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Sample records for accurate diagnosis based

  1. [Myasthenia gravis - optimal treatment and accurate diagnosis].

    PubMed

    Gilhus, Nils Erik; Kerty, Emilia; Løseth, Sissel; Mygland, Åse; Tallaksen, Chantal

    2016-07-01

    Around 700 people in Norway have myasthenia gravis, an autoimmune disease that affects neuromuscular transmission and results in fluctuating weakness in some muscles as its sole symptom. The diagnosis is based on typical symptoms and findings, detection of antibodies and neurophysiological examination. Symptomatic treatment with acetylcholinesterase inhibitors is generally effective, but most patients also require immunosuppressive drug treatment. Antigen-specific therapy is being tested in experimental disease models. PMID:27381787

  2. A new method of accurate broken rotor bar diagnosis based on modulation signal bispectrum analysis of motor current signals

    NASA Astrophysics Data System (ADS)

    Gu, F.; Wang, T.; Alwodai, A.; Tian, X.; Shao, Y.; Ball, A. D.

    2015-01-01

    Motor current signature analysis (MCSA) has been an effective way of monitoring electrical machines for many years. However, inadequate accuracy in diagnosing incipient broken rotor bars (BRB) has motivated many studies into improving this method. In this paper a modulation signal bispectrum (MSB) analysis is applied to motor currents from different broken bar cases and a new MSB based sideband estimator (MSB-SE) and sideband amplitude estimator are introduced for obtaining the amplitude at (1 ± 2 s)fs (s is the rotor slip and fs is the fundamental supply frequency) with high accuracy. As the MSB-SE has a good performance of noise suppression, the new estimator produces more accurate results in predicting the number of BRB, compared with conventional power spectrum analysis. Moreover, the paper has also developed an improved model for motor current signals under rotor fault conditions and an effective method to decouple the BRB current which interferes with that of speed oscillations associated with BRB. These provide theoretical supports for the new estimators and clarify the issues in using conventional bispectrum analysis.

  3. Accurate diagnosis of myalgic encephalomyelitis and chronic fatigue syndrome based upon objective test methods for characteristic symptoms

    PubMed Central

    Twisk, Frank NM

    2015-01-01

    Although myalgic encephalomyelitis (ME) and chronic fatigue syndrome (CFS) are considered to be synonymous, the definitional criteria for ME and CFS define two distinct, partially overlapping, clinical entities. ME, whether defined by the original criteria or by the recently proposed criteria, is not equivalent to CFS, let alone a severe variant of incapacitating chronic fatigue. Distinctive features of ME are: muscle weakness and easy muscle fatigability, cognitive impairment, circulatory deficits, a marked variability of the symptoms in presence and severity, but above all, post-exertional “malaise”: a (delayed) prolonged aggravation of symptoms after a minor exertion. In contrast, CFS is primarily defined by (unexplained) chronic fatigue, which should be accompanied by four out of a list of 8 symptoms, e.g., headaches. Due to the subjective nature of several symptoms of ME and CFS, researchers and clinicians have questioned the physiological origin of these symptoms and qualified ME and CFS as functional somatic syndromes. However, various characteristic symptoms, e.g., post-exertional “malaise” and muscle weakness, can be assessed objectively using well-accepted methods, e.g., cardiopulmonary exercise tests and cognitive tests. The objective measures acquired by these methods should be used to accurately diagnose patients, to evaluate the severity and impact of the illness objectively and to assess the positive and negative effects of proposed therapies impartially. PMID:26140274

  4. Accurate diagnosis of myalgic encephalomyelitis and chronic fatigue syndrome based upon objective test methods for characteristic symptoms.

    PubMed

    Twisk, Frank Nm

    2015-06-26

    Although myalgic encephalomyelitis (ME) and chronic fatigue syndrome (CFS) are considered to be synonymous, the definitional criteria for ME and CFS define two distinct, partially overlapping, clinical entities. ME, whether defined by the original criteria or by the recently proposed criteria, is not equivalent to CFS, let alone a severe variant of incapacitating chronic fatigue. Distinctive features of ME are: muscle weakness and easy muscle fatigability, cognitive impairment, circulatory deficits, a marked variability of the symptoms in presence and severity, but above all, post-exertional "malaise": a (delayed) prolonged aggravation of symptoms after a minor exertion. In contrast, CFS is primarily defined by (unexplained) chronic fatigue, which should be accompanied by four out of a list of 8 symptoms, e.g., headaches. Due to the subjective nature of several symptoms of ME and CFS, researchers and clinicians have questioned the physiological origin of these symptoms and qualified ME and CFS as functional somatic syndromes. However, various characteristic symptoms, e.g., post-exertional "malaise" and muscle weakness, can be assessed objectively using well-accepted methods, e.g., cardiopulmonary exercise tests and cognitive tests. The objective measures acquired by these methods should be used to accurately diagnose patients, to evaluate the severity and impact of the illness objectively and to assess the positive and negative effects of proposed therapies impartially. PMID:26140274

  5. Implementing Prenatal Diagnosis Based on Cell-Free Fetal DNA: Accurate Identification of Factors Affecting Fetal DNA Yield

    PubMed Central

    Barrett, Angela N.; Zimmermann, Bernhard G.; Wang, Darrell; Holloway, Andrew; Chitty, Lyn S.

    2011-01-01

    Objective Cell-free fetal DNA is a source of fetal genetic material that can be used for non-invasive prenatal diagnosis. Usually constituting less than 10% of the total cell free DNA in maternal plasma, the majority is maternal in origin. Optimizing conditions for maximizing yield of cell-free fetal DNA will be crucial for effective implementation of testing. We explore factors influencing yield of fetal DNA from maternal blood samples, including assessment of collection tubes containing cell-stabilizing agents, storage temperature, interval to sample processing and DNA extraction method used. Methods Microfluidic digital PCR was performed to precisely quantify male (fetal) DNA, total DNA and long DNA fragments (indicative of maternal cellular DNA). Real-time qPCR was used to assay for the presence of male SRY signal in samples. Results Total cell-free DNA quantity increased significantly with time in samples stored in K3EDTA tubes, but only minimally in cell stabilizing tubes. This increase was solely due to the presence of additional long fragment DNA, with no change in quantity of fetal or short DNA, resulting in a significant decrease in proportion of cell-free fetal DNA over time. Storage at 4°C did not prevent these changes. Conclusion When samples can be processed within eight hours of blood draw, K3EDTA tubes can be used. Prolonged transfer times in K3EDTA tubes should be avoided as the proportion of fetal DNA present decreases significantly; in these situations the use of cell stabilising tubes is preferable. The DNA extraction kit used may influence success rate of diagnostic tests. PMID:21998643

  6. Postmortem CT is more accurate than clinical diagnosis for identifying the immediate cause of death in hospitalized patients: a prospective autopsy-based study.

    PubMed

    Inai, Kunihiro; Noriki, Sakon; Kinoshita, Kazuyuki; Sakai, Toyohiko; Kimura, Hirohiko; Nishijima, Akihiko; Iwasaki, Hiromichi; Naiki, Hironobu

    2016-07-01

    Despite 75 to 90 % physician accuracy in determining the underlying cause of death, precision of determination of the immediate cause of death is approximately 40 %. In contrast, two thirds of immediate causes of death in hospitalized patients are correctly diagnosed by postmortem computed tomography (CT). Postmortem CT might provide an alternative approach to verifying the immediate cause of death. To evaluate the effectiveness of postmortem CT as an alternative method to determine the immediate cause of death in hospitalized patients, an autopsy-based prospective study was performed. Of 563 deaths from September 2011 to August 2013, 50 consecutive cadavers undergoing hospital autopsies with consent for additional postmortem CT at the University of Fukui were enrolled. The accuracy of determination of the immediate cause of death by postmortem CT was evaluated in these patients. Diagnostic discrepancy was also compared between radiologists and attending physicians. The immediate cause of death was correctly diagnosed in 37 of 50 subjects using postmortem CT (74 %), concerning 29 cases of respiratory failure, 4 of hemorrhage, 3 of liver failure and 1 of septic shock. Six cases of organ failure involving 13 patients were not identified as the cause of death by postmortem CT. Regarding the immediate cause of death, accuracy of clinical diagnosis was significantly lower than that of postmortem CT (46 vs 74 %, P < 0.01). Postmortem CT may be more useful than clinical diagnosis for identifying the immediate cause of death in hospitalized patients not undergoing autopsy. PMID:27085336

  7. A Highly Sensitive Porous Silicon (P-Si)-Based Human Kallikrein 2 (hK2) Immunoassay Platform toward Accurate Diagnosis of Prostate Cancer

    PubMed Central

    Lee, Sang Wook; Hosokawa, Kazuo; Kim, Soyoun; Jeong, Ok Chan; Lilja, Hans; Laurell, Thomas; Maeda, Mizuo

    2015-01-01

    Levels of total human kallikrein 2 (hK2), a protein involved the pathology of prostate cancer (PCa), could be used as a biomarker to aid in the diagnosis of this disease. In this study, we report on a porous silicon antibody immunoassay platform for the detection of serum levels of total hK2. The surface of porous silicon has a 3-dimensional macro- and nanoporous structure, which offers a large binding capacity for capturing probe molecules. The tailored pore size of the porous silicon also allows efficient immobilization of antibodies by surface adsorption, and does not require chemical immobilization. Monoclonal hK2 capture antibody (6B7) was dispensed onto P-Si chip using a piezoelectric dispenser. In total 13 × 13 arrays (169 spots) were spotted on the chip with its single spot volume of 300 pL. For an optimization of capture antibody condition, we firstly performed an immunoassay of the P-Si microarray under a titration series of hK2 in pure buffer (PBS) at three different antibody densities (75, 100 and 145 µg/mL). The best performance of the microarray platform was seen at 100 µg/mL of the capture antibody concentration (LOD was 100 fg/mL). The platform then was subsequently evaluated for a titration series of serum-spiked hK2 samples. The developed platform utilizes only 15 µL of serum per test and the total assay time is about 3 h, including immobilization of the capture antibody. The detection limit of the hK2 assay was 100 fg/mL in PBS buffer and 1 pg/mL in serum with a dynamic range of 106 (10−4 to 102 ng/mL). PMID:26007739

  8. Translation research: from accurate diagnosis to appropriate treatment

    PubMed Central

    Webb, Craig P; Pass, Harvey I

    2004-01-01

    This review article focuses on the various aspects of translational research, where research on human subjects can ultimately enhance the diagnosis and treatment of future patients. While we will use specific examples relating to the asbestos related cancer mesothelioma, it should be stressed that the general approach outlined throughout this review is readily applicable to other diseases with an underlying molecular basis. Through the integration of molecular-based technologies, systematic tissue procurement and medical informatics, we now have the ability to identify clinically applicable "genotype"-"phenotype" associations across cohorts of patients that can rapidly be translated into useful diagnostic and treatment strategies. This review will touch on the various steps in the translational pipeline, and highlight some of the most essential elements as well as possible roadblocks that can impact success of the program. Critical issues with regard to Institutional Review Board (IRB) and Health Insurance Portability and Accountability Act (HIPAA) compliance, data standardization, sample procurement, quality control (QC), quality assurance (QA), data analysis, preclinical models and clinical trials are addressed. The various facets of the translational pipeline have been incorporated into a fully integrated computational system, appropriately named Dx2Tx. This system readily allows for the identification of new diagnostic tests, the discovery of biomarkers and drugable targets, and prediction of optimal treatments based upon the underlying molecular basis of the disease. PMID:15496233

  9. Advanced tests for early and accurate diagnosis of Creutzfeldt-Jakob disease.

    PubMed

    Zanusso, Gianluigi; Monaco, Salvatore; Pocchiari, Maurizio; Caughey, Byron

    2016-06-01

    Early and accurate diagnosis of Creutzfeldt-Jakob disease (CJD) is a necessary to distinguish this untreatable disease from treatable rapidly progressive dementias, and to prevent iatrogenic transmission. Currently, definitive diagnosis of CJD requires detection of the abnormally folded, CJD-specific form of protease-resistant prion protein (PrP(CJD)) in brain tissue obtained postmortem or via biopsy; therefore, diagnosis of sporadic CJD in clinical practice is often challenging. Supporting investigations, including MRI, EEG and conventional analyses of cerebrospinal fluid (CSF) biomarkers, are helpful in the diagnostic work-up, but do not allow definitive diagnosis. Recently, novel ultrasensitive seeding assays, based on the amplified detection of PrP(CJD), have improved the diagnostic process; for example, real-time quaking-induced conversion (RT-QuIC) is a sensitive method to detect prion-seeding activity in brain homogenate from humans with any subtype of sporadic CJD. RT-QuIC can also be used for in vivo diagnosis of CJD: its diagnostic sensitivity in detecting PrP(CJD) in CSF samples is 96%, and its specificity is 100%. Recently, we provided evidence that RT-QuIC of olfactory mucosa brushings is a 97% sensitive and 100% specific for sporadic CJD. These assays provide a basis for definitive antemortem diagnosis of prion diseases and, in doing so, improve prospects for reducing the risk of prion transmission. Moreover, they can be used to evaluate outcome measures in therapeutic trials for these as yet untreatable infections. PMID:27174240

  10. Novel, In-House, SYBR Green Based One-Step rRT-PCR: Rapid and Accurate Diagnosis of Crimean-Congo Hemorrhagic Fever Virus in Suspected Patients From Iran

    PubMed Central

    Zahraei, Bentolhoda; Hashemzadeh, Mohammad Sadegh; Najarasl, Mohammad; Zahiriyeganeh, Samaneh; Tat, Mahdi; Metanat, Maliheh; Sepehri Rad, Nahid; Khansari-nejad, Behzad; Zafari, Ehsan; Sharti, Mojtaba; Dorostkar, Ruhollah

    2016-01-01

    Background The Crimean-Congo hemorrhagic fever (CCHF) virus causes severe disease in humans, with a high mortality rate. Since, there is no approved vaccine or specific treatment for CCHF, an early and accurate diagnosis, as well as reliable surveillance, is essential for case management and patient improvement. Objectives For this research, our aim was to evaluate the application of a novel SYBR Green based one-step real-time reverse-transcriptase polymerase chain reaction (rRT-PCR) assay for the in-house diagnosis of the CCHF virus. Patients and Methods In this experimental study, the highly conserved S-region sequence of the CCHF viral genome was first adapted from GenBank, and the specific primers targeting this region were designed. Then, the viral RNA was extracted from 75 serum samples from different patients in eastern Iran. The sensitivity and specificity of the primers were also evaluated in positive serum samples previously confirmed to have the CCHF virus, by this one-step rRT-PCR assay, as well as a DNA sequencing analysis. Results From a total of 75 suspected serum samples, 42 were confirmed to be positive for CCHF virus, with no false-positives detected by the sequencing results. After 40 amplification cycles, the melting curve analysis revealed a mean melting temperature (Tm) of 86.5 ± 0.6°C (quite different from those of the primer-dimers), and the positive samples showed only a small variation in the parameters. In all of the positive samples, the predicted length of 420 bp was confirmed by electrophoresis. Moreover, the sensitivity test showed that this assay can detect less than 20 copies of viral RNA per reaction. Conclusions This study showed that this novel one-step rRT-PCR assay is a rapid, reliable, repeatable, specific, sensitive, and simple tool for the detection of the CCHF virus. PMID:27099688

  11. Clinical Practice Guideline for Accurate Diagnosis and Effective Treatment of Gastrointestinal Stromal Tumor in Korea

    PubMed Central

    Kim, Kyoung-Mee; Sohn, Taesung; Choi, Dongil; Kang, Hye Jin; Ryu, Min-Hee; Kim, Woo Ho; Yang, Han-Kwang

    2010-01-01

    Despite the rarity in incidence and prevalence, gastrointestinal stromal tumor (GIST) has emerged as a distinct pathogenetic entity. And the clinical management of GIST has been evolving very rapidly due to the recent recognition of its oncogenic signal transduction pathway and the introduction of new molecular-targeted therapy. Successful management of GIST requires a multidisciplinary approach firmly based on accurate histopathologic diagnosis. However, there was no standardized guideline for the management of Korean GIST patients. In 2007, the Korean GIST study group (KGSG) published the first guideline for optimal diagnosis and treatment of GIST in Korea. As the second version of the guideline, we herein have updated recent clinical recommendations and reflected changes in diagnosis, surgical and medical treatments for more optimal clinical practice for GIST in Korea. We hope the guideline can be of help in enhancing the quality of diagnosis by members of the Korean associate of physicians involving in GIST patients's care and subsequently in achieving optimal efficacy of treatment. PMID:21060741

  12. Towards an expert system for accurate diagnosis and progress monitoring of Parkinson's disease.

    PubMed

    Alexiou, Athanasios; Psiha, Maria; Vlamos, Panayiotis

    2015-01-01

    While Parkinson's disease is a chronic and progressive movement disorder, no one can predict which symptoms will affect an individual patient. At the present time there is no cure for Parkinson's disease but instead a variety of alternative treatments provide relief from the symptoms. Due to these unpromising factors, we propose a new multi-scale ontology-based modeling technology for the accurate diagnosis of Parkinson's disease and its progress monitoring. The proposed model will be used to assess the status of the patient with PD corresponding treatments using a multilayer neural network. The proposed tool also aims to identify new associated physical and biological biomarkers from heterogeneous patients' data. The architecture of this expert system and its implementation in Protégé is presented in this paper. PMID:25416985

  13. Efficient Model-Based Diagnosis Engine

    NASA Technical Reports Server (NTRS)

    Fijany, Amir; Vatan, Farrokh; Barrett, Anthony; James, Mark; Mackey, Ryan; Williams, Colin

    2009-01-01

    An efficient diagnosis engine - a combination of mathematical models and algorithms - has been developed for identifying faulty components in a possibly complex engineering system. This model-based diagnosis engine embodies a twofold approach to reducing, relative to prior model-based diagnosis engines, the amount of computation needed to perform a thorough, accurate diagnosis. The first part of the approach involves a reconstruction of the general diagnostic engine to reduce the complexity of the mathematical-model calculations and of the software needed to perform them. The second part of the approach involves algorithms for computing a minimal diagnosis (the term "minimal diagnosis" is defined below). A somewhat lengthy background discussion is prerequisite to a meaningful summary of the innovative aspects of the present efficient model-based diagnosis engine. In model-based diagnosis, the function of each component and the relationships among all the components of the engineering system to be diagnosed are represented as a logical system denoted the system description (SD). Hence, the expected normal behavior of the engineering system is the set of logical consequences of the SD. Faulty components lead to inconsistencies between the observed behaviors of the system and the SD (see figure). Diagnosis - the task of finding faulty components - is reduced to finding those components, the abnormalities of which could explain all the inconsistencies. The solution of the diagnosis problem should be a minimal diagnosis, which is a minimal set of faulty components. A minimal diagnosis stands in contradistinction to the trivial solution, in which all components are deemed to be faulty, and which, therefore, always explains all inconsistencies.

  14. Simple, rapid and accurate molecular diagnosis of acute promyelocytic leukemia by loop mediated amplification technology

    PubMed Central

    Spinelli, Orietta; Rambaldi, Alessandro; Rigo, Francesca; Zanghì, Pamela; D'Agostini, Elena; Amicarelli, Giulia; Colotta, Francesco; Divona, Mariadomenica; Ciardi, Claudia; Coco, Francesco Lo; Minnucci, Giulia

    2015-01-01

    The diagnostic work-up of acute promyelocytic leukemia (APL) includes the cytogenetic demonstration of the t(15;17) translocation and/or the PML-RARA chimeric transcript by RQ-PCR or RT-PCR. This latter assays provide suitable results in 3-6 hours. We describe here two new, rapid and specific assays that detect PML-RARA transcripts, based on the RT-QLAMP (Reverse Transcription-Quenching Loop-mediated Isothermal Amplification) technology in which RNA retrotranscription and cDNA amplification are carried out in a single tube with one enzyme at one temperature, in fluorescence and real time format. A single tube triplex assay detects bcr1 and bcr3 PML-RARA transcripts along with GUS housekeeping gene. A single tube duplex assay detects bcr2 and GUSB. In 73 APL cases, these assays detected in 16 minutes bcr1, bcr2 and bcr3 transcripts. All 81 non-APL samples were negative by RT-QLAMP for chimeric transcripts whereas GUSB was detectable. In 11 APL patients in which RT-PCR yielded equivocal breakpoint type results, RT-QLAMP assays unequivocally and accurately defined the breakpoint type (as confirmed by sequencing). Furthermore, RT-QLAMP could amplify two bcr2 transcripts with particularly extended PML exon 6 deletions not amplified by RQ-PCR. RT-QLAMP reproducible sensitivity is 10−3 for bcr1 and bcr3 and 10−2 for bcr2 thus making this assay particularly attractive at diagnosis and leaving RQ-PCR for the molecular monitoring of minimal residual disease during the follow up. In conclusion, PML-RARA RT-QLAMP compared to RT-PCR or RQ-PCR is a valid improvement to perform rapid, simple and accurate molecular diagnosis of APL. PMID:25815362

  15. Barriers to accurate diagnosis and effective management of heart failure in primary care: qualitative study

    PubMed Central

    Fuat, Ahmet; Hungin, A Pali S; Murphy, Jeremy James

    2003-01-01

    overcome across primary and secondary care in implementation strategies that are specific to the locality and multifaceted. Single strategies—for example, the provision of guidelines—are unlikely to have an impact on clinical outcomes, and new, conjoint models of care need to be explored. What is already known on this topicHeart failure is a common condition with a high morbidity and mortality and is largely managed in primary careAlthough modern management with accurate diagnosis and treatment improves prognosis considerably, unacceptable variations exist in the clinical application of current guidelines for heart failureWhat this study addsGeneral practitioners expressed a lack of confidence in establishing an accurate diagnosis of left ventricular systolic dysfunction, even if open access echocardiography was availableUncertainty about diagnosis led to poor uptake of evidence based treatment strategies for heart failure patients, and, despite awareness, reluctance to initiate modern treatmentLocal organisational factors around NHS provision of diagnostic services, resources, and interaction between primary and secondary care influence how general practitioners manage heart failureImplementation strategies for heart failure management across primary and secondary care are needed that are specific to their locality and multifaceted PMID:12543836

  16. Accurate Molecular Polarizabilities Based on Continuum Electrostatics

    PubMed Central

    Truchon, Jean-François; Nicholls, Anthony; Iftimie, Radu I.; Roux, Benoît; Bayly, Christopher I.

    2013-01-01

    A novel approach for representing the intramolecular polarizability as a continuum dielectric is introduced to account for molecular electronic polarization. It is shown, using a finite-difference solution to the Poisson equation, that the Electronic Polarization from Internal Continuum (EPIC) model yields accurate gas-phase molecular polarizability tensors for a test set of 98 challenging molecules composed of heteroaromatics, alkanes and diatomics. The electronic polarization originates from a high intramolecular dielectric that produces polarizabilities consistent with B3LYP/aug-cc-pVTZ and experimental values when surrounded by vacuum dielectric. In contrast to other approaches to model electronic polarization, this simple model avoids the polarizability catastrophe and accurately calculates molecular anisotropy with the use of very few fitted parameters and without resorting to auxiliary sites or anisotropic atomic centers. On average, the unsigned error in the average polarizability and anisotropy compared to B3LYP are 2% and 5%, respectively. The correlation between the polarizability components from B3LYP and this approach lead to a R2 of 0.990 and a slope of 0.999. Even the F2 anisotropy, shown to be a difficult case for existing polarizability models, can be reproduced within 2% error. In addition to providing new parameters for a rapid method directly applicable to the calculation of polarizabilities, this work extends the widely used Poisson equation to areas where accurate molecular polarizabilities matter. PMID:23646034

  17. Development and Validation of a Highly Accurate Quantitative Real-Time PCR Assay for Diagnosis of Bacterial Vaginosis.

    PubMed

    Hilbert, David W; Smith, William L; Chadwick, Sean G; Toner, Geoffrey; Mordechai, Eli; Adelson, Martin E; Aguin, Tina J; Sobel, Jack D; Gygax, Scott E

    2016-04-01

    Bacterial vaginosis (BV) is the most common gynecological infection in the United States. Diagnosis based on Amsel's criteria can be challenging and can be aided by laboratory-based testing. A standard method for diagnosis in research studies is enumeration of bacterial morphotypes of a Gram-stained vaginal smear (i.e., Nugent scoring). However, this technique is subjective, requires specialized training, and is not widely available. Therefore, a highly accurate molecular assay for the diagnosis of BV would be of great utility. We analyzed 385 vaginal specimens collected prospectively from subjects who were evaluated for BV by clinical signs and Nugent scoring. We analyzed quantitative real-time PCR (qPCR) assays on DNA extracted from these specimens to quantify nine organisms associated with vaginal health or disease:Gardnerella vaginalis,Atopobium vaginae, BV-associated bacteria 2 (BVAB2, an uncultured member of the orderClostridiales),Megasphaeraphylotype 1 or 2,Lactobacillus iners,Lactobacillus crispatus,Lactobacillus gasseri, andLactobacillus jensenii We generated a logistic regression model that identifiedG. vaginalis,A. vaginae, andMegasphaeraphylotypes 1 and 2 as the organisms for which quantification provided the most accurate diagnosis of symptomatic BV, as defined by Amsel's criteria and Nugent scoring, with 92% sensitivity, 95% specificity, 94% positive predictive value, and 94% negative predictive value. The inclusion ofLactobacillusspp. did not contribute sufficiently to the quantitative model for symptomatic BV detection. This molecular assay is a highly accurate laboratory tool to assist in the diagnosis of symptomatic BV. PMID:26818677

  18. Informatics-based, highly accurate, noninvasive prenatal paternity testing

    PubMed Central

    Ryan, Allison; Baner, Johan; Demko, Zachary; Hill, Matthew; Sigurjonsson, Styrmir; Baird, Michael L.; Rabinowitz, Matthew

    2013-01-01

    Purpose: The aim of the study was to evaluate the diagnostic accuracy of an informatics-based, noninvasive, prenatal paternity test using array-based single-nucleotide polymorphism measurements of cell-free DNA isolated from maternal plasma. Methods: Blood samples were taken from 21 adult pregnant women (with gestational ages between 6 and 21 weeks), and a genetic sample was taken from the corresponding biological fathers. Paternity was confirmed by genetic testing of the infant, products of conception, control of fertilization, and/or preimplantation genetic diagnosis during in vitro fertilization. Parental DNA samples and maternal plasma cell-free DNA were amplified and analyzed using a HumanCytoSNP-12 array. An informatics-based method measured single-nucleotide polymorphism data, confirming or rejecting paternity. Each plasma sample with a sufficient fetal cell-free DNA fraction was independently tested against the confirmed father and 1,820 random, unrelated males. Results: One of the 21 samples had insufficient fetal cell-free DNA. The test correctly confirmed paternity for the remaining 20 samples (100%) when tested against the biological father, with P values of <10−4. For the 36,400 tests using an unrelated male as the alleged father, 99.95% (36,382) correctly excluded paternity and 0.05% (18) were indeterminate. There were no miscalls. Conclusion: A noninvasive paternity test using informatics-based analysis of single-nucleotide polymorphism array measurements accurately determined paternity early in pregnancy. PMID:23258349

  19. Safe, accurate, prenatal diagnosis of thanatophoric dysplasia using ultrasound and free fetal DNA

    PubMed Central

    Chitty, Lyn S; Khalil, Asma; Barrett, Angela N; Pajkrt, Eva; Griffin, David R; Cole, Tim J

    2013-01-01

    Objective To improve the prenatal diagnosis of thanatophoric dysplasia by defining the change in fetal size across gestation and the frequency of sonographic features, and developing non-invasive molecular genetic diagnosis based on cell-free fetal DNA (cffDNA) in maternal plasma. Methods Fetuses with a confirmed diagnosis of thanatophoric dysplasia were ascertained, records reviewed, sonographic features and measurements determined. Charts of fetal size were then constructed using the LMS (lambda-mu-sigma) method and compared with charts used in normal pregnancies and those complicated by achondroplasia. Cases in this cohort referred to our Regional Genetics Laboratory for molecular diagnosis using cffDNA were identified and results reviewed. Results Forty-two cases were scanned in our units. Commonly reported sonographic features were very short and sometimes bowed femora, frontal bossing, cloverleaf skull, short fingers, a small chest and polyhydramnios. Limb shortening was obvious from as early as 13 weeks' gestation, with minimal growth after 20 weeks. Analysis of cffDNA in three of these pregnancies confirmed the presence of the c.742C>CT (p.Arg248Cys) or the c.1948A>AG (p.Lys650Glu) mutation in the fibroblast growth factor receptor 3 gene. Conclusion These data should improve the accuracy of the sonographic diagnosis of thanatophoric dysplasia and have implications for reliable and safe targeted molecular confirmation using cffDNA. © 2013 The Authors. Prenatal Diagnosis published by John Wiley & Sons Ltd. PMID:23408600

  20. Urinary PCR as an increasingly useful tool for an accurate diagnosis of leptospirosis in livestock.

    PubMed

    Hamond, C; Martins, G; Loureiro, A P; Pestana, C; Lawson-Ferreira, R; Medeiros, M A; Lilenbaum, W

    2014-03-01

    The aim of the present study was to consider the wide usage of urinary PCR as an increasingly useful tool for an accurate diagnosis of leptospirosis in livestock. A total of 512 adult animals (300 cattle, 138 horses, 59 goats and 15 pigs), from herds/flocks with reproductive problems in Rio de Janeiro, Brazil was studied by serology and urinary PCR. From the 512 serum samples tested, 223 (43.5 %) were seroreactive (cattle: 45.6 %, horses: 41.3 %, goats: 34%and pigs: 60 %). PCR detected leptospiral DNA in 32.4 % (cattle: 21.6 %, horses: 36.2 %, goats: 77.4 % and pigs: 33.3 %. To our knowledge there is no another study including such a large number of samples (512) from different species, providing a comprehensive analysis of the usage of PCR for detecting leptospiral carriers in livestock. Serological and molecular results were discrepant, regardless the titre, what was an expected outcome. Nevertheless, it is impossible to establish agreement between these tests, since the two methodologies are conducted on different samples (MAT - serum; PCR - urine). Additionally, the MAT is an indirect method and PCR is a direct one. In conclusion, we have demonstrated that urinary PCR should be considered and encouraged as an increasingly useful tool for an accurate diagnosis of leptospirosis in livestock. PMID:24222053

  1. MicroRNA-200 Family Profile: A Promising Ancillary Tool for Accurate Cancer Diagnosis

    PubMed Central

    Liu, Xiaodong; Zhang, Jianhua; Xie, Botao; Li, Hao; Shen, Jihong; Chen, Jianheng

    2016-01-01

    Cancer is one of the most threatening diseases in the world and great interests have been paid to discover accurate and noninvasive methods for cancer diagnosis. The value of microRNA-200 (miRNA-200, miR-200) family has been revealed in many studies. However, the results from various studies were inconsistent, and thus a meta-analysis was designed and performed to assess the overall value of miRNA200 in cancer diagnosis. Relevant studies were searched electronically from the following databases: PubMed, Embase, Web of Science, the Cochrane Library, and Chinese National Knowledge Infrastructure. Keyword combined with “miR-200,” “cancer,” and “diagnosis” in any fields was used for searching relevant studies. Then, the pooled sensitivity, specificity, area under the curve (AUC), and partial AUC were calculated using the random-effects model. Heterogeneity among individual studies was also explored by subgroup analyses. A total of 28 studies from 18 articles with an overall sample size of 3676 subjects (2097 patients and 1579 controls) were included in this meta-analysis. The overall sensitivity and specificity with 95% confidence intervals (95% CIs) are 0.709 (95% CI: 0.657–0.755) and 0.667 (95% CI: 0.617–0.713), respectively. Additionally, AUC and partial AUC for the pooled data is 0.735 and 0.627, respectively. Subgroup analyses revealed that using miRNA-200 family for cancer diagnosis is more effective in white than in Asian ethnic groups. In addition, cancer diagnosis by miRNA using circulating specimen is more effective than that using noncirculating specimen. Finally, miRNA is more accurate in diagnosing endometrial cancer than other types of cancer, and some miRNA family members (miR-200b and miR-429) have superior diagnostic accuracy than other miR-200 family members. In conclusion, the profiling of miRNA-200 family is likely to be a valuable tool in cancer detection and diagnosis. PMID:26618619

  2. Knowledge-based nursing diagnosis

    NASA Astrophysics Data System (ADS)

    Roy, Claudette; Hay, D. Robert

    1991-03-01

    Nursing diagnosis is an integral part of the nursing process and determines the interventions leading to outcomes for which the nurse is accountable. Diagnoses under the time constraints of modern nursing can benefit from a computer assist. A knowledge-based engineering approach was developed to address these problems. A number of problems were addressed during system design to make the system practical extended beyond capture of knowledge. The issues involved in implementing a professional knowledge base in a clinical setting are discussed. System functions, structure, interfaces, health care environment, and terminology and taxonomy are discussed. An integrated system concept from assessment through intervention and evaluation is outlined.

  3. How accurate is the diagnosis of exercise induced asthma among Vancouver schoolchildren?

    PubMed Central

    Seear, M; Wensley, D; West, N

    2005-01-01

    Background: Limited access to exercise testing facilities means that the diagnosis of exercise induced asthma (EIA) is mainly based on self-reported respiratory symptoms. This is open to error since the correlation between exercise related symptoms and subsequent exercise testing has been shown to be poor. Aim: To study the accuracy of clinically diagnosed EIA among Vancouver schoolchildren. Methods: Fifty two children referred for investigation of poorly controlled EIA were studied. Following a careful history and physical examination, children performed pulmonary function tests before, then 5 and 15 minutes after a standardised treadmill exercise test. Based on overall assessment, a diagnostic explanation for each child's respiratory complaints was provided as far as possible. Results: Only eight children (15.4%) fulfilled diagnostic criteria for EIA (fall in FEV1 ⩾10%). Of the remainder: 12 (23.1%) were unfit, 14 (26.9%) had vocal cord dysfunction/sigh dyspnoea, 7 (13.5%) had a habit cough, and 11 (21.1%) had no abnormalities on clinical or laboratory testing, so were given no diagnosis. Initial reported symptoms of wheeze or cough often changed significantly following a careful history, particularly among the eight elite athletes. The final complaint was sometimes not respiratory, and, in a few cases, was not even associated with exercise. Conclusions: The clinical diagnosis of EIA is inaccurate among Vancouver schoolchildren, principally due to the unreliability of their initial exercise related complaints. Symptom exaggeration, familiarity with medical jargon, and psychogenic complaints are all common. A careful history is essential in this population before basing any diagnosis on self-reported respiratory symptoms. PMID:15855180

  4. Accurate diagnosis of thyroid follicular lesions from nuclear morphology using supervised learning

    PubMed Central

    Ozolek, John A.; Tosun, Akif Burak; Wang, Wei; Chen, Cheng; Kolouri, Soheil; Basu, Saurav; Huang, Hu; Rohde, Gustavo K.

    2014-01-01

    Follicular lesions of the thyroid remain significant diagnostic challenges in surgical pathology and cytology. The diagnosis often requires considerable resources and ancillary tests including immunohistochemistry, molecular studies, and expert consultation. Visual analyses of nuclear morphological features, generally speaking, have not been helpful in distinguishing this group of lesions. Here we describe a method for distinguishing between follicular lesions of the thyroid based on nuclear morphology. The method utilizes an optimal transport-based linear embedding for segmented nuclei, together with an adaptation of existing classification methods. We show the method outputs assignments (classification results) which are near perfectly correlated with the clinical diagnosis of several lesion types' lesions utilizing a database of 94 patients in total. Experimental comparisons also show the new method can significantly outperform standard numerical feature-type methods in terms of agreement with the clinical diagnosis gold standard. In addition, the new method could potentially be used to derive insights into biologically meaningful nuclear morphology differences in these lesions. Our methods could be incorporated into a tool for pathologists to aid in distinguishing between follicular lesions of the thyroid. In addition, these results could potentially provide nuclear morphological correlates of biological behavior and reduce health care costs by decreasing histotechnician and pathologist time and obviating the need for ancillary testing. PMID:24835183

  5. ACE-I Angioedema: Accurate Clinical Diagnosis May Prevent Epinephrine-Induced Harm

    PubMed Central

    Curtis, R. Mason; Felder, Sarah; Borici-Mazi, Rozita; Ball, Ian

    2016-01-01

    Introduction Upper airway angioedema is a life-threatening emergency department (ED) presentation with increasing incidence. Angiotensin-converting enzyme inhibitor induced angioedema (AAE) is a non-mast cell mediated etiology of angioedema. Accurate diagnosis by clinical examination can optimize patient management and reduce morbidity from inappropriate treatment with epinephrine. The aim of this study is to describe the incidence of angioedema subtypes and the management of AAE. We evaluate the appropriateness of treatments and highlight preventable iatrogenic morbidity. Methods We conducted a retrospective chart review of consecutive angioedema patients presenting to two tertiary care EDs between July 2007 and March 2012. Results Of 1,702 medical records screened, 527 were included. The cause of angioedema was identified in 48.8% (n=257) of cases. The most common identifiable etiology was AAE (33.1%, n=85), with a 60.0% male predominance. The most common AAE management strategies included diphenhydramine (63.5%, n=54), corticosteroids (50.6%, n=43) and ranitidine (31.8%, n=27). Epinephrine was administered in 21.2% (n=18) of AAE patients, five of whom received repeated doses. Four AAE patients required admission (4.7%) and one required endotracheal intubation. Epinephrine induced morbidity in two patients, causing myocardial ischemia or dysrhythmia shortly after administration. Conclusion AAE is the most common identifiable etiology of angioedema and can be accurately diagnosed by physical examination. It is easily confused with anaphylaxis and mismanaged with antihistamines, corticosteroids and epinephrine. There is little physiologic rationale for epinephrine use in AAE and much risk. Improved clinical differentiation of mast cell and non-mast cell mediated angioedema can optimize patient management. PMID:27330660

  6. Non-invasive prenatal diagnosis of achondroplasia and thanatophoric dysplasia: next-generation sequencing allows for a safer, more accurate, and comprehensive approach

    PubMed Central

    Chitty, Lyn S; Mason, Sarah; Barrett, Angela N; McKay, Fiona; Lench, Nicholas; Daley, Rebecca; Jenkins, Lucy A

    2015-01-01

    Abstract Objective Accurate prenatal diagnosis of genetic conditions can be challenging and usually requires invasive testing. Here, we demonstrate the potential of next-generation sequencing (NGS) for the analysis of cell-free DNA in maternal blood to transform prenatal diagnosis of monogenic disorders. Methods Analysis of cell-free DNA using a PCR and restriction enzyme digest (PCR–RED) was compared with a novel NGS assay in pregnancies at risk of achondroplasia and thanatophoric dysplasia. Results PCR–RED was performed in 72 cases and was correct in 88.6%, inconclusive in 7% with one false negative. NGS was performed in 47 cases and was accurate in 96.2% with no inconclusives. Both approaches were used in 27 cases, with NGS giving the correct result in the two cases inconclusive with PCR–RED. Conclusion NGS provides an accurate, flexible approach to non-invasive prenatal diagnosis of de novo and paternally inherited mutations. It is more sensitive than PCR–RED and is ideal when screening a gene with multiple potential pathogenic mutations. These findings highlight the value of NGS in the development of non-invasive prenatal diagnosis for other monogenic disorders. © 2015 The Authors. Prenatal Diagnosis published by John Wiley & Sons, Ltd. What's already known about this topic? Non-invasive prenatal diagnosis (NIPD) using PCR-based methods has been reported for the detection or exclusion of individual paternally inherited or de novo alleles in maternal plasma. What does this study add? NIPD using next generation sequencing provides an accurate, more sensitive approach which can be used to detect multiple mutations in a single assay and so is ideal when screening a gene with multiple potential pathogenic mutations. Next generation sequencing thus provides a flexible approach to non-invasive prenatal diagnosis ideal for use in a busy service laboratory. PMID:25728633

  7. Differential equation based method for accurate approximations in optimization

    NASA Technical Reports Server (NTRS)

    Pritchard, Jocelyn I.; Adelman, Howard M.

    1990-01-01

    A method to efficiently and accurately approximate the effect of design changes on structural response is described. The key to this method is to interpret sensitivity equations as differential equations that may be solved explicitly for closed form approximations, hence, the method is denoted the Differential Equation Based (DEB) method. Approximations were developed for vibration frequencies, mode shapes and static displacements. The DEB approximation method was applied to a cantilever beam and results compared with the commonly-used linear Taylor series approximations and exact solutions. The test calculations involved perturbing the height, width, cross-sectional area, tip mass, and bending inertia of the beam. The DEB method proved to be very accurate, and in most cases, was more accurate than the linear Taylor series approximation. The method is applicable to simultaneous perturbation of several design variables. Also, the approximations may be used to calculate other system response quantities. For example, the approximations for displacements are used to approximate bending stresses.

  8. Obtaining More Accurate Signals: Spatiotemporal Imaging of Cancer Sites Enabled by a Photoactivatable Aptamer-Based Strategy.

    PubMed

    Xiao, Heng; Chen, Yuqi; Yuan, Erfeng; Li, Wei; Jiang, Zhuoran; Wei, Lai; Su, Haomiao; Zeng, Weiwu; Gan, Yunjiu; Wang, Zijing; Yuan, Bifeng; Qin, Shanshan; Leng, Xiaohua; Zhou, Xin; Liu, Songmei; Zhou, Xiang

    2016-09-14

    Early cancer diagnosis is of great significance to relative cancer prevention and clinical therapy, and it is crucial to efficiently recognize cancerous tumor sites at the molecular level. Herein, we proposed a versatile and efficient strategy based on aptamer recognition and photoactivation imaging for cancer diagnosis. This is the first time that a visible light-controlled photoactivatable aptamer-based platform has been applied for cancer diagnosis. The photoactivatable aptamer-based strategy can accurately detect nucleolin-overexpressed tumor cells and can be used for highly selective cancer cell screening and tissue imaging. This strategy is available for both formalin-fixed paraffin-embedded tissue specimens and frozen sections. Moreover, the photoactivation techniques showed great progress in more accurate and persistent imaging to the use of traditional fluorophores. Significantly, the application of this strategy can produce the same accurate results in tissue specimen analysis as with classical hematoxylin-eosin staining and immunohistochemical technology. PMID:27550088

  9. Light Field Imaging Based Accurate Image Specular Highlight Removal

    PubMed Central

    Wang, Haoqian; Xu, Chenxue; Wang, Xingzheng; Zhang, Yongbing; Peng, Bo

    2016-01-01

    Specular reflection removal is indispensable to many computer vision tasks. However, most existing methods fail or degrade in complex real scenarios for their individual drawbacks. Benefiting from the light field imaging technology, this paper proposes a novel and accurate approach to remove specularity and improve image quality. We first capture images with specularity by the light field camera (Lytro ILLUM). After accurately estimating the image depth, a simple and concise threshold strategy is adopted to cluster the specular pixels into “unsaturated” and “saturated” category. Finally, a color variance analysis of multiple views and a local color refinement are individually conducted on the two categories to recover diffuse color information. Experimental evaluation by comparison with existed methods based on our light field dataset together with Stanford light field archive verifies the effectiveness of our proposed algorithm. PMID:27253083

  10. Note-accurate audio segmentation based on MPEG-7

    NASA Astrophysics Data System (ADS)

    Wellhausen, Jens

    2003-12-01

    Segmenting audio data into the smallest musical components is the basis for many further meta data extraction algorithms. For example, an automatic music transcription system needs to know where the exact boundaries of each tone are. In this paper a note accurate audio segmentation algorithm based on MPEG-7 low level descriptors is introduced. For a reliable detection of different notes, both features in the time and the frequency domain are used. Because of this, polyphonic instrument mixes and even melodies characterized by human voices can be examined with this alogrithm. For testing and verification of the note accurate segmentation, a simple music transcription system was implemented. The dominant frequency within each segment is used to build a MIDI file representing the processed audio data.

  11. A fast and accurate FPGA based QRS detection system.

    PubMed

    Shukla, Ashish; Macchiarulo, Luca

    2008-01-01

    An accurate Field Programmable Gate Array (FPGA) based ECG Analysis system is described in this paper. The design, based on a popular software based QRS detection algorithm, calculates the threshold value for the next peak detection cycle, from the median of eight previously detected peaks. The hardware design has accuracy in excess of 96% in detecting the beats correctly when tested with a subset of five 30 minute data records obtained from the MIT-BIH Arrhythmia database. The design, implemented using a proprietary design tool (System Generator), is an extension of our previous work and uses 76% resources available in a small-sized FPGA device (Xilinx Spartan xc3s500), has a higher detection accuracy as compared to our previous design and takes almost half the analysis time in comparison to software based approach. PMID:19163797

  12. Differential equation based method for accurate approximations in optimization

    NASA Technical Reports Server (NTRS)

    Pritchard, Jocelyn I.; Adelman, Howard M.

    1990-01-01

    This paper describes a method to efficiently and accurately approximate the effect of design changes on structural response. The key to this new method is to interpret sensitivity equations as differential equations that may be solved explicitly for closed form approximations, hence, the method is denoted the Differential Equation Based (DEB) method. Approximations were developed for vibration frequencies, mode shapes and static displacements. The DEB approximation method was applied to a cantilever beam and results compared with the commonly-used linear Taylor series approximations and exact solutions. The test calculations involved perturbing the height, width, cross-sectional area, tip mass, and bending inertia of the beam. The DEB method proved to be very accurate, and in msot cases, was more accurate than the linear Taylor series approximation. The method is applicable to simultaneous perturbation of several design variables. Also, the approximations may be used to calculate other system response quantities. For example, the approximations for displacement are used to approximate bending stresses.

  13. Model-based reconfiguration: Diagnosis and recovery

    NASA Technical Reports Server (NTRS)

    Crow, Judy; Rushby, John

    1994-01-01

    We extend Reiter's general theory of model-based diagnosis to a theory of fault detection, identification, and reconfiguration (FDIR). The generality of Reiter's theory readily supports an extension in which the problem of reconfiguration is viewed as a close analog of the problem of diagnosis. Using a reconfiguration predicate 'rcfg' analogous to the abnormality predicate 'ab,' we derive a strategy for reconfiguration by transforming the corresponding strategy for diagnosis. There are two obvious benefits of this approach: algorithms for diagnosis can be exploited as algorithms for reconfiguration and we have a theoretical framework for an integrated approach to FDIR. As a first step toward realizing these benefits we show that a class of diagnosis engines can be used for reconfiguration and we discuss algorithms for integrated FDIR. We argue that integrating recovery and diagnosis is an essential next step if this technology is to be useful for practical applications.

  14. Accurate phylogenetic classification of DNA fragments based onsequence composition

    SciTech Connect

    McHardy, Alice C.; Garcia Martin, Hector; Tsirigos, Aristotelis; Hugenholtz, Philip; Rigoutsos, Isidore

    2006-05-01

    Metagenome studies have retrieved vast amounts of sequenceout of a variety of environments, leading to novel discoveries and greatinsights into the uncultured microbial world. Except for very simplecommunities, diversity makes sequence assembly and analysis a verychallenging problem. To understand the structure a 5 nd function ofmicrobial communities, a taxonomic characterization of the obtainedsequence fragments is highly desirable, yet currently limited mostly tothose sequences that contain phylogenetic marker genes. We show that forclades at the rank of domain down to genus, sequence composition allowsthe very accurate phylogenetic 10 characterization of genomic sequence.We developed a composition-based classifier, PhyloPythia, for de novophylogenetic sequence characterization and have trained it on adata setof 340 genomes. By extensive evaluation experiments we show that themethodis accurate across all taxonomic ranks considered, even forsequences that originate fromnovel organisms and are as short as 1kb.Application to two metagenome datasets 15 obtained from samples ofphosphorus-removing sludge showed that the method allows the accurateclassification at genus level of most sequence fragments from thedominant populations, while at the same time correctly characterizingeven larger parts of the samples at higher taxonomic levels.

  15. Application of a cell microarray chip system for accurate, highly sensitive, and rapid diagnosis for malaria in Uganda

    PubMed Central

    Yatsushiro, Shouki; Yamamoto, Takeki; Yamamura, Shohei; Abe, Kaori; Obana, Eriko; Nogami, Takahiro; Hayashi, Takuya; Sesei, Takashi; Oka, Hiroaki; Okello-Onen, Joseph; Odongo-Aginya, Emmanuel I.; Alai, Mary Auma; Olia, Alex; Anywar, Dennis; Sakurai, Miki; Palacpac, Nirianne MQ; Mita, Toshihiro; Horii, Toshihiro; Baba, Yoshinobu; Kataoka, Masatoshi

    2016-01-01

    Accurate, sensitive, rapid, and easy operative diagnosis is necessary to prevent the spread of malaria. A cell microarray chip system including a push column for the recovery of erythrocytes and a fluorescence detector was employed for malaria diagnosis in Uganda. The chip with 20,944 microchambers (105 μm width and 50 μm depth) was made of polystyrene. For the analysis, 6 μl of whole blood was employed, and leukocytes were practically removed by filtration through SiO2-nano-fibers in a column. Regular formation of an erythrocyte monolayer in each microchamber was observed following dispersion of an erythrocyte suspension in a nuclear staining dye, SYTO 21, onto the chip surface and washing. About 500,000 erythrocytes were analyzed in a total of 4675 microchambers, and malaria parasite-infected erythrocytes could be detected in 5 min by using the fluorescence detector. The percentage of infected erythrocytes in each of 41 patients was determined. Accurate and quantitative detection of the parasites could be performed. A good correlation between examinations via optical microscopy and by our chip system was demonstrated over the parasitemia range of 0.0039–2.3438% by linear regression analysis (R2 = 0.9945). Thus, we showed the potential of this chip system for the diagnosis of malaria. PMID:27445125

  16. Application of a cell microarray chip system for accurate, highly sensitive, and rapid diagnosis for malaria in Uganda.

    PubMed

    Yatsushiro, Shouki; Yamamoto, Takeki; Yamamura, Shohei; Abe, Kaori; Obana, Eriko; Nogami, Takahiro; Hayashi, Takuya; Sesei, Takashi; Oka, Hiroaki; Okello-Onen, Joseph; Odongo-Aginya, Emmanuel I; Alai, Mary Auma; Olia, Alex; Anywar, Dennis; Sakurai, Miki; Palacpac, Nirianne Mq; Mita, Toshihiro; Horii, Toshihiro; Baba, Yoshinobu; Kataoka, Masatoshi

    2016-01-01

    Accurate, sensitive, rapid, and easy operative diagnosis is necessary to prevent the spread of malaria. A cell microarray chip system including a push column for the recovery of erythrocytes and a fluorescence detector was employed for malaria diagnosis in Uganda. The chip with 20,944 microchambers (105 μm width and 50 μm depth) was made of polystyrene. For the analysis, 6 μl of whole blood was employed, and leukocytes were practically removed by filtration through SiO2-nano-fibers in a column. Regular formation of an erythrocyte monolayer in each microchamber was observed following dispersion of an erythrocyte suspension in a nuclear staining dye, SYTO 21, onto the chip surface and washing. About 500,000 erythrocytes were analyzed in a total of 4675 microchambers, and malaria parasite-infected erythrocytes could be detected in 5 min by using the fluorescence detector. The percentage of infected erythrocytes in each of 41 patients was determined. Accurate and quantitative detection of the parasites could be performed. A good correlation between examinations via optical microscopy and by our chip system was demonstrated over the parasitemia range of 0.0039-2.3438% by linear regression analysis (R(2) = 0.9945). Thus, we showed the potential of this chip system for the diagnosis of malaria. PMID:27445125

  17. Knowledge-based diagnosis for aerospace systems

    NASA Technical Reports Server (NTRS)

    Atkinson, David J.

    1988-01-01

    The need for automated diagnosis in aerospace systems and the approach of using knowledge-based systems are examined. Research issues in knowledge-based diagnosis which are important for aerospace applications are treated along with a review of recent relevant research developments in Artificial Intelligence. The design and operation of some existing knowledge-based diagnosis systems are described. The systems described and compared include the LES expert system for liquid oxygen loading at NASA Kennedy Space Center, the FAITH diagnosis system developed at the Jet Propulsion Laboratory, the PES procedural expert system developed at SRI International, the CSRL approach developed at Ohio State University, the StarPlan system developed by Ford Aerospace, the IDM integrated diagnostic model, and the DRAPhys diagnostic system developed at NASA Langley Research Center.

  18. A novel, integrated PET-guided MRS technique resulting in more accurate initial diagnosis of high-grade glioma.

    PubMed

    Kim, Ellen S; Satter, Martin; Reed, Marilyn; Fadell, Ronald; Kardan, Arash

    2016-06-01

    Glioblastoma multiforme (GBM) is the most common and lethal malignant glioma in adults. Currently, the modality of choice for diagnosing brain tumor is high-resolution magnetic resonance imaging (MRI) with contrast, which provides anatomic detail and localization. Studies have demonstrated, however, that MRI may have limited utility in delineating the full tumor extent precisely. Studies suggest that MR spectroscopy (MRS) can also be used to distinguish high-grade from low-grade gliomas. However, due to operator dependent variables and the heterogeneous nature of gliomas, the potential for error in diagnostic accuracy with MRS is a concern. Positron emission tomography (PET) imaging with (11)C-methionine (MET) and (18)F-fluorodeoxyglucose (FDG) has been shown to add additional information with respect to tumor grade, extent, and prognosis based on the premise of biochemical changes preceding anatomic changes. Combined PET/MRS is a technique that integrates information from PET in guiding the location for the most accurate metabolic characterization of a lesion via MRS. We describe a case of glioblastoma multiforme in which MRS was initially non-diagnostic for malignancy, but when MRS was repeated with PET guidance, demonstrated elevated choline/N-acetylaspartate (Cho/NAA) ratio in the right parietal mass consistent with a high-grade malignancy. Stereotactic biopsy, followed by PET image-guided resection, confirmed the diagnosis of grade IV GBM. To our knowledge, this is the first reported case of an integrated PET/MRS technique for the voxel placement of MRS. Our findings suggest that integrated PET/MRS may potentially improve diagnostic accuracy in high-grade gliomas. PMID:27122050

  19. Fiber diffraction of skin and nails provides an accurate diagnosis of malignancies

    SciTech Connect

    James, Veronica J.

    2009-10-21

    An early diagnosis of malignancies correlates directly with a better prognosis. Yet for many malignancies there are no readily available, noninvasive, cost-effective diagnostic tests with patients often presenting too late for effective treatment. This article describes for the first time the use of fiber diffraction patterns of skin or fingernails, using X-ray sources, as a biometric diagnostic method for detecting neoplastic disorders including but not limited to melanoma, breast, colon and prostate cancers. With suitable further development, an early low-cost, totally noninvasive yet reliable diagnostic test could be conducted on a regular basis in local radiology facilities, as a confirmatory test for other diagnostic procedures or as a mass screening test using suitable small angle X-ray beam-lines at synchrotrons.

  20. Accurate diagnosis of renal transplant rejection by indium-111 platelet imaging despite postoperative cyclosporin therapy

    SciTech Connect

    Collier, B.D.; Adams, M.B.; Kauffman, H.M.; Trembath, L.; Hoffmann, R.G.; Tisdale, P.L.; Rao, S.A.; Hellman, R.S.; Isitman, A.T.

    1988-08-01

    Previous reports indicate that In-111 platelet scintigraphy (IPS) is a reliable test for the early diagnosis of acute post-operative renal transplant rejection (TR). However, the recent introduction of cyclosporin for post-transplantation immunosuppression requires that the diagnostic efficacy of IPS once again be established. Therefore, a prospective IPS study of 73 post-operative renal transplant recipients was conducted. Fourty-nine patients received cyclosporin and 24 patients did not receive this drug. Between these two patient groups, there were no significant differences in the diagnostic sensitivities (0.86 vs 0.80) and specificities (0.93 vs 0.84) with which TR was identified. We conclude that during the first two weeks following renal transplantation the cyclosporin treatment regimen used at our institution does not limit the reliability of IPS as a test for TR.

  1. Accurate mass spectrometry based protein quantification via shared peptides.

    PubMed

    Dost, Banu; Bandeira, Nuno; Li, Xiangqian; Shen, Zhouxin; Briggs, Steven P; Bafna, Vineet

    2012-04-01

    In mass spectrometry-based protein quantification, peptides that are shared across different protein sequences are often discarded as being uninformative with respect to each of the parent proteins. We investigate the use of shared peptides which are ubiquitous (~50% of peptides) in mass spectrometric data-sets for accurate protein identification and quantification. Different from existing approaches, we show how shared peptides can help compute the relative amounts of the proteins that contain them. Also, proteins with no unique peptide in the sample can still be analyzed for relative abundance. Our article uses shared peptides in protein quantification and makes use of combinatorial optimization to reduce the error in relative abundance measurements. We describe the topological and numerical properties required for robust estimates, and use them to improve our estimates for ill-conditioned systems. Extensive simulations validate our approach even in the presence of experimental error. We apply our method to a model of Arabidopsis thaliana root knot nematode infection, and investigate the differential role of several protein family members in mediating host response to the pathogen. PMID:22414154

  2. Prognostic factors in pediatric high-grade astrocytoma: the importance of accurate pathologic diagnosis.

    PubMed

    Hales, Russell K; Shokek, Ori; Burger, Peter C; Paynter, Nina P; Chaichana, Kaisorn L; Quiñones-Hinojosa, Alfredo; Jallo, George I; Cohen, Kenneth J; Song, Danny Y; Carson, Benjamin S; Wharam, Moody D

    2010-08-01

    To characterize a population of pediatric high-grade astrocytoma (HGA) patients by confirming the proportion with a correct diagnosis, and determine prognostic factors for survival in a subset diagnosed with uniform pathologic criteria. Sixty-three children diagnosed with HGA were treated at the Johns Hopkins Hospital between 1977 and 2004. A single neuropathologist (P.C.B.) reviewed all available histologic samples (n = 48). Log-rank analysis was used to compare survival by patient, tumor, and treatment factors. Median follow-up was 16 months for all patients and 155 months (minimum 54 months) for surviving patients. Median survival for all patients (n = 63) was 14 months with 10 long-term survivors (survival >48 months). At initial diagnosis, 27 patients were grade III (43%) and 36 grade IV (57%). Forty-eight patients had pathology slides available for review, including seven of ten long-term surviving patients. Four patients had non-HGA pathology, all of whom were long term survivors. The remaining 44 patients with confirmed HGG had a median survival of 14 months and prognostic analysis was confined to these patients. On multivariate analysis, five factors were associated with inferior survival: performance status (Lansky) <80% (13 vs. 15 months), bilaterality (13 vs. 19 months), parietal lobe location (13 vs. 16 months), resection less than gross total (13 vs. 22 months), and radiotherapy dose <50 Gy (9 vs. 16 months). Among patients with more than one of the five adverse factors (n = 27), median survival and proportion of long-term survivors were 12.9 months and 0%, compared with 41.4 months and 18% for patients with 0-1 adverse factors (n = 17). In an historical cohort of children with HGA, the potential for long term survival was confined to the subset with less than two of the following adverse prognostic factors: low performance status, bilaterality, parietal lobe site, less than gross total resection, and radiotherapy dose <50 Gy. Pathologic misdiagnosis

  3. Accurate Diagnosis of Sigmoid Colon Endometriosis by Immunohistochemistry and Transmission Electron Microscopy - A Case Report.

    PubMed

    Constantin, V; Carăp, A; Bobic, S; Pâun, I; Brâtilâ, E; Socea, B; Moroşanu, A-M; Mirancea, N

    2015-01-01

    Endometriosis is described as the presence of functioning endometrial tissue at sites outside the uterus. Up to 15% ofwomen in their reproductive period are affected by this condition. Endometriosis is mostly foundon the uterosacral ligaments, inside the rectovaginalseptum or vagina, in the rectosigmoid area, ovarianfossa, pelvic peritoneum, ureters, and bladder, causinga distortion of the pelvic anatomy. Colonic involvement is rare but is usually found at the level of the rectum or the sigmoid colon. Acute presentation with intestinal obstruction or perforation is rare. While malignant transformation of endometrial lesions is rare, findings of dysplasia on pathology sections can give rise to questions of management. Immunohistochemistry and electron microscopy can help decision making. We present the case of a 38 year old woman with intestinal obstruction caused by sigmoid colon endometriosis with moderate dysplasia in which transmission electron microscopy was used for postoperative diagnosis. Detailed analysis of these cases, while logistically difficult, can prove useful in understanding the etiology and pathophysiology of the disease. PMID:26531796

  4. Iofetamine I 123 single photon emission computed tomography is accurate in the diagnosis of Alzheimer's disease

    SciTech Connect

    Johnson, K.A.; Holman, B.L.; Rosen, T.J.; Nagel, J.S.; English, R.J.; Growdon, J.H. )

    1990-04-01

    To determine the diagnostic accuracy of iofetamine hydrochloride I 123 (IMP) with single photon emission computed tomography in Alzheimer's disease, we studied 58 patients with AD and 15 age-matched healthy control subjects. We used a qualitative method to assess regional IMP uptake in the entire brain and to rate image data sets as normal or abnormal without knowledge of subjects'clinical classification. The sensitivity and specificity of IMP with single photon emission computed tomography in AD were 88% and 87%, respectively. In 15 patients with mild cognitive deficits (Blessed Dementia Scale score, less than or equal to 10), sensitivity was 80%. With the use of a semiquantitative measure of regional cortical IMP uptake, the parietal lobes were the most functionally impaired in AD and the most strongly associated with the patients' Blessed Dementia Scale scores. These results indicated that IMP with single photon emission computed tomography may be a useful adjunct in the clinical diagnosis of AD in early, mild disease.

  5. Distributed real-time model-based diagnosis

    NASA Technical Reports Server (NTRS)

    Barrett, A. C.; Chung, S. H.

    2003-01-01

    This paper presents an approach to onboard anomaly diagnosis that combines the simplicity and real-time guarantee of a rule-based diagnosis system with the specification ease and coverage guarantees of a model-based diagnosis system.

  6. Accurate Alignment of Plasma Channels Based on Laser Centroid Oscillations

    SciTech Connect

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

    2011-03-23

    A technique has been developed to accurately align a laser beam through a plasma channel by minimizing the shift in laser centroid and angle at the channel outptut. If only the shift in centroid or angle is measured, then accurate alignment is provided by minimizing laser centroid motion at the channel exit as the channel properties are scanned. The improvement in alignment accuracy provided by this technique is important for minimizing electron beam pointing errors in laser plasma accelerators.

  7. TROP-2 immunohistochemistry: a highly accurate method in the differential diagnosis of papillary thyroid carcinoma.

    PubMed

    Bychkov, Andrey; Sampatanukul, Pichet; Shuangshoti, Shanop; Keelawat, Somboon

    2016-08-01

    We aimed to evaluate the diagnostic utility of the novel immunohistochemical marker TROP-2 on thyroid specimens (226 tumours and 207 controls). Whole slide immunohistochemistry was performed and scored by automated digital image analysis. Non-neoplastic thyroid, follicular adenomas, follicular carcinomas, and medullary carcinomas were negative for TROP-2 immunostaining. The majority of papillary thyroid carcinoma (PTC) specimens (94/114, 82.5%) were positive for TROP-2; however, the pattern of staining differed significantly between the histopathological variants. All papillary microcarcinomas (mPTC), PTC classic variant (PTC cv), and tall cell variant (PTC tcv) were TROP-2 positive, with mainly diffuse staining. In contrast, less than half of the PTC follicular variant specimens were positive for TROP-2, with only focal immunoreactivity. TROP-2 could identify PTC cv with 98.1% sensitivity and 97.5% specificity. ROC curve analysis found that the presence of >10% of TROP-2 positive cells in a tumour supported a diagnosis of PTC. The study of intratumoural heterogeneity showed that low-volume cytological samples of PTC cv could be adequately assessed by TROP-2 immunostaining. The TROP-2 H-score (intensity multiplied by proportion) was significantly associated with PTC variant and capsular invasion in encapsulated PTC follicular variant (p<0.001). None of the baseline (age, gender) and clinical (tumour size, nodal disease, stage) parameters were correlated with TROP-2 expression. In conclusion, TROP-2 membranous staining is a very sensitive and specific marker for PTC cv, PTC tcv, and mPTC, with high overall specificity for PTC. PMID:27311870

  8. Immunity-based diagnosis for a motherboard.

    PubMed

    Shida, Haruki; Okamoto, Takeshi; Ishida, Yoshiteru

    2011-01-01

    We have utilized immunity-based diagnosis to detect abnormal behavior of components on a motherboard. The immunity-based diagnostic model monitors voltages of some components, CPU temperatures, and fan speeds. We simulated abnormal behaviors of some components on the motherboard, and we utilized the immunity-based diagnostic model to evaluate motherboard sensors in two experiments. These experiments showed that the immunity-based diagnostic model was an effective method for detecting abnormal behavior of components on the motherboard. PMID:22163857

  9. Fast Algorithms for Model-Based Diagnosis

    NASA Technical Reports Server (NTRS)

    Fijany, Amir; Barrett, Anthony; Vatan, Farrokh; Mackey, Ryan

    2005-01-01

    Two improved new methods for automated diagnosis of complex engineering systems involve the use of novel algorithms that are more efficient than prior algorithms used for the same purpose. Both the recently developed algorithms and the prior algorithms in question are instances of model-based diagnosis, which is based on exploring the logical inconsistency between an observation and a description of a system to be diagnosed. As engineering systems grow more complex and increasingly autonomous in their functions, the need for automated diagnosis increases concomitantly. In model-based diagnosis, the function of each component and the interconnections among all the components of the system to be diagnosed (for example, see figure) are represented as a logical system, called the system description (SD). Hence, the expected behavior of the system is the set of logical consequences of the SD. Faulty components lead to inconsistency between the observed behaviors of the system and the SD. The task of finding the faulty components (diagnosis) reduces to finding the components, the abnormalities of which could explain all the inconsistencies. Of course, the meaningful solution should be a minimal set of faulty components (called a minimal diagnosis), because the trivial solution, in which all components are assumed to be faulty, always explains all inconsistencies. Although the prior algorithms in question implement powerful methods of diagnosis, they are not practical because they essentially require exhaustive searches among all possible combinations of faulty components and therefore entail the amounts of computation that grow exponentially with the number of components of the system.

  10. Fast and accurate line scanner based on white light interferometry

    NASA Astrophysics Data System (ADS)

    Lambelet, Patrick; Moosburger, Rudolf

    2013-04-01

    White-light interferometry is a highly accurate technology for 3D measurements. The principle is widely utilized in surface metrology instruments but rarely adopted for in-line inspection systems. The main challenges for rolling out inspection systems based on white-light interferometry to the production floor are its sensitivity to environmental vibrations and relatively long measurement times: a large quantity of data needs to be acquired and processed in order to obtain a single topographic measurement. Heliotis developed a smart-pixel CMOS camera (lock-in camera) which is specially suited for white-light interferometry. The demodulation of the interference signal is treated at the level of the pixel which typically reduces the acquisition data by one orders of magnitude. Along with the high bandwidth of the dedicated lock-in camera, vertical scan-speeds of more than 40mm/s are reachable. The high scan speed allows for the realization of inspection systems that are rugged against external vibrations as present on the production floor. For many industrial applications such as the inspection of wafer-bumps, surface of mechanical parts and solar-panel, large areas need to be measured. In this case either the instrument or the sample are displaced laterally and several measurements are stitched together. The cycle time of such a system is mostly limited by the stepping time for multiple lateral displacements. A line-scanner based on white light interferometry would eliminate most of the stepping time while maintaining robustness and accuracy. A. Olszak proposed a simple geometry to realize such a lateral scanning interferometer. We demonstrate that such inclined interferometers can benefit significantly from the fast in-pixel demodulation capabilities of the lock-in camera. One drawback of an inclined observation perspective is that its application is limited to objects with scattering surfaces. We therefore propose an alternate geometry where the incident light is

  11. Accurate genetic diagnosis of Finnish pulmonary arterial hypertension patients using oligonucleotide-selective sequencing

    PubMed Central

    Vattulainen, Sanna; Aho, Joonas; Salmenperä, Pertteli; Bruce, Siina; Tallila, Jonna; Gentile, Massimiliano; Sankelo, Marja; Laitinen, Tarja; Koskenvuo, Juha W; Alastalo, Tero-Pekka; Myllykangas, Samuel

    2015-01-01

    The genetic basis of pulmonary arterial hypertension (PAH) among Finnish PAH patients is poorly understood. We adopted a novel-targeted next-generation sequencing (NGS) approach called Oligonucleotide-Selective Sequencing (OS-Seq) and developed a custom data analysis and interpretation pipeline to identify pathogenic base substitutions, insertions, and deletions in seven genes associated with PAH (BMPR2, BMPR1B, ACVRL1, ENG, SMAD9, CAV1, and KCNK3) from Finnish PAH patients. This study represents the first clinical study with OS-Seq technology on patients suffering from a rare genetic disorder. We analyzed DNA samples from 21 Finnish PAH patients, whose BMPR2 and ACVRL1 mutation status had been previously studied using Sanger sequencing. Our sequencing panel covered 100% of the targeted base pairs with >15× sequencing depth. Pathogenic base substitutions were identified in the BMPR2 gene in 29% of the Finnish PAH cases. Two of the pathogenic variant-positive patients had been previously tested negative using Sanger sequencing. No clinically significant variants were identified in the six other PAH genes. Our study validates the use of targeted OS-Seq for genetic diagnostics of PAH and revealed pathogenic variants that had been previously missed using Sanger sequencing. PMID:26247051

  12. [An Accurate Diagnosis is Possible with a Systematic Analysis of Routine Laboratory Data].

    PubMed

    Yonekawa, Osamu

    2015-09-01

    Routine laboratory tests are ordered for almost all in- and outpatients. A systematic analysis of routine laboratory data can give doctors valuable clinical information about patients. In some cases, a correct diag- nosis can be made using laboratory data alone. In our laboratory, we use five processes to evaluate routine laboratory data. Firstly, we estimate the patient's general condition based on A/G, Hb, TP, Alb, ChE, and platelet (PLT) levels. Secondly, we look for inflammation and malignancy based on WBC, CRP, PLT, fibrinogen, and ESR levels and the protein electrophoresis pattern. Thirdly, we examine the major organs, especially the liver and kidney. We check the liver for hepatocyte damage, obstruction, hepatic synthetic function, infection, and malignancy. We estimate GFR and check the kidney for any localized damage. We then check the chemistry, hematology, and immunology. Finally, we form a conclusion after a comprehensive interpretation of the above four processes. With this systematic approach, any members of the laboratory unit can easily estimate the exact pathological status of the patient. In this case study, marked change of TP indicated non-selective loss from the skin; namely a burn. Tissue injury and infections due to different focuses were the most likely causes of severe inflammation. Neither the liver nor kidney was severely damaged. Continual bleeding and hemolysis through the clinical course probably caused anemia. Hypooxygenic respiratory failure and metabolic alkalosis were confirmed by blood gasses. Multiple organ failure was suggested. PMID:26731896

  13. PROMISE of Coronary CT Angiography: Precise and Accurate Diagnosis and Prognosis in Coronary Artery Disease.

    PubMed

    Thomas, Dustin M; Branch, Kelley R; Cury, Ricardo C

    2016-04-01

    Coronary computed tomography angiography (CCTA) is a rapidly growing and powerful diagnostic test that offers a great deal of precision with respect to diagnosing coronary artery disease (CAD). Guideline statements for patients with stable ischemic heart disease have recommended CCTA for only a limited portion of intermediate-risk patients who have relative or absolute contraindications for exercise or vasodilator stress testing. The publication of two large, prospective randomized clinical trials, the Prospective Multicenter Imaging Study for Evaluation of Chest Pain and the Scottish Computed Tomography of the Heart Trial are likely to expand these indications. These new data from large trials, in addition to other studies, show that CCTA is highly sensitive for the detection of CAD, identifies high-risk patients for cardiac events based on extent or plaque morphology of CAD that would not be identified by other noninvasive means, and provides significantly greater diagnostic certainty for proper treatment, including referral for invasive coronary angiography with revascularization more appropriately. Superior diagnostic accuracy and prognostic data with CCTA, when compared with other functional stress tests, may result in a reduction in unnecessary downstream testing and cost savings. In addition, newer CCTA applications hold the promise of providing a complete evaluation of a patient's coronary anatomy as well as a per-vessel ischemic evaluation. This review focuses on the interval knowledge obtained from newer data on CCTA in patients with stable ischemic heart disease, primarily focusing on the contributions of the Prospective Multicenter Imaging Study for Evaluation of Chest Pain and the Scottish Computed Tomography of the Heart Trial. PMID:27043808

  14. Accurate airway segmentation based on intensity structure analysis and graph-cut

    NASA Astrophysics Data System (ADS)

    Meng, Qier; Kitsaka, Takayuki; Nimura, Yukitaka; Oda, Masahiro; Mori, Kensaku

    2016-03-01

    This paper presents a novel airway segmentation method based on intensity structure analysis and graph-cut. Airway segmentation is an important step in analyzing chest CT volumes for computerized lung cancer detection, emphysema diagnosis, asthma diagnosis, and pre- and intra-operative bronchoscope navigation. However, obtaining a complete 3-D airway tree structure from a CT volume is quite challenging. Several researchers have proposed automated algorithms basically based on region growing and machine learning techniques. However these methods failed to detect the peripheral bronchi branches. They caused a large amount of leakage. This paper presents a novel approach that permits more accurate extraction of complex bronchial airway region. Our method are composed of three steps. First, the Hessian analysis is utilized for enhancing the line-like structure in CT volumes, then a multiscale cavity-enhancement filter is employed to detect the cavity-like structure from the previous enhanced result. In the second step, we utilize the support vector machine (SVM) to construct a classifier for removing the FP regions generated. Finally, the graph-cut algorithm is utilized to connect all of the candidate voxels to form an integrated airway tree. We applied this method to sixteen cases of 3D chest CT volumes. The results showed that the branch detection rate of this method can reach about 77.7% without leaking into the lung parenchyma areas.

  15. Accurate optical CD profiler based on specialized finite element method

    NASA Astrophysics Data System (ADS)

    Carrero, Jesus; Perçin, Gökhan

    2012-03-01

    As the semiconductor industry is moving to very low-k1 patterning solutions, the metrology problems facing process engineers are becoming much more complex. Choosing the right optical critical dimension (OCD) metrology technique is essential for bridging the metrology gap and achieving the required manufacturing volume throughput. The critical dimension scanning electron microscope (CD-SEM) measurement is usually distorted by the high aspect ratio of the photoresist and hard mask layers. CD-SEM measurements cease to correlate with complex three-dimensional profiles, such as the cases for double patterning and FinFETs, thus necessitating sophisticated, accurate and fast computational methods to bridge the gap. In this work, a suite of computational methods that complement advanced OCD equipment, and enabling them to operate at higher accuracies, are developed. In this article, a novel method for accurately modeling OCD profiles is presented. A finite element formulation in primal form is used to discretize the equations. The implementation uses specialized finite element spaces to solve Maxwell equations in two dimensions.

  16. FDSAC-SPICE: fault diagnosis software for analog circuit based on SPICE simulation

    NASA Astrophysics Data System (ADS)

    Cao, Yiqin; Cen, Zhao-Hui; Wei, Jiao-Long

    2009-12-01

    This paper presents a novel fault diagnosis software (called FDSAC-SPICE) based on SPICE simulator for analog circuits. Four important techniques in AFDS-SPICE, including visual user-interface(VUI), component modeling and fault modeling (CMFM), fault injection and fault simulation (FIFS), fault dictionary and fault diagnosis (FDFD), greatly increase design-for-test and diagnosis efficiency of analog circuit by building a fault modeling-injection-simulationdiagnosis environment to get prior fault knowledge of target circuit. AFDS-SPICE also generates accurate fault coverage statistics that are tied to the circuit specifications. With employing a dictionary diagnosis method based on node-signalcharacters and regular BPNN algorithm, more accurate and effective diagnosis results are available for analog circuit with tolerance.

  17. Accurate Anisotropic Fast Marching for Diffusion-Based Geodesic Tractography

    PubMed Central

    Jbabdi, S.; Bellec, P.; Toro, R.; Daunizeau, J.; Pélégrini-Issac, M.; Benali, H.

    2008-01-01

    Using geodesics for inferring white matter fibre tracts from diffusion-weighted MR data is an attractive method for at least two reasons: (i) the method optimises a global criterion, and hence is less sensitive to local perturbations such as noise or partial volume effects, and (ii) the method is fast, allowing to infer on a large number of connexions in a reasonable computational time. Here, we propose an improved fast marching algorithm to infer on geodesic paths. Specifically, this procedure is designed to achieve accurate front propagation in an anisotropic elliptic medium, such as DTI data. We evaluate the numerical performance of this approach on simulated datasets, as well as its robustness to local perturbation induced by fiber crossing. On real data, we demonstrate the feasibility of extracting geodesics to connect an extended set of brain regions. PMID:18299703

  18. An Accurate Projector Calibration Method Based on Polynomial Distortion Representation

    PubMed Central

    Liu, Miao; Sun, Changku; Huang, Shujun; Zhang, Zonghua

    2015-01-01

    In structure light measurement systems or 3D printing systems, the errors caused by optical distortion of a digital projector always affect the precision performance and cannot be ignored. Existing methods to calibrate the projection distortion rely on calibration plate and photogrammetry, so the calibration performance is largely affected by the quality of the plate and the imaging system. This paper proposes a new projector calibration approach that makes use of photodiodes to directly detect the light emitted from a digital projector. By analyzing the output sequence of the photoelectric module, the pixel coordinates can be accurately obtained by the curve fitting method. A polynomial distortion representation is employed to reduce the residuals of the traditional distortion representation model. Experimental results and performance evaluation show that the proposed calibration method is able to avoid most of the disadvantages in traditional methods and achieves a higher accuracy. This proposed method is also practically applicable to evaluate the geometric optical performance of other optical projection system. PMID:26492247

  19. A PC based fault diagnosis expert system

    NASA Technical Reports Server (NTRS)

    Marsh, Christopher A.

    1990-01-01

    The Integrated Status Assessment (ISA) prototype expert system performs system level fault diagnosis using rules and models created by the user. The ISA evolved from concepts to a stand-alone demonstration prototype using OPS5 on a LISP Machine. The LISP based prototype was rewritten in C and the C Language Integrated Production System (CLIPS) to run on a Personal Computer (PC) and a graphics workstation. The ISA prototype has been used to demonstrate fault diagnosis functions of Space Station Freedom's Operation Management System (OMS). This paper describes the development of the ISA prototype from early concepts to the current PC/workstation version used today and describes future areas of development for the prototype.

  20. Towards accurate porosity descriptors based on guest-host interactions.

    PubMed

    Paik, Dooam; Haranczyk, Maciej; Kim, Jihan

    2016-05-01

    For nanoporous materials at the characterization level, geometry-based approaches have become the methods of choice to provide information, often encoded in numerical descriptors, about the pores and the channels of a porous material. Examples of most common descriptors of the latter are pore limiting diameters, accessible surface area and accessible volume. The geometry-based methods exploit hard-sphere approximation for atoms, which (1) reduces costly computations of the interatomic interactions between the probe guest molecule and the porous material framework atoms, (2) effectively exploit applied mathematics methods such as Voronoi decomposition to represent and characterize porosity. In this work, we revisit and quantify the shortcoming of the geometry-based approaches. To do so, we have developed a series of algorithms to calculate pore descriptors such as void fraction, accessible surface area, pore limiting diameters (largest included sphere, and largest free sphere) based on a classical force field model of interactions between the guest and the framework atoms. Our resulting energy-based methods are tested on diverse sets of metal-organic frameworks and zeolite structures and comparisons against results obtained from geometric-based method indicate deviations in the cases for structures with small pore sizes. The method provides both high accuracy and performance making it suitable when screening a large database of materials. PMID:27054971

  1. An accurate clone-based haplotyping method by overlapping pool sequencing.

    PubMed

    Li, Cheng; Cao, Changchang; Tu, Jing; Sun, Xiao

    2016-07-01

    Chromosome-long haplotyping of human genomes is important to identify genetic variants with differing gene expression, in human evolution studies, clinical diagnosis, and other biological and medical fields. Although several methods have realized haplotyping based on sequencing technologies or population statistics, accuracy and cost are factors that prohibit their wide use. Borrowing ideas from group testing theories, we proposed a clone-based haplotyping method by overlapping pool sequencing. The clones from a single individual were pooled combinatorially and then sequenced. According to the distinct pooling pattern for each clone in the overlapping pool sequencing, alleles for the recovered variants could be assigned to their original clones precisely. Subsequently, the clone sequences could be reconstructed by linking these alleles accordingly and assembling them into haplotypes with high accuracy. To verify the utility of our method, we constructed 130 110 clones in silico for the individual NA12878 and simulated the pooling and sequencing process. Ultimately, 99.9% of variants on chromosome 1 that were covered by clones from both parental chromosomes were recovered correctly, and 112 haplotype contigs were assembled with an N50 length of 3.4 Mb and no switch errors. A comparison with current clone-based haplotyping methods indicated our method was more accurate. PMID:27095193

  2. An accurate clone-based haplotyping method by overlapping pool sequencing

    PubMed Central

    Li, Cheng; Cao, Changchang; Tu, Jing; Sun, Xiao

    2016-01-01

    Chromosome-long haplotyping of human genomes is important to identify genetic variants with differing gene expression, in human evolution studies, clinical diagnosis, and other biological and medical fields. Although several methods have realized haplotyping based on sequencing technologies or population statistics, accuracy and cost are factors that prohibit their wide use. Borrowing ideas from group testing theories, we proposed a clone-based haplotyping method by overlapping pool sequencing. The clones from a single individual were pooled combinatorially and then sequenced. According to the distinct pooling pattern for each clone in the overlapping pool sequencing, alleles for the recovered variants could be assigned to their original clones precisely. Subsequently, the clone sequences could be reconstructed by linking these alleles accordingly and assembling them into haplotypes with high accuracy. To verify the utility of our method, we constructed 130 110 clones in silico for the individual NA12878 and simulated the pooling and sequencing process. Ultimately, 99.9% of variants on chromosome 1 that were covered by clones from both parental chromosomes were recovered correctly, and 112 haplotype contigs were assembled with an N50 length of 3.4 Mb and no switch errors. A comparison with current clone-based haplotyping methods indicated our method was more accurate. PMID:27095193

  3. An Accurate Scalable Template-based Alignment Algorithm.

    PubMed

    Gardner, David P; Xu, Weijia; Miranker, Daniel P; Ozer, Stuart; Cannone, Jamie J; Gutell, Robin R

    2012-12-31

    The rapid determination of nucleic acid sequences is increasing the number of sequences that are available. Inherent in a template or seed alignment is the culmination of structural and functional constraints that are selecting those mutations that are viable during the evolution of the RNA. While we might not understand these structural and functional, template-based alignment programs utilize the patterns of sequence conservation to encapsulate the characteristics of viable RNA sequences that are aligned properly. We have developed a program that utilizes the different dimensions of information in rCAD, a large RNA informatics resource, to establish a profile for each position in an alignment. The most significant include sequence identity and column composition in different phylogenetic taxa. We have compared our methods with a maximum of eight alternative alignment methods on different sets of 16S and 23S rRNA sequences with sequence percent identities ranging from 50% to 100%. The results showed that CRWAlign outperformed the other alignment methods in both speed and accuracy. A web-based alignment server is available at http://www.rna.ccbb.utexas.edu/SAE/2F/CRWAlign. PMID:24772376

  4. Accurate tempo estimation based on harmonic + noise decomposition

    NASA Astrophysics Data System (ADS)

    Alonso, Miguel; Richard, Gael; David, Bertrand

    2006-12-01

    We present an innovative tempo estimation system that processes acoustic audio signals and does not use any high-level musical knowledge. Our proposal relies on a harmonic + noise decomposition of the audio signal by means of a subspace analysis method. Then, a technique to measure the degree of musical accentuation as a function of time is developed and separately applied to the harmonic and noise parts of the input signal. This is followed by a periodicity estimation block that calculates the salience of musical accents for a large number of potential periods. Next, a multipath dynamic programming searches among all the potential periodicities for the most consistent prospects through time, and finally the most energetic candidate is selected as tempo. Our proposal is validated using a manually annotated test-base containing 961 music signals from various musical genres. In addition, the performance of the algorithm under different configurations is compared. The robustness of the algorithm when processing signals of degraded quality is also measured.

  5. Knowledge-based fault diagnosis system for refuse collection vehicle

    NASA Astrophysics Data System (ADS)

    Tan, CheeFai; Juffrizal, K.; Khalil, S. N.; Nidzamuddin, M. Y.

    2015-05-01

    The refuse collection vehicle is manufactured by local vehicle body manufacturer. Currently; the company supplied six model of the waste compactor truck to the local authority as well as waste management company. The company is facing difficulty to acquire the knowledge from the expert when the expert is absence. To solve the problem, the knowledge from the expert can be stored in the expert system. The expert system is able to provide necessary support to the company when the expert is not available. The implementation of the process and tool is able to be standardize and more accurate. The knowledge that input to the expert system is based on design guidelines and experience from the expert. This project highlighted another application on knowledge-based system (KBS) approached in trouble shooting of the refuse collection vehicle production process. The main aim of the research is to develop a novel expert fault diagnosis system framework for the refuse collection vehicle.

  6. Knowledge-based fault diagnosis system for refuse collection vehicle

    SciTech Connect

    Tan, CheeFai; Juffrizal, K.; Khalil, S. N.; Nidzamuddin, M. Y.

    2015-05-15

    The refuse collection vehicle is manufactured by local vehicle body manufacturer. Currently; the company supplied six model of the waste compactor truck to the local authority as well as waste management company. The company is facing difficulty to acquire the knowledge from the expert when the expert is absence. To solve the problem, the knowledge from the expert can be stored in the expert system. The expert system is able to provide necessary support to the company when the expert is not available. The implementation of the process and tool is able to be standardize and more accurate. The knowledge that input to the expert system is based on design guidelines and experience from the expert. This project highlighted another application on knowledge-based system (KBS) approached in trouble shooting of the refuse collection vehicle production process. The main aim of the research is to develop a novel expert fault diagnosis system framework for the refuse collection vehicle.

  7. Mutation-based prenatal diagnosis of Herlitz junctional epidermolysis bullosa.

    PubMed

    Christiano, A M; Pulkkinen, L; McGrath, J A; Uitto, J

    1997-04-01

    Epidermolysis bullosa (EB) is a group of heritable diseases which manifest with blistering and erosions of the skin and mucous membranes. Due of life-threatening complications and significant long-term morbidity associated with the severe, neonatal lethal (Herlitz) form of junctional EB (H-JEB), there has been a demand for prenatal diagnosis from families at risk for recurrence. Previously, the only reliable method of prenatal diagnosis of EB was a fetal skin biopsy performed at 16-20 weeks' gestation and analysed by electron microscopy. Recently, the genes LAMA3, LAMB3, and LAMC2, encoding the polypeptide subunits of laminin 5, an anchoring filament protein, have been shown to contain mutations in H-JEB. In this study, direct detection of pathogenetic mutations in the laminin 5 genes was used to perform polymerase chain reaction (PCR)-based prenatal testing. DNA was obtained by chorionic villus sampling (CVS) at 10-15 weeks or amniocentesis at 12-19 weeks' gestation in 15 families at risk for recurrence of JEB. In 13 cases, the fetus was predicted to be either genetically normal or a clinically unaffected carrier of a mutation in one allele. These predictions have been validated in all cases by the birth of a healthy child. In two cases, an affected fetus was predicted, and the diagnosis was confirmed by subsequent fetal skin biopsy. These results demonstrate that DNA-based prenatal testing offers an early, expedient, and accurate method of prenatal diagnosis or an exclusion of Herlitz JEB. PMID:9160387

  8. DNA-based diagnosis of lymphatic filariasis.

    PubMed

    Nuchprayoon, Surang

    2009-09-01

    Lymphatic filariasis (LF) is still a major public health problem. The disease is ranked by the World Health Organization (WHO) as the second leading cause of permanent and long-term disability, and has been targeted for elimination by 2020. Effective diagnosis LF is required for treatment of infected individuals, for epidemiological assessment and for monitoring of the control program. Conventional diagnosis of LF depends on detection of microfilariae (Mf) in blood specimens, which has low sensitivity and specificity. Detection of specific circulating filarial antigens is regarded by WHO as the 'gold standard' for diagnosis of LF. However, the limitations of the antigen tests are cost and inconsistent availability. Although anti-filarial IgG4 antibody levels are associated with active LF infections, however, cross-reactivity with other filarial parasites is common. Not as sensitive as antigen tests, DNA-based techniques have been developed to diagnose and differentiate filarial parasites in humans, animal reservoir hosts, and mosquito vectors. These include DNA hybridization, polymerase chain reaction (PCR) amplification using specific primers (eg Ssp I repeat, pWb12 repeat, pWb-35 repeat, and LDR repeat for Wuchereria bancrofti and Hha I repeat, glutathione peroxidase gene, mitochondrial DNA for Brugia malayi), and universal primers, multiplex-PCR, PCR-restriction fragment length polymorphism (PCR-RFLP), PCR-enzyme linked immunosorbent assay (PCR-ELISA), as well as quantitative PCR. Furthermore, because bancroftian filariasis is endemic on the Thai-Myanmar border, the potential now exists for a re-emergence of bancroftian filariasis in Thailand, and random amplified polymorphic DNA (RAPD) analysis has proved effective to differentiate Thai and Myanmar strains of W. bancrofti. PMID:19842372

  9. Using In-Service and Coaching to Increase Teachers' Accurate Use of Research-Based Strategies

    ERIC Educational Resources Information Center

    Kretlow, Allison G.; Cooke, Nancy L.; Wood, Charles L.

    2012-01-01

    Increasing the accurate use of research-based practices in classrooms is a critical issue. Professional development is one of the most practical ways to provide practicing teachers with training related to research-based practices. This study examined the effects of in-service plus follow-up coaching on first grade teachers' accurate delivery of…

  10. Diagnosis of Dengue Infection Using Conventional and Biosensor Based Techniques.

    PubMed

    Parkash, Om; Shueb, Rafidah Hanim

    2015-10-01

    Dengue is an arthropod-borne viral disease caused by four antigenically different serotypes of dengue virus. This disease is considered as a major public health concern around the world. Currently, there is no licensed vaccine or antiviral drug available for the prevention and treatment of dengue disease. Moreover, clinical features of dengue are indistinguishable from other infectious diseases such as malaria, chikungunya, rickettsia and leptospira. Therefore, prompt and accurate laboratory diagnostic test is urgently required for disease confirmation and patient triage. The traditional diagnostic techniques for the dengue virus are viral detection in cell culture, serological testing, and RNA amplification using reverse transcriptase PCR. This paper discusses the conventional laboratory methods used for the diagnosis of dengue during the acute and convalescent phase and highlights the advantages and limitations of these routine laboratory tests. Subsequently, the biosensor based assays developed using various transducers for the detection of dengue are also reviewed. PMID:26492265

  11. Diagnosis of Dengue Infection Using Conventional and Biosensor Based Techniques

    PubMed Central

    Parkash, Om; Hanim Shueb, Rafidah

    2015-01-01

    Dengue is an arthropod-borne viral disease caused by four antigenically different serotypes of dengue virus. This disease is considered as a major public health concern around the world. Currently, there is no licensed vaccine or antiviral drug available for the prevention and treatment of dengue disease. Moreover, clinical features of dengue are indistinguishable from other infectious diseases such as malaria, chikungunya, rickettsia and leptospira. Therefore, prompt and accurate laboratory diagnostic test is urgently required for disease confirmation and patient triage. The traditional diagnostic techniques for the dengue virus are viral detection in cell culture, serological testing, and RNA amplification using reverse transcriptase PCR. This paper discusses the conventional laboratory methods used for the diagnosis of dengue during the acute and convalescent phase and highlights the advantages and limitations of these routine laboratory tests. Subsequently, the biosensor based assays developed using various transducers for the detection of dengue are also reviewed. PMID:26492265

  12. Wireless laptop-based phonocardiograph and diagnosis

    PubMed Central

    2015-01-01

    Auscultation is used to evaluate heart health, and can indicate when it’s needed to refer a patient to a cardiologist. Advanced phonocardiograph (PCG) signal processing algorithms are developed to assist the physician in the initial diagnosis but they are primarily designed and demonstrated with research quality equipment. Therefore, there is a need to demonstrate the applicability of those techniques with consumer grade instrument. Furthermore, routine monitoring would benefit from a wireless PCG sensor that allows continuous monitoring of cardiac signals of patients in physical activity, e.g., treadmill or weight exercise. In this work, a low-cost portable and wireless healthcare monitoring system based on PCG signal is implemented to validate and evaluate the most advanced algorithms. Off-the-shelf electronics and a notebook PC are used with MATLAB codes to record and analyze PCG signals which are collected with a notebook computer in tethered and wireless mode. Physiological parameters based on the S1 and S2 signals and MATLAB codes are demonstrated. While the prototype is based on MATLAB, the later is not an absolute requirement. PMID:26339555

  13. Fault diagnosis based on continuous simulation models

    NASA Technical Reports Server (NTRS)

    Feyock, Stefan

    1987-01-01

    The results are described of an investigation of techniques for using continuous simulation models as basis for reasoning about physical systems, with emphasis on the diagnosis of system faults. It is assumed that a continuous simulation model of the properly operating system is available. Malfunctions are diagnosed by posing the question: how can we make the model behave like that. The adjustments that must be made to the model to produce the observed behavior usually provide definitive clues to the nature of the malfunction. A novel application of Dijkstra's weakest precondition predicate transformer is used to derive the preconditions for producing the required model behavior. To minimize the size of the search space, an envisionment generator based on interval mathematics was developed. In addition to its intended application, the ability to generate qualitative state spaces automatically from quantitative simulations proved to be a fruitful avenue of investigation in its own right. Implementations of the Dijkstra transform and the envisionment generator are reproduced in the Appendix.

  14. Accurate TOA-Based UWB Localization System in Coal Mine Based on WSN

    NASA Astrophysics Data System (ADS)

    Cheng, Guangliang

    Over the last years, there has been a great deal of interest in Ultra Wideband (UWB) wireless communication and Wireless Sensor Networks(WSN), especially following the proposing of the internet of things by the MIT (Massachusetts Institute of Technology) in 1999, hich is also result in an increasing research on UWB and WSN applications. This article mainly introduced the accurate UWB Localization System based on WSN in coal mine. Firstly, we briefly introduced UWB and WSN Localization technology. Secondly, the advantages and disadvantages of the previous personnel localization technology in coal mine was analyzed and contrasted, and then the suitable personnel localization system in coal mine based on UWB signal and TOA estimate positioning scheme are presented. At last the rationality and feasibility of this scheme was proved through the simulation results.

  15. A mathematical framework for combining decisions of multiple experts toward accurate and remote diagnosis of malaria using tele-microscopy.

    PubMed

    Mavandadi, Sam; Feng, Steve; Yu, Frank; Dimitrov, Stoyan; Nielsen-Saines, Karin; Prescott, William R; Ozcan, Aydogan

    2012-01-01

    We propose a methodology for digitally fusing diagnostic decisions made by multiple medical experts in order to improve accuracy of diagnosis. Toward this goal, we report an experimental study involving nine experts, where each one was given more than 8,000 digital microscopic images of individual human red blood cells and asked to identify malaria infected cells. The results of this experiment reveal that even highly trained medical experts are not always self-consistent in their diagnostic decisions and that there exists a fair level of disagreement among experts, even for binary decisions (i.e., infected vs. uninfected). To tackle this general medical diagnosis problem, we propose a probabilistic algorithm to fuse the decisions made by trained medical experts to robustly achieve higher levels of accuracy when compared to individual experts making such decisions. By modelling the decisions of experts as a three component mixture model and solving for the underlying parameters using the Expectation Maximisation algorithm, we demonstrate the efficacy of our approach which significantly improves the overall diagnostic accuracy of malaria infected cells. Additionally, we present a mathematical framework for performing 'slide-level' diagnosis by using individual 'cell-level' diagnosis data, shedding more light on the statistical rules that should govern the routine practice in examination of e.g., thin blood smear samples. This framework could be generalized for various other tele-pathology needs, and can be used by trained experts within an efficient tele-medicine platform. PMID:23071544

  16. A Mathematical Framework for Combining Decisions of Multiple Experts toward Accurate and Remote Diagnosis of Malaria Using Tele-Microscopy

    PubMed Central

    Mavandadi, Sam; Dimitrov, Stoyan; Nielsen-Saines, Karin; Prescott, William R.; Ozcan, Aydogan

    2012-01-01

    We propose a methodology for digitally fusing diagnostic decisions made by multiple medical experts in order to improve accuracy of diagnosis. Toward this goal, we report an experimental study involving nine experts, where each one was given more than 8,000 digital microscopic images of individual human red blood cells and asked to identify malaria infected cells. The results of this experiment reveal that even highly trained medical experts are not always self-consistent in their diagnostic decisions and that there exists a fair level of disagreement among experts, even for binary decisions (i.e., infected vs. uninfected). To tackle this general medical diagnosis problem, we propose a probabilistic algorithm to fuse the decisions made by trained medical experts to robustly achieve higher levels of accuracy when compared to individual experts making such decisions. By modelling the decisions of experts as a three component mixture model and solving for the underlying parameters using the Expectation Maximisation algorithm, we demonstrate the efficacy of our approach which significantly improves the overall diagnostic accuracy of malaria infected cells. Additionally, we present a mathematical framework for performing ‘slide-level’ diagnosis by using individual ‘cell-level’ diagnosis data, shedding more light on the statistical rules that should govern the routine practice in examination of e.g., thin blood smear samples. This framework could be generalized for various other tele-pathology needs, and can be used by trained experts within an efficient tele-medicine platform. PMID:23071544

  17. The status of and future research into Myalgic Encephalomyelitis and Chronic Fatigue Syndrome: the need of accurate diagnosis, objective assessment, and acknowledging biological and clinical subgroups

    PubMed Central

    Twisk, Frank N. M.

    2014-01-01

    Although Myalgic Encephalomyelitis (ME) and Chronic Fatigue Syndrome (CFS) are used interchangeably, the diagnostic criteria define two distinct clinical entities. Cognitive impairment, (muscle) weakness, circulatory disturbances, marked variability of symptoms, and, above all, post-exertional malaise: a long-lasting increase of symptoms after a minor exertion, are distinctive symptoms of ME. This latter phenomenon separates ME, a neuro-immune illness, from chronic fatigue (syndrome), other disorders and deconditioning. The introduction of the label, but more importantly the diagnostic criteria for CFS have generated much confusion, mostly because chronic fatigue is a subjective and ambiguous notion. CFS was redefined in 1994 into unexplained (persistent or relapsing) chronic fatigue, accompanied by at least four out of eight symptoms, e.g., headaches and unrefreshing sleep. Most of the research into ME and/or CFS in the last decades was based upon the multivalent CFS criteria, which define a heterogeneous patient group. Due to the fact that fatigue and other symptoms are non-discriminative, subjective experiences, research has been hampered. Various authors have questioned the physiological nature of the symptoms and qualified ME/CFS as somatization. However, various typical symptoms can be assessed objectively using standardized methods. Despite subjective and unclear criteria and measures, research has observed specific abnormalities in ME/CFS repetitively, e.g., immunological abnormalities, oxidative and nitrosative stress, neurological anomalies, circulatory deficits and mitochondrial dysfunction. However, to improve future research standards and patient care, it is crucial that patients with post-exertional malaise (ME) and patients without this odd phenomenon are acknowledged as separate clinical entities that the diagnosis of ME and CFS in research and clinical practice is based upon accurate criteria and an objective assessment of characteristic symptoms

  18. Polyallelic structural variants can provide accurate, highly informative genetic markers focused on diagnosis and therapeutic targets: Accuracy vs. Precision.

    PubMed

    Roses, A D

    2016-02-01

    Structural variants (SVs) include all insertions, deletions, and rearrangements in the genome, with several common types of nucleotide repeats including single sequence repeats, short tandem repeats, and insertion-deletion length variants. Polyallelic SVs provide highly informative markers for association studies with well-phenotyped cohorts. SVs can influence gene regulation by affecting epigenetics, transcription, splicing, and/or translation. Accurate assays of polyallelic SV loci are required to define the range and allele frequency of variable length alleles. PMID:26517180

  19. Surgical biopsy with intra-operative frozen section. An accurate and cost-effective method for diagnosis of musculoskeletal sarcomas.

    PubMed

    Ashford, R U; McCarthy, S W; Scolyer, R A; Bonar, S F; Karim, R Z; Stalley, P D

    2006-09-01

    The most appropriate protocol for the biopsy of musculoskeletal tumours is controversial, with some authors advocating CT-guided core biopsy. At our hospital the initial biopsies of most musculoskeletal tumours has been by operative core biopsy with evaluation by frozen section which determines whether diagnostic tissue has been obtained and, if possible, gives the definitive diagnosis. In order to determine the accuracy and cost-effectiveness of this protocol we have undertaken a retrospective audit of biopsies of musculoskeletal tumours performed over a period of two years. A total of 104 patients had biopsies according to this regime. All gave the diagnosis apart from one minor error which did not alter the management of the patient. There was no requirement for re-biopsy. This protocol was more labour-intensive and 38% more costly than CT-guided core biopsy (AU$1804 vs AU$1308). However, the accuracy and avoidance of the anxiety associated with repeat biopsy outweighed these disadvantages. PMID:16943474

  20. An intelligent diagnosis model based on rough set theory

    NASA Astrophysics Data System (ADS)

    Li, Ze; Huang, Hong-Xing; Zheng, Ye-Lu; Wang, Zhou-Yuan

    2013-03-01

    Along with the popularity of computer and rapid development of information technology, how to increase the accuracy of the agricultural diagnosis becomes a difficult problem of popularizing the agricultural expert system. Analyzing existing research, baseing on the knowledge acquisition technology of rough set theory, towards great sample data, we put forward a intelligent diagnosis model. Extract rough set decision table from the samples property, use decision table to categorize the inference relation, acquire property rules related to inference diagnosis, through the means of rough set knowledge reasoning algorithm to realize intelligent diagnosis. Finally, we validate this diagnosis model by experiments. Introduce the rough set theory to provide the agricultural expert system of great sample data a effective diagnosis model.

  1. [Endocrine diagnosis in puberty--pathophysiologic bases].

    PubMed

    Girard, J

    1994-05-01

    Puberty is characterized by activation of the maturing gonads and by the thus started increased secretion of sexual steroids. Consequences are the appearance of secondary signs of puberty sensu strictori, i. e. the development of breasts in girls, the increase of testicle volume in boys, often followed by growing pubic hair, axillary hair, menarche or laryngeal growth (puberty vocal change) respectively. The most important accompanying symptom is the spurt of growth starting around 12 to 18 months after the onset of the development of the secondary pubertal signs. From the time sequence of the development and the possible delays, valuable diagnostic hints can be gained, giving rise to a more precise analysis of the hormonal phenomena of adolescence. In cases of pubertas tarda a primary malfunction must be differentiated from secondary hypogonadotropic functional defect. The syndromes should be classified correctly according to their etiology. The most frequent diagnosis is that of a simply delayed puberty. Acne, hypertrichosis, hirsutism are concomitant phenomena of puberty development which can indicate a hormonal imbalance (differential diagnosis AGS, ovarian hyperandrogeny). The swelling of breasts in boys (gynecomastia) is a common transitory phenomenon in male adolescence (DD, tumor of the gonads or Klinefelter syndrome). Interesting considerations of differential diagnosis apply also to the assessment of the enlargement of the thyroid gland in puberty, which affects more often girls than boys. PMID:8016754

  2. Simplified and optimized multispectral imaging for 5-ALA-based fluorescence diagnosis of malignant lesions.

    PubMed

    Minamikawa, Takeo; Matsuo, Hisataka; Kato, Yoshiyuki; Harada, Yoshinori; Otsuji, Eigo; Yanagisawa, Akio; Tanaka, Hideo; Takamatsu, Tetsuro

    2016-01-01

    5-aminolevulinic acid (5-ALA)-based fluorescence diagnosis is now clinically applied for accurate and ultrarapid diagnosis of malignant lesions such as lymph node metastasis during surgery. 5-ALA-based diagnosis evaluates fluorescence intensity of a fluorescent metabolite of 5-ALA, protoporphyrin IX (PPIX); however, the fluorescence of PPIX is often affected by autofluorescence of tissue chromophores, such as collagen and flavins. In this study, we demonstrated PPIX fluorescence estimation with autofluorescence elimination for 5-ALA-based fluorescence diagnosis of malignant lesions by simplified and optimized multispectral imaging. We computationally optimized observation wavelength regions for the estimation of PPIX fluorescence in terms of minimizing prediction error of PPIX fluorescence intensity in the presence of typical chromophores, collagen and flavins. By using the fluorescence intensities of the optimized wavelength regions, we verified quantitative detection of PPIX fluorescence by using chemical mixtures of PPIX, flavins, and collagen. Furthermore, we demonstrated detection capability by using metastatic and non-metastatic lymph nodes of colorectal cancer patients. These results suggest the potential and usefulness of the background-free estimation method of PPIX fluorescence for 5-ALA-based fluorescence diagnosis of malignant lesions, and we expect this method to be beneficial for intraoperative and rapid cancer diagnosis. PMID:27149301

  3. Simplified and optimized multispectral imaging for 5-ALA-based fluorescence diagnosis of malignant lesions

    PubMed Central

    Minamikawa, Takeo; Matsuo, Hisataka; Kato, Yoshiyuki; Harada, Yoshinori; Otsuji, Eigo; Yanagisawa, Akio; Tanaka, Hideo; Takamatsu, Tetsuro

    2016-01-01

    5-aminolevulinic acid (5-ALA)-based fluorescence diagnosis is now clinically applied for accurate and ultrarapid diagnosis of malignant lesions such as lymph node metastasis during surgery. 5-ALA-based diagnosis evaluates fluorescence intensity of a fluorescent metabolite of 5-ALA, protoporphyrin IX (PPIX); however, the fluorescence of PPIX is often affected by autofluorescence of tissue chromophores, such as collagen and flavins. In this study, we demonstrated PPIX fluorescence estimation with autofluorescence elimination for 5-ALA-based fluorescence diagnosis of malignant lesions by simplified and optimized multispectral imaging. We computationally optimized observation wavelength regions for the estimation of PPIX fluorescence in terms of minimizing prediction error of PPIX fluorescence intensity in the presence of typical chromophores, collagen and flavins. By using the fluorescence intensities of the optimized wavelength regions, we verified quantitative detection of PPIX fluorescence by using chemical mixtures of PPIX, flavins, and collagen. Furthermore, we demonstrated detection capability by using metastatic and non-metastatic lymph nodes of colorectal cancer patients. These results suggest the potential and usefulness of the background-free estimation method of PPIX fluorescence for 5-ALA-based fluorescence diagnosis of malignant lesions, and we expect this method to be beneficial for intraoperative and rapid cancer diagnosis. PMID:27149301

  4. Mass spectrometry-based protein identification with accurate statistical significance assignment

    PubMed Central

    Alves, Gelio; Yu, Yi-Kuo

    2015-01-01

    Motivation: Assigning statistical significance accurately has become increasingly important as metadata of many types, often assembled in hierarchies, are constructed and combined for further biological analyses. Statistical inaccuracy of metadata at any level may propagate to downstream analyses, undermining the validity of scientific conclusions thus drawn. From the perspective of mass spectrometry-based proteomics, even though accurate statistics for peptide identification can now be achieved, accurate protein level statistics remain challenging. Results: We have constructed a protein ID method that combines peptide evidences of a candidate protein based on a rigorous formula derived earlier; in this formula the database P-value of every peptide is weighted, prior to the final combination, according to the number of proteins it maps to. We have also shown that this protein ID method provides accurate protein level E-value, eliminating the need of using empirical post-processing methods for type-I error control. Using a known protein mixture, we find that this protein ID method, when combined with the Sorić formula, yields accurate values for the proportion of false discoveries. In terms of retrieval efficacy, the results from our method are comparable with other methods tested. Availability and implementation: The source code, implemented in C++ on a linux system, is available for download at ftp://ftp.ncbi.nlm.nih.gov/pub/qmbp/qmbp_ms/RAId/RAId_Linux_64Bit. Contact: yyu@ncbi.nlm.nih.gov Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25362092

  5. MONA: An accurate two-phase well flow model based on phase slippage

    SciTech Connect

    Asheim, H.

    1984-10-01

    In two phase flow, holdup and pressure loss are related to interfacial slippage. A model based on the slippage concept has been developed and tested using production well data from Forties, the Ekofisk area, and flowline data from Prudhoe Bay. The model developed turned out considerably more accurate than the standard models used for comparison.

  6. Recommendations for accurate CT diagnosis of suspected acute aortic syndrome (AAS)—on behalf of the British Society of Cardiovascular Imaging (BSCI)/British Society of Cardiovascular CT (BSCCT)

    PubMed Central

    Nicol, Edward; Morgan-Hughes, Gareth; Roobottom, Carl A; Roditi, Giles; Hamilton, Mark C K; Bull, Russell K; Pugliese, Franchesca; Williams, Michelle C; Stirrup, James; Padley, Simon; Taylor, Andrew; Davies, L Ceri; Bury, Roger; Harden, Stephen

    2016-01-01

    Accurate and timely assessment of suspected acute aortic syndrome is crucial in this life-threatening condition. Imaging with CT plays a central role in the diagnosis to allow expedited management. Diagnosis can be made using locally available expertise with optimized scanning parameters, making full use of recent advances in CT technology. Each imaging centre must optimize their protocols to allow accurate diagnosis, to optimize radiation dose and in particular to reduce the risk of false-positive diagnosis that may simulate disease. This document outlines the principles for the acquisition of motion-free imaging of the aorta in this context. PMID:26916280

  7. Recommendations for accurate CT diagnosis of suspected acute aortic syndrome (AAS)-on behalf of the British Society of Cardiovascular Imaging (BSCI)/British Society of Cardiovascular CT (BSCCT).

    PubMed

    Vardhanabhuti, Varut; Nicol, Edward; Morgan-Hughes, Gareth; Roobottom, Carl A; Roditi, Giles; Hamilton, Mark C K; Bull, Russell K; Pugliese, Franchesca; Williams, Michelle C; Stirrup, James; Padley, Simon; Taylor, Andrew; Davies, L Ceri; Bury, Roger; Harden, Stephen

    2016-05-01

    Accurate and timely assessment of suspected acute aortic syndrome is crucial in this life-threatening condition. Imaging with CT plays a central role in the diagnosis to allow expedited management. Diagnosis can be made using locally available expertise with optimized scanning parameters, making full use of recent advances in CT technology. Each imaging centre must optimize their protocols to allow accurate diagnosis, to optimize radiation dose and in particular to reduce the risk of false-positive diagnosis that may simulate disease. This document outlines the principles for the acquisition of motion-free imaging of the aorta in this context. PMID:26916280

  8. An Efficient Model-based Diagnosis Engine for Hybrid Systems Using Structural Model Decomposition

    NASA Technical Reports Server (NTRS)

    Bregon, Anibal; Narasimhan, Sriram; Roychoudhury, Indranil; Daigle, Matthew; Pulido, Belarmino

    2013-01-01

    Complex hybrid systems are present in a large range of engineering applications, like mechanical systems, electrical circuits, or embedded computation systems. The behavior of these systems is made up of continuous and discrete event dynamics that increase the difficulties for accurate and timely online fault diagnosis. The Hybrid Diagnosis Engine (HyDE) offers flexibility to the diagnosis application designer to choose the modeling paradigm and the reasoning algorithms. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. However, HyDE faces some problems regarding performance in terms of complexity and time. Our focus in this paper is on developing efficient model-based methodologies for online fault diagnosis in complex hybrid systems. To do this, we propose a diagnosis framework where structural model decomposition is integrated within the HyDE diagnosis framework to reduce the computational complexity associated with the fault diagnosis of hybrid systems. As a case study, we apply our approach to a diagnostic testbed, the Advanced Diagnostics and Prognostics Testbed (ADAPT), using real data.

  9. Fast and accurate circle detection using gradient-direction-based segmentation.

    PubMed

    Wu, Jianping; Chen, Ke; Gao, Xiaohui

    2013-06-01

    We present what is to our knowledge the first-ever fitting-based circle detection algorithm, namely, the fast and accurate circle (FACILE) detection algorithm, based on gradient-direction-based edge clustering and direct least square fitting. Edges are segmented into sections based on gradient directions, and each section is validated separately; valid arcs are then fitted and further merged to extract more accurate circle information. We implemented the algorithm with the C++ language and compared it with four other algorithms. Testing on simulated data showed FACILE was far superior to the randomized Hough transform, standard Hough transform, and fast circle detection using gradient pair vectors with regard to processing speed and detection reliability. Testing on publicly available standard datasets showed FACILE outperformed robust and precise circular detection, a state-of-art arc detection method, by 35% with regard to recognition rate and is also a significant improvement over the latter in processing speed. PMID:24323106

  10. Qualitative model-based diagnosis using possibility theory

    NASA Technical Reports Server (NTRS)

    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.

  11. Successful application of enzyme-labeled oligonucleotide probe for rapid and accurate cholera diagnosis in a clinical laboratory.

    PubMed

    Miyagi, K; Matsumoto, Y; Hayashi, K; Yoh, M; Yamamoto, K; Honda, T

    1994-01-01

    Two cholera cases were diagnosed using an enzyme-labeled oligonucleotide probe (ELONP) hybridization test for detection of cholera toxin gene (ctx) in a clinical laboratory at Osaka Airport Quarantine Station. The ELONP test with suspicious colonies of Vibrio cholerae O1 grown on TCBS or Vibrio agar plates gave positive result for ctx within 3 hr. We also tried to apply the ELONP test for direct detection of ctx in their stool and their non-selective culture. Specimens from Case #1, which contained 5.9 x 10(5) CFU/g of V. cholerae O1 in the stool, cultured for 7-8 hr or longer in alkaline peptone water or Marine broth at 37C, became positive for ctx. On the other hand, specimens from Case #2, which contained 8.7 x 10(8) CFU/ml (of V. cholerae O1 in the stool), gave positive result in this stool itself without any further culture. These data suggest that the ELONP test provides successfully a more rapid and accurate means of identifying "toxigenic" V. cholerae O1 in a clinical laboratory. PMID:7935049

  12. Secure Medical Diagnosis Using Rule Based Mining

    NASA Astrophysics Data System (ADS)

    Saleem Durai, M. A.; Sriman Narayana Iyengar, N. Ch.

    Security is the governing dynamics of all walks of life. Here we propose a secured medical diagnosis system. Certain specific rules are specified implicitly by the designer of the expert system and then symptoms for the diseases are obtained from the users and by using the pre defined confidence and support values we extract a threshold value which is used to conclude on a particular disease and the stage using Rule Mining. "THINK" CAPTCHA mechanism is used to distinguish between the human and the robots thereby eliminating the robots and preventing them from creating fake accounts and spam's. A novel image encryption mechanism is designed using genetic algorithm to encrypt the medical images thereby storing and sending the image data in a secured manner.

  13. Distributed Pedestrian Detection Alerts Based on Data Fusion with Accurate Localization

    PubMed Central

    García, Fernando; Jiménez, Felipe; Anaya, José Javier; Armingol, José María; Naranjo, José Eugenio; de la Escalera, Arturo

    2013-01-01

    Among Advanced Driver Assistance Systems (ADAS) pedestrian detection is a common issue due to the vulnerability of pedestrians in the event of accidents. In the present work, a novel approach for pedestrian detection based on data fusion is presented. Data fusion helps to overcome the limitations inherent to each detection system (computer vision and laser scanner) and provides accurate and trustable tracking of any pedestrian movement. The application is complemented by an efficient communication protocol, able to alert vehicles in the surroundings by a fast and reliable communication. The combination of a powerful location, based on a GPS with inertial measurement, and accurate obstacle localization based on data fusion has allowed locating the detected pedestrians with high accuracy. Tests proved the viability of the detection system and the efficiency of the communication, even at long distances. By the use of the alert communication, dangerous situations such as occlusions or misdetections can be avoided. PMID:24008284

  14. Distributed pedestrian detection alerts based on data fusion with accurate localization.

    PubMed

    García, Fernando; Jiménez, Felipe; Anaya, José Javier; Armingol, José María; Naranjo, José Eugenio; de la Escalera, Arturo

    2013-01-01

    Among Advanced Driver Assistance Systems (ADAS) pedestrian detection is a common issue due to the vulnerability of pedestrians in the event of accidents. In the present work, a novel approach for pedestrian detection based on data fusion is presented. Data fusion helps to overcome the limitations inherent to each detection system (computer vision and laser scanner) and provides accurate and trustable tracking of any pedestrian movement. The application is complemented by an efficient communication protocol, able to alert vehicles in the surroundings by a fast and reliable communication. The combination of a powerful location, based on a GPS with inertial measurement, and accurate obstacle localization based on data fusion has allowed locating the detected pedestrians with high accuracy. Tests proved the viability of the detection system and the efficiency of the communication, even at long distances. By the use of the alert communication, dangerous situations such as occlusions or misdetections can be avoided. PMID:24008284

  15. Can optical diagnosis of small colon polyps be accurate? Comparing standard scope without narrow banding to high definition scope with narrow banding

    PubMed Central

    Ashktorab, Hassan; Etaati, Firoozeh; Rezaeean, Farahnaz; Nouraie, Mehdi; Paydar, Mansour; Namin, Hassan Hassanzadeh; Sanderson, Andrew; Begum, Rehana; Alkhalloufi, Kawtar; Brim, Hassan; Laiyemo, Adeyinka O

    2016-01-01

    AIM: To study the accuracy of using high definition (HD) scope with narrow band imaging (NBI) vs standard white light colonoscope without NBI (ST), to predict the histology of the colon polyps, particularly those < 1 cm. METHODS: A total of 147 African Americans patients who were referred to Howard University Hospital for screening or, diagnostic or follow up colonoscopy, during a 12-mo period in 2012 were prospectively recruited. Some patients had multiple polyps and total number of polyps was 179. Their colonoscopies were performed by 3 experienced endoscopists who determined the size and stated whether the polyps being removed were hyperplastic or adenomatous polyps using standard colonoscopes or high definition colonoscopes with NBI. The histopathologic diagnosis was reported by pathologists as part of routine care. RESULTS: Of participants in the study, 55 (37%) were male and median (interquartile range) of age was 56 (19-80). Demographic, clinical characteristics, past medical history of patients, and the data obtained by two instruments were not significantly different and two methods detected similar number of polyps. In ST scope 89% of polyps were < 1 cm vs 87% in HD scope (P = 0.7). The ST scope had a positive predictive value (PPV) and positive likelihood ratio (PLR) of 86% and 4.0 for adenoma compared to 74% and 2.6 for HD scope. There was a trend of higher sensitivity for HD scope (68%) compare to ST scope (53%) with almost the same specificity. The ST scope had a PPV and PLR of 38% and 1.8 for hyperplastic polyp (HPP) compared to 42% and 2.2 for HD scope. The sensitivity and specificity of two instruments for HPP diagnosis were similar. CONCLUSION: Our results indicated that HD scope was more sensitive in diagnosis of adenoma than ST scope. Clinical diagnosis of HPP with either scope is less accurate compared to adenoma. Colonoscopy diagnosis is not yet fully matched with pathologic diagnosis of colon polyp. However with the advancement of both

  16. Phase-compensation-based dynamic time warping for fault diagnosis using the motor current signal

    NASA Astrophysics Data System (ADS)

    Zhen, D.; Zhao, H. L.; Gu, F.; Ball, A. D.

    2012-05-01

    Dynamic time warping (DTW) is a time-domain-based method and widely used in various similar recognition and data mining applications. This paper presents a phase-compensation-based DTW to process the motor current signals for detecting and quantifying various faults in a two-stage reciprocating compressor under different operating conditions. DTW is an effective method to align two signals for dissimilarity analysis. However, it has drawbacks such as singularities and high computational demands that limit its application in processing motor current signals for obtaining modulation characteristics accurately in diagnosing compressor faults. Therefore, a phase compensation approach is developed to reduce the singularity effect and a sliding window is designed to improve computing efficiency. Based on the proposed method, the motor current signals measured from the compressor induced with different common faults are analysed for fault diagnosis. Results show that residual signal analysis using the phase-compensation-based DTW allows the fault-related sideband features to be resolved more accurately for obtaining reliable fault detection and diagnosis. It provides an effective and easy approach to the analysis of motor current signals for better diagnosis in the time domain in comparison with conventional Fourier-transform-based methods.

  17. Prediction of Accurate Thermochemistry of Medium and Large Sized Radicals Using Connectivity-Based Hierarchy (CBH).

    PubMed

    Sengupta, Arkajyoti; Raghavachari, Krishnan

    2014-10-14

    Accurate modeling of the chemical reactions in many diverse areas such as combustion, photochemistry, or atmospheric chemistry strongly depends on the availability of thermochemical information of the radicals involved. However, accurate thermochemical investigations of radical systems using state of the art composite methods have mostly been restricted to the study of hydrocarbon radicals of modest size. In an alternative approach, systematic error-canceling thermochemical hierarchy of reaction schemes can be applied to yield accurate results for such systems. In this work, we have extended our connectivity-based hierarchy (CBH) method to the investigation of radical systems. We have calibrated our method using a test set of 30 medium sized radicals to evaluate their heats of formation. The CBH-rad30 test set contains radicals containing diverse functional groups as well as cyclic systems. We demonstrate that the sophisticated error-canceling isoatomic scheme (CBH-2) with modest levels of theory is adequate to provide heats of formation accurate to ∼1.5 kcal/mol. Finally, we predict heats of formation of 19 other large and medium sized radicals for which the accuracy of available heats of formation are less well-known. PMID:26588131

  18. Simple, fast and accurate eight points amplitude estimation method of sinusoidal signals for DSP based instrumentation

    NASA Astrophysics Data System (ADS)

    Vizireanu, D. N.; Halunga, S. V.

    2012-04-01

    A simple, fast and accurate amplitude estimation algorithm of sinusoidal signals for DSP based instrumentation is proposed. It is shown that eight samples, used in two steps, are sufficient. A practical analytical formula for amplitude estimation is obtained. Numerical results are presented. Simulations have been performed when the sampled signal is affected by white Gaussian noise and when the samples are quantized on a given number of bits.

  19. A Rapid, Fully Automated, Molecular-Based Assay Accurately Analyzes Sentinel Lymph Nodes for the Presence of Metastatic Breast Cancer

    PubMed Central

    Hughes, Steven J.; Xi, Liqiang; Raja, Siva; Gooding, William; Cole, David J.; Gillanders, William E.; Mikhitarian, Keidi; McCarty, Kenneth; Silver, Susan; Ching, Jesus; McMillan, William; Luketich, James D.; Godfrey, Tony E.

    2006-01-01

    Objective: To develop a fully automated, rapid, molecular-based assay that accurately and objectively evaluates sentinel lymph nodes (SLN) from breast cancer patients. Summary Background Data: Intraoperative analysis for the presence of metastatic cancer in SLNs from breast cancer patients lacks sensitivity. Even with immunohistochemical staining (IHC) and time-consuming review, alarming discordance in the interpretation of SLN has been observed. Methods: A total of 43 potential markers were evaluated for the ability to accurately characterize lymph node specimens from breast cancer patients as compared with complete histologic analysis including IHC. Selected markers then underwent external validation on 90 independent SLN specimens using rapid, multiplex quantitative reverse transcription-polymerase chain reaction (QRT-PCR) assays. Finally, 18 SLNs were analyzed using a completely automated RNA isolation, reverse transcription, and quantitative PCR instrument (GeneXpert). Results: Following analysis of potential markers, promising markers were evaluated to establish relative level of expression cutoff values that maximized classification accuracy. A validation set of 90 SLNs from breast cancer patients was prospectively characterized using 4 markers individually or in combinations, and the results compared with histologic analysis. A 2-marker assay was found to be 97.8% accurate (94% sensitive, 100% specific) compared with histologic analysis. The fully automated GeneXpert instrument produced comparable and reproducible results in less than 35 minutes. Conclusions: A rapid, fully automated QRT-PCR assay definitively characterizes breast cancer SLN with accuracy equal to conventional pathology. This approach is superior to intraoperative SLN analysis and can provide standardized, objective results to assist in pathologic diagnosis. PMID:16495705

  20. An interesting case of cryptogenic stroke in a young man due to left ventricular non-compaction: role of cardiac MRI in the accurate diagnosis

    PubMed Central

    Kannan, Arun; Das, Anindita; Janardhanan, Rajesh

    2014-01-01

    A 28-year-old man arrived for an outpatient cardiac MRI (CMR) study to evaluate cardiac structure. At the age of 24 the patient presented with acute onset expressive aphasia and was diagnosed with ischaemic stroke. Echocardiography at that time was reported as ‘apical wall thickening consistent with apical hypertrophic cardiomyopathy’. CMR revealed a moderately dilated left ventricle with abnormal appearance of the left ventricular (LV) apical segments. Further evaluation was consistent with a diagnosis of LV non­compaction (LVNC) cardiomyopathy with a ratio of non­compacted to compacted myocardium measuring 3. There was extensive delayed hyperenhancement signal involving multiple segments representing a significant myocardial scar which is shown to have a prognostic role. Our patient, with no significant cerebrovascular risk factors, would likely have had an embolic stroke. This case demonstrates the role of CMR in accurately diagnosing LVNC in a patient with young stroke where prior echocardiography was non­diagnostic. PMID:24962593

  1. Fully computed holographic stereogram based algorithm for computer-generated holograms with accurate depth cues.

    PubMed

    Zhang, Hao; Zhao, Yan; Cao, Liangcai; Jin, Guofan

    2015-02-23

    We propose an algorithm based on fully computed holographic stereogram for calculating full-parallax computer-generated holograms (CGHs) with accurate depth cues. The proposed method integrates point source algorithm and holographic stereogram based algorithm to reconstruct the three-dimensional (3D) scenes. Precise accommodation cue and occlusion effect can be created, and computer graphics rendering techniques can be employed in the CGH generation to enhance the image fidelity. Optical experiments have been performed using a spatial light modulator (SLM) and a fabricated high-resolution hologram, the results show that our proposed algorithm can perform quality reconstructions of 3D scenes with arbitrary depth information. PMID:25836429

  2. Accurate and efficient halo-based galaxy clustering modelling with simulations

    NASA Astrophysics Data System (ADS)

    Zheng, Zheng; Guo, Hong

    2016-06-01

    Small- and intermediate-scale galaxy clustering can be used to establish the galaxy-halo connection to study galaxy formation and evolution and to tighten constraints on cosmological parameters. With the increasing precision of galaxy clustering measurements from ongoing and forthcoming large galaxy surveys, accurate models are required to interpret the data and extract relevant information. We introduce a method based on high-resolution N-body simulations to accurately and efficiently model the galaxy two-point correlation functions (2PCFs) in projected and redshift spaces. The basic idea is to tabulate all information of haloes in the simulations necessary for computing the galaxy 2PCFs within the framework of halo occupation distribution or conditional luminosity function. It is equivalent to populating galaxies to dark matter haloes and using the mock 2PCF measurements as the model predictions. Besides the accurate 2PCF calculations, the method is also fast and therefore enables an efficient exploration of the parameter space. As an example of the method, we decompose the redshift-space galaxy 2PCF into different components based on the type of galaxy pairs and show the redshift-space distortion effect in each component. The generalizations and limitations of the method are discussed.

  3. Pattern-based fault diagnosis using neural networks

    NASA Technical Reports Server (NTRS)

    Dietz, W. E.; Kiech, E. L.; Ali, M.

    1988-01-01

    An architecture for a real-time pattern-based diagnostic expert system capable of accommodating noisy, incomplete, and possibly erroneous input data is outlined. Results from prototype systems applied to jet and rocket engine fault diagnosis are presented. The ability of a neural network-based system to be trained via the presentation of behavioral patterns associated with fault conditions is demonstrated.

  4. Robust High-Resolution Cloth Using Parallelism, History-Based Collisions and Accurate Friction

    PubMed Central

    Selle, Andrew; Su, Jonathan; Irving, Geoffrey; Fedkiw, Ronald

    2015-01-01

    In this paper we simulate high resolution cloth consisting of up to 2 million triangles which allows us to achieve highly detailed folds and wrinkles. Since the level of detail is also influenced by object collision and self collision, we propose a more accurate model for cloth-object friction. We also propose a robust history-based repulsion/collision framework where repulsions are treated accurately and efficiently on a per time step basis. Distributed memory parallelism is used for both time evolution and collisions and we specifically address Gauss-Seidel ordering of repulsion/collision response. This algorithm is demonstrated by several high-resolution and high-fidelity simulations. PMID:19147895

  5. Intestinal Intraepithelial Lymphocyte Cytometric Pattern Is More Accurate than Subepithelial Deposits of Anti-Tissue Transglutaminase IgA for the Diagnosis of Celiac Disease in Lymphocytic Enteritis

    PubMed Central

    García-Puig, Roger; Rosinach, Mercè; González, Clarisa; Alsina, Montserrat; Loras, Carme; Salas, Antonio; Viver, Josep M.; Esteve, Maria

    2014-01-01

    Background & Aims An increase in CD3+TCRγδ+ and a decrease in CD3− intraepithelial lymphocytes (IEL) is a characteristic flow cytometric pattern of celiac disease (CD) with atrophy. The aim was to evaluate the usefulness of both CD IEL cytometric pattern and anti-TG2 IgA subepithelial deposit analysis (CD IF pattern) for diagnosing lymphocytic enteritis due to CD. Methods Two-hundred and five patients (144 females) who underwent duodenal biopsy for clinical suspicion of CD and positive celiac genetics were prospectively included. Fifty had villous atrophy, 70 lymphocytic enteritis, and 85 normal histology. Eight patients with non-celiac atrophy and 15 with lymphocytic enteritis secondary to Helicobacter pylori acted as control group. Duodenal biopsies were obtained to assess both CD IEL flow cytometric (complete or incomplete) and IF patterns. Results Sensitivity of IF, and complete and incomplete cytometric patterns for CD diagnosis in patients with positive serology (Marsh 1+3) was 92%, 85 and 97% respectively, but only the complete cytometric pattern had 100% specificity. Twelve seropositive and 8 seronegative Marsh 1 patients had a CD diagnosis at inclusion or after gluten free-diet, respectively. CD cytometric pattern showed a better diagnostic performance than both IF pattern and serology for CD diagnosis in lymphocytic enteritis at baseline (95% vs 60% vs 60%, p = 0.039). Conclusions Analysis of the IEL flow cytometric pattern is a fast, accurate method for identifying CD in the initial diagnostic biopsy of patients presenting with lymphocytic enteritis, even in seronegative patients, and seems to be better than anti-TG2 intestinal deposits. PMID:25010214

  6. Epiretinal membrane: optical coherence tomography-based diagnosis and classification.

    PubMed

    Stevenson, William; Prospero Ponce, Claudia M; Agarwal, Daniel R; Gelman, Rachel; Christoforidis, John B

    2016-01-01

    Epiretinal membrane (ERM) is a disorder of the vitreomacular interface characterized by symptoms of decreased visual acuity and metamorphopsia. The diagnosis and classification of ERM has traditionally been based on clinical examination findings. However, modern optical coherence tomography (OCT) has proven to be more sensitive than clinical examination for the diagnosis of ERM. Furthermore, OCT-derived findings, such as central foveal thickness and inner segment ellipsoid band integrity, have shown clinical relevance in the setting of ERM. To date, no OCT-based ERM classification scheme has been widely accepted for use in clinical practice and investigation. Herein, we review the pathogenesis, diagnosis, and classification of ERMs and propose an OCT-based ERM classification system. PMID:27099458

  7. Epiretinal membrane: optical coherence tomography-based diagnosis and classification

    PubMed Central

    Stevenson, William; Prospero Ponce, Claudia M; Agarwal, Daniel R; Gelman, Rachel; Christoforidis, John B

    2016-01-01

    Epiretinal membrane (ERM) is a disorder of the vitreomacular interface characterized by symptoms of decreased visual acuity and metamorphopsia. The diagnosis and classification of ERM has traditionally been based on clinical examination findings. However, modern optical coherence tomography (OCT) has proven to be more sensitive than clinical examination for the diagnosis of ERM. Furthermore, OCT-derived findings, such as central foveal thickness and inner segment ellipsoid band integrity, have shown clinical relevance in the setting of ERM. To date, no OCT-based ERM classification scheme has been widely accepted for use in clinical practice and investigation. Herein, we review the pathogenesis, diagnosis, and classification of ERMs and propose an OCT-based ERM classification system. PMID:27099458

  8. An Evidential Approach To Model-Based Satellite Diagnosis

    NASA Astrophysics Data System (ADS)

    Bickmore, Timothy W.; Yoshimoto, Glenn M.

    1987-10-01

    Satellite diagnosis presents many unusual problems in the application of current knowledge-based diagnosis technology. The operation of satellite systems involves expertise that spans a large variety of systems, hardware, and software design areas. This expertise includes knowledge of design rationale and sensitivities, development history, test methods, test history, fault history and other indications of pedigree, and operational scenarios and environments. We have developed an approach to satellite diagnosis which can integrate evidence from a variety of diagnostic strategies encompassing this expertise. The system utilizes a structural and behavioral model of the satellite, and uses a form of spreading activation to perform the diagnostic procedures on the model. The various sources of diagnostic evidence are combined using a specially-tailored Dempster-Shafer based utility for modelling uncertainty. A prototype of a diagnostic system based on this approach has been implemented.

  9. Switched Fault Diagnosis Approach for Industrial Processes based on Hidden Markov Model

    NASA Astrophysics Data System (ADS)

    Wang, Lin; Yang, Chunjie; Sun, Youxian; Pan, Yijun; An, Ruqiao

    2015-11-01

    Traditional fault diagnosis methods based on hidden Markov model (HMM) use a unified method for feature extraction, such as principal component analysis (PCA), kernel principal component analysis (KPCA) and independent component analysis (ICA). However, every method has its own limitations. For example, PCA cannot extract nonlinear relationships among process variables. So it is inappropriate to extract all features of variables by only one method, especially when data characteristics are very complex. This article proposes a switched feature extraction procedure using PCA and KPCA based on nonlinearity measure. By the proposed method, we are able to choose the most suitable feature extraction method, which could improve the accuracy of fault diagnosis. A simulation from the Tennessee Eastman (TE) process demonstrates that the proposed approach is superior to the traditional one based on HMM and could achieve more accurate classification of various process faults.

  10. Histologic subtypes, immunohistochemistry, FISH or molecular screening for the accurate diagnosis of ALK-rearrangement in lung cancer: a comprehensive study of Caucasian non-smokers.

    PubMed

    Just, Pierre-Alexandre; Cazes, Aurélie; Audebourg, Anne; Cessot, Anatole; Pallier, Karine; Danel, Claire; Vacher-Lavenu, Marie-Cécile; Laurent-Puig, Pierre; Terris, Benoît; Blons, Hélène

    2012-06-01

    EML4-ALK adenocarcinomas constitute a new molecular subgroup of lung tumours that respond very well to crizotinib, an ALK inhibitor. However, the diagnosis of ALK rearrangement in lung cancer is challenging. The aim of this study was to compare the diagnostic accuracy of five different methods in a series of 20 EGFR(wt/wt) lung adenocarcinomas from non- or light- smokers. Multiplex RT-PCR was considered as gold standard and identified four ALK-rearranged tumours among the 20 tested tumours. qRT-PCR got an interpretability rate of 100% and accurately typed all 20 tumours. qRT-PCR from corresponding formalin-fixed paraffin-embedded (FFPE) specimens got an interpretability rate of 65%. Out of the four previously identified ALK-rearranged cases, three were interpretable and two were retrieved using FFPE qRT-PCR. ALK break-apart FISH got an interpretability rate of 60% and accurately typed all of the twelve remaining cases. Anti-ALK immunohistochemistry (IHC) accurately typed all twenty tumours using a cut-off value of strong staining of 100% tumour cells. The 16 non ALK-rearranged tumours got no/light staining in 13 cases, and a moderate staining of 80-100% tumour cells in 3 cases. We then analysed four solid signet-ring lung adenocarcinomas. FFPE qRT-PCR, FISH and immunohistochemistry were concordant in three cases, with positive and negative results in respectively one and two cases. The fourth case, which was positive by FISH and immunohistochemistry but negative by RT-PCR, was shown to have a non-EML4-ALK ALK-rearrangement. As various factors such as RNA quality, fixation quality and type of ALK rearrangement may impede ALK screening, we propose a combined FISH/molecular biology diagnostic algorithm in which anti-ALK immunohistochemistry is used as a pre-screening step. PMID:22153831

  11. HANDS2: accurate assignment of homoeallelic base-identity in allopolyploids despite missing data

    PubMed Central

    Khan, Amina; Belfield, Eric J.; Harberd, Nicholas P.; Mithani, Aziz

    2016-01-01

    Characterization of homoeallelic base-identity in allopolyploids is difficult since homeologous subgenomes are closely related and becomes further challenging if diploid-progenitor data is missing. We present HANDS2, a next-generation sequencing-based tool that enables highly accurate (>90%) genome-wide discovery of homeolog-specific base-identity in allopolyploids even in the absence of a diploid-progenitor. We applied HANDS2 to the transcriptomes of various cruciferous plants belonging to genus Brassica. Our results suggest that the three C genomes in Brassica are more similar to each other than the three A genomes, and provide important insights into the relationships between various Brassica tetraploids and their diploid-progenitors at a single-base resolution. PMID:27378447

  12. HANDS2: accurate assignment of homoeallelic base-identity in allopolyploids despite missing data.

    PubMed

    Khan, Amina; Belfield, Eric J; Harberd, Nicholas P; Mithani, Aziz

    2016-01-01

    Characterization of homoeallelic base-identity in allopolyploids is difficult since homeologous subgenomes are closely related and becomes further challenging if diploid-progenitor data is missing. We present HANDS2, a next-generation sequencing-based tool that enables highly accurate (>90%) genome-wide discovery of homeolog-specific base-identity in allopolyploids even in the absence of a diploid-progenitor. We applied HANDS2 to the transcriptomes of various cruciferous plants belonging to genus Brassica. Our results suggest that the three C genomes in Brassica are more similar to each other than the three A genomes, and provide important insights into the relationships between various Brassica tetraploids and their diploid-progenitors at a single-base resolution. PMID:27378447

  13. Benchmark data base for accurate van der Waals interaction in inorganic fragments

    NASA Astrophysics Data System (ADS)

    Brndiar, Jan; Stich, Ivan

    2012-02-01

    A range of inorganic materials, such as Sb, As, P, S, Se are built from van der Waals (vdW) interacting units forming the crystals, which neither the standard DFT GGA description as well as cheap quantum chemistry methods, such as MP2, do not describe correctly. We use this data base, for which have performed ultra accurate CCSD(T) calculations in complete basis set limit, to test the alternative approximate theories, such as Grimme [1], Langreth-Lundqvist [2], and Tkachenko-Scheffler [3]. While none of these theories gives entirely correct description, Grimme consistently provides more accurate results than Langreth-Lundqvist, which tend to overestimate the distances and underestimate the interaction energies for this set of systems. Contrary Tkachenko-Scheffler appear to yield surprisingly accurate and computationally cheap and convenient description applicable also for systems with appreciable charge transfer. [4pt] [1] S. Grimme, J. Comp. Chem. 27, 1787 (2006) [0pt] [2] K. Lee, et al., Phys. Rev. B 82 081101 (R) (2010) [0pt] [3] Tkachenko and M. Scheffler Phys. Rev. Lett. 102 073005 (2009).

  14. Chip-Based Sensors for Disease Diagnosis

    NASA Astrophysics Data System (ADS)

    Fang, Zhichao

    Nucleic acid analysis is one of the most important disease diagnostic approaches in medical practice, and has been commonly used in cancer biomarker detection, bacterial speciation and many other fields in laboratory. Currently, the application of powerful research methods for genetic analysis, including the polymerase chain reaction (PCR), DNA sequencing, and gene expression profiling using fluorescence microarrays, are not widely used in hospitals and extended-care units due to high-cost, long detection times, and extensive sample preparation. Bioassays, especially chip-based electrochemical sensors, may be suitable for the next generation of rapid, sensitive, and multiplexed detection tools. Herein, we report three different microelectrode platforms with capabilities enabled by nano- and microtechnology: nanoelectrode ensembles (NEEs), nanostructured microelectrodes (NMEs), and hierarchical nanostructured microelectrodes (HNMEs), all of which are able to directly detect unpurified RNA in clinical samples without enzymatic amplification. Biomarkers that are cancer and infectious disease relevant to clinical medicine were chosen to be the targets. Markers were successfully detected with clinically-relevant sensitivity. Using peptide nucleic acids (PNAs) as probes and an electrocatalytic reporter system, NEEs were able to detect prostate cancer-related gene fusions in tumor tissue samples with 100 ng of RNA. The development of NMEs improved the sensitivity of the assay further to 10 aM of DNA target, and multiplexed detection of RNA sequences of different prostate cancer-related gene fusion types was achieved on the chip-based NMEs platform. An HNMEs chip integrated with a bacterial lysis device was able to detect as few as 25 cfu bacteria in 30 minutes and monitor the detection in real time. Bacterial detection could also be performed in neat urine samples. The development of these versatile clinical diagnostic tools could be extended to the detection of various

  15. Main-Sequence Effective Temperatures from a Revised Mass-Luminosity Relation Based on Accurate Properties

    NASA Astrophysics Data System (ADS)

    Eker, Z.; Soydugan, F.; Soydugan, E.; Bilir, S.; Yaz Gökçe, E.; Steer, I.; Tüysüz, M.; Şenyüz, T.; Demircan, O.

    2015-04-01

    The mass-luminosity (M-L), mass-radius (M-R), and mass-effective temperature (M-{{T}eff}) diagrams for a subset of galactic nearby main-sequence stars with masses and radii accurate to ≤slant 3% and luminosities accurate to ≤slant 30% (268 stars) has led to a putative discovery. Four distinct mass domains have been identified, which we have tentatively associated with low, intermediate, high, and very high mass main-sequence stars, but which nevertheless are clearly separated by three distinct break points at 1.05, 2.4, and 7 {{M}⊙ } within the studied mass range of 0.38-32 {{M}⊙ }. Further, a revised mass-luminosity relation (MLR) is found based on linear fits for each of the mass domains identified. The revised, mass-domain based MLRs, which are classical (L\\propto {{M}α }), are shown to be preferable to a single linear, quadratic, or cubic equation representing an alternative MLR. Stellar radius evolution within the main sequence for stars with M\\gt 1 {{M}⊙ } is clearly evident on the M-R diagram, but it is not clear on the M-{{T}eff} diagram based on published temperatures. Effective temperatures can be calculated directly using the well known Stephan-Boltzmann law by employing the accurately known values of M and R with the newly defined MLRs. With the calculated temperatures, stellar temperature evolution within the main sequence for stars with M\\gt 1 {{M}⊙ } is clearly visible on the M-{{T}eff} diagram. Our study asserts that it is now possible to compute the effective temperature of a main-sequence star with an accuracy of ˜6%, as long as its observed radius error is adequately small (\\lt 1%) and its observed mass error is reasonably small (\\lt 6%).

  16. Biased Randomized Algorithm for Fast Model-Based Diagnosis

    NASA Technical Reports Server (NTRS)

    Williams, Colin; Vartan, Farrokh

    2005-01-01

    A biased randomized algorithm has been developed to enable the rapid computational solution of a propositional- satisfiability (SAT) problem equivalent to a diagnosis problem. The closest competing methods of automated diagnosis are described in the preceding article "Fast Algorithms for Model-Based Diagnosis" and "Two Methods of Efficient Solution of the Hitting-Set Problem" (NPO-30584), which appears elsewhere in this issue. It is necessary to recapitulate some of the information from the cited articles as a prerequisite to a description of the present method. As used here, "diagnosis" signifies, more precisely, a type of model-based diagnosis in which one explores any logical inconsistencies between the observed and expected behaviors of an engineering system. The function of each component and the interconnections among all the components of the engineering system are represented as a logical system. Hence, the expected behavior of the engineering system is represented as a set of logical consequences. Faulty components lead to inconsistency between the observed and expected behaviors of the system, represented by logical inconsistencies. Diagnosis - the task of finding the faulty components - reduces to finding the components, the abnormalities of which could explain all the logical inconsistencies. One seeks a minimal set of faulty components (denoted a minimal diagnosis), because the trivial solution, in which all components are deemed to be faulty, always explains all inconsistencies. In the methods of the cited articles, the minimal-diagnosis problem is treated as equivalent to a minimal-hitting-set problem, which is translated from a combinatorial to a computational problem by mapping it onto the Boolean-satisfiability and integer-programming problems. The integer-programming approach taken in one of the prior methods is complete (in the sense that it is guaranteed to find a solution if one exists) and slow and yields a lower bound on the size of the

  17. Highly Accurate Structure-Based Prediction of HIV-1 Coreceptor Usage Suggests Intermolecular Interactions Driving Tropism

    PubMed Central

    Kieslich, Chris A.; Tamamis, Phanourios; Guzman, Yannis A.; Onel, Melis; Floudas, Christodoulos A.

    2016-01-01

    HIV-1 entry into host cells is mediated by interactions between the V3-loop of viral glycoprotein gp120 and chemokine receptor CCR5 or CXCR4, collectively known as HIV-1 coreceptors. Accurate genotypic prediction of coreceptor usage is of significant clinical interest and determination of the factors driving tropism has been the focus of extensive study. We have developed a method based on nonlinear support vector machines to elucidate the interacting residue pairs driving coreceptor usage and provide highly accurate coreceptor usage predictions. Our models utilize centroid-centroid interaction energies from computationally derived structures of the V3-loop:coreceptor complexes as primary features, while additional features based on established rules regarding V3-loop sequences are also investigated. We tested our method on 2455 V3-loop sequences of various lengths and subtypes, and produce a median area under the receiver operator curve of 0.977 based on 500 runs of 10-fold cross validation. Our study is the first to elucidate a small set of specific interacting residue pairs between the V3-loop and coreceptors capable of predicting coreceptor usage with high accuracy across major HIV-1 subtypes. The developed method has been implemented as a web tool named CRUSH, CoReceptor USage prediction for HIV-1, which is available at http://ares.tamu.edu/CRUSH/. PMID:26859389

  18. Satellite-based damage mapping following the 2006 Indonesia earthquake—How accurate was it?

    NASA Astrophysics Data System (ADS)

    Kerle, Norman

    2010-12-01

    The Yogyakarta area in Indonesia suffered a devastating earthquake on 27 May 2006. There was an immediate international response, and the International Charter "Space and Major Disasters" was activated, leading to a rapid production of image-based damage maps and other assistance. Most of the acquired images were processed by UNOSAT and DLR-ZKI, while substantial damage mapping also occurred on the ground. This paper assesses the accuracy and completeness of the damage maps produced based on Charter data, using ground damage information collected during an extensive survey by Yogyakarta's Gadjah Mada University in the weeks following the earthquake and that has recently become available. More than 54,000 buildings or their remains were surveyed, resulting in an exceptional validation database. The UNOSAT damage maps outlining clusters of severe damage are very accurate, while earlier, more detailed results underestimated damage and missed larger areas. Damage maps produced by DLR-ZKI, using a damage-grid approach, were found to underestimate the extent and severity of the devastation. Both mapping results also suffer from limited image coverage and extensive cloud contamination. The ground mapping gives a more accurate picture of the extent of the damage, but also illustrates the challenge of mapping a vast area. The paper concludes with a discussion on ways to improve Charter-based damage maps by integration of local knowledge, and to create a wider impact through generation of customised mapping products using web map services.

  19. Fractal dimension based corneal fungal infection diagnosis

    NASA Astrophysics Data System (ADS)

    Balasubramanian, Madhusudhanan; Perkins, A. Louise; Beuerman, Roger W.; Iyengar, S. Sitharama

    2006-08-01

    We present a fractal measure based pattern classification algorithm for automatic feature extraction and identification of fungus associated with an infection of the cornea of the eye. A white-light confocal microscope image of suspected fungus exhibited locally linear and branching structures. The pixel intensity variation across the width of a fungal element was gaussian. Linear features were extracted using a set of 2D directional matched gaussian-filters. Portions of fungus profiles that were not in the same focal plane appeared relatively blurred. We use gaussian filters of standard deviation slightly larger than the width of a fungus to reduce discontinuities. Cell nuclei of cornea and nerves also exhibited locally linear structure. Cell nuclei were excluded by their relatively shorter lengths. Nerves in the cornea exhibited less branching compared with the fungus. Fractal dimensions of the locally linear features were computed using a box-counting method. A set of corneal images with fungal infection was used to generate class-conditional fractal measure distributions of fungus and nerves. The a priori class-conditional densities were built using an adaptive-mixtures method to reflect the true nature of the feature distributions and improve the classification accuracy. A maximum-likelihood classifier was used to classify the linear features extracted from test corneal images as 'normal' or 'with fungal infiltrates', using the a priori fractal measure distributions. We demonstrate the algorithm on the corneal images with culture-positive fungal infiltrates. The algorithm is fully automatic and will help diagnose fungal keratitis by generating a diagnostic mask of locations of the fungal infiltrates.

  20. Accurate modeling of switched reluctance machine based on hybrid trained WNN

    SciTech Connect

    Song, Shoujun Ge, Lefei; Ma, Shaojie; Zhang, Man

    2014-04-15

    According to the strong nonlinear electromagnetic characteristics of switched reluctance machine (SRM), a novel accurate modeling method is proposed based on hybrid trained wavelet neural network (WNN) which combines improved genetic algorithm (GA) with gradient descent (GD) method to train the network. In the novel method, WNN is trained by GD method based on the initial weights obtained per improved GA optimization, and the global parallel searching capability of stochastic algorithm and local convergence speed of deterministic algorithm are combined to enhance the training accuracy, stability and speed. Based on the measured electromagnetic characteristics of a 3-phase 12/8-pole SRM, the nonlinear simulation model is built by hybrid trained WNN in Matlab. The phase current and mechanical characteristics from simulation under different working conditions meet well with those from experiments, which indicates the accuracy of the model for dynamic and static performance evaluation of SRM and verifies the effectiveness of the proposed modeling method.

  1. Accurate Young's modulus measurement based on Rayleigh wave velocity and empirical Poisson's ratio

    NASA Astrophysics Data System (ADS)

    Li, Mingxia; Feng, Zhihua

    2016-07-01

    This paper presents a method for Young's modulus measurement based on Rayleigh wave speed. The error in Poisson's ratio has weak influence on the measurement of Young's modulus based on Rayleigh wave speed, and Poisson's ratio minimally varies in a certain material; thus, we can accurately estimate Young's modulus with surface wave speed and a rough Poisson's ratio. We numerically analysed three methods using Rayleigh, longitudinal, and transversal wave speed, respectively, and the error in Poisson's ratio shows the least influence on the result in the method involving Rayleigh wave speed. An experiment was performed and has proved the feasibility of this method. Device for speed measuring could be small, and no sample pretreatment is needed. Hence, developing a portable instrument based on this method is possible. This method makes a good compromise between usability and precision.

  2. Design of fault diagnosis system for inertial navigation system based on virtual technology

    NASA Astrophysics Data System (ADS)

    Hu, Baiqing; Wang, Boxiong; Li, An; Zhang, Mingzhao; Qin, Fangjun; Pan, Hua

    2006-11-01

    With regard to the complex structure of the inertial navigation system and the low rate of fault detection with BITE (built-in test equipment), a fault diagnosis system for INS based on virtual technologies (virtual instrument and virtual equipment) is proposed in this paper. The hardware of the system is a PXI computer with highly stable performance and strong extensibility. In addition to the basic functions of digital multimeter, oscilloscope and cymometer, it can also measure the attitude of the ship in real-time, connect and control the measurement instruments with digital interface. The software is designed with the languages of Measurement Studio for VB, JAVA, and CULT3D. Using the extensively applied fault-tree reasoning and fault cases makes fault diagnosis. To suit the system to the diagnosis for various navigation electronic equipments, the modular design concept is adopted for the software programming. Knowledge of the expert system is digitally processed and the parameters of the system's interface and the expert diagnosis knowledge are stored in the database. The application shows that system is stable in operation, easy to use, quick and accurate in fault diagnosis.

  3. Fault diagnosis using noise modeling and a new artificial immune system based algorithm

    NASA Astrophysics Data System (ADS)

    Abbasi, Farshid; Mojtahedi, Alireza; Ettefagh, Mir Mohammad

    2015-12-01

    A new fault classification/diagnosis method based on artificial immune system (AIS) algorithms for the structural systems is proposed. In order to improve the accuracy of the proposed method, i.e., higher success rate, Gaussian and non-Gaussian noise generating models are applied to simulate environmental noise. The identification of noise model, known as training process, is based on the estimation of the noise model parameters by genetic algorithms (GA) utilizing real experimental features. The proposed fault classification/diagnosis algorithm is applied to the noise contaminated features. Then, the results are compared to that obtained without noise modeling. The performance of the proposed method is examined using three laboratory case studies in two healthy and damaged conditions. Finally three different types of noise models are studied and it is shown experimentally that the proposed algorithm with non-Gaussian noise modeling leads to more accurate clustering of memory cells as the major part of the fault classification procedure.

  4. Sensor fault diagnosis for fast steering mirror system based on Kalman filter

    NASA Astrophysics Data System (ADS)

    Wang, Hongju; Bao, Qiliang; Yang, Haifeng; Tao, Sunjie

    2015-10-01

    In this paper, to improve the reliability of a two-axis fast steering mirror system with minimum hardware consumption, a fault diagnosis method based on Kalman filter was developed. The dynamics model of the two-axis FSM was established firstly, and then the state-space form of the FSM was adopted. A bank of Kalman filters for fault detection was designed based on the state-space form. The effects of the sensor faults on the innovation sequence were investigated, and a decision approach called weighted sum-squared residual (WSSR) was adopted to isolate the sensor faults. Sensor faults could be detected and isolated when the decision statistics changed. Experimental studies on a prototype system show that the faulty sensor can be isolated timely and accurately. Meanwhile, the mathematical model of FSM system was used to design fault diagnosis scheme in the proposed method, thus the consumption of the hardware and space is decreased.

  5. Using Bayesian Networks for Candidate Generation in Consistency-based Diagnosis

    NASA Technical Reports Server (NTRS)

    Narasimhan, Sriram; Mengshoel, Ole

    2008-01-01

    Consistency-based diagnosis relies heavily on the assumption that discrepancies between model predictions and sensor observations can be detected accurately. When sources of uncertainty like sensor noise and model abstraction exist robust schemes have to be designed to make a binary decision on whether predictions are consistent with observations. This risks the occurrence of false alarms and missed alarms when an erroneous decision is made. Moreover when multiple sensors (with differing sensing properties) are available the degree of match between predictions and observations can be used to guide the search for fault candidates. In this paper we propose a novel approach to handle this problem using Bayesian networks. In the consistency- based diagnosis formulation, automatically generated Bayesian networks are used to encode a probabilistic measure of fit between predictions and observations. A Bayesian network inference algorithm is used to compute most probable fault candidates.

  6. Problem-Based Learning: A Tutorial Model Incorporating Pharmaceutical Diagnosis.

    ERIC Educational Resources Information Center

    Culbertson, Vaughn L.; And Others

    1997-01-01

    Describes the problem-based learning methodology used at Idaho State University College of Pharmacy. Objectives of the four-semester course sequence are to emphasize fundamental basic science concepts, develop a system for pharmaceutical diagnosis, facilitate development of clinical problem-solving skills before clerkship, foster team-oriented…

  7. Skills Diagnosis Using IRT-Based Continuous Latent Trait Models

    ERIC Educational Resources Information Center

    Stout, William

    2007-01-01

    This article summarizes the continuous latent trait IRT approach to skills diagnosis as particularized by a representative variety of continuous latent trait models using item response functions (IRFs). First, several basic IRT-based continuous latent trait approaches are presented in some detail. Then a brief summary of estimation, model…

  8. Computer-based personality judgments are more accurate than those made by humans

    PubMed Central

    Youyou, Wu; Kosinski, Michal; Stillwell, David

    2015-01-01

    Judging others’ personalities is an essential skill in successful social living, as personality is a key driver behind people’s interactions, behaviors, and emotions. Although accurate personality judgments stem from social-cognitive skills, developments in machine learning show that computer models can also make valid judgments. This study compares the accuracy of human and computer-based personality judgments, using a sample of 86,220 volunteers who completed a 100-item personality questionnaire. We show that (i) computer predictions based on a generic digital footprint (Facebook Likes) are more accurate (r = 0.56) than those made by the participants’ Facebook friends using a personality questionnaire (r = 0.49); (ii) computer models show higher interjudge agreement; and (iii) computer personality judgments have higher external validity when predicting life outcomes such as substance use, political attitudes, and physical health; for some outcomes, they even outperform the self-rated personality scores. Computers outpacing humans in personality judgment presents significant opportunities and challenges in the areas of psychological assessment, marketing, and privacy. PMID:25583507

  9. Compression-based distance (CBD): a simple, rapid, and accurate method for microbiota composition comparison

    PubMed Central

    2013-01-01

    Background Perturbations in intestinal microbiota composition have been associated with a variety of gastrointestinal tract-related diseases. The alleviation of symptoms has been achieved using treatments that alter the gastrointestinal tract microbiota toward that of healthy individuals. Identifying differences in microbiota composition through the use of 16S rRNA gene hypervariable tag sequencing has profound health implications. Current computational methods for comparing microbial communities are usually based on multiple alignments and phylogenetic inference, making them time consuming and requiring exceptional expertise and computational resources. As sequencing data rapidly grows in size, simpler analysis methods are needed to meet the growing computational burdens of microbiota comparisons. Thus, we have developed a simple, rapid, and accurate method, independent of multiple alignments and phylogenetic inference, to support microbiota comparisons. Results We create a metric, called compression-based distance (CBD) for quantifying the degree of similarity between microbial communities. CBD uses the repetitive nature of hypervariable tag datasets and well-established compression algorithms to approximate the total information shared between two datasets. Three published microbiota datasets were used as test cases for CBD as an applicable tool. Our study revealed that CBD recaptured 100% of the statistically significant conclusions reported in the previous studies, while achieving a decrease in computational time required when compared to similar tools without expert user intervention. Conclusion CBD provides a simple, rapid, and accurate method for assessing distances between gastrointestinal tract microbiota 16S hypervariable tag datasets. PMID:23617892

  10. Accurate palm vein recognition based on wavelet scattering and spectral regression kernel discriminant analysis

    NASA Astrophysics Data System (ADS)

    Elnasir, Selma; Shamsuddin, Siti Mariyam; Farokhi, Sajad

    2015-01-01

    Palm vein recognition (PVR) is a promising new biometric that has been applied successfully as a method of access control by many organizations, which has even further potential in the field of forensics. The palm vein pattern has highly discriminative features that are difficult to forge because of its subcutaneous position in the palm. Despite considerable progress and a few practical issues, providing accurate palm vein readings has remained an unsolved issue in biometrics. We propose a robust and more accurate PVR method based on the combination of wavelet scattering (WS) with spectral regression kernel discriminant analysis (SRKDA). As the dimension of WS generated features is quite large, SRKDA is required to reduce the extracted features to enhance the discrimination. The results based on two public databases-PolyU Hyper Spectral Palmprint public database and PolyU Multi Spectral Palmprint-show the high performance of the proposed scheme in comparison with state-of-the-art methods. The proposed approach scored a 99.44% identification rate and a 99.90% verification rate [equal error rate (EER)=0.1%] for the hyperspectral database and a 99.97% identification rate and a 99.98% verification rate (EER=0.019%) for the multispectral database.

  11. Accurate similarity index based on activity and connectivity of node for link prediction

    NASA Astrophysics Data System (ADS)

    Li, Longjie; Qian, Lvjian; Wang, Xiaoping; Luo, Shishun; Chen, Xiaoyun

    2015-05-01

    Recent years have witnessed the increasing of available network data; however, much of those data is incomplete. Link prediction, which can find the missing links of a network, plays an important role in the research and analysis of complex networks. Based on the assumption that two unconnected nodes which are highly similar are very likely to have an interaction, most of the existing algorithms solve the link prediction problem by computing nodes' similarities. The fundamental requirement of those algorithms is accurate and effective similarity indices. In this paper, we propose a new similarity index, namely similarity based on activity and connectivity (SAC), which performs link prediction more accurately. To compute the similarity between two nodes, this index employs the average activity of these two nodes in their common neighborhood and the connectivities between them and their common neighbors. The higher the average activity is and the stronger the connectivities are, the more similar the two nodes are. The proposed index not only commendably distinguishes the contributions of paths but also incorporates the influence of endpoints. Therefore, it can achieve a better predicting result. To verify the performance of SAC, we conduct experiments on 10 real-world networks. Experimental results demonstrate that SAC outperforms the compared baselines.

  12. Prometheus: Scalable and Accurate Emulation of Task-Based Applications on Many-Core Systems.

    SciTech Connect

    Kestor, Gokcen; Gioiosa, Roberto; Chavarría-Miranda, Daniel

    2015-03-01

    Modeling the performance of non-deterministic parallel applications on future many-core systems requires the development of novel simulation and emulation techniques and tools. We present “Prometheus”, a fast, accurate and modular emulation framework for task-based applications. By raising the level of abstraction and focusing on runtime synchronization, Prometheus can accurately predict applications’ performance on very large many-core systems. We validate our emulation framework against two real platforms (AMD Interlagos and Intel MIC) and report error rates generally below 4%. We, then, evaluate Prometheus’ performance and scalability: our results show that Prometheus can emulate a task-based application on a system with 512K cores in 11.5 hours. We present two test cases that show how Prometheus can be used to study the performance and behavior of systems that present some of the characteristics expected from exascale supercomputer nodes, such as active power management and processors with a high number of cores but reduced cache per core.

  13. Computer-based personality judgments are more accurate than those made by humans.

    PubMed

    Youyou, Wu; Kosinski, Michal; Stillwell, David

    2015-01-27

    Judging others' personalities is an essential skill in successful social living, as personality is a key driver behind people's interactions, behaviors, and emotions. Although accurate personality judgments stem from social-cognitive skills, developments in machine learning show that computer models can also make valid judgments. This study compares the accuracy of human and computer-based personality judgments, using a sample of 86,220 volunteers who completed a 100-item personality questionnaire. We show that (i) computer predictions based on a generic digital footprint (Facebook Likes) are more accurate (r = 0.56) than those made by the participants' Facebook friends using a personality questionnaire (r = 0.49); (ii) computer models show higher interjudge agreement; and (iii) computer personality judgments have higher external validity when predicting life outcomes such as substance use, political attitudes, and physical health; for some outcomes, they even outperform the self-rated personality scores. Computers outpacing humans in personality judgment presents significant opportunities and challenges in the areas of psychological assessment, marketing, and privacy. PMID:25583507

  14. Highly accurate nitrogen dioxide (NO2) in nitrogen standards based on permeation.

    PubMed

    Flores, Edgar; Viallon, Joële; Moussay, Philippe; Idrees, Faraz; Wielgosz, Robert Ian

    2012-12-01

    The development and operation of a highly accurate primary gas facility for the dynamic production of mixtures of nitrogen dioxide (NO(2)) in nitrogen (N(2)) based on continuous weighing of a permeation tube and accurate impurity quantification and correction of the gas mixtures using Fourier transform infrared spectroscopy (FT-IR) is described. NO(2) gas mixtures in the range of 5 μmol mol(-1) to 15 μmol mol(-1) with a standard relative uncertainty of 0.4% can be produced with this facility. To achieve an uncertainty at this level, significant efforts were made to reduce, identify and quantify potential impurities present in the gas mixtures, such as nitric acid (HNO(3)). A complete uncertainty budget, based on the analysis of the performance of the facility, including the use of a FT-IR spectrometer and a nondispersive UV analyzer as analytical techniques, is presented in this work. The mixtures produced by this facility were validated and then selected to provide reference values for an international comparison of the Consultative Committee for Amount of Substance (CCQM), number CCQM-K74, (1) which was designed to evaluate the consistency of primary NO(2) gas standards from 17 National Metrology Institutes. PMID:23148702

  15. Polycrystalline diamond based detector for Z-pinch plasma diagnosis

    SciTech Connect

    Liu Linyue; Zhao Jizhen; Chen Liang; Ouyang Xiaoping; Wang Lan

    2010-08-15

    A detector setup based on polycrystalline chemical-vapor-deposition diamond film is developed with great characteristics: low dark current (lower than 60 pA within 3 V/{mu}m), fast pulsed response time (rise time: 2-3 ns), flat spectral response (3-5 keV), easy acquisition, low cost, and relative large sensitive area. The characterizing data on Qiangguang-I accelerator show that this detector can satisfy the practical requirements in Z-pinch plasma diagnosis very well, which offers a promising prototype for the x-ray detection in Z-pinch diagnosis.

  16. Diagnosis of helicopter gearboxes using structure-based networks

    NASA Technical Reports Server (NTRS)

    Jammu, Vinay B.; Danai, Kourosh; Lewicki, David G.

    1995-01-01

    A connectionist network is introduced for fault diagnosis of helicopter gearboxes that incorporates knowledge of the gearbox structure and characteristics of the vibration features as its fuzzy weights. Diagnosis is performed by propagating the abnormal features of vibration measurements through this Structure-Based Connectionist Network (SBCN), the outputs of which represent the fault possibility values for individual components of the gearbox. The performance of this network is evaluated by applying it to experimental vibration data from an OH-58A helicopter gearbox. The diagnostic results indicate that the network performance is comparable to those obtained from supervised pattern classification.

  17. Graphene fluorescence switch-based cooperative amplification: a sensitive and accurate method to detection microRNA.

    PubMed

    Liu, Haiyun; Li, Lu; Wang, Qian; Duan, Lili; Tang, Bo

    2014-06-01

    MicroRNAs (miRNAs) play significant roles in a diverse range of biological progress and have been regarded as biomarkers and therapeutic targets in cancer treatment. Sensitive and accurate detection of miRNAs is crucial for better understanding their roles in cancer cells and further validating their function in clinical diagnosis. Here, we developed a stable, sensitive, and specific miRNAs detection method on the basis of cooperative amplification combining with the graphene oxide (GO) fluorescence switch-based circular exponential amplification and the multimolecules labeling of SYBR Green I (SG). First, the target miRNA is adsorbed on the surface of GO, which can protect the miRNA from enzyme digest. Next, the miRNA hybridizes with a partial hairpin probe and then acts as a primer to initiate a strand displacement reaction to form a complete duplex. Finally, under the action of nicking enzyme, universal DNA fragments are released and used as triggers to initiate next reaction cycle, constituting a new circular exponential amplification. In the proposed strategy, a small amount of target miRNA can be converted to a large number of stable DNA triggers, leading to a remarkable amplification for the target. Moreover, compared with labeling with a 1:1 stoichiometric ratio, multimolecules binding of intercalating dye SG to double-stranded DNA (dsDNA) can induce significant enhancement of fluorescence signal and further improve the detection sensitivity. The extraordinary fluorescence quenching of GO used here guarantees the high signal-to-noise ratio. Due to the protection for target miRNA by GO, the cooperative amplification, and low fluorescence background, sensitive and accurate detection of miRNAs has been achieved. The strategy proposed here will offer a new approach for reliable quantification of miRNAs in medical research and early clinical diagnostics. PMID:24823448

  18. Modeling Sensor Reliability in Fault Diagnosis Based on Evidence Theory

    PubMed Central

    Yuan, Kaijuan; Xiao, Fuyuan; Fei, Liguo; Kang, Bingyi; Deng, Yong

    2016-01-01

    Sensor data fusion plays an important role in fault diagnosis. Dempster–Shafer (D-R) evidence theory is widely used in fault diagnosis, since it is efficient to combine evidence from different sensors. However, under the situation where the evidence highly conflicts, it may obtain a counterintuitive result. To address the issue, a new method is proposed in this paper. Not only the statistic sensor reliability, but also the dynamic sensor reliability are taken into consideration. The evidence distance function and the belief entropy are combined to obtain the dynamic reliability of each sensor report. A weighted averaging method is adopted to modify the conflict evidence by assigning different weights to evidence according to sensor reliability. The proposed method has better performance in conflict management and fault diagnosis due to the fact that the information volume of each sensor report is taken into consideration. An application in fault diagnosis based on sensor fusion is illustrated to show the efficiency of the proposed method. The results show that the proposed method improves the accuracy of fault diagnosis from 81.19% to 89.48% compared to the existing methods. PMID:26797611

  19. Modeling Sensor Reliability in Fault Diagnosis Based on Evidence Theory.

    PubMed

    Yuan, Kaijuan; Xiao, Fuyuan; Fei, Liguo; Kang, Bingyi; Deng, Yong

    2016-01-01

    Sensor data fusion plays an important role in fault diagnosis. Dempster-Shafer (D-R) evidence theory is widely used in fault diagnosis, since it is efficient to combine evidence from different sensors. However, under the situation where the evidence highly conflicts, it may obtain a counterintuitive result. To address the issue, a new method is proposed in this paper. Not only the statistic sensor reliability, but also the dynamic sensor reliability are taken into consideration. The evidence distance function and the belief entropy are combined to obtain the dynamic reliability of each sensor report. A weighted averaging method is adopted to modify the conflict evidence by assigning different weights to evidence according to sensor reliability. The proposed method has better performance in conflict management and fault diagnosis due to the fact that the information volume of each sensor report is taken into consideration. An application in fault diagnosis based on sensor fusion is illustrated to show the efficiency of the proposed method. The results show that the proposed method improves the accuracy of fault diagnosis from 81.19% to 89.48% compared to the existing methods. PMID:26797611

  20. Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding

    PubMed Central

    Wang, Xiang; Zheng, Yuan; Zhao, Zhenzhou; Wang, Jinping

    2015-01-01

    Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is a crucial task. In this paper a novel machinery fault diagnosis approach based on a statistical locally linear embedding (S-LLE) algorithm which is an extension of LLE by exploiting the fault class label information is proposed. The fault diagnosis approach first extracts the intrinsic manifold features from the high-dimensional feature vectors which are obtained from vibration signals that feature extraction by time-domain, frequency-domain and empirical mode decomposition (EMD), and then translates the complex mode space into a salient low-dimensional feature space by the manifold learning algorithm S-LLE, which outperforms other feature reduction methods such as PCA, LDA and LLE. Finally in the feature reduction space pattern classification and fault diagnosis by classifier are carried out easily and rapidly. Rolling bearing fault signals are used to validate the proposed fault diagnosis approach. The results indicate that the proposed approach obviously improves the classification performance of fault pattern recognition and outperforms the other traditional approaches. PMID:26153771

  1. Bearing Fault Diagnosis Based on Statistical Locally Linear Embedding.

    PubMed

    Wang, Xiang; Zheng, Yuan; Zhao, Zhenzhou; Wang, Jinping

    2015-01-01

    Fault diagnosis is essentially a kind of pattern recognition. The measured signal samples usually distribute on nonlinear low-dimensional manifolds embedded in the high-dimensional signal space, so how to implement feature extraction, dimensionality reduction and improve recognition performance is a crucial task. In this paper a novel machinery fault diagnosis approach based on a statistical locally linear embedding (S-LLE) algorithm which is an extension of LLE by exploiting the fault class label information is proposed. The fault diagnosis approach first extracts the intrinsic manifold features from the high-dimensional feature vectors which are obtained from vibration signals that feature extraction by time-domain, frequency-domain and empirical mode decomposition (EMD), and then translates the complex mode space into a salient low-dimensional feature space by the manifold learning algorithm S-LLE, which outperforms other feature reduction methods such as PCA, LDA and LLE. Finally in the feature reduction space pattern classification and fault diagnosis by classifier are carried out easily and rapidly. Rolling bearing fault signals are used to validate the proposed fault diagnosis approach. The results indicate that the proposed approach obviously improves the classification performance of fault pattern recognition and outperforms the other traditional approaches. PMID:26153771

  2. Computer-based diagnosis of illness in historical persons.

    PubMed

    Peters, T J

    2013-01-01

    Retrospective diagnosis of illness in historical figures is a popular but somewhat unreliable pastime due to the lack of detailed information and reliable reports about clinical features and disease progression. Modern computer-based diagnostic programmes have been used to supplement historical documents and accounts, offering new and more objective approaches to the retrospective investigations of the medical conditions of historical persons. In the case of King George III, modern technology has been used to strengthen the findings of previous reports rejecting the popular diagnosis of variegate porphyria in the King, his grandson Augustus d'Esté and his antecedent King James VI and I. Alternative diagnoses based on these programmes are indicated. The Operational Criteria in Studies of Psychotic Illness (OPCRIT) programme and the Young mania scale have been applied to the features described for George III and suggest a diagnosis of bipolar disorder. The neuro-diagnostic programme SimulConsult was applied to Augustus d'Esté and suggests a diagnosis of neuromyelitis optica rather than acute porphyria with secondarily multiple sclerosis, as proposed by others. James VI and I's complex medical history and the clinical features of his behavioural traits were also subjected to SimulConsult analysis; acute porphyria was rejected and the unexpected diagnosis of attenuated (mild) Lesch-Nyhan disease offered. A brief review of these approaches along with full reference listings to the methodology including validation are provided. Textual analysis of the written and verbal outputs of historical figures indicate possible future developments in the diagnosis of medical disorders in historical figures. PMID:23734360

  3. Possibilistic-clustering-based MR brain image segmentation with accurate initialization

    NASA Astrophysics Data System (ADS)

    Liao, Qingmin; Deng, Yingying; Dou, Weibei; Ruan, Su; Bloyet, Daniel

    2004-01-01

    Magnetic resonance image analysis by computer is useful to aid diagnosis of malady. We present in this paper a automatic segmentation method for principal brain tissues. It is based on the possibilistic clustering approach, which is an improved fuzzy c-means clustering method. In order to improve the efficiency of clustering process, the initial value problem is discussed and solved by combining with a histogram analysis method. Our method can automatically determine number of classes to cluster and the initial values for each class. It has been tested on a set of forty MR brain images with or without the presence of tumor. The experimental results showed that it is simple, rapid and robust to segment the principal brain tissues.

  4. A fault diagnosis methodology for rolling element bearings based on advanced signal pretreatment and autoregressive modelling

    NASA Astrophysics Data System (ADS)

    Al-Bugharbee, Hussein; Trendafilova, Irina

    2016-05-01

    This study proposes a methodology for rolling element bearings fault diagnosis which gives a complete and highly accurate identification of the faults present. It has two main stages: signals pretreatment, which is based on several signal analysis procedures, and diagnosis, which uses a pattern-recognition process. The first stage is principally based on linear time invariant autoregressive modelling. One of the main contributions of this investigation is the development of a pretreatment signal analysis procedure which subjects the signal to noise cleaning by singular spectrum analysis and then stationarisation by differencing. So the signal is transformed to bring it close to a stationary one, rather than complicating the model to bring it closer to the signal. This type of pretreatment allows the use of a linear time invariant autoregressive model and improves its performance when the original signals are non-stationary. This contribution is at the heart of the proposed method, and the high accuracy of the diagnosis is a result of this procedure. The methodology emphasises the importance of preliminary noise cleaning and stationarisation. And it demonstrates that the information needed for fault identification is contained in the stationary part of the measured signal. The methodology is further validated using three different experimental setups, demonstrating very high accuracy for all of the applications. It is able to correctly classify nearly 100 percent of the faults with regard to their type and size. This high accuracy is the other important contribution of this methodology. Thus, this research suggests a highly accurate methodology for rolling element bearing fault diagnosis which is based on relatively simple procedures. This is also an advantage, as the simplicity of the individual processes ensures easy application and the possibility for automation of the entire process.

  5. Rapid and accurate identification of microorganisms contaminating cosmetic products based on DNA sequence homology.

    PubMed

    Fujita, Y; Shibayama, H; Suzuki, Y; Karita, S; Takamatsu, S

    2005-12-01

    The aim of this study was to develop rapid and accurate procedures to identify microorganisms contaminating cosmetic products, based on the identity of the nucleotide sequences of the internal transcribed spacer (ITS) region of the ribosomal RNA coding DNA (rDNA). Five types of microorganisms were isolated from the inner portion of lotion bottle caps, skin care lotions, and cleansing gels. The rDNA ITS region of microorganisms was amplified through the use of colony-direct PCR or ordinal PCR using DNA extracts as templates. The nucleotide sequences of the amplified DNA were determined and subjected to homology search of a publicly available DNA database. Thereby, we obtained DNA sequences possessing high similarity with the query sequences from the databases of all the five organisms analyzed. The traditional identification procedure requires expert skills, and a time period of approximately 1 month to identify the microorganisms. On the contrary, 3-7 days were sufficient to complete all the procedures employed in the current method, including isolation and cultivation of organisms, DNA sequencing, and the database homology search. Moreover, it was possible to develop the skills necessary to perform the molecular techniques required for the identification procedures within 1 week. Consequently, the current method is useful for rapid and accurate identification of microorganisms, contaminating cosmetics. PMID:18492168

  6. MOSAIK: a hash-based algorithm for accurate next-generation sequencing short-read mapping.

    PubMed

    Lee, Wan-Ping; Stromberg, Michael P; Ward, Alistair; Stewart, Chip; Garrison, Erik P; Marth, Gabor T

    2014-01-01

    MOSAIK is a stable, sensitive and open-source program for mapping second and third-generation sequencing reads to a reference genome. Uniquely among current mapping tools, MOSAIK can align reads generated by all the major sequencing technologies, including Illumina, Applied Biosystems SOLiD, Roche 454, Ion Torrent and Pacific BioSciences SMRT. Indeed, MOSAIK was the only aligner to provide consistent mappings for all the generated data (sequencing technologies, low-coverage and exome) in the 1000 Genomes Project. To provide highly accurate alignments, MOSAIK employs a hash clustering strategy coupled with the Smith-Waterman algorithm. This method is well-suited to capture mismatches as well as short insertions and deletions. To support the growing interest in larger structural variant (SV) discovery, MOSAIK provides explicit support for handling known-sequence SVs, e.g. mobile element insertions (MEIs) as well as generating outputs tailored to aid in SV discovery. All variant discovery benefits from an accurate description of the read placement confidence. To this end, MOSAIK uses a neural-network based training scheme to provide well-calibrated mapping quality scores, demonstrated by a correlation coefficient between MOSAIK assigned and actual mapping qualities greater than 0.98. In order to ensure that studies of any genome are supported, a training pipeline is provided to ensure optimal mapping quality scores for the genome under investigation. MOSAIK is multi-threaded, open source, and incorporated into our command and pipeline launcher system GKNO (http://gkno.me). PMID:24599324

  7. Accurate real-time depth control for CP-SSOCT distal sensor based handheld microsurgery tools.

    PubMed

    Cheon, Gyeong Woo; Huang, Yong; Cha, Jaepyeng; Gehlbach, Peter L; Kang, Jin U

    2015-05-01

    This paper presents a novel intuitive targeting and tracking scheme that utilizes a common-path swept source optical coherence tomography (CP-SSOCT) distal sensor integrated handheld microsurgical tool. To achieve micron-order precision control, a reliable and accurate OCT distal sensing method is required; simultaneously, a prediction algorithm is necessary to compensate for the system delay associated with the computational, mechanical and electronic latencies. Due to the multi-layered structure of retina, it is necessary to develop effective surface detection methods rather than simple peak detection. To achieve this, a shifted cross-correlation method is applied for surface detection in order to increase robustness and accuracy in distal sensing. A predictor based on Kalman filter was implemented for more precise motion compensation. The performance was first evaluated using an established dry phantom consisting of stacked cellophane tape. This was followed by evaluation in an ex-vivo bovine retina model to assess system accuracy and precision. The results demonstrate highly accurate depth targeting with less than 5 μm RMSE depth locking. PMID:26137393

  8. Accurate real-time depth control for CP-SSOCT distal sensor based handheld microsurgery tools

    PubMed Central

    Cheon, Gyeong Woo; Huang, Yong; Cha, Jaepyeng; Gehlbach, Peter L.; Kang, Jin U.

    2015-01-01

    This paper presents a novel intuitive targeting and tracking scheme that utilizes a common-path swept source optical coherence tomography (CP-SSOCT) distal sensor integrated handheld microsurgical tool. To achieve micron-order precision control, a reliable and accurate OCT distal sensing method is required; simultaneously, a prediction algorithm is necessary to compensate for the system delay associated with the computational, mechanical and electronic latencies. Due to the multi-layered structure of retina, it is necessary to develop effective surface detection methods rather than simple peak detection. To achieve this, a shifted cross-correlation method is applied for surface detection in order to increase robustness and accuracy in distal sensing. A predictor based on Kalman filter was implemented for more precise motion compensation. The performance was first evaluated using an established dry phantom consisting of stacked cellophane tape. This was followed by evaluation in an ex-vivo bovine retina model to assess system accuracy and precision. The results demonstrate highly accurate depth targeting with less than 5 μm RMSE depth locking. PMID:26137393

  9. Accurate time-of-flight measurement of particle based on ECL-TTL Timer

    NASA Astrophysics Data System (ADS)

    Li, Deping; Liu, Jianguo; Huang, Shuhua; Gui, Huaqiao; Cheng, Yin; Wang, Jie; Lu, Yihuai

    2014-11-01

    Because of its aerodynamic diameter of the aerosol particles are stranded in different parts of different human respiratory system, thus affecting human health. Therefore, how to continue to effectively monitor the aerosol particles become increasingly concerned about. Use flight time of aerosol particle beam spectroscopy of atmospheric aerosol particle size distribution is the typical method for monitoring atmospheric aerosol particle size and particle concentration measurement , and it is the key point to accurate measurement of aerosol particle size spectra that measurement of aerosol particle flight time. In order to achieve accurate measurements of aerosol particles in time-of-flight, this paper design an ECL-TTL high-speed timer with ECL counter and TTL counter. The high-speed timer includes a clock generation, high-speed timer and the control module. Clock Generation Module using a crystal plus multiplier design ideas, take advantage of the stability of the crystal to provide a stable 500MHz clock signal is high counter. High count module design using ECL and TTL counter mix design, timing accuracy while effectively maintaining , expanding the timing range, and simplifies circuit design . High-speed counter control module controls high-speed counter start, stop and reset timely based on aerosol particles time-of-flight, is a key part of the high-speed counting. The high-speed counting resolution of 4ns, the full scale of 4096ns, has been successfully applied Aerodynamic Particle Sizer, to meet the precise measurement of aerosol particles time-of-flight.

  10. An accurate assay for HCV based on real-time fluorescence detection of isothermal RNA amplification.

    PubMed

    Wu, Xuping; Wang, Jianfang; Song, Jinyun; Li, Jiayan; Yang, Yongfeng

    2016-09-01

    Hepatitis C virus (HCV) is one of the common reasons of liver fibrosis and hepatocellular carcinoma (HCC). Early, rapid and accurate HCV RNA detection is important to prevent and control liver disease. A simultaneous amplification and testing (SAT) assay, which is based on isothermal amplification of RNA and real-time fluorescence detection, was designed to optimize routine HCV RNA detection. In this study, HCV RNA and an internal control (IC) were amplified and analyzed simultaneously by SAT assay and detection of fluorescence using routine real-time PCR equipment. The assay detected as few as 10 copies of HCV RNA transcripts. We tested 705 serum samples with SAT, among which 96.4% (680/705) showed consistent results compared with routine real-time PCR. About 92% (23/25) discordant samples were confirmed to be same results as SAT-HCV by using a second real-time PCR. The sensitivity and specificity of SAT-HCV assay were 99.6% (461/463) and 100% (242/242), respectively. In conclusion, the SAT assay is an accurate test with a high specificity and sensitivity which may increase the detection rate of HCV. It is therefore a promising tool to diagnose HCV infection. PMID:27283884

  11. Accurate Mobile Urban Mapping via Digital Map-Based SLAM †.

    PubMed

    Roh, Hyunchul; Jeong, Jinyong; Cho, Younggun; Kim, Ayoung

    2016-01-01

    This paper presents accurate urban map generation using digital map-based Simultaneous Localization and Mapping (SLAM). Throughout this work, our main objective is generating a 3D and lane map aiming for sub-meter accuracy. In conventional mapping approaches, achieving extremely high accuracy was performed by either (i) exploiting costly airborne sensors or (ii) surveying with a static mapping system in a stationary platform. Mobile scanning systems recently have gathered popularity but are mostly limited by the availability of the Global Positioning System (GPS). We focus on the fact that the availability of GPS and urban structures are both sporadic but complementary. By modeling both GPS and digital map data as measurements and integrating them with other sensor measurements, we leverage SLAM for an accurate mobile mapping system. Our proposed algorithm generates an efficient graph SLAM and achieves a framework running in real-time and targeting sub-meter accuracy with a mobile platform. Integrated with the SLAM framework, we implement a motion-adaptive model for the Inverse Perspective Mapping (IPM). Using motion estimation derived from SLAM, the experimental results show that the proposed approaches provide stable bird's-eye view images, even with significant motion during the drive. Our real-time map generation framework is validated via a long-distance urban test and evaluated at randomly sampled points using Real-Time Kinematic (RTK)-GPS. PMID:27548175

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

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

  13. Rule-based fault diagnosis of hall sensors and fault-tolerant control of PMSM

    NASA Astrophysics Data System (ADS)

    Song, Ziyou; Li, Jianqiu; Ouyang, Minggao; Gu, Jing; Feng, Xuning; Lu, Dongbin

    2013-07-01

    Hall sensor is widely used for estimating rotor phase of permanent magnet synchronous motor(PMSM). And rotor position is an essential parameter of PMSM control algorithm, hence it is very dangerous if Hall senor faults occur. But there is scarcely any research focusing on fault diagnosis and fault-tolerant control of Hall sensor used in PMSM. From this standpoint, the Hall sensor faults which may occur during the PMSM operating are theoretically analyzed. According to the analysis results, the fault diagnosis algorithm of Hall sensor, which is based on three rules, is proposed to classify the fault phenomena accurately. The rotor phase estimation algorithms, based on one or two Hall sensor(s), are initialized to engender the fault-tolerant control algorithm. The fault diagnosis algorithm can detect 60 Hall fault phenomena in total as well as all detections can be fulfilled in 1/138 rotor rotation period. The fault-tolerant control algorithm can achieve a smooth torque production which means the same control effect as normal control mode (with three Hall sensors). Finally, the PMSM bench test verifies the accuracy and rapidity of fault diagnosis and fault-tolerant control strategies. The fault diagnosis algorithm can detect all Hall sensor faults promptly and fault-tolerant control algorithm allows the PMSM to face failure conditions of one or two Hall sensor(s). In addition, the transitions between health-control and fault-tolerant control conditions are smooth without any additional noise and harshness. Proposed algorithms can deal with the Hall sensor faults of PMSM in real applications, and can be provided to realize the fault diagnosis and fault-tolerant control of PMSM.

  14. The diagnosis of hyper immunoglobulin e syndrome based on project management.

    PubMed

    Saghafi, Shiva; Pourpak, Zahra; Glocker, Cristina; Nussbaumer, Franziska; Babamahmoodi, Abdolreza; Grimbacher, Bodo; Moin, Mostafa

    2015-04-01

    Hyperimmunoglobulin E Syndrome (HIES) is a complex primary immunodeficiency characterized by both immunologic and non-immunologic manifestations. High serum IgE level, eosinophilia, eczema, recurrent skin and lung infections constitute the immunologic profile of HIES, whereas characteristic facial appearance, scoliosis, retained primary teeth, joint hyperextensibility, bone fractures following minimal trauma and craniosynostosis are the main non-immunologic manifestations. The diagnosis of HIES cannot be made by routine immunologic tests. As the main characteristic laboratory abnormalities of this syndrome are highly elevated serum IgE levels and eosinophilia; both features have a broad spectrum of differential diagnosis. The purpose of this essay was presenting the best way for diagnosis management of HIES. Based on the genetic reports of patients of the Center for Chronic Immunodeficiency (CCI) as a single center experience, and applying project management (PM) in health care research projects, we sought the best way for a rapid diagnosis of HIES. The combination of project management principles with immunologic and genetic knowledge to better define the laboratory and clinical diagnosis lead to an improvement of the management of patients with HIES. These results are shown in one "Decision Tree" which is based on 342 genetic reports of the CCI during the past ten years. It is necessary to facilitate the diagnostic analysis of suspected HIES patients; applying project management in health care research projects provides a better and more accurate diagnosis eventually leading to a better patients' care. This Abstract was presented at 16th Biennial Meeting of the European Society for Immunodeficiencies (ESID 2014), Prague, Czech Republic. PMID:25780878

  15. The use of multiple models in case-based diagnosis

    NASA Technical Reports Server (NTRS)

    Karamouzis, Stamos T.; Feyock, Stefan

    1993-01-01

    The work described in this paper has as its goal the integration of a number of reasoning techniques into a unified intelligent information system that will aid flight crews with malfunction diagnosis and prognostication. One of these approaches involves using the extensive archive of information contained in aircraft accident reports along with various models of the aircraft as the basis for case-based reasoning about malfunctions. Case-based reasoning draws conclusions on the basis of similarities between the present situation and prior experience. We maintain that the ability of a CBR program to reason about physical systems is significantly enhanced by the addition to the CBR program of various models. This paper describes the diagnostic concepts implemented in a prototypical case based reasoner that operates in the domain of in-flight fault diagnosis, the various models used in conjunction with the reasoner's CBR component, and results from a preliminary evaluation.

  16. Imaging-based diagnosis of acute renal allograft rejection

    PubMed Central

    Thölking, Gerold; Schuette-Nuetgen, Katharina; Kentrup, Dominik; Pawelski, Helga; Reuter, Stefan

    2016-01-01

    Kidney transplantation is the best available treatment for patients with end stage renal disease. Despite the introduction of effective immunosuppressant drugs, episodes of acute allograft rejection still endanger graft survival. Since efficient treatment of acute rejection is available, rapid diagnosis of this reversible graft injury is essential. For diagnosis of rejection, invasive core needle biopsy of the graft is the “gold-standard”. However, biopsy carries the risk of significant graft injury and is not immediately feasible in patients taking anticoagulants. Therefore, a non-invasive tool assessing the whole organ for specific and fast detection of acute allograft rejection is desirable. We herein review current imaging-based state of the art approaches for non-invasive diagnostics of acute renal transplant rejection. We especially focus on new positron emission tomography-based as well as targeted ultrasound-based methods. PMID:27011915

  17. Highly accurate coating composition control during co-sputtering, based on controlling plasma chromaticity

    SciTech Connect

    Anguita, J.V.; Thwaites, M.; Holton, B.; Hockley, P.; Holton, B.; Rand, S.

    2005-03-01

    Highly accurate control of sputtering processes is of paramount importance to industry. Plasma diagnostic equipment based on spectroscopic methods such as optical emission spectroscopy (OES) have been commercially available for many years and have the ability to deliver a high level of accuracy. Despite this, their complexity, demand for operator time, and disregard for the vast majority of the optical emission spectrum have rendered them as unpopular, and they are rarely used in manufacturing lines. This article introduces the measurement of the chromaticity of the plasma as a new method of analysis, as an alternative to OES. This method is simple, while maintaining a high level of sensitivity. Chromaticity monitors a wide range of the optical emission spectrum, obtaining a large amount of process information. It also averages and simplifies the data, making them easier to analyze.

  18. Generating clock signals for a cycle accurate, cycle reproducible FPGA based hardware accelerator

    DOEpatents

    Asaad, Sameth W.; Kapur, Mohit

    2016-01-05

    A method, system and computer program product are disclosed for generating clock signals for a cycle accurate FPGA based hardware accelerator used to simulate operations of a device-under-test (DUT). In one embodiment, the DUT includes multiple device clocks generating multiple device clock signals at multiple frequencies and at a defined frequency ratio; and the FPG hardware accelerator includes multiple accelerator clocks generating multiple accelerator clock signals to operate the FPGA hardware accelerator to simulate the operations of the DUT. In one embodiment, operations of the DUT are mapped to the FPGA hardware accelerator, and the accelerator clock signals are generated at multiple frequencies and at the defined frequency ratio of the frequencies of the multiple device clocks, to maintain cycle accuracy between the DUT and the FPGA hardware accelerator. In an embodiment, the FPGA hardware accelerator may be used to control the frequencies of the multiple device clocks.

  19. Highly accurate and fast optical penetration-based silkworm gender separation system

    NASA Astrophysics Data System (ADS)

    Kamtongdee, Chakkrit; Sumriddetchkajorn, Sarun; Chanhorm, Sataporn

    2015-07-01

    Based on our research work in the last five years, this paper highlights our innovative optical sensing system that can identify and separate silkworm gender highly suitable for sericulture industry. The key idea relies on our proposed optical penetration concepts and once combined with simple image processing operations leads to high accuracy in identifying of silkworm gender. Inside the system, there are electronic and mechanical parts that assist in controlling the overall system operation, processing the optical signal, and separating the female from male silkworm pupae. With current system performance, we achieve a very highly accurate more than 95% in identifying gender of silkworm pupae with an average system operational speed of 30 silkworm pupae/minute. Three of our systems are already in operation at Thailand's Queen Sirikit Sericulture Centers.

  20. A fast and accurate PCA based radiative transfer model: Extension to the broadband shortwave region

    NASA Astrophysics Data System (ADS)

    Kopparla, Pushkar; Natraj, Vijay; Spurr, Robert; Shia, Run-Lie; Crisp, David; Yung, Yuk L.

    2016-04-01

    Accurate radiative transfer (RT) calculations are necessary for many earth-atmosphere applications, from remote sensing retrieval to climate modeling. A Principal Component Analysis (PCA)-based spectral binning method has been shown to provide an order of magnitude increase in computational speed while maintaining an overall accuracy of 0.01% (compared to line-by-line calculations) over narrow spectral bands. In this paper, we have extended the PCA method for RT calculations over the entire shortwave region of the spectrum from 0.3 to 3 microns. The region is divided into 33 spectral fields covering all major gas absorption regimes. We find that the RT performance runtimes are shorter by factors between 10 and 100, while root mean square errors are of order 0.01%.

  1. Accurate mass - time tag library for LC/MS-based metabolite profiling of medicinal plants

    PubMed Central

    Cuthbertson, Daniel J.; Johnson, Sean R.; Piljac-Žegarac, Jasenka; Kappel, Julia; Schäfer, Sarah; Wüst, Matthias; Ketchum, Raymond E. B.; Croteau, Rodney B.; Marques, Joaquim V.; Davin, Laurence B.; Lewis, Norman G.; Rolf, Megan; Kutchan, Toni M.; Soejarto, D. Doel; Lange, B. Markus

    2013-01-01

    We report the development and testing of an accurate mass – time (AMT) tag approach for the LC/MS-based identification of plant natural products (PNPs) in complex extracts. An AMT tag library was developed for approximately 500 PNPs with diverse chemical structures, detected in electrospray and atmospheric pressure chemical ionization modes (both positive and negative polarities). In addition, to enable peak annotations with high confidence, MS/MS spectra were acquired with three different fragmentation energies. The LC/MS and MS/MS data sets were integrated into online spectral search tools and repositories (Spektraris and MassBank), thus allowing users to interrogate their own data sets for the potential presence of PNPs. The utility of the AMT tag library approach is demonstrated by the detection and annotation of active principles in 27 different medicinal plant species with diverse chemical constituents. PMID:23597491

  2. PRIMAL: Fast and Accurate Pedigree-based Imputation from Sequence Data in a Founder Population

    PubMed Central

    Livne, Oren E.; Han, Lide; Alkorta-Aranburu, Gorka; Wentworth-Sheilds, William; Abney, Mark; Ober, Carole; Nicolae, Dan L.

    2015-01-01

    Founder populations and large pedigrees offer many well-known advantages for genetic mapping studies, including cost-efficient study designs. Here, we describe PRIMAL (PedigRee IMputation ALgorithm), a fast and accurate pedigree-based phasing and imputation algorithm for founder populations. PRIMAL incorporates both existing and original ideas, such as a novel indexing strategy of Identity-By-Descent (IBD) segments based on clique graphs. We were able to impute the genomes of 1,317 South Dakota Hutterites, who had genome-wide genotypes for ~300,000 common single nucleotide variants (SNVs), from 98 whole genome sequences. Using a combination of pedigree-based and LD-based imputation, we were able to assign 87% of genotypes with >99% accuracy over the full range of allele frequencies. Using the IBD cliques we were also able to infer the parental origin of 83% of alleles, and genotypes of deceased recent ancestors for whom no genotype information was available. This imputed data set will enable us to better study the relative contribution of rare and common variants on human phenotypes, as well as parental origin effect of disease risk alleles in >1,000 individuals at minimal cost. PMID:25735005

  3. Fault diagnosis for stator winding bar hollow strand blockage of turbogenerators based on data fusion

    NASA Astrophysics Data System (ADS)

    Wang, Xianpei; Dai, Zheng Y.; Liu, Zhenxing; Chen, Yalin

    2003-09-01

    Stator Winding Bar Hollow Strand Blockage (SWBHSB) is one of the main faults for large turbo-generators with water and hydrogen cooling system. It will lead to increasing water temperature at the bar exit which may cause hidden troubles for turbo-generator's security. According to a three-layer-structural model of data fusion, this paper presents a fault diagnosis method for turbo-generators based on data fusion technology. Firstly, a bp network on pixel level fusion is set up, in which several temperature parameters at the bar exit are accurately computed. Then in feature level fusion, the fingerprints are distilled from the result of pixel level fusion. Finally, decision level fusion gives a fault diagnosis for the measuring channels and thermometric components. This method can effectively avoid problems such as misinformation and fake report.

  4. How Accurate Are Patients at Diagnosing the Cause of Their Knee Pain With the Help of a Web-based Symptom Checker?

    PubMed Central

    Bisson, Leslie J.; Komm, Jorden T.; Bernas, Geoffrey A.; Fineberg, Marc S.; Marzo, John M.; Rauh, Michael A.; Smolinski, Robert J.; Wind, William M.

    2016-01-01

    Background: Researching medical information is the third most popular activity online, and there are a variety of web-based symptom checker programs available. Purpose: This study evaluated a patient’s ability to self-diagnose their knee pain from a list of possible diagnoses supplied by an accurate symptom checker. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: All patients older than 18 years who presented to the office of 7 different fellowship-trained sports medicine surgeons over an 8-month period with a complaint of knee pain were asked to participate. A web-based symptom checker for knee pain was used; the program has a reported accuracy of 89%. The symptom checker generates a list of potential diagnoses after patients enter symptoms and links each diagnosis to informative content. After exploring the informative content, patients selected all diagnoses they felt could explain their symptoms. Each patient was later examined by a physician who was blinded to the differential generated by the program as well as the patient-selected diagnoses. A blinded third party compared the diagnoses generated by the program with those selected by the patient as well as the diagnoses determined by the physician. The level of matching between the patient-selected diagnoses and the physician’s diagnoses determined the patient’s ability to correctly diagnose their knee pain. Results: There were 163 male and 165 female patients, with a mean age of 48 years (range, 18-76 years). The program generated a mean 6.6 diagnoses (range, 2-15) per patient. Each patient had a mean 1.7 physician diagnoses (range, 1-4). Patients selected a mean 2 diagnoses (range, 1-9). The patient-selected diagnosis matched the physician’s diagnosis 58% of the time. Conclusion: With the aid of an accurate symptom checker, patients were able to correctly identify the cause of their knee pain 58% of the time. PMID:26962542

  5. Sensor-based fault diagnosis in a flight expert system

    NASA Technical Reports Server (NTRS)

    Ali, M.; Scharnhorst, D. A.

    1985-01-01

    A prototype of a knowledge-based flight expert system (FLES) has been developed to assist airplane pilots in monitoring, analyzing, and diagnosing faults and to provide support in reducing the pilot's own mistakes. A sensor simulation model has been developed to provide FLES with the airplane status information during the diagnostic process. The simulator is based partly on the Advanced Concept System (ACS), a future-generation airplane, and partly on the Boeing 737, an existing airplane. The architecture of FLES contains several subsystems. One of the major subsystems performs fault diagnosis in the electrical system of the ACS. This paper describes the mechanism and functionality of the automatic diagnosis performed in this expert system.

  6. Providing community-based health practitioners with timely and accurate discharge medicines information

    PubMed Central

    2012-01-01

    Background Accurate and timely medication information at the point of discharge is essential for continuity of care. There are scarce data on the clinical significance if poor quality medicines information is passed to the next episode of care. This study aimed to compare the number and clinical significance of medication errors and omission in discharge medicines information, and the timeliness of delivery of this information to community-based health practitioners, between the existing Hospital Discharge Summary (HDS) and a pharmacist prepared Medicines Information Transfer Fax (MITF). Method The study used a sample of 80 hospital patients who were at high risk of medication misadventure, and who had a MITF completed in the study period June – October 2009 at a tertiary referral hospital. The medicines information in participating patients’ MITFs was validated against their Discharge Prescriptions (DP). Medicines information in each patient’s HDS was then compared with their validated MITF. An expert clinical panel reviewed identified medication errors and omissions to determine their clinical significance. The time between patient discharge and the dispatching of the MITF and the HDS to each patient’s community-based practitioners was calculated from hospital records. Results DPs for 77 of the 80 patients were available for comparison with their MITFs. Medicines information in 71 (92%) of the MITFs matched that of the DP. Comparison of the HDS against the MITF revealed that no HDS was prepared for 16 (21%) patients. Of the remaining 61 patients; 33 (54%), had required medications omitted and 38 (62%) had medication errors in their HDS. The Clinical Panel rated the significance of errors or omissions for 70 patients (16 with no HDS prepared and 54 who’s HDS was inconsistent with the validated MITF). In 17 patients the error or omission was rated as insignificant to minor; 23 minor to moderate; 24 moderate to major and 6 major to catastrophic. 28 (35

  7. A hybrid MEMS-based microfluidic system for cancer diagnosis

    NASA Astrophysics Data System (ADS)

    Ortiz, Pedro; Keegan, Neil; Spoors, Julia; Hedley, John; Harris, Alun; Burdess, Jim; Burnett, Richard; Velten, Thomas; Biehl, Margit; Knoll, Thorsten; Haberer, Werner; Solomon, Matthew; Campitelli, Andrew; McNeil, Calum

    2008-12-01

    A microfluidic system for cancer diagnosis based around a core MEMS biosensor technology is presented in this paper. The principle of the MEMS biosensor is introduced and the functionalisation strategy for cancer marker recognition is described. In addition, the successful packaging and integration of functional MEMS biosensor devices are reported herein. This ongoing work represents one of the first hybrid systems to integrate a PCB packaged silicon MEMS device into a disposable microfluidic cartridge.

  8. Centered Kernel Alignment Enhancing Neural Network Pretraining for MRI-Based Dementia Diagnosis

    PubMed Central

    Cárdenas-Peña, David; Collazos-Huertas, Diego; Castellanos-Dominguez, German

    2016-01-01

    Dementia is a growing problem that affects elderly people worldwide. More accurate evaluation of dementia diagnosis can help during the medical examination. Several methods for computer-aided dementia diagnosis have been proposed using resonance imaging scans to discriminate between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and healthy controls (NC). Nonetheless, the computer-aided diagnosis is especially challenging because of the heterogeneous and intermediate nature of MCI. We address the automated dementia diagnosis by introducing a novel supervised pretraining approach that takes advantage of the artificial neural network (ANN) for complex classification tasks. The proposal initializes an ANN based on linear projections to achieve more discriminating spaces. Such projections are estimated by maximizing the centered kernel alignment criterion that assesses the affinity between the resonance imaging data kernel matrix and the label target matrix. As a result, the performed linear embedding allows accounting for features that contribute the most to the MCI class discrimination. We compare the supervised pretraining approach to two unsupervised initialization methods (autoencoders and Principal Component Analysis) and against the best four performing classification methods of the 2014 CADDementia challenge. As a result, our proposal outperforms all the baselines (7% of classification accuracy and area under the receiver-operating-characteristic curve) at the time it reduces the class biasing. PMID:27148392

  9. Towards more accurate numerical modeling of impedance based high frequency harmonic vibration

    NASA Astrophysics Data System (ADS)

    Lim, Yee Yan; Kiong Soh, Chee

    2014-03-01

    The application of smart materials in various fields of engineering has recently become increasingly popular. For instance, the high frequency based electromechanical impedance (EMI) technique employing smart piezoelectric materials is found to be versatile in structural health monitoring (SHM). Thus far, considerable efforts have been made to study and improve the technique. Various theoretical models of the EMI technique have been proposed in an attempt to better understand its behavior. So far, the three-dimensional (3D) coupled field finite element (FE) model has proved to be the most accurate. However, large discrepancies between the results of the FE model and experimental tests, especially in terms of the slope and magnitude of the admittance signatures, continue to exist and are yet to be resolved. This paper presents a series of parametric studies using the 3D coupled field finite element method (FEM) on all properties of materials involved in the lead zirconate titanate (PZT) structure interaction of the EMI technique, to investigate their effect on the admittance signatures acquired. FE model updating is then performed by adjusting the parameters to match the experimental results. One of the main reasons for the lower accuracy, especially in terms of magnitude and slope, of previous FE models is the difficulty in determining the damping related coefficients and the stiffness of the bonding layer. In this study, using the hysteretic damping model in place of Rayleigh damping, which is used by most researchers in this field, and updated bonding stiffness, an improved and more accurate FE model is achieved. The results of this paper are expected to be useful for future study of the subject area in terms of research and application, such as modeling, design and optimization.

  10. A Quadratic Spline based Interface (QUASI) reconstruction algorithm for accurate tracking of two-phase flows

    NASA Astrophysics Data System (ADS)

    Diwakar, S. V.; Das, Sarit K.; Sundararajan, T.

    2009-12-01

    A new Quadratic Spline based Interface (QUASI) reconstruction algorithm is presented which provides an accurate and continuous representation of the interface in a multiphase domain and facilitates the direct estimation of local interfacial curvature. The fluid interface in each of the mixed cells is represented by piecewise parabolic curves and an initial discontinuous PLIC approximation of the interface is progressively converted into a smooth quadratic spline made of these parabolic curves. The conversion is achieved by a sequence of predictor-corrector operations enforcing function ( C0) and derivative ( C1) continuity at the cell boundaries using simple analytical expressions for the continuity requirements. The efficacy and accuracy of the current algorithm has been demonstrated using standard test cases involving reconstruction of known static interface shapes and dynamically evolving interfaces in prescribed flow situations. These benchmark studies illustrate that the present algorithm performs excellently as compared to the other interface reconstruction methods available in literature. Quadratic rate of error reduction with respect to grid size has been observed in all the cases with curved interface shapes; only in situations where the interface geometry is primarily flat, the rate of convergence becomes linear with the mesh size. The flow algorithm implemented in the current work is designed to accurately balance the pressure gradients with the surface tension force at any location. As a consequence, it is able to minimize spurious flow currents arising from imperfect normal stress balance at the interface. This has been demonstrated through the standard test problem of an inviscid droplet placed in a quiescent medium. Finally, the direct curvature estimation ability of the current algorithm is illustrated through the coupled multiphase flow problem of a deformable air bubble rising through a column of water.

  11. Accurate and interpretable nanoSAR models from genetic programming-based decision tree construction approaches.

    PubMed

    Oksel, Ceyda; Winkler, David A; Ma, Cai Y; Wilkins, Terry; Wang, Xue Z

    2016-09-01

    The number of engineered nanomaterials (ENMs) being exploited commercially is growing rapidly, due to the novel properties they exhibit. Clearly, it is important to understand and minimize any risks to health or the environment posed by the presence of ENMs. Data-driven models that decode the relationships between the biological activities of ENMs and their physicochemical characteristics provide an attractive means of maximizing the value of scarce and expensive experimental data. Although such structure-activity relationship (SAR) methods have become very useful tools for modelling nanotoxicity endpoints (nanoSAR), they have limited robustness and predictivity and, most importantly, interpretation of the models they generate is often very difficult. New computational modelling tools or new ways of using existing tools are required to model the relatively sparse and sometimes lower quality data on the biological effects of ENMs. The most commonly used SAR modelling methods work best with large datasets, are not particularly good at feature selection, can be relatively opaque to interpretation, and may not account for nonlinearity in the structure-property relationships. To overcome these limitations, we describe the application of a novel algorithm, a genetic programming-based decision tree construction tool (GPTree) to nanoSAR modelling. We demonstrate the use of GPTree in the construction of accurate and interpretable nanoSAR models by applying it to four diverse literature datasets. We describe the algorithm and compare model results across the four studies. We show that GPTree generates models with accuracies equivalent to or superior to those of prior modelling studies on the same datasets. GPTree is a robust, automatic method for generation of accurate nanoSAR models with important advantages that it works with small datasets, automatically selects descriptors, and provides significantly improved interpretability of models. PMID:26956430

  12. Pairagon: a highly accurate, HMM-based cDNA-to-genome aligner

    PubMed Central

    Lu, David V.; Brown, Randall H.; Arumugam, Manimozhiyan; Brent, Michael R.

    2009-01-01

    Motivation: The most accurate way to determine the intron–exon structures in a genome is to align spliced cDNA sequences to the genome. Thus, cDNA-to-genome alignment programs are a key component of most annotation pipelines. The scoring system used to choose the best alignment is a primary determinant of alignment accuracy, while heuristics that prevent consideration of certain alignments are a primary determinant of runtime and memory usage. Both accuracy and speed are important considerations in choosing an alignment algorithm, but scoring systems have received much less attention than heuristics. Results: We present Pairagon, a pair hidden Markov model based cDNA-to-genome alignment program, as the most accurate aligner for sequences with high- and low-identity levels. We conducted a series of experiments testing alignment accuracy with varying sequence identity. We first created ‘perfect’ simulated cDNA sequences by splicing the sequences of exons in the reference genome sequences of fly and human. The complete reference genome sequences were then mutated to various degrees using a realistic mutation simulator and the perfect cDNAs were aligned to them using Pairagon and 12 other aligners. To validate these results with natural sequences, we performed cross-species alignment using orthologous transcripts from human, mouse and rat. We found that aligner accuracy is heavily dependent on sequence identity. For sequences with 100% identity, Pairagon achieved accuracy levels of >99.6%, with one quarter of the errors of any other aligner. Furthermore, for human/mouse alignments, which are only 85% identical, Pairagon achieved 87% accuracy, higher than any other aligner. Availability: Pairagon source and executables are freely available at http://mblab.wustl.edu/software/pairagon/ Contact: davidlu@wustl.edu; brent@cse.wustl.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19414532

  13. Digitalized accurate modeling of SPCB with multi-spiral surface based on CPC algorithm

    NASA Astrophysics Data System (ADS)

    Huang, Yanhua; Gu, Lizhi

    2015-09-01

    The main methods of the existing multi-spiral surface geometry modeling include spatial analytic geometry algorithms, graphical method, interpolation and approximation algorithms. However, there are some shortcomings in these modeling methods, such as large amount of calculation, complex process, visible errors, and so on. The above methods have, to some extent, restricted the design and manufacture of the premium and high-precision products with spiral surface considerably. This paper introduces the concepts of the spatially parallel coupling with multi-spiral surface and spatially parallel coupling body. The typical geometry and topological features of each spiral surface forming the multi-spiral surface body are determined, by using the extraction principle of datum point cluster, the algorithm of coupling point cluster by removing singular point, and the "spatially parallel coupling" principle based on the non-uniform B-spline for each spiral surface. The orientation and quantitative relationships of datum point cluster and coupling point cluster in Euclidean space are determined accurately and in digital description and expression, coupling coalescence of the surfaces with multi-coupling point clusters under the Pro/E environment. The digitally accurate modeling of spatially parallel coupling body with multi-spiral surface is realized. The smooth and fairing processing is done to the three-blade end-milling cutter's end section area by applying the principle of spatially parallel coupling with multi-spiral surface, and the alternative entity model is processed in the four axis machining center after the end mill is disposed. And the algorithm is verified and then applied effectively to the transition area among the multi-spiral surface. The proposed model and algorithms may be used in design and manufacture of the multi-spiral surface body products, as well as in solving essentially the problems of considerable modeling errors in computer graphics and

  14. mGene: accurate SVM-based gene finding with an application to nematode genomes.

    PubMed

    Schweikert, Gabriele; Zien, Alexander; Zeller, Georg; Behr, Jonas; Dieterich, Christoph; Ong, Cheng Soon; Philips, Petra; De Bona, Fabio; Hartmann, Lisa; Bohlen, Anja; Krüger, Nina; Sonnenburg, Sören; Rätsch, Gunnar

    2009-11-01

    We present a highly accurate gene-prediction system for eukaryotic genomes, called mGene. It combines in an unprecedented manner the flexibility of generalized hidden Markov models (gHMMs) with the predictive power of modern machine learning methods, such as Support Vector Machines (SVMs). Its excellent performance was proved in an objective competition based on the genome of the nematode Caenorhabditis elegans. Considering the average of sensitivity and specificity, the developmental version of mGene exhibited the best prediction performance on nucleotide, exon, and transcript level for ab initio and multiple-genome gene-prediction tasks. The fully developed version shows superior performance in 10 out of 12 evaluation criteria compared with the other participating gene finders, including Fgenesh++ and Augustus. An in-depth analysis of mGene's genome-wide predictions revealed that approximately 2200 predicted genes were not contained in the current genome annotation. Testing a subset of 57 of these genes by RT-PCR and sequencing, we confirmed expression for 24 (42%) of them. mGene missed 300 annotated genes, out of which 205 were unconfirmed. RT-PCR testing of 24 of these genes resulted in a success rate of merely 8%. These findings suggest that even the gene catalog of a well-studied organism such as C. elegans can be substantially improved by mGene's predictions. We also provide gene predictions for the four nematodes C. briggsae, C. brenneri, C. japonica, and C. remanei. Comparing the resulting proteomes among these organisms and to the known protein universe, we identified many species-specific gene inventions. In a quality assessment of several available annotations for these genomes, we find that mGene's predictions are most accurate. PMID:19564452

  15. Computer-aided diagnosis workstation and network system for chest diagnosis based on multislice CT images

    NASA Astrophysics Data System (ADS)

    Satoh, Hitoshi; Niki, Noboru; Eguchi, Kenji; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru

    2008-03-01

    Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images, a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification and a vertebra body analysis algorithm for quantitative evaluation of osteoporosis likelihood by using helical CT scanner for the lung cancer mass screening. The function to observe suspicious shadow in detail are provided in computer-aided diagnosis workstation with these screening algorithms. We also have developed the telemedicine network by using Web medical image conference system with the security improvement of images transmission, Biometric fingerprint authentication system and Biometric face authentication system. Biometric face authentication used on site of telemedicine makes "Encryption of file" and Success in login" effective. As a result, patients' private information is protected. Based on these diagnostic assistance methods, we have developed a new computer-aided workstation and a new telemedicine network that can display suspected lesions three-dimensionally in a short time. The results of this study indicate that our radiological information system without film by using computer-aided diagnosis workstation and our telemedicine network system can increase diagnostic speed, diagnostic accuracy and security improvement of medical information.

  16. Development and Evaluation of Reference Standards for Image-based Telemedicine Diagnosis and Clinical Research Studies in Ophthalmology

    PubMed Central

    Ryan, Michael C.; Ostmo, Susan; Jonas, Karyn; Berrocal, Audina; Drenser, Kimberly; Horowitz, Jason; Lee, Thomas C.; Simmons, Charles; Martinez-Castellanos, Maria-Ana; Chan, R.V. Paul; Chiang, Michael F.

    2014-01-01

    Information systems managing image-based data for telemedicine or clinical research applications require a reference standard representing the correct diagnosis. Accurate reference standards are difficult to establish because of imperfect agreement among physicians, and discrepancies between clinical vs. image-based diagnosis. This study is designed to describe the development and evaluation of reference standards for image-based diagnosis, which combine diagnostic impressions of multiple image readers with the actual clinical diagnoses. We show that agreement between image reading and clinical examinations was imperfect (689 [32%] discrepancies in 2148 image readings), as was inter-reader agreement (kappa 0.490-0.652). This was improved by establishing an image-based reference standard defined as the majority diagnosis given by three readers (13% discrepancies with image readers). It was further improved by establishing an overall reference standard that incorporated the clinical diagnosis (10% discrepancies with image readers). These principles of establishing reference standards may be applied to improve robustness of real-world systems supporting image-based diagnosis. PMID:25954463

  17. Gold nanospikes based microsensor as a highly accurate mercury emission monitoring system

    NASA Astrophysics Data System (ADS)

    Sabri, Ylias M.; Ippolito, Samuel J.; Tardio, James; Bansal, Vipul; O'Mullane, Anthony P.; Bhargava, Suresh K.

    2014-10-01

    Anthropogenic elemental mercury (Hg0) emission is a serious worldwide environmental problem due to the extreme toxicity of the heavy metal to humans, plants and wildlife. Development of an accurate and cheap microsensor based online monitoring system which can be integrated as part of Hg0 removal and control processes in industry is still a major challenge. Here, we demonstrate that forming Au nanospike structures directly onto the electrodes of a quartz crystal microbalance (QCM) using a novel electrochemical route results in a self-regenerating, highly robust, stable, sensitive and selective Hg0 vapor sensor. The data from a 127 day continuous test performed in the presence of volatile organic compounds and high humidity levels, showed that the sensor with an electrodeposted sensitive layer had 260% higher response magnitude, 3.4 times lower detection limit (~22 μg/m3 or ~2.46 ppbv) and higher accuracy (98% Vs 35%) over a Au control based QCM (unmodified) when exposed to a Hg0 vapor concentration of 10.55 mg/m3 at 101°C. Statistical analysis of the long term data showed that the nano-engineered Hg0 sorption sites on the developed Au nanospikes sensitive layer play a critical role in the enhanced sensitivity and selectivity of the developed sensor towards Hg0 vapor.

  18. Efficient and Accurate OTU Clustering with GPU-Based Sequence Alignment and Dynamic Dendrogram Cutting.

    PubMed

    Nguyen, Thuy-Diem; Schmidt, Bertil; Zheng, Zejun; Kwoh, Chee-Keong

    2015-01-01

    De novo clustering is a popular technique to perform taxonomic profiling of a microbial community by grouping 16S rRNA amplicon reads into operational taxonomic units (OTUs). In this work, we introduce a new dendrogram-based OTU clustering pipeline called CRiSPy. The key idea used in CRiSPy to improve clustering accuracy is the application of an anomaly detection technique to obtain a dynamic distance cutoff instead of using the de facto value of 97 percent sequence similarity as in most existing OTU clustering pipelines. This technique works by detecting an abrupt change in the merging heights of a dendrogram. To produce the output dendrograms, CRiSPy employs the OTU hierarchical clustering approach that is computed on a genetic distance matrix derived from an all-against-all read comparison by pairwise sequence alignment. However, most existing dendrogram-based tools have difficulty processing datasets larger than 10,000 unique reads due to high computational complexity. We address this difficulty by developing two efficient algorithms for CRiSPy: a compute-efficient GPU-accelerated parallel algorithm for pairwise distance matrix computation and a memory-efficient hierarchical clustering algorithm. Our experiments on various datasets with distinct attributes show that CRiSPy is able to produce more accurate OTU groupings than most OTU clustering applications. PMID:26451819

  19. Accurate and Fast Simulation of Channel Noise in Conductance-Based Model Neurons by Diffusion Approximation

    PubMed Central

    Linaro, Daniele; Storace, Marco; Giugliano, Michele

    2011-01-01

    Stochastic channel gating is the major source of intrinsic neuronal noise whose functional consequences at the microcircuit- and network-levels have been only partly explored. A systematic study of this channel noise in large ensembles of biophysically detailed model neurons calls for the availability of fast numerical methods. In fact, exact techniques employ the microscopic simulation of the random opening and closing of individual ion channels, usually based on Markov models, whose computational loads are prohibitive for next generation massive computer models of the brain. In this work, we operatively define a procedure for translating any Markov model describing voltage- or ligand-gated membrane ion-conductances into an effective stochastic version, whose computer simulation is efficient, without compromising accuracy. Our approximation is based on an improved Langevin-like approach, which employs stochastic differential equations and no Montecarlo methods. As opposed to an earlier proposal recently debated in the literature, our approximation reproduces accurately the statistical properties of the exact microscopic simulations, under a variety of conditions, from spontaneous to evoked response features. In addition, our method is not restricted to the Hodgkin-Huxley sodium and potassium currents and is general for a variety of voltage- and ligand-gated ion currents. As a by-product, the analysis of the properties emerging in exact Markov schemes by standard probability calculus enables us for the first time to analytically identify the sources of inaccuracy of the previous proposal, while providing solid ground for its modification and improvement we present here. PMID:21423712

  20. Base-resolution methylation patterns accurately predict transcription factor bindings in vivo

    PubMed Central

    Xu, Tianlei; Li, Ben; Zhao, Meng; Szulwach, Keith E.; Street, R. Craig; Lin, Li; Yao, Bing; Zhang, Feiran; Jin, Peng; Wu, Hao; Qin, Zhaohui S.

    2015-01-01

    Detecting in vivo transcription factor (TF) binding is important for understanding gene regulatory circuitries. ChIP-seq is a powerful technique to empirically define TF binding in vivo. However, the multitude of distinct TFs makes genome-wide profiling for them all labor-intensive and costly. Algorithms for in silico prediction of TF binding have been developed, based mostly on histone modification or DNase I hypersensitivity data in conjunction with DNA motif and other genomic features. However, technical limitations of these methods prevent them from being applied broadly, especially in clinical settings. We conducted a comprehensive survey involving multiple cell lines, TFs, and methylation types and found that there are intimate relationships between TF binding and methylation level changes around the binding sites. Exploiting the connection between DNA methylation and TF binding, we proposed a novel supervised learning approach to predict TF–DNA interaction using data from base-resolution whole-genome methylation sequencing experiments. We devised beta-binomial models to characterize methylation data around TF binding sites and the background. Along with other static genomic features, we adopted a random forest framework to predict TF–DNA interaction. After conducting comprehensive tests, we saw that the proposed method accurately predicts TF binding and performs favorably versus competing methods. PMID:25722376

  1. A Novel PCR-Based Approach for Accurate Identification of Vibrio parahaemolyticus.

    PubMed

    Li, Ruichao; Chiou, Jiachi; Chan, Edward Wai-Chi; Chen, Sheng

    2016-01-01

    A PCR-based assay was developed for more accurate identification of Vibrio parahaemolyticus through targeting the bla CARB-17 like element, an intrinsic β-lactamase gene that may also be regarded as a novel species-specific genetic marker of this organism. Homologous analysis showed that bla CARB-17 like genes were more conservative than the tlh, toxR and atpA genes, the genetic markers commonly used as detection targets in identification of V. parahaemolyticus. Our data showed that this bla CARB-17-specific PCR-based detection approach consistently achieved 100% specificity, whereas PCR targeting the tlh and atpA genes occasionally produced false positive results. Furthermore, a positive result of this test is consistently associated with an intrinsic ampicillin resistance phenotype of the test organism, presumably conferred by the products of bla CARB-17 like genes. We envision that combined analysis of the unique genetic and phenotypic characteristics conferred by bla CARB-17 shall further enhance the detection specificity of this novel yet easy-to-use detection approach to a level superior to the conventional methods used in V. parahaemolyticus detection and identification. PMID:26858713

  2. Gold nanospikes based microsensor as a highly accurate mercury emission monitoring system

    PubMed Central

    Sabri, Ylias M.; Ippolito, Samuel J.; Tardio, James; Bansal, Vipul; O'Mullane, Anthony P.; Bhargava, Suresh K.

    2014-01-01

    Anthropogenic elemental mercury (Hg0) emission is a serious worldwide environmental problem due to the extreme toxicity of the heavy metal to humans, plants and wildlife. Development of an accurate and cheap microsensor based online monitoring system which can be integrated as part of Hg0 removal and control processes in industry is still a major challenge. Here, we demonstrate that forming Au nanospike structures directly onto the electrodes of a quartz crystal microbalance (QCM) using a novel electrochemical route results in a self-regenerating, highly robust, stable, sensitive and selective Hg0 vapor sensor. The data from a 127 day continuous test performed in the presence of volatile organic compounds and high humidity levels, showed that the sensor with an electrodeposted sensitive layer had 260% higher response magnitude, 3.4 times lower detection limit (~22 μg/m3 or ~2.46 ppbv) and higher accuracy (98% Vs 35%) over a Au control based QCM (unmodified) when exposed to a Hg0 vapor concentration of 10.55 mg/m3 at 101°C. Statistical analysis of the long term data showed that the nano-engineered Hg0 sorption sites on the developed Au nanospikes sensitive layer play a critical role in the enhanced sensitivity and selectivity of the developed sensor towards Hg0 vapor. PMID:25338965

  3. A Novel PCR-Based Approach for Accurate Identification of Vibrio parahaemolyticus

    PubMed Central

    Li, Ruichao; Chiou, Jiachi; Chan, Edward Wai-Chi; Chen, Sheng

    2016-01-01

    A PCR-based assay was developed for more accurate identification of Vibrio parahaemolyticus through targeting the blaCARB-17 like element, an intrinsic β-lactamase gene that may also be regarded as a novel species-specific genetic marker of this organism. Homologous analysis showed that blaCARB-17 like genes were more conservative than the tlh, toxR and atpA genes, the genetic markers commonly used as detection targets in identification of V. parahaemolyticus. Our data showed that this blaCARB-17-specific PCR-based detection approach consistently achieved 100% specificity, whereas PCR targeting the tlh and atpA genes occasionally produced false positive results. Furthermore, a positive result of this test is consistently associated with an intrinsic ampicillin resistance phenotype of the test organism, presumably conferred by the products of blaCARB-17 like genes. We envision that combined analysis of the unique genetic and phenotypic characteristics conferred by blaCARB-17 shall further enhance the detection specificity of this novel yet easy-to-use detection approach to a level superior to the conventional methods used in V. parahaemolyticus detection and identification. PMID:26858713

  4. Application of a diagnosis-based clinical decision guide in patients with neck pain

    PubMed Central

    2011-01-01

    Background Neck pain (NP) is a common cause of disability. Accurate and efficacious methods of diagnosis and treatment have been elusive. A diagnosis-based clinical decision guide (DBCDG; previously referred to as a diagnosis-based clinical decision rule) has been proposed which attempts to provide the clinician with a systematic, evidence-based guide in applying the biopsychosocial model of care. The approach is based on three questions of diagnosis. The purpose of this study is to present the prevalence of findings using the DBCDG in consecutive patients with NP. Methods Demographic, diagnostic and baseline outcome measure data were gathered on a cohort of NP patients examined by one of three examiners trained in the application of the DBCDG. Results Data were gathered on 95 patients. Signs of visceral disease or potentially serious illness were found in 1%. Centralization signs were found in 27%, segmental pain provocation signs were found in 69% and radicular signs were found in 19%. Clinically relevant myofascial signs were found in 22%. Dynamic instability was found in 40%, oculomotor dysfunction in 11.6%, fear beliefs in 31.6%, central pain hypersensitivity in 4%, passive coping in 5% and depression in 2%. Conclusion The DBCDG can be applied in a busy private practice environment. Further studies are needed to investigate clinically relevant means to identify central pain hypersensitivity, oculomotor dysfunction, poor coping and depression, correlations and patterns among the diagnostic components of the DBCDG as well as inter-examiner reliability, validity and efficacy of treatment based on the DBCDG. PMID:21871119

  5. A hierarchical fuzzy rule-based approach to aphasia diagnosis.

    PubMed

    Akbarzadeh-T, Mohammad-R; Moshtagh-Khorasani, Majid

    2007-10-01

    Aphasia diagnosis is a particularly challenging medical diagnostic task due to the linguistic uncertainty and vagueness, inconsistencies in the definition of aphasic syndromes, large number of measurements with imprecision, natural diversity and subjectivity in test objects as well as in opinions of experts who diagnose the disease. To efficiently address this diagnostic process, a hierarchical fuzzy rule-based structure is proposed here that considers the effect of different features of aphasia by statistical analysis in its construction. This approach can be efficient for diagnosis of aphasia and possibly other medical diagnostic applications due to its fuzzy and hierarchical reasoning construction. Initially, the symptoms of the disease which each consists of different features are analyzed statistically. The measured statistical parameters from the training set are then used to define membership functions and the fuzzy rules. The resulting two-layered fuzzy rule-based system is then compared with a back propagating feed-forward neural network for diagnosis of four Aphasia types: Anomic, Broca, Global and Wernicke. In order to reduce the number of required inputs, the technique is applied and compared on both comprehensive and spontaneous speech tests. Statistical t-test analysis confirms that the proposed approach uses fewer Aphasia features while also presenting a significant improvement in terms of accuracy. PMID:17293167

  6. Does ultrasonography accurately diagnose acute cholecystitis? Improving diagnostic accuracy based on a review at a regional hospital

    PubMed Central

    Hwang, Hamish; Marsh, Ian; Doyle, Jason

    2014-01-01

    Background Acute cholecystitis is one of the most common diseases requiring emergency surgery. Ultrasonography is an accurate test for cholelithiasis but has a high false-negative rate for acute cholecystitis. The Murphy sign and laboratory tests performed independently are also not particularly accurate. This study was designed to review the accuracy of ultrasonography for diagnosing acute cholecystitis in a regional hospital. Methods We studied all emergency cholecystectomies performed over a 1-year period. All imaging studies were reviewed by a single radiologist, and all pathology was reviewed by a single pathologist. The reviewers were blinded to each other’s results. Results A total of 107 patients required an emergency cholecystectomy in the study period; 83 of them underwent ultrasonography. Interradiologist agreement was 92% for ultrasonography. For cholelithiasis, ultrasonography had 100% sensitivity, 18% specificity, 81% positive predictive value (PPV) and 100% negative predictive value (NPV). For acute cholecystitis, it had 54% sensitivity, 81% specificity, 85% PPV and 47% NPV. All patients had chronic cholecystitis and 67% had acute cholecystitis on histology. When combined with positive Murphy sign and elevated neutrophil count, an ultrasound showing cholelithiasis or acute cholecystitis yielded a sensitivity of 74%, specificity of 62%, PPV of 80% and NPV of 53% for the diagnosis of acute cholecystitis. Conclusion Ultrasonography alone has a high rate of false-negative studies for acute cholecystitis. However, a higher rate of accurate diagnosis can be achieved using a triad of positive Murphy sign, elevated neutrophil count and an ultrasound showing cholelithiasis or cholecystitis. PMID:24869607

  7. Accurate response surface approximations for weight equations based on structural optimization

    NASA Astrophysics Data System (ADS)

    Papila, Melih

    Accurate weight prediction methods are vitally important for aircraft design optimization. Therefore, designers seek weight prediction techniques with low computational cost and high accuracy, and usually require a compromise between the two. The compromise can be achieved by combining stress analysis and response surface (RS) methodology. While stress analysis provides accurate weight information, RS techniques help to transmit effectively this information to the optimization procedure. The focus of this dissertation is structural weight equations in the form of RS approximations and their accuracy when fitted to results of structural optimizations that are based on finite element analyses. Use of RS methodology filters out the numerical noise in structural optimization results and provides a smooth weight function that can easily be used in gradient-based configuration optimization. In engineering applications RS approximations of low order polynomials are widely used, but the weight may not be modeled well by low-order polynomials, leading to bias errors. In addition, some structural optimization results may have high-amplitude errors (outliers) that may severely affect the accuracy of the weight equation. Statistical techniques associated with RS methodology are sought in order to deal with these two difficulties: (1) high-amplitude numerical noise (outliers) and (2) approximation model inadequacy. The investigation starts with reducing approximation error by identifying and repairing outliers. A potential reason for outliers in optimization results is premature convergence, and outliers of such nature may be corrected by employing different convergence settings. It is demonstrated that outlier repair can lead to accuracy improvements over the more standard approach of removing outliers. The adequacy of approximation is then studied by a modified lack-of-fit approach, and RS errors due to the approximation model are reduced by using higher order polynomials. In

  8. PACS-Based Computer-Aided Detection and Diagnosis

    NASA Astrophysics Data System (ADS)

    Huang, H. K. (Bernie); Liu, Brent J.; Le, Anh HongTu; Documet, Jorge

    The ultimate goal of Picture Archiving and Communication System (PACS)-based Computer-Aided Detection and Diagnosis (CAD) is to integrate CAD results into daily clinical practice so that it becomes a second reader to aid the radiologist's diagnosis. Integration of CAD and Hospital Information System (HIS), Radiology Information System (RIS) or PACS requires certain basic ingredients from Health Level 7 (HL7) standard for textual data, Digital Imaging and Communications in Medicine (DICOM) standard for images, and Integrating the Healthcare Enterprise (IHE) workflow profiles in order to comply with the Health Insurance Portability and Accountability Act (HIPAA) requirements to be a healthcare information system. Among the DICOM standards and IHE workflow profiles, DICOM Structured Reporting (DICOM-SR); and IHE Key Image Note (KIN), Simple Image and Numeric Report (SINR) and Post-processing Work Flow (PWF) are utilized in CAD-HIS/RIS/PACS integration. These topics with examples are presented in this chapter.

  9. BCC skin cancer diagnosis based on texture analysis techniques

    NASA Astrophysics Data System (ADS)

    Chuang, Shao-Hui; Sun, Xiaoyan; Chang, Wen-Yu; Chen, Gwo-Shing; Huang, Adam; Li, Jiang; McKenzie, Frederic D.

    2011-03-01

    In this paper, we present a texture analysis based method for diagnosing the Basal Cell Carcinoma (BCC) skin cancer using optical images taken from the suspicious skin regions. We first extracted the Run Length Matrix and Haralick texture features from the images and used a feature selection algorithm to identify the most effective feature set for the diagnosis. We then utilized a Multi-Layer Perceptron (MLP) classifier to classify the images to BCC or normal cases. Experiments showed that detecting BCC cancer based on optical images is feasible. The best sensitivity and specificity we achieved on our data set were 94% and 95%, respectively.

  10. Intelligent diagnosis of short hydraulic signal based on improved EEMD and SVM with few low-dimensional training samples

    NASA Astrophysics Data System (ADS)

    Zhang, Meijun; Tang, Jian; Zhang, Xiaoming; Zhang, Jiaojiao

    2016-03-01

    The high accurate classification ability of an intelligent diagnosis method often needs a large amount of training samples with high-dimensional eigenvectors, however the characteristics of the signal need to be extracted accurately. Although the existing EMD(empirical mode decomposition) and EEMD(ensemble empirical mode decomposition) are suitable for processing non-stationary and non-linear signals, but when a short signal, such as a hydraulic impact signal, is concerned, their decomposition accuracy become very poor. An improve EEMD is proposed specifically for short hydraulic impact signals. The improvements of this new EEMD are mainly reflected in four aspects, including self-adaptive de-noising based on EEMD, signal extension based on SVM(support vector machine), extreme center fitting based on cubic spline interpolation, and pseudo component exclusion based on cross-correlation analysis. After the energy eigenvector is extracted from the result of the improved EEMD, the fault pattern recognition based on SVM with small amount of low-dimensional training samples is studied. At last, the diagnosis ability of improved EEMD+SVM method is compared with the EEMD+SVM and EMD+SVM methods, and its diagnosis accuracy is distinctly higher than the other two methods no matter the dimension of the eigenvectors are low or high. The improved EEMD is very propitious for the decomposition of short signal, such as hydraulic impact signal, and its combination with SVM has high ability for the diagnosis of hydraulic impact faults.

  11. SIFTER search: a web server for accurate phylogeny-based protein function prediction.

    PubMed

    Sahraeian, Sayed M; Luo, Kevin R; Brenner, Steven E

    2015-07-01

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access to precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. The SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded. PMID:25979264

  12. What input data are needed to accurately model electromagnetic fields from mobile phone base stations?

    PubMed

    Beekhuizen, Johan; Kromhout, Hans; Bürgi, Alfred; Huss, Anke; Vermeulen, Roel

    2015-01-01

    The increase in mobile communication technology has led to concern about potential health effects of radio frequency electromagnetic fields (RF-EMFs) from mobile phone base stations. Different RF-EMF prediction models have been applied to assess population exposure to RF-EMF. Our study examines what input data are needed to accurately model RF-EMF, as detailed data are not always available for epidemiological studies. We used NISMap, a 3D radio wave propagation model, to test models with various levels of detail in building and antenna input data. The model outcomes were compared with outdoor measurements taken in Amsterdam, the Netherlands. Results showed good agreement between modelled and measured RF-EMF when 3D building data and basic antenna information (location, height, frequency and direction) were used: Spearman correlations were >0.6. Model performance was not sensitive to changes in building damping parameters. Antenna-specific information about down-tilt, type and output power did not significantly improve model performance compared with using average down-tilt and power values, or assuming one standard antenna type. We conclude that 3D radio wave propagation modelling is a feasible approach to predict outdoor RF-EMF levels for ranking exposure levels in epidemiological studies, when 3D building data and information on the antenna height, frequency, location and direction are available. PMID:24472756

  13. PSAQ™ standards for accurate MS-based quantification of proteins: from the concept to biomedical applications.

    PubMed

    Picard, Guillaume; Lebert, Dorothée; Louwagie, Mathilde; Adrait, Annie; Huillet, Céline; Vandenesch, François; Bruley, Christophe; Garin, Jérôme; Jaquinod, Michel; Brun, Virginie

    2012-10-01

    Absolute protein quantification, i.e. determining protein concentrations in biological samples, is essential to our understanding of biological and physiopathological phenomena. Protein quantification methods based on the use of antibodies are very effective and widely used. However, over the last ten years, absolute protein quantification by mass spectrometry has attracted considerable interest, particularly for the study of systems biology and as part of biomarker development. This interest is mainly linked to the high multiplexing capacity of MS analysis, and to the availability of stable-isotope-labelled standards for quantification. This article describes the details of how to produce, control the quality and use a specific type of standard: Protein Standard Absolute Quantification (PSAQ™) standards. These standards are whole isotopically labelled proteins, analogues of the proteins to be assayed. PSAQ standards can be added early during sample treatment, thus they can correct for protein losses during sample prefractionation and for incomplete sample digestion. Because of this, quantification of target proteins is very accurate and precise using these standards. To illustrate the advantages of the PSAQ method, and to contribute to the increase in its use, selected applications in the biomedical field are detailed here. PMID:23019168

  14. Regularization Based Iterative Point Match Weighting for Accurate Rigid Transformation Estimation.

    PubMed

    Liu, Yonghuai; De Dominicis, Luigi; Wei, Baogang; Chen, Liang; Martin, Ralph R

    2015-09-01

    Feature extraction and matching (FEM) for 3D shapes finds numerous applications in computer graphics and vision for object modeling, retrieval, morphing, and recognition. However, unavoidable incorrect matches lead to inaccurate estimation of the transformation relating different datasets. Inspired by AdaBoost, this paper proposes a novel iterative re-weighting method to tackle the challenging problem of evaluating point matches established by typical FEM methods. Weights are used to indicate the degree of belief that each point match is correct. Our method has three key steps: (i) estimation of the underlying transformation using weighted least squares, (ii) penalty parameter estimation via minimization of the weighted variance of the matching errors, and (iii) weight re-estimation taking into account both matching errors and information learnt in previous iterations. A comparative study, based on real shapes captured by two laser scanners, shows that the proposed method outperforms four other state-of-the-art methods in terms of evaluating point matches between overlapping shapes established by two typical FEM methods, resulting in more accurate estimates of the underlying transformation. This improved transformation can be used to better initialize the iterative closest point algorithm and its variants, making 3D shape registration more likely to succeed. PMID:26357287

  15. Development of a high accurate gear measuring machine based on laser interferometry

    NASA Astrophysics Data System (ADS)

    Lin, Hu; Xue, Zi; Yang, Guoliang; Huang, Yao; Wang, Heyan

    2015-02-01

    Gear measuring machine is a specialized device for gear profile, helix or pitch measurement. The classic method for gear measurement and the conventional gear measuring machine are introduced. In this gear measuring machine, the Abbe errors arisen from the angle error of guideways hold a great weight in affection of profile measurement error. For minimize of the Abbe error, a laser measuring system is applied to develop a high accurate gear measuring machine. In this laser measuring system, two cube-corner reflectors are placed close to the tip of probe, a laser beam from laser head is splited along two paths, one is arranged tangent to the base circle of gear for the measurement of profile and pitch, another is arranged parallel to the gear axis for the measurement of helix, both laser measurement performed with a resolution of 0.3nm. This approach not only improves the accuracy of length measurement but minimize the Abbe offset directly. The configuration of this improved measuring machine is illustrated in detail. The measurements are performed automatically, and all the measurement signals from guide rails, rotary table, probe and laser measuring system are obtained synchronously. Software collects all the data for further calculation and evaluation. The first measurements for a gear involute artifact and a helix artifact are carried out, the results are shown and analyzed as well.

  16. Accurate recovery of articulator positions from acoustics: New conclusions based on human data

    SciTech Connect

    Hogden, J.; Lofqvist, A.; Gracco, V.; Zlokarnik, I.; Rubin, P.; Saltzman, E.

    1996-09-01

    Vocal tract models are often used to study the problem of mapping from the acoustic transfer function to the vocal tract area function (inverse mapping). Unfortunately, results based on vocal tract models are strongly affected by the assumptions underlying the models. In this study, the mapping from acoustics (digitized speech samples) to articulation (measurements of the positions of receiver coils placed on the tongue, jaw, and lips) is examined using human data from a single speaker: Simultaneous acoustic and articulator measurements made for vowel-to-vowel transitions, /g/ closures, and transitions into and out of /g/ closures. Articulator positions were measured using an EMMA system to track coils placed on the lips, jaw, and tongue. Using these data, look-up tables were created that allow articulator positions to be estimated from acoustic signals. On a data set not used for making look-up tables, correlations between estimated and actual coil positions of around 94{percent} and root-mean-squared errors around 2 mm are common for coils on the tongue. An error source evaluation shows that estimating articulator positions from quantized acoustics gives root-mean-squared errors that are typically less than 1 mm greater than the errors that would be obtained from quantizing the articulator positions themselves. This study agrees with and extends previous studies of human data by showing that for the data studied, speech acoustics can be used to accurately recover articulator positions. {copyright} {ital 1996 Acoustical Society of America.}

  17. Accurate localization of in-body medical implants based on spatial sparsity.

    PubMed

    Pourhomayoun, Mohammad; Jin, Zhanpeng; Fowler, Mark L

    2014-02-01

    Wearable and implantable wireless communication devices have in recent years gained increasing attention for medical diagnostics and therapeutics. In particular, wireless capsule endoscopy has become a popular method to visualize and diagnose the human gastrointestinal tract. Estimating the exact position of the capsule when each image is taken is a very critical issue in capsule endoscopy. Several approaches have been developed by researchers to estimate the capsule location. However, some unique challenges exist for in-body localization, such as the severe multipath issue caused by the boundaries of different organs, inconsistency of signal propagation velocity and path loss parameters inside the human body, and the regulatory restrictions on using high-bandwidth or high-power signals. In this paper, we propose a novel localization method based on spatial sparsity. We directly estimate the location of the capsule without going through the usual intermediate stage of first estimating time-of-arrival or received-signal strength, and then a second stage of estimating the location. We demonstrate the accuracy of the proposed method through extensive Monte Carlo simulations for radio frequency emission signals within the required power and bandwidth range. The results show that the proposed method is effective and accurate, even in massive multipath conditions. PMID:24108709

  18. SIFTER search: a web server for accurate phylogeny-based protein function prediction

    SciTech Connect

    Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

    2015-05-15

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access to precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.

  19. SIFTER search: a web server for accurate phylogeny-based protein function prediction

    DOE PAGESBeta

    Sahraeian, Sayed M.; Luo, Kevin R.; Brenner, Steven E.

    2015-05-15

    We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access tomore » precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.« less

  20. Accurate crop classification using hierarchical genetic fuzzy rule-based systems

    NASA Astrophysics Data System (ADS)

    Topaloglou, Charalampos A.; Mylonas, Stelios K.; Stavrakoudis, Dimitris G.; Mastorocostas, Paris A.; Theocharis, John B.

    2014-10-01

    This paper investigates the effectiveness of an advanced classification system for accurate crop classification using very high resolution (VHR) satellite imagery. Specifically, a recently proposed genetic fuzzy rule-based classification system (GFRBCS) is employed, namely, the Hierarchical Rule-based Linguistic Classifier (HiRLiC). HiRLiC's model comprises a small set of simple IF-THEN fuzzy rules, easily interpretable by humans. One of its most important attributes is that its learning algorithm requires minimum user interaction, since the most important learning parameters affecting the classification accuracy are determined by the learning algorithm automatically. HiRLiC is applied in a challenging crop classification task, using a SPOT5 satellite image over an intensively cultivated area in a lake-wetland ecosystem in northern Greece. A rich set of higher-order spectral and textural features is derived from the initial bands of the (pan-sharpened) image, resulting in an input space comprising 119 features. The experimental analysis proves that HiRLiC compares favorably to other interpretable classifiers of the literature, both in terms of structural complexity and classification accuracy. Its testing accuracy was very close to that obtained by complex state-of-the-art classification systems, such as the support vector machines (SVM) and random forest (RF) classifiers. Nevertheless, visual inspection of the derived classification maps shows that HiRLiC is characterized by higher generalization properties, providing more homogeneous classifications that the competitors. Moreover, the runtime requirements for producing the thematic map was orders of magnitude lower than the respective for the competitors.

  1. Diagnosis and office-based treatment of urinary incontinence in adults. Part one: diagnosis and testing

    PubMed Central

    Heidelbaugh, Joel J.; Jimbo, Masahito

    2013-01-01

    Urinary incontinence is a common problem in both men and women. This review article addresses its prevalence, risk factors, cost, the various types of incontinence, as well as how to diagnose them. The US Preventive Services Task Force, the Cochrane Database of Systematic Reviews, and PubMed were reviewed for articles focusing on urinary incontinence. Incontinence is a common problem with a high societal cost. It is frequently underreported by patients so it is appropriate for primary-care providers to screen all women and older men during visits. A thorough history and physical examination combined with easy office-based tests can often yield a clear diagnosis and rule out other transient illnesses contributing to the incontinence. Specialist referral is occasionally needed in specific situations before embarking on a treatment plan. PMID:23904857

  2. Fault diagnosis of motor drives using stator current signal analysis based on dynamic time warping

    NASA Astrophysics Data System (ADS)

    Zhen, D.; Wang, T.; Gu, F.; Ball, A. D.

    2013-01-01

    Electrical motor stator current signals have been widely used to monitor the condition of induction machines and their downstream mechanical equipment. The key technique used for current signal analysis is based on Fourier transform (FT) to extract weak fault sideband components from signals predominated with supply frequency component and its higher order harmonics. However, the FT based method has limitations such as spectral leakage and aliasing, leading to significant errors in estimating the sideband components. Therefore, this paper presents the use of dynamic time warping (DTW) to process the motor current signals for detecting and quantifying common faults in a downstream two-stage reciprocating compressor. DTW is a time domain based method and its algorithm is simple and easy to be embedded into real-time devices. In this study DTW is used to suppress the supply frequency component and highlight the sideband components based on the introduction of a reference signal which has the same frequency component as that of the supply power. Moreover, a sliding window is designed to process the raw signal using DTW frame by frame for effective calculation. Based on the proposed method, the stator current signals measured from the compressor induced with different common faults and under different loads are analysed for fault diagnosis. Results show that DTW based on residual signal analysis through the introduction of a reference signal allows the supply components to be suppressed well so that the fault related sideband components are highlighted for obtaining accurate fault detection and diagnosis results. In particular, the root mean square (RMS) values of the residual signal can indicate the differences between the healthy case and different faults under varying discharge pressures. It provides an effective and easy approach to the analysis of motor current signals for better fault diagnosis of the downstream mechanical equipment of motor drives in the time

  3. Development of a Fluorescence-Based Sensor for Rapid Diagnosis of Cyanide Exposure

    PubMed Central

    2015-01-01

    Although commonly known as a highly toxic chemical, cyanide is also an essential reagent for many industrial processes in areas such as mining, electroplating, and synthetic fiber production. The “heavy” use of cyanide in these industries, along with its necessary transportation, increases the possibility of human exposure. Because the onset of cyanide toxicity is fast, a rapid, sensitive, and accurate method for the diagnosis of cyanide exposure is necessary. Therefore, a field sensor for the diagnosis of cyanide exposure was developed based on the reaction of naphthalene dialdehyde, taurine, and cyanide, yielding a fluorescent β-isoindole. An integrated cyanide capture “apparatus”, consisting of sample and cyanide capture chambers, allowed rapid separation of cyanide from blood samples. Rabbit whole blood was added to the sample chamber, acidified, and the HCN gas evolved was actively transferred through a stainless steel channel to the capture chamber containing a basic solution of naphthalene dialdehyde (NDA) and taurine. The overall analysis time (including the addition of the sample) was <3 min, the linear range was 3.13–200 μM, and the limit of detection was 0.78 μM. None of the potential interferents investigated (NaHS, NH4OH, NaSCN, and human serum albumin) produced a signal that could be interpreted as a false positive or a false negative for cyanide exposure. Most importantly, the sensor was 100% accurate in diagnosing cyanide poisoning for acutely exposed rabbits. PMID:24383576

  4. Variogram-based fault diagnosis in an interconnected tank system.

    PubMed

    Kouadri, Abdelmalek; Aitouche, Mohanad Amokrane; Zelmat, Mimoun

    2012-05-01

    We consider in this paper the fault diagnosis problem of a three tank system DTS-200 pilot plant. The presented approach is based on the analysis of the variogram, which is a graphical variance representation that characterizes the distribution of a measured dataset, and is used to extract the sensor fault parameters. These parameters are obtained by determining the best mathematical model that fits the empirical data. Nonlinear regression techniques are used to estimate the model coefficients. Experimental study is provided to illustrate the potential applicability of this method in process monitoring. PMID:22369877

  5. Teaching medical diagnosis: a rule-based approach.

    PubMed

    Michalowski, W; Rubin, S; Aggarwal, H

    1993-01-01

    This paper discusses the design of a diagnostic process simulator which teaches medical students to think clinically. This was possible to achieve due to the application of a rule-based approach to represent diagnosis and treatments. Whilst using the simulator, as a result of the student's incorrect and correct decisions, the clinical situation changes accordingly. New diagnostic options result in the ability to choose further clinical and laboratory tests. The simulator is being implemented on Sun workstations and Macintosh computers using Prolog programming language. PMID:8139404

  6. Tumors of the cranial base: Diagnosis and treatment

    SciTech Connect

    Sekhar, L.N.; Schramm, V.L.

    1987-01-01

    The first section of this book highlights the differences and similarities in the pathology and biology of the various types of neoplasms of the cranial base. The second section covers improvements in radiological diagnosis with the advent of computed tomography, magnetic resonance imaging and a better knowledge of radiological anatomy. It also examines the significance and proper evaluation of minor symptoms to enable earlier diagnosis, as well as the advances in interventional radiology that have produced the balloon occlusion text and tumor embolization. Section three is on advanced neuroanesthetic techniques and intraoperative neurophysiological monitoring. Section four describes specialized treatment modalities including microsurgical resection with the laser, radiation therapy and chemotherapy. Section five reviews the latest techniques for reconstruction of the cranial base following resection, as well as the preservation and reconstruction of cranial nerves and cerebral blood vessels exposed during the surgery. The final three sections examine the lesions and surgical techniques specific to the different anatomical regions, i.e, the anterior, middle and posterior cranial base.

  7. Great Expectations: Expectation Based Reasoning in Medical Diagnosis

    PubMed Central

    Fisher, Paul R.; Miller, Perry L.; Swett, Henry A.

    1988-01-01

    Several different approaches to knowledge representation for medical expert systems have been explored. We suggest that a modified version of the script formalism, which we term “expectation-based reasoning”, may offer an additional knowledge representation for medical information, addressing certain shortcomings of previous approaches. This representation can drive expert system analysis for diagnosis and workup advice. The script formalism structures the knowledge base around a set of temporally sequenced event frames, each containing a list of default expectations. This model, we believe, allows straightforward knowledge generation from a domain expert, since it may closely parallel a central aspect of human clinical decision-making: that of projecting assumptions for a “hypothesize-and-test” inference mechanism. A prototype expectation-based expert system, OSCAR, is under development to explore this approach.

  8. An Expert Fitness Diagnosis System Based on Elastic Cloud Computing

    PubMed Central

    Tseng, Kevin C.; Wu, Chia-Chuan

    2014-01-01

    This paper presents an expert diagnosis system based on cloud computing. It classifies a user's fitness level based on supervised machine learning techniques. This system is able to learn and make customized diagnoses according to the user's physiological data, such as age, gender, and body mass index (BMI). In addition, an elastic algorithm based on Poisson distribution is presented to allocate computation resources dynamically. It predicts the required resources in the future according to the exponential moving average of past observations. The experimental results show that Naïve Bayes is the best classifier with the highest accuracy (90.8%) and that the elastic algorithm is able to capture tightly the trend of requests generated from the Internet and thus assign corresponding computation resources to ensure the quality of service. PMID:24723842

  9. Diffuse lung disease of infancy: a pattern-based, algorithmic approach to histological diagnosis.

    PubMed

    Armes, Jane E; Mifsud, William; Ashworth, Michael

    2015-02-01

    Diffuse lung disease (DLD) of infancy has multiple aetiologies and the spectrum of disease is substantially different from that seen in older children and adults. In many cases, a specific diagnosis renders a dire prognosis for the infant, with profound management implications. Two recently published series of DLD of infancy, collated from the archives of specialist centres, indicate that the majority of their cases were referred, implying that the majority of biopsies taken for DLD of infancy are first received by less experienced pathologists. The current literature describing DLD of infancy takes a predominantly aetiological approach to classification. We present an algorithmic, histological, pattern-based approach to diagnosis of DLD of infancy, which, with the aid of appropriate multidisciplinary input, including clinical and radiological expertise and ancillary diagnostic studies, may lead to an accurate and useful interim report, with timely exclusion of inappropriate diagnoses. Subsequent referral to a specialist centre for confirmatory diagnosis will be dependent on the individual case and the decision of the multidisciplinary team. PMID:25477529

  10. Diffuse lung disease of infancy: a pattern-based, algorithmic approach to histological diagnosis

    PubMed Central

    Armes, Jane E; Mifsud, William; Ashworth, Michael

    2015-01-01

    Diffuse lung disease (DLD) of infancy has multiple aetiologies and the spectrum of disease is substantially different from that seen in older children and adults. In many cases, a specific diagnosis renders a dire prognosis for the infant, with profound management implications. Two recently published series of DLD of infancy, collated from the archives of specialist centres, indicate that the majority of their cases were referred, implying that the majority of biopsies taken for DLD of infancy are first received by less experienced pathologists. The current literature describing DLD of infancy takes a predominantly aetiological approach to classification. We present an algorithmic, histological, pattern-based approach to diagnosis of DLD of infancy, which, with the aid of appropriate multidisciplinary input, including clinical and radiological expertise and ancillary diagnostic studies, may lead to an accurate and useful interim report, with timely exclusion of inappropriate diagnoses. Subsequent referral to a specialist centre for confirmatory diagnosis will be dependent on the individual case and the decision of the multidisciplinary team. PMID:25477529

  11. Microfluidic chip-based technologies: emerging platforms for cancer diagnosis

    PubMed Central

    2013-01-01

    The development of early and personalized diagnostic protocols is considered the most promising avenue to decrease mortality from cancer and improve outcome. The emerging microfluidic-based analyzing platforms hold high promises to fulfill high-throughput and high-precision screening with reduced equipment cost and low analysis time, as compared to traditional bulky counterparts in bench-top laboratories. This article overviewed the potential applications of microfluidic technologies for detection and monitoring of cancer through nucleic acid and protein biomarker analysis. The implications of the technologies in cancer cytology that can provide functional personalized diagnosis were highlighted. Finally, the future niches for using microfluidic-based systems in tumor screening were briefly discussed. PMID:24070124

  12. Validation of Three Early Ejaculation Diagnostic Tools: A Composite Measure Is Accurate and More Adequate for Diagnosis by Updated Diagnostic Criteria

    PubMed Central

    Jern, Patrick; Piha, Juhana; Santtila, Pekka

    2013-01-01

    Purpose To validate three early ejaculation diagnostic tools, and propose a new tool for diagnosis in line with proposed changes to diagnostic criteria. Significant changes to diagnostic criteria are expected in the near future. Available screening tools do not necessarily reflect proposed changes. Materials and Methods Data from 148 diagnosed early ejaculation patients (Mage = 42.8) and 892 controls (Mage = 33.1 years) from a population-based sample were used. Participants responded to three different questionnaires (Premature Ejaculation Profile; Premature Ejaculation Diagnostic Tool; Multiple Indicators of Premature Ejaculation). Stopwatch measured ejaculation latency times were collected from a subsample of early ejaculation patients. We used two types of responses to the questionnaires depending on the treatment status of the patients 1) responses regarding the situation before starting pharmacological treatment and 2) responses regarding current situation. Logistic regressions and Receiver Operating Characteristics were used to assess ability of both the instruments and individual items to differentiate between patients and controls. Results All instruments had very good precision (Areas under the Curve ranging from .93-.98). A new five-item instrument (named CHecklist for Early Ejaculation Symptoms – CHEES) consisting of high-performance variables selected from the three instruments had validity (Nagelkerke R2 range .51-.79 for backwards/forwards logistic regression) equal to or slightly better than any individual instrument (i.e., had slightly higher validity statistics, but these differences did not achieve statistical significance). Importantly, however, this instrument was more in line with proposed changes to diagnostic criteria. Conclusions All three screening tools had good validity. A new 5-item diagnostic tool (CHEES) based on the three instruments had equal or somewhat more favorable validity statistics compared to the other three tools, but is

  13. Is scintillometer measurement accurate enough for evaluating remote sensing based energy balance ET models?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The three evapotranspiration (ET) measurement/retrieval techniques used in this study, lysimeter, scintillometer and remote sensing vary in their level of complexity, accuracy, resolution and applicability. The lysimeter with its point measurement is the most accurate and direct method to measure ET...

  14. Using ground-based geophysics to rapidly and accurately map sub-surface acidity

    NASA Astrophysics Data System (ADS)

    Wong, Vanessa; Triantafilis, John; Johnston, Scott; Nhan, Terence; Page, Donald; Wege, Richard; Hirst, Phillip; Slavich, Peter

    2013-04-01

    Globally, large areas of coastal and estuarine floodplains are underlain by sulfidic sediments and acid sulfate soils (ASS). These soils can be environmentally hazardous due to their high acidity and large pool of potentially mobile metals. The floodplains are characterised by high spatial and temporal heterogeneity. On coastal floodplains, ASS are of moderate to high salinity, with salts derived mainly from either connate marine sources or oxidation of biogenic sulfides and the subsequent increases in soluble ions (e.g. SO42-) and acidity that follow oxidation. Enhanced acidity also increases the mobilisation of pH-sensitive trace metals such as Fe, Al, Mn, Zn and Ni and contributes to increasing apparent salinity. Ground-based geophysics using electromagnetic (EM) induction techniques have been used successfully and extensively to rapidly map soils for salinity management and precision agriculture. EM induction techniques measure apparent soil electrical conductivity (ECa), which is a function of salinity, clay content, water content, soil mineralogy and temperature to determine the spatial distribution of sub-surface conductivity. In this study, we used ECa as a proxy to map the surface and sub-surface spatial distribution of ASS and associated acidic groundwater. Three EM instruments were used, EM38, DUALEM-421 and EM34, which focus on different depth layers, in a survey of a coastal floodplain in eastern Australia. The EM surveys were calibrated with limited soil sampling and analysis (pH, EC, soluble and exchangeable salts and metals, particle size and titratable actual acidity (TAA)). Using fuzzy k-means clustering analysis, the EM38 and elevation data, from a digital elevation model, clearly identified three classes in the near-surface (0-2m) layers: i) levee soils, ii) fluvial sediment capping and iii) ASS (Fig. 4). Increasing the number of classes did not alter the classes identified. Joint inversion of the DUALEM-421 and EM34 data also identified

  15. Polymer electrolyte membrane fuel cell fault diagnosis based on empirical mode decomposition

    NASA Astrophysics Data System (ADS)

    Damour, Cédric; Benne, Michel; Grondin-Perez, Brigitte; Bessafi, Miloud; Hissel, Daniel; Chabriat, Jean-Pierre

    2015-12-01

    Diagnosis tool for water management is relevant to improve the reliability and lifetime of polymer electrolyte membrane fuel cells (PEMFCs). This paper presents a novel signal-based diagnosis approach, based on Empirical Mode Decomposition (EMD), dedicated to PEMFCs. EMD is an empirical, intuitive, direct and adaptive signal processing method, without pre-determined basis functions. The proposed diagnosis approach relies on the decomposition of FC output voltage to detect and isolate flooding and drying faults. The low computational cost of EMD, the reduced number of required measurements, and the high diagnosis accuracy of flooding and drying faults diagnosis make this approach a promising online diagnosis tool for PEMFC degraded modes management.

  16. Wavelet-Based Real-Time Diagnosis of Complex Systems

    NASA Technical Reports Server (NTRS)

    Gulati, Sandeep; Mackey, Ryan

    2003-01-01

    A new method of robust, autonomous real-time diagnosis of a time-varying complex system (e.g., a spacecraft, an advanced aircraft, or a process-control system) is presented here. It is based upon the characterization and comparison of (1) the execution of software, as reported by discrete data, and (2) data from sensors that monitor the physical state of the system, such as performance sensors or similar quantitative time-varying measurements. By taking account of the relationship between execution of, and the responses to, software commands, this method satisfies a key requirement for robust autonomous diagnosis, namely, ensuring that control is maintained and followed. Such monitoring of control software requires that estimates of the state of the system, as represented within the control software itself, are representative of the physical behavior of the system. In this method, data from sensors and discrete command data are analyzed simultaneously and compared to determine their correlation. If the sensed physical state of the system differs from the software estimate (see figure) or if the system fails to perform a transition as commanded by software, or such a transition occurs without the associated command, the system has experienced a control fault. This method provides a means of detecting such divergent behavior and automatically generating an appropriate warning.

  17. Self-diagnosis of smart structures based on dynamical properties

    NASA Astrophysics Data System (ADS)

    Fritzen, C.-P.; Kraemer, P.

    2009-08-01

    When we talk about "smart structures" we can think about different properties and capabilities which make a structure "intelligent" in a certain sense. Originally, the expression "smart" was used in the context that a structure can react and adapt to certain environmental conditions, such as change of shape, compensation of deformations, active vibration damping, etc. Over the last year, the expression "smart" has been extended to the field of structural health monitoring (SHM), where sensor networks, actuators and computational capabilities are used to enable a structure to perform a self-diagnosis with the goal that this structure can release early warnings about a critical health state, locate and classify damage or even to forecast the remaining life-time. This paper intends to give an overview and point out recent developments of vibration-based methods for SHM. All these methods have in common that a structural change due to a damage results in a more or less significant change of the dynamic behavior. For the diagnosis an inverse problem has to be solved. We discuss the use of modal information as well as the direct use of forced and ambient vibrations in the time and frequency domain. Examples from civil and aerospace engineering as well as off-shore wind energy plants show the applicability of these methods.

  18. Vibration sensor-based bearing fault diagnosis using ellipsoid-ARTMAP and differential evolution algorithms.

    PubMed

    Liu, Chang; Wang, Guofeng; Xie, Qinglu; Zhang, Yanchao

    2014-01-01

    Effective fault classification of rolling element bearings provides an important basis for ensuring safe operation of rotating machinery. In this paper, a novel vibration sensor-based fault diagnosis method using an Ellipsoid-ARTMAP network (EAM) and a differential evolution (DE) algorithm is proposed. The original features are firstly extracted from vibration signals based on wavelet packet decomposition. Then, a minimum-redundancy maximum-relevancy algorithm is introduced to select the most prominent features so as to decrease feature dimensions. Finally, a DE-based EAM (DE-EAM) classifier is constructed to realize the fault diagnosis. The major characteristic of EAM is that the sample distribution of each category is realized by using a hyper-ellipsoid node and smoothing operation algorithm. Therefore, it can depict the decision boundary of disperse samples accurately and effectively avoid over-fitting phenomena. To optimize EAM network parameters, the DE algorithm is presented and two objectives, including both classification accuracy and nodes number, are simultaneously introduced as the fitness functions. Meanwhile, an exponential criterion is proposed to realize final selection of the optimal parameters. To prove the effectiveness of the proposed method, the vibration signals of four types of rolling element bearings under different loads were collected. Moreover, to improve the robustness of the classifier evaluation, a two-fold cross validation scheme is adopted and the order of feature samples is randomly arranged ten times within each fold. The results show that DE-EAM classifier can recognize the fault categories of the rolling element bearings reliably and accurately. PMID:24936949

  19. Using Copula Distributions to Support More Accurate Imaging-Based Diagnostic Classifiers for Neuropsychiatric Disorders

    PubMed Central

    Bansal, Ravi; Hao, Xuejun; Liu, Jun; Peterson, Bradley S.

    2014-01-01

    Many investigators have tried to apply machine learning techniques to magnetic resonance images (MRIs) of the brain in order to diagnose neuropsychiatric disorders. Usually the number of brain imaging measures (such as measures of cortical thickness and measures of local surface morphology) derived from the MRIs (i.e., their dimensionality) has been large (e.g. >10) relative to the number of participants who provide the MRI data (<100). Sparse data in a high dimensional space increases the variability of the classification rules that machine learning algorithms generate, thereby limiting the validity, reproducibility, and generalizability of those classifiers. The accuracy and stability of the classifiers can improve significantly if the multivariate distributions of the imaging measures can be estimated accurately. To accurately estimate the multivariate distributions using sparse data, we propose to estimate first the univariate distributions of imaging data and then combine them using a Copula to generate more accurate estimates of their multivariate distributions. We then sample the estimated Copula distributions to generate dense sets of imaging measures and use those measures to train classifiers. We hypothesize that the dense sets of brain imaging measures will generate classifiers that are stable to variations in brain imaging measures, thereby improving the reproducibility, validity, and generalizability of diagnostic classification algorithms in imaging datasets from clinical populations. In our experiments, we used both computer-generated and real-world brain imaging datasets to assess the accuracy of multivariate Copula distributions in estimating the corresponding multivariate distributions of real-world imaging data. Our experiments showed that diagnostic classifiers generated using imaging measures sampled from the Copula were significantly more accurate and more reproducible than were the classifiers generated using either the real-world imaging

  20. Physiology-based diagnosis algorithm for arteriovenous fistula stenosis detection.

    PubMed

    Yeih, Dong-Feng; Wang, Yuh-Shyang; Huang, Yi-Chun; Chen, Ming-Fong; Lu, Shey-Shi

    2014-01-01

    In this paper, a diagnosis algorithm for arteriovenous fistula (AVF) stenosis is developed based on auscultatory features, signal processing, and machine learning. The AVF sound signals are recorded by electronic stethoscopes at pre-defined positions before and after percutaneous transluminal angioplasty (PTA) treatment. Several new signal features of stenosis are identified and quantified, and the physiological explanations for these features are provided. Utilizing support vector machine method, an average of 90% two-fold cross-validation hit-rate can be obtained, with angiography as the gold standard. This offers a non-invasive easy-to-use diagnostic method for medical staff or even patients themselves for early detection of AVF stenosis. PMID:25571021

  1. Computer-based assessment for facioscapulohumeral dystrophy diagnosis.

    PubMed

    Chambers, O; Milenković, J; Pražnikar, A; Tasič, J F

    2015-06-01

    The paper presents a computer-based assessment for facioscapulohumeral dystrophy (FSHD) diagnosis through characterisation of the fat and oedema percentages in the muscle region. A novel multi-slice method for the muscle-region segmentation in the T1-weighted magnetic resonance images is proposed using principles of the live-wire technique to find the path representing the muscle-region border. For this purpose, an exponential cost function is used that incorporates the edge information obtained after applying the edge-enhancement algorithm formerly designed for the fingerprint enhancement. The difference between the automatic segmentation and manual segmentation performed by a medical specialists is characterised using the Zijdenbos similarity index, indicating a high accuracy of the proposed method. Finally, the fat and oedema are quantified from the muscle region in the T1-weighted and T2-STIR magnetic resonance images, respectively, using the fuzzy c-mean clustering approach for 10 FSHD patients. PMID:25910520

  2. AuNPs modified, disposable, ITO based biosensor: Early diagnosis of heat shock protein 70.

    PubMed

    Sonuç Karaboğa, Münteha Nur; Şimşek, Çiğdem Sayıklı; Sezgintürk, Mustafa Kemal

    2016-10-15

    This paper describes a novel, simple, and disposable immunosensor based on indium-tin oxide (ITO) sheets modified with gold nanoparticles to sensitively analyze heat shock protein 70 (HSP70), a potential biomarker that could be evaluated in diagnosis of some carcinomas. Disposable ITO coated Polyethylene terephthalate (PET) electrodes were used and modified with gold nanoparticles in order to construct the biosensors. Optimization and characterization steps were analyzed by electrochemical techniques such as electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). Surface morphology of the biosensor was also identified by electrochemical methods, scanning electron microscopy (SEM), and atomic force microscopy (AFM). To interpret binding characterization of HSP70 to anti-HSP70 single frequency impedance method was successfully operated. Moreover, the proposed HSP70 immunosensor acquired good stability, repeatability, and reproducibility. Ultimately, proposed biosensor was introduced to real human serum samples to determine HSP70 sensitively and accurately. PMID:26318579

  3. Fault diagnosis of rotating machinery using an improved HHT based on EEMD and sensitive IMFs

    NASA Astrophysics Data System (ADS)

    Lei, Yaguo; Zuo, Ming J.

    2009-12-01

    A Hilbert-Huang transform (HHT) is a time-frequency technique and has been widely applied to analyzing vibration signals in the field of fault diagnosis of rotating machinery. It analyzes the vibration signals using intrinsic mode functions (IMFs) extracted using empirical mode decomposition (EMD). However, EMD sometimes cannot reveal the signal characteristics accurately because of the problem of mode mixing. Ensemble empirical mode decomposition (EEMD) was developed recently to alleviate this problem. The IMFs generated by EEMD have different sensitivity to faults. Some IMFs are sensitive and closely related to the faults but others are irrelevant. To enhance the accuracy of the HHT in fault diagnosis of rotating machinery, an improved HHT based on EEMD and sensitive IMFs is proposed in this paper. Simulated signals demonstrate the effectiveness of the improved HHT in diagnosing the faults of rotating machinery. Finally, the improved HHT is applied to diagnosing an early rub-impact fault of a heavy oil catalytic cracking machine set, and the application results prove that the improved HHT is superior to the HHT based on all IMFs of EMD.

  4. Development of a novel multiplex beads-based assay for autoantibody detection for colorectal cancer diagnosis.

    PubMed

    Villar-Vázquez, Roi; Padilla, Guillermo; Fernández-Aceñero, María Jesús; Suárez, Adolfo; Fuente, Eduardo; Pastor, Carlos; Calero, Miguel; Barderas, Rodrigo; Casal, J Ignacio

    2016-04-01

    Humoral response in cancer patients can be used for early cancer detection. By screening high-density protein microarrays with sera from colorectal cancer (CRC) patients and controls, we identified 16 tumor-associated antigens (TAAs) exhibiting high diagnostic value. This high number of TAAs requires the development of multiplex assays combining different antigens for a faster and more accurate prediction of CRC. Here, we have developed and optimized a bead-based assay using nine selected TAAs and two controls to provide a multiplex test for early CRC diagnosis. We screened a collection of 307 CRC patients' and control sera with the beads assay to identify and validate the best TAA combination for CRC detection. The multiplex bead-based assay exhibited a similar diagnostic performance to detect the humoral response in comparison to multiple ELISA analyses. After multivariate analysis, a panel composed of GTF2B, EDIL3, HCK, PIM1, STK4, and p53, together with gender and age, was identified as the best combination of TAAs for CRC diagnosis, achieving an AUC of 89.7%, with 66% sensitivity at 90.0% fixed specificity. The model was validated using bootstrapping analysis. In summary, we have developed a novel multiplex bead assay that after validation with a larger independent cohort of sera could be utilized in a high-throughput manner for population screening to facilitate the detection of early CRC patients. PMID:26915739

  5. Model-based diagnosis of a carbon dioxide removal assembly

    NASA Astrophysics Data System (ADS)

    Throop, David R.; Scarl, Ethan A.

    1992-03-01

    Model-based diagnosis (MBD) has been applied to a variety of mechanisms, but few of these have been in fluid flow domains. Important mechanism variables in these domains are continuous, and the mechanisms commonly contain complex recycle patterns. These properties violate some of the common assumptions for MBD. The CO2 removal assembly (CDRA) for the cabin atmosphere aboard NASA's Space Station Freedom is such a mechanism. Early work on diagnosing similar mechanisms showed that purely associative diagnostic systems could not adequately handle these mechanisms' frequent reconfigurations. This suggested a model-based approach and KATE was adapted to the domain. KATE is a constraint-based MBD shell. It has been successfully applied to liquid flow problems in handling liquid oxygen. However, that domain does not involve complex recycle streams, but the CDRA does. KATE had solved constraint sets by propagating parameter values through constraints; this method often fails on constraints sets which describe recycle systems. KATE was therefore extended to allow it to use external algebraic programs to solve its constraint sets. This paper describes the representational challenges involved in that extension, and describes adaptions which allowed KATE to work within the representational limitations imposed by those algebraic programs. It also presents preliminary results of the CDRA modeling.

  6. Microchip-based Devices for Molecular Diagnosis of Genetic Diseases.

    PubMed

    Cheng; Fortina; Surrey; Kricka; Wilding

    1996-09-01

    Microchips, constructed with a variety of microfabrication technologies (photolithography, micropatterning, microjet printing, light-directed chemical synthesis, laser stereochemical etching, and microcontact printing) are being applied to molecular biology. The new microchip-based analytical devices promise to solve the analytical problems faced by many molecular biologists (eg, contamination, low throughput, and high cost). They may revolutionize molecular biology and its application in clinical medicine, forensic science, and environmental monitoring. A typical biochemical analysis involves three main steps: (1) sample preparation, (2) biochemical reaction, and (3) detection (either separation or hybridization may be involved) accompanied by data acquisition and interpretation. The construction of a miniturized analyzer will therefore necessarily entail the miniaturization and integration of all three of these processes. The literature related to the miniaturization of these three processes indicates that the greatest emphasis so far is on the investigation and development of methods for the detection of nucleic acid, followed by the optimization of a biochemical reaction, such as the polymerase chain reaction. The first step involving sample preparation has received little attention. In this review the state of the art of, microchip-based, miniaturized analytical processes (eg, sample preparation, biochemical reaction, and detection of products) are outlined and the applications of microchip-based devices in the molecular diagnosis of genetic diseases are discussed. PMID:10462559

  7. Curvelet-based sampling for accurate and efficient multimodal image registration

    NASA Astrophysics Data System (ADS)

    Safran, M. N.; Freiman, M.; Werman, M.; Joskowicz, L.

    2009-02-01

    We present a new non-uniform adaptive sampling method for the estimation of mutual information in multi-modal image registration. The method uses the Fast Discrete Curvelet Transform to identify regions along anatomical curves on which the mutual information is computed. Its main advantages of over other non-uniform sampling schemes are that it captures the most informative regions, that it is invariant to feature shapes, orientations, and sizes, that it is efficient, and that it yields accurate results. Extensive evaluation on 20 validated clinical brain CT images to Proton Density (PD) and T1 and T2-weighted MRI images from the public RIRE database show the effectiveness of our method. Rigid registration accuracy measured at 10 clinical targets and compared to ground truth measurements yield a mean target registration error of 0.68mm(std=0.4mm) for CT-PD and 0.82mm(std=0.43mm) for CT-T2. This is 0.3mm (1mm) more accurate in the average (worst) case than five existing sampling methods. Our method has the lowest registration errors recorded to date for the registration of CT-PD and CT-T2 images in the RIRE website when compared to methods that were tested on at least three patient datasets.

  8. High-Resolution Tsunami Inundation Simulations Based on Accurate Estimations of Coastal Waveforms

    NASA Astrophysics Data System (ADS)

    Oishi, Y.; Imamura, F.; Sugawara, D.; Furumura, T.

    2015-12-01

    We evaluate the accuracy of high-resolution tsunami inundation simulations in detail using the actual observational data of the 2011 Tohoku-Oki earthquake (Mw9.0) and investigate the methodologies to improve the simulation accuracy.Due to the recent development of parallel computing technologies, high-resolution tsunami inundation simulations are conducted more commonly than before. To evaluate how accurately these simulations can reproduce inundation processes, we test several types of simulation configurations on a parallel computer, where we can utilize the observational data (e.g., offshore and coastal waveforms and inundation properties) that are recorded during the Tohoku-Oki earthquake.Before discussing the accuracy of inundation processes on land, the incident waves at coastal sites must be accurately estimated. However, for megathrust earthquakes, it is difficult to find the tsunami source that can provide accurate estimations of tsunami waveforms at every coastal site because of the complex spatiotemporal distribution of the source and the limitation of observation. To overcome this issue, we employ a site-specific source inversion approach that increases the estimation accuracy within a specific coastal site by applying appropriate weighting to the observational data in the inversion process.We applied our source inversion technique to the Tohoku tsunami and conducted inundation simulations using 5-m resolution digital elevation model data (DEM) for the coastal area around Miyako Bay and Sendai Bay. The estimated waveforms at the coastal wave gauges of these bays successfully agree with the observed waveforms. However, the simulations overestimate the inundation extent indicating the necessity to improve the inundation model. We find that the value of Manning's roughness coefficient should be modified from the often-used value of n = 0.025 to n = 0.033 to obtain proper results at both cities.In this presentation, the simulation results with several

  9. Cycle accurate and cycle reproducible memory for an FPGA based hardware accelerator

    DOEpatents

    Asaad, Sameh W.; Kapur, Mohit

    2016-03-15

    A method, system and computer program product are disclosed for using a Field Programmable Gate Array (FPGA) to simulate operations of a device under test (DUT). The DUT includes a device memory having a number of input ports, and the FPGA is associated with a target memory having a second number of input ports, the second number being less than the first number. In one embodiment, a given set of inputs is applied to the device memory at a frequency Fd and in a defined cycle of time, and the given set of inputs is applied to the target memory at a frequency Ft. Ft is greater than Fd and cycle accuracy is maintained between the device memory and the target memory. In an embodiment, a cycle accurate model of the DUT memory is created by separating the DUT memory interface protocol from the target memory storage array.

  10. Differential-equation-based representation of truncation errors for accurate numerical simulation

    NASA Astrophysics Data System (ADS)

    MacKinnon, Robert J.; Johnson, Richard W.

    1991-09-01

    High-order compact finite difference schemes for 2D convection-diffusion-type differential equations with constant and variable convection coefficients are derived. The governing equations are employed to represent leading truncation terms, including cross-derivatives, making the overall O(h super 4) schemes conform to a 3 x 3 stencil. It is shown that the two-dimensional constant coefficient scheme collapses to the optimal scheme for the one-dimensional case wherein the finite difference equation yields nodally exact results. The two-dimensional schemes are tested against standard model problems, including a Navier-Stokes application. Results show that the two schemes are generally more accurate, on comparable grids, than O(h super 2) centered differencing and commonly used O(h) and O(h super 3) upwinding schemes.

  11. Accurate and rapid optical characterization of an anisotropic guided structure based on a neural method.

    PubMed

    Robert, Stéphane; Battie, Yann; Jamon, Damien; Royer, Francois

    2007-04-10

    Optimal performances of integrated optical devices are obtained by the use of an accurate and reliable characterization method. The parameters of interest, i.e., optical indices and thickness of the waveguide structure, are calculated from effective indices by means of an inversion procedure. We demonstrate how an artificial neural network can achieve such a process. The artificial neural network used is a multilayer perceptron. The first result concerns a simulated anisotropic waveguide. The accuracy in the determination of optical indices and waveguide thickness is 5 x 10(-5) and 4 nm, respectively. Then an experimental application on a silica-titania thin film is performed. In addition, effective indices are measured by m-lines spectroscopy. Finally, a comparison with a classical optimization algorithm demonstrates the robustness of the neural method. PMID:17384718

  12. A correlative imaging based methodology for accurate quantitative assessment of bone formation in additive manufactured implants.

    PubMed

    Geng, Hua; Todd, Naomi M; Devlin-Mullin, Aine; Poologasundarampillai, Gowsihan; Kim, Taek Bo; Madi, Kamel; Cartmell, Sarah; Mitchell, Christopher A; Jones, Julian R; Lee, Peter D

    2016-06-01

    A correlative imaging methodology was developed to accurately quantify bone formation in the complex lattice structure of additive manufactured implants. Micro computed tomography (μCT) and histomorphometry were combined, integrating the best features from both, while demonstrating the limitations of each imaging modality. This semi-automatic methodology registered each modality using a coarse graining technique to speed the registration of 2D histology sections to high resolution 3D μCT datasets. Once registered, histomorphometric qualitative and quantitative bone descriptors were directly correlated to 3D quantitative bone descriptors, such as bone ingrowth and bone contact. The correlative imaging allowed the significant volumetric shrinkage of histology sections to be quantified for the first time (~15 %). This technique demonstrated the importance of location of the histological section, demonstrating that up to a 30 % offset can be introduced. The results were used to quantitatively demonstrate the effectiveness of 3D printed titanium lattice implants. PMID:27153828

  13. Computer-aided diagnosis workstation and database system for chest diagnosis based on multihelical CT images

    NASA Astrophysics Data System (ADS)

    Sato, Hitoshi; Niki, Noboru; Mori, Kiyoshi; Eguchi, Kenji; Kaneko, Masahiro; Moriyama, Noriyuki; Ohmatsu, Hironobu; Kakinuma, Ryutaro; Masuda, Hideo; Machida, Suguru; Sasagawa, Michizou

    2004-04-01

    Lung cancer is the most common cause, accounting for about 20% of all cancer deaths for males in Japan. Myocardial infarction is also known as a most fearful adult disease. Recently, multi-helical CT scanner advanced remarkably at the speed at which the chest CT images were acquired for screening examination. This screening examination requires a considerable number of images to be read. It is this time-consuming step that makes the use of multi-helical CT for mass screening. To overcome this problem, our group has developed a computer-aided diagnosis algorithm to automatically detect suspicious regions of lung cancer and coronary calcifications in chest CT images, so far. And in this time, our group has developed a newly computer-aided diagnosis workstation and database. These consist in three. First, it is an image processing system to automatically detect suspicious bronchial regions, pulmonary artery regions, plumonary vein regions and myocardial infarction regions at high speed. Second, they are two 1600 x 1200 matrix black and white liquid crystal monitor. Third, it is a terminal of image storage. These are connected mutually on the network. This makes it much easier to read images, since the 3D image of suspicious regions and shadow of suspicious regions can be displayed simultaneously on two 1600 x 1200 matrix liquid crystal monitor. The experimental results indicate that a newly computer-aided diagnosis workstation and database system can be effectively used in clinical practice to increase the speed and accuracy of routine diagnosis.

  14. Human immunodeficiency virus testing for patient-based and population-based diagnosis.

    PubMed

    Albritton, W L; Vittinghoff, E; Padian, N S

    1996-10-01

    Laboratory testing for human immunodeficiency virus (HIV) has been introduced for individual patient-based diagnosis as well as high-risk and low-risk population-based screening. The choice of test, confirmatory algorithm, and interpretative criteria used depend on the clinical setting. In the context of general population-based testing, factors affecting test performance will have to be considered carefully in the development of testing policy. PMID:8843247

  15. Computer-Aided Breast Cancer Diagnosis Based on the Analysis of Cytological Images of Fine Needle Biopsies.

    PubMed

    Filipczuk, Pawel; Fevens, Thomas; Krzyzak, Adam; Monczak, Roman

    2013-12-01

    The effectiveness of the treatment of breast cancer depends on its timely detection. An early step in the diagnosis is the cytological examination of breast material obtained directly from the tumor. This work reports on advances in computer-aided breast cancer diagnosis based on the analysis of cytological images of fine needle biopsies to characterize these biopsies as either benign or malignant. Instead of relying on the accurate segmentation of cell nuclei, the nuclei are estimated by circles using the circular Hough transform. The resulting circles are then filtered to keep only high-quality estimations for further analysis by a support vector machine which classifies detected circles as correct or incorrect on the basis of texture features and the percentage of nuclei pixels according to a nuclei mask obtained using Otsu's thresholding method. A set of 25 features of the nuclei is used in the classification of the biopsies by four different classifiers. The complete diagnostic procedure was tested on 737 microscopic images of fine needle biopsies obtained from patients and achieved 98.51% effectiveness. The results presented in this paper demonstrate that a computerized medical diagnosis system based on our method would be effective, providing valuable, accurate diagnostic information. PMID:23912498

  16. The fast and accurate 3D-face scanning technology based on laser triangle sensors

    NASA Astrophysics Data System (ADS)

    Wang, Jinjiang; Chang, Tianyu; Ge, Baozhen; Tian, Qingguo; Chen, Yang; Kong, Bin

    2013-08-01

    A laser triangle scanning method and the structure of 3D-face measurement system were introduced. In presented system, a liner laser source was selected as an optical indicated signal in order to scanning a line one times. The CCD image sensor was used to capture image of the laser line modulated by human face. The system parameters were obtained by system calibrated calculated. The lens parameters of image part of were calibrated with machine visual image method and the triangle structure parameters were calibrated with fine wire paralleled arranged. The CCD image part and line laser indicator were set with a linear motor carry which can achieve the line laser scanning form top of the head to neck. For the nose is ledge part and the eyes are sunk part, one CCD image sensor can not obtain the completed image of laser line. In this system, two CCD image sensors were set symmetric at two sides of the laser indicator. In fact, this structure includes two laser triangle measure units. Another novel design is there laser indicators were arranged in order to reduce the scanning time for it is difficult for human to keep static for longer time. The 3D data were calculated after scanning. And further data processing include 3D coordinate refine, mesh calculate and surface show. Experiments show that this system has simply structure, high scanning speed and accurate. The scanning range covers the whole head of adult, the typical resolution is 0.5mm.

  17. Accurate moving cast shadow suppression based on local color constancy detection.

    PubMed

    Amato, Ariel; Mozerov, Mikhail G; Bagdanov, Andrew D; Gonzàlez, Jordi

    2011-10-01

    This paper describes a novel framework for detection and suppression of properly shadowed regions for most possible scenarios occurring in real video sequences. Our approach requires no prior knowledge about the scene, nor is it restricted to specific scene structures. Furthermore, the technique can detect both achromatic and chromatic shadows even in the presence of camouflage that occurs when foreground regions are very similar in color to shadowed regions. The method exploits local color constancy properties due to reflectance suppression over shadowed regions. To detect shadowed regions in a scene, the values of the background image are divided by values of the current frame in the RGB color space. We show how this luminance ratio can be used to identify segments with low gradient constancy, which in turn distinguish shadows from foreground. Experimental results on a collection of publicly available datasets illustrate the superior performance of our method compared with the most sophisticated, state-of-the-art shadow detection algorithms. These results show that our approach is robust and accurate over a broad range of shadow types and challenging video conditions. PMID:21435975

  18. Towards first-principles based prediction of highly accurate electrochemical Pourbiax diagrams

    NASA Astrophysics Data System (ADS)

    Zeng, Zhenhua; Chan, Maria; Greeley, Jeff

    2015-03-01

    Electrochemical Pourbaix diagrams lie at the heart of aqueous electrochemical processes and are central to the identification of stable phases of metals for processes ranging from electrocatalysis to corrosion. Even though standard DFT calculations are potentially powerful tools for the prediction of such Pourbaix diagrams, inherent errors in the description of strongly-correlated transition metal (hydr)oxides, together with neglect of weak van der Waals (vdW) interactions, has limited the reliability of the predictions for even the simplest bulk systems; corresponding predictions for more complex alloy or surface structures are even more challenging . Through introduction of a Hubbard U correction, employment of a state-of-the-art van der Waals functional, and use of pure water as a reference state for the calculations, these errors are systematically corrected. The strong performance is illustrated on a series of bulk transition metal (Mn, Fe, Co and Ni) hydroxide, oxyhydroxide, binary and ternary oxides where the corresponding thermodynamics of oxidation and reduction can be accurately described with standard errors of less than 0.04 eV in comparison with experiment.

  19. Crack diagnosis of metallic profiles based on structural damage indicators

    NASA Astrophysics Data System (ADS)

    Preisler, A.; Steenbock, C.; Schröder, K.-U.

    2015-07-01

    Structural Health Monitoring (SHM) faces several challenges before large-scale industrial application. First of all damage diagnosis has to be reliable. Therefore, common SHM approaches use highly advanced sensor techniques to monitor the whole structure on all possible failures. This results in an enormous amount of data gathered during service. The general effort can be drastically reduced, if the knowledge achieved during the sizing process is used. During sizing, potential failure modes and critical locations, so called hot spots, are already evaluated. A very sensitive SHM system can be developed, when the monitoring effort shifts from the damage to its impact on the structural behaviour and the so called damage indicators. These are the two main components of the SmartSHM approach, which reduces the monitoring effort significantly. Not only the amount of data is minimized, but also reliability and robustness are ensured by the SmartSHM approach. This contribution demonstrates the SmartSHM approach by a cracked four point bending beam. To show general applicability a parametric study considering different profiles (bar, box, I, C, T, L, Z), crack positions and lengths has been performed. Questions of sensitivity and minimum size of the sensor network are discussed based on the results of the parametric study.

  20. Recent advances in biosensor based diagnosis of urinary tract infection.

    PubMed

    Kumar, M S; Ghosh, S; Nayak, S; Das, A P

    2016-06-15

    Urinary tract infections (UTIs) are potentially life threatening infections that are associated with high rates of incidence, recurrence and mortality. UTIs are characterized by several chronic infections which may lead to lethal consequences if left undiagnosed and untreated. The uropathogens are consistent across the globe. The most prevalent uropathogenic gram negative bacteria are Escherichia coli, Proteus mirabilis, Pseudomonas aeruginosa, Klebsiella pneumonia. Early detection and precise diagnosis of these infections will play a pivotal role in health care, pharmacological and biomedical sectors. A number of detection methods are available but their performances are not upto the mark. Therefore a more rapid, selective and highly sensitive technique for the detection and quantification of uropathogen levels in extremely minute concentrations need of the time. This review brings all the major concerns of UTI at one's doorstep such as clinical costs and incidence rate, several diagnostic approaches along with their advantages and disadvantages. Paying attention to detection approaches with emphasizing biosensor based recent developments in the quest for new diagnostics for UTI and the need for more sophisticated techniques in terms of selectivity and sensitivity is discussed. PMID:26890825

  1. An atlas of RNA base pairs involving modified nucleobases with optimal geometries and accurate energies

    PubMed Central

    Chawla, Mohit; Oliva, Romina; Bujnicki, Janusz M.; Cavallo, Luigi

    2015-01-01

    Posttranscriptional modifications greatly enhance the chemical information of RNA molecules, contributing to explain the diversity of their structures and functions. A significant fraction of RNA experimental structures available to date present modified nucleobases, with half of them being involved in H-bonding interactions with other bases, i.e. ‘modified base pairs’. Herein we present a systematic investigation of modified base pairs, in the context of experimental RNA structures. To this end, we first compiled an atlas of experimentally observed modified base pairs, for which we recorded occurrences and structural context. Then, for each base pair, we selected a representative for subsequent quantum mechanics calculations, to find out its optimal geometry and interaction energy. Our structural analyses show that most of the modified base pairs are non Watson–Crick like and are involved in RNA tertiary structure motifs. In addition, quantum mechanics calculations quantify and provide a rationale for the impact of the different modifications on the geometry and stability of the base pairs they participate in. PMID:26117545

  2. Mathematical model accurately predicts protein release from an affinity-based delivery system.

    PubMed

    Vulic, Katarina; Pakulska, Malgosia M; Sonthalia, Rohit; Ramachandran, Arun; Shoichet, Molly S

    2015-01-10

    Affinity-based controlled release modulates the delivery of protein or small molecule therapeutics through transient dissociation/association. To understand which parameters can be used to tune release, we used a mathematical model based on simple binding kinetics. A comprehensive asymptotic analysis revealed three characteristic regimes for therapeutic release from affinity-based systems. These regimes can be controlled by diffusion or unbinding kinetics, and can exhibit release over either a single stage or two stages. This analysis fundamentally changes the way we think of controlling release from affinity-based systems and thereby explains some of the discrepancies in the literature on which parameters influence affinity-based release. The rate of protein release from affinity-based systems is determined by the balance of diffusion of the therapeutic agent through the hydrogel and the dissociation kinetics of the affinity pair. Equations for tuning protein release rate by altering the strength (KD) of the affinity interaction, the concentration of binding ligand in the system, the rate of dissociation (koff) of the complex, and the hydrogel size and geometry, are provided. We validated our model by collapsing the model simulations and the experimental data from a recently described affinity release system, to a single master curve. Importantly, this mathematical analysis can be applied to any single species affinity-based system to determine the parameters required for a desired release profile. PMID:25449806

  3. An atlas of RNA base pairs involving modified nucleobases with optimal geometries and accurate energies.

    PubMed

    Chawla, Mohit; Oliva, Romina; Bujnicki, Janusz M; Cavallo, Luigi

    2015-08-18

    Posttranscriptional modifications greatly enhance the chemical information of RNA molecules, contributing to explain the diversity of their structures and functions. A significant fraction of RNA experimental structures available to date present modified nucleobases, with half of them being involved in H-bonding interactions with other bases, i.e. 'modified base pairs'. Herein we present a systematic investigation of modified base pairs, in the context of experimental RNA structures. To this end, we first compiled an atlas of experimentally observed modified base pairs, for which we recorded occurrences and structural context. Then, for each base pair, we selected a representative for subsequent quantum mechanics calculations, to find out its optimal geometry and interaction energy. Our structural analyses show that most of the modified base pairs are non Watson-Crick like and are involved in RNA tertiary structure motifs. In addition, quantum mechanics calculations quantify and provide a rationale for the impact of the different modifications on the geometry and stability of the base pairs they participate in. PMID:26117545

  4. PSIONplus: Accurate Sequence-Based Predictor of Ion Channels and Their Types

    PubMed Central

    Gao, Jianzhao; Cui, Wei; Sheng, Yajun; Ruan, Jishou; Kurgan, Lukasz

    2016-01-01

    Ion channels are a class of membrane proteins that attracts a significant amount of basic research, also being potential drug targets. High-throughput identification of these channels is hampered by the low levels of availability of their structures and an observation that use of sequence similarity offers limited predictive quality. Consequently, several machine learning predictors of ion channels from protein sequences that do not rely on high sequence similarity were developed. However, only one of these methods offers a wide scope by predicting ion channels, their types and four major subtypes of the voltage-gated channels. Moreover, this and other existing predictors utilize relatively simple predictive models that limit their accuracy. We propose a novel and accurate predictor of ion channels, their types and the four subtypes of the voltage-gated channels called PSIONplus. Our method combines a support vector machine model and a sequence similarity search with BLAST. The originality of PSIONplus stems from the use of a more sophisticated machine learning model that for the first time in this area utilizes evolutionary profiles and predicted secondary structure, solvent accessibility and intrinsic disorder. We empirically demonstrate that the evolutionary profiles provide the strongest predictive input among new and previously used input types. We also show that all new types of inputs contribute to the prediction. Results on an independent test dataset reveal that PSIONplus obtains relatively good predictive performance and outperforms existing methods. It secures accuracies of 85.4% and 68.3% for the prediction of ion channels and their types, respectively, and the average accuracy of 96.4% for the discrimination of the four ion channel subtypes. Standalone version of PSIONplus is freely available from https://sourceforge.net/projects/psion/ PMID:27044036

  5. PSIONplus: Accurate Sequence-Based Predictor of Ion Channels and Their Types.

    PubMed

    Gao, Jianzhao; Cui, Wei; Sheng, Yajun; Ruan, Jishou; Kurgan, Lukasz

    2016-01-01

    Ion channels are a class of membrane proteins that attracts a significant amount of basic research, also being potential drug targets. High-throughput identification of these channels is hampered by the low levels of availability of their structures and an observation that use of sequence similarity offers limited predictive quality. Consequently, several machine learning predictors of ion channels from protein sequences that do not rely on high sequence similarity were developed. However, only one of these methods offers a wide scope by predicting ion channels, their types and four major subtypes of the voltage-gated channels. Moreover, this and other existing predictors utilize relatively simple predictive models that limit their accuracy. We propose a novel and accurate predictor of ion channels, their types and the four subtypes of the voltage-gated channels called PSIONplus. Our method combines a support vector machine model and a sequence similarity search with BLAST. The originality of PSIONplus stems from the use of a more sophisticated machine learning model that for the first time in this area utilizes evolutionary profiles and predicted secondary structure, solvent accessibility and intrinsic disorder. We empirically demonstrate that the evolutionary profiles provide the strongest predictive input among new and previously used input types. We also show that all new types of inputs contribute to the prediction. Results on an independent test dataset reveal that PSIONplus obtains relatively good predictive performance and outperforms existing methods. It secures accuracies of 85.4% and 68.3% for the prediction of ion channels and their types, respectively, and the average accuracy of 96.4% for the discrimination of the four ion channel subtypes. Standalone version of PSIONplus is freely available from https://sourceforge.net/projects/psion/. PMID:27044036

  6. A valid, accurate, office based non-radioactive test for gastric emptying of solids

    PubMed Central

    Lee, J; Camilleri, M; Zinsmeister, A; Burton, D; Kost, L; Klein, P

    2000-01-01

    BACKGROUND—Current breath tests for measurement of gastric emptying of solids are expensive, possibly inaccurate, and require cumbersome calculations.
AIMS—We wished to validate a simplified solid gastric emptying test using a [13C]Spirulina platensis breath test for accurate results relative to scintigraphy.
SUBJECTS—Thirty healthy volunteers.
METHODS—We measured gastric emptying of egg containing [13C]S platensis and 99mTc sulphur colloid by breath 13CO2 and scintigraphy over six hours. A generalised linear regression model was used to predict t1/2 and tLAG by scintigraphy from breath 13CO2 data. The model was cross validated and normative data calculated for a prepacked [13C]meal.
RESULTS—Regression models using all breath data over six hours, for the first three hours, and for samples at 75, 90, and 180 minutes ("reduced model") predicted t1/2 and tLAG values similar to scintigraphy (tLAG 43 (SD 12) min; t1/2 100 (20) min). Standard deviations of differences in t1/2 and tLAG between scintigraphy and the "reduced model" were both 10 minutes. Gastric t1/2 for the prepacked [13C]meal was 91 (15) min (10-90% range: 74-118).
CONCLUSION—The [13C]S platensis breath test and a simple formula using breath 13CO2 at baseline, 90, and 180 minutes measured gastric emptying t1/2 for solids with results that were comparable with scintigraphy.


Keywords: stable isotope; breath test; gastric emptying PMID:10807886

  7. Accurate Gene Expression-Based Biodosimetry Using a Minimal Set of Human Gene Transcripts

    SciTech Connect

    Tucker, James D.; Joiner, Michael C.; Thomas, Robert A.; Grever, William E.; Bakhmutsky, Marina V.; Chinkhota, Chantelle N.; Smolinski, Joseph M.; Divine, George W.; Auner, Gregory W.

    2014-03-15

    Purpose: Rapid and reliable methods for conducting biological dosimetry are a necessity in the event of a large-scale nuclear event. Conventional biodosimetry methods lack the speed, portability, ease of use, and low cost required for triaging numerous victims. Here we address this need by showing that polymerase chain reaction (PCR) on a small number of gene transcripts can provide accurate and rapid dosimetry. The low cost and relative ease of PCR compared with existing dosimetry methods suggest that this approach may be useful in mass-casualty triage situations. Methods and Materials: Human peripheral blood from 60 adult donors was acutely exposed to cobalt-60 gamma rays at doses of 0 (control) to 10 Gy. mRNA expression levels of 121 selected genes were obtained 0.5, 1, and 2 days after exposure by reverse-transcriptase real-time PCR. Optimal dosimetry at each time point was obtained by stepwise regression of dose received against individual gene transcript expression levels. Results: Only 3 to 4 different gene transcripts, ASTN2, CDKN1A, GDF15, and ATM, are needed to explain ≥0.87 of the variance (R{sup 2}). Receiver-operator characteristics, a measure of sensitivity and specificity, of 0.98 for these statistical models were achieved at each time point. Conclusions: The actual and predicted radiation doses agree very closely up to 6 Gy. Dosimetry at 8 and 10 Gy shows some effect of saturation, thereby slightly diminishing the ability to quantify higher exposures. Analyses of these gene transcripts may be advantageous for use in a field-portable device designed to assess exposures in mass casualty situations or in clinical radiation emergencies.

  8. Antenna modeling considerations for accurate SAR calculations in human phantoms in close proximity to GSM cellular base station antennas.

    PubMed

    van Wyk, Marnus J; Bingle, Marianne; Meyer, Frans J C

    2005-09-01

    International bodies such as International Commission on Non-Ionizing Radiation Protection (ICNIRP) and the Institute for Electrical and Electronic Engineering (IEEE) make provision for human exposure assessment based on SAR calculations (or measurements) and basic restrictions. In the case of base station exposure this is mostly applicable to occupational exposure scenarios in the very near field of these antennas where the conservative reference level criteria could be unnecessarily restrictive. This study presents a variety of critical aspects that need to be considered when calculating SAR in a human body close to a mobile phone base station antenna. A hybrid FEM/MoM technique is proposed as a suitable numerical method to obtain accurate results. The verification of the FEM/MoM implementation has been presented in a previous publication; the focus of this study is an investigation into the detail that must be included in a numerical model of the antenna, to accurately represent the real-world scenario. This is accomplished by comparing numerical results to measurements for a generic GSM base station antenna and appropriate, representative canonical and human phantoms. The results show that it is critical to take the disturbance effect of the human phantom (a large conductive body) on the base station antenna into account when the antenna-phantom spacing is less than 300 mm. For these small spacings, the antenna structure must be modeled in detail. The conclusion is that it is feasible to calculate, using the proposed techniques and methodology, accurate occupational compliance zones around base station antennas based on a SAR profile and basic restriction guidelines. PMID:15931680

  9. Model-based monitoring and diagnosis of a satellite-based instrument

    NASA Technical Reports Server (NTRS)

    Bos, Andre; Callies, Jorg; Lefebvre, Alain

    1995-01-01

    For about a decade model-based reasoning has been propounded by a number of researchers. Maybe one of the most convincing arguments in favor of this kind of reasoning has been given by Davis in his paper on diagnosis from first principles (Davis 1984). Following their guidelines we have developed a system to verify the behavior of a satellite-based instrument GOME (which will be measuring Ozone concentrations in the near future (1995)). We start by giving a description of model-based monitoring. Besides recognizing that something is wrong, we also like to find the cause for misbehaving automatically. Therefore, we show how the monitoring technique can be extended to model-based diagnosis.

  10. Evidenced-based review of clinical studies on endodontic diagnosis.

    PubMed

    2009-08-01

    The practice of endodontics requires excellence in diagnostic skills. The importance of this topic has been underscored by a recent 2008 AAE-sponsored symposium on endodontic diagnosis, which will be highlighted in a special issue of the Journal of Endodontics. In this minireview, we focus on recent clinical studies that emphasize different aspects related to the diagnosis of disorders of the pulp-dentin complex. PMID:19631854

  11. Microwave-based medical diagnosis using particle swarm optimization algorithm

    NASA Astrophysics Data System (ADS)

    Modiri, Arezoo

    This dissertation proposes and investigates a novel architecture intended for microwave-based medical diagnosis (MBMD). Furthermore, this investigation proposes novel modifications of particle swarm optimization algorithm for achieving enhanced convergence performance. MBMD has been investigated through a variety of innovative techniques in the literature since the 1990's and has shown significant promise in early detection of some specific health threats. In comparison to the X-ray- and gamma-ray-based diagnostic tools, MBMD does not expose patients to ionizing radiation; and due to the maturity of microwave technology, it lends itself to miniaturization of the supporting systems. This modality has been shown to be effective in detecting breast malignancy, and hence, this study focuses on the same modality. A novel radiator device and detection technique is proposed and investigated in this dissertation. As expected, hardware design and implementation are of paramount importance in such a study, and a good deal of research, analysis, and evaluation has been done in this regard which will be reported in ensuing chapters of this dissertation. It is noteworthy that an important element of any detection system is the algorithm used for extracting signatures. Herein, the strong intrinsic potential of the swarm-intelligence-based algorithms in solving complicated electromagnetic problems is brought to bear. This task is accomplished through addressing both mathematical and electromagnetic problems. These problems are called benchmark problems throughout this dissertation, since they have known answers. After evaluating the performance of the algorithm for the chosen benchmark problems, the algorithm is applied to MBMD tumor detection problem. The chosen benchmark problems have already been tackled by solution techniques other than particle swarm optimization (PSO) algorithm, the results of which can be found in the literature. However, due to the relatively high level

  12. Towards Accurate Node-Based Detection of P2P Botnets

    PubMed Central

    2014-01-01

    Botnets are a serious security threat to the current Internet infrastructure. In this paper, we propose a novel direction for P2P botnet detection called node-based detection. This approach focuses on the network characteristics of individual nodes. Based on our model, we examine node's flows and extract the useful features over a given time period. We have tested our approach on real-life data sets and achieved detection rates of 99-100% and low false positives rates of 0–2%. Comparison with other similar approaches on the same data sets shows that our approach outperforms the existing approaches. PMID:25089287

  13. Towards accurate node-based detection of P2P botnets.

    PubMed

    Yin, Chunyong

    2014-01-01

    Botnets are a serious security threat to the current Internet infrastructure. In this paper, we propose a novel direction for P2P botnet detection called node-based detection. This approach focuses on the network characteristics of individual nodes. Based on our model, we examine node's flows and extract the useful features over a given time period. We have tested our approach on real-life data sets and achieved detection rates of 99-100% and low false positives rates of 0-2%. Comparison with other similar approaches on the same data sets shows that our approach outperforms the existing approaches. PMID:25089287

  14. "Perform, Measure Accurately, Optimise": On the Constitution of (Evidence-Based) Education Policy

    ERIC Educational Resources Information Center

    Decuypere, Mathias; Simons, Maarten; Masschelein, Jan

    2011-01-01

    This article takes its point of departure in the current tendency of education policy to become more and more evidence-based. The use of statistics and numbers seems to be a prerequisite for conducting a policy that is both efficient and effective. The kind of knowledge thus produced is regarded as factual and scientific. This article tries to get…

  15. PCR testing can be as accurate as culture for diagnosis of Ichthyophonus hoferi in Yukon River Chinook salmon Oncorhynchus tshawytscha .

    PubMed

    Hamazaki, Toshihide; Kahler, Eryn; Borba, Bonnie M; Burton, Tamara

    2013-07-01

    We evaluated the comparability of culture and PCR tests for detecting Ichthyophonus in Yukon River Chinook salmon Oncorhynchus tshawytscha from field samples collected at 3 locations (Emmonak, Chena, and Salcha, Alaska, USA) in 2004, 2005, and 2006. Assuming diagnosis by culture as the 'true' infection status, we calculated the sensitivity (correctly identifying fish positive for Ichthyophonus), specificity (correctly identifying fish negative for Ichthyophonus), and accuracy (correctly identifying both positive and negative fish) of PCR. Regardless of sampling locations and years, sensitivity, specificity, and accuracy exceeded 90%. Estimates of infection prevalence by PCR were similar to those by culture, except for Salcha 2005, where prevalence by PCR was significantly higher than that by culture (p < 0.0001). These results show that the PCR test is comparable to the culture test for diagnosing Ichthyophonus infection. PMID:23836767

  16. Estimation method of point spread function based on Kalman filter for accurately evaluating real optical properties of photonic crystal fibers.

    PubMed

    Shen, Yan; Lou, Shuqin; Wang, Xin

    2014-03-20

    The evaluation accuracy of real optical properties of photonic crystal fibers (PCFs) is determined by the accurate extraction of air hole edges from microscope images of cross sections of practical PCFs. A novel estimation method of point spread function (PSF) based on Kalman filter is presented to rebuild the micrograph image of the PCF cross-section and thus evaluate real optical properties for practical PCFs. Through tests on both artificially degraded images and microscope images of cross sections of practical PCFs, we prove that the proposed method can achieve more accurate PSF estimation and lower PSF variance than the traditional Bayesian estimation method, and thus also reduce the defocus effect. With this method, we rebuild the microscope images of two kinds of commercial PCFs produced by Crystal Fiber and analyze the real optical properties of these PCFs. Numerical results are in accord with the product parameters. PMID:24663461

  17. Temporal reasoning for diagnosis in a causal probabilistic knowledge base.

    PubMed

    Long, W

    1996-07-01

    We have added temporal reasoning to the Heart Disease Program (HDP) to take advantage of the temporal constraints inherent in cardiovascular reasoning. Some processes take place over minutes while others take place over months or years and a strictly probabilistic formalism can generate hypotheses that are impossible given the temporal relationships involved. The HDP has temporal constraints on the causal relations specified in the knowledge base and temporal properties on the patient input provided by the user. These are used in two ways. First, they are used to constrain the generation of the pre-computed causal pathways through the model that speed the generation of hypotheses. Second, they are used to generate time intervals for the instantiated nodes in the hypotheses, which are matched and adjusted as nodes are added to each evolving hypothesis. This domain offers a number of challenges for temporal reasoning. Since the nature of diagnostic reasoning is inferring a causal explanation from the evidence, many of the temporal intervals have few constraints and the reasoning has to make maximum use of those that exist. Thus, the HDP uses a temporal interval representation that includes the earliest and latest beginning and ending specified by the constraints. Some of the disease states can be corrected but some of the manifestations may remain. For example, a valve disease such as aortic stenosis produces hypertrophy that remains long after the valve has been replaced. This requires multiple time intervals to account for the existing findings. This paper discusses the issues and solutions that have been developed for temporal reasoning integrated with a pseudo-Bayesian probabilistic network in this challenging domain for diagnosis. PMID:8830922

  18. Use of a ray-based reconstruction algorithm to accurately quantify preclinical microSPECT images.

    PubMed

    Vandeghinste, Bert; Van Holen, Roel; Vanhove, Christian; De Vos, Filip; Vandenberghe, Stefaan; Staelens, Steven

    2014-01-01

    This work aimed to measure the in vivo quantification errors obtained when ray-based iterative reconstruction is used in micro-single-photon emission computed tomography (SPECT). This was investigated with an extensive phantom-based evaluation and two typical in vivo studies using 99mTc and 111In, measured on a commercially available cadmium zinc telluride (CZT)-based small-animal scanner. Iterative reconstruction was implemented on the GPU using ray tracing, including (1) scatter correction, (2) computed tomography-based attenuation correction, (3) resolution recovery, and (4) edge-preserving smoothing. It was validated using a National Electrical Manufacturers Association (NEMA) phantom. The in vivo quantification error was determined for two radiotracers: [99mTc]DMSA in naive mice (n  =  10 kidneys) and [111In]octreotide in mice (n  =  6) inoculated with a xenograft neuroendocrine tumor (NCI-H727). The measured energy resolution is 5.3% for 140.51 keV (99mTc), 4.8% for 171.30 keV, and 3.3% for 245.39 keV (111In). For 99mTc, an uncorrected quantification error of 28 ± 3% is reduced to 8 ± 3%. For 111In, the error reduces from 26 ± 14% to 6 ± 22%. The in vivo error obtained with 99mTc-dimercaptosuccinic acid ([99mTc]DMSA) is reduced from 16.2 ± 2.8% to -0.3 ± 2.1% and from 16.7 ± 10.1% to 2.2 ± 10.6% with [111In]octreotide. Absolute quantitative in vivo SPECT is possible without explicit system matrix measurements. An absolute in vivo quantification error smaller than 5% was achieved and exemplified for both [99mTc]DMSA and [111In]octreotide. PMID:24824961

  19. DERMA: A Melanoma Diagnosis Platform Based on Collaborative Multilabel Analog Reasoning

    PubMed Central

    Golobardes, Elisabet; Corral, Guiomar; Puig, Susana; Malvehy, Josep

    2014-01-01

    The number of melanoma cancer-related death has increased over the last few years due to the new solar habits. Early diagnosis has become the best prevention method. This work presents a melanoma diagnosis architecture based on the collaboration of several multilabel case-based reasoning subsystems called DERMA. The system has to face up several challenges that include data characterization, pattern matching, reliable diagnosis, and self-explanation capabilities. Experiments using subsystems specialized in confocal and dermoscopy images have provided promising results for helping experts to assess melanoma diagnosis. PMID:24578629

  20. Distributed bearing fault diagnosis based on vibration analysis

    NASA Astrophysics Data System (ADS)

    Dolenc, Boštjan; Boškoski, Pavle; Juričić, Đani

    2016-01-01

    Distributed bearing faults appear under various circumstances, for example due to electroerosion or the progression of localized faults. Bearings with distributed faults tend to generate more complex vibration patterns than those with localized faults. Despite the frequent occurrence of such faults, their diagnosis has attracted limited attention. This paper examines a method for the diagnosis of distributed bearing faults employing vibration analysis. The vibrational patterns generated are modeled by incorporating the geometrical imperfections of the bearing components. Comparing envelope spectra of vibration signals shows that one can distinguish between localized and distributed faults. Furthermore, a diagnostic procedure for the detection of distributed faults is proposed. This is evaluated on several bearings with naturally born distributed faults, which are compared with fault-free bearings and bearings with localized faults. It is shown experimentally that features extracted from vibrations in fault-free, localized and distributed fault conditions form clearly separable clusters, thus enabling diagnosis.

  1. EEMD based pitch evaluation method for accurate grating measurement by AFM

    NASA Astrophysics Data System (ADS)

    Li, Changsheng; Yang, Shuming; Wang, Chenying; Jiang, Zhuangde

    2016-09-01

    The pitch measurement and AFM calibration precision are significantly influenced by the grating pitch evaluation method. This paper presents the ensemble empirical mode decomposition (EEMD) based pitch evaluation method to relieve the accuracy deterioration caused by high and low frequency components of scanning profile during pitch evaluation. The simulation analysis shows that the application of EEMD can improve the pitch accuracy of the FFT-FT algorithm. The pitch error is small when the iteration number of the FFT-FT algorithms was 8. The AFM measurement of the 500 nm-pitch one-dimensional grating shows that the EEMD based pitch evaluation method could improve the pitch precision, especially the grating line position precision, and greatly expand the applicability of the gravity center algorithm when particles and impression marks were distributed on the sample surface. The measurement indicates that the nonlinearity was stable, and the nonlinearity of x axis and forward scanning was much smaller than their counterpart. Finally, a detailed pitch measurement uncertainty evaluation model suitable for commercial AFMs was demonstrated and a pitch uncertainty in the sub-nanometer range was achieved. The pitch uncertainty was reduced about 10% by EEMD.

  2. A Stationary Wavelet Entropy-Based Clustering Approach Accurately Predicts Gene Expression

    PubMed Central

    Nguyen, Nha; Vo, An; Choi, Inchan

    2015-01-01

    Abstract Studying epigenetic landscapes is important to understand the condition for gene regulation. Clustering is a useful approach to study epigenetic landscapes by grouping genes based on their epigenetic conditions. However, classical clustering approaches that often use a representative value of the signals in a fixed-sized window do not fully use the information written in the epigenetic landscapes. Clustering approaches to maximize the information of the epigenetic signals are necessary for better understanding gene regulatory environments. For effective clustering of multidimensional epigenetic signals, we developed a method called Dewer, which uses the entropy of stationary wavelet of epigenetic signals inside enriched regions for gene clustering. Interestingly, the gene expression levels were highly correlated with the entropy levels of epigenetic signals. Dewer separates genes better than a window-based approach in the assessment using gene expression and achieved a correlation coefficient above 0.9 without using any training procedure. Our results show that the changes of the epigenetic signals are useful to study gene regulation. PMID:25383910

  3. A novel ELISA-based diagnosis of acquired von Willebrand disease with increased VWF proteolysis.

    PubMed

    Rauch, Antoine; Caron, Claudine; Vincent, Flavien; Jeanpierre, Emmanuelle; Ternisien, Catherine; Boisseau, Pierre; Zawadzki, Christophe; Fressinaud, Edith; Borel-Derlon, Annie; Hermoire, Sylvie; Paris, Camille; Lavenu-Bombled, Cécile; Veyradier, Agnès; Ung, Alexandre; Vincentelli, André; van Belle, Eric; Lenting, Peter J; Goudemand, Jenny; Susen, Sophie

    2016-05-01

    Von Willebrand disease-type 2A (VWD-2A) and acquired von Willebrand syndrome (AVWS) due to aortic stenosis (AS) or left ventricular assist device (LVAD) are associated with an increased proteolysis of von Willebrand factor (VWF). Analysis of VWF multimeric profile is the most sensitive way to assess such increased VWF-proteolysis. However, several technical aspects hamper a large diffusion among routine diagnosis laboratories. This makes early diagnosis and early appropriate care of increased proteolysis challenging. In this context of unmet medical need, we developed a new ELISA aiming a quick, easy and reliable assessment of VWF-proteolysis. This ELISA was assessed successively in a LVAD-model, healthy subjects (n=39), acquired TTP-patients (n=4), VWD-patients (including VWD-2A(IIA), n=22; VWD-2B, n=26; VWD-2A(IIE), n=21; and VWD-1C, n=8) and in AVWS-patients (AS, n=9; LVAD, n=9; and MGUS, n=8). A standard of VWF-proteolysis was specifically developed. Extent of VWF-proteolysis was expressed as relative percentage and as VWF proteolysis/VWF:Ag ratio. A speed-dependent increase in VWF-proteolysis was assessed in the LVAD model whereas no proteolysis was observed in TTP-patients. In VWD-patients, VWF-proteolysis was significantly increased in VWD-2A(IIA) and VWD-2B and significantly decreased in VWD-2A(IIE) versus controls (p< 0.0001). In AVWS-patients, VWF-proteolysis was significantly increased in AS- and LVAD-patients compared to controls (p< 0.0001) and not detectable in MGUS-patients. A significant increase in VWF-proteolysis was detected as soon as three hours after LVAD implantation (p< 0.01). In conclusion, we describe a new ELISA allowing a rapid and accurate diagnosis of VWF-proteolysis validated in three different clinical situations. This assay represents a helpful alternative to electrophoresis-based assay in the diagnosis and management of AVWS with increased VWF-proteolysis. PMID:26791163

  4. Screening of the polyphenol content of tomato-based products through accurate-mass spectrometry (HPLC-ESI-QTOF).

    PubMed

    Vallverdú-Queralt, Anna; Jáuregui, Olga; Di Lecce, Giuseppe; Andrés-Lacueva, Cristina; Lamuela-Raventós, Rosa M

    2011-12-01

    Tomatoes, the second most important vegetable crop worldwide, are a key component in the so-called "Mediterranean diet" and its consumption has greatly increased worldwide over the past 2 decades, mostly due to a growing demand for tomato-based products such as ketchups, gazpachos and tomato juices. In this work, tomato-based products were analysed after a suitable work-up extraction procedure using liquid chromatography/electrospray ionisation-time of flight-mass spectrometry (HPLC-ESI-QTOF) with negative ion detection using information-dependent acquisition (IDA) to determine their phenolic composition. The compounds were confirmed by accurate mass measurements in MS and MS(2) modes. The elemental composition was selected according to the accurate masses and isotopic pattern. In this way, 47 compounds (simple phenolic and hydroxycinnamoylquinic acids and flavone, flavonol, flavanone and dihydrochalcone derivatives) were identified in tomato-based products, five of them, as far as was known, were previously unreported in tomatoes. The phenolic fingerprint showed that tomato-based products differ in phenolic composition, principally in protocatechuic acid-O-hexoside, apigenin and its glycosylated forms, quercetin-O-dihexoside, kaempferol-C-hexoside and eriodictyol-O-dihexoside. Gazpacho showed the highest number of phenolic compounds due to the vegetables added for its production. PMID:25212313

  5. An extended set of yeast-based functional assays accurately identifies human disease mutations.

    PubMed

    Sun, Song; Yang, Fan; Tan, Guihong; Costanzo, Michael; Oughtred, Rose; Hirschman, Jodi; Theesfeld, Chandra L; Bansal, Pritpal; Sahni, Nidhi; Yi, Song; Yu, Analyn; Tyagi, Tanya; Tie, Cathy; Hill, David E; Vidal, Marc; Andrews, Brenda J; Boone, Charles; Dolinski, Kara; Roth, Frederick P

    2016-05-01

    We can now routinely identify coding variants within individual human genomes. A pressing challenge is to determine which variants disrupt the function of disease-associated genes. Both experimental and computational methods exist to predict pathogenicity of human genetic variation. However, a systematic performance comparison between them has been lacking. Therefore, we developed and exploited a panel of 26 yeast-based functional complementation assays to measure the impact of 179 variants (101 disease- and 78 non-disease-associated variants) from 22 human disease genes. Using the resulting reference standard, we show that experimental functional assays in a 1-billion-year diverged model organism can identify pathogenic alleles with significantly higher precision and specificity than current computational methods. PMID:26975778

  6. An accurate tongue tissue strain synthesis using pseudo-wavelet reconstruction-based tagline detection

    NASA Astrophysics Data System (ADS)

    Yuan, Xiaohui; Ozturk, Cengizhan; Chi-Fishman, Gloria

    2007-03-01

    This paper describe our work on tagline detection and tissue strain synthesis. The tagline detection method extends our previous work 16 using pseudo-wavelet reconstruction. The novelty in tagline detection is that we integrated an active contour model and successfully improved the detection and indexing performance. Using pseudo-wavelet reconstruction-based method, prominent wavelet coefficients were retained while others were eliminated. Taglines were then extracted from the reconstructed images using thresholding. Due to noise and artifacts, a tagline can be broken into segments. We employed an active contour model that tracks the most likely segments and bridges them. Experiments demonstrated that our method extracts taglines automatically with greater robustness. Tissue strain was also reconstructed using extracted taglines.

  7. A second-order accurate kinetic-theory-based method for inviscid compressible flows

    NASA Technical Reports Server (NTRS)

    Deshpande, Suresh M.

    1986-01-01

    An upwind method for the numerical solution of the Euler equations is presented. This method, called the kinetic numerical method (KNM), is based on the fact that the Euler equations are moments of the Boltzmann equation of the kinetic theory of gases when the distribution function is Maxwellian. The KNM consists of two phases, the convection phase and the collision phase. The method is unconditionally stable and explicit. It is highly vectorizable and can be easily made total variation diminishing for the distribution function by a suitable choice of the interpolation strategy. The method is applied to a one-dimensional shock-propagation problem and to a two-dimensional shock-reflection problem.

  8. An extended set of yeast-based functional assays accurately identifies human disease mutations

    PubMed Central

    Sun, Song; Yang, Fan; Tan, Guihong; Costanzo, Michael; Oughtred, Rose; Hirschman, Jodi; Theesfeld, Chandra L.; Bansal, Pritpal; Sahni, Nidhi; Yi, Song; Yu, Analyn; Tyagi, Tanya; Tie, Cathy; Hill, David E.; Vidal, Marc; Andrews, Brenda J.; Boone, Charles; Dolinski, Kara; Roth, Frederick P.

    2016-01-01

    We can now routinely identify coding variants within individual human genomes. A pressing challenge is to determine which variants disrupt the function of disease-associated genes. Both experimental and computational methods exist to predict pathogenicity of human genetic variation. However, a systematic performance comparison between them has been lacking. Therefore, we developed and exploited a panel of 26 yeast-based functional complementation assays to measure the impact of 179 variants (101 disease- and 78 non-disease-associated variants) from 22 human disease genes. Using the resulting reference standard, we show that experimental functional assays in a 1-billion-year diverged model organism can identify pathogenic alleles with significantly higher precision and specificity than current computational methods. PMID:26975778

  9. Towards a more accurate annotation of tyrosine-based site-specific recombinases in bacterial genomes

    PubMed Central

    2012-01-01

    Background Tyrosine-based site-specific recombinases (TBSSRs) are DNA breaking-rejoining enzymes. In bacterial genomes, they play a major role in the comings and goings of mobile genetic elements (MGEs), such as temperate phage genomes, integrated conjugative elements (ICEs) or integron cassettes. TBSSRs are also involved in the segregation of plasmids and chromosomes, the resolution of plasmid dimers and of co-integrates resulting from the replicative transposition of transposons. With the aim of improving the annotation of TBSSR genes in genomic sequences and databases, which so far is far from robust, we built a set of over 1,300 TBSSR protein sequences tagged with their genome of origin. We organized them in families to investigate: i) whether TBSSRs tend to be more conserved within than between classes of MGE types and ii) whether the (sub)families may help in understanding more about the function of TBSSRs associated in tandem or trios on plasmids and chromosomes. Results A total of 67% of the TBSSRs in our set are MGE type specific. We define a new class of actinobacterial transposons, related to Tn554, containing one abnormally long TBSSR and one of typical size, and we further characterize numerous TBSSRs trios present in plasmids and chromosomes of α- and β-proteobacteria. Conclusions The simple in silico procedure described here, which uses a set of reference TBSSRs from defined MGE types, could contribute to greatly improve the annotation of tyrosine-based site-specific recombinases in plasmid, (pro)phage and other integrated MGE genomes. It also reveals TBSSRs families whose distribution among bacterial taxa suggests they mediate lateral gene transfer. PMID:22502997

  10. Switched integration amplifier-based photocurrent meter for accurate spectral responsivity measurement of photometers.

    PubMed

    Park, Seongchong; Hong, Kee-Suk; Kim, Wan-Seop

    2016-03-20

    This work introduces a switched integration amplifier (SIA)-based photocurrent meter for femtoampere (fA)-level current measurement, which enables us to measure a 107 dynamic range of spectral responsivity of photometers even with a common lamp-based monochromatic light source. We described design considerations and practices about operational amplifiers (op-amps), switches, readout methods, etc., to compose a stable SIA of low offset current in terms of leakage current and gain peaking in detail. According to the design, we made six SIAs of different integration capacitance and different op-amps and evaluated their offset currents. They showed an offset current of (1.5-85) fA with a slow variation of (0.5-10) fA for an hour under opened input. Applying a detector to the SIA input, the offset current and its variation were increased and the SIA readout became noisier due to finite shunt resistance and nonzero shunt capacitance of the detector. One of the SIAs with 10 pF nominal capacitance was calibrated using a calibrated current source at the current level of 10 nA to 1 fA and at the integration time of 2 to 65,536 ms. As a result, we obtained a calibration formula for integration capacitance as a function of integration time rather than a single capacitance value because the SIA readout showed a distinct dependence on integration time at a given current level. Finally, we applied it to spectral responsivity measurement of a photometer. It is demonstrated that the home-made SIA of 10 pF was capable of measuring a 107 dynamic range of spectral responsivity of a photometer. PMID:27140564

  11. High-Accurate Deformation Monitoring System Based on GPS and COMPASS

    NASA Astrophysics Data System (ADS)

    Xiao, Yugang; Jiang, Weiping; Xi, Ruijie; Peng, Lifeng

    2014-05-01

    The results of deformation monitoring system can be significantly enhanced in accuracy and availability with multiple GNSS systems. Phase II of COMPASS has completed a constellation of 14 satellites, 5 GEO satellites, 5 IGSO satellites and 4 MEO satellites, before the end of 2012 and can provide navigation services in Asia-Pacific areas now. Along with the release of the Interface Control Document (ICD), there are more combinations for us to select. In this study, we have developed a new deformation monitoring system based on two GNSS systems, GPS and COMPASS, with the strategy of double-difference and a wide variety of systematic error corrections. During the process of research and development, reliable methods of data preprocessing and bias fixing were used. We took advantage of the geometry-free observables (LG), Melbourne-Wubbena observables (MW) and single-difference residuals of ionosphere-free observables (LC) to detect the cycle slips of raw data, and then solved all of these cycle slips as bias parameters in the process of Least Square Algorithm to avoid the wrong repairs. As for the bias fixing, We utilized the method of bootstrap and decision function to solve the bias parameters as an integer one by one. Several steps were adopted to ensure the result of bias fixing was correct. The solution was given by 3 components of the baselines and their variances respectively, which could be used to evaluate the quality of the data-processing. Comparisons between the new system and systems which is based on single GNSS system show that the results are improved remarkably in accuracy and availability, especially in Asia-Pacific region, where the accuracy of mm-level for short baselines can be achieved easily. Along with more satellites being launched in the future, COMPASS will make more contribution to the deformation monitoring application worldwide. In addition, the solution can be further enhanced with more and more error correction models being put into

  12. Fault diagnosis of rolling element bearing based on S transform and gray level co-occurrence matrix

    NASA Astrophysics Data System (ADS)

    Zhao, Minghang; Tang, Baoping; Tan, Qian

    2015-08-01

    Time-frequency analysis is an effective tool to extract machinery health information contained in non-stationary vibration signals. Various time-frequency analysis methods have been proposed and successfully applied to machinery fault diagnosis. However, little research has been done on bearing fault diagnosis using texture features extracted from time-frequency representations (TFRs), although they may contain plenty of sensitive information highly related to fault pattern. Therefore, to make full use of the textural information contained in the TFRs, this paper proposes a novel fault diagnosis method based on S transform, gray level co-occurrence matrix (GLCM) and multi-class support vector machine (Multi-SVM). Firstly, S transform is chosen to generate the TFRs due to its advantages of providing frequency-dependent resolution while keeping a direct relationship with the Fourier spectrum. Secondly, the famous GLCM-based texture features are extracted for capturing fault pattern information. Finally, as a classifier which has good discrimination and generalization abilities, Multi-SVM is used for the classification. Experimental results indicate that the GLCM-based texture features extracted from TFRs can identify bearing fault patterns accurately, and provide higher accuracies than the traditional time-domain and frequency-domain features, wavelet packet node energy or two-direction 2D linear discriminant analysis based features of the same TFRs in most cases.

  13. Are satellite based rainfall estimates accurate enough for crop modelling under Sahelian climate?

    NASA Astrophysics Data System (ADS)

    Ramarohetra, J.; Sultan, B.

    2012-04-01

    Agriculture is considered as the most climate dependant human activity. In West Africa and especially in the sudano-sahelian zone, rain-fed agriculture - that represents 93% of cultivated areas and is the means of support of 70% of the active population - is highly vulnerable to precipitation variability. To better understand and anticipate climate impacts on agriculture, crop models - that estimate crop yield from climate information (e.g rainfall, temperature, insolation, humidity) - have been developed. These crop models are useful (i) in ex ante analysis to quantify the impact of different strategies implementation - crop management (e.g. choice of varieties, sowing date), crop insurance or medium-range weather forecast - on yields, (ii) for early warning systems and to (iii) assess future food security. Yet, the successful application of these models depends on the accuracy of their climatic drivers. In the sudano-sahelian zone , the quality of precipitation estimations is then a key factor to understand and anticipate climate impacts on agriculture via crop modelling and yield estimations. Different kinds of precipitation estimations can be used. Ground measurements have long-time series but an insufficient network density, a large proportion of missing values, delay in reporting time, and they have limited availability. An answer to these shortcomings may lie in the field of remote sensing that provides satellite-based precipitation estimations. However, satellite-based rainfall estimates (SRFE) are not a direct measurement but rather an estimation of precipitation. Used as an input for crop models, it determines the performance of the simulated yield, hence SRFE require validation. The SARRAH crop model is used to model three different varieties of pearl millet (HKP, MTDO, Souna3) in a square degree centred on 13.5°N and 2.5°E, in Niger. Eight satellite-based rainfall daily products (PERSIANN, CMORPH, TRMM 3b42-RT, GSMAP MKV+, GPCP, TRMM 3b42v6, RFEv2 and

  14. Clinical diagnosis support system based on case based fuzzy cognitive maps and semantic web.

    PubMed

    Douali, Nassim; De Roo, Jos; Jaulent, Marie-Christine

    2012-01-01

    Incorrect or improper diagnostic tests uses have important implications for health outcomes and costs. Clinical Decision Support Systems purports to optimize the use of diagnostic tests in clinical practice. The computerized medical reasoning should not only focus on existing medical knowledge but also on physician's previous experiences and new knowledge. Such medical knowledge is vague and defines uncertain relationships between facts and diagnosis, in this paper, Case Based Fuzzy Cognitive Maps (CBFCM) are proposed as an evolution of Fuzzy Cognitive Maps. They allow more complete representation of knowledge since case-based fuzzy rules are introduced to improve diagnosis decision. We have developed a framework for interacting with patient's data and formalizing knowledge from Guidelines in the domain of Urinary Tract Infection. The conducted study allowed us to test cognitive approaches for implementing Guidelines with Semantic Web tools. The advantage of this approach is to enable the sharing and reuse of knowledge from Guidelines, physicians experiences and simplify maintenance. PMID:22874199

  15. Developing an Accurate CFD Based Gust Model for the Truss Braced Wing Aircraft

    NASA Technical Reports Server (NTRS)

    Bartels, Robert E.

    2013-01-01

    The increased flexibility of long endurance aircraft having high aspect ratio wings necessitates attention to gust response and perhaps the incorporation of gust load alleviation. The design of civil transport aircraft with a strut or truss-braced high aspect ratio wing furthermore requires gust response analysis in the transonic cruise range. This requirement motivates the use of high fidelity nonlinear computational fluid dynamics (CFD) for gust response analysis. This paper presents the development of a CFD based gust model for the truss braced wing aircraft. A sharp-edged gust provides the gust system identification. The result of the system identification is several thousand time steps of instantaneous pressure coefficients over the entire vehicle. This data is filtered and downsampled to provide the snapshot data set from which a reduced order model is developed. A stochastic singular value decomposition algorithm is used to obtain a proper orthogonal decomposition (POD). The POD model is combined with a convolution integral to predict the time varying pressure coefficient distribution due to a novel gust profile. Finally the unsteady surface pressure response of the truss braced wing vehicle to a one-minus-cosine gust, simulated using the reduced order model, is compared with the full CFD.

  16. Towards a more accurate extraction of the SPICE netlist from MAGIC based layouts

    SciTech Connect

    Geronimo, G.D.

    1998-08-01

    The extraction of the SPICE netlist form MAGIC based layouts is investigated. It is assumed that the layout is fully coherent with the corresponding mask representation. The process of the extraction can be made in three steps: (1) extraction of .EXT file from layout, through MAGIC command extract; (2) extraction of the netlist from .EXT file through ext2spice extractor; and (3) correction of the netlist through ext2spice.corr program. Each of these steps introduces some approximations, most of which can be optimized, and some errors, most of which can be corrected. Aim of this work is the description of each step, of the approximations and errors on each step, and of the corresponding optimizations and corrections to be made in order to improve the accuracy of the extraction. The HP AMOS14TB 0.5 {micro}m process with linear capacitor and silicide block options and the corresponding SCN3MLC{_}SUBM.30.tech27 technology file will be used in the following examples.

  17. A novel approach for accurate identification of splice junctions based on hybrid algorithms.

    PubMed

    Mandal, Indrajit

    2015-01-01

    The precise prediction of splice junctions as 'exon-intron' or 'intron-exon' boundaries in a given DNA sequence is an important task in Bioinformatics. The main challenge is to determine the splice sites in the coding region. Due to the intrinsic complexity and the uncertainty in gene sequence, the adoption of data mining methods is increasingly becoming popular. There are various methods developed on different strategies in this direction. This article focuses on the construction of new hybrid machine learning ensembles that solve the splice junction task more effectively. A novel supervised feature reduction technique is developed using entropy-based fuzzy rough set theory optimized by greedy hill-climbing algorithm. The average prediction accuracy achieved is above 98% with 95% confidence interval. The performance of the proposed methods is evaluated using various metrics to establish the statistical significance of the results. The experiments are conducted using various schemes with human DNA sequence data. The obtained results are highly promising as compared with the state-of-the-art approaches in literature. PMID:25203504

  18. Region-Based Convolutional Networks for Accurate Object Detection and Segmentation.

    PubMed

    Girshick, Ross; Donahue, Jeff; Darrell, Trevor; Malik, Jitendra

    2016-01-01

    Object detection performance, as measured on the canonical PASCAL VOC Challenge datasets, plateaued in the final years of the competition. The best-performing methods were complex ensemble systems that typically combined multiple low-level image features with high-level context. In this paper, we propose a simple and scalable detection algorithm that improves mean average precision (mAP) by more than 50 percent relative to the previous best result on VOC 2012-achieving a mAP of 62.4 percent. Our approach combines two ideas: (1) one can apply high-capacity convolutional networks (CNNs) to bottom-up region proposals in order to localize and segment objects and (2) when labeled training data are scarce, supervised pre-training for an auxiliary task, followed by domain-specific fine-tuning, boosts performance significantly. Since we combine region proposals with CNNs, we call the resulting model an R-CNN or Region-based Convolutional Network. Source code for the complete system is available at http://www.cs.berkeley.edu/~rbg/rcnn. PMID:26656583

  19. Voxel-based registration of simulated and real patient CBCT data for accurate dental implant pose estimation

    NASA Astrophysics Data System (ADS)

    Moreira, António H. J.; Queirós, Sandro; Morais, Pedro; Rodrigues, Nuno F.; Correia, André Ricardo; Fernandes, Valter; Pinho, A. C. M.; Fonseca, Jaime C.; Vilaça, João. L.

    2015-03-01

    The success of dental implant-supported prosthesis is directly linked to the accuracy obtained during implant's pose estimation (position and orientation). Although traditional impression techniques and recent digital acquisition methods are acceptably accurate, a simultaneously fast, accurate and operator-independent methodology is still lacking. Hereto, an image-based framework is proposed to estimate the patient-specific implant's pose using cone-beam computed tomography (CBCT) and prior knowledge of implanted model. The pose estimation is accomplished in a threestep approach: (1) a region-of-interest is extracted from the CBCT data using 2 operator-defined points at the implant's main axis; (2) a simulated CBCT volume of the known implanted model is generated through Feldkamp-Davis-Kress reconstruction and coarsely aligned to the defined axis; and (3) a voxel-based rigid registration is performed to optimally align both patient and simulated CBCT data, extracting the implant's pose from the optimal transformation. Three experiments were performed to evaluate the framework: (1) an in silico study using 48 implants distributed through 12 tridimensional synthetic mandibular models; (2) an in vitro study using an artificial mandible with 2 dental implants acquired with an i-CAT system; and (3) two clinical case studies. The results shown positional errors of 67+/-34μm and 108μm, and angular misfits of 0.15+/-0.08° and 1.4°, for experiment 1 and 2, respectively. Moreover, in experiment 3, visual assessment of clinical data results shown a coherent alignment of the reference implant. Overall, a novel image-based framework for implants' pose estimation from CBCT data was proposed, showing accurate results in agreement with dental prosthesis modelling requirements.

  20. Sarcoma: concordance between initial diagnosis and centralized expert review in a population-based study within three European regions

    PubMed Central

    Ray-Coquard, I.; Montesco, M. C.; Coindre, J. M.; Dei Tos, A. P.; Lurkin, A.; Ranchère-Vince, D.; Vecchiato, A.; Decouvelaere, A. V.; Mathoulin-Pélissier, S.; Albert, S.; Cousin, P.; Cellier, D.; Toffolatti, L.; Rossi, C. R.; Blay, J. Y.

    2012-01-01

    Background Sarcomas represent a heterogeneous group of tumors. Accurate determination of histological diagnosis and prognostic factors is critical for the delineation of treatment strategies. The contribution of second opinion (SO) to improve diagnostic accuracy has been suggested for sarcoma but has never been established in population-based studies. Methods Histological data of patients diagnosed with sarcoma in Rhone-Alpes (France), Veneto (Italy) and Aquitaine (France) over a 2-year period were collected. Initial diagnoses were systematically compared with SO from regional and national experts. Results Of 2016 selected patients, 1463 (73%) matched the inclusion criteria and were analyzed. Full concordance between primary diagnosis and SO (the first pathologist and the expert reached identical conclusions) was observed in 824 (56%) cases, partial concordance (identical diagnosis of connective tumor but different grade or histological subtype) in 518 (35%) cases and complete discordance (benign versus malignant, different histological type or invalidation of the diagnosis of sarcoma) in 121 (8%) cases. The major discrepancies were related to histological grade (n = 274, 43%), histological type (n = 144, 24%), subtype (n = 18, 3%) and grade plus subtype or grade plus histological type (n = 178, 29%). Conclusion More than 40% of first histological diagnoses were modified at second reading, possibly resulting in different treatment decisions. PMID:22331640

  1. Towards an accurate and computationally-efficient modelling of Fe(II)-based spin crossover materials.

    PubMed

    Vela, Sergi; Fumanal, Maria; Ribas-Arino, Jordi; Robert, Vincent

    2015-07-01

    The DFT + U methodology is regarded as one of the most-promising strategies to treat the solid state of molecular materials, as it may provide good energetic accuracy at a moderate computational cost. However, a careful parametrization of the U-term is mandatory since the results may be dramatically affected by the selected value. Herein, we benchmarked the Hubbard-like U-term for seven Fe(ii)N6-based pseudo-octahedral spin crossover (SCO) compounds, using as a reference an estimation of the electronic enthalpy difference (ΔHelec) extracted from experimental data (T1/2, ΔS and ΔH). The parametrized U-value obtained for each of those seven compounds ranges from 2.37 eV to 2.97 eV, with an average value of U = 2.65 eV. Interestingly, we have found that this average value can be taken as a good starting point since it leads to an unprecedented mean absolute error (MAE) of only 4.3 kJ mol(-1) in the evaluation of ΔHelec for the studied compounds. Moreover, by comparing our results on the solid state and the gas phase of the materials, we quantify the influence of the intermolecular interactions on the relative stability of the HS and LS states, with an average effect of ca. 5 kJ mol(-1), whose sign cannot be generalized. Overall, the findings reported in this manuscript pave the way for future studies devoted to understand the crystalline phase of SCO compounds, or the adsorption of individual molecules on organic or metallic surfaces, in which the rational incorporation of the U-term within DFT + U yields the required energetic accuracy that is dramatically missing when using bare-DFT functionals. PMID:26040609

  2. Full Dimensional Vibrational Calculations for Methane Using AN Accurate New AB Initio Based Potential Energy Surface

    NASA Astrophysics Data System (ADS)

    Majumder, Moumita; Dawes, Richard; Wang, Xiao-Gang; Carrington, Tucker; Li, Jun; Guo, Hua; Manzhos, Sergei

    2014-06-01

    New potential energy surfaces for methane were constructed, represented as analytic fits to about 100,000 individual high-level ab initio data. Explicitly-correlated multireference data (MRCI-F12(AE)/CVQZ-F12) were computed using Molpro [1] and fit using multiple strategies. Fits with small to negligible errors were obtained using adaptations of the permutation-invariant-polynomials (PIP) approach [2,3] based on neural-networks (PIP-NN) [4,5] and the interpolative moving least squares (IMLS) fitting method [6] (PIP-IMLS). The PESs were used in full-dimensional vibrational calculations with an exact kinetic energy operator by representing the Hamiltonian in a basis of products of contracted bend and stretch functions and using a symmetry adapted Lanczos method to obtain eigenvalues and eigenvectors. Very close agreement with experiment was produced from the purely ab initio PESs. References 1- H.-J. Werner, P. J. Knowles, G. Knizia, 2012.1 ed. 2012, MOLPRO, a package of ab initio programs. see http://www.molpro.net. 2- Z. Xie and J. M. Bowman, J. Chem. Theory Comput 6, 26, 2010. 3- B. J. Braams and J. M. Bowman, Int. Rev. Phys. Chem. 28, 577, 2009. 4- J. Li, B. Jiang and Hua Guo, J. Chem. Phys. 139, 204103 (2013). 5- S Manzhos, X Wang, R Dawes and T Carrington, JPC A 110, 5295 (2006). 6- R. Dawes, X-G Wang, A.W. Jasper and T. Carrington Jr., J. Chem. Phys. 133, 134304 (2010).

  3. A new method based on the subpixel Gaussian model for accurate estimation of asteroid coordinates

    NASA Astrophysics Data System (ADS)

    Savanevych, V. E.; Briukhovetskyi, O. B.; Sokovikova, N. S.; Bezkrovny, M. M.; Vavilova, I. B.; Ivashchenko, Yu. M.; Elenin, L. V.; Khlamov, S. V.; Movsesian, Ia. S.; Dashkova, A. M.; Pogorelov, A. V.

    2015-08-01

    We describe a new iteration method to estimate asteroid coordinates, based on a subpixel Gaussian model of the discrete object image. The method operates by continuous parameters (asteroid coordinates) in a discrete observational space (the set of pixel potentials) of the CCD frame. In this model, the kind of coordinate distribution of the photons hitting a pixel of the CCD frame is known a priori, while the associated parameters are determined from a real digital object image. The method that is developed, which is flexible in adapting to any form of object image, has a high measurement accuracy along with a low calculating complexity, due to the maximum-likelihood procedure that is implemented to obtain the best fit instead of a least-squares method and Levenberg-Marquardt algorithm for minimization of the quadratic form. Since 2010, the method has been tested as the basis of our Collection Light Technology (COLITEC) software, which has been installed at several observatories across the world with the aim of the automatic discovery of asteroids and comets in sets of CCD frames. As a result, four comets (C/2010 X1 (Elenin), P/2011 NO1(Elenin), C/2012 S1 (ISON) and P/2013 V3 (Nevski)) as well as more than 1500 small Solar system bodies (including five near-Earth objects (NEOs), 21 Trojan asteroids of Jupiter and one Centaur object) have been discovered. We discuss these results, which allowed us to compare the accuracy parameters of the new method and confirm its efficiency. In 2014, the COLITEC software was recommended to all members of the Gaia-FUN-SSO network for analysing observations as a tool to detect faint moving objects in frames.

  4. A Cough-Based Algorithm for Automatic Diagnosis of Pertussis.

    PubMed

    Pramono, Renard Xaviero Adhi; Imtiaz, Syed Anas; Rodriguez-Villegas, Esther

    2016-01-01

    Pertussis is a contagious respiratory disease which mainly affects young children and can be fatal if left untreated. The World Health Organization estimates 16 million pertussis cases annually worldwide resulting in over 200,000 deaths. It is prevalent mainly in developing countries where it is difficult to diagnose due to the lack of healthcare facilities and medical professionals. Hence, a low-cost, quick and easily accessible solution is needed to provide pertussis diagnosis in such areas to contain an outbreak. In this paper we present an algorithm for automated diagnosis of pertussis using audio signals by analyzing cough and whoop sounds. The algorithm consists of three main blocks to perform automatic cough detection, cough classification and whooping sound detection. Each of these extract relevant features from the audio signal and subsequently classify them using a logistic regression model. The output from these blocks is collated to provide a pertussis likelihood diagnosis. The performance of the proposed algorithm is evaluated using audio recordings from 38 patients. The algorithm is able to diagnose all pertussis successfully from all audio recordings without any false diagnosis. It can also automatically detect individual cough sounds with 92% accuracy and PPV of 97%. The low complexity of the proposed algorithm coupled with its high accuracy demonstrates that it can be readily deployed using smartphones and can be extremely useful for quick identification or early screening of pertussis and for infection outbreaks control. PMID:27583523

  5. Inherited platelet disorders: toward DNA-based diagnosis

    PubMed Central

    Lentaigne, Claire; Freson, Kathleen; Laffan, Michael A.; Turro, Ernest

    2016-01-01

    Variations in platelet number, volume, and function are largely genetically controlled, and many loci associated with platelet traits have been identified by genome-wide association studies (GWASs).1 The genome also contains a large number of rare variants, of which a tiny fraction underlies the inherited diseases of humans. Research over the last 3 decades has led to the discovery of 51 genes harboring variants responsible for inherited platelet disorders (IPDs). However, the majority of patients with an IPD still do not receive a molecular diagnosis. Alongside the scientific interest, molecular or genetic diagnosis is important for patients. There is increasing recognition that a number of IPDs are associated with severe pathologies, including an increased risk of malignancy, and a definitive diagnosis can inform prognosis and care. In this review, we give an overview of these disorders grouped according to their effect on platelet biology and their clinical characteristics. We also discuss the challenge of identifying candidate genes and causal variants therein, how IPDs have been historically diagnosed, and how this is changing with the introduction of high-throughput sequencing. Finally, we describe how integration of large genomic, epigenomic, and phenotypic datasets, including whole genome sequencing data, GWASs, epigenomic profiling, protein–protein interaction networks, and standardized clinical phenotype coding, will drive the discovery of novel mechanisms of disease in the near future to improve patient diagnosis and management. PMID:27095789

  6. Inherited platelet disorders: toward DNA-based diagnosis.

    PubMed

    Lentaigne, Claire; Freson, Kathleen; Laffan, Michael A; Turro, Ernest; Ouwehand, Willem H

    2016-06-01

    Variations in platelet number, volume, and function are largely genetically controlled, and many loci associated with platelet traits have been identified by genome-wide association studies (GWASs).(1) The genome also contains a large number of rare variants, of which a tiny fraction underlies the inherited diseases of humans. Research over the last 3 decades has led to the discovery of 51 genes harboring variants responsible for inherited platelet disorders (IPDs). However, the majority of patients with an IPD still do not receive a molecular diagnosis. Alongside the scientific interest, molecular or genetic diagnosis is important for patients. There is increasing recognition that a number of IPDs are associated with severe pathologies, including an increased risk of malignancy, and a definitive diagnosis can inform prognosis and care. In this review, we give an overview of these disorders grouped according to their effect on platelet biology and their clinical characteristics. We also discuss the challenge of identifying candidate genes and causal variants therein, how IPDs have been historically diagnosed, and how this is changing with the introduction of high-throughput sequencing. Finally, we describe how integration of large genomic, epigenomic, and phenotypic datasets, including whole genome sequencing data, GWASs, epigenomic profiling, protein-protein interaction networks, and standardized clinical phenotype coding, will drive the discovery of novel mechanisms of disease in the near future to improve patient diagnosis and management. PMID:27095789

  7. Developing a Diagnosis Aiding Ontology Based on Hysteroscopy Image Processing

    NASA Astrophysics Data System (ADS)

    Poulos, Marios; Korfiatis, Nikolaos

    In this paper we describe an ontology design process which will introduce the steps and mechanisms required in order to create and develop an ontology which will be able to represent and describe the contents and attributes of hysteroscopy images, as well as their relationships, thus providing a useful ground for the development of tools related with medical diagnosis from physicians.

  8. Figure of merit of diamond power devices based on accurately estimated impact ionization processes

    NASA Astrophysics Data System (ADS)

    Hiraiwa, Atsushi; Kawarada, Hiroshi

    2013-07-01

    Although a high breakdown voltage or field is considered as a major advantage of diamond, there has been a large difference in breakdown voltages or fields of diamond devices in literature. Most of these apparently contradictory results did not correctly reflect material properties because of specific device designs, such as punch-through structure and insufficient edge termination. Once these data were removed, the remaining few results, including a record-high breakdown field of 20 MV/cm, were theoretically reproduced, exactly calculating ionization integrals based on the ionization coefficients that were obtained after compensating for possible errors involved in reported theoretical values. In this compensation, we newly developed a method for extracting an ionization coefficient from an arbitrary relationship between breakdown voltage and doping density in the Chynoweth's framework. The breakdown field of diamond was estimated to depend on the doping density more than other materials, and accordingly required to be compared at the same doping density. The figure of merit (FOM) of diamond devices, obtained using these breakdown data, was comparable to the FOMs of 4H-SiC and Wurtzite-GaN devices at room temperature, but was projected to be larger than the latter by more than one order of magnitude at higher temperatures about 300 °C. Considering the relatively undeveloped state of diamond technology, there is room for further enhancement of the diamond FOM, improving breakdown voltage and mobility. Through these investigations, junction breakdown was found to be initiated by electrons or holes in a p--type or n--type drift layer, respectively. The breakdown voltages in the two types of drift layers differed from each other in a strict sense but were practically the same. Hence, we do not need to care about the conduction type of drift layers, but should rather exactly calculate the ionization integral without approximating ionization coefficients by a power

  9. The multidisciplinary approach in the diagnosis of idiopathic pulmonary fibrosis: a patient case-based review.

    PubMed

    Tomassetti, Sara; Piciucchi, Sara; Tantalocco, Paola; Dubini, Alessandra; Poletti, Venerino

    2015-03-01

    Idiopathic pulmonary fibrosis (IPF) is a specific form of chronic, progressively fibrosing interstitial pneumonia that is associated with a significantly worse prognosis than other forms of chronic interstitial pneumonia. An early and accurate diagnosis of IPF is important to enable the initiation of disease-specific therapies, which have the potential to reduce disease progression, and the avoidance of inappropriate and potentially harmful drugs. Establishing an accurate diagnosis of IPF can be challenging. Recent studies and international guidelines advocate the importance of a multidisciplinary team (MDT) in the initial diagnostic assessment of patients with suspected IPF. Typical MDT members include a pulmonologist, a radiologist and a pathologist, with further input from a thoracic surgeon, a rheumatologist, a specialist nurse and an occupational physician where appropriate. Multidisciplinary diagnosis is considered the gold standard because it can improve the accuracy of diagnosis of IPF, avoid unnecessary testing (e.g. lung biopsy), and optimise patient management. Here we highlight the strengths and limitations of the multidisciplinary approach to IPF diagnosis through MDT discussion of two patient cases. PMID:25726558

  10. Image-based retrieval system and computer-aided diagnosis system for renal cortical scintigraphy images

    NASA Astrophysics Data System (ADS)

    Mumcuoğlu, Erkan; Nar, Fatih; Uğur, Omer; Bozkurt, M. Fani; Aslan, Mehmet

    2008-03-01

    Cortical renal (kidney) scintigraphy images are 2D images (256x256) acquired in three projection angles (posterior, right-posterior-oblique and left-posterior-oblique). These images are used by nuclear medicine specialists to examine the functional morphology of kidney parenchyma. The main visual features examined in reading the images are: size, location, shape and activity distribution (pixel intensity distribution within the boundary of each kidney). Among the above features, activity distribution (in finding scars if any) was found to have the least interobserver reproducibility. Therefore, in this study, we developed an image-based retrieval (IBR) and a computer-based diagnosis (CAD) system, focused on this feature in particular. The developed IBR and CAD algorithms start with automatic segmentation, boundary and landmark detection. Then, shape and activity distribution features are computed. Activity distribution feature is obtained using the acquired image and image set statistics of the normal patients. Active Shape Model (ASM) technique is used for more accurate kidney segmentation. In the training step of ASM, normal patient images are used. Retrieval performance is evaluated by calculating precision and recall. CAD performance is evaluated by specificity and sensitivity. To our knowledge, this paper is the first IBR or CAD system reported in the literature on renal cortical scintigraphy images.

  11. A MATLAB-based tool for accurate detection of perfect overlapping and nested inverted repeats in DNA sequences

    PubMed Central

    Sreeskandarajan, Sutharzan; Flowers, Michelle M.; Karro, John E.; Liang, Chun

    2014-01-01

    Summary: Palindromic sequences, or inverted repeats (IRs), in DNA sequences involve important biological processes such as DNA–protein binding, DNA replication and DNA transposition. Development of bioinformatics tools that are capable of accurately detecting perfect IRs can enable genome-wide studies of IR patterns in both prokaryotes and eukaryotes. Different from conventional string-comparison approaches, we propose a novel algorithm that uses a cumulative score system based on a prime number representation of nucleotide bases. We then implemented this algorithm as a MATLAB-based program for perfect IR detection. In comparison with other existing tools, our program demonstrates a high accuracy in detecting nested and overlapping IRs. Availability and implementation: The source code is freely available on (http://bioinfolab.miamioh.edu/bioinfolab/palindrome.php) Contact: liangc@miamioh.edu or karroje@miamioh.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24215021

  12. Implementation of a model based fault detection and diagnosis technique for actuation faults of the SSME

    NASA Technical Reports Server (NTRS)

    Duyar, A.; Guo, T.-H.; Merrill, W.; Musgrave, J.

    1991-01-01

    In a previous study, Guo, Merrill and Duyar, 1990, reported a conceptual development of a fault detection and diagnosis system for actuation faults of the Space Shuttle main engine. This study, which is a continuation of the previous work, implements the developed fault detection and diagnosis scheme for the real time actuation fault diagnosis of the Space Shuttle Main Engine. The scheme will be used as an integral part of an intelligent control system demonstration experiment at NASA Lewis. The diagnosis system utilizes a model based method with real time identification and hypothesis testing for actuation, sensor, and performance degradation faults.

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

    NASA Technical Reports Server (NTRS)

    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

  14. An Integrated Framework for Model-Based Distributed Diagnosis and Prognosis

    NASA Technical Reports Server (NTRS)

    Bregon, Anibal; Daigle, Matthew J.; Roychoudhury, Indranil

    2012-01-01

    Diagnosis and prognosis are necessary tasks for system reconfiguration and fault-adaptive control in complex systems. Diagnosis consists of detection, isolation and identification of faults, while prognosis consists of prediction of the remaining useful life of systems. This paper presents a novel integrated framework for model-based distributed diagnosis and prognosis, where system decomposition is used to enable the diagnosis and prognosis tasks to be performed in a distributed way. We show how different submodels can be automatically constructed to solve the local diagnosis and prognosis problems. We illustrate our approach using a simulated four-wheeled rover for different fault scenarios. Our experiments show that our approach correctly performs distributed fault diagnosis and prognosis in an efficient and robust manner.

  15. Diagnosing Students' Mental Models via the Web-Based Mental Models Diagnosis System

    ERIC Educational Resources Information Center

    Wang, Tzu-Hua; Chiu, Mei-Hung; Lin, Jing-Wen; Chou, Chin-Cheng

    2013-01-01

    Mental models play an important role in science education research. To extend the effectiveness of conceptual change research and to improve mental model identi?cation and diagnosis, the authors developed and tested the Web-Based Mental Models Diagnosis (WMMD) system. In this article, they describe their WMMD system, which goes beyond the…

  16. Bearing fault diagnosis based on spectrum images of vibration signals

    NASA Astrophysics Data System (ADS)

    Li, Wei; Qiu, Mingquan; Zhu, Zhencai; Wu, Bo; Zhou, Gongbo

    2016-03-01

    Bearing fault diagnosis has been a challenge in the monitoring activities of rotating machinery, and it’s receiving more and more attention. The conventional fault diagnosis methods usually extract features from the waveforms or spectrums of vibration signals in order to correctly classify faults. In this paper, a novel feature in the form of images is presented, namely analysis of the spectrum images of vibration signals. The spectrum images are simply obtained by doing fast Fourier transformation. Such images are processed with two-dimensional principal component analysis (2DPCA) to reduce the dimensions, and then a minimum distance method is applied to classify the faults of bearings. The effectiveness of the proposed method is verified with experimental data.

  17. Fiber probes based optical techniques for biomedical diagnosis

    NASA Astrophysics Data System (ADS)

    Arce-Diego, José L.; Fanjul-Vélez, Félix

    2007-06-01

    Although fiber optics have been applied in optical communication and sensor systems for several years in a very successful way, their first application was developed in medicine in the early 20's. Manufacturing and developing of optical fibers for biomedical purposes have required a lot of research efforts in order to achieve a non-invasive, in-vivo, and real-time diagnosis of different diseases in human or animal tissues. In general, optical fiber probes are designed as a function of the optical measurement technique. In this work, a brief description of the main optical techniques for optical characterization of biological tissues is presented. The recent advances in optical fiber probes for biomedical diagnosis in clinical analysis and optical biopsy in relation with the different spectroscopic or tomographic optical techniques are described.

  18. A Weibull statistics-based lignocellulose saccharification model and a built-in parameter accurately predict lignocellulose hydrolysis performance.

    PubMed

    Wang, Mingyu; Han, Lijuan; Liu, Shasha; Zhao, Xuebing; Yang, Jinghua; Loh, Soh Kheang; Sun, Xiaomin; Zhang, Chenxi; Fang, Xu

    2015-09-01

    Renewable energy from lignocellulosic biomass has been deemed an alternative to depleting fossil fuels. In order to improve this technology, we aim to develop robust mathematical models for the enzymatic lignocellulose degradation process. By analyzing 96 groups of previously published and newly obtained lignocellulose saccharification results and fitting them to Weibull distribution, we discovered Weibull statistics can accurately predict lignocellulose saccharification data, regardless of the type of substrates, enzymes and saccharification conditions. A mathematical model for enzymatic lignocellulose degradation was subsequently constructed based on Weibull statistics. Further analysis of the mathematical structure of the model and experimental saccharification data showed the significance of the two parameters in this model. In particular, the λ value, defined the characteristic time, represents the overall performance of the saccharification system. This suggestion was further supported by statistical analysis of experimental saccharification data and analysis of the glucose production levels when λ and n values change. In conclusion, the constructed Weibull statistics-based model can accurately predict lignocellulose hydrolysis behavior and we can use the λ parameter to assess the overall performance of enzymatic lignocellulose degradation. Advantages and potential applications of the model and the λ value in saccharification performance assessment were discussed. PMID:26121186

  19. Development of an Anti-Elicitin Antibody-Based Immunohistochemical Assay for Diagnosis of Pythiosis.

    PubMed

    Inkomlue, Ruchuros; Larbcharoensub, Noppadol; Karnsombut, Patcharee; Lerksuthirat, Tassanee; Aroonroch, Rangsima; Lohnoo, Tassanee; Yingyong, Wanta; Santanirand, Pitak; Sansopha, Lalana; Krajaejun, Theerapong

    2016-01-01

    Pythiosis is an emerging and life-threatening infectious disease of humans and animals living in tropical and subtropical countries and is caused by the fungus-like organism Pythium insidiosum. Antifungals are ineffective against this pathogen. Most patients undergo surgical removal of the infected organ, and many die from advanced infections. Early and accurate diagnosis leads to prompt management and promotes better prognosis for affected patients. Immunohistochemical assays (IHCs) have been developed using rabbit antibodies raised against P. insidiosum crude extract, i.e., culture filtrate antigen (CFA), for the histodiagnosis of pythiosis, but cross-reactivity with pathogenic fungi compromises the diagnostic performance of the IHC. Therefore, there is a need to improve detection specificity. Recently, the elicitin protein, ELI025, was identified in P. insidiosum, but it was not identified in other human pathogens, including true fungi. The ELI025-encoding gene was successfully cloned and expressed as a recombinant protein in Escherichia coli. This study aims to develop a new IHC using the rabbit anti-ELI025 antibody (anti-ELI) and to compare its performance with the previously reported anti-CFA-based IHC. Thirty-eight P. insidiosum histological sections stained positive by anti-ELI-based and anti-CFA-based IHCs indicating 100% detection sensitivity for the two assays. The anti-ELI antibody stained negative for all 49 negative-control sections indicating 100% detection specificity. In contrast, the anti-CFA antibody stained positive for one of the 49 negative controls (a slide prepared from Fusarium-infected tissue) indicating 98% detection specificity. In conclusion, the anti-ELI based IHC is sensitive and specific for the histodiagnosis of pythiosis and is an improvement over the anti-CFA-based assay. PMID:26719582

  20. Development of an Anti-Elicitin Antibody-Based Immunohistochemical Assay for Diagnosis of Pythiosis

    PubMed Central

    Inkomlue, Ruchuros; Larbcharoensub, Noppadol; Karnsombut, Patcharee; Lerksuthirat, Tassanee; Aroonroch, Rangsima; Lohnoo, Tassanee; Yingyong, Wanta; Santanirand, Pitak; Sansopha, Lalana

    2015-01-01

    Pythiosis is an emerging and life-threatening infectious disease of humans and animals living in tropical and subtropical countries and is caused by the fungus-like organism Pythium insidiosum. Antifungals are ineffective against this pathogen. Most patients undergo surgical removal of the infected organ, and many die from advanced infections. Early and accurate diagnosis leads to prompt management and promotes better prognosis for affected patients. Immunohistochemical assays (IHCs) have been developed using rabbit antibodies raised against P. insidiosum crude extract, i.e., culture filtrate antigen (CFA), for the histodiagnosis of pythiosis, but cross-reactivity with pathogenic fungi compromises the diagnostic performance of the IHC. Therefore, there is a need to improve detection specificity. Recently, the elicitin protein, ELI025, was identified in P. insidiosum, but it was not identified in other human pathogens, including true fungi. The ELI025-encoding gene was successfully cloned and expressed as a recombinant protein in Escherichia coli. This study aims to develop a new IHC using the rabbit anti-ELI025 antibody (anti-ELI) and to compare its performance with the previously reported anti-CFA-based IHC. Thirty-eight P. insidiosum histological sections stained positive by anti-ELI-based and anti-CFA-based IHCs indicating 100% detection sensitivity for the two assays. The anti-ELI antibody stained negative for all 49 negative-control sections indicating 100% detection specificity. In contrast, the anti-CFA antibody stained positive for one of the 49 negative controls (a slide prepared from Fusarium-infected tissue) indicating 98% detection specificity. In conclusion, the anti-ELI based IHC is sensitive and specific for the histodiagnosis of pythiosis and is an improvement over the anti-CFA-based assay. PMID:26719582

  1. Measuring laser power as a force: a new paradigm to accurately monitor optical power during laser-based machining operations

    NASA Astrophysics Data System (ADS)

    Williams, Paul; Simonds, Brian; Sowards, Jeffrey; Hadler, Joshua

    2016-03-01

    In laser manufacturing operations, accurate measurement of laser power is important for product quality, operational repeatability, and process validation. Accurate real-time measurement of high-power lasers, however, is difficult. Typical thermal power meters must absorb all the laser power in order to measure it. This constrains power meters to be large, slow and exclusive (that is, the laser cannot be used for its intended purpose during the measurement). To address these limitations, we have developed a different paradigm in laser power measurement where the power is not measured according to its thermal equivalent but rather by measuring the laser beam's momentum (radiation pressure). Very simply, light reflecting from a mirror imparts a small force perpendicular to the mirror which is proportional to the optical power. By mounting a high-reflectivity mirror on a high-sensitivity force transducer (scale), we are able to measure laser power in the range of tens of watts up to ~ 100 kW. The critical parameters for such a device are mirror reflectivity, angle of incidence, and scale sensitivity and accuracy. We will describe our experimental characterization of a radiation-pressure-based optical power meter. We have tested it for modulated and CW laser powers up to 92 kW in the laboratory and up to 20 kW in an experimental laser welding booth. We will describe present accuracy, temporal response, sources of measurement uncertainty, and hurdles which must be overcome to have an accurate power meter capable of routine operation as a turning mirror within a laser delivery head.

  2. Fault diagnosis for manifold absolute pressure sensor(MAP) of diesel engine based on Elman neural network observer

    NASA Astrophysics Data System (ADS)

    Wang, Yingmin; Zhang, Fujun; Cui, Tao; Zhou, Jinlong

    2016-03-01

    Intake system of diesel engine is a strong nonlinear system, and it is difficult to establish accurate model of intake system; and bias fault and precision degradation fault of MAP of diesel engine can't be diagnosed easily using model-based methods. Thus, a fault diagnosis method based on Elman neural network observer is proposed. By comparing simulation results of intake pressure based on BP network and Elman neural network, lower sampling error magnitude is gained using Elman neural network, and the error is less volatile. Forecast accuracy is between 0.015-0.017 5 and sample error is controlled within 0-0.07. Considering the output stability and complexity of solving comprehensively, Elman neural network with a single hidden layer and with 44 nodes is presented as intake system observer. By comparing the relations of confidence intervals of the residual value between the measured and predicted values, error variance and failures in various fault types. Then four typical MAP faults of diesel engine can be diagnosed: complete failure fault, bias fault, precision degradation fault and drift fault. The simulation results show: intake pressure is observable and selection of diagnostic strategy parameter reasonably can increase the accuracy of diagnosis; the proposed fault diagnosis method only depends on data and structural parameters of observer, not depends on the nonlinear model of air intake system. A fault diagnosis method is proposed not depending system model to observe intake pressure, and bias fault and precision degradation fault of MAP of diesel engine can be diagnosed based on residuals.

  3. Development and Validation of a Mass Spectrometry-Based Assay for the Molecular Diagnosis of Mucin-1 Kidney Disease.

    PubMed

    Blumenstiel, Brendan; DeFelice, Matthew; Birsoy, Ozge; Bleyer, Anthony J; Kmoch, Stanislav; Carter, Todd A; Gnirke, Andreas; Kidd, Kendrah; Rehm, Heidi L; Ronco, Lucienne; Lander, Eric S; Gabriel, Stacey; Lennon, Niall J

    2016-07-01

    Mucin-1 kidney disease, previously described as medullary cystic kidney disease type 1 (MCKD1, OMIM 174000), is an autosomal dominant tubulointerstitial kidney disease recently shown to be caused by a single-base insertion within the variable number tandem repeat region of the MUC1 gene. Because of variable age of disease onset and often subtle signs and symptoms, clinical diagnosis of mucin-1 kidney disease and differentiation from other forms of hereditary kidney disease have been difficult. The causal insertion resides in a variable number tandem repeat region with high GC content, which has made detection by standard next-generation sequencing impossible to date. The inherently difficult nature of this mutation required an alternative method for routine detection and clinical diagnosis of the disease. We therefore developed and validated a mass spectrometry-based probe extension assay with a series of internal controls to detect the insertion event using 24 previously characterized positive samples from patients with mucin-1 kidney disease and 24 control samples known to be wild type for the variant. Validation results indicate an accurate and reliable test for clinically establishing the molecular diagnosis of mucin-1 kidney disease with 100% sensitivity and specificity across 275 tests called. PMID:27157321

  4. Fault Diagnosis for the Heat Exchanger of the Aircraft Environmental Control System Based on the Strong Tracking Filter

    PubMed Central

    Ma, Jian; Lu, Chen; Liu, Hongmei

    2015-01-01

    The aircraft environmental control system (ECS) is a critical aircraft system, which provides the appropriate environmental conditions to ensure the safe transport of air passengers and equipment. The functionality and reliability of ECS have received increasing attention in recent years. The heat exchanger is a particularly significant component of the ECS, because its failure decreases the system’s efficiency, which can lead to catastrophic consequences. Fault diagnosis of the heat exchanger is necessary to prevent risks. However, two problems hinder the implementation of the heat exchanger fault diagnosis in practice. First, the actual measured parameter of the heat exchanger cannot effectively reflect the fault occurrence, whereas the heat exchanger faults are usually depicted by utilizing the corresponding fault-related state parameters that cannot be measured directly. Second, both the traditional Extended Kalman Filter (EKF) and the EKF-based Double Model Filter have certain disadvantages, such as sensitivity to modeling errors and difficulties in selection of initialization values. To solve the aforementioned problems, this paper presents a fault-related parameter adaptive estimation method based on strong tracking filter (STF) and Modified Bayes classification algorithm for fault detection and failure mode classification of the heat exchanger, respectively. Heat exchanger fault simulation is conducted to generate fault data, through which the proposed methods are validated. The results demonstrate that the proposed methods are capable of providing accurate, stable, and rapid fault diagnosis of the heat exchanger. PMID:25823010

  5. Fault diagnosis for the heat exchanger of the aircraft environmental control system based on the strong tracking filter.

    PubMed

    Ma, Jian; Lu, Chen; Liu, Hongmei

    2015-01-01

    The aircraft environmental control system (ECS) is a critical aircraft system, which provides the appropriate environmental conditions to ensure the safe transport of air passengers and equipment. The functionality and reliability of ECS have received increasing attention in recent years. The heat exchanger is a particularly significant component of the ECS, because its failure decreases the system's efficiency, which can lead to catastrophic consequences. Fault diagnosis of the heat exchanger is necessary to prevent risks. However, two problems hinder the implementation of the heat exchanger fault diagnosis in practice. First, the actual measured parameter of the heat exchanger cannot effectively reflect the fault occurrence, whereas the heat exchanger faults are usually depicted by utilizing the corresponding fault-related state parameters that cannot be measured directly. Second, both the traditional Extended Kalman Filter (EKF) and the EKF-based Double Model Filter have certain disadvantages, such as sensitivity to modeling errors and difficulties in selection of initialization values. To solve the aforementioned problems, this paper presents a fault-related parameter adaptive estimation method based on strong tracking filter (STF) and Modified Bayes classification algorithm for fault detection and failure mode classification of the heat exchanger, respectively. Heat exchanger fault simulation is conducted to generate fault data, through which the proposed methods are validated. The results demonstrate that the proposed methods are capable of providing accurate, stable, and rapid fault diagnosis of the heat exchanger. PMID:25823010

  6. Fault diagnosis based on signed directed graph and support vector machine

    NASA Astrophysics Data System (ADS)

    Han, Xiaoming; Lv, Qing; Xie, Gang; Zheng, Jianxia

    2011-12-01

    Support Vector Machine (SVM) based on Structural Risk Minimization (SRM) of Statistical Learning Theory has excellent performance in fault diagnosis. However, its training speed and diagnosis speed are relatively slow. Signed Directed Graph (SDG) based on deep knowledge model has better completeness that is knowledge representation ability. However, much quantitative information is not utilized in qualitative SDG model which often produces a false solution. In order to speed up the training and diagnosis of SVM and improve the diagnostic resolution of SDG, SDG and SVM are combined in this paper. Training samples' dimension of SVM is reduced to improve training speed and diagnosis speed by the consistent path of SDG; the resolution of SDG is improved by good classification performance of SVM. The Matlab simulation by Tennessee-Eastman Process (TEP) simulation system demonstrates the feasibility of the fault diagnosis algorithm proposed in this paper.

  7. Fault diagnosis based on signed directed graph and support vector machine

    NASA Astrophysics Data System (ADS)

    Han, Xiaoming; Lv, Qing; Xie, Gang; Zheng, Jianxia

    2012-01-01

    Support Vector Machine (SVM) based on Structural Risk Minimization (SRM) of Statistical Learning Theory has excellent performance in fault diagnosis. However, its training speed and diagnosis speed are relatively slow. Signed Directed Graph (SDG) based on deep knowledge model has better completeness that is knowledge representation ability. However, much quantitative information is not utilized in qualitative SDG model which often produces a false solution. In order to speed up the training and diagnosis of SVM and improve the diagnostic resolution of SDG, SDG and SVM are combined in this paper. Training samples' dimension of SVM is reduced to improve training speed and diagnosis speed by the consistent path of SDG; the resolution of SDG is improved by good classification performance of SVM. The Matlab simulation by Tennessee-Eastman Process (TEP) simulation system demonstrates the feasibility of the fault diagnosis algorithm proposed in this paper.

  8. Imaging-Based Diagnosis of Wernicke Encephalopathy: A Case Report

    PubMed Central

    Delavar Kasmaei, Hosein; Baratloo, Alireza; Soleymani, Maryam; Nasiri, Zahra

    2014-01-01

    Introduction: Wernicke encephalopathy (WE) is a medical emergency characterized by ataxia, confusion, nystagmus and ophthalmoplegia resulting from thiamin deficiency. Alcoholism is the common cause for this disease. Case Presentation: A 41 year old man was brought to our emergency department (ED) complaining of confusion. One week earlier he had started to experience severe nausea and vomiting followed by diplopia, dysarthria and also dysphagia. One day later he had experienced gait disturbance and progressive ataxia accompanied with confusion, apathy and disorientation. He had no history of alcoholism, drug abuse or previous surgery but had history of untreated Crohn disease. Just before arrival to our emergency department, he had been hospitalized in another center for about a week but all investigations had failed to provide a conclusive diagnosis. Upon admission to our ED, he was dysarthric and replied with inappropriate answers. On physical examination, bilateral horizontal nystagmus in lateral gaze, left abducens nerve palsy and upward gaze palsy were seen. Gag reflex was absent and plantar reflexes were upwards bilaterally. After reviewing all the previously performed management measures, MRI was performed and was consistent with the diagnosis of WE. Treatment with thiamine led to partial resolution of his upward gaze palsy and nystagmus on the first day. At the end of the third day of treatment, except for gate ataxia, all other symptoms completely resolved and he was fully conscious. After the fifth day his gait became normal and after one week he was discharged in good general condition. Discussion: After reviewing the current literature, it seems that brain MRI can be helpful in the diagnosis of WE in patients with the classic clinical trial in the absence of clear risk factors. PMID:25717447

  9. LGH: A Fast and Accurate Algorithm for Single Individual Haplotyping Based on a Two-Locus Linkage Graph.

    PubMed

    Xie, Minzhu; Wang, Jianxin; Chen, Xin

    2015-01-01

    Phased haplotype information is crucial in our complete understanding of differences between individuals at the genetic level. Given a collection of DNA fragments sequenced from a homologous pair of chromosomes, the problem of single individual haplotyping (SIH) aims to reconstruct a pair of haplotypes using a computer algorithm. In this paper, we encode the information of aligned DNA fragments into a two-locus linkage graph and approach the SIH problem by vertex labeling of the graph. In order to find a vertex labeling with the minimum sum of weights of incompatible edges, we develop a fast and accurate heuristic algorithm. It starts with detecting error-tolerant components by an adapted breadth-first search. A proper labeling of vertices is then identified for each component, with which sequencing errors are further corrected and edge weights are adjusted accordingly. After contracting each error-tolerant component into a single vertex, the above procedure is iterated on the resulting condensed linkage graph until error-tolerant components are no longer detected. The algorithm finally outputs a haplotype pair based on the vertex labeling. Extensive experiments on simulated and real data show that our algorithm is more accurate and faster than five existing algorithms for single individual haplotyping. PMID:26671798

  10. New approach based on tetrahedral-mesh geometry for accurate 4D Monte Carlo patient-dose calculation.

    PubMed

    Han, Min Cheol; Yeom, Yeon Soo; Kim, Chan Hyeong; Kim, Seonghoon; Sohn, Jason W

    2015-02-21

    In the present study, to achieve accurate 4D Monte Carlo dose calculation in radiation therapy, we devised a new approach that combines (1) modeling of the patient body using tetrahedral-mesh geometry based on the patient's 4D CT data, (2) continuous movement/deformation of the tetrahedral patient model by interpolation of deformation vector fields acquired through deformable image registration, and (3) direct transportation of radiation particles during the movement and deformation of the tetrahedral patient model. The results of our feasibility study show that it is certainly possible to construct 4D patient models (= phantoms) with sufficient accuracy using the tetrahedral-mesh geometry and to directly transport radiation particles during continuous movement and deformation of the tetrahedral patient model. This new approach not only produces more accurate dose distribution in the patient but also replaces the current practice of using multiple 3D voxel phantoms and combining multiple dose distributions after Monte Carlo simulations. For routine clinical application of our new approach, the use of fast automatic segmentation algorithms is a must. In order to achieve, simultaneously, both dose accuracy and computation speed, the number of tetrahedrons for the lungs should be optimized. Although the current computation speed of our new 4D Monte Carlo simulation approach is slow (i.e. ~40 times slower than that of the conventional dose accumulation approach), this problem is resolvable by developing, in Geant4, a dedicated navigation class optimized for particle transportation in tetrahedral-mesh geometry. PMID:25615567

  11. Knowledge based acquisition of rules for medical diagnosis

    SciTech Connect

    Drastal, G.A.; Kulikowski, C.A.

    1982-01-01

    Medical consultation systems in the expert framework contain rules written under the guidance of expert physicians. The authors present a methodology and preliminary implementation of a system which learns compiled rule chains from positive case examples of a diagnostic class and negative examples of alternative diagnostic classes. Rule acquisition is guided by the constraints of physiological process models represented in the system. Evaluation of the system is proceeding in the area of glaucoma diagnosis, and an example of an experiment in this domain is included. 9 references.

  12. Deep learning based syndrome diagnosis of chronic gastritis.

    PubMed

    Liu, Guo-Ping; Yan, Jian-Jun; Wang, Yi-Qin; Zheng, Wu; Zhong, Tao; Lu, Xiong; Qian, Peng

    2014-01-01

    In Traditional Chinese Medicine (TCM), most of the algorithms used to solve problems of syndrome diagnosis are superficial structure algorithms and not considering the cognitive perspective from the brain. However, in clinical practice, there is complex and nonlinear relationship between symptoms (signs) and syndrome. So we employed deep leaning and multilabel learning to construct the syndrome diagnostic model for chronic gastritis (CG) in TCM. The results showed that deep learning could improve the accuracy of syndrome recognition. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice. PMID:24734118

  13. Deep Learning Based Syndrome Diagnosis of Chronic Gastritis

    PubMed Central

    Liu, Guo-Ping; Wang, Yi-Qin; Zheng, Wu; Zhong, Tao; Lu, Xiong; Qian, Peng

    2014-01-01

    In Traditional Chinese Medicine (TCM), most of the algorithms used to solve problems of syndrome diagnosis are superficial structure algorithms and not considering the cognitive perspective from the brain. However, in clinical practice, there is complex and nonlinear relationship between symptoms (signs) and syndrome. So we employed deep leaning and multilabel learning to construct the syndrome diagnostic model for chronic gastritis (CG) in TCM. The results showed that deep learning could improve the accuracy of syndrome recognition. Moreover, the studies will provide a reference for constructing syndrome diagnostic models and guide clinical practice. PMID:24734118

  14. Molecules-in-Molecules: An Extrapolated Fragment-Based Approach for Accurate Calculations on Large Molecules and Materials.

    PubMed

    Mayhall, Nicholas J; Raghavachari, Krishnan

    2011-05-10

    We present a new extrapolated fragment-based approach, termed molecules-in-molecules (MIM), for accurate energy calculations on large molecules. In this method, we use a multilevel partitioning approach coupled with electronic structure studies at multiple levels of theory to provide a hierarchical strategy for systematically improving the computed results. In particular, we use a generalized hybrid energy expression, similar in spirit to that in the popular ONIOM methodology, that can be combined easily with any fragmentation procedure. In the current work, we explore a MIM scheme which first partitions a molecule into nonoverlapping fragments and then recombines the interacting fragments to form overlapping subsystems. By including all interactions with a cheaper level of theory, the MIM approach is shown to significantly reduce the errors arising from a single level fragmentation procedure. We report the implementation of energies and gradients and the initial assessment of the MIM method using both biological and materials systems as test cases. PMID:26610128

  15. The multiscale coarse-graining method. XI. Accurate interactions based on the centers of charge of coarse-grained sites

    SciTech Connect

    Cao, Zhen; Voth, Gregory A.

    2015-12-28

    It is essential to be able to systematically construct coarse-grained (CG) models that can efficiently and accurately reproduce key properties of higher-resolution models such as all-atom. To fulfill this goal, a mapping operator is needed to transform the higher-resolution configuration to a CG configuration. Certain mapping operators, however, may lose information related to the underlying electrostatic properties. In this paper, a new mapping operator based on the centers of charge of CG sites is proposed to address this issue. Four example systems are chosen to demonstrate this concept. Within the multiscale coarse-graining framework, CG models that use this mapping operator are found to better reproduce the structural correlations of atomistic models. The present work also demonstrates the flexibility of the mapping operator and the robustness of the force matching method. For instance, important functional groups can be isolated and emphasized in the CG model.

  16. A new approach based on embedding Green's functions into fixed-point iterations for highly accurate solution to Troesch's problem

    NASA Astrophysics Data System (ADS)

    Kafri, H. Q.; Khuri, S. A.; Sayfy, A.

    2016-03-01

    In this paper, a novel approach is introduced for the solution of the non-linear Troesch's boundary value problem. The underlying strategy is based on Green's functions and fixed-point iterations, including Picard's and Krasnoselskii-Mann's schemes. The resulting numerical solutions are compared with both the analytical solutions and numerical solutions that exist in the literature. Convergence of the iterative schemes is proved via manipulation of the contraction principle. It is observed that the method handles the boundary layer very efficiently, reduces lengthy calculations, provides rapid convergence, and yields accurate results particularly for large eigenvalues. Indeed, to our knowledge, this is the first time that this problem is solved successfully for very large eigenvalues, actually the rate of convergence increases as the magnitude of the eigenvalues increases.

  17. Ranking of predictor variables based on effect size criterion provides an accurate means of automatically classifying opinion column articles

    NASA Astrophysics Data System (ADS)

    Legara, Erika Fille; Monterola, Christopher; Abundo, Cheryl

    2011-01-01

    We demonstrate an accurate procedure based on linear discriminant analysis that allows automatic authorship classification of opinion column articles. First, we extract the following stylometric features of 157 column articles from four authors: statistics on high frequency words, number of words per sentence, and number of sentences per paragraph. Then, by systematically ranking these features based on an effect size criterion, we show that we can achieve an average classification accuracy of 93% for the test set. In comparison, frequency size based ranking has an average accuracy of 80%. The highest possible average classification accuracy of our data merely relying on chance is ∼31%. By carrying out sensitivity analysis, we show that the effect size criterion is superior than frequency ranking because there exist low frequency words that significantly contribute to successful author discrimination. Consistent results are seen when the procedure is applied in classifying the undisputed Federalist papers of Alexander Hamilton and James Madison. To the best of our knowledge, the work is the first attempt in classifying opinion column articles, that by virtue of being shorter in length (as compared to novels or short stories), are more prone to over-fitting issues. The near perfect classification for the longer papers supports this claim. Our results provide an important insight on authorship attribution that has been overlooked in previous studies: that ranking discriminant variables based on word frequency counts is not necessarily an optimal procedure.

  18. A homotopy-based sparse representation for fast and accurate shape prior modeling in liver surgical planning.

    PubMed

    Wang, Guotai; Zhang, Shaoting; Xie, Hongzhi; Metaxas, Dimitris N; Gu, Lixu

    2015-01-01

    Shape prior plays an important role in accurate and robust liver segmentation. However, liver shapes have complex variations and accurate modeling of liver shapes is challenging. Using large-scale training data can improve the accuracy but it limits the computational efficiency. In order to obtain accurate liver shape priors without sacrificing the efficiency when dealing with large-scale training data, we investigate effective and scalable shape prior modeling method that is more applicable in clinical liver surgical planning system. We employed the Sparse Shape Composition (SSC) to represent liver shapes by an optimized sparse combination of shapes in the repository, without any assumptions on parametric distributions of liver shapes. To leverage large-scale training data and improve the computational efficiency of SSC, we also introduced a homotopy-based method to quickly solve the L1-norm optimization problem in SSC. This method takes advantage of the sparsity of shape modeling, and solves the original optimization problem in SSC by continuously transforming it into a series of simplified problems whose solution is fast to compute. When new training shapes arrive gradually, the homotopy strategy updates the optimal solution on the fly and avoids re-computing it from scratch. Experiments showed that SSC had a high accuracy and efficiency in dealing with complex liver shape variations, excluding gross errors and preserving local details on the input liver shape. The homotopy-based SSC had a high computational efficiency, and its runtime increased very slowly when repository's capacity and vertex number rose to a large degree. When repository's capacity was 10,000, with 2000 vertices on each shape, homotopy method cost merely about 11.29 s to solve the optimization problem in SSC, nearly 2000 times faster than interior point method. The dice similarity coefficient (DSC), average symmetric surface distance (ASD), and maximum symmetric surface distance measurement

  19. Surface Plasmon Resonance for Cell-Based Clinical Diagnosis

    PubMed Central

    Yanase, Yuhki; Hiragun, Takaaki; Ishii, Kaori; Kawaguchi, Tomoko; Yanase, Tetsuji; Kawai, Mikio; Sakamoto, Kenji; Hide, Michihiro

    2014-01-01

    Non-invasive real-time observations and the evaluation of living cell conditions and functions are increasingly demanded in life sciences. Surface plasmon resonance (SPR) sensors detect the refractive index (RI) changes on the surface of sensor chips in label-free and on a real-time basis. Using SPR sensors, we and other groups have developed techniques to evaluate living cells' reactions in response to stimuli without any labeling in a real-time manner. The SPR imaging (SPRI) system for living cells may visualize single cell reactions and has the potential to expand application of SPR cell sensing for clinical diagnosis, such as multi-array cell diagnostic systems and detection of malignant cells among normal cells in combination with rapid cell isolation techniques. PMID:24618778

  20. Computer-aided diagnosis workstation for chest diagnosis based on multihelical CT images

    NASA Astrophysics Data System (ADS)

    Sato, Hitoshi; Niki, Noboru; Mori, Kiyoshi; Eguchi, Kenji; Kaneko, Masahiro; Kakinuma, Ryutarou; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru; Sasagawa, Michizou

    2005-04-01

    Mass screening based on helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images and a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification. We also have developed electronic medical recording system and prototype internet system for the community health in two or more regions by using the Virtual Private Network router. This electronic medical recording system and prototype internet system were developed so as not to loosen the communication among staffs of hospital. Based on these diagnostic assistance methods, we have now developed a new computer-aided workstation and database that can display suspected lesions three-dimensionally in a short time. This paper describes basic studies that have been conducted to evaluate this new system.

  1. Computer-aided diagnosis workstation and network system for chest diagnosis based on multislice CT images

    NASA Astrophysics Data System (ADS)

    Satoh, Hitoshi; Niki, Noboru; Mori, Kiyoshi; Eguchi, Kenji; Kaneko, Masahiro; Kakinuma, Ryutarou; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru

    2007-03-01

    Multislice CT scanner advanced remarkably at the speed at which the chest CT images were acquired for mass screening. Mass screening based on multislice CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images and a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification. Moreover, we have provided diagnostic assistance methods to medical screening specialists by using a lung cancer screening algorithm built into mobile helical CT scanner for the lung cancer mass screening done in the region without the hospital. We also have developed electronic medical recording system and prototype internet system for the community health in two or more regions by using the Virtual Private Network router and Biometric fingerprint authentication system and Biometric face authentication system for safety of medical information. Based on these diagnostic assistance methods, we have now developed a new computer-aided workstation and database that can display suspected lesions three-dimensionally in a short time. This paper describes basic studies that have been conducted to evaluate this new system.

  2. Automatic and accurate reconstruction of distal humerus contours through B-Spline fitting based on control polygon deformation.

    PubMed

    Mostafavi, Kamal; Tutunea-Fatan, O Remus; Bordatchev, Evgueni V; Johnson, James A

    2014-12-01

    The strong advent of computer-assisted technologies experienced by the modern orthopedic surgery prompts for the expansion of computationally efficient techniques to be built on the broad base of computer-aided engineering tools that are readily available. However, one of the common challenges faced during the current developmental phase continues to remain the lack of reliable frameworks to allow a fast and precise conversion of the anatomical information acquired through computer tomography to a format that is acceptable to computer-aided engineering software. To address this, this study proposes an integrated and automatic framework capable to extract and then postprocess the original imaging data to a common planar and closed B-Spline representation. The core of the developed platform relies on the approximation of the discrete computer tomography data by means of an original two-step B-Spline fitting technique based on successive deformations of the control polygon. In addition to its rapidity and robustness, the developed fitting technique was validated to produce accurate representations that do not deviate by more than 0.2 mm with respect to alternate representations of the bone geometry that were obtained through different-contact-based-data acquisition or data processing methods. PMID:25515225

  3. Diagnosis by integrating model-based reasoning with knowledge-based reasoning

    NASA Technical Reports Server (NTRS)

    Bylander, Tom

    1988-01-01

    Our research investigates how observations can be categorized by integrating a qualitative physical model with experiential knowledge. Our domain is diagnosis of pathologic gait in humans, in which the observations are the gait motions, muscle activity during gait, and physical exam data, and the diagnostic hypotheses are the potential muscle weaknesses, muscle mistimings, and joint restrictions. Patients with underlying neurological disorders typically have several malfunctions. Among the problems that need to be faced are: the ambiguity of the observations, the ambiguity of the qualitative physical model, correspondence of the observations and hypotheses to the qualitative physical model, the inherent uncertainty of experiential knowledge, and the combinatorics involved in forming composite hypotheses. Our system divides the work so that the knowledge-based reasoning suggests which hypotheses appear more likely than others, the qualitative physical model is used to determine which hypotheses explain which observations, and another process combines these functionalities to construct a composite hypothesis based on explanatory power and plausibility. We speculate that the reasoning architecture of our system is generally applicable to complex domains in which a less-than-perfect physical model and less-than-perfect experiential knowledge need to be combined to perform diagnosis.

  4. Dixon sequence with superimposed model-based bone compartment provides highly accurate PET/MR attenuation correction of the brain

    PubMed Central

    Koesters, Thomas; Friedman, Kent P.; Fenchel, Matthias; Zhan, Yiqiang; Hermosillo, Gerardo; Babb, James; Jelescu, Ileana O.; Faul, David; Boada, Fernando E.; Shepherd, Timothy M.

    2016-01-01

    Simultaneous PET/MR of the brain is a promising new technology for characterizing patients with suspected cognitive impairment or epilepsy. Unlike CT though, MR signal intensities do not provide a direct correlate to PET photon attenuation correction (AC) and inaccurate radiotracer standard uptake value (SUV) estimation could limit future PET/MR clinical applications. We tested a novel AC method that supplements standard Dixon-based tissue segmentation with a superimposed model-based bone compartment. Methods We directly compared SUV estimation for MR-based AC methods to reference CT AC in 16 patients undergoing same-day, single 18FDG dose PET/CT and PET/MR for suspected neurodegeneration. Three Dixon-based MR AC methods were compared to CT – standard Dixon 4-compartment segmentation alone, Dixon with a superimposed model-based bone compartment, and Dixon with a superimposed bone compartment and linear attenuation correction optimized specifically for brain tissue. The brain was segmented using a 3D T1-weighted volumetric MR sequence and SUV estimations compared to CT AC for whole-image, whole-brain and 91 FreeSurfer-based regions-of-interest. Results Modifying the linear AC value specifically for brain and superimposing a model-based bone compartment reduced whole-brain SUV estimation bias of Dixon-based PET/MR AC by 95% compared to reference CT AC (P < 0.05) – this resulted in a residual −0.3% whole-brain mean SUV bias. Further, brain regional analysis demonstrated only 3 frontal lobe regions with SUV estimation bias of 5% or greater (P < 0.05). These biases appeared to correlate with high individual variability in the frontal bone thickness and pneumatization. Conclusion Bone compartment and linear AC modifications result in a highly accurate MR AC method in subjects with suspected neurodegeneration. This prototype MR AC solution appears equivalent than other recently proposed solutions, and does not require additional MR sequences and scan time. These

  5. Hyperspectral imaging-based spatially-resolved technique for accurate measurement of the optical properties of horticultural products

    NASA Astrophysics Data System (ADS)

    Cen, Haiyan

    Hyperspectral imaging-based spatially-resolved technique is promising for determining the optical properties and quality attributes of horticultural and food products. However, considerable challenges still exist for accurate determination of spectral absorption and scattering properties from intact horticultural products. The objective of this research was, therefore, to develop and optimize hyperspectral imaging-based spatially-resolved technique for accurate measurement of the optical properties of horticultural products. Monte Carlo simulations and experiments for model samples of known optical properties were performed to optimize the inverse algorithm of a single-layer diffusion model and the optical designs, for extracting the absorption (micro a) and reduced scattering (micros') coefficients from spatially-resolved reflectance profiles. The logarithm and integral data transformation and the relative weighting methods were found to greatly improve the parameter estimation accuracy with the relative errors of 10.4%, 10.7%, and 11.4% for micro a, and 6.6%, 7.0%, and 7.1% for micros', respectively. More accurate measurements of optical properties were obtained when the light beam was of Gaussian type with the diameter of less than 1 mm, and the minimum and maximum source-detector distances were 1.5 mm and 10--20 transport mean free paths, respectively. An optical property measuring prototype was built, based on the optimization results, and evaluated for automatic measurement of absorption and reduced scattering coefficients for the wavelengths of 500--1,000 nm. The instrument was used to measure the optical properties, and assess quality/maturity, of 500 'Redstar' peaches and 1039 'Golden Delicious' (GD) and 1040 'Delicious' (RD) apples. A separate study was also conducted on confocal laser scanning and scanning electron microscopic image analysis and compression test of fruit tissue specimens to measure the structural and mechanical properties of 'Golden

  6. Development of model-based fault diagnosis algorithms for MASCOTTE cryogenic test bench

    NASA Astrophysics Data System (ADS)

    Iannetti, A.; Marzat, J.; Piet-Lahanier, H.; Ordonneau, G.; Vingert, L.

    2014-12-01

    This article describes the on-going results of a fault diagnosis benchmark for a cryogenic rocket engine demonstrator. The benchmark consists in the use of classical model- based fault diagnosis methods to monitor the status of the cooling circuit of the MASCOTTE cryogenic bench. The algorithms developed are validated on real data from the last 2014 firing campaign (ATAC campaign). The objective of this demonstration is to find practical diagnosis alternatives to classical redline providing more flexible means of data exploitation in real time and for post processing.

  7. Accurate optical wavefront reconstruction based on reciprocity of an optical path using low resolution spatial light modulators

    NASA Astrophysics Data System (ADS)

    Li, Zhiyang

    2010-10-01

    A method for high precision optical wavefront reconstruction using low resolution spatial light modulators (SLMs) was proposed. It utilizes an adiabatic waveguide taper consisting of a plurality of single-mode waveguides to decompose an incident light field into simple fundamental modes of the single-mode waveguides. By digital generation of the conjugate fields of those simple fundamental modes a field proportional to the original incident light field might be reconstructed accurately based on reciprocity. Devices based on the method using transparent and reflective SLMs possess no aberration like that of a conventional optic lens and are able to achieve diffraction limited resolution. Specifically on the surface of the narrow end of a taper a resolution much higher than half of the wavelength is attainable. The device may work in linear mode and possesses unlimited theoretical 3D space-bandwidth product (SBP). The SBP of a real device is limited by the accuracy of SLMs. A pair of 8-bit SLMs with 1000 × 1000 = 10 6 pixels could provide a SBP of about 5 × 10 4. The SBP may expand by 16 times if 10-bit SLMs with the same number of pixels are employed or 16 successive frames are used to display one scene. The device might be used as high precision optical tweezers, or employed for continuous or discrete real-time 3D display, 3D measurement, machine vision, etc.

  8. There's plenty of gloom at the bottom: the many challenges of accurate quantitation in size-based oligomeric separations.

    PubMed

    Striegel, André M

    2013-11-01

    There is a variety of small-molecule species (e.g., tackifiers, plasticizers, oligosaccharides) the size-based characterization of which is of considerable scientific and industrial importance. Likewise, quantitation of the amount of oligomers in a polymer sample is crucial for the import and export of substances into the USA and European Union (EU). While the characterization of ultra-high molar mass macromolecules by size-based separation techniques is generally considered a challenge, it is this author's contention that a greater challenge is encountered when trying to perform, for quantitation purposes, separations in and of the oligomeric region. The latter thesis is expounded herein, by detailing the various obstacles encountered en route to accurate, quantitative oligomeric separations by entropically dominated techniques such as size-exclusion chromatography, hydrodynamic chromatography, and asymmetric flow field-flow fractionation, as well as by methods which are, principally, enthalpically driven such as liquid adsorption and temperature gradient interaction chromatography. These obstacles include, among others, the diminished sensitivity of static light scattering (SLS) detection at low molar masses, the non-constancy of the response of SLS and of commonly employed concentration-sensitive detectors across the oligomeric region, and the loss of oligomers through the accumulation wall membrane in asymmetric flow field-flow fractionation. The battle is not lost, however, because, with some care and given a sufficient supply of sample, the quantitation of both individual oligomeric species and of the total oligomeric region is often possible. PMID:23887277

  9. Accurate Segmentation of CT Male Pelvic Organs via Regression-Based Deformable Models and Multi-Task Random Forests.

    PubMed

    Gao, Yaozong; Shao, Yeqin; Lian, Jun; Wang, Andrew Z; Chen, Ronald C; Shen, Dinggang

    2016-06-01

    Segmenting male pelvic organs from CT images is a prerequisite for prostate cancer radiotherapy. The efficacy of radiation treatment highly depends on segmentation accuracy. However, accurate segmentation of male pelvic organs is challenging due to low tissue contrast of CT images, as well as large variations of shape and appearance of the pelvic organs. Among existing segmentation methods, deformable models are the most popular, as shape prior can be easily incorporated to regularize the segmentation. Nonetheless, the sensitivity to initialization often limits their performance, especially for segmenting organs with large shape variations. In this paper, we propose a novel approach to guide deformable models, thus making them robust against arbitrary initializations. Specifically, we learn a displacement regressor, which predicts 3D displacement from any image voxel to the target organ boundary based on the local patch appearance. This regressor provides a non-local external force for each vertex of deformable model, thus overcoming the initialization problem suffered by the traditional deformable models. To learn a reliable displacement regressor, two strategies are particularly proposed. 1) A multi-task random forest is proposed to learn the displacement regressor jointly with the organ classifier; 2) an auto-context model is used to iteratively enforce structural information during voxel-wise prediction. Extensive experiments on 313 planning CT scans of 313 patients show that our method achieves better results than alternative classification or regression based methods, and also several other existing methods in CT pelvic organ segmentation. PMID:26800531

  10. Scalable implementations of accurate excited-state coupled cluster theories: application of high-level methods to porphyrin based systems

    SciTech Connect

    Kowalski, Karol; Krishnamoorthy, Sriram; Olson, Ryan M.; Tipparaju, Vinod; Apra, Edoardo

    2011-11-30

    The development of reliable tools for excited-state simulations is emerging as an extremely powerful computational chemistry tool for understanding complex processes in the broad class of light harvesting systems and optoelectronic devices. Over the last years we have been developing equation of motion coupled cluster (EOMCC) methods capable of tackling these problems. In this paper we discuss the parallel performance of EOMCC codes which provide accurate description of the excited-state correlation effects. Two aspects are discuss in details: (1) a new algorithm for the iterative EOMCC methods based on the novel task scheduling algorithms, and (2) parallel algorithms for the non-iterative methods describing the effect of triply excited configurations. We demonstrate that the most computationally intensive non-iterative part can take advantage of 210,000 cores of the Cray XT5 system at OLCF. In particular, we demonstrate the importance of non-iterative many-body methods for achieving experimental level of accuracy for several porphyrin-based system.

  11. A novel biosensor based on competitive SERS immunoassay and magnetic separation for accurate and sensitive detection of chloramphenicol.

    PubMed

    Yang, Kang; Hu, Yongjun; Dong, Ning

    2016-06-15

    The accurate and sensitive detection of chloramphenicol (CAP) is particularly imperative to public health and safety. Here, we present a novel sensor for residual CAP detection based on competitive surface-enhanced Raman scattering (SERS) immunoassay and magnetic separation. In this nanosensor, functionalized Au nanoparticles (AuNPs) were labeled with the Raman reporter molecule (e.g. 4,4'-dipyridyl). With the addition of free CAP, a competitive immune reaction was initiated between free CAP and above AuNPs for conjugating with CAP antibody-modified magnetic nanoparticles (MNPs). Instead of the solid substrate, the antibody conjugated-magnetic beads were used as supporting materials and separation tools in the present sensor. With the aid of a magnet, the mixture was removed from the supernatant for concentration effects. This caused obvious change of SERS signal intensity obtained from supernatant. The SERS signals were collected from the supernatant directly, which made the SERS measurements more stable, repeatable and reliable. The proposed SERS-based magnetic immunosensor allows us to detect CAP in a fast, selective and sensitive (1.0 pg/mL) manner over a wide concentration range ( 1-1 × 10(4)pg/mL). In addition, these results demonstrate that this immunosensor holds great potential for the detection of antibiotics in real aquatic environment, which is crucial to our life. PMID:26866562

  12. Imaging-based diagnosis of autosomal dominant polycystic kidney disease.

    PubMed

    Pei, York; Hwang, Young-Hwan; Conklin, John; Sundsbak, Jamie L; Heyer, Christina M; Chan, Winnie; Wang, Kairong; He, Ning; Rattansingh, Anand; Atri, Mostafa; Harris, Peter C; Haider, Masoom A

    2015-03-01

    The clinical use of conventional ultrasonography (US) in autosomal dominant polycystic kidney disease (ADPKD) is currently limited by reduced diagnostic sensitivity, especially in at-risk subjects younger than 30 years of age. In this single-center prospective study, we compared the diagnostic performance of MRI with that of high-resolution (HR) US in 126 subjects ages 16-40 years born with a 50% risk of ADPKD who underwent both these renal imaging studies and comprehensive PKD1 and PKD2 mutation screening. Concurrently, 45 healthy control subjects without a family history of ADPKD completed the same imaging protocol. We analyzed 110 at-risk subjects whose disease status was unequivocally defined by molecular testing and 45 unaffected healthy control subjects. Using a total of >10 cysts as a test criterion in subjects younger than 30 years of age, we found that MRI provided both a sensitivity and specificity of 100%. Comparison of our results from HR US with those from a previous study of conventional US using the test criterion of a total of three or more cysts found a higher diagnostic sensitivity (approximately 97% versus approximately 82%) with a slightly decreased specificity (approximately 98% versus 100%) in this study. Similar results were obtained in test subjects between the ages of 30 and 40 years old. These results suggest that MRI is highly sensitive and specific for diagnosis of ADPKD. HR US has the potential to rival the diagnostic performance of MRI but is both center- and operator-dependent. PMID:25074509

  13. Improving model-based diagnosis through algebraic analysis: The Petri net challenge

    SciTech Connect

    Portinale, L.

    1996-12-31

    The present paper describes the empirical evaluation of a linear algebra approach to model-based diagnosis, in case the behavioral model of the device under examination is described through a Petri net model. In particular, we show that algebraic analysis based on P-invariants of the net model, can significantly improve the performance of a model-based diagnostic system, while keeping the integrity of a general framework defined from a formal logical theory. A system called INVADS is described and experimental results, performed on a car fault domain and involving the comparison of different implementations of P-invariant based diagnosis, are then discussed.

  14. Administrative Codes Combined with Medical Records-based Criteria Accurately Identified Bacterial Infections among Rheumatoid Arthritis Patients

    PubMed Central

    Patkar, Nivedita M.; Curtis, Jeffrey R.; Teng, Gim Gee; Allison, Jeroan J.; Saag, Michael; Martin, Carolyn; Saag, Kenneth G.

    2009-01-01

    Objective To evaluate diagnostic properties of International Classification of Diseases, Version 9 (ICD-9) diagnosis codes and infection criteria to identify bacterial infections among rheumatoid arthritis (RA) patients. Study Design and Setting We performed a cross- sectional study of RA patients with and without ICD-9 codes for bacterial infections. Sixteen bacterial infection criteria were developed. Diagnostic properties of comprehensive and restrictive sets of ICD-9 codes and the infection criteria were tested against an adjudicated review of medical records. Results Records on 162 RA patients with and 50 without purported bacterial infections were reviewed. Positive (PPV) and negative predictive values (NPVs) of ICD-9 codes ranged from 54% – 85% and 84% – 100%, respectively. PPVs of the medical records-based criteria were: 84% and 89% for “definite” and “definite or empirically treated” infections, respectively. PPV of infection criteria increased by 50% as disease prevalence increased using ICD-9 codes to enhance infection likelihood. Conclusion ICD-9 codes alone may misclassify bacterial infections in hospitalized RA patients. Misclassification varies with the specificity of the codes used and strength of evidence required to confirm infections. Combining ICD-9 codes with infection criteria identified infections with greatest accuracy. Novel infection criteria may limit the requirement to review medical records. PMID:18834713

  15. An Event-Based Approach to Distributed Diagnosis of Continuous Systems

    NASA Technical Reports Server (NTRS)

    Daigle, Matthew; Roychoudhurry, Indranil; Biswas, Gautam; Koutsoukos, Xenofon

    2010-01-01

    Distributed fault diagnosis solutions are becoming necessary due to the complexity of modern engineering systems, and the advent of smart sensors and computing elements. This paper presents a novel event-based approach for distributed diagnosis of abrupt parametric faults in continuous systems, based on a qualitative abstraction of measurement deviations from the nominal behavior. We systematically derive dynamic fault signatures expressed as event-based fault models. We develop a distributed diagnoser design algorithm that uses these models for designing local event-based diagnosers based on global diagnosability analysis. The local diagnosers each generate globally correct diagnosis results locally, without a centralized coordinator, and by communicating a minimal number of measurements between themselves. The proposed approach is applied to a multi-tank system, and results demonstrate a marked improvement in scalability compared to a centralized approach.

  16. Development of a component centered fault monitoring and diagnosis knowledge based system for space power system

    NASA Technical Reports Server (NTRS)

    Lee, S. C.; Lollar, Louis F.

    1988-01-01

    The overall approach currently being taken in the development of AMPERES (Autonomously Managed Power System Extendable Real-time Expert System), a knowledge-based expert system for fault monitoring and diagnosis of space power systems, is discussed. The system architecture, knowledge representation, and fault monitoring and diagnosis strategy are examined. A 'component-centered' approach developed in this project is described. Critical issues requiring further study are identified.

  17. Papanicolaou stain may not be necessary in majority of head and neck fine-needle aspirations: evidence from a correlation study between Diff-Quik-based onsite diagnosis and final diagnosis in 287 head and neck fine-needle aspirations.

    PubMed

    Wu, Maoxin; Idrees, Muhammad; Zhang, Zhengbin; Genden, Eric; Burstein, David E

    2010-11-01

    Fine-needle aspiration (FNA) is a useful tool for immediate assessment of palpable lesions, especially in the head and neck region. The objective of this study is to evaluate the degree of correlation between Diff-Quik-based onsite diagnosis (OD) and final diagnosis (FD) and further improve the efficiency of FNA practice. Two hundred and eighty-seven cytopathologist-performed FNAs from the head and neck region were evaluated. Number of passes, number and type of slides and correlation (agreement, modified final diagnosis and disagreement) between OD and FD were evaluated. Among 287 FNAs, the average number of passes per FNA case was 2 (range, 1-5&.rpar;). The mean number of slides reviewed per case was 5 including 2 Diff-Quik (D-Q)-stained slides, 2 Papanicolaou (Pap)-stained slides, and 1 cell block (CB)/1 cytospin (Cy). 247 of 287 (86%) cases showed agreement between OD and FD. FD on 36 out of 287 cases (12.5%) was slightly modified or refined after reviewing additional slides. A major diagnostic discrepancy was noted in four cases (1.5%), three of which were classified as squamous cell carcinoma on final diagnosis, and confirmed on surgical follow-up. Accurate diagnosis can be achieved in the majority (86%) of head and neck FNAs based on immediate examination of D-Q stained slides alone. In a small number of cases (12.5%), reviewing additional slides may refine the final diagnosis. In rare cases, especially cystic squamous lesions, Pap-stained slides appeared to be helpful. It is plausible to use D-Q-stained slides alone with most head and neck FNAs in order to provide more cost effective and efficient triaging and patient management. PMID:20301212

  18. A Hybrid Intelligent Diagnosis Approach for Quick Screening of Alzheimer's Disease Based on Multiple Neuropsychological Rating Scales

    PubMed Central

    Zhao, Yinhong; Lu, Xudong; Duan, Huilong

    2015-01-01

    Neuropsychological testing is an effective means for the screening of Alzheimer's disease. Multiple neuropsychological rating scales should be used together to get subjects' comprehensive cognitive state due to the limitation of a single scale, but it is difficult to operate in primary clinical settings because of the inadequacy of time and qualified clinicians. Aiming at identifying AD's stages more accurately and conveniently in screening, we proposed a computer-aided diagnosis approach based on critical items extracted from multiple neuropsychological scales. The proposed hybrid intelligent approach combines the strengths of rough sets, genetic algorithm, and Bayesian network. There are two stages: one is attributes reduction technique based on rough sets and genetic algorithm, which can find out the most discriminative items for AD diagnosis in scales; the other is uncertain reasoning technique based on Bayesian network, which can forecast the probability of suffering from AD. The experimental data set consists of 500 cases collected by a top hospital in China and each case is determined by the expert panel. The results showed that the proposed approach could not only reduce items drastically with the same classification precision, but also perform better on identifying different stages of AD comparing with other existing scales. PMID:25815043

  19. A hybrid intelligent diagnosis approach for quick screening of Alzheimer's disease based on multiple neuropsychological rating scales.

    PubMed

    Yin, Ziming; Zhao, Yinhong; Lu, Xudong; Duan, Huilong

    2015-01-01

    Neuropsychological testing is an effective means for the screening of Alzheimer's disease. Multiple neuropsychological rating scales should be used together to get subjects' comprehensive cognitive state due to the limitation of a single scale, but it is difficult to operate in primary clinical settings because of the inadequacy of time and qualified clinicians. Aiming at identifying AD's stages more accurately and conveniently in screening, we proposed a computer-aided diagnosis approach based on critical items extracted from multiple neuropsychological scales. The proposed hybrid intelligent approach combines the strengths of rough sets, genetic algorithm, and Bayesian network. There are two stages: one is attributes reduction technique based on rough sets and genetic algorithm, which can find out the most discriminative items for AD diagnosis in scales; the other is uncertain reasoning technique based on Bayesian network, which can forecast the probability of suffering from AD. The experimental data set consists of 500 cases collected by a top hospital in China and each case is determined by the expert panel. The results showed that the proposed approach could not only reduce items drastically with the same classification precision, but also perform better on identifying different stages of AD comparing with other existing scales. PMID:25815043

  20. Change in the diagnosis of inflammatory bowel disease: a hospital-based cohort study from Korea

    PubMed Central

    Lee, Ho-Su; Choe, Jaewon; Lee, Hyo Jeong; Hwang, Sung Wook; Park, Sang Hyoung; Yang, Dong-Hoon; Kim, Kyung-Jo; Ye, Byong Duk; Byeon, Jeong-Sik; Myung, Seung-Jae; Yoon, Yong Sik; Yu, Chang Sik; Kim, Jin-Ho

    2016-01-01

    Background/Aims Accurately diagnosing inflammatory bowel disease (IBD) remains a challenge, but is crucial for providing proper management for affected patients. The aim of the present study was to evaluate the frequency of change in diagnosis in Korean patients who were referred to our institution with a diagnosis of IBD. Methods We enrolled 1,444 patients diagnosed with ulcerative colitis (UC) and 1,452 diagnosed with Crohn's disease (CD), who had been referred to the Asan Medical Center between January 2010 and December 2014. These patients were assessed and subsequently classified as having UC, CD, indeterminate colitis, possible IBD, or non-IBD. Results During a median follow-up of 15.9 months, 400 of the 2,896 patients (13.8%) analyzed in this study experienced a change in diagnosis. A change in diagnosis from UC to CD, or vice-versa, was made in 24 of 1,444 patients (1.7%) and 23 of 1,452 patients (1.6%), respectively. A change to a non-IBD diagnosis was the most common modification; 7.5% (108 of 1444) and 12.7% (184 of 1452) of the patients with a referral diagnosis of UC and CD, respectively, were reclassified as having non-IBD. Among the 292 patients who were ultimately determined not to have IBD, 135 (55 UC and 80 CD cases) had received IBD-related medication. Conclusions There are diagnostic uncertainties and difficulties in relation to IBD. Therefore, precise assessment and systematic follow-up are essential in the management of this condition. PMID:27433148

  1. All-solid very large mode area ytterbium-doped silica microstructured fiber based on accurate control on cladding index.

    PubMed

    Wei, Huifeng; Chen, Kangkang; Yang, Yucheng; Li, Jinyan

    2016-04-18

    We have demonstrated a new approach for developing very large mode area silica-based microstructured Ytterbium (Yb)-doped fibers. The microstructured region acting as pump cladding around the core is composed by periodically arranged low-index Fluorine-doped silica inclusions with an extremely low filling ratio of 0.088. To the best of our knowledge, we achieved the most accurate controlling on cladding index by 1 × 10-5 via our passively doped cladding (PDC) method. Two fibers with 127μm and 50μm core diameter respectively were fabricated from the same final preform designed by this approach. It is verified that our 50μm core diameter fiber can maintain robust single mode behavior at 1064nm wavelength. The advantage of an all-solid structure along with a much simpler fabrication process makes our approach very suitable for realizing very large mode area fibers for high power fiber laser application. PMID:27137328

  2. Accurate D-bar Reconstructions of Conductivity Images Based on a Method of Moment with Sinc Basis.

    PubMed

    Abbasi, Mahdi

    2014-01-01

    Planar D-bar integral equation is one of the inverse scattering solution methods for complex problems including inverse conductivity considered in applications such as Electrical impedance tomography (EIT). Recently two different methodologies are considered for the numerical solution of D-bar integrals equation, namely product integrals and multigrid. The first one involves high computational burden and the other one suffers from low convergence rate (CR). In this paper, a novel high speed moment method based using the sinc basis is introduced to solve the two-dimensional D-bar integral equation. In this method, all functions within D-bar integral equation are first expanded using the sinc basis functions. Then, the orthogonal properties of their products dissolve the integral operator of the D-bar equation and results a discrete convolution equation. That is, the new moment method leads to the equation solution without direct computation of the D-bar integral. The resulted discrete convolution equation maybe adapted to a suitable structure to be solved using fast Fourier transform. This allows us to reduce the order of computational complexity to as low as O (N (2)log N). Simulation results on solving D-bar equations arising in EIT problem show that the proposed method is accurate with an ultra-linear CR. PMID:24696808

  3. Accurate D-bar Reconstructions of Conductivity Images Based on a Method of Moment with Sinc Basis

    PubMed Central

    Abbasi, Mahdi

    2014-01-01

    Planar D-bar integral equation is one of the inverse scattering solution methods for complex problems including inverse conductivity considered in applications such as Electrical impedance tomography (EIT). Recently two different methodologies are considered for the numerical solution of D-bar integrals equation, namely product integrals and multigrid. The first one involves high computational burden and the other one suffers from low convergence rate (CR). In this paper, a novel high speed moment method based using the sinc basis is introduced to solve the two-dimensional D-bar integral equation. In this method, all functions within D-bar integral equation are first expanded using the sinc basis functions. Then, the orthogonal properties of their products dissolve the integral operator of the D-bar equation and results a discrete convolution equation. That is, the new moment method leads to the equation solution without direct computation of the D-bar integral. The resulted discrete convolution equation maybe adapted to a suitable structure to be solved using fast Fourier transform. This allows us to reduce the order of computational complexity to as low as O (N2log N). Simulation results on solving D-bar equations arising in EIT problem show that the proposed method is accurate with an ultra-linear CR. PMID:24696808

  4. Computer-aided diagnosis workstation and telemedicine network system for chest diagnosis based on multislice CT images

    NASA Astrophysics Data System (ADS)

    Satoh, Hitoshi; Niki, Noboru; Eguchi, Kenji; Ohmatsu, Hironobu; Kakinuma, Ryutaru; Moriyama, Noriyuki

    2009-02-01

    Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. Moreover, the doctor who diagnoses a medical image is insufficient in Japan. To overcome these problems, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images, a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification and a vertebra body analysis algorithm for quantitative evaluation of osteoporosis likelihood by using helical CT scanner for the lung cancer mass screening. The functions to observe suspicious shadow in detail are provided in computer-aided diagnosis workstation with these screening algorithms. We also have developed the telemedicine network by using Web medical image conference system with the security improvement of images transmission, Biometric fingerprint authentication system and Biometric face authentication system. Biometric face authentication used on site of telemedicine makes "Encryption of file" and "Success in login" effective. As a result, patients' private information is protected. We can share the screen of Web medical image conference system from two or more web conference terminals at the same time. An opinion can be exchanged mutually by using a camera and a microphone that are connected with workstation. Based on these diagnostic assistance methods, we have developed a new computer-aided workstation and a new telemedicine network that can display suspected lesions three-dimensionally in a short time. The results of this study indicate that our radiological information system without film by using computer-aided diagnosis workstation and our telemedicine network system can increase diagnostic speed, diagnostic accuracy and

  5. Optimal multivariate method for Raman spectroscopy based diagnosis of nasopharyngeal carcinoma

    NASA Astrophysics Data System (ADS)

    Chen, Bingling; Li, Shaoxin; Li, Jianghua; Guo, Zhouyi; Chen, Qiuyan; Mai, Haiqiang

    2013-12-01

    In this paper, we evaluated four kinds of classification algorithms on Raman spectra for nasopharyngeal carcinoma (NPC) diagnosis: Bayesian classification (BC), Linear discriminate analysis (LDA), Mahalanobis distance after the principal component analysis (PCA); as well the Genetic algorithm-LDA. A total of 225 Raman spectra were acquired from 120 tissue sites of 63 patients, in which 56 Raman spectra were from normal tissue, whereas 171 Raman spectra were from cancer nasopharyngeal tissue. The averaged Raman spectrum of NPC could be distinguished from that of the control group by the above multivariate analysis. Discrimination analysis of PCA-BC revealed that the highest sensitivity, specificity and overall accuracy of cancer diagnosis were 98% (1/56), 99% (1/171), and 99%, respectively. The results showed that Raman spectroscopy in combination with Bayesian classification had high enough sensitivity and specificity to accurately detect and diagnose NPC.

  6. Diagnosis of Morquio Syndrome in Dried Blood Spots Based on a New MRM-MS Assay

    PubMed Central

    Cozma, Claudia; Eichler, Sabrina; Wittmann, Gyula; Flores Bonet, Alba; Kramp, Guido Johannes; Giese, Anne-Katrin; Rolfs, Arndt

    2015-01-01

    Background Mucopolysaccharidosis IVA (MPS IVA; Morquio A disease) is an autosomal recessive disease caused and characterized by a decreased activity of N-acetylgalactosamine-6-sulfate sulfatase (GALNS), resulting in accumulation of keratan sulfate and chondroitin-6-sulfate in tissues and secondary organ damage. Recently approved enzyme replacement therapy renders the easy and early identification of MPS IVA of out-most importance. Methodology We propose a completely new assay for the stable and reproducible detection of GALNS deficiency in dry blood spots (DBS). For the validation blood samples were taken from 59 healthy individuals and 24 randomly selected genetically confirmed MPS IVA patients. The material extracted from DBS was incubated with a 4-methylumbelliferyl-β-D-galactopyranoside-6-sulfate as a specific substrate. Final enzymatic product, 4-methylumbelliferone, obtained after adding exogenous beta-galactosidase, was quantified by LC/MRM-MS (liquid-chromatography/multiple-reaction-monitoring mass-spectrometry). 4-propyl-5-hydroxy-7-methyl-2h-chromen-2-one was used as internal standard, a compound with a similar molecular structure and fragmentation pattern in negative ion mode as 4-methylumbelliferone. Findings The enzymatic assay yielded a positive and negative predictive value of 1.0 for genetically confirmed MPS IVA patients (GALNS activity of 0.35 ± 0.21 μmol/L/h) and for controls with normal GALNS activity (23.1 ± 5.3 μmol/L /h). With present enzymatic conditions, the reaction yield in dried blood spots is at least 20 fold higher than any previously reported data with other assays. Interpretation The present LC/MRM-MS based assay for MPS IVA diagnosis provides an easy, highly-standardized, accurate and innovative quantification of the enzymatic product in vitro and distinguishes perfectly between MPS IVA affected patients and normal controls. This technique will significantly simplify the early detection of MPS IVA patients. PMID:26147980

  7. Is there a role for DWI in the diagnosis of sacroiliitis based on ASAS criteria?

    PubMed Central

    Sahin, Neslin; Hacibeyoglu, Hatice; Ince, Ozlem; Solak, Aynur; Uyar, Belkiz; Erol, Ozlem; Uslu, Zulal Alnur; Kobak, Senol

    2015-01-01

    Purpose: Sacroiliitis based on MRI is one of the main diagnostic criteria of axial spondyloarthritis (SpA). Our purpose was to assess (a) whether apparent diffusion coefficient (ADC) values on diffusion-weighted imaging (DWI) differ between regions of bone marrow edema (BME) and subchondral normal-appearing bone marrow (NABM) in active sacroiliitis, (b) whether ADC values can differentiate early SpA and chronic SpA, both in the active and inactive phase, and (c) whether ADC values are related to laboratory findings. Materials and methods: 47 patients (24 female, 23 male, mean age: 38.53 years) with the diagnosis of SpA were included in this retrospective study. 20 age- and sex-matched subjects without SpA constituted the control group. ADC measurements were taken from all lesions and NABM of each sacroiliac joint. Results: A total number of 120 subchondral BME lesions (acute: 17, chronic active: 103) were noted. The mean ADC values of the BME lesions (1.30 ± 0.18 × 10-3 mm2/s) were significantly higher than the ADC values in the NABM regions (0.55 ± 0.08 × 10-3 mm2/s) as well as in both the control group (0.56 ± 0.05 × 10-3 mm2/s) and the chronic inactive group (0.54 ± 0.03 × 10-3 mm2/s). There were more BME regions in patients with chronic active sacroiliitis than early SpA patients. Correlation was found between the CRP values and ADC values. Conclusion: DWI with ADC values may be complementary to FS T2-weighted or STIR MR images for accurately diagnosing inflammatory sacroiliitis. The value of DWI versus dynamic contrast-enhanced imaging in the follow-up needs to be clarified. PMID:26221298

  8. Limitations of haemozoin-based diagnosis of Plasmodium falciparum using dark-field microscopy

    PubMed Central

    2014-01-01

    Background The haemozoin crystal continues to be investigated extensively for its potential as a biomarker for malaria diagnostics. In order for haemozoin to be a valuable biomarker, it must be present in detectable quantities in the peripheral blood and distinguishable from false positives. Here, dark-field microscopy coupled with sophisticated image processing algorithms is used to characterize the abundance of detectable haemozoin within infected erythrocytes from field samples in order to determine the window of detection in peripheral blood. Methods Thin smears from Plasmodium falciparum-infected and uninfected patients were imaged in both dark field (DF) unstained and bright field (BF) Giemsa-stained modes. The images were co-registered such that each parasite had thumbnails in both BF and DF modes, providing an accurate map between parasites and DF objects. This map was used to find the abundance of haemozoin as a function of parasite stage through careful parasite staging and correlation with DF objects. An automated image-processing and classification algorithm classified the bright spots in the DF images as either haemozoin or non-haemozoin objects. Results The algorithm distinguishes haemozoin from non-haemozoin objects in DF images with an object-level sensitivity of 95% and specificity of 97%. Ring stages older than about 6 hours begin to show detectable haemozoin, and rings between 10–16 hours reliably contain detectable haemozoin. However, DF microscopy coupled with the image-processing algorithm detect no haemozoin in rings younger than six hours. Discussion Although this method demonstrates the most sensitive detection of haemozoin in field samples reported to date, it does not detect haemozoin in ring-stage parasites younger than six hours. Thus, haemozoin is a poor biomarker for field samples primarily composed of young ring-stage parasites because the crystal is not present in detectable quantities by the methods described here. Based on

  9. Egnos-Based Multi-Sensor Accurate and Reliable Navigation in Search-And Missions with Uavs

    NASA Astrophysics Data System (ADS)

    Molina, P.; Colomina, I.; Vitoria, T.; Silva, P. F.; Stebler, Y.; Skaloud, J.; Kornus, W.; Prades, R.

    2011-09-01

    This paper will introduce and describe the goals, concept and overall approach of the European 7th Framework Programme's project named CLOSE-SEARCH, which stands for 'Accurate and safe EGNOS-SoL Navigation for UAV-based low-cost SAR operations'. The goal of CLOSE-SEARCH is to integrate in a helicopter-type unmanned aerial vehicle, a thermal imaging sensor and a multi-sensor navigation system (based on the use of a Barometric Altimeter (BA), a Magnetometer (MAGN), a Redundant Inertial Navigation System (RINS) and an EGNOS-enabled GNSS receiver) with an Autonomous Integrity Monitoring (AIM) capability, to support the search component of Search-And-Rescue operations in remote, difficult-to-access areas and/or in time critical situations. The proposed integration will result in a hardware and software prototype that will demonstrate an end-to-end functionality, that is to fly in patterns over a region of interest (possibly inaccessible) during day or night and also under adverse weather conditions and locate there disaster survivors or lost people through the detection of the body heat. This paper will identify the technical challenges of the proposed approach, from navigating with a BA/MAGN/RINS/GNSS-EGNOSbased integrated system to the interpretation of thermal images for person identification. Moreover, the AIM approach will be described together with the proposed integrity requirements. Finally, this paper will show some results obtained in the project during the first test campaign performed on November 2010. On that day, a prototype was flown in three different missions to assess its high-level performance and to observe some fundamental mission parameters as the optimal flying height and flying speed to enable body recognition. The second test campaign is scheduled for the end of 2011.

  10. Fault Diagnosis Strategies for SOFC-Based Power Generation Plants.

    PubMed

    Costamagna, Paola; De Giorgi, Andrea; Gotelli, Alberto; Magistri, Loredana; Moser, Gabriele; Sciaccaluga, Emanuele; Trucco, Andrea

    2016-01-01

    The success of distributed power generation by plants based on solid oxide fuel cells (SOFCs) is hindered by reliability problems that can be mitigated through an effective fault detection and isolation (FDI) system. However, the numerous operating conditions under which such plants can operate and the random size of the possible faults make identifying damaged plant components starting from the physical variables measured in the plant very difficult. In this context, we assess two classical FDI strategies (model-based with fault signature matrix and data-driven with statistical classification) and the combination of them. For this assessment, a quantitative model of the SOFC-based plant, which is able to simulate regular and faulty conditions, is used. Moreover, a hybrid approach based on the random forest (RF) classification method is introduced to address the discrimination of regular and faulty situations due to its practical advantages. Working with a common dataset, the FDI performances obtained using the aforementioned strategies, with different sets of monitored variables, are observed and compared. We conclude that the hybrid FDI strategy, realized by combining a model-based scheme with a statistical classifier, outperforms the other strategies. In addition, the inclusion of two physical variables that should be measured inside the SOFCs can significantly improve the FDI performance, despite the actual difficulty in performing such measurements. PMID:27556472

  11. Online model-based diagnosis to support autonomous operation of an advanced life support system

    NASA Technical Reports Server (NTRS)

    Biswas, Gautam; Manders, Eric-Jan; Ramirez, John; Mahadevan, Nagabhusan; Abdelwahed, Sherif

    2004-01-01

    This article describes methods for online model-based diagnosis of subsystems of the advanced life support system (ALS). The diagnosis methodology is tailored to detect, isolate, and identify faults in components of the system quickly so that fault-adaptive control techniques can be applied to maintain system operation without interruption. We describe the components of our hybrid modeling scheme and the diagnosis methodology, and then demonstrate the effectiveness of this methodology by building a detailed model of the reverse osmosis (RO) system of the water recovery system (WRS) of the ALS. This model is validated with real data collected from an experimental testbed at NASA JSC. A number of diagnosis experiments run on simulated faulty data are presented and the results are discussed.

  12. Online model-based diagnosis to support autonomous operation of an advanced life support system.

    PubMed

    Biswas, Gautam; Manders, Eric-Jan; Ramirez, John; Mahadevan, Nagabhusan; Abdelwahed, Sherif

    2004-01-01

    This article describes methods for online model-based diagnosis of subsystems of the advanced life support system (ALS). The diagnosis methodology is tailored to detect, isolate, and identify faults in components of the system quickly so that fault-adaptive control techniques can be applied to maintain system operation without interruption. We describe the components of our hybrid modeling scheme and the diagnosis methodology, and then demonstrate the effectiveness of this methodology by building a detailed model of the reverse osmosis (RO) system of the water recovery system (WRS) of the ALS. This model is validated with real data collected from an experimental testbed at NASA JSC. A number of diagnosis experiments run on simulated faulty data are presented and the results are discussed. PMID:15880907

  13. Broken wires diagnosis method numerical simulation based on smart cable structure

    NASA Astrophysics Data System (ADS)

    Li, Sheng; Zhou, Min; Yang, Yan

    2014-12-01

    The smart cable with embedded distributed fiber optical Bragg grating (FBG) sensors was chosen as the object to study a new diagnosis method about broken wires of the bridge cable. The diagnosis strategy based on cable force and stress distribution state of steel wires was put forward. By establishing the bridge-cable and cable-steel wires model, the broken wires sample database was simulated numerically. A method of the characterization cable state pattern which can both represent the degree and location of broken wires inside a cable was put forward. The training and predicting results of the sample database by the back propagation (BP) neural network showed that the proposed broken wires diagnosis method was feasible and expanded the broken wires diagnosis research area by using the smart cable which was used to be only representing cable force.

  14. High-Throughput Sequencing, a Versatile Weapon to Support Genome-Based Diagnosis in Infectious Diseases: Applications to Clinical Bacteriology

    PubMed Central

    Caboche, Ségolène; Audebert, Christophe; Hot, David

    2014-01-01

    The recent progresses of high-throughput sequencing (HTS) technologies enable easy and cost-reduced access to whole genome sequencing (WGS) or re-sequencing. HTS associated with adapted, automatic and fast bioinformatics solutions for sequencing applications promises an accurate and timely identification and characterization of pathogenic agents. Many studies have demonstrated that data obtained from HTS analysis have allowed genome-based diagnosis, which has been consistent with phenotypic observations. These proofs of concept are probably the first steps toward the future of clinical microbiology. From concept to routine use, many parameters need to be considered to promote HTS as a powerful tool to help physicians and clinicians in microbiological investigations. This review highlights the milestones to be completed toward this purpose. PMID:25437800

  15. Physically-based modeling of speed sensors for fault diagnosis and fault tolerant control in wind turbines

    NASA Astrophysics Data System (ADS)

    Weber, Wolfgang; Jungjohann, Jonas; Schulte, Horst

    2014-12-01

    In this paper, a generic physically-based modeling framework for encoder type speed sensors is derived. The consideration takes into account the nominal fault-free and two most relevant fault cases. The advantage of this approach is a reconstruction of the output waveforms in dependence of the internal physical parameter changes which enables a more accurate diagnosis and identification of faulty incremental encoders i.a. in wind turbines. The objectives are to describe the effect of the tilt and eccentric of the encoder disk on the digital output signals and the influence of the accuracy of the speed measurement in wind turbines. Simulation results show the applicability and effectiveness of the proposed approach.

  16. Improving liver fibrosis diagnosis based on forward and backward second harmonic generation signals

    NASA Astrophysics Data System (ADS)

    Peng, Qiwen; Zhuo, Shuangmu; So, Peter T. C.; Yu, Hanry

    2015-02-01

    The correlation of forward second harmonic generation (SHG) signal and backward SHG signal in different liver fibrosis stages was investigated. We found that three features, including the collagen percentage for forward SHG, the collagen percentage for backward SHG, and the average intensity ratio of two kinds of SHG signals, can quantitatively stage liver fibrosis in thioacetamide-induced rat model. We demonstrated that the combination of all three features by using a support vector machine classification algorithm can provide a more accurate prediction than each feature alone in fibrosis diagnosis.

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

    NASA Technical Reports Server (NTRS)

    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.

  18. Development of fault diagnosis system for transformer based on multi-class support vector machines

    NASA Astrophysics Data System (ADS)

    Cao, Jian; Qian, Suxiang; Hu, Hongsheng; Yan, Gongbiao

    2007-12-01

    The support vector machine (SVM) is an algorithm based on structure risk minimizing principle and having high generalization ability. It is strong to solve the problem with small sample, nonlinear and high dimension. The fundamental theory of DGA (Dissolved Gas Analysis, DGA) and fault characteristic of transformer is firstly researched in this paper, and then the disadvantages of traditional method of transformer fault diagnosis are analyzed, finally, a new fault diagnosis method using multi-class support vector machines (M-SVMs) based on DGA theory for transformer is put forward. Then the fault diagnosis model based on M-SVMs for transformer is established. At the same time, the fault diagnosis system based on M-SVMs for transformer is developed. The system can realize the acquisition of the dissolving gas in the transformer oil and data timely and low cost transmission by GPRS (General Packet Radio Service, GPRS). And it can identify out the transformer running state according to the acquisition data. The test results show that the method proposed has an excellent performance on correct ratio. And it can overcome the disadvantage of the traditional three-ratio method which lacks of fault coding and no fault types in the existent coding. Combining the wireless communication technology with the monitoring technology, the designed and developed system can greatly improve the real-time and continuity for the transformer' condition monitoring and fault diagnosis.

  19. Prediction of colorectal cancer diagnosis based on circulating plasma proteins.

    PubMed

    Surinova, Silvia; Choi, Meena; Tao, Sha; Schüffler, Peter J; Chang, Ching-Yun; Clough, Timothy; Vysloužil, Kamil; Khoylou, Marta; Srovnal, Josef; Liu, Yansheng; Matondo, Mariette; Hüttenhain, Ruth; Weisser, Hendrik; Buhmann, Joachim M; Hajdúch, Marián; Brenner, Hermann; Vitek, Olga; Aebersold, Ruedi

    2015-09-01

    Non-invasive detection of colorectal cancer with blood-based markers is a critical clinical need. Here we describe a phased mass spectrometry-based approach for the discovery, screening, and validation of circulating protein biomarkers with diagnostic value. Initially, we profiled human primary tumor tissue epithelia and characterized about 300 secreted and cell surface candidate glycoproteins. These candidates were then screened in patient systemic circulation to identify detectable candidates in blood plasma. An 88-plex targeting method was established to systematically monitor these proteins in two large and independent cohorts of plasma samples, which generated quantitative clinical datasets at an unprecedented scale. The data were deployed to develop and evaluate a five-protein biomarker signature for colorectal cancer detection. PMID:26253081

  20. Shape-based diagnosis of the aortic valve

    NASA Astrophysics Data System (ADS)

    Ionasec, Razvan Ioan; Tsymbal, Alexey; Vitanovski, Dime; Georgescu, Bogdan; Zhou, S. Kevin; Navab, Nassir; Comaniciu, Dorin

    2009-02-01

    Disorders of the aortic valve represent a common cardiovascular disease and an important public-health problem worldwide. Pathological valves are currently determined from 2D images through elaborate qualitative evalu- ations and complex measurements, potentially inaccurate and tedious to acquire. This paper presents a novel diagnostic method, which identies diseased valves based on 3D geometrical models constructed from volumetric data. A parametric model, which includes relevant anatomic landmarks as well as the aortic root and lea ets, represents the morphology of the aortic valve. Recently developed robust segmentation methods are applied to estimate the patient specic model parameters from end-diastolic cardiac CT volumes. A discriminative distance function, learned from equivalence constraints in the product space of shape coordinates, determines the corresponding pathology class based on the shape information encoded by the model. Experiments on a heterogeneous set of 63 patients aected by various diseases demonstrated the performance of our method with 94% correctly classied valves.

  1. Automatic construction of a large-scale and accurate drug-side-effect association knowledge base from biomedical literature.

    PubMed

    Xu, Rong; Wang, QuanQiu

    2014-10-01

    Systems approaches to studying drug-side-effect (drug-SE) associations are emerging as an active research area for drug target discovery, drug repositioning, and drug toxicity prediction. However, currently available drug-SE association databases are far from being complete. Herein, in an effort to increase the data completeness of current drug-SE relationship resources, we present an automatic learning approach to accurately extract drug-SE pairs from the vast amount of published biomedical literature, a rich knowledge source of side effect information for commercial, experimental, and even failed drugs. For the text corpus, we used 119,085,682 MEDLINE sentences and their parse trees. We used known drug-SE associations derived from US Food and Drug Administration (FDA) drug labels as prior knowledge to find relevant sentences and parse trees. We extracted syntactic patterns associated with drug-SE pairs from the resulting set of parse trees. We developed pattern-ranking algorithms to prioritize drug-SE-specific patterns. We then selected a set of patterns with both high precisions and recalls in order to extract drug-SE pairs from the entire MEDLINE. In total, we extracted 38,871 drug-SE pairs from MEDLINE using the learned patterns, the majority of which have not been captured in FDA drug labels to date. On average, our knowledge-driven pattern-learning approach in extracting drug-SE pairs from MEDLINE has achieved a precision of 0.833, a recall of 0.407, and an F1 of 0.545. We compared our approach to a support vector machine (SVM)-based machine learning and a co-occurrence statistics-based approach. We show that the pattern-learning approach is largely complementary to the SVM- and co-occurrence-based approaches with significantly higher precision and F1 but lower recall. We demonstrated by correlation analysis that the extracted drug side effects correlate positively with both drug targets, metabolism, and indications. PMID:24928448

  2. An accurate and inexpensive color-based assay for detecting severe anemia in a limited-resource setting.

    PubMed

    McGann, Patrick T; Tyburski, Erika A; de Oliveira, Vysolela; Santos, Brigida; Ware, Russell E; Lam, Wilbur A

    2015-12-01

    Severe anemia is an important cause of morbidity and mortality among children in resource-poor settings, but laboratory diagnostics are often limited in these locations. To address this need, we developed a simple, inexpensive, and color-based point-of-care (POC) assay to detect severe anemia. The purpose of this study was to evaluate the accuracy of this novel POC assay to detect moderate and severe anemia in a limited-resource setting. The study was a cross-sectional study conducted on children with sickle cell anemia in Luanda, Angola. The hemoglobin concentrations obtained by the POC assay were compared to reference values measured by a calibrated automated hematology analyzer. A total of 86 samples were analyzed (mean hemoglobin concentration 6.6 g/dL). There was a strong correlation between the hemoglobin concentrations obtained by the POC assay and reference values obtained from an automated hematology analyzer (r=0.88, P<0.0001). The POC assay demonstrated excellent reproducibility (r=0.93, P<0.0001) and the reagents appeared to be durable in a tropical setting (r=0.93, P<0.0001). For the detection of severe anemia that may require blood transfusion (hemoglobin <5 g/dL), the POC assay had sensitivity of 88.9% and specificity of 98.7%. These data demonstrate that an inexpensive (<$0.25 USD) POC assay accurately estimates low hemoglobin concentrations and has the potential to become a transformational diagnostic tool for severe anemia in limited-resource settings. PMID:26317494

  3. RNA-Based Detection Does not Accurately Enumerate Living Escherichia coli O157:H7 Cells on Plants

    PubMed Central

    Ju, Wenting; Moyne, Anne-Laure; Marco, Maria L.

    2016-01-01

    The capacity to distinguish between living and dead cells is an important, but often unrealized, attribute of rapid detection methods for foodborne pathogens. In this study, the numbers of enterohemorrhagic Escherichia coli O157:H7 after inoculation onto Romaine lettuce plants and on plastic (abiotic) surfaces were measured over time by culturing, and quantitative PCR (qPCR), propidium monoazide (PMA)-qPCR, and reverse transcriptase (RT)-qPCR targeting E. coli O157:H7 gapA, rfbE, eae, and lpfA genes and gene transcripts. On Romaine lettuce plants incubated at low relative humidity, E. coli O157:H7 cell numbers declined 107-fold within 96 h according to culture-based assessments. In contrast, there were no reductions in E. coli levels according to qPCR and only 100- and 1000-fold lower numbers per leaf by RT-qPCR and PMA-qPCR, respectively. Similar results were obtained upon exposure of E. coli O157:H7 to desiccation conditions on a sterile plastic surface. Subsequent investigation of mixtures of living and dead E. coli O157:H7 cells strongly indicated that PMA-qPCR detection was subject to false-positive enumerations of viable targets when in the presence of 100-fold higher numbers of dead cells. RT-qPCR measurements of killed E. coli O157:H7 as well as for RNaseA-treated E. coli RNA confirmed that transcripts from dead cells and highly degraded RNA were also amplified by RT-qPCR. These findings show that neither PMA-qPCR nor RT-qPCR provide accurate estimates of bacterial viability in environments where growth and survival is limited. PMID:26955370

  4. RNA-Based Detection Does not Accurately Enumerate Living Escherichia coli O157:H7 Cells on Plants.

    PubMed

    Ju, Wenting; Moyne, Anne-Laure; Marco, Maria L

    2016-01-01

    The capacity to distinguish between living and dead cells is an important, but often unrealized, attribute of rapid detection methods for foodborne pathogens. In this study, the numbers of enterohemorrhagic Escherichia coli O157:H7 after inoculation onto Romaine lettuce plants and on plastic (abiotic) surfaces were measured over time by culturing, and quantitative PCR (qPCR), propidium monoazide (PMA)-qPCR, and reverse transcriptase (RT)-qPCR targeting E. coli O157:H7 gapA, rfbE, eae, and lpfA genes and gene transcripts. On Romaine lettuce plants incubated at low relative humidity, E. coli O157:H7 cell numbers declined 10(7)-fold within 96 h according to culture-based assessments. In contrast, there were no reductions in E. coli levels according to qPCR and only 100- and 1000-fold lower numbers per leaf by RT-qPCR and PMA-qPCR, respectively. Similar results were obtained upon exposure of E. coli O157:H7 to desiccation conditions on a sterile plastic surface. Subsequent investigation of mixtures of living and dead E. coli O157:H7 cells strongly indicated that PMA-qPCR detection was subject to false-positive enumerations of viable targets when in the presence of 100-fold higher numbers of dead cells. RT-qPCR measurements of killed E. coli O157:H7 as well as for RNaseA-treated E. coli RNA confirmed that transcripts from dead cells and highly degraded RNA were also amplified by RT-qPCR. These findings show that neither PMA-qPCR nor RT-qPCR provide accurate estimates of bacterial viability in environments where growth and survival is limited. PMID:26955370

  5. Diagnosis of pneumothorax using a microwave-based detector

    NASA Astrophysics Data System (ADS)

    Ling, Geoffrey S. F.; Riechers, Ronald G., Sr.; Pasala, Krishna M.; Blanchard, Jeremy; Nozaki, Masako; Ramage, Anthony; Jackson, William; Rosner, Michael; Garcia-Pinto, Patricia; Yun, Catherine; Butler, Nathan; Riechers, Ronald G., Jr.; Williams, Daniel; Zeidman, Seth M.; Rhee, Peter; Ecklund, James M.; Fitzpatrick, Thomas; Lockhart, Stephen

    2001-08-01

    A novel method for identifying pneumothorax is presented. This method is based on a novel device that uses electromagnetic waves in the microwave radio frequency (RF) region and a modified algorithm previously used for the estimation of the angle of arrival of radar signals. In this study, we employ this radio frequency triage tool (RAFT) to the clinical condition of pneumothorax, which is a collapsed lung. In anesthetized pigs, RAFT can detect changes in the RF signature from a lung that is 20 percent or greater collapsed. These results are compared to chest x-ray. Both studies are equivalent in their ability to detect pneumothorax in pigs.

  6. Design and Implementation of Harmful Algal Bloom Diagnosis System Based on J2EE Platform

    NASA Astrophysics Data System (ADS)

    Guo, Chunfeng; Zheng, Haiyong; Ji, Guangrong; Lv, Liang

    According to the shortcomings which are time consuming and laborious of the traditional HAB (Harmful Algal Bloom) diagnosis by the experienced experts using microscope, all kinds of methods and technologies to identify HAB emerged such as microscopic images, molecular biology, characteristics of pigments analysis, fluorescence spectra, inherent optical properties, etc. This paper proposes the design and implementation of a web-based diagnosis system integrating the popular methods for HAB identification. This system is designed with J2EE platform based on MVC (Model-View-Controller) model as well as technologies such as JSP, Servlets, EJB and JDBC.

  7. A Novel Mittag-Leffler Kernel Based Hybrid Fault Diagnosis Method for Wheeled Robot Driving System.

    PubMed

    Yuan, Xianfeng; Song, Mumin; Zhou, Fengyu; Chen, Zhumin; Li, Yan

    2015-01-01

    The wheeled robots have been successfully applied in many aspects, such as industrial handling vehicles, and wheeled service robots. To improve the safety and reliability of wheeled robots, this paper presents a novel hybrid fault diagnosis framework based on Mittag-Leffler kernel (ML-kernel) support vector machine (SVM) and Dempster-Shafer (D-S) fusion. Using sensor data sampled under different running conditions, the proposed approach initially establishes multiple principal component analysis (PCA) models for fault feature extraction. The fault feature vectors are then applied to train the probabilistic SVM (PSVM) classifiers that arrive at a preliminary fault diagnosis. To improve the accuracy of preliminary results, a novel ML-kernel based PSVM classifier is proposed in this paper, and the positive definiteness of the ML-kernel is proved as well. The basic probability assignments (BPAs) are defined based on the preliminary fault diagnosis results and their confidence values. Eventually, the final fault diagnosis result is archived by the fusion of the BPAs. Experimental results show that the proposed framework not only is capable of detecting and identifying the faults in the robot driving system, but also has better performance in stability and diagnosis accuracy compared with the traditional methods. PMID:26229526

  8. A Novel Mittag-Leffler Kernel Based Hybrid Fault Diagnosis Method for Wheeled Robot Driving System

    PubMed Central

    Yuan, Xianfeng; Song, Mumin; Zhou, Fengyu; Chen, Zhumin; Li, Yan

    2015-01-01

    The wheeled robots have been successfully applied in many aspects, such as industrial handling vehicles, and wheeled service robots. To improve the safety and reliability of wheeled robots, this paper presents a novel hybrid fault diagnosis framework based on Mittag-Leffler kernel (ML-kernel) support vector machine (SVM) and Dempster-Shafer (D-S) fusion. Using sensor data sampled under different running conditions, the proposed approach initially establishes multiple principal component analysis (PCA) models for fault feature extraction. The fault feature vectors are then applied to train the probabilistic SVM (PSVM) classifiers that arrive at a preliminary fault diagnosis. To improve the accuracy of preliminary results, a novel ML-kernel based PSVM classifier is proposed in this paper, and the positive definiteness of the ML-kernel is proved as well. The basic probability assignments (BPAs) are defined based on the preliminary fault diagnosis results and their confidence values. Eventually, the final fault diagnosis result is archived by the fusion of the BPAs. Experimental results show that the proposed framework not only is capable of detecting and identifying the faults in the robot driving system, but also has better performance in stability and diagnosis accuracy compared with the traditional methods. PMID:26229526

  9. Toward Biological Diagnosis System Based on Digital Versatile Disc Technology

    NASA Astrophysics Data System (ADS)

    Arai, Tomofumi; Gopinath, Subash C. B.; Mizuno, Hiroshi; Kumar, Penmetcha K. R.; Rockstuhl, Carsten; Awazu, Koichi; Tominaga, Junji

    2007-06-01

    A novel biosensor utilizing an interference of light reflected at the interfaces of a multilayer structure is proposed. This biosensor detects analytes by monitoring the changes in reflection intensity due to their adsorption to the sensor surface, on which functional biomolecules are immobilized to specifically bind to the analytes. The proposed biosensing instrument is based on a commercial digital versatile disc (DVD) system, which allows the instrument to be small and inexpensive. For the preliminary examination, SiO2 thin films with a well-defined thickness were deposited on the sensor surface. The reflection intensity varied almost linearly depending on the thickness of the SiO2 films in a thickness range of 2-10 nm. Subsequently, it was demonstrated that biotin-streptavidin binding events were clearly detectable on a rotating disc substrate at a constant linear velocity of 4.0 m/s. We named this interference-based biosensor BioDVD, which is expected to be useful for high-throughput multi-analyte bioassays.

  10. Bead-based microfluidic immunoassay for diagnosis of Johne's disease

    SciTech Connect

    Wadhwa, Ashutosh; Foote, Robert; Shaw, Robert W; Eda, Shigetoshi

    2012-01-01

    Microfluidics technology offers a platform for development of point-of-care diagnostic devices for various infectious diseases. In this study, we examined whether serodiagnosis of Johne s disease (JD) can be conducted in a bead-based microfluidic assay system. Magnetic micro-beads were coated with antigens of the causative agent of JD, Mycobacterium avium subsp. paratuberculosis. The antigen-coated beads were incubated with serum samples of JD-positive or negative serum samples and then with a fluorescently-labeled secondary antibody (SAB). To confirm binding of serum antibodies to the antigen, the beads were subjected to flow cytometric analysis. Different conditions (dilutions of serum and SAB, types of SAB, and types of magnetic beads) were optimized for a great degree of differentiation between the JD-negative and JD-positive samples. Using the optimized conditions, we tested a well-classified set of 155 serum samples from JD negative and JD-positive cattle by using the bead-based flow cytometric assay. Of 105 JD-positive samples, 63 samples (60%) showed higher antibody binding levels than a cut-off value determined by using antibody binding levels of JD-negative samples. In contrast, only 43-49 JD-positive samples showed higher antibody binding levels than the cut-off value when the samples were tested by commercially-available immunoassays. Microfluidic assays were performed by magnetically immobilizing a number of beads within a microchannel of a glass microchip and detecting antibody on the collected beads by laser-induced fluorescence. Antigen-coated magnetic beads treated with bovine serum sample and fluorescently-labeled SAB were loaded into a microchannel to measure the fluorescence (reflecting level of antibody binding) on the beads in the microfluidic system. When the results of five bovine serum samples obtained with the system were compared to those obtained with the flow cytometer, a high level of correlation (linear regression, r2 = 0.994) was

  11. Computer-aided diagnosis workstation and database system for chest diagnosis based on multi-helical CT images

    NASA Astrophysics Data System (ADS)

    Satoh, Hitoshi; Niki, Noboru; Mori, Kiyoshi; Eguchi, Kenji; Kaneko, Masahiro; Kakinuma, Ryutarou; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru; Sasagawa, Michizou

    2006-03-01

    Multi-helical CT scanner advanced remarkably at the speed at which the chest CT images were acquired for mass screening. Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images and a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification. We also have developed electronic medical recording system and prototype internet system for the community health in two or more regions by using the Virtual Private Network router and Biometric fingerprint authentication system and Biometric face authentication system for safety of medical information. Based on these diagnostic assistance methods, we have now developed a new computer-aided workstation and database that can display suspected lesions three-dimensionally in a short time. This paper describes basic studies that have been conducted to evaluate this new system. The results of this study indicate that our computer-aided diagnosis workstation and network system can increase diagnostic speed, diagnostic accuracy and safety of medical information.

  12. Case-based reasoning as a computer aid to diagnosis

    NASA Astrophysics Data System (ADS)

    Floyd, Carey E., Jr.; Lo, Joseph Y.; Tourassi, Georgia D.

    1999-05-01

    A Case-Based Reasoning (CBR) system has been developed to predict the outcome of excisional biopsy from mammographic findings. CBR is implemented by comparing the current case to all previous cases and examining the outcomes for those previous cases that match the current case. Patients from breast screening who have suspicious findings on their diagnostic mammogram, are candidates for biopsy. The false positive rate for the decision to biopsy is currently between 66% and 90%. The CBR system is designed to support the decision to biopsy. The mammograms are read by clinicians using a standard reporting lexicon (BI- RADSTM). These findings are compared to a database of findings from cases with known outcomes (from biopsy). The fraction of similar cases that were malignant is returned. The clinician can then consider this result when making the decision regarding biopsy. The system was evaluated using round-robin sampling scheme and performed with a Receiver Operating Characteristic area of 0.77.

  13. Cancer Mortality in People Treated with Antidepressants before Cancer Diagnosis: A Population Based Cohort Study

    PubMed Central

    Sun, Yuelian; Vedsted, Peter; Fenger-Grøn, Morten; Wu, Chun Sen; Bech, Bodil Hammer; Olsen, Jørn; Benros, Michael Eriksen; Vestergaard, Mogens

    2015-01-01

    Background Depression is common after a cancer diagnosis and is associated with an increased mortality, but it is unclear whether depression occurring before the cancer diagnosis affects cancer mortality. We aimed to study cancer mortality of people treated with antidepressants before cancer diagnosis. Methods and Findings We conducted a population based cohort study of all adults diagnosed with cancer between January 2003 and December 2010 in Denmark (N = 201,662). We obtained information on cancer from the Danish Cancer Registry, on the day of death from the Danish Civil Registry, and on redeemed antidepressants from the Danish National Prescription Registry. Current users of antidepressants were defined as those who redeemed the latest prescription of antidepressant 0–4 months before cancer diagnosis (irrespective of earlier prescriptions), and former users as those who redeemed the latest prescription five or more months before cancer diagnosis. We estimated an all-cause one-year mortality rate ratio (MRR) and a conditional five-year MRR for patients who survived the first year after cancer diagnosis and confidence interval (CI) using a Cox proportional hazards regression model. Overall, 33,111 (16.4%) patients redeemed at least one antidepressant prescription in the three years before cancer diagnosis of whom 21,851 (10.8%) were current users at the time of cancer diagnosis. Current antidepressant users had a 32% higher one-year mortality (MRR = 1.32, 95% CI: 1.29–1.35) and a 22% higher conditional five-year mortality (MRR = 1.22, 95% CI: 1.17–1.26) if patients survived the first year after the cancer diagnosis than patients not redeeming antidepressants. The one-year mortality was particularly high for patients who initiated antidepressant treatment within four months before cancer diagnosis (MRR = 1.54, 95% CI: 1.47–1.61). Former users had no increased cancer mortality. Conclusions Initiation of antidepressive treatment prior to cancer diagnosis is

  14. Paper-based diagnostic devices for clinical paraquat poisoning diagnosis.

    PubMed

    Kuan, Chen-Meng; Lin, Szu-Ting; Yen, Tzung-Hai; Wang, Yu-Lin; Cheng, Chao-Min

    2016-05-01

    This article unveils the development of a paper-based analytical device designed to rapidly detect and clinically diagnose paraquat (PQ) poisoning. Using wax printing technology, we fabricated a PQ detection device by pattering hydrophobic boundaries on paper. This PQ detection device employs a colorimetric sodium dithionite assay or an ascorbic acid assay to indicate the PQ level in a buffer system or in a human serum system in 10 min. In this test, colorimetric changes, blue in color, were observable with the naked eye. By curve fitting models of sodium dithionite and ascorbic acid assays in normal human serum, we evaluated serum PQ levels for five PQ-poisoned patients before hemoperfusion (HP) treatment and one PQ-poisoned patient after HP treatment. As evidenced by similar detection outcomes, the analytical performance of our device can compete with that of the highest clinical standard, i.e., spectrophotometry, with less complicated sample preparation and with more rapid results. Accordingly, we believe that our rapid PQ detection can benefit physicians determining timely treatment strategies for PQ-poisoned patients once they are taken to hospitals, and that this approach will increase survival rates. PMID:27462379

  15. Intelligent gearbox diagnosis methods based on SVM, wavelet lifting and RBR.

    PubMed

    Gao, Lixin; Ren, Zhiqiang; Tang, Wenliang; Wang, Huaqing; Chen, Peng

    2010-01-01

    Given the problems in intelligent gearbox diagnosis methods, it is difficult to obtain the desired information and a large enough sample size to study; therefore, we propose the application of various methods for gearbox fault diagnosis, including wavelet lifting, a support vector machine (SVM) and rule-based reasoning (RBR). In a complex field environment, it is less likely for machines to have the same fault; moreover, the fault features can also vary. Therefore, a SVM could be used for the initial diagnosis. First, gearbox vibration signals were processed with wavelet packet decomposition, and the signal energy coefficients of each frequency band were extracted and used as input feature vectors in SVM for normal and faulty pattern recognition. Second, precision analysis using wavelet lifting could successfully filter out the noisy signals while maintaining the impulse characteristics of the fault; thus effectively extracting the fault frequency of the machine. Lastly, the knowledge base was built based on the field rules summarized by experts to identify the detailed fault type. Results have shown that SVM is a powerful tool to accomplish gearbox fault pattern recognition when the sample size is small, whereas the wavelet lifting scheme can effectively extract fault features, and rule-based reasoning can be used to identify the detailed fault type. Therefore, a method that combines SVM, wavelet lifting and rule-based reasoning ensures effective gearbox fault diagnosis. PMID:22399894

  16. Tetralogy of Fallot Cardiac Function Evaluation and Intelligent Diagnosis Based on Dual-Source Computed Tomography Cardiac Images.

    PubMed

    Cai, Ken; Rongqian, Yang; Li, Lihua; Xie, Zi; Ou, Shanxing; Chen, Yuke; Dou, Jianhong

    2016-05-01

    Tetralogy of Fallot (TOF) is the most common complex congenital heart disease (CHD) of the cyanotic type. Studies on ventricular functions have received an increasing amount of attention as the development of diagnosis and treatment technology for CHD continues to advance. Reasonable options for imaging examination and accurate assessment of preoperative and postoperative left ventricular functions of TOF patients are important in improving the cure rate of TOF radical operation, therapeutic evaluation, and judgment prognosis. Therefore, with the aid of dual-source computed tomography (DSCT), cardiac images with high temporal resolution and high definition, we measured the left ventricular time-volume curve using image data and calculating the left ventricular function parameters to conduct the preliminary evaluation on TOF patients. To comprehensively evaluate the cardiac function, the segmental ventricular wall function parameters were measured, and the measurement results were mapped to a bull's eye diagram to realize the standardization of segmental ventricular wall function evaluation. Finally, we introduced a new clustering method based on auto-regression model parameters and combined this method with Euclidean distance measurements to establish an intelligent diagnosis of TOF. The results of this experiment show that the TOF evaluation and the intelligent diagnostic methods proposed in this article are feasible. PMID:26496001

  17. Congenital neutropenia: diagnosis, molecular bases and patient management

    PubMed Central

    2011-01-01

    The term congenital neutropenia encompasses a family of neutropenic disorders, both permanent and intermittent, severe (<0.5 G/l) or mild (between 0.5-1.5 G/l), which may also affect other organ systems such as the pancreas, central nervous system, heart, muscle and skin. Neutropenia can lead to life-threatening pyogenic infections, acute gingivostomatitis and chronic parodontal disease, and each successive infection may leave permanent sequelae. The risk of infection is roughly inversely proportional to the circulating polymorphonuclear neutrophil count and is particularly high at counts below 0.2 G/l. When neutropenia is detected, an attempt should be made to establish the etiology, distinguishing between acquired forms (the most frequent, including post viral neutropenia and auto immune neutropenia) and congenital forms that may either be isolated or part of a complex genetic disease. Except for ethnic neutropenia, which is a frequent but mild congenital form, probably with polygenic inheritance, all other forms of congenital neutropenia are extremely rare and have monogenic inheritance, which may be X-linked or autosomal, recessive or dominant. About half the forms of congenital neutropenia with no extra-hematopoetic manifestations and normal adaptive immunity are due to neutrophil elastase (ELANE) mutations. Some patients have severe permanent neutropenia and frequent infections early in life, while others have mild intermittent neutropenia. Congenital neutropenia may also be associated with a wide range of organ dysfunctions, as for example in Shwachman-Diamond syndrome (associated with pancreatic insufficiency) and glycogen storage disease type Ib (associated with a glycogen storage syndrome). So far, the molecular bases of 12 neutropenic disorders have been identified. Treatment of severe chronic neutropenia should focus on prevention of infections. It includes antimicrobial prophylaxis, generally with trimethoprim-sulfamethoxazole, and also granulocyte

  18. Computer-aided diagnosis of breast cancer based on fine needle biopsy microscopic images.

    PubMed

    Kowal, Marek; Filipczuk, Paweł; Obuchowicz, Andrzej; Korbicz, Józef; Monczak, Roman

    2013-10-01

    Prompt and widely available diagnostics of breast cancer is crucial for the prognosis of patients. One of the diagnostic methods is the analysis of cytological material from the breast. This examination requires extensive knowledge and experience of the cytologist. Computer-aided diagnosis can speed up the diagnostic process and allow for large-scale screening. One of the largest challenges in the automatic analysis of cytological images is the segmentation of nuclei. In this study, four different clustering algorithms are tested and compared in the task of fast nuclei segmentation. K-means, fuzzy C-means, competitive learning neural networks and Gaussian mixture models were incorporated for clustering in the color space along with adaptive thresholding in grayscale. These methods were applied in a medical decision support system for breast cancer diagnosis, where the cases were classified as either benign or malignant. In the segmented nuclei, 42 morphological, topological and texture features were extracted. Then, these features were used in a classification procedure with three different classifiers. The system was tested for classification accuracy by means of microscopic images of fine needle breast biopsies. In cooperation with the Regional Hospital in Zielona Góra, 500 real case medical images from 50 patients were collected. The acquired classification accuracy was approximately 96-100%, which is very promising and shows that the presented method ensures accurate and objective data acquisition that could be used to facilitate breast cancer diagnosis. PMID:24034748

  19. Development of an unmanned aerial vehicle-based spray system for highly accurate site-specific application

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Application of crop production and protection materials is a crucial component in the high productivity of American agriculture. Agricultural chemical application is frequently needed at a specific time and location for accurate site-specific management of crop pests. Piloted aircrafts that carry ...

  20. The Analysis of Organizational Diagnosis on Based Six Box Model in Universities

    ERIC Educational Resources Information Center

    Hamid, Rahimi; Siadat, Sayyed Ali; Reza, Hoveida; Arash, Shahin; Ali, Nasrabadi Hasan; Azizollah, Arbabisarjou

    2011-01-01

    Purpose: The analysis of organizational diagnosis on based six box model at universities. Research method: Research method was descriptive-survey. Statistical population consisted of 1544 faculty members of universities which through random strafed sampling method 218 persons were chosen as the sample. Research Instrument were organizational…

  1. An Intelligent Learning Diagnosis System for Web-Based Thematic Learning Platform

    ERIC Educational Resources Information Center

    Huang, Chenn-Jung; Liu, Ming-Chou; Chu, San-Shine; Cheng, Chih-Lun

    2007-01-01

    This work proposes an intelligent learning diagnosis system that supports a Web-based thematic learning model, which aims to cultivate learners' ability of knowledge integration by giving the learners the opportunities to select the learning topics that they are interested, and gain knowledge on the specific topics by surfing on the Internet to…

  2. Optical Coherence Tomography-based Diagnosis of Polypoidal Choroidal Vasculopathy in Korean Patients

    PubMed Central

    Chang, Young Suk; Kim, Jong Woo; Lee, Tae Gon; Kim, Chul Gu

    2016-01-01

    Purpose To evaluate the efficacy of an optical coherence tomography (OCT)-based diagnosis of polypoidal choroidal vasculopathy (PCV) in Korean patients. Methods This retrospective, observational case series included 263 eyes of 263 patients (147 eyes with PCV and 116 eyes with typical exudative, age-related macular degeneration [AMD]) who had been diagnosed with treatment naïve exudative AMD. Eyes with three or more of the following OCT findings were diagnosed with PCV: multiple retinal pigment epithelial detachment (RPED), a sharp RPED peak, an RPED notch, a hyporeflective lumen representing polyps, and hyperreflective intraretinal hard exudates. The OCT-based diagnosis was compared with the gold-standard indocyanine green angiography-based method. The sensitivity and specificity of the OCT-based diagnosis was also estimated. An additional analysis was performed using a choroidal thickness criterion. Eyes with a subfoveal choroidal thickness greater than 300 µm were also diagnosed with PCV despite having only two OCT features. Results In eyes with PCV, three or more OCT features were observed in 126 of 147 eyes (85.7%), and the incidence of typical exudative AMD was 16 of 116 eyes (13.8%). The sensitivity and specificity of an OCT-based diagnosis were 85.7% and 86.2%, respectively. After applying the choroidal thickness criterion, the sensitivity increased from 85.7% to 89.8%, and the specificity decreased from 86.2% to 84.5%. Conclusions The OCT-based diagnosis of PCV showed a high sensitivity and specificity in Korean patients. The addition of a choroidal thickness criterion improved the sensitivity of the method with a minimal decrease in its specificity. PMID:27247519

  3. Screening and early diagnosis of osteoporosis through X-ray and ultrasound based techniques

    PubMed Central

    Pisani, Paola; Renna, Maria Daniela; Conversano, Francesco; Casciaro, Ernesto; Muratore, Maurizio; Quarta, Eugenio; Paola, Marco Di; Casciaro, Sergio

    2013-01-01

    Effective prevention and management of osteoporosis would require suitable methods for population screenings and early diagnosis. Current clinically-available diagnostic methods are mainly based on the use of either X-rays or ultrasound (US). All X-ray based methods provide a measure of bone mineral density (BMD), but it has been demonstrated that other structural aspects of the bone are important in determining fracture risk, such as mechanical features and elastic properties, which cannot be assessed using densitometric techniques. Among the most commonly used techniques, dual X-ray absorptiometry (DXA) is considered the current “gold standard” for osteoporosis diagnosis and fracture risk prediction. Unfortunately, as other X-ray based techniques, DXA has specific limitations (e.g., use of ionizing radiation, large size of the equipment, high costs, limited availability) that hinder its application for population screenings and primary care diagnosis. This has resulted in an increasing interest in developing reliable pre-screening tools for osteoporosis such as quantitative ultrasound (QUS) scanners, which do not involve ionizing radiation exposure and represent a cheaper solution exploiting portable and widely available devices. Furthermore, the usefulness of QUS techniques in fracture risk prediction has been proven and, with the last developments, they are also becoming a more and more reliable approach for assessing bone quality. However, the US assessment of osteoporosis is currently used only as a pre-screening tool, requiring a subsequent diagnosis confirmation by means of a DXA evaluation. Here we illustrate the state of art in the early diagnosis of this “silent disease” and show up recent advances for its prevention and improved management through early diagnosis. PMID:24349644

  4. A dynamic integrated fault diagnosis method for power transformers.

    PubMed

    Gao, Wensheng; Bai, Cuifen; Liu, Tong

    2015-01-01

    In order to diagnose transformer fault efficiently and accurately, a dynamic integrated fault diagnosis method based on Bayesian network is proposed in this paper. First, an integrated fault diagnosis model is established based on the causal relationship among abnormal working conditions, failure modes, and failure symptoms of transformers, aimed at obtaining the most possible failure mode. And then considering the evidence input into the diagnosis model is gradually acquired and the fault diagnosis process in reality is multistep, a dynamic fault diagnosis mechanism is proposed based on the integrated fault diagnosis model. Different from the existing one-step diagnosis mechanism, it includes a multistep evidence-selection process, which gives the most effective diagnostic test to be performed in next step. Therefore, it can reduce unnecessary diagnostic tests and improve the accuracy and efficiency of diagnosis. Finally, the dynamic integrated fault diagnosis method is applied to actual cases, and the validity of this method is verified. PMID:25685841

  5. APPLYING TENSOR-BASED MORPHOMETRY TO PARAMETRIC SURFACES CAN IMPROVE MRI-BASED DISEASE DIAGNOSIS

    PubMed Central

    Wang, Yalin; Yuan, Lei; Shi, Jie; Greve, Alexander; Ye, Jieping; Toga, Arthur W.; Reiss, Allan L.; Thompson, Paul M.

    2013-01-01

    Many methods have been proposed for computer-assisted diagnostic classification. Full tensor information and machine learning with 3D maps derived from brain images may help detect subtle differences or classify subjects into different groups. Here we develop a new approach to apply tensor-based morphometry to parametric surface models for diagnostic classification. We use this approach to identify cortical surface features for use in diagnostic classifiers. First, with holomorphic 1-forms, we compute an efficient and accurate conformal mapping from a multiply connected mesh to the so-called slit domain. Next, the surface parameterization approach provides a natural way to register anatomical surfaces across subjects using a constrained harmonic map. To analyze anatomical differences, we then analyze the full Riemannian surface metric tensors, which retain multivariate information on local surface geometry. As the number of voxels in a 3D image is large, sparse learning is a promising method to select a subset of imaging features and to improve classification accuracy. Focusing on vertices with greatest effect sizes, we train a diagnostic classifier using the surface features selected by an ℓ1-norm based sparse learning method. Stability selection is applied to validate the selected feature sets. We tested the algorithm on MRI-derived cortical surfaces from 42 subjects with genetically confirmed Williams syndrome and 40 age-matched controls, multivariate statistics on the local tensors gave greater effect sizes for detecting group differences relative to other TBM-based statistics including analysis of the Jacobian determinant and the largest eigenvalue of the surface metric. Our method also gave reasonable classification results relative to the Jacobian determinant, the pair of eigenvalues of the Jacobian matrix and volume features. This analysis pipeline may boost the power of morphometry studies, and may assist with image-based classification. PMID:23435208

  6. Investigation of candidate data structures and search algorithms to support a knowledge based fault diagnosis system

    NASA Technical Reports Server (NTRS)

    Bosworth, Edward L., Jr.

    1987-01-01

    The focus of this research is the investigation of data structures and associated search algorithms for automated fault diagnosis of complex systems such as the Hubble Space Telescope. Such data structures and algorithms will form the basis of a more sophisticated Knowledge Based Fault Diagnosis System. As a part of the research, several prototypes were written in VAXLISP and implemented on one of the VAX-11/780's at the Marshall Space Flight Center. This report describes and gives the rationale for both the data structures and algorithms selected. A brief discussion of a user interface is also included.

  7. Early diagnosis of Lemierre's syndrome based on a medical history and physical findings.

    PubMed

    Murata, Yutaka; Wada, Mikio; Kawashima, Atsushi; Kagawa, Keizo

    2013-01-01

    A 37-year-old woman presented with fever and rigor after experiencing respiratory symptoms the previous week that had resolved within a few days. On presentation, her neck was swollen along the right sternocleidomastoid muscle, and chest CT showed pulmonary septic embolisms. Lemierre's syndrome was strongly suspected based on the patient's medical history and physical findings. Further examination revealed venous thrombus, and Fusobacterium necrophorum was later isolated from blood cultures. Antibiotics for anaerobes were administered before a final diagnosis was made, and the patient's symptoms thereafter improved. A rapid diagnosis is essential, since Lemierre's syndrome can be fatal with a diagnostic delay. PMID:23318865

  8. Model-based diagnosis of large diesel engines based on angular speed variations of the crankshaft

    NASA Astrophysics Data System (ADS)

    Desbazeille, M.; Randall, R. B.; Guillet, F.; El Badaoui, M.; Hoisnard, C.

    2010-07-01

    This work aims at monitoring large diesel engines by analyzing the crankshaft angular speed variations. It focuses on a powerful 20-cylinder diesel engine with crankshaft natural frequencies within the operating speed range. First, the angular speed variations are modeled at the crankshaft free end. This includes modeling both the crankshaft dynamical behavior and the excitation torques. As the engine is very large, the first crankshaft torsional modes are in the low frequency range. A model with the assumption of a flexible crankshaft is required. The excitation torques depend on the in-cylinder pressure curve. The latter is modeled with a phenomenological model. Mechanical and combustion parameters of the model are optimized with the help of actual data. Then, an automated diagnosis based on an artificially intelligent system is proposed. Neural networks are used for pattern recognition of the angular speed waveforms in normal and faulty conditions. Reference patterns required in the training phase are computed with the model, calibrated using a small number of actual measurements. Promising results are obtained. An experimental fuel leakage fault is successfully diagnosed, including detection and localization of the faulty cylinder, as well as the approximation of the fault severity.

  9. Condition Monitoring and Fault Diagnosis of Wet-Shift Clutch Transmission Based on Multi-technology

    NASA Astrophysics Data System (ADS)

    Chen, Man; Wang, Liyong; Ma, Biao

    Based on the construction feature and operating principle of the wet-shift clutch transmission, the condition monitoring and fault diagnosis for the transmission of the tracklayer with wet-shift clutch were implemented with using the oil analysis technology, function parameter test method and vibration analysis technology. The new fault diagnosis methods were proposed, which are to build the gray modeling with the oil analysis data, and to test the function parameter of the clutch press, the rotate speed of each gear, the oil press of the steer system and lubrication system and the hydraulic torque converter. It's validated that the representative function signals were chosen to execute the condition monitoring analysis, when the fault symptoms were found, and the oil analysis data were used to apply the gray modeling to forecast the fault occurs time can satisfy the demand of the condition monitoring and fault diagnosis for the transmission regular work.

  10. Satellite fault diagnosis using support vector machines based on a hybrid voting mechanism.

    PubMed

    Yin, Hong; Yang, Shuqiang; Zhu, Xiaoqian; Jin, Songchang; Wang, Xiang

    2014-01-01

    The satellite fault diagnosis has an important role in enhancing the safety, reliability, and availability of the satellite system. However, the problem of enormous parameters and multiple faults makes a challenge to the satellite fault diagnosis. The interactions between parameters and misclassifications from multiple faults will increase the false alarm rate and the false negative rate. On the other hand, for each satellite fault, there is not enough fault data for training. To most of the classification algorithms, it will degrade the performance of model. In this paper, we proposed an improving SVM based on a hybrid voting mechanism (HVM-SVM) to deal with the problem of enormous parameters, multiple faults, and small samples. Many experimental results show that the accuracy of fault diagnosis using HVM-SVM is improved. PMID:25215324

  11. Satellite Fault Diagnosis Using Support Vector Machines Based on a Hybrid Voting Mechanism

    PubMed Central

    Yang, Shuqiang; Zhu, Xiaoqian; Jin, Songchang; Wang, Xiang

    2014-01-01

    The satellite fault diagnosis has an important role in enhancing the safety, reliability, and availability of the satellite system. However, the problem of enormous parameters and multiple faults makes a challenge to the satellite fault diagnosis. The interactions between parameters and misclassifications from multiple faults will increase the false alarm rate and the false negative rate. On the other hand, for each satellite fault, there is not enough fault data for training. To most of the classification algorithms, it will degrade the performance of model. In this paper, we proposed an improving SVM based on a hybrid voting mechanism (HVM-SVM) to deal with the problem of enormous parameters, multiple faults, and small samples. Many experimental results show that the accuracy of fault diagnosis using HVM-SVM is improved. PMID:25215324

  12. Sequential fuzzy diagnosis method for motor roller bearing in variable operating conditions based on vibration analysis.

    PubMed

    Li, Ke; Ping, Xueliang; Wang, Huaqing; Chen, Peng; Cao, Yi

    2013-01-01

    A novel intelligent fault diagnosis method for motor roller bearings which operate under unsteady rotating speed and load is proposed in this paper. The pseudo Wigner-Ville distribution (PWVD) and the relative crossing information (RCI) methods are used for extracting the feature spectra from the non-stationary vibration signal measured for condition diagnosis. The RCI is used to automatically extract the feature spectrum from the time-frequency distribution of the vibration signal. The extracted feature spectrum is instantaneous, and not correlated with the rotation speed and load. By using the ant colony optimization (ACO) clustering algorithm, the synthesizing symptom parameters (SSP) for condition diagnosis are obtained. The experimental results shows that the diagnostic sensitivity of the SSP is higher than original symptom parameter (SP), and the SSP can sensitively reflect the characteristics of the feature spectrum for precise condition diagnosis. Finally, a fuzzy diagnosis method based on sequential inference and possibility theory is also proposed, by which the conditions of the machine can be identified sequentially as well. PMID:23793021

  13. Sequential Fuzzy Diagnosis Method for Motor Roller Bearing in Variable Operating Conditions Based on Vibration Analysis

    PubMed Central

    Li, Ke; Ping, Xueliang; Wang, Huaqing; Chen, Peng; Cao, Yi

    2013-01-01

    A novel intelligent fault diagnosis method for motor roller bearings which operate under unsteady rotating speed and load is proposed in this paper. The pseudo Wigner-Ville distribution (PWVD) and the relative crossing information (RCI) methods are used for extracting the feature spectra from the non-stationary vibration signal measured for condition diagnosis. The RCI is used to automatically extract the feature spectrum from the time-frequency distribution of the vibration signal. The extracted feature spectrum is instantaneous, and not correlated with the rotation speed and load. By using the ant colony optimization (ACO) clustering algorithm, the synthesizing symptom parameters (SSP) for condition diagnosis are obtained. The experimental results shows that the diagnostic sensitivity of the SSP is higher than original symptom parameter (SP), and the SSP can sensitively reflect the characteristics of the feature spectrum for precise condition diagnosis. Finally, a fuzzy diagnosis method based on sequential inference and possibility theory is also proposed, by which the conditions of the machine can be identified sequentially as well. PMID:23793021

  14. NGS-based Molecular diagnosis of 105 eyeGENE® probands with Retinitis Pigmentosa

    PubMed Central

    Ge, Zhongqi; Bowles, Kristen; Goetz, Kerry; Scholl, Hendrik P. N.; Wang, Feng; Wang, Xinjing; Xu, Shan; Wang, Keqing; Wang, Hui; Chen, Rui

    2015-01-01

    The National Ophthalmic Disease Genotyping and Phenotyping Network (eyeGENE®) was established in an effort to facilitate basic and clinical research of human inherited eye disease. In order to provide high quality genetic testing to eyeGENE®’s enrolled patients which potentially aids clinical diagnosis and disease treatment, we carried out a pilot study and performed Next-generation sequencing (NGS) based molecular diagnosis for 105 Retinitis Pigmentosa (RP) patients randomly selected from the network. A custom capture panel was designed, which incorporated 195 known retinal disease genes, including 61 known RP genes. As a result, disease-causing mutations were identified in 52 out of 105 probands (solving rate of 49.5%). A total of 82 mutations were identified, and 48 of them were novel. Interestingly, for three probands the molecular diagnosis was inconsistent with the initial clinical diagnosis, while for five probands the molecular information suggested a different inheritance model other than that assigned by the physician. In conclusion, our study demonstrated that NGS target sequencing is efficient and sufficiently precise for molecular diagnosis of a highly heterogeneous patient cohort from eyeGENE®. PMID:26667666

  15. Rapid immunohistochemistry based on alternating current electric field for intraoperative diagnosis of brain tumors.

    PubMed

    Tanino, Mishie; Sasajima, Toshio; Nanjo, Hiroshi; Akesaka, Shiori; Kagaya, Masami; Kimura, Taichi; Ishida, Yusuke; Oda, Masaya; Takahashi, Masataka; Sugawara, Taku; Yoshioka, Toshiaki; Nishihara, Hiroshi; Akagami, Yoichi; Goto, Akiteru; Minamiya, Yoshihiro; Tanaka, Shinya

    2015-01-01

    Rapid immunohistochemistry (R-IHC) can contribute to the intraoperative diagnosis of central nervous system (CNS) tumors. We have recently developed a new IHC method based on an alternating current electric field to facilitate the antigen-antibody reaction. To ensure the requirement of R-IHC for intraoperative diagnosis, 183 cases of CNS tumors were reviewed regarding the accuracy rate of diagnosis without R-IHC. The diagnostic accuracy was 90.7 % (166/183 cases) [corrected] in which definitive diagnoses were not provided in 17 cases because of the failure of glioma grading and differential diagnosis of lymphoma and glioma. To establish the clinicopathological application, R-IHC for frozen specimens was compared with standard IHC for permanent specimens. 33 gliomas were analyzed, and the Ki-67/MIB-1 indices of frozen specimens by R-IHC were consistent with the grade and statistically correlated with those of permanent specimens. Thus, R-IHC provided supportive information to determine the grade of glioma. For discrimination between glioma and lymphoma, R-IHC was able to provide clear results of CD20 and Ki-67/MIB-1 in four frozen specimens of CNS lymphoma as well as standard IHC. We conclude that the R-IHC for frozen specimens can provide important information for intraoperative diagnosis of CNS tumors. PMID:24807101

  16. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    PubMed Central

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  17. A Fault Diagnosis Methodology for Gear Pump Based on EEMD and Bayesian Network

    PubMed Central

    Liu, Zengkai; Liu, Yonghong; Shan, Hongkai; Cai, Baoping; Huang, Qing

    2015-01-01

    This paper proposes a fault diagnosis methodology for a gear pump based on the ensemble empirical mode decomposition (EEMD) method and the Bayesian network. Essentially, the presented scheme is a multi-source information fusion based methodology. Compared with the conventional fault diagnosis with only EEMD, the proposed method is able to take advantage of all useful information besides sensor signals. The presented diagnostic Bayesian network consists of a fault layer, a fault feature layer and a multi-source information layer. Vibration signals from sensor measurement are decomposed by the EEMD method and the energy of intrinsic mode functions (IMFs) are calculated as fault features. These features are added into the fault feature layer in the Bayesian network. The other sources of useful information are added to the information layer. The generalized three-layer Bayesian network can be developed by fully incorporating faults and fault symptoms as well as other useful information such as naked eye inspection and maintenance records. Therefore, diagnostic accuracy and capacity can be improved. The proposed methodology is applied to the fault diagnosis of a gear pump and the structure and parameters of the Bayesian network is established. Compared with artificial neural network and support vector machine classification algorithms, the proposed model has the best diagnostic performance when sensor data is used only. A case study has demonstrated that some information from human observation or system repair records is very helpful to the fault diagnosis. It is effective and efficient in diagnosing faults based on uncertain, incomplete information. PMID:25938760

  18. A Fault Diagnosis Methodology for Gear Pump Based on EEMD and Bayesian Network.

    PubMed

    Liu, Zengkai; Liu, Yonghong; Shan, Hongkai; Cai, Baoping; Huang, Qing

    2015-01-01

    This paper proposes a fault diagnosis methodology for a gear pump based on the ensemble empirical mode decomposition (EEMD) method and the Bayesian network. Essentially, the presented scheme is a multi-source information fusion based methodology. Compared with the conventional fault diagnosis with only EEMD, the proposed method is able to take advantage of all useful information besides sensor signals. The presented diagnostic Bayesian network consists of a fault layer, a fault feature layer and a multi-source information layer. Vibration signals from sensor measurement are decomposed by the EEMD method and the energy of intrinsic mode functions (IMFs) are calculated as fault features. These features are added into the fault feature layer in the Bayesian network. The other sources of useful information are added to the information layer. The generalized three-layer Bayesian network can be developed by fully incorporating faults and fault symptoms as well as other useful information such as naked eye inspection and maintenance records. Therefore, diagnostic accuracy and capacity can be improved. The proposed methodology is applied to the fault diagnosis of a gear pump and the structure and parameters of the Bayesian network is established. Compared with artificial neural network and support vector machine classification algorithms, the proposed model has the best diagnostic performance when sensor data is used only. A case study has demonstrated that some information from human observation or system repair records is very helpful to the fault diagnosis. It is effective and efficient in diagnosing faults based on uncertain, incomplete information. PMID:25938760

  19. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    PubMed

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  20. Distributed model-based nonlinear sensor fault diagnosis in wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Lo, Chun; Lynch, Jerome P.; Liu, Mingyan

    2016-01-01

    Wireless sensors operating in harsh environments have the potential to be error-prone. This paper presents a distributive model-based diagnosis algorithm that identifies nonlinear sensor faults. The diagnosis algorithm has advantages over existing fault diagnosis methods such as centralized model-based and distributive model-free methods. An algorithm is presented for detecting common non-linearity faults without using reference sensors. The study introduces a model-based fault diagnosis framework that is implemented within a pair of wireless sensors. The detection of sensor nonlinearities is shown to be equivalent to solving the largest empty rectangle (LER) problem, given a set of features extracted from an analysis of sensor outputs. A low-complexity algorithm that gives an approximate solution to the LER problem is proposed for embedment in resource constrained wireless sensors. By solving the LER problem, sensors corrupted by non-linearity faults can be isolated and identified. Extensive analysis evaluates the performance of the proposed algorithm through simulation.

  1. Rule Extracting based on MCG with its Application in Helicopter Power Train Fault Diagnosis

    NASA Astrophysics Data System (ADS)

    Wang, M.; Hu, N. Q.; Qin, G. J.

    2011-07-01

    In order to extract decision rules for fault diagnosis from incomplete historical test records for knowledge-based damage assessment of helicopter power train structure. A method that can directly extract the optimal generalized decision rules from incomplete information based on GrC was proposed. Based on semantic analysis of unknown attribute value, the granule was extended to handle incomplete information. Maximum characteristic granule (MCG) was defined based on characteristic relation, and MCG was used to construct the resolution function matrix. The optimal general decision rule was introduced, with the basic equivalent forms of propositional logic, the rules were extracted and reduction from incomplete information table. Combined with a fault diagnosis example of power train, the application approach of the method was present, and the validity of this method in knowledge acquisition was proved.

  2. Semi-supervised weighted kernel clustering based on gravitational search for fault diagnosis.

    PubMed

    Li, Chaoshun; Zhou, Jianzhong

    2014-09-01

    Supervised learning method, like support vector machine (SVM), has been widely applied in diagnosing known faults, however this kind of method fails to work correctly when new or unknown fault occurs. Traditional unsupervised kernel clustering can be used for unknown fault diagnosis, but it could not make use of the historical classification information to improve diagnosis accuracy. In this paper, a semi-supervised kernel clustering model is designed to diagnose known and unknown faults. At first, a novel semi-supervised weighted kernel clustering algorithm based on gravitational search (SWKC-GS) is proposed for clustering of dataset composed of labeled and unlabeled fault samples. The clustering model of SWKC-GS is defined based on wrong classification rate of labeled samples and fuzzy clustering index on the whole dataset. Gravitational search algorithm (GSA) is used to solve the clustering model, while centers of clusters, feature weights and parameter of kernel function are selected as optimization variables. And then, new fault samples are identified and diagnosed by calculating the weighted kernel distance between them and the fault cluster centers. If the fault samples are unknown, they will be added in historical dataset and the SWKC-GS is used to partition the mixed dataset and update the clustering results for diagnosing new fault. In experiments, the proposed method has been applied in fault diagnosis for rotatory bearing, while SWKC-GS has been compared not only with traditional clustering methods, but also with SVM and neural network, for known fault diagnosis. In addition, the proposed method has also been applied in unknown fault diagnosis. The results have shown effectiveness of the proposed method in achieving expected diagnosis accuracy for both known and unknown faults of rotatory bearing. PMID:24981891

  3. Raman spectroscopy for early real-time endoscopic optical diagnosis based on biochemical changes during the carcinogenesis of Barrett’s esophagus

    PubMed Central

    Shi, Hong; Chen, Su-Yu; Lin, Kai

    2016-01-01

    Raman spectroscopy is a spectroscopic technique based on the inelastic scattering of monochromatic light that represents the molecular composition of the interrogated volume to provide a direct molecular fingerprint. Several investigations have revealed that confocal Raman spectroscopy can differentiate non-dysplastic Barrett’s esophagus from esophageal high-grade dysplasia and adenocarcinoma with high sensitivity and specificity. An automated on-line Raman spectral diagnostic system has made it possible to use Raman spectroscopy to guide accurate target biopsy instead of multiple random forceps-biopsies, this novel system is expected to improve in vivo precancerous diagnosis and tissue characterization of Barrett’s esophagus. PMID:26981179

  4. Fault diagnosis method based on FFT-RPCA-SVM for Cascaded-Multilevel Inverter.

    PubMed

    Wang, Tianzhen; Qi, Jie; Xu, Hao; Wang, Yide; Liu, Lei; Gao, Diju

    2016-01-01

    Thanks to reduced switch stress, high quality of load wave, easy packaging and good extensibility, the cascaded H-bridge multilevel inverter is widely used in wind power system. To guarantee stable operation of system, a new fault diagnosis method, based on Fast Fourier Transform (FFT), Relative Principle Component Analysis (RPCA) and Support Vector Machine (SVM), is proposed for H-bridge multilevel inverter. To avoid the influence of load variation on fault diagnosis, the output voltages of the inverter is chosen as the fault characteristic signals. To shorten the time of diagnosis and improve the diagnostic accuracy, the main features of the fault characteristic signals are extracted by FFT. To further reduce the training time of SVM, the feature vector is reduced based on RPCA that can get a lower dimensional feature space. The fault classifier is constructed via SVM. An experimental prototype of the inverter is built to test the proposed method. Compared to other fault diagnosis methods, the experimental results demonstrate the high accuracy and efficiency of the proposed method. PMID:26626623

  5. The Usefulness of Clinical-Practice-Based Laboratory Data in Facilitating the Diagnosis of Dengue Illness

    PubMed Central

    Liu, Jien-Wei; Lee, Ing-Kit; Wang, Lin; Chen, Rong-Fu; Yang, Kuender D.

    2013-01-01

    Alertness to dengue and making a timely diagnosis is extremely important in the treatment of dengue and containment of dengue epidemics. We evaluated the complementary role of clinical-practice-based laboratory data in facilitating suspicion/diagnosis of dengue. One hundred overall dengue (57 dengue fever [DF] and 43 dengue hemorrhagic fever [DHF]) cases and another 100 nondengue cases (78 viral infections other than dengue, 6 bacterial sepsis, and 16 miscellaneous diseases) were analyzed. We separately compared individual laboratory variables (platelet count [PC] , prothrombin time [PT], activated partial thromboplastin time [APTT], alanine aminotransferase [ALT], and aspartate aminotransferase [AST]) and varied combined variables of DF and/or DHF cases with the corresponding ones of nondengue cases. The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) in the diagnosis of DF and/or DHF were measured based on these laboratory variables. While trade-off between sensitivity and specificity, and/or suboptimal PPV/NPV was found at measurements using these variables, prolonged APTT + normal PT + PC < 100 × 109 cells/L had a favorable sensitivity, specificity, PPV, and NPV in diagnosis of DF and/or DHF. In conclusion, these data suggested that prolonged APTT + normal PT + PC < 100 × 109 cells/L is useful in evaluating the likelihood of DF and/or DHF. PMID:24455678

  6. Computational complexity issues in operative diagnosis of graph-based systems

    SciTech Connect

    Rao, N.S.V. )

    1993-04-01

    Systems that can be modeled as graphs, such that nodes represent the components and the edges represent the fault propagation between the components, are considered. Some components are equipped with alarms that ring in response to faulty conditions. In these systems, two types of problems are studied: (a) fault diagnosis, and (b) alarm placement. The fault diagnosis problems deal with computing the set of all potential failure sources that correspond to a set of ringing alarms A[sub R]. First, the single faults, where exactly one component can become faulty at any time, are considered. Systems are classified into zero-time and nonzero-time systems based on fault propagation times, and the latter is further classified based on the knowledge of propagation times. For each of these classes algorithms are presented for single fault diagnosis. The problem of detecting multiple faults is shown to be NP-complete. An alarm placement problem, that requires a single fault to be uniquely diagnosed, is examined; various versions of this problem are shown to be NP-complete. The single fault diagnosis algorithms have been implemented and tested.

  7. Medical Diagnosis System of Breast Cancer Using FCM Based Parallel Neural Networks

    NASA Astrophysics Data System (ADS)

    Hwang, Sang-Hyun; Kim, Dongwon; Kang, Tae-Koo; Park, Gwi-Tae

    In this paper, a new methodology for medical diagnosis based on fuzzy clustering and parallel neural networks is proposed. Intelligent systems have various fields. Breast cancer is one of field to be targeted, which is the most common tumor-related disease among women. Diagnosis of breast cancer is not task for medical expert owing to many attributes of the disease. So we proposed a new method, FCM based parallel neural networks to handle difficult. FCM based parallel neural networks composed of two parts. One is classifying breast cancer data using Fuzzy c-means clustering method (FCM). The other is designing the multiple neural networks using classified data by FCM. The proposed methodology is experimented, evaluated, and compared the performance with other existed models. As a result we can show the effectiveness and precision of the proposed method are better than other previous models.

  8. A Novel Diagnosis Method for a Hall Plates-Based Rotary Encoder with a Magnetic Concentrator

    PubMed Central

    Meng, Bumin; Wang, Yaonan; Sun, Wei; Yuan, Xiaofang

    2014-01-01

    In the last few years, rotary encoders based on two-dimensional complementary metal oxide semiconductors (CMOS) Hall plates with a magnetic concentrator have been developed to measure contactless absolute angle. There are various error factors influencing the measuring accuracy, which are difficult to locate after the assembly of encoder. In this paper, a model-based rapid diagnosis method is presented. Based on an analysis of the error mechanism, an error model is built to compare minimum residual angle error and to quantify the error factors. Additionally, a modified particle swarm optimization (PSO) algorithm is used to reduce the calculated amount. The simulation and experimental results show that this diagnosis method is feasible to quantify the causes of the error and to reduce iteration significantly. PMID:25090417

  9. A novel diagnosis method for a Hall plates-based rotary encoder with a magnetic concentrator.

    PubMed

    Meng, Bumin; Wang, Yaonan; Sun, Wei; Yuan, Xiaofang

    2014-01-01

    In the last few years, rotary encoders based on two-dimensional complementary metal oxide semiconductors (CMOS) Hall plates with a magnetic concentrator have been developed to measure contactless absolute angle. There are various error factors influencing the measuring accuracy, which are difficult to locate after the assembly of encoder. In this paper, a model-based rapid diagnosis method is presented. Based on an analysis of the error mechanism, an error model is built to compare minimum residual angle error and to quantify the error factors. Additionally, a modified particle swarm optimization (PSO) algorithm is used to reduce the calculated amount. The simulation and experimental results show that this diagnosis method is feasible to quantify the causes of the error and to reduce iteration significantly. PMID:25090417

  10. Automatic differential diagnosis of pancreatic serous and mucinous cystadenomas based on morphological features.

    PubMed

    Song, Jae-Won; Lee, Ju-Hong; Choi, Joon-Hyuk; Chun, Seok-Ju

    2013-01-01

    Generally, pathological diagnosis using an electron microscope is time-consuming and likely to result in a subjective judgment, because pathologists perform manual screening of tissue slides at high magnifications. Recently, the advent of digital pathology technology has provided the basis for convenient screening and quantitative analysis by digitizing tissue slides through a computer system. However, a screening process with high magnification still takes quite a long time. To solve these problems, recently the use of computer-aided design techniques for performing pathologic diagnosis has been increasing in digital pathology. For pathological diagnosis, we need different diagnostic methods for different regions with different characteristics. Therefore, in order to effectively diagnose different lesions and types of diseases, a quantitative method for extracting specific features is required in computerized pathologic diagnosis. This study is about an automated differential diagnosis system to differentiate between benign serous cystadenoma and possibly-malignant mucinous cystadenoma. In order to diagnose cystic tumors, the first step is identifying a cystic region and inspecting its epithelial cells. First, we identify the lumen boundary of a cyst using the Direction Cumulative Map considering 8-ways. Then, the Epithelial Nuclei Identification algorithm is used to discern epithelial nuclei. After that, three morphological features for the differential diagnosis of mucinous and serous cystadenomas are extracted. To demonstrate the superiority of the proposed features, the experiments compared performance of the classifiers learned by using the proposed morphological features and the classical morphological features based on nuclei. The classifiers in the simulations are as follows; Bayesian Classifier, k-Nearest Neighbors, Support Vector Machine, and Artificial Neural Network. The results show that all classifiers using the proposed features have the best

  11. Medium-Based Noninvasive Preimplantation Genetic Diagnosis for Human α-Thalassemias-SEA

    PubMed Central

    Wu, Haitao; Ding, Chenhui; Shen, Xiaoting; Wang, Jing; Li, Rong; Cai, Bing; Xu, Yanwen; Zhong, Yiping; Zhou, Canquan

    2015-01-01

    Abstract To develop a noninvasive medium-based preimplantation genetic diagnosis (PGD) test for α-thalassemias-SEA. The embryos of α-thalassemia-SEA carriers undergoing in vitro fertilization (IVF) were cultured. Single cells were biopsied from blastomeres and subjected to fluorescent gap polymerase chain reaction (PCR) analysis; the spent culture media that contained embryo genomic DNA and corresponding blastocysts as verification were subjected to quantitative-PCR (Q-PCR) detection of α-thalassemia-SEA. The diagnosis efficiency and allele dropout (ADO) ratio were calculated, and the cell-free DNA concentration was quantitatively assessed in the culture medium. The diagnosis efficiency of medium-based α-thalassemias–SEA detection significantly increased compared with that of biopsy-based fluorescent gap PCR analysis (88.6% vs 82.1%, P < 0.05). There is no significant difference regarding ADO ratio between them. The optimal time for medium-based α-thalassemias–SEA detection is Day 5 (D5) following IVF. Medium-based α-thalassemias–SEA detection could represent a novel, quick, and noninvasive approach for carriers to undergo IVF and PGD. PMID:25816038

  12. Plus Disease in Retinopathy of Prematurity: Pilot Study of Computer-Based and Expert Diagnosis

    PubMed Central

    Gelman, Rony; Jiang, Lei; Du, Yunling E.; Martinez-Perez, M. Elena; Flynn, John T.; Chiang, Michael F.

    2008-01-01

    Purpose To measure accuracy of plus disease diagnosis by recognized experts in retinopathy of prematurity (ROP), and to conduct a pilot study examining performance of a computer-based image analysis system, Retinal Image multiScale Analysis (RISA). Methods Twenty-two ROP experts independently interpreted a set of 34 wide-angle retinal images for presence of plus disease. A reference standard diagnosis based on expert consensus was defined for each image. Images were analyzed by the computer-based system using individual and linear combinations of system parameters for arterioles and venules: integrated curvature (IC), diameter, and tortuosity index (TI). Sensitivity, specificity, and receiver operating characteristic areas under the curve (AUC) for plus disease diagnosis compared to the reference standard were determined for each expert, as well as for the computer-based system. Results Expert sensitivity ranged from 0.308–1.000, specificity ranged from 0.571–1.000, and AUC ranged from 0.784–1.000. Among individual computer system parameters, venular IC had highest AUC (0.853). Among all computer system parameters, the linear combination of arteriolar IC, arteriolar TI, venular IC, venular diameter, and venular TI had highest AUC (0.967), which was greater than that of 18 (81.8%) of 22 experts. Conclusions Accuracy of ROP experts for plus disease diagnosis is imperfect. A computer-based image analysis system has potential to diagnose plus disease with high accuracy. Further research involving RISA system parameter cut-off values from this study are required to fully validate performance of this computer-based system compared to that of human experts. PMID:18029210

  13. An approach to fault diagnosis of vacuum cleaner motors based on sound analysis

    NASA Astrophysics Data System (ADS)

    Benko, Uros̆; Petrovc̆ic̆, Janko; Juričić, Đani; Tavčar, Joža; Rejec, Jožica

    2005-03-01

    This paper addresses the problem of the detailed quality end-test of vacuum cleaner motors at the end of the manufacturing cycle. For the prototyping purposes a test rig has been constructed and is presented in short. The diagnostic system built hereto takes advantage of vibration, sound and commutation analysis as well as parity relation checks. The paper focuses on the sound analysis module and provides two main contributions. First, an analysis of sound sources is performed and a set of appropriate features is suggested. Second, efficient signal processing algorithms are developed in order to detect and localise bearing faults, defects in fan impeller, improper brush-commutator contacts and rubbing of rotating surfaces. A thorough laboratory study shows that the underlying diagnostic modules provide accurate diagnosis, high sensitivity with respect to faults, and good diagnostic resolution.

  14. Pathologic diagnosis of achondrogenesis type 2 in a fragmented fetus: case report and evidence-based differential diagnostic approach in the early midtrimester.

    PubMed

    Weisman, Paul S; Kashireddy, Papreddy V; Ernst, Linda M

    2014-01-01

    As a group, lethal genetic skeletal disorders (GSDs) usually result in death within the perinatal period. Because lethal GSDs are often ultrasonographically detectible by early midtrimester, dilation and evacuation (D&E) is the method of choice for elective termination of pregnancy in many institutions. However, because the diagnosis of the lethal GSDs relies heavily upon radiologic examination of fetal remains, reaching an accurate diagnosis in this setting can be challenging. We report an autopsy case of a fetus delivered by D&E at 15 4/7 weeks gestation with radiologic, histologic, and genetic findings compatible with achondrogenesis type 2 and discuss an evidence-based differential diagnostic approach to lethal GSDs terminated by early midtrimester D&E. PMID:24144387

  15. Additional correction for energy transfer efficiency calculation in filter-based Förster resonance energy transfer microscopy for more accurate results

    NASA Astrophysics Data System (ADS)

    Sun, Yuansheng; Periasamy, Ammasi

    2010-03-01

    Förster resonance energy transfer (FRET) microscopy is commonly used to monitor protein interactions with filter-based imaging systems, which require spectral bleedthrough (or cross talk) correction to accurately measure energy transfer efficiency (E). The double-label (donor+acceptor) specimen is excited with the donor wavelength, the acceptor emission provided the uncorrected FRET signal and the donor emission (the donor channel) represents the quenched donor (qD), the basis for the E calculation. Our results indicate this is not the most accurate determination of the quenched donor signal as it fails to consider the donor spectral bleedthrough (DSBT) signals in the qD for the E calculation, which our new model addresses, leading to a more accurate E result. This refinement improves E comparisons made with lifetime and spectral FRET imaging microscopy as shown here using several genetic (FRET standard) constructs, where cerulean and venus fluorescent proteins are tethered by different amino acid linkers.

  16. Development of solid - based paper strips for rapid diagnosis of Pseudorabies infection.

    PubMed

    Joon Tam, Yew; Mohd Lila, Mohd Azmi; Bahaman, Abdul Rani

    2004-12-01

    the solid - based test strip towards pseudorabies antibodies was high with a detection limit of 1 to 10,000 - dilution factor. The specificity of the assay was 100% with no cross - reaction being observed with other sera or antibodies. Accurate reading time needed for confirmation of the assay can be completed in 5 min with a whole blood sample of 25 microl. The colloidal gold - labelled antibody is stable at room temperature for 6 months or more (data not shown). Findings from this study indicated that the solid - based test strip assay system provided high sensitivity and specificity for the detection of pseudorabies at low levels of antibody concentration. The assay was rapid, simple, cheap, and does not require any sophisticated equipment. Thus, the solid based test strip will be a useful serological screening technique or for rapid diagnosis of an infectious disease in target populations of animals characterised by heterogeneous antibody responses. PMID:16493404

  17. An accurate and efficient acoustic eigensolver based on a fast multipole BEM and a contour integral method

    NASA Astrophysics Data System (ADS)

    Zheng, Chang-Jun; Gao, Hai-Feng; Du, Lei; Chen, Hai-Bo; Zhang, Chuanzeng

    2016-01-01

    An accurate numerical solver is developed in this paper for eigenproblems governed by the Helmholtz equation and formulated through the boundary element method. A contour integral method is used to convert the nonlinear eigenproblem into an ordinary eigenproblem, so that eigenvalues can be extracted accurately by solving a set of standard boundary element systems of equations. In order to accelerate the solution procedure, the parameters affecting the accuracy and efficiency of the method are studied and two contour paths are compared. Moreover, a wideband fast multipole method is implemented with a block IDR (s) solver to reduce the overall solution cost of the boundary element systems of equations with multiple right-hand sides. The Burton-Miller formulation is employed to identify the fictitious eigenfrequencies of the interior acoustic problems with multiply connected domains. The actual effect of the Burton-Miller formulation on tackling the fictitious eigenfrequency problem is investigated and the optimal choice of the coupling parameter as α = i / k is confirmed through exterior sphere examples. Furthermore, the numerical eigenvalues obtained by the developed method are compared with the results obtained by the finite element method to show the accuracy and efficiency of the developed method.

  18. Automatic small bowel tumor diagnosis by using multi-scale wavelet-based analysis in wireless capsule endoscopy images

    PubMed Central

    2012-01-01

    Background Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. Method The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. Results The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice. PMID:22236465

  19. Developing an Intelligent System for Diagnosis of Asthma Based on Artificial Neural Network

    PubMed Central

    Alizadeh, Behrouz; Safdari, Reza; Zolnoori, Maryam; Bashiri, Azadeh

    2015-01-01

    Introduction: Lack of proper diagnosis and inadequate treatment of asthma, leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson’s coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different modes was made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. So considering the data mining approaches due to the nature of medical data is necessary. PMID:26483595

  20. Diagnosis and treatment of Merkel Cell Carcinoma. European consensus-based interdisciplinary guideline.

    PubMed

    Lebbe, Celeste; Becker, Jürgen C; Grob, Jean-Jacques; Malvehy, Josep; Del Marmol, Veronique; Pehamberger, Hubert; Peris, Ketty; Saiag, Philippe; Middleton, Mark R; Bastholt, Lars; Testori, Alessandro; Stratigos, Alexander; Garbe, Claus

    2015-11-01

    Merkel cell carcinoma (MCC) is a rare tumour of the skin of neuro-endocrine origin probably developing from neuronal mechanoreceptors. A collaborative group of multidisciplinary experts form the European Dermatology Forum (EDF), The European Association of Dermato-Oncology (EADO) and the European Organization of Research and Treatment of Cancer (EORTC) was formed to make recommendations on MCC diagnosis and management, based on a critical review of the literature, existing guidelines and expert's experience. Clinical features of the cutaneous/subcutaneous nodules hardly contribute to the diagnosis of MCC. The diagnosis is made by histopathology, and an incisional or excisional biopsy is mandatory. Immunohistochemical staining contributes to clarification of the diagnosis. Initial work-up comprises ultrasound of the loco-regional lymph nodes and total body scanning examinations. The primary tumour should be excised with 1-2cm margins. In patients without clinical evidence of regional lymph node involvement, sentinel node biopsy is recommended, if possible, and will be taken into account in a new version of the AJCC classification. In patients with regional lymph node involvement radical lymphadenectomy is recommended. Adjuvant radiotherapy might be considered in patients with multiple affected lymph nodes of extracapsular extension. In unresectable metastatic MCC mono- or poly-chemotherapy achieve high remission rates. However, responses are usually short lived. Treatment within clinical trials is regarded as a standard of care in disseminated MCC. PMID:26257075

  1. A Fault Alarm and Diagnosis Method Based on Sensitive Parameters and Support Vector Machine

    NASA Astrophysics Data System (ADS)

    Zhang, Jinjie; Yao, Ziyun; Lv, Zhiquan; Zhu, Qunxiong; Xu, Fengtian; Jiang, Zhinong

    2015-08-01

    Study on the extraction of fault feature and the diagnostic technique of reciprocating compressor is one of the hot research topics in the field of reciprocating machinery fault diagnosis at present. A large number of feature extraction and classification methods have been widely applied in the related research, but the practical fault alarm and the accuracy of diagnosis have not been effectively improved. Developing feature extraction and classification methods to meet the requirements of typical fault alarm and automatic diagnosis in practical engineering is urgent task. The typical mechanical faults of reciprocating compressor are presented in the paper, and the existing data of online monitoring system is used to extract fault feature parameters within 15 types in total; the inner sensitive connection between faults and the feature parameters has been made clear by using the distance evaluation technique, also sensitive characteristic parameters of different faults have been obtained. On this basis, a method based on fault feature parameters and support vector machine (SVM) is developed, which will be applied to practical fault diagnosis. A better ability of early fault warning has been proved by the experiment and the practical fault cases. Automatic classification by using the SVM to the data of fault alarm has obtained better diagnostic accuracy.

  2. Design-based approach to ethics in computer-aided diagnosis

    NASA Astrophysics Data System (ADS)

    Collmann, Jeff R.; Lin, Jyh-Shyan; Freedman, Matthew T.; Wu, Chris Y.; Hayes, Wendelin S.; Mun, Seong K.

    1996-04-01

    A design-based approach to ethical analysis examines how computer scientists, physicians and patients make and justify choices in designing, using and reacting to computer-aided diagnosis (CADx) systems. The basic hypothesis of this research is that values are embedded in CADx systems during all phases of their development, not just retrospectively imposed on them. This paper concentrates on the work of computer scientists and physicians as they attempt to resolve central technical questions in designing clinically functional CADx systems for lung cancer and breast cancer diagnosis. The work of Lo, Chan, Freedman, Lin, Wu and their colleagues provides the initial data on which this study is based. As these researchers seek to increase the rate of true positive classifications of detected abnormalities in chest radiographs and mammograms, they explore dimensions of the fundamental ethical principal of beneficence. The training of CADx systems demonstrates the key ethical dilemmas inherent in their current design.

  3. Study on Hankel matrix-based SVD and its application in rolling element bearing fault diagnosis

    NASA Astrophysics Data System (ADS)

    Jiang, Huiming; Chen, Jin; Dong, Guangming; Liu, Tao; Chen, Gang

    2015-02-01

    Based on the traditional theory of singular value decomposition (SVD), singular values (SVs) and ratios of neighboring singular values (NSVRs) are introduced to the feature extraction of vibration signals. The proposed feature extraction method is called SV-NSVR. Combined with selected SV-NSVR features, continuous hidden Markov model (CHMM) is used to realize the automatic classification. Then the SV-NSVR and CHMM based method is applied in fault diagnosis and performance assessment of rolling element bearings. The simulation and experimental results show that this method has a higher accuracy for the bearing fault diagnosis compared with those using other SVD features, and it is effective for the performance assessment of rolling element bearings.

  4. Identification of fidgety movements and prediction of CP by the use of computer-based video analysis is more accurate when based on two video recordings.

    PubMed

    Adde, Lars; Helbostad, Jorunn; Jensenius, Alexander R; Langaas, Mette; Støen, Ragnhild

    2013-08-01

    This study evaluates the role of postterm age at assessment and the use of one or two video recordings for the detection of fidgety movements (FMs) and prediction of cerebral palsy (CP) using computer vision software. Recordings between 9 and 17 weeks postterm age from 52 preterm and term infants (24 boys, 28 girls; 26 born preterm) were used. Recordings were analyzed using computer vision software. Movement variables, derived from differences between subsequent video frames, were used for quantitative analysis. Sensitivities, specificities, and area under curve were estimated for the first and second recording, or a mean of both. FMs were classified based on the Prechtl approach of general movement assessment. CP status was reported at 2 years. Nine children developed CP of whom all recordings had absent FMs. The mean variability of the centroid of motion (CSD) from two recordings was more accurate than using only one recording, and identified all children who were diagnosed with CP at 2 years. Age at assessment did not influence the detection of FMs or prediction of CP. The accuracy of computer vision techniques in identifying FMs and predicting CP based on two recordings should be confirmed in future studies. PMID:23343036

  5. HyDE Framework for Stochastic and Hybrid Model-Based Diagnosis

    NASA Technical Reports Server (NTRS)

    Narasimhan, Sriram; Brownston, Lee

    2012-01-01

    Hybrid Diagnosis Engine (HyDE) is a general framework for stochastic and hybrid model-based diagnosis that offers flexibility to the diagnosis application designer. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. Several alternative algorithms are available for the various steps in diagnostic reasoning. This approach is extensible, with support for the addition of new modeling paradigms as well as diagnostic reasoning algorithms for existing or new modeling paradigms. HyDE is a general framework for stochastic hybrid model-based diagnosis of discrete faults; that is, spontaneous changes in operating modes of components. HyDE combines ideas from consistency-based and stochastic approaches to model- based diagnosis using discrete and continuous models to create a flexible and extensible architecture for stochastic and hybrid diagnosis. HyDE supports the use of multiple paradigms and is extensible to support new paradigms. HyDE generates candidate diagnoses and checks them for consistency with the observations. It uses hybrid models built by the users and sensor data from the system to deduce the state of the system over time, including changes in state indicative of faults. At each time step when observations are available, HyDE checks each existing candidate for continued consistency with the new observations. If the candidate is consistent, it continues to remain in the candidate set. If it is not consistent, then the information about the inconsistency is used to generate successor candidates while discarding the candidate that was inconsistent. The models used by HyDE are similar to simulation models. They describe the expected behavior of the system under nominal and fault conditions. The model can be constructed in modular and hierarchical fashion by building component/subsystem models (which may themselves contain component/ subsystem models) and linking them through shared variables/parameters. The

  6. Accurate single-day titration of adenovirus vectors based on equivalence of protein VII nuclear dots and infectious particles

    PubMed Central

    Walkiewicz, Marcin P.; Morral, Nuria; Engel, Daniel A.

    2009-01-01

    Summary Protein VII is an abundant component of adenovirus particles and is tightly associated with the viral DNA. It enters the nucleus along with the infecting viral genome and remains bound throughout early phase. Protein VII can be visualized by immunofluorescent staining as discrete dots in the infected cell nucleus. Comparison between protein VII staining and expression of the 72 kDa DNA binding protein revealed a one-to-one correspondence between protein VII dots and infectious viral genomes. A similar relationship was observed for a helper-dependent adenovirus vector expressing green fluorescent protein. This relationship allowed accurate titration of adenovirus preparations, including wild-type and helper-dependent vectors, using a one-day immunofluorescence method. The method can be applied to any adenovirus vector and gives results equivalent to the standard plaque assay. PMID:19406166

  7. Computer-aided diagnosis in breast MRI based on unsupervised clustering techniques

    NASA Astrophysics Data System (ADS)

    Meyer-Baese, Anke; Wismueller, Axel; Lange, Oliver; Leinsinger, Gerda

    2004-04-01

    Exploratory data analysis techniques are applied to the segmentation of lesions in MRI mammography as a first step of a computer-aided diagnosis system. Three new unsupervised clustering techniques are tested on biomedical time-series representing breast MRI scans: fuzzy clustering based on deterministic annealing, "neural gas" network, and topographic independent component analysis. While the first two methods enable a correct segmentation of the lesion, the latter, although incorporating a topographic mapping, fails to detect and subclassify lesions.

  8. Fault Diagnosis System of Wind Turbine Generator Based on Petri Net

    NASA Astrophysics Data System (ADS)

    Zhang, Han

    Petri net is an important tool for discrete event dynamic systems modeling and analysis. And it has great ability to handle concurrent phenomena and non-deterministic phenomena. Currently Petri nets used in wind turbine fault diagnosis have not participated in the actual system. This article will combine the existing fuzzy Petri net algorithms; build wind turbine control system simulation based on Siemens S7-1200 PLC, while making matlab gui interface for migration of the system to different platforms.

  9. Computer-Based Image Analysis for Plus Disease Diagnosis in Retinopathy of Prematurity

    PubMed Central

    Wittenberg, Leah A.; Jonsson, Nina J.; Chan, RV Paul; Chiang, Michael F.

    2014-01-01

    Presence of plus disease in retinopathy of prematurity (ROP) is an important criterion for identifying treatment-requiring ROP. Plus disease is defined by a standard published photograph selected over 20 years ago by expert consensus. However, diagnosis of plus disease has been shown to be subjective and qualitative. Computer-based image analysis, using quantitative methods, has potential to improve the objectivity of plus disease diagnosis. The objective was to review the published literature involving computer-based image analysis for ROP diagnosis. The PubMed and Cochrane library databases were searched for the keywords “retinopathy of prematurity” AND “image analysis” AND/OR “plus disease.” Reference lists of retrieved articles were searched to identify additional relevant studies. All relevant English-language studies were reviewed. There are four main computer-based systems, ROPtool (AU ROC curve, plus tortuosity 0.95, plus dilation 0.87), RISA (AU ROC curve, arteriolar TI 0.71, venular diameter 0.82), Vessel Map (AU ROC curve, arteriolar dilation 0.75, venular dilation 0.96), and CAIAR (AU ROC curve, arteriole tortuosity 0.92, venular dilation 0.91), attempting to objectively analyze vessel tortuosity and dilation in plus disease in ROP. Some of them show promise for identification of plus disease using quantitative methods. This has potential to improve the diagnosis of plus disease, and may contribute to the management of ROP using both traditional binocular indirect ophthalmoscopy and image-based telemedicine approaches. PMID:21366159

  10. Analysis of algebraic reconstruction technique for accurate imaging of gas temperature and concentration based on tunable diode laser absorption spectroscopy

    NASA Astrophysics Data System (ADS)

    Hui-Hui, Xia; Rui-Feng, Kan; Jian-Guo, Liu; Zhen-Yu, Xu; Ya-Bai, He

    2016-06-01

    An improved algebraic reconstruction technique (ART) combined with tunable diode laser absorption spectroscopy(TDLAS) is presented in this paper for determining two-dimensional (2D) distribution of H2O concentration and temperature in a simulated combustion flame. This work aims to simulate the reconstruction of spectroscopic measurements by a multi-view parallel-beam scanning geometry and analyze the effects of projection rays on reconstruction accuracy. It finally proves that reconstruction quality dramatically increases with the number of projection rays increasing until more than 180 for 20 × 20 grid, and after that point, the number of projection rays has little influence on reconstruction accuracy. It is clear that the temperature reconstruction results are more accurate than the water vapor concentration obtained by the traditional concentration calculation method. In the present study an innovative way to reduce the error of concentration reconstruction and improve the reconstruction quality greatly is also proposed, and the capability of this new method is evaluated by using appropriate assessment parameters. By using this new approach, not only the concentration reconstruction accuracy is greatly improved, but also a suitable parallel-beam arrangement is put forward for high reconstruction accuracy and simplicity of experimental validation. Finally, a bimodal structure of the combustion region is assumed to demonstrate the robustness and universality of the proposed method. Numerical investigation indicates that the proposed TDLAS tomographic algorithm is capable of detecting accurate temperature and concentration profiles. This feasible formula for reconstruction research is expected to resolve several key issues in practical combustion devices. Project supported by the Young Scientists Fund of the National Natural Science Foundation of China (Grant No. 61205151), the National Key Scientific Instrument and Equipment Development Project of China (Grant

  11. Single nucleotide polymorphism-based microarray analysis for the diagnosis of hydatidiform moles

    PubMed Central

    XIE, YINGJUN; PEI, XIAOJUAN; DONG, YU; WU, HUIQUN; WU, JIANZHU; SHI, HUIJUAN; ZHUANG, XUYING; SUN, XIAOFANG; HE, JIALING

    2016-01-01

    In clinical diagnostics, single nucleotide polymorphism (SNP)-based microarray analysis enables the detection of copy number variations (CNVs), as well as copy number neutral regions, that are absent of heterozygosity throughout the genome. The aim of the present study was to evaluate the effectiveness and sensitivity of SNP-based microarray analysis in the diagnosis of hydatidiform mole (HM). By using whole-genome SNP microarray analysis, villous genotypes were detected, and the ploidy of villous tissue was determined to identify HMs. A total of 66 villous tissues and two twin tissues were assessed in the present study. Among these samples, 11 were triploid, one was tetraploid, 23 were abnormal aneuploidy, three were complete genome homozygosity, and the remaining ones were normal ploidy. The most noteworthy finding of the present study was the identification of six partial HMs and three complete HMs from those samples that were not identified as being HMs on the basis of the initial diagnosis of experienced obstetricians. This study has demonstrated that the application of an SNP-based microarray analysis was able to increase the sensitivity of diagnosis for HMs with partial and complete HMs, which makes the identification of these diseases at an early gestational age possible. PMID:27151252

  12. Single nucleotide polymorphism-based microarray analysis for the diagnosis of hydatidiform moles.

    PubMed

    Xie, Yingjun; Pei, Xiaojuan; Dong, Yu; Wu, Huiqun; Wu, Jianzhu; Shi, Huijuan; Zhuang, Xuying; Sun, Xiaofang; He, Jialing

    2016-07-01

    In clinical diagnostics, single nucleotide polymorphism (SNP)-based microarray analysis enables the detection of copy number variations (CNVs), as well as copy number neutral regions, that are absent of heterozygosity throughout the genome. The aim of the present study was to evaluate the effectiveness and sensitivity of SNP‑based microarray analysis in the diagnosis of hydatidiform mole (HM). By using whole‑genome SNP microarray analysis, villous genotypes were detected, and the ploidy of villous tissue was determined to identify HMs. A total of 66 villous tissues and two twin tissues were assessed in the present study. Among these samples, 11 were triploid, one was tetraploid, 23 were abnormal aneuploidy, three were complete genome homozygosity, and the remaining ones were normal ploidy. The most noteworthy finding of the present study was the identification of six partial HMs and three complete HMs from those samples that were not identified as being HMs on the basis of the initial diagnosis of experienced obstetricians. This study has demonstrated that the application of an SNP‑based microarray analysis was able to increase the sensitivity of diagnosis for HMs with partial and complete HMs, which makes the identification of these diseases at an early gestational age possible. PMID:27151252

  13. Towards a physiologically based diagnosis of anorexia nervosa and bulimia nervosa.

    PubMed

    Hatch, Kent A; Spangler, Diane L; Backus, Elizabeth M; Balagna, Jonathan T; Burns, Keven S; Guzman, Brooke S; Hubbard, Matthew J; Lindblad, Stephanie L; Roeder, Beverly L; Ryther, Natalie E; Seawright, Max A; Tyau, Jaymie N; Williams, Dustin

    2007-11-01

    Diagnosis of anorexia nervosa (AN) and bulimia nervosa (BN), while including such physiological data as weight and the reproductive status of the individual, are primarily based on questionnaires and interviews that rely on self-report of both body-related concerns and eating-related behaviors. While some key components of eating disorders are psychological and thus introspective in nature, reliance on self-report for the assessment of eating-related behaviors and nutritional status lacks the objectivity that a physiologically based measure could provide. The development of a more physiologically informed diagnosis for AN and BN would provide a more objective means of diagnosing these disorders, provide a sound physiological basis for diagnosing subclinical disorders and could also aid in monitoring the effectiveness of treatments for these disorders. Empirically supported, physiologically based methods for diagnosing AN and BN are reviewed herein as well as promising physiological measures that may potentially be used in the diagnosis of AN and BN. PMID:18020913

  14. Targeted Proteomics Enables Simultaneous Quantification of Folate Receptor Isoforms and Potential Isoform-based Diagnosis in Breast Cancer

    PubMed Central

    Yang, Ting; Xu, Feifei; Fang, Danjun; Chen, Yun

    2015-01-01

    The distinct roles of protein isoforms in cancer are becoming increasingly evident. FRα and FRβ, two major isoforms of the folate receptor family, generally have different cellular distribution and tissue specificity. However, the presence of FRβ in breast tumors, where FRα is normally expressed, complicates this situation. Prior to applying any FR isoform-based diagnosis and therapeutics, it is essential to monitor the expression profile of FR isoforms in a more accurate manner. An LC-MS/MS-based targeted proteomics assay was developed and validated in this study because of the lack of suitable methodology for the simultaneous and specific measurement of highly homologous isoforms occurring at low concentrations. FRα and FRβ monitoring was achieved by measuring their surrogate isoform-specific peptides. Five human breast cell lines, isolated macrophages and 60 matched pairs of breast tissue samples were subjected to the analysis. The results indicated that FRβ was overexpressed in tumor-associated macrophages (TAMs) but not epithelial cells, in addition to an enhanced level of FRα in breast cancer cells and tissue samples. Moreover, the levels of the FR isoforms were evaluated according to the histology, histopathological features and molecular subtypes of breast cancer. Several positive associations with PR/ER and HER2 status and metastasis were revealed. PMID:26573433

  15. A fault diagnosis approach for diesel engine valve train based on improved ITD and SDAG-RVM

    NASA Astrophysics Data System (ADS)

    Yu, Liu; Junhong, Zhang; Fengrong, Bi; Jiewei, Lin; Wenpeng, Ma

    2015-02-01

    Targeting the non-stationary characteristics of the vibration signals of a diesel engine valve train, and the limitation of the autoregressive (AR) model, a novel approach based on the improved intrinsic time-scale decomposition (ITD) and relevance vector machine (RVM) is proposed in this paper for the identification of diesel engine valve train faults. The approach mainly consists of three stages: First, prior to the feature extraction, non-uniform B-spline interpolation is introduced to the ITD method for the fitting of baseline signal, then the improved ITD is used to decompose the non-stationary signals into a set of stationary proper rotation components (PRCs). Second, the AR model is established for each PRC, and the first several AR coefficients together with the remnant variance of all PRCs are regarded as the fault feature vectors. Finally, a new separability based directed acyclic graph (SDAG) method is proposed to determine the structure of multi-class RVM, and the fault feature vectors are classified using the SDAG-RVM classifier to recognize the fault of the diesel engine valve train. The experimental results demonstrate that the proposed fault diagnosis approach can effectively extract the fault features and accurately identify the fault patterns.

  16. Differential diagnosis of Brucella abortus by real-time PCR based on a single-nucleotide polymorphisms

    PubMed Central

    KIM, Ji-Yeon; KANG, Sung-Il; LEE, Jin Ju; LEE, Kichan; SUNG, So-Ra; ERDENEBAATAAR, Janchivdorj; VANAABAATAR, Batbaatar; JUNG, Suk Chan; PARK, Yong Ho; YOO, Han-Sang; HER, Moon

    2015-01-01

    To diagnose brucellosis effectively, many genus- and species-specific detection methods based on PCR have been developed. With conventional PCR assays, real-time PCR techniques have been developed as rapid diagnostic tools. Among them, real-time PCR using hybridization probe (hybprobe) has been recommended for bacteria with high DNA homology among species, with which it is possible to make an accurate diagnosis by means of an amplification curve and melting peak analysis. A hybprobe for B. abortus was designed from a specific single-nucleotide polymorphism (SNP) on the fbaA gene. This probe only showed specific amplification of B. abortus from approximately the 14th cycle, given a melting peak at 69°C. The sensitivity of real-time PCR was revealed to be 20 fg/µl by 10-fold DNA dilution, and the detection limit was 4 CFU in clinical samples. This real-time PCR showed greater sensitivity than that of conventional PCR and previous real-time PCR based on Taqman probe. Therefore, this new real-time PCR assay could be helpful for differentiating B. abortus infection with rapidity and accuracy. PMID:26666176

  17. Differential diagnosis of Brucella abortus by real-time PCR based on a single-nucleotide polymorphisms.

    PubMed

    Kim, Ji-Yeon; Kang, Sung-Il; Lee, Jin Ju; Lee, Kichan; Sung, So-Ra; Erdenebaataar, Janchivdorj; Vanaabaatar, Batbaatar; Jung, Suk Chan; Park, Yong Ho; Yoo, Han-Sang; Her, Moon

    2016-05-01

    To diagnose brucellosis effectively, many genus- and species-specific detection methods based on PCR have been developed. With conventional PCR assays, real-time PCR techniques have been developed as rapid diagnostic tools. Among them, real-time PCR using hybridization probe (hybprobe) has been recommended for bacteria with high DNA homology among species, with which it is possible to make an accurate diagnosis by means of an amplification curve and melting peak analysis. A hybprobe for B. abortus was designed from a specific single-nucleotide polymorphism (SNP) on the fbaA gene. This probe only showed specific amplification of B. abortus from approximately the 14th cycle, given a melting peak at 69°C. The sensitivity of real-time PCR was revealed to be 20 fg/µl by 10-fold DNA dilution, and the detection limit was 4 CFU in clinical samples. This real-time PCR showed greater sensitivity than that of conventional PCR and previous real-time PCR based on Taqman probe. Therefore, this new real-time PCR assay could be helpful for differentiating B. abortus infection with rapidity and accuracy. PMID:26666176

  18. Implementation of a model based fault detection and diagnosis for actuation faults of the Space Shuttle main engine

    NASA Technical Reports Server (NTRS)

    Duyar, A.; Guo, T.-H.; Merrill, W.; Musgrave, J.

    1992-01-01

    In a previous study, Guo, Merrill and Duyar, 1990, reported a conceptual development of a fault detection and diagnosis system for actuation faults of the space shuttle main engine. This study, which is a continuation of the previous work, implements the developed fault detection and diagnosis scheme for the real time actuation fault diagnosis of the space shuttle main engine. The scheme will be used as an integral part of an intelligent control system demonstration experiment at NASA Lewis. The diagnosis system utilizes a model based method with real time identification and hypothesis testing for actuation, sensor, and performance degradation faults.

  19. [Atypical manifestation of severe mitral valve insufficiency. On the diagnosis and differential diagnosis based on a case report].

    PubMed

    Schwohl, T; Herhahn, J; Schroeder, B

    1990-04-01

    Report on a severe mitral valve insufficiency in a patient in whom all chordae tendinae of the posterior cusp of the mitral valve had completely ruptured for inexplicable reasons. An unusual feature of this condition was the prolonged clinical course for a period of two weeks and the markedly unilateral lung infiltrations seen on the plain x-ray of the thorax. Evidently non-specific inflammation parameters, such as elevated temperature, accelerated sedimentation rate, leukocytosis with shift to the left, prompted differential diagnosis of atypical pneumonia, e.g. legionellosis due to the identification of legionella antigen in the urine. In view of the fact that the patient had the initial signs and symptoms (dyspnoea, partly sanguineous sputum) after working in the garden (possible inhalation of a noxious substance?) we suspected an exogenous allergic alveolitis. This, however, could be excluded by a bronchoalveolar lavage (there were no lymphocytes in the wash). Last but not least, differential diagnosis of Goodpasture's syndrome was considered, where the pulmonary manifestation (haemorrhagic pneumonia) may precede the renal sign (glomerulonephritis). Diagnosis was finally established in the typical manner via echocardiography. Quantification of the mitral insufficiency was achieved by right cardiac catheterisation (v-wave 60 mmHg) and cardioangiography. Immediate mitral valve replacement surgery was effected without problems. However, the patient died on the 10th postoperative day from bacterial pneumonia. PMID:2360711

  20. Accurately control and flatten gain spectrum of L-band erbium doped fiber amplifier based on suitable gain-clamping

    NASA Astrophysics Data System (ADS)

    Yang, Jiuru; Meng, Xiangyu; Liu, Chunyu

    2016-04-01

    The increasing traffic with dynamic nature requires the applications of gain-clamped L-band erbium-doped fiber amplifier (EDFA). However, the weak or over clamping may lead the unexpected gain-compression and flatness-worsening. In this article, to enhance practicality, we modify the partly gain-clamping configuration and utilize a pair of C-band fiber Bragg gratings (FBGs) to non-uniformly compress the gain spectrum of L-band. Through a comprehensive test and comparison, the suitable gain-clamping region for the amplified signals is found, and the gain in L-band is accurately controlled and flattened under the matched central wavelength of FBGs. The experimental results show that, our designed L-band EDFA achieves a trade-off among the output gain, flatness and stability. The ±0.44 dB flatness and 20.2 dB average gain are together obtained in the range of 1570-1610 nm, with the ±0.1 dB stability of signals in over 30 dBm dynamic range.

  1. A Novel Local Learning based Approach With Application to Breast Cancer Diagnosis

    SciTech Connect

    Xu, Songhua; Tourassi, Georgia

    2012-01-01

    The purpose of this study is to develop and evaluate a novel local learning-based approach for computer-assisted diagnosis of breast cancer. Our new local learning based algorithm using the linear logistic regression method as its base learner is described. Overall, our algorithm will perform its stochastic searching process until the total allowed computing time is used up by our random walk process in identifying the most suitable population subdivision scheme and their corresponding individual base learners. The proposed local learning-based approach was applied for the prediction of breast cancer given 11 mammographic and clinical findings reported by physicians using the BI-RADS lexicon. Our database consisted of 850 patients with biopsy confirmed diagnosis (290 malignant and 560 benign). We also compared the performance of our method with a collection of publicly available state-of-the-art machine learning methods. Predictive performance for all classifiers was evaluated using 10-fold cross validation and Receiver Operating Characteristics (ROC) analysis. Figure 1 reports the performance of 54 machine learning methods implemented in the machine learning toolkit Weka (version 3.0). We introduced a novel local learning-based classifier and compared it with an extensive list of other classifiers for the problem of breast cancer diagnosis. Our experiments show that the algorithm superior prediction performance outperforming a wide range of other well established machine learning techniques. Our conclusion complements the existing understanding in the machine learning field that local learning may capture complicated, non-linear relationships exhibited by real-world datasets.

  2. Wayside acoustic diagnosis of defective train bearings based on signal resampling and information enhancement

    NASA Astrophysics Data System (ADS)

    He, Qingbo; Wang, Jun; Hu, Fei; Kong, Fanrang

    2013-10-01

    The diagnosis of train bearing defects plays a significant role to maintain the safety of railway transport. Among various defect detection techniques, acoustic diagnosis is capable of detecting incipient defects of a train bearing as well as being suitable for wayside monitoring. However, the wayside acoustic signal will be corrupted by the Doppler effect and surrounding heavy noise. This paper proposes a solution to overcome these two difficulties in wayside acoustic diagnosis. In the solution, a dynamically resampling method is firstly presented to reduce the Doppler effect, and then an adaptive stochastic resonance (ASR) method is proposed to enhance the defective characteristic frequency automatically by the aid of noise. The resampling method is based on a frequency variation curve extracted from the time-frequency distribution (TFD) of an acoustic signal by dynamically minimizing the local cost functions. For the ASR method, the genetic algorithm is introduced to adaptively select the optimal parameter of the multiscale noise tuning (MST)-based stochastic resonance (SR) method. The proposed wayside acoustic diagnostic scheme combines signal resampling and information enhancement, and thus is expected to be effective in wayside defective bearing detection. The experimental study verifies the effectiveness of the proposed solution.

  3. Image-based computer-assisted diagnosis system for benign paroxysmal positional vertigo

    NASA Astrophysics Data System (ADS)

    Kohigashi, Satoru; Nakamae, Koji; Fujioka, Hiromu

    2005-04-01

    We develop the image based computer assisted diagnosis system for benign paroxysmal positional vertigo (BPPV) that consists of the balance control system simulator, the 3D eye movement simulator, and the extraction method of nystagmus response directly from an eye movement image sequence. In the system, the causes and conditions of BPPV are estimated by searching the database for record matching with the nystagmus response for the observed eye image sequence of the patient with BPPV. The database includes the nystagmus responses for simulated eye movement sequences. The eye movement velocity is obtained by using the balance control system simulator that allows us to simulate BPPV under various conditions such as canalithiasis, cupulolithiasis, number of otoconia, otoconium size, and so on. Then the eye movement image sequence is displayed on the CRT by the 3D eye movement simulator. The nystagmus responses are extracted from the image sequence by the proposed method and are stored in the database. In order to enhance the diagnosis accuracy, the nystagmus response for a newly simulated sequence is matched with that for the observed sequence. From the matched simulation conditions, the causes and conditions of BPPV are estimated. We apply our image based computer assisted diagnosis system to two real eye movement image sequences for patients with BPPV to show its validity.

  4. Recombinant antigen-based enzyme-linked immunosorbent assay for diagnosis of Baylisascaris procyonis larva migrans.

    PubMed

    Dangoudoubiyam, Sriveny; Vemulapalli, Ramesh; Ndao, Momar; Kazacos, Kevin R

    2011-10-01

    Baylisascaris larva migrans is an important zoonotic disease caused by Baylisascaris procyonis, the raccoon roundworm, and is being increasingly considered in the differential diagnosis of eosinophilic meningoencephalitis in children and young adults. Although a B. procyonis excretory-secretory (BPES) antigen-based enzyme-linked immunosorbent assay (ELISA) and a Western blot assay are useful in the immunodiagnosis of this infection, cross-reactivity remains a major problem. Recently, a recombinant B. procyonis antigen, BpRAG1, was reported for use in the development of improved serological assays for the diagnosis of Baylisascaris larva migrans. In this study, we tested a total of 384 human patient serum samples in a BpRAG1 ELISA, including samples from 20 patients with clinical Baylisascaris larva migrans, 137 patients with other parasitic infections (8 helminth and 4 protozoan), and 227 individuals with unknown/suspected parasitic infections. A sensitivity of 85% and a specificity of 86.9% were observed with the BpRAG1 ELISA, compared to only 39.4% specificity with the BPES ELISA. In addition, the BpRAG1 ELISA had a low degree of cross-reactivity with antibodies to Toxocara infection (25%), while the BPES antigen showed 90.6% cross-reactivity. Based on these results, the BpRAG1 antigen has a high degree of sensitivity and specificity and should be very useful and reliable in the diagnosis and seroepidemiology of Baylisascaris larva migrans by ELISA. PMID:21832102

  5. Development of the Task-Based Expert System for Machine Fault Diagnosis

    NASA Astrophysics Data System (ADS)

    Bo, Ma; Zhi-nong, Jiang; Zhong-qing, Wei

    2012-05-01

    The operating mechanism of expert systems widely used in fault diagnosis is to formulate a set of diagnostic rules, according to the mechanism and symptoms of faults, in order to instruct the fault diagnosis or directly give diagnostic results. In practice, due to differences existing in such aspects as production technology, drivers, etc., a certain fault may derive from different causes, which will lead to a lower diagnostic accuracy of expert systems. Besides, a variety of expert systems now available have a dual problem of low generality and low expandability, of which the former can lead to the repeated development of expert systems for different machines, while the latter restricts users from expanding the system. Aimed at these problems, a type of task-based software architecture of expert system is proposed in this paper, which permits a specific optimization based on a set of common rules, and allows users to add or modify rules on a man-machine dialog so as to keep on absorbing and improving the expert knowledge. Finally, the integration of the expert system with the condition monitoring system to implement the automatic and semi-automatic diagnosis is introduced.

  6. Data-based hybrid tension estimation and fault diagnosis of cold rolling continuous annealing processes.

    PubMed

    Liu, Qiang; Chai, Tianyou; Wang, Hong; Qin, Si-Zhao Joe

    2011-12-01

    The continuous annealing process line (CAPL) of cold rolling is an important unit to improve the mechanical properties of steel strips in steel making. In continuous annealing processes, strip tension is an important factor, which indicates whether the line operates steadily. Abnormal tension profile distribution along the production line can lead to strip break and roll slippage. Therefore, it is essential to estimate the whole tension profile in order to prevent the occurrence of faults. However, in real annealing processes, only a limited number of strip tension sensors are installed along the machine direction. Since the effects of strip temperature, gas flow, bearing friction, strip inertia, and roll eccentricity can lead to nonlinear tension dynamics, it is difficult to apply the first-principles induced model to estimate the tension profile distribution. In this paper, a novel data-based hybrid tension estimation and fault diagnosis method is proposed to estimate the unmeasured tension between two neighboring rolls. The main model is established by an observer-based method using a limited number of measured tensions, speeds, and currents of each roll, where the tension error compensation model is designed by applying neural networks principal component regression. The corresponding tension fault diagnosis method is designed using the estimated tensions. Finally, the proposed tension estimation and fault diagnosis method was applied to a real CAPL in a steel-making company, demonstrating the effectiveness of the proposed method. PMID:21954208

  7. Remote Fault Information Acquisition and Diagnosis System of the Combine Harvester Based on LabVIEW

    NASA Astrophysics Data System (ADS)

    Chen, Jin; Wu, Pei; Xu, Kai

    Most combine harvesters have not be equipped with online fault diagnosis system. A fault information acquisition and diagnosis system of the Combine Harvester based on LabVIEW is designed, researched and developed. Using ARM development board, by collecting many sensors' signals, this system can achieve real-time measurement, collection, displaying and analysis of different parts of combine harvesters. It can also realize detection online of forward velocity, roller speed, engine temperature, etc. Meanwhile the system can judge the fault location. A new database function is added so that we can search the remedial measures to solve the faults and also we can add new faults to the database. So it is easy to take precautions against before the combine harvester breaking down then take measures to service the harvester.

  8. Livingstone Model-Based Diagnosis of Earth Observing One Infusion Experiment

    NASA Technical Reports Server (NTRS)

    Hayden, Sandra C.; Sweet, Adam J.; Christa, Scott E.

    2004-01-01

    The Earth Observing One satellite, launched in November 2000, is an active earth science observation platform. This paper reports on the progress of an infusion experiment in which the Livingstone 2 Model-Based Diagnostic engine is deployed on Earth Observing One, demonstrating the capability to monitor the nominal operation of the spacecraft under command of an on-board planner, and demonstrating on-board diagnosis of spacecraft failures. Design and development of the experiment, specification and validation of diagnostic scenarios, characterization of performance results and benefits of the model- based approach are presented.

  9. Diagnosis of cardiovascular abnormalities from compressed ECG: a data mining-based approach.

    PubMed

    Sufi, Fahim; Khalil, Ibrahim

    2011-01-01

    Usage of compressed ECG for fast and efficient telecardiology application is crucial, as ECG signals are enormously large in size. However, conventional ECG diagnosis algorithms require the compressed ECG packets to be decompressed before diagnosis can be performed. This added step of decompression before performing diagnosis for every ECG packet introduces unnecessary delay, which is undesirable for cardiovascular diseased (CVD) patients. In this paper, we are demonstrating an innovative technique that performs real-time classification of CVD. With the help of this real-time classification of CVD, the emergency personnel or the hospital can automatically be notified via SMS/MMS/e-mail when a life-threatening cardiac abnormality of the CVD affected patient is detected. Our proposed system initially uses data mining techniques, such as attribute selection (i.e., selects only a few features from the compressed ECG) and expectation maximization (EM)-based clustering. These data mining techniques running on a hospital server generate a set of constraints for representing each of the abnormalities. Then, the patient's mobile phone receives these set of constraints and employs a rule-based system that can identify each of abnormal beats in real time. Our experimentation results on 50 MIT-BIH ECG entries reveal that the proposed approach can successfully detect cardiac abnormalities (e.g., ventricular flutter/fibrillation, premature ventricular contraction, atrial fibrillation, etc.) with 97% accuracy on average. This innovative data mining technique on compressed ECG packets enables faster identification of cardiac abnormality directly from the compressed ECG, helping to build an efficient telecardiology diagnosis system. PMID:21097383

  10. [Application of optimized parameters SVM based on photoacoustic spectroscopy method in fault diagnosis of power transformer].

    PubMed

    Zhang, Yu-xin; Cheng, Zhi-feng; Xu, Zheng-ping; Bai, Jing

    2015-01-01

    In order to solve the problems such as complex operation, consumption for the carrier gas and long test period in traditional power transformer fault diagnosis approach based on dissolved gas analysis (DGA), this paper proposes a new method which is detecting 5 types of characteristic gas content in transformer oil such as CH4, C2H2, C2H4, C2H6 and H2 based on photoacoustic Spectroscopy and C2H2/C2H4, CH4/H2, C2H4/C2H6 three-ratios data are calculated. The support vector machine model was constructed using cross validation method under five support vector machine functions and four kernel functions, heuristic algorithms were used in parameter optimization for penalty factor c and g, which to establish the best SVM model for the highest fault diagnosis accuracy and the fast computing speed. Particles swarm optimization and genetic algorithm two types of heuristic algorithms were comparative studied in this paper for accuracy and speed in optimization. The simulation result shows that SVM model composed of C-SVC, RBF kernel functions and genetic algorithm obtain 97. 5% accuracy in test sample set and 98. 333 3% accuracy in train sample set, and genetic algorithm was about two times faster than particles swarm optimization in computing speed. The methods described in this paper has many advantages such as simple operation, non-contact measurement, no consumption for the carrier gas, long test period, high stability and sensitivity, the result shows that the methods described in this paper can instead of the traditional transformer fault diagnosis by gas chromatography and meets the actual project needs in transformer fault diagnosis. PMID:25993810

  11. Development of a simple, accurate SPME-based method for assay of VOCs in column breakthrough experiments.

    PubMed

    Salaices Avila, Manuel Alejandro; Breiter, Roman; Mott, Henry

    2007-01-01

    Solid-phase microextraction (SPME) with gas chromatography is to be used for assay of effluent liquid samples from soil column experiments associated with VOC fate/transport studies. One goal of the fate/transport studies is to develop accurate, highly reproducible column breakthrough curves for 1,2-cis-dichloroethylene (cis-DCE) and trichloroethylene (TCE) to better understand interactions with selected natural solid phases. For SPME, the influences of the sample equilibration time, extraction temperature and the ratio of volume of sample bottle to that of the liquid sample (V(T)/V(w)) are the critical factors that could influence accuracy and precision of the measured results. Equilibrium between the gas phase and liquid phase was attained after 200 min of equilibration time. The temperature must be carefully controlled due to variation of both the Henry's constant (K(h)) and the fibre/gas phase distribution coefficient (K(fg)). K(h) decreases with decreasing temperature while K(fg) increases. Low V(T)/V(w) yields better sensitivity but results in analyte losses and negative bias of the resultant assay. High V(T)/V(w) ratio yields reduced sensitivity but analyte losses were found to be minimal, leading to better accuracy and reproducibility. A fast SPME method was achieved, 5 min for SPME extraction and 3.10 min for GC analysis. A linear calibration function in the gas phase was developed to analyse the breakthrough curve data, linear between a range of 0.9-236 microgl(-1), and a detection limit lower than 5 microgl(-1). PMID:16844196

  12. Accurate electrical prediction of memory array through SEM-based edge-contour extraction using SPICE simulation

    NASA Astrophysics Data System (ADS)

    Shauly, Eitan; Rotstein, Israel; Peltinov, Ram; Latinski, Sergei; Adan, Ofer; Levi, Shimon; Menadeva, Ovadya

    2009-03-01

    The continues transistors scaling efforts, for smaller devices, similar (or larger) drive current/um and faster devices, increase the challenge to predict and to control the transistor off-state current. Typically, electrical simulators like SPICE, are using the design intent (as-drawn GDS data). At more sophisticated cases, the simulators are fed with the pattern after lithography and etch process simulations. As the importance of electrical simulation accuracy is increasing and leakage is becoming more dominant, there is a need to feed these simulators, with more accurate information extracted from physical on-silicon transistors. Our methodology to predict changes in device performances due to systematic lithography and etch effects was used in this paper. In general, the methodology consists on using the OPCCmaxTM for systematic Edge-Contour-Extraction (ECE) from transistors, taking along the manufacturing and includes any image distortions like line-end shortening, corner rounding and line-edge roughness. These measurements are used for SPICE modeling. Possible application of this new metrology is to provide a-head of time, physical and electrical statistical data improving time to market. In this work, we applied our methodology to analyze a small and large array's of 2.14um2 6T-SRAM, manufactured using Tower Standard Logic for General Purposes Platform. 4 out of the 6 transistors used "U-Shape AA", known to have higher variability. The predicted electrical performances of the transistors drive current and leakage current, in terms of nominal values and variability are presented. We also used the methodology to analyze an entire SRAM Block array. Study of an isolation leakage and variability are presented.

  13. A mutate-and-map strategy accurately infers the base pairs of a 35-nucleotide model RNA

    PubMed Central

    Kladwang, Wipapat; Cordero, Pablo; Das, Rhiju

    2011-01-01

    We present a rapid experimental strategy for inferring base pairs in structured RNAs via an information-rich extension of classic chemical mapping approaches. The mutate-and-map method, previously applied to a DNA/RNA helix, systematically searches for single mutations that enhance the chemical accessibility of base-pairing partners distant in sequence. To test this strategy for structured RNAs, we have carried out mutate-and-map measurements for a 35-nt hairpin, called the MedLoop RNA, embedded within an 80-nt sequence. We demonstrate the synthesis of all 105 single mutants of the MedLoop RNA sequence and present high-throughput DMS, CMCT, and SHAPE modification measurements for this library at single-nucleotide resolution. The resulting two-dimensional data reveal visually clear, punctate features corresponding to RNA base pair interactions as well as more complex features; these signals can be qualitatively rationalized by comparison to secondary structure predictions. Finally, we present an automated, sequence-blind analysis that permits the confident identification of nine of the 10 MedLoop RNA base pairs at single-nucleotide resolution, while discriminating against all 1460 false-positive base pairs. These results establish the accuracy and information content of the mutate-and-map strategy and support its feasibility for rapidly characterizing the base-pairing patterns of larger and more complex RNA systems. PMID:21239468

  14. How to accurately bypass damage

    PubMed Central

    Broyde, Suse; Patel, Dinshaw J.

    2016-01-01

    Ultraviolet radiation can cause cancer through DNA damage — specifically, by linking adjacent thymine bases. Crystal structures show how the enzyme DNA polymerase η accurately bypasses such lesions, offering protection. PMID:20577203

  15. Early diagnosis of Irkut virus infection using magnetic bead-based serum peptide profiling by MALDI-TOF MS in a mouse model.

    PubMed

    Li, Nan; Liu, Ye; Hao, Zhuo; Zhang, Shoufeng; Hu, Rongliang; Li, Jiping

    2014-01-01

    Early diagnosis is important for the prompt post-exposure prophylaxis of lyssavirus infections. To diagnose Irkut virus (IRKV) infection during incubation in mice, a novel method using magnetic bead-based serum peptide profiling by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been established. For this test, serum peptides were concentrated by adsorption to and elution from the magnetic bead-based weak cation ion exchanger. Mass spectrograms obtained by MALDI-TOF MS were analyzed using ClinProTools bioinformatics software. Construction of the diagnostic model was performed using serum samples from mice infected with IRKV and rabies virus (RABV) BD06, Flury-LEP, and SRV9 (as controls). The method accurately diagnosed sera 2, 4 and 8 days after IRKV and RABV infections. The sensitivity, specificity, and total accuracy of diagnosis were 86.7%, 95.2%, and 92.9%, respectively. However, IRKV could not be differentiated from RABV 1 day after infection. The results of the present study indicate that serum peptide profiling by MALDI-TOF MS is a promising technique for the early clinical diagnosis of lyssavirus infections and needs to be further tested in humans and farm animals. PMID:24670473

  16. Toward Quantitatively Accurate Calculation of the Redox-Associated Acid–Base and Ligand Binding Equilibria of Aquacobalamin

    DOE PAGESBeta

    Johnston, Ryne C.; Zhou, Jing; Smith, Jeremy C.; Parks, Jerry M.

    2016-07-08

    In redox processes in complex transition metal-containing species are often intimately associated with changes in ligand protonation states and metal coordination number. Moreover, a major challenge is therefore to develop consistent computational approaches for computing pH-dependent redox and ligand dissociation properties of organometallic species. Reduction of the Co center in the vitamin B12 derivative aquacobalamin can be accompanied by ligand dissociation, protonation, or both, making these properties difficult to compute accurately. We examine this challenge here by using density functional theory and continuum solvation to compute Co ligand binding equilibrium constants (Kon/off), pKas and reduction potentials for models of aquacobalaminmore » in aqueous solution. We consider two models for cobalamin ligand coordination: the first follows the hexa, penta, tetra coordination scheme for CoIII, CoII, and CoI species, respectively, and the second model features saturation of each vacant axial coordination site on CoII and CoI species with a single, explicit water molecule to maintain six directly interacting ligands or water molecules in each oxidation state. Comparing these two coordination schemes in combination with five dispersion-corrected density functionals, we find that the accuracy of the computed properties is largely independent of the scheme used, but including only a continuum representation of the solvent yields marginally better results than saturating the first solvation shell around Co throughout. PBE performs best, displaying balanced accuracy and superior performance overall, with RMS errors of 80 mV for seven reduction potentials, 2.0 log units for five pKas and 2.3 log units for two log Kon/off values for the aquacobalamin system. Furthermore, we find that the BP86 functional commonly used in corrinoid studies suffers from erratic behavior and inaccurate descriptions of Co axial ligand binding, leading to substantial errors in predicted

  17. Toward Quantitatively Accurate Calculation of the Redox-Associated Acid-Base and Ligand Binding Equilibria of Aquacobalamin.

    PubMed

    Johnston, Ryne C; Zhou, Jing; Smith, Jeremy C; Parks, Jerry M

    2016-08-01

    Redox processes in complex transition metal-containing species are often intimately associated with changes in ligand protonation states and metal coordination number. A major challenge is therefore to develop consistent computational approaches for computing pH-dependent redox and ligand dissociation properties of organometallic species. Reduction of the Co center in the vitamin B12 derivative aquacobalamin can be accompanied by ligand dissociation, protonation, or both, making these properties difficult to compute accurately. We examine this challenge here by using density functional theory and continuum solvation to compute Co-ligand binding equilibrium constants (Kon/off), pKas, and reduction potentials for models of aquacobalamin in aqueous solution. We consider two models for cobalamin ligand coordination: the first follows the hexa, penta, tetra coordination scheme for Co(III), Co(II), and Co(I) species, respectively, and the second model features saturation of each vacant axial coordination site on Co(II) and Co(I) species with a single, explicit water molecule to maintain six directly interacting ligands or water molecules in each oxidation state. Comparing these two coordination schemes in combination with five dispersion-corrected density functionals, we find that the accuracy of the computed properties is largely independent of the scheme used, but including only a continuum representation of the solvent yields marginally better results than saturating the first solvation shell around Co throughout. PBE performs best, displaying balanced accuracy and superior performance overall, with RMS errors of 80 mV for seven reduction potentials, 2.0 log units for five pKas and 2.3 log units for two log Kon/off values for the aquacobalamin system. Furthermore, we find that the BP86 functional commonly used in corrinoid studies suffers from erratic behavior and inaccurate descriptions of Co-axial ligand binding, leading to substantial errors in predicted pKas and

  18. Stable and accurate hybrid finite volume methods based on pure convexity arguments for hyperbolic systems of conservation law

    NASA Astrophysics Data System (ADS)

    De Vuyst, Florian

    2004-01-01

    This exploratory work tries to present first results of a novel approach for the numerical approximation of solutions of hyperbolic systems of conservation laws. The objective is to define stable and "reasonably" accurate numerical schemes while being free from any upwind process and from any computation of derivatives or mean Jacobian matrices. That means that we only want to perform flux evaluations. This would be useful for "complicated" systems like those of two-phase models where solutions of Riemann problems are hard, see impossible to compute. For Riemann or Roe-like solvers, each fluid model needs the particular computation of the Jacobian matrix of the flux and the hyperbolicity property which can be conditional for some of these models makes the matrices be not R-diagonalizable everywhere in the admissible state space. In this paper, we rather propose some numerical schemes where the stability is obtained using convexity considerations. A certain rate of accuracy is also expected. For that, we propose to build numerical hybrid fluxes that are convex combinations of the second-order Lax-Wendroff scheme flux and the first-order modified Lax-Friedrichs scheme flux with an "optimal" combination rate that ensures both minimal numerical dissipation and good accuracy. The resulting scheme is a central scheme-like method. We will also need and propose a definition of local dissipation by convexity for hyperbolic or elliptic-hyperbolic systems. This convexity argument allows us to overcome the difficulty of nonexistence of classical entropy-flux pairs for certain systems. We emphasize the systematic feature of the method which can be fastly implemented or adapted to any kind of systems, with general analytical or data-tabulated equations of state. The numerical results presented in the paper are not superior to many existing state-of-the-art numerical methods for conservation laws such as ENO, MUSCL or central scheme of Tadmor and coworkers. The interest is rather

  19. Fault Tree Based Diagnosis with Optimal Test Sequencing for Field Service Engineers

    NASA Technical Reports Server (NTRS)

    Iverson, David L.; George, Laurence L.; Patterson-Hine, F. A.; Lum, Henry, Jr. (Technical Monitor)

    1994-01-01

    When field service engineers go to customer sites to service equipment, they want to diagnose and repair failures quickly and cost effectively. Symptoms exhibited by failed equipment frequently suggest several possible causes which require different approaches to diagnosis. This can lead the engineer to follow several fruitless paths in the diagnostic process before they find the actual failure. To assist in this situation, we have developed the Fault Tree Diagnosis and Optimal Test Sequence (FTDOTS) software system that performs automated diagnosis and ranks diagnostic hypotheses based on failure probability and the time or cost required to isolate and repair each failure. FTDOTS first finds a set of possible failures that explain exhibited symptoms by using a fault tree reliability model as a diagnostic knowledge to rank the hypothesized failures based on how likely they are and how long it would take or how much it would cost to isolate and repair them. This ordering suggests an optimal sequence for the field service engineer to investigate the hypothesized failures in order to minimize the time or cost required to accomplish the repair task. Previously, field service personnel would arrive at the customer site and choose which components to investigate based on past experience and service manuals. Using FTDOTS running on a portable computer, they can now enter a set of symptoms and get a list of possible failures ordered in an optimal test sequence to help them in their decisions. If facilities are available, the field engineer can connect the portable computer to the malfunctioning device for automated data gathering. FTDOTS is currently being applied to field service of medical test equipment. The techniques are flexible enough to use for many different types of devices. If a fault tree model of the equipment and information about component failure probabilities and isolation times or costs are available, a diagnostic knowledge base for that device can be

  20. Participatory diagnosis in urban planning: proposal for a learning process based on geographical information.

    PubMed

    Joerin, Florent; Desthieux, Gilles; Beuze, Sandrine Billeau; Nembrini, Aurore

    2009-05-01

    Urban planning involves compromise between the diverse and often contradictory issues supported by the different stakeholders. The literature generally agrees on the need to broaden the participation base to overcome this difficulty. However, participation should not be limited to problem solving, but should also take place in the problem setting phase. This paper proposes a participatory diagnosis process for structuring the problem setting phase. We describe an experiment in a participatory diagnosis conducted with the residents of a Geneva neighborhood. The experiment began by identifying the residents' concerns, which were then reformulated under broader issues. Some 20 spatial indicators were built using GIS tools, and were then applied in a second phase of resident consultations to assess the relative importance of each issue. The ensuing priority issues formed the core of the diagnosis. The approach emphasized comparison between the daily experiences of residents and so-called official information (i.e. census tract, traffic measurement, and so on). The residents were therefore involved in a learning process that allowed them to consolidate or modify their opinions. The process led to the emergence of a clearly defined collective awareness that supplanted individual aspirations. PMID:18562082

  1. A Bayesian least squares support vector machines based framework for fault diagnosis and failure prognosis

    NASA Astrophysics Data System (ADS)

    Khawaja, Taimoor Saleem

    A high-belief low-overhead Prognostics and Health Management (PHM) system is desired for online real-time monitoring of complex non-linear systems operating in a complex (possibly non-Gaussian) noise environment. This thesis presents a Bayesian Least Squares Support Vector Machine (LS-SVM) based framework for fault diagnosis and failure prognosis in nonlinear non-Gaussian systems. The methodology assumes the availability of real-time process measurements, definition of a set of fault indicators and the existence of empirical knowledge (or historical data) to characterize both nominal and abnormal operating conditions. An efficient yet powerful Least Squares Support Vector Machine (LS-SVM) algorithm, set within a Bayesian Inference framework, not only allows for the development of real-time algorithms for diagnosis and prognosis but also provides a solid theoretical framework to address key concepts related to classification for diagnosis and regression modeling for prognosis. SVM machines are founded on the principle of Structural Risk Minimization (SRM) which tends to find a good trade-off between low empirical risk and small capacity. The key features in SVM are the use of non-linear kernels, the absence of local minima, the sparseness of the solution and the capacity control obtained by optimizing the margin. The Bayesian Inference framework linked with LS-SVMs allows a probabilistic interpretation of the results for diagnosis and prognosis. Additional levels of inference provide the much coveted features of adaptability and tunability of the modeling parameters. The two main modules considered in this research are fault diagnosis and failure prognosis. With the goal of designing an efficient and reliable fault diagnosis scheme, a novel Anomaly Detector is suggested based on the LS-SVM machines. The proposed scheme uses only baseline data to construct a 1-class LS-SVM machine which, when presented with online data is able to distinguish between normal behavior

  2. Mass Spectrometry-based Workflow for Accurate Quantification of Escherichia coli Enzymes: How Proteomics Can Play a Key Role in Metabolic Engineering*

    PubMed Central

    Trauchessec, Mathieu; Jaquinod, Michel; Bonvalot, Aline; Brun, Virginie; Bruley, Christophe; Ropers, Delphine; de Jong, Hidde; Garin, Jérôme; Bestel-Corre, Gwenaëlle; Ferro, Myriam

    2014-01-01

    Metabolic engineering aims to design high performance microbial strains producing compounds of interest. This requires systems-level understanding; genome-scale models have therefore been developed to predict metabolic fluxes. However, multi-omics data including genomics, transcriptomics, fluxomics, and proteomics may be required to model the metabolism of potential cell factories. Recent technological advances to quantitative proteomics have made mass spectrometry-based quantitative assays an interesting alternative to more traditional immuno-affinity based approaches. This has improved specificity and multiplexing capabilities. In this study, we developed a quantification workflow to analyze enzymes involved in central metabolism in Escherichia coli (E. coli). This workflow combined full-length isotopically labeled standards with selected reaction monitoring analysis. First, full-length 15N labeled standards were produced and calibrated to ensure accurate measurements. Liquid chromatography conditions were then optimized for reproducibility and multiplexing capabilities over a single 30-min liquid chromatography-MS analysis. This workflow was used to accurately quantify 22 enzymes involved in E. coli central metabolism in a wild-type reference strain and two derived strains, optimized for higher NADPH production. In combination with measurements of metabolic fluxes, proteomics data can be used to assess different levels of regulation, in particular enzyme abundance and catalytic rate. This provides information that can be used to design specific strains used in biotechnology. In addition, accurate measurement of absolute enzyme concentrations is key to the development of predictive kinetic models in the context of metabolic engineering. PMID:24482123

  3. Computer aided diagnosis based on medical image processing and artificial intelligence methods

    NASA Astrophysics Data System (ADS)

    Stoitsis, John; Valavanis, Ioannis; Mougiakakou, Stavroula G.; Golemati, Spyretta; Nikita, Alexandra; Nikita, Konstantina S.

    2006-12-01

    Advances in imaging technology and computer science have greatly enhanced interpretation of medical images, and contributed to early diagnosis. The typical architecture of a Computer Aided Diagnosis (CAD) system includes image pre-processing, definition of region(s) of interest, features extraction and selection, and classification. In this paper, the principles of CAD systems design and development are demonstrated by means of two examples. The first one focuses on the differentiation between symptomatic and asymptomatic carotid atheromatous plaques. For each plaque, a vector of texture and motion features was estimated, which was then reduced to the most robust ones by means of ANalysis of VAriance (ANOVA). Using fuzzy c-means, the features were then clustered into two classes. Clustering performances of 74%, 79%, and 84% were achieved for texture only, motion only, and combinations of texture and motion features, respectively. The second CAD system presented in this paper supports the diagnosis of focal liver lesions and is able to characterize liver tissue from Computed Tomography (CT) images as normal, hepatic cyst, hemangioma, and hepatocellular carcinoma. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of neural network classifiers. The achieved classification performance was 100%, 93.75% and 90.63% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis.

  4. Accurate and easy-to-use assessment of contiguous DNA methylation sites based on proportion competitive quantitative-PCR and lateral flow nucleic acid biosensor.

    PubMed

    Xu, Wentao; Cheng, Nan; Huang, Kunlun; Lin, Yuehe; Wang, Chenguang; Xu, Yuancong; Zhu, Longjiao; Du, Dan; Luo, Yunbo

    2016-06-15

    Many types of diagnostic technologies have been reported for DNA methylation, but they require a standard curve for quantification or only show moderate accuracy. Moreover, most technologies have difficulty providing information on the level of methylation at specific contiguous multi-sites, not to mention easy-to-use detection to eliminate labor-intensive procedures. We have addressed these limitations and report here a cascade strategy that combines proportion competitive quantitative PCR (PCQ-PCR) and lateral flow nucleic acid biosensor (LFNAB), resulting in accurate and easy-to-use assessment. The P16 gene with specific multi-methylated sites, a well-studied tumor suppressor gene, was used as the target DNA sequence model. First, PCQ-PCR provided amplification products with an accurate proportion of multi-methylated sites following the principle of proportionality, and double-labeled duplex DNA was synthesized. Then, a LFNAB strategy was further employed for amplified signal detection via immune affinity recognition, and the exact level of site-specific methylation could be determined by the relative intensity of the test line and internal reference line. This combination resulted in all recoveries being greater than 94%, which are pretty satisfactory recoveries in DNA methylation assessment. Moreover, the developed cascades show significantly high usability as a simple, sensitive, and low-cost tool. Therefore, as a universal platform for sensing systems for the detection of contiguous multi-sites of DNA methylation without external standards and expensive instrumentation, this PCQ-PCR-LFNAB cascade method shows great promise for the point-of-care diagnosis of cancer risk and therapeutics. PMID:26914373

  5. Computer-Based Image Analysis for Plus Disease Diagnosis in Retinopathy of Prematurity: Performance of the “i-ROP” System and Image Features Associated With Expert Diagnosis

    PubMed Central

    Ataer-Cansizoglu, Esra; Bolon-Canedo, Veronica; Campbell, J. Peter; Bozkurt, Alican; Erdogmus, Deniz; Kalpathy-Cramer, Jayashree; Patel, Samir; Jonas, Karyn; Chan, R. V. Paul; Ostmo, Susan; Chiang, Michael F.

    2015-01-01

    Purpose We developed and evaluated the performance of a novel computer-based image analysis system for grading plus disease in retinopathy of prematurity (ROP), and identified the image features, shapes, and sizes that best correlate with expert diagnosis. Methods A dataset of 77 wide-angle retinal images from infants screened for ROP was collected. A reference standard diagnosis was determined for each image by combining image grading from 3 experts with the clinical diagnosis from ophthalmoscopic examination. Manually segmented images were cropped into a range of shapes and sizes, and a computer algorithm was developed to extract tortuosity and dilation features from arteries and veins. Each feature was fed into our system to identify the set of characteristics that yielded the highest-performing system compared to the reference standard, which we refer to as the “i-ROP” system. Results Among the tested crop shapes, sizes, and measured features, point-based measurements of arterial and venous tortuosity (combined), and a large circular cropped image (with radius 6 times the disc diameter), provided the highest diagnostic accuracy. The i-ROP system achieved 95% accuracy for classifying preplus and plus disease compared to the reference standard. This was comparable to the performance of the 3 individual experts (96%, 94%, 92%), and significantly higher than the mean performance of 31 nonexperts (81%). Conclusions This comprehensive analysis of computer-based plus disease suggests that it may be feasible to develop a fully-automated system based on wide-angle retinal images that performs comparably to expert graders at three-level plus disease discrimination. Translational Relevance Computer-based image analysis, using objective and quantitative retinal vascular features, has potential to complement clinical ROP diagnosis by ophthalmologists. PMID:26644965

  6. RCK: accurate and efficient inference of sequence- and structure-based protein–RNA binding models from RNAcompete data

    PubMed Central

    Orenstein, Yaron; Wang, Yuhao; Berger, Bonnie

    2016-01-01

    Motivation: Protein–RNA interactions, which play vital roles in many processes, are mediated through both RNA sequence and structure. CLIP-based methods, which measure protein–RNA binding in vivo, suffer from experimental noise and systematic biases, whereas in vitro experiments capture a clearer signal of protein RNA-binding. Among them, RNAcompete provides binding affinities of a specific protein to more than 240 000 unstructured RNA probes in one experiment. The computational challenge is to infer RNA structure- and sequence-based binding models from these data. The state-of-the-art in sequence models, Deepbind, does not model structural preferences. RNAcontext models both sequence and structure preferences, but is outperformed by GraphProt. Unfortunately, GraphProt cannot detect structural preferences from RNAcompete data due to the unstructured nature of the data, as noted by its developers, nor can it be tractably run on the full RNACompete dataset. Results: We develop RCK, an efficient, scalable algorithm that infers both sequence and structure preferences based on a new k-mer based model. Remarkably, even though RNAcompete data is designed to be unstructured, RCK can still learn structural preferences from it. RCK significantly outperforms both RNAcontext and Deepbind in in vitro binding prediction for 244 RNAcompete experiments. Moreover, RCK is also faster and uses less memory, which enables scalability. While currently on par with existing methods in in vivo binding prediction on a small scale test, we demonstrate that RCK will increasingly benefit from experimentally measured RNA structure profiles as compared to computationally predicted ones. By running RCK on the entire RNAcompete dataset, we generate and provide as a resource a set of protein–RNA structure-based models on an unprecedented scale. Availability and Implementation: Software and models are freely available at http://rck.csail.mit.edu/ Contact: bab@mit.edu Supplementary information

  7. The KATE shell: An implementation of model-based control, monitor and diagnosis

    NASA Technical Reports Server (NTRS)

    Cornell, Matthew

    1987-01-01

    The conventional control and monitor software currently used by the Space Center for Space Shuttle processing has many limitations such as high maintenance costs, limited diagnostic capabilities and simulation support. These limitations have caused the development of a knowledge based (or model based) shell to generically control and monitor electro-mechanical systems. The knowledge base describes the system's structure and function and is used by a software shell to do real time constraints checking, low level control of components, diagnosis of detected faults, sensor validation, automatic generation of schematic diagrams and automatic recovery from failures. This approach is more versatile and more powerful than the conventional hard coded approach and offers many advantages over it, although, for systems which require high speed reaction times or aren't well understood, knowledge based control and monitor systems may not be appropriate.

  8. Microwave-based stroke diagnosis making global prehospital thrombolytic treatment possible.

    PubMed

    Persson, Mikael; Fhager, Andreas; Trefná, Hana Dobsicek; Yu, Yinan; McKelvey, Tomas; Pegenius, Göran; Karlsson, Jan-Erik; Elam, Mikael

    2014-11-01

    Here, we present two different brain diagnostic devices based on microwave technology and the associated two first proof-of-principle measurements that show that the systems can differentiate hemorrhagic from ischemic stroke in acute stroke patients, as well as differentiate hemorrhagic patients from healthy volunteers. The system was based on microwave scattering measurements with an antenna system worn on the head. Measurement data were analyzed with a machine-learning algorithm that is based on training using data from patients with a known condition. Computer tomography images were used as reference. The detection methodology was evaluated with the leave-one-out validation method combined with a Monte Carlo-based bootstrap step. The clinical motivation for this project is that ischemic stroke patients may receive acute thrombolytic treatment at hospitals, dramatically reducing or abolishing symptoms. A microwave system is suitable for prehospital use, and therefore has the potential to allow significantly earlier diagnosis and treatment than today. PMID:24951677

  9. A non-contact method based on multiple signal classification algorithm to reduce the measurement time for accurately heart rate detection.

    PubMed

    Bechet, P; Mitran, R; Munteanu, M

    2013-08-01

    Non-contact methods for the assessment of vital signs are of great interest for specialists due to the benefits obtained in both medical and special applications, such as those for surveillance, monitoring, and search and rescue. This paper investigates the possibility of implementing a digital processing algorithm based on the MUSIC (Multiple Signal Classification) parametric spectral estimation in order to reduce the observation time needed to accurately measure the heart rate. It demonstrates that, by proper dimensioning the signal subspace, the MUSIC algorithm can be optimized in order to accurately assess the heart rate during an 8-28 s time interval. The validation of the processing algorithm performance was achieved by minimizing the mean error of the heart rate after performing simultaneous comparative measurements on several subjects. In order to calculate the error the reference value of heart rate was measured using a classic measurement system through direct contact. PMID:24007088

  10. A non-contact method based on multiple signal classification algorithm to reduce the measurement time for accurately heart rate detection

    NASA Astrophysics Data System (ADS)

    Bechet, P.; Mitran, R.; Munteanu, M.

    2013-08-01

    Non-contact methods for the assessment of vital signs are of great interest for specialists due to the benefits obtained in both medical and special applications, such as those for surveillance, monitoring, and search and rescue. This paper investigates the possibility of implementing a digital processing algorithm based on the MUSIC (Multiple Signal Classification) parametric spectral estimation in order to reduce the observation time needed to accurately measure the heart rate. It demonstrates that, by proper dimensioning the signal subspace, the MUSIC algorithm can be optimized in order to accurately assess the heart rate during an 8-28 s time interval. The validation of the processing algorithm performance was achieved by minimizing the mean error of the heart rate after performing simultaneous comparative measurements on several subjects. In order to calculate the error the reference value of heart rate was measured using a classic measurement system through direct contact.

  11. Accurate kinematic measurement at interfaces between dissimilar materials using conforming finite-element-based digital image correlation

    NASA Astrophysics Data System (ADS)

    Tao, Ran; Moussawi, Ali; Lubineau, Gilles; Pan, Bing

    2016-06-01

    Digital image correlation (DIC) is now an extensively applied full-field measurement technique with subpixel accuracy. A systematic drawback of this technique, however, is the smoothening of the kinematic field (e.g., displacement and strains) across interfaces between dissimilar materials, where the deformation gradient is known to be large. This can become an issue when a high level of accuracy is needed, for example, in the interfacial region of composites or joints. In this work, we described the application of global conforming finite-element-based DIC technique to obtain precise kinematic fields at interfaces between dissimilar materials. Speckle images from both numerical and actual experiments processed by the described global DIC technique better captured sharp strain gradient at the interface than local subset-based DIC.

  12. A time domain based method for the accurate measurement of Q-factor and resonance frequency of microwave resonators

    SciTech Connect

    Gyüre, B.; Márkus, B. G.; Bernáth, B.; Simon, F.; Murányi, F.

    2015-09-15

    We present a novel method to determine the resonant frequency and quality factor of microwave resonators which is faster, more stable, and conceptually simpler than the yet existing techniques. The microwave resonator is pumped with the microwave radiation at a frequency away from its resonance. It then emits an exponentially decaying radiation at its eigen-frequency when the excitation is rapidly switched off. The emitted microwave signal is down-converted with a microwave mixer, digitized, and its Fourier transformation (FT) directly yields the resonance curve in a single shot. Being a FT based method, this technique possesses the Fellgett (multiplex) and Connes (accuracy) advantages and it conceptually mimics that of pulsed nuclear magnetic resonance. We also establish a novel benchmark to compare accuracy of the different approaches of microwave resonator measurements. This shows that the present method has similar accuracy to the existing ones, which are based on sweeping or modulating the frequency of the microwave radiation.

  13. An accurate 3D shape context based non-rigid registration method for mouse whole-body skeleton registration

    NASA Astrophysics Data System (ADS)

    Xiao, Di; Zahra, David; Bourgeat, Pierrick; Berghofer, Paula; Acosta Tamayo, Oscar; Wimberley, Catriona; Gregoire, Marie C.; Salvado, Olivier

    2011-03-01

    Small animal image registration is challenging because of its joint structure, and posture and position difference in each acquisition without a standard scan protocol. In this paper, we face the issue of mouse whole-body skeleton registration from CT images. A novel method is developed for analyzing mouse hind-limb and fore-limb postures based on geodesic path descriptor and then registering the major skeletons and fore limb skeletons initially by thin-plate spline (TPS) transform based on the obtained geodesic paths and their enhanced correspondence fields. A target landmark correction method is proposed for improving the registration accuracy of the improved 3D shape context non-rigid registration method we previously proposed. A novel non-rigid registration framework, combining the skeleton posture analysis, geodesic path based initial alignment and 3D shape context model, is proposed for mouse whole-body skeleton registration. The performance of the proposed methods and framework was tested on 12 pairs of mouse whole-body skeletons. The experimental results demonstrated the flexibility, stability and accuracy of the proposed framework for automatic mouse whole body skeleton registration.

  14. Diagnosis System Based on Wavelet Transform, Fractal Dimension and Neural Network

    NASA Astrophysics Data System (ADS)

    El-Ramsisi, Abdallah M.; Khalil, Hassan A.

    In this study we introduce a diagnosis system based on wavelet and fractal dimension for diagnose the Heart Mitral Valve Diseases. This study deals with the feature extraction from the Doppler signal waveform at heart mitral valve using ultrasound. Wavelet packet transforms, Fourier transform and Fractal Dimension methods are used for feature extraction from the DHS signals. The back-propagation neural network is used to classify the extracted features. The system has been evaluated in 162 samples that contain 89 normal and 73 abnormal. The results showed that the classification was about 91% for normal and abnormal cases.

  15. Diagnosis of disc herniation based on classifiers and features generated from spine MR images

    NASA Astrophysics Data System (ADS)

    Koh, Jaehan; Chaudhary, Vipin; Dhillon, Gurmeet

    2010-03-01

    In recent years the demand for an automated method for diagnosis of disc abnormalities has grown as more patients suffer from lumbar disorders and radiologists have to treat more patients reliably in a limited amount of time. In this paper, we propose and compare several classifiers that diagnose disc herniation, one of the common problems of the lumbar spine, based on lumbar MR images. Experimental results on a limited data set of 68 clinical cases with 340 lumbar discs show that our classifiers can diagnose disc herniation with 97% accuracy.

  16. A logic based expert system (LBES) for fault diagnosis of power system

    SciTech Connect

    Park, Y.M.; Kim, G.W.; Sohn, J.M.

    1997-02-01

    This paper proposes an expert system for fault diagnosis of power system using a new inference method. Expertise is, in this paper, represented by logical implications and converted into a Boolean function. Unlike conventional rule-based expert systems, the expertise is converted into Prime Implicants (PIs) which are logically complete and sound. Therefore, off-line inference is possible by off-line identification of PIs, which reduces the on-line inference time considerably and makes it possible to utilize the proposed expert system in real-time environment. This paper also presents alarm verification and correction method for relay and circuit breaker (CB) using pre-identified PIs.

  17. A pseudo wavelet-based method for accurate tagline tracing on tagged MR images of the tongue

    NASA Astrophysics Data System (ADS)

    Yuan, Xiaohui; Ozturk, Cengizhan; Chi-Fishman, Gloria

    2006-03-01

    In this paper, we present a pseudo wavelet-based tagline detection method. The tagged MR image is transformed to the wavelet domain, and the prominent tagline coefficients are retained while others are eliminated. Significant stripes are extracted via segmentation, which are mixtures of tags and anatomical boundary that resembles line. A refinement step follows such that broken lines or isolated points are grouped or eliminated. Without assumption on tag models, our method extracts taglines automatically regardless their width and spacing. In addition, founded on the multi-resolution wavelet analysis, our method reconstructs taglines precisely and shows great robustness to various types of taglines.

  18. Model-Based Diagnosis and Prognosis of a Water Recycling System

    NASA Technical Reports Server (NTRS)

    Roychoudhury, Indranil; Hafiychuk, Vasyl; Goebel, Kai Frank

    2013-01-01

    A water recycling system (WRS) deployed at NASA Ames Research Center s Sustainability Base (an energy efficient office building that integrates some novel technologies developed for space applications) will serve as a testbed for long duration testing of next generation spacecraft water recycling systems for future human spaceflight missions. This system cleans graywater (waste water collected from sinks and showers) and recycles it into clean water. Like all engineered systems, the WRS is prone to standard degradation due to regular use, as well as other faults. Diagnostic and prognostic applications will be deployed on the WRS to ensure its safe, efficient, and correct operation. The diagnostic and prognostic results can be used to enable condition-based maintenance to avoid unplanned outages, and perhaps extend the useful life of the WRS. Diagnosis involves detecting when a fault occurs, isolating the root cause of the fault, and identifying the extent of damage. Prognosis involves predicting when the system will reach its end of life irrespective of whether an abnormal condition is present or not. In this paper, first, we develop a physics model of both nominal and faulty system behavior of the WRS. Then, we apply an integrated model-based diagnosis and prognosis framework to the simulation model of the WRS for several different fault scenarios to detect, isolate, and identify faults, and predict the end of life in each fault scenario, and present the experimental results.

  19. A Feature Extraction Method Based on Information Theory for Fault Diagnosis of Reciprocating Machinery

    PubMed Central

    Wang, Huaqing; Chen, Peng

    2009-01-01

    This paper proposes a feature extraction method based on information theory for fault diagnosis of reciprocating machinery. A method to obtain symptom parameter waves is defined in the time domain using the vibration signals, and an information wave is presented based on information theory, using the symptom parameter waves. A new way to determine the difference spectrum of envelope information waves is also derived, by which the feature spectrum can be extracted clearly and machine faults can be effectively differentiated. This paper also compares the proposed method with the conventional Hilbert-transform-based envelope detection and with a wavelet analysis technique. Practical examples of diagnosis for a rolling element bearing used in a diesel engine are provided to verify the effectiveness of the proposed method. The verification results show that the bearing faults that typically occur in rolling element bearings, such as outer-race, inner-race, and roller defects, can be effectively identified by the proposed method, while these bearing faults are difficult to detect using either of the other techniques it was compared to. PMID:22574021

  20. A knowledge-based system for diagnosis of mastitis problems at the herd level. 1. Concepts.

    PubMed

    Hogeveen, H; Noordhuizen-Stassen, E N; Tepp, D M; Kremer, W D; van Vliet, J H; Brand, A

    1995-07-01

    Much specialized knowledge is involved in the diagnosis of a mastitis problem at the herd level. Because of their problem-solving capacities, knowledge-based systems can be very useful to support the diagnosis of mastitis problems in the herd. Conditional causal models with multiple layers are used as a representation scheme for the development of a knowledge-based system for diagnosing mastitis problems. Construction of models requires extensive cooperation between the knowledge engineer and the domain expert. The first layer consists of three overview models: the general overview conditional causal model, the contagious overview conditional causal model, and the environmental overview conditional causal model, giving a causal description of the pathways through which mastitis problems can occur. The conditional causal model for primary udder defense and the conditional causal model for host defense are attached to the overview models at the second layer, and the conditional causal model for deep primary udder defense is attached to the conditional causal model for the primary udder defense at the third layer. Based on quantitative user input, the system determines the qualitative values of the nodes that are used for reasoning. The developed models showed that conditional causal models are a good method for modeling the mechanisms involved in a mastitis problem. The system needs to be extended in order to be useful in practical circumstances. PMID:7593836

  1. Fault diagnosis in spur gears based on genetic algorithm and random forest

    NASA Astrophysics Data System (ADS)

    Cerrada, Mariela; Zurita, Grover; Cabrera, Diego; Sánchez, René-Vinicio; Artés, Mariano; Li, Chuan

    2016-03-01

    There are growing demands for condition-based monitoring of gearboxes, and therefore new methods to improve the reliability, effectiveness, accuracy of the gear fault detection ought to be evaluated. Feature selection is still an important aspect in machine learning-based diagnosis in order to reach good performance of the diagnostic models. On the other hand, random forest classifiers are suitable models in industrial environments where large data-samples are not usually available for training such diagnostic models. The main aim of this research is to build up a robust system for the multi-class fault diagnosis in spur gears, by selecting the best set of condition parameters on time, frequency and time-frequency domains, which are extracted from vibration signals. The diagnostic system is performed by using genetic algorithms and a classifier based on random forest, in a supervised environment. The original set of condition parameters is reduced around 66% regarding the initial size by using genetic algorithms, and still get an acceptable classification precision over 97%. The approach is tested on real vibration signals by considering several fault classes, one of them being an incipient fault, under different running conditions of load and velocity.

  2. A feature extraction method based on information theory for fault diagnosis of reciprocating machinery.

    PubMed

    Wang, Huaqing; Chen, Peng

    2009-01-01

    This paper proposes a feature extraction method based on information theory for fault diagnosis of reciprocating machinery. A method to obtain symptom parameter waves is defined in the time domain using the vibration signals, and an information wave is presented based on information theory, using the symptom parameter waves. A new way to determine the difference spectrum of envelope information waves is also derived, by which the feature spectrum can be extracted clearly and machine faults can be effectively differentiated. This paper also compares the proposed method with the conventional Hilbert-transform-based envelope detection and with a wavelet analysis technique. Practical examples of diagnosis for a rolling element bearing used in a diesel engine are provided to verify the effectiveness of the proposed method. The verification results show that the bearing faults that typically occur in rolling element bearings, such as outer-race, inner-race, and roller defects, can be effectively identified by the proposed method, while these bearing faults are difficult to detect using either of the other techniques it was compared to. PMID:22574021

  3. Classification and clinical diagnosis of fibromyalgia syndrome: recommendations of recent evidence-based interdisciplinary guidelines.

    PubMed

    Fitzcharles, Mary-Ann; Shir, Yoram; Ablin, Jacob N; Buskila, Dan; Amital, Howard; Henningsen, Peter; Häuser, Winfried

    2013-01-01

    Objectives. Fibromyalgia syndrome (FMS), characterized by subjective complaints without physical or biomarker abnormality, courts controversy. Recommendations in recent guidelines addressing classification and diagnosis were examined for consistencies or differences. Methods. Systematic searches from January 2008 to February 2013 of the US-American National Guideline Clearing House, the Scottish Intercollegiate Guidelines Network, Guidelines International Network, and Medline for evidence-based guidelines for the management of FMS were conducted. Results. Three evidence-based interdisciplinary guidelines, independently developed in Canada, Germany, and Israel, recommended that FMS can be clinically diagnosed by a typical cluster of symptoms following a defined evaluation including history, physical examination, and selected laboratory tests, to exclude another somatic disease. Specialist referral is only recommended when some other physical or mental illness is reasonably suspected. The diagnosis can be based on the (modified) preliminary American College of Rheumatology (ACR) 2010 diagnostic criteria. Discussion. Guidelines from three continents showed remarkable consistency regarding the clinical concept of FMS, acknowledging that FMS is neither a distinct rheumatic nor mental disorder, but rather a cluster of symptoms, not explained by another somatic disease. While FMS remains an integral part of rheumatology, it is not an exclusive rheumatic condition and spans a broad range of medical disciplines. PMID:24379886

  4. Classification and Clinical Diagnosis of Fibromyalgia Syndrome: Recommendations of Recent Evidence-Based Interdisciplinary Guidelines

    PubMed Central

    Fitzcharles, Mary-Ann; Shir, Yoram; Ablin, Jacob N.; Buskila, Dan; Henningsen, Peter

    2013-01-01

    Objectives. Fibromyalgia syndrome (FMS), characterized by subjective complaints without physical or biomarker abnormality, courts controversy. Recommendations in recent guidelines addressing classification and diagnosis were examined for consistencies or differences. Methods. Systematic searches from January 2008 to February 2013 of the US-American National Guideline Clearing House, the Scottish Intercollegiate Guidelines Network, Guidelines International Network, and Medline for evidence-based guidelines for the management of FMS were conducted. Results. Three evidence-based interdisciplinary guidelines, independently developed in Canada, Germany, and Israel, recommended that FMS can be clinically diagnosed by a typical cluster of symptoms following a defined evaluation including history, physical examination, and selected laboratory tests, to exclude another somatic disease. Specialist referral is only recommended when some other physical or mental illness is reasonably suspected. The diagnosis can be based on the (modified) preliminary American College of Rheumatology (ACR) 2010 diagnostic criteria. Discussion. Guidelines from three continents showed remarkable consistency regarding the clinical concept of FMS, acknowledging that FMS is neither a distinct rheumatic nor mental disorder, but rather a cluster of symptoms, not explained by another somatic disease. While FMS remains an integral part of rheumatology, it is not an exclusive rheumatic condition and spans a broad range of medical disciplines. PMID:24379886

  5. Near-infrared hyperspectral unmixing based on a minimum volume criterion for fast and accurate chemometric characterization of counterfeit tablets.

    PubMed

    Lopes, Marta B; Wolff, Jean-Claude; Bioucas-Dias, José M; Figueiredo, Mário A T

    2010-02-15

    A rapid detection of the nonauthenticity of suspect tablets is a key first step in the fight against pharmaceutical counterfeiting. The chemical characterization of these tablets is the logical next step to evaluate their impact on patient health and help authorities in tracking their source. Hyperspectral unmixing of near-infrared (NIR) image data is an emerging effective technology to infer the number of compounds, their spectral signatures, and the mixing fractions in a given tablet, with a resolution of a few tens of micrometers. In a linear mixing scenario, hyperspectral vectors belong to a simplex whose vertices correspond to the spectra of the compounds present in the sample. SISAL (simplex identification via split augmented Lagrangian), MVSA (minimum volume simplex analysis), and MVES (minimum-volume enclosing simplex) are recent algorithms designed to identify the vertices of the minimum volume simplex containing the spectral vectors and the mixing fractions at each pixel (vector). This work demonstrates the usefulness of these techniques, based on minimum volume criteria, for unmixing NIR hyperspectral data of tablets. The experiments herein reported show that SISAL/MVSA and MVES largely outperform MCR-ALS (multivariate curve resolution-alternating least-squares), which is considered the state-of-the-art in spectral unmixing for analytical chemistry. These experiments are based on synthetic data (studying the effect of noise and the presence/absence of pure pixels) and on a real data set composed of NIR images of counterfeit tablets. PMID:20095581

  6. Quaternion-Based Unscented Kalman Filter for Accurate Indoor Heading Estimation Using Wearable Multi-Sensor System

    PubMed Central

    Yuan, Xuebing; Yu, Shuai; Zhang, Shengzhi; Wang, Guoping; Liu, Sheng

    2015-01-01

    Inertial navigation based on micro-electromechanical system (MEMS) inertial measurement units (IMUs) has attracted numerous researchers due to its high reliability and independence. The heading estimation, as one of the most important parts of inertial navigation, has been a research focus in this field. Heading estimation using magnetometers is perturbed by magnetic disturbances, such as indoor concrete structures and electronic equipment. The MEMS gyroscope is also used for heading estimation. However, the accuracy of gyroscope is unreliable with time. In this paper, a wearable multi-sensor system has been designed to obtain the high-accuracy indoor heading estimation, according to a quaternion-based unscented Kalman filter (UKF) algorithm. The proposed multi-sensor system including one three-axis accelerometer, three single-axis gyroscopes, one three-axis magnetometer and one microprocessor minimizes the size and cost. The wearable multi-sensor system was fixed on waist of pedestrian and the quadrotor unmanned aerial vehicle (UAV) for heading estimation experiments in our college building. The results show that the mean heading estimation errors are less 10° and 5° to multi-sensor system fixed on waist of pedestrian and the quadrotor UAV, respectively, compared to the reference path. PMID:25961384

  7. Quaternion-based unscented Kalman filter for accurate indoor heading estimation using wearable multi-sensor system.

    PubMed

    Yuan, Xuebing; Yu, Shuai; Zhang, Shengzhi; Wang, Guoping; Liu, Sheng

    2015-01-01

    Inertial navigation based on micro-electromechanical system (MEMS) inertial measurement units (IMUs) has attracted numerous researchers due to its high reliability and independence. The heading estimation, as one of the most important parts of inertial navigation, has been a research focus in this field. Heading estimation using magnetometers is perturbed by magnetic disturbances, such as indoor concrete structures and electronic equipment. The MEMS gyroscope is also used for heading estimation. However, the accuracy of gyroscope is unreliable with time. In this paper, a wearable multi-sensor system has been designed to obtain the high-accuracy indoor heading estimation, according to a quaternion-based unscented Kalman filter (UKF) algorithm. The proposed multi-sensor system including one three-axis accelerometer, three single-axis gyroscopes, one three-axis magnetometer and one microprocessor minimizes the size and cost. The wearable multi-sensor system was fixed on waist of pedestrian and the quadrotor unmanned aerial vehicle (UAV) for heading estimation experiments in our college building. The results show that the mean heading estimation errors are less 10° and 5° to multi-sensor system fixed on waist of pedestrian and the quadrotor UAV, respectively, compared to the reference path. PMID:25961384

  8. Evidence-based guideline summary: Evaluation, diagnosis, and management of congenital muscular dystrophy

    PubMed Central

    Kang, Peter B.; Morrison, Leslie; Iannaccone, Susan T.; Graham, Robert J.; Bönnemann, Carsten G.; Rutkowski, Anne; Hornyak, Joseph; Wang, Ching H.; North, Kathryn; Oskoui, Maryam; Getchius, Thomas S.D.; Cox, Julie A.; Hagen, Erin E.; Gronseth, Gary; Griggs, Robert C.

    2015-01-01

    Objective: To delineate optimal diagnostic and therapeutic approaches to congenital muscular dystrophy (CMD) through a systematic review and analysis of the currently available literature. Methods: Relevant, peer-reviewed research articles were identified using a literature search of the MEDLINE, EMBASE, and Scopus databases. Diagnostic and therapeutic data from these articles were extracted and analyzed in accordance with the American Academy of Neurology classification of evidence schemes for diagnostic, prognostic, and therapeutic studies. Recommendations were linked to the strength of the evidence, other related literature, and general principles of care. Results: The geographic and ethnic backgrounds, clinical features, brain imaging studies, muscle imaging studies, and muscle biopsies of children with suspected CMD help predict subtype-specific diagnoses. Genetic testing can confirm some subtype-specific diagnoses, but not all causative genes for CMD have been described. Seizures and respiratory complications occur in specific subtypes. There is insufficient evidence to determine the efficacy of various treatment interventions to optimize respiratory, orthopedic, and nutritional outcomes, and more data are needed regarding complications. Recommendations: Multidisciplinary care by experienced teams is important for diagnosing and promoting the health of children with CMD. Accurate assessment of clinical presentations and genetic data will help in identifying the correct subtype-specific diagnosis in many cases. Multiorgan system complications occur frequently; surveillance and prompt interventions are likely to be beneficial for affected children. More research is needed to fill gaps in knowledge regarding this category of muscular dystrophies. PMID:25825463

  9. A GC/MS-based metabolomic approach for reliable diagnosis of phenylketonuria.

    PubMed

    Xiong, Xiyue; Sheng, Xiaoqi; Liu, Dan; Zeng, Ting; Peng, Ying; Wang, Yichao

    2015-11-01

    ), which showed that phenylacetic acid may be used as a reliable discriminator for the diagnosis of PKU. The low false positive rate (1-specificity, 0.064) can be eliminated or at least greatly reduced by simultaneously referring to other markers, especially phenylpyruvic acid, a unique marker in PKU. Additionally, this standard was obtained with high sensitivity and specificity in a less invasive manner for diagnosing PKU compared with the Phe/Tyr ratio. Therefore, we conclude that urinary metabolomic information based on the improved oximation-silylation method together with GC/MS may be reliable for the diagnosis and differential diagnosis of PKU. PMID:26410738

  10. Improvement of fluorescence-enhanced optical tomography with improved optical filtering and accurate model-based reconstruction algorithms

    NASA Astrophysics Data System (ADS)

    Lu, Yujie; Zhu, Banghe; Darne, Chinmay; Tan, I.-Chih; Rasmussen, John C.; Sevick-Muraca, Eva M.

    2011-12-01

    The goal of preclinical fluorescence-enhanced optical tomography (FEOT) is to provide three-dimensional fluorophore distribution for a myriad of drug and disease discovery studies in small animals. Effective measurements, as well as fast and robust image reconstruction, are necessary for extensive applications. Compared to bioluminescence tomography (BLT), FEOT may result in improved image quality through higher detected photon count rates. However, background signals that arise from excitation illumination affect the reconstruction quality, especially when tissue fluorophore concentration is low and/or fluorescent target is located deeply in tissues. We show that near-infrared fluorescence (NIRF) imaging with an optimized filter configuration significantly reduces the background noise. Model-based reconstruction with a high-order approximation to the radiative transfer equation further improves the reconstruction quality compared to the diffusion approximation. Improvements in FEOT are demonstrated experimentally using a mouse-shaped phantom with targets of pico- and subpico-mole NIR fluorescent dye.

  11. FastME 2.0: A Comprehensive, Accurate, and Fast Distance-Based Phylogeny Inference Program.

    PubMed

    Lefort, Vincent; Desper, Richard; Gascuel, Olivier

    2015-10-01

    FastME provides distance algorithms to infer phylogenies. FastME is based on balanced minimum evolution, which is the very principle of Neighbor Joining (NJ). FastME improves over NJ by performing topological moves using fast, sophisticated algorithms. The first version of FastME only included Nearest Neighbor Interchange. The new 2.0 version also includes Subtree Pruning and Regrafting, while remaining as fast as NJ and providing a number of facilities: Distance estimation for DNA and proteins with various models and options, bootstrapping, and parallel computations. FastME is available using several interfaces: Command-line (to be integrated in pipelines), PHYLIP-like, and a Web server (http://www.atgc-montpellier.fr/fastme/). PMID:26130081

  12. CIMIDx: Prototype for a Cloud-Based System to Support Intelligent Medical Image Diagnosis With Efficiency

    PubMed Central

    2015-01-01

    Background The Internet has greatly enhanced health care, helping patients stay up-to-date on medical issues and general knowledge. Many cancer patients use the Internet for cancer diagnosis and related information. Recently, cloud computing has emerged as a new way of delivering health services but currently, there is no generic and fully automated cloud-based self-management intervention for breast cancer patients, as practical guidelines are lacking. Objective We investigated the prevalence and predictors of cloud use for medical diagnosis among women with breast cancer to gain insight into meaningful usage parameters to evaluate the use of generic, fully automated cloud-based self-intervention, by assessing how breast cancer survivors use a generic self-management model. The goal of this study was implemented and evaluated with a new prototype called “CIMIDx”, based on representative association rules that support the diagnosis of medical images (mammograms). Methods The proposed Cloud-Based System Support Intelligent Medical Image Diagnosis (CIMIDx) prototype includes two modules. The first is the design and development of the CIMIDx training and test cloud services. Deployed in the cloud, the prototype can be used for diagnosis and screening mammography by assessing the cancers detected, tumor sizes, histology, and stage of classification accuracy. To analyze the prototype’s classification accuracy, we conducted an experiment with data provided by clients. Second, by monitoring cloud server requests, the CIMIDx usage statistics were recorded for the cloud-based self-intervention groups. We conducted an evaluation of the CIMIDx cloud service usage, in which browsing functionalities were evaluated from the end-user’s perspective. Results We performed several experiments to validate the CIMIDx prototype for breast health issues. The first set of experiments evaluated the diagnostic performance of the CIMIDx framework. We collected medical information

  13. A systematic approach to the magnetic resonance imaging-based differential diagnosis of congenital Müllerian duct anomalies and their mimics.

    PubMed

    Yoo, Roh-Eul; Cho, Jeong Yeon; Kim, Sang Youn; Kim, Seung Hyup

    2015-01-01

    Müllerian duct anomalies (MDAs) represent a wide spectrum of developmental abnormalities related to various gynecologic and obstetric complications, including primary amenorrhea, infertility, and endometriosis. The use of diverse imaging modalities, in conjunction with clinical information, provide important clues to the diagnosis of MDAs. Diagnostic imaging work-up for MDAs often begins with hysterosalpingography (HSG) and/or ultrasonography (US). Although HSG and/or US may suffice to detect the presence of a uterine abnormality, magnetic resonance (MR) imaging is generally needed to classify the abnormality into a specific MDA category. MR imaging has been gaining in popularity for use in evaluating MDAs, by virtue of its noninvasiveness, lack of ionizing radiation, and capability for multiplanar imaging and soft tissue characterization. Abnormalities in the external uterine fundal contour are readily recognized with MR imaging, allowing for clear differentiation between a fusion anomaly, such as a uterus didelphys or a bicornuate uterus, and a resorption anomaly, such as a septate uterus. Furthermore, MR imaging enables clear depiction of a rudimentary uterine horn in a unicornuate uterus. Accurate differential diagnosis of MDAs on the basis of their characteristic MR imaging findings is crucial, because the rates of gynecologic and obstetric complications vary considerably among MDAs. The diagnostic accuracy may be enhanced by adopting a systematic approach to MR imaging-based differential diagnosis. PMID:25070770

  14. An accurate online calibration system based on combined clamp-shape coil for high voltage electronic current transformers.

    PubMed

    Li, Zhen-hua; Li, Hong-bin; Zhang, Zhi

    2013-07-01

    Electronic transformers are widely used in power systems because of their wide bandwidth and good transient performance. However, as an emerging technology, the failure rate o