-01

    Self-Diagnostic technology is a crucial method for improving the reliability, availability and maintainability of a computing system. It aims to make the computing system own the ability of monitoring its states, recognizing and locating the faults without manual operations. Based on the finite state machine model and the fault model, this paper proposes a new Self-Diagnostic model and a method for building this model. The states of the computing system are described via the values resulted from the system key point monitoring units, while the fault types through the fault eigenvectors, and then the associated attributes among diverse fault types are analyzed and the relevant fault model is constructed in order to make the computing system diagnose itself automatically through recognizing and locating the faults. The method and model we proposed is meaningful for improving the reliability and Self- Diagnosticability of a computing system.%自诊断(Self-Diagnostic)技术旨在使计算系统具备在无需人为干涉的情况下监控自身状态、识别并定位故障的能力,是提高计算系统可靠性和可维护性的重要方法;基于有限状态机模型和故障模型,提出了一种新的系统自诊断模型及其建模方法,利用系统关键点检测单元和故障特征向量的方法分别描述系统状态和故障类型,分析不同故障类型间的关联属性并建立相应的故障模型,使得系统能够准确识别自身正/异常状态,对可能出现的故障进行准确识别和定位,在复杂故障环境下同样具备良好的诊断能力;对于提高系统可靠性、建立具备较高自诊断能力的计算系统具有重要意义.

  3. A novel neural-wavelet approach for process diagnostics and complex system modeling

    Science.gov (United States)

    Gao, Rong

    Neural networks have been effective in several engineering applications because of their learning abilities and robustness. However certain shortcomings, such as slow convergence and local minima, are always associated with neural networks, especially neural networks applied to highly nonlinear and non-stationary problems. These problems can be effectively alleviated by integrating a new powerful tool, wavelets, into conventional neural networks. The multi-resolution analysis and feature localization capabilities of the wavelet transform offer neural networks new possibilities for learning. A neural wavelet network approach developed in this thesis enjoys fast convergence rate with little possibility to be caught at a local minimum. It combines the localization properties of wavelets with the learning abilities of neural networks. Two different testbeds are used for testing the efficiency of the new approach. The first is magnetic flowmeter-based process diagnostics: here we extend previous work, which has demonstrated that wavelet groups contain process information, to more general process diagnostics. A loop at Applied Intelligent Systems Lab (AISL) is used for collecting and analyzing data through the neural-wavelet approach. The research is important for thermal-hydraulic processes in nuclear and other engineering fields. The neural-wavelet approach developed is also tested with data from the electric power grid. More specifically, the neural-wavelet approach is used for performing short-term and mid-term prediction of power load demand. In addition, the feasibility of determining the type of load using the proposed neural wavelet approach is also examined. The notion of cross scale product has been developed as an expedient yet reliable discriminator of loads. Theoretical issues involved in the integration of wavelets and neural networks are discussed and future work outlined.

  4. 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...

  5. Structured syncope care pathways based on lean six sigma methodology optimises resource use with shorter time to diagnosis and increased diagnostic yield.

    Directory of Open Access Journals (Sweden)

    Leon Martens

    Full Text Available To conduct a pilot study on the potential to optimise care pathways in syncope/Transient Loss of Consciousness management by using Lean Six Sigma methodology while maintaining compliance with ESC and/or NICE guidelines.Five hospitals in four European countries took part. The Lean Six Sigma methodology consisted of 3 phases: 1 Assessment phase, in which baseline performance was mapped in each centre, processes were evaluated and a new operational model was developed with an improvement plan that included best practices and change management; 2 Improvement phase, in which optimisation pathways and standardised best practice tools and forms were developed and implemented. Staff were trained on new processes and change-management support provided; 3 Sustaining phase, which included support, refinement of tools and metrics. The impact of the implementation of new pathways was evaluated on number of tests performed, diagnostic yield, time to diagnosis and compliance with guidelines. One hospital with focus on geriatric populations was analysed separately from the other four.With the new pathways, there was a 59% reduction in the average time to diagnosis (p = 0.048 and a 75% increase in diagnostic yield (p = 0.007. There was a marked reduction in repetitions of diagnostic tests and improved prioritisation of indicated tests.Applying a structured Lean Six Sigma based methodology to pathways for syncope management has the potential to improve time to diagnosis and diagnostic yield.

  6. A diagnostic evaluation model for complex research partnerships with community engagement: the partnership for Native American Cancer Prevention (NACP) model.

    Science.gov (United States)

    Trotter, Robert T; Laurila, Kelly; Alberts, David; Huenneke, Laura F

    2015-02-01

    Complex community oriented health care prevention and intervention partnerships fail or only partially succeed at alarming rates. In light of the current rapid expansion of critically needed programs targeted at health disparities in minority populations, we have designed and are testing an "logic model plus" evaluation model that combines classic logic model and query based evaluation designs (CDC, NIH, Kellogg Foundation) with advances in community engaged designs derived from industry-university partnership models. These approaches support the application of a "near real time" feedback system (diagnosis and intervention) based on organizational theory, social network theory, and logic model metrics directed at partnership dynamics, combined with logic model metrics.

  7. Validity of diagnostic computer-based air and forehead bone conduction audiometry.

    Science.gov (United States)

    Swanepoel, De Wet; Biagio, Leigh

    2011-04-01

    Computer-based audiometry allows for novel applications, including remote testing and automation, that may improve the accessibility and efficiency of hearing assessment in various clinical and occupational health settings. This study describes the validity of computer-based, diagnostic air and forehead bone conduction audiometry when compared wtih conventional industry standard audiometry in a sound booth environment. A sample of 30 subjects (19 to 77 years of age) was assessed with computer-based (KUDUwave 5000) and industry standard conventional audiometers (GSI 61) to compare air and bone conduction thresholds and test-retest reliability. Air conduction thresholds for the two audiometers corresponded within 5 dB or less in more than 90% of instances, with an average absolute difference of 3.5 dB (3.8 SD) and a 95% confidence interval of 2.6 to 4.5 dB. Bone conduction thresholds for the two audiometers corresponded within 10 dB or less in 92% of instances, with an average absolute difference of 4.9 dB (4.9 SD) and a 95% confidence interval of 3.6 to 6.1 dB. The average absolute test-retest threshold difference for bone conduction on the industry standard audiometer was 5.1 dB (5.3 SD) and for the computer-based audiometer 7.1 dB (6.4 SD). Computer-based audiometry provided air and bone conduction thresholds within the test-retest reliability limits of industry standard audiometry.

  8. 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.

  9. Smart material platforms for miniaturized devices: implications in disease models and diagnostics.

    Science.gov (United States)

    Verma, Ritika; Adhikary, Rishi Rajat; Banerjee, Rinti

    2016-05-24

    Smart materials are responsive to multiple stimuli like light, temperature, pH and redox reactions with specific changes in state. Various functionalities in miniaturised devices can be achieved through the application of "smart materials" that respond to changes in their surroundings. The change in state of the materials in the presence of a stimulus may be used for on demand alteration of flow patterns in devices, acting as microvalves, as scaffolds for cellular aggregation or as modalities for signal amplification. In this review, we discuss the concepts of smart trigger responsive materials and their applications in miniaturized devices both for organ-on-a-chip disease models and for point-of-care diagnostics. The emphasis is on leveraging the smartness of these materials for example, to allow on demand sample actuation, ion dependent spheroid models for cancer or light dependent contractility of muscle films for organ-on-a-chip applications. The review throws light on the current status, scope for technological enhancements, challenges for translation and future prospects of increased incorporation of smart materials as integral parts of miniaturized devices.

  10. Modeling and analysis of breakdown EMI protection for MITICA insulation and embedded diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Pesce, A., E-mail: alberto.pesce@igi.cnr.it [Consorzio RFX – Associazione EURATOM-ENEA sulla Fusione, Corso Stati Uniti 4, 35127 Padova (Italy); Pomaro, N.; Zamengo, A.; Bigi, M.; Toigo, V. [Consorzio RFX – Associazione EURATOM-ENEA sulla Fusione, Corso Stati Uniti 4, 35127 Padova (Italy)

    2013-10-15

    Highlights: ► A fast transient model of MITICA electrical system with all relevant conductors has been developed. ► MITICA insulations on Source and main Bushing are at high risk due to electrical breakdowns. ► The introduction of capacitances in some critical points is effective to reduce overvoltages. ► Signal cables must be screened at both ends to and follow the route of reference potential conductors. -- Abstract: On the Padova PRIMA facility the prototype of the ITER HNBs will be tested in the device called MITICA (Megavolt ITER Injector and Concept Advancement). During Beam operation breakdowns will occur across the accelerator grids and Source components causing transient high voltages between parts normally at low voltages, so stressing the electrical insulation of sensor cables, connectors and feedthroughs. The MITICA electrical model implemented to estimate the characteristics of the voltage transients is here described, with particular emphasis on the feedthroughs, on the source insulation and on the embedded diagnostic system. As severe stresses result with the present design mitigating measures are necessary to avoid damage and maintain proper operation. The solution proposed and supported by the analyses to introduce concentrated capacitances in some critical points turns out to be suitable in terms of electrical effects and of technical compatibility with the main requirements of MITICA environment.

  11. 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.

  12. Infrared Thermography-based Biophotonics: Integrated Diagnostic Technique for Systemic Reaction Monitoring

    Science.gov (United States)

    Vainer, Boris G.; Morozov, Vitaly V.

    A peculiar branch of biophotonics is a measurement, visualisation and quantitative analysis of infrared (IR) radiation emitted from living object surfaces. Focal plane array (FPA)-based IR cameras make it possible to realize in medicine the so called interventional infrared thermal diagnostics. An integrated technique aimed at the advancement of this new approach in biomedical science and practice is described in the paper. The assembled system includes a high-performance short-wave (2.45-3.05 μm) or long-wave (8-14 μm) IR camera, two laser Doppler flowmeters (LDF) and additional equipment and complementary facilities implementing the monitoring of human cardiovascular status. All these means operate synchronously. It is first ascertained the relationship between infrared thermography (IRT) and LDF data in humans in regard to their systemic cardiovascular reactivity. Blood supply real-time dynamics in a narcotized patient is first visualized and quantitatively represented during surgery in order to observe how the general hyperoxia influences thermoregulatory mechanisms; an abrupt increase in temperature of the upper limb is observed using IRT. It is outlined that the IRT-based integrated technique may act as a take-off runway leading to elaboration of informative new methods directly applicable to medicine and biomedical sciences.

  13. 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.

  14. HMM-based Trust Model

    DEFF Research Database (Denmark)

    ElSalamouny, Ehab; Nielsen, Mogens; Sassone, Vladimiro

    2010-01-01

    with their dynamic behaviour. Using Hidden Markov Models (HMMs) for both modelling and approximating the behaviours of principals, we introduce the HMM-based trust model as a new approach to evaluating trust in systems exhibiting dynamic behaviour. This model avoids the fixed behaviour assumption which is considered...... 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....

  15. Model-based Software Engineering

    DEFF Research Database (Denmark)

    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...

  16. 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.

  17. 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.

  18. 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…

  19. Meta-analysis for diagnostic accuracy studies: a new statistical model using beta-binomial distributions and bivariate copulas.

    Science.gov (United States)

    Kuss, Oliver; Hoyer, Annika; Solms, Alexander

    2014-01-15

    There are still challenges when meta-analyzing data from studies on diagnostic accuracy. This is mainly due to the bivariate nature of the response where information on sensitivity and specificity must be summarized while accounting for their correlation within a single trial. In this paper, we propose a new statistical model for the meta-analysis for diagnostic accuracy studies. This model uses beta-binomial distributions for the marginal numbers of true positives and true negatives and links these margins by a bivariate copula distribution. The new model comes with all the features of the current standard model, a bivariate logistic regression model with random effects, but has the additional advantages of a closed likelihood function and a larger flexibility for the correlation structure of sensitivity and specificity. In a simulation study, which compares three copula models and two implementations of the standard model, the Plackett and the Gauss copula do rarely perform worse but frequently better than the standard model. We use an example from a meta-analysis to judge the diagnostic accuracy of telomerase (a urinary tumor marker) for the diagnosis of primary bladder cancer for illustration.

  20. 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.

  1. Element-Based Computational Model

    Directory of Open Access Journals (Sweden)

    Conrad Mueller

    2012-02-01

    Full Text Available A variation on the data-flow model is proposed to use for developing parallel architectures. While the model is a data driven model it has significant differences to the data-flow model. The proposed model has an evaluation cycleof processing elements (encapsulated data that is similar to the instruction cycle of the von Neumann model. The elements contain the information required to process them. The model is inherently parallel. An emulation of the model has been implemented. The objective of this paper is to motivate support for taking the research further. Using matrix multiplication as a case study, the element/data-flow based model is compared with the instruction-based model. This is done using complexity analysis followed by empirical testing to verify this analysis. The positive results are given as motivation for the research to be taken to the next stage - that is, implementing the model using FPGAs.

  2. Curriculum-Based Measurement as a Predictor of Performance on a State Assessment: Diagnostic Efficiency of Local Norms

    Science.gov (United States)

    Sandberg Patton, Karen L.; Reschly, Amy L.; Appleton, James

    2014-01-01

    With the concurrent emphasis on accountability, prevention, and early intervention, curriculum-based measurement of reading (R-CBM) is playing an increasingly important role in the educational process. This study investigated the differences in diagnostic accuracy and utility between commercial norms and local norms when making high-stakes, local…

  3. Effects of Concept Map Extraction and a Test-Based Diagnostic Environment on Learning Achievement and Learners' Perceptions

    Science.gov (United States)

    Lin, Yu-Shih; Chang, Yi-Chun; Liew, Keng-Hou; Chu, Chih-Ping

    2016-01-01

    Computerised testing and diagnostics are critical challenges within an e-learning environment, where the learners can assess their learning performance through tests. However, a test result based on only a single score is insufficient information to provide a full picture of learning performance. In addition, because test results implicitly…

  4. Diagnostics of recombining laser plasma parameters based on He-like ion resonance lines intensity ratios

    Science.gov (United States)

    Ryazantsev, S. N.; Skobelev, I. Yu; Faenov, A. Ya; Pikuz, T. A.; Grum-Grzhimailo, A. N.; Pikuz, S. A.

    2016-11-01

    While the plasma created by powerful laser expands from the target surface it becomes overcooled, i.e. recombining one. Improving of diagnostic methods applicable for such plasma is rather important problem in laboratory astrophysics nowadays because laser produced jets are fully scalable to young stellar objects. Such scaling is possible because of the plasma hydrodynamic equations invariance under some transformations. In this paper it is shown that relative intensities of the resonance transitions in He-like ions can be used to measure the parameters of recombining plasma. Intensity of the spectral lines corresponding to these transitions is sensitive to the density in the range of 1016-1020 cm-3 while the temperature ranges from 10 to 100 eV for ions with nuclear charge Zn ∼ 10. Calculations were carried out for F VIII ion and allowed to determine parameters of plasma jets created by nanosecond laser system ELFIE (Ecole Polytechnique, France) for astrophysical phenomenon modelling. Obtained dependencies are quite universal and can be used for any recombining plasma containing He-like fluorine ions.

  5. A novel antiproton radial diagnostic based on octupole induced ballistic loss

    CERN Document Server

    Andresen, G B; Bowe, P D; Bray, C C; Butler, E; Cesar, C L; Chapman, S; Charlton, M; Fajans, J; Fujiwara, M C; Funakoshi, R; Gill, D R; Hangst, J S; Hardy, W N; Hayano, R S; Hayden, M E; Humphries, A J; Hydomako, R; Jenkins, M J; Jørgensen, L V; Kurchaninov, L; Lambo, R; Madsen, N; Nolan, P; Olchanski, K; Olin, A; Page, R D; Povilus, A; Pusa, P; Robicheaux, F; Sarid, E; Seif El Nasr, S; Silveira, D M; Storey, J W; Thompson, R I; van der Werf, D P; Wurtele, J S; Yamazaki, Y

    2008-01-01

    We report results from a novel diagnostic that probes the outer radial profile of trapped antiproton clouds. The diagnostic allows us to determine the profile by monitoring the time-history of antiproton losses that occur as an octupole field in the antiproton confinement region is increased. We show several examples of how this diagnostic helps us to understand the radial dynamics of antiprotons in normal and nested Penning-Malmberg traps. Better understanding of these dynamics may aid current attempts to trap antihydrogen atoms.

  6. The Correlation-Base-Selection Algorithm for Diagnostic Schizophrenia Based on Blood-Based Gene Expression Signatures

    Science.gov (United States)

    Zhang, Hang; Xie, Ziyang; Yang, Yuwen; Zhao, Yizhen

    2017-01-01

    Microarray analysis of gene expression is often used to diagnose different types of disease. Many studies report remarkable achievements in nervous system disease. Clinical diagnosis of schizophrenia (SCZ) still depends on doctors' experience, which is unreliable and needs to be more objective and quantified. To solve this problem, we collected whole blood gene expression data from four studies, including 152 individuals with schizophrenia (SCZ) and 138 normal controls in different regions. The correlation-based feature selection (CFS, one of the machine learning methods) algorithm was applied in this study, and 103 significantly differentially expressed genes between patients and controls, called “feature genes,” were selected; then, a model for SCZ diagnosis was built. The samples were subdivided into 10 groups, and cross-validation showed that the model we constructed achieved nearly 100% classification accuracy. Mathematical evaluation of the datasets before and after data processing proved the effectiveness of our algorithm. Feature genes were enriched in Parkinson's disease, oxidative phosphorylation, and TGF-beta signaling pathways, which were previously reported to be associated with SCZ. These results suggest that the analysis of gene expression in whole blood by our model could be a useful tool for diagnosing SCZ. PMID:28280741

  7. 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.

  8. Wavefront sensor based diagnostic of FERMI FEL photon beam (Conference Presentation)

    Science.gov (United States)

    Raimondi, Lorenzo; Mahne, Nicola; Manfredda, Michele; Svetina, Cristian; Cocco, Daniele; Capotondi, Flavio; Pedersoli, Emanuele; Kiskinova, Maya; Zangrando, Marco

    2016-09-01

    FERMI is the first seeded EUV-SXR free electron laser (FEL) user facility, and it is operated at Elettra Sincrotrone Trieste. Two of the four already operating beamlines, namely LDM (Low Density Matter) and DiProI (Diffraction and Projection Imaging), use a Kirkpatrick-Baez (K-B) active X-ray optics system for focusing the FEL pulses onto the target under investigation. A wafefront sensor is used as diagnostic for the characterization of the focused spot and for the optimization of the parameters of these active optical systems as well. The aim of this work is, first, to describe in detail the optimization procedure using the wavefront sensor through the minimization of the Zernike coefficients, and second, report on the final results obtained on the K-B optical system at the DiProI endstation. The wavefront sensor, mounted out of focus behind the DiProI chamber, allows to compute the intensity distribution of the FEL beam, typically a mix between several modes resulting in a "noisy hyper-Gaussian" intensity profile, and the wavefront residual from ideal propagation shape and after tilt correction. Combining these two measures we can obtain the electric field of the wave out of focus. Propagating back the electric field we reconstruct the focal spot in far field approximation. In this way the sensor works as a diagnostic reconstructing the focal spot. On the other hand, after modelling the electric field with a Zernike polynomial it is easy and fast to optimize the mirror bending and the optical system angles by minimizing the aberrations, quantified in terms of Zernike coefficients. Since each coefficient corresponds to a single parameter, they can be minimized one at the time. Online wavefront measurements have made possible the optimization of the bending acting on the mirror curvature, and of the (pitch and roll) angle positions of the K-B system. From the wavefront measurements we have inferred a focal spot for DiProI of 5.5 μm x 6.2 μm at 32 nm wavelength

  9. Single Colour Diagnostics of the Mass-to-light Ratio: Predictions from Galaxy Formation Models

    CERN Document Server

    Wilkins, Stephen M; Baugh, Carlton M; Lacey, Cedric G; Zuntz, Joe

    2013-01-01

    Accurate galaxy stellar masses are crucial to better understand the physical mechanisms driving the galaxy formation process. We use synthetic star formation and metal enrichment histories predicted by the {\\sc galform} galaxy formation model to investigate the precision with which various colours $(m_{a}-m_{b})$ can alone be used as diagnostics of the stellar mass-to-light ratio. As an example, we find that, at $z=0$, the {\\em intrinsic} (B$_{f435w}-$V$_{f606w}$) colour can be used to determine the intrinsic rest-frame $V$-band stellar mass-to-light ratio ($\\log_{10}\\Gamma_{V}=\\log_{10}[(M/M_{\\odot})/(L_{V}/L_{V\\odot})]$) with a precision of $\\sigma_{lg\\Gamma}\\simeq 0.06$ when the initial mass function and redshift are known beforehand. While the presence of dust, assuming a universal attenuation curve, can have a systematic effect on the inferred mass-to-light ratio using a single-colour relation, this is typically small as it is often possible to choose a colour for which the dust reddening vector is appro...

  10. 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.

  11. 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.

  12. A highly sensitive and selective diagnostic assay based on virus nanoparticles

    Science.gov (United States)

    Park, Jin-Seung; Cho, Moon Kyu; Lee, Eun Jung; Ahn, Keum-Young; Lee, Kyung Eun; Jung, Jae Hun; Cho, Yunjung; Han, Sung-Sik; Kim, Young Keun; Lee, Jeewon

    2009-04-01

    Early detection of the protein marker troponin I in patients with a higher risk of acute myocardial infarction can reduce the risk of death from heart attacks. Most troponin assays are currently based on the conventional enzyme linked immunosorbent assay and have detection limits in the nano- and picomolar range. Here, we show that by combining viral nanoparticles, which are engineered to have dual affinity for troponin antibodies and nickel, with three-dimensional nanostructures including nickel nanohairs, we can detect troponin levels in human serum samples that are six to seven orders of magnitude lower than those detectable using conventional enzyme linked immunosorbent assays. The viral nanoparticle helps to orient the antibodies for maximum capture of the troponin markers. High densities of antibodies on the surfaces of the nanoparticles and nanohairs lead to greater binding of the troponin markers, which significantly enhances detection sensitivities. The nickel nanohairs are re-useable and can reproducibly differentiate healthy serum from unhealthy ones. We expect other viral nanoparticles to form similar highly sensitive diagnostic assays for a variety of other protein markers.

  13. Opportunities for bead-based multiplex assays in veterinary diagnostic laboratories.

    Science.gov (United States)

    Christopher-Hennings, Jane; Araujo, Karla P C; Souza, Carlos J H; Fang, Ying; Lawson, Steven; Nelson, Eric A; Clement, Travis; Dunn, Michael; Lunney, Joan K

    2013-11-01

    Bead-based multiplex assays (BBMAs) are applicable for high throughput, simultaneous detection of multiple analytes in solution (from several to 50-500 analytes within a single, small sample volume). Currently, few assays are commercially available for veterinary applications, but they are available to identify and measure various cytokines, growth factors and their receptors, inflammatory proteins, kinases and inhibitors, neurobiology proteins, and pathogens and antibodies in human beings, nonhuman primates, and rodent species. In veterinary medicine, various nucleic acid and protein-coupled beads can be used in, or for the development of, antigen and antibody BBMAs, with the advantage that more data can be collected using approximately the same amount of labor as used for other antigen and antibody assays. Veterinary-related BBMAs could be used for detection of pathogens, genotyping, measurement of hormone levels, and in disease surveillance and vaccine assessment. It will be important to evaluate whether BBMAs are "fit for purpose," how costs and efficiencies compare between assays, which assays are published or commercially available for specific veterinary applications, and what procedures are involved in the development of the assays. It is expected that many veterinary-related BBMAs will be published and/or become commercially available in the next few years. The current review summarizes the BBMA technology and some of the currently available BBMAs developed for veterinary settings. Some of the human diagnostic BBMAs are also described, providing an example of possible templates for future development of new veterinary-related BBMAs.

  14. 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.

  15. In vivo endoscopic tissue diagnostics based on spectroscopic absorption, scattering, and phase function properties.

    Science.gov (United States)

    Thueler, Philippe; Charvet, Igor; Bevilacqua, Frederic; St Ghislain, M; Ory, G; Marquet, Pierre; Meda, Paolo; Vermeulen, Ben; Depeursinge, Christian

    2003-07-01

    A fast spectroscopic system for superficial and local determination of the absorption and scattering properties of tissue (480 to 950 nm) is described. The probe can be used in the working channel of an endoscope. The scattering properties include the reduced scattering coefficient and a parameter of the phase function called gamma, which depends on its first two moments. The inverse problem algorithm is based on the fit of absolute reflectance measurements to cubic B-spline functions derived from the interpolation of a set of Monte Carlo simulations. The algorithm's robustness was tested with simulations altered with various amounts of noise. The method was also assessed on tissue phantoms of known optical properties. Finally, clinical measurements performed endoscopically in vivo in the stomach of human subjects are presented. The absorption and scattering properties were found to be significantly different in the antrum and in the fundus and are correlated with histopathologic observations. The method and the instrument show promise for noninvasive tissue diagnostics of various epithelia.

  16. Flux Emergence In The Solar Photosphere - Diagnostics Based On 3-D Rradiation-MHD Simulations

    Science.gov (United States)

    Yelles Chaouche, L.; Cheung, M.; Lagg, A.; Solanki, S.

    2006-08-01

    We investigate flux tube emergence in the solar photosphere using a diagnostic procedure based on analyzing Stokes signals from different spectral lines calculated in 3-D radiation-MHD simulations. The simulations include the effects of radiative transport and partial ionization and cover layers both above and below the solar surface. The simulations consider the emergence of a twisted magnetic flux tube through the solar surface. We consider different stages in the emergence process, starting from the early appearance of the flux tube at the solar surface, and following the emergence process until the emerged flux looks similar to a normal bipolar region. At every stage we compute line profiles by numerically solving the Unno-Rachkovsky equations at every horizontal grid point. Then, following observational practice, we apply Milne-Eddington-type inversions to the synthetic spectra in order to retrieve different atmospheric parameters. We include the influence of spatial smearing on the deduced atmospheric parameters to identify signatures of different stages of flux emergence in the solar photosphere.

  17. Molecular diagnostics for pharmacogenomic testing of fluoropyrimidine based-therapy: costs, methods and applications.

    Science.gov (United States)

    Di Francia, Raffaele; Berretta, Massimiliano; Catapano, Oriana; Canzoniero, Lorella M T; Formisano, Luigi

    2011-07-01

    Abstract Genetic testing of drug response represents an important goal for targeted therapy. In particular, 5-fluorouracil (5-FU) is the backbone of several chemotherapic protocols for treatment of solid tumors. Unfortunately, in some patients, 5-FU is toxic and causes gastrointestinal and hematologic lesions leading to the suspension of therapy. Some adverse drug responses can be predicted by pharmacogenomics. Recently, several polymorphic traits of different genes involved with 5-FU biotransformation have been reported. Many methods have been used for qualitative and quantitative assessment of the mutational status of these genes, without a precise cost-effectiveness analysis. This article reviews recent findings on the seven germline polymorphic traits of four genes involved in the biotransformation of the 5-FU. In particular, we analyze the most common platforms used to identify the specific genetic alterations and their relative costs. Genotyping can be performed either by custom service laboratories or academic reference laboratories by using either the commercial kits (when available) or "in house" tests. By random selection of 20 certified laboratories out of a total of 71, we estimate that the cost of the analysis/single trait is on average €120.00 as custom genotyping service. "In house" validated tests by PCR-based platforms cost approximately €20.00 per single polimorphism. On the basis of this information, the lab manager can evaluate the advantage and limitations, in terms of costs and applicability, of the most appropriate methods for diagnostics of 5-FU pharmacogenomics tests.

  18. Identifying strategy use in category learning tasks: a case for more diagnostic data and models.

    Science.gov (United States)

    Donkin, Chris; Newell, Ben R; Kalish, Mike; Dunn, John C; Nosofsky, Robert M

    2015-07-01

    The strength of conclusions about the adoption of different categorization strategies-and their implications for theories about the cognitive and neural bases of category learning-depend heavily on the techniques for identifying strategy use. We examine performance in an often-used "information-integration" category structure and demonstrate that strategy identification is affected markedly by the range of models under consideration, the type of data collected, and model-selection techniques. We use a set of 27 potential models that represent alternative rule-based and information-integration categorization strategies. Our experimental paradigm includes the presentation of nonreinforced transfer stimuli that improve one's ability to discriminate among the predictions of alternative models. Our model-selection techniques incorporate uncertainty in the identification of individuals as either rule-based or information-integration strategy users. Based on this analysis we identify 48% of participants as unequivocally using an information-integration strategy. However, adopting the standard practice of using a restricted set of models, restricted data, and ignoring the degree of support for a particular strategy, we would typically conclude that 89% of participants used an information-integration strategy. We discuss the implications of potentially erroneous strategy identification for the security of conclusions about the categorization capabilities of various participant and patient groups.

  19. 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.

  20. On-Line Fast Motor Fault Diagnostics Based on Fuzzy Neural Networks

    Institute of Scientific and Technical Information of China (English)

    DONG Mingchui; CHEANG Takson; CHAN Sileong

    2009-01-01

    An on-line method was developed to improve diagnostic accuracy and speed for analyzing run-ning motors on site. On-line pre-measured data was used as the basis for constructing the membership functions used in a fuzzy neural network (FNN) as well as for network training to reduce the effects of vari-ous static factors, such as unbalanced input power and asymmetrical motor alignment, to increase accuracy.The preprocessed data and fuzzy logic were used to find the nonlinear mapping relationships between the data and the conclusions. The FNN was then constructed to carry motor fault diagnostics, which gives fast accurate diagnostics. The on-line fast motor fault diagnostics clearly indicate the fault type, location, and severity in running motors. This approach can also be extended to other applications.

  1. 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.

  2. Review of Physicochemical-Based Diagnostic Techniques for Assessing Insulation Condition in Aged Transformers

    Directory of Open Access Journals (Sweden)

    Janvier Sylvestre N’cho

    2016-05-01

    Full Text Available A power transformer outage has a dramatic financial consequence not only for electric power systems utilities but also for interconnected customers. The service reliability of this important asset largely depends upon the condition of the oil-paper insulation. Therefore, by keeping the qualities of oil-paper insulation system in pristine condition, the maintenance planners can reduce the decline rate of internal faults. Accurate diagnostic methods for analyzing the condition of transformers are therefore essential. Currently, there are various electrical and physicochemical diagnostic techniques available for insulation condition monitoring of power transformers. This paper is aimed at the description, analysis and interpretation of modern physicochemical diagnostics techniques for assessing insulation condition in aged transformers. Since fields and laboratory experiences have shown that transformer oil contains about 70% of diagnostic information, the physicochemical analyses of oil samples can therefore be extremely useful in monitoring the condition of power transformers.

  3. Diagnostic non-invasive model of large risky esophageal varices in cirrhotic hepatitis C virus patients

    Science.gov (United States)

    Elalfy, Hatem; Elsherbiny, Walid; Abdel Rahman, Ashraf; Elhammady, Dina; Shaltout, Shaker Wagih; Elsamanoudy, Ayman Z; El Deek, Bassem

    2016-01-01

    AIM To build a diagnostic non-invasive model for screening of large varices in cirrhotic hepatitis C virus (HCV) patients. METHODS This study was conducted on 124 post-HCV cirrhotic patients presenting to the clinics of the Endemic Medicine Department at Mansoura University Hospital for evaluation before HCV antiviral therapy: 78 were Child A and 46 were Child B (score ≤ 8). Inclusion criteria for patients enrolled in this study was presence of cirrhotic HCV (diagnosed by either biopsy or fulfillment of clinical basis). Exclusion criteria consisted of patients with other etiologies of liver cirrhosis, e.g., hepatitis B virus and patients with high MELD score on transplant list. All patients were subjected to full medical record, full basic investigations, endoscopy, and computed tomography (CT), and then divided into groups with no varices, small varices, or large risky varices. In addition, values of Fibrosis-4 score (FIB-4), aminotransferase-to-platelet ratio index (APRI), and platelet count/splenic diameter ratio (PC/SD) were also calculated. RESULTS Detection of large varies is a multi-factorial process, affected by many variables. Choosing binary logistic regression, dependent factors were either large or small varices while independent factors included CT variables such coronary vein diameter, portal vein (PV) diameter, lieno-renal shunt and other laboratory non-invasive variables namely FIB-4, APRI, and platelet count/splenic diameter. Receiver operating characteristic (ROC) curve was plotted to determine the accuracy of non-invasive parameters for predicting the presence of large esophageal varices and the area under the ROC curve for each one of these parameters was obtained. A model was established and the best model for prediction of large risky esophageal varices used both PC/SD and PV diameter (75% accuracy), while the logistic model equation was shown to be (PV diameter × -0.256) plus (PC/SD × -0.006) plus (8.155). Values nearing 2 or more denote

  4. Diagnostic Air Quality Model Evaluation of Source-Specific Primary and Secondary Fine Particulate Carbon

    Science.gov (United States)

    Ambient measurements of 78 source-specific tracers of primary and secondary carbonaceous fine particulate matter collected at four midwestern United States locations over a full year (March 2004–February 2005) provided an unprecedented opportunity to diagnostically evaluate...

  5. Static Digital Telepathology: A Model for Diagnostic and Educational Support to Pathologists in the Developing World

    Directory of Open Access Journals (Sweden)

    Aliyah R. Sohani

    2012-01-01

    Full Text Available Background: The practice of pathology in the developing world presents challenges in terms of limited resources, shortages of trained personnel, and lack of continuing education programs. Telepathology holds promise as a means of diagnostic and educational support.

  6. Cyclones and extreme windstorm events over Europe under climate change: Global and regional climate model diagnostics

    Science.gov (United States)

    Leckebusch, G. C.; Ulbrich, U.

    2003-04-01

    More than any changes of the climate system mean state conditions, the development of extreme events may influence social, economic and legal aspects of our society. This linkage results from the impact of extreme climate events (natural hazards) on environmental systems which again are directly linked to human activities. Prominent examples from the recent past are the record breaking rainfall amounts of August 2002 in central Europe which produced widespread floodings or the wind storm Lothar of December 1999. Within the MICE (Modelling the Impact of Climate Extremes) project framework an assessment of the impact of changes in extremes will be done. The investigation is carried out for several different impact categories as agriculture, energy use and property damage. Focus is laid on the diagnostics of GCM and RCM simulations under different climate change scenarios. In this study we concentrate on extreme windstorms and their relationship to cyclone activity in the global HADCM3 as well as in the regional HADRM3 model under two climate change scenarios (SRESA2a, B2a). In order to identify cyclones we used an objective algorithm from Murry and Simmonds which was widely tested under several different conditions. A slight increase in the occurrence of systems is identified above northern parts of central Europe for both scenarios. For more severe systems (core pressure wind events can be defined via different percentile values of the windspeed (e.g. above the 95 percentile). By this means the relationship between strong wind events and cyclones is also investigated. For several regions (e.g. Germany, France, Spain) a shift to more deep cyclones connected with an increasing number of strong wind events is found.

  7. 胸腔积液肿瘤标志物的PCA和OPLS-DA模型对肺癌的诊断价值研究%Diagnostic value of tumor markers in pleural effusion for patients with lung cancer based on PCA and OPLS-DA models

    Institute of Scientific and Technical Information of China (English)

    周志强; 田刚

    2016-01-01

    Objective To evaluate the combined diagnostic values of CEA ,Cyfra21‐1 ,NSE ,SCC and Pro‐GRP for patients with lung cancer .Methods Totally 127 cases with lung cancer were selected in the hospital from Feb .2014 to Mar .2016 ,which were di‐vided as lung cancer group .And 154 patients with benign pleural effusion were selected as control group .Concentrations of CEA , Cyfra21‐1 ,NSE ,SCC and Pro‐GRP in pleural effusion were measured by the electrochemiluminescence and chemiluminescence as‐says .The methods of principal component analysis (PCA) and orthogonal partial least squares‐discriminant analysis (OPLS‐DA) were used for evaluation the diagnostic performances of five tumor markers in pleural effusion for patients with lung cancer .Results Concentrations of CEA ,Cyfra21‐1 ,NSE ,SCC and Pro‐GRP in pleural effusion in the lung cancer group were significantly higher than that in the control group (P< 0 .01) .PCA model revealed that there was different metabolic profiling between lung cancer group and control group ,showing a tendency of discrimination .The lung cancer and other benign lung diseases were effectively dis‐criminated by the OPLS‐DA model with 88 .6% (124/140) of sensitivity ,90 .9% (140/154) of specificity and 89 .8% (264/294) of accuracy ,respectively .Conclusion Based on tumor markers of CEA ,Cyfra21‐1 ,NSE ,SCC and Pro‐GRP in pleural effusion ,the PCA and OPLS‐DA models are helpful for the diagnosis of lung cancer .%目的:探讨联合检测胸腔积液中癌胚抗原(CEA)、细胞角蛋白19片段(Cyfra21‐1)、神经元特异性烯醇化酶(NSE)、鳞状细胞癌抗原(SCC)和胃泌素释放肽前体(Pro‐GRP)对肺癌的诊断价值。方法选择西南医科大学附属医院2014年2月至2016年3月127例肺癌患者为肺癌组,随机选择154例良性胸腔积液患者为对照组。采用电化学发光法和化学发光法测定胸腔积液中CEA、Cyfra21‐1、NSE和SCC和Pro‐GRP

  8. 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...

  9. Model-based consensus

    NARCIS (Netherlands)

    Boumans, Marcel

    2014-01-01

    The aim of the rational-consensus method is to produce “rational consensus”, that is, “mathematical aggregation”, by weighing the performance of each expert on the basis of his or her knowledge and ability to judge relevant uncertainties. The measurement of the performance of the experts is based on

  10. Model-based consensus

    NARCIS (Netherlands)

    M. Boumans

    2014-01-01

    The aim of the rational-consensus method is to produce "rational consensus", that is, "mathematical aggregation", by weighing the performance of each expert on the basis of his or her knowledge and ability to judge relevant uncertainties. The measurement of the performance of the experts is based on

  11. 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

  12. 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.

  13. Diagnostic accuracy of culture-based and PCR-based detection tests for methicillin-resistant Staphylococcus aureus : a meta-analysis

    NARCIS (Netherlands)

    Luteijn, J. M.; Hubben, G. A. A.; Pechlivanoglou, P.; Bonten, M. J.; Postma, M. J.

    2011-01-01

    P>A systematic review and meta-analysis were performed to determine and compare the sensitivity and specificity of PCR-based and culture-based diagnostic tests for methicillin-resistant Staphylococcus aureus (MRSA). Our analysis included 74 accuracy measurements from 29 publications. Nine tests were

  14. Diagnostic Accuracy of Methylated SEPT9 for Blood-based Colorectal Cancer Detection: A Systematic Review and Meta-Analysis

    Science.gov (United States)

    Nian, Jiayun; Sun, Xu; Ming, SuYang; Yan, Chen; Ma, Yunfei; Feng, Ying; Yang, Lin; Yu, Mingwei; Zhang, Ganlin; Wang, Xiaomin

    2017-01-01

    Objectives: More convenient and effective blood-based methods are believed to increase colorectal cancer (CRC) detection adoption. The effectiveness of methylated SPET9 for CRC detection has been reviewed in the newly published recommendation statement by US Preventive Services Task Force (USPSTF), while detailed instructions were not provided, which may be a result of insufficient evidence. Therefore, more evidence is needed to assist practitioners to thoroughly understand the utilization of this special maker. Methods: Based on the standard method, a systematic review and meta-analysis was performed. Quadas-2 was used to assess the methodological quality of studies. Relevant studies were searched and screened from PubMed, Embase and other literature databases up to June 1, 2016. Pooled sensitivity, specificity and diagnostic odds ratio were summarized by bivariate mixed effect model and area under the curve (AUC) was estimated by hierarchical summary receiver operator characteristic curve. Results: 25 studies were included for analysis. The pooled sensitivity, specificity and AUC were 0.71, 0.92 and 0.88, respectively. Among the various methods and assays, Epipro Colon 2.0 with 2/3 algorithm was the most effective in colorectal cancer detection. Positive ratio of mSEPT9 was higher in advanced CRC (45% in I, 70% in II, 76% in III, 79% in IV) and lower differentiation (31% in high, 73% in moderate, 90% in low) tissue. However, this marker has poor ability of identifying precancerous lesions according to current evidence. Conclusions: mSEPT9 is a reliable blood-based marker in CRC detection, particularly advanced CRC. Epipro Colon 2.0 with 2/3 algorithm is currently the optimal method and assay to detect CRC. PMID:28102859

  15. Event-Based Conceptual Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    The paper demonstrates that a wide variety of event-based modeling approaches are based on special cases of the same general event concept, and that the general event concept can be used to unify the otherwise unrelated fields of information modeling and process modeling. A set of event......-based modeling approaches are analyzed and the results are used to formulate a general event concept that can be used for unifying the seemingly unrelated event concepts. Events are characterized as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms...... of information structures. The general event concept can be used to guide systems analysis and design and to improve modeling approaches....

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

    DEFF Research Database (Denmark)

    Sera, Dezso

    it was possible to achieve relatively good accuracy. The main advantage of the method is that it relies on already determined parameters (Rsm, Vt) based on measurements, therefore reducing the errors introduced by the limitation of the single-exponential model especially at low irradiation conditions......., which is therefore not affected by the environmental fluctuations. The method has been implemented based on the Perturb and Observe (P&O), and the experimental results demonstrate that it preserves the advantages of the existing tracker in being highly efficient during stable conditions, having a simple...... behaviour of PV panels is given, followed by the parameter determination for the five-parameter single-exponential model based on datasheet values, which has been used for the implementation of a PV simulator taking in account the shape, size ant intensity of partial shadow in respect to bypass diodes...

  17. 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.

  18. Backreflection diagnostics for ultra-intense laser plasma experiments based on frequency resolved optical gating

    Science.gov (United States)

    Wagner, F.; Hornung, J.; Schmidt, C.; Eckhardt, M.; Roth, M.; Stöhlker, T.; Bagnoud, V.

    2017-02-01

    We report on the development and implementation of a time resolved backscatter diagnostics for high power laser plasma experiments at the petawatt-class laser facility PHELIX. Pulses that are backscattered or reflected from overcritical plasmas are characterized spectrally and temporally resolved using a specially designed second harmonic generation frequency resolved optical gating system. The diagnostics meets the requirements made by typical experiments, i.e., a spectral bandwidth of more than 30 nm with sub-nanometer resolution and a temporal window of 10 ps with 50 fs temporal resolution. The diagnostics is permanently installed at the PHELIX target area and can be used to study effects such as laser-hole boring or relativistic self-phase-modulation which are important features of laser-driven particle acceleration experiments.

  19. 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

  20. Empirically Based, Agent-based models

    Directory of Open Access Journals (Sweden)

    Elinor Ostrom

    2006-12-01

    Full Text Available There is an increasing drive to combine agent-based models with empirical methods. An overview is provided of the various empirical methods that are used for different kinds of questions. Four categories of empirical approaches are identified in which agent-based models have been empirically tested: case studies, stylized facts, role-playing games, and laboratory experiments. We discuss how these different types of empirical studies can be combined. The various ways empirical techniques are used illustrate the main challenges of contemporary social sciences: (1 how to develop models that are generalizable and still applicable in specific cases, and (2 how to scale up the processes of interactions of a few agents to interactions among many agents.

  1. 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 high-fidelity...

  2. Constraint Based Modeling Going Multicellular.

    Science.gov (United States)

    Martins Conde, Patricia do Rosario; Sauter, Thomas; Pfau, Thomas

    2016-01-01

    Constraint based modeling has seen applications in many microorganisms. For example, there are now established methods to determine potential genetic modifications and external interventions to increase the efficiency of microbial strains in chemical production pipelines. In addition, multiple models of multicellular organisms have been created including plants and humans. While initially the focus here was on modeling individual cell types of the multicellular organism, this focus recently started to switch. Models of microbial communities, as well as multi-tissue models of higher organisms have been constructed. These models thereby can include different parts of a plant, like root, stem, or different tissue types in the same organ. Such models can elucidate details of the interplay between symbiotic organisms, as well as the concerted efforts of multiple tissues and can be applied to analyse the effects of drugs or mutations on a more systemic level. In this review we give an overview of the recent development of multi-tissue models using constraint based techniques and the methods employed when investigating these models. We further highlight advances in combining constraint based models with dynamic and regulatory information and give an overview of these types of hybrid or multi-level approaches.

  3. Diagnostics of induction motor based on spectral analysis of stator current signal with application of fuzzy classifier

    OpenAIRE

    2010-01-01

    New implementation of diagnostics of imminent failure conditions of induction motor was presented. Software to recognize the current ofinduction motor was implemented. System of current recognition is based on a study of the frequency spectrum of stator current signal.Fuzzy classifier was applied. The studies were carried out for four imminent failure conditions of induction motor. The results confirm thatthe system can be useful for detecting damage and protect the engines.

  4. Analytical Redundancy Design for Aeroengine Sensor Fault Diagnostics Based on SROS-ELM

    OpenAIRE

    Jun Zhou; Yuan Liu; Tianhong Zhang

    2016-01-01

    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 measurement...

  5. Event-Based Conceptual Modeling

    DEFF Research Database (Denmark)

    Bækgaard, Lars

    2009-01-01

    The purpose of the paper is to obtain insight into and provide practical advice for event-based conceptual modeling. We analyze a set of event concepts and use the results to formulate a conceptual event model that is used to identify guidelines for creation of dynamic process models and static...... information models. We characterize events as short-duration processes that have participants, consequences, and properties, and that may be modeled in terms of information structures. The conceptual event model is used to characterize a variety of event concepts and it is used to illustrate how events can...... be used to integrate dynamic modeling of processes and static modeling of information structures. The results are unique in the sense that no other general event concept has been used to unify a similar broad variety of seemingly incompatible event concepts. The general event concept can be used...

  6. 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.

  7. 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 activit...

  8. A Needs-Based Approach to the Development of a Diagnostic College English Speaking Test

    Science.gov (United States)

    Zhao, Zhongbao

    2014-01-01

    This paper investigated the current situation of oral English teaching, learning, and assessment at the tertiary level in China through needs analysis and explored the implications for the development of a diagnostic speaking test. Through random sampling, the researcher administered both a student questionnaire and a teacher questionnaire to over…

  9. 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

  10. 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

  11. 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

  12. A Strategy to Help Teachers Make a Difference: A Diagnostic-Prescriptive Teaching Model

    Science.gov (United States)

    Peterson, Lee T.; McBrayer, John

    1976-01-01

    The authors discuss the development of a diagnostic-prescriptive teaching and learning program in the Youngstown public school system; give background material; describe organizational form and implementation; and conclude with a series of "points to ponder" for educators contemplating a similar venture. (MB)

  13. 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

  14. Diagnostic modeling of dimethylsulfide production in coastal water west of the Antarctic Peninsula

    Science.gov (United States)

    Hermann, Maria; Najjar, Raymond G.; Neeley, Aimee R.; Vila-Costa, Maria; Dacey, John W. H.; DiTullio, Giacomo, R.; Kieber, David J.; Kiene, Ronald P.; Matrai, Patricia A.; Simo, Rafel; Vernet, Maria

    2012-01-01

    The rate of gross biological dimethylsulfide (DMS) production at two coastal sites west of the Antarctic Peninsula, off Anvers Island, near Palmer Station, was estimated using a diagnostic approach that combined field measurements from 1 January 2006 through 1 March 2006 and a one-dimensional physical model of ocean mixing. The average DMS production rate in the upper water column (0-60 m) was estimated to be 3.1 +/- 0.6 nM/d at station B (closer to shore) and 2.7 +/- 0.6 nM/d1 at station E (further from shore). The estimated DMS replacement time was on the order of 1 d at both stations. DMS production was greater in the mixed layer than it was below the mixed layer. The average DMS production normalized to chlorophyll was 0.5 +/- nM/d)/(mg cubic m) at station B and 0.7 +/- 0.2 (nM/d)/(mg/cubic m3) at station E. When the diagnosed production rates were normalized to the observed concentrations of total dimethylsulfoniopropionate (DMSPt, the biogenic precursor of DMS), we found a remarkable similarity between our estimates at stations B and E (0.06 +/- 0.02 and 0.04 +/- 0.01 (nM DMS / d1)/(nM DMSP), respectively) and the results obtained in a previous study from a contrasting biogeochemical environment in the North Atlantic subtropical gyre (0.047 =/- 0.006 and 0.087 +/- 0.014 (nM DMS d1)/(nM DMSP) in a cyclonic and anticyclonic eddy, respectively).We propose that gross biological DMS production normalized to DMSPt might be relatively independent of the biogeochemical environment, and place our average estimate at 0.06 +/- 0.01 (nM DMS / d)/(nM DMSPt). The significance of this finding is that it can provide a means to use DMSPt measurements to extrapolate gross biological DMS production, which is extremely difficult to measure experimentally under realistic in situ conditions.

  15. Towards literature-based feature selection for diagnostic classification: A meta-analysis of resting-state fMRI in depression

    Directory of Open Access Journals (Sweden)

    Benedikt eSundermann

    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

  16. OMIP contribution to CMIP6: experimental and diagnostic protocol for the physical component of the Ocean Model Intercomparison Project

    Science.gov (United States)

    Griffies, Stephen M.; Danabasoglu, Gokhan; Durack, Paul J.; Adcroft, Alistair J.; Balaji, V.; Böning, Claus W.; Chassignet, Eric P.; Curchitser, Enrique; Deshayes, Julie; Drange, Helge; Fox-Kemper, Baylor; Gleckler, Peter J.; Gregory, Jonathan M.; Haak, Helmuth; Hallberg, Robert W.; Heimbach, Patrick; Hewitt, Helene T.; Holland, David M.; Ilyina, Tatiana; Jungclaus, Johann H.; Komuro, Yoshiki; Krasting, John P.; Large, William G.; Marsland, Simon J.; Masina, Simona; McDougall, Trevor J.; Nurser, A. J. George; Orr, James C.; Pirani, Anna; Qiao, Fangli; Stouffer, Ronald J.; Taylor, Karl E.; Treguier, Anne Marie; Tsujino, Hiroyuki; Uotila, Petteri; Valdivieso, Maria; Wang, Qiang; Winton, Michael; Yeager, Stephen G.

    2016-09-01

    The Ocean Model Intercomparison Project (OMIP) is an endorsed project in the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses CMIP6 science questions, investigating the origins and consequences of systematic model biases. It does so by providing a framework for evaluating (including assessment of systematic biases), understanding, and improving ocean, sea-ice, tracer, and biogeochemical components of climate and earth system models contributing to CMIP6. Among the WCRP Grand Challenges in climate science (GCs), OMIP primarily contributes to the regional sea level change and near-term (climate/decadal) prediction GCs.OMIP provides (a) an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing; and (b) a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) detailing methods for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II (Interannual Forcing) have become the standard methods to evaluate global ocean/sea-ice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP, HighResMIP (High Resolution MIP), as well as the ocean/sea-ice OMIP simulations.

  17. 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.

  18. Gaseous electron multiplier-based soft x-ray plasma diagnostics development: Preliminary tests at ASDEX Upgrade

    Science.gov (United States)

    Chernyshova, M.; Malinowski, K.; Czarski, T.; Wojeński, A.; Vezinet, D.; Poźniak, K. T.; Kasprowicz, G.; Mazon, D.; Jardin, A.; Herrmann, A.; Kowalska-Strzeciwilk, E.; Krawczyk, R.; Kolasiński, P.; Zabołotny, W.; Zienkiewicz, P.

    2016-11-01

    A Gaseous Electron Multiplier (GEM)-based detector is being developed for soft X-ray diagnostics on tokamaks. Its main goal is to facilitate transport studies of impurities like tungsten. Such studies are very relevant to ITER, where the excessive accumulation of impurities in the plasma core should be avoided. This contribution provides details of the preliminary tests at ASDEX Upgrade (AUG) with a focus on the most important aspects for detector operation in harsh radiation environment. It was shown that both spatially and spectrally resolved data could be collected, in a reasonable agreement with other AUG diagnostics. Contributions to the GEM signal include also hard X-rays, gammas, and neutrons. First simulations of the effect of high-energy photons have helped understanding these contributions.

  19. 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...... for 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...

  20. Multifunctional quantum dots-based cancer diagnostics and stem cell therapeutics for regenerative medicine.

    Science.gov (United States)

    Onoshima, Daisuke; Yukawa, Hiroshi; Baba, Yoshinobu

    2015-12-01

    A field of recent diagnostics and therapeutics has been advanced with quantum dots (QDs). QDs have developed into new formats of biomolecular sensing to push the limits of detection in biology and medicine. QDs can be also utilized as bio-probes or labels for biological imaging of living cells and tissues. More recently, QDs has been demonstrated to construct a multifunctional nanoplatform, where the QDs serve not only as an imaging agent, but also a nanoscaffold for diagnostic and therapeutic modalities. This review highlights the promising applications of multi-functionalized QDs as advanced nanosensors for diagnosing cancer and as innovative fluorescence probes for in vitro or in vivo stem cell imaging in regenerative medicine.

  1. Thrombocytosis: Diagnostic Evaluation, Thrombotic Risk Stratification, and Risk-Based Management Strategies

    Directory of Open Access Journals (Sweden)

    Jonathan S. Bleeker

    2011-01-01

    Full Text Available Thrombocytosis is a commonly encountered clinical scenario, with a large proportion of cases discovered incidentally. The differential diagnosis for thrombocytosis is broad and the diagnostic process can be challenging. Thrombocytosis can be spurious, attributed to a reactive process or due to clonal disorder. This distinction is important as it carries implications for evaluation, prognosis, and treatment. Clonal thrombocytosis associated with the myeloproliferative neoplasms, especially essential thrombocythemia and polycythemia vera, carries a unique prognostic profile, with a markedly increased risk of thrombosis. This risk is the driving factor behind treatment strategies in these disorders. Clinical trials utilizing targeted therapies in thrombocytosis are ongoing with new therapeutic targets waiting to be explored. This paper will outline the mechanisms underlying thrombocytosis, the diagnostic evaluation of thrombocytosis, complications of thrombocytosis with a special focus on thrombotic risk as well as treatment options for clonal processes leading to thrombocytosis, including essential thrombocythemia and polycythemia vera.

  2. 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.

  3. 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.

  4. A clinical diagnostic model for predicting influenza among young adult military personnel with febrile respiratory illness in Singapore.

    Directory of Open Access Journals (Sweden)

    Vernon J Lee

    Full Text Available INTRODUCTION: Influenza infections present with wide-ranging clinical features. We aim to compare the differences in presentation between influenza and non-influenza cases among those with febrile respiratory illness (FRI to determine predictors of influenza infection. METHODS: Personnel with FRI (defined as fever ≥ 37.5 °C, with cough or sore throat were recruited from the sentinel surveillance system in the Singapore military. Nasal washes were collected, and tested using the Resplex II and additional PCR assays for etiological determination. Interviewer-administered questionnaires collected information on patient demographics and clinical features. Univariate comparison of the various parameters was conducted, with statistically significant parameters entered into a multivariate logistic regression model. The final multivariate model for influenza versus non-influenza cases was used to build a predictive probability clinical diagnostic model. RESULTS: 821 out of 2858 subjects recruited from 11 May 2009 to 25 Jun 2010 had influenza, of which 434 (52.9% had 2009 influenza A (H1N1, 58 (7.1% seasonal influenza A (H3N2 and 269 (32.8% influenza B. Influenza-positive cases were significantly more likely to present with running nose, chills and rigors, ocular symptoms and higher temperature, and less likely with sore throat, photophobia, injected pharynx, and nausea/vomiting. Our clinical diagnostic model had a sensitivity of 65% (95% CI: 58%, 72%, specificity of 69% (95% CI: 62%, 75%, and overall accuracy of 68% (95% CI: 64%, 71%, performing significantly better than conventional influenza-like illness (ILI criteria. CONCLUSIONS: Use of a clinical diagnostic model may help predict influenza better than the conventional ILI definition among young adults with FRI.

  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. Improving diagnostic accuracy using agent-based distributed data mining system.

    Science.gov (United States)

    Sridhar, S

    2013-09-01

    The use of data mining techniques to improve the diagnostic system accuracy is investigated in this paper. The data mining algorithms aim to discover patterns and extract useful knowledge from facts recorded in databases. Generally, the expert systems are constructed for automating diagnostic procedures. The learning component uses the data mining algorithms to extract the expert system rules from the database automatically. Learning algorithms can assist the clinicians in extracting knowledge automatically. As the number and variety of data sources is dramatically increasing, another way to acquire knowledge from databases is to apply various data mining algorithms that extract knowledge from data. As data sets are inherently distributed, the distributed system uses agents to transport the trained classifiers and uses meta learning to combine the knowledge. Commonsense reasoning is also used in association with distributed data mining to obtain better results. Combining human expert knowledge and data mining knowledge improves the performance of the diagnostic system. This work suggests a framework of combining the human knowledge and knowledge gained by better data mining algorithms on a renal and gallstone data set.

  7. 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.

  8. NGS-based transcriptome profiling reveals biomarkers for companion diagnostics of the TGF-β receptor blocker galunisertib in HCC.

    Science.gov (United States)

    Cao, Yuan; Agarwal, Rahul; Dituri, Francesco; Lupo, Luigi; Trerotoli, Paolo; Mancarella, Serena; Winter, Peter; Giannelli, Gianluigi

    2017-02-23

    Transforming growth factor-beta (TGF-β) signaling has gained extensive interest in hepatocellular carcinoma (HCC). The small molecule kinase inhibitor galunisertib, targeting the TGF-β receptor I (TGF-βRI), blocks HCC progression in preclinical models and shows promising effects in ongoing clinical trials. As the drug is not similarly effective in all patients, this study was aimed at identifying new companion diagnostics biomarkers for patient stratification. Next-generation sequencing-based massive analysis of cDNA ends was used to investigate the transcriptome of an invasive HCC cell line responses to TGF-β1 and galunisertib. These identified mRNA were validated in 78 frozen HCC samples and in 26 ex-vivo HCC tissues treated in culture with galunisertib. Respective protein levels in patients blood were measured by enzyme-linked immunosorbent assay. SKIL, PMEPA1 ANGPTL4, SNAI1, Il11 and c4orf26 were strongly upregulated by TGF-β1 and downregulated by galunisertib in different HCC cell lines. In the 78 HCC samples, only SKIL and PMEPA1 (P<0.001) were correlated with endogenous TGF-β1. In ex-vivo samples, SKIL and PMEPA1 were strongly downregulated (P<0.001), and correlated (P<0.001) with endogenous TGF-β1. SKIL and PMEPA1 mRNA expression in tumor tissues was significantly increased compared with controls and not correlated with protein levels in the blood of paired HCC patients. SKIL and PMEPA1 mRNA levels were positively correlated with TGF-β1 mRNA concentrations in HCC tissues and strongly downregulated by galunisertib. The target genes identified here may serve as biomarkers for the stratification of HCC patients undergoing treatment with galunisertib.

  9. A novel serum metabolomics-based diagnostic approach for colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Shin Nishiumi

    Full Text Available BACKGROUND: To improve the quality of life of colorectal cancer patients, it is important to establish new screening methods for early diagnosis of colorectal cancer. METHODOLOGY/PRINCIPAL FINDINGS: We performed serum metabolome analysis using gas-chromatography/mass-spectrometry (GC/MS. First, the accuracy of our GC/MS-based serum metabolomic analytical method was evaluated by calculating the RSD% values of serum levels of various metabolites. Second, the intra-day (morning, daytime, and night and inter-day (among 3 days variances of serum metabolite levels were examined. Then, serum metabolite levels were compared between colorectal cancer patients (N = 60; N = 12 for each stage from 0 to 4 and age- and sex-matched healthy volunteers (N = 60 as a training set. The metabolites whose levels displayed significant changes were subjected to multiple logistic regression analysis using the stepwise variable selection method, and a colorectal cancer prediction model was established. The prediction model was composed of 2-hydroxybutyrate, aspartic acid, kynurenine, and cystamine, and its AUC, sensitivity, specificity, and accuracy were 0.9097, 85.0%, 85.0%, and 85.0%, respectively, according to the training set data. In contrast, the sensitivity, specificity, and accuracy of CEA were 35.0%, 96.7%, and 65.8%, respectively, and those of CA19-9 were 16.7%, 100%, and 58.3%, respectively. The validity of the prediction model was confirmed using colorectal cancer patients (N = 59 and healthy volunteers (N = 63 as a validation set. At the validation set, the sensitivity, specificity, and accuracy of the prediction model were 83.1%, 81.0%, and 82.0%, respectively, and these values were almost the same as those obtained with the training set. In addition, the model displayed high sensitivity for detecting stage 0-2 colorectal cancer (82.8%. CONCLUSIONS/SIGNIFICANCE: Our prediction model established via GC/MS-based serum metabolomic analysis

  10. Agent Based Multiviews Requirements Model

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Based on the current researches of viewpoints oriented requirements engineering and intelligent agent, we present the concept of viewpoint agent and its abstract model based on a meta-language for multiviews requirements engineering. It provided a basis for consistency checking and integration of different viewpoint requirements, at the same time, these checking and integration works can automatically realized in virtue of intelligent agent's autonomy, proactiveness and social ability. Finally, we introduce the practical application of the model by the case study of data flow diagram.

  11. Continuum and line modeling of disks around young stars II. Line diagnostics for GASPS from the DENT grid

    CERN Document Server

    Kamp, I; Pinte, C; Tilling, I; Thi, W -F; Menard, F; Duchene, G; Augereau, J -C

    2011-01-01

    Aims. We want to understand the chemistry and physics of disks on the basis of a large unbiased and statistically relevant grid of disk models. One of the main goals is to explore the diagnostic power of various gas emission lines and line ratios for deriving main disk parameters such as the gas mass. Methods. We explore the results of the DENT grid (Disk Evolution with Neat Theory) that consists of 300 000 disk models with 11 free parameters. Through a statistical analysis, we search for correlations and trends in an effort to find tools for disk diagnostic. Results. All calculated quantities like species masses, temperatures, continuum and line fluxes differ by several orders of magnitude across the entire parameter space. The broad distribution of these quantities as a function of input parameters shows the limitation of using a prototype T Tauri or Herbig Ae/Be disk model. The statistical analysis of the DENT grid shows that CO gas is rarely the dominant carbon reservoir in disks. Models with large inner ...

  12. Evidence Based Medicine; Positive and Negative Likelihood Ratios of Diagnostic Tests

    Directory of Open Access Journals (Sweden)

    Alireza Baratloo

    2015-10-01

    Full Text Available In the previous two parts of educational manuscript series in Emergency, we explained some screening characteristics of diagnostic tests including accuracy, sensitivity, specificity, and positive and negative predictive values. In the 3rd  part we aimed to explain positive and negative likelihood ratio (LR as one of the most reliable performance measures of a diagnostic test. To better understand this characteristic of a test, it is first necessary to fully understand the concept of sensitivity and specificity. So we strongly advise you to review the 1st part of this series again. In short, the likelihood ratios are about the percentage of people with and without a disease but having the same test result. The prevalence of a disease can directly influence screening characteristics of a diagnostic test, especially its sensitivity and specificity. Trying to eliminate this effect, LR was developed. Pre-test probability of a disease multiplied by positive or negative LR can estimate post-test probability. Therefore, LR is the most important characteristic of a test to rule out or rule in a diagnosis. A positive likelihood ratio > 1 means higher probability of the disease to be present in a patient with a positive test. The further from 1, either higher or lower, the stronger the evidence to rule in or rule out the disease, respectively. It is obvious that tests with LR close to one are less practical. On the other hand, LR further from one will have more value for application in medicine. Usually tests with 0.1 < LR > 10 are considered suitable for implication in routine practice.

  13. Diagnostics of Electron Beams Based on Cherenkov Radiation in an Optical Fiber

    Science.gov (United States)

    Vukolov, A. V.; Novokshonov, A. I.; Potylitsyn, A. P.; Uglov, S. R.

    2017-02-01

    The use of an optical fiber in which Cherenkov radiation is generated instead of a metal wire for scanning a beam profile allows a compact and noise-proof device for diagnostics of charged particle beams in a wide energy range to be developed. Results of experimental investigation of the yield of Vavilov-Cherenkov radiation generated in optical fibers with thickness in the range from 0.125 to 1 mm by electrons with energy of 5.7 MeV are presented.

  14. Control of Multibunch Longitudinal Instabilities and Beam Diagnostics Using a DSP-based Feedback System

    Energy Technology Data Exchange (ETDEWEB)

    Teytelman, Dmitry

    2000-03-30

    A bunch-by-bunch longitudinal feedback system has been designed and built to control coupled-bunch instabilities in the PEP-II machine. A prototype system has been installed at the Advanced Light Source at LBNL. Programmable DSPs allow longitudinal feedback processing in conjunction with data acquisition or instrumentation algorithms. Here the authors describe techniques developed for different beam and system diagnostics, such as measurements of the modal growth and damping rates and measurements of the bunch-by-bunch currents. Results from the Advanced Light Source are presented to illustrate these techniques.

  15. A contactless microwave-based diagnostic tool for high repetition rate laser systems

    CERN Document Server

    Braggio, C

    2014-01-01

    We report on a novel electro-optic device for the diagnostics of high repetition rate laser systems. It is composed of a microwave receiver and of a second order nonlinear crystal, whose irradiation with a train of short laser pulses produces a time-dependent polarization in the crystal itself as a consequence of optical rectification. This process gives rise to the emission of microwave radiation that is detected by a receiver and is analyzed to infer the repetition rate and intensity of the pulses. We believe that this new method may overcome some of the limitations of photodetection techniques.

  16. Model-Based Security Testing

    CERN Document Server

    Schieferdecker, Ina; Schneider, Martin; 10.4204/EPTCS.80.1

    2012-01-01

    Security testing aims at validating software system requirements related to security properties like confidentiality, integrity, authentication, authorization, availability, and non-repudiation. Although security testing techniques are available for many years, there has been little approaches that allow for specification of test cases at a higher level of abstraction, for enabling guidance on test identification and specification as well as for automated test generation. Model-based security testing (MBST) is a relatively new field and especially dedicated to the systematic and efficient specification and documentation of security test objectives, security test cases and test suites, as well as to their automated or semi-automated generation. In particular, the combination of security modelling and test generation approaches is still a challenge in research and of high interest for industrial applications. MBST includes e.g. security functional testing, model-based fuzzing, risk- and threat-oriented testing,...

  17. A Memory-Based Model of Posttraumatic Stress Disorder: Evaluating Basic Assumptions Underlying the PTSD Diagnosis

    Science.gov (United States)

    Rubin, David C.; Berntsen, Dorthe; Bohni, Malene Klindt

    2008-01-01

    In the mnemonic model of posttraumatic stress disorder (PTSD), the current memory of a negative event, not the event itself, determines symptoms. The model is an alternative to the current event-based etiology of PTSD represented in the "Diagnostic and Statistical Manual of Mental Disorders" (4th ed., text rev.; American Psychiatric Association,…

  18. A new interferometry-based electron density fluctuation diagnostic on Alcator C-Moda)

    Science.gov (United States)

    Kasten, C. P.; Irby, J. H.; Murray, R.; White, A. E.; Pace, D. C.

    2012-10-01

    The two-color interferometry diagnostic on the Alcator C-Mod tokamak has been upgraded to measure fluctuations in the electron density and density gradient for turbulence and transport studies. Diagnostic features and capabilities are described. In differential mode, fast phase demodulation electronics detect the relative phase change between ten adjacent, radially-separated (ΔR = 1.2 cm, adjustable), vertical-viewing chords, which allows for measurement of the line-integrated electron density gradient. The system can be configured to detect the absolute phase shift of each chord by comparison to a local oscillator, measuring the line-integrated density. Each chord is sensitive to density fluctuations with kR < 20.3 cm-1 and is digitized at up to 10 MS/s, resolving aspects of ion temperature gradient-driven modes and other long-wavelength turbulence. Data from C-Mod discharges is presented, including observations of the quasi-coherent mode in enhanced D-alpha H-mode plasmas and the weakly coherent mode in I-mode.

  19. Diagnostic value of antithyroid peroxidase antibody for incidental autoimmune thyroiditis based on histopathologic results.

    Science.gov (United States)

    Rho, Myung Ho; Kim, Dong Wook; Hong, Hyun Pyo; Park, Young Mi; Kwon, Min Jeong; Jung, Soo Jin; Kim, Young Wook; Kang, Taewoo

    2012-12-01

    Detection of antithyroid peroxidase antibody (TPOAb) is widely used in the diagnosis of autoimmune thyroiditis (AIT), but no research has evaluated the diagnostic accuracy of TPOAb detection using histopathologic reference standards. To fill this research gap, this study assessed the diagnostic accuracy of detection of TPOAb and that of other serological markers in asymptomatic patients who had been diagnosed with AIT by histopathologic analysis after thyroid surgery. After review of patient records, 598 patients who had undergone thyroid nodule surgery were enrolled for examination for thyroid parenchyma by a pathologist and classification into no co-existing lymphocytic thyroiditis, Hashimoto thyroiditis, or non-Hashimoto type of lymphocytic thyroiditis (NHLT). The correlation between patient serological data and thyroid parenchyma pathology was analyzed. Statistically significant differences (P lymphocytic thyroiditis and no co-existing lymphocytic thyroiditis groups regarding thyroid-stimulating hormone (TSH) and TPOAb levels. And, TPOAb titer was significantly associated with the degree of inflammation. An abnormal TPOAb titer was found in 86 of the 598 patients (14.4 %) and the specificity of TPOAb detection for AIT diagnosis was found to be 96.9 %. The prevalence of Hashimoto thyroiditis and NHLT in the 560 papillary thyroid cancer (PTC) patients was found to be 7.9 and 17.9 %, respectively. The results indicate that TPOAb titer is associated with the degree of thyroid inflammation and that detection of TPOAb is a very specific means of diagnosing AIT. The results also indicate that the incidence of AIT and PTC coexistence is relatively high.

  20. PCA3 and PCA3-Based Nomograms Improve Diagnostic Accuracy in Patients Undergoing First Prostate Biopsy

    Directory of Open Access Journals (Sweden)

    Virginie Vlaeminck-Guillem

    2013-08-01

    Full Text Available 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. The PCA3 test was performed before ≥12-core initial prostate biopsy, along with standard risk factor assessment. Diagnostic performance of the PCA3 test was evaluated. The three available nomograms (Hansen’s and Chun’s nomograms, as well as the updated Prostate Cancer Prevention Trial risk calculator; PCPT were applied to the cohort, and their predictive accuracies were assessed in terms of biopsy outcome: the presence of any prostate cancer (PCa and high-grade prostate cancer (HGPCa. The PCA3 score provided significant predictive accuracy. While the PCPT risk calculator appeared less accurate; both Chun’s and Hansen’s nomograms provided good calibration and high net benefit on decision curve analyses. When applying nomogram-derived PCa probability thresholds ≤30%, ≤6% of HGPCa would have been missed, while avoiding up to 48% of unnecessary biopsies. The urinary PCA3 test and PCA3-incorporating nomograms can be considered as reliable tools to aid in the initial biopsy decision.

  1. Modeling and Diagnostics of Fuel Cell Porous Media for Improving Water Transport

    Energy Technology Data Exchange (ETDEWEB)

    Allen, Jeff; M' edici, Ezequiel

    2011-07-01

    When a fuel cell is operating at high current density, water accumulation is a significant cause of performance and component degradation. Investigating the water transport inside the fuel cell is a challenging task due to opacity of the components, the randomness of the porous materials, and the difficulty in gain access to the interior for measurement due to the small dimensions of components. Numerical simulation can provide a good insight of the evolution of the water transport under different working condition. However, the validation of those simulations is remains an issue due the same experimental obstacles associated with in-situ measurements. The discussion herein will focus on pore-network modeling of the water transport on the PTL and the insights gained from simulations as well as in the validation technique. The implications of a recently published criterion to characterize PTL, based on percolation theory, and validate numerical simulation are discussed.

  2. A meta-analysis of the diagnostic accuracy of dengue virus-specific IgA antibody-based tests for detection of dengue infection.

    Science.gov (United States)

    Alagarasu, K; Walimbe, A M; Jadhav, S M; Deoshatwar, A R

    2016-03-01

    Immunoglobulin A (IgA)-based tests have been evaluated in different studies for their utility in diagnosing dengue infections. In most of the studies, the results were inconclusive because of a small sample size. Hence, a meta-analysis involving nine studies with 2096 samples was performed to assess the diagnostic accuracy of IgA-based tests in diagnosing dengue infections. The analysis was conducted using Meta-Disc software. The results revealed that IgA-based tests had an overall sensitivity, specificity, diagnostic odds ratio, and positive and negative likelihood ratios of 73·9%, 95·2%, 66·7, 22·0 and 0·25, respectively. Significant heterogeneity was observed between the studies. The type of test, infection status and day of sample collection influenced the diagnostic accuracy. The IgA-based diagnostic tests showed a greater accuracy when the samples were collected 4 days after onset of symptoms and for secondary infections. The results suggested that IgA-based tests had a moderate level of accuracy and are diagnostic of the disease. However, negative results cannot be used alone for dengue diagnosis. More prospective studies comparing the diagnostic accuracy of combinations of antigen-based tests with either IgA or IgM are needed and might be useful for suggesting the best strategy for dengue diagnosis.

  3. Evaluating Frequency, Diagnostic Quality, and Cost of Lyme Borreliosis Testing in Germany: A Retrospective Model Analysis

    Directory of Open Access Journals (Sweden)

    I. Müller

    2012-01-01

    Full Text Available Background. Data on the economic impact of Lyme borreliosis (LB on European health care systems is scarce. This project focused on the epidemiology and costs for laboratory testing in LB patients in Germany. Materials and Methods. We performed a sentinel analysis of epidemiological and medicoeconomic data for 2007 and 2008. Data was provided by a German statutory health insurance (DAK company covering approx. 6.04 million members. In addition, the quality of diagnostic testing for LB in Germany was studied. Results. In 2007 and 2008, the incident diagnosis LB was coded on average for 15,742 out of 6.04 million insured members (0.26%. 20,986 EIAs and 12,558 immunoblots were ordered annually for these patients. For all insured members in the outpatient sector, a total of 174,820 EIAs and 52,280 immunoblots were reimbursed annually to health care providers (cost: 2,600,850€. For Germany, the overall expected cost is estimated at 51,215,105€. However, proficiency testing data questioned test quality and standardization of diagnostic assays used. Conclusion. Findings from this study suggest ongoing issues related to care for LB and may help to improve future LB disease management.

  4. Development of Fault Models for Hybrid Fault Detection and Diagnostics Algorithm: October 1, 2014 -- May 5, 2015

    Energy Technology Data Exchange (ETDEWEB)

    Cheung, Howard; Braun, James E.

    2015-12-31

    This report describes models of building faults created for OpenStudio to support the ongoing development of fault detection and diagnostic (FDD) algorithms at the National Renewable Energy Laboratory. Building faults are operating abnormalities that degrade building performance, such as using more energy than normal operation, failing to maintain building temperatures according to the thermostat set points, etc. Models of building faults in OpenStudio can be used to estimate fault impacts on building performance and to develop and evaluate FDD algorithms. The aim of the project is to develop fault models of typical heating, ventilating and air conditioning (HVAC) equipment in the United States, and the fault models in this report are grouped as control faults, sensor faults, packaged and split air conditioner faults, water-cooled chiller faults, and other uncategorized faults. The control fault models simulate impacts of inappropriate thermostat control schemes such as an incorrect thermostat set point in unoccupied hours and manual changes of thermostat set point due to extreme outside temperature. Sensor fault models focus on the modeling of sensor biases including economizer relative humidity sensor bias, supply air temperature sensor bias, and water circuit temperature sensor bias. Packaged and split air conditioner fault models simulate refrigerant undercharging, condenser fouling, condenser fan motor efficiency degradation, non-condensable entrainment in refrigerant, and liquid line restriction. Other fault models that are uncategorized include duct fouling, excessive infiltration into the building, and blower and pump motor degradation.

  5. Integrated diagnostic technique for nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Gofuku, Akio [Graduate School of Natural Science and Technology, Okayama University, Okayama (Japan)

    2014-12-15

    It is very important to detect and identify small anomalies and component failures for the safe operation of complex and large-scale artifacts such as nuclear power plants. Each diagnostic technique has its own advantages and limitations. These facts inspire us not only to enhance the capability of diagnostic techniques but also to integrate the results of diagnostic subsystems in order to obtain more accurate diagnostic results. The article describes the outline of four diagnostic techniques developed for the condition monitoring of the fast breeder reactor 'Monju'. The techniques are (1) estimation technique of important state variables based on a physical model of the component, (2) a state identification technique by non-linear discrimination function applying SVM (Support Vector Machine), (3) a diagnostic technique applying WT (Wavelet Transformation) to detect changes in the characteristics of measurement signals, and (4) a state identification technique effectively using past cases. In addition, a hybrid diagnostic system in which a final diagnostic result is given by integrating the results from subsystems is introduced, where two sets of values called confidence values and trust values are used. A technique to determine the trust value is investigated under the condition that the confidence value is determined by each subsystem.

  6. Diagnostic Value of Liquid-Based Cytology in Urothelial Carcinoma Diagnosis: A Systematic Review and Meta-Analysis.

    Directory of Open Access Journals (Sweden)

    You Luo

    Full Text Available To evaluate the value of liquid-based cytology (LBC in the diagnosis of urothelial carcinoma.Diagnostic studies were searched for the diagnostic value of LBC in urothelial carcinoma in PubMed, Embase, Cochrane Library, Web of Science, CBM and CNKI. The latest retrieval date was September 2014. The data were extracted and the quality of the included studies was independently assessed by 2 reviewers. Stata 13 software was used to perform the statistical analysis. The research was conducted in compliance with the PRISMA statement.Nineteen studies, which included 8293 patients, were evaluated. The results of the meta-analysis showed that the pooled sensitivity and specificity of LBC were 0.58 (0.51-0.65 and 0.96 (0.93-0.98, respectively. The diagnostic odds ratio (DOR was 31 (18-56 and the area under the curve (AUC of summary receiver operating characteristic (SROC was 0.83 (0.80-0.86. The post-test probability was 80% when a positive diagnosis was made. Compared with high grade urothelial carcinoma (HGUC, the sensitivity of detecting low-grade urothelial carcinoma (LGUC was significantly lower, risk ratio of sensitivity was 0.54 (0.43-0.66, P<0.001. However, no significant sensitivity improvement was observed with LBC when compared with traditional cytospin cytology, risk ratio was 1.03 (0.94-1.14, P = 0.524.Despite LBC having a pooled 58% positive rate for urothelial carcinoma diagnosis in our meta-analysis, no significant improvement in sensitivity was observed based on the studies evaluated. Further research is needed to validate these findings.

  7. Evolvable Smartphone-Based Point-of-Care Systems For In-Vitro Diagnostics

    DEFF Research Database (Denmark)

    Patou, François

    -to-consumer applications remain scarce. This thesis addresses this limitation. After identifying system evolvability as a key enabler to the adoption and long-lasting success of next-generation point-of-care systems by favoring the integration of new technologies, streamlining the reengineering efforts for system upgrades...... architecture at initial design-time. Important considerations arise as to where in Lab-on-Chip/smart-device platforms can these mechanisms be integrated, and how to implement them. Our investigation revolves around the silicon-nanowire biological field effect transistor, a promising biosensing technology...... enablers for the decentralization of many in-vitro medical diagnostics applications to the point-of-care, supporting the advent of a preventive and personalized medicine. Although the technical feasibility and the potential of Lab-on-Chip/smart-device systems is repeatedly demonstrated, direct...

  8. A fully automated in vitro diagnostic system based on magnetic tunnel junction arrays and superparamagnetic particles

    Science.gov (United States)

    Lian, Jie; Chen, Si; Qiu, Yuqin; Zhang, Suohui; Shi, Stone; Gao, Yunhua

    2012-04-01

    A fully automated in vitro diagnostic (IVD) system for diagnosing acute myocardial infarction was developed using high sensitivity MTJ array as sensors and nano-magnetic particles as tags. On the chip is an array of 12 × 106 MTJ devices integrated onto a 3 metal layer CMOS circuit. The array is divided into 48 detection areas, therefore 48 different types of bio targets can be analyzed simultaneously if needed. The chip is assembled with a micro-fluidic cartridge which contains all the reagents necessary for completing the assaying process. Integrated with electrical, mechanical and micro-fluidic pumping devices and with the reaction protocol programed in a microprocessor, the system only requires a simple one-step analyte application procedure to operate and yields results of the three major AMI bio-markers (cTnI, MYO, CK-MB) in 15 mins.

  9. Diagnostics of DC and Induction Motors Based on the Analysis of Acoustic Signals

    Science.gov (United States)

    Glowacz, A.

    2014-10-01

    In this paper, a non-invasive method of early fault diagnostics of electric motors was proposed. This method uses acoustic signals generated by electric motors. Essential features were extracted from acoustic signals of motors. A plan of study of acoustic signals of electric motors was proposed. Researches were carried out for faultless induction motor, induction motor with one faulty rotor bar, induction motor with two faulty rotor bars and flawless Direct Current, and Direct Current motor with shorted rotor coils. Researches were carried out for methods of signal processing: log area ratio coefficients, Multiple signal classification, Nearest Neighbor classifier and the Bayes classifier. A pattern creation process was carried out using 40 samples of sound. In the identification process 130 five-second test samples were used. The proposed approach will also reduce the costs of maintenance and the number of faulty motors in the industry.

  10. Diagnostic cerebrospinal fluid biomarkers for Parkinson's disease: a pathogenetically based approach.

    Science.gov (United States)

    van Dijk, Karin D; Teunissen, Charlotte E; Drukarch, Benjamin; Jimenez, Connie R; Groenewegen, Henk J; Berendse, Henk W; van de Berg, Wilma D J

    2010-09-01

    The inaccuracy of the early diagnosis of Parkinson's disease (PD) has been a major incentive for studies aimed at the identification of biomarkers. Brain-derived cerebrospinal fluid (CSF) proteins are potential biomarkers considering the major role that proteins play in PD pathogenesis. In this review, we discuss the current hypotheses about the pathogenesis of PD and identify the most promising candidate biomarkers among the CSF proteins studied so far. The list of potential markers includes proteins involved in various pathogenetic processes, such as oxidative stress and protein aggregation. This list will undoubtedly grow in the near future by application of CSF proteomics and subsequent validation of identified proteins. Probably a single biomarker will not suffice to reach high sensitivity and specificity, because PD is pathogenetically heterogeneous and shares etiological factors with other neurodegenerative diseases. Furthermore, identified candidate biomarkers will have to be thoroughly validated before they can be implemented as diagnostic aids.

  11. [Bases for the formation of an ultrasound diagnostic image of orbital tissue].

    Science.gov (United States)

    Kharlap, S I; Vashkulatova, E A; Safonova, T N; Skvortsova, N V

    2010-01-01

    The paper touches upon the specific features of the structure of orbital formations, by considering their anatomic topography and biophysical properties. By studying the results of investigations of the morphological and biophysical studies of orbital tissues, the authors analyze their features and compare their relationships. These results unraveling each of the considered orbital anatomic elements from the acoustic profile ranges may be useful in understanding the nature of clinical changes, which will be able to interpret these or those diagnostic signs--guides and to trace their evolution. In addition, this approach can help interpret the texture of an ultrasound digital image of eye socket soft tissue and permit one to look at pathological clinical manifestations from the so-called biophysical essence. This will allow additional information to be gleaned, by analyzing the usual signs.

  12. Molecular diagnostic for boll weevil (Coleoptera: Curculionidae) based on amplification of three species-specific microsatellites.

    Science.gov (United States)

    Kim, Kyung Seok; Szendrei, Zsofia; Rodriguez-Saona, Cesar; Mulder, Phillip G; Sappington, Thomas W

    2009-04-01

    The boll weevil, Anthonomus grandis grandis Boheman (Coleoptera: Curculionidae), is a serious pest of cultivated cotton, Gossypium hirsutum L., in the Americas, and reinfestation of zones from which they have been eradicated is of perpetual concern. Extensive arrays of pheromone traps monitor for reintroductions, but occasionally the traps collect nontarget weevils that can be misidentified by scouts. For example, the congeneric pepper weevil, Anthonomus eugenii Cano, and other superficially similar weevils are attracted to components of the boll weevil lure or trap color. Although morphologically distinguishable by trained personnel, the potential for misidentification is compounded when captured weevils are dismembered or partially consumed by ants or ground beetles that sometimes feed on them in the traps. Because misidentification can have expensive consequences, a molecular diagnostic tool would be of great value to eradication managers. We demonstrate that a cocktail of three primer pairs in a single polymerase chain reaction (PCR) amplify species-specific microsatellites that unambiguously distinguish the boll weevil from three other weevil species tested, including pepper weevil; cranberry weevil, Anthonomus eugenii musculus Say; and pecan weevil, Curculio caryae Horn. However, it does not distinguish the boll weevil from the subspecific "thurberia" weevil. A universal internal transcribed spacer primer pair included in the cocktail cross-amplifies DNA from all species, serving as a positive control. Furthermore, the diagnostic primers amplified the target microsatellites from various boll weevil adult body parts, indicating that the PCR technology using the primer cocktail is sensitive enough to positively identify a boll weevil even when the body is partly degraded.

  13. 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.

  14. Attachment insecurities, maladaptive perfectionism, and eating disorder symptoms: a latent mediated and moderated structural equation modeling analysis across diagnostic groups.

    Science.gov (United States)

    Dakanalis, Antonios; Timko, C Alix; Zanetti, M Assunta; Rinaldi, Lucio; Prunas, Antonio; Carrà, Giuseppe; Riva, Giuseppe; Clerici, Massimo

    2014-01-30

    Although 96-100% of individuals with eating disorders (EDs) report insecure attachment, the specific mechanisms by which adult insecure attachment dimensions affect ED symptomatology remain to date largely unknown. This study examined maladaptive perfectionism as both a mediator and a moderator of the relationship between insecure attachment (anxiety and avoidance) and ED symptomatology in a clinical, treatment seeking, sample. Insecure anxious and avoidant attachment, maladaptive perfectionism, and ED symptomatology were assessed in 403 participants from three medium size specialized care centres for EDs in Italy. Structural equation modeling indicated that maladaptive perfectionism served as mediator between both insecure attachment patterns and ED symptomatology. It also interacted with insecure attachment to predict higher levels of ED symptoms - highlighting the importance of both insecure attachment patterns and maladaptive aspects of perfectionism as treatment targets. Multiple-group comparison analysis did not reveal differences across diagnostic groups (AN, BN, EDNOS) in mediating, main and interaction effects of perfectionism. These findings are consistent with recent discussions on the classification and treatment of EDs that have highlighted similarities between ED diagnostic groups and could be viewed through the lens of the Trans-theoretical Model of EDs. Implications for future research and intervention are discussed.

  15. Capturing natural-colour 3D models of insects for species discovery and diagnostics.

    Directory of Open Access Journals (Sweden)

    Chuong V Nguyen

    Full Text Available Collections of biological specimens are fundamental to scientific understanding and characterization of natural diversity-past, present and future. This paper presents a system for liberating useful information from physical collections by bringing specimens into the digital domain so they can be more readily shared, analyzed, annotated and compared. It focuses on insects and is strongly motivated by the desire to accelerate and augment current practices in insect taxonomy which predominantly use text, 2D diagrams and images to describe and characterize species. While these traditional kinds of descriptions are informative and useful, they cannot cover insect specimens "from all angles" and precious specimens are still exchanged between researchers and collections for this reason. Furthermore, insects can be complex in structure and pose many challenges to computer vision systems. We present a new prototype for a practical, cost-effective system of off-the-shelf components to acquire natural-colour 3D models of insects from around 3 mm to 30 mm in length. ("Natural-colour" is used to contrast with "false-colour", i.e., colour generated from, or applied to, gray-scale data post-acquisition. Colour images are captured from different angles and focal depths using a digital single lens reflex (DSLR camera rig and two-axis turntable. These 2D images are processed into 3D reconstructions using software based on a visual hull algorithm. The resulting models are compact (around 10 megabytes, afford excellent optical resolution, and can be readily embedded into documents and web pages, as well as viewed on mobile devices. The system is portable, safe, relatively affordable, and complements the sort of volumetric data that can be acquired by computed tomography. This system provides a new way to augment the description and documentation of insect species holotypes, reducing the need to handle or ship specimens. It opens up new opportunities to collect

  16. Capturing natural-colour 3D models of insects for species discovery and diagnostics.

    Science.gov (United States)

    Nguyen, Chuong V; Lovell, David R; Adcock, Matt; La Salle, John

    2014-01-01

    Collections of biological specimens are fundamental to scientific understanding and characterization of natural diversity-past, present and future. This paper presents a system for liberating useful information from physical collections by bringing specimens into the digital domain so they can be more readily shared, analyzed, annotated and compared. It focuses on insects and is strongly motivated by the desire to accelerate and augment current practices in insect taxonomy which predominantly use text, 2D diagrams and images to describe and characterize species. While these traditional kinds of descriptions are informative and useful, they cannot cover insect specimens "from all angles" and precious specimens are still exchanged between researchers and collections for this reason. Furthermore, insects can be complex in structure and pose many challenges to computer vision systems. We present a new prototype for a practical, cost-effective system of off-the-shelf components to acquire natural-colour 3D models of insects from around 3 mm to 30 mm in length. ("Natural-colour" is used to contrast with "false-colour", i.e., colour generated from, or applied to, gray-scale data post-acquisition.) Colour images are captured from different angles and focal depths using a digital single lens reflex (DSLR) camera rig and two-axis turntable. These 2D images are processed into 3D reconstructions using software based on a visual hull algorithm. The resulting models are compact (around 10 megabytes), afford excellent optical resolution, and can be readily embedded into documents and web pages, as well as viewed on mobile devices. The system is portable, safe, relatively affordable, and complements the sort of volumetric data that can be acquired by computed tomography. This system provides a new way to augment the description and documentation of insect species holotypes, reducing the need to handle or ship specimens. It opens up new opportunities to collect data for research

  17. Model-Based Security Testing

    Directory of Open Access Journals (Sweden)

    Ina Schieferdecker

    2012-02-01

    Full Text Available Security testing aims at validating software system requirements related to security properties like confidentiality, integrity, authentication, authorization, availability, and non-repudiation. Although security testing techniques are available for many years, there has been little approaches that allow for specification of test cases at a higher level of abstraction, for enabling guidance on test identification and specification as well as for automated test generation. Model-based security testing (MBST is a relatively new field and especially dedicated to the systematic and efficient specification and documentation of security test objectives, security test cases and test suites, as well as to their automated or semi-automated generation. In particular, the combination of security modelling and test generation approaches is still a challenge in research and of high interest for industrial applications. MBST includes e.g. security functional testing, model-based fuzzing, risk- and threat-oriented testing, and the usage of security test patterns. This paper provides a survey on MBST techniques and the related models as well as samples of new methods and tools that are under development in the European ITEA2-project DIAMONDS.

  18. Development of an epitope conservancy analysis tool to facilitate the design of epitope-based diagnostics and vaccines

    Directory of Open Access Journals (Sweden)

    Fusseder Nicolas

    2007-09-01

    Full Text Available Abstract Background In an epitope-based vaccine setting, the use of conserved epitopes would be expected to provide broader protection across multiple strains, or even species, than epitopes derived from highly variable genome regions. Conversely, in a diagnostic and disease monitoring setting, epitopes that are specific to a given pathogen strain, for example, can be used to monitor responses to that particular infectious strain. In both cases, concrete information pertaining to the degree of conservancy of the epitope(s considered is crucial. Results To assist in the selection of epitopes with the desired degree of conservation, we have developed a new tool to determine the variability of epitopes within a given set of protein sequences. The tool was implemented as a component of the Immune Epitope Database and Analysis Resources (IEDB, and is directly accessible at http://tools.immuneepitope.org/tools/conservancy. Conclusion An epitope conservancy analysis tool was developed to analyze the variability or conservation of epitopes. The tool is user friendly, and is expected to aid in the design of epitope-based vaccines and diagnostics.

  19. A Framework to Debug Diagnostic Matrices

    Science.gov (United States)

    Kodal, Anuradha; Robinson, Peter; Patterson-Hine, Ann

    2013-01-01

    Diagnostics is an important concept in system health and monitoring of space operations. Many of the existing diagnostic algorithms utilize system knowledge in the form of diagnostic matrix (D-matrix, also popularly known as diagnostic dictionary, fault signature matrix or reachability matrix) gleaned from physical models. But, sometimes, this may not be coherent to obtain high diagnostic performance. In such a case, it is important to modify this D-matrix based on knowledge obtained from other sources such as time-series data stream (simulated or maintenance data) within the context of a framework that includes the diagnostic/inference algorithm. A systematic and sequential update procedure, diagnostic modeling evaluator (DME) is proposed to modify D-matrix and wrapper logic considering least expensive solution first. This iterative procedure includes conditions ranging from modifying 0s and 1s in the matrix, or adding/removing the rows (failure sources) columns (tests). We will experiment this framework on datasets from DX challenge 2009.

  20. Retrofitting Non-Cognitive-Diagnostic Reading Assessment under the Generalized DINA Model Framework

    Science.gov (United States)

    Chen, Huilin; Chen, Jinsong

    2016-01-01

    Cognitive diagnosis models (CDMs) are psychometric models developed mainly to assess examinees' specific strengths and weaknesses in a set of skills or attributes within a domain. By adopting the Generalized-DINA model framework, the recently developed general modeling framework, we attempted to retrofit the PISA reading assessments, a…