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Sample records for based diagnostic model

  1. Divergence-based tests for model diagnostic

    Czech Academy of Sciences Publication Activity Database

    Hobza, Tomáš; Esteban, M. D.; Morales, D.; Marhuenda, Y.

    2008-01-01

    Roč. 78, č. 13 (2008), s. 1702-1710 ISSN 0167-7152 R&D Projects: GA MŠk 1M0572 Grant - others:Instituto Nacional de Estadistica (ES) MTM2006-05693 Institutional research plan: CEZ:AV0Z10750506 Keywords : goodness of fit * devergence statistics * GLM * model checking * bootstrap Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.445, year: 2008 http://library.utia.cas.cz/separaty/2008/SI/hobza-divergence-based%20tests%20for%20model%20diagnostic.pdf

  2. 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

  3. Bayesian Based Diagnostic Model for Condition Based Maintenance of Offshore Wind Farms

    Directory of Open Access Journals (Sweden)

    Masoud Asgarpour

    2018-01-01

    Full Text Available Operation and maintenance costs are a major contributor to the Levelized Cost of Energy for electricity produced by offshore wind and can be significantly reduced if existing corrective actions are performed as efficiently as possible and if future corrective actions are avoided by performing sufficient preventive actions. This paper presents an applied and generic diagnostic model for fault detection and condition based maintenance of offshore wind components. The diagnostic model is based on two probabilistic matrices; first, a confidence matrix, representing the probability of detection using each fault detection method, and second, a diagnosis matrix, representing the individual outcome of each fault detection method. Once the confidence and diagnosis matrices of a component are defined, the individual diagnoses of each fault detection method are combined into a final verdict on the fault state of that component. Furthermore, this paper introduces a Bayesian updating model based on observations collected by inspections to decrease the uncertainty of initial confidence matrix. The framework and implementation of the presented diagnostic model are further explained within a case study for a wind turbine component based on vibration, temperature, and oil particle fault detection methods. The last part of the paper will have a discussion of the case study results and present conclusions.

  4. A tool for model based diagnostics of the AGS Booster

    International Nuclear Information System (INIS)

    Luccio, A.

    1993-01-01

    A model-based algorithmic tool was developed to search for lattice errors by a systematic analysis of orbit data in the AGS Booster synchrotron. The algorithm employs transfer matrices calculated with MAD between points in the ring. Iterative model fitting of the data allows one to find and eventually correct magnet displacements and angles or field errors. The tool, implemented on a HP-Apollo workstation system, has proved very general and of immediate physical interpretation

  5. 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...

  6. Experience with model based display for advanced diagnostics and control

    International Nuclear Information System (INIS)

    Staffon, J.D.; Lindsay, R.W.

    1989-01-01

    A full color, model based display system based on the Rankine thermodynamic cycle has been developed for use at the Experimental Breeder Reactor II by plant operators, engineers, and experimenters. The displays generate a real time thermodynamic model of the plant processes on computer screens to provide a direct indication of the plant performance. Operators and others who view the displays are no longer required to mentally ''construct'' a model of the process before acting. The model based display accurately depicts the plant states. It appears to effectively reduce the gulf of evaluation, which should result in a significant reduction in human operator errors if this plant display approach is adopted by the nuclear industry. Preliminary comments from users, including operators, indicate an overwhelming acceptance of the display approach. The displays incorporate alarm functions as well as levels of detail ''paging'' capability. The system is developed on a computer network which allows the easy addition of displays as well as extra computers. Constructing a complete console can be rapid and inexpensive. 1 ref., 2 figs

  7. Spatial enhancement of ECG using diagnostic similarity score based lead selective multi-scale linear model.

    Science.gov (United States)

    Nallikuzhy, Jiss J; Dandapat, S

    2017-06-01

    In this work, a new patient-specific approach to enhance the spatial resolution of ECG is proposed and evaluated. The proposed model transforms a three-lead ECG into a standard twelve-lead ECG thereby enhancing its spatial resolution. The three leads used for prediction are obtained from the standard twelve-lead ECG. The proposed model takes advantage of the improved inter-lead correlation in wavelet domain. Since the model is patient-specific, it also selects the optimal predictor leads for a given patient using a lead selection algorithm. The lead selection algorithm is based on a new diagnostic similarity score which computes the diagnostic closeness between the original and the spatially enhanced leads. Standard closeness measures are used to assess the performance of the model. The similarity in diagnostic information between the original and the spatially enhanced leads are evaluated using various diagnostic measures. Repeatability and diagnosability are performed to quantify the applicability of the model. A comparison of the proposed model is performed with existing models that transform a subset of standard twelve-lead ECG into the standard twelve-lead ECG. From the analysis of the results, it is evident that the proposed model preserves diagnostic information better compared to other models. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. A signal-detection-based diagnostic-feature-detection model of eyewitness identification.

    Science.gov (United States)

    Wixted, John T; Mickes, Laura

    2014-04-01

    The theoretical understanding of eyewitness identifications made from a police lineup has long been guided by the distinction between absolute and relative decision strategies. In addition, the accuracy of identifications associated with different eyewitness memory procedures has long been evaluated using measures like the diagnosticity ratio (the correct identification rate divided by the false identification rate). Framed in terms of signal-detection theory, both the absolute/relative distinction and the diagnosticity ratio are mainly relevant to response bias while remaining silent about the key issue of diagnostic accuracy, or discriminability (i.e., the ability to tell the difference between innocent and guilty suspects in a lineup). Here, we propose a signal-detection-based model of eyewitness identification, one that encourages the use of (and helps to conceptualize) receiver operating characteristic (ROC) analysis to measure discriminability. Recent ROC analyses indicate that the simultaneous presentation of faces in a lineup yields higher discriminability than the presentation of faces in isolation, and we propose a diagnostic feature-detection hypothesis to account for that result. According to this hypothesis, the simultaneous presentation of faces allows the eyewitness to appreciate that certain facial features (viz., those that are shared by everyone in the lineup) are non-diagnostic of guilt. To the extent that those non-diagnostic features are discounted in favor of potentially more diagnostic features, the ability to discriminate innocent from guilty suspects will be enhanced.

  9. A Model-Based Expert System for Space Power Distribution Diagnostics

    Science.gov (United States)

    Quinn, Todd M.; Schlegelmilch, Richard F.

    1994-01-01

    When engineers diagnose system failures, they often use models to confirm system operation. This concept has produced a class of advanced expert systems that perform model-based diagnosis. A model-based diagnostic expert system for the Space Station Freedom electrical power distribution test bed is currently being developed at the NASA Lewis Research Center. The objective of this expert system is to autonomously detect and isolate electrical fault conditions. Marple, a software package developed at TRW, provides a model-based environment utilizing constraint suspension. Originally, constraint suspension techniques were developed for digital systems. However, Marple provides the mechanisms for applying this approach to analog systems such as the test bed, as well. The expert system was developed using Marple and Lucid Common Lisp running on a Sun Sparc-2 workstation. The Marple modeling environment has proved to be a useful tool for investigating the various aspects of model-based diagnostics. This report describes work completed to date and lessons learned while employing model-based diagnostics using constraint suspension within an analog system.

  10. Diagnostic classification based on functional connectivity in chronic pain: model optimization in fibromyalgia and rheumatoid arthritis.

    Science.gov (United States)

    Sundermann, Benedikt; Burgmer, Markus; Pogatzki-Zahn, Esther; Gaubitz, Markus; Stüber, Christoph; Wessolleck, Erik; Heuft, Gereon; Pfleiderer, Bettina

    2014-03-01

    The combination of functional magnetic resonance imaging (fMRI) of the brain with multivariate pattern analysis (MVPA) has been proposed as a possible diagnostic tool. Goal of this investigation was to identify potential functional connectivity (FC) differences in the salience network (SN) and default mode network (DMN) between fibromyalgia syndrome (FMS), rheumatoid arthritis (RA), and controls (HC) and to evaluate the diagnostic applicability of derived pattern classification approaches. The resting period during an fMRI examination was retrospectively analyzed in women with FMS (n = 17), RA (n = 16), and HC (n = 17). FC was calculated for SN and DMN subregions. Classification accuracies of discriminative MVPA models were evaluated with cross-validation: (1) inferential test of a single method, (2) explorative model optimization. No inferentially tested model was able to classify subjects with statistically significant accuracy. However, the diagnostic ability for the differential diagnostic problem exhibited a trend to significance (accuracy: 69.7%, P = .086). Optimized models in the explorative analysis reached accuracies up to 73.5% (FMS vs. HC), 78.8% (RA vs. HC), and 78.8% (FMS vs. RA) whereas other models performed at or below chance level. Comparable support vector machine approaches performed above average for all three problems. Observed accuracies are not sufficient to reliably differentiate between FMS and RA for diagnostic purposes. However, some indirect evidence in support of the feasibility of this approach is provided. This exploratory analysis constitutes a fundamental model optimization effort to be based on in further investigations. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

  11. Application of a model based on fuzzy logic for evaluating nursing diagnostic accuracy of students.

    Science.gov (United States)

    Lopes, Maria Helena Baena de Moraes; Jensen, Rodrigo; da Cruz, Diná de Almeida Lopes Monteiro; Matos, Fabiana Gonçalves de Oliveira Azevedo; Silveira, Paulo Sérgio Panse; Ortega, Neli Regina Siqueira

    2013-09-01

    To describe a model for assessing nursing diagnostic accuracy and its application to undergraduate students, comparing students' performance according to the course year. This model, based on the theory of fuzzy sets, guides a student through three steps: (a) the student must parameterize the model by establishing relationship values between defining characteristic/risk factors and nursing diagnoses; (b) presentation of a clinical case; (c) the student must define the presence of each defining characteristic/risk factors for the clinical case. Subsequently, the model computes the most plausible diagnoses by taking into account the values indicated by the student. This gives the student a performance score in comparison with parameters and diagnoses that were previously provided by nursing experts. These nursing experts collaborated with the construction of the model indicating the strength of the relationship between the concepts, meaning, they parameterized the model to compare the student's choice with the expert's choice (gold standard), thus generating performance scores for the student. The model was tested using three clinical cases presented to 38 students in their third and fourth years of the undergraduate nursing course. Third year students showed superior performance in identifying the presence of defining characteristic/risk factors, while fourth year students showed superior performance in the diagnoses by the model. The Model for Evaluation of Diagnostic Accuracy Based on Fuzzy Logic applied in this study is feasible and can be used to evaluate students' performance. In this regard, it will open a broad variety of applications for learning and nursing research. Despite the ease in filling the printed questionnaires out, the number of steps and fields to fill in may explain the considerable number of questionnaires with incorrect or missing data. This was solved in the digital version of the questionnaire. In addition, in more complex cases, it is

  12. Modeling FAMA ion beam diagnostics based on the Ptolemy II model

    Energy Technology Data Exchange (ETDEWEB)

    Balvanovic, R., E-mail: broman@vinca.rs [Laboratory of Physics, Vinca Institute of Nuclear Sciences, University of Belgrade, PO Box 522, 11001 Belgrade (Serbia); Belicev, P. [Laboratory of Physics, Vinca Institute of Nuclear Sciences, University of Belgrade, PO Box 522, 11001 Belgrade (Serbia); Radjenovic, B. [Institute of Physics, University of Belgrade, Pregrevica 118, 11080 Belgrade (Serbia)

    2012-10-21

    The previously developed model of ion beam transport control of the FAMA facility is further enhanced by equipping it with the model of ion beam diagnostics. The model of control, executing once, is adjusted so that it executes in iterative mode, where each iteration samples the input beam normally distributed over initial phase space and calculates a single trajectory through the facility beam lines. The model takes into account only the particles that manage to pass through all the beam line apertures, emulating in this way a Faraday cup and a beam profile meter. Generated are also beam phase space distributions and horizontal and vertical beam profiles at the end of the beam transport lines the FAMA facility consists of. By adding the model of ion beam diagnostics to the model of ion beam transport control, the process of determining optimal ion beam control parameters is eased and speeded up, and the understanding of influence of control parameters on the ion beam characteristics is improved.

  13. Streamlined ion torrent PGM-based diagnostics: BRCA1 and BRCA2 genes as a model.

    Science.gov (United States)

    Tarabeux, Julien; Zeitouni, Bruno; Moncoutier, Virginie; Tenreiro, Henrique; Abidallah, Khadija; Lair, Séverine; Legoix-Né, Patricia; Leroy, Quentin; Rouleau, Etienne; Golmard, Lisa; Barillot, Emmanuel; Stern, Marc-Henri; Rio-Frio, Thomas; Stoppa-Lyonnet, Dominique; Houdayer, Claude

    2014-04-01

    To meet challenges in terms of throughput and turnaround time, many diagnostic laboratories are shifting from Sanger sequencing to higher throughput next-generation sequencing (NGS) platforms. Bearing in mind that the performance and quality criteria expected from NGS in diagnostic or research settings are strikingly different, we have developed an Ion Torrent's PGM-based routine diagnostic procedure for BRCA1/2 sequencing. The procedure was first tested on a training set of 62 control samples, and then blindly validated on 77 samples in parallel with our routine technique. The training set was composed of difficult cases, for example, insertions and/or deletions of various sizes, large-scale rearrangements and, obviously, mutations occurring in homopolymer regions. We also compared two bioinformatic solutions in this diagnostic context, an in-house academic pipeline and the commercially available NextGene software (Softgenetics). NextGene analysis provided higher sensitivity, as four previously undetected single-nucleotide variations were found. Regarding specificity, an average of 1.5 confirmatory Sanger sequencings per patient was needed for complete BRCA1/2 screening. Large-scale rearrangements were identified by two distinct analyses, that is, bioinformatics and fragment analysis with electrophoresis profile comparison. Turnaround time was enhanced, as a series of 30 patients were sequenced by one technician, making the results available for the clinician in 10 working days following blood sampling. BRCA1/2 genes are a good model, representative of the difficulties commonly encountered in diagnostic settings, which is why we believe our findings are of interest for the whole community, and the pipeline described can be adapted by any user of PGM for diagnostic purposes.

  14. 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. Copyright © 2015 John Wiley & Sons, Ltd.

  15. A Model-based Health Monitoring and Diagnostic System for the UH-60 Helicopter. Appendix D

    Science.gov (United States)

    Patterson-Hine, Ann; Hindson, William; Sanderfer, Dwight; Deb, Somnath; Domagala, Chuck

    2001-01-01

    Model-based reasoning techniques hold much promise in providing comprehensive monitoring and diagnostics capabilities for complex systems. We are exploring the use of one of these techniques, which utilizes multi-signal modeling and the TEAMS-RT real-time diagnostic engine, on the UH-60 Rotorcraft Aircrew Systems Concepts Airborne Laboratory (RASCAL) flight research aircraft. We focus on the engine and transmission systems, and acquire sensor data across the 1553 bus as well as by direct analog-to-digital conversion from sensors to the QHuMS (Qualtech health and usage monitoring system) computer. The QHuMS computer uses commercially available components and is rack-mounted in the RASCAL facility. A multi-signal model of the transmission and engine subsystems enables studies of system testability and analysis of the degree of fault isolation available with various instrumentation suites. The model and examples of these analyses will be described and the data architectures enumerated. Flight tests of this system will validate the data architecture and provide real-time flight profiles to be further analyzed in the laboratory.

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

    Directory of Open Access Journals (Sweden)

    Swagata Payra

    2014-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-03-15

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

  18. 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…

  19. Reactor noise diagnostics based on multivariate autoregressive modeling: Application to LOFT [Loss-of-Fluid-Test] reactor process noise

    International Nuclear Information System (INIS)

    Gloeckler, O.; Upadhyaya, B.R.

    1987-01-01

    Multivariate noise analysis of power reactor operating signals is useful for plant diagnostics, for isolating process and sensor anomalies, and for automated plant monitoring. In order to develop a reliable procedure, the previously established techniques for empirical modeling of fluctuation signals in power reactors have been improved. Application of the complete algorithm to operational data from the Loss-of-Fluid-Test (LOFT) Reactor showed that earlier conjectures (based on physical modeling) regarding the perturbation sources in a Pressurized Water Reactor (PWR) affecting coolant temperature and neutron power fluctuations can be systematically explained. This advanced methodology has important implication regarding plant diagnostics, and system or sensor anomaly isolation. 6 refs., 24 figs

  20. Getting expert systems off the ground: Lessons learned from integrating model-based diagnostics with prototype flight hardware

    Science.gov (United States)

    Stephan, Amy; Erikson, Carol A.

    1991-11-01

    As an initial attempt to introduce expert system technology into an onboard environment, a model based diagnostic system using the TRW MARPLE software tool was integrated with prototype flight hardware and its corresponding control software. Because this experiment was designed primarily to test the effectiveness of the model based reasoning technique used, the expert system ran on a separate hardware platform, and interactions between the control software and the model based diagnostics were limited. While this project met its objective of showing that model based reasoning can effectively isolate failures in flight hardware, it also identified the need for an integrated development path for expert system and control software for onboard applications. In developing expert systems that are ready for flight, artificial intelligence techniques must be evaluated to determine whether they offer a real advantage onboard, identify which diagnostic functions should be performed by the expert systems and which are better left to the procedural software, and work closely with both the hardware and the software developers from the beginning of a project to produce a well designed and thoroughly integrated application.

  1. Research on Fault Diagnostic System in CVT Based on UDS

    Directory of Open Access Journals (Sweden)

    Jiande Wang

    2015-01-01

    Full Text Available A communication model of diagnostic network and implementation of unified diagnostic services (UDS based on controller area network (CAN bus are presented in this paper, and fault diagnostic function of transmission control unit (TCU, USB- (universal serial bus- CAN hardware and software modules, and fault diagnostic software based on personal computer (PC are designed. Model diagnostic method is applied on ratio control, and fault diagnostic system is tested in vehicle.

  2. Bayesian modelling of fusion diagnostics

    Science.gov (United States)

    Fischer, R.; Dinklage, A.; Pasch, E.

    2003-07-01

    Integrated data analysis of fusion diagnostics is the combination of different, heterogeneous diagnostics in order to improve physics knowledge and reduce the uncertainties of results. One example is the validation of profiles of plasma quantities. Integration of different diagnostics requires systematic and formalized error analysis for all uncertainties involved. The Bayesian probability theory (BPT) allows a systematic combination of all information entering the measurement descriptive model that considers all uncertainties of the measured data, calibration measurements, physical model parameters and measurement nuisance parameters. A sensitivity analysis of model parameters allows crucial uncertainties to be found, which has an impact on both diagnostic improvement and design. The systematic statistical modelling within the BPT is used for reconstructing electron density and electron temperature profiles from Thomson scattering data from the Wendelstein 7-AS stellarator. The inclusion of different diagnostics and first-principle information is discussed in terms of improvements.

  3. Specialist integrated haematological malignancy diagnostic services: an Activity Based Cost (ABC) analysis of a networked laboratory service model.

    Science.gov (United States)

    Dalley, C; Basarir, H; Wright, J G; Fernando, M; Pearson, D; Ward, S E; Thokula, P; Krishnankutty, A; Wilson, G; Dalton, A; Talley, P; Barnett, D; Hughes, D; Porter, N R; Reilly, J T; Snowden, J A

    2015-04-01

    Specialist Integrated Haematological Malignancy Diagnostic Services (SIHMDS) were introduced as a standard of care within the UK National Health Service to reduce diagnostic error and improve clinical outcomes. Two broad models of service delivery have become established: 'co-located' services operating from a single-site and 'networked' services, with geographically separated laboratories linked by common management and information systems. Detailed systematic cost analysis has never been published on any established SIHMDS model. We used Activity Based Costing (ABC) to construct a cost model for our regional 'networked' SIHMDS covering a two-million population based on activity in 2011. Overall estimated annual running costs were £1 056 260 per annum (£733 400 excluding consultant costs), with individual running costs for diagnosis, staging, disease monitoring and end of treatment assessment components of £723 138, £55 302, £184 152 and £94 134 per annum, respectively. The cost distribution by department was 28.5% for haematology, 29.5% for histopathology and 42% for genetics laboratories. Costs of the diagnostic pathways varied considerably; pathways for myelodysplastic syndromes and lymphoma were the most expensive and the pathways for essential thrombocythaemia and polycythaemia vera being the least. ABC analysis enables estimation of running costs of a SIHMDS model comprised of 'networked' laboratories. Similar cost analyses for other SIHMDS models covering varying populations are warranted to optimise quality and cost-effectiveness in delivery of modern haemato-oncology diagnostic services in the UK as well as internationally. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  4. Development of diagnostic model of lung cancer based on multiple tumor markers and data mining.

    Science.gov (United States)

    Wang, Zhaoxian; Feng, Feifei; Zhou, Xiaoshan; Duan, Liju; Wang, Jing; Wu, Yongjun; Wang, Na

    2017-11-07

    To develop early intelligent discriminative model of lung cancer and evaluate the efficiency of diagnosis value. Based on the genetic polymorphism profile of CYP1A1-rs1048943, GSTM1, mEH-rs1051740, XRCC1-rs1799782 and XRCC1-rs25489 and the methylations of p16 and RASSF1A gene, and the length of telomere in the peripheral blood from 200 lung cancer patients and 200 health persons, the discriminative model was established through decision tree and ANN technique. ACU of the discriminative model based on multiple tumour markers increased by about 10%; The accuracy rate of decision tree model and ANN model for testing set were 93.00% and 89.62% respectively. The ROC analysis showed the decision tree model's AUC is 0.929 (0.894∼0.964), the ANN model's AUC is 0.894 (0.853∼0.935). However, the classify accuracy rate and AUC of Fisher discriminatory analysis model are all about 0.7. The early intelligent discriminative model of lung cancer based on multiple tumor markers and data mining techniques has a higher accuracy rate and might be useful for early diagnosis of lung cancer.

  5. Spatial pattern evaluation of a calibrated national hydrological model - a remote-sensing-based diagnostic approach

    Science.gov (United States)

    Mendiguren, Gorka; Koch, Julian; Stisen, Simon

    2017-11-01

    Distributed hydrological models are traditionally evaluated against discharge stations, emphasizing the temporal and neglecting the spatial component of a model. The present study widens the traditional paradigm by highlighting spatial patterns of evapotranspiration (ET), a key variable at the land-atmosphere interface, obtained from two different approaches at the national scale of Denmark. The first approach is based on a national water resources model (DK-model), using the MIKE-SHE model code, and the second approach utilizes a two-source energy balance model (TSEB) driven mainly by satellite remote sensing data. Ideally, the hydrological model simulation and remote-sensing-based approach should present similar spatial patterns and driving mechanisms of ET. However, the spatial comparison showed that the differences are significant and indicate insufficient spatial pattern performance of the hydrological model.The differences in spatial patterns can partly be explained by the fact that the hydrological model is configured to run in six domains that are calibrated independently from each other, as it is often the case for large-scale multi-basin calibrations. Furthermore, the model incorporates predefined temporal dynamics of leaf area index (LAI), root depth (RD) and crop coefficient (Kc) for each land cover type. This zonal approach of model parameterization ignores the spatiotemporal complexity of the natural system. To overcome this limitation, this study features a modified version of the DK-model in which LAI, RD and Kc are empirically derived using remote sensing data and detailed soil property maps in order to generate a higher degree of spatiotemporal variability and spatial consistency between the six domains. The effects of these changes are analyzed by using empirical orthogonal function (EOF) analysis to evaluate spatial patterns. The EOF analysis shows that including remote-sensing-derived LAI, RD and Kc in the distributed hydrological model adds

  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 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

    2015-01-01

    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. PMID:26541245

  8. Knowledge based diagnostics in nuclear power plants

    International Nuclear Information System (INIS)

    Baldeweg, F.; Fiedler, U.; Weiss, F.P.; Werner, M.

    1987-01-01

    In this paper a special process diagnostic system (PDS) is presented. It must be seen as the result of a long term work on computerized process surveillance and control; it includes a model based system for noise analysis of mechanical vibrations, which has recently been enhanced by using of knowledge based technique (expert systems). The paper discusses the process diagnostic frame concept and emphasize the vibration analysis expert system

  9. Cytokine-based Predictive Models to Estimate the Probability of Chronic Periodontitis: Development of Diagnostic Nomograms.

    Science.gov (United States)

    Tomás, I; Arias-Bujanda, N; Alonso-Sampedro, M; Casares-de-Cal, M A; Sánchez-Sellero, C; Suárez-Quintanilla, D; Balsa-Castro, C

    2017-09-14

    Although a distinct cytokine profile has been described in the gingival crevicular fluid (GCF) of patients with chronic periodontitis, there is no evidence of GCF cytokine-based predictive models being used to diagnose the disease. Our objectives were: to obtain GCF cytokine-based predictive models; and develop nomograms derived from them. A sample of 150 participants was recruited: 75 periodontally healthy controls and 75 subjects affected by chronic periodontitis. Sixteen mediators were measured in GCF using the Luminex 100™ instrument: GMCSF, IFNgamma, IL1alpha, IL1beta, IL2, IL3, IL4, IL5, IL6, IL10, IL12p40, IL12p70, IL13, IL17A, IL17F and TNFalpha. Cytokine-based models were obtained using multivariate binary logistic regression. Models were selected for their ability to predict chronic periodontitis, considering the different role of the cytokines involved in the inflammatory process. The outstanding predictive accuracy of the resulting smoking-adjusted models showed that IL1alpha, IL1beta and IL17A in GCF are very good biomarkers for distinguishing patients with chronic periodontitis from periodontally healthy individuals. The predictive ability of these pro-inflammatory cytokines was increased by incorporating IFN gamma and IL10. The nomograms revealed the amount of periodontitis-associated imbalances between these cytokines with pro-inflammatory and anti-inflammatory effects in terms of a particular probability of having chronic periodontitis.

  10. Reliability analysis of laser ultrasonics for train axle diagnostics based on model assisted POD curves

    Science.gov (United States)

    Malik, M. S.; Cavuto, A.; Martarelli, M.; Pandarese, G.; Revel, G. M.

    2014-05-01

    High speed train axles are integrated for a lifetime and it is time and resource consuming to conduct in service inspection with high accuracy. Laser ultrasonics is a proposed solution as a subset of non-contact measuring methods effective also for hard to reach areas and even recently proved to be effective using Laser Doppler Vibrometer (LDV) or air-coupled probes in reception. A reliability analysis of laser ultrasonics for this specific application is here performed. The research is mainly based on numerical study of the effect of high energy laser pulses on the surface of a steel axle and of the behavior of the ultrasonic waves in detecting possible defects. Probability of Detection (POD) concept is used as an estimated reliability of the inspection method. In particular Model Assisted Probability of Detection (MAPOD), a modified form of POD where models are used to infer results for making a decisive statistical approach of POD curve, is here adopted. This paper implements this approach by taking the inputs from limited experiments conducted on a high speed train axle using laser ultrasonics (source pulsed Nd:Yag, reception by high-frequency LDV) to calibrate a multiphysics FE model and by using the calibrated model to generate data samples statistically representative of damaged train axles. The simulated flaws are in accordance with the real defects present on the axle. A set of flaws of different depth has been modeled in order to assess the laser ultrasonics POD for this specific application.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

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

    International Nuclear Information System (INIS)

    Carl Stern; Martin Lee

    1999-01-01

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

  16. 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

  17. 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.

  18. Eigenvalue based inverse model of beam for structural modification and diagnostics: examples of using

    Directory of Open Access Journals (Sweden)

    Leszek Majkut

    Full Text Available In the work, in order to solve the inverse problem, i.e. the problem of finding values of the additional quantities (mass, elasticity, the beam inverse model was proposed. Analysis of this model allows finding such a value of additional mass (elasticity as a function of its localization so that the free vibration frequency changes to desirable value. The criteria for choice of the “proper” pair (mass - its position, including the criterion allowing changing the position of the vibration node of the second mode of the free vibrations, were given. Analysis of the influence of uncertainties in the determination of the additional quantity value and its position on the desired free vibration frequency was carried out, too. The proposed beam inverse model can be employing to identification of the beam cracks. In such a case, the input quantity is free vibration frequency measured on the damaged object. Each determined free-vibration frequency allows determining the flexibility curve for the spring modeling crack as a function of its position. The searched parameters of the crack (its depth and position are indicated by the common point of two arbitrary curves. Accuracy of crack parameters determination depends on accuracy (uncertainty of frequency measurement. Only some regions containing the searched crack parameters can be obtained in such a situation.

  19. Risk-adjusted capitation based on the Diagnostic Cost Group Model: an empirical evaluation with health survey information

    NARCIS (Netherlands)

    L.M. Lamers (Leida)

    1999-01-01

    textabstractOBJECTIVE: To evaluate the predictive accuracy of the Diagnostic Cost Group (DCG) model using health survey information. DATA SOURCES/STUDY SETTING: Longitudinal data collected for a sample of members of a Dutch sickness fund. In the Netherlands the sickness

  20. 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.

  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. 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.

  3. Influence diagnostics in meta-regression model.

    Science.gov (United States)

    Shi, Lei; Zuo, ShanShan; Yu, Dalei; Zhou, Xiaohua

    2017-09-01

    This paper studies the influence diagnostics in meta-regression model including case deletion diagnostic and local influence analysis. We derive the subset deletion formulae for the estimation of regression coefficient and heterogeneity variance and obtain the corresponding influence measures. The DerSimonian and Laird estimation and maximum likelihood estimation methods in meta-regression are considered, respectively, to derive the results. Internal and external residual and leverage measure are defined. The local influence analysis based on case-weights perturbation scheme, responses perturbation scheme, covariate perturbation scheme, and within-variance perturbation scheme are explored. We introduce a method by simultaneous perturbing responses, covariate, and within-variance to obtain the local influence measure, which has an advantage of capable to compare the influence magnitude of influential studies from different perturbations. An example is used to illustrate the proposed methodology. Copyright © 2017 John Wiley & Sons, Ltd.

  4. Evidence-based Diagnostics: Adult Septic Arthritis

    Science.gov (United States)

    Carpenter, Christopher R.; Schuur, Jeremiah D.; Everett, Worth W.; Pines, Jesse M.

    2011-01-01

    Background Acutely swollen or painful joints are common complaints in the emergency department (ED). Septic arthritis in adults is a challenging diagnosis, but prompt differentiation of a bacterial etiology is crucial to minimize morbidity and mortality. Objectives The objective was to perform a systematic review describing the diagnostic characteristics of history, physical examination, and bedside laboratory tests for nongonococcal septic arthritis. A secondary objective was to quantify test and treatment thresholds using derived estimates of sensitivity and specificity, as well as best-evidence diagnostic and treatment risks and anticipated benefits from appropriate therapy. Methods Two electronic search engines (PUBMED and EMBASE) were used in conjunction with a selected bibliography and scientific abstract hand search. Inclusion criteria included adult trials of patients presenting with monoarticular complaints if they reported sufficient detail to reconstruct partial or complete 2 × 2 contingency tables for experimental diagnostic test characteristics using an acceptable criterion standard. Evidence was rated by two investigators using the Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS). When more than one similarly designed trial existed for a diagnostic test, meta-analysis was conducted using a random effects model. Interval likelihood ratios (LRs) were computed when possible. To illustrate one method to quantify theoretical points in the probability of disease whereby clinicians might cease testing altogether and either withhold treatment (test threshold) or initiate definitive therapy in lieu of further diagnostics (treatment threshold), an interactive spreadsheet was designed and sample calculations were provided based on research estimates of diagnostic accuracy, diagnostic risk, and therapeutic risk/benefits. Results The prevalence of nongonococcal septic arthritis in ED patients with a single acutely painful joint is approximately 27

  5. Evidence synthesis to inform model-based cost-effectiveness evaluations of diagnostic tests: a methodological review of health technology assessments.

    Science.gov (United States)

    Shinkins, Bethany; Yang, Yaling; Abel, Lucy; Fanshawe, Thomas R

    2017-04-14

    Evaluations of diagnostic tests are challenging because of the indirect nature of their impact on patient outcomes. Model-based health economic evaluations of tests allow different types of evidence from various sources to be incorporated and enable cost-effectiveness estimates to be made beyond the duration of available study data. To parameterize a health-economic model fully, all the ways a test impacts on patient health must be quantified, including but not limited to diagnostic test accuracy. We assessed all UK NIHR HTA reports published May 2009-July 2015. Reports were included if they evaluated a diagnostic test, included a model-based health economic evaluation and included a systematic review and meta-analysis of test accuracy. From each eligible report we extracted information on the following topics: 1) what evidence aside from test accuracy was searched for and synthesised, 2) which methods were used to synthesise test accuracy evidence and how did the results inform the economic model, 3) how/whether threshold effects were explored, 4) how the potential dependency between multiple tests in a pathway was accounted for, and 5) for evaluations of tests targeted at the primary care setting, how evidence from differing healthcare settings was incorporated. The bivariate or HSROC model was implemented in 20/22 reports that met all inclusion criteria. Test accuracy data for health economic modelling was obtained from meta-analyses completely in four reports, partially in fourteen reports and not at all in four reports. Only 2/7 reports that used a quantitative test gave clear threshold recommendations. All 22 reports explored the effect of uncertainty in accuracy parameters but most of those that used multiple tests did not allow for dependence between test results. 7/22 tests were potentially suitable for primary care but the majority found limited evidence on test accuracy in primary care settings. The uptake of appropriate meta-analysis methods for

  6. 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.

  7. Nanotechnology based diagnostics for neurological disorders

    International Nuclear Information System (INIS)

    Kurek, Nicholas S.; Chandra, Sathees B.

    2012-01-01

    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)

  8. 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)

  9. Kernel-Based Visual Hazard Comparison (kbVHC): a Simulation-Free Diagnostic for Parametric Repeated Time-to-Event Models.

    Science.gov (United States)

    Goulooze, Sebastiaan C; Välitalo, Pyry A J; Knibbe, Catherijne A J; Krekels, Elke H J

    2017-11-27

    Repeated time-to-event (RTTE) models are the preferred method to characterize the repeated occurrence of clinical events. Commonly used diagnostics for parametric RTTE models require representative simulations, which may be difficult to generate in situations with dose titration or informative dropout. Here, we present a novel simulation-free diagnostic tool for parametric RTTE models; the kernel-based visual hazard comparison (kbVHC). The kbVHC aims to evaluate whether the mean predicted hazard rate of a parametric RTTE model is an adequate approximation of the true hazard rate. Because the true hazard rate cannot be directly observed, the predicted hazard is compared to a non-parametric kernel estimator of the hazard rate. With the degree of smoothing of the kernel estimator being determined by its bandwidth, the local kernel bandwidth is set to the lowest value that results in a bootstrap coefficient of variation (CV) of the hazard rate that is equal to or lower than a user-defined target value (CV target ). The kbVHC was evaluated in simulated scenarios with different number of subjects, hazard rates, CV target values, and hazard models (Weibull, Gompertz, and circadian-varying hazard). The kbVHC was able to distinguish between Weibull and Gompertz hazard models, even when the hazard rate was relatively low (< 2 events per subject). Additionally, it was more sensitive than the Kaplan-Meier VPC to detect circadian variation of the hazard rate. An additional useful feature of the kernel estimator is that it can be generated prior to model development to explore the shape of the hazard rate function.

  10. Field-based systems and advanced diagnostics

    International Nuclear Information System (INIS)

    Eryurek, E.

    1998-01-01

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

  11. Acquiring, Representing, and Evaluating a Competence Model of Diagnostic Strategy.

    Science.gov (United States)

    Clancey, William J.

    This paper describes NEOMYCIN, a computer program that models one physician's diagnostic reasoning within a limited area of medicine. NEOMYCIN's knowledge base and reasoning procedure constitute a model of how human knowledge is organized and how it is used in diagnosis. The hypothesis is tested that such a procedure can be used to simulate both…

  12. 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.

  13. 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....... Diagnostic studies using CD63 or CD203c in hymenoptera, food and drug allergy are critically discussed. Basophil-based tests are indicated for allergy testing in selected cases but should only be performed by experienced laboratories....

  14. High Performance Modeling of Novel Diagnostics Configuration

    Science.gov (United States)

    Smith, Dalton; Gibson, John; Lodes, Rylie; Malcolm, Hayden; Nakamoto, Teagan; Parrack, Kristina; Trujillo, Christopher; Wilde, Zak; Los Alamos Laboratories Q-6 Students Team

    2017-06-01

    A novel diagnostics method to measure the Hayes Electric Effect was tested and verified against computerized models. Where standard PVDF diagnostics utilize piezoelectric materials to measure detonation pressure through strain-induced electrical signals, the PVDF was used in a novel technique by also detecting the detonation's induced electric field. The ALE-3D Hydro Codes predicted the performance by calculating detonation velocities, pressures, and arrival times. These theoretical results then validated the experimental use of the PVDF repurposed to specifically track the Hayes Electric Effect. Los Alamos National Laboratories Q-6.

  15. 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...

  16. Graphene-based nanoprobes for molecular diagnostics.

    Science.gov (United States)

    Chen, Shixing; Li, Fuwu; Fan, Chunhai; Song, Shiping

    2015-10-07

    In recent years, graphene has received widespread attention owing to its extraordinary electrical, chemical, optical, mechanical and structural properties. Lately, considerable interest has been focused on exploring the potential applications of graphene in life sciences, particularly in disease-related molecular diagnostics. In particular, the coupling of functional molecules with graphene as a nanoprobe offers an excellent platform to realize the detection of biomarkers, such as nucleic acids, proteins and other bioactive molecules, with high performance. This article reviews emerging graphene-based nanoprobes in electrical, optical and other assay methods and their application in various strategies of molecular diagnostics. In particular, this review focuses on the construction of graphene-based nanoprobes and their special advantages for the detection of various bioactive molecules. Properties of graphene-based materials and their functionalization are also comprehensively discussed in view of the development of nanoprobes. Finally, future challenges and perspectives of graphene-based nanoprobes are discussed.

  17. Climate Model Diagnostic Analyzer Web Service System

    Science.gov (United States)

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

    2014-12-01

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

  18. An ontology-driven, diagnostic modeling system.

    Science.gov (United States)

    Haug, Peter J; Ferraro, Jeffrey P; Holmen, John; Wu, Xinzi; Mynam, Kumar; Ebert, Matthew; Dean, Nathan; Jones, Jason

    2013-06-01

    To present a system that uses knowledge stored in a medical ontology to automate the development of diagnostic decision support systems. To illustrate its function through an example focused on the development of a tool for diagnosing pneumonia. We developed a system that automates the creation of diagnostic decision-support applications. It relies on a medical ontology to direct the acquisition of clinic data from a clinical data warehouse and uses an automated analytic system to apply a sequence of machine learning algorithms that create applications for diagnostic screening. We refer to this system as the ontology-driven diagnostic modeling system (ODMS). We tested this system using samples of patient data collected in Salt Lake City emergency rooms and stored in Intermountain Healthcare's enterprise data warehouse. The system was used in the preliminary development steps of a tool to identify patients with pneumonia in the emergency department. This tool was compared with a manually created diagnostic tool derived from a curated dataset. The manually created tool is currently in clinical use. The automatically created tool had an area under the receiver operating characteristic curve of 0.920 (95% CI 0.916 to 0.924), compared with 0.944 (95% CI 0.942 to 0.947) for the manually created tool. Initial testing of the ODMS demonstrates promising accuracy for the highly automated results and illustrates the route to model improvement. The use of medical knowledge, embedded in ontologies, to direct the initial development of diagnostic computing systems appears feasible.

  19. Modeling sequential context effects in diagnostic interpretation of screening mammograms.

    Science.gov (United States)

    Alamudun, Folami; Paulus, Paige; Yoon, Hong-Jun; Tourassi, Georgia

    2018-07-01

    Prior research has shown that physicians' medical decisions can be influenced by sequential context, particularly in cases where successive stimuli exhibit similar characteristics when analyzing medical images. This type of systematic error is known to psychophysicists as sequential context effect as it indicates that judgments are influenced by features of and decisions about the preceding case in the sequence of examined cases, rather than being based solely on the peculiarities unique to the present case. We determine if radiologists experience some form of context bias, using screening mammography as the use case. To this end, we explore correlations between previous perceptual behavior and diagnostic decisions and current decisions. We hypothesize that a radiologist's visual search pattern and diagnostic decisions in previous cases are predictive of the radiologist's current diagnostic decisions. To test our hypothesis, we tasked 10 radiologists of varied experience to conduct blind reviews of 100 four-view screening mammograms. Eye-tracking data and diagnostic decisions were collected from each radiologist under conditions mimicking clinical practice. Perceptual behavior was quantified using the fractal dimension of gaze scanpath, which was computed using the Minkowski-Bouligand box-counting method. To test the effect of previous behavior and decisions, we conducted a multifactor fixed-effects ANOVA. Further, to examine the predictive value of previous perceptual behavior and decisions, we trained and evaluated a predictive model for radiologists' current diagnostic decisions. ANOVA tests showed that previous visual behavior, characterized by fractal analysis, previous diagnostic decisions, and image characteristics of previous cases are significant predictors of current diagnostic decisions. Additionally, predictive modeling of diagnostic decisions showed an overall improvement in prediction error when the model is trained on additional information about

  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. New Diagnostics to Assess Model Performance

    Science.gov (United States)

    Koh, Tieh-Yong

    2013-04-01

    The comparison of model performance between the tropics and the mid-latitudes is particularly problematic for observables like temperature and humidity: in the tropics, these observables have little variation and so may give an apparent impression that model predictions are often close to observations; on the contrary, they vary widely in mid-latitudes and so the discrepancy between model predictions and observations might be unnecessarily over-emphasized. We have developed a suite of mathematically rigorous diagnostics that measures normalized errors accounting for the observed and modeled variability of the observables themselves. Another issue in evaluating model performance is the relative importance of getting the variance of an observable right versus getting the modeled variation to be in phase with the observed. The correlation-similarity diagram was designed to analyse the pattern error of a model by breaking it down into contributions from amplitude and phase errors. A final and important question pertains to the generalization of scalar diagnostics to analyse vector observables like wind. In particular, measures of variance and correlation must be properly derived to avoid the mistake of ignoring the covariance between north-south and east-west winds (hence wrongly assuming that the north-south and east-west directions form a privileged vector basis for error analysis). There is also a need to quantify systematic preferences in the direction of vector wind errors, which we make possible by means of an error anisotropy diagram. Although the suite of diagnostics is mentioned with reference to model verification here, it is generally applicable to quantify differences between two datasets (e.g. from two observation platforms). Reference publication: Koh, T. Y. et al. (2012), J. Geophys. Res., 117, D13109, doi:10.1029/2011JD017103. also available at http://www.ntu.edu.sg/home/kohty

  2. 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…

  3. The DINA model as a constrained general diagnostic model: Two variants of a model equivalency.

    Science.gov (United States)

    von Davier, Matthias

    2014-02-01

    The 'deterministic-input noisy-AND' (DINA) model is one of the more frequently applied diagnostic classification models for binary observed responses and binary latent variables. The purpose of this paper is to show that the model is equivalent to a special case of a more general compensatory family of diagnostic models. Two equivalencies are presented. Both project the original DINA skill space and design Q-matrix using mappings into a transformed skill space as well as a transformed Q-matrix space. Both variants of the equivalency produce a compensatory model that is mathematically equivalent to the (conjunctive) DINA model. This equivalency holds for all DINA models with any type of Q-matrix, not only for trivial (simple-structure) cases. The two versions of the equivalency presented in this paper are not implied by the recently suggested log-linear cognitive diagnosis model or the generalized DINA approach. The equivalencies presented here exist independent of these recently derived models since they solely require a linear - compensatory - general diagnostic model without any skill interaction terms. Whenever it can be shown that one model can be viewed as a special case of another more general one, conclusions derived from any particular model-based estimates are drawn into question. It is widely known that multidimensional models can often be specified in multiple ways while the model-based probabilities of observed variables stay the same. This paper goes beyond this type of equivalency by showing that a conjunctive diagnostic classification model can be expressed as a constrained special case of a general compensatory diagnostic modelling framework. © 2013 The British Psychological Society.

  4. Forward modeling of JET polarimetry diagnostic

    International Nuclear Information System (INIS)

    Ford, Oliver; Svensson, J.; Boboc, A.; McDonald, D. C.

    2008-01-01

    An analytical Bayesian inversion of the JET interferometry line integrated densities into density profiles and associated uncertainty information, is demonstrated. These are used, with a detailed model of plasma polarimetry, to predict the rotation and ellipticity for the JET polarimeter. This includes the lateral channels, for over 45,000 time points over 1313 JET pulses. Good agreement with measured values is shown for a number of channels. For the remaining channels, the requirement of a more detailed model of the diagnostic is demonstrated. A commonly used approximation for the Cotton-Mouton effect on the lateral channels is also evaluated.

  5. 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.

  6. 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

  7. 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.

  8. SYNTHESIS OF INFORMATION MODEL FOR ALTERNATIVE FUNCTIONAL DIAGNOSTICS PROCEDURE

    OpenAIRE

    P. F. Shchapov; R. P. Miguschenko

    2014-01-01

    Probabilistic approaches in information theory and information theory of measurement, allowing to calculate and analyze the amount expected to models measuring conversions and encoding tasks random measurement signals were considered. A probabilistic model of diagnostic information model transformation and diagnostic procedures was developed. Conditions for obtaining the maximum amount of diagnostic information were found out.

  9. 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.

  10. 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.

  11. Convergence diagnostics for Eigenvalue problems with linear regression model

    International Nuclear Information System (INIS)

    Shi, Bo; Petrovic, Bojan

    2011-01-01

    Although the Monte Carlo method has been extensively used for criticality/Eigenvalue problems, a reliable, robust, and efficient convergence diagnostics method is still desired. Most methods are based on integral parameters (multiplication factor, entropy) and either condense the local distribution information into a single value (e.g., entropy) or even disregard it. We propose to employ the detailed cycle-by-cycle local flux evolution obtained by using mesh tally mechanism to assess the source and flux convergence. By applying a linear regression model to each individual mesh in a mesh tally for convergence diagnostics, a global convergence criterion can be obtained. We exemplify this method on two problems and obtain promising diagnostics results. (author)

  12. Atomic Models for Motional Stark Effects Diagnostics

    Energy Technology Data Exchange (ETDEWEB)

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

    2007-07-26

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

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

    International Nuclear Information System (INIS)

    Saunders, Margaret; Palmer, Maria; Preece, Alan; Millard, Roger

    2002-01-01

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

  14. The Role of Data Assimilation in Model Diagnostics

    Science.gov (United States)

    Nearing, G. S.; Ruddell, B.; Clark, M. P.; Nijssen, B.

    2016-12-01

    To make reliable predictions under nonstationary conditions we must build physically realistic models. However, because hydrological systems are compendiums of dynamic interactions between many different components and processes, it is difficult to use a direct comparison between model predictions and observations of integrated system responses to determine exactly which process representation(s) in any given model might contribute to or compensate for prediction error. Hydrologists and Earth Systems Modelers might recognize this problem as one of model diagnostics, however this is a classical problem that affects almost all aspects of scientific investigation - it is the confirmation holism aspect of the Duhem-Quine thesis. We propose here a systematic way to attack this problem that is based on a fundamental logic-based interpretation of the Duhem-Quine problem. The general idea is that diagnostic evaluation of complex systems models will involve tracking information flows through and between different interacting components in a given model structure, and that it is actually these information flows that we should wish to validate, evaluate or benchmark against observations. The problem is that we rarely have observations of all pertinent states and fluxes at all relevant spatiotemporal scales, and we propose that the fundamental resolution to this problem is data assimilation. The key insight is that data assimilation is simply the projection of information onto the states of a dynamical systems model. We discuss the implications of this for doing science and making predictions with coupled land surface hydrology models, as well as the risks associated with using sub-optimal data assimilation strategies. We will finally outline a few application examples where we found that land surface models apparently have a systematic problem with underestimating the connectivity between hydrological and ecological processes. We will us these examples to show how data-assimilation-based

  15. Statistical physics of medical diagnostics: Study of a probabilistic model

    Science.gov (United States)

    Mashaghi, Alireza; Ramezanpour, Abolfazl

    2018-03-01

    We study a diagnostic strategy which is based on the anticipation of the diagnostic process by simulation of the dynamical process starting from the initial findings. We show that such a strategy could result in more accurate diagnoses compared to a strategy that is solely based on the direct implications of the initial observations. We demonstrate this by employing the mean-field approximation of statistical physics to compute the posterior disease probabilities for a given subset of observed signs (symptoms) in a probabilistic model of signs and diseases. A Monte Carlo optimization algorithm is then used to maximize an objective function of the sequence of observations, which favors the more decisive observations resulting in more polarized disease probabilities. We see how the observed signs change the nature of the macroscopic (Gibbs) states of the sign and disease probability distributions. The structure of these macroscopic states in the configuration space of the variables affects the quality of any approximate inference algorithm (so the diagnostic performance) which tries to estimate the sign-disease marginal probabilities. In particular, we find that the simulation (or extrapolation) of the diagnostic process is helpful when the disease landscape is not trivial and the system undergoes a phase transition to an ordered phase.

  16. Augmenting Epidemiological Models with Point-Of-Care Diagnostics Data.

    Directory of Open Access Journals (Sweden)

    Özgür Özmen

    Full Text Available Although adoption of newer Point-of-Care (POC diagnostics is increasing, there is a significant challenge using POC diagnostics data to improve epidemiological models. In this work, we propose a method to process zip-code level POC datasets and apply these processed data to calibrate an epidemiological model. We specifically develop a calibration algorithm using simulated annealing and calibrate a parsimonious equation-based model of modified Susceptible-Infected-Recovered (SIR dynamics. The results show that parsimonious models are remarkably effective in predicting the dynamics observed in the number of infected patients and our calibration algorithm is sufficiently capable of predicting peak loads observed in POC diagnostics data while staying within reasonable and empirical parameter ranges reported in the literature. Additionally, we explore the future use of the calibrated values by testing the correlation between peak load and population density from Census data. Our results show that linearity assumptions for the relationships among various factors can be misleading, therefore further data sources and analysis are needed to identify relationships between additional parameters and existing calibrated ones. Calibration approaches such as ours can determine the values of newly added parameters along with existing ones and enable policy-makers to make better multi-scale decisions.

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

    Data.gov (United States)

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

  18. 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...

  19. Diagnostic reasoning using qualitative causal models

    International Nuclear Information System (INIS)

    Sudduth, A.L.

    1992-01-01

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

  20. Bayesian Analysis Diagnostics: Diagnosing Predictive and Parameter Uncertainty for Hydrological Models

    Science.gov (United States)

    Thyer, Mark; Kavetski, Dmitri; Evin, Guillaume; Kuczera, George; Renard, Ben; McInerney, David

    2015-04-01

    All scientific and statistical analysis, particularly in natural sciences, is based on approximations and assumptions. For example, the calibration of hydrological models using approaches such as Nash-Sutcliffe efficiency and/or simple least squares (SLS) objective functions may appear to be 'assumption-free'. However, this is a naïve point of view, as SLS assumes that the model residuals (residuals=observed-predictions) are independent, homoscedastic and Gaussian. If these assumptions are poor, parameter inference and model predictions will be correspondingly poor. An essential step in model development is therefore to verify the assumptions and approximations made in the modeling process. Diagnostics play a key role in verifying modeling assumptions. An important advantage of the formal Bayesian approach is that the modeler is required to make the assumptions explicit. Specialized diagnostics can then be developed and applied to test and verify their assumptions. This paper presents a suite of statistical and modeling diagnostics that can be used by environmental modelers to test their modeling calibration assumptions and diagnose model deficiencies. Three major types of diagnostics are presented: Residual Diagnostics Residual diagnostics are used to test whether the assumptions of the residual error model within the likelihood function are compatible with the data. This includes testing for statistical independence, homoscedasticity, unbiasedness, Gaussianity and any distributional assumptions. Parameter Uncertainty and MCMC Diagnostics An important part of Bayesian analysis is assess parameter uncertainty. Markov Chain Monte Carlo (MCMC) methods are a powerful numerical tool for estimating these uncertainties. Diagnostics based on posterior parameter distributions can be used to assess parameter identifiability, interactions and correlations. This provides a very useful tool for detecting and remedying model deficiencies. In addition, numerical diagnostics are

  1. 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.

  2. 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.

  3. Incorporating published univariable associations in diagnostic and prognostic modeling

    NARCIS (Netherlands)

    T.P.A. Debray (Thomas); H. Koffijberg (Hendrik); D. Lu (Difei); Y. Vergouwe (Yvonne); E.W. Steyerberg (Ewout); K.G.M. Moons (Karel)

    2012-01-01

    textabstractBackground: Diagnostic and prognostic literature is overwhelmed with studies reporting univariable predictor-outcome associations. Currently, methods to incorporate such information in the construction of a prediction model are underdeveloped and unfamiliar to many researchers. Methods.

  4. Increasing Authenticity of Simulation-Based Assessment in Diagnostic Radiology

    NARCIS (Netherlands)

    van der Gijp, Anouk; Ravesloot, Cécile J.; Tipker, Corinne A.; de Crom, Kim; Rutgers, Dik R.; van der Schaaf, Marieke F.; van der Schaaf, Irene C.; Mol, Christian P.; Vincken, Koen L.; ten Cate, Olle Th J.; Maas, Mario; van Schaik, Jan P. J.

    2017-01-01

    Introduction: Clinical reasoning in diagnostic imaging professions is a complex skill that requires processing of visual information and image manipulation skills. We developed a digital simulation-based test method to increase authenticity of image interpretation skill assessment. Methods: A

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

    International Nuclear Information System (INIS)

    Carpenter, K.H.; Booker, R.H.

    1983-10-01

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

  6. A fluctuation-induced plasma transport diagnostic based upon fast-Fourier transform spectral analysis

    Science.gov (United States)

    Powers, E. J.; Kim, Y. C.; Hong, J. Y.; Roth, J. R.; Krawczonek, W. M.

    1978-01-01

    A diagnostic, based on fast Fourier-transform spectral analysis techniques, that provides experimental insight into the relationship between the experimentally observable spectral characteristics of the fluctuations and the fluctuation-induced plasma transport is described. The model upon which the diagnostic technique is based and its experimental implementation is discussed. Some characteristic results obtained during the course of an experimental study of fluctuation-induced transport in the electric field dominated NASA Lewis bumpy torus plasma are presented.

  7. Educational and Scientific Applications of Climate Model Diagnostic Analyzer

    Science.gov (United States)

    Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Zhang, J.; Bao, Q.

    2016-12-01

    Climate Model Diagnostic Analyzer (CMDA) is a web-based information system designed for the climate modeling and model analysis community to analyze climate data from models and observations. CMDA provides tools to diagnostically analyze climate data for model validation and improvement, and to systematically manage analysis provenance for sharing results with other investigators. CMDA utilizes cloud computing resources, multi-threading computing, machine-learning algorithms, web service technologies, and provenance-supporting technologies to address technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. As CMDA infrastructure and technology have matured, we have developed the educational and scientific applications of CMDA. Educationally, CMDA supported the summer school of the JPL Center for Climate Sciences for three years since 2014. In the summer school, the students work on group research projects where CMDA provide datasets and analysis tools. Each student is assigned to a virtual machine with CMDA installed in Amazon Web Services. A provenance management system for CMDA is developed to keep track of students' usages of CMDA, and to recommend datasets and analysis tools for their research topic. The provenance system also allows students to revisit their analysis results and share them with their group. Scientifically, we have developed several science use cases of CMDA covering various topics, datasets, and analysis types. Each use case developed is described and listed in terms of a scientific goal, datasets used, the analysis tools used, scientific results discovered from the use case, an analysis result such as output plots and data files, and a link to the exact analysis service call with all the input arguments filled. For example, one science use case is the evaluation of NCAR CAM5 model with MODIS total cloud fraction. The analysis service used is Difference Plot Service of

  8. Choosing wisely: a model-based analysis evaluating the trade-offs in cancer benefit and diagnostic referrals among alternative HPV testing strategies in Norway.

    Science.gov (United States)

    Burger, Emily A; Pedersen, Kine; Sy, Stephen; Kristiansen, Ivar Sønbø; Kim, Jane J

    2017-09-05

    Forthcoming cervical cancer screening strategies involving human papillomavirus (HPV) testing for women not vaccinated against HPV infections may increase colposcopy referral rates. We quantified health and resource trade-offs associated with alternative HPV-based algorithms to inform decision-makers when choosing between candidate algorithms. We used a mathematical simulation model of HPV-induced cervical carcinogenesis in Norway. We compared the current cytology-based strategy to alternative strategies that varied by the switching age to primary HPV testing (ages 25-34 years), the routine screening frequency (every 3-10 years), and management of HPV-positive, cytology-negative women. Model outcomes included reductions in lifetime cervical cancer risk, relative colposcopy rates, and colposcopy rates per cervical cancer prevented. The age of switching to primary HPV testing and the screening frequency had the largest impacts on cancer risk reductions, which ranged from 90.9% to 96.3% compared to no screening. In contrast, increasing the follow-up intensity of HPV-positive, cytology-negative women provided only minor improvements in cancer benefits, but generally required considerably higher rates of colposcopy referrals compared to current levels, resulting in less efficient cervical cancer prevention. We found that in order to maximise cancer benefits HPV-based screening among unvaccinated women should not be delayed: rather, policy makers should utilise the triage mechanism to control colposcopy referrals.

  9. Diagnostics

    DEFF Research Database (Denmark)

    Donné, A.J.H.; Costley, A.E.; Barnsley, R.

    2007-01-01

    In order to support the operation of ITER and the planned experimental programme an extensive set of plasma and first wall measurements will be required. The number and type of required measurements will be similar to those made on the present-day large tokamaks while the specification...... of the measurements—time and spatial resolutions, etc—will in some cases be more stringent. Many of the measurements will be used in the real time control of the plasma driving a requirement for very high reliability in the systems (diagnostics) that provide the measurements. The implementation of diagnostic systems......&D is needed to prepare the systems. In some cases the environmental difficulties are so severe that new diagnostic techniques are required. The starting point in the development of diagnostics for ITER is to define the measurement requirements and develop their justification. It is necessary to include all...

  10. Paper based microfluidic devices for environmental diagnostics

    CSIR Research Space (South Africa)

    Govindasamy, K

    2012-09-01

    Full Text Available such as elevated temperatures and mechanical stresses. Paper based microfluidic chips are patterned with micron sized hydrophobic barriers which penetrate the paper?s cross section. These barriers guide the capillary movement of fluids through the cellulose...

  11. Improved diagnostic model for estimating wind energy

    Energy Technology Data Exchange (ETDEWEB)

    Endlich, R.M.; Lee, J.D.

    1983-03-01

    Because wind data are available only at scattered locations, a quantitative method is needed to estimate the wind resource at specific sites where wind energy generation may be economically feasible. This report describes a computer model that makes such estimates. The model uses standard weather reports and terrain heights in deriving wind estimates; the method of computation has been changed from what has been used previously. The performance of the current model is compared with that of the earlier version at three sites; estimates of wind energy at four new sites are also presented.

  12. In Search of Optimal Cognitive Diagnostic Model(s) for ESL Grammar Test Data

    Science.gov (United States)

    Yi, Yeon-Sook

    2017-01-01

    This study compares five cognitive diagnostic models in search of optimal one(s) for English as a Second Language grammar test data. Using a unified modeling framework that can represent specific models with proper constraints, the article first fit the full model (the log-linear cognitive diagnostic model, LCDM) and investigated which model…

  13. 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.”

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

    DEFF Research Database (Denmark)

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

    2007-01-01

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

  15. Diagnostics and modeling of high pressure streamer induced discharges

    International Nuclear Information System (INIS)

    Marode, E.; Dessante, P.; Deschamps, N.; Deniset, C.

    2001-01-01

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

  16. Modeling companion diagnostics in economic evaluations of targeted oncology therapies: systematic review and methodological checklist.

    Science.gov (United States)

    Doble, Brett; Tan, Marcus; Harris, Anthony; Lorgelly, Paula

    2015-02-01

    The successful use of a targeted therapy is intrinsically linked to the ability of a companion diagnostic to correctly identify patients most likely to benefit from treatment. The aim of this study was to review the characteristics of companion diagnostics that are of importance for inclusion in an economic evaluation. Approaches for including these characteristics in model-based economic evaluations are compared with the intent to describe best practice methods. Five databases and government agency websites were searched to identify model-based economic evaluations comparing a companion diagnostic and subsequent treatment strategy to another alternative treatment strategy with model parameters for the sensitivity and specificity of the companion diagnostic (primary synthesis). Economic evaluations that limited model parameters for the companion diagnostic to only its cost were also identified (secondary synthesis). Quality was assessed using the Quality of Health Economic Studies instrument. 30 studies were included in the review (primary synthesis n = 12; secondary synthesis n = 18). Incremental cost-effectiveness ratios may be lower when the only parameter for the companion diagnostic included in a model is the cost of testing. Incorporating the test's accuracy in addition to its cost may be a more appropriate methodological approach. Altering the prevalence of the genetic biomarker, specific population tested, type of test, test accuracy and timing/sequence of multiple tests can all impact overall model results. The impact of altering a test's threshold for positivity is unknown as it was not addressed in any of the included studies. Additional quality criteria as outlined in our methodological checklist should be considered due to the shortcomings of standard quality assessment tools in differentiating studies that incorporate important test-related characteristics and those that do not. There is a need to refine methods for incorporating the characteristics

  17. 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.

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

    International Nuclear Information System (INIS)

    Isa, Nor Ashidi Mat

    2015-01-01

    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

  19. 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.

  20. A Model-Free Diagnostic for Single-Peakedness of Item Responses Using Ordered Conditional Means

    Science.gov (United States)

    Polak, Marike; De Rooij, Mark; Heiser, Willem J.

    2012-01-01

    In this article we propose a model-free diagnostic for single-peakedness (unimodality) of item responses. Presuming a unidimensional unfolding scale and a given item ordering, we approximate item response functions of all items based on ordered conditional means (OCM). The proposed OCM methodology is based on Thurstone & Chave's (1929) "criterion…

  1. Outcome of Presumptive Versus Rapid Diagnostic Tests-Based ...

    African Journals Online (AJOL)

    First, 50 children with malaria-pneumonia symptom overlap were consecutively enrolled and treated presumptively with antibiotics and antimalarials irrespective of malaria test result (control arm).Then, another 50 eligible children were enrolled and treated with antibiotics with/out antimalarials based on rapid diagnostic test ...

  2. Breast Cancer Diagnostics Based on Spatial Genome Organization

    Science.gov (United States)

    2012-07-01

    breast tissues made up of invasive breast carcinomas, benign diseased tissues ( fibroadenoma and hyperplasia) and normal breast tissues [11]. To enable an...positioning patterns were also compared between benign disease ( fibroadenoma and hyperplasia; not including atypical hyperplasia, which is linked to breast ...AD_________________ Award Number: W81XWH-08-2-0098 TITLE: Breast Cancer Diagnostics Based on

  3. Rapid development of paper-based fluidic diagnostic devices

    CSIR Research Space (South Africa)

    Smith, S

    2014-11-01

    Full Text Available We present a method for rapid and low-cost development of microfluidic diagnostic devices using paper-based techniques. Specifically, the implementation of fluidic flow paths and electronics on paper are demonstrated, with the goal of producing...

  4. Differential Item Functioning Assessment in Cognitive Diagnostic Modeling: Applying the Wald Test to Investigate DIF in the Generalized DINA Model Framework

    Science.gov (United States)

    Hou, Likun

    2013-01-01

    Analyzing examinees' responses using cognitive diagnostic models (CDMs) have the advantages of providing richer diagnostic information. To ensure the validity of the results from these models, differential item functioning (DIF) in CDMs needs to be investigated. In this dissertation, the model-based DIF detection method, Wald-CDM procedure is…

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

    International Nuclear Information System (INIS)

    Kress, B.; Baehren, W.

    2001-01-01

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

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

    International Nuclear Information System (INIS)

    Shelton, R; O'Brien, D; Nelson, J; Kamperschroer, J

    2007-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Shelton, R; O' Brien, D; Nelson, J; Kamperschroer, J

    2007-05-07

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

  8. 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.

  9. Alternative models of DSM-5 PTSD: Examining diagnostic implications.

    Science.gov (United States)

    Murphy, Siobhan; Hansen, Maj; Elklit, Ask; Yong Chen, Yoke; Raudzah Ghazali, Siti; Shevlin, Mark

    2018-04-01

    The factor structure of DSM-5 posttraumatic stress disorder (PTSD) has been extensively debated with evidence supporting the recently proposed seven-factor Hybrid model. However, despite myriad studies examining PTSD symptom structure few have assessed the diagnostic implications of these proposed models. This study aimed to generate PTSD prevalence estimates derived from the 7 alternative factor models and assess whether pre-established risk factors associated with PTSD (e.g., transportation accidents and sexual victimisation) produce consistent risk estimates. Seven alternative models were estimated within a confirmatory factor analytic framework using the PTSD Checklist for DSM-5 (PCL-5). Data were analysed from a Malaysian adolescent community sample (n = 481) of which 61.7% were female, with a mean age of 17.03 years. The results indicated that all models provided satisfactory model fit with statistical superiority for the Externalising Behaviours and seven-factor Hybrid models. The PTSD prevalence estimates varied substantially ranging from 21.8% for the DSM-5 model to 10.0% for the Hybrid model. Estimates of risk associated with PTSD were inconsistent across the alternative models, with substantial variation emerging for sexual victimisation. These findings have important implications for research and practice and highlight that more research attention is needed to examine the diagnostic implications emerging from the alternative models of PTSD. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Diagnostic Measures for the Cox Regression Model with Missing Covariates.

    Science.gov (United States)

    Zhu, Hongtu; Ibrahim, Joseph G; Chen, Ming-Hui

    2015-12-01

    This paper investigates diagnostic measures for assessing the influence of observations and model misspecification in the presence of missing covariate data for the Cox regression model. Our diagnostics include case-deletion measures, conditional martingale residuals, and score residuals. The Q-distance is proposed to examine the effects of deleting individual observations on the estimates of finite-dimensional and infinite-dimensional parameters. Conditional martingale residuals are used to construct goodness of fit statistics for testing possible misspecification of the model assumptions. A resampling method is developed to approximate the p -values of the goodness of fit statistics. Simulation studies are conducted to evaluate our methods, and a real data set is analyzed to illustrate their use.

  11. Caries detection using light-based diagnostic tools.

    Science.gov (United States)

    Rechmann, Peter; Rechmann, Beate M T; Featherstone, John D B

    2012-09-01

    Modern caries treatment concepts like caries management by risk assessment--CAMBRA--entail diagnosing early caries lesions in a precavitated stage to make it possible to reverse the caries process with remineralization and bacteria reduction efforts. Newer, sensitive caries diagnostic tools can serve not only for early detection but also for monitoring of caries lesions to confirm the success of prevention and remineralization efforts. This article describes light-based caries diagnostic tools, with emphasis on fluorescence-based techniques, and compares the most common available fluorescence-based tools with a standardized visual caries inspection system-the International Caries Detection and Assessment System (ICDAS II). Fluorescence tools that provide high-resolution fluorescence pictures are likely to provide more reliable scores than fluorescence devices that assess via a single spot. The better visibility of the high-resolution fluorescence imaging could prevent unnecessary operative interventions.

  12. Development of a rule-based diagnostic platform on an object-oriented expert system shell

    International Nuclear Information System (INIS)

    Wang, Wenlin; Yang, Ming; Seong, Poong Hyun

    2016-01-01

    Highlights: • Multilevel Flow Model represents system knowledge as a domain map in expert system. • Rule-based fault diagnostic expert system can identify root cause via a causal chain. • Rule-based fault diagnostic expert system can be used for fault simulation training. - Abstract: This paper presents the development and implementation of a real-time rule-based diagnostic platform. The knowledge is acquired from domain experts and textbooks and the design of the fault diagnosis expert system was performed in the following ways: (i) establishing of corresponding classes and instances to build the domain map, (ii) creating of generic fault models based on events, and (iii) building of diagnostic reasoning based on rules. Knowledge representation is a complicated issue of expert systems. One highlight of this paper is that the Multilevel Flow Model has been used to represent the knowledge, which composes the domain map within the expert system as well as providing a concise description of the system. The developed platform is illustrated using the pressure safety system of a pressurized water reactor as an example of the simulation test bed; the platform is developed using the commercial and industrially validated software G2. The emulation test was conducted and it has been proven that the fault diagnosis expert system can identify the faults correctly and in a timely way; this system can be used as a simulation-based training tool to assist operators to make better decisions.

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

    Science.gov (United States)

    Starcevic, Vladan

    2017-06-01

    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.

  14. 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.

  15. Monte Carlo model of diagnostic X-ray dosimetry

    International Nuclear Information System (INIS)

    Khrutchinsky, Arkady; Kutsen, Semion; Gatskevich, George

    2008-01-01

    Full text: A Monte Carlo simulation of absorbed dose distribution in patient's tissues is often used in a dosimetry assessment of X-ray examinations. The results of such simulations in Belarus are presented in the report based on an anthropomorphic tissue-equivalent Rando-like physical phantom. The phantom corresponds to an adult 173 cm high and of 73 kg and consists of a torso and a head made of tissue-equivalent plastics which model soft (muscular), bone, and lung tissues. It consists of 39 layers (each 25 mm thick), including 10 head and neck ones, 16 chest and 13 pelvis ones. A tomographic model of the phantom has been developed from its CT-scan images with a voxel size of 0.88 x 0.88 x 4 mm 3 . A necessary pixelization in Mathematics-based in-house program was carried out for the phantom to be used in the radiation transport code MCNP-4b. The final voxel size of 14.2 x 14.2 x 8 mm 3 was used for the reasonable computer consuming calculations of absorbed dose in tissues and organs in various diagnostic X-ray examinations. MCNP point detectors allocated through body slices obtained as a result of the pixelization were used to calculate the absorbed dose. X-ray spectra generated by the empirical TASMIP model were verified on the X-ray units MEVASIM and SIREGRAPH CF. Absorbed dose distributions in the phantom volume were determined by the corresponding Monte Carlo simulations with a set of point detectors. Doses in organs of the adult phantom computed from the absorbed dose distributions by another Mathematics-based in-house program were estimated for 22 standard organs for various standard X-ray examinations. The results of Monte Carlo simulations were compared with the results of direct measurements of the absorbed dose in the phantom on the X-ray unit SIREGRAPH CF with the calibrated thermo-luminescent dosimeter DTU-01. The measurements were carried out in specified locations of different layers in heart, lungs, liver, pancreas, and stomach at high voltage of

  16. Qualitative Event-Based Diagnosis: Case Study on the Second International Diagnostic Competition

    Science.gov (United States)

    Daigle, Matthew; Roychoudhury, Indranil

    2010-01-01

    We describe a diagnosis algorithm entered into the Second International Diagnostic Competition. We focus on the first diagnostic problem of the industrial track of the competition in which a diagnosis algorithm must detect, isolate, and identify faults in an electrical power distribution testbed and provide corresponding recovery recommendations. The diagnosis algorithm embodies a model-based approach, centered around qualitative event-based fault isolation. Faults produce deviations in measured values from model-predicted values. The sequence of these deviations is matched to those predicted by the model in order to isolate faults. We augment this approach with model-based fault identification, which determines fault parameters and helps to further isolate faults. We describe the diagnosis approach, provide diagnosis results from running the algorithm on provided example scenarios, and discuss the issues faced, and lessons learned, from implementing the approach

  17. A diagnostic tree model for polytomous responses with multiple strategies.

    Science.gov (United States)

    Ma, Wenchao

    2018-04-23

    Constructed-response items have been shown to be appropriate for cognitively diagnostic assessments because students' problem-solving procedures can be observed, providing direct evidence for making inferences about their proficiency. However, multiple strategies used by students make item scoring and psychometric analyses challenging. This study introduces the so-called two-digit scoring scheme into diagnostic assessments to record both students' partial credits and their strategies. This study also proposes a diagnostic tree model (DTM) by integrating the cognitive diagnosis models with the tree model to analyse the items scored using the two-digit rubrics. Both convergent and divergent tree structures are considered to accommodate various scoring rules. The MMLE/EM algorithm is used for item parameter estimation of the DTM, and has been shown to provide good parameter recovery under varied conditions in a simulation study. A set of data from TIMSS 2007 mathematics assessment is analysed to illustrate the use of the two-digit scoring scheme and the DTM. © 2018 The British Psychological Society.

  18. 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.

  19. 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.

  20. 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.

  1. Increasing Authenticity of Simulation-Based Assessment in Diagnostic Radiology.

    Science.gov (United States)

    van der Gijp, Anouk; Ravesloot, Cécile J; Tipker, Corinne A; de Crom, Kim; Rutgers, Dik R; van der Schaaf, Marieke F; van der Schaaf, Irene C; Mol, Christian P; Vincken, Koen L; Ten Cate, Olle Th J; Maas, Mario; van Schaik, Jan P J

    2017-12-01

    Clinical reasoning in diagnostic imaging professions is a complex skill that requires processing of visual information and image manipulation skills. We developed a digital simulation-based test method to increase authenticity of image interpretation skill assessment. A digital application, allowing volumetric image viewing and manipulation, was used for three test administrations of the national Dutch Radiology Progress Test for residents. This study describes the development and implementation process in three phases. To assess authenticity of the digital tests, perceived image quality and correspondence to clinical practice were evaluated and compared with previous paper-based tests (PTs). Quantitative and qualitative evaluation results were used to improve subsequent tests. Authenticity of the first digital test was not rated higher than the PTs. Test characteristics and environmental conditions, such as image manipulation options and ambient lighting, were optimized based on participants' comments. After adjustments in the third digital test, participants favored the image quality and clinical correspondence of the digital image questions over paper-based image questions. Digital simulations can increase authenticity of diagnostic radiology assessments compared with paper-based testing. However, authenticity does not necessarily increase with higher fidelity. It can be challenging to simulate the image interpretation task of clinical practice in a large-scale assessment setting, because of technological limitations. Optimizing image manipulation options, the level of ambient light, time limits, and question types can help improve authenticity of simulation-based radiology assessments.

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

    Science.gov (United States)

    Olsson, T.; Funk, P.

    2012-05-01

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

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

    International Nuclear Information System (INIS)

    Olsson, T; Funk, P

    2012-01-01

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

  4. Solar Prominence Modelling and Plasma Diagnostics at ALMA Wavelengths

    Science.gov (United States)

    Rodger, Andrew; Labrosse, Nicolas

    2017-09-01

    Our aim is to test potential solar prominence plasma diagnostics as obtained with the new solar capability of the Atacama Large Millimeter/submillimeter Array (ALMA). We investigate the thermal and plasma diagnostic potential of ALMA for solar prominences through the computation of brightness temperatures at ALMA wavelengths. The brightness temperature, for a chosen line of sight, is calculated using the densities of electrons, hydrogen, and helium obtained from a radiative transfer code under non-local thermodynamic equilibrium (non-LTE) conditions, as well as the input internal parameters of the prominence model in consideration. Two distinct sets of prominence models were used: isothermal-isobaric fine-structure threads, and large-scale structures with radially increasing temperature distributions representing the prominence-to-corona transition region. We compute brightness temperatures over the range of wavelengths in which ALMA is capable of observing (0.32 - 9.6 mm), however, we particularly focus on the bands available to solar observers in ALMA cycles 4 and 5, namely 2.6 - 3.6 mm (Band 3) and 1.1 - 1.4 mm (Band 6). We show how the computed brightness temperatures and optical thicknesses in our models vary with the plasma parameters (temperature and pressure) and the wavelength of observation. We then study how ALMA observables such as the ratio of brightness temperatures at two frequencies can be used to estimate the optical thickness and the emission measure for isothermal and non-isothermal prominences. From this study we conclude that for both sets of models, ALMA presents a strong thermal diagnostic capability, provided that the interpretation of observations is supported by the use of non-LTE simulation results.

  5. Building a satellite climate diagnostics data base for real-time climate monitoring

    International Nuclear Information System (INIS)

    Ropelewski, C.F.

    1991-01-01

    The paper discusses the development of a data base, the Satellite Climate Diagnostic Data Base (SCDDB), for real time operational climate monitoring utilizing current satellite data. Special attention is given to the satellite-derived quantities useful for monitoring global climate changes, the requirements of SCDDB, and the use of conventional meteorological data and model assimilated data in developing the SCDDB. Examples of prototype SCDDB products are presented. 10 refs

  6. Modeling experimental plasma diagnostics in the FLASH code: proton radiography

    Science.gov (United States)

    Flocke, Norbert; Weide, Klaus; Feister, Scott; Tzeferacos, Petros; Lamb, Donald

    2017-10-01

    Proton radiography is an important diagnostic tool for laser plasma experiments and for studying magnetized plasmas. We describe a new synthetic proton radiography diagnostic recently implemented into the FLASH code. FLASH is an open source, finite-volume Eulerian, spatially adaptive radiation hydrodynamics and magneto-hydrodynamics code that incorporates capabilities for a broad range of physical processes. Proton radiography is modeled through the use of the (relativistic) Lorentz force equation governing the motion of protons through 3D domains. Both instantaneous (one time step) and time-resolved (over many time steps) proton radiography can be simulated. The code module is also equipped with several different setup options (beam structure and detector screen placements) to reproduce a large variety of experimental proton radiography designs. FLASH's proton radiography diagnostic unit can be used either during runtime or in post-processing of simulation results. FLASH is publicly available at flash.uchicago.edu. U.S. DOE NNSA, U.S. DOE NNSA ASC, U.S. DOE Office of Science and NSF.

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

    Science.gov (United States)

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

    2014-01-01

    Key clinical studies for HIV coreceptor antagonists have used the phenotyping-based Trofile test. Meanwhile various simpler-to-do genotypic tests have become available that are compatible with standard laboratory equipment and Web-based interpretation tools. However, these systems typically analyze only the most prominent virus sequence in a specimen. We present a new diagnostic HIV tropism test not needing DNA sequencing. The system, XTrack, uses physical properties of DNA duplexes after hybridization of single-stranded HIV-1 env V3 loop probes to the clinical specimen. Resulting “heteroduplexes” possess unique properties driven by sequence relatedness to the reference and resulting in a discrete electrophoretic mobility. A detailed optimization process identified diagnostic probe candidates relating best to a large number of HIV-1 sequences with known tropism. From over 500 V3 sequences representing all main HIV-1 subtypes (Los Alamos database), we obtained a small set of probes to determine the tropism in clinical samples. We found a high concordance with the commercial TrofileES test (84.9%) and the Web-based tool Geno2Pheno (83.0%). Moreover, the new system reveals mixed virus populations, and it was successful on specimens with low virus loads or on provirus from leukocytes. A replicative phenotyping system was used for validation. Our data show that the XTrack test is favorably suitable for routine diagnostics. It detects and dissects mixed virus populations and viral minorities; samples with viral loads (VL) of <200 copies/ml are successfully analyzed. We further expect that the principles of the platform can be adapted also to other sequence-divergent pathogens, such as hepatitis B and C viruses. PMID:25502529

  8. 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

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

    Science.gov (United States)

    Reinitz, David M.; Yoshino, T.P.; Cole, Rebecca A.

    2007-01-01

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

  10. Plasmon-Based Colorimetric Nanosensors for Ultrasensitive Molecular Diagnostics.

    Science.gov (United States)

    Tang, Longhua; Li, Jinghong

    2017-07-28

    Colorimetric detection of target analytes with high specificity and sensitivity is of fundamental importance to clinical and personalized point-of-care diagnostics. Because of their extraordinary optical properties, plasmonic nanomaterials have been introduced into colorimetric sensing systems, which provide significantly improved sensitivity in various biosensing applications. Here we review the recent progress on these plasmonic nanoparticles-based colorimetric nanosensors for ultrasensitive molecular diagnostics. According to their different colorimetric signal generation mechanisms, these plasmonic nanosensors are classified into two categories: (1) interparticle distance-dependent colorimetric assay based on target-induced forming cross-linking assembly/aggregate of plasmonic nanoparticles; and (2) size/morphology-dependent colorimetric assay by target-controlled growth/etching of the plasmonic nanoparticles. The sensing fundamentals and cutting-edge applications will be provided for each of them, particularly focusing on signal generation and/or amplification mechanisms that realize ultrasensitive molecular detection. Finally, we also discuss the challenge and give our future perspective in this emerging field.

  11. Power System Transient Diagnostics Based on Novel Traveling Wave Detection

    Science.gov (United States)

    Hamidi, Reza Jalilzadeh

    Modern electrical power systems demand novel diagnostic approaches to enhancing the system resiliency by improving the state-of-the-art algorithms. The proliferation of high-voltage optical transducers and high time-resolution measurements provide opportunities to develop novel diagnostic methods of very fast transients in power systems. At the same time, emerging complex configuration, such as multi-terminal hybrid transmission systems, limits the applications of the traditional diagnostic methods, especially in fault location and health monitoring. The impedance-based fault-location methods are inefficient for cross-bounded cables, which are widely used for connection of offshore wind farms to the main grid. Thus, this dissertation first presents a novel traveling wave-based fault-location method for hybrid multi-terminal transmission systems. The proposed method utilizes time-synchronized high-sampling voltage measurements. The traveling wave arrival times (ATs) are detected by observation of the squares of wavelet transformation coefficients. Using the ATs, an over-determined set of linear equations are developed for noise reduction, and consequently, the faulty segment is determined based on the characteristics of the provided equation set. Then, the fault location is estimated. The accuracy and capabilities of the proposed fault location method are evaluated and also compared to the existing traveling-wave-based method for a wide range of fault parameters. In order to improve power systems stability, auto-reclosing (AR), single-phase auto-reclosing (SPAR), and adaptive single-phase auto-reclosing (ASPAR) methods have been developed with the final objectives of distinguishing between the transient and permanent faults to clear the transient faults without de-energization of the solid phases. However, the features of the electrical arcs (transient faults) are severely influenced by a number of random parameters, including the convection of the air and plasma

  12. ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation Value-Added Product

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Chengzhu [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Xie, Shaocheng [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-10-15

    A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Infrastructure Team at Lawrence Livermore National Laboratory (LLNL) to facilitate the use of long-term, high-frequency measurements from the ARM Facility in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The Coupled Model Intercomparison Project (CMIP) model data sets are also included in the package to enable model intercomparison as demonstrated in Zhang et al. (2017). The mean of the CMIP model can serve as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, and radiative fluxes, with plan to extend to more fields, such as aerosol and microphysics properties. Process-oriented diagnostics focusing on individual cloud- and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. The version 1.0 package is designed based on data collected at ARM’s Southern Great Plains (SGP) Research Facility, with the plan to extend to other ARM sites. The metrics and diagnostics package is currently built upon standard Python libraries and additional Python packages developed by DOE (such as CDMS and CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first present the input data, which

  13. Diagnostic accuracy of impression-free digital models.

    Science.gov (United States)

    Akyalcin, Sercan; Cozad, Benjamin E; English, Jeryl D; Colville, Clark D; Laman, Stephen

    2013-12-01

    Impression-free techniques might eliminate the potential shortcomings of digital dental models. Chairside scanners offer the advantage of obtaining digital dental models directly from the patient without the need for dental impressions. The aim of this study was to evaluate the accuracy of 3-dimensional digital models acquired from a chairside intraoral scanner compared with both manual and cone-beam computed tomography measurements of the same dental anatomy. The study sample comprised 60 dry skulls. Each skull had the maxillary and mandibular arches scanned with a Cadent iTero scanner (Align Technology, San Jose, Calif) and had a cone-beam computed tomography scan taken with a CS 9300 unit (Carestream Health, Atlanta, Ga). Linear measurements in all 3 dimensions of the space in each dental arch together with tooth-size arch-length analysis for both the maxillary and mandibular arches were carried out manually on the dry skulls with calipers and digitally on the scanned 3-dimensional models and cone-beam computed tomography images. Intraclass correlation (ICC) analysis was performed for all variables tested in the study groups, with the manual measurements on the dry skulls as the gold standard. The Bland-Altman analysis was also applied to the data to graphically display the agreement of the diagnostic measurements obtained from these methods. Measurements from the iTero models demonstrated near-perfect agreement (ICC, 0.91-0.99) with the caliper measurements. Cone-beam computed tomography measurements had moderate to high levels of agreement (ICC, 0.65-0.99) compared with the caliper measurements. Direct digital acquisition of the dental arches with a chairside scanner provided almost 1-to-1 diagnostic information of the investigated anatomy and was superior to the cone-beam computed tomography measurements. Copyright © 2013 American Association of Orthodontists. Published by Mosby, Inc. All rights reserved.

  14. ORNL diagnostic and modeling development for LAPD ICRF experiments

    Science.gov (United States)

    Isler, R. C.; Caughman, J. B. O.; Lau, C.; Martin, E. H.; Perkins, R. J.; Compernolle, B. Van; Vincena, S.; Tripathi, S. K. P.; Gekelman, W.

    2017-10-01

    PPPL, UCLA, and ORNL scientists have recently collaborated on a three week ICRF campaign at the upgraded LAPD device to study near field-plasma interactions associated with a single strap antenna driven at 2.38 MHz with 100 kW of RF power. This poster highlights ORNL involvement through implementation of the following diagnostics: an optical emission probe to measure neutral density, a retarding field energy analyzer to measure fast ions, phase locked imaging to measure line integrated RF-driven optical emission fluctuations, and an RF compensated triple Langmuir probe to measure density and temperature. To interpret the results of the experimental campaign a 3D cold plasma finite element model with realistic antenna and vacuum vessel geometry was developed in COMSOL. A summary of these results will be discussed. Highlights include a proof of principle localized and spatially resolved measurement of the neutral density, a strong increase in RF-driven optical emission fluctuations directly in front of the RF antenna strap, a shift in fast ion energies near the plasma edge, and qualitative agreement between the COMSOL cold plasma model with the various diagnostics. Funded by the DOE OFES (DE-AC05-00OR22725, DE-AC02-09CH11466, and DE-FC02-07ER54918) and the Univ. of California (12-LR-237124).

  15. Bayesian latent class models with conditionally dependent diagnostic tests: a case study.

    Science.gov (United States)

    Menten, Joris; Boelaert, Marleen; Lesaffre, Emmanuel

    2008-09-30

    In the assessment of the accuracy of diagnostic tests for infectious diseases, the true disease status of the subjects is often unknown due to the lack of a gold standard test. Latent class models with two latent classes, representing diseased and non-diseased subjects, are often used to analyze this type of data. In its basic format, latent class analysis requires the observed outcomes to be statistically independent conditional on the disease status. In most diagnostic settings, this assumption is highly questionable. During the last decade, several methods have been proposed to estimate latent class models with conditional dependence between the test results. A class of flexible fixed and random effects models were described by Dendukuri and Joseph in a Bayesian framework. We illustrate these models using the analysis of a diagnostic study of three field tests and an imperfect reference test for the diagnosis of visceral leishmaniasis. We show that, as observed earlier by Albert and Dodd, different dependence models may result in similar fits to the data while resulting in different inferences. Given this problem, selection of appropriate latent class models should be based on substantive subject matter knowledge. If several clinically plausible models are supported by the data, a sensitivity analysis should be performed by describing the results obtained from different models and using different priors. Copyright (c) 2008 John Wiley & Sons, Ltd.

  16. Expert diagnostic system for moving-coil loudspeakers using nonlinear modeling.

    Science.gov (United States)

    Bai, Mingsian R; Huang, Chau-Min

    2009-02-01

    This work aims at the development of an expert diagnostic system for moving-coil loudspeakers. Special emphasis is placed on the defects resulting from loudspeaker nonlinearities. As a loudspeaker operates in the large signal domain, nonlinear distortions may arise and impair sound quality. Analysis of nonlinear responses can shed light on potential design faults of a loudspeaker. By exploiting this fact, this expert diagnostic system enables classification of design faults using a defect database alongside an intelligent fault inference module. Six types of defects are investigated in this paper. A large signal model based on electromechanical analogous circuits is employed for generating the defect database, through which a neural-fuzzy network is utilized for inferring the defect types. Numerical simulations and experimental investigations were undertaken for validating the loudspeaker diagnostic system.

  17. CBDS: Constraint-based diagnostic system for malfunction identification in the nuclear power plant

    International Nuclear Information System (INIS)

    Ha, J.

    1992-01-01

    Traditional rule-based diagnostic expert systems use the experience of experts in the form of rules that associate symptoms with underlying faults. A commonly recognized failing of such systems is their narrow range of expertise and their inability to recognize problems outside this range of expertise. A model base diagnostic system isolating malfunctioning components-CBDS, the Constraint based Diagnostic System-has been developed. Since the intended behavior of a device is more predictable than unintended behaviors (faults), a model based system using the intended behavior has a potential to diagnose unexpected malfunctions by considering faults as open-quotes anything other than the intended behavior.close quotes As a knowledge base, the CBDS generates and decomposes a constraint network based on the structure and behavior model, which are represented symbolically in algebraic equations. Behaviors of generic components are organized in a component model library. Once the library is available, actual domain knowledge can be represented by declaring component types and their connections. To capture various plant knowledge, the mixed model was developed which allow the use of different parameter types in one equation by defining various operators. The CBDS uses the general idea of model based diagnosis. It detects a discrepancy between observation and prediction using constraint propagation, which carriers and accumulates the assumptions when parameter values are deduced. When measured plant parameters are asserted into a constraint network and are propagated through the network, a discrepancy will be detected if there exists any malfunctioning component. The CBDS was tested in the Recirculation Flow Control System of a BWR, and has been shown to be able to diagnose unexpected events

  18. 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.

  19. Modeling pulsed excitation for gas-phase laser diagnostics

    International Nuclear Information System (INIS)

    Settersten, Thomas B.; Linne, Mark A.

    2002-01-01

    Excitation dynamics for pulsed optical excitation are described with the density-matrix equations and the rate equations for a two-level system. A critical comparison of the two descriptions is made with complete and consistent formalisms that are amenable to the modeling of applied laser-diagnostic techniques. General solutions, resulting from numerical integration of the differential equations describing the excitation process, are compared for collisional conditions that range from the completely coherent limit to the steady-state limit, for which the two formalisms are identical. This analysis demonstrates the failure of the rate equations to correctly describe the transient details of the excitation process outside the steady-state limit. However, reasonable estimates of the resultant population are obtained for nonsaturating (linear) excitation. This comparison provides the laser diagnostician with the means to evaluate the appropriate model for excitation through a simple picture of the breakdown of the rate-equation validity

  20. Diagnostic Air Quality Model Evaluation of Source-Specific ...

    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 the results of a numerical air quality model. Previous analyses of these measurements demonstrated excellent mass closure for the variety of contributing sources. In this study, a carbon-apportionment version of the Community Multiscale Air Quality (CMAQ) model was used to track primary organic and elemental carbon emissions from 15 independent sources such as mobile sources and biomass burning in addition to four precursor-specific classes of secondary organic aerosol (SOA) originating from isoprene, terpenes, aromatics, and sesquiterpenes. Conversion of the source-resolved model output into organic tracer concentrations yielded a total of 2416 data pairs for comparison with observations. While emission source contributions to the total model bias varied by season and measurement location, the largest absolute bias of −0.55 μgC/m3 was attributed to insufficient isoprene SOA in the summertime CMAQ simulation. Biomass combustion was responsible for the second largest summertime model bias (−0.46 μgC/m3 on average). Several instances of compensating errors were also evident; model underpredictions in some sectors were masked by overpredictions in others. The National Exposure Research L

  1. Screen printed paper-based diagnostic devices with polymeric inks.

    Science.gov (United States)

    Sun, Ju-Yen; Cheng, Chao-Min; Liao, Ying-Chih

    2015-01-01

    A simple and low-cost fabrication method for paper-based diagnostic devices (PBDDs) is described in this study. Street-available polymer solutions were screen printed onto filter papers to create hydrophobic patterns for fluidic channels. In order to obtain fully functional hydrophobic patterns for fluids, the original polymer solutions were diluted with butyl acetate to yield a suitable viscosity range between 30-200 cP for complete patterning on paper. Typical pH and glucose tests with color indicators were performed on the screen printed PBDDs. Images of the PBDDs were analyzed by computers to obtain calibration curves for pH between 2 and 12 and glucose concentration ranging from 10-1000 mmol dm(-3). Detection of formaldehyde in acetone was also carried out to show the possibility of using this PBBD for analytical detection with organic solvents. An exemplar PBDD with simultaneous pH and glucose detection was also used to demonstrate the feasibility of applying this technique for realistic diagnostic applications.

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

    NARCIS (Netherlands)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2012-12-01

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

  4. 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

  5. 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

  6. Fuzzy logic-based diagnostic algorithm for implantable cardioverter defibrillators.

    Science.gov (United States)

    Bárdossy, András; Blinowska, Aleksandra; Kuzmicz, Wieslaw; Ollitrault, Jacky; Lewandowski, Michał; Przybylski, Andrzej; Jaworski, Zbigniew

    2014-02-01

    The paper presents a diagnostic algorithm for classifying cardiac tachyarrhythmias for implantable cardioverter defibrillators (ICDs). The main aim was to develop an algorithm that could reduce the rate of occurrence of inappropriate therapies, which are often observed in existing ICDs. To achieve low energy consumption, which is a critical factor for implantable medical devices, very low computational complexity of the algorithm was crucial. The study describes and validates such an algorithm and estimates its clinical value. The algorithm was based on the heart rate variability (HRV) analysis. The input data for our algorithm were: RR-interval (I), as extracted from raw intracardiac electrogram (EGM), and in addition two other features of HRV called here onset (ONS) and instability (INST). 6 diagnostic categories were considered: ventricular fibrillation (VF), ventricular tachycardia (VT), sinus tachycardia (ST), detection artifacts and irregularities (including extrasystoles) (DAI), atrial tachyarrhythmias (ATF) and no tachycardia (i.e. normal sinus rhythm) (NT). The initial set of fuzzy rules based on the distributions of I, ONS and INST in the 6 categories was optimized by means of a software tool for automatic rule assessment using simulated annealing. A training data set with 74 EGM recordings was used during optimization, and the algorithm was validated with a validation data set with 58 EGM recordings. Real life recordings stored in defibrillator memories were used. Additionally the algorithm was tested on 2 sets of recordings from the PhysioBank databases: MIT-BIH Arrhythmia Database and MIT-BIH Supraventricular Arrhythmia Database. A custom CMOS integrated circuit implementing the diagnostic algorithm was designed in order to estimate the power consumption. A dedicated Web site, which provides public online access to the algorithm, has been created and is available for testing it. The total number of events in our training and validation sets was 132. In

  7. Paper-based smart microfluidics for education and low-cost diagnostics

    Directory of Open Access Journals (Sweden)

    Suzanne Smith

    2015-11-01

    Full Text Available Current centralised healthcare models pose many challenges, particularly for developing countries such as South Africa, where travel and time costs make it difficult for patients to seek healthcare, even when urgently needed. To address this issue, point-of-care (PoC tests, which are performed at or near the site of clinical care, have gained popularity and are actively being developed. Microfluidic systems, in which small volumes of fluids can be processed, provide an ideal platform on which to develop PoC diagnostic solutions. Specifically, the emerging field of paper-based microfluidics, with advantages such as low-cost, disposability and minimal external equipment requirements, provides unique opportunities for addressing healthcare issues in developing countries. This work explores the field of paper-based microfluidics, with step-by-step instructions on the design, manufacture and testing processes to realise paper-based devices towards diagnostic applications. Paper-based microfluidic and electronic components are presented, as well as the integration of these components to provide smart paper-based devices. This serves as an educational tool, enabling both beginners and experts in the field to fast-track development of unique paper-based solutions towards PoC diagnostics, with emphasis on the South African context, where both the need for and impact of these solutions are great.

  8. Diagnostic modeling of the ARM experimental configuration. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Somerville, R.C.J.

    1998-04-01

    A major accomplishment of this work was to demonstrate the viability of using in-situ data in both mid-continent North America (SGP CART site) and Tropical Western Pacific (TOGA-COARE) locations to provide the horizontal advective flux convergences which force and constrain the Single-Column Model (SCM) which was the main theoretical tool of this work. The author has used TOGA-COARE as a prototype for the ARM TWP site. Results show that SCMs can produce realistic budgets over the ARM sites without relying on parameterization-dependent operational numerical weather prediction objective analyses. The single-column model is diagnostic rather than prognostic. It is numerically integrated in time as an initial value problem which is forced and constrained by observational data. The input is an observed initial state, plus observationally derived estimates of the time-dependent advection terms in the conservation equations, provided at all model layers. Its output is a complete heat and water budget, including temperature and moisture profiles, clouds and their radiative properties, diabatic heating terms, surface energy balance components, and hydrologic cycle elements, all specified as functions of time. These SCM results should be interpreted in light of the original motivation and purpose of ARM and its goal to improve the treatment of cloud-radiation interactions in climate models.

  9. Diagnostic system based on condition turbogenerator Petri nets

    International Nuclear Information System (INIS)

    Kachur, S.A.; Shakhova, N.V.

    2016-01-01

    A stochastic model of the automated monitoring systems and process control turbine generator based on Petri nets, allowing to detect local changes in the state of the stator windings of turbogenerator, is presented in the paper [ru

  10. Music-based Autism Diagnostics (MUSAD) - A newly developed diagnostic measure for adults with intellectual developmental disabilities suspected of autism.

    Science.gov (United States)

    Bergmann, Thomas; Sappok, Tanja; Diefenbacher, Albert; Dames, Sibylle; Heinrich, Manuel; Ziegler, Matthias; Dziobek, Isabel

    2015-01-01

    The MUSAD was developed as a diagnostic observational instrument in an interactional music framework. It is based on the ICD-10/DSM-5 criteria for autism spectrum disorder (ASD) and was designed to assess adults on a lower level of functioning, including individuals with severe language impairments. This study aimed to evaluate the psychometric properties of the newly developed instrument. Calculations were based on a consecutive clinical sample of N=76 adults with intellectual and developmental disabilities (IDD) suspected of ASD. Objectivity, test-retest reliability, and construct validity were calculated and a confirmatory factor analysis was applied to verify a reduced and optimized test version. The structural model showed a good fit, while internal consistency of the subscales was excellent (ω>.92). Item difficulties ranged between .04≤pi≤.82 and item-total correlation from .21 to .85. Objectivity was assessed by comparing the scorings of two external raters based on a subsample of n=12; interrater agreement was .71 (ICC 2, 1). Reliability was calculated for four test repetitions: the average ICC (3, 1) was .69. Convergent ASD measures correlated significantly with the MUSAD, while the discriminant Modified Overt Aggression Scale (MOAS) showed no significant overlap. Confirmation of factorial structure and acceptable psychometric properties suggest that the MUSAD is a promising new instrument for diagnosing ASD in adults with IDD. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. 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.

  12. 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.

  13. Incorporating published univariable associations in diagnostic and prognostic modeling

    Directory of Open Access Journals (Sweden)

    A Debray Thomas P

    2012-08-01

    Full Text Available Abstract Background Diagnostic and prognostic literature is overwhelmed with studies reporting univariable predictor-outcome associations. Currently, methods to incorporate such information in the construction of a prediction model are underdeveloped and unfamiliar to many researchers. Methods This article aims to improve upon an adaptation method originally proposed by Greenland (1987 and Steyerberg (2000 to incorporate previously published univariable associations in the construction of a novel prediction model. The proposed method improves upon the variance estimation component by reconfiguring the adaptation process in established theory and making it more robust. Different variants of the proposed method were tested in a simulation study, where performance was measured by comparing estimated associations with their predefined values according to the Mean Squared Error and coverage of the 90% confidence intervals. Results Results demonstrate that performance of estimated multivariable associations considerably improves for small datasets where external evidence is included. Although the error of estimated associations decreases with increasing amount of individual participant data, it does not disappear completely, even in very large datasets. Conclusions The proposed method to aggregate previously published univariable associations with individual participant data in the construction of a novel prediction models outperforms established approaches and is especially worthwhile when relatively limited individual participant data are available.

  14. Alternative methods of fuel consumption metering based on the on-board diagnostics outputs

    Directory of Open Access Journals (Sweden)

    Jiří Čupera

    2005-01-01

    Full Text Available The article describes alternative methods of fuel consumption measurement based on model with using the diagnostic outputs of engine control unit. On-board diagnosis (the second level, known as OBD-2 has been mandated by government regulation because of advanced damage control systems in newer cars. However, its signals can be used for accurate analyses of power or torque measurement. On-board diagnostics offers many various parameters such a spark advance, intake air temperature, coolant temperature, throttle position, air flow mass and so on. Many of them have been unavailable without using sophisticated and expensive instrumentation. In the article are described two ways of fuel consumption measuring which are based on intake air consumption and knowledge about air-fuel ratio. First of them is founded on voltage output of oxygen sensor, the second on short (long term fuel trim. As is shown at the end the second way gives more accurately results.

  15. Diagnostic models of intelligent tutor system for teaching skills to solve algebraic equations

    Directory of Open Access Journals (Sweden)

    Andrey Grigoriyevich Chukhray

    2007-10-01

    Full Text Available In this paper one solution for teaching skills to solve n-power algebraic equation by Lobachevsky-Greffe-Dandelen method is described. Student’s mistakes are discovered and classified. Based on signal-parametric approach to fault diagnosis in dynamic systems mathematical diagnostic models which allow detecting mistake classes by comparing student calculated results and system calculated results are created. Features of proposed diagnostic models application are presented. Intelligent tutor system is developed and used on “Automatic Control Theory” practical training by third year students of National Aerospace University.

  16. Development and validation of risk models and molecular diagnostics to permit personalized management of cancer.

    Science.gov (United States)

    Pu, Xia; Ye, Yuanqing; Wu, Xifeng

    2014-01-01

    Despite the advances made in cancer management over the past few decades, improvements in cancer diagnosis and prognosis are still poor, highlighting the need for individualized strategies. Toward this goal, risk prediction models and molecular diagnostic tools have been developed, tailoring each step of risk assessment from diagnosis to treatment and clinical outcomes based on the individual's clinical, epidemiological, and molecular profiles. These approaches hold increasing promise for delivering a new paradigm to maximize the efficiency of cancer surveillance and efficacy of treatment. However, they require stringent study design, methodology development, comprehensive assessment of biomarkers and risk factors, and extensive validation to ensure their overall usefulness for clinical translation. In the current study, the authors conducted a systematic review using breast cancer as an example and provide general guidelines for risk prediction models and molecular diagnostic tools, including development, assessment, and validation. © 2013 American Cancer Society.

  17. 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.

  18. Effects of Computer-Based Diagnostic Instruction and Non-Diagnostic Instruction on Laboratory Achievement in General Science.

    Science.gov (United States)

    McKenzie, Danny L.; Karnau, Sally A.

    The effects of computer-based diagnostic testing on the laboratory achievement of 91 preservice elementary teachers were assessed. These teachers were enrolled in one of four laboratory sections of a general science course. Intact classes were randomly assigned to one of two treatment groups. All students completed the same laboratory activities…

  19. A diagnostic model to estimate winds and small-scale drag from Mars Observer PMIRR data

    Science.gov (United States)

    Barnes, J. R.

    1993-01-01

    Theoretical and modeling studies indicate that small-scale drag due to breaking gravity waves is likely to be of considerable importance for the circulation in the middle atmospheric region (approximately 40-100 km altitude) on Mars. Recent earth-based spectroscopic observations have provided evidence for the existence of circulation features, in particular, a warm winter polar region, associated with gravity wave drag. Since the Mars Observer PMIRR experiment will obtain temperature profiles extending from the surface up to about 80 km altitude, it will be extensively sampling middle atmospheric regions in which gravity wave drag may play a dominant role. Estimating the drag then becomes crucial to the estimation of the atmospheric winds from the PMIRR-observed temperatures. An interative diagnostic model based upon one previously developed and tested with earth satellite temperature data will be applied to the PMIRR measurements to produce estimates of the small-scale zonal drag and three-dimensional wind fields in the Mars middle atmosphere. This model is based on the primitive equations, and can allow for time dependence (the time tendencies used may be based upon those computed in a Fast Fourier Mapping procedure). The small-scale zonal drag is estimated as the residual in the zonal momentum equation; the horizontal winds having first been estimated from the meridional momentum equation and the continuity equation. The scheme estimates the vertical motions from the thermodynamic equation, and thus needs estimates of the diabatic heating based upon the observed temperatures. The latter will be generated using a radiative model. It is hoped that the diagnostic scheme will be able to produce good estimates of the zonal gravity wave drag in the Mars middle atmosphere, estimates that can then be used in other diagnostic or assimilation efforts, as well as more theoretical studies.

  20. 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

  1. 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.

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

    Science.gov (United States)

    Gu, Peiqin; Chen, Huajun; Yu, Tong

    2013-01-01

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

  3. A diagnostic approach to constraining flow partitioning in hydrologic models using a multiobjective optimization framework

    Science.gov (United States)

    Shafii, Mahyar; Basu, Nandita; Craig, James R.; Schiff, Sherry L.; Van Cappellen, Philippe

    2017-04-01

    Hydrologic models are often tasked with replicating historical hydrographs but may do so without accurately reproducing the internal hydrological functioning of the watershed, including the flow partitioning, which is critical for predicting solute movement through the catchment. Here we propose a novel partitioning-focused calibration technique that utilizes flow-partitioning coefficients developed based on the pioneering work of L'vovich (1979). Our hypothesis is that inclusion of the L'vovich partitioning relations in calibration increases model consistency and parameter identifiability and leads to superior model performance with respect to flow partitioning than using traditional hydrological signatures (e.g., flow duration curve indices) alone. The L'vovich approach partitions the annual precipitation into four components (quick flow, soil wetting, slow flow, and evapotranspiration) and has been shown to work across a range of climatic and landscape settings. A new diagnostic multicriteria model calibration methodology is proposed that first quantifies four calibration measures for watershed functions based on the L'vovich theory, and then utilizes them as calibration criteria. The proposed approach is compared with a traditional hydrologic signature-based calibration for two conceptual bucket models. Results reveal that the proposed approach not only improves flow partitioning in the model compared to signature-based calibration but is also capable of diagnosing flow-partitioning inaccuracy and suggesting relevant model improvements. Furthermore, the proposed partitioning-based calibration approach is shown to increase parameter identifiability. This model calibration approach can be readily applied to other models.

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

    International Nuclear Information System (INIS)

    Yoshikawa, Shinji; Endou, Akira; Kitamura, Yoshinobu; Sasajima, Munehiko; Ikeda, Mitsuru; Mizoguchi, Riichiro.

    1994-01-01

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

  5. Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

    Science.gov (United States)

    Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

    2018-01-01

    The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

  6. 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...

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

    Directory of Open Access Journals (Sweden)

    Athanasios Tsalatsanis

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

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

    Science.gov (United States)

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

    2015-01-01

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

  9. 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...

  10. Smartphone-Based Food Diagnostic Technologies: A Review

    Directory of Open Access Journals (Sweden)

    Giovanni Rateni

    2017-06-01

    Full Text Available A new generation of mobile sensing approaches offers significant advantages over traditional platforms in terms of test speed, control, low cost, ease-of-operation, and data management, and requires minimal equipment and user involvement. The marriage of novel sensing technologies with cellphones enables the development of powerful lab-on-smartphone platforms for many important applications including medical diagnosis, environmental monitoring, and food safety analysis. This paper reviews the recent advancements and developments in the field of smartphone-based food diagnostic technologies, with an emphasis on custom modules to enhance smartphone sensing capabilities. These devices typically comprise multiple components such as detectors, sample processors, disposable chips, batteries and software, which are integrated with a commercial smartphone. One of the most important aspects of developing these systems is the integration of these components onto a compact and lightweight platform that requires minimal power. To date, researchers have demonstrated several promising approaches employing various sensing techniques and device configurations. We aim to provide a systematic classification according to the detection strategy, providing a critical discussion of strengths and weaknesses. We have also extended the analysis to the food scanning devices that are increasingly populating the Internet of Things (IoT market, demonstrating how this field is indeed promising, as the research outputs are quickly capitalized on new start-up companies.

  11. Smartphone-Based Food Diagnostic Technologies: A Review.

    Science.gov (United States)

    Rateni, Giovanni; Dario, Paolo; Cavallo, Filippo

    2017-06-20

    A new generation of mobile sensing approaches offers significant advantages over traditional platforms in terms of test speed, control, low cost, ease-of-operation, and data management, and requires minimal equipment and user involvement. The marriage of novel sensing technologies with cellphones enables the development of powerful lab-on-smartphone platforms for many important applications including medical diagnosis, environmental monitoring, and food safety analysis. This paper reviews the recent advancements and developments in the field of smartphone-based food diagnostic technologies, with an emphasis on custom modules to enhance smartphone sensing capabilities. These devices typically comprise multiple components such as detectors, sample processors, disposable chips, batteries and software, which are integrated with a commercial smartphone. One of the most important aspects of developing these systems is the integration of these components onto a compact and lightweight platform that requires minimal power. To date, researchers have demonstrated several promising approaches employing various sensing techniques and device configurations. We aim to provide a systematic classification according to the detection strategy, providing a critical discussion of strengths and weaknesses. We have also extended the analysis to the food scanning devices that are increasingly populating the Internet of Things (IoT) market, demonstrating how this field is indeed promising, as the research outputs are quickly capitalized on new start-up companies.

  12. Medical diagnostic system based on image receivers of various spectral ranges

    Science.gov (United States)

    Siniakova, Olga G.; Ishmuhametov, Airat I.

    1996-04-01

    The medical diagnostics is one of the most important spheres of application of measuring and diagnostic systems based on introscopy methods. The modern medical introscopy diagnostics has in its arsenal many various devices using x-ray radiation with energy from 10 to 100 keV (roentgenological diagnostics, x-ray computer tomography), gamma radiation of radionuclides with energy 10 - 300 keV (radionuclide diagnostics), infrared radiation of human body (thermovision), optical radiation range (endoscopic diagnostics). The application of high- frequency sound fluctuations (ultrasonography) is also effective for tasks of medical diagnostics. The microwave sources based on nuclear magnetic resonance (magnetic resonance imaging) are used for reception the images of internal structures of human body. The prompt development of modern medical introscopy diagnostics observable in last years is connected first of all with wide application of computer facilities for receiving, processing, restoration and analysis of images. It gives the additional opportunity to increase the reliability, accuracy, sensitivity and timeliness of diagnostic decisions. The images received both by scintillation gamma camera and by specialized x-ray or gamma radiation video camera based on charge- coupled devices can be used for evaluation of structural and functional state of vital organs and systems. One of the main tasks at development of medical diagnostic systems is the reduction of optical image to form that maximally facilitates its analysis to the doctor. The article considers the diagnostic system oriented on receiving, processing and evaluating data of radionuclide imaging studies.

  13. Towards a blood-based diagnostic panel for bipolar disorder

    NARCIS (Netherlands)

    F. Haenisch (Frieder); J.D. Cooper (Jason); A. Reif (Andreas); S. Kittel-Schneider (Sarah); J. Steiner (Johann); F.M. Leweke (Marcus); M. Rothermundt (Matthias); N.J.M. van Beveren (Nico); B. Crespo-Facorro (Benedicto); D. Niebuhr (David); D. Cowan (David); N. Weber (Natalya); R.H. Yolken (Robert); B.W.J.H. Penninx (Brenda W.J.H.); S. Bahn (Sabine)

    2015-01-01

    markdownabstract_Background:_ Bipolar disorder (BD) is a costly, devastating and life shortening mental disorder that is often misdiagnosed, especially on initial presentation. Misdiagnosis frequently results in ineffective treatment. We investigated the utility of a biomarker panel as a diagnostic

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

    International Nuclear Information System (INIS)

    Naito, O.

    2010-01-01

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

  15. Development of genomic based diagnostics in various application domains

    DEFF Research Database (Denmark)

    Szallasi, Zoltan Imre

    2017-01-01

    We will review the revolution brought about by low cost next generation sequencing in a wide array of diagnostic and industrial applications with a special emphasis on computational requirements and big data challenges.......We will review the revolution brought about by low cost next generation sequencing in a wide array of diagnostic and industrial applications with a special emphasis on computational requirements and big data challenges....

  16. Fast infectious diseases diagnostics based on microfluidic biochip system

    Directory of Open Access Journals (Sweden)

    Qin Huang

    2017-03-01

    Full Text Available Molecular diagnostics is one of the most important tools currently in use for clinical pathogen detection due to its high sensitivity, specificity, and low consume of sample and reagent is keyword to low cost molecular diagnostics. In this paper, a sensitive DNA isothermal amplification method for fast clinical infectious diseases diagnostics at aM concentrations of DNA was developed using a polycarbonate (PC microfluidic chip. A portable confocal optical fluorescence detector was specifically developed for the microfluidic chip that was capable of highly sensitive real-time detection of amplified products for sequence-specific molecular identification near the optical diffraction limit with low background. The molecular diagnostics of Listeria monocytogenes with nucleic acid extracted from stool samples was performed at a minimum DNA template concentration of 3.65aM, and a detection limit of less than five copies of genomic DNA. Contrast to the general polymerase chain reaction (PCR at eppendorf (EP tube, the detection time in our developed method was reduced from 1.5h to 45min for multi-target parallel detection, the consume of sample and reagent was dropped from 25μL to 1.45μL. This novel microfluidic chip system and method can be used to develop a micro total analysis system as a clinically relevant pathogen molecular diagnostics method via the amplification of targets, with potential applications in biotechnology, medicine, and clinical molecular diagnostics.

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

    International Nuclear Information System (INIS)

    Lee, J.C.; Martin, W.R.

    1986-01-01

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

  18. An integrated stewardship model : Antimicrobial, infection prevention and diagnostic (AID)

    NARCIS (Netherlands)

    Dik, Jan-Willem H.; Poelman, Randy; Friedrich, Alexander W.; Panday, Prashant Nannan; Lo-Ten-Foe, Jerome R.; van Assen, Sander; van Gemert-Pijnen, Julia E. W. C.; Niesters, Hubert G. M.; Hendrix, Ron; Sinha, Bhanu

    2016-01-01

    Considering the threat of antimicrobial resistance and the difficulties it entails in treating infections, it is necessary to cross borders and approach infection management in an integrated, multidisciplinary manner. We propose the antimicrobial, infection prevention and diagnostic stewardship

  19. An integrated stewardship model: antimicrobial, infection prevention and diagnostic (AID)

    NARCIS (Netherlands)

    Dik, Jan-Willem H.; Poelman, Randy; Friedrich, Alexander W.; Panday, Prashant N.; Lo-Ten-Foe, Jerome R.; van Assen, Sander; van Gemert-Pijnen, Julia E.W.C.; Niesters, Hubert G.M.; Hendrix, Ron; Sinha, Bhanu

    2015-01-01

    Considering the threat of antimicrobial resistance and the difficulties it entails in treating infections, it is necessary to cross borders and approach infection management in an integrated, multidisciplinary manner. We propose the antimicrobial, infection prevention and diagnostic stewardship

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

    International Nuclear Information System (INIS)

    Janne d'Othee, Bertrand; Siebert, Uwe; Cury, Ricardo; Jadvar, Hossein; Dunn, Edward J.; Hoffmann, Udo

    2008-01-01

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

  1. Companion diagnostics

    DEFF Research Database (Denmark)

    Jørgensen, Jan Trøst; Hersom, Maria

    2016-01-01

    . Despite having discussed personalized medicine for more than a decade, we still see that most drug prescriptions for severe chronic diseases are largely based on 'trial and error' and not on solid biomarker data. However, with the advance of molecular diagnostics and a subsequent increased understanding...... of disease mechanisms, things are slowly changing. Within the last few years, we have seen an increasing number of predictive biomarker assays being developed to guide the use of targeted cancer drugs. This type of assay is called companion diagnostics and is developed in parallel to the drug using the drug-diagnostic...... co-development model. The development of companion diagnostics is a relatively new discipline and in this review, different aspects will be discussed including clinical and regulatory issues. Furthermore, examples of drugs, such as the ALK and PD-1/PD-L1 inhibitors, that have been approved recently...

  2. 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.

  3. Graphical and numerical diagnostic tools to assess suitability of multiple imputations and imputation models.

    Science.gov (United States)

    Bondarenko, Irina; Raghunathan, Trivellore

    2016-07-30

    Multiple imputation has become a popular approach for analyzing incomplete data. Many software packages are available to multiply impute the missing values and to analyze the resulting completed data sets. However, diagnostic tools to check the validity of the imputations are limited, and the majority of the currently available methods need considerable knowledge of the imputation model. In many practical settings, however, the imputer and the analyst may be different individuals or from different organizations, and the analyst model may or may not be congenial to the model used by the imputer. This article develops and evaluates a set of graphical and numerical diagnostic tools for two practical purposes: (i) for an analyst to determine whether the imputations are reasonable under his/her model assumptions without actually knowing the imputation model assumptions; and (ii) for an imputer to fine tune the imputation model by checking the key characteristics of the observed and imputed values. The tools are based on the numerical and graphical comparisons of the distributions of the observed and imputed values conditional on the propensity of response. The methodology is illustrated using simulated data sets created under a variety of scenarios. The examples focus on continuous and binary variables, but the principles can be used to extend methods for other types of variables. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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

    International Nuclear Information System (INIS)

    Korteniemi, A.

    1990-01-01

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

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

    DEFF Research Database (Denmark)

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

    2014-01-01

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

  6. 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.

  7. 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.

  8. 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. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  9. Simulation-based education leads to decreased use of fluoroscopy in diagnostic coronary angiography.

    Science.gov (United States)

    Prenner, Stuart B; Wayne, Diane B; Sweis, Ranya N; Cohen, Elaine R; Feinglass, Joe M; Schimmel, Daniel R

    2017-08-02

    The aim of this study is to determine whether simulation-based education (SBE) translates into reduced procedure time, radiation, and contrast use in actual clinical care. As a high volume procedure often performed by novice cardiology fellows, diagnostic coronary angiography represents an excellent target for SBE. Reports of SBE in interventional cardiology are limited and there is little understanding of the potential downstream clinical impact of these interventions. All diagnostic coronary angiograms performed at a single center between January 1, 2011 and June 30, 2015 were analyzed. Random effects linear regression models were used to compare outcomes between procedures performed by 12 cardiology fellows who underwent simulation-based training and those performed by 20 traditionally trained fellows. Thirty-two cardiology fellows performed 2,783 diagnostic coronary angiograms. Procedures performed by fellows trained with SBE were shorter (mean of 23.98 min vs. 24.94 min, P = 0.034) and were performed with decreased radiation (mean of 56,348 mGycm 2 vs. 66,120 mGycm 2 , P < 0.001). After controlling for year in training, procedure year, access site, and supervising attending physician, training on the simulator was independently associated with 117 fewer seconds of fluoroscopy time per procedure (P = 0.04). Diagnostic coronary angiography SBE is associated with decreased use of fluoroscopy in downstream clinical care. SBE may be a useful tool to reduce radiation exposure in the cardiac catheterization laboratory. © 2017 Wiley Periodicals, Inc.

  10. Diagnostic radiographic examinations in Saudi Arabia based on ...

    African Journals Online (AJOL)

    Variations in patient dose arising from a specific X-ray examination may emerge from complex causes, but in general, low peak kilovolt and high milli Amperes were associated with the higher doses. The results of this study will prove useful information for the formulation of NDRLs and also provide local diagnostic reference ...

  11. 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.

  12. 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…

  13. APPLIED DIAGNOSTIC MODULE FOR DETERMINING COGNITIVE MODEL PARAMETERS OF SUBJECTS OF EDUCATION IN AN ADAPTIVE ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    Anatoly N. Vetrov

    2017-01-01

    Full Text Available Abstract. Objectives To increase the functional efficiency of information and educational environments created by automated training systems by realising individually oriented formation of knowledge using adaptive generation of heterogeneous educational influences based on an innovative block of parametric cognitive models and a set of programs to support the automation of research tasks. Method System analysis and modeling of the information and educational environment. In the process of automating the diagnosis of the individual personality characteristics of the subject of education, each method of investigation determines the input: localisation of research method, name of block of questions (subtest, textual explanatory content, formulation of question and answer variants, nominal value of the time interval for displaying the formulation of the question, as well as the graphical accompaniment of a specific question and answers thereto. Results The applied diagnostic module acts as a component of the automated learning system with adaptation properties on the basis of the innovative block of parametric cognitive models. The training system implements the generation of an ordered sequence of informational and educational influences that reflect the content of the subject of a study. Conclusion The applied diagnostic module is designed to automate the study of physiological, psychological and linguistic parameters of the cognitive model of the subject of education to provide a systematic analysis of the information and educational environment and the realisation of adaptive generation of educational influences by using training automation approaches that allow the individual characteristics of trainees to be taken into account. 

  14. Using a web-based application to define the accuracy of diagnostic tests when the gold standard is imperfect.

    Directory of Open Access Journals (Sweden)

    Cherry Lim

    Full Text Available Estimates of the sensitivity and specificity for new diagnostic tests based on evaluation against a known gold standard are imprecise when the accuracy of the gold standard is imperfect. Bayesian latent class models (LCMs can be helpful under these circumstances, but the necessary analysis requires expertise in computational programming. Here, we describe open-access web-based applications that allow non-experts to apply Bayesian LCMs to their own data sets via a user-friendly interface.Applications for Bayesian LCMs were constructed on a web server using R and WinBUGS programs. The models provided (http://mice.tropmedres.ac include two Bayesian LCMs: the two-tests in two-population model (Hui and Walter model and the three-tests in one-population model (Walter and Irwig model. Both models are available with simplified and advanced interfaces. In the former, all settings for Bayesian statistics are fixed as defaults. Users input their data set into a table provided on the webpage. Disease prevalence and accuracy of diagnostic tests are then estimated using the Bayesian LCM, and provided on the web page within a few minutes. With the advanced interfaces, experienced researchers can modify all settings in the models as needed. These settings include correlation among diagnostic test results and prior distributions for all unknown parameters. The web pages provide worked examples with both models using the original data sets presented by Hui and Walter in 1980, and by Walter and Irwig in 1988. We also illustrate the utility of the advanced interface using the Walter and Irwig model on a data set from a recent melioidosis study. The results obtained from the web-based applications were comparable to those published previously.The newly developed web-based applications are open-access and provide an important new resource for researchers worldwide to evaluate new diagnostic tests.

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

    Science.gov (United States)

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

    2016-02-01

    The protozoan Neospora caninum is a primary infectious cause of abortion in cattle that causes significant economic losses worldwide. Because effective vaccines and licensed pharmacological treatments are currently unavailable, control measures rely on biosecurity and management practice. Serological diagnosis plays a crucial role in the identification of infected animals and several tests have been developed. However, owing to the particular dynamics of the host-parasite interaction and to the characteristics of the currently used diagnostic tools, a proportion of infected cattle may not be reliably identified, and can potentially undermine efforts towards the control of bovine neosporosis. Current diagnostic methods for N. caninum infection in cattle and the advances necessary to support effective control strategies are discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Flexible substrate-based devices for point-of-care diagnostics

    Science.gov (United States)

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

    2016-01-01

    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 their 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 at the POC. PMID:27344425

  17. Incremental Validity of Multidimensional Proficiency Scores from Diagnostic Classification Models: An Illustration for Elementary School Mathematics

    Science.gov (United States)

    Kunina-Habenicht, Olga; Rupp, André A.; Wilhelm, Oliver

    2017-01-01

    Diagnostic classification models (DCMs) hold great potential for applications in summative and formative assessment by providing discrete multivariate proficiency scores that yield statistically driven classifications of students. Using data from a newly developed diagnostic arithmetic assessment that was administered to 2032 fourth-grade students…

  18. A Plasma Edge Electron Density Diagnostic Based on a Doppler-free Measurement of Stark Broadening

    Science.gov (United States)

    Zafar, Abdullah; Martin, Elijah; Shannon, Steve

    2017-10-01

    Passive spectroscopic measurements of Stark broadening have been reliably used to determine electron density for decades. A low-density limit of 1e19 m-3 exists using these passive techniques due to Doppler and instrument broadening. At Oak Ridge National Laboratory, a novel diagnostic approach for measuring electron density using Stark broadening is currently under development and is capable of extending the low-density limit to 1e16 m-3 . The diagnostic is based on measuring the spectral line profile of a Balmer series transition using Doppler-free saturation spectroscopy, a laser-based absorption technique. The spectrum is then fit to a quantum mechanical model using the Explicit Zeeman Stark Spectral Simulator (EZSSS) code to extract the electron density. The increased sensitivity to the electron density is realized because Doppler-free saturation spectroscopy (DFSS) can greatly reduce the Doppler broadening and essentially eliminate the instrument broadening. DFSS has been successfully employed to measure spectral data in a magnetized (500-800 G), low temperature (5 eV), low density (1e17-1e18 m-3), He/H2 and He/CH4 plasma in the mTorr pressure range. Experimentally measured pi and sigma H-alpha spectra, fit using the EZSSS code, will be presented. A quantitative model to accurately predict crossover peaks and dips will also be given. This work was supported by the US. D.O.E. contract DE-AC05-00OR22725.

  19. Development of the Model of the System of Managerial Diagnostics of the Enterprise on the Basis of Improvement of Diagnostic Purposes

    Directory of Open Access Journals (Sweden)

    Grzegorz Pawlowski

    2017-11-01

    Full Text Available The purpose of the article is to develop a model of the system of managerial diagnostics of the enterprise on the basis of the improvement of diagnostic purposes. The developed model of the system of managerial diagnostics of the enterprise is a set of subjects (owners, managers, investors, specialists, etc., objects (management system, resources, technology, methods (a set of methods and means, business indicators and criteria (parameters that, when interacting, provide the achievement (efficient and effective of the diagnostic objectives of the system of the objectives of managerial diagnostics of the enterprise, taking into account the compliance of its competitive strategy of the state of the environment function of direct action (competitors, customers, suppliers, mediators, and other contact audiences in the context of improving the efficiency and developing the management. It is determined that the system of goals of the model of the system of managerial diagnostics of the enterprise (taking into account the ensuring of the compliance of the system of management with strategic goals and tactical tasks form the following key diagnostic objectives that require improvement on the basis of business indicators (parameters, namely: 1 diagnostics of the effectiveness of controlling the internal business processes of the enterprise; 2 diagnostics of the effectiveness of the typical organizational structure of enterprise management; 3 diagnostics of the efficiency of standardization of the work of linear and functional managers and specialists at the enterprise; 4 diagnostics of the enterprise in the areas of vocational education, labor activity and motivation, innovation work and social development; 5 diagnostics of the level of conflict in the team at the enterprise; 6 diagnostics of efficiency of use of information technologies in the management of the enterprise. The prospect of further research in this area is to improve the complex system of

  20. Advanced error diagnostics of the CMAQ and Chimere modelling systems within the AQMEII3 model evaluation framework

    Directory of Open Access Journals (Sweden)

    E. Solazzo

    2017-09-01

    Full Text Available The work here complements the overview analysis of the modelling systems participating in the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3 by focusing on the performance for hourly surface ozone by two modelling systems, Chimere for Europe and CMAQ for North America. The evaluation strategy outlined in the course of the three phases of the AQMEII activity, aimed to build up a diagnostic methodology for model evaluation, is pursued here and novel diagnostic methods are proposed. In addition to evaluating the base case simulation in which all model components are configured in their standard mode, the analysis also makes use of sensitivity simulations in which the models have been applied by altering and/or zeroing lateral boundary conditions, emissions of anthropogenic precursors, and ozone dry deposition. To help understand of the causes of model deficiencies, the error components (bias, variance, and covariance of the base case and of the sensitivity runs are analysed in conjunction with timescale considerations and error modelling using the available error fields of temperature, wind speed, and NOx concentration. The results reveal the effectiveness and diagnostic power of the methods devised (which remains the main scope of this study, allowing the detection of the timescale and the fields that the two models are most sensitive to. The representation of planetary boundary layer (PBL dynamics is pivotal to both models. In particular, (i the fluctuations slower than ∼ 1.5 days account for 70–85 % of the mean square error of the full (undecomposed ozone time series; (ii a recursive, systematic error with daily periodicity is detected, responsible for 10–20 % of the quadratic total error; (iii errors in representing the timing of the daily transition between stability regimes in the PBL are responsible for a covariance error as large as 9 ppb (as much as the standard deviation of the network

  1. 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/.

  2. Postscript: Making Important Distinctions--Diagnostic Models, Theoretical Models, and the Mnemonic Model of PTSD

    Science.gov (United States)

    Monroe, Scott M.; Mineka, Susan

    2008-01-01

    Our commentary was intended to stimulate discussion about what we perceive to be shortcomings of the mnemonic model and its research base, in the hope of shedding some light on key questions for understanding posttraumatic stress disorder (PTSD). In our view, Berntsen, Rubin, and Bohni have responded only to what they perceive to be shortcomings…

  3. 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

  4. Single-chip microcomputer based protection, diagnostic and recording system for longwall shearers

    Energy Technology Data Exchange (ETDEWEB)

    Heyduk, A.; Krasucki, F. (Politechnika Slaska, Gliwice (Poland). Katedra Elektryfikacji i Automatyzacji Gornictwa)

    1993-05-01

    Presents a concept of microcomputer-aided operation, protection, diagnostics and recording for shearer loaders. A two-stage mathematical model is suggested and explained. The model represents the thermal processes that determine the overcurrent protection of drive motors. Circuits for monitoring fuses, supply voltages, contacts, relays, contactors and electro-hydraulic distributors with the use of transoptors are shown. Recording characteristic operation parameters of a shearer loader during the 5 minutes before a failure is proposed. Protection, diagnosis and control functions are suggested as additional functions to the microcomputer-aided system of shearer loader control being developed at the Silesian Technical University. The system is based on the NECmicroPD 78310 microprocessor. 10 refs.

  5. Problems in detecting misfit of latent class models in diagnostic research without a gold standard were shown.

    Science.gov (United States)

    van Smeden, Maarten; Oberski, Daniel L; Reitsma, Johannes B; Vermunt, Jeroen K; Moons, Karel G M; de Groot, Joris A H

    2016-06-01

    The objective of this study was to evaluate the performance of goodness-of-fit testing to detect relevant violations of the assumptions underlying the criticized "standard" two-class latent class model. Often used to obtain sensitivity and specificity estimates for diagnostic tests in the absence of a gold reference standard, this model relies on assuming that diagnostic test errors are independent. When this assumption is violated, accuracy estimates may be biased: goodness-of-fit testing is often used to evaluate the assumption and prevent bias. We investigate the performance of goodness-of-fit testing by Monte Carlo simulation. The simulation scenarios are based on three empirical examples. Goodness-of-fit tests lack power to detect relevant misfit of the standard two-class latent class model at sample sizes that are typically found in empirical diagnostic studies. The goodness-of-fit tests that are based on asymptotic theory are not robust to the sparseness of data. A parametric bootstrap procedure improves the evaluation of goodness of fit in the case of sparse data. Our simulation study suggests that relevant violation of the local independence assumption underlying the standard two-class latent class model may remain undetected in empirical diagnostic studies, potentially leading to biased estimates of sensitivity and specificity. Copyright © 2015 Elsevier Inc. All rights reserved.

  6. Bayesian modelling of multiple diagnostics at Wendelstein 7-X using the Minerva framework

    Science.gov (United States)

    Kwak, Sehyun; Svensson, Jakob; Bozhenkov, Sergey; Trimino Mora, Humberto; Hoefel, Udo; Pavone, Andrea; Krychowiak, Maciej; Langenberg, Andreas; Ghim, Young-Chul; W7-X Team Team

    2017-10-01

    Wendelstein 7-X (W7-X) is a large scale optimised stellarator designed for steady-state operation with fusion reactor relevant conditions. Consistent inference of physics parameters and their associated uncertainties requires the capability to handle the complexity of the entire system, including physics models of multiple diagnostics. A Bayesian model has been developed in the Minerva framework to infer electron temperature and density profiles from multiple diagnostics in a consistent way. Here, the physics models predict the data of multiple diagnostics in a joint Bayesian analysis. The electron temperature and density profiles are modelled by Gaussian processes with hyperparameters. Markov chain Monte Carlo methods explore the full posterior of electron temperature and density profiles as well as possible combinations of hyperparameters and calibration factors. This results in a profile inference with proper uncertainties reflecting both statistical error and the automatic calibration for diagnostics.

  7. Published diagnostic models safely excluded colorectal cancer in an independent primary care validation study

    NARCIS (Netherlands)

    Elias, Sjoerd G; Kok, Liselotte; Witteman, Ben J M; Goedhard, Jelle G; Romberg-Camps, Mariëlle J L; Muris, Jean W M; de Wit, Niek J; Moons, Karel G M

    OBJECTIVE: To validate published diagnostic models for their ability to safely reduce unnecessary endoscopy referrals in primary care patients suspected of significant colorectal disease. STUDY DESIGN AND SETTING: Following a systematic literature search, we independently validated the identified

  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. Refining process representation in high-resolution models of headwater catchments using internal catchment diagnostics

    Science.gov (United States)

    Kelleher, C.; McGlynn, B. L.; Wagener, T.

    2014-12-01

    As the complexity of the problems we seek to address with process-based models continues to increase, our approaches to improving confidence in our predictions must keep pace. Process-based, distributed models have been applied in headwater catchments to address many different objectives, all of which are linked by their reliance on the selection of a catchment-representative parameter set or sets. While these parameter sets are typically obtained through calibration to the streamflow hydrograph, it is widely acknowledged that there is often insufficient information in the hydrograph to effectively address parameter equifinality. Here, we suggest that optimal parameter sets can be obtained with an additional step in the calibration process that considers the spatial representation of internal catchment behavior (e.g. space-time distributions of evapotranspiration, water table depth, presence of overland flow, soil water). Modeled internal catchment behavior is an under-utilized but valuable source of information for separating plausible from unlikely model scenarios. We demonstrate how spatial patterns of hydrologic states and fluxes across annual, seasonal, and event time scales can improve the calibration process and reduce likely parameter sets. Our approach is applied to an extensively monitored headwater catchment in Tenderfoot Creek Experimental Forest in central Montana, simulated using the Distributed Hydrology-Soil-Vegetation Model. Consideration of spatial diagnostics in the calibration process has great potential to ensure a holistic representation of catchment dynamics as well as to increase confidence in conclusions from these types of modeling applications.

  10. 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.

  11. A Laser-Based Diagnostic Suite for Hypersonic Test Facilities, Phase II

    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....

  12. A Laser-Based Diagnostic Suite for Hypersonic Test Facilities, Phase I

    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....

  13. Paper-based smart microfluidics for education and low-cost diagnostics

    CSIR Research Space (South Africa)

    Smith, S

    2015-11-01

    Full Text Available to develop PoC diagnostic solutions. Specifically, the emerging field of paper-based microfluidics, with advantages such as low-cost, disposability and minimal external equipment requirements, provides unique opportunities for addressing healthcare issues...

  14. 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.

  15. 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

    or on the polymerase chain reaction (PCR) [1]. In this work we demonstrate detection of DNA coils formed from a Vibrio Cholerae DNA target at pM concentrations using a novel opto-magnetic approach exploiting the dynamic collective behavior of magnetic nanobeads. The technique relies on measurements of the light...... 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...... and isothermal rolling circle amplification from Vibrio cholerae DNA. The detection method is shown in Figure 1. MNBs which specifically bind to the micrometric sized DNA coil cannot rotate under the field action as free beads and form chains; this results in a strongly modified opto-magnetic signal. As a core...

  16. 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.

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

    International Nuclear Information System (INIS)

    Sonoda, Y.; Kanemoto, S.; Imaruoka, H.

    1990-01-01

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

  18. Web Based VRML Modelling

    NARCIS (Netherlands)

    Kiss, S.; Sarfraz, M.

    2004-01-01

    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

  19. Web Based VRML Modelling

    NARCIS (Netherlands)

    Kiss, S.; Banissi, E.; Khosrowshahi, F.; Sarfraz, M.; Ursyn, A.

    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

  20. Diagnostic models of the pre-test probability of stable coronary artery disease: A systematic review

    Directory of Open Access Journals (Sweden)

    Ting He

    Full Text Available A comprehensive search of PubMed and Embase was performed in January 2015 to examine the available literature on validated diagnostic models of the pre-test probability of stable coronary artery disease and to describe the characteristics of the models. Studies that were designed to develop and validate diagnostic models of pre-test probability for stable coronary artery disease were included. Data regarding baseline patient characteristics, procedural characteristics, modeling methods, metrics of model performance, risk of bias, and clinical usefulness were extracted. Ten studies involving the development of 12 models and two studies focusing on external validation were identified. Seven models were validated internally, and seven models were validated externally. Discrimination varied between studies that were validated internally (C statistic 0.66-0.81 and externally (0.49-0.87. Only one study presented reclassification indices. The majority of better performing models included sex, age, symptoms, diabetes, smoking, and hyperlipidemia as variables. Only two diagnostic models evaluated the effects on clinical decision making processes or patient outcomes. Most diagnostic models of the pre-test probability of stable coronary artery disease have had modest success, and very few present data regarding the effects of these models on clinical decision making processes or patient outcomes.

  1. Paper based diagnostics for personalized health care: Emerging technologies and commercial aspects.

    Science.gov (United States)

    Mahato, Kuldeep; Srivastava, Ananya; Chandra, Pranjal

    2017-10-15

    Personalized health care (PHC) is being appreciated globally to combat clinical complexities underlying various metabolic or infectious disorders including diabetes, cardiovascular, communicable diseases etc. Effective diagnoses majorly depend on initial identification of the causes which are nowadays being practiced in disease-oriented approach, where personal health profile is often overlooked. The adoption of PHC has shown significantly improved diagnoses in various conditions including emergency, ambulatory, and remote area. PHC includes personalized health monitoring (PHM), which is its integral part and may provide valuable information's on various clinical conditions. In PHC, bio-fluids are analyzed using various diagnostic devices including lab based equipment and biosensors. Among all types of biosensing systems, paper based biosensors are commercially attracted due to its portability, easy availability, cheaper manufacturing cost, and transportability. Not only these, various intrinsic properties of paper has facilitated the development of paper based miniaturized sensors, which has recently gained ASSURED (Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment free, Deliverable to all end-users) status for point of care diagnosis in miniaturized settings. In this review, importance of paper based biosensors and their compatibility for affordable and low cost diagnostics has been elaborated with various examples. Limitations and strategies to overcome the challenges of paper biosensor have also been discussed. We have provided elaborated tables which describe the types, model specifications, sensing mechanisms, target biomarkers, and analytical performance of the paper biosensors with their respective applications in real sample matrices. Different commercial aspects of paper biosensor have also been explained using SWOT (Strength, Weakness, Opportunities, Threats) analysis. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. Coronary Heart Disease Preoperative Gesture Interactive Diagnostic System Based on Augmented Reality.

    Science.gov (United States)

    Zou, Yi-Bo; Chen, Yi-Min; Gao, Ming-Ke; Liu, Quan; Jiang, Si-Yu; Lu, Jia-Hui; Huang, Chen; Li, Ze-Yu; Zhang, Dian-Hua

    2017-08-01

    Coronary heart disease preoperative diagnosis plays an important role in the treatment of vascular interventional surgery. Actually, most doctors are used to diagnosing the position of the vascular stenosis and then empirically estimating vascular stenosis by selective coronary angiography images instead of using mouse, keyboard and computer during preoperative diagnosis. The invasive diagnostic modality is short of intuitive and natural interaction and the results are not accurate enough. Aiming at above problems, the coronary heart disease preoperative gesture interactive diagnostic system based on Augmented Reality is proposed. The system uses Leap Motion Controller to capture hand gesture video sequences and extract the features which that are the position and orientation vector of the gesture motion trajectory and the change of the hand shape. The training planet is determined by K-means algorithm and then the effect of gesture training is improved by multi-features and multi-observation sequences for gesture training. The reusability of gesture is improved by establishing the state transition model. The algorithm efficiency is improved by gesture prejudgment which is used by threshold discriminating before recognition. The integrity of the trajectory is preserved and the gesture motion space is extended by employing space rotation transformation of gesture manipulation plane. Ultimately, the gesture recognition based on SRT-HMM is realized. The diagnosis and measurement of the vascular stenosis are intuitively and naturally realized by operating and measuring the coronary artery model with augmented reality and gesture interaction techniques. All of the gesture recognition experiments show the distinguish ability and generalization ability of the algorithm and gesture interaction experiments prove the availability and reliability of the system.

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

    International Nuclear Information System (INIS)

    Viljoen, G.J.; Romito, M.; Kara, P.D.

    2005-01-01

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

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

    OpenAIRE

    Kontić Ljiljana

    2012-01-01

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

  5. 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

  6. Behavior of gadolinium-based diagnostics in water treatment

    International Nuclear Information System (INIS)

    Cyris, Maike

    2013-01-01

    , 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 -1 )(L μmol -1 ) 1/n for Gd-BT-DO3A, on Chemviron RD 90 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 -1 s -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 determinations (rate constants > 10 9 M -1 s -1

  7. 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. Published by Elsevier Inc.

  8. What's in a Name? Health Care Providers' Perceptions of Pediatric Pain Patients Based on Diagnostic Labels.

    Science.gov (United States)

    Betsch, Taylor A; Gorodzinsky, Ayala Y; Finley, G A; Sangster, Michael; Chorney, Jill

    2017-08-01

    Diagnostic labels can help patients better understand their symptoms and can influence providers' treatment planning and patient interactions. Recurrent pain is common in childhood; however, there are various diagnostic labels used. The objective of this study was to evaluate the influence of diagnostic labels on pediatric health care providers' perceptions of pediatric chronic pain patients. Using an online survey, providers were randomly assigned to 1 of 2 vignette conditions (differing only in diagnostic label provided) and completed questionnaires about their perceptions of the vignette patient. Responses from 58 participants were analyzed. The 2 groups, based on diagnostic conditions used (fibromyalgia and chronic widespread pain) did not differ significantly on general demographics and health care providers' perceptions of the patient. Perceived origin of the pain influenced providers' perceptions; pain of a perceived medical origin was negatively correlated with stigmatization and positively correlated with sympathy. Perceived psychological origin was positively correlated with stigmatization and providers' age. Health care providers' perceptions of children's pain are more likely influenced by the presumed etiology rather than the diagnostic label used. Pain believed to be more medically based was associated with more positive reactions from providers (ie, less stigmatization). Older providers in particular perceived the patient more negatively if they believe the pain to be psychologically based. The findings of this pediatric study replicated findings from adult literature on chronic pain, suggesting that children and adults are subject to negative perceptions from health care providers when the providers believe the pain to be psychological in origin.

  9. Model Based Temporal Reasoning

    Science.gov (United States)

    Rabin, Marla J.; Spinrad, Paul R.; Fall, Thomas C.

    1988-03-01

    Systems that assess the real world must cope with evidence that is uncertain, ambiguous, and spread over time. Typically, the most important function of an assessment system is to identify when activities are occurring that are unusual or unanticipated. Model based temporal reasoning addresses both of these requirements. The differences among temporal reasoning schemes lies in the methods used to avoid computational intractability. If we had n pieces of data and we wanted to examine how they were related, the worst case would be where we had to examine every subset of these points to see if that subset satisfied the relations. This would be 2n, which is intractable. Models compress this; if several data points are all compatible with a model, then that model represents all those data points. Data points are then considered related if they lie within the same model or if they lie in models that are related. Models thus address the intractability problem. They also address the problem of determining unusual activities if the data do not agree with models that are indicated by earlier data then something out of the norm is taking place. The models can summarize what we know up to that time, so when they are not predicting correctly, either something unusual is happening or we need to revise our models. The model based reasoner developed at Advanced Decision Systems is thus both intuitive and powerful. It is currently being used on one operational system and several prototype systems. It has enough power to be used in domains spanning the spectrum from manufacturing engineering and project management to low-intensity conflict and strategic assessment.

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

    International Nuclear Information System (INIS)

    Raval, Jayesh V.; Purohit, Shishir; Joisa, Y. Shankara

    2015-01-01

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

  11. Refining multi-model projections of temperature extremes by evaluation against land–atmosphere coupling diagnostics

    Directory of Open Access Journals (Sweden)

    S. Sippel

    2017-05-01

    , the differences between projected and present-day climate extremes are affected to a lesser extent by the applied constraint, i.e. projected changes are reduced locally by around 0.5 to 1 °C – but this remains a local effect in regions that are highly sensitive to land–atmosphere coupling. In summary, our approach offers a physically consistent, diagnostic-based avenue to evaluate multi-model ensembles and subsequently reduce model biases in simulated and projected extreme temperatures.

  12. Refining multi-model projections of temperature extremes by evaluation against land-atmosphere coupling diagnostics

    Science.gov (United States)

    Sippel, Sebastian; Zscheischler, Jakob; Mahecha, Miguel D.; Orth, Rene; Reichstein, Markus; Vogel, Martha; Seneviratne, Sonia I.

    2017-05-01

    and present-day climate extremes are affected to a lesser extent by the applied constraint, i.e. projected changes are reduced locally by around 0.5 to 1 °C - but this remains a local effect in regions that are highly sensitive to land-atmosphere coupling. In summary, our approach offers a physically consistent, diagnostic-based avenue to evaluate multi-model ensembles and subsequently reduce model biases in simulated and projected extreme temperatures.

  13. 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

  14. Scalable Topic Modeling: Online Learning, Diagnostics, and Recommendation

    Science.gov (United States)

    2017-03-01

    ideas (recommendation). We went beyond the scope of the proposal in several ways, exploring applications as diverse as neuroscience, sociology , and...DiMaggio, M. Nag, and D. Blei. Exploiting affinities between topic modeling and the sociological perspective on culture: Application to newspaper...coverage of U.S. government arts funding. Poetics, 41:6, 2013. 8. D. Blei. Topic modeling and digital humanities. Journal of Digital Humanities, 2(1), 2013

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

    Science.gov (United States)

    Tantra, Ratna; van Heeren, Henne

    2013-06-21

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

  16. 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.

  17. Practical Steps for Informing Literacy Instruction: A Diagnostic Decision-Making Model.

    Science.gov (United States)

    Kibby, Michael W.

    This monograph presents a diagnostic decision-making model for reading, elementary, and special education teachers to use as a guide in assessing and evaluating students' reading abilities to design and provide more appropriate reading instruction. The model in the monograph gives an overall perspective or gestalt of the components and strategies…

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

    DEFF Research Database (Denmark)

    Canonica, Giorgio Walter; Ansotegui, Ignacio J; Pawankar, Ruby

    2013-01-01

    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...... 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...

  19. Integration of Diagnostic Microbiology in a Model of Total Laboratory Automation.

    Science.gov (United States)

    Da Rin, Giorgio; Zoppelletto, Maira; Lippi, Giuseppe

    2016-02-01

    Although automation has become widely utilized in certain areas of diagnostic testing, its adoption in diagnostic microbiology has proceeded much more slowly. To describe our real-world experience of integrating an automated instrument for diagnostic microbiology (Walk-Away Specimen Processor, WASPLab) within a model of total laboratory automation (TLA). The implementation process was divided into 2 phases. The former period, lasting approximately 6 weeks, entailed the installation of the WASPLab processor to operate as a stand-alone instrumentation, whereas the latter, lasting approximately 2 weeks, involved physical connection of the WASPLab with the automation. Using the WASPLab instrument in conjunction with the TLA model, we obtained a time savings equivalent to the work of 1.2 full-time laboratory technicians for diagnostic microbiology. The connection of WASPLab to TLA allowed its management by a generalist or clinical chemistry technician, with no need for microbiology skills on the part of either worker. Hence, diagnostic microbiology could be performed by the staff that is already using the TLA, extending their activities to include processing urgent clinical chemistry and hematology specimens. The time to result was also substantially improved. According to our experience, using the WASPLab instrument as part of a TLA in diagnostic microbiology holds great promise for optimizing laboratory workflow and improving the quality of testing. © American Society for Clinical Pathology, 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  20. Magnetic-particle-sensing based diagnostic protocols and applications.

    Science.gov (United States)

    Takamura, Tsukasa; Ko, Pil Ju; Sharma, Jaiyam; Yukino, Ryoji; Ishizawa, Shunji; Sandhu, Adarsh

    2015-06-04

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

  1. Information matrix estimation procedures for cognitive diagnostic models.

    Science.gov (United States)

    Liu, Yanlou; Xin, Tao; Andersson, Björn; Tian, Wei

    2018-03-06

    Two new methods to estimate the asymptotic covariance matrix for marginal maximum likelihood estimation of cognitive diagnosis models (CDMs), the inverse of the observed information matrix and the sandwich-type estimator, are introduced. Unlike several previous covariance matrix estimators, the new methods take into account both the item and structural parameters. The relationships between the observed information matrix, the empirical cross-product information matrix, the sandwich-type covariance matrix and the two approaches proposed by de la Torre (2009, J. Educ. Behav. Stat., 34, 115) are discussed. Simulation results show that, for a correctly specified CDM and Q-matrix or with a slightly misspecified probability model, the observed information matrix and the sandwich-type covariance matrix exhibit good performance with respect to providing consistent standard errors of item parameter estimates. However, with substantial model misspecification only the sandwich-type covariance matrix exhibits robust performance. © 2018 The British Psychological Society.

  2. A predictive diagnostic model using multiparametric MRI for differentiating uterine carcinosarcoma from carcinoma of the uterine corpus.

    Science.gov (United States)

    Kamishima, Yuki; Takeuchi, Mitsuru; Kawai, Tatsuya; Kawaguchi, Takatsune; Yamaguchi, Ken; Takahashi, Naoki; Ito, Masato; Arakawa, Toshinao; Yamamoto, Akiko; Suzuki, Kazushi; Ogawa, Masaki; Takeuchi, Moe; Shibamoto, Yuta

    2017-08-01

    To construct a diagnostic model for differentiating carcinosarcoma from carcinoma of the uterus. Twenty-six patients with carcinosarcomas and 26 with uterine corpus carcinomas constituted a derivation cohort. The following nine MRI features of the tumors were evaluated: inhomogeneity, predominant signal intensity, presence of hyper- and hypointense areas, conspicuity of tumor margin, cervical canal extension on T2WI, presence of hyperintense areas on T1WI, contrast defect area volume percentage, and degree of enhancement. Two predictive models-with and without contrast-were constructed using multivariate logistic regression analysis. Fifteen other patients with carcinosarcomas and 30 patients with carcinomas constituted a validation cohort. The sensitivity and specificity of each model for the validation cohort were calculated. Inhomogeneity, predominant signal intensity on T2WI, and presence of hyperintense areas on T1WI were significant predictors in the unenhanced-MRI-based model. Presence of hyperintensity on T1WI, contrast defect area volume percentage, and degree of enhancement were significant predictors in the enhanced-MRI-based model. The sensitivity/specificity of unenhanced MRI were 87/73 and 87/70% according to reviewer 1 and 2, respectively. The sensitivity/specificity of the enhanced-MRI-based model were 87/70% according to both reviewers. Our diagnostic models can differentiate carcinosarcoma from carcinoma of the uterus with high sensitivity and moderate specificity.

  3. 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...

  4. Operative and diagnostic hysteroscopy: A novel learning model combining new animal models and virtual reality simulation.

    Science.gov (United States)

    Bassil, Alfred; Rubod, Chrystèle; Borghesi, Yves; Kerbage, Yohan; Schreiber, Elie Servan; Azaïs, Henri; Garabedian, Charles

    2017-04-01

    Hysteroscopy is one of the most common gynaecological procedure. Training for diagnostic and operative hysteroscopy can be achieved through numerous previously described models like animal models or virtual reality simulation. We present our novel combined model associating virtual reality and bovine uteruses and bladders. End year residents in obstetrics and gynaecology attended a full day workshop. The workshop was divided in theoretical courses from senior surgeons and hands-on training in operative hysteroscopy and virtual reality Essure ® procedures using the EssureSim™ and Pelvicsim™ simulators with multiple scenarios. Theoretical and operative knowledge was evaluated before and after the workshop and General Points Averages (GPAs) were calculated and compared using a Student's T test. GPAs were significantly higher after the workshop was completed. The biggest difference was observed in operative knowledge (0,28 GPA before workshop versus 0,55 after workshop, pvirtual reality simulation is an efficient model not described before. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Modeling and experimental diagnostics in polymer electrolyte fuel cells

    Science.gov (United States)

    Springer, T. E.; Wilson, M. S.; Gottesfeld, S.

    1993-12-01

    This paper presents a fit between model and experiments for well-humidified polymer electrolyte fuel cells operated to maximum current density with a range of cathode gas compositions. The model considers, in detail, losses caused by: (1) interfacial kinetics at the Pt/ionomer interface; (2) gas-transport and ionic-conductivity limitations in the catalyst layer; and (3) gas-transport limitations in the cathode backing. Our experimental data were collected with cells that utilized thin-film catalyst layers bonded directly to the membrane, and a separate catalyst-free hydrophobic backing layer. This structure allows a clearer resolution of the processes taking place in each of these distinguishable parts of the cathode. In our final comparison of model predictions with the experimental data, we stress the simultaneous fit of a family of complete polarization curves obtained for gas compositions ranging from 5 atoms O2 to a mixture of 5% O2 in N2, employing in each case the same model parameters for interracial kinetics, catalyst-layer transport, and backing-layer transport. This approach allowed us to evaluate losses in the cathode backing and in the cathode catalyst layer, and thus identify the improvements required to enhance the performance of air cathodes in polymer electrolyte fuel cells. Finally, we show that effects of graded depletion in oxygen along the gas flow channel can be accurately modeled using a uniform effective oxygen concentration in the flow channel, equal to the average of inlet and exit concentrations. This approach has enabled simplified and accurate consideration of oxygen utilization effects.

  6. MicroTCA based Platform for advanced particle accelerators diagnostics

    CERN Document Server

    Juszczyk, Bartłomiej

    2014-01-01

    All over the world there are many research centers that are conducting researches with use of particle accelerators. Thanks to various experiments we could better understand surrounding world. But, there are still a lot of unknowns to explore which science needs better instruments. One of these tools are measurement systems. Unfortunately currently used solutions do not provide sufficient performance to satisfy growing needs. This implies the search for new solutions. One of such solution is a modern uTCA architecture. In this document an open source project of a base card (AFC -AMC to FMC carrier board) based on this standard has been described. This card is equipped with two FMC connectors, which allow to connect wide variety of extension cards. In combination with a powerful FPGA device this card is an universal base circuit for variety of projects. Among the others it allows to implement algorithms which are collecting data from fast ADCs and to process these data. Moreover the applied uTCA architecture p...

  7. Comparison among cognitive diagnostic models for the TIMSS 2007 fourth grade mathematics assessment.

    Science.gov (United States)

    Yamaguchi, Kazuhiro; Okada, Kensuke

    2018-01-01

    A variety of cognitive diagnostic models (CDMs) have been developed in recent years to help with the diagnostic assessment and evaluation of students. Each model makes different assumptions about the relationship between students' achievement and skills, which makes it important to empirically investigate which CDMs better fit the actual data. In this study, we examined this question by comparatively fitting representative CDMs to the Trends in International Mathematics and Science Study (TIMSS) 2007 assessment data across seven countries. The following two major findings emerged. First, in accordance with former studies, CDMs had a better fit than did the item response theory models. Second, main effects models generally had a better fit than other parsimonious or the saturated models. Related to the second finding, the fit of the traditional parsimonious models such as the DINA and DINO models were not optimal. The empirical educational implications of these findings are discussed.

  8. Comparison among cognitive diagnostic models for the TIMSS 2007 fourth grade mathematics assessment.

    Directory of Open Access Journals (Sweden)

    Kazuhiro Yamaguchi

    Full Text Available A variety of cognitive diagnostic models (CDMs have been developed in recent years to help with the diagnostic assessment and evaluation of students. Each model makes different assumptions about the relationship between students' achievement and skills, which makes it important to empirically investigate which CDMs better fit the actual data. In this study, we examined this question by comparatively fitting representative CDMs to the Trends in International Mathematics and Science Study (TIMSS 2007 assessment data across seven countries. The following two major findings emerged. First, in accordance with former studies, CDMs had a better fit than did the item response theory models. Second, main effects models generally had a better fit than other parsimonious or the saturated models. Related to the second finding, the fit of the traditional parsimonious models such as the DINA and DINO models were not optimal. The empirical educational implications of these findings are discussed.

  9. Does the interpersonal model apply across eating disorder diagnostic groups? A structural equation modeling approach.

    Science.gov (United States)

    Ivanova, Iryna V; Tasca, Giorgio A; Proulx, Geneviève; Bissada, Hany

    2015-11-01

    Interpersonal model has been validated with binge-eating disorder (BED), but it is not yet known if the model applies across a range of eating disorders (ED). The goal of this study was to investigate the validity of the interpersonal model in anorexia nervosa (restricting type; ANR and binge-eating/purge type; ANBP), bulimia nervosa (BN), BED, and eating disorder not otherwise specified (EDNOS). Data from a cross-sectional sample of 1459 treatment-seeking women diagnosed with ANR, ANBP, BN, BED and EDNOS were examined for indirect effects of interpersonal problems on ED psychopathology mediated through negative affect. Findings from structural equation modeling demonstrated the mediating role of negative affect in four of the five diagnostic groups. There were significant, medium to large (.239, .558), indirect effects in the ANR, BN, BED and EDNOS groups but not in the ANBP group. The results of the first reverse model of interpersonal problems as a mediator between negative affect and ED psychopathology were nonsignificant, suggesting the specificity of these hypothesized paths. However, in the second reverse model ED psychopathology was related to interpersonal problems indirectly through negative affect. This is the first study to find support for the interpersonal model of ED in a clinical sample of women with diverse ED diagnoses, though there may be a reciprocal relationship between ED psychopathology and relationship problems through negative affect. Negative affect partially explains the relationship between interpersonal problems and ED psychopathology in women diagnosed with ANR, BN, BED and EDNOS. Interpersonal psychotherapies for ED may be addressing the underlying interpersonal-affective difficulties, thereby reducing ED psychopathology. Copyright © 2015 Elsevier Inc. All rights reserved.

  10. Diagnostic accuracy of three-dimensional CT reconstruction and cephalometry for lateral skull base tumors.

    Science.gov (United States)

    Xie, X Z; Huo, X K

    2015-10-01

    To explore the diagnostic accuracy of three-dimensional CT reconstruction and cephalometry in lateral skull base tumors. Fifty-eight patients with lateral skull base tumors were randomly divided into control group (n = 29, examined with conventional diagnostic technique) or study group (n = 29, examined with three-dimensional CT reconstruction and cephalometry). The diagnostic accuracy, tumor distribution and image characteristics were compared between both patient groups. In control group, preoperative tumor diagnosis was consistent with intraoperative diagnosis in 20 patients, similar in 7 patients and discrepant in 2 patients. In study group, there were 24 consistent, 4 similar, and 1 discrepant diagnoses (p cephalometry provides accurate diagnosis of lateral skull base tumors, which is helpful for subsequent surgical treatment.

  11. Full Life Cycle of Data Analysis with Climate Model Diagnostic Analyzer (CMDA)

    Science.gov (United States)

    Lee, S.; Zhai, C.; Pan, L.; Tang, B.; Zhang, J.; Bao, Q.; Malarout, N.

    2017-12-01

    We have developed a system that supports the full life cycle of a data analysis process, from data discovery, to data customization, to analysis, to reanalysis, to publication, and to reproduction. The system called Climate Model Diagnostic Analyzer (CMDA) is designed to demonstrate that the full life cycle of data analysis can be supported within one integrated system for climate model diagnostic evaluation with global observational and reanalysis datasets. CMDA has four subsystems that are highly integrated to support the analysis life cycle. Data System manages datasets used by CMDA analysis tools, Analysis System manages CMDA analysis tools which are all web services, Provenance System manages the meta data of CMDA datasets and the provenance of CMDA analysis history, and Recommendation System extracts knowledge from CMDA usage history and recommends datasets/analysis tools to users. These four subsystems are not only highly integrated but also easily expandable. New datasets can be easily added to Data System and scanned to be visible to the other subsystems. New analysis tools can be easily registered to be available in the Analysis System and Provenance System. With CMDA, a user can start a data analysis process by discovering datasets of relevance to their research topic using the Recommendation System. Next, the user can customize the discovered datasets for their scientific use (e.g. anomaly calculation, regridding, etc) with tools in the Analysis System. Next, the user can do their analysis with the tools (e.g. conditional sampling, time averaging, spatial averaging) in the Analysis System. Next, the user can reanalyze the datasets based on the previously stored analysis provenance in the Provenance System. Further, they can publish their analysis process and result to the Provenance System to share with other users. Finally, any user can reproduce the published analysis process and results. By supporting the full life cycle of climate data analysis

  12. 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.

  13. 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.

  14. ETHERNET BASED EMBEDDED SYSTEM FOR FEL DIAGNOSTICS AND CONTROLS

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-10-24

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

  15. Modelling multiple thresholds in meta-analysis of diagnostic test accuracy studies

    Directory of Open Access Journals (Sweden)

    Susanne Steinhauser

    2016-08-01

    Full Text Available Abstract Background In meta-analyses of diagnostic test accuracy, routinely only one pair of sensitivity and specificity per study is used. However, for tests based on a biomarker or a questionnaire often more than one threshold and the corresponding values of true positives, true negatives, false positives and false negatives are known. Methods We present a new meta-analysis approach using this additional information. It is based on the idea of estimating the distribution functions of the underlying biomarker or questionnaire within the non-diseased and diseased individuals. Assuming a normal or logistic distribution, we estimate the distribution parameters in both groups applying a linear mixed effects model to the transformed data. The model accounts for across-study heterogeneity and dependence of sensitivity and specificity. In addition, a simulation study is presented. Results We obtain a summary receiver operating characteristic (SROC curve as well as the pooled sensitivity and specificity at every specific threshold. Furthermore, the determination of an optimal threshold across studies is possible through maximization of the Youden index. We demonstrate our approach using two meta-analyses of B type natriuretic peptide in heart failure and procalcitonin as a marker for sepsis. Conclusions Our approach uses all the available information and results in an estimation not only of the performance of the biomarker but also of the threshold at which the optimal performance can be expected.

  16. Evaluation of Diagnostic CO2 Flux and Transport Modeling in NU-WRF and GEOS-5

    Science.gov (United States)

    Kawa, S. R.; Collatz, G. J.; Tao, Z.; Wang, J. S.; Ott, L. E.; Liu, Y.; Andrews, A. E.; Sweeney, C.

    2015-12-01

    We report on recent diagnostic (constrained by observations) model simulations of atmospheric CO2 flux and transport using a newly developed facility in the NASA Unified-Weather Research and Forecast (NU-WRF) model. The results are compared to CO2 data (ground-based, airborne, and GOSAT) and to corresponding simulations from a global model that uses meteorology from the NASA GEOS-5 Modern Era Retrospective analysis for Research and Applications (MERRA). The objective of these intercomparisons is to assess the relative strengths and weaknesses of the respective models in pursuit of an overall carbon process improvement at both regional and global scales. Our guiding hypothesis is that the finer resolution and improved land surface representation in NU-WRF will lead to better comparisons with CO2 data than those using global MERRA, which will, in turn, inform process model development in global prognostic models. Initial intercomparison results, however, have generally been mixed: NU-WRF is better at some sites and times but not uniformly. We are examining the model transport processes in detail to diagnose differences in the CO2 behavior. These comparisons are done in the context of a long history of simulations from the Parameterized Chemistry and Transport Model, based on GEOS-5 meteorology and Carnegie Ames-Stanford Approach-Global Fire Emissions Database (CASA-GFED) fluxes, that capture much of the CO2 variation from synoptic to seasonal to global scales. We have run the NU-WRF model using unconstrained, internally generated meteorology within the North American domain, and with meteorological 'nudging' from Global Forecast System and North American Regional Reanalysis (NARR) in an effort to optimize the CO2 simulations. Output results constrained by NARR show the best comparisons to data. Discrepancies, of course, may arise either from flux or transport errors and compensating errors are possible. Resolving their interplay is also important to using the data in

  17. Lanthanide-based laser-induced phosphorescence for spray diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Voort, D. D. van der, E-mail: d.d.v.d.voort@tue.nl; Water, W. van de; Kunnen, R. P. J.; Clercx, H. J. H.; Heijst, G. J. F. van [Applied Physics Department, Eindhoven University of Technology, 5612 AZ Eindhoven (Netherlands); Maes, N. C. J.; Sweep, A. M.; Dam, N. J. [Mechanical Engineering Department, Eindhoven University of Technology, 5612 AZ Eindhoven (Netherlands); Lamberts, T. [Institute of Theoretical Chemistry, University of Stuttgart, D-70569 Stuttgart (Germany)

    2016-03-15

    Laser-induced phosphorescence (LIP) is a relatively recent and versatile development for studying flow dynamics. This work investigates certain lanthanide-based molecular complexes for their use in LIP for high-speed sprays. Lanthanide complexes in solutions have been shown to possess long phosphorescence lifetimes (∼1-2 ms) and to emit light in the visible wavelength range. In particular, europium and terbium complexes are investigated using fluorescence/phosphorescence spectrometry, showing that europium-thenoyltrifluoracetone-trioctylphosphineoxide (Eu-TTA-TOPO) can be easily and efficiently excited using a standard frequency-tripled Nd:YAG laser. The emitted spectrum, with maximum intensity at a wavelength of 614 nm, is shown not to vary strongly with temperature (293-383 K). The decay constant of the phosphorescence, while independent of ambient pressure, decreases by approximately 12 μs/K between 323 and 373 K, with the base level of the decay constant dependent on the used solvent. The complex does not luminesce in the gas or solid state, meaning only the liquid phase is visualized, even in an evaporating spray. By using an internally excited spray containing the phosphorescent complex, the effect of vaporization is shown through the decrease in measured intensity over the length of the spray, together with droplet size measurements using interferometric particle imaging. This study shows that LIP, using the Eu-TTA-TOPO complex, can be used with different solvents, including diesel surrogates. Furthermore, it can be easily handled and used in sprays to investigate spray breakup and evaporation.

  18. Lanthanide-based laser-induced phosphorescence for spray diagnostics

    Science.gov (United States)

    van der Voort, D. D.; Maes, N. C. J.; Lamberts, T.; Sweep, A. M.; van de Water, W.; Kunnen, R. P. J.; Clercx, H. J. H.; van Heijst, G. J. F.; Dam, N. J.

    2016-03-01

    Laser-induced phosphorescence (LIP) is a relatively recent and versatile development for studying flow dynamics. This work investigates certain lanthanide-based molecular complexes for their use in LIP for high-speed sprays. Lanthanide complexes in solutions have been shown to possess long phosphorescence lifetimes (˜1-2 ms) and to emit light in the visible wavelength range. In particular, europium and terbium complexes are investigated using fluorescence/phosphorescence spectrometry, showing that europium-thenoyltrifluoracetone-trioctylphosphineoxide (Eu-TTA-TOPO) can be easily and efficiently excited using a standard frequency-tripled Nd:YAG laser. The emitted spectrum, with maximum intensity at a wavelength of 614 nm, is shown not to vary strongly with temperature (293-383 K). The decay constant of the phosphorescence, while independent of ambient pressure, decreases by approximately 12 μs/K between 323 and 373 K, with the base level of the decay constant dependent on the used solvent. The complex does not luminesce in the gas or solid state, meaning only the liquid phase is visualized, even in an evaporating spray. By using an internally excited spray containing the phosphorescent complex, the effect of vaporization is shown through the decrease in measured intensity over the length of the spray, together with droplet size measurements using interferometric particle imaging. This study shows that LIP, using the Eu-TTA-TOPO complex, can be used with different solvents, including diesel surrogates. Furthermore, it can be easily handled and used in sprays to investigate spray breakup and evaporation.

  19. Toward an in-situ analytics and diagnostics framework for earth system models

    Science.gov (United States)

    Anantharaj, Valentine; Wolf, Matthew; Rasch, Philip; Klasky, Scott; Williams, Dean; Jacob, Rob; Ma, Po-Lun; Kuo, Kwo-Sen

    2017-04-01

    The development roadmaps for many earth system models (ESM) aim for a globally cloud-resolving model targeting the pre-exascale and exascale systems of the future. The ESMs will also incorporate more complex physics, chemistry and biology - thereby vastly increasing the fidelity of the information content simulated by the model. We will then be faced with an unprecedented volume of simulation output that would need to be processed and analyzed concurrently in order to derive the valuable scientific results. We are already at this threshold with our current generation of ESMs at higher resolution simulations. Currently, the nominal I/O throughput in the Community Earth System Model (CESM) via Parallel IO (PIO) library is around 100 MB/s. If we look at the high frequency I/O requirements, it would require an additional 1 GB / simulated hour, translating to roughly 4 mins wallclock / simulated-day => 24.33 wallclock hours / simulated-model-year => 1,752,000 core-hours of charge per simulated-model-year on the Titan supercomputer at the Oak Ridge Leadership Computing Facility. There is also a pending need for 3X more volume of simulation output . Meanwhile, many ESMs use instrument simulators to run forward models to compare model simulations against satellite and ground-based instruments, such as radars and radiometers. The CFMIP Observation Simulator Package (COSP) is used in CESM as well as the Accelerated Climate Model for Energy (ACME), one of the ESMs specifically targeting current and emerging leadership-class computing platforms These simulators can be computationally expensive, accounting for as much as 30% of the computational cost. Hence the data are often written to output files that are then used for offline calculations. Again, the I/O bottleneck becomes a limitation. Detection and attribution studies also use large volume of data for pattern recognition and feature extraction to analyze weather and climate phenomenon such as tropical cyclones

  20. Earth System Models Underestimate Soil Carbon Diagnostic Times in Dry and Cold Regions.

    Science.gov (United States)

    Jing, W.; Xia, J.; Zhou, X.; Huang, K.; Huang, Y.; Jian, Z.; Jiang, L.; Xu, X.; Liang, J.; Wang, Y. P.; Luo, Y.

    2017-12-01

    Soils contain the largest organic carbon (C) reservoir in the Earth's surface and strongly modulate the terrestrial feedback to climate change. Large uncertainty exists in current Earth system models (ESMs) in simulating soil organic C (SOC) dynamics, calling for a systematic diagnosis on their performance based on observations. Here, we built a global database of SOC diagnostic time (i.e.,turnover times; τsoil) measured at 320 sites with four different approaches. We found that the estimated τsoil was comparable among approaches of 14C dating () (median with 25 and 75 percentiles), 13C shifts due to vegetation change () and the ratio of stock over flux (), but was shortest from laboratory incubation studies (). The state-of-the-art ESMs underestimated the τsoil in most biomes, even by >10 and >5 folds in cold and dry regions, respectively. Moreover,we identified clear negative dependences of τsoil on temperature and precipitation in both of the observational and modeling results. Compared with Community Land Model (version 4), the incorporation of soil vertical profile (CLM4.5) could substantially extend the τsoil of SOC. Our findings suggest the accuracy of climate-C cycle feedback in current ESMs could be enhanced by an improved understanding of SOC dynamics under the limited hydrothermal conditions.

  1. Skull base tumor model.

    Science.gov (United States)

    Gragnaniello, Cristian; Nader, Remi; van Doormaal, Tristan; Kamel, Mahmoud; Voormolen, Eduard H J; Lasio, Giovanni; Aboud, Emad; Regli, Luca; Tulleken, Cornelius A F; Al-Mefty, Ossama

    2010-11-01

    Resident duty-hours restrictions have now been instituted in many countries worldwide. Shortened training times and increased public scrutiny of surgical competency have led to a move away from the traditional apprenticeship model of training. The development of educational models for brain anatomy is a fascinating innovation allowing neurosurgeons to train without the need to practice on real patients and it may be a solution to achieve competency within a shortened training period. The authors describe the use of Stratathane resin ST-504 polymer (SRSP), which is inserted at different intracranial locations to closely mimic meningiomas and other pathological entities of the skull base, in a cadaveric model, for use in neurosurgical training. Silicone-injected and pressurized cadaveric heads were used for studying the SRSP model. The SRSP presents unique intrinsic metamorphic characteristics: liquid at first, it expands and foams when injected into the desired area of the brain, forming a solid tumorlike structure. The authors injected SRSP via different passages that did not influence routes used for the surgical approach for resection of the simulated lesion. For example, SRSP injection routes included endonasal transsphenoidal or transoral approaches if lesions were to be removed through standard skull base approach, or, alternatively, SRSP was injected via a cranial approach if the removal was planned to be via the transsphenoidal or transoral route. The model was set in place in 3 countries (US, Italy, and The Netherlands), and a pool of 13 physicians from 4 different institutions (all surgeons and surgeons in training) participated in evaluating it and provided feedback. All 13 evaluating physicians had overall positive impressions of the model. The overall score on 9 components evaluated--including comparison between the tumor model and real tumor cases, perioperative requirements, general impression, and applicability--was 88% (100% being the best possible

  2. Turning the Page: Advancing Paper-Based Microfluidics for Broad Diagnostic Application.

    Science.gov (United States)

    Gong, Max M; Sinton, David

    2017-06-28

    Infectious diseases are a major global health issue. Diagnosis is a critical first step in effectively managing their spread. Paper-based microfluidic diagnostics first emerged in 2007 as a low-cost alternative to conventional laboratory testing, with the goal of improving accessibility to medical diagnostics in developing countries. In this review, we examine the advances in paper-based microfluidic diagnostics for medical diagnosis in the context of global health from 2007 to 2016. The theory of fluid transport in paper is first presented. The next section examines the strategies that have been employed to control fluid and analyte transport in paper-based assays. Tasks such as mixing, timing, and sequential fluid delivery have been achieved in paper and have enabled analytical capabilities comparable to those of conventional laboratory methods. The following section examines paper-based sample processing and analysis. The most impactful advancement here has been the translation of nucleic acid analysis to a paper-based format. Smartphone-based analysis is another exciting development with potential for wide dissemination. The last core section of the review highlights emerging health applications, such as male fertility testing and wearable diagnostics. We conclude the review with the future outlook, remaining challenges, and emerging opportunities.

  3. Fluorescence multispectral imaging-based diagnostic system for atherosclerosis.

    Science.gov (United States)

    Ho, Cassandra Su Lyn; Horiuchi, Toshikatsu; Taniguchi, Hiroaki; Umetsu, Araya; Hagisawa, Kohsuke; Iwaya, Keiichi; Nakai, Kanji; Azmi, Amalina; Zulaziz, Natasha; Azhim, Azran; Shinomiya, Nariyoshi; Morimoto, Yuji

    2016-08-20

    Composition of atherosclerotic arterial walls is rich in lipids such as cholesterol, unlike normal arterial walls. In this study, we aimed to utilize this difference to diagnose atherosclerosis via multispectral fluorescence imaging, which allows for identification of fluorescence originating from the substance in the arterial wall. The inner surface of extracted arteries (rabbit abdominal aorta, human coronary artery) was illuminated by 405 nm excitation light and multispectral fluorescence images were obtained. Pathological examination of human coronary artery samples were carried out and thickness of arteries were calculated by measuring combined media and intima thickness. The fluorescence spectra in atherosclerotic sites were different from those in normal sites. Multiple regions of interest (ROI) were selected within each sample and a ratio between two fluorescence intensity differences (where each intensity difference is calculated between an identifier wavelength and a base wavelength) from each ROI was determined, allowing for discrimination of atherosclerotic sites. Fluorescence intensity and thickness of artery were found to be significantly correlated. These results indicate that multispectral fluorescence imaging provides qualitative and quantitative evaluations of atherosclerosis and is therefore a viable method of diagnosing the disease.

  4. 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.

  5. Vibration-based Fault Diagnostic of a Spur Gearbox

    Directory of Open Access Journals (Sweden)

    Hartono Dennis

    2016-01-01

    Full Text Available This paper presents comparative studies of Fast Fourier Transform (FFT, Short Time Fourier Transform (STFT and Continuous Wavelet Transform (CWT as several advanced time-frequency analysis methods for diagnosing an early stage of spur gear tooth failure. An incipient fault of a chipped tooth was investigated in this work using vibration measurements from a spur gearbox test rig. Time Synchronous Averaging was implemented for the analysis to enhance the clarity of fault feature from the gear of interest. Based on the experimental results and analysis, it was shown that FFT method could identify the location of the faulty gear with sufficient accuracy. On the other hand, Short Time Fourier Transform method could not provide the angular location information of the faulty gear. It was found that the Continuous Wavelet Transform method offered the best representation of angle-frequency representation. It was not only able to distinguish the difference between the normal and faulty gearboxes from the joint angle-frequency results but could also provide an accurate angular location of the faulty gear tooth in the gearbox.

  6. 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.

  7. The Impact of Model Misspecification on Parameter Estimation and Item-Fit Assessment in Log-Linear Diagnostic Classification Models

    Science.gov (United States)

    Kunina-Habenicht, Olga; Rupp, Andre A.; Wilhelm, Oliver

    2012-01-01

    Using a complex simulation study we investigated parameter recovery, classification accuracy, and performance of two item-fit statistics for correct and misspecified diagnostic classification models within a log-linear modeling framework. The basic manipulated test design factors included the number of respondents (1,000 vs. 10,000), attributes (3…

  8. Novel Infiltration Diagnostics based on Laser-line Scanning and Infrared Temperature Field Imaging

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Xinwei [Iowa State Univ., Ames, IA (United States)

    2017-12-08

    This project targets the building energy efficiency problems induced by building infiltration/leaks. The current infiltration inspection techniques often require extensive visual inspection and/or whole building pressure test. These current techniques cannot meet more than three of the below five criteria of ideal infiltration diagnostics: 1. location and extent diagnostics, 2. building-level application, 3. least surface preparation, 4. weather-proof, and 5. non-disruption to building occupants. These techniques are either too expensive or time consuming, and often lack accuracy and repeatability. They are hardly applicable to facades/facades section. The goal of the project was to develop a novel infiltration diagnostics technology based on laser line-scanning and simultaneous infrared temperature imaging. A laboratory scale experimental setup was designed to mimic a model house of well-defined pressure difference below or above the outside pressure. Algorithms and Matlab-based programs had been developed for recognition of the hole location in infrared images. Our experiment based on laser wavelengths of 450 and 1550 nm and laser beam diameters of 4-25 mm showed that the location of the holes could be identified using laser heating; the diagnostic approach however could not readily distinguish between infiltration and non-infiltration points. To significantly improve the scanning throughput and recognition accuracy, a second approach was explored, developed, and extensively tested. It incorporates a liquid spray on the surface to induce extra phase change cooling effect. In this spray method, we termed it as PECIT (Phase-change Enhanced Cooling Infrared Thermography), phase-change enhanced cooling was used, which significantly amplifies the effect of air flow (infiltration and exfiltration). This heat transfer method worked extremely well to identify infiltration and exfiltration locations with high accuracy and increased throughput. The PECIT technique was

  9. GPIB based instrumentation and control system for ADITYA Thomson Scattering Diagnostic

    Energy Technology Data Exchange (ETDEWEB)

    Patel, Kiran, E-mail: kkpatel@ipr.res.in; Pillai, Vishal; Singh, Neha; Chaudhary, Vishnu; Thomas, Jinto; Kumar, Ajai

    2016-11-15

    The ADITYA Thomson Scattering Diagnostic is a single point Ruby laser based system with a spectrometer for spectral dispersion and photomultiplier tubes for the detection of scattered light. The system uses CAMAC (Computer Automated Measurement And Control) based control and data acquisition system, which synchronizes the Ruby laser, detectors and the digitizer. Previously used serial based CAMAC controller is upgraded to GPIB (General Purpose Interface Bus) based CAMAC controller for configuration and data transfer. The communication protocols for different instruments are converted to a single GPIB based for better interface. The entire control and data acquisition program is developed on LabVIEW platform for versatile operation of diagnostics with improved user friendly GUI (Graphical User Interfaces) and allows user to remotely update the laser firing time with respect to the plasma shot. The software is in handshake with the Tokamak main control program through network to minimize manual interventions for the operation of the diagnostics. The upgraded system improved the performance of the diagnostics in comparison to earlier in terms of better data transmission rate, easy to maintain and program is upgradable.

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

    Directory of Open Access Journals (Sweden)

    Svechtarov V.

    2015-05-01

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

  11. 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.

  12. Advanced error diagnostics of the CMAQ and Chimere modelling systems within the AQMEII3 model evaluation framework

    OpenAIRE

    E. Solazzo; C. Hogrefe; A. Colette; M. Garcia-Vivanco; M. Garcia-Vivanco; S. Galmarini

    2017-01-01

    The work here complements the overview analysis of the modelling systems participating in the third phase of the Air Quality Model Evaluation International Initiative (AQMEII3) by focusing on the performance for hourly surface ozone by two modelling systems, Chimere for Europe and CMAQ for North America. The evaluation strategy outlined in the course of the three phases of the AQMEII activity, aimed to build up a diagnostic methodology for model evaluation, is pursued her...

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

    International Nuclear Information System (INIS)

    Marinoni, A.

    2009-10-01

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

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

    Science.gov (United States)

    Borghese, Peter; Lacey, Sandi

    2014-01-01

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

  15. A reusable simulation model to evaluate the effects of walk-in for diagnostic examinations

    NARCIS (Netherlands)

    Braaksma, A.; Kortbeek, N.; Smid, K.; Sprengers, M. E. S.

    2017-01-01

    Enabling patients to walk in for their diagnostic examination without an appointment has considerable potential in terms of quality of care, patient service, and system efficiency. We present a model to evaluate the effect of implementing a combined walk-in and appointment system, offering

  16. 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.

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

    International Nuclear Information System (INIS)

    Finlay, K.; Norman, G.R.; Keane, D.R.; Stolberg, H.

    2006-01-01

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

  18. 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.

  19. Qualitative model-based diagnosis using possibility theory

    Science.gov (United States)

    Joslyn, Cliff

    1994-01-01

    The potential for the use of possibility in the qualitative model-based diagnosis of spacecraft systems is described. The first sections of the paper briefly introduce the Model-Based Diagnostic (MBD) approach to spacecraft fault diagnosis; Qualitative Modeling (QM) methodologies; and the concepts of possibilistic modeling in the context of Generalized Information Theory (GIT). Then the necessary conditions for the applicability of possibilistic methods to qualitative MBD, and a number of potential directions for such an application, are described.

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

    International Nuclear Information System (INIS)

    Reifman, J.; Wei, T.Y.C.; Vitela, J.E.; Applequist, C. A.; Chasensky, T.M.

    1996-01-01

    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

  1. Validation of Learning Effort Algorithm for Real-Time Non-Interfering Based Diagnostic Technique

    Science.gov (United States)

    Hsu, Pi-Shan; Chang, Te-Jeng

    2011-01-01

    The objective of this research is to validate the algorithm of learning effort which is an indicator of a new real-time and non-interfering based diagnostic technique. IC3 Mentor, the adaptive e-learning platform fulfilling the requirements of intelligent tutor system, was applied to 165 university students. The learning records of the subjects…

  2. Smartphone-Based Mobile Detection Platform for Molecular Diagnostics and Spatiotemporal Disease Mapping.

    Science.gov (United States)

    Song, Jinzhao; Pandian, Vikram; Mauk, Michael G; Bau, Haim H; Cherry, Sara; Tisi, Laurence C; Liu, Changchun

    2018-04-03

    Rapid and quantitative molecular diagnostics in the field, at home, and at remote clinics is essential for evidence-based disease management, control, and prevention. Conventional molecular diagnostics requires extensive sample preparation, relatively sophisticated instruments, and trained personnel, restricting its use to centralized laboratories. To overcome these limitations, we designed a simple, inexpensive, hand-held, smartphone-based mobile detection platform, dubbed "smart-connected cup" (SCC), for rapid, connected, and quantitative molecular diagnostics. Our platform combines bioluminescent assay in real-time and loop-mediated isothermal amplification (BART-LAMP) technology with smartphone-based detection, eliminating the need for an excitation source and optical filters that are essential in fluorescent-based detection. The incubation heating for the isothermal amplification is provided, electricity-free, with an exothermic chemical reaction, and incubation temperature is regulated with a phase change material. A custom Android App was developed for bioluminescent signal monitoring and analysis, target quantification, data sharing, and spatiotemporal mapping of disease. SCC's utility is demonstrated by quantitative detection of Zika virus (ZIKV) in urine and saliva and HIV in blood within 45 min. We demonstrate SCC's connectivity for disease spatiotemporal mapping with a custom-designed website. Such a smart- and connected-diagnostic system does not require any lab facilities and is suitable for use at home, in the field, in the clinic, and particularly in resource-limited settings in the context of Internet of Medical Things (IoMT).

  3. Approach to building knowledge bases in information-measuring systems diagnostics of acute leukemias

    Science.gov (United States)

    Nikitaev, V. G.; Pronichev, A. N.; Polyakov, E. V.; Dmitrieva, V. V.

    2018-01-01

    The paper describes an approach for the formation of the reference base of peripheral blood cells and bone marrow in information-measuring systems of acute leukemia diagnostics. The proposed approach has allowed to create a system, that is enable peer evaluation of blood cells needed for the training of recognition systems when carrying out microscopic studies.

  4. Development of a Diagnostic Prediction Model for Conductive Conditions in Neonates Using Wideband Acoustic Immittance.

    Science.gov (United States)

    Myers, Joshua; Kei, Joseph; Aithal, Sreedevi; Aithal, Venkatesh; Driscoll, Carlie; Khan, Asaduzzaman; Manuel, Alehandrea; Joseph, Anjali; Malicka, Alicja N

    2018-03-03

    Wideband acoustic immittance (WAI) is an emerging test of middle-ear function with potential applications for neonates in screening and diagnostic settings. Previous large-scale diagnostic accuracy studies have assessed the performance of WAI against evoked otoacoustic emissions, but further research is needed using a more stringent reference standard. Research into suitable quantitative techniques to analyze the large volume of data produced by WAI is still in its infancy. Prediction models are an attractive method for analysis of multivariate data because they provide individualized probabilities that a subject has the condition. A clinically useful prediction model must accurately discriminate between normal and abnormal cases and be well calibrated (i.e., give accurate predictions). The present study aimed to develop a diagnostic prediction model for detecting conductive conditions in neonates using WAI. A stringent reference standard was created by combining results of high-frequency tympanometry and distortion product otoacoustic emissions. High-frequency tympanometry and distortion product otoacoustic emissions were performed on both ears of 629 healthy neonates to assess outer- and middle-ear function. Wideband absorbance and complex admittance (magnitude and phase) were measured at frequencies ranging from 226 to 8000 Hz in each neonate at ambient pressure using a click stimulus. Results from one ear of each neonate were used to develop the prediction model. WAI results were used as logistic regression predictors to model the probability that an ear had outer/middle-ear dysfunction. WAI variables were modeled both linearly and nonlinearly, to test whether allowing nonlinearity improved model fit and thus calibration. The best-fitting model was validated using the opposite ears and with bootstrap resampling. The best-fitting model used absorbance at 1000 and 2000 Hz, admittance magnitude at 1000 and 2000 Hz, and admittance phase at 1000 and 4000 Hz modeled

  5. A process model in continuing professional development: Exploring diagnostic radiographers' views

    International Nuclear Information System (INIS)

    Henwood, Suzanne M.; Taket, Ann

    2008-01-01

    This article is based on an exploratory, interpretative grounded theory study that looked at practitioners' perceptions of continuing professional development (CPD) in diagnostic radiography in the UK. Using a combination of in-depth interviews and secondary analysis of published material, a dynamic CPD process model was generated. The study aimed to explore what radiographers understood by the term CPD and whether it was perceived to have any impact on clinical practice. The study aimed to identify and investigate the components of CPD and how they interact with one another, to help to explain what is happening within CPD and what contributes to its effectiveness. The CPD process was shown to be complex, dynamic and centred on the Individual. Supporting components of Facilitation and External Influences were identified as important in maximising the potential impact of CPD. The three main categories were shown to interact dynamically and prior to Participation were shown to have a 'superadditive' effect, where the total effect was greater than the sum of the three individual parts. This study showed that radiographers are generally unaware of the holistic concept of CPD, using instead narrow definitions of CPD with little or no expectation of any impact on practice, focusing predominantly on personal gain. The model produced in the study provided a tool that practitioners reported was helpful in reflecting on their own involvment in CPD

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

    International Nuclear Information System (INIS)

    Tafalla, D.; Tabares, F.L.; Ortiz, P.; Herrero, V.J.; Tanarro, I.

    1998-01-01

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

  7. 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.

  8. Bayesian spatio-temporal modeling of Schistosoma japonicum prevalence data in the absence of a diagnostic 'gold' standard.

    Directory of Open Access Journals (Sweden)

    Xian-Hong Wang

    Full Text Available BACKGROUND: Spatial modeling is increasingly utilized to elucidate relationships between demographic, environmental, and socioeconomic factors, and infectious disease prevalence data. However, there is a paucity of studies focusing on spatio-temporal modeling that take into account the uncertainty of diagnostic techniques. METHODOLOGY/PRINCIPAL FINDINGS: We obtained Schistosoma japonicum prevalence data, based on a standardized indirect hemagglutination assay (IHA, from annual reports from 114 schistosome-endemic villages in Dangtu County, southeastern part of the People's Republic of China, for the period 1995 to 2004. Environmental data were extracted from satellite images. Socioeconomic data were available from village registries. We used Bayesian spatio-temporal models, accounting for the sensitivity and specificity of the IHA test via an equation derived from the law of total probability, to relate the observed with the 'true' prevalence. The risk of S. japonicum was positively associated with the mean land surface temperature, and negatively correlated with the mean normalized difference vegetation index and distance to the nearest water body. There was no significant association between S. japonicum and socioeconomic status of the villages surveyed. The spatial correlation structures of the observed S. japonicum seroprevalence and the estimated infection prevalence differed from one year to another. Variance estimates based on a model adjusted for the diagnostic error were larger than unadjusted models. The generated prediction map for 2005 showed that most of the former and current infections occur in close proximity to the Yangtze River. CONCLUSION/SIGNIFICANCE: Bayesian spatial-temporal modeling incorporating diagnostic uncertainty is a suitable approach for risk mapping S. japonicum prevalence data. The Yangtze River and its tributaries govern schistosomiasis transmission in Dangtu County, but spatial correlation needs to be taken

  9. Bayesian spatio-temporal modeling of Schistosoma japonicum prevalence data in the absence of a diagnostic 'gold' standard.

    Science.gov (United States)

    Wang, Xian-Hong; Zhou, Xiao-Nong; Vounatsou, Penelope; Chen, Zhao; Utzinger, Jürg; Yang, Kun; Steinmann, Peter; Wu, Xiao-Hua

    2008-06-11

    Spatial modeling is increasingly utilized to elucidate relationships between demographic, environmental, and socioeconomic factors, and infectious disease prevalence data. However, there is a paucity of studies focusing on spatio-temporal modeling that take into account the uncertainty of diagnostic techniques. We obtained Schistosoma japonicum prevalence data, based on a standardized indirect hemagglutination assay (IHA), from annual reports from 114 schistosome-endemic villages in Dangtu County, southeastern part of the People's Republic of China, for the period 1995 to 2004. Environmental data were extracted from satellite images. Socioeconomic data were available from village registries. We used Bayesian spatio-temporal models, accounting for the sensitivity and specificity of the IHA test via an equation derived from the law of total probability, to relate the observed with the 'true' prevalence. The risk of S. japonicum was positively associated with the mean land surface temperature, and negatively correlated with the mean normalized difference vegetation index and distance to the nearest water body. There was no significant association between S. japonicum and socioeconomic status of the villages surveyed. The spatial correlation structures of the observed S. japonicum seroprevalence and the estimated infection prevalence differed from one year to another. Variance estimates based on a model adjusted for the diagnostic error were larger than unadjusted models. The generated prediction map for 2005 showed that most of the former and current infections occur in close proximity to the Yangtze River. Bayesian spatial-temporal modeling incorporating diagnostic uncertainty is a suitable approach for risk mapping S. japonicum prevalence data. The Yangtze River and its tributaries govern schistosomiasis transmission in Dangtu County, but spatial correlation needs to be taken into consideration when making risk prediction at small scales.

  10. Reporting guidelines for diagnostic accuracy studies that use Bayesian latent class models (STARD-BLCM)

    DEFF Research Database (Denmark)

    Kostoulas, Polychronis; Nielsen, Søren S.; Branscum, Adam J.

    2017-01-01

    Evaluation of medical tests is usually based on comparing their results to those from a perfect reference (gold standard) procedure. The Standards for Reporting of Diagnostic Accuracy (STARD) initiative (http://www.equator-network.org/reporting-guidelines/stard/) developed reporting guidelines...

  11. Ages and transit times as important diagnostics of model performance for predicting carbon dynamics in terrestrial vegetation models

    Science.gov (United States)

    Ceballos-Núñez, Verónika; Richardson, Andrew D.; Sierra, Carlos A.

    2018-03-01

    The global carbon cycle is strongly controlled by the source/sink strength of vegetation as well as the capacity of terrestrial ecosystems to retain this carbon. These dynamics, as well as processes such as the mixing of old and newly fixed carbon, have been studied using ecosystem models, but different assumptions regarding the carbon allocation strategies and other model structures may result in highly divergent model predictions. We assessed the influence of three different carbon allocation schemes on the C cycling in vegetation. First, we described each model with a set of ordinary differential equations. Second, we used published measurements of ecosystem C compartments from the Harvard Forest Environmental Measurement Site to find suitable parameters for the different model structures. And third, we calculated C stocks, release fluxes, radiocarbon values (based on the bomb spike), ages, and transit times. We obtained model simulations in accordance with the available data, but the time series of C in foliage and wood need to be complemented with other ecosystem compartments in order to reduce the high parameter collinearity that we observed, and reduce model equifinality. Although the simulated C stocks in ecosystem compartments were similar, the different model structures resulted in very different predictions of age and transit time distributions. In particular, the inclusion of two storage compartments resulted in the prediction of a system mean age that was 12-20 years older than in the models with one or no storage compartments. The age of carbon in the wood compartment of this model was also distributed towards older ages, whereas fast cycling compartments had an age distribution that did not exceed 5 years. As expected, models with C distributed towards older ages also had longer transit times. These results suggest that ages and transit times, which can be indirectly measured using isotope tracers, serve as important diagnostics of model structure

  12. Ages and transit times as important diagnostics of model performance for predicting carbon dynamics in terrestrial vegetation models

    Directory of Open Access Journals (Sweden)

    V. Ceballos-Núñez

    2018-03-01

    Full Text Available The global carbon cycle is strongly controlled by the source/sink strength of vegetation as well as the capacity of terrestrial ecosystems to retain this carbon. These dynamics, as well as processes such as the mixing of old and newly fixed carbon, have been studied using ecosystem models, but different assumptions regarding the carbon allocation strategies and other model structures may result in highly divergent model predictions. We assessed the influence of three different carbon allocation schemes on the C cycling in vegetation. First, we described each model with a set of ordinary differential equations. Second, we used published measurements of ecosystem C compartments from the Harvard Forest Environmental Measurement Site to find suitable parameters for the different model structures. And third, we calculated C stocks, release fluxes, radiocarbon values (based on the bomb spike, ages, and transit times. We obtained model simulations in accordance with the available data, but the time series of C in foliage and wood need to be complemented with other ecosystem compartments in order to reduce the high parameter collinearity that we observed, and reduce model equifinality. Although the simulated C stocks in ecosystem compartments were similar, the different model structures resulted in very different predictions of age and transit time distributions. In particular, the inclusion of two storage compartments resulted in the prediction of a system mean age that was 12–20 years older than in the models with one or no storage compartments. The age of carbon in the wood compartment of this model was also distributed towards older ages, whereas fast cycling compartments had an age distribution that did not exceed 5 years. As expected, models with C distributed towards older ages also had longer transit times. These results suggest that ages and transit times, which can be indirectly measured using isotope tracers, serve as important

  13. A Simple Diagnostic Model of the Circulation Beneath an Ice Shelf

    Science.gov (United States)

    Jenkins, Adrian; Nøst, Ole Anders

    2017-04-01

    The ocean circulation beneath ice shelves supplies the heat required to melt ice and exports the resulting freshwater. It therefore plays a key role in determining the mass balance and geometry of the ice shelves and hence the restraint they impose on the outflow of grounded ice from the interior of the ice sheet. Despite this critical role in regulating the ice sheet's contribution to eustatic sea level, an understanding of some of the most basic features of the circulation is lacking. The conventional paradigm is one of a buoyancy-forced overturning circulation, with inflow of warm, salty water along the seabed and outflow of cooled and freshened waters along the ice base. However, most sub-ice-shelf cavities are broad relative to the internal Rossby radius, so a horizontal circulation accompanies the overturning. Primitive equation ocean models applied to idealised geometries produce cyclonic gyres of comparable magnitude, but in the absence of a theoretical understanding of what controls the gyre strength, those solutions can only be validated against each other. Furthermore, we have no understanding of how the gyre circulation should change given more complex geometries. To begin to address this gap in our theoretical understanding we present a simple, linear, steady-state model for the circulation beneath an ice shelf. Our approach in analogous to that of Stommel's classic analysis of the wind-driven gyres, but is complicated by the fact that his most basic assumption of homogeneity is inappropriate. The only forcing on the flow beneath an ice shelf arises because of the horizontal density gradients set up by melting. We thus arrive at a diagnostic model which gives us the depth-dependent horizontal circulation that results from an imposed geometry and density distribution. We describe the development of the model and present some preliminary solutions for the simplest cavity geometries.

  14. Planning diagnostic imaging work-up strategies using case-based reasoning.

    OpenAIRE

    Kahn, C. E.

    1994-01-01

    ISIS is a developmental decision support system that helps physicians select diagnostic imaging procedures. It uses case-based reasoning, an artificial-intelligence approach that emphasizes reasoning and planning from prior experience. The development, training, and evaluation of a prototype system were used to guide the development of ISIS. To realize a clinically useful system, particular emphasis has been placed on increasing the depth and breadth of case-based knowledge, enhancing the exp...

  15. 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. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Rapid tomographic reconstruction based on machine learning for time-resolved combustion diagnostics

    Science.gov (United States)

    Yu, Tao; Cai, Weiwei; Liu, Yingzheng

    2018-04-01

    Optical tomography has attracted surged research efforts recently due to the progress in both the imaging concepts and the sensor and laser technologies. The high spatial and temporal resolutions achievable by these methods provide unprecedented opportunity for diagnosis of complicated turbulent combustion. However, due to the high data throughput and the inefficiency of the prevailing iterative methods, the tomographic reconstructions which are typically conducted off-line are computationally formidable. In this work, we propose an efficient inversion method based on a machine learning algorithm, which can extract useful information from the previous reconstructions and build efficient neural networks to serve as a surrogate model to rapidly predict the reconstructions. Extreme learning machine is cited here as an example for demonstrative purpose simply due to its ease of implementation, fast learning speed, and good generalization performance. Extensive numerical studies were performed, and the results show that the new method can dramatically reduce the computational time compared with the classical iterative methods. This technique is expected to be an alternative to existing methods when sufficient training data are available. Although this work is discussed under the context of tomographic absorption spectroscopy, we expect it to be useful also to other high speed tomographic modalities such as volumetric laser-induced fluorescence and tomographic laser-induced incandescence which have been demonstrated for combustion diagnostics.

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

    International Nuclear Information System (INIS)

    Piros, Attila; Veres, Gábor

    2013-01-01

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

  18. Diagnostics of surface wave driven low pressure plasmas based on indium monoiodide-argon system

    International Nuclear Information System (INIS)

    Ögün, C M; Kaiser, C; Kling, R; Heering, W

    2015-01-01

    Indium monoiodide is proposed as a suitable alternative to hazardous mercury, i.e. the emitting component inside the compact fluorescent lamps (CFL), with comparable luminous efficacy. Indium monoiodide-argon low pressure lamps are electrodelessly driven with surface waves, which are launched and coupled into the lamp by the ‘surfatron’, a microwave coupler optimized for an efficient operation at a frequency of 2.45 GHz. A non intrusive diagnostic method based on spatially resolved optical emission spectroscopy is employed to characterize the plasma parameters. The line emission coefficients of the plasma are derived by means of Abel’s inversion from the measured spectral radiance data. The characteristic plasma parameters, e.g. electron temperature and density are determined by comparing the experimentally obtained line emission coefficients with simulated ones from a collisional-radiative model. Additionally, a method to determine the absolute plasma efficiency via irradiance measurements without any goniometric setup is presented. In this way, the relationship between the plasma efficiency and the plasma parameters can be investigated systematically for different operating configurations, e.g. electrical input power, buffer gas pressure and cold spot temperature. The performance of indium monoiodide-argon plasma is compared with that of conventional CFLs. (paper)

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-10-15

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

  20. Model-based segmentation of femur and pelvis

    NARCIS (Netherlands)

    Güzel, S.; Heese, H.S.; Dries, S.P.M.

    2008-01-01

    The document consists of a diploma thesis, which describes a completely automated segmentation chain for the bones of the human hip joint from diagnostic MR images including the model-building process for the corresponding anatomical structures. Mainly relying on the well-established model-based

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

    International Nuclear Information System (INIS)

    Baggest, D.S.; Rothweil, D.A.; Pang, S.

    1995-12-01

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

  2. Diagnostic utility of novel MRI-based biomarkers for Alzheimer's disease: diffusion tensor imaging and deformation-based morphometry.

    Science.gov (United States)

    Friese, Uwe; Meindl, Thomas; Herpertz, Sabine C; Reiser, Maximilian F; Hampel, Harald; Teipel, Stefan J

    2010-01-01

    We report evidence that multivariate analyses of deformation-based morphometry and diffusion tensor imaging (DTI) data can be used to discriminate between healthy participants and patients with Alzheimer's disease (AD) with comparable diagnostic accuracy. In contrast to other studies on MRI-based biomarkers which usually only focus on a single modality, we derived deformation maps from high-dimensional normalization of T1-weighted images, as well as mean diffusivity maps and fractional anisotropy maps from DTI of the same group of 21 patients with AD and 20 healthy controls. Using an automated multivariate analysis of the entire brain volume, widespread decreased white matter integrity and atrophy effects were found in cortical and subcortical regions of AD patients. Mean diffusivity maps and deformation maps were equally effective in discriminating between AD patients and controls (AUC =0.88 vs. AUC=0.85) while fractional anisotropy maps performed slightly inferior. Combining the maps from different modalities in a logistic regression model resulted in a classification accuracy of AUC=0.86 after leave-one-out cross-validation. It remains to be shown if this automated multivariate analysis of DTI-measures can improve early diagnosis of AD in predementia stages.

  3. 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.

  4. 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.

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

    Directory of Open Access Journals (Sweden)

    Matthias Hübenthal

    Full Text Available 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

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

    International Nuclear Information System (INIS)

    Morman, J.A.; Reifman, J.; Vitela, J.E.; Wei, T.Y.C.; Applequist, C.A.; Hippely, P.; Kuk, W.; Tsoukalas, L.H.

    1998-01-01

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

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

    International Nuclear Information System (INIS)

    Morman, J.A.; Reifman, J.; Wei, T.Y.C.

    1997-01-01

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

  8. Air quality modeling for accountability research: Operational, dynamic, and diagnostic evaluation

    Science.gov (United States)

    Henneman, Lucas R. F.; Liu, Cong; Hu, Yongtao; Mulholland, James A.; Russell, Armistead G.

    2017-10-01

    Photochemical grid models play a central role in air quality regulatory frameworks, including in air pollution accountability research, which seeks to demonstrate the extent to which regulations causally impacted emissions, air quality, and public health. There is a need, however, to develop and demonstrate appropriate practices for model application and evaluation in an accountability framework. We employ a combination of traditional and novel evaluation techniques to assess four years (2001-02, 2011-12) of simulated pollutant concentrations across a decade of major emissions reductions using the Community Multiscale Air Quality (CMAQ) model. We have grouped our assessments in three categories: Operational evaluation investigates how well CMAQ captures absolute concentrations; dynamic evaluation investigates how well CMAQ captures changes in concentrations across the decade of changing emissions; diagnostic evaluation investigates how CMAQ attributes variability in concentrations and sensitivities to emissions between meteorology and emissions, and how well this attribution compares to empirical statistical models. In this application, CMAQ captures O3 and PM2.5 concentrations and change over the decade in the Eastern United States similarly to past CMAQ applications and in line with model evaluation guidance; however, some PM2.5 species-EC, OC, and sulfate in particular-exhibit high biases in various months. CMAQ-simulated PM2.5 has a high bias in winter months and low bias in the summer, mainly due to a high bias in OC during the cold months and low bias in OC and sulfate during the summer. Simulated O3 and PM2.5 changes across the decade have normalized mean bias of less than 2.5% and 17%, respectively. Detailed comparisons suggest biased EC emissions, negative wintertime SO42- sensitivities to mobile source emissions, and incomplete capture of OC chemistry in the summer and winter. Photochemical grid model-simulated O3 and PM2.5 responses to emissions and

  9. 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). Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. 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...

  11. Newborn Congenital Cytomegalovirus Screening Based on Clinical Manifestations and Evaluation of DNA-based Assays for In Vitro Diagnostics.

    Science.gov (United States)

    Fujii, Tomoyuki; Oka, Akira; Morioka, Ichiro; Moriuchi, Hiroyuki; Koyano, Shin; Yamada, Hideto; Saito, Shigeru; Sameshima, Hiroshi; Nagamatsu, Takeshi; Tsuchida, Shinya; Inoue, Naoki

    2017-10-01

    To establish a strategy for congenital cytomegalovirus (cCMV) screening and to establish confirmatory assays approved as in vitro diagnostics by the regulatory authorities, we evaluated the clinical risks and performance of diagnostic assays developed by commercial companies, since cCMV infection has significant clinical consequences. Newborns with clinical manifestations considered to be consequences of cCMV infection (n = 575) were screened for the presence of cytomegalovirus (CMV) DNA in urine specimens collected onto filter paper placed in their diapers using the polymerase chain reaction-based assay reported previously. Liquid urine specimens were obtained from all of 20 CMV-positive newborns and 107 of the CMV-negative newborns identified in the screening. We used these 127 specimens, as well as 12 from cCMV cases identified in a previous study and 41 from healthy newborns, to compare the performance of 2 commercial assays and 1 in-house assay. The risk-based screening allowed the identification of cCMV cases at least 10-fold more efficiently than our previous universal screening, although there appears to be a limit to the identification of asymptomatically infected newborns. Although CMV-specific IgM during pregnancy was found frequently in mothers of cCMV newborns, CMV-IgM alone is not an effective diagnostic marker. The urine-filter-based assay and the 3 diagnostic assays yielded identical results. Although risk-based and universal newborn screening strategies for cCMV infection each have their respective advantages and disadvantages, urine-filter-based assay followed by confirmatory in vitro diagnostics assays is able to identify cCMV cases efficiently.

  12. Fault Diagnostics in Power Electronics Based Brake-by-Wire Systems

    Science.gov (United States)

    2006-05-22

    brake-by-wire system as soon as they occur. We developed a brake-by-wire ( BBW ) system model using Simplorer software that implements the full control...the BBW system. It has the capabilities of detecting faulty conditions immediately after they occur, and pinpointing to specific faulty conditions...within less than 0.02s on the bench setup BBW . The performance of the hierarchical fuzzy diagnostic system is also compared with two other fuzzy

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

    Science.gov (United States)

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

    2016-01-01

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

  14. 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.

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

    Science.gov (United States)

    Shogilev, Daniel J.; Duus, Nicolaj; Odom, Stephen R.; Shapiro, Nathan I.

    2014-01-01

    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 very limited

  16. Diagnostic radiography exposure increases the risk for thyroid microcarcinoma: a population-based case-control study.

    Science.gov (United States)

    Zhang, Yawei; Chen, Yingtai; Huang, Huang; Sandler, Jason; Dai, Min; Ma, Shuangge; Udelsman, Robert

    2015-09-01

    Thyroid cancer incidence and diagnostic radiography exposures, particularly computed tomography (CT) scanning and nuclear medicine examinations, have increased substantially in the USA. However, very few epidemiologic studies have directly investigated their associations. A population-based case-control study was conducted in Connecticut in 2010-2011, including 462 histologically confirmed incident thyroid cancer cases and 498 population-based controls. Multivariate unconditional logistic regression models were used to estimate the associations between diagnostic radiography and the risk of thyroid cancer, controlling for potential confounding factors. Exposure to any form of diagnostic radiography was associated with an increased risk of well-differentiated thyroid microcarcinoma [tumor size≤10 mm, odds ratio (OR)=2.76, 95% confidence interval (CI): 1.31-5.81]. The highest risk increase occurred with nuclear medicine examinations (excluding cardiology tests and thyroid uptake studies; OR=5.47, 95% CI: 2.10-14.23), followed by chest CT scanning (OR=4.30, 95% CI: 1.66-11.14), head and neck CT scanning (OR=3.88, 95% CI: 1.75-8.63), upper gastrointestinal series (OR=3.56, 95% CI: 1.54-8.21), lower gastrointestinal series (OR=3.29, 95% CI: 1.41-7.66), kidney radiography involving dye injection into a vein or artery (OR=3.21, 95% CI: 1.20-8.54), mammography (OR=2.95, 95% CI: 1.14-7.61), chest radiography (OR=2.93, 95% CI: 1.37-6.29), and abdomen CT scanning (OR=2.54, 95% CI: 1.02-6.30). No significant associations were found between these imaging modalities and thyroid tumors larger than 10 mm. This study provides the first direct evidence that CT scanning and nuclear medicine examinations are associated with an increased risk of thyroid cancer. The novel finding that an array of diagnostic radiography procedures are associated with thyroid microcarcinomas warrants further investigation.

  17. 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.

  18. Support vector machine based diagnostic system for breast cancer using swarm intelligence.

    Science.gov (United States)

    Chen, Hui-Ling; Yang, Bo; Wang, Gang; Wang, Su-Jing; Liu, Jie; Liu, Da-You

    2012-08-01

    Breast cancer is becoming a leading cause of death among women in the whole world, meanwhile, it is confirmed that the early detection and accurate diagnosis of this disease can ensure a long survival of the patients. In this paper, a swarm intelligence technique based support vector machine classifier (PSO_SVM) is proposed for breast cancer diagnosis. In the proposed PSO-SVM, the issue of model selection and feature selection in SVM is simultaneously solved under particle swarm (PSO optimization) framework. A weighted function is adopted to design the objective function of PSO, which takes into account the average accuracy rates of SVM (ACC), the number of support vectors (SVs) and the selected features simultaneously. Furthermore, time varying acceleration coefficients (TVAC) and inertia weight (TVIW) are employed to efficiently control the local and global search in PSO algorithm. The effectiveness of PSO-SVM has been rigorously evaluated against the Wisconsin Breast Cancer Dataset (WBCD), which is commonly used among researchers who use machine learning methods for breast cancer diagnosis. The proposed system is compared with the grid search method with feature selection by F-score. The experimental results demonstrate that the proposed approach not only obtains much more appropriate model parameters and discriminative feature subset, but also needs smaller set of SVs for training, giving high predictive accuracy. In addition, Compared to the existing methods in previous studies, the proposed system can also be regarded as a promising success with the excellent classification accuracy of 99.3% via 10-fold cross validation (CV) analysis. Moreover, a combination of five informative features is identified, which might provide important insights to the nature of the breast cancer disease and give an important clue for the physicians to take a closer attention. We believe the promising result can ensure that the physicians make very accurate diagnostic decision in

  19. Final Report for 'Modeling Electron Cloud Diagnostics for High-Intensity Proton Accelerators'

    International Nuclear Information System (INIS)

    Veitzer, Seth A.

    2009-01-01

    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.

  20. 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.

  1. 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.

  2. 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.

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

    International Nuclear Information System (INIS)

    Ha, Jun Su; Seong, Poong Hyun

    2005-01-01

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

  4. 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.

  5. Cadaver-based abscess model for medical training.

    Science.gov (United States)

    Ellis, Michael Stanley; Nelson, Joseph T; Kartchner, Jeffrey Zane; Yousef, Karl Andrew; Adamas-Rappaport, William J; Amini, Richard

    2017-01-01

    Ultrasound imaging is a rapid and noninvasive tool ideal for the imaging of soft tissue infections and is associated with a change of clinician management plans in 50% of cases. We developed a realistic skin abscess diagnostic and therapeutic training model using fresh frozen cadavers and common, affordable materials. Details for construction of the model and suggested variations are presented. This cadaver-based abscess model produces high-quality sonographic images with internal echogenicity similar to a true clinical abscess, and is ideal for teaching sonographic diagnostic skills in addition to the technical skills of incision and drainage or needle aspiration.

  6. Application of visually based, computerised diagnostic decision support system in dermatological medical education: a pilot study.

    Science.gov (United States)

    Chou, Wan-Yi; Tien, Peng-Tai; Lin, Fang-Yu; Chiu, Pin-Chi

    2017-05-01

    Medical education has shifted from memory-based practice to evidence-based decisions. The question arises: how can we ensure that all students get correct and systematic information? Visually based, computerised diagnostic decision support system (VCDDSS, VisualDx) may just fit our needs. A pilot study was conducted to investigate its role in medical education and clinical practice. This was a prospective study, including one consultant dermatologist, 51 medical students and 13 dermatology residents, conducted in the dermatology teaching clinic at China Medical University Hospital from 30 December 2014 to 21 April 2015. Clinical diagnoses of 13 patients were made before and after using VCDDSS. Questionnaires were filled out at the end. The consultant dermatologist's diagnosis was defined as the standard answer; the Sign test was used to analyse diagnostic accuracy and the Fisher exact test to analyse questionnaires. There was an 18.75% increase in diagnostic accuracy after use of VCDDSS (62.5-81.25%; p value system in clinical practice, medical education, residency training, and patient education in the future. Further large-scale studies should be planned to confirm its application. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  7. Mechanism-based diagnostic reasoning: thoughts on teaching introductory clinical pathology.

    Science.gov (United States)

    Bender, Holly S.; Lockee, Barbara B.; Danielson, Jared A.; Mills, Eric M.; Boon, G. Daniel; Burton, John K.; Vermeer, Pamela J.; Zimmerman, Kurt L.; Hilmer, Kelly M.

    2000-01-01

    Teaching introductory clinical pathology to veterinary students is a challenging endeavor that requires a shift in learning strategies from rote memorization to diagnostic reasoning. Educational research has identified discrete cognitive stages required to achieve the automated, unconscious thinking process used by experts. Building on this knowledge, we developed a case-based approach to clinical pathology instruction that actively engages students in the learning process and links performance with positive reward. Simulated cases provide context and create a structure, or "schema", which enhances the learning process by enabling students to synthesize facts and link them with their causal mechanism to reach a defensible diagnostic conclusion. Web-based tools, including the "Problem List Generator" and tutorials, have been developed to facilitate this process. Through the collaborative Biomedical Informatics Research Group, we are working to further develop and evaluate Web-based instructional tools and new educational methods, to clarify the diagnostic reasoning processes used by experienced clinical pathologists, and, ultimately, to better educate our future students to be effective diagnosticians.

  8. Wavenumber selection based analysis in Raman spectroscopy improves skin cancer diagnostic specificity.

    Science.gov (United States)

    Zhao, Jianhua; Zeng, Haishan; Kalia, Sunil; Lui, Harvey

    2016-02-07

    Real-time Raman spectroscopy can be used to assist in assessing skin lesions suspicious for cancer. Most of the diagnostic algorithms are based on full band of the Raman spectra, either in the fingerprint region or the high wavenumber region. In this paper we explored wavenumber selection based analysis in Raman spectroscopy for skin cancer diagnosis. Wavenumber selection was implemented using windows of wavenumber and leave-one-out cross-validated stepwise regression or least and shrinkage selection operator (LASSO). The diagnostic algorithms were then generated from the selected windows of wavenumber using multivariate statistical analyses, including principal component and general discriminate analysis (PC-GDA) and partial least squares (PLS). In total a combined cohort of 645 confirmed lesions from 573 patients encompassing skin cancers, precancers and benign skin lesions were included, which were divided into training cohort (n = 518) and testing cohort (n = 127) according to the measurement time. It was found that the area under the receiver operating characteristic curve (ROC) was improved from 0.861-0.891 to 0.891-0.911 and the diagnostic specificity for fixed sensitivity 0.99-0.90 was improved from 0.17-0.65 to 0.20-0.75 with wavenumber selection based analysis.

  9. Severe childhood asthma and allergy to furry animals: refined assessment using molecular-based allergy diagnostics.

    Science.gov (United States)

    Konradsen, Jon R; Nordlund, Björn; Onell, Annica; Borres, Magnus P; Grönlund, Hans; Hedlin, Gunilla

    2014-03-01

    Allergy to cats and dogs and polysensitization towards these animals are associated with severe childhood asthma. Molecular-based allergy diagnostics offers new opportunities for improved characterization and has been suggested to be particularly useful in patients with polysensitization and/or severe asthma. The aim was to use extract- and molecular-based allergy diagnostics to compare patterns of IgE sensitization towards aeroallergens in children with problematic severe and controlled asthma. Children with a positive ImmunoCAP towards any furry animal (cat, dog or horse) were recruited from a Nationwide Swedish study on severe childhood asthma. Severe (n = 37, age 13 years) and controlled (n = 28, age 14 years) asthmatics underwent assessment of allergic sensitization by ImmunoCap (kUA /l) and immunosolid-phase allergen chip (ISAC). In addition, Asthma Control Test, spirometry and a methacholine challenge were performed. Children with severe asthma had lower asthma control (p Molecular-based allergy diagnostics revealed a more complex molecular spreading of allergen components in children with the most severe disease. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  10. Reliability modelling of redundant safety systems without automatic diagnostics incorporating common cause failures and process demand.

    Science.gov (United States)

    Alizadeh, Siamak; Sriramula, Srinivas

    2017-11-01

    Redundant safety systems are commonly used in the process industry to respond to hazardous events. In redundant systems composed of identical units, Common Cause Failures (CCFs) can significantly influence system performance with regards to reliability and safety. However, their impact has been overlooked due to the inherent complexity of modelling common cause induced failures. This article develops a reliability model for a redundant safety system using Markov analysis approach. The proposed model incorporates process demands in conjunction with CCF for the first time and evaluates their impacts on the reliability quantification of safety systems without automatic diagnostics. The reliability of the Markov model is quantified by considering the Probability of Failure on Demand (PFD) as a measure for low demand systems. The safety performance of the model is analysed using Hazardous Event Frequency (HEF) to evaluate the frequency of entering a hazardous state that will lead to an accident if the situation is not controlled. The utilisation of Markov model for a simple case study of a pressure protection system is demonstrated and it is shown that the proposed approach gives a sufficiently accurate result for all demand rates, durations, component failure rates and corresponding repair rates for low demand mode of operation. The Markov model proposed in this paper assumes the absence of automatic diagnostics, along with multiple stage repair strategy for CCFs and restoration of the system from hazardous state to the "as good as new" state. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  11. Flexible non-linear predictive models for large-scale wind turbine diagnostics

    DEFF Research Database (Denmark)

    Bach-Andersen, Martin; Rømer-Odgaard, Bo; Winther, Ole

    2017-01-01

    We demonstrate how flexible non-linear models can provide accurate and robust predictions on turbine component temperature sensor data using data-driven principles and only a minimum of system modeling. The merits of different model architectures are evaluated using data from a large set...... of turbines operating under diverse conditions. We then go on to test the predictive models in a diagnostic setting, where the output of the models are used to detect mechanical faults in rotor bearings. Using retrospective data from 22 actual rotor bearing failures, the fault detection performance...... of the models are quantified using a structured framework that provides the metrics required for evaluating the performance in a fleet wide monitoring setup. It is demonstrated that faults are identified with high accuracy up to 45 days before a warning from the hard-threshold warning system....

  12. 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 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.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.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.

  13. GPC-HCC model: a combination of glybican-3 with other routine parameters improves the diagnostic efficacy in hepatocellular carcinoma.

    Science.gov (United States)

    Attallah, Abdelfattah M; El-Far, Mohamed; Omran, Mohamed M; Abdelrazek, Mohamed A; Attallah, Ahmed A; Saeed, Aya M; Farid, Khaled

    2016-09-01

    Conflicting results for circulating glypican-3 (GPC3) were reported in hepatocellular carcinoma (HCC) diagnosis. We aimed to improve the diagnostic power of GPC3 by developing a GPC-HCC model for diagnosing HCC. GPC3 was tested for HCC (138), liver cirrhosis (56), and fibrosis (62) patients by ELISA. Data from patient groups were retrospectively analyzed. A novel score, GPC-HCC, based on combination of GPC3 and routine laboratory tests, was developed for HCC diagnosis. The GPC-HCC model values produced a significant 1.7-fold increase in liver cirrhosis and 3.2-fold increase in HCC, in comparison with liver fibrosis. In contrast to GPC3 and alpha fetoprotein (AFP), the GPC-HCC model showed high HCC diagnostic power with area under the curve (AUC) of 0.939, sensitivity 93 %, specificity 93 %, positive predictive value 89 %, negative predictive value 95 %, and efficiency 93 %. GPC-HCC AUC in HCC with single tumor, absent vascular invasion, and tumor size ≤3 cm were 0.93, 0.92, and 0.92, respectively, compared with 0.63, 0.63, and 0.64, respectively, for GPC3 and 0.69, 0.70, 0.55, respectively, for AFP. In conclusion, owing to these promising findings, the combination of GPC3 with other laboratory simple routine tests (GPC-HCC model) could improve the diagnostic power of GPC3 in HCC screening and follow up of cirrhotic patients.

  14. Evaluation of machine learning algorithms and structural features for optimal MRI-based diagnostic prediction in psychosis

    Science.gov (United States)

    Salvador, Raymond; Radua, Joaquim; Canales-Rodríguez, Erick J.; Solanes, Aleix; Sarró, Salvador; Goikolea, José M.; Valiente, Alicia; Monté, Gemma C.; Natividad, María del Carmen; Guerrero-Pedraza, Amalia; Moro, Noemí; Fernández-Corcuera, Paloma; Amann, Benedikt L.; Maristany, Teresa; Vieta, Eduard; McKenna, Peter J.; Pomarol-Clotet, Edith

    2017-01-01

    A relatively large number of studies have investigated the power of structural magnetic resonance imaging (sMRI) data to discriminate patients with schizophrenia from healthy controls. However, very few of them have also included patients with bipolar disorder, allowing the clinically relevant discrimination between both psychotic diagnostics. To assess the efficacy of sMRI data for diagnostic prediction in psychosis we objectively evaluated the discriminative power of a wide range of commonly used machine learning algorithms (ridge, lasso, elastic net and L0 norm regularized logistic regressions, a support vector classifier, regularized discriminant analysis, random forests and a Gaussian process classifier) on main sMRI features including grey and white matter voxel-based morphometry (VBM), vertex-based cortical thickness and volume, region of interest volumetric measures and wavelet-based morphometry (WBM) maps. All possible combinations of algorithms and data features were considered in pairwise classifications of matched samples of healthy controls (N = 127), patients with schizophrenia (N = 128) and patients with bipolar disorder (N = 128). Results show that the selection of feature type is important, with grey matter VBM (without data reduction) delivering the best diagnostic prediction rates (averaging over classifiers: schizophrenia vs. healthy 75%, bipolar disorder vs. healthy 63% and schizophrenia vs. bipolar disorder 62%) whereas algorithms usually yielded very similar results. Indeed, those grey matter VBM accuracy rates were not even improved by combining all feature types in a single prediction model. Further multi-class classifications considering the three groups simultaneously made evident a lack of predictive power for the bipolar group, probably due to its intermediate anatomical features, located between those observed in healthy controls and those found in patients with schizophrenia. Finally, we provide MRIPredict (https

  15. A unification of models for meta-analysis of diagnostic accuracy studies without a gold standard.

    Science.gov (United States)

    Liu, Yulun; Chen, Yong; Chu, Haitao

    2015-06-01

    Several statistical methods for meta-analysis of diagnostic accuracy studies have been discussed in the presence of a gold standard. However, in practice, the selected reference test may be imperfect due to measurement error, non-existence, invasive nature, or expensive cost of a gold standard. It has been suggested that treating an imperfect reference test as a gold standard can lead to substantial bias in the estimation of diagnostic test accuracy. Recently, two models have been proposed to account for imperfect reference test, namely, a multivariate generalized linear mixed model (MGLMM) and a hierarchical summary receiver operating characteristic (HSROC) model. Both models are very flexible in accounting for heterogeneity in accuracies of tests across studies as well as the dependence between tests. In this article, we show that these two models, although with different formulations, are closely related and are equivalent in the absence of study-level covariates. Furthermore, we provide the exact relations between the parameters of these two models and assumptions under which two models can be reduced to equivalent submodels. On the other hand, we show that some submodels of the MGLMM do not have corresponding equivalent submodels of the HSROC model, and vice versa. With three real examples, we illustrate the cases when fitting the MGLMM and HSROC models leads to equivalent submodels and hence identical inference, and the cases when the inferences from two models are slightly different. Our results generalize the important relations between the bivariate generalized linear mixed model and HSROC model when the reference test is a gold standard. © 2014, The International Biometric Society.

  16. 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 mod......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...

  17. Opto-electronic DNA chip-based integrated card for clinical diagnostics.

    Science.gov (United States)

    Marchand, Gilles; Broyer, Patrick; Lanet, Véronique; Delattre, Cyril; Foucault, Frédéric; Menou, Lionel; Calvas, Bernard; Roller, Denis; Ginot, Frédéric; Campagnolo, Raymond; Mallard, Frédéric

    2008-02-01

    Clinical diagnostics is one of the most promising applications for microfluidic lab-on-a-chip or lab-on-card systems. DNA chips, which provide multiparametric data, are privileged tools for genomic analysis. However, automation of molecular biology protocol and use of these DNA chips in fully integrated systems remains a great challenge. Simplicity of chip and/or card/instrument interfaces is amongst the most critical issues to be addressed. Indeed, current detection systems for DNA chip reading are often complex, expensive, bulky and even limited in terms of sensitivity or accuracy. Furthermore, for liquid handling in the lab-on-cards, many devices use complex and bulky systems, either to directly manipulate fluids, or to ensure pneumatic or mechanical control of integrated valves. All these drawbacks prevent or limit the use of DNA-chip-based integrated systems, for point-of-care testing or as a routine diagnostics tool. We present here a DNA-chip-based protocol integration on a plastic card for clinical diagnostics applications including: (1) an opto-electronic DNA-chip, (2) fluid handling using electrically activated embedded pyrotechnic microvalves with closing/opening functions. We demonstrate both fluidic and electric packaging of the optoelectronic DNA chip without major alteration of its electronical and biological functionalities, and fluid control using novel electrically activable pyrotechnic microvalves. Finally, we suggest a complete design of a card dedicated to automation of a complex biological protocol with a fully electrical fluid handling and DNA chip reading.

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

    Science.gov (United States)

    Bruno, John G

    2015-04-16

    Despite the great promise of nucleic acid aptamers in the areas of diagnostics and therapeutics for their facile in vitro development, lack of immunogenicity and other desirable properties, few truly successful aptamer-based products exist in the clinical or other markets. Core reasons for these commercial deficiencies probably stem from industrial commitment to antibodies including a huge financial investment in humanized monoclonal antibodies and a general ignorance about aptamers and their performance among the research and development community. Given the early failures of some strong commercial efforts to gain government approval and bring aptamer-based products to market, it may seem that aptamers are doomed to take a backseat to antibodies forever. However, the key advantages of aptamers over antibodies coupled with niche market needs that only aptamers can fill and more recent published data still point to a bright commercial future for aptamers in areas such as infectious disease and cancer diagnostics and therapeutics. As more researchers and entrepreneurs become familiar with aptamers, it seems inevitable that aptamers will at least be considered for expanded roles in diagnostics and therapeutics. This review also examines new aptamer modifications and attempts to predict new aptamer applications that could revolutionize biomedical technology in the future and lead to marketed products.

  19. Advanced DNA-Based Point-of-Care Diagnostic Methods for Plant Diseases Detection

    Directory of Open Access Journals (Sweden)

    Han Yih Lau

    2017-12-01

    Full Text Available Diagnostic technologies for the detection of plant pathogens with point-of-care capability and high multiplexing ability are an essential tool in the fight to reduce the large agricultural production losses caused by plant diseases. The main desirable characteristics for such diagnostic assays are high specificity, sensitivity, reproducibility, quickness, cost efficiency and high-throughput multiplex detection capability. This article describes and discusses various DNA-based point-of care diagnostic methods for applications in plant disease detection. Polymerase chain reaction (PCR is the most common DNA amplification technology used for detecting various plant and animal pathogens. However, subsequent to PCR based assays, several types of nucleic acid amplification technologies have been developed to achieve higher sensitivity, rapid detection as well as suitable for field applications such as loop-mediated isothermal amplification, helicase-dependent amplification, rolling circle amplification, recombinase polymerase amplification, and molecular inversion probe. The principle behind these technologies has been thoroughly discussed in several review papers; herein we emphasize the application of these technologies to detect plant pathogens by outlining the advantages and disadvantages of each technology in detail.

  20. Theoretical modelling of experimental diagnostic procedures employed during pre-dose dosimetry of quartz

    International Nuclear Information System (INIS)

    Pagonis, V.; Chen, R.; Kitis, G.

    2006-01-01

    The pre-dose technique in thermoluminescence (TL) is used for dating archaeological ceramics and for accident dosimetry. During routine applications of this technique, the sensitisation of the quartz samples is measured as a function of the annealing temperature, yielding the so-called thermal activation characteristic (TAC). The measurement of multiple TACs and the study of the effect of UV-radiation on the TL sensitivity of quartz are important analytical and diagnostic tools. In this paper, it is shown that a modified Zimmerman model for quartz can successfully model the experimental steps undertaken during a measurement of multiple TACs. (authors)

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

    International Nuclear Information System (INIS)

    Suarez Antola, R.

    2001-03-01

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

  2. 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. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. Scintillator Based Energetic Ion Loss Diagnostic for the National Spherical Torus Experiment

    Energy Technology Data Exchange (ETDEWEB)

    D.S. Darrow

    2007-07-02

    A scintillator based energetic ion loss detector has been built and installed on the National Spherical Torus Experiment (NSTX) 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 to 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.

  4. Development and Optimisation of the SPS and LHC beam diagnostics based on Synchrotron Radiation monitors

    CERN Document Server

    AUTHOR|(CDS)2081364; Roncarolo, Federico

    Measuring the beam transverse emittance is fundamental in every accelerator, in particular for colliders, where its precise determination is essential to maximize the luminosity and thus the performance of the colliding beams.
 Synchrotron Radiation (SR) is a versatile tool for non-destructive beam diagnostics, since its characteristics are closely related to those of the source beam. At CERN, being the only available diagnostics at high beam intensity and energy, SR monitors are exploited as the proton beam size monitor of the two higher energy machines, the Super Proton Synchrotron (SPS) and the Large Hadron Collider (LHC). The thesis work documented in this report focused on the design, development, characterization and optimization of these beam size monitors. Such studies were based on a comprehensive set of theoretical calculations, numerical simulations and experiments. A powerful simulation tool has been developed combining conventional softwares for SR simulation and optics design, thus allowing t...

  5. Diagnostics of oral lichen planus based on analysis of volatile organic compounds in saliva

    Science.gov (United States)

    Kistenev, Yury; Borisov, Alexey; Shapovalov, Alexander; Baydik, Olga; Titarenko, Maria

    2017-03-01

    The ability of diagnostics of oral lichen planus (OLP) based on spectral analysis of saliva using the THz spectroscopy is presented. The study included 8 patients with clinically proven OLP. The comparison group consisted of 8 healthy volunteers. Absorption spectra of the saliva was measured using time-domain spectrometer T-spec (EXPLA) in the range 0.2-3THz and have been considered as the feature vectors of the state. The spatial distribution of the objects under study in the feature space was analyzed using principle component analysis. The groups under study were shown to separate in full. Thus, the saliva analysis by the THz spectroscopy technique can be potentially used as a method of noninvasive diagnostics of the OLP.

  6. 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

  7. 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.

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

    International Nuclear Information System (INIS)

    Queiroz, Carlos E.B.; Gerber Junior, Walmoli; Jahn, Tiago R.; Hahn, Tiago T.; Fontana, Thiago S.; Bolzan, Vagner

    2013-01-01

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

  9. An Integrated Model-Based Diagnostic and Prognostic Framework

    Data.gov (United States)

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

  10. 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. 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

  12. Fitting N-mixture models to count data with unmodeled heterogeneity: Bias, diagnostics, and alternative approaches

    Science.gov (United States)

    Duarte, Adam; Adams, Michael J.; Peterson, James T.

    2018-01-01

    Monitoring animal populations is central to wildlife and fisheries management, and the use of N-mixture models toward these efforts has markedly increased in recent years. Nevertheless, relatively little work has evaluated estimator performance when basic assumptions are violated. Moreover, diagnostics to identify when bias in parameter estimates from N-mixture models is likely is largely unexplored. We simulated count data sets using 837 combinations of detection probability, number of sample units, number of survey occasions, and type and extent of heterogeneity in abundance or detectability. We fit Poisson N-mixture models to these data, quantified the bias associated with each combination, and evaluated if the parametric bootstrap goodness-of-fit (GOF) test can be used to indicate bias in parameter estimates. We also explored if assumption violations can be diagnosed prior to fitting N-mixture models. In doing so, we propose a new model diagnostic, which we term the quasi-coefficient of variation (QCV). N-mixture models performed well when assumptions were met and detection probabilities were moderate (i.e., ≥0.3), and the performance of the estimator improved with increasing survey occasions and sample units. However, the magnitude of bias in estimated mean abundance with even slight amounts of unmodeled heterogeneity was substantial. The parametric bootstrap GOF test did not perform well as a diagnostic for bias in parameter estimates when detectability and sample sizes were low. The results indicate the QCV is useful to diagnose potential bias and that potential bias associated with unidirectional trends in abundance or detectability can be diagnosed using Poisson regression. This study represents the most thorough assessment to date of assumption violations and diagnostics when fitting N-mixture models using the most commonly implemented error distribution. Unbiased estimates of population state variables are needed to properly inform management decision

  13. Visual saliency models for summarization of diagnostic hysteroscopy videos in healthcare systems.

    Science.gov (United States)

    Muhammad, Khan; Ahmad, Jamil; Sajjad, Muhammad; Baik, Sung Wook

    2016-01-01

    In clinical practice, diagnostic hysteroscopy (DH) videos are recorded in full which are stored in long-term video libraries for later inspection of previous diagnosis, research and training, and as an evidence for patients' complaints. However, a limited number of frames are required for actual diagnosis, which can be extracted using video summarization (VS). Unfortunately, the general-purpose VS methods are not much effective for DH videos due to their significant level of similarity in terms of color and texture, unedited contents, and lack of shot boundaries. Therefore, in this paper, we investigate visual saliency models for effective abstraction of DH videos by extracting the diagnostically important frames. The objective of this study is to analyze the performance of various visual saliency models with consideration of domain knowledge and nominate the best saliency model for DH video summarization in healthcare systems. Our experimental results indicate that a hybrid saliency model, comprising of motion, contrast, texture, and curvature saliency, is the more suitable saliency model for summarization of DH videos in terms of extracted keyframes and accuracy.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2009-02-26

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

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

    Digital Repository Service at National Institute of Oceanography (India)

    Bahulayan, N.; Shaji, C.

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

  16. Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution

    Science.gov (United States)

    Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

    2017-01-01

    It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images. PMID:29062159

  17. Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution.

    Science.gov (United States)

    Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

    2017-03-01

    It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images.

  18. 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.

  19. Symptom diagnostics based on clinical records: a tool for scientific research in child psychiatry?

    Science.gov (United States)

    de Jong, Marianne; Punt, Marja; de Groot, Erik; Hielkema, Tjitske; Struik, Marianne; Minderaa, Ruud B; Hadders-Algra, Mijna

    2009-05-01

    Child psychiatric diagnoses are generally based on a clinical examination and not on standardized questionnaires. The present study assessed whether symptom diagnostics based on clinical records facilitates the use of non-standardized clinical material for research. Six hundred and eighty-five children, referred to a third level child psychiatric centre in the Netherlands, were, after extensive multidisciplinary examination, classified according to the multi-axial classification scheme for psychiatric disorders in childhood and adolescence (MAC-ICD-9). By two raters 44 behavioural symptoms were scored based on the clinical records of these children. Interrater agreement on symptoms in 50 records was performed. Principal components analysis on symptom scores of all children was performed; factor scores were related with MAC-ICD-9 classifications. Interrater reliability for behavioural symptoms was excellent (kappa = 0.88). Many children with psychiatric problems suffer from a large number of behavioural symptoms. Factor scores of the symptoms revealed recognizable and well interpretable entities and indicated overlap in symptomatology and comorbidity. A symptom-based diagnostic approach based on extensive clinical patient files may provide a special dimension to improve the reliability of psychiatric classification.

  20. Bacterial clonal diagnostics as a tool for evidence-based empiric antibiotic selection.

    Directory of Open Access Journals (Sweden)

    Veronika Tchesnokova

    Full Text Available Despite the known clonal distribution of antibiotic resistance in many bacteria, empiric (pre-culture antibiotic selection still relies heavily on species-level cumulative antibiograms, resulting in overuse of broad-spectrum agents and excessive antibiotic/pathogen mismatch. Urinary tract infections (UTIs, which account for a large share of antibiotic use, are caused predominantly by Escherichia coli, a highly clonal pathogen. In an observational clinical cohort study of urgent care patients with suspected UTI, we assessed the potential for E. coli clonal-level antibiograms to improve empiric antibiotic selection. A novel PCR-based clonotyping assay was applied to fresh urine samples to rapidly detect E. coli and the urine strain's clonotype. Based on a database of clonotype-specific antibiograms, the acceptability of various antibiotics for empiric therapy was inferred using a 20%, 10%, and 30% allowed resistance threshold. The test's performance characteristics and possible effects on prescribing were assessed. The rapid test identified E. coli clonotypes directly in patients' urine within 25-35 minutes, with high specificity and sensitivity compared to culture. Antibiotic selection based on a clonotype-specific antibiogram could reduce the relative likelihood of antibiotic/pathogen mismatch by ≥ 60%. Compared to observed prescribing patterns, clonal diagnostics-guided antibiotic selection could safely double the use of trimethoprim/sulfamethoxazole and minimize fluoroquinolone use. In summary, a rapid clonotyping test showed promise for improving empiric antibiotic prescribing for E. coli UTI, including reversing preferential use of fluoroquinolones over trimethoprim/sulfamethoxazole. The clonal diagnostics approach merges epidemiologic surveillance, antimicrobial stewardship, and molecular diagnostics to bring evidence-based medicine directly to the point of care.

  1. 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

  2. Bacterial clonal diagnostics as a tool for evidence-based empiric antibiotic selection.

    Science.gov (United States)

    Tchesnokova, Veronika; Avagyan, Hovhannes; Rechkina, Elena; Chan, Diana; Muradova, Mariya; Haile, Helen Ghirmai; Radey, Matthew; Weissman, Scott; Riddell, Kim; Scholes, Delia; Johnson, James R; Sokurenko, Evgeni V

    2017-01-01

    Despite the known clonal distribution of antibiotic resistance in many bacteria, empiric (pre-culture) antibiotic selection still relies heavily on species-level cumulative antibiograms, resulting in overuse of broad-spectrum agents and excessive antibiotic/pathogen mismatch. Urinary tract infections (UTIs), which account for a large share of antibiotic use, are caused predominantly by Escherichia coli, a highly clonal pathogen. In an observational clinical cohort study of urgent care patients with suspected UTI, we assessed the potential for E. coli clonal-level antibiograms to improve empiric antibiotic selection. A novel PCR-based clonotyping assay was applied to fresh urine samples to rapidly detect E. coli and the urine strain's clonotype. Based on a database of clonotype-specific antibiograms, the acceptability of various antibiotics for empiric therapy was inferred using a 20%, 10%, and 30% allowed resistance threshold. The test's performance characteristics and possible effects on prescribing were assessed. The rapid test identified E. coli clonotypes directly in patients' urine within 25-35 minutes, with high specificity and sensitivity compared to culture. Antibiotic selection based on a clonotype-specific antibiogram could reduce the relative likelihood of antibiotic/pathogen mismatch by ≥ 60%. Compared to observed prescribing patterns, clonal diagnostics-guided antibiotic selection could safely double the use of trimethoprim/sulfamethoxazole and minimize fluoroquinolone use. In summary, a rapid clonotyping test showed promise for improving empiric antibiotic prescribing for E. coli UTI, including reversing preferential use of fluoroquinolones over trimethoprim/sulfamethoxazole. The clonal diagnostics approach merges epidemiologic surveillance, antimicrobial stewardship, and molecular diagnostics to bring evidence-based medicine directly to the point of care.

  3. Model-based Software Engineering

    DEFF Research Database (Denmark)

    Kindler, Ekkart

    2010-01-01

    The vision of model-based software engineering is to make models the main focus of software development and to automatically generate software from these models. Part of that idea works already today. But, there are still difficulties when it comes to behaviour. Actually, there is no lack in models...

  4. Review: Diagnostic accuracy of PCR-based detection tests for Helicobacter Pylori in stool samples.

    Science.gov (United States)

    Khadangi, Fatemeh; Yassi, Maryam; Kerachian, Mohammad Amin

    2017-12-01

    Although different methods have been established to detect Helicobacter pylori (H. pylori) infection, identifying infected patients is an ongoing challenge. The aim of this meta-analysis was to provide pooled diagnostic accuracy measures for stool PCR test in the diagnosis of H. pylori infection. In this study, a systematic review and meta-analysis were carried out on various sources, including MEDLINE, Web of Sciences, and the Cochrane Library from April 1, 1999, to May 1, 2016. This meta-analysis adheres to the guidelines provided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses report (PRISMA Statement). The clinical value of DNA stool PCR test was based on the pooled false positive, false negative, true positive, and true negative of different genes. Twenty-six of 328 studies identified met the eligibility criteria. Stool PCR test had a performance of 71% (95% CI: 68-73) sensitivity, 96% (95% CI: 94-97) specificity, and 65.6 (95% CI: 30.2-142.5) diagnostic odds ratio (DOR) in diagnosis of H. pylori. The DOR of genes which showed the highest performance of stool PCR tests was as follows: 23S rRNA 152.5 (95% CI: 55.5-418.9), 16S rRNA 67.9 (95%CI: 6.4-714.3), and glmM 68.1 (95%CI: 20.1-231.7). The sensitivity and specificity of stool PCR test are relatively in the same spectrum of other diagnostic methods for the detection of H. pylori infection. In descending order of significance, the most diagnostic candidate genes using PCR detection were 23S rRNA, 16S rRNA, and glmM. PCR for 23S rRNA gene which has the highest performance could be applicable to detect H. pylori infection. © 2017 John Wiley & Sons Ltd.

  5. 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.

  6. 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

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

    International Nuclear Information System (INIS)

    Van Atta, Angela J.; Baskin, Henry J.; Maves, Connie K.; Dansie, David M.; Rollins, Michael D.; Bolte, Robert G.; Mundorff, Michael B.; Andrews, Seth P.

    2015-01-01

    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

  8. The Cloud Feedback Model Intercomparison Project (CFMIP Diagnostic Codes Catalogue – metrics, diagnostics and methodologies to evaluate, understand and improve the representation of clouds and cloud feedbacks in climate models

    Directory of Open Access Journals (Sweden)

    Y. Tsushima

    2017-11-01

    Full Text Available The CFMIP Diagnostic Codes Catalogue assembles cloud metrics, diagnostics and methodologies, together with programs to diagnose them from general circulation model (GCM outputs written by various members of the CFMIP community. This aims to facilitate use of the diagnostics by the wider community studying climate and climate change. This paper describes the diagnostics and metrics which are currently in the catalogue, together with examples of their application to model evaluation studies and a summary of some of the insights these diagnostics have provided into the main shortcomings in current GCMs. Analysis of outputs from CFMIP and CMIP6 experiments will also be facilitated by the sharing of diagnostic codes via this catalogue.Any code which implements diagnostics relevant to analysing clouds – including cloud–circulation interactions and the contribution of clouds to estimates of climate sensitivity in models – and which is documented in peer-reviewed studies, can be included in the catalogue. We very much welcome additional contributions to further support community analysis of CMIP6 outputs.

  9. The Cloud Feedback Model Intercomparison Project (CFMIP) Diagnostic Codes Catalogue - metrics, diagnostics and methodologies to evaluate, understand and improve the representation of clouds and cloud feedbacks in climate models

    Science.gov (United States)

    Tsushima, Yoko; Brient, Florent; Klein, Stephen A.; Konsta, Dimitra; Nam, Christine C.; Qu, Xin; Williams, Keith D.; Sherwood, Steven C.; Suzuki, Kentaroh; Zelinka, Mark D.

    2017-11-01

    The CFMIP Diagnostic Codes Catalogue assembles cloud metrics, diagnostics and methodologies, together with programs to diagnose them from general circulation model (GCM) outputs written by various members of the CFMIP community. This aims to facilitate use of the diagnostics by the wider community studying climate and climate change. This paper describes the diagnostics and metrics which are currently in the catalogue, together with examples of their application to model evaluation studies and a summary of some of the insights these diagnostics have provided into the main shortcomings in current GCMs. Analysis of outputs from CFMIP and CMIP6 experiments will also be facilitated by the sharing of diagnostic codes via this catalogue.Any code which implements diagnostics relevant to analysing clouds - including cloud-circulation interactions and the contribution of clouds to estimates of climate sensitivity in models - and which is documented in peer-reviewed studies, can be included in the catalogue. We very much welcome additional contributions to further support community analysis of CMIP6 outputs.

  10. A phase angle based diagnostic scheme to planetary gear faults diagnostics under non-stationary operational conditions

    Science.gov (United States)

    Feng, Ke; Wang, Kesheng; Ni, Qing; Zuo, Ming J.; Wei, Dongdong

    2017-11-01

    Planetary gearbox is a critical component for rotating machinery. It is widely used in wind turbines, aerospace and transmission systems in heavy industry. Thus, it is important to monitor planetary gearboxes, especially for fault diagnostics, during its operational conditions. However, in practice, operational conditions of planetary gearbox are often characterized by variations of rotational speeds and loads, which may bring difficulties for fault diagnosis through the measured vibrations. In this paper, phase angle data extracted from measured planetary gearbox vibrations is used for fault detection under non-stationary operational conditions. Together with sample entropy, fault diagnosis on planetary gearbox is implemented. The proposed scheme is explained and demonstrated in both simulation and experimental studies. The scheme proves to be effective and features advantages on fault diagnosis of planetary gearboxes under non-stationary operational conditions.

  11. 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.

  12. The application of special technologies in diagnostic anatomic pathology: is it consistent with the principles of evidence-based medicine?

    Science.gov (United States)

    Marchevsky, Alberto M

    2005-05-01

    Proponents of evidence-based medicine (EBM) have emphasized the need to consider the quality of different sources of medical information and have proposed various methods to integrate available "best evidence" into rules, guidelines and other diagnostic, therapeutic and prognostic models. The various factors that can affect the internal validity of studies in anatomic pathology, such as interobserver variability, use of retrospective rather than prospective data and others, are reviewed. The need for testing for the external validity of the results of anatomic pathology studies is introduced, using "test sets" of cases that have not been used to generate the classification or prognostic models. This methodology has been seldom used in anatomic pathology to validate the generalizability of various "entities," usefulness of diagnostic tests under different conditions and other information. Basic concepts of meta-analysis for research synthesis are introduced; these methods have been seldom used in anatomic pathology to integrate information from different studies using quantitative techniques rather than summary tables that merely list the results of various publications. The potential use of decision analysis and value of information analysis for the adoption of new tests is briefly discussed.

  13. 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

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

    International Nuclear Information System (INIS)

    Edwards, R.M.; Chavez, C.; Kamarthi, S.; Dharap, S.; Lindsay, R.W.; Staffon, J.

    1990-01-01

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

  15. 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.

  16. Building Modern Vibration Diagnostics Systems Based on the Frequency-Time Transformations of A Measured Signal

    Directory of Open Access Journals (Sweden)

    Yasoveev Vasikh

    2016-01-01

    Full Text Available Basic methods of analysis of vibration transducers signals were reviewed. Continuous wavelet transform, being a time-frequency transform, was found to be an advanced mathematical tool for analysis of vibration signals. Experimental studies revealed obvious changes in the continuous wavelet transform spectrum depending on the existing defects. A method for detection and identification of technological violations based on the analysis of CWT spectrum components and normalized correlation coefficient was suggested. In accordance with the suggested method software for vibration diagnostics was developed.

  17. 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. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. Effects of using the developing nurses' thinking model on nursing students' diagnostic accuracy.

    Science.gov (United States)

    Tesoro, Mary Gay

    2012-08-01

    This quasi-experimental study tested the effectiveness of an educational model, Developing Nurses' Thinking (DNT), on nursing students' clinical reasoning to achieve patient safety. Teaching nursing students to develop effective thinking habits that promote positive patient outcomes and patient safety is a challenging endeavor. Positive patient outcomes and safety are achieved when nurses accurately interpret data and subsequently implement appropriate plans of care. This study's pretest-posttest design determined whether use of the DNT model during 2 weeks of clinical postconferences improved nursing students' (N = 83) diagnostic accuracy. The DNT model helps students to integrate four constructs-patient safety, domain knowledge, critical thinking processes, and repeated practice-to guide their thinking when interpreting patient data and developing effective plans of care. The posttest scores of students from the intervention group showed statistically significant improvement in accuracy. Copyright 2012, SLACK Incorporated.

  19. Laser diagnostics of biofractals

    International Nuclear Information System (INIS)

    Ushenko, A G

    1999-01-01

    An optical approach to the problem of modeling and diagnostics of the structures of biofractal formations was considered in relation to human bone tissue. A model was proposed for the optical properties of this tissue, including three levels of fractal organisation: microcrystaline, macrocrystallne, and architectural. The studies were based on laser coherent polarrimetry ensuring the retrieval of the fullest information about the optical and polarisation properties of bone tissue. A method was developed for contactless noninvasive diagnostics of the orientational and mineralogical structure of bone tissue considered as a biofractal. (lasers in medicine)

  20. Combining item response theory and diagnostic classification models: a psychometric model for scaling ability and diagnosing misconceptions.

    Science.gov (United States)

    Bradshaw, Laine; Templin, Jonathan

    2014-07-01

    Traditional testing procedures typically utilize unidimensional item response theory (IRT) models to provide a single, continuous estimate of a student's overall ability. Advances in psychometrics have focused on measuring multiple dimensions of ability to provide more detailed feedback for students, teachers, and other stakeholders. Diagnostic classification models (DCMs) provide multidimensional feedback by using categorical latent variables that represent distinct skills underlying a test that students may or may not have mastered. The Scaling Individuals and Classifying Misconceptions (SICM) model is presented as a combination of a unidimensional IRT model and a DCM where the categorical latent variables represent misconceptions instead of skills. In addition to an estimate of ability along a latent continuum, the SICM model provides multidimensional, diagnostic feedback in the form of statistical estimates of probabilities that students have certain misconceptions. Through an empirical data analysis, we show how this additional feedback can be used by stakeholders to tailor instruction for students' needs. We also provide results from a simulation study that demonstrate that the SICM MCMC estimation algorithm yields reasonably accurate estimates under large-scale testing conditions.

  1. Line Shape Modeling for the Diagnostic of the Electron Density in a Corona Discharge

    Directory of Open Access Journals (Sweden)

    Joël Rosato

    2017-09-01

    Full Text Available We present an analysis of spectra observed in a corona discharge designed for the study of dielectrics in electrical engineering. The medium is a gas of helium and the discharge was performed at the vicinity of a tip electrode under high voltage. The shape of helium lines is dominated by the Stark broadening due to the plasma microfield. Using a computer simulation method, we examine the sensitivity of the He 492 nm line shape to the electron density. Our results indicate the possibility of a density diagnostic based on passive spectroscopy. The influence of collisional broadening due to interactions between the emitters and neutrals is discussed.

  2. 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.

  3. Reduction of the inappropriate ICD therapies by implementing a new fuzzy logic-based diagnostic algorithm.

    Science.gov (United States)

    Lewandowski, Michał; Przybylski, Andrzej; Kuźmicz, Wiesław; Szwed, Hanna

    2013-09-01

    The aim of the study was to analyze the value of a completely new fuzzy logic-based detection algorithm (FA) in comparison with arrhythmia classification algorithms used in existing ICDs in order to demonstrate whether the rate of inappropriate therapies can be reduced. On the basis of the RR intervals database containing arrhythmia events and controls recordings from the ICD memory a diagnostic algorithm was developed and tested by a computer program. This algorithm uses the same input signals as existing ICDs: RR interval as the primary input variable and two variables derived from it, onset and stability. However, it uses 15 fuzzy rules instead of fixed thresholds used in existing devices. The algorithm considers 6 diagnostic categories: (1) VF (ventricular fibrillation), (2) VT (ventricular tachycardia), (3) ST (sinus tachycardia), (4) DAI (artifacts and heart rhythm irregularities including extrasystoles and T-wave oversensing-TWOS), (5) ATF (atrial and supraventricular tachycardia or fibrillation), and 96) NT (sinus rhythm). This algorithm was tested on 172 RR recordings from different ICDs in the follow-up of 135 patients. All diagnostic categories of the algorithm were present in the analyzed recordings: VF (n = 35), VT (n = 48), ST (n = 14), DAI (n = 32), ATF (n = 18), NT (n = 25). Thirty-eight patients (31.4%) in the studied group received inappropriate ICD therapies. In all these cases the final diagnosis of the algorithm was correct (19 cases of artifacts, 11 of atrial fibrillation and 8 of ST) and fuzzy rules algorithm implementation would have withheld unnecessary therapies. Incidence of inappropriate therapies: 3 vs. 38 (the proposed algorithm vs. ICD diagnosis, respectively) differed significantly (p fuzzy logic based algorithm seems to be promising and its implementation could diminish ICDs inappropriate therapies. We found FA usefulness in correct diagnosis of sinus tachycardia, atrial fibrillation and artifacts in comparison with tested ICDs.

  4. Modelling the transport of optical photons in scintillation detectors for diagnostic and radiotherapy imaging

    Science.gov (United States)

    Roncali, Emilie; Mosleh-Shirazi, Mohammad Amin; Badano, Aldo

    2017-10-01

    Computational modelling of radiation transport can enhance the understanding of the relative importance of individual processes involved in imaging systems. Modelling is a powerful tool for improving detector designs in ways that are impractical or impossible to achieve through experimental measurements. Modelling of light transport in scintillation detectors used in radiology and radiotherapy imaging that rely on the detection of visible light plays an increasingly important role in detector design. Historically, researchers have invested heavily in modelling the transport of ionizing radiation while light transport is often ignored or coarsely modelled. Due to the complexity of existing light transport simulation tools and the breadth of custom codes developed by users, light transport studies are seldom fully exploited and have not reached their full potential. This topical review aims at providing an overview of the methods employed in freely available and other described optical Monte Carlo packages and analytical models and discussing their respective advantages and limitations. In particular, applications of optical transport modelling in nuclear medicine, diagnostic and radiotherapy imaging are described. A discussion on the evolution of these modelling tools into future developments and applications is presented. The authors declare equal leadership and contribution regarding this review.

  5. From SOMAmer-based biomarker discovery to diagnostic and clinical applications: a SOMAmer-based, streamlined multiplex proteomic assay.

    Directory of Open Access Journals (Sweden)

    Stephan Kraemer

    Full Text Available Recently, we reported a SOMAmer-based, highly multiplexed assay for the purpose of biomarker identification. To enable seamless transition from highly multiplexed biomarker discovery assays to a format suitable and convenient for diagnostic and life-science applications, we developed a streamlined, plate-based version of the assay. The plate-based version of the assay is robust, sensitive (sub-picomolar, rapid, can be highly multiplexed (upwards of 60 analytes, and fully automated. We demonstrate that quantification by microarray-based hybridization, Luminex bead-based methods, and qPCR are each compatible with our platform, further expanding the breadth of proteomic applications for a wide user community.

  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......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...... datasets. Our model also outperforms A Decision Cluster Classification (ADCC) and the Decision Cluster Forest Classification (DCFC) models on the Reuters-21578 dataset....

  7. Biogeochemical protocols and diagnostics for the CMIP6 Ocean Model Intercomparison Project (OMIP

    Directory of Open Access Journals (Sweden)

    J. C. Orr

    2017-06-01

    Full Text Available The Ocean Model Intercomparison Project (OMIP focuses on the physics and biogeochemistry of the ocean component of Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6. OMIP aims to provide standard protocols and diagnostics for ocean models, while offering a forum to promote their common assessment and improvement. It also offers to compare solutions of the same ocean models when forced with reanalysis data (OMIP simulations vs. when integrated within fully coupled Earth system models (CMIP6. Here we detail simulation protocols and diagnostics for OMIP's biogeochemical and inert chemical tracers. These passive-tracer simulations will be coupled to ocean circulation models, initialized with observational data or output from a model spin-up, and forced by repeating the 1948–2009 surface fluxes of heat, fresh water, and momentum. These so-called OMIP-BGC simulations include three inert chemical tracers (CFC-11, CFC-12, SF6 and biogeochemical tracers (e.g., dissolved inorganic carbon, carbon isotopes, alkalinity, nutrients, and oxygen. Modelers will use their preferred prognostic BGC model but should follow common guidelines for gas exchange and carbonate chemistry. Simulations include both natural and total carbon tracers. The required forced simulation (omip1 will be initialized with gridded observational climatologies. An optional forced simulation (omip1-spunup will be initialized instead with BGC fields from a long model spin-up, preferably for 2000 years or more, and forced by repeating the same 62-year meteorological forcing. That optional run will also include abiotic tracers of total dissolved inorganic carbon and radiocarbon, CTabio and 14CTabio, to assess deep-ocean ventilation and distinguish the role of physics vs. biology. These simulations will be forced by observed atmospheric histories of the three inert gases and CO2 as well as carbon isotope ratios of CO2. OMIP-BGC simulation

  8. Biogeochemical protocols and diagnostics for the CMIP6 Ocean Model Intercomparison Project (OMIP)

    Science.gov (United States)

    Orr, James C.; Najjar, Raymond G.; Aumont, Olivier; Bopp, Laurent; Bullister, John L.; Danabasoglu, Gokhan; Doney, Scott C.; Dunne, John P.; Dutay, Jean-Claude; Graven, Heather; Griffies, Stephen M.; John, Jasmin G.; Joos, Fortunat; Levin, Ingeborg; Lindsay, Keith; Matear, Richard J.; McKinley, Galen A.; Mouchet, Anne; Oschlies, Andreas; Romanou, Anastasia; Schlitzer, Reiner; Tagliabue, Alessandro; Tanhua, Toste; Yool, Andrew

    2017-06-01

    The Ocean Model Intercomparison Project (OMIP) focuses on the physics and biogeochemistry of the ocean component of Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). OMIP aims to provide standard protocols and diagnostics for ocean models, while offering a forum to promote their common assessment and improvement. It also offers to compare solutions of the same ocean models when forced with reanalysis data (OMIP simulations) vs. when integrated within fully coupled Earth system models (CMIP6). Here we detail simulation protocols and diagnostics for OMIP's biogeochemical and inert chemical tracers. These passive-tracer simulations will be coupled to ocean circulation models, initialized with observational data or output from a model spin-up, and forced by repeating the 1948-2009 surface fluxes of heat, fresh water, and momentum. These so-called OMIP-BGC simulations include three inert chemical tracers (CFC-11, CFC-12, SF6) and biogeochemical tracers (e.g., dissolved inorganic carbon, carbon isotopes, alkalinity, nutrients, and oxygen). Modelers will use their preferred prognostic BGC model but should follow common guidelines for gas exchange and carbonate chemistry. Simulations include both natural and total carbon tracers. The required forced simulation (omip1) will be initialized with gridded observational climatologies. An optional forced simulation (omip1-spunup) will be initialized instead with BGC fields from a long model spin-up, preferably for 2000 years or more, and forced by repeating the same 62-year meteorological forcing. That optional run will also include abiotic tracers of total dissolved inorganic carbon and radiocarbon, CTabio and 14CTabio, to assess deep-ocean ventilation and distinguish the role of physics vs. biology. These simulations will be forced by observed atmospheric histories of the three inert gases and CO2 as well as carbon isotope ratios of CO2. OMIP-BGC simulation protocols are

  9. 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...

  10. 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

  11. Activity-based DEVS modeling

    DEFF Research Database (Denmark)

    Alshareef, Abdurrahman; Sarjoughian, Hessam S.; Zarrin, Bahram

    2018-01-01

    architecture and the UML concepts. In this paper, we further this work by grounding Activity-based DEVS modeling and developing a fully-fledged modeling engine to demonstrate applicability. We also detail the relevant aspects of the created metamodel in terms of modeling and simulation. A significant number...

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

    Science.gov (United States)

    Diekstra, Adinda; Bosgoed, Ermanno; Rikken, Alwin; van Lier, Bart; Kamsteeg, Erik-Jan; Tychon, Marloes; Derks, Ronny C; van Soest, Ronald A; Mensenkamp, Arjen R; Scheffer, Hans; Neveling, Kornelia; Nelen, Marcel R

    2015-01-01

    Dideoxy-based chain termination sequencing developed by Sanger is the gold standard sequencing approach and allows clinical diagnostics of disorders with relatively low genetic heterogeneity. Recently, new next generation sequencing (NGS) technologies have found their way into diagnostic laboratories, enabling the sequencing of large targeted gene panels or exomes. The development of benchtop NGS instruments now allows the analysis of single genes or small gene panels, making these platforms increasingly competitive with Sanger sequencing. We developed a generic automated ion semiconductor sequencing work flow that can be used in a clinical setting and can serve as a substitute for Sanger sequencing. Standard amplicon-based enrichment remained identical to PCR for Sanger sequencing. A novel postenrichment pooling strategy was developed, limiting the number of library preparations and reducing sequencing costs up to 70% compared to Sanger sequencing. A total of 1224 known pathogenic variants were analyzed, yielding an analytical sensitivity of 99.92% and specificity of 99.99%. In a second experiment, a total of 100 patient-derived DNA samples were analyzed using a blind analysis. The results showed an analytical sensitivity of 99.60% and specificity of 99.98%, comparable to Sanger sequencing. Ion semiconductor sequencing can be a first choice mutation scanning technique, independent of the genes analyzed. © 2014 American Association for Clinical Chemistry.

  13. Evaluating photographic scales of facial pores and diagnostic agreement of tests using latent class models.

    Science.gov (United States)

    Ning, Yao; Qing, Zeng; Qing, Wang; Li, Li

    2017-02-01

    Ordinal severity scales illustrated by photographs have been widely developed to help dermatologists in evaluating skin problems or improvements. Numerous scales have been published, and none of them were used for assessing facial pores. A five-point photographic scale of facial pores was formulated, and photographs of pores on nasal ala from 128 female volunteers were acquired. Five dermatologists with similar experiences rated the 128 photographs independently using the reference photographs. Latent Class Models (LCM) were used to analyze the data. Firstly, we hypothesized that the conditional probabilities of the five dermatologists were identical to build the first LCM and without the restriction to formulate the second LCM. Conditional probability and posterior probability were also calculated. The five-point scales were ambiguous as the raters actually had difficulties in distinguishing between some adjacent categories. Adjacent categories were pooled for reanalyzing, and the model fitted well. The newly developed photographic scale of Chinese facial pores should be redefined to improve their quality and reproducibility in future studies. Standardized scales for the measurement of aging and response to cosmetic therapy were essential for assessing diagnostic experiment. The LCM can effectively deal with diagnostic test of agreement and reproducibility.

  14. Smoldering multiple myeloma: pathophysiologic insights, novel diagnostics, clinical risk models, and treatment strategies.

    Science.gov (United States)

    Kazandjian, Dickran; Mailankody, Sham; Korde, Neha; Landgren, Ola

    2014-09-01

    Smoldering multiple myeloma (SMM) is a plasma cell disorder first described in 1980 when 6 patients were observed to meet the diagnostic criteria of multiple myeloma, defined as bone marrow plasmacytosis of 10% or greater or M protein level of 3 g/dL or greater, but did not have end-organ damage. Subsequent studies showed that the cumulative risk of SMM progression to symptomatic myeloma in 15 years was 73%. Since this time, advances have been made in understanding the biology of progression; namely, the contribution of branching evolution and microenvironment models to clonal heterogeneity. In parallel to this, clinical risk models using standard platforms of serum, bone marrow, and fluorescence in situ hybridization markers along with newer technologies of flow cytometry, gene expression profiling, and magnetic resonance imaging have been developed for prognostic stratification. Treatment has extended to the early myeloma category owing to more sensitive diagnostic approaches. The development of novel treatments will have to take into consideration our current knowledge of biological transformation. While it may be attractive to initiate early treatment in light of recent studies for high-risk SMM patients, clinical trial evidence of efficacy vs toxicity is still in its infancy. In our opinion, high-risk SMM patients should be strongly encouraged to enroll in treatment clinical trials, but treatment with unapproved agents or indications is not supported outside of trials.

  15. 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

  16. A General Latent Class Model for Performance Evaluation of Diagnostic Tests in the Absence of a Gold Standard: An Application to Chagas Disease

    Directory of Open Access Journals (Sweden)

    Gilberto de Araujo Pereira

    2012-01-01

    Full Text Available We propose a new general Bayesian latent class model for evaluation of the performance of multiple diagnostic tests in situations in which no gold standard test exists based on a computationally intensive approach. The modeling represents an interesting and suitable alternative to models with complex structures that involve the general case of several conditionally independent diagnostic tests, covariates, and strata with different disease prevalences. The technique of stratifying the population according to different disease prevalence rates does not add further marked complexity to the modeling, but it makes the model more flexible and interpretable. To illustrate the general model proposed, we evaluate the performance of six diagnostic screening tests for Chagas disease considering some epidemiological variables. Serology at the time of donation (negative, positive, inconclusive was considered as a factor of stratification in the model. The general model with stratification of the population performed better in comparison with its concurrents without stratification. The group formed by the testing laboratory Biomanguinhos FIOCRUZ-kit (c-ELISA and rec-ELISA is the best option in the confirmation process by presenting false-negative rate of 0.0002% from the serial scheme. We are 100% sure that the donor is healthy when these two tests have negative results and he is chagasic when they have positive results.

  17. The Diagnostic Efficacy of Cone-beam Computed Tomography in Endodontics: A Systematic Review and Analysis by a Hierarchical Model of Efficacy.

    Science.gov (United States)

    Rosen, Eyal; Taschieri, Silvio; Del Fabbro, Massimo; Beitlitum, Ilan; Tsesis, Igor

    2015-07-01

    The aim of this study was to evaluate the diagnostic efficacy of cone-beam computed tomographic (CBCT) imaging in endodontics based on a systematic search and analysis of the literature using an efficacy model. A systematic search of the literature was performed to identify studies evaluating the use of CBCT imaging in endodontics. The identified studies were subjected to strict inclusion criteria followed by an analysis using a hierarchical model of efficacy (model) designed for appraisal of the literature on the levels of efficacy of a diagnostic imaging modality. Initially, 485 possible relevant articles were identified. After title and abstract screening and a full-text evaluation, 58 articles (12%) that met the inclusion criteria were analyzed and allocated to levels of efficacy. Most eligible articles (n = 52, 90%) evaluated technical characteristics or the accuracy of CBCT imaging, which was defined in this model as low levels of efficacy. Only 6 articles (10%) proclaimed to evaluate the efficacy of CBCT imaging to support the practitioner's decision making; treatment planning; and, ultimately, the treatment outcome, which was defined as higher levels of efficacy. The expected ultimate benefit of CBCT imaging to the endodontic patient as evaluated by its level of diagnostic efficacy is unclear and is mainly limited to its technical and diagnostic accuracy efficacies. Even for these low levels of efficacy, current knowledge is limited. Therefore, a cautious and rational approach is advised when considering CBCT imaging for endodontic purposes. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

  18. Suprathermal electron studies in Tokamak plasmas by means of diagnostic measurements and modeling

    International Nuclear Information System (INIS)

    Kamleitner, J.

    2015-01-01

    To achieve reactor-relevant conditions in a tokamak plasma, auxiliary heating systems are required and can be realized by waves injected in the plasma that heat ions or electrons. Electron cyclotron resonant heating (ECRH) is a very flexible and robust technique featuring localized power deposition and current drive (CD) capabilities. Its fundamental principles are well understood and the application of ECRH is a proven and established tool; electron cyclotron current drive (ECCD) is regularly used to develop advanced scenarios and control magneto-hydrodynamics (MHD) instabilities in the plasma by tailoring the current profile. There remain important open questions, such as the phase space dynamics, the observed radial broadening of the supra-thermal electron distribution function and discrepancies in predicted and experimental CD efficiency. A main goal is to improve the understanding of wave-particle interaction in plasmas and current drive mechanisms. This was accomplished by combined experimental and numerical studies, strongly based on the conjunction of hard X-ray (HXR) Bremsstrahlung measurements and Fokker-Planck modelling, characterizing the supra-thermal electron population. The hard X-ray tomographic spectrometer (HXRS) diagnostic was developed to perform these studies by investigating spatial HXR emission asymmetries in the co- and counter-current directions and within the poloidal plane. The system uses cadmium-telluride detectors and digital acquisition to store the complete time history of incoming photon pulses. An extensive study of digital pulse processing algorithms was performed and its application allows the HXRS to handle high count rates in a noisy tokamak environment. Numerical tools were developed to improve the time resolution by conditional averaging and to obtain local information with the general tomographic inversion package. The interfaces of the LUKE code and the well-established CQL3D Fokker-Planck code to the Tokamak a

  19. Suprathermal electron studies in Tokamak plasmas by means of diagnostic measurements and modeling

    Energy Technology Data Exchange (ETDEWEB)

    Kamleitner, J.

    2015-07-01

    To achieve reactor-relevant conditions in a tokamak plasma, auxiliary heating systems are required and can be realized by waves injected in the plasma that heat ions or electrons. Electron cyclotron resonant heating (ECRH) is a very flexible and robust technique featuring localized power deposition and current drive (CD) capabilities. Its fundamental principles are well understood and the application of ECRH is a proven and established tool; electron cyclotron current drive (ECCD) is regularly used to develop advanced scenarios and control magneto-hydrodynamics (MHD) instabilities in the plasma by tailoring the current profile. There remain important open questions, such as the phase space dynamics, the observed radial broadening of the supra-thermal electron distribution function and discrepancies in predicted and experimental CD efficiency. A main goal is to improve the understanding of wave-particle interaction in plasmas and current drive mechanisms. This was accomplished by combined experimental and numerical studies, strongly based on the conjunction of hard X-ray (HXR) Bremsstrahlung measurements and Fokker-Planck modelling, characterizing the supra-thermal electron population. The hard X-ray tomographic spectrometer (HXRS) diagnostic was developed to perform these studies by investigating spatial HXR emission asymmetries in the co- and counter-current directions and within the poloidal plane. The system uses cadmium-telluride detectors and digital acquisition to store the complete time history of incoming photon pulses. An extensive study of digital pulse processing algorithms was performed and its application allows the HXRS to handle high count rates in a noisy tokamak environment. Numerical tools were developed to improve the time resolution by conditional averaging and to obtain local information with the general tomographic inversion package. The interfaces of the LUKE code and the well-established CQL3D Fokker-Planck code to the Tokamak a

  20. Hybrid approach for fault diagnosis based on multilevel flow model and information fusion of nuclear power plant

    International Nuclear Information System (INIS)

    Ma Jie; Guo Lifeng; Zhang Yusheng; Peng Qiao; Ruan Minzhi

    2011-01-01

    In order to improve the ability of condition monitoring and fault diagnostic system, a hybrid intelligent diagnostic system based on multilevel flow model (MFM) and information fusion was proposed. This method utilized information fusion technique to improve the rapidness and veracity of fault diagnosis, and made use of MFM to explain the alarm propagation path, which could enhance the comprehension of diagnostic result. The emulation test proves that the hybrid intelligent diagnostic system can identify fault and propose the alarm analysis quickly. (authors)

  1. Diagnostic x-ray exposure increases the risk of thyroid microcarcinoma: a population-based case-control study

    Science.gov (United States)

    Zhang, Yawei; Chen, Yingtai; Huang, Huang; Sandler, Jason; Dai, Min; Ma, Shuangge; Udelsman, Robert

    2015-01-01

    Objective Thyroid cancer incidence and diagnostic x-ray exposures, particularly CT scans and nuclear medicine examinations have increased substantially in the United States. However, very few epidemiologic studies have directly investigated their associations. Methods A population-based case-control study was conducted in Connecticut in 2010–2011 including 462 histologically confirmed incident thyroid cancer cases and 498 population-based controls. Multivariate unconditional logistic regression models were used to estimate the associations between diagnostic x-rays and risk of thyroid cancer controlling for potential confounding factors. Results Exposure to any diagnostic x-rays was associated with an increased risk of well-differentiated thyroid microcarcinoma (tumor size ≤10 mm, OR=2.76, 95%CI: 1.31–5.81). The highest risk increase occurred with nuclear medicine examinations (excluding cardiology tests and thyroid uptake studies; OR=5.47, 95%CI: 2.10–14.23), followed by chest CT scans (OR=4.30, 95%CI: 1.66–11.14), head and neck CT scans (OR=3.88, 95%CI: 1.75–8.63), upper gastrointestinal series (OR=3.56, 95%CI: 1.54–8.21), lower gastrointestinal series (OR=3.29, 95%CI: 1.41–7.66), kidney x-rays involving dye injection into a vein or artery (OR=3.21, 95%CI: 1.20–8.54), mammograms (OR=2.95, 95%CI: 1.14–7.61), chest x-rays (OR=2.93, 95%CI: 1.37–6.29), and abdomen CT scans (OR=2.54, 95%CI: 1.02–6.30). No significant associations were found between these imaging modalities and thyroid tumors larger than 10 mm. Conclusions This study provides the first direct evidence that CT scans and nuclear medicine examinations are associated with an increased risk of thyroid cancer. The novel finding that an array of diagnostic x-ray procedures are associated thyroid microcarcinomas warrants further investigation. PMID:25932870

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

    International Nuclear Information System (INIS)

    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

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

    International Nuclear Information System (INIS)

    Eggert, H.; Scherer, K.P.; Stiller, P.

    1989-01-01

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

  4. Guided waves based diagnostic imaging of circumferential cracks in small-diameter pipe.

    Science.gov (United States)

    Liu, Kehai; Wu, Zhanjun; Jiang, Youqiang; Wang, Yishou; Zhou, Kai; Chen, Yingpu

    2016-02-01

    To improve the safety and reliability of pipeline structures, much work has been done using ultrasonic guided waves methods for pipe inspection. Though good for evaluating the defects in the pipes, most of the methods lack the capability to precisely identify the defects in the pipe features like welds or supports. Therefore, a novel guided wave based cross-sectional diagnostic imaging algorithm was developed to improve the ability of circumferential cracks identification in the pipe features. To ensure the accuracy of the imaging, an angular profile-based frequency selection method is presented. As validation, the approach was employed to identify the presence and location of a small circumferential crack with 1.13% cross sectional area (CSA) in the welding zone of a 48 mm diameter type 304 stainless steel pipe. Accurate identification results have demonstrated the effectiveness of the developed approach. Copyright © 2015. Published by Elsevier B.V.

  5. Diagnostic tools for evaluating quasi-horizontal transport in global-scale chemistry models

    Science.gov (United States)

    Lee, Huikyo; Youn, Daeok; Patten, Kenneth O.; Olsen, Seth C.; Wuebbles, Donald J.

    2012-10-01

    The upper troposphere and lower stratosphere (UTLS) plays an important role in climate and atmospheric chemistry. Despite its importance on the point of causing deep intrusions of tropics originated air into the midlatitudes, the quasi-horizontal transport process in the UTLS, represented by global chemistry-transport models (CTMs) or chemistry-climate models (CCMs), cannot easily be diagnosed with conventional analyses on isobaric surfaces. We use improved diagnostic tools to better evaluate CTMs and CCMs relative to satellite observations in the region of UTLS. Using the Hellinger distance, vertical profiles of probability density functions (PDFs) of chemical tracers simulated by the Model for OZone And Related chemical Tracers 3.1 (MOZART-3.1) are quantitatively compared with satellite data from the Microwave Limb Sounder (MLS) instrument in the tropopause relative altitude coordinate to characterize features of tracer distributions near the tropopause. Overall, the comparison of PDFs between MLS and MOZART-3.1 did not satisfy the same population assumption. Conditional PDFs are used to understand the meteorological differences between global climate models and the real atmosphere and the conditional PDFs between MOZART-3.1 and MLS showed better agreement compared to the original PDFs. The low static stability during high tropopause heights at midlatitudes suggests that the variation of tropopause height is related to transport processes from the tropics to midlatitudes. MOZART-3.1 with the GEOS4 GCM winds reproduces episodes of the tropical air intrusions. However, our diagnostic analyses show that the GEOS4 GCM did not properly reproduce the high tropopause cases at midlatitudes especially in spring.

  6. Model-Based Real Time Assessment of Capability Left for Spacecraft Under Failure Mode, Phase I

    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...

  7. Three-Dimensional Visual Patient Based on Electronic Medical Diagnostic Records.

    Science.gov (United States)

    Shi, Liehang; Sun, Jianyong; Yang, Yuanyuan; Ling, Tonghui; Wang, Mingqing; Gu, Yiping; Yang, Zhiming; Hua, Yanqing; Zhang, Jianguo

    2018-01-01

    an innovative concept and method is introduced to use a 3-D anatomical graphic pattern called visual patient (VP) visually to index, represent, and render the medical diagnostic records (MDRs) of a patient, so that a doctor can quickly learn the current and historical medical status of the patient by manipulating VP. The MDRs can be imaging diagnostic reports and DICOM images, laboratory reports and clinical summaries which can have clinical information relating to medical status of human organs or body parts. the concept and method included three steps. First, a VP data model called visual index object (VIO) and a VP graphic model called visual anatomic object (VAO) were introduced. Second, a series of processing methods of parsing and extracting key information from MDRs were used to fill the attributes of the VIO model of a patient. Third, a VP system (VPS) was designed to map VIO to VAO, to create a VP instance for each patient. a prototype VPS has been implemented in a simulated hospital PACS/RIS integrated environment. Two evaluation results showed that more than 70% participating radiologists would like to use the VPS in their radiological imaging tasks, and the efficiency of using VPS to review the tested patients' MDRs was 2.24 times higher than that of using PACS/RIS, while the average accuracy by using PACS/RIS was better than that by using VPS; however, this difference was only about 4%. the developed VPS can show the medical status of patient organs/sub-organs with 3-D anatomical graphic pattern and will be welcomed by radiologists with better efficiency in reviewing the patients' MDRs and with acceptable accuracy. the VP introduces a new way for medical professionals to access and interact with a huge amount of patient records with better efficiency in the big data era.

  8. 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

  9. 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.; hide

    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.

  10. Isolated clinic hypertension: diagnostic criteria based on 24-h blood pressure definition.

    Science.gov (United States)

    Vinyoles, Ernest; Rodriguez-Blanco, Teresa; de la Sierra, Alejandro; Felip, Angela; Banegas, José R; de la Cruz, Juan J; Gorostidi, Manuel; Sobrino, Javier; Segura, Julián; Roca-Cusachs, Alex; Ruilope, Luís M

    2010-12-01

    The use of diagnostic criteria based on 24-h ambulatory blood pressure (BP) values could improve prognostic value by incorporating night BP, minimize biases and improve the diagnostic reproducibility of isolated clinic hypertension (ICH). We estimate the 24-h BP cut-off points that best discriminate and predict the two diagnostic thresholds of mean daytime BP for ICH (135/85 and 130/80 mmHg). Cross-sectional, comparative, multicentre study in 6176 untreated hypertensive patients, whose BP was measured by ambulatory BP monitoring. ICH was defined with an office BP of ≥140/≥90 mmHg and a daytime BP of <135/<85 mmHg (ICH1) or <130/80 mmHg (ICH2). Sensitivity, specificity, positive likelihood ratio (LR+), odds ratio (OR), error rate, predictive values, κ values and 95% confidence interval were calculated for each possible cut-off point for ICH1 and ICH2. One thousand eight hundred and seven patients (29.2%) and 960 patients (15.5%) met ICH1 and ICH2 criteria, respectively. The 24-h BP cut-off points that best predict ICH1 and ICH2 are less than 132/82 mmHg (sensitivity: 93.6%, specificity: 94.3%, LR+: 16.6, OR: 1367.1, error rate: 5.9, κ 0.86) and less than 127/77 mmHg (sensitivity: 90.8%, specificity: 97.4%, LR+: 34.6, OR: 1041.5, error rate: 3.6,κ 0.86), respectively. These values achieved the best balance of sensitivity and specificity, together with the highest values of LR+ and OR and the lowest error rate. The 24-h BP cut-off point that best predicts the daytime criterion of less than 135/85 and less than 130/80 mmHg are 132/82 and 127/77 mmHg, respectively. These 24-h cut-off points may add value to ambulatory blood pressure monitoring for both diagnostic and management future decisions.

  11. DIAGNOSTICS OF MOTOR ABILITY AS A BASE OF CORRECTION PLANNING OF TRANSFORMATION PROCESSES IN SPECIAL POPULATIONS

    Directory of Open Access Journals (Sweden)

    Kosta Goranović

    2011-08-01

    Full Text Available In the research, at sample of 80 tested, employees in the special police force, as representatives of police population age from 20 to 25, diagnostics of motor potential in transitive period of annual macrostructure was done. The aim of the research was doing potential correction in planning and programming of transformation process in the next cycles of sports preparation on the base of diagnosed quantitative value of motor abilities. Besides analyses of achieved values, the difference was established between two leading teams in the space of measuring potential. The research results indicated to statistically important differences between two groups of tested people, as well as to unacceptable level of development in some abilities. The achieved results are, from aspect of training process’ control, the indicator to instructors’ team on the need of correction of transformation process’ content, with aim of improving bad segments. Diagnostics of motor abilities with measuring instruments in terrain conditions is one of methods, which can be in function of valorising transformation process of the special police force, taking into account specifics of their professional manifestation.

  12. Laboratory-based validation of the baseline sensors of the ITER diagnostic residual gas analyzer

    Energy Technology Data Exchange (ETDEWEB)

    Biewer, Theodore M. [ORNL; Marcus, Chris [ORNL; Klepper, C Christopher [ORNL; Andrew, Philip [ITER Organization, Cadarache, France; Gardner, W. L. [United States ITER Project Office; Graves, Van B. [ORNL; Hughes, Shaun [ITER Organization, Saint Paul Lez Durance, France

    2017-10-01

    The divertor-specific ITER Diagnostic Residual Gas Analyzer (DRGA) will provide essential information relating to DT fusion plasma performance. This includes pulse-resolving measurements of the fuel isotopic mix reaching the pumping ducts, as well as the concentration of the helium generated as the ash of the fusion reaction. In the present baseline design, the cluster of sensors attached to this diagnostic's differentially pumped analysis chamber assembly includes a radiation compatible version of a commercial quadrupole mass spectrometer, as well as an optical gas analyzer using a plasma-based light excitation source. This paper reports on a laboratory study intended to validate the performance of this sensor cluster, with emphasis on the detection limit of the isotopic measurement. This validation study was carried out in a laboratory set-up that closely prototyped the analysis chamber assembly configuration of the baseline design. This includes an ITER-specific placement of the optical gas measurement downstream from the first turbine of the chamber's turbo-molecular pump to provide sufficient light emission while preserving the gas dynamics conditions that allow for \\textasciitilde 1 s response time from the sensor cluster [1].

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

    International Nuclear Information System (INIS)

    Hada, Mahesh Singh; Chakravarty, Abhijit; Mukherjee, Partha

    2014-01-01

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

  14. Development of a diagnostic decision tree for obstructive pulmonary diseases based on real-life data

    Directory of Open Access Journals (Sweden)

    Esther I. Metting

    2016-01-01

    Full Text Available The aim of this study was to develop and explore the diagnostic accuracy of a decision tree derived from a large real-life primary care population. Data from 9297 primary care patients (45% male, mean age 53±17 years with suspicion of an obstructive pulmonary disease was derived from an asthma/chronic obstructive pulmonary disease (COPD service where patients were assessed using spirometry, the Asthma Control Questionnaire, the Clinical COPD Questionnaire, history data and medication use. All patients were diagnosed through the Internet by a pulmonologist. The Chi-squared Automatic Interaction Detection method was used to build the decision tree. The tree was externally validated in another real-life primary care population (n=3215. Our tree correctly diagnosed 79% of the asthma patients, 85% of the COPD patients and 32% of the asthma–COPD overlap syndrome (ACOS patients. External validation showed a comparable pattern (correct: asthma 78%, COPD 83%, ACOS 24%. Our decision tree is considered to be promising because it was based on real-life primary care patients with a specialist's diagnosis. In most patients the diagnosis could be correctly predicted. Predicting ACOS, however, remained a challenge. The total decision tree can be implemented in computer-assisted diagnostic systems for individual patients. A simplified version of this tree can be used in daily clinical practice as a desk tool.

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

    Science.gov (United States)

    Hada, Mahesh Singh; Chakravarty, Abhijit; Mukherjee, Partha

    2014-10-01

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

  16. Gravimetric Viral Diagnostics: QCM Based Biosensors for Early Detection of Viruses

    Directory of Open Access Journals (Sweden)

    Adeel Afzal

    2017-02-01

    Full Text Available Viruses are pathogenic microorganisms that can inhabit and replicate in human bodies causing a number of widespread infectious diseases such as influenza, gastroenteritis, hepatitis, meningitis, pneumonia, acquired immune deficiency syndrome (AIDS etc. A majority of these viral diseases are contagious and can spread from infected to healthy human beings. The most important step in the treatment of these contagious diseases and to prevent their unwanted spread is to timely detect the disease-causing viruses. Gravimetric viral diagnostics based on quartz crystal microbalance (QCM transducers and natural or synthetic receptors are miniaturized sensing platforms that can selectively recognize and quantify harmful virus species. Herein, a review of the label-free QCM virus sensors for clinical diagnostics and point of care (POC applications is presented with major emphasis on the nature and performance of different receptors ranging from the natural or synthetic antibodies to selective macromolecular materials such as DNA and aptamers. A performance comparison of different receptors is provided and their limitations are discussed.

  17. Laboratory-based validation of the baseline sensors of the ITER diagnostic residual gas analyzer

    Science.gov (United States)

    Klepper, C. C.; Biewer, T. M.; Marcus, C.; Andrew, P.; Gardner, W. L.; Graves, V. B.; Hughes, S.

    2017-10-01

    The divertor-specific ITER Diagnostic Residual Gas Analyzer (DRGA) will provide essential information relating to DT fusion plasma performance. This includes pulse-resolving measurements of the fuel isotopic mix reaching the pumping ducts, as well as the concentration of the helium generated as the ash of the fusion reaction. In the present baseline design, the cluster of sensors attached to this diagnostic's differentially pumped analysis chamber assembly includes a radiation compatible version of a commercial quadrupole mass spectrometer, as well as an optical gas analyzer using a plasma-based light excitation source. This paper reports on a laboratory study intended to validate the performance of this sensor cluster, with emphasis on the detection limit of the isotopic measurement. This validation study was carried out in a laboratory set-up that closely prototyped the analysis chamber assembly configuration of the baseline design. This includes an ITER-specific placement of the optical gas measurement downstream from the first turbine of the chamber's turbo-molecular pump to provide sufficient light emission while preserving the gas dynamics conditions that allow for \\textasciitilde 1 s response time from the sensor cluster [1].

  18. THE DIAGNOSTICS OF INDUCTION MOTORS ROTOR BAR BREAKS BASED ON THE ANALYSIS OF ELECTROMOTIVE FORCE IN THE STATOR WINDINGS

    Directory of Open Access Journals (Sweden)

    M.V. Zagirnyak

    2014-12-01

    Full Text Available A method for diagnostics of the induction motor rotor bar breaks, based on the wavelet-analysis of the electromotive force induced in the stator windings in the rundown mode is developed. A method for decomposition of the electromotive force of the stator winding phase to the electromotive force signals of the active sides of winding coils using Z-transformation theory is developed. The effectiveness of the proposed diagnostic method was experimentally confirmed.

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

    Science.gov (United States)

    Perell, Katharina; Vincent, Martin; Vainer, Ben; Petersen, Bodil Laub; Federspiel, Birgitte; Møller, Anne Kirstine; Madsen, Mette; Hansen, Niels Richard; Friis-Hansen, Lennart; Nielsen, Finn Cilius; Daugaard, Gedske

    2015-01-01

    Identification of the primary tumor site in patients with metastatic cancer is clinically important, but remains a challenge. Hence, efforts have been made towards establishing new diagnostic tools. Molecular profiling is a promising diagnostic approach, but tissue heterogeneity and inadequacy may negatively affect the accuracy and usability of molecular classifiers. We have developed and validated a microRNA-based classifier, which predicts the primary tumor site of liver biopsies, containing a limited number of tumor cells. Concurrently we explored the influence of surrounding normal tissue on classification. MicroRNA profiling was performed using quantitative Real-Time PCR on formalin-fixed paraffin-embedded samples. 278 primary tumors and liver metastases, representing nine primary tumor classes, as well as normal liver samples were used as a training set. A statistical model was applied to adjust for normal liver tissue contamination. Performance was estimated by cross-validation, followed by independent validation on 55 liver core biopsies with a tumor content as low as 10%. A microRNA classifier developed, using the statistical contamination model, showed an overall classification accuracy of 74.5% upon independent validation. Two-thirds of the samples were classified with high-confidence, with an accuracy of 92% on high-confidence predictions. A classifier trained without adjusting for liver tissue contamination, showed a classification accuracy of 38.2%. Our results indicate that surrounding normal tissue from the biopsy site may critically influence molecular classification. A significant improvement in classification accuracy was obtained when the influence of normal tissue was limited by application of a statistical contamination model. Copyright © 2014 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

  20. The application of multiloop diagnostics model to assess and improve the economic security of enterprises

    Directory of Open Access Journals (Sweden)

    Pluzhnikov Vladimir

    2017-01-01

    Full Text Available The author’s research is dedicated to the enhancement of the level of the enterprise economic safety. This task involves developing the concept of an integrated system for early prevention of dangers and threats of business activity, substantiation of procedures for regulating the activities of the enterprise in accordance with the changing external and internal factors. Multiloop diagnostics model is proposed to identify causal relations of management dysfunction. It allows you to receive an adequate assessment of the basic parameters of activity of the enterprise and accurately identify its status. Researching problems of economic safety of the enterprise such diagnostic methods as economic and logical analysis, statistical monitoring and strategic management were applied. There was made a conclusion that a qualitative assessment is a key tool of the level assessment of the enterprise economic safety, its control, and monitoring. It allows you to get reliable information about the real possibilities of the enterprise at different stages of development, to monitor and evaluate the level of economic security, find effective solutions to transition to a higher level of economic safety of the enterprise.

  1. [The interplay of diagnostic and antimicrobial stewardship for the management of septic patients: the Tuscan model.

    Science.gov (United States)

    Forni, Silvia; Toccafondi, Giulio; Viaggi, Bruno; Grazzini, Maddalena; D'Arienzo, Sara; Gemmi, Fabrizio; Vannucci, Andrea; Tulli, Giorgio

    2018-02-01

    Antimicrobial resistance is a global threat caused by the rapid spread of multiresistant microorganisms. Antimicrobial stewardship (AS) is a coordinated intervention designed to improve the appropriate use of antimicrobials by promoting the selection of the optimal drug regimen, dose, duration of therapy and route of administration. AS programs have proved effective in reducing antimicrobial resistance, inappropriate antimicrobial use and in improving patient outcomes. Recently developed rapid diagnostic technologies in microbiology (RDTM) allows a faster and etiological diagnosis of infection and a reduction in the use of unnecessary empirical therapies. This may result in important advancement in time-critical care pathways for septic patients. Nevertheless, RDTM are costly and if not rationally positioned may consume resources and hinder the efficacy of AS programs. In this regard, Tuscany Region is engaged in designing, through a systemic approach, an effective high-quality clinical microbiological service grid. In order to develop a sustainable and equitable model for integrating diagnostic and antimicrobial stewardship we conducted a survey in the regional network of 14 microbiological laboratories. The results shows that in order to develop a sustainable service we need to improve the communication at the interface between laboratories and care unit, harmonize the time windows for processing samples and to devise a robust score for stratifying patient with suspected sepsis.

  2. An empirical model of diagnostic x-ray attenuation under narrow-beam geometry

    International Nuclear Information System (INIS)

    Mathieu, Kelsey B.; Kappadath, S. Cheenu; White, R. Allen; Atkinson, E. Neely; Cody, Dianna D.

    2011-01-01

    Purpose: The purpose of this study was to develop and validate a mathematical model to describe narrow-beam attenuation of kilovoltage x-ray beams for the intended applications of half-value layer (HVL) and quarter-value layer (QVL) estimations, patient organ shielding, and computer modeling. Methods: An empirical model, which uses the Lambert W function and represents a generalized Lambert-Beer law, was developed. To validate this model, transmission of diagnostic energy x-ray beams was measured over a wide range of attenuator thicknesses [0.49-33.03 mm Al on a computed tomography (CT) scanner, 0.09-1.93 mm Al on two mammography systems, and 0.1-0.45 mm Cu and 0.49-14.87 mm Al using general radiography]. Exposure measurements were acquired under narrow-beam geometry using standard methods, including the appropriate ionization chamber, for each radiographic system. Nonlinear regression was used to find the best-fit curve of the proposed Lambert W model to each measured transmission versus attenuator thickness data set. In addition to validating the Lambert W model, we also assessed the performance of two-point Lambert W interpolation compared to traditional methods for estimating the HVL and QVL [i.e., semilogarithmic (exponential) and linear interpolation]. Results: The Lambert W model was validated for modeling attenuation versus attenuator thickness with respect to the data collected in this study (R 2 > 0.99). Furthermore, Lambert W interpolation was more accurate and less sensitive to the choice of interpolation points used to estimate the HVL and/or QVL than the traditional methods of semilogarithmic and linear interpolation. Conclusions: The proposed Lambert W model accurately describes attenuation of both monoenergetic radiation and (kilovoltage) polyenergetic beams (under narrow-beam geometry).

  3. The development of a hassle-based diagnostic scale for predicting burnout in call centres

    Directory of Open Access Journals (Sweden)

    Willie A. Visser

    2009-08-01

    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. Knowledge-based process control and diagnostics for orbital cryogen transfer

    Science.gov (United States)

    Raymond, Eric A.

    1989-01-01

    AFDex is a rule based system designed to provide intelligent process control, diagnosis, and error recovery for a Shuttle based cryogenic experiment, SHOOT (Superfluid Helium On-Orbit Transfer). This paper describes the AFDex system in the context of traditional associative, model-based, and qualitative systems and discusses the implications of this first expert system in space.

  5. STARD-BLCM: Standards for the Reporting of Diagnostic accuracy studies that use Bayesian Latent Class Models

    DEFF Research Database (Denmark)

    Kostoulas, Polychronis; Nielsen, Søren S.; Branscum, Adam J.

    2017-01-01

    . In such cases, a valid alternative to classical test evaluation involves the use of latent class models that do not require a priori knowledge of disease status. Latent class models have been successfully implemented in a Bayesian framework for over 20 years. The objective of this work was to identify the STARD...... items that require modification and develop a modified version of STARD for studies that use Bayesian latent class analysis to estimate diagnostic test accuracy in the absence of a reference standard. Examples and elaborations for each of the modified items are provided. The new guidelines, termed STARD......-BLCM (Standards for Reporting of Diagnostic accuracy studies that use Bayesian Latent Class Models), will facilitate improved quality of reporting on the design, conduct and results of diagnostic accuracy studies that use Bayesian latent class models....

  6. Development of Laser Based Plasma Diagnostics for Fusion Research on NSTX-U

    Science.gov (United States)

    Barchfeld, Robert Adam

    plasma diagnostics. Plasma diagnostics collect data from fusion reactors in a number of different ways. Among these are far infrared (FIR) laser based systems. By probing a fusion plasma with FIR lasers, many properties can be measured, such as density and density fluctuations. This dissertation discusses the theory and design of two laser based diagnostic instruments: 1) the Far Infrared Tangential Interferometer and Polarimeter (FIReTIP) systems, and 2) the High-ktheta Scattering System. Both of these systems have been designed and fabricated at UC Davis for use on the National Spherical Torus Experiment - Upgrade (NSTX-U), located at Princeton Plasma Physics Laboratory (PPPL). These systems will aid PPPL scientists in fusion research. The FIReTIP system uses 119 ?m methanol lasers to pass through the plasma core to measure a chord averaged plasma density through interferometry. It can also measure the toroidal magnetic field strength by the way of polarimetery. The High-ktheta Scattering System uses a 693 GHz formic acid laser to measure electron scale turbulence. Through collective Thomson scattering, as the probe beam passes through the plasma, collective electron motion will scatter power to a receiver with the angle determined by the turbulence wavenumber. This diagnostic will measure ktheta from 7 to 40 cm-1 with a 4-channel receiver array. The High-ktheta Scattering system was designed to facilitate research on electron temperature gradient (ETG) modes, which are believed to be a major contributor to anomalous transport on NSTX-U. The design and testing of these plasma diagnostics are described in detail. There are a broad range of components detailed including: optically pumped gas FIR lasers, overmoded low loss waveguide, launching and receiving optical designs, quasi-optical mixers, electronics, and monitoring and control systems. Additionally, details are provided for laser maintenance, alignment techniques, and the fundamentals of nano-CNC-machining.

  7. 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...

  8. 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...

  9. Aptamer-based radiopharmaceuticals for diagnostic imaging and targeted radiotherapy of epithelial tumors

    Energy Technology Data Exchange (ETDEWEB)

    Missailidis, Sotiris [The Open University, Milton Keynes (United Kingdom). Dept. of Chemistry and Analytical Sciences]. E-mail: s.missailidis@open.ac.uk; Perkins, Alan [University of Nottingham (United Kingdom). Dept. of Medical Physics; Santos-Filho, Sebastiao David; Fonseca, Adenilson de Souza da; Bernardo-Filho, Mario [Universidade do Estado do Rio de Janeiro (UERJ), RJ (Brazil). Inst. de Biologia Roberto Alcantara Gomes. Dept. de Biofisica e Biometria

    2008-12-15

    In the continuous search for earlier diagnosis and improved therapeutic modalities against cancer, based on our constantly increasing knowledge of cancer biology, aptamers hold the promise to expand on current antibody success, but overcoming some of the problems faced with antibodies as therapeutic or delivery agents in cancer. However, as the first aptamer reached the market as an inhibitor against angiogenesis for the treatment of macular degeneration, aptamers have found only limited applications or interest in oncology, and even less as radiopharmaceuticals for diagnostic imaging and targeted radiotherapy of tumours. Yet, the chemistry for the labelling of aptamers and the options to alter their pharmacokinetic properties, to make them suitable for use as radiopharmaceuticals is now available and recent advances in their development can demonstrate that these molecules would make them ideal delivery vehicles for the development of targeted radiopharmaceuticals that could deliver their radiation load with accuracy to the tumour site, offering improved therapeutic properties and reduced side effects. (author)

  10. Recent Developments in Synthetic Carbohydrate-Based Diagnostics, Vaccines, and Therapeutics.

    Science.gov (United States)

    Fernández-Tejada, Alberto; Cañada, F Javier; Jiménez-Barbero, Jesús

    2015-07-20

    Glycans are everywhere in biological systems, being involved in many cellular events with important implications for medical purposes. Building upon a detailed understanding of the functional roles of carbohydrates in molecular recognition processes and disease states, glycans are increasingly being considered as key players in pharmacological research. On the basis of the important progress recently made in glycochemistry, glycobiology, and glycomedicine, we provide a complete overview of successful applications and future perspectives of carbohydrates in the biopharmaceutical and medical fields. This review highlights the development of carbohydrate-based diagnostics, exemplified by glycan imaging techniques and microarray platforms, synthetic oligosaccharide vaccines against infectious diseases (e.g., HIV) and cancer, and finally carbohydrate-derived therapeutics, including glycomimetic drugs and glycoproteins. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Tomographic capabilities of the new GEM based SXR diagnostic of WEST

    Science.gov (United States)

    Jardin, A.; Mazon, D.; O'Mullane, M.; Mlynar, J.; Loffelmann, V.; Imrisek, M.; Chernyshova, M.; Czarski, T.; Kasprowicz, G.; Wojenski, A.; Bourdelle, C.; Malard, P.

    2016-07-01

    The tokamak WEST (Tungsten Environment in Steady-State Tokamak) will start operating by the end of 2016 as a test bed for the ITER divertor components in long pulse operation. In this context, radiative cooling of heavy impurities like tungsten (W) in the Soft X-ray (SXR) range [0.1 keV; 20 keV] is a critical issue for the plasma core performances. Thus reliable tools are required to monitor the local impurity density and avoid W accumulation. The WEST SXR diagnostic will be equipped with two new GEM (Gas Electron Multiplier) based poloidal cameras allowing to perform 2D tomographic reconstructions in tunable energy bands. In this paper tomographic capabilities of the Minimum Fisher Information (MFI) algorithm developed for Tore Supra and upgraded for WEST are investigated, in particular through a set of emissivity phantoms and the standard WEST scenario including reconstruction errors, influence of noise as well as computational time.

  12. Aptamer-based radiopharmaceuticals for diagnostic imaging and targeted radiotherapy of epithelial tumors

    International Nuclear Information System (INIS)

    Missailidis, Sotiris; Perkins, Alan; Santos-Filho, Sebastiao David; Fonseca, Adenilson de Souza da; Bernardo-Filho, Mario

    2008-01-01

    In the continuous search for earlier diagnosis and improved therapeutic modalities against cancer, based on our constantly increasing knowledge of cancer biology, aptamers hold the promise to expand on current antibody success, but overcoming some of the problems faced with antibodies as therapeutic or delivery agents in cancer. However, as the first aptamer reached the market as an inhibitor against angiogenesis for the treatment of macular degeneration, aptamers have found only limited applications or interest in oncology, and even less as radiopharmaceuticals for diagnostic imaging and targeted radiotherapy of tumours. Yet, the chemistry for the labelling of aptamers and the options to alter their pharmacokinetic properties, to make them suitable for use as radiopharmaceuticals is now available and recent advances in their development can demonstrate that these molecules would make them ideal delivery vehicles for the development of targeted radiopharmaceuticals that could deliver their radiation load with accuracy to the tumour site, offering improved therapeutic properties and reduced side effects. (author)

  13. Model-Based Diagnosis in a Power Distribution Test-Bed

    Science.gov (United States)

    Scarl, E.; McCall, K.

    1998-01-01

    The Rodon model-based diagnosis shell was applied to a breadboard test-bed, modeling an automated power distribution system. The constraint-based modeling paradigm and diagnostic algorithm were found to adequately represent the selected set of test scenarios.

  14. Accurate diagnostics for Bovine tuberculosis based on high-throughput sequencing.

    Directory of Open Access Journals (Sweden)

    Alexander Churbanov

    Full Text Available BACKGROUND: Bovine tuberculosis (bTB is an enduring contagious disease of cattle that has caused substantial losses to the global livestock industry. Despite large-scale eradication efforts, bTB continues to persist. Current bTB tests rely on the measurement of immune responses in vivo (skin tests, and in vitro (bovine interferon-γ release assay. Recent developments are characterized by interrogating the expression of an increasing number of genes that participate in the immune response. Currently used assays have the disadvantages of limited sensitivity and specificity, which may lead to incomplete eradication of bTB. Moreover, bTB that reemerges from wild disease reservoirs requires early and reliable diagnostics to prevent further spread. In this work, we use high-throughput sequencing of the peripheral blood mononuclear cells (PBMCs transcriptome to identify an extensive panel of genes that participate in the immune response. We also investigate the possibility of developing a reliable bTB classification framework based on RNA-Seq reads. METHODOLOGY/PRINCIPAL FINDINGS: Pooled PBMC mRNA samples from unaffected calves as well as from those with disease progression of 1 and 2 months were sequenced using the Illumina Genome Analyzer II. More than 90 million reads were splice-aligned against the reference genome, and deposited to the database for further expression analysis and visualization. Using this database, we identified 2,312 genes that were differentially expressed in response to bTB infection (p<10(-8. We achieved a bTB infected status classification accuracy of more than 99% with split-sample validation on newly designed and learned mixtures of expression profiles. CONCLUSIONS/SIGNIFICANCE: We demonstrated that bTB can be accurately diagnosed at the early stages of disease progression based on RNA-Seq high-throughput sequencing. The inclusion of multiple genes in the diagnostic panel, combined with the superior sensitivity and broader

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

    Science.gov (United States)

    GUO, HONGFEI; ZHOU, YIJIE

    2011-01-01

    Bivariate random effect models are currently one of the main methods recommended to synthesize diagnostic test accuracy studies. However, only the logit-transformation on sensitivity and specificity has been previously considered in the literature. In this paper, we consider a bivariate generalized linear mixed model to jointly model the sensitivities and specificities, and discuss the estimation of the summary receiver operating characteristic curve (ROC) and the area under the ROC curve (AUC). As the special cases of this model, we discuss the commonly used logit, probit and complementary log-log transformations. To evaluate the impact of misspecification of the link functions on the estimation, we present two case studies and a set of simulation studies. Our study suggests that point estimation of the median sensitivity and specificity, and AUC is relatively robust to the misspecification of the link functions. However, the misspecification of link functions has a noticeable impact on the standard error estimation and the 95% confidence interval coverage, which emphasizes the importance of choosing an appropriate link function to make statistical inference. PMID:19959794

  16. Team Interaction Coaching with Educators of Adolescents Who Are Deaf-Blind: Applying the Diagnostic Intervention Model

    Science.gov (United States)

    Janssen, Marleen J.; Riksen-Walraven, J. Marianne; Van Dijk, Jan P. M.; Ruijssenaars, Wied A. J. J. M.; Vlaskamp, Carla

    2007-01-01

    In an earlier publication, we presented the Diagnostic Intervention Model, which can be used as a guide in the design and conduct of interventions to foster harmonious interactions between children who are deaf-blind and their educators. This article demonstrates the use of the model in everyday practice and the effects of its application in two…

  17. Team interaction coaching with educators of adolescents who are deaf-blind : Applying the Diagnostic Intervention Model

    NARCIS (Netherlands)

    Janssen, Marleen J.; Riksen-Walraven, J. Marianne; Van Dijk, Jan P. A.; Ruijssenaars, Wied A. J. J. M.; Vlaskarnp, Carla

    2007-01-01

    In an earlier publication, we presented the Diagnostic Intervention Model, which can be used as a guide in the design and conduct of interventions to foster harmonious interactions between children who are deaf-blind and their educators. This article demonstrates the use of the model in everyday

  18. 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.

  19. 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. Copyright © 2011 Elsevier Inc. All rights reserved.

  20. Indication-based diagnostic reference levels for adult CT-examinations in Finland.

    Science.gov (United States)

    Lajunen, A

    2015-07-01

    A diagnostic reference level (DRL) is a predefined dose level, which should not be exceeded in an examination that is conducted appropriately on an average-sized patient. Since dose from only one examination should not be compared with a DRL, the average dose from a good sample of at least 10 average-sized patients should be compared. The previous DRLs for computed tomography (CT)-examinations for adults in Finland were issued in 2007 and only covered examinations conducted on a particular body region. Because the image quality requirements, and thus the dose needed, vary between different indications, there has been a call for indication-based DRLs for CT. The new indication-based DRLs for CT came into effect on June 2013. They are based on a dose survey performed in 2012. Doses were collected from examinations conducted on a particular body region, based on some indication and from some special examination types. The DRLs were set according to the third quartile approach. On average, the DRLs for a particular body region dropped ∼ 20 % from the previous DRLs. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  1. Model-based biosignal interpretation.

    Science.gov (United States)

    Andreassen, S

    1994-03-01

    Two relatively new approaches to model-based biosignal interpretation, qualitative simulation and modelling by causal probabilistic networks, are compared to modelling by differential equations. A major problem in applying a model to an individual patient is the estimation of the parameters. The available observations are unlikely to allow a proper estimation of the parameters, and even if they do, the task appears to have exponential computational complexity if the model is non-linear. Causal probabilistic networks have both differential equation models and qualitative simulation as special cases, and they can provide both Bayesian and maximum-likelihood parameter estimates, in most cases in much less than exponential time. In addition, they can calculate the probabilities required for a decision-theoretical approach to medical decision support. The practical applicability of causal probabilistic networks to real medical problems is illustrated by a model of glucose metabolism which is used to adjust insulin therapy in type I diabetic patients.

  2. Model-based machine learning.

    Science.gov (United States)

    Bishop, Christopher M

    2013-02-13

    Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

  3. 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...

  4. 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

  5. An informatics model for guiding assembly of telemicrobiology workstations for malaria collaborative diagnostics using commodity products and open-source software.

    Science.gov (United States)

    Suhanic, West; Crandall, Ian; Pennefather, Peter

    2009-07-17

    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. 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. 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. 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 groups in a distributed and collaborative fashion. The workstation

  6. A Sensor-Based Method for Diagnostics of Machine Tool Linear Axes.

    Science.gov (United States)

    Vogl, Gregory W; Weiss, Brian A; Donmez, M Alkan

    2015-01-01

    A linear axis is a vital subsystem of machine tools, which are vital systems within many manufacturing operations. When installed and operating within a manufacturing facility, a machine tool needs to stay in good condition for parts production. All machine tools degrade during operations, yet knowledge of that degradation is illusive; specifically, accurately detecting degradation of linear axes is a manual and time-consuming process. Thus, manufacturers need automated and efficient methods to diagnose the condition of their machine tool linear axes without disruptions to production. The Prognostics and Health Management for Smart Manufacturing Systems (PHM4SMS) project at the National Institute of Standards and Technology (NIST) developed a sensor-based method to quickly estimate the performance degradation of linear axes. The multi-sensor-based method uses data collected from a 'sensor box' to identify changes in linear and angular errors due to axis degradation; the sensor box contains inclinometers, accelerometers, and rate gyroscopes to capture this data. The sensors are expected to be cost effective with respect to savings in production losses and scrapped parts for a machine tool. Numerical simulations, based on sensor bandwidth and noise specifications, show that changes in straightness and angular errors could be known with acceptable test uncertainty ratios. If a sensor box resides on a machine tool and data is collected periodically, then the degradation of the linear axes can be determined and used for diagnostics and prognostics to help optimize maintenance, production schedules, and ultimately part quality.

  7. Diagnostic accuracy of tablet-based software for the detection of concussion.

    Directory of Open Access Journals (Sweden)

    Suosuo Yang

    Full Text Available Despite the high prevalence of traumatic brain injuries (TBI, there are few rapid and straightforward tests to improve its assessment. To this end, we developed a tablet-based software battery ("BrainCheck" for concussion detection that is well suited to sports, emergency department, and clinical settings. This article is a study of the diagnostic accuracy of BrainCheck. We administered BrainCheck to 30 TBI patients and 30 pain-matched controls at a hospital Emergency Department (ED, and 538 healthy individuals at 10 control test sites. We compared the results of the tablet-based assessment against physician diagnoses derived from brain scans, clinical examination, and the SCAT3 test, a traditional measure of TBI. We found consistent distributions of normative data and high test-retest reliability. Based on these assessments, we defined a composite score that distinguishes TBI from non-TBI individuals with high sensitivity (83% and specificity (87%. We conclude that our testing application provides a rapid, portable testing method for TBI.

  8. Performance of amplicon-based next generation DNA sequencing for diagnostic gene mutation profiling in oncopathology.

    Science.gov (United States)

    Sie, Daoud; Snijders, Peter J F; Meijer, Gerrit A; Doeleman, Marije W; van Moorsel, Marinda I H; van Essen, Hendrik F; Eijk, Paul P; Grünberg, Katrien; van Grieken, Nicole C T; Thunnissen, Erik; Verheul, Henk M; Smit, Egbert F; Ylstra, Bauke; Heideman, Daniëlle A M

    2014-10-01

    Next generation DNA sequencing (NGS) holds promise for diagnostic applications, yet implementation in routine molecular pathology practice requires performance evaluation on DNA derived from routine formalin-fixed paraffin-embedded (FFPE) tissue specimens. The current study presents a comprehensive analysis of TruSeq Amplicon Cancer Panel-based NGS using a MiSeq Personal sequencer (TSACP-MiSeq-NGS) for somatic mutation profiling. TSACP-MiSeq-NGS (testing 212 hotspot mutation amplicons of 48 genes) and a data analysis pipeline were evaluated in a retrospective learning/test set approach (n = 58/n = 45 FFPE-tumor DNA samples) against 'gold standard' high-resolution-melting (HRM)-sequencing for the genes KRAS, EGFR, BRAF and PIK3CA. Next, the performance of the validated test algorithm was assessed in an independent, prospective cohort of FFPE-tumor DNA samples (n = 75). In the learning set, a number of minimum parameter settings was defined to decide whether a FFPE-DNA sample is qualified for TSACP-MiSeq-NGS and for calling mutations. The resulting test algorithm revealed 82% (37/45) compliance to the quality criteria and 95% (35/37) concordant assay findings for KRAS, EGFR, BRAF and PIK3CA with HRM-sequencing (kappa = 0.92; 95% CI = 0.81-1.03) in the test set. Subsequent application of the validated test algorithm to the prospective cohort yielded a success rate of 84% (63/75), and a high concordance with HRM-sequencing (95% (60/63); kappa = 0.92; 95% CI = 0.84-1.01). TSACP-MiSeq-NGS detected 77 mutations in 29 additional genes. TSACP-MiSeq-NGS is suitable for diagnostic gene mutation profiling in oncopathology.

  9. Focal congenital hyperinsulinism managed by medical treatment: a diagnostic algorithm based on molecular genetic screening.

    Science.gov (United States)

    Maiorana, Arianna; Barbetti, Fabrizio; Boiani, Arianna; Rufini, Vittoria; Pizzoferro, Milena; Francalanci, Paola; Faletra, Flavio; Nichols, Colin G; Grimaldi, Chiara; de Ville de Goyet, Jean; Rahier, Jacques; Henquin, Jean-Claude; Dionisi-Vici, Carlo

    2014-11-01

    Congenital hyperinsulinism (CHI) requires rapid diagnosis and treatment to avoid irreversible neurological sequelae due to hypoglycaemia. Aetiological diagnosis is instrumental in directing the appropriate therapy. Current diagnostic algorithms provide a complete set of diagnostic tools including (i) biochemical assays, (ii) genetic facility and (iii) state-of-the-art imaging. They consider the response to a therapeutic diazoxide trial an early, crucial step before proceeding (or not) to specific genetic testing and eventually imaging, aimed at distinguishing diffuse vs focal CHI. However, interpretation of the diazoxide test is not trivial and can vary between research groups, which may lead to inappropriate decisions. Objective of this report is proposing a new algorithm in which early genetic screening, rather than diazoxide trial, dictates subsequent clinical decisions. Two CHI patients weaned from parenteral glucose infusion and glucagon after starting diazoxide. No hypoglycaemia was registered during a 72-h continuous glucose monitoring (CGMS), or hypoglycaemic episodes were present for no longer than 3% of 72-h. Normoglycaemia was obtained by low-medium dose diazoxide combined with frequent carbohydrate feeds for several years. We identified monoallelic, paternally inherited mutations in KATP channel genes, and (18) F-DOPA PET-CT revealed a focal lesion that was surgically resected, resulting in complete remission of hypoglycaemia. Although rare, some patients with focal lesions may be responsive to diazoxide. As a consequence, we propose an algorithm that is not based on a 'formal' diazoxide response but on genetic testing, in which patients carrying paternally inherited ABCC8 or KCNJ11 mutations should always be subjected to (18) F-DOPA PET-CT. © 2014 John Wiley & Sons Ltd.

  10. Diagnostic performance of an acoustic-based system for coronary artery disease risk stratification.

    Science.gov (United States)

    Winther, Simon; Nissen, Louise; Schmidt, Samuel Emil; Westra, Jelmer Sybren; Rasmussen, Laust Dupont; Knudsen, Lars Lyhne; Madsen, Lene Helleskov; Kirk Johansen, Jane; Larsen, Bjarke Skogstad; Struijk, Johannes Jan; Frost, Lars; Holm, Niels Ramsing; Christiansen, Evald Høj; Botker, Hans Erik; Bøttcher, Morten

    2017-11-09

    Diagnosing coronary artery disease (CAD) continues to require substantial healthcare resources. Acoustic analysis of transcutaneous heart sounds of cardiac movement and intracoronary turbulence due to obstructive coronary disease could potentially change this. The aim of this study was thus to test the diagnostic accuracy of a new portable acoustic device for detection of CAD. We included 1675 patients consecutively with low to intermediate likelihood of CAD who had been referred for cardiac CT angiography. If significant obstruction was suspected in any coronary segment, patients were referred to invasive angiography and fractional flow reserve (FFR) assessment. Heart sound analysis was performed in all patients. A predefined acoustic CAD-score algorithm was evaluated; subsequently, we developed and validated an updated CAD-score algorithm that included both acoustic features and clinical risk factors. Low risk is indicated by a CAD-score value ≤20. Haemodynamically significant CAD assessed from FFR was present in 145 (10.0%) patients. In the entire cohort, the predefined CAD-score had a sensitivity of 63% and a specificity of 44%. In total, 50% had an updated CAD-score value ≤20. At this cut-off, sensitivity was 81% (95% CI 73% to 87%), specificity 53% (95% CI 50% to 56%), positive predictive value 16% (95% CI 13% to 18%) and negative predictive value 96% (95% CI 95% to 98%) for diagnosing haemodynamically significant CAD. Sound-based detection of CAD enables risk stratification superior to clinical risk scores. With a negative predictive value of 96%, this new acoustic rule-out system could potentially supplement clinical assessment to guide decisions on the need for further diagnostic investigation. ClinicalTrials.gov identifier NCT02264717; Results. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  11. Experimental guinea pig model of dermatophytosis: a simple and useful tool for the evaluation of new diagnostics and antifungals

    DEFF Research Database (Denmark)

    Saunte, D.M.; Hasselby, J.P.; Brillowska-Dabrowska, A.

    2008-01-01

    The aim of this study was to establish a simple guinea pig model for the purpose of evaluating diagnostic principles and treatment modalities for dermatophytic infections. The following variables were evaluated; pre-treatment of the skin by shaving versus tape stripping, Microsporum canis...... of the model was evaluated with a recently developed diagnostic pan-dermatophyte PCR and antifungal treatment was tested with an oral solution of itraconazole, 10 mg/kg, once daily during days 3-14 of the test period. Pre-treatment of the skin with a manual razor was for practical reasons preferable to tape...

  12. Means-End based Functional Modeling for Intelligent Control: Modeling and Experiments with an Industrial Heat Pump System

    DEFF Research Database (Denmark)

    Saleem, Arshad

    2007-01-01

    The purpose of this paper is to present a Multilevel Flow Model (MFM) of an industrial heat pump system and its use for diagnostic reasoning. MFM is functional modeling language supporting an explicit means-ends intelligent control strategy for large industrial process plants. The model is used...... in several diagnostic experiments analyzing different fault scenarios. The model and results of the experiments are explained and it is shown how MFM based intelligent modeling and automated reasoning can improve the fault diagnosis process significantly....

  13. 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.

  14. Computer-Based Modeling Environments

    Science.gov (United States)

    1989-01-01

    1988). "An introduction to graph-based modeling Rich. E. (1983). Artificial Inteligence , McGraw-Hill, New York. systems", Working Paper 88-10-2...Hall, J., S. Lippman, and J. McCall. "Expected Utility Maximizing Job Search," Chapter 7 of Studies in the Economics of Search, 1979, North-Holland. WMSI...The same shape has been used theory, as knowledge representation in artificial for data sources and analytical models because, at intelligence, and as

  15. ALCBEAM - Neutral beam formation and propagation code for beam-based plasma diagnostics

    Science.gov (United States)

    Bespamyatnov, I. O.; Rowan, W. L.; Liao, K. T.

    2012-03-01

    ALCBEAM is a new three-dimensional neutral beam formation and propagation code. It was developed to support the beam-based diagnostics installed on the Alcator C-Mod tokamak. The purpose of the code is to provide reliable estimates of the local beam equilibrium parameters: such as beam energy fractions, density profiles and excitation populations. The code effectively unifies the ion beam formation, extraction and neutralization processes with beam attenuation and excitation in plasma and neutral gas and beam stopping by the beam apertures. This paper describes the physical processes interpreted and utilized by the code, along with exploited computational methods. The description is concluded by an example simulation of beam penetration into plasma of Alcator C-Mod. The code is successfully being used in Alcator C-Mod tokamak and expected to be valuable in the support of beam-based diagnostics in most other tokamak environments. Program summaryProgram title: ALCBEAM Catalogue identifier: AEKU_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKU_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 66 459 No. of bytes in distributed program, including test data, etc.: 7 841 051 Distribution format: tar.gz Programming language: IDL Computer: Workstation, PC Operating system: Linux RAM: 1 GB Classification: 19.2 Nature of problem: Neutral beams are commonly used to heat and/or diagnose high-temperature magnetically-confined laboratory plasmas. An accurate neutral beam characterization is required for beam-based measurements of plasma properties. Beam parameters such as density distribution, energy composition, and atomic excited populations of the beam atoms need to be known. Solution method: A neutral beam is initially formed as an ion beam which is extracted from

  16. A dual purpose data base for research and diagnostic assessment of student writing

    Directory of Open Access Journals (Sweden)

    Judy M. Parr

    2010-08-01

    Full Text Available The data base of writing examined serves a dual purpose. Here it is used as a research tool and the writing performance from the large, nationally representative sample (N = 20,947 of students (years 4 to 12 interrogated to examine patterns of performance in writing. However, the data base was designed to underpin a software tool for diagnostic assessment of writing. Viewing writing as accomplishing social communicative goals, performance was considered in terms of seven main purposes the writer may seek to achieve. Tasks related to each purpose were encapsulated in 60 writing prompts that included stimulus material. Participants produced one writing sample; the design ensured appropriate representation across writing purposes. Samples were scored using criteria differentiated according to purpose and curriculum level of schooling and acceptable reliability obtained. Analyses indicate that growth was most marked between years 8 and 10, arguably, as opportunity to write increases and writing is linked to learning in content areas. Variability in performance is relatively low at primary school and high at secondary school. Students at any level did not write equally well for different purposes. Mean scores across purposes at primary school were relatively similar with to instruct and to explain highest. By years 11-12 there is a considerable gap between the highest scores (for narrate and report and the lowest, recount, reflecting likely opportunities to practice writing for different purposes. Although girls performed better than boys, the difference in mean scores narrows by years 11-12.

  17. Activities identification for activity-based cost/management applications of the diagnostics outpatient procedures.

    Science.gov (United States)

    Alrashdan, Abdalla; Momani, Amer; Ababneh, Tamador

    2012-01-01

    One of the most challenging problems facing healthcare providers is to determine the actual cost for their procedures, which is important for internal accounting and price justification to insurers. The objective of this paper is to find suitable categories to identify the diagnostic outpatient medical procedures and translate them from functional orientation to process orientation. A hierarchal task tree is developed based on a classification schema of procedural activities. Each procedure is seen as a process consisting of a number of activities. This makes a powerful foundation for activity-based cost/management implementation and provides enough information to discover the value-added and non-value-added activities that assist in process improvement and eventually may lead to cost reduction. Work measurement techniques are used to identify the standard time of each activity at the lowest level of the task tree. A real case study at a private hospital is presented to demonstrate the proposed methodology. © 2011 National Association for Healthcare Quality.

  18. G-quadruplex-based aptamers against protein targets in therapy and diagnostics.

    Science.gov (United States)

    Platella, Chiara; Riccardi, Claudia; Montesarchio, Daniela; Roviello, Giovanni N; Musumeci, Domenica

    2017-05-01

    Nucleic acid aptamers are single-stranded DNA or RNA molecules identified to recognize with high affinity specific targets including proteins, small molecules, ions, whole cells and even entire organisms, such as viruses or bacteria. They can be identified from combinatorial libraries of DNA or RNA oligonucleotides by SELEX technology, an in vitro iterative selection procedure consisting of binding (capture), partitioning and amplification steps. Remarkably, many of the aptamers selected against biologically relevant protein targets are G-rich sequences that can fold into stable G-quadruplex (G4) structures. Aiming at disseminating novel inspiring ideas within the scientific community in the field of G4-structures, the emphasis of this review is placed on: 1) recent advancements in SELEX technology for the efficient and rapid identification of new candidate aptamers (introduction of microfluidic systems and next generation sequencing); 2) recurrence of G4 structures in aptamers selected by SELEX against biologically relevant protein targets; 3) discovery of several G4-forming motifs in important regulatory regions of the human or viral genome bound by endogenous proteins, which per se can result into potential aptamers; 4) an updated overview of G4-based aptamers with therapeutic potential and 5) a discussion on the most attractive G4-based aptamers for diagnostic applications. This article is part of a Special Issue entitled "G-quadruplex" Guest Editor: Dr. Concetta Giancola and Dr. Daniela Montesarchio. Copyright © 2016 Elsevier B.V. All rights reserved.

  19. Optoacoustic diagnostic modality: from idea to clinical studies with highly compact laser diode-based systems

    Science.gov (United States)

    Esenaliev, Rinat O.

    2017-09-01

    Optoacoustic (photoacoustic) diagnostic modality is a technique that combines high optical contrast and ultrasound spatial resolution. We proposed using the optoacoustic technique for a number of applications, including cancer detection, monitoring of thermotherapy (hyperthermia, coagulation, and freezing), monitoring of cerebral blood oxygenation in patients with traumatic brain injury, neonatal patients, fetuses during late-stage labor, central venous oxygenation monitoring, and total hemoglobin concentration monitoring as well as hematoma detection and characterization. We developed and built optical parametric oscillator-based systems and multiwavelength, fiber-coupled highly compact, laser diode-based systems for optoacoustic imaging, monitoring, and sensing. To provide sufficient output pulse energy, a specially designed fiber-optic system was built and incorporated in ultrasensitive, wideband optoacoustic probes. We performed preclinical and clinical tests of the systems and the optoacoustic probes in backward mode for most of the applications and in forward mode for the breast cancer and cerebral applications. The high pulse energy and repetition rate allowed for rapid data acquisition with high signal-to-noise ratio from cerebral blood vessels, such as the superior sagittal sinus, central veins, and peripheral veins and arteries, as well as from intracranial hematomas. The optoacoustic systems were capable of automatic, real-time, continuous measurements of blood oxygenation in these blood vessels.

  20. Negative emotionality across diagnostic models: RDoC, DSM-5 Section III, and FFM.

    Science.gov (United States)

    Gore, Whitney L; Widiger, Thomas A

    2018-03-01

    The research domain criteria (RDoC) were established in an effort to explore underlying dimensions that cut across many existing disorders and to provide an alternative to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). One purpose of the present study was to suggest a potential alignment of RDoC negative valence with 2 other dimensional models of negative emotionality: five-factor model (FFM) neuroticism and the DSM-5 Section III negative affectivity. A second purpose of the study, though, was to compare their coverage of negative emotionality, more specifically with respect to affective instability. Participants were adult community residents (N = 90) currently in mental health treatment. Participants received self-report measures of RDoC negative valence, FFM neuroticism, and DSM-5 Section III negative affectivity, along with measures of affective instability, borderline personality disorder, and impairment. Findings suggested that RDoC negative valence is commensurate with FFM neuroticism and DSM-5 Section III negative affectivity, and it would be beneficial if it was expanded to include affective instability. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  1. Application of support vector machine model for enhancing the diagnostic value of tumor markers in gastric cancer

    International Nuclear Information System (INIS)

    Wang Hui; Huang Gang

    2010-01-01

    Objective: To evaluate the early diagnostic value of tumor markers for gastric cancer using support vector machine (SVM) model. Methods: Subjects involved in the study consisted of 262 cases with gastric cancer, 156 cases with benign gastric diseases and 149 healthy controls. From those subjects, five tumor markers, carcinoembryonic antigen (CEA), carbohydrate (CA) 125, CA19-9, alphafetoprotein (AFP) and CA50, were assayed and collected to make the datasets. To modify SVM model to fit the diagnostic classifiers, radial basis function was adopted and kernel function was optimized and validated by grid search and cross validation. For comparative study, methods of combination tests of five markers, Logistic regression, and decision tree were also used. Results: For gastric cancer, the diagnostic accuracy of the combination tests, Logistic regression, decision tree and SVM model were 46.2%, 64.5%, 63.9% and 95.1% respectively. SVM model significantly elevated the diagnostic value comparing with other three methods. Conclusion: The application of SVM model is of high value in enhancing the tumor marker for the diagnosis of gastric cancer. (authors)

  2. A diagnostic strategy for pulmonary embolism based on standardised pretest probability and perfusion lung scanning: a management study

    International Nuclear Information System (INIS)

    Miniati, Massimo; Monti, Simonetta; Bauleo, Carolina; Scoscia, Elvio; Tonelli, Lucia; Dainelli, Alba; Catapano, Giosue; Formichi, Bruno; Di Ricco, Giorgio; Prediletto, Renato; Carrozzi, Laura; Marini, Carlo

    2003-01-01

    Pulmonary embolism remains a challenging diagnostic problem. We developed a simple diagnostic strategy based on combination of assessment of the pretest probability with perfusion lung scan results to reduce the need for pulmonary angiography. We studied 390 consecutive patients (78% in-patients) with suspected pulmonary embolism. The pretest probability was rated low ( 10%, ≤50%), moderately high (>50%, ≤90%) or high (>90%) according to a structured clinical model. Perfusion lung scans were independently assigned to one of four categories: normal; near-normal; abnormal, suggestive of pulmonary embolism (wedge-shaped perfusion defects); abnormal, not suggestive of pulmonary embolism (perfusion defects other than wedge shaped). Pulmonary embolism was diagnosed in patients with abnormal scans suggestive of pulmonary embolism and moderately high or high pretest probability. Patients with normal or near-normal scans and those with abnormal scans not suggestive of pulmonary embolism and low pretest probability were deemed not to have pulmonary embolism. All other patients were allocated to pulmonary angiography. Patients in whom pulmonary embolism was excluded were left untreated. All patients were followed up for 1 year. Pulmonary embolism was diagnosed non-invasively in 132 patients (34%), and excluded in 191 (49%). Pulmonary angiography was required in 67 patients (17%). The prevalence of pulmonary embolism was 41% (n=160). Patients in whom pulmonary embolism was excluded had a thrombo-embolic risk of 0.4% (95% confidence interval: 0.0%-2.8%). Our strategy permitted a non-invasive diagnosis or exclusion of pulmonary embolism in 83% of the cases (95% confidence interval: 79%-86%), and appeared to be safe. (orig.)

  3. 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. Copyright © 2015 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    Martens, Leon; Goode, Grahame; Wold, Johan F H; Beck, Lionel; Martin, Georgina; Perings, Christian; Stolt, Pelle; Baggerman, Lucas

    2014-01-01

    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.

  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. 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. Copyright © 2013 John Wiley & Sons, Ltd.

  7. Biomaterials-based 3D cell printing for next-generation therapeutics and diagnostics.

    Science.gov (United States)

    Jang, Jinah; Park, Ju Young; Gao, Ge; Cho, Dong-Woo

    2018-02-01

    Building human tissues via 3D cell printing technology has received particular attention due to its process flexibility and versatility. This technology enables the recapitulation of unique features of human tissues and the all-in-one manufacturing process through the design of smart and advanced biomaterials and proper polymerization techniques. For the optimal engineering of tissues, a higher-order assembly of physiological components, including cells, biomaterials, and biomolecules, should meet the critical requirements for tissue morphogenesis and vascularization. The convergence of 3D cell printing with a microfluidic approach has led to a significant leap in the vascularization of engineering tissues. In addition, recent cutting-edge technology in stem cells and genetic engineering can potentially be adapted to the 3D tissue fabrication technique, and it has great potential to shift the paradigm of disease modeling and the study of unknown disease mechanisms required for precision medicine. This review gives an overview of recent developments in 3D cell printing and bioinks and provides technical requirements for engineering human tissues. Finally, we propose suggestions on the development of next-generation therapeutics and diagnostics. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. STARD-BLCM: Standards for the Reporting of Diagnostic accuracy studies that use Bayesian Latent Class Models.

    Science.gov (United States)

    Kostoulas, Polychronis; Nielsen, Søren S; Branscum, Adam J; Johnson, Wesley O; Dendukuri, Nandini; Dhand, Navneet K; Toft, Nils; Gardner, Ian A

    2017-03-01

    The Standards for the Reporting of Diagnostic Accuracy (STARD) statement, which was recently updated to the STARD2015 statement, was developed to encourage complete and transparent reporting of test accuracy studies. Although STARD principles apply broadly, the checklist is limited to studies designed to evaluate the accuracy of tests when the disease status is determined from a perfect reference procedure or an imperfect one with known measures of test accuracy. However, a reference standard does not always exist, especially in the case of infectious diseases with a long latent period. In such cases, a valid alternative to classical test evaluation involves the use of latent class models that do not require a priori knowledge of disease status. Latent class models have been successfully implemented in a Bayesian framework for over 20 years. The objective of this work was to identify the STARD items that require modification and develop a modified version of STARD for studies that use Bayesian latent class analysis to estimate diagnostic test accuracy in the absence of a reference standard. Examples and elaborations for each of the modified items are provided. The new guidelines, termed STARD-BLCM (Standards for Reporting of Diagnostic accuracy studies that use Bayesian Latent Class Models), will facilitate improved quality of reporting on the design, conduct and results of diagnostic accuracy studies that use Bayesian latent class models. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

  9. Problems in detecting misfit of latent class models in diagnostic research without a gold standard were shown

    NARCIS (Netherlands)

    van Smeden, M.; Oberski, D.L.; Reitsma, J.B.; Vermunt, J.K.; Moons, K.G.M.; de Groot, J.A.H.

    2016-01-01

    Objectives The objective of this study was to evaluate the performance of goodness-of-fit testing to detect relevant violations of the assumptions underlying the criticized “standard” two-class latent class model. Often used to obtain sensitivity and specificity estimates for diagnostic tests in the

  10. Problems in detecting misfit of latent class models in diagnostic research without a gold standard were shown

    NARCIS (Netherlands)

    Van Smeden, Maarten; Oberski, Daniel L.; Reitsma, Johannes B.; Vermunt, Jeroen K.; Moons, Karel G M; De Groot, Joris A H

    2016-01-01

    Objectives The objective of this study was to evaluate the performance of goodness-of-fit testing to detect relevant violations of the assumptions underlying the criticized "standard" two-class latent class model. Often used to obtain sensitivity and specificity estimates for diagnostic tests in the

  11. Problems in detecting misfit of latent class models in diagnostic research without a gold standard were shown

    NARCIS (Netherlands)

    van Smeden, Maarten|info:eu-repo/dai/nl/413981983; Oberski, Daniel L; Reitsma, Johannes B|info:eu-repo/dai/nl/189853107; Vermunt, Jeroen K; Moons, Karel G M|info:eu-repo/dai/nl/152483519; de Groot, JAH|info:eu-repo/dai/nl/314072268

    OBJECTIVES: The objective of this study was to evaluate the performance of goodness-of-fit testing to detect relevant violations of the assumptions underlying the criticized 'standard' 2-class latent class model. Often used to obtain sensitivity and specificity estimates for diagnostic tests in the

  12. Radiation doses by radiation diagnostics at the border of a hospital. Calculation model for Nuclear Energy Law regulations

    International Nuclear Information System (INIS)

    Shapiro, B.; Thijssen, T.; De Jong, R.

    2000-01-01

    According to the Nuclear Energy Law in the Netherlands radiation doses at the border of a specific institute (e.g. hospitals) must be determined which can not simply be done by measurements. In this article a model calculation for radiation diagnostics is described

  13. 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. (c) 2015 APA, all rights reserved.

  14. Application of new simulation algorithms for modeling rf diagnostics of electron clouds

    International Nuclear Information System (INIS)

    Veitzer, Seth A.; Smithe, David N.; Stoltz, Peter H.

    2012-01-01

    Traveling wave rf diagnostics of electron cloud build-up show promise as a non-destructive technique for measuring plasma density and the efficacy of mitigation techniques. However, it is very difficult to derive an absolute measure of plasma density from experimental measurements for a variety of technical reasons. Detailed numerical simulations are vital in order to understand experimental data, and have successfully modeled build-up. Such simulations are limited in their ability to reproduce experimental data due to the large separation of scales inherent to the problem. Namely, one must resolve both rf frequencies in the GHz range, as well as the plasma modulation frequency of tens of MHz, while running for very long simulations times, on the order of microseconds. The application of new numerical simulation techniques allow us to bridge the simulation scales in this problem and produce spectra that can be directly compared to experiments. The first method is to use a plasma dielectric model to measure plasma-induced phase shifts in the rf wave. The dielectric is modulated at a low frequency, simulating the effects of multiple bunch crossings. This allows simulations to be performed without kinetic particles representing the plasma, which both speeds up the simulations as well as reduces numerical noise from interpolation of particle charge and currents onto the computational grid. Secondly we utilize a port boundary condition model to simultaneously absorb rf at the simulation boundaries, and to launch the rf into the simulation. This method improves the accuracy of simulations by restricting rf frequencies better than adding an external (finite) current source to drive rf, and absorbing layers at the boundaries. We also explore the effects of non-uniform plasma densities on the simulated spectra.

  15. Fast and accurate Bayesian model criticism and conflict diagnostics using R-INLA

    KAUST Repository

    Ferkingstad, Egil

    2017-10-16

    Bayesian hierarchical models are increasingly popular for realistic modelling and analysis of complex data. This trend is accompanied by the need for flexible, general and computationally efficient methods for model criticism and conflict detection. Usually, a Bayesian hierarchical model incorporates a grouping of the individual data points, as, for example, with individuals in repeated measurement data. In such cases, the following question arises: Are any of the groups “outliers,” or in conflict with the remaining groups? Existing general approaches aiming to answer such questions tend to be extremely computationally demanding when model fitting is based on Markov chain Monte Carlo. We show how group-level model criticism and conflict detection can be carried out quickly and accurately through integrated nested Laplace approximations (INLA). The new method is implemented as a part of the open-source R-INLA package for Bayesian computing (http://r-inla.org).

  16. Thorax X-ray diagnostics. DDS (double base description system). Uniform terminology and standardized sytematics. Correct diagnosis

    International Nuclear Information System (INIS)

    Kulke, H.M.

    2012-01-01

    The booklet describes the so called DDS (double-base description system) to be used in the frame of medical thorax X-ray examinations with modern imaging devices. The following issues are discussed: Description features, shadow characterization, general fundamentals, procedural methodology, diagnostic findings protocol, examples and case descriptions.

  17. Photoelectric diagnostics of InGaN-based LEDs in static and dynamic modes

    Science.gov (United States)

    Radaev, O. A.; Frolov, I. V.; Sergeev, V. A.

    2017-11-01

    The method and measuring installation for diagnostics of light-emitting heterostructures (HS) with the quantum well (QW) by registration of the photocurrent arising in case of radiation of HS the narrow-band optical radiation of different wavelength i