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  1. 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.

  2. Diagnostic limitations to accurate diagnosis of cholera.

    PubMed

    Alam, Munirul; Hasan, Nur A; Sultana, Marzia; Nair, G Balakrish; Sadique, A; Faruque, A S G; Endtz, Hubert P; Sack, R B; Huq, A; Colwell, R R; Izumiya, Hidemasa; Morita, Masatomo; Watanabe, Haruo; Cravioto, Alejandro

    2010-11-01

    The treatment regimen for diarrhea depends greatly on correct diagnosis of its etiology. Recent diarrhea outbreaks in Bangladesh showed Vibrio cholerae to be the predominant cause, although more than 40% of the suspected cases failed to show cholera etiology by conventional culture methods (CMs). In the present study, suspected cholera stools collected from every 50th patient during an acute diarrheal outbreak were analyzed extensively using different microbiological and molecular tools to determine their etiology. Of 135 stools tested, 86 (64%) produced V. cholerae O1 by CMs, while 119 (88%) tested positive for V. cholerae O1 by rapid cholera dipstick (DS) assay; all but three samples positive for V. cholerae O1 by CMs were also positive for V. cholerae O1 by DS assay. Of 49 stools that lacked CM-based cholera etiology despite most being positive for V. cholerae O1 by DS assay, 25 (51%) had coccoid V. cholerae O1 cells as confirmed by direct fluorescent antibody (DFA) assay, 36 (73%) amplified primers for the genes wbe O1 and ctxA by multiplex-PCR (M-PCR), and 31 (63%) showed El Tor-specific lytic phage on plaque assay (PA). Each of these methods allowed the cholera etiology to be confirmed for 97% of the stool samples. The results suggest that suspected cholera stools that fail to show etiology by CMs during acute diarrhea outbreaks may be due to the inactivation of V. cholerae by in vivo vibriolytic action of the phage and/or nonculturability induced as a host response.

  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.

  5. Imaging tests for accurate diagnosis of acute biliary pancreatitis.

    PubMed

    Şurlin, Valeriu; Săftoiu, Adrian; Dumitrescu, Daniela

    2014-11-28

    Gallstones represent the most frequent aetiology of acute pancreatitis in many statistics all over the world, estimated between 40%-60%. Accurate diagnosis of acute biliary pancreatitis (ABP) is of outmost importance because clearance of lithiasis [gallbladder and common bile duct (CBD)] rules out recurrences. Confirmation of biliary lithiasis is done by imaging. The sensitivity of the ultrasonography (US) in the detection of gallstones is over 95% in uncomplicated cases, but in ABP, sensitivity for gallstone detection is lower, being less than 80% due to the ileus and bowel distension. Sensitivity of transabdominal ultrasonography (TUS) for choledocolithiasis varies between 50%-80%, but the specificity is high, reaching 95%. Diameter of the bile duct may be orientative for diagnosis. Endoscopic ultrasonography (EUS) seems to be a more effective tool to diagnose ABP rather than endoscopic retrograde cholangiopancreatography (ERCP), which should be performed only for therapeutic purposes. As the sensitivity and specificity of computerized tomography are lower as compared to state-of-the-art magnetic resonance cholangiopancreatography (MRCP) or EUS, especially for small stones and small diameter of CBD, the later techniques are nowadays preferred for the evaluation of ABP patients. ERCP has the highest accuracy for the diagnosis of choledocholithiasis and is used as a reference standard in many studies, especially after sphincterotomy and balloon extraction of CBD stones. Laparoscopic ultrasonography is a useful tool for the intraoperative diagnosis of choledocholithiasis. Routine exploration of the CBD in cases of patients scheduled for cholecystectomy after an attack of ABP was not proven useful. A significant rate of the so-called idiopathic pancreatitis is actually caused by microlithiasis and/or biliary sludge. In conclusion, the general algorithm for CBD stone detection starts with anamnesis, serum biochemistry and then TUS, followed by EUS or MRCP. In the end

  6. SNP-array based whole genome homozygosity mapping: a quick and powerful tool to achieve an accurate diagnosis in LGMD2 patients.

    PubMed

    Papić, Lea; Fischer, Dirk; Trajanoski, Slave; Höftberger, Romana; Fischer, Carina; Ströbel, Thomas; Schmidt, Wolfgang M; Bittner, Reginald E; Schabhüttl, Maria; Gruber, Karin; Pieber, Thomas R; Janecke, Andreas R; Auer-Grumbach, Michaela

    2011-01-01

    A large number of novel disease genes have been identified by homozygosity mapping and the positional candidate approach. In this study we used single nucleotide polymorphism (SNP) array-based, whole genome homozygosity mapping as the first step to a molecular diagnosis in the highly heterogeneous muscle disease, limb girdle muscular dystrophy (LGMD). In a consanguineous family, both affected siblings showed homozygous blocks on chromosome 15 corresponding to the LGMD2A locus. Direct sequencing of CAPN3, encoding calpain-3, identified a homozygous deletion c.483delG (p.Ile162SerfsX17). In a sporadic LGMD patient complete absence of caveolin-3 on Western blot was observed. However, a mutation in CAV3 could not be detected. Homozygosity mapping revealed a large homozygous block at the LGMD2I locus, and direct sequencing of FKRP encoding fukutin-related-protein detected the common homozygous c.826 C>A (p.Leu276Ile) mutation. Subsequent re-examination of this patient's muscle biopsy showed aberrant α-dystroglycan glycosylation. In summary, we show that whole-genome homozygosity mapping using low cost SNP arrays provides a fast and non-invasive method to identify disease-causing mutations in sporadic patients or sibs from consanguineous families in LGMD2. Furthermore, this is the first study describing that in addition to PTRF, encoding polymerase I and transcript release factor, FKRP mutations may cause secondary caveolin-3 deficiency.

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

    PubMed

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

    2015-05-22

    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 10(2) ng/mL).

  8. 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

  9. Accurate telemonitoring of Parkinson's disease diagnosis using robust inference system.

    PubMed

    Mandal, Indrajit; Sairam, N

    2013-05-01

    This work presents more precise computational methods for improving the diagnosis of Parkinson's disease based on the detection of dysphonia. New methods are presented for enhanced evaluation and recognize Parkinson's disease affected patients at early stage. Analysis is performed with significant level of error tolerance rate and established our results with corrected T-test. Here new ensembles and other machine learning methods consisting of multinomial logistic regression classifier with Haar wavelets transformation as projection filter that outperform logistic regression is used. Finally a novel and reliable inference system is presented for early recognition of people affected by this disease and presents a new measure of the severity of the disease. Feature selection method is based on Support Vector Machines and ranker search method. Performance analysis of each model is compared to the existing methods and examines the main advancements and concludes with propitious results. Reliable methods are proposed for treating Parkinson's disease that includes sparse multinomial logistic regression, Bayesian network, Support Vector Machines, Artificial Neural Networks, Boosting methods and their ensembles. The study aim at improving the quality of Parkinson's disease treatment by tracking them and reinforce the viability of cost effective, regular and precise telemonitoring application.

  10. Odontoma-associated tooth impaction: accurate diagnosis with simple methods? Case report and literature review.

    PubMed

    Troeltzsch, Matthias; Liedtke, Jan; Troeltzsch, Volker; Frankenberger, Roland; Steiner, Timm; Troeltzsch, Markus

    2012-10-01

    Odontomas account for the largest fraction of odontogenic tumors and are frequent causes of tooth impaction. A case of a 13-year-old female patient with an odontoma-associated impaction of a mandibular molar is presented with a review of the literature. Preoperative planning involved simple and convenient methods such as clinical examination and panoramic radiography, which led to a diagnosis of complex odontoma and warranted surgical removal. The clinical diagnosis was confirmed histologically. Multidisciplinary consultation may enable the clinician to find the accurate diagnosis and appropriate therapy based on the clinical and radiographic appearance. Modern radiologic methods such as cone-beam computed tomography or computed tomography should be applied only for special cases, to decrease radiation.

  11. 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

  12. Accurate stone analysis: the impact on disease diagnosis and treatment.

    PubMed

    Mandel, Neil S; Mandel, Ian C; Kolbach-Mandel, Ann M

    2017-02-01

    This manuscript reviews the requirements for acceptable compositional analysis of kidney stones using various biophysical methods. High-resolution X-ray powder diffraction crystallography and Fourier transform infrared spectroscopy (FTIR) are the only acceptable methods in our labs for kidney stone analysis. The use of well-constructed spectral reference libraries is the basis for accurate and complete stone analysis. The literature included in this manuscript identify errors in most commercial laboratories and in some academic centers. We provide personal comments on why such errors are occurring at such high rates, and although the work load is rather large, it is very worthwhile in providing accurate stone compositions. We also provide the results of our almost 90,000 stone analyses and a breakdown of the number of components we have observed in the various stones. We also offer advice on determining the method used by the various FTIR equipment manufacturers who also provide a stone analysis library so that the FTIR users can feel comfortable in the accuracy of their reported results. Such an analysis on the accuracy of the individual reference libraries could positively influence the reduction in their respective error rates.

  13. Detailed behavioral assessment promotes accurate diagnosis in patients with disorders of consciousness

    PubMed Central

    Gilutz, Yael; Lazary, Avraham; Karpin, Hana; Vatine, Jean-Jacques; Misha, Tamar; Fortinsky, Hadassah; Sharon, Haggai

    2015-01-01

    Introduction: Assessing the awareness level in patients with disorders of consciousness (DOC) is made on the basis of exhibited behaviors. However, since motor signs of awareness (i.e., non-reflex motor responses) can be very subtle, differentiating the vegetative from minimally conscious states (which is in itself not clear-cut) is often challenging. Even the careful clinician relying on standardized scales may arrive at a wrong diagnosis. Aim: To report our experience in tackling this problem by using two in-house use assessment procedures developed at Reuth Rehabilitation Hospital, and demonstrate their clinical significance by reviewing two cases. Methods: (1) Reuth DOC Response Assessment (RDOC-RA) –administered in addition to the standardized tools, and emphasizes the importance of assessing a wide range of motor responses. In our experience, in some patients the only evidence for awareness may be a private specific movement that is not assessed by standard assessment tools. (2) Reuth DOC Periodic Intervention Model (RDOC-PIM) – current literature regarding assessment and diagnosis in DOC refers mostly to the acute phase of up to 1 year post injury. However, we have found major changes in responsiveness occurring 1 year or more post-injury in many patients. Therefore, we conduct periodic assessments at predetermined times points to ensure patients are not misdiagnosed or neurological changes overlooked. Results: In the first case the RDOC-RA promoted a more accurate diagnosis than that based on standardized scales alone. The second case shows how the RDOC-PIM allowed us to recognize late recovery and promoted reinstatement of treatment with good results. Conclusion: Adding a detailed periodic assessment of DOC patients to existing scales can yield critical information, promoting better diagnosis, treatment, and clinical outcomes. We discuss the implications of this observation for the future development and validation of assessment tools in DOC patients

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

    PubMed Central

    Smith, William L.; Chadwick, Sean G.; Toner, Geoffrey; Mordechai, Eli; Adelson, Martin E.; Aguin, Tina J.; Sobel, Jack D.

    2016-01-01

    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 order Clostridiales), Megasphaera phylotype 1 or 2, Lactobacillus iners, Lactobacillus crispatus, Lactobacillus gasseri, and Lactobacillus jensenii. We generated a logistic regression model that identified G. vaginalis, A. vaginae, and Megasphaera phylotypes 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 of Lactobacillus spp. 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

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

    PubMed

    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.

  16. 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

  17. Histoplasmosis and skin lesions in HIV: a safe and accurate diagnosis.

    PubMed

    Moreno-Coutiño, Gabriela; Hernández-Castro, Rigoberto; Toussaint-Caire, Sonia; Montiel-Robles, Melisa; Sánchez-Pérez, Fiama Selene; Xicohtencatl-Cortés, Juan

    2015-07-01

    Human histoplasmosis is caused by the dimorphic fungus Histoplasma capsulatum. This infection can run asymptomatic or be life-threatening, depending fundamentally on the host's immune status. Immunocompromised patients can present disseminated disease to the skin, making the biopsy an accessible approach. The current diagnosis gold standard is fungal culture which takes several days or weeks to grow and must be handled in a biosafe laboratory which is avoided if we use the technique here described. We propose the use of molecular biology for diagnosis confirmation, considering it can shorten diagnosis lapse, has good specificity and sensitivity and reduces the risk of infection for the medical and laboratory personnel. Seven paraffin-embedded skin biopsy samples were included from patients with confirmed HIV and histoplasmosis diagnosis. Total DNA was isolated and molecular typing of H. capsulatum var. capsulatum. All samples were positive. This is a safe and accurate method for skin histoplasmosis diagnosis.

  18. 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.

  19. Race and Socioeconomic Status as Confounding Variables in the Accurate Diagnosis of Alcoholism.

    ERIC Educational Resources Information Center

    Luepnitz, Roy R.; And Others

    1982-01-01

    Studied the incidence of bias related to race and socioeconomic status which could confound the diagnosis of alcoholism. Graduate psychology students made a diagnosis based on videotapes. Results indicated lower socioeconomic class individuals were more often diagnosed correctly for alcoholism, and Blacks were diagnosed alcoholic more often than…

  20. 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.

  1. Diagnostic yield of blood clot culture in the accurate diagnosis of enteric fever and human brucellosis.

    PubMed

    Mantur, Basappa G; Bidari, Laxman H; Akki, Aravind S; Mulimani, Mallanna S; Tikare, Nitin V

    2007-01-01

    Culture of blood is the most frequent, accurate means of diagnosing bacteremia in enteric fever and brucellosis. However, conventional blood culturing is slow in isolating bacteria causing these diseases. In this work, we evaluated the performance of blood clot culture and conventional whole blood cultures in the accurate diagnosis of enteric fever (253 cases) and human brucellosis (71cases). The blood clot culture was found to be much more sensitive for both Salmonella (more by 34.4%, P< 0.001) and Brucella (more by 22.6%, P<0.001) than whole blood culture. Bacterial growth was significantly faster in cultures of blood clot compared to whole blood (1.1 versus 2.6 days for Salmonella, 3.1 versus 8.2 days for Brucella melitensis, respectively). The rapid confirmation of the etiological agent would facilitate an early institution of appropriate antimicrobial therapy, thereby reducing clinical morbidity especially in an endemic population. It is worthwile practicing blood clot culture for the accurate diagnosis of enteric fever and brucellosis in developing countries where diagnostic facilities by advanced technologies like automated culture systems and PCR are not available.

  2. Open lung biopsy: a safe, reliable and accurate method for diagnosis in diffuse lung disease.

    PubMed

    Shah, S S; Tsang, V; Goldstraw, P

    1992-01-01

    The ideal method for obtaining lung tissue for diagnosis should provide high diagnostic yield with low morbidity and mortality. We reviewed all 432 patients (mean age 55 years) who underwent an open lung biopsy at this hospital over a 10-year period. Twenty-four patients (5.5%) were immunocompromised. One hundred and twenty-five patients were on steroid therapy at the time of operation. Open lung biopsy provided a firm diagnosis in 410 cases overall (94.9%) and in 20 out of 24 patients in the immunocompromised group (83.3%). The commonest diagnosis was cryptogenic fibrosing alveolitis (173 patients). Twenty-two patients (5.1%) suffered complications following the procedure: wound infection 11 patients, pneumothorax 9 patients and haemothorax 1 patient. Thirteen patients (3.0%) died following open lung biopsy, but in only 1 patient was the death attributable to the procedure itself. We conclude that open lung biopsy is an accurate and safe method for establishing a diagnosis in diffuse lung disease with a high yield and minimal risk.

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

    PubMed

    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.

  4. Ultrasound-guided core needle biopsy of the breast: does frozen section give an accurate diagnosis?

    PubMed

    Mueller-Holzner, Elisabeth; Frede, Thomas; Daniaux, Martin; Ban, Michael; Taucher, Susanne; Schneitter, Alois; Zeimet, Alain G; Marth, Christian

    2007-12-01

    Reducing the period of uncertainty between the discovery of a breast tumor and histological diagnosis alleviates the psychological impact of breast cancer to an important degree. We aimed to verify whether histological results obtained with frozen sections of core needle biopsies (CNBs) offer an accurate and reliable tool for minimising this period. In 2619 cases we compared histological diagnosis on frozen sections with those on paraffin sections of CNB and finally with the results of open biopsies. Of the cases 49% were proved malignant and 51% benign. In 99.3% of the malignant lesions preceding CNB was correctly classified as B5 (n = 1185, 92.9%) or at least B4 (n = 82, 6.4%) in frozen and in paraffin sections. There were seven false-negative cases in frozen (false-negative rate = 0.5%) and five false-negative cases (false-negative rate = 0.4%) in paraffin sections of CNB. On frozen sections complete sensitivity was 99.5% and the positive predictive value of B5 was 99.9%. There was one false-positive case in frozen sections and one in paraffin sections. False-positive rate = 0.08%, negative predictive value for B2 = 99.4% for frozen and 99.6% for paraffin sections; full specificity was 85.9 for frozen and 85.8 for paraffin sections of CNBs. Immediate investigation of CNB in frozen sections is an accurate diagnostic method and an important step in reducing psychological strain on patients with breast tumors and may be offered by specialised Breast Assessment Units.

  5. Rapid and Accurate Diagnosis of Human Intestinal Spirochetosis by Fluorescence In Situ Hybridization▿

    PubMed Central

    Schmiedel, Dinah; Epple, Hans-Jörg; Loddenkemper, Christoph; Ignatius, Ralf; Wagner, Jutta; Hammer, Bettina; Petrich, Annett; Stein, Harald; Göbel, Ulf B.; Schneider, Thomas; Moter, Annette

    2009-01-01

    Human intestinal spirochetosis (HIS) is associated with overgrowth of the large intestine by spirochetes of the genus Brachyspira. The microbiological diagnosis of HIS is hampered by the fastidious nature and slow growth of Brachyspira spp. In clinical practice, HIS is diagnosed histopathologically, and a significant portion of cases may be missed. Fluorescence in situ hybridization (FISH) is a molecular method that allows the visualization and identification of single bacteria within tissue sections. In this study, we analyzed intestinal biopsy samples from five patients with possible HIS. All specimens yielded positive results by histopathological techniques. PCR amplification and sequencing of the 16S rRNA gene were performed. Sequences of two isolates clustered in the group of Brachyspira aalborgi, whereas in three cases, the sequences were highly similar to that of Brachyspira pilosicoli. Three phylotypes showed mismatches at distinct nucleotide positions with Brachyspira sp. sequences published previously. In addition, culture for Brachyspira was successful in three cases. On the basis of these data, we designed and evaluated a Brachyspira genus-specific 16S rRNA-directed FISH probe that detects all of the Brachyspira spp. published to date. FISH of biopsy samples resulted in strong, unequivocal signals of brush-like formations at the crypt surfaces. This technique allowed simultaneous visualization of single spirochetes and their identification as Brachyspira spp. In conclusion, FISH provides a fast and accurate technique for the visualization and identification of intestinal spirochetes in tissue sections. It therefore represents a valuable tool for routine diagnosis of HIS. PMID:19279178

  6. 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

  7. 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

  8. 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.

  9. Accurate genome relative abundance estimation based on shotgun metagenomic reads.

    PubMed

    Xia, Li C; Cram, Jacob A; Chen, Ting; Fuhrman, Jed A; Sun, Fengzhu

    2011-01-01

    Accurate estimation of microbial community composition based on metagenomic sequencing data is fundamental for subsequent metagenomics analysis. Prevalent estimation methods are mainly based on directly summarizing alignment results or its variants; often result in biased and/or unstable estimates. We have developed a unified probabilistic framework (named GRAMMy) by explicitly modeling read assignment ambiguities, genome size biases and read distributions along the genomes. Maximum likelihood method is employed to compute Genome Relative Abundance of microbial communities using the Mixture Model theory (GRAMMy). GRAMMy has been demonstrated to give estimates that are accurate and robust across both simulated and real read benchmark datasets. We applied GRAMMy to a collection of 34 metagenomic read sets from four metagenomics projects and identified 99 frequent species (minimally 0.5% abundant in at least 50% of the data-sets) in the human gut samples. Our results show substantial improvements over previous studies, such as adjusting the over-estimated abundance for Bacteroides species for human gut samples, by providing a new reference-based strategy for metagenomic sample comparisons. GRAMMy can be used flexibly with many read assignment tools (mapping, alignment or composition-based) even with low-sensitivity mapping results from huge short-read datasets. It will be increasingly useful as an accurate and robust tool for abundance estimation with the growing size of read sets and the expanding database of reference genomes.

  10. 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.

  11. A novel 33-Gene targeted resequencing panel provides accurate, clinical-grade diagnosis and improves patient management for rare inherited anaemias.

    PubMed

    Roy, Noémi B A; Wilson, Edward A; Henderson, Shirley; Wray, Katherine; Babbs, Christian; Okoli, Steven; Atoyebi, Wale; Mixon, Avery; Cahill, Mary R; Carey, Peter; Cullis, Jonathan; Curtin, Julie; Dreau, Helene; Ferguson, David J P; Gibson, Brenda; Hall, Georgina; Mason, Joanne; Morgan, Mary; Proven, Melanie; Qureshi, Amrana; Sanchez Garcia, Joaquin; Sirachainan, Nongnuch; Teo, Juliana; Tedgård, Ulf; Higgs, Doug; Roberts, David; Roberts, Irene; Schuh, Anna

    2016-10-01

    Accurate diagnosis of rare inherited anaemias is challenging, requiring a series of complex and expensive laboratory tests. Targeted next-generation-sequencing (NGS) has been used to investigate these disorders, but the selection of genes on individual panels has been narrow and the validation strategies used have fallen short of the standards required for clinical use. Clinical-grade validation of negative results requires the test to distinguish between lack of adequate sequencing reads at the locations of known mutations and a real absence of mutations. To achieve a clinically-reliable diagnostic test and minimize false-negative results we developed an open-source tool (CoverMi) to accurately determine base-coverage and the 'discoverability' of known mutations for every sample. We validated our 33-gene panel using Sanger sequencing and microarray. Our panel demonstrated 100% specificity and 99·7% sensitivity. We then analysed 57 clinical samples: molecular diagnoses were made in 22/57 (38·6%), corresponding to 32 mutations of which 16 were new. In all cases, accurate molecular diagnosis had a positive impact on clinical management. Using a validated NGS-based platform for routine molecular diagnosis of previously undiagnosed congenital anaemias is feasible in a clinical diagnostic setting, improves precise diagnosis and enhances management and counselling of the patient and their family.

  12. 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

  13. 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.

  14. 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.

  15. High order accurate finite difference schemes based on symmetry preservation

    NASA Astrophysics Data System (ADS)

    Ozbenli, Ersin; Vedula, Prakash

    2016-11-01

    A new algorithm for development of high order accurate finite difference schemes for numerical solution of partial differential equations using Lie symmetries is presented. Considering applicable symmetry groups (such as those relevant to space/time translations, Galilean transformation, scaling, rotation and projection) of a partial differential equation, invariant numerical schemes are constructed based on the notions of moving frames and modified equations. Several strategies for construction of invariant numerical schemes with a desired order of accuracy are analyzed. Performance of the proposed algorithm is demonstrated using analysis of one-dimensional partial differential equations, such as linear advection diffusion equations inviscid Burgers equation and viscous Burgers equation, as our test cases. Through numerical simulations based on these examples, the expected improvement in accuracy of invariant numerical schemes (up to fourth order) is demonstrated. Advantages due to implementation and enhanced computational efficiency inherent in our proposed algorithm are presented. Extension of the basic framework to multidimensional partial differential equations is also discussed.

  16. 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.

  17. Accurate Diagnosis of Severe Hypospadias Using 2D and 3D Ultrasounds

    PubMed Central

    López Ramón y Cajal, Carlos; Marín Ortiz, Elena; Sarmiento Carrera, Nerea

    2016-01-01

    The hypospadias is the most common urogenital anomaly of male neonates but the prenatal diagnosis of this is often missed before birth. We present the prenatal diagnosis of a severe penoscrotal hypospadias using 2D and 3D ultrasounds. 3D sonography allowed us the best evaluation of the genitals and their anatomical relations. This ample detailed study allowed us to show the findings to the parents and the pediatric surgeon and to configure the best information about the prognosis and surgical treatment. PMID:27774326

  18. Accurate measurement method for tube's endpoints based on machine vision

    NASA Astrophysics Data System (ADS)

    Liu, Shaoli; Jin, Peng; Liu, Jianhua; Wang, Xiao; Sun, Peng

    2017-01-01

    Tubes are used widely in aerospace vehicles, and their accurate assembly can directly affect the assembling reliability and the quality of products. It is important to measure the processed tube's endpoints and then fix any geometric errors correspondingly. However, the traditional tube inspection method is time-consuming and complex operations. Therefore, a new measurement method for a tube's endpoints based on machine vision is proposed. First, reflected light on tube's surface can be removed by using photometric linearization. Then, based on the optimization model for the tube's endpoint measurements and the principle of stereo matching, the global coordinates and the relative distance of the tube's endpoint are obtained. To confirm the feasibility, 11 tubes are processed to remove the reflected light and then the endpoint's positions of tubes are measured. The experiment results show that the measurement repeatability accuracy is 0.167 mm, and the absolute accuracy is 0.328 mm. The measurement takes less than 1 min. The proposed method based on machine vision can measure the tube's endpoints without any surface treatment or any tools and can realize on line measurement.

  19. How accurate are leukocyte indices and C-reactive protein for diagnosis of neonatal sepsis?

    PubMed Central

    da Silva, Orlando; Ohlsson, Arne

    1998-01-01

    Early diagnosis of neonatal sepsis is often difficult to make. Treatment on the basis of clinical suspicion and risk factors may result in overtreatment. A previous review of the usefulness of C-reactive protein and leukocyte indices concluded that these test results should be interpreted with caution. The present paper reviews and, when appropriate, revises, in light of new information, the conclusions reached in the previous systematic review of the topic. PMID:20401235

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. D-dimer testing and acute venous thromboembolism. A shortcut to accurate diagnosis?

    PubMed

    Becker, D M; Philbrick, J T; Bachhuber, T L; Humphries, J E

    1996-05-13

    D-dimer fragments can be measured easily in plasma and whole blood, and the presence or absence of D-dimer could be useful in the diagnostic evaluation of venous thromboembolism. We systematically reviewed the English literature for articles that compared D-dimer results with those of other tests for deep venous thrombosis or pulmonary embolism. Twenty-nine studies were selected for detailed review, and we noted wide variability in assay performance, heterogeneity among subjects, and failure to define absence or presence of venous thromboembolism by a comprehensive criterion standard for diagnosis. These methodologic problems limit the generalizability of the published estimates of D-dimer accuracy for deep venous thrombosis or pulmonary embolism, and the clinical utility of this potentially important test remains unproved.

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. Comparison of PCR, culturing and Pap smear microscopy for accurate diagnosis of genital Actinomyces.

    PubMed

    Kaya, Dilek; Demirezen, Şayeste; Hasçelik, Gülşen; Gülmez Kivanç, Dolunay; Beksaç, Mehmet Sinan

    2013-05-01

    Members of the genus Actinomyces, Gram-positive, non-spore-forming anaerobic bacteria, are normal inhabitants of the mucosal surfaces of the oral, gastrointestinal and genital tracts. Identification of these bacteria using conventional methods is generally difficult because of their complex transport and growth requirements and their fastidious and slow-growing nature. However, in recent years, the advancement of molecular techniques has provided much improved identification and differentiation of closely related Actinomyces species. The aim of the present study was to evaluate the efficacy of the PCR technique in the diagnosis of genital Actinomyces in comparison with culturing and Papanicolaou (Pap) smear microscopy. Multiple sampling was conducted from 200 women using smear microscopy, culturing and PCR. Cyto-brushes were smeared on glass slides and stained using the routine Pap technique. Culturing was performed from a sterile swab, and Actinomyces were determined using the BBL Crystal ANR ID kit. PCR was performed from a second swab, and the Actinomyces type was determined using type-specific primers designed in our laboratory. Only one vaginal fluid sample (0.5%) revealed Actinomyces-like organisms on Pap smear examination. Actinomyces were detected in nine samples (4.5%) using the BBL Crystal ANR ID kit. Using PCR, eight samples (4%) were found positive for Actinomyces. No specimens that gave positive results by Pap smear microscopy and culturing could be confirmed by PCR. Pap smear microscopy and culturing were both found to have zero sensitivity for Actinomyces. PCR appears to be a sensitive and reliable diagnostic method for the detection of Actinomyces, which are difficult to cultivate from genital samples. PCR can be used for diagnostic confirmation in cases diagnosed by conventional methods, to prevent false-positive results.

  10. The International Classification of Headache Disorders: accurate diagnosis of orofacial pain?

    PubMed

    Benoliel, R; Birman, N; Eliav, E; Sharav, Y

    2008-07-01

    The aim was to apply diagnostic criteria, as published by the International Headache Society (IHS), to the diagnosis of orofacial pain. A total of 328 consecutive patients with orofacial pain were collected over a period of 2 years. The orofacial pain clinic routinely employs criteria published by the IHS, the American Academy of Orofacial Pain (AAOP) and the Research Diagnostic Criteria for Temporomandibular Disorders (RDCTMD). Employing IHS criteria, 184 patients were successfully diagnosed (56%), including 34 with persistent idiopathic facial pain. In the remaining 144 we applied AAOP/RDCTMD criteria and diagnosed 120 as masticatory myofascial pain (MMP) resulting in a diagnostic efficiency of 92.7% (304/328) when applying the three classifications (IHS, AAOP, RDCTMD). Employing further published criteria, 23 patients were diagnosed as neurovascular orofacial pain (NVOP, facial migraine) and one as a neuropathy secondary to connective tissue disease. All the patients were therefore allocated to predefined diagnoses. MMP is clearly defined by AAOP and the RDCTMD. However, NVOP is not defined by any of the above classification systems. The features of MMP and NVOP are presented and analysed with calculations for positive (PPV) and negative predictive values (NPV). In MMP the combination of facial pain aggravated by jaw movement, and the presence of three or more tender muscles resulted in a PPV = 0.82 and a NPV = 0.86. For NVOP the combination of facial pain, throbbing quality, autonomic and/or systemic features and attack duration of > 60 min gave a PPV = 0.71 and a NPV = 0.95. Expansion of the IHS system is needed so as to integrate more orofacial pain syndromes.

  11. 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.

  12. 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.

  13. 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.

  14. Collagen, type XI, alpha 1: an accurate marker for differential diagnosis of breast carcinoma invasiveness in core needle biopsies.

    PubMed

    Freire, Javier; Domínguez-Hormaetxe, Saioa; Pereda, Saray; De Juan, Ana; Vega, Alfonso; Simón, Laureano; Gómez-Román, Javier

    2014-12-01

    Accurate diagnosis of invasive breast lesions, when analyzed by Core Needle Biopsy, may suppose a major challenge for the pathologist. Various markers of invasiveness such as laminin, S-100 protein, P63 or calponin have been described; however, none of them is completely reliable. The use of a specific marker of the infiltrating tumor microenvironment seems vital to support the diagnosis of invasive against in situ lesions. At this point, Collagen, type XI, alpha 1 (COL11A1), might be helpful since it has been described to be associated to cancer associated fibroblasts in other tumors such as lung, pancreas or colorectal. This paper aims to analyze the role of COL11A1 as a marker of invasiveness in breast tumor lesions. Two hundred and one breast Core Needle Biopsy samples were analyzed by immunohistochemistry against pro-COL11A1. The results show a significant difference (p < 0.0001) when comparing the expression in infiltrative tumors (93%) versus immunostaining of non-invasive lesions (4%). Forty cases of underestimated DCIS were also stained for COL11A1, presenting a sensitivity of 90% when compared with p63 and calponin which not tagged invasion. In conclusion, pro-COL11A1 expression is a promising marker of invasive breast lesions, and may be included in immunohistochemical panels aiming at identifying infiltration in problematic breast lesions.

  15. Lateral Flow Rapid Test for Accurate and Early Diagnosis of Scrub Typhus: A Febrile Illness of Historically Military Importance in the Pacific Rim.

    PubMed

    Chao, Chien-Chung; Zhangm, Zhiwen; Weissenberger, Giulia; Chen, Hua-Wei; Ching, Wei-Mei

    2017-03-01

    Scrub typhus (ST) is an infection caused by Orientia tsutsugamushi. Historically, ST was ranked as the second most important arthropod-borne medical problem only behind malaria during World War II and the Vietnam War. The disease occurs mainly in Southeast Asia and has been shown to emerge and reemerge in new areas, implying the increased risk for U.S. military and civilian personnel deployed to these regions. ST can effectively be treated by doxycycline provided the diagnosis is made early, before the development of severe complications. Scrub Typhus Detect is a lateral flow rapid test based on a mixture of recombinant 56-kDa antigens with broad reactivity. The performance of this prototype product was evaluated against indirect immunofluorescence assay, the serological gold standard. Using 249 prospectively collected samples from Thailand, the sensitivity and specificity for IgM was found to be 100% and 92%, respectively, suggesting a high potential of this product for clinical use. This product will provide a user friendly, rapid, and accurate diagnosis of ST for clinicians to provide timely and accurate treatments of deployed personnel.

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. Sialendoscopy-based diagnosis and treatment of salivary ductal obstructions.

    PubMed

    Liao, Gui Qing; Su, Yu Xiong; Zheng, Guang Sen; Liang, Li Zhong

    2010-01-01

    Salivary gland ductal obstruction is traditionally treated by sialoadenectomy when conservative measures fail. During the last decade, sialendoscopy has become the preferred approach in the management of salivary ductal obstructions. Sialendoscopy can provide direct, accurate and reliable visualisation of the salivary duct lumen and ductal pathologies, and can eliminate pathologies with miniaturised instrumentation. Now, sialendoscopic surgery is a promising option for patients who can be offered a satisfactory clinical outcome while avoiding sialoadenectomy. The present article briefly outlines sialendoscopy-based diagnosis and treatment of salivary ductal obstructions.

  1. Hydrogen sulfide detection based on reflection: from a poison test approach of ancient China to single-cell accurate localization.

    PubMed

    Kong, Hao; Ma, Zhuoran; Wang, Song; Gong, Xiaoyun; Zhang, Sichun; Zhang, Xinrong

    2014-08-05

    With the inspiration of an ancient Chinese poison test approach, we report a rapid hydrogen sulfide detection strategy in specific areas of live cells using silver needles with good spatial resolution of 2 × 2 μm(2). Besides the accurate-localization ability, this reflection-based strategy also has attractive merits of convenience and robust response when free pretreatment and short detection time are concerned. The success of endogenous H2S level evaluation in cellular cytoplasm and nuclear of human A549 cells promises the application potential of our strategy in scientific research and medical diagnosis.

  2. 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.

  3. Cardiac troponins I and T: molecular markers for early diagnosis, prognosis, and accurate triaging of patients with acute myocardial infarction.

    PubMed

    Tiwari, Ram P; Jain, Anubhav; Khan, Zakir; Kohli, Veena; Bharmal, R N; Kartikeyan, S; Bisen, Prakash S

    2012-12-01

    Acute myocardial infarction (AMI) is the leading cause of death worldwide, with early diagnosis still being difficult. Promising new cardiac biomarkers such as troponins and creatine kinase (CK) isoforms are being studied and integrated into clinical practice for early diagnosis of AMI. The cardiac-specific troponins I and T (cTnI and cTnT) have good sensitivity and specificity as indicators of myocardial necrosis and are superior to CK and its MB isoenzyme (CK-MB) in this regard. Besides being potential biologic markers, cardiac troponins also provide significant prognostic information. The introduction of novel high-sensitivity troponin assays has enabled more sensitive and timely diagnosis or exclusion of acute coronary syndromes. This review summarizes the available information on the potential of troponins and other cardiac markers in early diagnosis and prognosis of AMI, and provides perspectives on future diagnostic approaches to AMI.

  4. 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.

  5. 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.

  6. How accurate are the wrist-based heart rate monitors during walking and running activities? Are they accurate enough?

    PubMed Central

    An, Hyun-Sung; Dinkel, Danae M; Noble, John M; Lee, Jung-Min

    2016-01-01

    Background Heart rate (HR) monitors are valuable devices for fitness-orientated individuals. There has been a vast influx of optical sensing blood flow monitors claiming to provide accurate HR during physical activities. These monitors are worn on the arm and wrist to detect HR with photoplethysmography (PPG) techniques. Little is known about the validity of these wearable activity trackers. Aim Validate the Scosche Rhythm (SR), Mio Alpha (MA), Fitbit Charge HR (FH), Basis Peak (BP), Microsoft Band (MB), and TomTom Runner Cardio (TT) wireless HR monitors. Methods 50 volunteers (males: n=32, age 19–43 years; females: n=18, age 19–38 years) participated. All monitors were worn simultaneously in a randomised configuration. The Polar RS400 HR chest strap was the criterion measure. A treadmill protocol of one 30 min bout of continuous walking and running at 3.2, 4.8, 6.4, 8.0, and 9.6 km/h (5 min at each protocol speed) with HR manually recorded every minute was completed. Results For group comparisons, the mean absolute percentage error values were: 3.3%, 3.6%, 4.0%, 4.6%, 4.8% and 6.2% for TT, BP, RH, MA, MB and FH, respectively. Pearson product-moment correlation coefficient (r) was observed: r=0.959 (TT), r=0.956 (MB), r=0.954 (BP), r=0.933 (FH), r=0.930 (RH) and r=0.929 (MA). Results from 95% equivalency testing showed monitors were found to be equivalent to those of the criterion HR (±10% equivalence zone: 98.15–119.96). Conclusions The results demonstrate that the wearable activity trackers provide an accurate measurement of HR during walking and running activities. PMID:27900173

  7. Summary Report on the Graded Prognostic Assessment: An Accurate and Facile Diagnosis-Specific Tool to Estimate Survival for Patients With Brain Metastases

    PubMed Central

    Sperduto, Paul W.; Kased, Norbert; Roberge, David; Xu, Zhiyuan; Shanley, Ryan; Luo, Xianghua; Sneed, Penny K.; Chao, Samuel T.; Weil, Robert J.; Suh, John; Bhatt, Amit; Jensen, Ashley W.; Brown, Paul D.; Shih, Helen A.; Kirkpatrick, John; Gaspar, Laurie E.; Fiveash, John B.; Chiang, Veronica; Knisely, Jonathan P.S.; Sperduto, Christina Maria; Lin, Nancy; Mehta, Minesh

    2012-01-01

    Purpose Our group has previously published the Graded Prognostic Assessment (GPA), a prognostic index for patients with brain metastases. Updates have been published with refinements to create diagnosis-specific Graded Prognostic Assessment indices. The purpose of this report is to present the updated diagnosis-specific GPA indices in a single, unified, user-friendly report to allow ease of access and use by treating physicians. Methods A multi-institutional retrospective (1985 to 2007) database of 3,940 patients with newly diagnosed brain metastases underwent univariate and multivariate analyses of prognostic factors associated with outcomes by primary site and treatment. Significant prognostic factors were used to define the diagnosis-specific GPA prognostic indices. A GPA of 4.0 correlates with the best prognosis, whereas a GPA of 0.0 corresponds with the worst prognosis. Results Significant prognostic factors varied by diagnosis. For lung cancer, prognostic factors were Karnofsky performance score, age, presence of extracranial metastases, and number of brain metastases, confirming the original Lung-GPA. For melanoma and renal cell cancer, prognostic factors were Karnofsky performance score and the number of brain metastases. For breast cancer, prognostic factors were tumor subtype, Karnofsky performance score, and age. For GI cancer, the only prognostic factor was the Karnofsky performance score. The median survival times by GPA score and diagnosis were determined. Conclusion Prognostic factors for patients with brain metastases vary by diagnosis, and for each diagnosis, a robust separation into different GPA scores was discerned, implying considerable heterogeneity in outcome, even within a single tumor type. In summary, these indices and related worksheet provide an accurate and facile diagnosis-specific tool to estimate survival, potentially select appropriate treatment, and stratify clinical trials for patients with brain metastases. PMID:22203767

  8. 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

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

    PubMed

    Parkash, Om; Shueb, Rafidah Hanim

    2015-10-19

    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.

  10. 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

  11. 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

  12. Wireless laptop-based phonocardiograph and diagnosis.

    PubMed

    Dao, Amy T

    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.

  13. 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.

  14. An Accurate Heading Solution using MEMS-based Gyroscope and Magnetometer Integrated System (Preliminary Results)

    NASA Astrophysics Data System (ADS)

    El-Diasty, M.

    2014-11-01

    An accurate heading solution is required for many applications and it can be achieved by high grade (high cost) gyroscopes (gyros) which may not be suitable for such applications. Micro-Electro Mechanical Systems-based (MEMS) is an emerging technology, which has the potential of providing heading solution using a low cost MEMS-based gyro. However, MEMS-gyro-based heading solution drifts significantly over time. The heading solution can also be estimated using MEMS-based magnetometer by measuring the horizontal components of the Earth magnetic field. The MEMS-magnetometer-based heading solution does not drift over time, but are contaminated by high level of noise and may be disturbed by the presence of magnetic field sources such as metal objects. This paper proposed an accurate heading estimation procedure based on the integration of MEMS-based gyro and magnetometer measurements that correct gyro and magnetometer measurements where gyro angular rates of changes are estimated using magnetometer measurements and then integrated with the measured gyro angular rates of changes with a robust filter to estimate the heading. The proposed integration solution is implemented using two data sets; one was conducted in static mode without magnetic disturbances and the second was conducted in kinematic mode with magnetic disturbances. The results showed that the proposed integrated heading solution provides accurate, smoothed and undisturbed solution when compared with magnetometerbased and gyro-based heading solutions.

  15. Robust high-resolution cloth using parallelism, history-based collisions, and accurate friction.

    PubMed

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

    2009-01-01

    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.

  16. Accurate lithography hotspot detection based on PCA-SVM classifier with hierarchical data clustering

    NASA Astrophysics Data System (ADS)

    Gao, Jhih-Rong; Yu, Bei; Pan, David Z.

    2014-03-01

    As technology nodes continues shrinking, layout patterns become more sensitive to lithography processes, resulting in lithography hotspots that need to be identified and eliminated during physical verification. In this paper, we propose an accurate hotspot detection approach based on PCA (principle component analysis)-SVM (sup- port vector machine) classifier. Several techniques, including hierarchical data clustering, data balancing, and multi-level training, are provided to enhance performance of the proposed approach. Our approach is accurate and more efficient than conventional time-consuming lithography simulation; in the meanwhile, provides high flexibility to adapt to new lithography processes and rules.

  17. 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.

  18. 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

  19. 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

    2013-09-04

    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.

  20. Teaching Evidence-Based Physical Diagnosis: Six Bedside Lessons.

    PubMed

    McGee, Steven

    2016-12-01

    Evidence-based physical diagnosis is an essential part of the bedside curriculum. By using the likelihood ratio, a simple measure of diagnostic accuracy, teachers can quickly adapt this approach to their bedside teaching. Six recurring themes in evidence-based physical diagnosis are fully reviewed, with examples, in this article.

  1. A fluorescence-based quantitative real-time PCR assay for accurate Pocillopora damicornis species identification

    NASA Astrophysics Data System (ADS)

    Thomas, Luke; Stat, Michael; Evans, Richard D.; Kennington, W. Jason

    2016-09-01

    Pocillopora damicornis is one of the most extensively studied coral species globally, but high levels of phenotypic plasticity within the genus make species identification based on morphology alone unreliable. As a result, there is a compelling need to develop cheap and time-effective molecular techniques capable of accurately distinguishing P. damicornis from other congeneric species. Here, we develop a fluorescence-based quantitative real-time PCR (qPCR) assay to genotype a single nucleotide polymorphism that accurately distinguishes P. damicornis from other morphologically similar Pocillopora species. We trial the assay across colonies representing multiple Pocillopora species and then apply the assay to screen samples of Pocillopora spp. collected at regional scales along the coastline of Western Australia. This assay offers a cheap and time-effective alternative to Sanger sequencing and has broad applications including studies on gene flow, dispersal, recruitment and physiological thresholds of P. damicornis.

  2. 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.

  3. 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.

  4. Accurate description of argon and water adsorption on surfaces of graphene-based carbon allotropes.

    PubMed

    Kysilka, Jiří; Rubeš, Miroslav; Grajciar, Lukáš; Nachtigall, Petr; Bludský, Ota

    2011-10-20

    Accurate interaction energies of nonpolar (argon) and polar (water) adsorbates with graphene-based carbon allotropes were calculated by means of a combined density functional theory (DFT)-ab initio computational scheme. The calculated interaction energy of argon with graphite (-9.7 kJ mol(-1)) is in excellent agreement with the available experimental data. The calculated interaction energy of water with graphene and graphite is -12.8 and -14.6 kJ mol(-1), respectively. The accuracy of combined DFT-ab initio methods is discussed in detail based on a comparison with the highly precise interaction energies of argon and water with coronene obtained at the coupled-cluster CCSD(T) level extrapolated to the complete basis set (CBS) limit. A new strategy for a reliable estimate of the CBS limit is proposed for systems where numerical instabilities occur owing to basis-set near-linear dependence. The most accurate estimate of the argon and water interaction with coronene (-8.1 and -14.0 kJ mol(-1), respectively) is compared with the results of other methods used for the accurate description of weak intermolecular interactions.

  5. Accurate compensation of the low-frequency components for the FFT-based turbulent phase screen.

    PubMed

    Xiang, Jingsong

    2012-01-02

    Standard FFT-based turbulent phase screen generation method has very large errors due to the undersampling of the low frequency components. Subharmonic methods are the main low frequency components compensating methods to improve the accuracy, but the residual errors are still large. In this paper I propose a new low frequency components compensating method, which is based on the correlation matrix phase screen generation methods. Using this method, the low frequency components can be compensated accurately, both of the accuracy and speed are superior to those of the subharmonic methods.

  6. Robust and accurate fundamental frequency estimation based on dominant harmonic components.

    PubMed

    Nakatani, Tomohiro; Irino, Toshio

    2004-12-01

    This paper presents a new method for robust and accurate fundamental frequency (F0) estimation in the presence of background noise and spectral distortion. Degree of dominance and dominance spectrum are defined based on instantaneous frequencies. The degree of dominance allows one to evaluate the magnitude of individual harmonic components of the speech signals relative to background noise while reducing the influence of spectral distortion. The fundamental frequency is more accurately estimated from reliable harmonic components which are easy to select given the dominance spectra. Experiments are performed using white and babble background noise with and without spectral distortion as produced by a SRAEN filter. The results show that the present method is better than previously reported methods in terms of both gross and fine F0 errors.

  7. 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

  8. 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

  9. Application of the fault diagnosis strategy based on hierarchical information fusion in motors fault diagnosis

    NASA Astrophysics Data System (ADS)

    Xia, Li; Fei, Qi

    2006-03-01

    This paper has analyzed merits and demerits of both neural network technique and of the information fusion methods based on the D-S (dempster-shafer evidence) Theory as well as their complementarity, proposed the hierarchical information fusion fault diagnosis strategy by combining the neural network technique and the fused decision diagnosis based on D-S Theory, and established a corresponding functional model. Thus, we can not only solve a series of problems caused by rapid growth in size and complexity of neural network structure with diagnosis parameters increasing, but also can provide effective method for basic probability assignment in D-S Theory. The application of the strategy to diagnosing faults of motor bearings has proved that this method is of fairly high accuracy and reliability in fault diagnosis.

  10. Theory-Based Diagnosis and Remediation of Writing Disabilities.

    ERIC Educational Resources Information Center

    Berninger, Virginia W.; And Others

    1991-01-01

    Briefly reviews recent trends in research on writing; introduces theory-based model being developed for differential diagnosis of writing disabilities at neuropsychological, linguistic, and cognitive levels; presents cases and patterns in cases that illustrate differential diagnosis of writing disabilities at linguistic level; and suggests…

  11. A failure diagnosis system based on a neural network classifier for the space shuttle main engine

    NASA Technical Reports Server (NTRS)

    Duyar, Ahmet; Merrill, Walter

    1990-01-01

    A conceptual design of a model based failure detection and diagnosis system is developed for the space shuttle main engine. This design relies on the accurate and reliable identification of the parameters of the highly nonlinear and very complex engine. The design approach is presented in some detail and results for a failed valve are presented. These preliminary results verify that the developed parameter identification technique together with a neural network classifier can be used for this purpose.

  12. 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

  13. Extending model-based diagnosis for analog thermodynamical devices

    NASA Technical Reports Server (NTRS)

    Rouquette, Nicolas; Chien, Steve; Robertson, Charles

    1993-01-01

    The increasing complexity of process control applications have posed difficult problems in fault detection, isolation, and recovery. Deep knowledge-based approaches, such as model-based diagnosis, have offered some promise in addressing these problems. However, the difficulties of adapting these techniques to situations involving numerical reasoning and noise have limited the applicability of these techniques. This paper describes an extension of classical model-based diagnosis techniques to deal with sparse data, noise, and complex noninvertible numerical models. These diagnosis techniques are being applied to the External Active Thermal Control System for Space Station Freedom.

  14. 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).

  15. [RDBH-method and big DyeTM terminator technology in accurate diagnosis of β-thalassemia and the allelic polymorphism of β-globin cluster].

    PubMed

    Akperova, G A

    2014-11-01

    IThe purpose of this study was to evaluate of the efficiency of RDBH-method and Big DyeTM Terminator technology in an accurate diagnosis of β-thalassemia and the allelic polymorphism of β-globin cluster. It was done a complete hematology analysis (HB, MCH, MCV, MCHC, RBC, Hct, HbA2, HbF, Serum iron, Serum ferritin at four children (males, 6-10 years old) and their parents. Molecular analysis included Reverse Dot-Blot Hybridization StripAssay (RDBH) and DNA sequencing on ABI PRISM Big DyeTM Terminator. Hematologic and molecular parameters were contradictory. The homozygosity for β0-thalassemia (β0IVS2.1[G>A] and β0codon 8[-AA]) at three boys with the mild clinical manifestation and heterozygosity of their parents for mutations, and the absence of β-globin mutations at parents and a boy who holds monthly transfusion was established by RDBH-analysis. DNA sequencing by technology Big DyeTM Terminator showed polymorphism at positions -551 and -521 of Cap5'-region (-650-250) - (AT)7(T)7 and (AT)8(T)5. Application of the integrated clinical-molecular approach is an ideal method for an accurate diagnosis, identification of asymptomatic carriers and a reduce of the risk of complications from β-thalassemia, moreover screening of γG-gene and the level of fetal hemoglobin in early childhood will help manage of β-thalassemia clinic and prevent heavy consequences of the disease.

  16. Accurate Quantitative Sensing of Intracellular pH based on Self-ratiometric Upconversion Luminescent Nanoprobe

    NASA Astrophysics Data System (ADS)

    Li, Cuixia; Zuo, Jing; Zhang, Li; Chang, Yulei; Zhang, Youlin; Tu, Langping; Liu, Xiaomin; Xue, Bin; Li, Qiqing; Zhao, Huiying; Zhang, Hong; Kong, Xianggui

    2016-12-01

    Accurate quantitation of intracellular pH (pHi) is of great importance in revealing the cellular activities and early warning of diseases. A series of fluorescence-based nano-bioprobes composed of different nanoparticles or/and dye pairs have already been developed for pHi sensing. Till now, biological auto-fluorescence background upon UV-Vis excitation and severe photo-bleaching of dyes are the two main factors impeding the accurate quantitative detection of pHi. Herein, we have developed a self-ratiometric luminescence nanoprobe based on förster resonant energy transfer (FRET) for probing pHi, in which pH-sensitive fluorescein isothiocyanate (FITC) and upconversion nanoparticles (UCNPs) were served as energy acceptor and donor, respectively. Under 980 nm excitation, upconversion emission bands at 475 nm and 645 nm of NaYF4:Yb3+, Tm3+ UCNPs were used as pHi response and self-ratiometric reference signal, respectively. This direct quantitative sensing approach has circumvented the traditional software-based subsequent processing of images which may lead to relatively large uncertainty of the results. Due to efficient FRET and fluorescence background free, a highly-sensitive and accurate sensing has been achieved, featured by 3.56 per unit change in pHi value 3.0–7.0 with deviation less than 0.43. This approach shall facilitate the researches in pHi related areas and development of the intracellular drug delivery systems.

  17. Accurate Quantitative Sensing of Intracellular pH based on Self-ratiometric Upconversion Luminescent Nanoprobe

    PubMed Central

    Li, Cuixia; Zuo, Jing; Zhang, Li; Chang, Yulei; Zhang, Youlin; Tu, Langping; Liu, Xiaomin; Xue, Bin; Li, Qiqing; Zhao, Huiying; Zhang, Hong; Kong, Xianggui

    2016-01-01

    Accurate quantitation of intracellular pH (pHi) is of great importance in revealing the cellular activities and early warning of diseases. A series of fluorescence-based nano-bioprobes composed of different nanoparticles or/and dye pairs have already been developed for pHi sensing. Till now, biological auto-fluorescence background upon UV-Vis excitation and severe photo-bleaching of dyes are the two main factors impeding the accurate quantitative detection of pHi. Herein, we have developed a self-ratiometric luminescence nanoprobe based on förster resonant energy transfer (FRET) for probing pHi, in which pH-sensitive fluorescein isothiocyanate (FITC) and upconversion nanoparticles (UCNPs) were served as energy acceptor and donor, respectively. Under 980 nm excitation, upconversion emission bands at 475 nm and 645 nm of NaYF4:Yb3+, Tm3+ UCNPs were used as pHi response and self-ratiometric reference signal, respectively. This direct quantitative sensing approach has circumvented the traditional software-based subsequent processing of images which may lead to relatively large uncertainty of the results. Due to efficient FRET and fluorescence background free, a highly-sensitive and accurate sensing has been achieved, featured by 3.56 per unit change in pHi value 3.0–7.0 with deviation less than 0.43. This approach shall facilitate the researches in pHi related areas and development of the intracellular drug delivery systems. PMID:27934889

  18. 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.

  19. Application of PCR-based methods for diagnosis of intestinal parasitic infections in the clinical laboratory.

    PubMed

    Verweij, Jaco J

    2014-12-01

    For many years PCR- and other DNA-based methods of pathogen detection have been available in most clinical microbiology laboratories; however, until recently these tools were not routinely exploited for the diagnosis of parasitic infections. Laboratories were initially reluctant to implement PCR as incorporation of such assays within the algorithm of tools available for the most accurate diagnosis of a large variety of parasites was unclear. With regard to diagnosis of intestinal parasitic infections, the diversity of parasites that one can expect in most settings is far less than the parasitological textbooks would have you believe, hence developing a simplified diagnostic triage is feasible. Therefore the classical algorithm based on population, patient groups, use of immuno-suppressive drugs, travel history etc. is also applicable to decide when to perform and which additional techniques are to be used, if a multiplex PCR panel is used as a first-line screening diagnostic.

  20. Fast and accurate computation of system matrix for area integral model-based algebraic reconstruction technique

    NASA Astrophysics Data System (ADS)

    Zhang, Shunli; Zhang, Dinghua; Gong, Hao; Ghasemalizadeh, Omid; Wang, Ge; Cao, Guohua

    2014-11-01

    Iterative algorithms, such as the algebraic reconstruction technique (ART), are popular for image reconstruction. For iterative reconstruction, the area integral model (AIM) is more accurate for better reconstruction quality than the line integral model (LIM). However, the computation of the system matrix for AIM is more complex and time-consuming than that for LIM. Here, we propose a fast and accurate method to compute the system matrix for AIM. First, we calculate the intersection of each boundary line of a narrow fan-beam with pixels in a recursive and efficient manner. Then, by grouping the beam-pixel intersection area into six types according to the slopes of the two boundary lines, we analytically compute the intersection area of the narrow fan-beam with the pixels in a simple algebraic fashion. Overall, experimental results show that our method is about three times faster than the Siddon algorithm and about two times faster than the distance-driven model (DDM) in computation of the system matrix. The reconstruction speed of our AIM-based ART is also faster than the LIM-based ART that uses the Siddon algorithm and DDM-based ART, for one iteration. The fast reconstruction speed of our method was accomplished without compromising the image quality.

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

    PubMed

    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/.

  2. Identification of Bile Duct Paucity in Alagille Syndrome: Using CK7 and EMA Immunohistochemistry as a Reliable Panel for Accurate Diagnosis.

    PubMed

    Herman, Haley K; Abramowsky, Carlos R; Caltharp, Shelley; Metry, Diana; Cundiff, Caitlin A; Romero, Rene; Gillespie, Scott E; Shehata, Bahig M

    2016-01-01

    Bile duct paucity is the absence or marked reduction in the number of interlobular bile ducts (ILBD) within portal tracts. Its syndromic variant, Alagille syndrome (ALGS), is a multisystem disorder with effects on the liver, cardiovascular system, skeleton, face, and eyes. It is inherited as an autosomal dominant trait due to defects in NOTCH signaling pathway. ALGS is characterized by vanishing ILBD with subsequent chronic obstructive cholestasis in approximately 89% of cases. Cholestasis stimulates formation of new bile ductules through a process of neoductular reaction, making it difficult to evaluate the presence or absence of ILBD. Therefore, finding a method to differentiate clearly between ILBD and the ductular proliferation is essential for accurate diagnosis. A database search identified 28 patients with confirmed diagnosis of ALGS between 1992 and 2014. Additionally, 7 controls were used. A panel of two immunostains, cytokeratin 7 (CK7) and epithelial membrane antigen (EMA), was performed. CK7 highlighted the bile duct epithelium of ILBD and ductular proliferation, while EMA stained only the brush border of ILBD. In our ALGS group, the ratio of EMA-positive ILBD to identified portal tracts was 12.6% (range, 0%-41%). However, this same ratio was 95.0% (range, 90%-100%) among control cases (P < 0.001). We propose a panel of two immunostains, CK7 and EMA, to differentiate ILBD from ductular proliferation in patients with cholestasis. With this panel, identification of bile duct paucity can be achieved. Additional studies, including molecular confirmation and clinical correlation, would provide a definitive diagnosis of ALGS.

  3. 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

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

    NASA Astrophysics Data System (ADS)

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

    2014-04-01

    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.

  5. 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.

  6. 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.

  7. 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

  8. A highly accurate wireless digital sun sensor based on profile detecting and detector multiplexing technologies

    NASA Astrophysics Data System (ADS)

    Wei, Minsong; Xing, Fei; You, Zheng

    2017-01-01

    The advancing growth of micro- and nano-satellites requires miniaturized sun sensors which could be conveniently applied in the attitude determination subsystem. In this work, a profile detecting technology based high accurate wireless digital sun sensor was proposed, which could transform a two-dimensional image into two-linear profile output so that it can realize a high update rate under a very low power consumption. A multiple spots recovery approach with an asymmetric mask pattern design principle was introduced to fit the multiplexing image detector method for accuracy improvement of the sun sensor within a large Field of View (FOV). A FOV determination principle based on the concept of FOV region was also proposed to facilitate both sub-FOV analysis and the whole FOV determination. A RF MCU, together with solar cells, was utilized to achieve the wireless and self-powered functionality. The prototype of the sun sensor is approximately 10 times lower in size and weight compared with the conventional digital sun sensor (DSS). Test results indicated that the accuracy of the prototype was 0.01° within a cone FOV of 100°. Such an autonomous DSS could be equipped flexibly on a micro- or nano-satellite, especially for highly accurate remote sensing applications.

  9. 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.

  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. 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.

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

    PubMed

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

    2012-12-04

    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.

  13. 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.

  14. Accurate mask-based spatially regularized correlation filter for visual tracking

    NASA Astrophysics Data System (ADS)

    Gu, Xiaodong; Xu, Xinping

    2017-01-01

    Recently, discriminative correlation filter (DCF)-based trackers have achieved extremely successful results in many competitions and benchmarks. These methods utilize a periodic assumption of the training samples to efficiently learn a classifier. However, this assumption will produce unwanted boundary effects, which severely degrade the tracking performance. Correlation filters with limited boundaries and spatially regularized DCFs were proposed to reduce boundary effects. However, their methods used the fixed mask or predesigned weights function, respectively, which was unsuitable for large appearance variation. We propose an accurate mask-based spatially regularized correlation filter for visual tracking. Our augmented objective can reduce the boundary effect even in large appearance variation. In our algorithm, the masking matrix is converted into the regularized function that acts on the correlation filter in frequency domain, which makes the algorithm fast convergence. Our online tracking algorithm performs favorably against state-of-the-art trackers on OTB-2015 Benchmark in terms of efficiency, accuracy, and robustness.

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

    PubMed Central

    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

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

    PubMed

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

    2016-08-18

    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.

  17. Directed Sample Interrogation Utilizing an Accurate Mass Exclusion-Based Data-Dependent Acquisition Strategy (AMEx)

    PubMed Central

    Rudomin, Emily L.; Carr, Steven A.; Jaffe, Jacob D.

    2009-01-01

    The ability to perform thorough sampling is of critical importance when using mass spectrometry to characterize complex proteomic mixtures. A common approach is to re-interrogate a sample multiple times by LC-MS/MS. However, the conventional data-dependent acquisition methods that are typically used in proteomics studies will often redundantly sample high-intensity precursor ions while failing to sample low-intensity precursors entirely. We describe a method wherein the masses of successfully identified peptides are used to generate an accurate mass exclusion list such that those precursors are not selected for sequencing during subsequent analyses. We performed multiple concatenated analytical runs to sample a complex cell lysate, using either accurate mass exclusion-based data-dependent acquisition (AMEx) or standard data-dependent acquisition, and found that utilization of AMEx on an ESI-Orbitrap instrument significantly increases the total number of validated peptide identifications relative to a standard DDA approach. The additional identified peptides represent precursor ions that exhibit low signal intensity in the sample. Increasing the total number of peptide identifications augmented the number of proteins identified, as well as improved the sequence coverage of those proteins. Together, these data indicate that using AMEx is an effective strategy to improve the characterization of complex proteomic mixtures. PMID:19344186

  18. Directed sample interrogation utilizing an accurate mass exclusion-based data-dependent acquisition strategy (AMEx).

    PubMed

    Rudomin, Emily L; Carr, Steven A; Jaffe, Jacob D

    2009-06-01

    The ability to perform thorough sampling is of critical importance when using mass spectrometry to characterize complex proteomic mixtures. A common approach is to reinterrogate a sample multiple times by LC-MS/MS. However, the conventional data-dependent acquisition methods that are typically used in proteomics studies will often redundantly sample high-intensity precursor ions while failing to sample low-intensity precursors entirely. We describe a method wherein the masses of successfully identified peptides are used to generate an accurate mass exclusion list such that those precursors are not selected for sequencing during subsequent analyses. We performed multiple concatenated analytical runs to sample a complex cell lysate, using either accurate mass exclusion-based data-dependent acquisition (AMEx) or standard data-dependent acquisition, and found that utilization of AMEx on an ESI-Orbitrap instrument significantly increases the total number of validated peptide identifications relative to a standard DDA approach. The additional identified peptides represent precursor ions that exhibit low signal intensity in the sample. Increasing the total number of peptide identifications augmented the number of proteins identified, as well as improved the sequence coverage of those proteins. Together, these data indicate that using AMEx is an effective strategy to improve the characterization of complex proteomic mixtures.

  19. 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

  20. 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).

  1. 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.

  2. Accurate and efficient computation of nonlocal potentials based on Gaussian-sum approximation

    NASA Astrophysics Data System (ADS)

    Exl, Lukas; Mauser, Norbert J.; Zhang, Yong

    2016-12-01

    We introduce an accurate and efficient method for the numerical evaluation of nonlocal potentials, including the 3D/2D Coulomb, 2D Poisson and 3D dipole-dipole potentials. Our method is based on a Gaussian-sum approximation of the singular convolution kernel combined with a Taylor expansion of the density. Starting from the convolution formulation of the nonlocal potential, for smooth and fast decaying densities, we make a full use of the Fourier pseudospectral (plane wave) approximation of the density and a separable Gaussian-sum approximation of the kernel in an interval where the singularity (the origin) is excluded. The potential is separated into a regular integral and a near-field singular correction integral. The first is computed with the Fourier pseudospectral method, while the latter is well resolved utilizing a low-order Taylor expansion of the density. Both parts are accelerated by fast Fourier transforms (FFT). The method is accurate (14-16 digits), efficient (O (Nlog ⁡ N) complexity), low in storage, easily adaptable to other different kernels, applicable for anisotropic densities and highly parallelizable.

  3. 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.

  4. 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.

  5. Tracking false-negative results in molecular diagnosis: proposal of a triplex-PCR based method for leishmaniasis diagnosis

    PubMed Central

    2014-01-01

    Background Molecular biological methods have become increasingly relevant to the diagnosis and control of infectious diseases, such as leishmaniasis. Since various factors may affect the sensitivity of PCR assays, including DNA yield and purity, an optimal extraction method is pivotal. Losses of a parasite’s DNA during extraction may significantly impair its detection by PCR and lead to false-negative results. This study proposes a triplex PCR assay targeting the parasite’s DNA, an external control (pUC18) and an internal control (G3PD) for accurate diagnosis of leishmaniasis. Results Two primer pairs were designed to detect the plasmid pUC18 and a triplex PCR assay targeting the Leishmania braziliensis kinetoplast DNA, the external control and the internal control was standardized. The triplex PCR assay was assessed for its ability to detect the three target DNA fragments simultaneously. PCR products from pUC18 DNA resulted in bands of 368 (P1) and 316 (P2) base pairs (bp). The triplex PCR optimized with the chosen external control system (P1) allowed the simultaneous detection of the internal control (G3PD – 567 bp) as well as of small quantities (10 pg) of the target parasite’s DNA, detected by amplification of a 138 bp product. Conclusions The new tool standardized herein enables a more reliable interpretation of PCR results, mainly by contributing to quality assurance of leishmaniasis diagnosis. Furthermore, after simple standardization steps, this protocol could be applied to the diagnosis of other infectious diseases in reference laboratories. This triplex PCR enables the assessment of small losses during the DNA extraction process, problems concerning DNA degradation (sample quality) and the detection of L. braziliensis kDNA. PMID:24808911

  6. Analog filter diagnosis using the oscillation based method

    NASA Astrophysics Data System (ADS)

    Andrejević Stošović, Miona; Milić, Miljana; Litovski, Vanćo

    2012-12-01

    Oscillation Based Testing (OBT) is an effective and simple solution to the testing problem of continuous time analogue electronic filters. In this paper, diagnosis based on OBT is described for the first time. It will be referred to as OBD. A fault dictionary is created and used to perform diagnosis with artificial neural networks (ANNs) implemented as classifiers. The robustness of the ANN diagnostic concept is also demonstrated by the addition of white noise to the “measured” signals. The implementation of the new concept is demonstrated by testing and diagnosis of a second order notch cell realized with one operational amplifier. Single soft and catastrophic faults are considered in detail and an example of the diagnosis of double soft faults is also given.

  7. Validity of a Claims-Based Diagnosis of Obesity Among Medicare Beneficiaries.

    PubMed

    Lloyd, Jennifer T; Blackwell, Steve A; Wei, Iris I; Howell, Benjamin L; Shrank, William H

    2015-12-01

    Population-level data on obesity are difficult to obtain. Claims-based data sets are useful for studying public health at a population level but lack physical measurements. The objective of this study was to determine the validity of a claims-based measure of obesity compared to obesity diagnosed with clinical data as well as the validity among older adults who suffer from chronic disease. This study used data from the National Health and Nutrition Examination Survey 1999-2004 for adults aged ≥ 65 successfully linked to 1999-2007 Medicare claims (N = 3,554). Sensitivity, specificity, positive and negative predictive values, κ statistics as well as logistic regression analyses were computed for the claims-based diagnosis of obesity versus obesity diagnosed with body mass index. The claims-based diagnosis of obesity underestimates the true prevalence in the older Medicare population with a low sensitivity (18.4%). However, this method has a high specificity (97.3%) and is accurate when it is present. Sensitivity was improved when comparing the claim-based diagnosis to Class II obesity (34.2%) and when used in combination with chronic conditions such as diabetes, congestive heart failure, chronic obstructive pulmonary disease, or depression. Understanding the validity of a claims-based obesity diagnosis could aid researchers in understanding the feasibility of conducting research on obesity using claims data.

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

    SciTech Connect

    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.

  9. A fast and accurate image-based measuring system for isotropic reflection materials

    NASA Astrophysics Data System (ADS)

    Kim, Duck Bong; Kim, Kang Yeon; Park, Kang Su; Seo, Myoung Kook; Lee, Kwan H.

    2008-08-01

    We present a novel image-based BRDF (Bidirectional Reflectance Distribution Function) measurement system for materials that have isotropic reflectance properties. Our proposed system is fast due to simple set up and automated operations. It also provides a wide angular coverage and noise reduction capability so that it achieves accuracy that is needed for computer graphics applications. We test the uniformity and constancy of the light source and the reciprocity of the measurement system. We perform a photometric calibration of HDR (High Dynamic Range) camera to recover an accurate radiance map from each HDR image. We verify our proposed system by comparing it with a previous imagebased BRDF measurement system. We demonstrate the efficiency and accuracy of our proposed system by generating photorealistic images of the measured BRDF data that include glossy blue, green plastics, gold coated metal and gold metallic paints.

  10. 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

  11. 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.

  12. PRIMAL: Fast and accurate pedigree-based imputation from sequence data in a founder population.

    PubMed

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

    2015-03-01

    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.

  13. High-accurate optical vector analysis based on optical single-sideband modulation

    NASA Astrophysics Data System (ADS)

    Xue, Min; Pan, Shilong

    2016-11-01

    Most of the efforts devoted to the area of optical communications were on the improvement of the optical spectral efficiency. Varies innovative optical devices are thus developed to finely manipulate the optical spectrum. Knowing the spectral responses of these devices, including the magnitude, phase and polarization responses, is of great importance for their fabrication and application. To achieve high-resolution characterization, optical vector analyzers (OVAs) based on optical single-sideband (OSSB) modulation have been proposed and developed. Benefiting from the mature and highresolution microwave technologies, the OSSB-based OVA can potentially achieve a resolution of sub-Hz. However, the accuracy is restricted by the measurement errors induced by the unwanted first-order sideband and the high-order sidebands in the OSSB signal, since electrical-to-optical conversion and optical-to-electrical conversion are essentially required to achieve high-resolution frequency sweeping and extract the magnitude and phase information in the electrical domain. Recently, great efforts have been devoted to improve the accuracy of the OSSB-based OVA. In this paper, the influence of the unwanted-sideband induced measurement errors and techniques for implementing high-accurate OSSB-based OVAs are discussed.

  14. Highly accurate moving object detection in variable bit rate video-based traffic monitoring systems.

    PubMed

    Huang, Shih-Chia; Chen, Bo-Hao

    2013-12-01

    Automated motion detection, which segments moving objects from video streams, is the key technology of intelligent transportation systems for traffic management. Traffic surveillance systems use video communication over real-world networks with limited bandwidth, which frequently suffers because of either network congestion or unstable bandwidth. Evidence supporting these problems abounds in publications about wireless video communication. Thus, to effectively perform the arduous task of motion detection over a network with unstable bandwidth, a process by which bit-rate is allocated to match the available network bandwidth is necessitated. This process is accomplished by the rate control scheme. This paper presents a new motion detection approach that is based on the cerebellar-model-articulation-controller (CMAC) through artificial neural networks to completely and accurately detect moving objects in both high and low bit-rate video streams. The proposed approach is consisted of a probabilistic background generation (PBG) module and a moving object detection (MOD) module. To ensure that the properties of variable bit-rate video streams are accommodated, the proposed PBG module effectively produces a probabilistic background model through an unsupervised learning process over variable bit-rate video streams. Next, the MOD module, which is based on the CMAC network, completely and accurately detects moving objects in both low and high bit-rate video streams by implementing two procedures: 1) a block selection procedure and 2) an object detection procedure. The detection results show that our proposed approach is capable of performing with higher efficacy when compared with the results produced by other state-of-the-art approaches in variable bit-rate video streams over real-world limited bandwidth networks. Both qualitative and quantitative evaluations support this claim; for instance, the proposed approach achieves Similarity and F1 accuracy rates that are 76

  15. Accurate determination of screw position in treating fifth metatarsal base fractures to shorten radiation exposure time

    PubMed Central

    Wang, Xu; Zhang, Chao; Wang, Chen; Huang, Jia Zhang; Ma, Xin

    2016-01-01

    INTRODUCTION Anatomical markers can help to guide lag screw placement during surgery for internal fixation of fifth metatarsal base fractures. This study aimed to identify the optimal anatomical markers and thus reduce radiation exposure. METHODS A total of 50 patients in Huashan Hospital, Shanghai, China, who underwent oblique foot radiography in the lateral position were randomly selected. The angles between the fifth metatarsal axis and cuboid articular surface were measured to determine the optimal lag screw placement relative to anatomical markers. RESULTS The line connecting the styloid process of the fifth metatarsal base with the second metatarsophalangeal (MTP) joint intersected with the fifth metatarsal base fracture line at an angle of 86.85° ± 5.44°. The line connecting the fifth metatarsal base styloid with the third and fourth MTP joints intersected with the fracture line at angles of 93.28° ± 5.24° and 100.95° ± 5.00°, respectively. The proximal articular surface of the fifth metatarsal base intersected with the line connecting the styloid process of the fifth metatarsal base with the second, third and fourth MTP joints at angles of 24.02° ± 4.77°, 30.79° ± 4.53° and 38.08° ± 4.54°, respectively. CONCLUSION The fifth metatarsal base styloid and third MTP joint can be used as anatomical markers for lag screw placement in fractures involving the fifth tarsometatarsal joint. The connection line, which is normally perpendicular to the fracture line, provides sufficient mechanical stability to facilitate accurate screw placement. The use of these anatomical markers could help to reduce unnecessary radiation exposure for patients and medical staff. PMID:26767892

  16. Robust and Accurate Vision-Based Pose Estimation Algorithm Based on Four Coplanar Feature Points

    PubMed Central

    Zhang, Zimiao; Zhang, Shihai; Li, Qiu

    2016-01-01

    Vision-based pose estimation is an important application of machine vision. Currently, analytical and iterative methods are used to solve the object pose. The analytical solutions generally take less computation time. However, the analytical solutions are extremely susceptible to noise. The iterative solutions minimize the distance error between feature points based on 2D image pixel coordinates. However, the non-linear optimization needs a good initial estimate of the true solution, otherwise they are more time consuming than analytical solutions. Moreover, the image processing error grows rapidly with measurement range increase. This leads to pose estimation errors. All the reasons mentioned above will cause accuracy to decrease. To solve this problem, a novel pose estimation method based on four coplanar points is proposed. Firstly, the coordinates of feature points are determined according to the linear constraints formed by the four points. The initial coordinates of feature points acquired through the linear method are then optimized through an iterative method. Finally, the coordinate system of object motion is established and a method is introduced to solve the object pose. The growing image processing error causes pose estimation errors the measurement range increases. Through the coordinate system, the pose estimation errors could be decreased. The proposed method is compared with two other existing methods through experiments. Experimental results demonstrate that the proposed method works efficiently and stably. PMID:27999338

  17. Arrhythmias in athletes: evidence-based strategies and challenges for diagnosis, management, and sports eligibility.

    PubMed

    Fragakis, Nikolaos; Pagourelias, Efstathios D; Koskinas, Konstantinos C; Vassilikos, Vassilios

    2013-01-01

    Assessment and management of cardiac rhythm disorders in athletes is particularly challenging. An accurate diagnosis and optimal risk-stratification are often limited because of substantial phenotypic overlap between pathological entities and adaptive cardiovascular responses that normally occur in athletes. An accurate diagnosis, however, is particularly important in this population, as 2 competing risks need to be cautiously balanced: the risk of under-diagnosis of an arrhythmogenic substrate that may trigger life-threatening events versus the risk of over-diagnosis that may result in an athlete's improper disqualification. Accordingly, the management of arrhythmias in athletes may pose therapeutic dilemmas, and often differs substantially compared with the general population. In this review, we present the most frequently observed arrhythmias in athletes and briefly discuss their pathophysiologic substrate. We further propose diagnostic and therapeutic strategies based upon current guidelines, official recommendations, and emerging evidence from relevant clinical investigations. We focus particularly on disparities in current guidelines regarding the management of certain rhythm disorders, as these areas of uncertainty may reflect the challenging nature of these disorders and may indicate the need for individualized approaches in every-day clinical practice. A better understanding of the normal electrophysiological responses to chronic exercise, and of the pathophysiological basis and the true clinical significance of arrhythmias in athletes, may enhance decision-making, and may allow for management strategies which more prudently weigh the risk-to-benefit ratio of each approach.

  18. Two Stage Helical Gearbox Fault Detection and Diagnosis based on Continuous Wavelet Transformation of Time Synchronous Averaged Vibration Signals

    NASA Astrophysics Data System (ADS)

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

    2012-05-01

    Vibration signals from a gearbox are usually very noisy which makes it difficult to find reliable symptoms of a fault in a multistage gearbox. This paper explores the use of time synchronous average (TSA) to suppress the noise and Continue Wavelet Transformation (CWT) to enhance the non-stationary nature of fault signal for more accurate fault diagnosis. The results obtained in diagnosis an incipient gear breakage show that fault diagnosis results can be improved by using an appropriate wavelet. Moreover, a new scheme based on the level of wavelet coefficient amplitudes of baseline data alone, without faulty data samples, is suggested to select an optimal wavelet.

  19. Life-Cycle-Management of CV Cables based on Degradation Diagnosis

    NASA Astrophysics Data System (ADS)

    Kato, Takeyoshi; Niwa, Mamoru; Suzuoki, Yasuo

    Life-cycle management combined with degradation diagnosis is useful for preventing an unexpected failure and extending service life of electric power apparatuses, minimizing life-cycle cost. We examined a method of life-cycle management based on TBM (Time-Based Maintenance) and CBM (Condition Based Maintenance), and evaluated the economic effect of degradation diagnosis. To carry out reliable life cycle management, however, accurate data on the relation between extent of degradation and failure probability or remaining life as well as a well-established diagnostic method are necessary. In this paper, we examine the influence of accuracy of the data used to determine the optimum diagnostic parameters and evaluate how the life-cycle cost is affected by the employment of inaccurate data. As more condition-oriented life-cycle management, we discuss the effects of a method of life-cycle management based on two diagnosis intervals in terms of reliable life-cycle management. We also discuss the measurement sensitivity necessary for an effective asset management based on diagnosis.

  20. An Optimized Fluorescence-Based Bidimensional Immunoproteomic Approach for Accurate Screening of Autoantibodies

    PubMed Central

    Launay, David; Sobanski, Vincent; Dussart, Patricia; Chafey, Philippe; Broussard, Cédric; Duban-Deweer, Sophie; Vermersch, Patrick; Prin, Lionel; Lefranc, Didier

    2015-01-01

    Serological proteome analysis (SERPA) combines classical proteomic technology with effective separation of cellular protein extracts on two-dimensional gel electrophoresis, western blotting, and identification of the antigenic spot of interest by mass spectrometry. A critical point is related to the antigenic target characterization by mass spectrometry, which depends on the accuracy of the matching of antigenic reactivities on the protein spots during the 2D immunoproteomic procedures. The superimposition, based essentially on visual criteria of antigenic and protein spots, remains the major limitation of SERPA. The introduction of fluorescent dyes in proteomic strategies, commonly known as 2D-DIGE (differential in-gel electrophoresis), has boosted the qualitative capabilities of 2D electrophoresis. Based on this 2D-DIGE strategy, we have improved the conventional SERPA by developing a new and entirely fluorescence-based bi-dimensional immunoproteomic (FBIP) analysis, performed with three fluorescent dyes. To optimize the alignment of the different antigenic maps, we introduced a landmark map composed of a combination of specific antibodies. This methodological development allows simultaneous revelation of the antigenic, landmark and proteomic maps on each immunoblot. A computer-assisted process using commercially available software automatically leads to the superimposition of the different maps, ensuring accurate localization of antigenic spots of interest. PMID:26132557

  1. Accurate B-spline-based 3-D interpolation scheme for digital volume correlation.

    PubMed

    Ren, Maodong; Liang, Jin; Wei, Bin

    2016-12-01

    An accurate and efficient 3-D interpolation scheme, based on sampling theorem and Fourier transform technique, is proposed to reduce the sub-voxel matching error caused by intensity interpolation bias in digital volume correlation. First, the influence factors of the interpolation bias are investigated theoretically using the transfer function of an interpolation filter (henceforth filter) in the Fourier domain. A law that the positional error of a filter can be expressed as a function of fractional position and wave number is found. Then, considering the above factors, an optimized B-spline-based recursive filter, combining B-spline transforms and least squares optimization method, is designed to virtually eliminate the interpolation bias in the process of sub-voxel matching. Besides, given each volumetric image containing different wave number ranges, a Gaussian weighting function is constructed to emphasize or suppress certain of wave number ranges based on the Fourier spectrum analysis. Finally, a novel software is developed and series of validation experiments were carried out to verify the proposed scheme. Experimental results show that the proposed scheme can reduce the interpolation bias to an acceptable level.

  2. On scalable lossless video coding based on sub-pixel accurate MCTF

    NASA Astrophysics Data System (ADS)

    Yea, Sehoon; Pearlman, William A.

    2006-01-01

    We propose two approaches to scalable lossless coding of motion video. They achieve SNR-scalable bitstream up to lossless reconstruction based upon the subpixel-accurate MCTF-based wavelet video coding. The first approach is based upon a two-stage encoding strategy where a lossy reconstruction layer is augmented by a following residual layer in order to obtain (nearly) lossless reconstruction. The key advantages of our approach include an 'on-the-fly' determination of bit budget distribution between the lossy and the residual layers, freedom to use almost any progressive lossy video coding scheme as the first layer and an added feature of near-lossless compression. The second approach capitalizes on the fact that we can maintain the invertibility of MCTF with an arbitrary sub-pixel accuracy even in the presence of an extra truncation step for lossless reconstruction thanks to the lifting implementation. Experimental results show that the proposed schemes achieve compression ratios not obtainable by intra-frame coders such as Motion JPEG-2000 thanks to their inter-frame coding nature. Also they are shown to outperform the state-of-the-art non-scalable inter-frame coder H.264 (JM) lossless mode, with the added benefit of bitstream embeddedness.

  3. Surface plasmon resonance based biosensor: A new platform for rapid diagnosis of livestock diseases

    PubMed Central

    Sahoo, Pravas Ranjan; Swain, Parthasarathi; Nayak, Sudhanshu Mohan; Bag, Sudam; Mishra, Smruti Ranjan

    2016-01-01

    Surface plasmon resonance (SPR) based biosensors are the most advanced and developed optical label-free biosensor technique used for powerful detection with vast applications in environmental protection, biotechnology, medical diagnostics, drug screening, food safety, and security as well in livestock sector. The livestock sector which contributes the largest economy of India, harbors many bacterial, viral, and fungal diseases impacting a great loss to the production and productive potential which is a major concern in both small and large ruminants. Hence, an accurate, sensitive, and rapid diagnosis is required for prevention of these above-mentioned diseases. SPR based biosensor assay may fulfill the above characteristics which lead to a greater platform for rapid diagnosis of different livestock diseases. Hence, this review may give a detail idea about the principle, recent development of SPR based biosensor techniques and its application in livestock sector. PMID:28096602

  4. 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

  5. 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

  6. Poisonous or non-poisonous plants? DNA-based tools and applications for accurate identification.

    PubMed

    Mezzasalma, Valerio; Ganopoulos, Ioannis; Galimberti, Andrea; Cornara, Laura; Ferri, Emanuele; Labra, Massimo

    2017-01-01

    Plant exposures are among the most frequently reported cases to poison control centres worldwide. This is a growing condition due to recent societal trends oriented towards the consumption of wild plants as food, cosmetics, or medicine. At least three general causes of plant poisoning can be identified: plant misidentification, introduction of new plant-based supplements and medicines with no controls about their safety, and the lack of regulation for the trading of herbal and phytochemical products. Moreover, an efficient screening for the occurrence of plants poisonous to humans is also desirable at the different stages of the food supply chain: from the raw material to the final transformed product. A rapid diagnosis of intoxication cases is necessary in order to provide the most reliable treatment. However, a precise taxonomic characterization of the ingested species is often challenging. In this review, we provide an overview of the emerging DNA-based tools and technologies to address the issue of poisonous plant identification. Specifically, classic DNA barcoding and its applications using High Resolution Melting (Bar-HRM) ensure high universality and rapid response respectively, whereas High Throughput Sequencing techniques (HTS) provide a complete characterization of plant residues in complex matrices. The pros and cons of each approach have been evaluated with the final aim of proposing a general user's guide to molecular identification directed to different stakeholder categories interested in the diagnostics of poisonous plants.

  7. 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.

  8. 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

  9. 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.

  10. An Accurate Non-Cooperative Method for Measuring Textureless Spherical Target Based on Calibrated Lasers

    PubMed Central

    Wang, Fei; Dong, Hang; Chen, Yanan; Zheng, Nanning

    2016-01-01

    Strong demands for accurate non-cooperative target measurement have been arising recently for the tasks of assembling and capturing. Spherical objects are one of the most common targets in these applications. However, the performance of the traditional vision-based reconstruction method was limited for practical use when handling poorly-textured targets. In this paper, we propose a novel multi-sensor fusion system for measuring and reconstructing textureless non-cooperative spherical targets. Our system consists of four simple lasers and a visual camera. This paper presents a complete framework of estimating the geometric parameters of textureless spherical targets: (1) an approach to calibrate the extrinsic parameters between a camera and simple lasers; and (2) a method to reconstruct the 3D position of the laser spots on the target surface and achieve the refined results via an optimized scheme. The experiment results show that our proposed calibration method can obtain a fine calibration result, which is comparable to the state-of-the-art LRF-based methods, and our calibrated system can estimate the geometric parameters with high accuracy in real time. PMID:27941705

  11. Accurate read-based metagenome characterization using a hierarchical suite of unique signatures

    PubMed Central

    Freitas, Tracey Allen K.; Li, Po-E; Scholz, Matthew B.; Chain, Patrick S. G.

    2015-01-01

    A major challenge in the field of shotgun metagenomics is the accurate identification of organisms present within a microbial community, based on classification of short sequence reads. Though existing microbial community profiling methods have attempted to rapidly classify the millions of reads output from modern sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, errors and biases in sequencing technologies, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here, we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling method with significantly and consistently smaller FDR than any other available method. Our algorithm circumvents false positives using a series of non-redundant signature databases and examines Genomic Origins Through Taxonomic CHAllenge (GOTTCHA). GOTTCHA was tested and validated on 20 synthetic and mock datasets ranging in community composition and complexity, was applied successfully to data generated from spiked environmental and clinical samples, and robustly demonstrates superior performance compared with other available tools. PMID:25765641

  12. SILAC-Based Quantitative Strategies for Accurate Histone Posttranslational Modification Profiling Across Multiple Biological Samples.

    PubMed

    Cuomo, Alessandro; Soldi, Monica; Bonaldi, Tiziana

    2017-01-01

    Histone posttranslational modifications (hPTMs) play a key role in regulating chromatin dynamics and fine-tuning DNA-based processes. Mass spectrometry (MS) has emerged as a versatile technology for the analysis of histones, contributing to the dissection of hPTMs, with special strength in the identification of novel marks and in the assessment of modification cross talks. Stable isotope labeling by amino acid in cell culture (SILAC), when adapted to histones, permits the accurate quantification of PTM changes among distinct functional states; however, its application has been mainly confined to actively dividing cell lines. A spike-in strategy based on SILAC can be used to overcome this limitation and profile hPTMs across multiple samples. We describe here the adaptation of SILAC to the analysis of histones, in both standard and spike-in setups. We also illustrate its coupling to an implemented "shotgun" workflow, by which heavy arginine-labeled histone peptides, produced upon Arg-C digestion, are qualitatively and quantitatively analyzed in an LC-MS/MS system that combines ultrahigh-pressure liquid chromatography (UHPLC) with new-generation Orbitrap high-resolution instrument.

  13. 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

  14. An Accurate Non-Cooperative Method for Measuring Textureless Spherical Target Based on Calibrated Lasers.

    PubMed

    Wang, Fei; Dong, Hang; Chen, Yanan; Zheng, Nanning

    2016-12-09

    Strong demands for accurate non-cooperative target measurement have been arising recently for the tasks of assembling and capturing. Spherical objects are one of the most common targets in these applications. However, the performance of the traditional vision-based reconstruction method was limited for practical use when handling poorly-textured targets. In this paper, we propose a novel multi-sensor fusion system for measuring and reconstructing textureless non-cooperative spherical targets. Our system consists of four simple lasers and a visual camera. This paper presents a complete framework of estimating the geometric parameters of textureless spherical targets: (1) an approach to calibrate the extrinsic parameters between a camera and simple lasers; and (2) a method to reconstruct the 3D position of the laser spots on the target surface and achieve the refined results via an optimized scheme. The experiment results show that our proposed calibration method can obtain a fine calibration result, which is comparable to the state-of-the-art LRF-based methods, and our calibrated system can estimate the geometric parameters with high accuracy in real time.

  15. Accurate and fast simulation of channel noise in conductance-based model neurons by diffusion approximation.

    PubMed

    Linaro, Daniele; Storace, Marco; Giugliano, Michele

    2011-03-01

    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.

  16. Accurate shape from focus based on focus adjustment in optical microscopy.

    PubMed

    Shim, Seong-O; Malik, Aamir Saeed; Choi, Tae-Sun

    2009-05-01

    Optical microscopy allows a magnified view of the sample while decreasing the depth of focus. Although the acquired images from limited depth of field have both blurred and focused regions, they can provide depth information. The technique to estimate the depth and 3D shape of an object from the images of the same sample obtained at different focus settings is called shape from focus (SFF). In SFF, the measure of focus--sharpness--is the crucial part for final 3D shape estimation. The conventional methods compute sharpness by applying focus measure operator on each 2D image frame of the image sequence. However, such methods do not reflect the accurate focus levels in an image because the focus levels for curved objects require information from neighboring pixels in the adjacent frames too. To address this issue, we propose a new method based on focus adjustment which takes the values of the neighboring pixels from the adjacent image frames that have approximately the same initial depth as of the center pixel and then it re-adjusts the center value accordingly. Experiments were conducted on synthetic and microscopic objects, and the results show that the proposed technique generates better shape and takes less computation time in comparison with previous SFF methods based on focused image surface (FIS) and dynamic programming.

  17. 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

  18. 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

  19. A cost-effective transparency-based digital imaging for efficient and accurate wound area measurement.

    PubMed

    Li, Pei-Nan; Li, Hong; Wu, Mo-Li; Wang, Shou-Yu; Kong, Qing-You; Zhang, Zhen; Sun, Yuan; Liu, Jia; Lv, De-Cheng

    2012-01-01

    Wound measurement is an objective and direct way to trace the course of wound healing and to evaluate therapeutic efficacy. Nevertheless, the accuracy and efficiency of the current measurement methods need to be improved. Taking the advantages of reliability of transparency tracing and the accuracy of computer-aided digital imaging, a transparency-based digital imaging approach is established, by which data from 340 wound tracing were collected from 6 experimental groups (8 rats/group) at 8 experimental time points (Day 1, 3, 5, 7, 10, 12, 14 and 16) and orderly archived onto a transparency model sheet. This sheet was scanned and its image was saved in JPG form. Since a set of standard area units from 1 mm(2) to 1 cm(2) was integrated into the sheet, the tracing areas in JPG image were measured directly, using the "Magnetic lasso tool" in Adobe Photoshop program. The pixel values/PVs of individual outlined regions were obtained and recorded in an average speed of 27 second/region. All PV data were saved in an excel form and their corresponding areas were calculated simultaneously by the formula of Y (PV of the outlined region)/X (PV of standard area unit) × Z (area of standard unit). It took a researcher less than 3 hours to finish area calculation of 340 regions. In contrast, over 3 hours were expended by three skillful researchers to accomplish the above work with traditional transparency-based method. Moreover, unlike the results obtained traditionally, little variation was found among the data calculated by different persons and the standard area units in different sizes and shapes. Given its accurate, reproductive and efficient properties, this transparency-based digital imaging approach would be of significant values in basic wound healing research and clinical practice.

  20. 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.

  1. 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.

  2. A fault diagnosis system for PV power station based on global partitioned gradually approximation method

    NASA Astrophysics Data System (ADS)

    Wang, S.; Zhang, X. N.; Gao, D. D.; Liu, H. X.; Ye, J.; Li, L. R.

    2016-08-01

    As the solar photovoltaic (PV) power is applied extensively, more attentions are paid to the maintenance and fault diagnosis of PV power plants. Based on analysis of the structure of PV power station, the global partitioned gradually approximation method is proposed as a fault diagnosis algorithm to determine and locate the fault of PV panels. The PV array is divided into 16x16 blocks and numbered. On the basis of modularly processing of the PV array, the current values of each block are analyzed. The mean current value of each block is used for calculating the fault weigh factor. The fault threshold is defined to determine the fault, and the shade is considered to reduce the probability of misjudgments. A fault diagnosis system is designed and implemented with LabVIEW. And it has some functions including the data realtime display, online check, statistics, real-time prediction and fault diagnosis. Through the data from PV plants, the algorithm is verified. The results show that the fault diagnosis results are accurate, and the system works well. The validity and the possibility of the system are verified by the results as well. The developed system will be benefit for the maintenance and management of large scale PV array.

  3. 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

  4. Accurate eQTL prioritization with an ensemble-based framework.

    PubMed

    Zeng, Haoyang; Edwards, Matthew D; Guo, Yuchun; Gifford, David K

    2017-02-21

    We present a novel ensemble-based computational framework, EnsembleExpr, that achieved the best performance in the Fourth Critical Assessment of Genome Interpretation (CAGI4) "eQTL-causal SNPs" challenge for identifying eQTLs and prioritizing their gene expression effects. Expression quantitative trait loci (eQTLs) are genome sequence variants that result in gene expression changes and thus are prime suspects in the search for contributions to the causality of complex traits. When EnsembleExpr is trained on data from massively parallel reporter assays (MPRA) it accurately predicts reporter expression levels from unseen regulatory sequences and identifies sequence variants that exhibit significant changes in reporter expression. Compared with other state-of-the-art methods, EnsembleExpr achieved competitive performance when applied on eQTL datasets determined by other protocols. We envision EnsembleExpr to be a resource to help interpret non-coding regulatory variants and prioritize disease-associated mutations for downstream validation. This article is protected by copyright. All rights reserved.

  5. 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.

  6. 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.

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

    PubMed Central

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

    2015-01-01

    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

  8. 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.}

  9. 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.

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

    DOE PAGES

    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

  11. An accurate potential energy curve for helium based on ab initio calculations

    NASA Astrophysics Data System (ADS)

    Janzen, A. R.; Aziz, R. A.

    1997-07-01

    Korona, Williams, Bukowski, Jeziorski, and Szalewicz [J. Chem. Phys. 106, 1 (1997)] constructed a completely ab initio potential for He2 by fitting their calculations using infinite order symmetry adapted perturbation theory at intermediate range, existing Green's function Monte Carlo calculations at short range and accurate dispersion coefficients at long range to a modified Tang-Toennies potential form. The potential with retardation added to the dipole-dipole dispersion is found to predict accurately a large set of microscopic and macroscopic experimental data. The potential with a significantly larger well depth than other recent potentials is judged to be the most accurate characterization of the helium interaction yet proposed.

  12. 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.

  13. 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…

  14. Model-based fault detection and diagnosis in ALMA subsystems

    NASA Astrophysics Data System (ADS)

    Ortiz, José; Carrasco, Rodrigo A.

    2016-07-01

    The Atacama Large Millimeter/submillimeter Array (ALMA) observatory, with its 66 individual telescopes and other central equipment, generates a massive set of monitoring data every day, collecting information on the performance of a variety of critical and complex electrical, electronic and mechanical components. This data is crucial for most troubleshooting efforts performed by engineering teams. More than 5 years of accumulated data and expertise allow for a more systematic approach to fault detection and diagnosis. This paper presents model-based fault detection and diagnosis techniques to support corrective and predictive maintenance in a 24/7 minimum-downtime observatory.

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

    PubMed

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

    2010-08-01

    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/mum), 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. 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.

  18. Breast cancer early diagnosis based on hybrid strategy.

    PubMed

    Li, Peng; Bi, Tingting; Huang, Jiuling; Li, Siben

    2014-01-01

    The frequent occurrence of breast cancer and its serious consequences have attracted worldwide attention in recent years. Problems such as low rate of accuracy and poor self-adaptability still exist in traditional diagnosis. In order to solve these problems, an AdaBoost-SVM classification algorithm, combined with the cluster boundary sampling preprocessing techniques (CBS-AdaBoost-SVM), is proposed in this paper for the early diagnosis of breast cancer. The algorithm uses machine learning method to diagnose the unknown image data. Moreover, not all of the characteristics play positive roles for classification. To address this issue the paper delete redundant features by using Rough set attribute reduction algorithm based on the genetic algorithm (GA). The effectiveness of the proposed methods are examined on DDSM by calculating its accuracy, confusion matrix, and receiver operating characteristic curves, which give important clues to the physicians for early diagnosis of breast cancer.

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

    PubMed

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

    2015-07-06

    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.

  20. 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

  1. 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

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

    PubMed

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

    2016-01-18

    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.

  3. A feature-based learning framework for accurate prostate localization in CT images.

    PubMed

    Liao, Shu; Shen, Dinggang

    2012-08-01

    Automatic segmentation of prostate in CT images plays an important role in medical image analysis and image guided radiation therapy. It remains as a challenging problem mainly due to three issues: First, the image contrast between the prostate and its surrounding tissues is low in prostate CT images and no obvious boundaries can be observed. Second, the unpredictable prostate motion causes large position variations of the prostate in the treatment images scanned at different treatment days. Third, the uncertainty of the existence of bowel gas in treatment images significantly changes the image appearance even for images taken from the same patient. To address these issues, in this paper we are motivated to propose a feature based learning framework for accurate prostate localization in CT images. The main contributions of the proposed method lie in the following aspects: (1) Anatomical features are extracted from input images and adopted as signatures for each voxel. The most robust and informative features are identified by the feature selection process to help localize the prostate. (2) Regions with salient features but irrelevant to the localization of prostate, such as regions filled with bowel gas are automatically filtered out by the proposed method. (3) An online update mechanism is adopted in this paper to adaptively combine both population information and patient-specific information to localize the prostate. The proposed method is evaluated on a CT prostate dataset of 24 patients to localize the prostate, where each patient has more than 10 longitudinal images scanned at different treatment times. It is also compared with several state-of- the-art prostate localization algorithms in CT images, and the experimental results demonstrate that the proposed method achieves the highest localization accuracy among all the methods under comparison.

  4. 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.

  5. Structure-based constitutive model can accurately predict planar biaxial properties of aortic wall tissue.

    PubMed

    Polzer, S; Gasser, T C; Novak, K; Man, V; Tichy, M; Skacel, P; Bursa, J

    2015-03-01

    Structure-based constitutive models might help in exploring mechanisms by which arterial wall histology is linked to wall mechanics. This study aims to validate a recently proposed structure-based constitutive model. Specifically, the model's ability to predict mechanical biaxial response of porcine aortic tissue with predefined collagen structure was tested. Histological slices from porcine thoracic aorta wall (n=9) were automatically processed to quantify the collagen fiber organization, and mechanical testing identified the non-linear properties of the wall samples (n=18) over a wide range of biaxial stretches. Histological and mechanical experimental data were used to identify the model parameters of a recently proposed multi-scale constitutive description for arterial layers. The model predictive capability was tested with respect to interpolation and extrapolation. Collagen in the media was predominantly aligned in circumferential direction (planar von Mises distribution with concentration parameter bM=1.03 ± 0.23), and its coherence decreased gradually from the luminal to the abluminal tissue layers (inner media, b=1.54 ± 0.40; outer media, b=0.72 ± 0.20). In contrast, the collagen in the adventitia was aligned almost isotropically (bA=0.27 ± 0.11), and no features, such as families of coherent fibers, were identified. The applied constitutive model captured the aorta biaxial properties accurately (coefficient of determination R(2)=0.95 ± 0.03) over the entire range of biaxial deformations and with physically meaningful model parameters. Good predictive properties, well outside the parameter identification space, were observed (R(2)=0.92 ± 0.04). Multi-scale constitutive models equipped with realistic micro-histological data can predict macroscopic non-linear aorta wall properties. Collagen largely defines already low strain properties of media, which explains the origin of wall anisotropy seen at this strain level. The structure and mechanical

  6. Computed tomography-based biomarker provides unique signature for diagnosis of COPD phenotypes and disease progression.

    PubMed

    Galbán, Craig J; Han, Meilan K; Boes, Jennifer L; Chughtai, Komal A; Meyer, Charles R; Johnson, Timothy D; Galbán, Stefanie; Rehemtulla, Alnawaz; Kazerooni, Ella A; Martinez, Fernando J; Ross, Brian D

    2012-11-01

    Chronic obstructive pulmonary disease (COPD) is increasingly being recognized as a highly heterogeneous disorder, composed of varying pathobiology. Accurate detection of COPD subtypes by image biomarkers is urgently needed to enable individualized treatment, thus improving patient outcome. We adapted the parametric response map (PRM), a voxel-wise image analysis technique, for assessing COPD phenotype. We analyzed whole-lung computed tomography (CT) scans acquired at inspiration and expiration of 194 individuals with COPD from the COPDGene study. PRM identified the extent of functional small airways disease (fSAD) and emphysema as well as provided CT-based evidence that supports the concept that fSAD precedes emphysema with increasing COPD severity. PRM is a versatile imaging biomarker capable of diagnosing disease extent and phenotype while providing detailed spatial information of disease distribution and location. PRM's ability to differentiate between specific COPD phenotypes will allow for more accurate diagnosis of individual patients, complementing standard clinical techniques.

  7. 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

  8. 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.

  9. 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...

  10. 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

  11. 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

  12. [PCR-based diagnosis of mucormycosis in tissue samples].

    PubMed

    Bialek, R; Zelck, U E

    2013-11-01

    Mucormycosis is characterized by a rapid, often fatal progression. Early diagnosis of invasive mucormycosis is the key for timely therapeutic intervention and improved survival. Contrary to the more prevalent aspergillosis, effective antifungal therapy of mucormycosis is mainly limited to amphotericin B. Given the importance to guide the timely initiation of amphotericin B and possible surgical intervention, rapid and specific identification of fungal hyphae is essential. Conventional histopathology depends on abundance and morphology of the fungi as well as on the skills of the personnel, and usually shows an accuracy of 80 %. PCR assays targeting fungal ribosomal genes to identify Mucorales at least at genus level increase sensitivity, allow a rapid identification as well as detection of double mold infections. Thus, PCR assays are beneficial to complement existing approaches. They are recommended to rapidly specify tissue diagnosis and accurate identification of fungi. This will help to guide effective therapy and thereby, survival will increase. Retrospective analyses of mucormycosis by PCR help to evaluate therapeutic interventions and will optimize treatment options.

  13. 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

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

    PubMed

    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.

  15. Model-based fault diagnosis in continuous dynamic systems.

    PubMed

    Lo, C H; Wong, Y K; Rad, A B

    2004-07-01

    Traditional fault detection and isolation methods are based on quantitative models which are sometimes difficult and costly to obtain. In this paper, qualitative bond graph (QBG) reasoning is adopted as the modeling scheme to generate a set of qualitative equations. The QBG method provides a unified approach for modeling engineering systems, in particular, mechatronic systems. An input-output qualitative equation derived from QBG formalism performs continuous system monitoring. Fault diagnosis is activated when a discrepancy is observed between measured abnormal behavior and predicted system behavior. Genetic algorithms (GA's) are then used to search for possible faulty components among a system of qualitative equations. In order to demonstrate the performance of the proposed algorithm, we have tested it on a laboratory scale servo-tank liquid process rig. Results of the proposed model-based fault detection and diagnosis algorithm for the process rig are presented and discussed.

  16. 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.

  17. Diagnosis of Compartment Syndrome Based on Tissue Oxygenation

    DTIC Science & Technology

    2013-10-01

    measured with microprobes has been shown to be highly correlated with tissue oxygenation and the extent of ischemia reperfusion injury .3 Near-infrared...Tissue Oxygenation PRINCIPAL INVESTIGATOR: Hubert Kim, M.D., Ph.D. CONTRACTING ORGANIZATION: Northern California Institute for...SUBTITLE Diagnosis of Compartment Syndrome based on Tissue Oxygenation 5a. CONTRACT NUMBER 5b. GRANT NUMBER W81XWH-10-1-1024 5c. PROGRAM ELEMENT

  18. Accurate calculation and Matlab based fast realization of merit function's Hesse matrix for the design of multilayer optical coating

    NASA Astrophysics Data System (ADS)

    Wu, Su-Yong; Long, Xing-Wu; Yang, Kai-Yong

    2009-09-01

    To improve the current status of home multilayer optical coating design with low speed and poor efficiency when a large layer number occurs, the accurate calculation and fast realization of merit function’s gradient and Hesse matrix is pointed out. Based on the matrix method to calculate the spectral properties of multilayer optical coating, an analytic model is established theoretically. And the corresponding accurate and fast computation is successfully achieved by programming with Matlab. Theoretical and simulated results indicate that this model is mathematically strict and accurate, and its maximal precision can reach floating-point operations in the computer, with short time and fast speed. Thus it is very suitable to improve the optimal search speed and efficiency of local optimization methods based on the derivatives of merit function. It has outstanding performance in multilayer optical coating design with a large layer number.

  19. Crack Diagnosis of Wind Turbine Blades Based on EMD Method

    NASA Astrophysics Data System (ADS)

    Hong-yu, CUI; Ning, DING; Ming, HONG

    2016-11-01

    Wind turbine blades are both the source of power and the core technology of wind generators. After long periods of time or in some extreme conditions, cracks or damage can occur on the surface of the blades. If the wind generators continue to work at this time, the crack will expand until the blade breaks, which can lead to incalculable losses. Therefore, a crack diagnosis method based on EMD for wind turbine blades is proposed in this paper. Based on aerodynamics and fluid-structure coupling theory, an aero-elastic analysis on wind turbine blades model is first made in ANSYS Workbench. Second, based on the aero-elastic analysis and EMD method, the blade cracks are diagnosed and identified in the time and frequency domains, respectively. Finally, the blade model, strain gauge, dynamic signal acquisition and other equipment are used in an experimental study of the aero-elastic analysis and crack damage diagnosis of wind turbine blades to verify the crack diagnosis method proposed in this paper.

  20. Sample pretreatment and nucleic acid-based detection for fast diagnosis utilizing microfluidic systems.

    PubMed

    Wang, Jung-Hao; Wang, Chih-Hung; Lee, Gwo-Bin

    2012-06-01

    Recently, micro-electro-mechanical-systems (MEMS) technology and micromachining techniques have enabled miniaturization of biomedical devices and systems. Not only do these techniques facilitate the development of miniaturized instrumentation for biomedical analysis, but they also open a new era for integration of microdevices for performing accurate and sensitive diagnostic assays. A so-called "micro-total-analysis-system", which integrates sample pretreatment, transport, reaction, and detection on a small chip in an automatic format, can be realized by combining functional microfluidic components manufactured by specific MEMS technologies. Among the promising applications using microfluidic technologies, nucleic acid-based detection has shown considerable potential recently. For instance, micro-polymerase chain reaction chips for rapid DNA amplification have attracted considerable interest. In addition, microfluidic devices for rapid sample pretreatment prior to nucleic acid-based detection have also achieved significant progress in the recent years. In this review paper, microfluidic systems for sample preparation, nucleic acid amplification and detection for fast diagnosis will be reviewed. These microfluidic devices and systems have several advantages over their large-scale counterparts, including lower sample/reagent consumption, lower power consumption, compact size, faster analysis, and lower per unit cost. The development of these microfluidic devices and systems may provide a revolutionary platform technology for fast sample pretreatment and accurate, sensitive diagnosis.

  1. 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.

  2. Asymptotic expansion based equation of state for hard-disk fluids offering accurate virial coefficients.

    PubMed

    Tian, Jianxiang; Gui, Yuanxing; Mulero, A

    2010-01-01

    Despite the fact that more than 30 analytical expressions for the equation of state of hard-disk fluids have been proposed in the literature, none of them is capable of reproducing the currently accepted numeric or estimated values for the first eighteen virial coefficients. Using the asymptotic expansion method, extended to the first ten virial coefficients for hard-disk fluids, fifty-seven new expressions for the equation of state have been studied. Of these, a new equation of state is selected which reproduces accurately all the first eighteen virial coefficients. Comparisons for the compressibility factor with computer simulations show that this new equation is as accurate as other similar expressions with the same number of parameters. Finally, the location of the poles of the 57 new equations shows that there are some particular configurations which could give both the accurate virial coefficients and the correct closest packing fraction in the future when higher than the tenth virial coefficients are numerically calculated.

  3. 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.

  4. 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

  5. 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

  6. Accurate two-dimensional model of an arrayed-waveguide grating demultiplexer and optimal design based on the reciprocity theory.

    PubMed

    Dai, Daoxin; He, Sailing

    2004-12-01

    An accurate two-dimensional (2D) model is introduced for the simulation of an arrayed-waveguide grating (AWG) demultiplexer by integrating the field distribution along the vertical direction. The equivalent 2D model has almost the same accuracy as the original three-dimensional model and is more accurate for the AWG considered here than the conventional 2D model based on the effective-index method. To further improve the computational efficiency, the reciprocity theory is applied to the optimal design of a flat-top AWG demultiplexer with a special input structure.

  7. 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.

  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. Yield-Ensuring DAC-Embedded Opamp Design Based on Accurate Behavioral Model Development

    NASA Astrophysics Data System (ADS)

    Jang, Yeong-Shin; Nguyen, Hoai-Nam; Ryu, Seung-Tak; Lee, Sang-Gug

    An accurate behavioral model of a DAC-embedded opamp (DAC-opamp) is developed for a yield-ensuring LCD column driver design. A lookup table for the V-I curve of the unit differential pair in the DAC-opamp is extracted from a circuit simulation and is later manipulated through a random error insertion. Virtual ground assumption simplifies the output voltage estimation algorithm. The developed behavioral model of a 5-bit DAC-opamp shows good agreement with the circuit level simulation with less than 5% INL difference.

  10. Simple X-ray versus ultrasonography examination in blunt chest trauma: effective tools of accurate diagnosis and considerations for rib fractures

    PubMed Central

    Hwang, Eun Gu; Lee, Yunjung

    2016-01-01

    Simple radiography is the best diagnostic tool for rib fractures caused by chest trauma, but it has some limitations. Thus, other tools are also being used. The aims of this study were to investigate the effectiveness of ultrasonography (US) for identifying rib fractures and to identify influencing factors of its effectiveness. Between October 2003 and August 2007, 201 patients with blunt chest trauma were available to undergo chest radiographic and US examinations for diagnosis of rib fractures. The two modalities were compared in terms of effectiveness based on simple radiographic readings and US examination results. We also investigated the factors that influenced the effectiveness of US examination. Rib fractures were detected on radiography in 69 patients (34.3%) but not in 132 patients. Rib fractures were diagnosed by using US examination in 160 patients (84.6%). Of the 132 patients who showed no rib fractures on radiography, 92 showed rib fractures on US. Among the 69 patients of rib fracture detected on radiography, 33 had additional rib fractures detected on US. Of the patients, 76 (37.8%) had identical radiographic and US results, and 125 (62.2%) had fractures detected on US that were previously undetected on radiography or additional fractures detected on US. Age, duration until US examination, and fracture location were not significant influencing factors. However, in the group without detected fractures on radiography, US showed a more significant effectiveness than in the group with detected fractures on radiography (P=0.003). US examination could detect unnoticed rib fractures on simple radiography. US examination is especially more effective in the group without detected fractures on radiography. More attention should be paid to patients with chest trauma who have no detected fractures on radiography. PMID:28119889

  11. Novel micelle PCR-based method for accurate, sensitive and quantitative microbiota profiling.

    PubMed

    Boers, Stefan A; Hays, John P; Jansen, Ruud

    2017-04-05

    In the last decade, many researchers have embraced 16S rRNA gene sequencing techniques, which has led to a wealth of publications and documented differences in the composition of microbial communities derived from many different ecosystems. However, comparison between different microbiota studies is currently very difficult due to the lack of a standardized 16S rRNA gene sequencing protocol. Here we report on a novel approach employing micelle PCR (micPCR) in combination with an internal calibrator that allows for standardization of microbiota profiles via their absolute abundances. The addition of an internal calibrator allows the researcher to express the resulting operational taxonomic units (OTUs) as a measure of 16S rRNA gene copies by correcting the number of sequences of each individual OTU in a sample for efficiency differences in the NGS process. Additionally, accurate quantification of OTUs obtained from negative extraction control samples allows for the subtraction of contaminating bacterial DNA derived from the laboratory environment or chemicals/reagents used. Using equimolar synthetic microbial community samples and low biomass clinical samples, we demonstrate that the calibrated micPCR/NGS methodology possess a much higher precision and a lower limit of detection compared with traditional PCR/NGS, resulting in more accurate microbiota profiles suitable for multi-study comparison.

  12. Novel micelle PCR-based method for accurate, sensitive and quantitative microbiota profiling

    PubMed Central

    Boers, Stefan A.; Hays, John P.; Jansen, Ruud

    2017-01-01

    In the last decade, many researchers have embraced 16S rRNA gene sequencing techniques, which has led to a wealth of publications and documented differences in the composition of microbial communities derived from many different ecosystems. However, comparison between different microbiota studies is currently very difficult due to the lack of a standardized 16S rRNA gene sequencing protocol. Here we report on a novel approach employing micelle PCR (micPCR) in combination with an internal calibrator that allows for standardization of microbiota profiles via their absolute abundances. The addition of an internal calibrator allows the researcher to express the resulting operational taxonomic units (OTUs) as a measure of 16S rRNA gene copies by correcting the number of sequences of each individual OTU in a sample for efficiency differences in the NGS process. Additionally, accurate quantification of OTUs obtained from negative extraction control samples allows for the subtraction of contaminating bacterial DNA derived from the laboratory environment or chemicals/reagents used. Using equimolar synthetic microbial community samples and low biomass clinical samples, we demonstrate that the calibrated micPCR/NGS methodology possess a much higher precision and a lower limit of detection compared with traditional PCR/NGS, resulting in more accurate microbiota profiles suitable for multi-study comparison. PMID:28378789

  13. 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

  14. Development of a fluorescence-based sensor for rapid diagnosis of cyanide exposure.

    PubMed

    Jackson, Randy; Oda, Robert P; Bhandari, Raj K; Mahon, Sari B; Brenner, Matthew; Rockwood, Gary A; Logue, Brian A

    2014-02-04

    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.

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. ILT based defect simulation of inspection images accurately predicts mask defect printability on wafer

    NASA Astrophysics Data System (ADS)

    Deep, Prakash; Paninjath, Sankaranarayanan; Pereira, Mark; Buck, Peter

    2016-05-01

    At advanced technology nodes mask complexity has been increased because of large-scale use of resolution enhancement technologies (RET) which includes Optical Proximity Correction (OPC), Inverse Lithography Technology (ILT) and Source Mask Optimization (SMO). The number of defects detected during inspection of such mask increased drastically and differentiation of critical and non-critical defects are more challenging, complex and time consuming. Because of significant defectivity of EUVL masks and non-availability of actinic inspection, it is important and also challenging to predict the criticality of defects for printability on wafer. This is one of the significant barriers for the adoption of EUVL for semiconductor manufacturing. Techniques to decide criticality of defects from images captured using non actinic inspection images is desired till actinic inspection is not available. High resolution inspection of photomask images detects many defects which are used for process and mask qualification. Repairing all defects is not practical and probably not required, however it's imperative to know which defects are severe enough to impact wafer before repair. Additionally, wafer printability check is always desired after repairing a defect. AIMSTM review is the industry standard for this, however doing AIMSTM review for all defects is expensive and very time consuming. Fast, accurate and an economical mechanism is desired which can predict defect printability on wafer accurately and quickly from images captured using high resolution inspection machine. Predicting defect printability from such images is challenging due to the fact that the high resolution images do not correlate with actual mask contours. The challenge is increased due to use of different optical condition during inspection other than actual scanner condition, and defects found in such images do not have correlation with actual impact on wafer. Our automated defect simulation tool predicts

  20. 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.

  1. Accurate and computationally efficient prediction of thermochemical properties of biomolecules using the generalized connectivity-based hierarchy.

    PubMed

    Sengupta, Arkajyoti; Ramabhadran, Raghunath O; Raghavachari, Krishnan

    2014-08-14

    In this study we have used the connectivity-based hierarchy (CBH) method to derive accurate heats of formation of a range of biomolecules, 18 amino acids and 10 barbituric acid/uracil derivatives. The hierarchy is based on the connectivity of the different atoms in a large molecule. It results in error-cancellation reaction schemes that are automated, general, and can be readily used for a broad range of organic molecules and biomolecules. Herein, we first locate stable conformational and tautomeric forms of these biomolecules using an accurate level of theory (viz. CCSD(T)/6-311++G(3df,2p)). Subsequently, the heats of formation of the amino acids are evaluated using the CBH-1 and CBH-2 schemes and routinely employed density functionals or wave function-based methods. The calculated heats of formation obtained herein using modest levels of theory and are in very good agreement with those obtained using more expensive W1-F12 and W2-F12 methods on amino acids and G3 results on barbituric acid derivatives. Overall, the present study (a) highlights the small effect of including multiple conformers in determining the heats of formation of biomolecules and (b) in concurrence with previous CBH studies, proves that use of the more effective error-cancelling isoatomic scheme (CBH-2) results in more accurate heats of formation with modestly sized basis sets along with common density functionals or wave function-based methods.

  2. Adaptive PCA based fault diagnosis scheme in imperial smelting process.

    PubMed

    Hu, Zhikun; Chen, Zhiwen; Gui, Weihua; Jiang, Bin

    2014-09-01

    In this paper, an adaptive fault detection scheme based on a recursive principal component analysis (PCA) is proposed to deal with the problem of false alarm due to normal process changes in real process. Our further study is also dedicated to develop a fault isolation approach based on Generalized Likelihood Ratio (GLR) test and Singular Value Decomposition (SVD) which is one of general techniques of PCA, on which the off-set and scaling fault can be easily isolated with explicit off-set fault direction and scaling fault classification. The identification of off-set and scaling fault is also applied. The complete scheme of PCA-based fault diagnosis procedure is proposed. The proposed scheme is first applied to Imperial Smelting Process, and the results show that the proposed strategies can be able to mitigate false alarms and isolate faults efficiently.

  3. Computer-aided diagnosis of early knee osteoarthritis based on MRI T2 mapping.

    PubMed

    Wu, Yixiao; Yang, Ran; Jia, Sen; Li, Zhanjun; Zhou, Zhiyang; Lou, Ting

    2014-01-01

    This work was aimed at studying the method of computer-aided diagnosis of early knee OA (OA: osteoarthritis). Based on the technique of MRI (MRI: Magnetic Resonance Imaging) T2 Mapping, through computer image processing, feature extraction, calculation and analysis via constructing a classifier, an effective computer-aided diagnosis method for knee OA was created to assist doctors in their accurate, timely and convenient detection of potential risk of OA. In order to evaluate this method, a total of 1380 data from the MRI images of 46 samples of knee joints were collected. These data were then modeled through linear regression on an offline general platform by the use of the ImageJ software, and a map of the physical parameter T2 was reconstructed. After the image processing, the T2 values of ten regions in the WORMS (WORMS: Whole-organ Magnetic Resonance Imaging Score) areas of the articular cartilage were extracted to be used as the eigenvalues in data mining. Then,a RBF (RBF: Radical Basis Function) network classifier was built to classify and identify the collected data. The classifier exhibited a final identification accuracy of 75%, indicating a good result of assisting diagnosis. Since the knee OA classifier constituted by a weights-directly-determined RBF neural network didn't require any iteration, our results demonstrated that the optimal weights, appropriate center and variance could be yielded through simple procedures. Furthermore, the accuracy for both the training samples and the testing samples from the normal group could reach 100%. Finally, the classifier was superior both in time efficiency and classification performance to the frequently used classifiers based on iterative learning. Thus it was suitable to be used as an aid to computer-aided diagnosis of early knee OA.

  4. Do modelled or satellite-based estimates of surface solar irradiance accurately describe its temporal variability?

    NASA Astrophysics Data System (ADS)

    Bengulescu, Marc; Blanc, Philippe; Boilley, Alexandre; Wald, Lucien

    2017-02-01

    This study investigates the characteristic time-scales of variability found in long-term time-series of daily means of estimates of surface solar irradiance (SSI). The study is performed at various levels to better understand the causes of variability in the SSI. First, the variability of the solar irradiance at the top of the atmosphere is scrutinized. Then, estimates of the SSI in cloud-free conditions as provided by the McClear model are dealt with, in order to reveal the influence of the clear atmosphere (aerosols, water vapour, etc.). Lastly, the role of clouds on variability is inferred by the analysis of in-situ measurements. A description of how the atmosphere affects SSI variability is thus obtained on a time-scale basis. The analysis is also performed with estimates of the SSI provided by the satellite-derived HelioClim-3 database and by two numerical weather re-analyses: ERA-Interim and MERRA2. It is found that HelioClim-3 estimates render an accurate picture of the variability found in ground measurements, not only globally, but also with respect to individual characteristic time-scales. On the contrary, the variability found in re-analyses correlates poorly with all scales of ground measurements variability.

  5. Fast and accurate auto focusing algorithm based on two defocused images using discrete cosine transform

    NASA Astrophysics Data System (ADS)

    Park, Byung-Kwan; Kim, Sung-Su; Chung, Dae-Su; Lee, Seong-Deok; Kim, Chang-Yeong

    2008-02-01

    This paper describes the new method for fast auto focusing in image capturing devices. This is achieved by using two defocused images. At two prefixed lens positions, two defocused images are taken and defocused blur levels in each image are estimated using Discrete Cosine Transform (DCT). These DCT values can be classified into distance from the image capturing device to main object, so we can make distance vs. defocused blur level classifier. With this classifier, relation between two defocused blur levels can give the device the best focused lens step. In the case of ordinary auto focusing like Depth from Focus (DFF), it needs several defocused images and compares high frequency components in each image. Also known as hill-climbing method, the process requires about half number of images in all focus lens steps for focusing in general. Since this new method requires only two defocused images, it can save lots of time for focusing or reduce shutter lag time. Compared to existing Depth from Defocus (DFD) which uses two defocused images, this new algorithm is simple and accurate as DFF method. Because of this simplicity and accuracy, this method can also be applied to fast 3D depth map construction.

  6. Radiator standards for accurate IR calibrations in remote sensing based on heatpipe blackbodies

    NASA Astrophysics Data System (ADS)

    Hartmann, Juergen; Fischer, Joachim

    1999-09-01

    The demand of instrumentation in the field of remote sensing is increasing rapidly. For international compatibility, for reliable results and precise long-term investigation, necessary for example in the measurement of climatic trends, accurate traceability of the results to international standards or SI-units is mandatory. Additionally, interpretation of the results strongly requires a careful evaluation of the involved errors and the resulting uncertainties in order to allow for a rating of the obtained results. For that purpose quality assurance was introduced, not only for industrial fabrication, but also, and with increasing tendency, for industrial and scientific research. As an overview, the necessity and the possibilities of quality assurance in the area of remote sensing are discussed. Taking remote sensing of temperature as an example, the general approach is described. For that purpose, a description of heatpipe blackbodies used as standard radiation sources and of the apparatus for measuring the area of the beam limiting apertures is given. We also introduce the applied mathematical model for determination of the emissivity of the blackbodies, which crucially influenced the detected radiation temperature and the uncertainty. Finally the evaluation procedure of the uncertainties is described and a sophisticated estimation of the overall uncertainty is presented.

  7. Uniform and accurate single-cell sequencing based on emulsion whole-genome amplification

    PubMed Central

    Fu, Yusi; Li, Chunmei; Lu, Sijia; Zhou, Wenxiong; Tang, Fuchou; Xie, X. Sunney; Huang, Yanyi

    2015-01-01

    Whole-genome amplification (WGA) for next-generation sequencing has seen wide applications in biology and medicine when characterization of the genome of a single cell is required. High uniformity and fidelity of WGA is needed to accurately determine genomic variations, such as copy number variations (CNVs) and single-nucleotide variations (SNVs). Prevailing WGA methods have been limited by fluctuation of the amplification yield along the genome, as well as false-positive and -negative errors for SNV identification. Here, we report emulsion WGA (eWGA) to overcome these problems. We divide single-cell genomic DNA into a large number (105) of picoliter aqueous droplets in oil. Containing only a few DNA fragments, each droplet is led to reach saturation of DNA amplification before demulsification such that the differences in amplification gain among the fragments are minimized. We demonstrate the proof-of-principle of eWGA with multiple displacement amplification (MDA), a popular WGA method. This easy-to-operate approach enables simultaneous detection of CNVs and SNVs in an individual human cell, exhibiting significantly improved amplification evenness and accuracy. PMID:26340991

  8. Uniform and accurate single-cell sequencing based on emulsion whole-genome amplification.

    PubMed

    Fu, Yusi; Li, Chunmei; Lu, Sijia; Zhou, Wenxiong; Tang, Fuchou; Xie, X Sunney; Huang, Yanyi

    2015-09-22

    Whole-genome amplification (WGA) for next-generation sequencing has seen wide applications in biology and medicine when characterization of the genome of a single cell is required. High uniformity and fidelity of WGA is needed to accurately determine genomic variations, such as copy number variations (CNVs) and single-nucleotide variations (SNVs). Prevailing WGA methods have been limited by fluctuation of the amplification yield along the genome, as well as false-positive and -negative errors for SNV identification. Here, we report emulsion WGA (eWGA) to overcome these problems. We divide single-cell genomic DNA into a large number (10(5)) of picoliter aqueous droplets in oil. Containing only a few DNA fragments, each droplet is led to reach saturation of DNA amplification before demulsification such that the differences in amplification gain among the fragments are minimized. We demonstrate the proof-of-principle of eWGA with multiple displacement amplification (MDA), a popular WGA method. This easy-to-operate approach enables simultaneous detection of CNVs and SNVs in an individual human cell, exhibiting significantly improved amplification evenness and accuracy.

  9. Improving molecular diagnosis of aniridia and WAGR syndrome using customized targeted array-based CGH

    PubMed Central

    Vallespín, Elena; Villaverde, Cristina; Martín-Arenas, Rubén; Vélez-Monsalve, Camilo; Lorda-Sánchez, Isabel; Nevado, Julián; Trujillo-Tiebas, María José; Lapunzina, Pablo; Ayuso, Carmen; Corton, Marta

    2017-01-01

    Chromosomal deletions at 11p13 are a frequent cause of congenital Aniridia, a rare pan-ocular genetic disease, and of WAGR syndrome, accounting up to 30% of cases. First-tier genetic testing for newborn with aniridia, to detect 11p13 rearrangements, includes Multiplex Ligation-dependent Probe Amplification (MLPA) and karyotyping. However, neither of these approaches allow obtaining a complete picture of the high complexity of chromosomal deletions and breakpoints in aniridia. Here, we report the development and validation of a customized targeted array-based comparative genomic hybridization, so called WAGR-array, for comprehensive high-resolution analysis of CNV in the WAGR locus. Our approach increased the detection rate in a Spanish cohort of 38 patients with aniridia, WAGR syndrome and other related ocular malformations, allowing to characterize four undiagnosed aniridia cases, and to confirm MLPA findings in four additional patients. For all patients, breakpoints were accurately established and a contiguous deletion syndrome, involving a large number of genes, was identified in three patients. Moreover, we identified novel microdeletions affecting 3' PAX6 regulatory regions in three families with isolated aniridia. This tool represents a good strategy for the genetic diagnosis of aniridia and associated syndromes, allowing for a more accurate CNVs detection, as well as a better delineation of breakpoints. Our results underline the clinical importance of performing exhaustive and accurate analysis of chromosomal rearrangements for patients with aniridia, especially newborns and those without defects in PAX6 after diagnostic screening. PMID:28231309

  10. An accurate air temperature measurement system based on an envelope pulsed ultrasonic time-of-flight technique

    NASA Astrophysics Data System (ADS)

    Huang, Y. S.; Huang, Y. P.; Huang, K. N.; Young, M. S.

    2007-11-01

    A new microcomputer based air temperature measurement system is presented. An accurate temperature measurement is derived from the measurement of sound velocity by using an ultrasonic time-of-flight (TOF) technique. The study proposes a novel algorithm that combines both amplitude modulation (AM) and phase modulation (PM) to get the TOF measurement. The proposed system uses the AM and PM envelope square waveform (APESW) to reduce the error caused by inertia delay. The APESW ultrasonic driving waveform causes an envelope zero and phase inversion phenomenon in the relative waveform of the receiver. To accurately achieve a TOF measurement, the phase inversion phenomenon was used to sufficiently identify the measurement pulse in the received waveform. Additionally, a counter clock technique was combined to compute the phase shifts of the last incomplete cycle for TOF. The presented system can obtain 0.1% TOF resolution for the period corresponding to the 40kHz frequency ultrasonic wave. Consequently, with the integration of a humidity compensation algorithm, a highly accurate and high resolution temperature measurement can be achieved using the accurate TOF measurement. Experimental results indicate that the combined standard uncertainty of the temperature measurement is approximately 0.39°C. The main advantages of this system are high resolution measurements, narrow bandwidth requirements, and ease of implementation.

  11. 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.

  12. 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.

  13. 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.

  14. First imported Plasmodium ovale malaria in Central America: case report of a Guatemalan soldier and a call to improve its accurate diagnosis.

    PubMed

    Castellanos, María Eugenia; Díaz, Sheilee; Parsons, Emily; Peruski, Leonard F; Enríquez, Fabiola; Ramírez, Juan Luis; Padilla, Norma

    2015-01-01

    The Mesoamerican Ministers of Health have set 2020 as the target for malaria elimination to be achieved in the region. Imported malaria cases are a potential threat to countries attempting elimination or working to prevent resurgence. We report the first imported Plasmodium ovale infection with molecular confirmation in Central America, which occurred in a Guatemalan soldier that had been deployed in Africa. The obstacles for its diagnosis using the standard microscopy technique and the need to improve its detection are discussed.

  15. Application of the rank-based method to DNA methylation for cancer diagnosis.

    PubMed

    Li, Hongdong; Hong, Guini; Xu, Hui; Guo, Zheng

    2015-01-25

    Detecting aberrant DNA methylation as diagnostic or prognostic biomarkers for cancer has been a topic of considerable interest recently. However, current classifiers based on absolute methylation values detected from a cohort of samples are typically difficult to be transferable to other cohorts of samples. Here, focusing on relative methylation levels, we employed a modified rank-based method to extract reversal pairs of CpG sites whose relative methylation level orderings differ between disease samples and normal controls for cancer diagnosis. The reversal pairs identified for five cancer types respectively show excellent prediction performance with the accuracy above 95%. Furthermore, when evaluating the reversal pairs identified for one cancer type in an independent cohorts of samples, we found that they could distinguish different subtypes of this cancer or different malignant stages including early stage of this cancer from normal controls. The identified reversal pairs also appear to be specific to cancer type. In conclusion, the reversal pairs detected by the rank-based method could be used for accurate cancer diagnosis, which are transferable to independent cohorts of samples.

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

    PubMed

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

    2014-06-16

    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.

  17. 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

  18. 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

  19. "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…

  20. Compound fault diagnosis of gearboxes based on GFT component extraction

    NASA Astrophysics Data System (ADS)

    Ou, Lu; Yu, Dejie

    2016-11-01

    Compound fault diagnosis of gearboxes is of great importance to the long-term safe operation of rotating machines, and the key is to separate different fault components. In this paper, the path graph is introduced into the vibration signal analysis and the graph Fourier transform (GFT) of vibration signals are investigated from the graph spectrum domain. To better extract the fault components in gearboxes, a new adjacency weight matrix is defined and then the GFT of simulation signals of the gear and the bearing with localized faults are analyzed. Further, since the GFT graph spectrum of the gear fault component and the bearing fault component are mainly distributed in the low-order region and the high-order region, respectively, a novel method for the compound fault diagnosis of gearboxes based on GFT component extraction is proposed. In this method, the nonzero ratios, which are introduced to analyze the eigenvectors auxiliary, and the GFT of a gearbox vibration signal, are firstly calculated. Then, the order thresholds for reconstructed fault components are determined and the fault components are extracted. Finally, the Hilbert demodulation analyses are conducted. According to the envelope spectra of the fault components, the faults of the gear and the bearing can be diagnosed respectively. The performance of the proposed method is validated by the simulation data and the experiment signals from a gearbox with compound faults.

  1. 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.

  2. Blockage fault diagnosis method of combine harvester based on BPNN and DS evidence theory

    NASA Astrophysics Data System (ADS)

    Chen, Jin; Xu, Kai; Wang, Yifan; Wang, Kun; Wang, Shuqing

    2017-01-01

    According to the complexity and the lack of intelligent analysis method of combine harvester blockage fault , this paper puts forward a method , based on the combination of BP neural network (BPNN)and DS evidence theory , for combine harvester blockage fault diagnosis. Choosing cutting table auger, conveyer trough, threshing cylinder and grain conveying auger as the study, this paper divides the condition of combine harvester into four categories, namely, normal, slightly blocking, blockage, severe blockage, which being as an identification framework for DS evidence theory. BP neural network is used for analysing speed information of monitoring points and distributing basic probability for each proposition in the identification framework. Dempster combination rule converged information at different time to obtain diagnostic results.Test results show that this method can timely and accurately judge the work state of combine harvester, the blocking fault warning time will be increased to 2 seconds and the success probability of blocking fault warning reach more than 90%.

  3. A Rolling Element Bearing Fault Diagnosis Approach Based on Multifractal Theory and Gray Relation Theory

    PubMed Central

    Li, Jingchao; Cao, Yunpeng; Ying, Yulong; Li, Shuying

    2016-01-01

    Bearing failure is one of the dominant causes of failure and breakdowns in rotating machinery, leading to huge economic loss. Aiming at the nonstationary and nonlinear characteristics of bearing vibration signals as well as the complexity of condition-indicating information distribution in the signals, a novel rolling element bearing fault diagnosis method based on multifractal theory and gray relation theory was proposed in the paper. Firstly, a generalized multifractal dimension algorithm was developed to extract the characteristic vectors of fault features from the bearing vibration signals, which can offer more meaningful and distinguishing information reflecting different bearing health status in comparison with conventional single fractal dimension. After feature extraction by multifractal dimensions, an adaptive gray relation algorithm was applied to implement an automated bearing fault pattern recognition. The experimental results show that the proposed method can identify various bearing fault types as well as severities effectively and accurately. PMID:28036329

  4. Safety region estimation and fault diagnosis of wheels based on LSSVM and PNN

    NASA Astrophysics Data System (ADS)

    Cao, Kang; Sun, Fei; Xing, Zongyi

    2017-03-01

    A method based on Least Squares Support Vector Machine (LSSVM) and Probabilistic Neural Networks (PNN) was proposed to monitor wheels state of urban rail vehicle real-time and discover the wheels fault in time, which is used in safety region estimation and fault diagnosis of wheels. Firstly, the Intrinsic Mode Functions (IMF) can be obtained by using EMD on the track vibration signals generated by the SIMPACK, and features of each IMFs were extracted. Afterwards, LSSVM was adopted to estimate safety region of wheels service status. Finally, PNN was used to recognize the three states of wheel including normal wheel, wheel flat, out of round wheel. Experimental results show that the proposed method can identify wheel working state and fault type accurately and effectively.

  5. 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.

  6. A Rolling Element Bearing Fault Diagnosis Approach Based on Multifractal Theory and Gray Relation Theory.

    PubMed

    Li, Jingchao; Cao, Yunpeng; Ying, Yulong; Li, Shuying

    2016-01-01

    Bearing failure is one of the dominant causes of failure and breakdowns in rotating machinery, leading to huge economic loss. Aiming at the nonstationary and nonlinear characteristics of bearing vibration signals as well as the complexity of condition-indicating information distribution in the signals, a novel rolling element bearing fault diagnosis method based on multifractal theory and gray relation theory was proposed in the paper. Firstly, a generalized multifractal dimension algorithm was developed to extract the characteristic vectors of fault features from the bearing vibration signals, which can offer more meaningful and distinguishing information reflecting different bearing health status in comparison with conventional single fractal dimension. After feature extraction by multifractal dimensions, an adaptive gray relation algorithm was applied to implement an automated bearing fault pattern recognition. The experimental results show that the proposed method can identify various bearing fault types as well as severities effectively and accurately.

  7. NESmapper: accurate prediction of leucine-rich nuclear export signals using activity-based profiles.

    PubMed

    Kosugi, Shunichi; Yanagawa, Hiroshi; Terauchi, Ryohei; Tabata, Satoshi

    2014-09-01

    The nuclear export of proteins is regulated largely through the exportin/CRM1 pathway, which involves the specific recognition of leucine-rich nuclear export signals (NESs) in the cargo proteins, and modulates nuclear-cytoplasmic protein shuttling by antagonizing the nuclear import activity mediated by importins and the nuclear import signal (NLS). Although the prediction of NESs can help to define proteins that undergo regulated nuclear export, current methods of predicting NESs, including computational tools and consensus-sequence-based searches, have limited accuracy, especially in terms of their specificity. We found that each residue within an NES largely contributes independently and additively to the entire nuclear export activity. We created activity-based profiles of all classes of NESs with a comprehensive mutational analysis in mammalian cells. The profiles highlight a number of specific activity-affecting residues not only at the conserved hydrophobic positions but also in the linker and flanking regions. We then developed a computational tool, NESmapper, to predict NESs by using profiles that had been further optimized by training and combining the amino acid properties of the NES-flanking regions. This tool successfully reduced the considerable number of false positives, and the overall prediction accuracy was higher than that of other methods, including NESsential and Wregex. This profile-based prediction strategy is a reliable way to identify functional protein motifs. NESmapper is available at http://sourceforge.net/projects/nesmapper.

  8. Efficient and accurate optimal linear phase FIR filter design using opposition-based harmony search algorithm.

    PubMed

    Saha, S K; Dutta, R; Choudhury, R; Kar, R; Mandal, D; Ghoshal, S P

    2013-01-01

    In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. RGA, PSO, and DE have also been adopted for the sake of comparison. The original harmony search algorithm is chosen as the parent one, and opposition-based approach is applied. During the initialization, randomly generated population of solutions is chosen, opposite solutions are also considered, and the fitter one is selected as a priori guess. In harmony memory, each such solution passes through memory consideration rule, pitch adjustment rule, and then opposition-based reinitialization generation jumping, which gives the optimum result corresponding to the least error fitness in multidimensional search space of FIR filter design. Incorporation of different control parameters in the basic HS algorithm results in the balancing of exploration and exploitation of search space. Low pass, high pass, band pass, and band stop FIR filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems.

  9. [A new method of tremor diagnosis based on singular value decomposition of EMD].

    PubMed

    Ai, Lingmei; Wang, Jue

    2009-12-01

    Aiming at three kinds of tremor, including essential tremor (ET), Parkinsonian disease (PD) tremor and physiological tremor (PT), which are subjected to frequent clinical misdiagnosis, a new method based on singular value decomposition (SVD) of empirical mode decomposition (EMD) and support vector machine (SVM) for the recognition of tremor is proposed in this paper. First, the hand acceleration signals of three different types of 40 tremor voluntary subjects were collected on the basis of informed consent, and the EMD method was used to decompose the signals into a number of stationary intrinsic mode functions (IMFs). Then the preceding four IMFs which could describe signals were selected, and the initial feature vector matrixes were formed. After the application of SVD technique to the initial feature vector matrixes, the singular values were obtained and used as the feature vectors of tremor types to be put in the support vector machine classifier as well as in the identification of tremor types. The results of experiment have shown that the proposed diagnosis method based on SVD of EMD and SVM can extract tremor features effectively and identify tremor types accurately. It also provides a new assistant approach for clinical diagnosis of tremor.

  10. 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.

  11. A stationary wavelet entropy-based clustering approach accurately predicts gene expression.

    PubMed

    Nguyen, Nha; Vo, An; Choi, Inchan; Won, Kyoung-Jae

    2015-03-01

    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.

  12. Plantar fasciitis: evidence-based review of diagnosis and therapy.

    PubMed

    Cole, Charles; Seto, Craig; Gazewood, John

    2005-12-01

    Plantar fasciitis causes heel pain in active as well as sedentary adults of all ages. The condition is more likely to occur in persons who are obese or in those who are on their feet most of the day. A diagnosis of plantar fasciitis is based on the patient's history and physical findings. The accuracy of radiologic studies in diagnosing plantar heel pain is unknown. Most interventions used to manage plantar fasciitis have not been studied adequately; however, shoe inserts, stretching exercises, steroid injection, and custom-made night splints may be beneficial. Extracorporeal shock wave therapy may effectively treat runners with chronic heel pain but is ineffective in other patients. Limited evidence suggests that casting or surgery may be beneficial when conservative measures fail.

  13. 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.

  14. Accurate group velocity estimation for unmanned aerial vehicle-based acoustic atmospheric tomography.

    PubMed

    Rogers, Kevin J; Finn, Anthony

    2017-02-01

    Acoustic atmospheric tomography calculates temperature and wind velocity fields in a slice or volume of atmosphere based on travel time estimates between strategically located sources and receivers. The technique discussed in this paper uses the natural acoustic signature of an unmanned aerial vehicle as it overflies an array of microphones on the ground. The sound emitted by the aircraft is recorded on-board and by the ground microphones. The group velocities of the intersecting sound rays are then derived by comparing these measurements. Tomographic inversion is used to estimate the temperature and wind fields from the group velocity measurements. This paper describes a technique for deriving travel time (and hence group velocity) with an accuracy of 0.1% using these assets. This is shown to be sufficient to obtain highly plausible tomographic inversion results that correlate well with independent SODAR measurements.

  15. Novel wavelength-accurate InP-based arrayed waveguide grating

    NASA Astrophysics Data System (ADS)

    Pan, Pan; An, Jun-Ming; Wang, Hong-Jie; Wang, Yue; Zhang, Jia-Shun; Wang, Liang-Liang; Dai, Hong-Qing; Zhang, Xiao-Guang; Wu, Yuan-Da; Hu, Xiong-Wei

    2014-04-01

    A 13-channel, InP-based arrayed waveguide grating (AWG) is designed and fabricated in which the on-chip loss of the central channel is about -5 dB and the crosstalk is less than -23 dB in the center of the spectrum response. However, the central wavelength and channel spacing are deviated from the design values. To improve their accuracy, an optimized design is adopted to compensate the process error. As a result, the central wavelength 1549.9 nm and channel spacing 1.59 nm are obtained in the experiment, while their design values are 1549.32 nm and 1.6 nm, respectively. The route capability and thermo-optic characteristic of the AWG are also discussed in detail.

  16. 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

  17. Deterministic versus evidence-based attitude towards clinical diagnosis.

    PubMed

    Soltani, Akbar; Moayyeri, Alireza

    2007-08-01

    Generally, two basic classes have been proposed for scientific explanation of events. Deductive reasoning emphasizes on reaching conclusions about a hypothesis based on verification of universal laws pertinent to that hypothesis, while inductive or probabilistic reasoning explains an event by calculation of some probabilities for that event to be related to a given hypothesis. Although both types of reasoning are used in clinical practice, evidence-based medicine stresses on the advantages of the second approach for most instances in medical decision making. While 'probabilistic or evidence-based' reasoning seems to involve more mathematical formulas at the first look, this attitude is more dynamic and less imprisoned by the rigidity of mathematics comparing with 'deterministic or mathematical attitude'. In the field of medical diagnosis, appreciation of uncertainty in clinical encounters and utilization of likelihood ratio as measure of accuracy seem to be the most important characteristics of evidence-based doctors. Other characteristics include use of series of tests for refining probability, changing diagnostic thresholds considering external evidences and nature of the disease, and attention to confidence intervals to estimate uncertainty of research-derived parameters.

  18. Accurate Measurement of Brain Changes in Longitudinal MRI Scans using Tensor-Based Morphometry

    PubMed Central

    Hua, Xue; Gutman, Boris; Boyle, Christina; Rajagopalan, Priya; Leow, Alex D.; Yanovsky, Igor; Kumar, Anand R.; Toga, Arthur W.; Jack, Clifford R.; Schuff, Norbert; Alexander, Gene E.; Chen, Kewei; Reiman, Eric M.; Weiner, Michael W.; Thompson, Paul M.

    2011-01-01

    This paper responds to Thompson and Holland (2011), who challenged our tensor-based morphometry (TBM) method for estimating rates of brain changes in serial MRI from 431 subjects scanned every 6 months, for 2 years. Thompson and Holland noted an unexplained jump in our atrophy rate estimates: an offset between 0-6 months that may bias clinical trial power calculations. We identified why this jump occurs and propose a solution. By enforcing inverse-consistency in our TBM method, the offset dropped from 1.4% to 0.28%, giving plausible anatomical trajectories. Transitivity error accounted for the minimal remaining offset. Drug trial sample size estimates with the revised TBM-derived metrics are highly competitive with other methods, though higher than previously reported sample size estimates by a factor of 1.6 to 2.4. Importantly, estimates are far below those given in the critique. To demonstrate a 25% slowing of atrophic rates with 80% power, 62 AD and 129 MCI subjects would be required for a 2-year trial, and 91 AD and 192 MCI subjects for a 1-year trial. PMID:21320612

  19. [Extracting THz absorption coefficient spectrum based on accurate determination of sample thickness].

    PubMed

    Li, Zhi; Zhang, Zhao-hui; Zhao, Xiao-yan; Su, Hai-xia; Yan, Fang

    2012-04-01

    Extracting absorption spectrum in THz band is one of the important aspects in THz applications. Sample's absorption coefficient has a complex nonlinear relationship with its thickness. However, as it is not convenient to measure the thickness directly, absorption spectrum is usually determined incorrectly. Based on the method proposed by Duvillaret which was used to precisely determine the thickness of LiNbO3, the approach to measuring the absorption coefficient spectra of glutamine and histidine in frequency range from 0.3 to 2.6 THz(1 THz = 10(12) Hz) was improved in this paper. In order to validate the correctness of this absorption spectrum, we designed a series of experiments to compare the linearity of absorption coefficient belonging to one kind amino acid in different concentrations. The results indicate that as agreed by Lambert-Beer's Law, absorption coefficient spectrum of amino acid from the improved algorithm performs better linearity with its concentration than that from the common algorithm, which can be the basis of quantitative analysis in further researches.

  20. 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.

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

    PubMed Central

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

    2016-01-01

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

  2. Accurate alignment of functional EPI data to anatomical MRI using a physics-based distortion model.

    PubMed

    Studholme, C; Constable, R T; Duncan, J S

    2000-11-01

    Mapping of functional magnetic resonance imaging (fMRI) to conventional anatomical MRI is a valuable step in the interpretation of fMRI activations. One of the main limits on the accuracy of this alignment arises from differences in the geometric distortion induced by magnetic field inhomogeneity. This paper describes an approach to the registration of echo planar image (EPI) data to conventional anatomical images which takes into account this difference in geometric distortion. We make use of an additional spin echo EPI image and use the known signal conservation in spin echo distortion to derive a specialized multimodality nonrigid registration algorithm. We also examine a plausible modification using log-intensity evaluation of the criterion to provide increased sensitivity in areas of low EPI signal. A phantom-based imaging experiment is used to evaluate the behavior of the different criteria, comparing nonrigid displacement estimates to those provided by a imagnetic field mapping acquisition. The algorithm is then applied to a range of nine brain imaging studies illustrating global and local improvement in the anatomical alignment and localization of fMRI activations.

  3. 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.

  4. 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.

  5. β-human chorionic gonadotropin assay in vaginal washing fluid for the accurate diagnosis of premature rupture of membranes during late pregnancy

    PubMed Central

    Temel, Orhan; Çöğendez, Ebru; Selçuk, Selçuk; Asoğlu, Mehmet Reşit; Kaya, Erdal

    2013-01-01

    Objective To determine whether the measurement of beta-human chorionic gonadotropin (β-hCG) levels in vaginal fluid is useful for the diagnosis of premature rupture of membranes (PROM). Material and Methods A total of 92 pregnant women between 24 and 40 weeks gestation participated in this study. The patients with fluid leaking from the vagina were designated Group 1, the patients with no fluid leaking from the vagina were Group 2, and those with a suspicion of fluid leaking from the vagina were classified as Group 3. Irrigating the posterior vaginal fornix with 5 mL sterile saline was used to measure β-hCG levels of the patients. Receiver operator curve (ROC) analysis was used to determine the cut-off value for a positive diagnosis. Results The β-hCG levels of vaginal fluid were measured as 20.5±25.0 mIU/mL, 254.6±346.8 mIU/mL, and 74.3±100.8 mIU/mL in Group 1, Group 2, and Group 3, respectively. Vaginal β-hCG level was higher statistically significantly in Group 2 than Group 1 and 3 (p<0.001). 100 mIU/mL was accepted as a cut-off value by using the receiver operating characteristic curve. According to 100 mIU/mL, sensitivity, specificity, positive predictive and negative predictive values were calculated as 71.2, 100, 100, and 65.1%, respectively. Conclusion The study showed that the measurement of β-hCG level in vaginal washing fluid is an efficient and easy diagnostic test for predicting the amount of fluid leaking from the vagina. However, due to the low negative predictive value of the test, it would not be convenient in daily practice. PMID:24592106

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

    PubMed

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

    2015-07-07

    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.

  7. 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.

  8. 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).

  9. Home-based Diagnosis of Obstructive Sleep Apnea in an Urban Population

    PubMed Central

    Garg, Natasha; Rolle, Andrew J.; Lee, Todd A.; Prasad, Bharati

    2014-01-01

    Study Objectives: Home-based diagnosis of obstructive sleep apnea (OSA) with portable monitoring (PM) is increasingly utilized, but remains understudied in underserved and minority populations. We tested the feasibility of home PM in an urban population at risk for OSA compared to in-laboratory polysomnography (PSG) and examined patient preference with respect to home PM versus PSG. Methods: Randomized crossover study of home PM (WatchPAT200) and in-laboratory simultaneous PSG and PM in 75 urban African Americans with high pre-test probability of OSA, identified with the Berlin questionnaire. Results: Fifty-seven of 75 participants were women, average age 45 ± 11 years (mean ± SD), 35% with ≤ high school education, and 76% with annual household income < $50,000. Technical failure rates were 5.3% for home vs. 3.1% for in-laboratory PM. There was good agreement between apnea hypopnea index on PSG; AHIPSG and AHI on home PM (mean ± 2 SD of the differences = 0.64 ± 46.5 and intraclass correlation coefficient; ICC = 0.73). The areas under the curve for the receiver-operator characteristic curves for home PM were 0.90 for AHIPSG ≥ 5, 0.95 for AHIPSG ≥ 10, and 0.92 for AHIPSG ≥ 15. 62/75 (82%) participants preferred home over in-laboratory testing. Conclusions: Home PM for diagnosis of OSA in a high risk urban population is feasible, accurate, and preferred by patients. As home PM may improve access to care, the cost-effectiveness of this diagnostic strategy for OSA should be examined in underserved urban and rural populations. Clinical Trials Registration: ClinicalTrials.gov, identifier: NCT01997723 Citation: Garg N, Rolle AJ, Lee TA, Prasad B. Home-based diagnosis of obstructive sleep apnea in an urban population. J Clin Sleep Med 2014;10(8):879-885. PMID:25126034

  10. 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.

  11. A blood-based, 7-metabolite signature for the early diagnosis of Alzheimer's disease.

    PubMed

    Olazarán, Javier; Gil-de-Gómez, Luis; Rodríguez-Martín, Andrés; Valentí-Soler, Meritxell; Frades-Payo, Belén; Marín-Muñoz, Juan; Antúnez, Carmen; Frank-García, Ana; Acedo-Jiménez, Carmen; Morlán-Gracia, Lorenzo; Petidier-Torregrossa, Roberto; Guisasola, María Concepción; Bermejo-Pareja, Félix; Sánchez-Ferro, Álvaro; Pérez-Martínez, David A; Manzano-Palomo, Sagrario; Farquhar, Ruth; Rábano, Alberto; Calero, Miguel

    2015-01-01

    Accurate blood-based biomarkers of Alzheimer's disease (AD) could constitute simple, inexpensive, and non-invasive tools for the early diagnosis and treatment of this devastating neurodegenerative disease. We sought to develop a robust AD biomarker panel by identifying alterations in plasma metabolites that persist throughout the continuum of AD pathophysiology. Using a multicenter, cross-sectional study design, we based our analysis on metabolites whose levels were altered both in AD patients and in patients with amnestic mild cognitive impairment (aMCI), the earliest identifiable stage of AD. UPLC coupled to mass spectrometry was used to independently compare the levels of 495 plasma metabolites in aMCI (n = 58) and AD (n = 100) patients with those of normal cognition controls (NC, n = 93). Metabolite alterations common to both aMCI and AD patients were used to generate a logistic regression model that accurately distinguished AD from NC patients. The final panel consisted of seven metabolites: three amino acids (glutamic acid, alanine, and aspartic acid), one non-esterified fatty acid (22:6n-3, DHA), one bile acid (deoxycholic acid), one phosphatidylethanolamine [PE(36:4)], and one sphingomyelin [SM(39:1)]. Detailed analysis ruled out the influence of potential confounding variables, including comorbidities and treatments, on each of the seven biomarkers. The final model accurately distinguished AD from NC patients (AUC, 0.918). Importantly, the model also distinguished aMCI from NC patients (AUC, 0.826), indicating its potential diagnostic utility in early disease stages. These findings describe a sensitive biomarker panel that may facilitate the specific detection of early-stage AD through the analysis of plasma samples.

  12. Novel synthetic index-based adaptive stochastic resonance method and its application in bearing fault diagnosis

    NASA Astrophysics Data System (ADS)

    Zhou, Peng; Lu, Siliang; Liu, Fang; Liu, Yongbin; Li, Guihua; Zhao, Jiwen

    2017-03-01

    Stochastic resonance (SR), which is characterized by the fact that proper noise can be utilized to enhance weak periodic signals, has been widely applied in weak signal detection. SR is a nonlinear parameterized filter, and the output signal relies on the system parameters for the deterministic input signal. The most commonly used index for parameter tuning in the SR procedure is the signal-to-noise ratio (SNR). However, using the SNR index to evaluate the denoising effect of SR quantitatively is insufficient when the target signal frequency cannot be estimated accurately. To address this issue, six different indexes, namely, power spectral kurtosis of the SR output signal, correlation coefficient between the SR output and the original signal, peak SNR, structural similarity, root mean square error, and smoothness, are constructed in this study to measure the SR output quantitatively. These six quantitative indexes are fused into a new synthetic quantitative index (SQI) via a back propagation neural network to guide the adaptive parameter selection of the SR procedure. The index fusion procedure reduces the instability of each index and thus improves the robustness of parameter tuning. In addition, genetic algorithm is utilized to quickly select the optimal SR parameters. The efficiency of bearing fault diagnosis is thus further improved. The effectiveness and efficiency of the proposed SQI-based adaptive SR method for bearing fault diagnosis are verified through numerical and experiment analyses.

  13. Wavelet-synchronization methodology: a new approach for EEG-based diagnosis of ADHD.

    PubMed

    Ahmadlou, Mehran; Adeli, Hojjat

    2010-01-01

    A multi-paradigm methodology is presented for electroencephalogram (EEG) based diagnosis of Attention-Deficit/Hyperactivity Disorder (ADHD) through adroit integration of nonlinear science; wavelets, a signal processing technique; and neural networks, a pattern recognition technique. The selected nonlinear features are generalized synchronizations known as synchronization likelihoods (SL), both among all electrodes and among electrode pairs. The methodology consists of three parts: first detecting the more synchronized loci (group 1) and loci with more discriminative deficit connections (group 2). Using SLs among all electrodes, discriminative SLs in certain sub-bands are extracted. In part two, SLs are computed, not among all electrodes, but between loci of group 1 and loci of group 2 in all sub-bands and the band-limited EEG. This part leads to more accurate detection of deficit connections, and not just deficit areas, but more discriminative SLs in sub-bands with finer resolutions. In part three, a classification technique, radial basis function neural network, is used to distinguish ADHD from normal subjects. The methodology was applied to EEG data obtained from 47 ADHD and 7 control individuals with eyes closed. The Radial Basis Function (RBF) neural network classifier yielded a high accuracy of 95.6% for diagnosis of the ADHD in the feature space discovered in this research with a variance of 0.7%.

  14. 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.

  15. Photoacoustic-based nanomedicine for cancer diagnosis and therapy.

    PubMed

    Sim, Changbeom; Kim, Haemin; Moon, Hyungwon; Lee, Hohyeon; Chang, Jin Ho; Kim, Hyuncheol

    2015-04-10

    Photoacoustic imaging is the latest promising diagnostic modality that has various advantages such as high spatial resolution, deep penetration depth, and use of non-ionizing radiation. It also employs a non-invasive imaging technique and optically functionalized imaging. The goal of this study was to develop a nanomedicine for simultaneous cancer therapy and diagnosis based on photoacoustic imaging. Human serum albumin nanoparticles loaded with melanin and paclitaxel (HMP-NPs) were developed using the desolvation technique. The photoacoustic-based diagnostic and chemotherapeutic properties of HMP-NPs were evaluated through in vitro and in vivo experiments. The size and zeta potential of the HMP-NPs were found to be 192.8±21.11nm and -22.2±4.39mV, respectively. In in vitro experiments, HMP-NPs produced increased photoacoustic signal intensity because of the loaded melanin and decreased cellular viability because of the encapsulated paclitaxel, compared to the free human serum albumin nanoparticles (the control). In vivo experiments showed that the HMP-NPs efficiently accumulated inside the tumor, resulting in the enhanced photoacoustic signal intensity in the tumor site, compared to the normal tissues. The in vivo chemotherapy study demonstrated that HMP-NPs had the capability to treat cancer for an extended period. In conclusion, HMP-NPs were simultaneously capable of photoacoustic diagnostic and chemotherapy against cancer.

  16. Nonlinear Process Fault Diagnosis Based on Serial Principal Component Analysis.

    PubMed

    Deng, Xiaogang; Tian, Xuemin; Chen, Sheng; Harris, Chris J

    2016-12-22

    Many industrial processes contain both linear and nonlinear parts, and kernel principal component analysis (KPCA), widely used in nonlinear process monitoring, may not offer the most effective means for dealing with these nonlinear processes. This paper proposes a new hybrid linear-nonlinear statistical modeling approach for nonlinear process monitoring by closely integrating linear principal component analysis (PCA) and nonlinear KPCA using a serial model structure, which we refer to as serial PCA (SPCA). Specifically, PCA is first applied to extract PCs as linear features, and to decompose the data into the PC subspace and residual subspace (RS). Then, KPCA is performed in the RS to extract the nonlinear PCs as nonlinear features. Two monitoring statistics are constructed for fault detection, based on both the linear and nonlinear features extracted by the proposed SPCA. To effectively perform fault identification after a fault is detected, an SPCA similarity factor method is built for fault recognition, which fuses both the linear and nonlinear features. Unlike PCA and KPCA, the proposed method takes into account both linear and nonlinear PCs simultaneously, and therefore, it can better exploit the underlying process's structure to enhance fault diagnosis performance. Two case studies involving a simulated nonlinear process and the benchmark Tennessee Eastman process demonstrate that the proposed SPCA approach is more effective than the existing state-of-the-art approach based on KPCA alone, in terms of nonlinear process fault detection and identification.

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

    PubMed Central

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

    2016-01-01

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

  18. 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.

  19. 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.

  20. Optimal Resonant Band Demodulation Based on an Improved Correlated Kurtosis and Its Application in Bearing Fault Diagnosis.

    PubMed

    Chen, Xianglong; Zhang, Bingzhi; Feng, Fuzhou; Jiang, Pengcheng

    2017-02-13

    The kurtosis-based indexes are usually used to identify the optimal resonant frequency band. However, kurtosis can only describe the strength of transient impulses, which cannot differentiate impulse noises and repetitive transient impulses cyclically generated in bearing vibration signals. As a result, it may lead to inaccurate results in identifying resonant frequency bands, in demodulating fault features and hence in fault diagnosis. In view of those drawbacks, this manuscript redefines the correlated kurtosis based on kurtosis and auto-correlative function, puts forward an improved correlated kurtosis based on squared envelope spectrum of bearing vibration signals. Meanwhile, this manuscript proposes an optimal resonant band demodulation method, which can adaptively determine the optimal resonant frequency band and accurately demodulate transient fault features of rolling bearings, by combining the complex Morlet wavelet filter and the Particle Swarm Optimization algorithm. Analysis of both simulation data and experimental data reveal that the improved correlated kurtosis can effectively remedy the drawbacks of kurtosis-based indexes and the proposed optimal resonant band demodulation is more accurate in identifying the optimal central frequencies and bandwidth of resonant bands. Improved fault diagnosis results in experiment verified the validity and advantage of the proposed method over the traditional kurtosis-based indexes.

  1. Optimal Resonant Band Demodulation Based on an Improved Correlated Kurtosis and Its Application in Bearing Fault Diagnosis

    PubMed Central

    Chen, Xianglong; Zhang, Bingzhi; Feng, Fuzhou; Jiang, Pengcheng

    2017-01-01

    The kurtosis-based indexes are usually used to identify the optimal resonant frequency band. However, kurtosis can only describe the strength of transient impulses, which cannot differentiate impulse noises and repetitive transient impulses cyclically generated in bearing vibration signals. As a result, it may lead to inaccurate results in identifying resonant frequency bands, in demodulating fault features and hence in fault diagnosis. In view of those drawbacks, this manuscript redefines the correlated kurtosis based on kurtosis and auto-correlative function, puts forward an improved correlated kurtosis based on squared envelope spectrum of bearing vibration signals. Meanwhile, this manuscript proposes an optimal resonant band demodulation method, which can adaptively determine the optimal resonant frequency band and accurately demodulate transient fault features of rolling bearings, by combining the complex Morlet wavelet filter and the Particle Swarm Optimization algorithm. Analysis of both simulation data and experimental data reveal that the improved correlated kurtosis can effectively remedy the drawbacks of kurtosis-based indexes and the proposed optimal resonant band demodulation is more accurate in identifying the optimal central frequencies and bandwidth of resonant bands. Improved fault diagnosis results in experiment verified the validity and advantage of the proposed method over the traditional kurtosis-based indexes. PMID:28208820

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

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

    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.

  3. Optimal construction of a fast and accurate polarisable water potential based on multipole moments trained by machine learning.

    PubMed

    Handley, Chris M; Hawe, Glenn I; Kell, Douglas B; Popelier, Paul L A

    2009-08-14

    To model liquid water correctly and to reproduce its structural, dynamic and thermodynamic properties warrants models that account accurately for electronic polarisation. We have previously demonstrated that polarisation can be represented by fluctuating multipole moments (derived by quantum chemical topology) predicted by multilayer perceptrons (MLPs) in response to the local structure of the cluster. Here we further develop this methodology of modeling polarisation enabling control of the balance between accuracy, in terms of errors in Coulomb energy and computing time. First, the predictive ability and speed of two additional machine learning methods, radial basis function neural networks (RBFNN) and Kriging, are assessed with respect to our previous MLP based polarisable water models, for water dimer, trimer, tetramer, pentamer and hexamer clusters. Compared to MLPs, we find that RBFNNs achieve a 14-26% decrease in median Coulomb energy error, with a factor 2.5-3 slowdown in speed, whilst Kriging achieves a 40-67% decrease in median energy error with a 6.5-8.5 factor slowdown in speed. Then, these compromises between accuracy and speed are improved upon through a simple multi-objective optimisation to identify Pareto-optimal combinations. Compared to the Kriging results, combinations are found that are no less accurate (at the 90th energy error percentile), yet are 58% faster for the dimer, and 26% faster for the pentamer.

  4. Rapid and Accurate T2 Mapping from Multi Spin Echo Data Using Bloch-Simulation-Based Reconstruction

    PubMed Central

    Ben-Eliezer, Noam; Sodickson, Daniel K; Block, Tobias Kai

    2014-01-01

    Purpose Quantitative T2-relaxation-based contrast has the potential to provide valuable clinical information. Practical T2-mapping, however, is impaired either by prohibitively long acquisition times or by contamination of fast multi-echo protocols by stimulated and indirect echoes. This work presents a novel post-processing approach aiming to overcome the common penalties associated with multi-echo protocols, and enabling rapid and accurate mapping of T2 relaxation values. Methods Bloch simulations are used to estimate the actual echo modulation curve (EMC) in a multi spin-echo experiment. Simulations are repeated for a range of T2 values and transmit field scales, yielding a database of simulated EMCs, which is then used to identify the T2 value whose EMC most closely matches the experimentally measured data at each voxel. Results T2 maps of both phantom and in vivo scans were successfully reconstructed, closely matching maps produced from single spin-echo data. Results were consistent over the physiological range of T2 values and across different experimental settings. Conclusion The proposed technique allows accurate T2 mapping in clinically feasible scan times, free of user- and scanner-dependent variations, while providing a comprehensive framework that can be extended to model other parameters (e.g., T1, B1+, B0, diffusion) and support arbitrary acquisition schemes. PMID:24648387

  5. 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.

  6. Diagnosis of GLDAS LSM based aridity index and dryland identification.

    PubMed

    Ghazanfari, Sadegh; Pande, Saket; Hashemy, Mehdy; Sonneveld, Ben

    2013-04-15

    The identification of dryland areas is crucial for guiding policy aimed at intervening in water-stressed areas and addressing the perennial livelihood or food insecurity of these areas. However, the prevailing aridity indices (such as UNEP aridity index) have methodological limitations that restrict their use in delineating drylands and may be insufficient for decision-making frameworks. In this study, we propose a new aridity index based on based on 3 decades of soil moisture time series by accounting for site-specific soil and vegetation that partitions precipitation into the competing demands of evaporation and runoff. Our proposed aridity index is the frequency at which the dominant soil moisture value at a location is not exceeded by the dominant soil moisture values in all of the other locations. To represent the dominant spatial template of the soil moisture conditions, we extract the first eigenfunction from the empirical orthogonal function (EOF) analysis from 3 GLDAS land surface models (LSMs): VIC, MOSAIC and NOAH at 1 × 1 degree spatial resolution. The EOF analysis reveals that the first eigenfunction explains 33%, 43% and 47% of the VIC, NOAH and MOSAIC models, respectively. We compare each LSM aridity indices with the UNEP aridity index, which is created based on LSM data forcings. The VIC aridity index displays a pattern most closely resembling that of UNEP, although all of the LSM-based indices accurately isolate the dominant dryland areas. The UNEP classification identifies portions of south-central Africa, southeastern United States and eastern India as drier than predicted by all of the LSMs. The NOAH and MOSAIC LSMs categorize portions of southwestern Africa as drier than the other two classifications, while all of the LSMs classify portions of central India as wetter than the UNEP classification. We compare all aridity maps with the long-term average NDVI values. Results show that vegetation cover in areas that the UNEP index classifies as

  7. Empirical Mode Decomposition Based Features for Diagnosis and Prognostics of Systems

    DTIC Science & Technology

    2008-04-01

    bearing fault diagnosis – their effectiveness and flexibilities. Journal of Vibration and Acoustics July 2001, ASME. 3. Staszewski, W. J. Structural...Empirical Mode Decomposition Based Features for Diagnosis and Prognostics of Systems by Hiralal Khatri, Kenneth Ranney, Kwok Tom, and Romeo...Laboratory Adelphi, MD 20783-1197 ARL-TR-4301 April 2008 Empirical Mode Decomposition Based Features for Diagnosis and Prognostics of Systems

  8. 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.

  9. 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.

  10. 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.

  11. Evidence-based diagnosis and management of acute bronchitis.

    PubMed

    Hart, Ann Marie

    2014-09-18

    Acute bronchitis is a common respiratory infection seen in primary care settings. This article examines the current evidence for diagnosis and management of acute bronchitis in adults and provides recommendations for primary care clinical practice.

  12. 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.

  13. Accurate segmentation of partially overlapping cervical cells based on dynamic sparse contour searching and GVF snake model.

    PubMed

    Guan, Tao; Zhou, Dongxiang; Liu, Yunhui

    2015-07-01

    Overlapping cells segmentation is one of the challenging topics in medical image processing. In this paper, we propose to approximately represent the cell contour as a set of sparse contour points, which can be further partitioned into two parts: the strong contour points and the weak contour points. We consider the cell contour extraction as a contour points locating problem and propose an effective and robust framework for segmentation of partially overlapping cells in cervical smear images. First, the cell nucleus and the background are extracted by a morphological filtering-based K-means clustering algorithm. Second, a gradient decomposition-based edge enhancement method is developed for enhancing the true edges belonging to the center cell. Then, a dynamic sparse contour searching algorithm is proposed to gradually locate the weak contour points in the cell overlapping regions based on the strong contour points. This algorithm involves the least squares estimation and a dynamic searching principle, and is thus effective to cope with the cell overlapping problem. Using the located contour points, the Gradient Vector Flow Snake model is finally employed to extract the accurate cell contour. Experiments have been performed on two cervical smear image datasets containing both single cells and partially overlapping cells. The high accuracy of the cell contour extraction result validates the effectiveness of the proposed method.

  14. 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.

  15. 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

    2016-05-02

    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.

  16. 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

  17. 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

  18. Kurtosis based weighted sparse model with convex optimization technique for bearing fault diagnosis

    NASA Astrophysics Data System (ADS)

    Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Yan, Ruqiang

    2016-12-01

    The bearing failure, generating harmful vibrations, is one of the most frequent reasons for machine breakdowns. Thus, performing bearing fault diagnosis is an essential procedure to improve the reliability of the mechanical system and reduce its operating expenses. Most of the previous studies focused on rolling bearing fault diagnosis could be categorized into two main families, kurtosis-based filter method and wavelet-based shrinkage method. Although tremendous progresses have been made, their effectiveness suffers from three potential drawbacks: firstly, fault information is often decomposed into proximal frequency bands and results in impulsive feature frequency band splitting (IFFBS) phenomenon, which significantly degrades the performance of capturing the optimal information band; secondly, noise energy spreads throughout all frequency bins and contaminates fault information in the information band, especially under the heavy noisy circumstance; thirdly, wavelet coefficients are shrunk equally to satisfy the sparsity constraints and most of the feature information energy are thus eliminated unreasonably. Therefore, exploiting two pieces of prior information (i.e., one is that the coefficient sequences of fault information in the wavelet basis is sparse, and the other is that the kurtosis of the envelope spectrum could evaluate accurately the information capacity of rolling bearing faults), a novel weighted sparse model and its corresponding framework for bearing fault diagnosis is proposed in this paper, coined KurWSD. KurWSD formulates the prior information into weighted sparse regularization terms and then obtains a nonsmooth convex optimization problem. The alternating direction method of multipliers (ADMM) is sequentially employed to solve this problem and the fault information is extracted through the estimated wavelet coefficients. Compared with state-of-the-art methods, KurWSD overcomes the three drawbacks and utilizes the advantages of both family

  19. Pattern-Based Medical Diagnosis on a Microcomputer*

    PubMed Central

    Fisher, Paul R.; Kurlander, David J.

    1980-01-01

    A differential diagnosis microcomputer program has been written that utilizes both pattern-recognition and logical analysis in its algorithm. Together with auxilliary routines, the program (called DX) performs medical diagnosis, stores and retrieves patient information, creates new model symptom sets using information from the patient pool, and trains its own data matrices. Designed to be user oriented, DX can communicate the reasoning behind its decisions, thereby complementing the physician's own skills. This microcomputer system is geared towards community practices because the matrices are trained by statistics DX gathers from the local patient population. Although the program was written to be used in any area of medical practice, the arrays are presently being trained for the diagnosis of presentations of the acute abdomen.

  20. Comparing the standards of one metabolic equivalent of task in accurately estimating physical activity energy expenditure based on acceleration.

    PubMed

    Kim, Dohyun; Lee, Jongshill; Park, Hoon Ki; Jang, Dong Pyo; Song, Soohwa; Cho, Baek Hwan; Jung, Yoo-Suk; Park, Rae-Woong; Joo, Nam-Seok; Kim, In Young

    2016-08-24

    The purpose of the study is to analyse how the standard of resting metabolic rate (RMR) affects estimation of the metabolic equivalent of task (MET) using an accelerometer. In order to investigate the effect on estimation according to intensity of activity, comparisons were conducted between the 3.5 ml O2 · kg(-1) · min(-1) and individually measured resting VO2 as the standard of 1 MET. MET was estimated by linear regression equations that were derived through five-fold cross-validation using 2 types of MET values and accelerations; the accuracy of estimation was analysed through cross-validation, Bland and Altman plot, and one-way ANOVA test. There were no significant differences in the RMS error after cross-validation. However, the individual RMR-based estimations had as many as 0.5 METs of mean difference in modified Bland and Altman plots than RMR of 3.5 ml O2 · kg(-1) · min(-1). Finally, the results of an ANOVA test indicated that the individual RMR-based estimations had less significant differences between the reference and estimated values at each intensity of activity. In conclusion, the RMR standard is a factor that affects accurate estimation of METs by acceleration; therefore, RMR requires individual specification when it is used for estimation of METs using an accelerometer.

  1. 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.

  2. A highly accurate dynamic contact angle algorithm for drops on inclined surface based on ellipse-fitting.

    PubMed

    Xu, Z N; Wang, S Y

    2015-02-01

    To improve the accuracy in the calculation of dynamic contact angle for drops on the inclined surface, a significant number of numerical drop profiles on the inclined surface with different inclination angles, drop volumes, and contact angles are generated based on the finite difference method, a least-squares ellipse-fitting algorithm is used to calculate the dynamic contact angle. The influences of the above three factors are systematically investigated. The results reveal that the dynamic contact angle errors, including the errors of the left and right contact angles, evaluated by the ellipse-fitting algorithm tend to increase with inclination angle/drop volume/contact angle. If the drop volume and the solid substrate are fixed, the errors of the left and right contact angles increase with inclination angle. After performing a tremendous amount of computation, the critical dimensionless drop volumes corresponding to the critical contact angle error are obtained. Based on the values of the critical volumes, a highly accurate dynamic contact angle algorithm is proposed and fully validated. Within nearly the whole hydrophobicity range, it can decrease the dynamic contact angle error in the inclined plane method to less than a certain value even for different types of liquids.

  3. Accurate reconstruction of the optical parameter distribution in participating medium based on the frequency-domain radiative transfer equation

    NASA Astrophysics Data System (ADS)

    Qiao, Yao-Bin; Qi, Hong; Zhao, Fang-Zhou; Ruan, Li-Ming

    2016-12-01

    Reconstructing the distribution of optical parameters in the participating medium based on the frequency-domain radiative transfer equation (FD-RTE) to probe the internal structure of the medium is investigated in the present work. The forward model of FD-RTE is solved via the finite volume method (FVM). The regularization term formatted by the generalized Gaussian Markov random field model is used in the objective function to overcome the ill-posed nature of the inverse problem. The multi-start conjugate gradient (MCG) method is employed to search the minimum of the objective function and increase the efficiency of convergence. A modified adjoint differentiation technique using the collimated radiative intensity is developed to calculate the gradient of the objective function with respect to the optical parameters. All simulation results show that the proposed reconstruction algorithm based on FD-RTE can obtain the accurate distributions of absorption and scattering coefficients. The reconstructed images of the scattering coefficient have less errors than those of the absorption coefficient, which indicates the former are more suitable to probing the inner structure. Project supported by the National Natural Science Foundation of China (Grant No. 51476043), the Major National Scientific Instruments and Equipment Development Special Foundation of China (Grant No. 51327803), and the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No. 51121004).

  4. Accurate grading of brain gliomas by soft independent modeling of class analogy based on non-negative matrix factorization of proton magnetic resonance spectra.

    PubMed

    Ghasemi, K; Khanmohammadi, M; Saligheh Rad, H

    2016-02-01

    Hydrogen magnetic resonance spectroscopy ((1) H-MRS) is a non-invasive technique which provides a 'frequency-signal intensity' spectrum of biochemical compounds of tissues in the body. Although this method is currently used in human brain studies, accurate classification of in-vivo (1) H-MRS is a challenging task in the diagnosis of brain tumors. Problems such as overlapping metabolite peaks, incomplete information on background component and low signal-to-noise ratio disturb classification results of this spectroscopic method. This study presents an alternative approach to the soft independent modeling of class analogy (SIMCA) technique, using non-negative matrix factorization (NMF) for dimensionality reduction. In the adopted strategy, the performance of SIMCA was improved by application of a robust algorithm for classification in the presence of noisy measurements. Total of 219 spectra from two databases were taken by water-suppressed short echo-time (1) H-MRS, acquired from different subjects with different stages of glial brain tumors (Grade II (26 cases), grade III (24 cases), grade IV (41 cases), as well as 25 healthy cases). The SIMCA was performed using two approaches: (i) principal component analysis (PCA) and (ii) non-negative matrix factorization (NMF), as a modified approach. Square prediction error was considered to assess the class membership of the external validation set. Finally, several figures of merit such as the correct classification rate (CCR), sensitivity and specificity were calculated. Results of SIMCA based on NMF showed significant improvement in percentage of correctly classified samples, 91.4% versus 83.5% for PCA-based model in an independent test set.

  5. 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.

  6. 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

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

    PubMed Central

    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

  8. Computed tomography-based diagnosis of diffuse compensatory enlargement of coronary arteries using scaling power laws

    PubMed Central

    Huo, Yunlong; Choy, Jenny Susana; Wischgoll, Thomas; Luo, Tong; Teague, Shawn D.; Bhatt, Deepak L.; Kassab, Ghassan S.

    2013-01-01

    Glagov's positive remodelling in the early stages of coronary atherosclerosis often results in plaque rupture and acute events. Because positive remodelling is generally diffused along the epicardial coronary arterial tree, it is difficult to diagnose non-invasively. Hence, the objective of the study is to assess the use of scaling power law for the diagnosis of positive remodelling of coronary arteries based on computed tomography (CT) images. Epicardial coronary arterial trees were reconstructed from CT scans of six Ossabaw pigs fed on a high-fat, high-cholesterol, atherogenic diet for eight months as well as the same number of body-weight-matched farm pigs fed on a lean chow (101.9±16.1 versus 91.5±13.1 kg). The high-fat diet Ossabaw pig model showed diffuse positive remodelling of epicardial coronary arteries. Good fit of measured coronary data to the length–volume scaling power law ( where Lc and Vc are crown length and volume) were found for both the high-fat and control groups (R2 = 0.95±0.04 and 0.99±0.01, respectively). The coefficient, KLV, decreased significantly in the high-fat diet group when compared with the control (14.6±2.6 versus 40.9±5.6). The flow–length scaling power law, however, was nearly unaffected by the positive remodelling. The length–volume and flow–length scaling power laws were preserved in epicardial coronary arterial trees after positive remodelling. KLV < 18 in the length–volume scaling relation is a good index of positive remodelling of coronary arteries. These findings provide a clinical rationale for simple, accurate and non-invasive diagnosis of positive remodelling of coronary arteries, using conventional CT scans. PMID:23365197

  9. 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

  10. Accurate optical simulation of nano-particle based internal scattering layers for light outcoupling from organic light emitting diodes

    NASA Astrophysics Data System (ADS)

    Egel, Amos; Gomard, Guillaume; Kettlitz, Siegfried W.; Lemmer, Uli

    2017-02-01

    We present a numerical strategy for the accurate simulation of light extraction from organic light emitting diodes (OLEDs) comprising an internal nano-particle based scattering layer. On the one hand, the light emission and propagation through the OLED thin film system (including the scattering layer) is treated by means of rigorous wave optics calculations using the T-matrix formalism. On the other hand, the propagation through the substrate is modeled in a ray optics approach. The results from the wave optics calculations enter in terms of the initial substrate radiation pattern and the bidirectional reflectivity distribution of the OLED stack with scattering layer. In order to correct for the truncation error due to a finite number of particles in the simulations, we extrapolate the results to infinitely extended scattering layers. As an application example, we estimate the optimal particle filling fraction for an internal scattering layer in a realistic OLED geometry. The presented treatment is designed to emerge from electromagnetic theory with as few additional assumptions as possible. It could thus serve as a baseline to validate faster but approximate simulation approaches.

  11. Aptamer-conjugated live human immune cell based biosensors for the accurate detection of C-reactive protein

    PubMed Central

    Hwang, Jangsun; Seo, Youngmin; Jo, Yeonho; Son, Jaewoo; Choi, Jonghoon

    2016-01-01

    C-reactive protein (CRP) is a pentameric protein that is present in the bloodstream during inflammatory events, e.g., liver failure, leukemia, and/or bacterial infection. The level of CRP indicates the progress and prognosis of certain diseases; it is therefore necessary to measure CRP levels in the blood accurately. The normal concentration of CRP is reported to be 1–3 mg/L. Inflammatory events increase the level of CRP by up to 500 times; accordingly, CRP is a biomarker of acute inflammatory disease. In this study, we demonstrated the preparation of DNA aptamer-conjugated peripheral blood mononuclear cells (Apt-PBMCs) that specifically capture human CRP. Live PBMCs functionalized with aptamers could detect different levels of human CRP by producing immune complexes with reporter antibody. The binding behavior of Apt-PBMCs toward highly concentrated CRP sites was also investigated. The immune responses of Apt-PBMCs were evaluated by measuring TNF-alpha secretion after stimulating the PBMCs with lipopolysaccharides. In summary, engineered Apt-PBMCs have potential applications as live cell based biosensors and for in vitro tracing of CRP secretion sites. PMID:27708384

  12. 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.

  13. Aptamer-conjugated live human immune cell based biosensors for the accurate detection of C-reactive protein

    NASA Astrophysics Data System (ADS)

    Hwang, Jangsun; Seo, Youngmin; Jo, Yeonho; Son, Jaewoo; Choi, Jonghoon

    2016-10-01

    C-reactive protein (CRP) is a pentameric protein that is present in the bloodstream during inflammatory events, e.g., liver failure, leukemia, and/or bacterial infection. The level of CRP indicates the progress and prognosis of certain diseases; it is therefore necessary to measure CRP levels in the blood accurately. The normal concentration of CRP is reported to be 1–3 mg/L. Inflammatory events increase the level of CRP by up to 500 times; accordingly, CRP is a biomarker of acute inflammatory disease. In this study, we demonstrated the preparation of DNA aptamer-conjugated peripheral blood mononuclear cells (Apt-PBMCs) that specifically capture human CRP. Live PBMCs functionalized with aptamers could detect different levels of human CRP by producing immune complexes with reporter antibody. The binding behavior of Apt-PBMCs toward highly concentrated CRP sites was also investigated. The immune responses of Apt-PBMCs were evaluated by measuring TNF-alpha secretion after stimulating the PBMCs with lipopolysaccharides. In summary, engineered Apt-PBMCs have potential applications as live cell based biosensors and for in vitro tracing of CRP secretion sites.

  14. 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

  15. Smartphone-based multispectral imaging: system development and potential for mobile skin diagnosis

    PubMed Central

    Kim, Sewoong; Cho, Dongrae; Kim, Jihun; Kim, Manjae; Youn, Sangyeon; Jang, Jae Eun; Je, Minkyu; Lee, Dong Hun; Lee, Boreom; Farkas, Daniel L.; Hwang, Jae Youn

    2016-01-01

    We investigate the potential of mobile smartphone-based multispectral imaging for the quantitative diagnosis and management of skin lesions. Recently, various mobile devices such as a smartphone have emerged as healthcare tools. They have been applied for the early diagnosis of nonmalignant and malignant skin diseases. Particularly, when they are combined with an advanced optical imaging technique such as multispectral imaging and analysis, it would be beneficial for the early diagnosis of such skin diseases and for further quantitative prognosis monitoring after treatment at home. Thus, we demonstrate here the development of a smartphone-based multispectral imaging system with high portability and its potential for mobile skin diagnosis. The results suggest that smartphone-based multispectral imaging and analysis has great potential as a healthcare tool for quantitative mobile skin diagnosis. PMID:28018743

  16. Smartphone-based multispectral imaging: system development and potential for mobile skin diagnosis.

    PubMed

    Kim, Sewoong; Cho, Dongrae; Kim, Jihun; Kim, Manjae; Youn, Sangyeon; Jang, Jae Eun; Je, Minkyu; Lee, Dong Hun; Lee, Boreom; Farkas, Daniel L; Hwang, Jae Youn

    2016-12-01

    We investigate the potential of mobile smartphone-based multispectral imaging for the quantitative diagnosis and management of skin lesions. Recently, various mobile devices such as a smartphone have emerged as healthcare tools. They have been applied for the early diagnosis of nonmalignant and malignant skin diseases. Particularly, when they are combined with an advanced optical imaging technique such as multispectral imaging and analysis, it would be beneficial for the early diagnosis of such skin diseases and for further quantitative prognosis monitoring after treatment at home. Thus, we demonstrate here the development of a smartphone-based multispectral imaging system with high portability and its potential for mobile skin diagnosis. The results suggest that smartphone-based multispectral imaging and analysis has great potential as a healthcare tool for quantitative mobile skin diagnosis.

  17. 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

  18. 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.

  19. 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.

  20. Development of a Ground-Based Differential Absorption Lidar for High Accurate Measurements of Vertical CO2 Concentration Profiles

    NASA Astrophysics Data System (ADS)

    Nagasawa, Chikao; Abo, Makoto; Shibata, Yasukuni; Nagai, Tomohiro; Nakazato, Masahisa; Sakai, Tetsu; Tsukamoto, Makoto; Sakaizawa, Daisuku

    2010-05-01

    High-accurate vertical carbon dioxide (CO2) profiles are highly desirable in the inverse method to improve quantification and understanding of the global sink and source of CO2, and also global climate change. We have developed a ground based 1.6μm differential absorption lidar (DIAL) to achieve high accurate measurements of vertical CO2 profiles in the atmosphere. The DIAL system is constructed from the optical parametric oscillation(OPO) transmitter and the direct detection receiving system that included a near-infrared photomultiplier tube operating at photon counting mode. The primitive DIAL measurement was achieved successfully the vertical CO2 profile up to 7 km altitude with an error less than 1.0 % by integration time of 50 minutes and vertical resolution of 150m. We are developing the next generation 1.6 μm DIAL that can measure simultaneously the vertical CO2 concentration, temperature and pressure profiles in the atmosphere. The output laser of the OPO is 20mJ at a 500 Hz repetition rate and a 600mm diameter telescope is employed for this measurement. A very narrow interference filter (0.5nm FWHM) is used for daytime measurement. As the spectra of absorption lines of any molecules are influenced basically by the temperature and pressure in the atmosphere, it is important to measure them simultaneously so that the better accuracy of the DIAL measurement may be realized. Moreover, the value of the retrieved CO2 concentration will be improved remarkably by processing the iteration assignment of CO2 concentration, temperature and pressure, which measured by DIAL techniques. This work was financially supported by the Japan EOS Promotion Program by the MEXT Japan and System Development Program for Advanced Measurement and Analysis by the JST. Reference D. Sakaizawa, C. Nagasawa, T. Nagai, M. Abo, Y. Shibata, H. Nagai, M. Nakazato, and T. Sakai, Development of a 1.6μm differential absorption lidar with a quasi-phase-matching optical parametric oscillator and

  1. Development of Ground-Based DIAL Techniques for High Accurate Measurements of CO2 Concentration Profiles in the Atmosphere

    NASA Astrophysics Data System (ADS)

    Nagasawa, C.; Abo, M.; Shibata, Y.; Nagai, T.; Nakazato, M.; Sakai, T.; Tsukamoto, M.; Sakaizawa, D.

    2009-12-01

    High-accurate vertical carbon dioxide (CO2) profiles are highly desirable in the inverse method to improve quantification and understanding of the global sink and source of CO2, and also global climate change. We have developed a ground based 1.6μm differential absorption lidar (DIAL) to achieve high accurate measurements of vertical CO2 profiles in the atmosphere. The DIAL system is constructed from the optical parametric oscillation(OPO) transmitter and the direct detection receiving system that included a near-infrared photomultiplier tube operating at photon counting mode (Fig.1). The primitive DIAL measurement was achieved successfully the vertical CO2 profile up to 7 km altitude with an error less than 1.0 % by integration time of 50 minutes and vertical resolution of 150m. We develop the next generation 1.6 μm DIAL that can measure simultaneously the vertical CO2 concentration, temperature and pressure profiles in the atmosphere. The characteristics of the 1.6 μm DIALs of the primitive and next generations are shown in Table 1. As the spectra of absorption lines of any molecules are influenced basically by the temperature and pressure in the atmosphere, it is important to measure them simultaneously so that the better accuracy of the DIAL measurement may be realized. Moreover, the value of the retrieved CO2 concentration will be improved remarkably by processing the iteration assignment of CO2 concentration, temperature and pressure which measured by DIAL techniques. This work was financially supported by the Japan EOS Promotion Program by the MEXT Japan and System Development Program for Advanced Measurement and Analysis by the JST. Reference D. Sakaisawa et al., Development of a 1.6μm differential absorption lidar with a quasi-phase-matching optical parametric oscillator and photon-counting detector for the vertical CO2 profile, Applied Optics, Vol.48, No.4, pp.748-757, 2009. Fig. 1 Experimental setup of the 1.6 μm CO2 DIAL. Comparison of primitive

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. Prediction and diagnosis of renal cell carcinoma using nuclear magnetic resonance-based serum metabolomics and self-organizing maps

    PubMed Central

    Zheng, Hong; Ji, Jiansong; Zhao, Liangcai; Chen, Minjiang; Shi, An; Pan, Linlin; Huang, Yiran; Zhang, Huajie; Dong, Baijun; Gao, Hongchang

    2016-01-01

    Diagnosis of renal cell carcinoma (RCC) at an early stage is challenging, but it provides the best chance for cure. We aimed to develop a predictive diagnostic method for early-stage RCC based on a biomarker cluster using nuclear magnetic resonance (NMR)-based serum metabolomics and self-organizing maps (SOMs). We trained and validated the SOM model using serum metabolome data from 104 participants, including healthy individuals and early-stage RCC patients. To assess the predictive capability of the model, we analyzed an independent cohort of 22 subjects. We then used our method to evaluate changes in the metabolic patterns of 23 RCC patients before and after nephrectomy. A biomarker cluster of 7 metabolites (alanine, creatine, choline, isoleucine, lactate, leucine, and valine) was identified for the early diagnosis of RCC. The trained SOM model using a biomarker cluster was able to classify 22 test subjects into the appropriate categories. Following nephrectomy, all RCC patients were classified as healthy, which was indicative of metabolic recovery. But using a diagnostic criterion of 0.80, only 3 of the 23 subjects could not be confidently assessed as metabolically recovered after nephrectomy. We successfully followed-up 17 RCC patients for 8 years post-nephrectomy. Eleven of these patients who diagnosed as metabolic recovery remained healthy after 8 years. Our data suggest that a SOM model using a biomarker cluster from serum metabolome can accurately predict early RCC diagnosis and can be used to evaluate postoperative metabolic recovery. PMID:27463020

  7. Analyzing reliability of seizure diagnosis based on semiology.

    PubMed

    Jin, Bo; Wu, Han; Xu, Jiahui; Yan, Jianwei; Ding, Yao; Wang, Z Irene; Guo, Yi; Wang, Zhongjin; Shen, Chunhong; Chen, Zhong; Ding, Meiping; Wang, Shuang

    2014-12-01

    This study aimed to determine the accuracy of seizure diagnosis by semiological analysis and to assess the factors that affect diagnostic reliability. A total of 150 video clips of seizures from 50 patients (each with three seizures of the same type) were observed by eight epileptologists, 12 neurologists, and 20 physicians (internists). The videos included 37 series of epileptic seizures, eight series of physiologic nonepileptic events (PNEEs), and five series of psychogenic nonepileptic seizures (PNESs). After observing each video, the doctors chose the diagnosis of epileptic seizures or nonepileptic events for the patient; if the latter was chosen, they further chose the diagnosis of PNESs or PNEEs. The overall diagnostic accuracy rate for epileptic seizures and nonepileptic events increased from 0.614 to 0.660 after observations of all three seizures (p < 0.001). The diagnostic sensitivity and specificity of epileptic seizures were 0.770 and 0.808, respectively, for the epileptologists. These values were significantly higher than those for the neurologists (0.660 and 0.699) and physicians (0.588 and 0.658). A wide range of diagnostic accuracy was found across the various seizures types. An accuracy rate of 0.895 for generalized tonic-clonic seizures was the highest, followed by 0.800 for dialeptic seizures and then 0.760 for automotor seizures. The accuracy rates for myoclonic seizures (0.530), hypermotor seizures (0.481), gelastic/dacrystic seizures (0.438), and PNESs (0.430) were poor. The reliability of semiological diagnosis of seizures is greatly affected by the seizure type as well as the doctor's experience. Although the overall reliability is limited, it can be improved by observing more seizures.

  8. Design and Diagnosis Problem Solving with Multifunctional Technical Knowledge Bases

    DTIC Science & Technology

    1992-09-29

    Causal I ordering theory (Iwasaki & Simon 86) is used to reveal causal dependencies among variables in a set of equations and produce a graph...Knowledge in Device Design .......................................................... 145 QP is More Than SPQR and Dynamical Systems Theory : Response to...SThe concept of abduction has been used to frame the problem of diagnosis, scientific theory formation, natural language understanding, and is a more

  9. Non-invasive diagnosis of papillary thyroid microcarcinoma: a NMR-based metabolomics approach

    PubMed Central

    Lu, Jinghui; Hu, Sanyuan; Miccoli, Paolo; Zeng, Qingdong; Liu, Shaozhuang; Ran, Lin; Hu, Chunxiao

    2016-01-01

    Papillary thyroid microcarcinoma (PTMC) is a subtype of papillary thyroid carcinoma (PTC). Because its diameter is less than 10 mm, diagnosing it accurately is difficult with traditional methods such as image examinations and FNA (Fine Needle Aspiration). Investigating the metabolic changes induced by PTMC may enhance the understanding of its pathogenesis and provide important information for a new diagnosis method and treatment plan. In this study, high resolution magic angle spin (HRMAS) spectroscopy and 1H-nuclear magnetic resonance (1H-NMR) spectroscopy were used to screen metabolic changes in thyroid tissues and plasma from PTMC patients respectively. The results revealed reduced levels of fatty acids and elevated levels of several amino acids (phenylalanine, tyrosine, lactate, serine, cystine, lysine, glutamine/glutamate, taurine, leucine, alanine, isoleucine and valine) in thyroid tissues, as well as reduced levels of amino acids such as valine, tyrosine, proline, lysine, leucine and elevated levels of glucose, mannose, pyruvate and 3-hydroxybutyrate in plasma, are involved in the metabolic alterations in PTMC. In addition, a receiver operating characteristic (ROC) curve model for PTMC prediction was able to classify cases with good sensitivity and specificity using 9 significant changed metabolites in plasma. This work illustrates that the NMR-based metabolomics approach is capable of providing more sensitive diagnostic results and more systematic therapeutic information for PTMC. PMID:27835583

  10. Development of a FPGA based fuzzy neural network system for early diagnosis of critical health condition of a patient.

    PubMed

    Chowdhury, Shubhajit Roy; Saha, Hiranmay

    2010-02-01

    The paper describes the design and training of a fuzzy neural network used for early diagnosis of a patient through an FPGA based implementation of a smart instrument. The system employs a fuzzy interface cascaded with a feed-forward neural network. In order to obtain an optimum decision regarding the future pathophysiological state of a patient, the optimal weights of the synapses between the neurons have been determined by using inverse delayed function model of neurons. The neurons that are considered in the proposed network are devoid of self connections instead of commonly used self connected neurons. The current work also find out the optimal number of neurons in the hidden layer for accurate diagnosis as against the available number of CLB in the FPGA. The system has been trained and tested with renal data of patients taken at 10 days interval of time. Applying the methodology, the chance of attainment of critical renal condition of a patient has been predicted with an accuracy of 95.2%, 30 days ahead of actually attaining the critical condition. The system has also been tested for pathophysiological state prediction of patients at multiple time steps ahead and the prediction at the next instant of time stands out to be the most accurate.

  11. Rolling bearing fault detection and diagnosis based on composite multiscale fuzzy entropy and ensemble support vector machines

    NASA Astrophysics Data System (ADS)

    Zheng, Jinde; Pan, Haiyang; Cheng, Junsheng

    2017-02-01

    To timely detect the incipient failure of rolling bearing and find out the accurate fault location, a novel rolling bearing fault diagnosis method is proposed based on the composite multiscale fuzzy entropy (CMFE) and ensemble support vector machines (ESVMs). Fuzzy entropy (FuzzyEn), as an improvement of sample entropy (SampEn), is a new nonlinear method for measuring the complexity of time series. Since FuzzyEn (or SampEn) in single scale can not reflect the complexity effectively, multiscale fuzzy entropy (MFE) is developed by defining the FuzzyEns of coarse-grained time series, which represents the system dynamics in different scales. However, the MFE values will be affected by the data length, especially when the data are not long enough. By combining information of multiple coarse-grained time series in the same scale, the CMFE algorithm is proposed in this paper to enhance MFE, as well as FuzzyEn. Compared with MFE, with the increasing of scale factor, CMFE obtains much more stable and consistent values for a short-term time series. In this paper CMFE is employed to measure the complexity of vibration signals of rolling bearings and is applied to extract the nonlinear features hidden in the vibration signals. Also the physically meanings of CMFE being suitable for rolling bearing fault diagnosis are explored. Based on these, to fulfill an automatic fault diagnosis, the ensemble SVMs based multi-classifier is constructed for the intelligent classification of fault features. Finally, the proposed fault diagnosis method of rolling bearing is applied to experimental data analysis and the results indicate that the proposed method could effectively distinguish different fault categories and severities of rolling bearings.

  12. Fault detection and diagnosis based on modeling and estimation methods.

    PubMed

    Huang, Sunan; Tan, Kok Kiong

    2009-05-01

    This paper investigates the problem of fault detection and diagnosis in a class of nonlinear systems with modeling uncertainties. A nonlinear observer is first designed for monitoring fault. Radial basis function (RBF) neural network is used in this observer to approximate the unknown nonlinear dynamics. When a fault occurs, another RBF is triggered to capture the nonlinear characteristics of the fault function. The fault model obtained by the second neural network (NN) can be used for identifying the failure mode by comparing it with any known failure modes. Finally, a simulation example is presented to illustrate the effectiveness of the proposed scheme.

  13. Epilepsy: current evidence-based paradigms for diagnosis and treatment.

    PubMed

    Bates, Kimberly

    2015-06-01

    Although epilepsy has a prevalence of 5 to 7 per 1000 persons in the United States, it continues to be a poorly understood condition. Given the number of patients in the United States with epilepsy, it is very likely that primary care physicians will continue to provide care for these patients. This article refreshes some of the knowledge around the diagnosis of epilepsy, discusses special populations that may require additional management considerations, highlights the association of epilepsy with multiple comorbidities, and discusses antiepileptic drug (AED) treatment, including issues surrounding adherence and safety of AED therapy.

  14. 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.

  15. Fault diagnosis algorithm based on switching function for boost converters

    NASA Astrophysics Data System (ADS)

    Cho, H.-K.; Kwak, S.-S.; Lee, S.-H.

    2015-07-01

    A fault diagnosis algorithm, which is necessary for constructing a reliable power conversion system, should detect fault occurrences as soon as possible to protect the entire system from fatal damages resulting from system malfunction. In this paper, a fault diagnosis algorithm is proposed to detect open- and short-circuit faults that occur in a boost converter switch. The inductor voltage is abnormally kept at a positive DC value during a short-circuit fault in the switch or at a negative DC value during an open-circuit fault condition until the inductor current becomes zero. By employing these abnormal properties during faulty conditions, the inductor voltage is compared with the switching function to detect each fault type by generating fault alarms when a fault occurs. As a result, from the fault alarm, a decision is made in response to the fault occurrence and the fault type in less than two switching time periods using the proposed algorithm constructed in analogue circuits. In addition, the proposed algorithm has good resistivity to discontinuous current-mode operation. As a result, this algorithm features the advantages of low cost and simplicity because of its simple analogue circuit configuration.

  16. 2D nanomaterials based electrochemical biosensors for cancer diagnosis.

    PubMed

    Wang, Lu; Xiong, Qirong; Xiao, Fei; Duan, Hongwei

    2017-03-15

    Cancer is a leading cause of death in the world. Increasing evidence has demonstrated that early diagnosis holds the key towards effective treatment outcome. Cancer biomarkers are extensively used in oncology for cancer diagnosis and prognosis. Electrochemical sensors play key roles in current laboratory and clinical analysis of diverse chemical and biological targets. Recent development of functional nanomaterials offers new possibilities of improving the performance of electrochemical sensors. In particular, 2D nanomaterials have stimulated intense research due to their unique array of structural and chemical properties. The 2D materials of interest cover broadly across graphene, graphene derivatives (i.e., graphene oxide and reduced graphene oxide), and graphene-like nanomaterials (i.e., 2D layered transition metal dichalcogenides, graphite carbon nitride and boron nitride nanomaterials). In this review, we summarize recent advances in the synthesis of 2D nanomaterials and their applications in electrochemical biosensing of cancer biomarkers (nucleic acids, proteins and some small molecules), and present a personal perspective on the future direction of this area.

  17. 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 ...

  18. 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.

  19. 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.

  20. Malfunction diagnosis of sensors based on correlation of measurements

    NASA Astrophysics Data System (ADS)

    Lu, Wei; Teng, Jun; Wen, Runfa; Zhu, Jiayi; Li, Chao

    2017-02-01

    Structural health monitoring (SHM) is a type of on-site characterization of a real-world full-scale structure that is subjected to the real-world load cases. The fundamental element of SHM is the structural response measurements by sensors, the reliability of which is significant for safety assessment and other SHM applications. The paper proposed a method to diagnosis the fault in sensors using the correlation of measurements. The correlation of the variations of the measurements is examined using the sliding time windows, which is the principle to determine the fault in the sensors. The strain measurements from the SHM system of a real world structure, Shenzhen Bay Stadium, are performed to simulate the faults in sensors and to verify the effectiveness of the proposed method.

  1. 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.

  2. 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.

  3. Paper-based point-of-care testing for diagnosis of dengue infections.

    PubMed

    Choi, Jane Ru; Hu, Jie; Wang, ShuQi; Yang, Hui; Wan Abas, Wan Abu Bakar; Pingguan-Murphy, Belinda; Xu, Feng

    2017-02-01

    Dengue endemic is a serious healthcare concern in tropical and subtropical countries. Although well-established laboratory tests can provide early diagnosis of acute dengue infections, access to these tests is limited in developing countries, presenting an urgent need to develop simple, rapid, and robust diagnostic tools. Point-of-care (POC) devices, particularly paper-based POC devices, are typically rapid, cost-effective and user-friendly, and they can be used as diagnostic tools for the prompt diagnosis of dengue at POC settings. Here, we review the importance of rapid dengue diagnosis, current dengue diagnostic methods, and the development of paper-based POC devices for diagnosis of dengue infections at the POC.

  4. 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.

  5. Development of an accurate EPID-based output measurement and dosimetric verification tool for electron beam therapy

    PubMed Central

    Ding, Aiping; Xing, Lei; Han, Bin

    2015-01-01

    chamber measurements. The average discrepancy between EPID and ion chamber/film measurements was 0.81% ± 0.60% (SD) and 1.34% ± 0.75%, respectively. For the three clinical cases, the difference in output between the EPID- and ion chamber array measured values was found to be 1.13% ± 0.11%, 0.54% ± 0.10%, and 0.74% ± 0.11%, respectively. Furthermore, the γ-index analysis showed an excellent agreement between the EPID- and ion chamber array measured dose distributions: 100% of the pixels passed the criteria of 3%/3 mm. When the γ-index was set to be 2%/2 mm, the pass rate was found to be 99.0% ± 0.07%, 98.2% ± 0.14%, and 100% for the three cases. Conclusions: The EPID dosimetry system developed in this work provides an accurate and reliable tool for routine output measurement and dosimetric verification of electron beam therapy. Coupled with its portability and ease of use, the proposed system promises to replace the current film-based approach for fast and reliable assessment of small and irregular electron field dosimetry. PMID:26133618

  6. 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.

  7. 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

  8. Accurate recapture identification for genetic mark-recapture studies with error-tolerant likelihood-based match calling and sample clustering.

    PubMed

    Sethi, Suresh A; Linden, Daniel; Wenburg, John; Lewis, Cara; Lemons, Patrick; Fuller, Angela; Hare, Matthew P

    2016-12-01

    Error-tolerant likelihood-based match calling presents a promising technique to accurately identify recapture events in genetic mark-recapture studies by combining probabilities of latent genotypes and probabilities of observed genotypes, which may contain genotyping errors. Combined with clustering algorithms to group samples into sets of recaptures based upon pairwise match calls, these tools can be used to reconstruct accurate capture histories for mark-recapture modelling. Here, we assess the performance of a recently introduced error-tolerant likelihood-based match-calling model and sample clustering algorithm for genetic mark-recapture studies. We assessed both biallelic (i.e. single nucleotide polymorphisms; SNP) and multiallelic (i.e. microsatellite; MSAT) markers using a combination of simulation analyses and case study data on Pacific walrus (Odobenus rosmarus divergens) and fishers (Pekania pennanti). A novel two-stage clustering approach is demonstrated for genetic mark-recapture applications. First, repeat captures within a sampling occasion are identified. Subsequently, recaptures across sampling occasions are identified. The likelihood-based matching protocol performed well in simulation trials, demonstrating utility for use in a wide range of genetic mark-recapture studies. Moderately sized SNP (64+) and MSAT (10-15) panels produced accurate match calls for recaptures and accurate non-match calls for samples from closely related individuals in the face of low to moderate genotyping error. Furthermore, matching performance remained stable or increased as the number of genetic markers increased, genotyping error notwithstanding.

  9. Accurate recapture identification for genetic mark–recapture studies with error-tolerant likelihood-based match calling and sample clustering

    PubMed Central

    Linden, Daniel; Wenburg, John; Lewis, Cara; Lemons, Patrick; Fuller, Angela; Hare, Matthew P.

    2016-01-01

    Error-tolerant likelihood-based match calling presents a promising technique to accurately identify recapture events in genetic mark–recapture studies by combining probabilities of latent genotypes and probabilities of observed genotypes, which may contain genotyping errors. Combined with clustering algorithms to group samples into sets of recaptures based upon pairwise match calls, these tools can be used to reconstruct accurate capture histories for mark–recapture modelling. Here, we assess the performance of a recently introduced error-tolerant likelihood-based match-calling model and sample clustering algorithm for genetic mark–recapture studies. We assessed both biallelic (i.e. single nucleotide polymorphisms; SNP) and multiallelic (i.e. microsatellite; MSAT) markers using a combination of simulation analyses and case study data on Pacific walrus (Odobenus rosmarus divergens) and fishers (Pekania pennanti). A novel two-stage clustering approach is demonstrated for genetic mark–recapture applications. First, repeat captures within a sampling occasion are identified. Subsequently, recaptures across sampling occasions are identified. The likelihood-based matching protocol performed well in simulation trials, demonstrating utility for use in a wide range of genetic mark–recapture studies. Moderately sized SNP (64+) and MSAT (10–15) panels produced accurate match calls for recaptures and accurate non-match calls for samples from closely related individuals in the face of low to moderate genotyping error. Furthermore, matching performance remained stable or increased as the number of genetic markers increased, genotyping error notwithstanding. PMID:28083094

  10. 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

  11. Functional protease profiling for laboratory based diagnosis of invasive aspergillosis.

    PubMed

    Sabbagh, Bassel; Costina, Victor; Buchheidt, Dieter; Reinwald, Mark; Neumaier, Michael; Findeisen, Peter

    2015-07-01

    Invasive aspergillosis (IA) remains difficult to diagnose in immunocompromised patients, because diagnostic criteria according to EORTC/MSG guidelines are often not met and have low sensitivity. Hence there is an urgent need to improve diagnostic procedures by developing novel approaches. In the present study, we present a proof of concept experiment for the monitoring of Aspergillus associated protease activity in serum specimens for diagnostic purpose. Synthetic peptides that are selectively cleaved by proteases secreted from Aspergillus species were selected from our own experiments and published data. These so called reporter peptides (RP, n=5) were added to serum specimens from healthy controls (HC, n=101) and patients with proven (IA, n=9) and possible (PIA, n=144) invasive aspergillosis. Spiked samples were incubated ex vivo under strictly standardized conditions. Proteolytic fragments were analyzed using MALDI-TOF mass spectrometry. Spiked specimens of IA patients had highest concentrations of RP-fragments followed by PIA and HC. The median signal intensity was 116.546 (SD, 53.063) for IA and 5.009 (SD, 8.432) for HC. A cut-off >36.910 was chosen that performed with 100% specificity and sensitivity. Patients with PIA had either values above [53% (76/144)] or below [47% (67/144)] this chosen cut-off. The detection of respective reporter peptide fragments can easily be performed by MALDI TOF mass spectrometry. In this proof of concept study we were able to demonstrate that serum specimens of patients with IA have increased proteolytic activity towards selected reporter peptides. However, the diagnostic value of functional protease profiling has to be validated in further prospective studies. It is likely that a combination of existing and new methods will be required to achieve optimal performance for diagnosis of IA in the future.

  12. 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.

  13. NMF-Based Analysis of SPECT Brain Images for the Diagnosis of Alzheimer's Disease

    NASA Astrophysics Data System (ADS)

    Padilla, Pablo; Górriz, Juan-Manuel; Ramírez, Javier; Lang, Elmar; Chaves, Rosa; Segovia, Fermin; Álvarez, Ignacio; Salas-González, Diego; López, Miriam

    This paper offers a computer-aided diagnosis (CAD) technique for early diagnosis of Alzheimer's disease (AD) by means of single photon emission computed tomography (SPECT) image classification. The SPECT database for different patients is analyzed by applying the Fisher discriminant ratio (FDR) and non-negative matrix factorization (NMF) for the selection and extraction of the most significative features of each patient SPECT data, in order to reduce the large dimensionality of the input data and the problem of the curse of dimensionality, extracting score features. The NMF-transformed set of data, with reduced number of features, is classified by means of support vector machines (SVM) classification. The proposed NMF+SVM method yields up to 94% classification accuracy, thus becoming an accurate method for SPECT image classification. For the sake of completeness, comparison between conventional PCA+SVM method and the proposed method is also provided.

  14. [Diagnosis and treatment of heparin-induced thrombocytopenia (HIT) based on its atypical immunological features].

    PubMed

    Miyata, Shigeki; Maeda, Takuma

    2016-03-01

    Heparin-induced thrombocytopenia (HIT) is a prothrombotic side effect of heparin therapy caused by HIT antibodies, i.e., anti-platelet factor 4 (PF4)/heparin IgG with platelet-activating properties. For serological diagnosis, antigen immunoassays are commonly used worldwide. However, such assays do not indicate their platelet-activating properties, leading to low specificity for the HIT diagnosis. Therefore, over-diagnosis is currently the most serious problem associated with HIT. The detection of platelet-activating antibodies using a washed platelet activation assay is crucial for appropriate HIT diagnosis. Recent advances in our understanding of the pathogenesis of HIT include it having several clinical features atypical for an immune-mediated disease. Heparin-naïve patients can develop IgG antibodies as early as day 4, as in a secondary immune response. Evidence for an anamnestic response on heparin re-exposure is lacking. In addition, HIT antibodies are relatively short-lived, unlike those in a secondary immune response. These lines of evidence suggest that the mechanisms underlying HIT antibody formation may be compatible with a non-T cell-dependent immune reaction. These atypical clinical and serological features should be carefully considered while endeavoring to accurately diagnose HIT, which leads to appropriate therapies such as immediate administration of an alternative anticoagulant to prevent thromboembolic events and re-administration of heparin during surgery involving cardiopulmonary bypass when HIT antibodies are no longer detectable.

  15. NMF-SVM based CAD tool applied to functional brain images for the diagnosis of Alzheimer's disease.

    PubMed

    Padilla, P; López, M; Górriz, J M; Ramírez, J; Salas-González, D; Álvarez, I

    2012-02-01

    This paper presents a novel computer-aided diagnosis (CAD) technique for the early diagnosis of the Alzheimer's disease (AD) based on nonnegative matrix factorization (NMF) and support vector machines (SVM) with bounds of confidence. The CAD tool is designed for the study and classification of functional brain images. For this purpose, two different brain image databases are selected: a single photon emission computed tomography (SPECT) database and positron emission tomography (PET) images, both of them containing data for both Alzheimer's disease (AD) patients and healthy controls as a reference. These databases are analyzed by applying the Fisher discriminant ratio (FDR) and nonnegative matrix factorization (NMF) for feature selection and extraction of the most relevant features. The resulting NMF-transformed sets of data, which contain a reduced number of features, are classified by means of a SVM-based classifier with bounds of confidence for decision. The proposed NMF-SVM method yields up to 91% classification accuracy with high sensitivity and specificity rates (upper than 90%). This NMF-SVM CAD tool becomes an accurate method for SPECT and PET AD image classification.

  16. Analysis of SPECT brain images for the diagnosis of Alzheimer's disease based on NMF for feature extraction.

    PubMed

    Padilla, P; Górriz, J M; Ramírez, J; Lang, E W; Chaves, R; Segovia, F; López, M; Salas-González, D; Alvarez, I

    2010-08-02

    This letter presents a novel computer-aided diagnosis (CAD) technique for the early diagnosis of Alzheimer's disease (AD) based on non-negative matrix factorization (NMF) analysis applied to single photon emission computed tomography (SPECT) images. A baseline normalized SPECT database containing normalized data for both AD patients and healthy reference patients is selected for this study. The SPECT database is analyzed by applying the Fisher discriminant ratio (FDR) for feature selection and NMF for feature extraction of relevant components of each subject. The main goal of these preprocessing steps is to reduce the large dimensionality of the input data and to relieve the so called "curse of dimensionality" problem. The resulting NMF-transformed set of data, which contains a reduced number of features, is classified by means of a support vector machines based classification technique (SVM). The proposed NMF + SVM method yields up to 94% classification accuracy, with high sensitivity and specificity values (upper than 90%), becoming an accurate method for SPECT image classification. For the sake of completeness, comparison between another recently developed principal component analysis (PCA) plus SVM method and the proposed method is also provided, yielding results for the NMF + SVM approach that outperform the behavior of the reference PCA + SVM or conventional voxel-as-feature (VAF) plus SVM methods.

  17. [Diagnosis "risk of pneumonia" evidence-based evaluation and comparison of nursing interventions].

    PubMed

    Haslinger-Baumann, Elisabeth; Burns, Evelin

    2007-12-01

    In home nursing care, professionally qualified nurses make decisions on their own which must be based on the latest scientific research. The goal of this systematic literature review was to examine if the interventions of the diagnosis "Risk of Pneumonia" as used by a home care service provider in Austria are based on scientific evidence. Based on the research question "Can the interventions of the diagnosis 'risk of pneumonia' be found in the scientific nursing literature?", four evidence-based guidelines from various databases and institutes were identified and evaluated using a standardized checklist. The result of the analysis is that the majority of the Nursing diagnosis interventions can be found in the guidelines. It is also recommended in the guidelines to advise and support clients to stop smoking and inoculate against influenza/pneumonia. Similarly, assessment tools should be used to estimate the severity of pneumonia. The intervention of oral hygiene as a prophylactic intervention against pneumonia should get particular attention.

  18. Accurate lithography hotspot detection based on principal component analysis-support vector machine classifier with hierarchical data clustering

    NASA Astrophysics Data System (ADS)

    Yu, Bei; Gao, Jhih-Rong; Ding, Duo; Zeng, Xuan; Pan, David Z.

    2015-01-01

    As technology nodes continue to shrink, layout patterns become more sensitive to lithography processes, resulting in lithography hotspots that need to be identified and eliminated during physical verification. We propose an accurate hotspot detection approach based on principal component analysis-support vector machine classifier. Several techniques, including hierarchical data clustering, data balancing, and multilevel training, are provided to enhance the performance of the proposed approach. Our approach is accurate and more efficient than conventional time-consuming lithography simulation and provides a high flexibility for adapting to new lithography processes and rules.

  19. 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

  20. 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.

  1. BTeam, a Novel BRET-based Biosensor for the Accurate Quantification of ATP Concentration within Living Cells

    PubMed Central

    Yoshida, Tomoki; Kakizuka, Akira; Imamura, Hiromi

    2016-01-01

    ATP levels may represent fundamental health conditions of cells. However, precise measurement of intracellular ATP levels in living cells is hindered by the lack of suitable methodologies. Here, we developed a novel ATP biosensor termed “BTeam”. BTeam comprises a yellow fluorescent protein (YFP), the ATP binding domain of the ε subunit of the bacterial ATP synthase, and an ATP-nonconsuming luciferase (NLuc). To attain emission, BTeam simply required NLuc substrate. BTeam showed elevated bioluminescence resonance energy transfer efficiency upon ATP binding, resulted in the emission spectra changes correlating with ATP concentrations. By using values of YFP/NLuc emission ratio to represent ATP levels, BTeam achieved steady signal outputs even though emission intensities were altered. With this biosensor, we succeeded in the accurate quantification of intracellular ATP concentrations of a population of living cells, as demonstrated by detecting the slight distribution in the cytosol (3.7–4.1 mM) and mitochondrial matrix (2.4–2.7 mM) within some cultured cell lines. Furthermore, BTeam allowed continuous tracing of cytosolic ATP levels of the same cells, as well as bioluminescent imaging of cytosolic ATP dynamics within individual cells. This simple and accurate technique should be an effective method for quantitative measurement of intracellular ATP concentrations. PMID:28000761

  2. 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.

  3. A repeat protein-based DNA polymerase inhibitor for an efficient and accurate gene amplification by PCR.

    PubMed

    Hwang, Da-Eun; Shin, Yong-Keol; Munashingha, Palinda Ruvan; Park, So-Yeon; Seo, Yeon-Soo; Kim, Hak-Sung

    2016-12-01

    A polymerase chain reaction (PCR) using a thermostable DNA polymerase is the most widely applied method in many areas of research, including life sciences, biotechnology, and medical sciences. However, a conventional PCR incurs an amplification of undesired genes mainly owing to non-specifically annealed primers and the formation of a primer-dimer complex. Herein, we present the development of a Taq DNA polymerase-specific repebody, which is a small-sized protein binder composed of leucine rich repeat (LRR) modules, as a thermolabile inhibitor for a precise and accurate gene amplification by PCR. We selected a repebody that specifically binds to the DNA polymerase through a phage display, and increased its affinity to up to 10 nM through a modular evolution approach. The repebody was shown to effectively inhibit DNA polymerase activity at low temperature and undergo thermal denaturation at high temperature, leading to a rapid and full recovery of the polymerase activity, during the initial denaturation step of the PCR. The performance and utility of the repebody was demonstrated through an accurate and efficient amplification of a target gene without nonspecific gene products in both conventional and real-time PCRs. The repebody is expected to be effectively utilized as a thermolabile inhibitor in a PCR. Biotechnol. Bioeng. 2016;113: 2544-2552. © 2016 Wiley Periodicals, Inc.

  4. 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.

  5. 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

    2016-08-22

    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.

  6. Fault Diagnosis Strategies for SOFC-Based Power Generation Plants

    PubMed Central

    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

  7. Physically based diagnosis and prognosis of cracked rotor shafts

    NASA Astrophysics Data System (ADS)

    Oppenheimer, Charles H.; Loparo, Kenneth A.

    2002-07-01

    A physics-based approach for diagnostics and prognostics using integrated observers and life models is presented. Observers are filters based on physical models of machine- fault combinations and use measured machine signatures to identify and characterize the state of a machine. Observers are adaptively deployed as a machine wears and can be coupled with one another to handle interacting conditions and faults. The scheme is detailed using the fault of a cracked rotor shaft that interacts with gravity and imbalance. Observers for shaft cracking and imbalance are presented. The observers provide machine condition and fault strengths to life models used to determine remaining machine life. A life model based on the Forman crack growth law of linear elastic fracture mechanics is developed to determine the number of machine cycles remaining until catastrophic failure.

  8. Hyperspectral image-based analysis of weathering sensitivity for safety diagnosis of Seongsan Ilchulbong Peak

    NASA Astrophysics Data System (ADS)

    Kim, Sungho; Kim, Heekang

    2016-10-01

    This paper presents a weathering sensitivity analysis method for the safety diagnosis of Seongsan Ilchulbong Peak using hyperspectral images. Remote sensing-based safety diagnosis is important for preventing accidents in famous mountains. A hyperspectral correlation-based method is proposed to evaluate the weathering sensitivity. The three issues are how to reduce the illumination effect, how to remove camera motion while acquiring images on a boat, and how to define the weathering sensitivity index. A novel minimum subtraction and maximum normalization (MSM-norm) method is proposed to solve the shadow and specular illumination problem. Geometrically distorted hyperspectral images are corrected by estimating the borderline of the mountain and sea surface. The final issue is solved by proposing a weathering sensitivity index (WS-Index) based on a spectral angle mapper. Real experiments on the Seongsan Ilchulbong Peak (UNESCO, World Natural Heritage) highlighted the feasibility of the proposed method in safety diagnosis by the weathering sensitivity index.

  9. FY90 Based Cost Models to Support Diagnosis Related Management

    DTIC Science & Technology

    1992-08-04

    models presented here were based upon the final model formhs selected for use with the FY88 data. With the exception of identifying outlying fa- cilities...CENTER EXPENSE MODELS ARMY ALV SASER IC NONCLINICIAN EXPENSES 2 1 4 7 CLINICIAN EXPENSES 6 4 6 16 AMBULATORY EXPENSES 0 2 4 6 TOTAL EXPENSES* 1 0 2 3

  10. Fast and accurate auto-focusing algorithm based on the combination of depth from focus and improved depth from defocus.

    PubMed

    Zhang, Xuedian; Liu, Zhaoqing; Jiang, Minshan; Chang, Min

    2014-12-15

    An auto-focus method for digital imaging systems is proposed that combines depth from focus (DFF) and improved depth from defocus (DFD). The traditional DFD method is improved to become more rapid, which achieves a fast initial focus. The defocus distance is first calculated by the improved DFD method. The result is then used as a search step in the searching stage of the DFF method. A dynamic focusing scheme is designed for the control software, which is able to eliminate environmental disturbances and other noises so that a fast and accurate focus can be achieved. An experiment is designed to verify the proposed focusing method and the results show that the method's efficiency is at least 3-5 times higher than that of the traditional DFF method.

  11. 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

  12. Sensor-based diagnosis using knowledge of structure and function

    NASA Technical Reports Server (NTRS)

    Scarl, Ethan A.; Jamieson, John R.; Delaune, Carl I.

    1987-01-01

    A system for fault detection and isolation called LES, developed at the Kennedy Space Center for the Space Shuttle's Launch Processing System, is a well-developed diagnostic system that is simultaneously model-based and sensor-based. This experiment has led to a surprising result: the failure of a sensor can not only be handled in precisely the same way as the failure of any other object, but may present an especially easy case. Classical rule-based diagnostic systems need to find out whether or not their sensors are telling them the truth before they can safely draw inferences from them. By contrast, while LES does treat sensors as a special case, it does so only because there may exist a short cut that allows them to be handled more simply than other objects. LES uses both structural and functional knowledge, and has found cases in which the structural knowledge can be economically replaced by the judicious use of functional relationships; LES' functional relationships are stored in exactly one place, so they must be inverted to determine hypothetical values for possibly faulty objects. The inversion process has been extended to include conditional functions not normally considered to have inverses.

  13. 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.

  14. 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.

  15. 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.

  16. Decision tree and PCA-based fault diagnosis of rotating machinery

    NASA Astrophysics Data System (ADS)

    Sun, Weixiang; Chen, Jin; Li, Jiaqing

    2007-04-01

    After analysing the flaws of conventional fault diagnosis methods, data mining technology is introduced to fault diagnosis field, and a new method based on C4.5 decision tree and principal component analysis (PCA) is proposed. In this method, PCA is used to reduce features after data collection, preprocessing and feature extraction. Then, C4.5 is trained by using the samples to generate a decision tree model with diagnosis knowledge. At last the tree model is used to make diagnosis analysis. To validate the method proposed, six kinds of running states (normal or without any defect, unbalance, rotor radial rub, oil whirl, shaft crack and a simultaneous state of unbalance and radial rub), are simulated on Bently Rotor Kit RK4 to test C4.5 and PCA-based method and back-propagation neural network (BPNN). The result shows that C4.5 and PCA-based diagnosis method has higher accuracy and needs less training time than BPNN.

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. A Dynamic Integrated Fault Diagnosis Method for Power Transformers

    PubMed Central

    Gao, Wensheng; 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

  3. 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

  4. 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

  5. [Active crop canopy sensor-based nitrogen diagnosis for potato].

    PubMed

    Yu, Jing; Li, Fei; Qin, Yong-Lin; Fan, Ming-Shou

    2013-11-01

    In the present study, two potato experiments involving different N rates in 2011 were conducted in Wuchuan County and Linxi County, Inner Mongolia. Normalized difference vegetation index (NDVI) was collected by an active GreenSeeker crop canopy sensor to estimate N status of potato. The results show that the NDVI readings were poorly correlated with N nutrient indicators of potato at vegetative Growth stage due to the influence of soil background. With the advance of growth stages, NDVI values were exponentially related to plant N uptake (R2 = 0.665) before tuber bulking stage and were linearly related to plant N concentration (R2 = 0.699) when plant fully covered soil. In conclusion, GreenSeeker active crop sensor is a promising tool to estimate N status for potato plants. The findings from this study may be useful for developing N recommendation method based on active crop canopy sensor.

  6. Infrared thermography based on artificial intelligence as a screening method for carpal tunnel syndrome diagnosis.

    PubMed

    Jesensek Papez, B; Palfy, M; Mertik, M; Turk, Z

    2009-01-01

    This study further evaluated a computer-based infrared thermography (IRT) system, which employs artificial neural networks for the diagnosis of carpal tunnel syndrome (CTS) using a large database of 502 thermal images of the dorsal and palmar side of 132 healthy and 119 pathological hands. It confirmed the hypothesis that the dorsal side of the hand is of greater importance than the palmar side when diagnosing CTS thermographically. Using this method it was possible correctly to classify 72.2% of all hands (healthy and pathological) based on dorsal images and > 80% of hands when only severely affected and healthy hands were considered. Compared with the gold standard electromyographic diagnosis of CTS, IRT cannot be recommended as an adequate diagnostic tool when exact severity level diagnosis is required, however we conclude that IRT could be used as a screening tool for severe cases in populations with high ergonomic risk factors of CTS.

  7. Wavelet-based EEG processing for computer-aided seizure detection and epilepsy diagnosis.

    PubMed

    Faust, Oliver; Acharya, U Rajendra; Adeli, Hojjat; Adeli, Amir

    2015-03-01

    Electroencephalography (EEG) is an important tool for studying the human brain activity and epileptic processes in particular. EEG signals provide important information about epileptogenic networks that must be analyzed and understood before the initiation of therapeutic procedures. Very small variations in EEG signals depict a definite type of brain abnormality. The challenge is to design and develop signal processing algorithms which extract this subtle information and use it for diagnosis, monitoring and treatment of patients with epilepsy. This paper presents a review of wavelet techniques for computer-aided seizure detection and epilepsy diagnosis with an emphasis on research reported during the past decade. A multiparadigm approach based on the integration of wavelets, nonlinear dynamics and chaos theory, and neural networks advanced by Adeli and associates is the most effective method for automated EEG-based diagnosis of epilepsy.

  8. 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.

  9. Intelligent Gearbox Diagnosis Methods Based on SVM, Wavelet Lifting and RBR

    PubMed Central

    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

  10. Novel blood-based microRNA biomarker panel for early diagnosis of chronic pancreatitis

    PubMed Central

    Xin, Lei; Gao, Jun; Wang, Dan; Lin, Jin-Huan; Liao, Zhuan; Ji, Jun-Tao; Du, Ting-Ting; Jiang, Fei; Hu, Liang-Hao; Li, Zhao-Shen

    2017-01-01

    Chronic pancreatitis (CP) is an inflammatory disease characterized by progressive fibrosis of pancreas. Early diagnosis will improve the prognosis of patients. This study aimed to obtain serum miRNA biomarkers for early diagnosis of CP. In the current study, we analyzed the differentially expressed miRNAs (DEmiRs) of CP patients from Gene Expression Omnibus (GEO), and the DEmiRs in plasma of early CP patients (n = 10) from clinic by miRNA microarrays. Expression levels of DEmiRs were further tested in clinical samples including early CP patients (n = 20), late CP patients (n = 20) and healthy controls (n = 18). The primary endpoints were area under curve (AUC) and expression levels of DEmiRs. Four DEmiRs (hsa-miR-320a-d) were obtained from GEO CP, meanwhile two (hsa-miR-221 and hsa-miR-130a) were identified as distinct biomarkers of early CP by miRNA microarrays. When applied on clinical serum samples, hsa-miR-320a-d were accurate in predicting late CP, while hsa-miR-221 and hsa-miR-130a were accurate in predicting early CP with AUC of 100.0% and 87.5%. Our study indicates that miRNA expression profile is different in early and late CP. Hsa-miR-221 and hsa-miR-130a are biomarkers of early CP, and the panel of the above 6 serum miRNAs has the potential to be applied clinically for early diagnosis of CP. PMID:28074846

  11. Fault Diagnosis for Rotating Machinery: A Method based on Image Processing

    PubMed Central

    Lu, Chen; Wang, Yang; Ragulskis, Minvydas; Cheng, Yujie

    2016-01-01

    Rotating machinery is one of the most typical types of mechanical equipment and plays a significant role in industrial applications. Condition monitoring and fault diagnosis of rotating machinery has gained wide attention for its significance in preventing catastrophic accident and guaranteeing sufficient maintenance. With the development of science and technology, fault diagnosis methods based on multi-disciplines are becoming the focus in the field of fault diagnosis of rotating machinery. This paper presents a multi-discipline method based on image-processing for fault diagnosis of rotating machinery. Different from traditional analysis method in one-dimensional space, this study employs computing method in the field of image processing to realize automatic feature extraction and fault diagnosis in a two-dimensional space. The proposed method mainly includes the following steps. First, the vibration signal is transformed into a bi-spectrum contour map utilizing bi-spectrum technology, which provides a basis for the following image-based feature extraction. Then, an emerging approach in the field of image processing for feature extraction, speeded-up robust features, is employed to automatically exact fault features from the transformed bi-spectrum contour map and finally form a high-dimensional feature vector. To reduce the dimensionality of the feature vector, thus highlighting main fault features and reducing subsequent computing resources, t-Distributed Stochastic Neighbor Embedding is adopt to reduce the dimensionality of the feature vector. At last, probabilistic neural network is introduced for fault identification. Two typical rotating machinery, axial piston hydraulic pump and self-priming centrifugal pumps, are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method based on image-processing achieves a high accuracy, thus providing a highly effective means to fault diagnosis for rotating machinery. PMID

  12. Fault Diagnosis for Rotating Machinery: A Method based on Image Processing.

    PubMed

    Lu, Chen; Wang, Yang; Ragulskis, Minvydas; Cheng, Yujie

    2016-01-01

    Rotating machinery is one of the most typical types of mechanical equipment and plays a significant role in industrial applications. Condition monitoring and fault diagnosis of rotating machinery has gained wide attention for its significance in preventing catastrophic accident and guaranteeing sufficient maintenance. With the development of science and technology, fault diagnosis methods based on multi-disciplines are becoming the focus in the field of fault diagnosis of rotating machinery. This paper presents a multi-discipline method based on image-processing for fault diagnosis of rotating machinery. Different from traditional analysis method in one-dimensional space, this study employs computing method in the field of image processing to realize automatic feature extraction and fault diagnosis in a two-dimensional space. The proposed method mainly includes the following steps. First, the vibration signal is transformed into a bi-spectrum contour map utilizing bi-spectrum technology, which provides a basis for the following image-based feature extraction. Then, an emerging approach in the field of image processing for feature extraction, speeded-up robust features, is employed to automatically exact fault features from the transformed bi-spectrum contour map and finally form a high-dimensional feature vector. To reduce the dimensionality of the feature vector, thus highlighting main fault features and reducing subsequent computing resources, t-Distributed Stochastic Neighbor Embedding is adopt to reduce the dimensionality of the feature vector. At last, probabilistic neural network is introduced for fault identification. Two typical rotating machinery, axial piston hydraulic pump and self-priming centrifugal pumps, are selected to demonstrate the effectiveness of the proposed method. Results show that the proposed method based on image-processing achieves a high accuracy, thus providing a highly effective means to fault diagnosis for rotating machinery.

  13. Full Discretisations for Nonlinear Evolutionary Inequalities Based on Stiffly Accurate Runge-Kutta and hp-Finite Element Methods.

    PubMed

    Gwinner, J; Thalhammer, M

    The convergence of full discretisations by implicit Runge-Kutta and nonconforming Galerkin methods applied to nonlinear evolutionary inequalities is studied. The scope of applications includes differential inclusions governed by a nonlinear operator that is monotone and fulfills a certain growth condition. A basic assumption on the considered class of stiffly accurate Runge-Kutta time discretisations is a stability criterion which is in particular satisfied by the Radau IIA and Lobatto IIIC methods. In order to allow nonconforming hp-finite element approximations of unilateral constraints, set convergence of convex subsets in the sense of Glowinski-Mosco-Stummel is utilised. An appropriate formulation of the fully discrete variational inequality is deduced on the basis of a characteristic example of use, a Signorini-type initial-boundary value problem. Under hypotheses close to the existence theory of nonlinear first-order evolutionary equations and inequalities involving a monotone main part, a convergence result for the piecewise constant in time interpolant is established.

  14. Accurate Attitude Estimation Using ARS under Conditions of Vehicle Movement Based on Disturbance Acceleration Adaptive Estimation and Correction

    PubMed Central

    Xing, Li; Hang, Yijun; Xiong, Zhi; Liu, Jianye; Wan, Zhong

    2016-01-01

    This paper describes a disturbance acceleration adaptive estimate and correction approach for an attitude reference system (ARS) so as to improve the attitude estimate precision under vehicle movement conditions. The proposed approach depends on a Kalman filter, where the attitude error, the gyroscope zero offset error and the disturbance acceleration error are estimated. By switching the filter decay coefficient of the disturbance acceleration model in different acceleration modes, the disturbance acceleration is adaptively estimated and corrected, and then the attitude estimate precision is improved. The filter was tested in three different disturbance acceleration modes (non-acceleration, vibration-acceleration and sustained-acceleration mode, respectively) by digital simulation. Moreover, the proposed approach was tested in a kinematic vehicle experiment as well. Using the designed simulations and kinematic vehicle experiments, it has been shown that the disturbance acceleration of each mode can be accurately estimated and corrected. Moreover, compared with the complementary filter, the experimental results have explicitly demonstrated the proposed approach further improves the attitude estimate precision under vehicle movement conditions. PMID:27754469

  15. Cooling device for bradycardia based on Peltier element for accurate anastomosis of off-pump coronary artery bypass grafting.

    PubMed

    Kuniyoshi, Yukio; Koja, Kageharu; Miyagi, Kazufumi; Shimoji, Mituyoshi; Uezu, Tooru; Arakaki, Katuya; Yamashiro, Satoshi; Mabuni, Katuhito; Senaha, Shigenobu

    2002-10-01

    Upon introducing off-pump coronary artery bypass grafting (CABG), the indications for CABG were expanded to include patients who previously had no operative indications. For accurate anastomosis, various devices and methods have been developed. Bradycardia is easily induced by drug administration. However, this method of achieving bradycardia also has adverse effects on cardiac function. We have developed a new device to decrease the heart rate by regional cooling of the sino-atrial node. The new device is incorporated with Peltier's element, which uses an electric charge to create a temperature gradient on both of its surfaces. In terms of the cooling ability of this device, its cooling surface is chilled from 25 degrees C to 0 degrees C within 30 s. During in vivo animal experiments, this device has been shown to decrease the myocardial temperature around the sino-atrial node to 15 degrees C and suppress sino-atrial node activity, resulting in bradycardia to 60 beats/min level. In summary, the simple and easily applicable device for local cooling in combination with the application of diltiazem for effective heart rate reduction may be very helpful for the surgeon and may avoid disadvantages for critically ill patients.

  16. A PSO-based rule extractor for medical diagnosis.

    PubMed

    Hsieh, Yi-Zeng; Su, Mu-Chun; Wang, Pa-Chun

    2014-06-01

    One of the major bottlenecks in applying conventional neural networks to the medical field is that it is very difficult to interpret, in a physically meaningful way, because the learned knowledge is numerically encoded in the trained synaptic weights. In one of our previous works, we proposed a class of Hyper-Rectangular Composite Neural Networks (HRCNNs) of which synaptic weights can be interpreted as a set of crisp If-Then rules; however, a trained HRCNN may result in some ineffective If-Then rules which can only justify very few positive examples (i.e., poor generalization). This motivated us to propose a PSO-based Fuzzy Hyper-Rectangular Composite Neural Network (PFHRCNN) which applies particle swarm optimization (PSO) to trim the rules generated by a trained HRCNN while the recognition performance will not be degraded or even be improved. The performance of the proposed PFHRCNN is demonstrated on three benchmark medical databases including liver disorders data set, the breast cancer data set and the Parkinson's disease data set.

  17. Congenital neutropenia: diagnosis, molecular bases and patient management.

    PubMed

    Donadieu, Jean; Fenneteau, Odile; Beaupain, Blandine; Mahlaoui, Nizar; Chantelot, Christine Bellanné

    2011-05-19

    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-hematopoietic 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. Sexuality after a cancer diagnosis: A population‐based study

    PubMed Central

    Wardle, Jane; Steptoe, Andrew; Fisher, Abigail

    2016-01-01

    BACKGROUND This study explored differences in sexual activity, function, and concerns between cancer survivors and cancer‐free controls in a population‐based study. METHODS The data were from 2982 men and 3708 women who were 50 years old or older and were participating in the English Longitudinal Study of Ageing. Sexual well‐being was assessed with the Sexual Relationships and Activities Questionnaire, and cancer diagnoses were self‐reported. RESULTS There were no differences between cancer survivors and controls in levels of sexual activity (76.0% vs 78.5% for men and 58.2% vs 55.5% for women) or sexual function. Men and women with cancer diagnoses were more dissatisfied with their sex lives than controls (age‐adjusted percentages: 30.9% vs 19.8% for men [P = .023] and 18.2% vs 11.8% for women [P = .034]), and women with cancer were more concerned about levels of sexual desire (10.2% vs 7.1%; P = .006). Women diagnosed < 5 years ago were more likely to report difficulty with becoming aroused (55.4% vs 31.8%; P = .016) and achieving orgasm (60.6% vs 28.3%; P < .001) and were more concerned about sexual desire (14.8% vs 7.1%; P = .007) and orgasmic experience (17.6% vs 7.1%; P = .042) than controls, but there were no differences in men. CONCLUSIONS Self‐reports of sexual activity and functioning in older people with cancer are broadly comparable to age‐matched, cancer‐free controls. There is a need to identify the causes of sexual dissatisfaction among long‐term cancer survivors despite apparently normal levels of sexual activity and function for their age. The development of interventions addressing low sexual desire and problems with sexual functioning in women is also important and may be particularly relevant for cancer survivors after treatment. Cancer 2016;122:3883–3891. © 2016 American Cancer Society. PMID:27531631

  19. Accurate thermochemistry from a parameterized coupled-cluster singles and doubles model and a local pair natural orbital based implementation for applications to larger systems.

    PubMed

    Huntington, Lee M J; Hansen, Andreas; Neese, Frank; Nooijen, Marcel

    2012-02-14

    We have recently introduced a parameterized coupled-cluster singles and doubles model (pCCSD(α, β)) that consists of a bivariate parameterization of the CCSD equations and is inspired by the coupled electron pair approximations. In our previous work, it was demonstrated that the pCCSD(-1, 1) method is an improvement over CCSD for the calculation of geometries, harmonic frequencies, and potential energy surfaces for single bond-breaking. In this paper, we find suitable pCCSD parameters for applications in reaction thermochemistry and thermochemical kinetics. The motivation is to develop an accurate and economical methodology that, when coupled with a robust local correlation framework based on localized pair natural orbitals, is suitable for large-scale thermochemical applications for sizeable molecular systems. It is demonstrated that the original pCCSD(-1, 1) method and several other pCCSD methods are a significant improvement upon the standard CCSD approach and that these methods often approach the accuracy of CCSD(T) for the calculation of reaction energies and barrier heights. We also show that a local version of the pCCSD methodology, implemented within the local pair natural orbital (LPNO) based CCSD code in ORCA, is sufficiently accurate for wide-scale chemical applications. The LPNO based methodology allows us for routine applications to intermediate sized (20-100 atoms) molecular systems and is a significantly more accurate alternative to MP2 and density functional theory for the prediction of reaction energies and barrier heights.

  20. 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

  1. 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).

  2. MYCIN: A Knowledge-Based Consultation Program for Infectious Disease Diagnosis.

    ERIC Educational Resources Information Center

    van Melle, William

    1978-01-01

    Describes the structure of MYCIN, a computer-based consultation system designed to assist physicians in the diagnosis of and therapy selection for patients with bacterial infections, and an explanation system which can answer simple English questions in order to justify its advice or educate the user. (Author/VT)

  3. 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…

  4. 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

  5. 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.

  6. Abnormal placentation: evidence-based diagnosis and management of placenta previa, placenta accreta, and vasa previa.

    PubMed

    Rao, Kiran Prabhaker; Belogolovkin, Victoria; Yankowitz, Jerome; Spinnato, Joseph A

    2012-08-01

    Placenta previa, placenta accreta, and vasa previa cause significant maternal and perinatal morbidity and mortality. With the increasing incidence of both cesarean delivery and pregnancies using assisted reproductive technology, these 3 conditions are becoming more common. Advances in grayscale and Doppler ultrasound have facilitated prenatal diagnosis of abnormal placentation to allow the development of multidisciplinary management plans to achieve the best outcomes for mother and baby. We present a comprehensive review of the literature on abnormal placentation including an evidence-based approach to diagnosis and management.

  7. Anatomic diagnosis of congenital heart disease. A practical approach based on the sequentiality principle.

    PubMed

    Cervantes-Salazar, Jorge; Curi-Curi, Pedro; Ramírez-Marroquín, Samuel; Calderón-Colmenero, Juan; Munoz-Castellanos, Luis

    2010-01-01

    Based on the sequentiality principle, this review proposes a practical method that allows the systematization of the anatomic diagnosis of congenital heart disease. We emphasize the need to use sequential connection between the different cardiac segments: atria, ventricles and great arteries. Five ordered steps are defined, which include determination of atrial situs and of the connection features between the ventricles and the great arteries. Related lesions and some additional special features are a second stage in the sequential analysis of congenital heart disease, which is also important for the integral diagnosis.

  8. 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.

  9. Technical advances in flow cytometry-based diagnosis and monitoring of paroxysmal nocturnal hemoglobinuria

    PubMed Central

    Correia, Rodolfo Patussi; Bento, Laiz Cameirão; Bortolucci, Ana Carolina Apelle; Alexandre, Anderson Marega; Vaz, Andressa da Costa; Schimidell, Daniela; Pedro, Eduardo de Carvalho; Perin, Fabricio Simões; Nozawa, Sonia Tsukasa; Mendes, Cláudio Ernesto Albers; Barroso, Rodrigo de Souza; Bacal, Nydia Strachman

    2016-01-01

    ABSTRACT Objective: To discuss the implementation of technical advances in laboratory diagnosis and monitoring of paroxysmal nocturnal hemoglobinuria for validation of high-sensitivity flow cytometry protocols. Methods: A retrospective study based on analysis of laboratory data from 745 patient samples submitted to flow cytometry for diagnosis and/or monitoring of paroxysmal nocturnal hemoglobinuria. Results: Implementation of technical advances reduced test costs and improved flow cytometry resolution for paroxysmal nocturnal hemoglobinuria clone detection. Conclusion: High-sensitivity flow cytometry allowed more sensitive determination of paroxysmal nocturnal hemoglobinuria clone type and size, particularly in samples with small clones. PMID:27759825

  10. Toward Quantitatively Accurate Calculation of the Redox-Associated Acid–Base and Ligand Binding Equilibria of Aquacobalamin

    SciTech Connect

    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 aquacobalamin 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

  11. Toward Quantitatively Accurate Calculation of the Redox-Associated Acid–Base and Ligand Binding Equilibria of Aquacobalamin

    DOE PAGES

    Johnston, Ryne C.; Zhou, Jing; Smith, Jeremy C.; ...

    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

  12. 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

    2016-08-04

    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

  13. 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.

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. Late diagnosis of congenital toxoplasmosis based on serological follow-up: A case report.

    PubMed

    Dard, Céline; Chemla, Cathy; Fricker-Hidalgo, Hélène; Brenier-Pinchart, Marie-Pierre; Baret, Marie; Mzabi, Alexandre; Villena, Isabelle; Pelloux, Hervé

    2017-04-01

    Toxoplasma gondii is a protozoan parasite infecting up to one third of the world's population. T. gondii infection is usually benign in immunocompetent patients but can be life-threatening when congenitally transmitted. Congenital toxoplasmosis presentation ranges from severe central nervous system and ocular features, to a well appearing newborn with onset of complications late in childhood. The diagnosis of subclinical form remains important since early treatment reduces later complications such as chorioretinitis. We report an atypical case of congenital toxoplasmosis with a delayed diagnosis, based on Toxoplasma-specific serological follow-up. The infant was born to a mother who became infected during pregnancy, thus inducing infant biological and clinical follow-up. Neither biological nor clinical arguments favored a diagnosis of congenital toxoplasmosis until ten months of life. Congenital toxoplasmosis was then suspected because of an unusual increase of specific IgG levels. Diagnosis was confirmed by detection of newly synthesized newborn Ig isotypes using complementary comparative mother-to-child immunological profile techniques and specific treatment therefore administered. This report highlights the importance to follow up newborns at risk of congenital toxoplasmosis with specific and newborn-appropriate techniques until Toxoplasma-IgG titers are completely negative. This allows not only the exclusion of congenital toxoplasmosis when serology becomes negative, but also the diagnosis and treatment of congenital toxoplasmosis when infection is detected later in development.

  19. NGS-based Molecular diagnosis of 105 eyeGENE(®) probands with Retinitis Pigmentosa.

    PubMed

    Ge, Zhongqi; Bowles, Kristen; Goetz, Kerry; Scholl, Hendrik P N; Wang, Feng; Wang, Xinjing; Xu, Shan; Wang, Keqing; Wang, Hui; Chen, Rui

    2015-12-15

    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(®).

  20. 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

  1. 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

  2. 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.

  3. 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

    2016-01-08

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  4. 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

  5. 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.

  6. Fragmentation pathways of drugs of abuse and their metabolites based on QTOF MS/MS and MS(E) accurate-mass spectra.

    PubMed

    Bijlsma, Lubertus; Sancho, Juan V; Hernández, Félix; Niessen, Wilfried M A

    2011-09-01

    A study of the fragmentation pathways of several classes of drugs of abuse (cannabinoids, ketamine, amphetamine and amphetamine-type stimulants (ATS), cocaine and opiates) and their related substances has been made. The knowledge of the fragmentation is highly useful for specific fragment selection or for recognition of related compounds when developing MS-based analytical methods for the trace-level determination of these compounds in complex matrices. In this work, accurate-mass spectra of selected compounds were obtained using liquid chromatography coupled to quadrupole time-of-flight mass spectrometry, performing both MS/MS and MS(E) experiments. As regards fragmentation behavior, the mass spectra of both approaches were quite similar and were useful to study the fragmentation of the drugs investigated. Accurate-mass spectra of 37 drugs of abuse and related compounds, including metabolites and deuterated analogues, were studied in this work, and structures of fragment ions were proposed. The accurate-mass data obtained allowed to confirm structures and fragmentation pathways previously proposed based on nominal mass measurements, although new insights and structure proposals were achieved in some particular cases, especially for amphetamine and ATS, 11-nor-9-carboxy-Δ(9)-tetrahydrocannabinol (THC-COOH) and opiates.

  7. Finite Element Modelling of a Field-Sensed Magnetic Suspended System for Accurate Proximity Measurement Based on a Sensor Fusion Algorithm with Unscented Kalman Filter.

    PubMed

    Chowdhury, Amor; Sarjaš, Andrej

    2016-09-15

    The presented paper describes accurate distance measurement for a field-sensed magnetic suspension system. The proximity measurement is based on a Hall effect sensor. The proximity sensor is installed directly on the lower surface of the electro-magnet, which means that it is very sensitive to external magnetic influences and disturbances. External disturbances interfere with the information signal and reduce the usability and reliability of the proximity measurements and, consequently, the whole application operation. A sensor fusion algorithm is deployed for the aforementioned reasons. The sensor fusion algorithm is based on the Unscented Kalman Filter, where a nonlinear dynamic model was derived with the Finite Element Modelling approach. The advantage of such modelling is a more accurate dynamic model parameter estimation, especially in the case when the real structure, materials and dimensions of the real-time application are known. The novelty of the paper is the design of a compact electro-magnetic actuator with a built-in low cost proximity sensor for accurate proximity measurement of the magnetic object. The paper successively presents a modelling procedure with the finite element method, design and parameter settings of a sensor fusion algorithm with Unscented Kalman Filter and, finally, the implementation procedure and results of real-time operation.

  8. Finite Element Modelling of a Field-Sensed Magnetic Suspended System for Accurate Proximity Measurement Based on a Sensor Fusion Algorithm with Unscented Kalman Filter

    PubMed Central

    Chowdhury, Amor; Sarjaš, Andrej

    2016-01-01

    The presented paper describes accurate distance measurement for a field-sensed magnetic suspension system. The proximity measurement is based on a Hall effect sensor. The proximity sensor is installed directly on the lower surface of the electro-magnet, which means that it is very sensitive to external magnetic influences and disturbances. External disturbances interfere with the information signal and reduce the usability and reliability of the proximity measurements and, consequently, the whole application operation. A sensor fusion algorithm is deployed for the aforementioned reasons. The sensor fusion algorithm is based on the Unscented Kalman Filter, where a nonlinear dynamic model was derived with the Finite Element Modelling approach. The advantage of such modelling is a more accurate dynamic model parameter estimation, especially in the case when the real structure, materials and dimensions of the real-time application are known. The novelty of the paper is the design of a compact electro-magnetic actuator with a built-in low cost proximity sensor for accurate proximity measurement of the magnetic object. The paper successively presents a modelling procedure with the finite element method, design and parameter settings of a sensor fusion algorithm with Unscented Kalman Filter and, finally, the implementation procedure and results of real-time operation. PMID:27649197

  9. 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.

  10. Evidence-based algorithm for diagnosis and assessment in psoriatic arthritis: results by Italian DElphi in psoriatic Arthritis (IDEA).

    PubMed

    Lapadula, G; Marchesoni, A; Salaffi, F; Ramonda, R; Salvarani, C; Punzi, L; Costa, L; Caso, F; Simone, D; Baiocchi, G; Scioscia, C; Di Carlo, M; Scarpa, R; Ferraccioli, G

    2016-12-16

    Psoriatic arthritis (PsA) is a chronic inflammatory disease involving skin, peripheral joints, entheses, and axial skeleton. The disease is frequently associated with extrarticular manifestations (EAMs) and comorbidities. In order to create a protocol for PsA diagnosis and global assessment of patients with an algorithm based on anamnestic, clinical, laboratory and imaging procedures, we established a DElphi study on a national scale, named Italian DElphi in psoriatic Arthritis (IDEA). After a literature search, a Delphi poll, involving 52 rheumatologists, was performed. On the basis of the literature search, 202 potential items were identified. The steering committee planned at least two Delphi rounds. In the first Delphi round, the experts judged each of the 202 items using a score ranging from 1 to 9 based on its increasing clinical relevance. The questions posed to experts were How relevant is this procedure/observation/sign/symptom for assessment of a psoriatic arthritis patient? Proposals of additional items, not included in the questionnaire, were also encouraged. The results of the poll were discussed by the Steering Committee, which evaluated the necessity for removing selected procedures or adding additional ones, according to criteria of clinical appropriateness and sustainability. A total of 43 recommended diagnosis and assessment procedures, recognized as items, were derived by combination of the Delphi survey and two National Expert Meetings, and grouped in different areas. Favourable opinion was reached in 100% of cases for several aspects covering the following areas: medical (familial and personal) history, physical evaluation, imaging tool, second level laboratory tests, disease activity measurement and extrarticular manifestations. After performing PsA diagnosis, identification of specific disease activity scores and clinimetric approaches were suggested for assessing the different clinical subsets. Further, results showed the need for

  11. Kawasaki disease: an evidence based approach to diagnosis, treatment, and proposals for future research

    PubMed Central

    Brogan, P; Bose, A; Burgner, D; Shingadia, D; Tulloh, R; Michie, C; Klein, N; Booy, R; Levin, M; Dillon, M

    2002-01-01

    This article proposes a clinical guideline for the diagnosis and treatment of Kawasaki disease in the UK based on the best available evidence to date, and highlights areas of practice where evidence is anecdotal or based on retrospective data. Future research as proposed by the London Kawasaki Disease Research Group is outlined, and clinicians are invited to prospectively enrol their suspected cases into this collaborative research project. PMID:11919108

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. A time domain based method for the accurate measurement of Q-factor and resonance frequency of microwave resonators

    NASA Astrophysics Data System (ADS)

    Gyüre, B.; Márkus, B. G.; Bernáth, B.; Murányi, F.; Simon, F.

    2015-09-01

    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.

  18. An intelligent system for lung cancer diagnosis using a new genetic algorithm based feature selection method.

    PubMed

    Lu, Chunhong; Zhu, Zhaomin; Gu, Xiaofeng

    2014-09-01

    In this paper, we develop a novel feature selection algorithm based on the genetic algorithm (GA) using a specifically devised trace-based separability criterion. According to the scores of class separability and variable separability, this criterion measures the significance of feature subset, independent of any specific classification. In addition, a mutual information matrix between variables is used as features for classification, and no prior knowledge about the cardinality of feature subset is required. Experiments are performed by using a standard lung cancer dataset. The obtained solutions are verified with three different classifiers, including the support vector machine (SVM), the back-propagation neural network (BPNN), and the K-nearest neighbor (KNN), and compared with those obtained by the whole feature set, the F-score and the correlation-based feature selection methods. The comparison results show that the proposed intelligent system has a good diagnosis performance and can be used as a promising tool for lung cancer diagnosis.

  19. 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.

  20. A Knowledge-Based System for the Computer Assisted Diagnosis of Endoscopic Images

    NASA Astrophysics Data System (ADS)

    Kage, Andreas; Münzenmayer, Christian; Wittenberg, Thomas

    Due to the actual demographic development the use of Computer-Assisted Diagnosis (CAD) systems becomes a more important part of clinical workflows and clinical decision making. Because changes on the mucosa of the esophagus can indicate the first stage of cancerous developments, there is a large interest to detect and correctly diagnose any such lesion. We present a knowledge-based system which is able to support a physician with the interpretation and diagnosis of endoscopic images of the esophagus. Our system is designed to support the physician directly during the examination of the patient, thus prodving diagnostic assistence at the point of care (POC). Based on an interactively marked region in an endoscopic image of interest, the system provides a diagnostic suggestion, based on an annotated reference image database. Furthermore, using relevant feedback mechanisms, the results can be enhanced interactively.

  1. 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.

  2. 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.

  3. Evidence based review of the impact of image enhanced endoscopy in the diagnosis of gastric disorders

    PubMed Central

    Hussain, Ikram; Ang, Tiing Leong

    2016-01-01

    Gastric cancer is the third most common cause of cancer-related death. Advanced stages of gastric cancers generally have grim prognosis. But, good prognosis can be achieved if such cancers are detected, diagnosed and resected at early stages. However, early gastric cancers and its precursors often produce only subtle mucosal changes and therefore quite commonly remain elusive at the conventional examination with white light endoscopy. Image-enhanced endoscopy makes mucosal lesions more conspicuous and can therefore potentially yield earlier and more accurate diagnoses. Recent years have seen growing work of research in support of various types of image enhanced endoscopy (IEE) techniques (e.g., dye-chromoendoscopy; magnification endoscopy; narrow-band imaging; flexible spectral imaging color enhancement; and I-SCAN) for a variety of gastric pathologies. In this review, we will examine the evidence for the utilization of various IEE techniques in the diagnosis of gastric disorders. PMID:28042388

  4. Robust fault diagnosis for reaction flywheel based on reduced-order observer

    NASA Astrophysics Data System (ADS)

    Wang, Min; Qin, Shiyin

    2008-10-01

    In this paper, a reduced-order observer is applied to fault diagnosis for reaction flywheels in satellite attitude control system. The benefit of this approach is able to estimate the fault signal of reaction flywheel in the presence of unknown inputs. Through ingenious state transformation, the original system is decomposed into two subsystems, one of which is driven by known inputs only. Thus, after a reduced-order observer being designed, the subsystem's accurate state estimation can be obtained without the effect of unknown inputs, consequently, the unknown inputs can be estimated. In this case the fault signals of reaction flywheels may come down to a part of unknown inputs, then the faults can be detected according to the estimated unknown inputs.

  5. BIOACCESSIBILITY TESTS ACCURATELY ESTIMATE ...

    EPA Pesticide Factsheets

    Hazards of soil-borne Pb to wild birds may be more accurately quantified if the bioavailability of that Pb is known. To better understand the bioavailability of Pb to birds, we measured blood Pb concentrations in Japanese quail (Coturnix japonica) fed diets containing Pb-contaminated soils. Relative bioavailabilities were expressed by comparison with blood Pb concentrations in quail fed a Pb acetate reference diet. Diets containing soil from five Pb-contaminated Superfund sites had relative bioavailabilities from 33%-63%, with a mean of about 50%. Treatment of two of the soils with P significantly reduced the bioavailability of Pb. The bioaccessibility of the Pb in the test soils was then measured in six in vitro tests and regressed on bioavailability. They were: the “Relative Bioavailability Leaching Procedure” (RBALP) at pH 1.5, the same test conducted at pH 2.5, the “Ohio State University In vitro Gastrointestinal” method (OSU IVG), the “Urban Soil Bioaccessible Lead Test”, the modified “Physiologically Based Extraction Test” and the “Waterfowl Physiologically Based Extraction Test.” All regressions had positive slopes. Based on criteria of slope and coefficient of determination, the RBALP pH 2.5 and OSU IVG tests performed very well. Speciation by X-ray absorption spectroscopy demonstrated that, on average, most of the Pb in the sampled soils was sorbed to minerals (30%), bound to organic matter 24%, or present as Pb sulfate 18%. Ad

  6. A genetic study of neurofibromatosis type 1 (NF1) in south-western Ontario. II. A PCR based approach to molecular and prenatal diagnosis using linkage.

    PubMed Central

    Rodenhiser, D I; Ainsworth, P J; Coulter-Mackie, M B; Singh, S M; Jung, J H

    1993-01-01

    Neurofibromatosis type 1 (NF1) is a common, autosomal dominant genetic disorder with a variety of highly variable symptoms including cutaneous manifestations (such as café au lait spots), Lisch nodules, plexiform neurofibromas, skeletal abnormalities, an increased risk for malignancy, and the development of learning disabilities. The wide clinical variability of expression of the disease phenotype and high (spontaneous) mutation rate of the NF1 gene indicate that careful clinical examination of patients and family members is necessary to provide an accurate diagnosis of the disease. Since very few NF1 mutations have been identified, and with the apparent lack of a predominant mutation in this large, highly mutable gene, molecular diagnosis of NF1 will continue to be based on haplotypes using linkage analysis. Here we report our experiences while providing a molecular diagnostic service for NF1 in the ethnically diverse region of south-western Ontario. Molecular diagnoses with at least one informative probe/enzyme combination are reported for 19 families including two families requesting prenatal diagnosis for NF1. We have augmented the classical Southern based approach to linkage analysis with the use of PCR based assays for molecular linkage. Furthermore, criteria have been established in our laboratory for executing molecular linkage based on heterozygosity values, recombination fractions, and the use of intragenic probes/markers. Images PMID:8320697

  7. 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

  8. 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

    2015-05-07

    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.

  9. StatSTEM: An efficient approach for accurate and precise model-based quantification of atomic resolution electron microscopy images.

    PubMed

    De Backer, A; van den Bos, K H W; Van den Broek, W; Sijbers, J; Van Aert, S

    2016-12-01

    An efficient model-based estimation algorithm is introduced to quantify the atomic column positions and intensities from atomic resolution (scanning) transmission electron microscopy ((S)TEM) images. This algorithm uses the least squares estimator on image segments containing individual columns fully accounting for overlap between neighbouring columns, enabling the analysis of a large field of view. For this algorithm, the accuracy and precision with which measurements for the atomic column positions and scattering cross-sections from annular dark field (ADF) STEM images can be estimated, has been investigated. The highest attainable precision is reached even for low dose images. Furthermore, the advantages of the model-based approach taking into account overlap between neighbouring columns are highlighted. This is done for the estimation of the distance between two neighbouring columns as a function of their distance and for the estimation of the scattering cross-section which is compared to the integrated intensity from a Voronoi cell. To provide end-users this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license.

  10. Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System

    NASA Astrophysics Data System (ADS)

    Ben Rabah, N.; Saddem, R.; Ben Hmida, F.; Carre-Menetrier, V.; Tagina, M.

    2017-01-01

    Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach.

  11. 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

  12. Accurate determination of lattice parameters based on Niggli reduced cell theory by using digitized electron diffraction micrograph.

    PubMed

    Yang, Yi; Cai, Canying; Lin, Jianguo; Gong, Lunjun; Yang, Qibin

    2017-05-01

    In this paper, we used Niggli reduced cell theory to determine lattice constants of a micro/nano crystal by using electron diffraction patterns. The Niggli reduced cell method enhanced the accuracy of lattice constant measurement obviously, because the lengths and the angles of lattice vectors of a primitive cell can be measured directly on the electron micrographs instead of a double tilt holder. With the aid of digitized algorithm and least square optimization by using three digitized micrographs, a valid reciprocal Niggli reduced cell number can be obtained. Thus a reciprocal and real Bravais lattices are acquired. The results of three examples, i.e., Mg4Zn7, an unknown phase (Precipitate phase in nickel-base superalloy) and Ba4Ti13O30 showed that the maximum errors are 1.6% for lengths and are 0.3% for angles.

  13. Improvement of fluorescence-enhanced optical tomography with improved optical filtering and accurate model-based reconstruction algorithms.

    PubMed

    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.

  14. 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.

  15. Accurate pKa calculation of the conjugate acids of alkanolamines, alkaloids and nucleotide bases by quantum chemical methods.

    PubMed

    Gangarapu, Satesh; Marcelis, Antonius T M; Zuilhof, Han

    2013-04-02

    The pKa of the conjugate acids of alkanolamines, neurotransmitters, alkaloid drugs and nucleotide bases are calculated with density functional methods (B3LYP, M08-HX and M11-L) and ab initio methods (SCS-MP2, G3). Implicit solvent effects are included with a conductor-like polarizable continuum model (CPCM) and universal solvation models (SMD, SM8). G3, SCS-MP2 and M11-L methods coupled with SMD and SM8 solvation models perform well for alkanolamines with mean unsigned errors below 0.20 pKa units, in all cases. Extending this method to the pKa calculation of 35 nitrogen-containing compounds spanning 12 pKa units showed an excellent correlation between experimental and computational pKa values of these 35 amines with the computationally low-cost SM8/M11-L density functional approach.

  16. Multi-period medical diagnosis method using a single valued neutrosophic similarity measure based on tangent function.

    PubMed

    Ye, Jun; Fu, Jing

    2016-01-01

    Because of the increased volume of information available to physicians from advanced medical technology, the obtained information of each symptom with respect to a disease may contain truth, falsity and indeterminacy information. Since a single-valued neutrosophic set (SVNS) consists of the three terms like the truth-membership, indeterminacy-membership and falsity-membership functions, it is very suitable for representing indeterminate and inconsistent information. Then, similarity measure plays an important role in pattern recognition and medical diagnosis. However, existing medical diagnosis methods can only handle the single period medical diagnosis problem, but cannot deal with the multi-period medical diagnosis problems with neutrosophic information. Hence, the purpose of this paper was to propose similarity measures between SVNSs based on tangent function and a multi-period medical diagnosis method based on the similarity measure and the weighted aggregation of multi-period information to solve multi-period medical diagnosis problems with single-valued neutrosophic information. Then, we compared the tangent similarity measures of SVNSs with existing similarity measures of SVNSs by a numerical example about pattern recognitions to indicate the effectiveness and rationality of the proposed similarity measures. In the multi-period medical diagnosis method, we can find a proper diagnosis for a patient by the proposed similarity measure between the symptoms and the considered diseases represented by SVNSs and the weighted aggregation of multi-period information. Then, a multi-period medical diagnosis example was presented to demonstrate the application of the proposed diagnosis method and to indicate the effectiveness of the proposed diagnosis method by the comparative analysis. The diagnosis results showed that the developed multi-period medical diagnosis method can help doctors make a proper diagnosis by the comprehensive information of multi-periods.

  17. An accurate online calibration system based on combined clamp-shape coil for high voltage electronic current transformers

    SciTech Connect

    Li, Zhen-hua; Li, Hong-bin; Zhang, Zhi

    2013-07-15

    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 of electronic transformers is higher than that of traditional transformers. As a result, the calibration period needs to be shortened. Traditional calibration methods require the power of transmission line be cut off, which results in complicated operation and power off loss. This paper proposes an online calibration system which can calibrate electronic current transformers without power off. In this work, the high accuracy standard current transformer and online operation method are the key techniques. Based on the clamp-shape iron-core coil and clamp-shape air-core coil, a combined clamp-shape coil is designed as the standard current transformer. By analyzing the output characteristics of the two coils, the combined clamp-shape coil can achieve verification of the accuracy. So the accuracy of the online calibration system can be guaranteed. Moreover, by employing the earth potential working method and using two insulating rods to connect the combined clamp-shape coil to the high voltage bus, the operation becomes simple and safe. Tests in China National Center for High Voltage Measurement and field experiments show that the proposed system has a high accuracy of up to 0.05 class.

  18. The effect of porosity on cell ingrowth into accurately defined, laser-made, polylactide-based 3D scaffolds

    NASA Astrophysics Data System (ADS)

    Danilevicius, Paulius; Georgiadi, Leoni; Pateman, Christopher J.; Claeyssens, Frederik; Chatzinikolaidou, Maria; Farsari, Maria

    2015-05-01

    The aim of this study is to demonstrate the accuracy required for the investigation of the role of solid scaffolds' porosity in cell proliferation. We therefore present a qualitative investigation into the effect of porosity on MC3T3-E1 pre-osteoblastic cell ingrowth of three-dimensional (3D) scaffolds fabricated by direct femtosecond laser writing. The material we used is a purpose made photosensitive pre-polymer based on polylactide. We designed and fabricated complex, geometry-controlled 3D scaffolds with pore sizes ranging from 25 to 110 μm, representing porosities 70%, 82%, 86%, and 90%. The 70% porosity scaffolds did not support cell growth initially and in the long term. For the other porosities, we found a strong adhesion of the pre-osteoblastic cells from the first hours after seeding and a remarkable proliferation increase after 3 weeks and up to 8 weeks. The 86% porosity scaffolds exhibited a higher efficiency compared to 82% and 90%. In addition, bulk material degradation studies showed that the employed, highly-acrylated polylactide is degradable. These findings support the potential use of the proposed material and the scaffold fabrication technique in bone tissue engineering.

  19. 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 of electronic transformers is higher than that of traditional transformers. As a result, the calibration period needs to be shortened. Traditional calibration methods require the power of transmission line be cut off, which results in complicated operation and power off loss. This paper proposes an online calibration system which can calibrate electronic current transformers without power off. In this work, the high accuracy standard current transformer and online operation method are the key techniques. Based on the clamp-shape iron-core coil and clamp-shape air-core coil, a combined clamp-shape coil is designed as the standard current transformer. By analyzing the output characteristics of the two coils, the combined clamp-shape coil can achieve verification of the accuracy. So the accuracy of the online calibration system can be guaranteed. Moreover, by employing the earth potential working method and using two insulating rods to connect the combined clamp-shape coil to the high voltage bus, the operation becomes simple and safe. Tests in China National Center for High Voltage Measurement and field experiments show that the proposed system has a high accuracy of up to 0.05 class.

  20. An accurate online calibration system based on combined clamp-shape coil for high voltage electronic current transformers

    NASA Astrophysics Data System (ADS)

    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 of electronic transformers is higher than that of traditional transformers. As a result, the calibration period needs to be shortened. Traditional calibration methods require the power of transmission line be cut off, which results in complicated operation and power off loss. This paper proposes an online calibration system which can calibrate electronic current transformers without power off. In this work, the high accuracy standard current transformer and online operation method are the key techniques. Based on the clamp-shape iron-core coil and clamp-shape air-core coil, a combined clamp-shape coil is designed as the standard current transformer. By analyzing the output characteristics of the two coils, the combined clamp-shape coil can achieve verification of the accuracy. So the accuracy of the online calibration system can be guaranteed. Moreover, by employing the earth potential working method and using two insulating rods to connect the combined clamp-shape coil to the high voltage bus, the operation becomes simple and safe. Tests in China National Center for High Voltage Measurement and field experiments show that the proposed system has a high accuracy of up to 0.05 class.

  1. Accurate quantification of local changes for carotid arteries in 3D ultrasound images using convex optimization-based deformable registration

    NASA Astrophysics Data System (ADS)

    Cheng, Jieyu; Qiu, Wu; Yuan, Jing; Fenster, Aaron; Chiu, Bernard

    2016-03-01

    Registration of longitudinally acquired 3D ultrasound (US) images plays an important role in monitoring and quantifying progression/regression of carotid atherosclerosis. We introduce an image-based non-rigid registration algorithm to align the baseline 3D carotid US with longitudinal images acquired over several follow-up time points. This algorithm minimizes the sum of absolute intensity differences (SAD) under a variational optical-flow perspective within a multi-scale optimization framework to capture local and global deformations. Outer wall and lumen were segmented manually on each image, and the performance of the registration algorithm was quantified by Dice similarity coefficient (DSC) and mean absolute distance (MAD) of the outer wall and lumen surfaces after registration. In this study, images for 5 subjects were registered initially by rigid registration, followed by the proposed algorithm. Mean DSC generated by the proposed algorithm was 79:3+/-3:8% for lumen and 85:9+/-4:0% for outer wall, compared to 73:9+/-3:4% and 84:7+/-3:2% generated by rigid registration. Mean MAD of 0:46+/-0:08mm and 0:52+/-0:13mm were generated for lumen and outer wall respectively by the proposed algorithm, compared to 0:55+/-0:08mm and 0:54+/-0:11mm generated by rigid registration. The mean registration time of our method per image pair was 143+/-23s.

  2. 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

  3. Rapid and Accurate Detection of Urinary Pathogens by Mobile IMS-Based Electronic Nose: A Proof-of-Principle Study

    PubMed Central

    Roine, Antti; Saviauk, Taavi; Kumpulainen, Pekka; Karjalainen, Markus; Tuokko, Antti; Aittoniemi, Janne; Vuento, Risto; Lekkala, Jukka; Lehtimäki, Terho; Tammela, Teuvo L.; Oksala, Niku K. J.

    2014-01-01

    Urinary tract infection (UTI) is a common disease with significant morbidity and economic burden, accounting for a significant part of the workload in clinical microbiology laboratories. Current clinical chemisty point-of-care diagnostics rely on imperfect dipstick analysis which only provides indirect and insensitive evidence of urinary bacterial pathogens. An electronic nose (eNose) is a handheld device mimicking mammalian olfaction that potentially offers affordable and rapid analysis of samples without preparation at athmospheric pressure. In this study we demonstrate the applicability of ion mobility spectrometry (IMS) –based eNose to discriminate the most common UTI pathogens from gaseous headspace of culture plates rapidly and without sample preparation. We gathered a total of 101 culture samples containing four most common UTI bacteries: E. coli, S. saprophyticus, E. faecalis, Klebsiella spp and sterile culture plates. The samples were analyzed using ChemPro 100i device, consisting of IMS cell and six semiconductor sensors. Data analysis was conducted by linear discriminant analysis (LDA) and logistic regression (LR). The results were validated by leave-one-out and 5-fold cross validation analysis. In discrimination of sterile and bacterial samples sensitivity of 95% and specificity of 97% were achieved. The bacterial species were identified with sensitivity of 95% and specificity of 96% using eNose as compared to urine bacterial cultures. In conclusion: These findings strongly demonstrate the ability of our eNose to discriminate bacterial cultures and provides a proof of principle to use this method in urinanalysis of UTI. PMID:25526592

  4. Integration of a silicon-based microprobe into a gear measuring instrument for accurate measurement of micro gears

    NASA Astrophysics Data System (ADS)

    Ferreira, N.; Krah, T.; Jeong, D. C.; Metz, D.; Kniel, K.; Dietzel, A.; Büttgenbach, S.; Härtig, F.

    2014-06-01

    The integration of silicon micro probing systems into conventional gear measuring instruments (GMIs) allows fully automated measurements of external involute micro spur gears of normal modules smaller than 1 mm. This system, based on a silicon microprobe, has been developed and manufactured at the Institute for Microtechnology of the Technische Universität Braunschweig. The microprobe consists of a silicon sensor element and a stylus which is oriented perpendicularly to the sensor. The sensor is fabricated by means of silicon bulk micromachining. Its small dimensions of 6.5 mm × 6.5 mm allow compact mounting in a cartridge to facilitate the integration into a GMI. In this way, tactile measurements of 3D microstructures can be realized. To enable three-dimensional measurements with marginal forces, four Wheatstone bridges are built with diffused piezoresistors on the membrane of the sensor. On the reverse of the membrane, the stylus is glued perpendicularly to the sensor on a boss to transmit the probing forces to the sensor element during measurements. Sphere diameters smaller than 300 µm and shaft lengths of 5 mm as well as measurement forces from 10 µN enable the measurements of 3D microstructures. Such micro probing systems can be integrated into universal coordinate measuring machines and also into GMIs to extend their field of application. Practical measurements were carried out at the Physikalisch-Technische Bundesanstalt by qualifying the microprobes on a calibrated reference sphere to determine their sensitivity and their physical dimensions in volume. Following that, profile and helix measurements were carried out on a gear measurement standard with a module of 1 mm. The comparison of the measurements shows good agreement between the measurement values and the calibrated values. This result is a promising basis for the realization of smaller probe diameters for the tactile measurement of micro gears with smaller modules.

  5. MBRidge: an accurate and cost-effective method for profiling DNA methylome at single-base resolution.

    PubMed

    Cai, Wanshi; Mao, Fengbiao; Teng, Huajing; Cai, Tao; Zhao, Fangqing; Wu, Jinyu; Sun, Zhong Sheng

    2015-08-01

    Organisms and cells, in response to environmental influences or during development, undergo considerable changes in DNA methylation on a genome-wide scale, which are linked to a variety of biological processes. Using MethylC-seq to decipher DNA methylome at single-base resolution is prohibitively costly. In this study, we develop a novel approach, named MBRidge, to detect the methylation levels of repertoire CpGs, by innovatively introducing C-hydroxylmethylated adapters and bisulfate treatment into the MeDIP-seq protocol and employing ridge regression in data analysis. A systematic evaluation of DNA methylome in a human ovarian cell line T29 showed that MBRidge achieved high correlation (R > 0.90) with much less cost (∼10%) in comparison with MethylC-seq. We further applied MBRidge to profiling DNA methylome in T29H, an oncogenic counterpart of T29's. By comparing methylomes of T29H and T29, we identified 131790 differential methylation regions (DMRs), which are mainly enriched in carcinogenesis-related pathways. These are substantially different from 7567 DMRs that were obtained by RRBS and related with cell development or differentiation. The integrated analysis of DMRs in the promoter and expression of DMR-corresponding genes revealed that DNA methylation enforced reverse regulation of gene expression, depending on the distance from the proximal DMR to transcription starting sites in both mRNA and lncRNA. Taken together, our results demonstrate that MBRidge is an efficient and cost-effective method that can be widely applied to profiling DNA methylomes.

  6. 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

  7. A preliminary study of breast cancer diagnosis using laboratory based small angle x-ray scattering

    NASA Astrophysics Data System (ADS)

    Round, A. R.; Wilkinson, S. J.; Hall, C. J.; Rogers, K. D.; Glatter, O.; Wess, T.; Ellis, I. O.

    2005-09-01

    Breast tissue collected from tumour samples and normal tissue from bi-lateral mastectomy procedures were examined using small angle x-ray scattering. Previous work has indicated that breast tissue disease diagnosis could be performed using small angle x-ray scattering (SAXS) from a synchrotron radiation source. The technique would be more useful to health services if it could be made to work using a conventional x-ray source. Consistent and reliable differences in x-ray scatter distributions were observed between samples from normal and tumour tissue samples using the laboratory based 'SAXSess' system. Albeit from a small number of samples, a sensitivity of 100% was obtained. This result encourages us to pursue the implementation of SAXS as a laboratory based diagnosis technique.

  8. Fault diagnosis based on support vector machines with parameter optimisation by artificial immunisation algorithm

    NASA Astrophysics Data System (ADS)

    Yuan, Shengfa; Chu, Fulei

    2007-04-01

    Support vector machines (SVM) is a new general machine-learning tool based on the structural risk minimisation principle that exhibits good generalisation when fault samples are few, it is especially fit for classification, forecasting and estimation in small-sample cases such as fault diagnosis, but some parameters in SVM are selected by man's experience, this has hampered its efficiency in practical application. Artificial immunisation algorithm (AIA) is used to optimise the parameters in SVM in this paper. The AIA is a new optimisation method based on the biologic immune principle of human being and other living beings. It can effectively avoid the premature convergence and guarantees the variety of solution. With the parameters optimised by AIA, the total capability of the SVM classifier is improved. The fault diagnosis of turbo pump rotor shows that the SVM optimised by AIA can give higher recognition accuracy than the normal SVM.

  9. Are diagnosis specific outcome indicators based on administrative data useful in assessing quality of hospital care?

    PubMed Central

    Scott, I; Youlden, D; Coory, M

    2004-01-01

    Background: Hospital performance reports based on administrative data should distinguish differences in quality of care between hospitals from case mix related variation and random error effects. A study was undertaken to determine which of 12 diagnosis-outcome indicators measured across all hospitals in one state had significant risk adjusted systematic (or special cause) variation (SV) suggesting differences in quality of care. For those that did, we determined whether SV persists within hospital peer groups, whether indicator results correlate at the individual hospital level, and how many adverse outcomes would be avoided if all hospitals achieved indicator values equal to the best performing 20% of hospitals. Methods: All patients admitted during a 12 month period to 180 acute care hospitals in Queensland, Australia with heart failure (n = 5745), acute myocardial infarction (AMI) (n = 3427), or stroke (n = 2955) were entered into the study. Outcomes comprised in-hospital deaths, long hospital stays, and 30 day readmissions. Regression models produced standardised, risk adjusted diagnosis specific outcome event ratios for each hospital. Systematic and random variation in ratio distributions for each indicator were then apportioned using hierarchical statistical models. Results: Only five of 12 (42%) diagnosis-outcome indicators showed significant SV across all hospitals (long stays and same diagnosis readmissions for heart failure; in-hospital deaths and same diagnosis readmissions for AMI; and in-hospital deaths for stroke). Significant SV was only seen for two indicators within hospital peer groups (same diagnosis readmissions for heart failure in tertiary hospitals and inhospital mortality for AMI in community hospitals). Only two pairs of indicators showed significant correlation. If all hospitals emulated the best performers, at least 20% of AMI and stroke deaths, heart failure long stays, and heart failure and AMI readmissions could be avoided

  10. Diagnosis of IBS: symptoms, symptom-based criteria, biomarkers or 'psychomarkers'?

    PubMed

    Sood, Ruchit; Law, Graham R; Ford, Alexander C

    2014-11-01

    IBS is estimated to have a prevalence of up to 20% in Western populations and results in substantial costs to health-care services worldwide, estimated to be US$1 billion per year in the USA. IBS remains difficult to diagnose due to its multifactorial aetiology, heterogeneous nature and overlap of symptoms with organic pathologies, such as coeliac disease and IBD. As a result, IBS often continues to be a diagnosis of exclusion, resulting in unnecessary investigations. Available methods for the diagnosis of IBS-including the current gold standard, the Rome III criteria-perform only moderately well. Visceral hypersensitivity and altered pain perception do not discriminate between IBS and other functional gastrointestinal diseases or health with any great accuracy. Attention has now turned to developing novel biomarkers and using psychological markers (so-called psychomarkers) to aid the diagnosis of IBS. This Review describes how useful symptoms, symptom-based criteria, biomarkers and psychomarkers, and indeed combinations of all these approaches, are in the diagnosis of IBS. Future directions in diagnosing IBS could include combining demographic data, gastrointestinal symptoms, biomarkers and psychomarkers using statistical methods. Latent class analysis to distinguish between IBS and non-IBS symptom profiles might also represent a promising avenue for future research.

  11. Differential diagnosis of ovarian tumors based primarily on their patterns and cell types.

    PubMed

    Young, R H; Scully, R E

    2001-08-01

    The differential diagnosis of ovarian tumors is reviewed based on their patterns and cell types. This approach, which differs from the standard textbook discussion of each neoplasm as an entity, has practical value as differential diagnosis depends largely on the pattern or patterns and cell type or types of tumors. Awareness of the broad range of lesions that may exhibit particular patterns or contain one or more cell types is crucial in formulating a differential diagnosis. The following patterns are considered: moderate-to-large-glandular and hollow-tubular; solid tubular and pseudotubular; cords and ribbons; insular; trabecular; slit-like and reticular spaces; microglandular and microfollicular; macrofollicular and pseudomacrofollicular; papillary; diffuse; fibromatous-thecomatous; and biphasic and pseudobiphasic. The following cell types are considered: small round cells; spindle cells; mucinous cells, comprising columnar, goblet cell and signet ring cell subtypes; clear cells; hobnail cells; oxyphil cells; and transitional cells. The morphologic diversity of ovarian tumors poses many challenges; knowledge of the occurrence and frequency of these patterns and cell types in various tumors and tumor-like lesions is of paramount diagnostic importance. A specific diagnosis can usually be made by evaluating routinely stained slides, but much less often, special staining, immunohistochemical staining or, very rarely, ultrastructural examination is also required. Finally, clinical data, operative findings, and gross features of the lesions may provide important, and at times decisive diagnostic clues.

  12. 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

  13. Evaluation of PCR-based preimplantation genetic diagnosis applied to monogenic diseases: a collaborative ESHRE PGD consortium study.

    PubMed

    Dreesen, Jos; Destouni, Aspasia; Kourlaba, Georgia; Degn, Birte; Mette, Wulf Christensen; Carvalho, Filipa; Moutou, Celine; Sengupta, Sioban; Dhanjal, Seema; Renwick, Pamela; Davies, Steven; Kanavakis, Emmanouel; Harton, Gary; Traeger-Synodinos, Joanne

    2014-08-01

    Preimplantation genetic diagnosis (PGD) for monogenic disorders currently involves polymerase chain reaction (PCR)-based methods, which must be robust, sensitive and highly accurate, precluding misdiagnosis. Twelve adverse misdiagnoses reported to the ESHRE PGD-Consortium are likely an underestimate. This retrospective study, involving six PGD centres, assessed the validity of PCR-based PGD through reanalysis of untransferred embryos from monogenic-PGD cycles. Data were collected on the genotype concordance at PGD and follow-up from 940 untransferred embryos, including details on the parameters of PGD cycles: category of monogenic disease, embryo morphology, embryo biopsy and genotype assay strategy. To determine the validity of PCR-based PGD, the sensitivity (Se), specificity (Sp) and diagnostic accuracy were calculated. Stratified analyses were also conducted to assess the influence of the parameters above on the validity of PCR-based PGD. The analysis of overall data showed that 93.7% of embryos had been correctly classified at the time of PGD, with Se of 99.2% and Sp of 80.9%. The stratified analyses found that diagnostic accuracy is statistically significantly higher when PGD is performed on two cells versus one cell (P=0.001). Se was significantly higher when multiplex protocols versus singleplex protocols were applied (P=0.005), as well as for PGD applied on cells from good compared with poor morphology embryos (P=0.032). Morphology, however, did not affect diagnostic accuracy. Multiplex PCR-based methods on one cell, are as robust as those on two cells regarding false negative rate, which is the most important criteria for clinical PGD applications. Overall, this study demonstrates the validity, robustness and high diagnostic value of PCR-based PGD.

  14. Observer based on-line fault diagnosis of continuous systems modeled as Petri nets.

    PubMed

    Renganathan, K; Bhaskar, Vidhyacharan

    2010-10-01

    This paper describes a technique for achieving on-line fault diagnosis in continuous systems that are modeled using Petri nets. The effect of place markings and transition markings are considered and based on the computed error between the initial marking and subsequent markings evolved in time, the faults are categorized assuming that the markings are both observable and unobservable. An algorithm has been suitably proposed for achieving detection of faults for a typical continuous three tank system along with suitable results.

  15. Knowledge-based and integrated monitoring and diagnosis in autonomous power systems

    NASA Technical Reports Server (NTRS)

    Momoh, J. A.; Zhang, Z. Z.

    1990-01-01

    A new technique of knowledge-based and integrated monitoring and diagnosis (KBIMD) to deal with abnormalities and incipient or potential failures in autonomous power systems is presented. The KBIMD conception is discussed as a new function of autonomous power system automation. Available diagnostic modelling, system structure, principles and strategies are suggested. In order to verify the feasibility of the KBIMD, a preliminary prototype expert system is designed to simulate the KBIMD function in a main electric network of the autonomous power system.

  16. 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.

  17. Delayed diagnosis of central skull-base osteomyelitis with abscess: case report and learning points.

    PubMed

    Chawdhary, G; Hussain, S; Corbridge, R

    2017-01-01

    Central skull-base osteomyelitis (CSBO) is a rare life-threatening infection, usually resulting from medial spread of necrotising otitis externa. Here, we describe a case with no identifiable source of infection, causing a delay in diagnosis. An 80-year-old man with Crohn's disease treated with mesalazine presented with collapse and tonic-clonic seizure. Computed tomography and magnetic resonance imaging showed a nasopharyngeal mass that was initially thought to be a neoplasm. Awaiting formal biopsy, he represented with collapse and repeat imaging showed features of abscess formation. Review of previous scans revealed skull-base erosion and the diagnosis was revised to skull-base osteomyelitis. This is the first reported case of CSBO associated with mesalazine use, an aminosalicylate used in Crohn's disease. It is only the second reported case with abscess formation. We discuss the learning points in making a timely diagnosis and examine the potential association of factors such as mesalazine use and abscess formation in this case.

  18. Centrifugal compressor fault diagnosis based on qualitative simulation and thermal parameters

    NASA Astrophysics Data System (ADS)

    Lu, Yunsong; Wang, Fuli; Jia, Mingxing; Qi, Yuanchen

    2016-12-01

    This paper concerns fault diagnosis of centrifugal compressor based on thermal parameters. An improved qualitative simulation (QSIM) based fault diagnosis method is proposed to diagnose the faults of centrifugal compressor in a gas-steam combined-cycle power plant (CCPP). The qualitative models under normal and two faulty conditions have been built through the analysis of the principle of centrifugal compressor. To solve the problem of qualitative description of the observations of system variables, a qualitative trend extraction algorithm is applied to extract the trends of the observations. For qualitative states matching, a sliding window based matching strategy which consists of variables operating ranges constraints and qualitative constraints is proposed. The matching results are used to determine which QSIM model is more consistent with the running state of system. The correct diagnosis of two typical faults: seal leakage and valve stuck in the centrifugal compressor has validated the targeted performance of the proposed method, showing the advantages of fault roots containing in thermal parameters.

  19. Metabolic profile at first-time schizophrenia diagnosis: a population-based cross-sectional study

    PubMed Central

    Horsdal, Henriette Thisted; Benros, Michael Eriksen; Köhler-Forsberg, Ole; Krogh, Jesper; Gasse, Christiane

    2017-01-01

    Objective Schizophrenia and/or antipsychotic drug use are associated with metabolic abnormalities; however, knowledge regarding metabolic status and physician’s monitoring of metabolic status at first schizophrenia diagnosis is sparse. We assessed the prevalence of monitoring for metabolic blood abnormalities and characterized the metabolic profiles in people with a first-time schizophrenia diagnosis. Methods This is a population-based cross-sectional study including all adults born in Denmark after January 1, 1955, with their first schizophrenia diagnosis between 2000 and 2012 in the Central Denmark Region. Information on metabolic parameters was obtained from a clinical laboratory information system. Associations were calculated using Wilcoxon rank-sum tests, chi-square tests, logistic regression, and Spearman’s correlation coefficients. Results A total of 2,452 people with a first-time schizophrenia diagnosis were identified, of whom 1,040 (42.4%) were monitored for metabolic abnormalities. Among those monitored, 58.4% had an abnormal lipid profile and 13.8% had an abnormal glucose profile. People who had previously filled prescription(s) for antipsychotic drugs were more likely to present an abnormal lipid measure (65.7% vs 46.8%, P<0.001) and abnormal glucose profile (16.4% vs 10.1%, P=0.01). Conclusion Metabolic abnormalities are common at first schizophrenia diagnosis, particularly among those with previous antipsychotic prescription(s). Increased metabolic abnormalities already present in the early phase of schizophrenia emphasize the need for increased monitoring and management. PMID:28280344

  20. A hybrid fault diagnosis approach based on mixed-domain state features for rotating machinery.

    PubMed

    Xue, Xiaoming; Zhou, Jianzhong

    2017-01-01

    To make further improvement in the diagnosis accuracy and efficiency, a mixed-domain state features data based hybrid fault diagnosis approach, which systematically blends both the statistical analysis approach and the artificial intelligence technology, is proposed in this work for rolling element bearings. For simplifying the fault diagnosis problems, the execution of the proposed method is divided into three steps, i.e., fault preliminary detection, fault type recognition and fault degree identification. In the first step, a preliminary judgment about the health status of the equipment can be evaluated by the statistical analysis method based on the permutation entropy theory. If fault exists, the following two processes based on the artificial intelligence approach are performed to further recognize the fault type and then identify the fault degree. For the two subsequent steps, mixed-domain state features containing time-domain, frequency-domain and multi-scale features are extracted to represent the fault peculiarity under different working conditions. As a powerful time-frequency analysis method, the fast EEMD method was employed to obtain multi-scale features. Furthermore, due to the information redundancy and the submergence of original feature space, a novel manifold learning method (modified LGPCA) is introduced to realize the low-dimensional representations for high-dimensional feature space. Finally, two cases with 12 working conditions respectively have been employed to evaluate the performance of the proposed method, where vibration signals were measured from an experimental bench of rolling element bearing. The analysis results showed the effectiveness and the superiority of the proposed method of which the diagnosis thought is more suitable for practical application.

  1. Spinal tuberculosis: diagnosis and management.

    PubMed

    Rasouli, Mohammad R; Mirkoohi, Maryam; Vaccaro, Alexander R; Yarandi, Kourosh Karimi; Rahimi-Movaghar, Vafa

    2012-12-01

    The spinal column is involved in less than 1% of all cases of tuberculosis (TB). Spinal TB is a very dangerous typ