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Sample records for accurate diagnosis based

  1. 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

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

    PubMed

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

    2016-07-01

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

  3. 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).

  4. 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.

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

    PubMed

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

    2016-06-01

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

  6. Accurate Documentation of Malnutrition Diagnosis Reflects Increased Healthcare Resource Utilization.

    PubMed

    Phillips, Wendy

    2015-10-01

    Nutrition support professionals often care for the sickest of hospitalized patients. An understanding of healthcare payment models can help the nutrition support professional know how documentation of nutrition status can ensure maximum resources are available to care for these patients. Medicare is the major funding source for many hospitals in the United States. Hospitals receive payments using the Acute Care Hospital Inpatient Prospective Payment System, which classifies patients into Medical Severity Diagnosis-Related Groups (MS-DRGs) to determine payment amounts. Documentation of comorbidities and complications can increase the payment hospitals receive to offset increased resource utilization. This article explains how malnutrition documentation and coding can influence the case mix index, an indicator of level of acuity of patients treated at the hospital, and the payment the hospital receives to care for the patient.

  7. 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. PMID:25815362

  8. 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

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

    PubMed Central

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

    2003-01-01

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

  10. 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.

  11. Accurate Molecular Polarizabilities Based on Continuum Electrostatics

    PubMed Central

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

    2013-01-01

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

  12. 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…

  13. Accurate diagnosis of axillary lymph node metastasis using contrast-enhanced ultrasonography with Sonazoid

    PubMed Central

    MATSUZAWA, FUMIHIKO; EINAMA, TAKAHIRO; ABE, HIRONORI; SUZUKI, TAKASHI; HAMAGUCHI, JUN; KAGA, TERUMI; SATO, MAMI; OOMURA, MASAKO; TAKATA, YUMIKO; FUJIBE, AYAKO; TAKEDA, CHIE; TAMURA, ETSUYA; TAKETOMI, AKINOBU; KYUNO, KENICHI

    2015-01-01

    Axillary lymph node enlargement following sentinel lymph node biopsy (SLNB) is often difficult to accurately diagnose. In keeping with the characteristically tortuous and aberrant pattern of tumor neovasculature, metastatic lymph nodes exhibit peripheral and mixed vascularity, resulting in a microvasculature that is often difficult to visualize. Contrast-enhanced ultrasonography (CEUS) with Sonazoid, a new generation contrast agent for ultrasonography, allows for the visualization of lymph node microvessels and may enable a more accurate evaluation of lymph node metastasis. This is a case report of axillary lymph node enlargement following SLNB, in which CEUS with Sonazoid resulted in an accurate diagnosis. On the basis of our experience with this case, we have initiated a clinical trial to evaluate the detection of lymph node metastasis through the use of CEUS in breast cancer patients. PMID:25798257

  14. Primary leiomyoma of the liver: accurate preoperative diagnosis on liver biopsy

    PubMed Central

    Sousa, Helena T; Portela, Francisco; Semedo, Luis; Furtado, Emanuel; Marinho, Carol; Cipriano, Maria A; Leitão, Maximino C

    2009-01-01

    Primary leiomyoma of the liver is an exceptionally rare tumour in non-immunocompromised patients. Preoperative diagnosis of the lesion is difficult as complete imaging of this type of lesion is scarcely defined and preoperative biopsy was not the practice in previously reported cases. We report a voluminous primary leiomyoma of the liver occurring in a healthy middle-aged woman where a preoperative diagnosis was accurately achieved on biopsy. Because of its size, surgery was undertaken for exclusion of malignancy. A 16-month uneventful follow-up has been completed. We discuss the advantage of a preoperative diagnosis and propose that an imaging-guided liver biopsy should be undertaken, provided malignancy features are absent. This could prevent liver surgery merely for diagnostic purposes. Finally, we report imaging features that have not been previously described, namely on magnetic resonance imaging, which may provide an insight about the nature of this particular lesion and, advantageously, contribute toward a non-invasive diagnosis. PMID:21686574

  15. Gabor feature-based registration: accurate alignment without fiducial markers

    NASA Astrophysics Data System (ADS)

    Parra, Nestor A.; Parra, Carlos A.

    2007-03-01

    Accurate registration of diagnosis and treatment images is a critical factor for the success of radiotherapy. This study presents a feature-based image registration algorithm that uses a branch- and-bound method to search the space of possible transformations, as well as a Hausdorff distance metric to evaluate their quality. This distance is computed in the space of responses to a circular Gabor filter, in which, for each point of interest in both reference and subject images, a vector of complex responses to different Gabor kernels is computed. Each kernel is generated using different frequencies and variances of the Gabor function, which determines correspondent regions in the images to be registered, by virtue of its rotation invariance characteristics. Responses to circular Gabor filters have also been reported in literature as a successful tool for image classification; and in this particular application we utilize them for patient positioning in cranial radiotherapy. For test purposes, we use 2D portal images acquired with an electronic portal imaging device (EPID). Our method presents EPID-EPID registrations errors under 0.2 mm for translations and 0.05 deg for rotations (subpixel accuracy). We are using fiducial marker registration as the ground truth for comparisons. Registration times average 2.70 seconds based on 1400 feature points using a 1.4 GHz processor.

  16. 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.

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

    PubMed

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

    2014-07-01

    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.

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. Biotechnology-based allergy diagnosis and vaccination.

    PubMed

    Bhalla, Prem L; Singh, Mohan B

    2008-03-01

    The diagnosis and immunotherapy currently applied to allergic diseases involve the use of crude extracts of the allergen source without defining the allergy-eliciting molecule(s). Advances in recombinant DNA technology have made identification, cloning, expression and epitope mapping of clinically significant allergens possible. Recombinant allergens that retain the immunological features of natural allergens form the basis of accurate protein-chip-based methods for diagnosing allergic conditions. The ability to produce rationally designed hypoallergenic forms of allergens is leading to the development of novel and safe forms of allergy vaccines with improved efficacy. The initial clinical tests on recombinant-allergen-based vaccine preparations have provided positive results, and ongoing developments in areas such as alternative routes of vaccine delivery will enhance patient compliance.

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

    PubMed

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

    2016-09-14

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

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

    PubMed

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

    2016-09-14

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

  5. Light Field Imaging Based Accurate Image Specular Highlight Removal.

    PubMed

    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

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

    NASA Astrophysics Data System (ADS)

    Wellhausen, Jens

    2003-12-01

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

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. Accurate diagnosis of Helicobacter pylori. 13C-urea breath test.

    PubMed

    Graham, D Y; Klein, P D

    2000-12-01

    The preferred schema for management of Helicobacter pylori infection is diagnosis, treatment, and confirmation of cure. The 13C-urea breath test is ideal for active H. pylori infection for those in whom endoscopy is not required (e.g., those in whom cancer is not suspected) because it offers the combination of simplicity, accuracy, reliability, and absence of exposure to radioactivity. New versions of the test also offer increasing simplicity and lower costs. PMID:11190073

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

    PubMed

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

    2016-01-01

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

  13. 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

  14. 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

    2016-08-01

    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.

  15. 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.

  16. 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.

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

    PubMed

    James, Veronica J

    2009-07-01

    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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

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

    PubMed

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

    2016-08-01

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

  3. 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.

  4. 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

  5. Distributed real-time model-based diagnosis

    NASA Technical Reports Server (NTRS)

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

    2003-01-01

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

  6. 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.

  7. Immunity-based diagnosis for a motherboard.

    PubMed

    Shida, Haruki; Okamoto, Takeshi; Ishida, Yoshiteru

    2011-01-01

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

  8. Fast Algorithms for Model-Based Diagnosis

    NASA Technical Reports Server (NTRS)

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

    2005-01-01

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

  9. 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.

  10. 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

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

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

    PubMed Central

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

    2016-01-01

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

  13. An Accurate Scalable Template-based Alignment Algorithm.

    PubMed

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

    2012-12-31

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

  14. A Novel IgM-capture enzyme-linked immunosorbent assay using recombinant Vag8 fusion protein for the accurate and early diagnosis of Bordetella pertussis infection.

    PubMed

    Otsuka, Nao; Gotoh, Kensei; Nishimura, Naoko; Ozaki, Takao; Nakamura, Yukitsugu; Haga, Kiyohito; Yamazaki, Makoto; Gondaira, Fumio; Okada, Kenji; Miyaji, Yusuke; Toyoizumi-Ajisaka, Hiromi; Shibayama, Keigo; Arakawa, Yoshichika; Kamachi, Kazunari

    2016-05-01

    An ELISA that measures anti-PT IgG antibody has been used widely for the serodiagnosis of pertussis; however, the IgG-based ELISA is inadequate for patients during the acute phase of the disease because of the slow response of anti-PT IgG antibodies. To solve this problem, we developed a novel IgM-capture ELISA that measures serum anti-Bordetella pertussis Vag8 IgM levels for the accurate and early diagnosis of pertussis. First, we confirmed that Vag8 was highly expressed in all B. pertussis isolates tested (n = 30), but little or none in other Bordetella species, and that DTaP vaccines did not induce anti-Vag8 IgG antibodies in mice (i.e. the antibody level could be unaffected by the vaccination). To determine the immune response to Vag8 in B. pertussis infection, anti-Vag8 IgM levels were compared between 38 patients (acute phase of pertussis) and 29 healthy individuals using the anti-Vag8 IgM-capture ELISA. The results revealed that the anti-Vag8 IgM levels were significantly higher in the patients compared with the healthy individuals (P < 0.001). ROC analysis also showed that the anti-Vag8 IgM-capture ELISA has higher diagnostic accuracy (AUC, 0.92) than a commercial anti-PT IgG ELISA kit. Moreover, it was shown that anti-Vag8 IgM antibodies were induced earlier than anti-PT IgG antibodies on sequential patients' sera. These data indicate that our novel anti-Vag8 IgM-capture ELISA is a potentially useful tool for making the accurate and early diagnosis of B. pertussis infection.

  15. 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.

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

    ERIC Educational Resources Information Center

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

    2012-01-01

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

  17. Metal-based nanosystems for diagnosis.

    PubMed

    Popescu, Roxana Cristina; Fufă, Mariana Oana Mihaela; Grumezescu, Alexandru Mihai

    2015-01-01

    The impressive diversity related to etiologic factors and the distinctive genetic and immunological behavior attained by various conditions represent the fundamental reasons for high-rated inefficient and eventual hazardous strategies entailed by conventional healthcare practice. Thanks to the tremendous progress reported in nanotechnology during the last decades, various unconventional and promising strategies have been successfully developed and examined with respect to potential genuine biomedical applications. Given the amazing possibility to manipulate matter at a molecular and atomic level and the incessant need to design and implement personalized therapies, various nanosized systems have thus been engineered. Among the newly developed nanomaterials, metallic nanoparticles have gain attention during the intense biomedical research activity, thanks to their peculiar size-conditioned properties. An efficient therapeutic strategy begins with an accurate diagnosis result, so the immediate requirement of such specific detection tools is conspicuous. The use of silver and gold in day-to-day activities is acknowledged since ancient times, but the novel technological opportunities extended their particular applications towards personalized medicine. It is worthy to mention that the unexpected nanodimension-related features of the aforementioned noble metals strongly recommend them for a large number of current applications in nanomedicine, including novel and specific metallic nanostructures used in diagnostics.

  18. 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

    2014-08-01

    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.

  19. 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.

  20. 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.

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

    PubMed

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

    1997-04-01

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

  2. 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.

  3. 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

  4. 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

  5. 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

  6. 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.

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

    PubMed

    Roses, A D

    2016-02-01

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

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

    SciTech Connect

    Asheim, H.

    1984-10-01

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

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

    PubMed Central

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

    2016-01-01

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

  10. An accurate, convective energy equation based automated meshing technique for analysis of blood vessels and tissues.

    PubMed

    White, J A; Dutton, A W; Schmidt, J A; Roemer, R B

    2000-01-01

    An automated three-element meshing method for generating finite element based models for the accurate thermal analysis of blood vessels imbedded in tissue has been developed and evaluated. The meshing method places eight noded hexahedral elements inside the vessels where advective flows exist, and four noded tetrahedral elements in the surrounding tissue. The higher order hexahedrals are used where advective flow fields occur, since high accuracy is required and effective upwinding algorithms exist. Tetrahedral elements are placed in the remaining tissue region, since they are computationally more efficient and existing automatic tetrahedral mesh generators can be used. Five noded pyramid elements connect the hexahedrals and tetrahedrals. A convective energy equation (CEE) based finite element algorithm solves for the temperature distributions in the flowing blood, while a finite element formulation of a generalized conduction equation is used in the surrounding tissue. Use of the CEE allows accurate solutions to be obtained without the necessity of assuming ad hoc values for heat transfer coefficients. Comparisons of the predictions of the three-element model to analytical solutions show that the three-element model accurately simulates temperature fields. Energy balance checks show that the three-element model has small, acceptable errors. In summary, this method provides an accurate, automatic finite element gridding procedure for thermal analysis of irregularly shaped tissue regions that contain important blood vessels. At present, the models so generated are relatively large (in order to obtain accurate results) and are, thus, best used for providing accurate reference values for checking other approximate formulations to complicated, conjugated blood heat transfer problems.

  11. 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

  12. 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

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

    PubMed

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

    2013-01-01

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

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

    PubMed

    Girard, J

    1994-05-01

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

  15. 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.

  16. An accurate single-electron pump based on a highly tunable silicon quantum dot.

    PubMed

    Rossi, Alessandro; Tanttu, Tuomo; Tan, Kuan Yen; Iisakka, Ilkka; Zhao, Ruichen; Chan, Kok Wai; Tettamanzi, Giuseppe C; Rogge, Sven; Dzurak, Andrew S; Möttönen, Mikko

    2014-06-11

    Nanoscale single-electron pumps can be used to generate accurate currents, and can potentially serve to realize a new standard of electrical current based on elementary charge. Here, we use a silicon-based quantum dot with tunable tunnel barriers as an accurate source of quantized current. The charge transfer accuracy of our pump can be dramatically enhanced by controlling the electrostatic confinement of the dot using purposely engineered gate electrodes. Improvements in the operational robustness, as well as suppression of nonadiabatic transitions that reduce pumping accuracy, are achieved via small adjustments of the gate voltages. We can produce an output current in excess of 80 pA with experimentally determined relative uncertainty below 50 parts per million.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

    Sengupta, Arkajyoti; Raghavachari, Krishnan

    2014-10-14

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

  20. Accurate and efficient loop selections by the DFIRE-based all-atom statistical potential.

    PubMed

    Zhang, Chi; Liu, Song; Zhou, Yaoqi

    2004-02-01

    The conformations of loops are determined by the water-mediated interactions between amino acid residues. Energy functions that describe the interactions can be derived either from physical principles (physical-based energy function) or statistical analysis of known protein structures (knowledge-based statistical potentials). It is commonly believed that statistical potentials are appropriate for coarse-grained representation of proteins but are not as accurate as physical-based potentials when atomic resolution is required. Several recent applications of physical-based energy functions to loop selections appear to support this view. In this article, we apply a recently developed DFIRE-based statistical potential to three different loop decoy sets (RAPPER, Jacobson, and Forrest-Woolf sets). Together with a rotamer library for side-chain optimization, the performance of DFIRE-based potential in the RAPPER decoy set (385 loop targets) is comparable to that of AMBER/GBSA for short loops (two to eight residues). The DFIRE is more accurate for longer loops (9 to 12 residues). Similar trend is observed when comparing DFIRE with another physical-based OPLS/SGB-NP energy function in the large Jacobson decoy set (788 loop targets). In the Forrest-Woolf decoy set for the loops of membrane proteins, the DFIRE potential performs substantially better than the combination of the CHARMM force field with several solvation models. The results suggest that a single-term DFIRE-statistical energy function can provide an accurate loop prediction at a fraction of computing cost required for more complicate physical-based energy functions. A Web server for academic users is established for loop selection at the softwares/services section of the Web site http://theory.med.buffalo.edu/.

  1. Accurate and fast fiber transfer delay measurement based on phase discrimination and frequency measurement

    NASA Astrophysics Data System (ADS)

    Dong, J. W.; Wang, B.; Gao, C.; Wang, L. J.

    2016-09-01

    An accurate and fast fiber transfer delay measurement method is demonstrated. As a key technique, a simple ambiguity resolving process based on phase discrimination and frequency measurement is used to overcome the contradiction between measurement accuracy and system complexity. The system achieves a high measurement accuracy of 0.2 ps with a 0.1 ps measurement resolution and a large dynamic range up to 50 km as well as no dead zone.

  2. Novel accurate and scalable 3-D MT forward solver based on a contracting integral equation method

    NASA Astrophysics Data System (ADS)

    Kruglyakov, M.; Geraskin, A.; Kuvshinov, A.

    2016-11-01

    We present a novel, open source 3-D MT forward solver based on a method of integral equations (IE) with contracting kernel. Special attention in the solver is paid to accurate calculations of Green's functions and their integrals which are cornerstones of any IE solution. The solver supports massive parallelization and is able to deal with highly detailed and contrasting models. We report results of a 3-D numerical experiment aimed at analyzing the accuracy and scalability of the code.

  3. 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.

  4. Can simple tests performed in the primary care setting provide accurate and efficient diagnosis of benign prostatic hyperplasia? Rationale and design of the Diagnosis Improvement in Primary Care Trial.

    PubMed

    Carballido, J; Fourcade, R; Pagliarulo, A; Cricelli, C; Brenes, F; Pedromingo-Marino, A; Castro, R

    2009-08-01

    Effective treatment of benign prostatic hyperplasia (BPH) improves lower urinary tract symptoms (LUTS) and patient quality of life, and reduces the risk of complications arising from disease progression. However, treatment can only be initiated when men with BPH are identified by accurate diagnostic tests. Current evidence suggests that diagnostic procedures employed by primary care physicians vary widely across Europe. The expected increases in BPH prevalence accompanying the gradual aging of the population, coupled with greater use of medical therapy, mean that general practitioners (GPs) are likely to have an increasingly important role in managing the condition. The GP/primary care clinic is therefore an attractive target location for strategies designed to improve the accuracy of BPH diagnosis. The Diagnosis Improvement in Primary Care Trial (D-IMPACT) is a prospective, multicentre, epidemiological study that aims to identify the optimal subset of simple tests applied by GPs in the primary care setting to diagnose BPH in men who spontaneously report obstructive (voiding) and/or irritative (storage) LUTS. These tests comprise medical history, symptom assessment with the International Prostate Symptom Score questionnaire, urinalysis, measurement of serum levels of prostate-specific antigen and subjective GP diagnosis after completing all tests including digital rectal examination. GP diagnoses and all other tests will be compared with gold-standard diagnoses provided by specialist urologists following completion of additional diagnostic tests. D-IMPACT will establish the diagnostic performance using a non-subjective and reproducible algorithm. An adjusted and multivariate analysis of the results of D-IMPACT will allow identification of the most efficient combination of tests that facilitate accurate BPH diagnosis in the primary care setting. In addition, D-IMPACT will estimate the prevalence of BPH in patients who present spontaneously to GPs with LUTS. PMID

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. Secure Medical Diagnosis Using Rule Based Mining

    NASA Astrophysics Data System (ADS)

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

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

  10. 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

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

    PubMed Central

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

    2016-01-01

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

  12. An Accurate Scene Segmentation Method Based on Graph Analysis Using Object Matching and Audio Feature

    NASA Astrophysics Data System (ADS)

    Yamamoto, Makoto; Haseyama, Miki

    A method for accurate scene segmentation using two kinds of directed graph obtained by object matching and audio features is proposed. Generally, in audiovisual materials, such as broadcast programs and movies, there are repeated appearances of similar shots that include frames of the same background, object or place, and such shots are included in a single scene. Many scene segmentation methods based on this idea have been proposed; however, since they use color information as visual features, they cannot provide accurate scene segmentation results if the color features change in different shots for which frames include the same object due to camera operations such as zooming and panning. In order to solve this problem, scene segmentation by the proposed method is realized by using two novel approaches. In the first approach, object matching is performed between two frames that are each included in different shots. By using these matching results, repeated appearances of shots for which frames include the same object can be successfully found and represented as a directed graph. The proposed method also generates another directed graph that represents the repeated appearances of shots with similar audio features in the second approach. By combined use of these two directed graphs, degradation of scene segmentation accuracy, which results from using only one kind of graph, can be avoided in the proposed method and thereby accurate scene segmentation can be realized. Experimental results performed by applying the proposed method to actual broadcast programs are shown to verify the effectiveness of the proposed method.

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

    NASA Astrophysics Data System (ADS)

    Brndiar, Jan; Stich, Ivan

    2012-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  15. 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.

  16. Comparison of Procedure-Based and Diagnosis-Based Identifications of Severe Sepsis and Disseminated Intravascular Coagulation in Administrative Data

    PubMed Central

    Yamana, Hayato; Horiguchi, Hiromasa; Fushimi, Kiyohide; Yasunaga, Hideo

    2016-01-01

    Background Diagnoses recorded in administrative databases have limited utility for accurate identification of severe sepsis and disseminated intravascular coagulation (DIC). We evaluated the performance of alternative identification methods that use procedure records. Methods We obtained data for adult patients admitted to intensive care units in three hospitals during a 1-year period. Severe sepsis and DIC were identified by three means: laboratory data, diagnoses, and procedures. Using laboratory data as a reference, the sensitivity and specificity of procedure-based methods and diagnosis-based methods were compared. Results Of 595 intensive care unit admissions, 212 (35.6%) and 81 (13.6%) were identified as severe sepsis and DIC, respectively, using laboratory data. The sensitivity of procedure-based methods for identifying severe sepsis was 64.2%, and the specificity was 65.3%. Two diagnosis-based methods —the Angus and Martin algorithms— exhibited sensitivities of 21.7% and 14.6% and specificities of 98.7% and 99.5%, respectively, for severe sepsis. For DIC, the sensitivity of procedure-based methods was 55.6%, and the specificity was 67.1%, and the sensitivity and specificity of diagnosis-based methods were 35.8% and 98.2%, respectively. Conclusions Procedure-based methods were more sensitive and less specific than diagnosis-based methods in identifying severe sepsis and DIC. Procedure records could improve disease identification in administrative databases. PMID:27064132

  17. 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.

  18. 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.

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

    NASA Astrophysics Data System (ADS)

    Li, Mingxia; Feng, Zhihua

    2016-07-01

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

  20. Accurate coronary modeling procedure using 2D calibrated projections based on 2D centerline points on a single projection

    NASA Astrophysics Data System (ADS)

    Movassaghi, Babak; Rasche, Volker; Viergever, Max A.; Niessen, Wiro J.

    2004-05-01

    For the diagnosis of ischemic heart disease, accurate quantitative analysis of the coronary arteries is important. In coronary angiography, a number of projections is acquired from which 3D models of the coronaries can be reconstructed. A signifcant limitation of the current 3D modeling procedures is the required user interaction for defining the centerlines of the vessel structures in the 2D projections. Currently, the 3D centerlines of the coronary tree structure are calculated based on the interactively determined centerlines in two projections. For every interactively selected centerline point in a first projection the corresponding point in a second projection has to be determined interactively by the user. The correspondence is obtained based on the epipolar-geometry. In this paper a method is proposed to retrieve all the information required for the modeling procedure, by the interactive determination of the 2D centerline-points in only one projection. For every determined 2D centerline-point the corresponding 3D centerline-point is calculated by the analysis of the 1D gray value functions of the corresponding epipolarlines in space for all available 2D projections. This information is then used to build a 3D representation of the coronary arteries using coronary modeling techniques. The approach is illustrated on the analysis of calibrated phantom and calibrated coronary projection data.

  1. 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.

  2. 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

  3. 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.

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

    PubMed

    Youyou, Wu; Kosinski, Michal; Stillwell, David

    2015-01-27

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

  5. 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.

  6. 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.

  7. 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.

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

    PubMed

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

    2014-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

  10. Accurate Segmentation of Cervical Cytoplasm and Nuclei Based on Multiscale Convolutional Network and Graph Partitioning.

    PubMed

    Song, Youyi; Zhang, Ling; Chen, Siping; Ni, Dong; Lei, Baiying; Wang, Tianfu

    2015-10-01

    In this paper, a multiscale convolutional network (MSCN) and graph-partitioning-based method is proposed for accurate segmentation of cervical cytoplasm and nuclei. Specifically, deep learning via the MSCN is explored to extract scale invariant features, and then, segment regions centered at each pixel. The coarse segmentation is refined by an automated graph partitioning method based on the pretrained feature. The texture, shape, and contextual information of the target objects are learned to localize the appearance of distinctive boundary, which is also explored to generate markers to split the touching nuclei. For further refinement of the segmentation, a coarse-to-fine nucleus segmentation framework is developed. The computational complexity of the segmentation is reduced by using superpixel instead of raw pixels. Extensive experimental results demonstrate that the proposed cervical nucleus cell segmentation delivers promising results and outperforms existing methods.

  11. Accurate multiple view 3D reconstruction using patch-based stereo for large-scale scenes.

    PubMed

    Shen, Shuhan

    2013-05-01

    In this paper, we propose a depth-map merging based multiple view stereo method for large-scale scenes which takes both accuracy and efficiency into account. In the proposed method, an efficient patch-based stereo matching process is used to generate depth-map at each image with acceptable errors, followed by a depth-map refinement process to enforce consistency over neighboring views. Compared to state-of-the-art methods, the proposed method can reconstruct quite accurate and dense point clouds with high computational efficiency. Besides, the proposed method could be easily parallelized at image level, i.e., each depth-map is computed individually, which makes it suitable for large-scale scene reconstruction with high resolution images. The accuracy and efficiency of the proposed method are evaluated quantitatively on benchmark data and qualitatively on large data sets.

  12. 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

  13. 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.

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2005-12-01

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

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

    PubMed

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

    2016-09-01

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

  17. 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

  18. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  20. 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.

  1. 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

  2. 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

  3. Biased Randomized Algorithm for Fast Model-Based Diagnosis

    NASA Technical Reports Server (NTRS)

    Williams, Colin; Vartan, Farrokh

    2005-01-01

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

  4. 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.

  5. Allowable forward model misspecification for accurate basis decomposition in a silicon detector based spectral CT.

    PubMed

    Bornefalk, Hans; Persson, Mats; Danielsson, Mats

    2015-03-01

    Material basis decomposition in the sinogram domain requires accurate knowledge of the forward model in spectral computed tomography (CT). Misspecifications over a certain limit will result in biased estimates and make quantum limited (where statistical noise dominates) quantitative CT difficult. We present a method whereby users can determine the degree of allowed misspecification error in a spectral CT forward model and still have quantification errors that are limited by the inherent statistical uncertainty. For a particular silicon detector based spectral CT system, we conclude that threshold determination is the most critical factor and that the bin edges need to be known to within 0.15 keV in order to be able to perform quantum limited material basis decomposition. The method as such is general to all multibin systems.

  6. 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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    DOEpatents

    Asaad, Sameth W.; Kapur, Mohit

    2016-01-05

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

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

    PubMed

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

    2015-07-01

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

  10. Apparatus for accurate density measurements of fluids based on a magnetic suspension balance

    NASA Astrophysics Data System (ADS)

    Gong, Maoqiong; Li, Huiya; Guo, Hao; Dong, Xueqiang; Wu, J. F.

    2012-06-01

    A new apparatus for accurate pressure, density and temperature (p, ρ, T) measurements over wide ranges of (p, ρ, T) (90 K to 290 K; 0 MPa to 3 MPa; 0 kg/m3 to 2000 kg/m3) is described. This apparatus is based on a magnetic suspension balance which applies the Archimedes' buoyancy principle. In order to verify the new apparatus, comprehensive (p, ρ, T) measurements on pure nitrogen were carried out. The maximum relative standard uncertainty is 0.09% in density. The maximum standard uncertainty in temperature is 5 mK, and that in pressure is 250 Pa for 1.5 MPa and 390 Pa for 3MPa full scale range respectively. The experimental data were compared with selected literature data and good agreements were found.

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

    PubMed Central

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

    2015-01-01

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

  12. 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.

  13. 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

  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. 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.

  16. 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.

  17. Fractal dimension based corneal fungal infection diagnosis

    NASA Astrophysics Data System (ADS)

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

    2006-08-01

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

  18. Grid technology in tissue-based diagnosis: fundamentals and potential developments.

    PubMed

    Görtler, Jürgen; Berghoff, Martin; Kayser, Gian; Kayser, Klaus

    2006-01-01

    Tissue-based diagnosis still remains the most reliable and specific diagnostic medical procedure. It is involved in all technological developments in medicine and biology and incorporates tools of quite different applications. These range from molecular genetics to image acquisition and recognition algorithms (for image analysis), or from tissue culture to electronic communication services. Grid technology seems to possess all features to efficiently target specific constellations of an individual patient in order to obtain a detailed and accurate diagnosis in providing all relevant information and references. Grid technology can be briefly explained by so-called nodes that are linked together and share certain communication rules in using open standards. The number of nodes can vary as well as their functionality, depending on the needs of a specific user at a given point in time. In the beginning of grid technology, the nodes were used as supercomputers in combining and enhancing the computation power. At present, at least five different Grid functions can be distinguished, that comprise 1) computation services, 2) data services, 3) application services, 4) information services, and 5) knowledge services. The general structures and functions of a Grid are described, and their potential implementation into virtual tissue-based diagnosis is analyzed. As a result Grid technology offers a new dimension to access distributed information and knowledge and to improving the quality in tissue-based diagnosis and therefore improving the medical quality.

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

    PubMed Central

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

    2016-01-01

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

  20. An accurate skull stripping method based on simplex meshes and histogram analysis for magnetic resonance images.

    PubMed

    Galdames, Francisco J; Jaillet, Fabrice; Perez, Claudio A

    2012-01-01

    Skull stripping methods are designed to eliminate the non-brain tissue in magnetic resonance (MR) brain images. Removal of non-brain tissues is a fundamental step in enabling the processing of brain MR images. The aim of this study is to develop an automatic accurate skull stripping method based on deformable models and histogram analysis. A rough-segmentation step is used to find the optimal starting point for the deformation and is based on thresholds and morphological operators. Thresholds are computed using comparisons with an atlas, and modeling by Gaussians. The deformable model is based on a simplex mesh and its deformation is controlled by the image local gray levels and the information obtained on the gray level modeling of the rough-segmentation. Our Simplex Mesh and Histogram Analysis Skull Stripping (SMHASS) method was tested on the following international databases commonly used in scientific articles: BrainWeb, Internet Brain Segmentation Repository (IBSR), and Segmentation Validation Engine (SVE). A comparison was performed against three of the best skull stripping methods previously published: Brain Extraction Tool (BET), Brain Surface Extractor (BSE), and Hybrid Watershed Algorithm (HWA). Performance was measured using the Jaccard index (J) and Dice coefficient (κ). Our method showed the best performance and differences were statistically significant (p<0.05): J=0.904 and κ=0.950 on BrainWeb; J=0.905 and κ=0.950 on IBSR; J=0.946 and κ=0.972 on SVE.

  1. 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.

  2. 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

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

    SciTech Connect

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

    2010-08-15

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

  4. 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.

  5. 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

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

    PubMed

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

    2016-09-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

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

    NASA Astrophysics Data System (ADS)

    Lim, Yee Yan; Kiong Soh, Chee

    2014-03-01

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

  9. 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. PMID:25227050

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. PNA-based microbial pathogen identification and resistance marker detection: an accurate, isothermal rapid assay based on genome-specific features

    PubMed Central

    Smolina, Irina; Miller, Nancy S.; Frank-Kamenetskii, Maxim

    2010-01-01

    With the rapidly growing availability of the entire genome sequences of microbial pathogens, there is unmet need for increasingly sensitive systems to monitor the gene-specific markers for diagnosis of bacteremia that enables an earlier detection of causative agent and determination of drug resistance. To address these challenges, a novel FISH-type genomic sequence-based molecular technique is proposed that can identify bacteria and simultaneously detect antibiotic resistance markers for rapid and accurate testing of pathogens. The approach is based on a synergistic combination of advanced Peptide Nucleic Acid (PNA)-based technology and signal-enhancing Rolling Circle Amplification (RCA) reaction to achieve a highly specific and sensitive assay. A specific PNA-DNA construct serves as an exceedingly selective and very effective biomarker, while RCA enhances detection sensitivity and provide with a highly multiplexed assay system. Distinct-color fluorescent decorator probes are used to identify about 20-nucleotide-long signature sequences in bacterial genomic DNA and/or key genetic markers of drug resistance in order to identify and characterize various pathogens. The technique's potential and its utility for clinical diagnostics are illustrated by identification of S. aureus with simultaneous discrimination of methicillin-sensitive (MSSA) versus methicillin-resistant (MRSA) strains. Overall these promising results hint to the adoption of PNA-based rapid sensitive detection for diagnosis of other clinically relevant organisms. Thereby, new assay enables significantly earlier administration of appropriate antimicrobial therapy and may, thus have a positive impact on the outcome of the patient. PMID:20953307

  16. 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

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

    PubMed

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

    2015-01-01

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

  18. A colorimetric-based accurate method for the determination of enterovirus 71 titer.

    PubMed

    Pourianfar, Hamid Reza; Javadi, Arman; Grollo, Lara

    2012-12-01

    The 50 % tissue culture infectious dose (TCID50) is still one of the most commonly used techniques for estimating virus titers. However, the traditional TCID50 assay is time consuming, susceptible to subjective errors and generates only quantal data. Here, we describe a colorimetric-based approach for the titration of Enterovirus 71 (EV71) using a modified method for making virus dilutions. In summary, the titration of EV71 using MTT or MTS staining with a modified virus dilution method decreased the time of the assay and eliminated the subjectivity of observational results, improving accuracy, reproducibility and reliability of virus titration, in comparison with the conventional TCID50 approach (p < 0.01). In addition, the results provided evidence that there was better correlation between a plaquing assay and our approach when compared to the traditional TCID50 approach. This increased accuracy also improved the ability to predict the number of virus plaque forming units present in a solution. These improvements could be of use for any virological experimentation, where a quick accurate titration of a virus capable of causing cell destruction is required or a sensible estimation of the number of viral plaques based on TCID50 of a virus is desired.

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

    PubMed

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

    2016-01-01

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

  20. 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

  1. 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

  2. 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

  3. 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.

  4. A diagnosis-based clinical decision rule for spinal pain part 2: review of the literature

    PubMed Central

    Murphy, Donald R; Hurwitz, Eric L; Nelson, Craig F

    2008-01-01

    Background Spinal pain is a common and often disabling problem. The research on various treatments for spinal pain has, for the most part, suggested that while several interventions have demonstrated mild to moderate short-term benefit, no single treatment has a major impact on either pain or disability. There is great need for more accurate diagnosis in patients with spinal pain. In a previous paper, the theoretical model of a diagnosis-based clinical decision rule was presented. The approach is designed to provide the clinician with a strategy for arriving at a specific working diagnosis from which treatment decisions can be made. It is based on three questions of diagnosis. In the current paper, the literature on the reliability and validity of the assessment procedures that are included in the diagnosis-based clinical decision rule is presented. Methods The databases of Medline, Cinahl, Embase and MANTIS were searched for studies that evaluated the reliability and validity of clinic-based diagnostic procedures for patients with spinal pain that have relevance for questions 2 (which investigates characteristics of the pain source) and 3 (which investigates perpetuating factors of the pain experience). In addition, the reference list of identified papers and authors' libraries were searched. Results A total of 1769 articles were retrieved, of which 138 were deemed relevant. Fifty-one studies related to reliability and 76 related to validity. One study evaluated both reliability and validity. Conclusion Regarding some aspects of the DBCDR, there are a number of studies that allow the clinician to have a reasonable degree of confidence in his or her findings. This is particularly true for centralization signs, neurodynamic signs and psychological perpetuating factors. There are other aspects of the DBCDR in which a lesser degree of confidence is warranted, and in which further research is needed. PMID:18694490

  5. Multi-reference-based multiple alignment statistics enables accurate protein-particle pickup from noisy images.

    PubMed

    Kawata, Masaaki; Sato, Chikara

    2013-04-01

    Data mining from noisy data/images is one of the most important themes in modern science and technology. Statistical image processing is a promising technique for analysing such data. Automation of particle pickup from noisy electron micrographs is essential, especially when improvement of the resolution of single particle analysis requires a huge number of particle images. For such a purpose, reference-based matching using primary three-dimensional (3D) model projections is mainly adopted. In the matching, however, the highest peaks of the correlation may not accurately indicate particles when the image is very noisy. In contrast, the density and the heights of the peaks should reflect the probability distribution of the particles. To statistically determine the particle positions from the peak distributions, we have developed a density-based peak search followed by a peak selection based on average peak height, using multi-reference alignment (MRA). Its extension, using multi-reference multiple alignment (MRMA), was found to enable particle pickup at higher accuracy even from extremely noisy images with a signal-to-noise ratio of 0.001. We refer to these new methods as stochastic pickup with MRA (MRA-StoPICK) or with MRMA (MRMA-StoPICK). MRMA-StoPICK has a higher pickup accuracy and furthermore, is almost independent of parameter settings. They were successfully applied to cryo-electron micrographs of Rice dwarf virus. Because current computational resources and parallel data processing environments allow somewhat CPU-intensive MRA-StoPICK and MRMA-StoPICK to be performed in a short period, these methods are expected to allow high-resolution analysis of the 3D structure of particles.

  6. 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

  7. 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.

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

    PubMed

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

    2015-01-01

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

  9. 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.}

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

    PubMed

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

    2015-07-01

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

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

    PubMed

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

    2014-02-01

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

  12. 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.

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

    PubMed

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

    2014-02-01

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

  14. Structural modal parameter identification and damage diagnosis based on Hilbert-Huang transform

    NASA Astrophysics Data System (ADS)

    Han, Jianping; Zheng, Peijuan; Wang, Hongtao

    2014-03-01

    Traditional modal parameter identification methods have many disadvantages, especially when used for processing nonlinear and non-stationary signals. In addition, they are usually not able to accurately identify the damping ratio and damage. In this study, methods based on the Hilbert-Huang transform (HHT) are investigated for structural modal parameter identification and damage diagnosis. First, mirror extension and prediction via a radial basis function (RBF) neural network are used to restrain the troublesome end-effect issue in empirical mode decomposition (EMD), which is a crucial part of HHT. Then, the approaches based on HHT combined with other techniques, such as the random decrement technique (RDT), natural excitation technique (NExT) and stochastic subspace identification (SSI), are proposed to identify modal parameters of structures. Furthermore, a damage diagnosis method based on the HHT is also proposed. Time-varying instantaneous frequency and instantaneous energy are used to identify the damage evolution of the structure. The relative amplitude of the Hilbert marginal spectrum is used to identify the damage location of the structure. Finally, acceleration records at gauge points from shaking table testing of a 12-story reinforced concrete frame model are taken to validate the proposed approaches. The results show that the proposed approaches based on HHT for modal parameter identification and damage diagnosis are reliable and practical.

  15. Accurate prediction of solvent accessibility using neural networks-based regression.

    PubMed

    Adamczak, Rafał; Porollo, Aleksey; Meller, Jarosław

    2004-09-01

    Accurate prediction of relative solvent accessibilities (RSAs) of amino acid residues in proteins may be used to facilitate protein structure prediction and functional annotation. Toward that goal we developed a novel method for improved prediction of RSAs. Contrary to other machine learning-based methods from the literature, we do not impose a classification problem with arbitrary boundaries between the classes. Instead, we seek a continuous approximation of the real-value RSA using nonlinear regression, with several feed forward and recurrent neural networks, which are then combined into a consensus predictor. A set of 860 protein structures derived from the PFAM database was used for training, whereas validation of the results was carefully performed on several nonredundant control sets comprising a total of 603 structures derived from new Protein Data Bank structures and had no homology to proteins included in the training. Two classes of alternative predictors were developed for comparison with the regression-based approach: one based on the standard classification approach and the other based on a semicontinuous approximation with the so-called thermometer encoding. Furthermore, a weighted approximation, with errors being scaled by the observed levels of variability in RSA for equivalent residues in families of homologous structures, was applied in order to improve the results. The effects of including evolutionary profiles and the growth of sequence databases were assessed. In accord with the observed levels of variability in RSA for different ranges of RSA values, the regression accuracy is higher for buried than for exposed residues, with overall 15.3-15.8% mean absolute errors and correlation coefficients between the predicted and experimental values of 0.64-0.67 on different control sets. The new method outperforms classification-based algorithms when the real value predictions are projected onto two-class classification problems with several commonly

  16. 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.

  17. 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.

  18. 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

  19. Next-generation sequencing-based molecular diagnosis of 82 retinitis pigmentosa probands from Northern Ireland

    PubMed Central

    Zhao, Li; Wang, Feng; Wang, Hui; Li, Yumei; Alexander, Sharon; Wang, Keqing; Willoughby, Colin E.; Zaneveld, Jacques E.; Jiang, Lichun; Soens, Zachry T.; Earle, Philip; Simpson, David

    2015-01-01

    Retinitis pigmentosa (RP) is a group of inherited retinal disorders characterized by progressive photoreceptor degeneration. An accurate molecular diagnosis is essential for disease characterization and clinical prognoses. A retinal capture panel that enriches 186 known retinal disease genes, including 55 known RP genes, was developed. Targeted next-generation sequencing was performed for a cohort of 82 unrelated RP cases from Northern Ireland, including 46 simplex cases and 36 familial cases. Disease-causing mutations were identified in 49 probands, including 28 simplex cases and 21 familial cases, achieving a solving rate of 60 %. In total, 65 pathogenic mutations were found, and 29 of these were novel. Interestingly, the molecular information of 12 probands was neither consistent with their initial inheritance pattern nor clinical diagnosis. Further clinical reassessment resulted in a refinement of the clinical diagnosis in 11 patients. This is the first study to apply next-generation sequencing-based, comprehensive molecular diagnoses to a large number of RP probands from Northern Ireland. Our study shows that molecular information can aid clinical diagnosis, potentially changing treatment options, current family counseling and management. PMID:25472526

  20. 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

  1. 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.

  2. 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.

  3. Application of a diagnosis-based clinical decision guide in patients with low back pain

    PubMed Central

    2011-01-01

    Background Low back pain (LBP) is common and costly. Development of accurate and efficacious methods of diagnosis and treatment has been identified as a research priority. A diagnosis-based clinical decision guide (DBCDG; previously referred to as a diagnosis-based clinical decision rule) has been proposed which attempts to provide the clinician with a systematic, evidence-based means to apply the biopsychosocial model of care. The approach is based on three questions of diagnosis. The purpose of this study is to present the prevalence of findings using the DBCDG in consecutive patients with LBP. Methods Demographic, diagnostic and baseline outcome measure data were gathered on a cohort of LBP patients examined by one of three examiners trained in the application of the DBCDG. Results Data were gathered on 264 patients. Signs of visceral disease or potentially serious illness were found in 2.7%. Centralization signs were found in 41%, lumbar and sacroiliac segmental signs in 23% and 27%, respectively and radicular signs were found in 24%. Clinically relevant myofascial signs were diagnosed in 10%. Dynamic instability was diagnosed in 63%, fear beliefs in 40%, central pain hypersensitivity in 5%, passive coping in 3% and depression in 3%. Conclusion The DBCDG can be applied in a busy private practice environment. Further studies are needed to investigate clinically relevant means to identify central pain hypersensitivity, poor coping and depression, correlations and patterns among the diagnostic components of the DBCDG as well as inter-examiner reliability and efficacy of treatment based on the DBCDG. PMID:22018026

  4. 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.

  5. Tropical cyclogenesis: a numerical diagnosis based on helical flow organization

    NASA Astrophysics Data System (ADS)

    Levina, G. V.; Montgomery, M. T.

    2014-10-01

    A numerical diagnosis for tropical cyclogenesis is proposed based on nearcloud-resolving atmospheric simulation. Calculation and analyses of helical and energetic characteristics together with hydro- and thermodynamic flow fields allow the diagnosis of tropical cyclogenesis as an event when the primary and secondary circulations become linked on system scales thereby making the nascent large-scale vortex helical. A key process of vertical vorticity generation from horizontal components and its amplification by special convective coherent structures - Vortical Hot Towers (VHTs) - is highlighted. The process is found to be a pathway for generation of a velocity field with linked vortex lines of horizontal and vertical vorticity on local and system scales. The role of VHTs as connectors of the primary and secondary circulation is emphasized.

  6. 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.

  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. 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

  9. 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

  10. 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

  11. 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

  12. 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

    2014-02-01

    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.

  13. 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.

  14. 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

  15. 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.

  16. An expert fitness diagnosis system based on elastic cloud computing.

    PubMed

    Tseng, Kevin C; Wu, Chia-Chuan

    2014-01-01

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

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

    PubMed Central

    Tseng, Kevin C.; Wu, Chia-Chuan

    2014-01-01

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

  18. 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.

  19. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  2. 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

  3. 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.

  4. Vibration Sensor-Based Bearing Fault Diagnosis Using Ellipsoid-ARTMAP and Differential Evolution Algorithms

    PubMed Central

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

    2014-01-01

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

  5. 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.

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

    PubMed

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

    2016-06-01

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

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

    NASA Technical Reports Server (NTRS)

    Gulati, Sandeep; Mackey, Ryan

    2003-01-01

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

  8. 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.

  9. 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.

  10. 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

  11. Computer-based assessment for facioscapulohumeral dystrophy diagnosis.

    PubMed

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

    2015-06-01

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

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

    PubMed

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

    2016-04-01

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

  13. RAP: Accurate and Fast Motif Finding Based on Protein-Binding Microarray Data

    PubMed Central

    Orenstein, Yaron; Mick, Eran

    2013-01-01

    Abstract The novel high-throughput technology of protein-binding microarrays (PBMs) measures binding intensity of a transcription factor to thousands of DNA probe sequences. Several algorithms have been developed to extract binding-site motifs from these data. Such motifs are commonly represented by positional weight matrices. Previous studies have shown that the motifs produced by these algorithms are either accurate in predicting in vitro binding or similar to previously published motifs, but not both. In this work, we present a new simple algorithm to infer binding-site motifs from PBM data. It outperforms prior art both in predicting in vitro binding and in producing motifs similar to literature motifs. Our results challenge previous claims that motifs with lower information content are better models for transcription-factor binding specificity. Moreover, we tested the effect of motif length and side positions flanking the “core” motif in the binding site. We show that side positions have a significant effect and should not be removed, as commonly done. A large drop in the results quality of all methods is observed between in vitro and in vivo binding prediction. The software is available on acgt.cs.tau.ac.il/rap. PMID:23464877

  14. TIARA: a database for accurate analysis of multiple personal genomes based on cross-technology

    PubMed Central

    Hong, Dongwan; Park, Sung-Soo; Ju, Young Seok; Kim, Sheehyun; Shin, Jong-Yeon; Kim, Sujung; Yu, Saet-Byeol; Lee, Won-Chul; Lee, Seungbok; Park, Hansoo; Kim, Jong-Il; Seo, Jeong-Sun

    2011-01-01

    High-throughput genomic technologies have been used to explore personal human genomes for the past few years. Although the integration of technologies is important for high-accuracy detection of personal genomic variations, no databases have been prepared to systematically archive genomes and to facilitate the comparison of personal genomic data sets prepared using a variety of experimental platforms. We describe here the Total Integrated Archive of Short-Read and Array (TIARA; http://tiara.gmi.ac.kr) database, which contains personal genomic information obtained from next generation sequencing (NGS) techniques and ultra-high-resolution comparative genomic hybridization (CGH) arrays. This database improves the accuracy of detecting personal genomic variations, such as SNPs, short indels and structural variants (SVs). At present, 36 individual genomes have been archived and may be displayed in the database. TIARA supports a user-friendly genome browser, which retrieves read-depths (RDs) and log2 ratios from NGS and CGH arrays, respectively. In addition, this database provides information on all genomic variants and the raw data, including short reads and feature-level CGH data, through anonymous file transfer protocol. More personal genomes will be archived as more individuals are analyzed by NGS or CGH array. TIARA provides a new approach to the accurate interpretation of personal genomes for genome research. PMID:21051338

  15. 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

  16. 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.

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

    PubMed

    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 40 kHz 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 degrees C. The main advantages of this system are high resolution measurements, narrow bandwidth requirements, and ease of implementation.

  18. Outcomes Evaluation in "Faith"-Based Social Services: Are We Evaluating "Faith" Accurately?

    ERIC Educational Resources Information Center

    Ferguson, Kristin M.; Wu, Qiaobing; Spruijt-Metz, Donna; Dyrness, Grace

    2007-01-01

    In response to a recent call for research on the effectiveness of faith-based organizations, this article synthesizes how effectiveness has been defined and measured in evaluation research of faith-based programs. Although evidence indicates that religion can have a positive impact on individuals' well-being, no prior comprehensive review exists…

  19. 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.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2015-01-10

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-08-18

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

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

    PubMed

    Yin, Chunyong

    2014-01-01

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

  5. 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

  6. 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. PMID:25649659

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

    PubMed

    Shen, Yan; Lou, Shuqin; Wang, Xin

    2014-03-20

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

  8. 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.

  9. Accurate energies of hydrogen bonded nucleic acid base pairs and triplets in tRNA tertiary interactions

    PubMed Central

    2006-01-01

    Tertiary interactions are crucial in maintaining the tRNA structure and functionality. We used a combined sequence analysis and quantum mechanics approach to calculate accurate energies of the most frequent tRNA tertiary base pairing interactions. Our analysis indicates that six out of the nine classical tertiary interactions are held in place mainly by H-bonds between the bases. In the remaining three cases other effects have to be considered. Tertiary base pairing interaction energies range from −8 to −38 kcal/mol in yeast tRNAPhe and are estimated to contribute roughly 25% of the overall tRNA base pairing interaction energy. Six analyzed posttranslational chemical modifications were shown to have minor effect on the geometry of the tertiary interactions. Modifications that introduce a positive charge strongly stabilize the corresponding tertiary interactions. Non-additive effects contribute to the stability of base triplets. PMID:16461956

  10. A deep learning based framework for accurate segmentation of cervical cytoplasm and nuclei.

    PubMed

    Song, Youyi; Zhang, Ling; Chen, Siping; Ni, Dong; Li, Baopu; Zhou, Yongjing; Lei, Baiying; Wang, Tianfu

    2014-01-01

    In this paper, a superpixel and convolution neural network (CNN) based segmentation method is proposed for cervical cancer cell segmentation. Since the background and cytoplasm contrast is not relatively obvious, cytoplasm segmentation is first performed. Deep learning based on CNN is explored for region of interest detection. A coarse-to-fine nucleus segmentation for cervical cancer cell segmentation and further refinement is also developed. Experimental results show that an accuracy of 94.50% is achieved for nucleus region detection and a precision of 0.9143±0.0202 and a recall of 0.8726±0.0008 are achieved for nucleus cell segmentation. Furthermore, our comparative analysis also shows that the proposed method outperforms the related methods.

  11. Recognizing the link between CKD and CVD in the primary care setting: accurate and early diagnosis for timely and appropriate intervention.

    PubMed

    Basile, Jan N

    2007-05-01

    Chronic kidney disease (CKD), which is becoming increasingly prevalent in the US and worldwide, eventually progresses to end-stage renal disease (ESRD), requiring renal replacement therapy. Diabetes and hypertension, the two leading causes of CKD, are themselves reaching near epidemic proportions. Hypertension can cause both the development and progression of CKD, and CKD is a significant risk factor for the development of cardiovascular disease. Indeed, CKD patients are more likely to die of cardiovascular complications than progress to ESRD. However, data indicate that early recognition and management of CKD can have a significant positive impact on disease outcome. This creates an important interventional opportunity for the primary care physician. This report describes the major risk factors and comorbidities associated with the development and progression of CKD and offers suggestions for timely diagnosis and management of CKD in the primary care setting.

  12. Clustering diagnosis of rolling element bearing fault based on integrated Autoregressive/Autoregressive Conditional Heteroscedasticity model

    NASA Astrophysics Data System (ADS)

    Wang, Guofeng; Liu, Chang; Cui, Yinhu

    2012-09-01

    Feature extraction plays an important role in the clustering analysis. In this paper an integrated Autoregressive (AR)/Autoregressive Conditional Heteroscedasticity (ARCH) model is proposed to characterize the vibration signal and the model coefficients are adopted as feature vectors to realize clustering diagnosis of rolling element bearings. The main characteristic is that the AR item and ARCH item are interrelated with each other so that it can depict the excess kurtosis and volatility clustering information in the vibration signal more accurately in comparison with two-stage AR/ARCH model. To testify the correctness, four kinds of bearing signals are adopted for parametric modeling by using the integrated and two-stage AR/ARCH model. The variance analysis of the model coefficients shows that the integrated AR/ARCH model can get more concentrated distribution. Taking these coefficients as feature vectors, K means based clustering is utilized to realize the automatic classification of bearing fault status. The results show that the proposed method can get more accurate results in comparison with two-stage model and discrete wavelet decomposition.

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

    PubMed

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

    1996-10-01

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

  14. A sensitive and accurate atomic magnetometer based on free spin precession

    NASA Astrophysics Data System (ADS)

    Grujić, Zoran D.; Koss, Peter A.; Bison, Georg; Weis, Antoine

    2015-05-01

    We present a laser-based atomic magnetometer that allows inferring the modulus of a magnetic field from the free Larmor precession of spin-oriented Cs vapour atoms. The detection of free spin precession (FSP) is not subject to systematic readout errors that occur in phase feedback-controlled magnetometers in which the spin precession is actively driven by an oscillating field or a modulation of light parameters, such as frequency, amplitude, or polarization. We demonstrate that an FSP-magnetometer can achieve a ˜200 fT/√Hz sensitivity (<100 fT/√Hz in the shotnoise limit) and an absolute accuracy at the same level.

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

    PubMed Central

    Nguyen, Nha; Vo, An; Choi, Inchan

    2015-01-01

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

  16. 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.

  17. Some recommendations for an accurate estimation of Lanice conchilega density based on tube counts

    NASA Astrophysics Data System (ADS)

    van Hoey, Gert; Vincx, Magda; Degraer, Steven

    2006-12-01

    The tube building polychaete Lanice conchilega is a common and ecologically important species in intertidal and shallow subtidal sands. It builds a characteristic tube with ragged fringes and can retract rapidly into its tube to depths of more than 20 cm. Therefore, it is very difficult to sample L. conchilega individuals, especially with a Van Veen grab. Consequently, many studies have used tube counts as estimates of real densities. This study reports on some aspects to be considered when using tube counts as a density estimate of L. conchilega, based on intertidal and subtidal samples. Due to its accuracy and independence of sampling depth, the tube method is considered the prime method to estimate the density of L. conchilega. However, caution is needed when analyzing samples with fragile young individuals and samples from areas where temporary physical disturbance is likely to occur.

  18. Virtual Contrast for Coronary Vessels Based on Level Set Generated Subvoxel Accurate Centerlines

    PubMed Central

    Van Uitert, Robert; Wolf, Ivo; Tzatha, Efstathia; Gharib, Ahmed M; Summers, Ronald; Meinzer, Hans-Peter; Pettigrew, Roderic

    2006-01-01

    We present a tool for tracking coronary vessels in MRI scans of the human heart to aid in the screening of heart diseases. The vessels are identified through a single click inside each vessel present in a standard orthogonal view. The vessel identification results from a series of computational steps including eigenvalue analysis of the Hessian of the MRI image followed by a level set-based extraction of the vessel centerline. All identified vessels are highlighted using a virtual contrast agent and displayed simultaneously in a spherical curved reformation view. In cases of over segmentation, the vessel traces can be shortened by a click on each vessel end point. Intermediate analysis results of the vessel computation steps can be displayed as well. We successfully validated the tool on 40 MRI scans demonstrating accuracy and significant time savings over manual vessel tracing. PMID:23165062

  19. 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

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

    PubMed

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

    2016-05-01

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

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

    PubMed

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

    2016-05-01

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

  2. 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.

  3. Accurate determination of imaging modality using an ensemble of text- and image-based classifiers.

    PubMed

    Kahn, Charles E; Kalpathy-Cramer, Jayashree; Lam, Cesar A; Eldredge, Christina E

    2012-02-01

    Imaging modality can aid retrieval of medical images for clinical practice, research, and education. We evaluated whether an ensemble classifier could outperform its constituent individual classifiers in determining the modality of figures from radiology journals. Seventeen automated classifiers analyzed 77,495 images from two radiology journals. Each classifier assigned one of eight imaging modalities--computed tomography, graphic, magnetic resonance imaging, nuclear medicine, positron emission tomography, photograph, ultrasound, or radiograph-to each image based on visual and/or textual information. Three physicians determined the modality of 5,000 randomly selected images as a reference standard. A "Simple Vote" ensemble classifier assigned each image to the modality that received the greatest number of individual classifiers' votes. A "Weighted Vote" classifier weighted each individual classifier's vote based on performance over a training set. For each image, this classifier's output was the imaging modality that received the greatest weighted vote score. We measured precision, recall, and F score (the harmonic mean of precision and recall) for each classifier. Individual classifiers' F scores ranged from 0.184 to 0.892. The simple vote and weighted vote classifiers correctly assigned 4,565 images (F score, 0.913; 95% confidence interval, 0.905-0.921) and 4,672 images (F score, 0.934; 95% confidence interval, 0.927-0.941), respectively. The weighted vote classifier performed significantly better than all individual classifiers. An ensemble classifier correctly determined the imaging modality of 93% of figures in our sample. The imaging modality of figures published in radiology journals can be determined with high accuracy, which will improve systems for image retrieval.

  4. Accurate prediction of kidney allograft outcome based on creatinine course in the first 6 months posttransplant.

    PubMed

    Fritsche, L; Hoerstrup, J; Budde, K; Reinke, P; Neumayer, H-H; Frei, U; Schlaefer, A

    2005-03-01

    Most attempts to predict early kidney allograft loss are based on the patient and donor characteristics at baseline. We investigated how the early posttransplant creatinine course compares to baseline information in the prediction of kidney graft failure within the first 4 years after transplantation. Two approaches to create a prediction rule for early graft failure were evaluated. First, the whole data set was analysed using a decision-tree building software. The software, rpart, builds classification or regression models; the resulting models can be represented as binary trees. In the second approach, a Hill-Climbing algorithm was applied to define cut-off values for the median creatinine level and creatinine slope in the period between day 60 and 180 after transplantation. Of the 497 patients available for analysis, 52 (10.5%) experienced an early graft loss (graft loss within the first 4 years after transplantation). From the rpart algorithm, a single decision criterion emerged: Median creatinine value on days 60 to 180 higher than 3.1 mg/dL predicts early graft failure (accuracy 95.2% but sensitivity = 42.3%). In contrast, the Hill-Climbing algorithm delivered a cut-off of 1.8 mg/dL for the median creatinine level and a cut-off of 0.3 mg/dL per month for the creatinine slope (sensitivity = 69.5% and specificity 79.0%). Prediction rules based on median and slope of creatinine levels in the first half year after transplantation allow early identification of patients who are at risk of loosing their graft early after transplantation. These patients may benefit from therapeutic measures tailored for this high-risk setting. PMID:15848516

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

    PubMed

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

    2016-03-20

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

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

    NASA Astrophysics Data System (ADS)

    Ramarohetra, J.; Sultan, B.

    2012-04-01

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

  7. [Acute pancreatitis: guideline-based diagnosis and treatment].

    PubMed

    Tuennemann, J; Mössner, J; Beer, S

    2014-09-01

    Acute pancreatitis is most frequently of biliary or alcoholic origin and less frequently due to iatrogenic (ERCP, medication) or metabolic causes. Diagnosis is usually based on abdominal pain and elevation of serum lipase to more than three-times the normal limit. Acute pancreatitis can either resolve quickly following an oedematous swelling or present as a severe necrotizing form. A major risk is the systemic inflammatory response syndrome (SIRS), which can cause multi-organ failure. Prediction of disease course is initially difficult, thus necessitating immediate therapy and regular re-evaluation. In order to prove or exclude biliary genesis, abdominal ultrasonography should first be performed and endoscopic ultrasound may also be required. Primary therapy includes rapid and correctly dosed fluid substitution. Biliary pancreatitis requires causal treatment. In the case of cholangitis, stone extraction must be performed immediately; in the absence of cholangitis, it might be advisable to wait for spontaneous stone clearance. Timely cholecystectomy is necessary in all cases of biliary pancreatitis. PMID:25139706

  8. 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.

  9. 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.

  10. 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

  11. 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.

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

    PubMed

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

    2016-01-01

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

  13. SOAP3-dp: Fast, Accurate and Sensitive GPU-Based Short Read Aligner

    PubMed Central

    Zhu, Xiaoqian; Wu, Edward; Lee, Lap-Kei; Lin, Haoxiang; Zhu, Wenjuan; Cheung, David W.; Ting, Hing-Fung; Yiu, Siu-Ming; Peng, Shaoliang; Yu, Chang; Li, Yingrui; Li, Ruiqiang; Lam, Tak-Wah

    2013-01-01

    To tackle the exponentially increasing throughput of Next-Generation Sequencing (NGS), most of the existing short-read aligners can be configured to favor speed in trade of accuracy and sensitivity. SOAP3-dp, through leveraging the computational power of both CPU and GPU with optimized algorithms, delivers high speed and sensitivity simultaneously. Compared with widely adopted aligners including BWA, Bowtie2, SeqAlto, CUSHAW2, GEM and GPU-based aligners BarraCUDA and CUSHAW, SOAP3-dp was found to be two to tens of times faster, while maintaining the highest sensitivity and lowest false discovery rate (FDR) on Illumina reads with different lengths. Transcending its predecessor SOAP3, which does not allow gapped alignment, SOAP3-dp by default tolerates alignment similarity as low as 60%. Real data evaluation using human genome demonstrates SOAP3-dp's power to enable more authentic variants and longer Indels to be discovered. Fosmid sequencing shows a 9.1% FDR on newly discovered deletions. SOAP3-dp natively supports BAM file format and provides the same scoring scheme as BWA, which enables it to be integrated into existing analysis pipelines. SOAP3-dp has been deployed on Amazon-EC2, NIH-Biowulf and Tianhe-1A. PMID:23741504

  14. 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.

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

    PubMed

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

    2015-07-01

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

  16. 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).

  17. 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

  18. Polymerase chain reaction amplifying mycobacterial DNA from aspirates obtained by endoscopic ultrasound allows accurate diagnosis of mycobacterial disease in HIV-positive patients with abdominal lymphadenopathy.

    PubMed

    Nieuwoudt, Martin; Lameris, Roeland; Corcoran, Craig; Rossouw, Theresa M; Slavik, Tomas; Du Plessis, Johannie; Omoshoro-Jones, Jones A O; Stivaktas, Paraskevi; Potgieter, Fritz; Van der Merwe, Schalk W

    2014-09-01

    Abdominal lymphadenopathy in human immunodeficiency virus (HIV) infection remains a diagnostic challenge. We performed a prospective cohort study by recruiting 31 symptomatic HIV + patients with abdominal lymphadenopathy and assessing the diagnostic yield of endoscopic ultrasound fine-needle aspiration (EUS-FNA). Mean age was 38 years; 52% were female; and mean CD4 count and viral load were 124 cells/μL and 4 log, respectively. EUS confirmed additional mediastinal nodes in 26%. The porta hepatis was the most common abdominal site. Aspirates obtained by EUS-FNA were subjected to cytology, culture and polymerase chain reaction (PCR) analysis. Mycobacterial infections were confirmed in 67.7%, and 31% had reactive lymphadenopathy. Cytology and culture had low sensitivity, whereas PCR identified 90% of mycobacterial infections. By combining the appearance of aspirates obtained by EUS-FNA and cytologic specimens, we developed a diagnostic algorithm to indicate when analysis with PCR would be useful. PCR performed on material obtained by EUS-FNA was highly accurate in confirming mycobacterial disease and determining genotypic drug resistance.

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

    PubMed

    2009-08-01

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

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

    NASA Astrophysics Data System (ADS)

    Modiri, Arezoo

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

  1. 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.

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

    PubMed

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

    2015-09-01

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

  3. 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.

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

    PubMed

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

    2016-05-01

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

  5. 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.

  6. An evolutionary model-based algorithm for accurate phylogenetic breakpoint mapping and subtype prediction in HIV-1.

    PubMed

    Kosakovsky Pond, Sergei L; Posada, David; Stawiski, Eric; Chappey, Colombe; Poon, Art F Y; Hughes, Gareth; Fearnhill, Esther; Gravenor, Mike B; Leigh Brown, Andrew J; Frost, Simon D W

    2009-11-01

    Genetically diverse pathogens (such as Human Immunodeficiency virus type 1, HIV-1) are frequently stratified into phylogenetically or immunologically defined subtypes for classification purposes. Computational identification of such subtypes is helpful in surveillance, epidemiological analysis and detection of novel variants, e.g., circulating recombinant forms in HIV-1. A number of conceptually and technically different techniques have been proposed for determining the subtype of a query sequence, but there is not a universally optimal approach. We present a model-based phylogenetic method for automatically subtyping an HIV-1 (or other viral or bacterial) sequence, mapping the location of breakpoints and assigning parental sequences in recombinant strains as well as computing confidence levels for the inferred quantities. Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL) procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. We applied SCUEAL to all available polymerase (pol) sequences from two large databases, the Stanford Drug Resistance database and the UK HIV Drug Resistance Database. Comparing with subtypes which had previously been assigned revealed that a minor but substantial (approximately 5%) fraction of pure subtype sequences may in fact be within- or inter-subtype recombinants. A free implementation of SCUEAL is provided as a module for the HyPhy package and the Datamonkey web server. Our method is especially useful when an accurate automatic classification of an unknown strain is desired, and is positioned to complement and extend faster but less accurate methods. Given the increasingly frequent use of HIV subtype information in studies focusing on the effect of subtype on treatment, clinical outcome, pathogenicity and vaccine design, the importance of accurate

  7. Distributed bearing fault diagnosis based on vibration analysis

    NASA Astrophysics Data System (ADS)

    Dolenc, Boštjan; Boškoski, Pavle; Juričić, Đani

    2016-01-01

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

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

    PubMed Central

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

    2012-01-01

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

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

    PubMed

    Xie, Minzhu; Wang, Jianxin; Chen, Xin

    2015-01-01

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

  10. 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.

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

    PubMed

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

    2012-01-01

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

  12. 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.

  13. 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

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

    PubMed

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

    2016-01-01

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

  15. 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

  16. The multiscale coarse-graining method. XI. Accurate interactions based on the centers of charge of coarse-grained sites.

    PubMed

    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. PMID:26723601

  17. 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.

  18. Accurate recovery of 4D left ventricular deformations using volumetric B-splines incorporating phase based displacement estimates

    NASA Astrophysics Data System (ADS)

    Chen, Jian; Tustison, Nicholas J.; Amini, Amir A.

    2006-03-01

    In this paper, an improved framework for estimation of 3-D left-ventricular deformations from tagged MRI is presented. Contiguous short- and long-axis tagged MR images are collected and are used within a 4-D B-Spline based deformable model to determine 4-D displacements and strains. An initial 4-D B-spline model fitted to sparse tag line data is first constructed by minimizing a 4-D Chamfer distance potential-based energy function for aligning isoparametric planes of the model with tag line locations; subsequently, dense virtual tag lines based on 2-D phase-based displacement estimates and the initial model are created. A final 4-D B-spline model with increased knots is fitted to the virtual tag lines. From the final model, we can extract accurate 3-D myocardial deformation fields and corresponding strain maps which are local measures of non-rigid deformation. Lagrangian strains in simulated data are derived which show improvement over our previous work. The method is also applied to 3-D tagged MRI data collected in a canine.

  19. 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.

  20. A homotopy-based sparse representation for fast and accurate shape prior modeling in liver surgical planning.

    PubMed

    Wang, Guotai; Zhang, Shaoting; Xie, Hongzhi; Metaxas, Dimitris N; Gu, Lixu

    2015-01-01

    Shape prior plays an important role in accurate and robust liver segmentation. However, liver shapes have complex variations and accurate modeling of liver shapes is challenging. Using large-scale training data can improve the accuracy but it limits the computational efficiency. In order to obtain accurate liver shape priors without sacrificing the efficiency when dealing with large-scale training data, we investigate effective and scalable shape prior modeling method that is more applicable in clinical liver surgical planning system. We employed the Sparse Shape Composition (SSC) to represent liver shapes by an optimized sparse combination of shapes in the repository, without any assumptions on parametric distributions of liver shapes. To leverage large-scale training data and improve the computational efficiency of SSC, we also introduced a homotopy-based method to quickly solve the L1-norm optimization problem in SSC. This method takes advantage of the sparsity of shape modeling, and solves the original optimization problem in SSC by continuously transforming it into a series of simplified problems whose solution is fast to compute. When new training shapes arrive gradually, the homotopy strategy updates the optimal solution on the fly and avoids re-computing it from scratch. Experiments showed that SSC had a high accuracy and efficiency in dealing with complex liver shape variations, excluding gross errors and preserving local details on the input liver shape. The homotopy-based SSC had a high computational efficiency, and its runtime increased very slowly when repository's capacity and vertex number rose to a large degree. When repository's capacity was 10,000, with 2000 vertices on each shape, homotopy method cost merely about 11.29 s to solve the optimization problem in SSC, nearly 2000 times faster than interior point method. The dice similarity coefficient (DSC), average symmetric surface distance (ASD), and maximum symmetric surface distance measurement

  1. 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

  2. Clinical validation of surface-enhanced Raman scattering-based immunoassays in the early diagnosis of rheumatoid arthritis.

    PubMed

    Chon, Hyangah; Wang, Rui; Lee, Sangyeop; Bang, So-Young; Lee, Hye-Soon; Bae, Sang-Cheol; Hong, Sung Hyun; Yoon, Young Ho; Lim, Dong Woo; deMello, Andrew J; Choo, Jaebum

    2015-11-01

    We assessed the clinical feasibility of conducting immunoassays based on surface-enhanced Raman scattering (SERS) in the early diagnosis of rheumatoid arthritis (RA). An autoantibody against citrullinated peptide (anti-CCP) was used as a biomarker, magnetic beads conjugated with CCP were used as substrates, and the SERS nanotags were comprised of anti-human IgG-conjugated hollow gold nanospheres (HGNs). We were able to determine the anti-CCP serum levels successfully by observing the distinctive Raman intensities corresponding to the SERS nanotags. At high concentrations of anti-CCP (>25 U/mL), the results obtained from the SERS assay confirmed those obtained via an ELISA-based assay. Nevertheless, quantitation via our SERS-based assay is significantly more accurate at low concentrations (<25 U/mL). In this study, we compared the results of an anti-CCP assay of 74 clinical blood samples obtained from the SERS-based assay to that of a commercial ELISA kit. The results of the anti-CCP-positive group (n = 31, >25 U/mL) revealed a good correlation between the ELISA and SERS-based assays. However, in the anti-CCP-negative group (n = 43, <25 U/mL), the SERS-based assay was shown to be more reproducible. Accordingly, we suggest that SERS-based assays are novel and potentially useful tools in the early diagnosis of RA.

  3. 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.

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

    ERIC Educational Resources Information Center

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

    2013-01-01

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

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

    PubMed

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

    2016-01-01

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

  6. 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

  7. 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.

  8. Evaluation of the sample needed to accurately estimate outcome-based measurements of dairy welfare on farm.

    PubMed

    Endres, M I; Lobeck-Luchterhand, K M; Espejo, L A; Tucker, C B

    2014-01-01

    Dairy welfare assessment programs are becoming more common on US farms. Outcome-based measurements, such as locomotion, hock lesion, hygiene, and body condition scores (BCS), are included in these assessments. The objective of the current study was to investigate the proportion of cows in the pen or subsamples of pens on a farm needed to provide an accurate estimate of the previously mentioned measurements. In experiment 1, we evaluated cows in 52 high pens (50 farms) for lameness using a 1- to 5-scale locomotion scoring system (1 = normal and 5 = severely lame; 24.4 and 6% of animals were scored ≥ 3 or ≥ 4, respectively). Cows were also given a BCS using a 1- to 5-scale, where 1 = emaciated and 5 = obese; cows were rarely thin (BCS ≤ 2; 0.10% of cows) or fat (BCS ≥ 4; 0.11% of cows). Hygiene scores were assessed on a 1- to 5-scale with 1 = clean and 5 = severely dirty; 54.9% of cows had a hygiene score ≥ 3. Hock injuries were classified as 1 = no lesion, 2 = mild lesion, and 3 = severe lesion; 10.6% of cows had a score of 3. Subsets of data were created with 10 replicates of random sampling that represented 100, 90, 80, 70, 60, 50, 40, 30, 20, 15, 10, 5, and 3% of the cows measured/pen. In experiment 2, we scored the same outcome measures on all cows in lactating pens from 12 farms and evaluated using pen subsamples: high; high and fresh; high, fresh, and hospital; and high, low, and hospital. For both experiments, the association between the estimates derived from all subsamples and entire pen (experiment 1) or herd (experiment 2) prevalence was evaluated using linear regression. To be considered a good estimate, 3 criteria must be met: R(2)>0.9, slope = 1, and intercept = 0. In experiment 1, on average, recording 15% of the pen represented the percentage of clinically lame cows (score ≥ 3), whereas 30% needed to be measured to estimate severe lameness (score ≥ 4). Only 15% of the pen was needed to estimate the percentage of the herd with a hygiene

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

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

    PubMed

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

    2016-07-01

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

  11. 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

  12. 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.

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

    PubMed

    Ma, Jian; Lu, Chen; Liu, Hongmei

    2015-01-01

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

  14. Current status of nanoparticle-based imaging agents for early diagnosis of cancer and atherosclerosis.

    PubMed

    Saravanakumar, Gurusamy; Kim, Kwangmeyung; Park, Jae Hyung; Rhee, Kyehan; Kwon, Ick Chan

    2009-02-01

    Endothelium plays a vital role in various vascular functions, and its dysfunction is a key underlying process closely related to diverse array of diseases such as atherosclerosis and tumor. Therefore, early detection of endothelial dysfunction at the functional or molecular level is of high importance for effective therapy. Recent advances in nanotechnology and our understanding in cellular and molecular biology have provided various biomedical imaging modalities and nanosized multimodal imaging agents. Multimodal nanoparticles that encompass the targeting ligands and magnetic/optical imaging labels enable us to visualize the pathophysiological process of various diseases using multiple imaging techniques. To visualize the specific pathogenic process at the molecular level, the imaging probe needs to be surface-functionalized with specific affinity ligands such as monoclonal antibodies (mAb). Combining the functional imaging agents along with therapeutic drugs has great potential for effective early detection, accurate diagnosis, and treatment of disease. The current review will highlight the application of various nanoparticle-based imaging agents and their recent developments in diagnosing endothelium dysfunction with a special emphasis on atherosclerosis and cancer.

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

    NASA Astrophysics Data System (ADS)

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

    2011-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-01-01

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

  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. Ultimately accurate SRAF replacement for practical phases using an adaptive search algorithm based on the optimal gradient method

    NASA Astrophysics Data System (ADS)

    Maeda, Shimon; Nosato, Hirokazu; Matsunawa, Tetsuaki; Miyairi, Masahiro; Nojima, Shigeki; Tanaka, Satoshi; Sakanashi, Hidenori; Murakawa, Masahiro; Saito, Tamaki; Higuchi, Tetsuya; Inoue, Soichi

    2010-04-01

    SRAF (Sub Resolution Assist Feature) technique has been widely used for DOF enhancement. Below 40nm design node, even in the case of using the SRAF technique, the resolution limit is approached due to the use of hyper NA imaging or low k1 lithography conditions especially for the contact layer. As a result, complex layout patterns or random patterns like logic data or intermediate pitch patterns become increasingly sensitive to photo-resist pattern fidelity. This means that the need for more accurate resolution technique is increasing in order to cope with lithographic patterning fidelity issues in low k1 lithography conditions. To face with these issues, new SRAF technique like model based SRAF using an interference map or inverse lithography technique has been proposed. But these approaches don't have enough assurance for accuracy or performance, because the ideal mask generated by these techniques is lost when switching to a manufacturable mask with Manhattan structures. As a result it might be very hard to put these things into practice and production flow. In this paper, we propose the novel method for extremely accurate SRAF placement using an adaptive search algorithm. In this method, the initial position of SRAF is generated by the traditional SRAF placement such as rule based SRAF, and it is adjusted by adaptive algorithm using the evaluation of lithography simulation. This method has three advantages which are preciseness, efficiency and industrial applicability. That is, firstly, the lithography simulation uses actual computational model considering process window, thus our proposed method can precisely adjust the SRAF positions, and consequently we can acquire the best SRAF positions. Secondly, because our adaptive algorithm is based on optimal gradient method, which is very simple algorithm and rectilinear search, the SRAF positions can be adjusted with high efficiency. Thirdly, our proposed method, which utilizes the traditional SRAF placement, is

  19. Accurate diagnosis of Helicobacter pylori. Other tests.

    PubMed

    Bravos, E D; Gilman, R H

    2000-12-01

    The application of polymerase chain reaction (PCR) with respect to Helicobacter pylori is useful for molecular epidemiologic aspects and detection purposes. The authors address the current detection methods by PCR aimed at detecting H. pylori in clinical samples collected by less invasive methods, such as gastric juice, saliva, dental plaque, and feces. Enzyme immunoassay also is discussed.

  20. 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.

  1. 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.

  2. Deep Learning Based Syndrome Diagnosis of Chronic Gastritis

    PubMed Central

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

    2014-01-01

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

  3. Kernel-based learning from both qualitative and quantitative labels: application to prostate cancer diagnosis based on multiparametric MR imaging.

    PubMed

    Niaf, Émilie; Flamary, Rémi; Rouvière, Olivier; Lartizien, Carole; Canu, Stéphane

    2014-03-01

    Building an accurate training database is challenging in supervised classification. For instance, in medical imaging, radiologists often delineate malignant and benign tissues without access to the histological ground truth, leading to uncertain data sets. This paper addresses the pattern classification problem arising when available target data include some uncertainty information. Target data considered here are both qualitative (a class label) or quantitative (an estimation of the posterior probability). In this context, usual discriminative methods, such as the support vector machine (SVM), fail either to learn a robust classifier or to predict accurate probability estimates. We generalize the regular SVM by introducing a new formulation of the learning problem to take into account class labels as well as class probability estimates. This original reformulation into a probabilistic SVM (P-SVM) can be efficiently solved by adapting existing flexible SVM solvers. Furthermore, this framework allows deriving a unique learned prediction function for both decision and posterior probability estimation providing qualitative and quantitative predictions. The method is first tested on synthetic data sets to evaluate its properties as compared with the classical SVM and fuzzy-SVM. It is then evaluated on a clinical data set of multiparametric prostate magnetic resonance images to assess its performances in discriminating benign from malignant tissues. P-SVM is shown to outperform classical SVM as well as the fuzzy-SVM in terms of probability predictions and classification performances, and demonstrates its potential for the design of an efficient computer-aided decision system for prostate cancer diagnosis based on multiparametric magnetic resonance (MR) imaging.

  4. 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.

  5. Diagnosis-Based Risk Adjustment for Medicare Capitation Payments

    PubMed Central

    Ellis, Randall P.; Pope, Gregory C.; Iezzoni, Lisa I.; Ayanian, John Z.; Bates, David W.; Burstin, Helen; Ash, Arlene S.

    1996-01-01

    Using 1991-92 data for a 5-percent Medicare sample, we develop, estimate, and evaluate risk-adjustment models that utilize diagnostic information from both inpatient and ambulatory claims to adjust payments for aged and disabled Medicare enrollees. Hierarchical coexisting conditions (HCC) models achieve greater explanatory power than diagnostic cost group (DCG) models by taking account of multiple coexisting medical conditions. Prospective models predict average costs of individuals with chronic conditions nearly as well as concurrent models. All models predict medical costs far more accurately than the current health maintenance organization (HMO) payment formula. PMID:10172666

  6. 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.

  7. 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

  8. Accurate D-bar Reconstructions of Conductivity Images Based on a Method of Moment with Sinc Basis.

    PubMed

    Abbasi, Mahdi

    2014-01-01

    Planar D-bar integral equation is one of the inverse scattering solution methods for complex problems including inverse conductivity considered in applications such as Electrical impedance tomography (EIT). Recently two different methodologies are considered for the numerical solution of D-bar integrals equation, namely product integrals and multigrid. The first one involves high computational burden and the other one suffers from low convergence rate (CR). In this paper, a novel high speed moment method based using the sinc basis is introduced to solve the two-dimensional D-bar integral equation. In this method, all functions within D-bar integral equation are first expanded using the sinc basis functions. Then, the orthogonal properties of their products dissolve the integral operator of the D-bar equation and results a discrete convolution equation. That is, the new moment method leads to the equation solution without direct computation of the D-bar integral. The resulted discrete convolution equation maybe adapted to a suitable structure to be solved using fast Fourier transform. This allows us to reduce the order of computational complexity to as low as O (N (2)log N). Simulation results on solving D-bar equations arising in EIT problem show that the proposed method is accurate with an ultra-linear CR.

  9. 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

  10. All-solid very large mode area ytterbium-doped silica microstructured fiber based on accurate control on cladding index.

    PubMed

    Wei, Huifeng; Chen, Kangkang; Yang, Yucheng; Li, Jinyan

    2016-04-18

    We have demonstrated a new approach for developing very large mode area silica-based microstructured Ytterbium (Yb)-doped fibers. The microstructured region acting as pump cladding around the core is composed by periodically arranged low-index Fluorine-doped silica inclusions with an extremely low filling ratio of 0.088. To the best of our knowledge, we achieved the most accurate controlling on cladding index by 1 × 10-5 via our passively doped cladding (PDC) method. Two fibers with 127μm and 50μm core diameter respectively were fabricated from the same final preform designed by this approach. It is verified that our 50μm core diameter fiber can maintain robust single mode behavior at 1064nm wavelength. The advantage of an all-solid structure along with a much simpler fabrication process makes our approach very suitable for realizing very large mode area fibers for high power fiber laser application. PMID:27137328

  11. ACCURATE ORBITAL INTEGRATION OF THE GENERAL THREE-BODY PROBLEM BASED ON THE D'ALEMBERT-TYPE SCHEME

    SciTech Connect

    Minesaki, Yukitaka

    2013-03-15

    We propose an accurate orbital integration scheme for the general three-body problem that retains all conserved quantities except angular momentum. The scheme is provided by an extension of the d'Alembert-type scheme for constrained autonomous Hamiltonian systems. Although the proposed scheme is merely second-order accurate, it can precisely reproduce some periodic, quasiperiodic, and escape orbits. The Levi-Civita transformation plays a role in designing the scheme.

  12. Accurate Orbital Integration of the General Three-body Problem Based on the d'Alembert-type Scheme

    NASA Astrophysics Data System (ADS)

    Minesaki, Yukitaka

    2013-03-01

    We propose an accurate orbital integration scheme for the general three-body problem that retains all conserved quantities except angular momentum. The scheme is provided by an extension of the d'Alembert-type scheme for constrained autonomous Hamiltonian systems. Although the proposed scheme is merely second-order accurate, it can precisely reproduce some periodic, quasiperiodic, and escape orbits. The Levi-Civita transformation plays a role in designing the scheme.

  13. 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.

  14. Papanicolaou stain may not be necessary in majority of head and neck fine-needle aspirations: evidence from a correlation study between Diff-Quik-based onsite diagnosis and final diagnosis in 287 head and neck fine-needle aspirations.

    PubMed

    Wu, Maoxin; Idrees, Muhammad; Zhang, Zhengbin; Genden, Eric; Burstein, David E

    2010-11-01

    Fine-needle aspiration (FNA) is a useful tool for immediate assessment of palpable lesions, especially in the head and neck region. The objective of this study is to evaluate the degree of correlation between Diff-Quik-based onsite diagnosis (OD) and final diagnosis (FD) and further improve the efficiency of FNA practice. Two hundred and eighty-seven cytopathologist-performed FNAs from the head and neck region were evaluated. Number of passes, number and type of slides and correlation (agreement, modified final diagnosis and disagreement) between OD and FD were evaluated. Among 287 FNAs, the average number of passes per FNA case was 2 (range, 1-5&.rpar;). The mean number of slides reviewed per case was 5 including 2 Diff-Quik (D-Q)-stained slides, 2 Papanicolaou (Pap)-stained slides, and 1 cell block (CB)/1 cytospin (Cy). 247 of 287 (86%) cases showed agreement between OD and FD. FD on 36 out of 287 cases (12.5%) was slightly modified or refined after reviewing additional slides. A major diagnostic discrepancy was noted in four cases (1.5%), three of which were classified as squamous cell carcinoma on final diagnosis, and confirmed on surgical follow-up. Accurate diagnosis can be achieved in the majority (86%) of head and neck FNAs based on immediate examination of D-Q stained slides alone. In a small number of cases (12.5%), reviewing additional slides may refine the final diagnosis. In rare cases, especially cystic squamous lesions, Pap-stained slides appeared to be helpful. It is plausible to use D-Q-stained slides alone with most head and neck FNAs in order to provide more cost effective and efficient triaging and patient management. PMID:20301212

  15. Polymerase chain reaction-based molecular diagnosis of cutaneous infections in dermatopathology.

    PubMed

    Swick, Brian L

    2012-12-01

    Conventional methods, including microscopy, culture, and serologic studies, are a mainstay in the diagnosis of cutaneous infection. However, owing to limitations associated with these techniques, such as low sensitivity for standard microscopy and in the case of culture delay in diagnosis, polymerase chain-reaction based molecular techniques have taken on an expanding role in the diagnosis of infectious processes in dermatopathology. In particular, these assays are a useful adjunct in the diagnosis of cutaneous tuberculosis, atypical mycobacterial infection, leprosy, Lyme disease, syphilis, rickettsioses, leishmaniasis, and some fungal and viral infections. Already in the case of tuberculosis and atypical mycobacterial infection, standardized polymerase chain-reaction assays are commonly used for diagnostic purposes. With time, additional molecular-based techniques will decrease in cost and gain increased standardization, thus delivering rapid diagnostic confirmation for many difficult-to-diagnose cutaneous infections from standard formalin-fixed paraffin-embedded tissue specimens.

  16. Automatic construction of a large-scale and accurate drug-side-effect association knowledge base from biomedical literature.

    PubMed

    Xu, Rong; Wang, QuanQiu

    2014-10-01

    Systems approaches to studying drug-side-effect (drug-SE) associations are emerging as an active research area for drug target discovery, drug repositioning, and drug toxicity prediction. However, currently available drug-SE association databases are far from being complete. Herein, in an effort to increase the data completeness of current drug-SE relationship resources, we present an automatic learning approach to accurately extract drug-SE pairs from the vast amount of published biomedical literature, a rich knowledge source of side effect information for commercial, experimental, and even failed drugs. For the text corpus, we used 119,085,682 MEDLINE sentences and their parse trees. We used known drug-SE associations derived from US Food and Drug Administration (FDA) drug labels as prior knowledge to find relevant sentences and parse trees. We extracted syntactic patterns associated with drug-SE pairs from the resulting set of parse trees. We developed pattern-ranking algorithms to prioritize drug-SE-specific patterns. We then selected a set of patterns with both high precisions and recalls in order to extract drug-SE pairs from the entire MEDLINE. In total, we extracted 38,871 drug-SE pairs from MEDLINE using the learned patterns, the majority of which have not been captured in FDA drug labels to date. On average, our knowledge-driven pattern-learning approach in extracting drug-SE pairs from MEDLINE has achieved a precision of 0.833, a recall of 0.407, and an F1 of 0.545. We compared our approach to a support vector machine (SVM)-based machine learning and a co-occurrence statistics-based approach. We show that the pattern-learning approach is largely complementary to the SVM- and co-occurrence-based approaches with significantly higher precision and F1 but lower recall. We demonstrated by correlation analysis that the extracted drug side effects correlate positively with both drug targets, metabolism, and indications.

  17. Improving model-based diagnosis through algebraic analysis: The Petri net challenge

    SciTech Connect

    Portinale, L.

    1996-12-31

    The present paper describes the empirical evaluation of a linear algebra approach to model-based diagnosis, in case the behavioral model of the device under examination is described through a Petri net model. In particular, we show that algebraic analysis based on P-invariants of the net model, can significantly improve the performance of a model-based diagnostic system, while keeping the integrity of a general framework defined from a formal logical theory. A system called INVADS is described and experimental results, performed on a car fault domain and involving the comparison of different implementations of P-invariant based diagnosis, are then discussed.

  18. RNA-Based Detection Does not Accurately Enumerate Living Escherichia coli O157:H7 Cells on Plants

    PubMed Central

    Ju, Wenting; Moyne, Anne-Laure; Marco, Maria L.

    2016-01-01

    The capacity to distinguish between living and dead cells is an important, but often unrealized, attribute of rapid detection methods for foodborne pathogens. In this study, the numbers of enterohemorrhagic Escherichia coli O157:H7 after inoculation onto Romaine lettuce plants and on plastic (abiotic) surfaces were measured over time by culturing, and quantitative PCR (qPCR), propidium monoazide (PMA)-qPCR, and reverse transcriptase (RT)-qPCR targeting E. coli O157:H7 gapA, rfbE, eae, and lpfA genes and gene transcripts. On Romaine lettuce plants incubated at low relative humidity, E. coli O157:H7 cell numbers declined 107-fold within 96 h according to culture-based assessments. In contrast, there were no reductions in E. coli levels according to qPCR and only 100- and 1000-fold lower numbers per leaf by RT-qPCR and PMA-qPCR, respectively. Similar results were obtained upon exposure of E. coli O157:H7 to desiccation conditions on a sterile plastic surface. Subsequent investigation of mixtures of living and dead E. coli O157:H7 cells strongly indicated that PMA-qPCR detection was subject to false-positive enumerations of viable targets when in the presence of 100-fold higher numbers of dead cells. RT-qPCR measurements of killed E. coli O157:H7 as well as for RNaseA-treated E. coli RNA confirmed that transcripts from dead cells and highly degraded RNA were also amplified by RT-qPCR. These findings show that neither PMA-qPCR nor RT-qPCR provide accurate estimates of bacterial viability in environments where growth and survival is limited. PMID:26955370

  19. RNA-Based Detection Does not Accurately Enumerate Living Escherichia coli O157:H7 Cells on Plants.

    PubMed

    Ju, Wenting; Moyne, Anne-Laure; Marco, Maria L

    2016-01-01

    The capacity to distinguish between living and dead cells is an important, but often unrealized, attribute of rapid detection methods for foodborne pathogens. In this study, the numbers of enterohemorrhagic Escherichia coli O157:H7 after inoculation onto Romaine lettuce plants and on plastic (abiotic) surfaces were measured over time by culturing, and quantitative PCR (qPCR), propidium monoazide (PMA)-qPCR, and reverse transcriptase (RT)-qPCR targeting E. coli O157:H7 gapA, rfbE, eae, and lpfA genes and gene transcripts. On Romaine lettuce plants incubated at low relative humidity, E. coli O157:H7 cell numbers declined 10(7)-fold within 96 h according to culture-based assessments. In contrast, there were no reductions in E. coli levels according to qPCR and only 100- and 1000-fold lower numbers per leaf by RT-qPCR and PMA-qPCR, respectively. Similar results were obtained upon exposure of E. coli O157:H7 to desiccation conditions on a sterile plastic surface. Subsequent investigation of mixtures of living and dead E. coli O157:H7 cells strongly indicated that PMA-qPCR detection was subject to false-positive enumerations of viable targets when in the presence of 100-fold higher numbers of dead cells. RT-qPCR measurements of killed E. coli O157:H7 as well as for RNaseA-treated E. coli RNA confirmed that transcripts from dead cells and highly degraded RNA were also amplified by RT-qPCR. These findings show that neither PMA-qPCR nor RT-qPCR provide accurate estimates of bacterial viability in environments where growth and survival is limited. PMID:26955370

  20. An accurate and inexpensive color-based assay for detecting severe anemia in a limited-resource setting.

    PubMed

    McGann, Patrick T; Tyburski, Erika A; de Oliveira, Vysolela; Santos, Brigida; Ware, Russell E; Lam, Wilbur A

    2015-12-01

    Severe anemia is an important cause of morbidity and mortality among children in resource-poor settings, but laboratory diagnostics are often limited in these locations. To address this need, we developed a simple, inexpensive, and color-based point-of-care (POC) assay to detect severe anemia. The purpose of this study was to evaluate the accuracy of this novel POC assay to detect moderate and severe anemia in a limited-resource setting. The study was a cross-sectional study conducted on children with sickle cell anemia in Luanda, Angola. The hemoglobin concentrations obtained by the POC assay were compared to reference values measured by a calibrated automated hematology analyzer. A total of 86 samples were analyzed (mean hemoglobin concentration 6.6 g/dL). There was a strong correlation between the hemoglobin concentrations obtained by the POC assay and reference values obtained from an automated hematology analyzer (r=0.88, P<0.0001). The POC assay demonstrated excellent reproducibility (r=0.93, P<0.0001) and the reagents appeared to be durable in a tropical setting (r=0.93, P<0.0001). For the detection of severe anemia that may require blood transfusion (hemoglobin <5 g/dL), the POC assay had sensitivity of 88.9% and specificity of 98.7%. These data demonstrate that an inexpensive (<$0.25 USD) POC assay accurately estimates low hemoglobin concentrations and has the potential to become a transformational diagnostic tool for severe anemia in limited-resource settings.

  1. 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.

  2. Change in the diagnosis of inflammatory bowel disease: a hospital-based cohort study from Korea

    PubMed Central

    Lee, Ho-Su; Choe, Jaewon; Lee, Hyo Jeong; Hwang, Sung Wook; Park, Sang Hyoung; Yang, Dong-Hoon; Kim, Kyung-Jo; Ye, Byong Duk; Byeon, Jeong-Sik; Myung, Seung-Jae; Yoon, Yong Sik; Yu, Chang Sik; Kim, Jin-Ho

    2016-01-01

    Background/Aims Accurately diagnosing inflammatory bowel disease (IBD) remains a challenge, but is crucial for providing proper management for affected patients. The aim of the present study was to evaluate the frequency of change in diagnosis in Korean patients who were referred to our institution with a diagnosis of IBD. Methods We enrolled 1,444 patients diagnosed with ulcerative colitis (UC) and 1,452 diagnosed with Crohn's disease (CD), who had been referred to the Asan Medical Center between January 2010 and December 2014. These patients were assessed and subsequently classified as having UC, CD, indeterminate colitis, possible IBD, or non-IBD. Results During a median follow-up of 15.9 months, 400 of the 2,896 patients (13.8%) analyzed in this study experienced a change in diagnosis. A change in diagnosis from UC to CD, or vice-versa, was made in 24 of 1,444 patients (1.7%) and 23 of 1,452 patients (1.6%), respectively. A change to a non-IBD diagnosis was the most common modification; 7.5% (108 of 1444) and 12.7% (184 of 1452) of the patients with a referral diagnosis of UC and CD, respectively, were reclassified as having non-IBD. Among the 292 patients who were ultimately determined not to have IBD, 135 (55 UC and 80 CD cases) had received IBD-related medication. Conclusions There are diagnostic uncertainties and difficulties in relation to IBD. Therefore, precise assessment and systematic follow-up are essential in the management of this condition. PMID:27433148

  3. [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.

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

    NASA Astrophysics Data System (ADS)

    Satoh, Hitoshi; Niki, Noboru; Eguchi, Kenji; Ohmatsu, Hironobu; Kakinuma, Ryutaru; Moriyama, Noriyuki

    2009-02-01

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

  5. 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

  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. 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.

  8. Broken wires diagnosis method numerical simulation based on smart cable structure

    NASA Astrophysics Data System (ADS)

    Li, Sheng; Zhou, Min; Yang, Yan

    2014-12-01

    The smart cable with embedded distributed fiber optical Bragg grating (FBG) sensors was chosen as the object to study a new diagnosis method about broken wires of the bridge cable. The diagnosis strategy based on cable force and stress distribution state of steel wires was put forward. By establishing the bridge-cable and cable-steel wires model, the broken wires sample database was simulated numerically. A method of the characterization cable state pattern which can both represent the degree and location of broken wires inside a cable was put forward. The training and predicting results of the sample database by the back propagation (BP) neural network showed that the proposed broken wires diagnosis method was feasible and expanded the broken wires diagnosis research area by using the smart cable which was used to be only representing cable force.

  9. Online model-based diagnosis to support autonomous operation of an advanced life support system.

    PubMed

    Biswas, Gautam; Manders, Eric-Jan; Ramirez, John; Mahadevan, Nagabhusan; Abdelwahed, Sherif

    2004-01-01

    This article describes methods for online model-based diagnosis of subsystems of the advanced life support system (ALS). The diagnosis methodology is tailored to detect, isolate, and identify faults in components of the system quickly so that fault-adaptive control techniques can be applied to maintain system operation without interruption. We describe the components of our hybrid modeling scheme and the diagnosis methodology, and then demonstrate the effectiveness of this methodology by building a detailed model of the reverse osmosis (RO) system of the water recovery system (WRS) of the ALS. This model is validated with real data collected from an experimental testbed at NASA JSC. A number of diagnosis experiments run on simulated faulty data are presented and the results are discussed. PMID:15880907

  10. 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 ...

  11. 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

  12. 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.

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

    PubMed

    Costamagna, Paola; De Giorgi, Andrea; Gotelli, Alberto; Magistri, Loredana; Moser, Gabriele; Sciaccaluga, Emanuele; Trucco, Andrea

    2016-01-01

    The success of distributed power generation by plants based on solid oxide fuel cells (SOFCs) is hindered by reliability problems that can be mitigated through an effective fault detection and isolation (FDI) system. However, the numerous operating conditions under which such plants can operate and the random size of the possible faults make identifying damaged plant components starting from the physical variables measured in the plant very difficult. In this context, we assess two classical FDI strategies (model-based with fault signature matrix and data-driven with statistical classification) and the combination of them. For this assessment, a quantitative model of the SOFC-based plant, which is able to simulate regular and faulty conditions, is used. Moreover, a hybrid approach based on the random forest (RF) classification method is introduced to address the discrimination of regular and faulty situations due to its practical advantages. Working with a common dataset, the FDI performances obtained using the aforementioned strategies, with different sets of monitored variables, are observed and compared. We conclude that the hybrid FDI strategy, realized by combining a model-based scheme with a statistical classifier, outperforms the other strategies. In addition, the inclusion of two physical variables that should be measured inside the SOFCs can significantly improve the FDI performance, despite the actual difficulty in performing such measurements. PMID:27556472

  14. 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.

  15. 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.

  16. Towards a physiologically based diagnosis of anorexia nervosa and bulimia nervosa.

    PubMed

    Hatch, Kent A; Spangler, Diane L; Backus, Elizabeth M; Balagna, Jonathan T; Burns, Keven S; Guzman, Brooke S; Hubbard, Matthew J; Lindblad, Stephanie L; Roeder, Beverly L; Ryther, Natalie E; Seawright, Max A; Tyau, Jaymie N; Williams, Dustin

    2007-11-01

    Diagnosis of anorexia nervosa (AN) and bulimia nervosa (BN), while including such physiological data as weight and the reproductive status of the individual, are primarily based on questionnaires and interviews that rely on self-report of both body-related concerns and eating-related behaviors. While some key components of eating disorders are psychological and thus introspective in nature, reliance on self-report for the assessment of eating-related behaviors and nutritional status lacks the objectivity that a physiologically based measure could provide. The development of a more physiologically informed diagnosis for AN and BN would provide a more objective means of diagnosing these disorders, provide a sound physiological basis for diagnosing subclinical disorders and could also aid in monitoring the effectiveness of treatments for these disorders. Empirically supported, physiologically based methods for diagnosing AN and BN are reviewed herein as well as promising physiological measures that may potentially be used in the diagnosis of AN and BN.

  17. Shape-based diagnosis of the aortic valve

    NASA Astrophysics Data System (ADS)

    Ionasec, Razvan Ioan; Tsymbal, Alexey; Vitanovski, Dime; Georgescu, Bogdan; Zhou, S. Kevin; Navab, Nassir; Comaniciu, Dorin

    2009-02-01

    Disorders of the aortic valve represent a common cardiovascular disease and an important public-health problem worldwide. Pathological valves are currently determined from 2D images through elaborate qualitative evalu- ations and complex measurements, potentially inaccurate and tedious to acquire. This paper presents a novel diagnostic method, which identies diseased valves based on 3D geometrical models constructed from volumetric data. A parametric model, which includes relevant anatomic landmarks as well as the aortic root and lea ets, represents the morphology of the aortic valve. Recently developed robust segmentation methods are applied to estimate the patient specic model parameters from end-diastolic cardiac CT volumes. A discriminative distance function, learned from equivalence constraints in the product space of shape coordinates, determines the corresponding pathology class based on the shape information encoded by the model. Experiments on a heterogeneous set of 63 patients aected by various diseases demonstrated the performance of our method with 94% correctly classied valves.

  18. Studies in knowledge-based diagnosis of failures in robotic assembly

    NASA Technical Reports Server (NTRS)

    Lam, Raymond K.; Pollard, Nancy S.; Desai, Rajiv S.

    1990-01-01

    The telerobot diagnostic system (TDS) is a knowledge-based system that is being developed for identification and diagnosis of failures in the space robotic domain. The system is able to isolate the symptoms of the failure, generate failure hypotheses based on these symptoms, and test their validity at various levels by interpreting or simulating the effects of the hypotheses on results of plan execution. The implementation of the TDS is outlined. The classification of failures and the types of system models used by the TDS are discussed. A detailed example of the TDS approach to failure diagnosis is provided.

  19. A Novel Mittag-Leffler Kernel Based Hybrid Fault Diagnosis Method for Wheeled Robot Driving System.

    PubMed

    Yuan, Xianfeng; Song, Mumin; Zhou, Fengyu; Chen, Zhumin; Li, Yan

    2015-01-01

    The wheeled robots have been successfully applied in many aspects, such as industrial handling vehicles, and wheeled service robots. To improve the safety and reliability of wheeled robots, this paper presents a novel hybrid fault diagnosis framework based on Mittag-Leffler kernel (ML-kernel) support vector machine (SVM) and Dempster-Shafer (D-S) fusion. Using sensor data sampled under different running conditions, the proposed approach initially establishes multiple principal component analysis (PCA) models for fault feature extraction. The fault feature vectors are then applied to train the probabilistic SVM (PSVM) classifiers that arrive at a preliminary fault diagnosis. To improve the accuracy of preliminary results, a novel ML-kernel based PSVM classifier is proposed in this paper, and the positive definiteness of the ML-kernel is proved as well. The basic probability assignments (BPAs) are defined based on the preliminary fault diagnosis results and their confidence values. Eventually, the final fault diagnosis result is archived by the fusion of the BPAs. Experimental results show that the proposed framework not only is capable of detecting and identifying the faults in the robot driving system, but also has better performance in stability and diagnosis accuracy compared with the traditional methods. PMID:26229526

  20. 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

  1. 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.

  2. 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.

  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. A Fault Diagnosis Approach for Rolling Bearings Based on EMD Method and Eigenvector Algorithm

    NASA Astrophysics Data System (ADS)

    Zhang, Jinyu; Huang, Xianxiang

    Fault diagnosis of rolling bearings is still a very important and difficult research task on engineering. After analyzing the shortcomings of current bearing fault diagnosis technologies, a new approach based on Empirical Mode Decomposition (EMD) and blind equalization eigenvector algorithm (EVA) for rolling bearings fault diagnosis is proposed. In this approach, the characteristic high-frequency signal with amplitude and channel modulation of a rolling bearing with local damage is first separated from the mechanical vibration signal as an Intrinsic Mode Function (IMF) by using EMD, then the source impact vibration signal yielded by local damage is extracted by means of a EVA model and algorithm. Finally, the presented approach is used to analyze an impacting experiment and two real signals collected from rolling bearings with outer race damage or inner race damage. The results show that the EMD and EVA based approach can effectively detect rolling bearing fault.

  6. 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.

  7. 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

  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. 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

  11. Paper-based diagnostic devices for clinical paraquat poisoning diagnosis.

    PubMed

    Kuan, Chen-Meng; Lin, Szu-Ting; Yen, Tzung-Hai; Wang, Yu-Lin; Cheng, Chao-Min

    2016-05-01

    This article unveils the development of a paper-based analytical device designed to rapidly detect and clinically diagnose paraquat (PQ) poisoning. Using wax printing technology, we fabricated a PQ detection device by pattering hydrophobic boundaries on paper. This PQ detection device employs a colorimetric sodium dithionite assay or an ascorbic acid assay to indicate the PQ level in a buffer system or in a human serum system in 10 min. In this test, colorimetric changes, blue in color, were observable with the naked eye. By curve fitting models of sodium dithionite and ascorbic acid assays in normal human serum, we evaluated serum PQ levels for five PQ-poisoned patients before hemoperfusion (HP) treatment and one PQ-poisoned patient after HP treatment. As evidenced by similar detection outcomes, the analytical performance of our device can compete with that of the highest clinical standard, i.e., spectrophotometry, with less complicated sample preparation and with more rapid results. Accordingly, we believe that our rapid PQ detection can benefit physicians determining timely treatment strategies for PQ-poisoned patients once they are taken to hospitals, and that this approach will increase survival rates. PMID:27462379

  12. Computer-aided diagnosis of breast cancer based on fine needle biopsy microscopic images.

    PubMed

    Kowal, Marek; Filipczuk, Paweł; Obuchowicz, Andrzej; Korbicz, Józef; Monczak, Roman

    2013-10-01

    Prompt and widely available diagnostics of breast cancer is crucial for the prognosis of patients. One of the diagnostic methods is the analysis of cytological material from the breast. This examination requires extensive knowledge and experience of the cytologist. Computer-aided diagnosis can speed up the diagnostic process and allow for large-scale screening. One of the largest challenges in the automatic analysis of cytological images is the segmentation of nuclei. In this study, four different clustering algorithms are tested and compared in the task of fast nuclei segmentation. K-means, fuzzy C-means, competitive learning neural networks and Gaussian mixture models were incorporated for clustering in the color space along with adaptive thresholding in grayscale. These methods were applied in a medical decision support system for breast cancer diagnosis, where the cases were classified as either benign or malignant. In the segmented nuclei, 42 morphological, topological and texture features were extracted. Then, these features were used in a classification procedure with three different classifiers. The system was tested for classification accuracy by means of microscopic images of fine needle breast biopsies. In cooperation with the Regional Hospital in Zielona Góra, 500 real case medical images from 50 patients were collected. The acquired classification accuracy was approximately 96-100%, which is very promising and shows that the presented method ensures accurate and objective data acquisition that could be used to facilitate breast cancer diagnosis. PMID:24034748

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

    PubMed Central

    2011-01-01

    The term congenital neutropenia encompasses a family of neutropenic disorders, both permanent and intermittent, severe (<0.5 G/l) or mild (between 0.5-1.5 G/l), which may also affect other organ systems such as the pancreas, central nervous system, heart, muscle and skin. Neutropenia can lead to life-threatening pyogenic infections, acute gingivostomatitis and chronic parodontal disease, and each successive infection may leave permanent sequelae. The risk of infection is roughly inversely proportional to the circulating polymorphonuclear neutrophil count and is particularly high at counts below 0.2 G/l. When neutropenia is detected, an attempt should be made to establish the etiology, distinguishing between acquired forms (the most frequent, including post viral neutropenia and auto immune neutropenia) and congenital forms that may either be isolated or part of a complex genetic disease. Except for ethnic neutropenia, which is a frequent but mild congenital form, probably with polygenic inheritance, all other forms of congenital neutropenia are extremely rare and have monogenic inheritance, which may be X-linked or autosomal, recessive or dominant. About half the forms of congenital neutropenia with no extra-hematopoetic manifestations and normal adaptive immunity are due to neutrophil elastase (ELANE) mutations. Some patients have severe permanent neutropenia and frequent infections early in life, while others have mild intermittent neutropenia. Congenital neutropenia may also be associated with a wide range of organ dysfunctions, as for example in Shwachman-Diamond syndrome (associated with pancreatic insufficiency) and glycogen storage disease type Ib (associated with a glycogen storage syndrome). So far, the molecular bases of 12 neutropenic disorders have been identified. Treatment of severe chronic neutropenia should focus on prevention of infections. It includes antimicrobial prophylaxis, generally with trimethoprim-sulfamethoxazole, and also granulocyte

  14. Additional correction for energy transfer efficiency calculation in filter-based Förster resonance energy transfer microscopy for more accurate results

    NASA Astrophysics Data System (ADS)

    Sun, Yuansheng; Periasamy, Ammasi

    2010-03-01

    Förster resonance energy transfer (FRET) microscopy is commonly used to monitor protein interactions with filter-based imaging systems, which require spectral bleedthrough (or cross talk) correction to accurately measure energy transfer efficiency (E). The double-label (donor+acceptor) specimen is excited with the donor wavelength, the acceptor emission provided the uncorrected FRET signal and the donor emission (the donor channel) represents the quenched donor (qD), the basis for the E calculation. Our results indicate this is not the most accurate determination of the quenched donor signal as it fails to consider the donor spectral bleedthrough (DSBT) signals in the qD for the E calculation, which our new model addresses, leading to a more accurate E result. This refinement improves E comparisons made with lifetime and spectral FRET imaging microscopy as shown here using several genetic (FRET standard) constructs, where cerulean and venus fluorescent proteins are tethered by different amino acid linkers.

  15. 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…

  16. The Analysis of Organizational Diagnosis on Based Six Box Model in Universities

    ERIC Educational Resources Information Center

    Hamid, Rahimi; Siadat, Sayyed Ali; Reza, Hoveida; Arash, Shahin; Ali, Nasrabadi Hasan; Azizollah, Arbabisarjou

    2011-01-01

    Purpose: The analysis of organizational diagnosis on based six box model at universities. Research method: Research method was descriptive-survey. Statistical population consisted of 1544 faculty members of universities which through random strafed sampling method 218 persons were chosen as the sample. Research Instrument were organizational…

  17. An accurate and efficient acoustic eigensolver based on a fast multipole BEM and a contour integral method

    NASA Astrophysics Data System (ADS)

    Zheng, Chang-Jun; Gao, Hai-Feng; Du, Lei; Chen, Hai-Bo; Zhang, Chuanzeng

    2016-01-01

    An accurate numerical solver is developed in this paper for eigenproblems governed by the Helmholtz equation and formulated through the boundary element method. A contour integral method is used to convert the nonlinear eigenproblem into an ordinary eigenproblem, so that eigenvalues can be extracted accurately by solving a set of standard boundary element systems of equations. In order to accelerate the solution procedure, the parameters affecting the accuracy and efficiency of the method are studied and two contour paths are compared. Moreover, a wideband fast multipole method is implemented with a block IDR (s) solver to reduce the overall solution cost of the boundary element systems of equations with multiple right-hand sides. The Burton-Miller formulation is employed to identify the fictitious eigenfrequencies of the interior acoustic problems with multiply connected domains. The actual effect of the Burton-Miller formulation on tackling the fictitious eigenfrequency problem is investigated and the optimal choice of the coupling parameter as α = i / k is confirmed through exterior sphere examples. Furthermore, the numerical eigenvalues obtained by the developed method are compared with the results obtained by the finite element method to show the accuracy and efficiency of the developed method.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. 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.

  4. 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(®).

  5. Accurate single-day titration of adenovirus vectors based on equivalence of protein VII nuclear dots and infectious particles.

    PubMed

    Walkiewicz, Marcin P; Morral, Nuria; Engel, Daniel A

    2009-08-01

    Protein VII is an abundant component of adenovirus particles and is tightly associated with the viral DNA. It enters the nucleus along with the infecting viral genome and remains bound throughout early phase. Protein VII can be visualized by immunofluorescent staining as discrete dots in the infected cell nucleus. Comparison between protein VII staining and expression of the 72kDa DNA-binding protein revealed a one-to-one correspondence between protein VII dots and infectious viral genomes. A similar relationship was observed for a helper-dependent adenovirus vector expressing green fluorescent protein. This relationship allowed accurate titration of adenovirus preparations, including wild-type and helper-dependent vectors, using a 1-day immunofluorescence method. The method can be applied to any adenovirus vector and gives results equivalent to the standard plaque assay.

  6. Accurate single-day titration of adenovirus vectors based on equivalence of protein VII nuclear dots and infectious particles.

    PubMed

    Walkiewicz, Marcin P; Morral, Nuria; Engel, Daniel A

    2009-08-01

    Protein VII is an abundant component of adenovirus particles and is tightly associated with the viral DNA. It enters the nucleus along with the infecting viral genome and remains bound throughout early phase. Protein VII can be visualized by immunofluorescent staining as discrete dots in the infected cell nucleus. Comparison between protein VII staining and expression of the 72kDa DNA-binding protein revealed a one-to-one correspondence between protein VII dots and infectious viral genomes. A similar relationship was observed for a helper-dependent adenovirus vector expressing green fluorescent protein. This relationship allowed accurate titration of adenovirus preparations, including wild-type and helper-dependent vectors, using a 1-day immunofluorescence method. The method can be applied to any adenovirus vector and gives results equivalent to the standard plaque assay. PMID:19406166

  7. 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

  8. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    PubMed

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

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

  9. 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.

  10. 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

  11. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    PubMed

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  12. 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.

  13. 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

  14. 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

  15. 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.

  16. Pathologic diagnosis of achondrogenesis type 2 in a fragmented fetus: case report and evidence-based differential diagnostic approach in the early midtrimester.

    PubMed

    Weisman, Paul S; Kashireddy, Papreddy V; Ernst, Linda M

    2014-01-01

    As a group, lethal genetic skeletal disorders (GSDs) usually result in death within the perinatal period. Because lethal GSDs are often ultrasonographically detectible by early midtrimester, dilation and evacuation (D&E) is the method of choice for elective termination of pregnancy in many institutions. However, because the diagnosis of the lethal GSDs relies heavily upon radiologic examination of fetal remains, reaching an accurate diagnosis in this setting can be challenging. We report an autopsy case of a fetus delivered by D&E at 15 4/7 weeks gestation with radiologic, histologic, and genetic findings compatible with achondrogenesis type 2 and discuss an evidence-based differential diagnostic approach to lethal GSDs terminated by early midtrimester D&E. PMID:24144387

  17. 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.

  18. The usefulness of clinical-practice-based laboratory data in facilitating the diagnosis of dengue illness.

    PubMed

    Liu, Jien-Wei; Lee, Ing-Kit; Wang, Lin; Chen, Rong-Fu; Yang, Kuender D

    2013-01-01

    Alertness to dengue and making a timely diagnosis is extremely important in the treatment of dengue and containment of dengue epidemics. We evaluated the complementary role of clinical-practice-based laboratory data in facilitating suspicion/diagnosis of dengue. One hundred overall dengue (57 dengue fever [DF] and 43 dengue hemorrhagic fever [DHF]) cases and another 100 nondengue cases (78 viral infections other than dengue, 6 bacterial sepsis, and 16 miscellaneous diseases) were analyzed. We separately compared individual laboratory variables (platelet count [PC] , prothrombin time [PT], activated partial thromboplastin time [APTT], alanine aminotransferase [ALT], and aspartate aminotransferase [AST]) and varied combined variables of DF and/or DHF cases with the corresponding ones of nondengue cases. The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) in the diagnosis of DF and/or DHF were measured based on these laboratory variables. While trade-off between sensitivity and specificity, and/or suboptimal PPV/NPV was found at measurements using these variables, prolonged APTT + normal PT + PC < 100 × 10(9) cells/L had a favorable sensitivity, specificity, PPV, and NPV in diagnosis of DF and/or DHF. In conclusion, these data suggested that prolonged APTT + normal PT + PC < 100 × 10(9) cells/L is useful in evaluating the likelihood of DF and/or DHF.

  19. The Usefulness of Clinical-Practice-Based Laboratory Data in Facilitating the Diagnosis of Dengue Illness

    PubMed Central

    Liu, Jien-Wei; Lee, Ing-Kit; Wang, Lin; Chen, Rong-Fu; Yang, Kuender D.

    2013-01-01

    Alertness to dengue and making a timely diagnosis is extremely important in the treatment of dengue and containment of dengue epidemics. We evaluated the complementary role of clinical-practice-based laboratory data in facilitating suspicion/diagnosis of dengue. One hundred overall dengue (57 dengue fever [DF] and 43 dengue hemorrhagic fever [DHF]) cases and another 100 nondengue cases (78 viral infections other than dengue, 6 bacterial sepsis, and 16 miscellaneous diseases) were analyzed. We separately compared individual laboratory variables (platelet count [PC] , prothrombin time [PT], activated partial thromboplastin time [APTT], alanine aminotransferase [ALT], and aspartate aminotransferase [AST]) and varied combined variables of DF and/or DHF cases with the corresponding ones of nondengue cases. The sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) in the diagnosis of DF and/or DHF were measured based on these laboratory variables. While trade-off between sensitivity and specificity, and/or suboptimal PPV/NPV was found at measurements using these variables, prolonged APTT + normal PT + PC < 100 × 109 cells/L had a favorable sensitivity, specificity, PPV, and NPV in diagnosis of DF and/or DHF. In conclusion, these data suggested that prolonged APTT + normal PT + PC < 100 × 109 cells/L is useful in evaluating the likelihood of DF and/or DHF. PMID:24455678

  20. Fault diagnosis method based on FFT-RPCA-SVM for Cascaded-Multilevel Inverter.

    PubMed

    Wang, Tianzhen; Qi, Jie; Xu, Hao; Wang, Yide; Liu, Lei; Gao, Diju

    2016-01-01

    Thanks to reduced switch stress, high quality of load wave, easy packaging and good extensibility, the cascaded H-bridge multilevel inverter is widely used in wind power system. To guarantee stable operation of system, a new fault diagnosis method, based on Fast Fourier Transform (FFT), Relative Principle Component Analysis (RPCA) and Support Vector Machine (SVM), is proposed for H-bridge multilevel inverter. To avoid the influence of load variation on fault diagnosis, the output voltages of the inverter is chosen as the fault characteristic signals. To shorten the time of diagnosis and improve the diagnostic accuracy, the main features of the fault characteristic signals are extracted by FFT. To further reduce the training time of SVM, the feature vector is reduced based on RPCA that can get a lower dimensional feature space. The fault classifier is constructed via SVM. An experimental prototype of the inverter is built to test the proposed method. Compared to other fault diagnosis methods, the experimental results demonstrate the high accuracy and efficiency of the proposed method. PMID:26626623

  1. Gene-Based Multiclass Cancer Diagnosis with Class-Selective Rejections

    PubMed Central

    Jrad, Nisrine; Grall-Maës, Edith; Beauseroy, Pierre

    2009-01-01

    Supervised learning of microarray data is receiving much attention in recent years. Multiclass cancer diagnosis, based on selected gene profiles, are used as adjunct of clinical diagnosis. However, supervised diagnosis may hinder patient care, add expense or confound a result. To avoid this misleading, a multiclass cancer diagnosis with class-selective rejection is proposed. It rejects some patients from one, some, or all classes in order to ensure a higher reliability while reducing time and expense costs. Moreover, this classifier takes into account asymmetric penalties dependant on each class and on each wrong or partially correct decision. It is based on ν-1-SVM coupled with its regularization path and minimizes a general loss function defined in the class-selective rejection scheme. The state of art multiclass algorithms can be considered as a particular case of the proposed algorithm where the number of decisions is given by the classes and the loss function is defined by the Bayesian risk. Two experiments are carried out in the Bayesian and the class selective rejection frameworks. Five genes selected datasets are used to assess the performance of the proposed method. Results are discussed and accuracies are compared with those computed by the Naive Bayes, Nearest Neighbor, Linear Perceptron, Multilayer Perceptron, and Support Vector Machines classifiers. PMID:19584932

  2. Gene-based multiclass cancer diagnosis with class-selective rejections.

    PubMed

    Jrad, Nisrine; Grall-Maës, Edith; Beauseroy, Pierre

    2009-01-01

    Supervised learning of microarray data is receiving much attention in recent years. Multiclass cancer diagnosis, based on selected gene profiles, are used as adjunct of clinical diagnosis. However, supervised diagnosis may hinder patient care, add expense or confound a result. To avoid this misleading, a multiclass cancer diagnosis with class-selective rejection is proposed. It rejects some patients from one, some, or all classes in order to ensure a higher reliability while reducing time and expense costs. Moreover, this classifier takes into account asymmetric penalties dependent on each class and on each wrong or partially correct decision. It is based on nu-1-SVM coupled with its regularization path and minimizes a general loss function defined in the class-selective rejection scheme. The state of art multiclass algorithms can be considered as a particular case of the proposed algorithm where the number of decisions is given by the classes and the loss function is defined by the Bayesian risk. Two experiments are carried out in the Bayesian and the class selective rejection frameworks. Five genes selected datasets are used to assess the performance of the proposed method. Results are discussed and accuracies are compared with those computed by the Naive Bayes, Nearest Neighbor, Linear Perceptron, Multilayer Perceptron, and Support Vector Machines classifiers.

  3. 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.

  4. A novel diagnosis method for a Hall plates-based rotary encoder with a magnetic concentrator.

    PubMed

    Meng, Bumin; Wang, Yaonan; Sun, Wei; Yuan, Xiaofang

    2014-01-01

    In the last few years, rotary encoders based on two-dimensional complementary metal oxide semiconductors (CMOS) Hall plates with a magnetic concentrator have been developed to measure contactless absolute angle. There are various error factors influencing the measuring accuracy, which are difficult to locate after the assembly of encoder. In this paper, a model-based rapid diagnosis method is presented. Based on an analysis of the error mechanism, an error model is built to compare minimum residual angle error and to quantify the error factors. Additionally, a modified particle swarm optimization (PSO) algorithm is used to reduce the calculated amount. The simulation and experimental results show that this diagnosis method is feasible to quantify the causes of the error and to reduce iteration significantly. PMID:25090417

  5. Fanconi Anemia and its Diagnosis

    PubMed Central

    Auerbach, Arleen D.

    2009-01-01

    Fanconi anemia (FA) is a genetically and phenotypically heterogeneous recessive disorder characterized by diverse congenital malformations, progressive pancytopenia, and predisposition to both hematologic malignancies and solid tumors. Congenital anomalies vary from patient to patient and may affect skeletal morphogenesis as well as any of the major organ systems. Although this highly variable phenotype makes accurate diagnosis on the basis of clinical manifestations difficult in some patients, laboratory study of chromosomal breakage induced by diepoxybutane (DEB) or other crosslinking agents provides a unique cellular marker for the diagnosis of the disorder either prenatally or postnatally. Diagnosis based on abnormal response to DNA crosslinking agents can be used to identify the pre-anemia patient as well as patients with aplastic anemia or leukemia who may or may not have the physical stigmata associated with the syndrome. This overview will present our present knowledge regarding the varied phenotypic manifestations of FA and procedures for diagnosis based upon abnormal DNA damage responses. PMID:19622403

  6. Plus Disease in Retinopathy of Prematurity: Pilot Study of Computer-Based and Expert Diagnosis

    PubMed Central

    Gelman, Rony; Jiang, Lei; Du, Yunling E.; Martinez-Perez, M. Elena; Flynn, John T.; Chiang, Michael F.

    2008-01-01

    Purpose To measure accuracy of plus disease diagnosis by recognized experts in retinopathy of prematurity (ROP), and to conduct a pilot study examining performance of a computer-based image analysis system, Retinal Image multiScale Analysis (RISA). Methods Twenty-two ROP experts independently interpreted a set of 34 wide-angle retinal images for presence of plus disease. A reference standard diagnosis based on expert consensus was defined for each image. Images were analyzed by the computer-based system using individual and linear combinations of system parameters for arterioles and venules: integrated curvature (IC), diameter, and tortuosity index (TI). Sensitivity, specificity, and receiver operating characteristic areas under the curve (AUC) for plus disease diagnosis compared to the reference standard were determined for each expert, as well as for the computer-based system. Results Expert sensitivity ranged from 0.308–1.000, specificity ranged from 0.571–1.000, and AUC ranged from 0.784–1.000. Among individual computer system parameters, venular IC had highest AUC (0.853). Among all computer system parameters, the linear combination of arteriolar IC, arteriolar TI, venular IC, venular diameter, and venular TI had highest AUC (0.967), which was greater than that of 18 (81.8%) of 22 experts. Conclusions Accuracy of ROP experts for plus disease diagnosis is imperfect. A computer-based image analysis system has potential to diagnose plus disease with high accuracy. Further research involving RISA system parameter cut-off values from this study are required to fully validate performance of this computer-based system compared to that of human experts. PMID:18029210

  7. Automatic small bowel tumor diagnosis by using multi-scale wavelet-based analysis in wireless capsule endoscopy images

    PubMed Central

    2012-01-01

    Background Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. Method The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. Results The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice. PMID:22236465

  8. How accurate is the reporting of stroke in hospital discharge data? A pilot validation study using a population-based stroke registry as control.

    PubMed

    Aboa-Eboulé, Corine; Mengue, Dominique; Benzenine, Eric; Hommel, Marc; Giroud, Maurice; Béjot, Yannick; Quantin, Catherine

    2013-02-01

    Population-based stroke registries can provide valid stroke incidence because they ensure exhaustiveness of case ascertainment. However, their results are difficult to extrapolate because they cover a small population. The French Hospital Discharge Database (FHDDB), which routinely collects administrative data, could be a useful tool for providing data on the nationwide burden of stroke. The aim of our pilot study was to assess the validity of stroke diagnosis reported in the FHDDB. All records of patients with a diagnosis of stroke between 2004 and 2008 were retrieved from the FHDDB of Dijon Teaching Hospital. The Dijon Stroke Registry was considered as the gold standard. The sensitivity, positive predictive value (PPV), and weighted kappa were calculated. The Dijon Stroke Registry identified 811 patients with a stroke, among whom 186 were missed by the FHDDB and thus considered false-negatives. The FHDDB identified 903 patients discharged following a stroke including 625 true-positives confirmed by the registry and 278 false-positives. The overall sensitivity and PPV of the FHDDB for the diagnosis of stroke were, respectively, 77.1 % (95 % CI 74.2-80) and 69.2 % (95 % CI 66.1-72.2). For cardioembolic and lacunar strokes, the FHDDB yielded higher PPVs (respectively 86.7 and 84.6 %; p < 0.0001) than those of other stroke subtypes. The PPV but not sensitivity significantly increased over the years (p < 0.0001). Agreement with the stroke registry was moderate (kappa 52.8; 95 % CI 46.8-58.9). The FHDDB-based stroke diagnosis showed moderate validity compared with the Dijon Stroke Registry as the gold standard. However, its accuracy (PPV) increased with time and was higher for some stroke subtypes.

  9. Accurate electrical prediction of memory array through SEM-based edge-contour extraction using SPICE simulation

    NASA Astrophysics Data System (ADS)

    Shauly, Eitan; Rotstein, Israel; Peltinov, Ram; Latinski, Sergei; Adan, Ofer; Levi, Shimon; Menadeva, Ovadya

    2009-03-01

    The continues transistors scaling efforts, for smaller devices, similar (or larger) drive current/um and faster devices, increase the challenge to predict and to control the transistor off-state current. Typically, electrical simulators like SPICE, are using the design intent (as-drawn GDS data). At more sophisticated cases, the simulators are fed with the pattern after lithography and etch process simulations. As the importance of electrical simulation accuracy is increasing and leakage is becoming more dominant, there is a need to feed these simulators, with more accurate information extracted from physical on-silicon transistors. Our methodology to predict changes in device performances due to systematic lithography and etch effects was used in this paper. In general, the methodology consists on using the OPCCmaxTM for systematic Edge-Contour-Extraction (ECE) from transistors, taking along the manufacturing and includes any image distortions like line-end shortening, corner rounding and line-edge roughness. These measurements are used for SPICE modeling. Possible application of this new metrology is to provide a-head of time, physical and electrical statistical data improving time to market. In this work, we applied our methodology to analyze a small and large array's of 2.14um2 6T-SRAM, manufactured using Tower Standard Logic for General Purposes Platform. 4 out of the 6 transistors used "U-Shape AA", known to have higher variability. The predicted electrical performances of the transistors drive current and leakage current, in terms of nominal values and variability are presented. We also used the methodology to analyze an entire SRAM Block array. Study of an isolation leakage and variability are presented.

  10. Computed-tomography-based finite-element models of long bones can accurately capture strain response to bending and torsion.

    PubMed

    Varghese, Bino; Short, David; Penmetsa, Ravi; Goswami, Tarun; Hangartner, Thomas

    2011-04-29

    Finite element (FE) models of long bones constructed from computed-tomography (CT) data are emerging as an invaluable tool in the field of bone biomechanics. However, the performance of such FE models is highly dependent on the accurate capture of geometry and appropriate assignment of material properties. In this study, a combined numerical-experimental study is performed comparing FE-predicted surface strains with strain-gauge measurements. Thirty-six major, cadaveric, long bones (humerus, radius, femur and tibia), which cover a wide range of bone sizes, were tested under three-point bending and torsion. The FE models were constructed from trans-axial volumetric CT scans, and the segmented bone images were corrected for partial-volume effects. The material properties (Young's modulus for cortex, density-modulus relationship for trabecular bone and Poisson's ratio) were calibrated by minimizing the error between experiments and simulations among all bones. The R(2) values of the measured strains versus load under three-point bending and torsion were 0.96-0.99 and 0.61-0.99, respectively, for all bones in our dataset. The errors of the calculated FE strains in comparison to those measured using strain gauges in the mechanical tests ranged from -6% to 7% under bending and from -37% to 19% under torsion. The observation of comparatively low errors and high correlations between the FE-predicted strains and the experimental strains, across the various types of bones and loading conditions (bending and torsion), validates our approach to bone segmentation and our choice of material properties.

  11. 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

  12. 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

  13. 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

  14. 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.

  15. Study on Hankel matrix-based SVD and its application in rolling element bearing fault diagnosis

    NASA Astrophysics Data System (ADS)

    Jiang, Huiming; Chen, Jin; Dong, Guangming; Liu, Tao; Chen, Gang

    2015-02-01

    Based on the traditional theory of singular value decomposition (SVD), singular values (SVs) and ratios of neighboring singular values (NSVRs) are introduced to the feature extraction of vibration signals. The proposed feature extraction method is called SV-NSVR. Combined with selected SV-NSVR features, continuous hidden Markov model (CHMM) is used to realize the automatic classification. Then the SV-NSVR and CHMM based method is applied in fault diagnosis and performance assessment of rolling element bearings. The simulation and experimental results show that this method has a higher accuracy for the bearing fault diagnosis compared with those using other SVD features, and it is effective for the performance assessment of rolling element bearings.

  16. Computer-Aided Diagnosis and Quantification of Cirrhotic Livers Based on Morphological Analysis and Machine Learning

    PubMed Central

    Chen, Yen-Wei; Luo, Jie; Dong, Chunhua; Han, Xianhua; Tateyama, Tomoko; Furukawa, Akira; Kanasaki, Shuzo

    2013-01-01

    It is widely known that morphological changes of the liver and the spleen occur during the clinical course of chronic liver diseases. In this paper, we proposed a morphological analysis method based on statistical shape models (SSMs) of the liver and spleen for computer-aided diagnosis and quantification of the chronic liver. We constructed not only the liver SSM but also the spleen SSM and a joint SSM of the liver and the spleen for a morphologic analysis of the cirrhotic liver in CT images. The effective modes are selected based on both its accumulation contribution rate and its correlation with doctor's opinions (stage labels). We then learn a mapping function between the selected mode and the stage of chronic liver. The mapping function was used for diagnosis and staging of chronic liver diseases. PMID:24187579

  17. Design-based approach to ethics in computer-aided diagnosis

    NASA Astrophysics Data System (ADS)

    Collmann, Jeff R.; Lin, Jyh-Shyan; Freedman, Matthew T.; Wu, Chris Y.; Hayes, Wendelin S.; Mun, Seong K.

    1996-04-01

    A design-based approach to ethical analysis examines how computer scientists, physicians and patients make and justify choices in designing, using and reacting to computer-aided diagnosis (CADx) systems. The basic hypothesis of this research is that values are embedded in CADx systems during all phases of their development, not just retrospectively imposed on them. This paper concentrates on the work of computer scientists and physicians as they attempt to resolve central technical questions in designing clinically functional CADx systems for lung cancer and breast cancer diagnosis. The work of Lo, Chan, Freedman, Lin, Wu and their colleagues provides the initial data on which this study is based. As these researchers seek to increase the rate of true positive classifications of detected abnormalities in chest radiographs and mammograms, they explore dimensions of the fundamental ethical principal of beneficence. The training of CADx systems demonstrates the key ethical dilemmas inherent in their current design.

  18. 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.; Parks, Jerry M.

    2016-07-08

    In redox processes in complex transition metal-containing species are often intimately associated with changes in ligand protonation states and metal coordination number. Moreover, a major challenge is therefore to develop consistent computational approaches for computing pH-dependent redox and ligand dissociation properties of organometallic species. Reduction of the Co center in the vitamin B12 derivative aquacobalamin can be accompanied by ligand dissociation, protonation, or both, making these properties difficult to compute accurately. We examine this challenge here by using density functional theory and continuum solvation to compute Co ligand binding equilibrium constants (Kon/off), pKas and reduction potentials for models of aquacobalaminmore » in aqueous solution. We consider two models for cobalamin ligand coordination: the first follows the hexa, penta, tetra coordination scheme for CoIII, CoII, and CoI species, respectively, and the second model features saturation of each vacant axial coordination site on CoII and CoI species with a single, explicit water molecule to maintain six directly interacting ligands or water molecules in each oxidation state. Comparing these two coordination schemes in combination with five dispersion-corrected density functionals, we find that the accuracy of the computed properties is largely independent of the scheme used, but including only a continuum representation of the solvent yields marginally better results than saturating the first solvation shell around Co throughout. PBE performs best, displaying balanced accuracy and superior performance overall, with RMS errors of 80 mV for seven reduction potentials, 2.0 log units for five pKas and 2.3 log units for two log Kon/off values for the aquacobalamin system. Furthermore, we find that the BP86 functional commonly used in corrinoid studies suffers from erratic behavior and inaccurate descriptions of Co axial ligand binding, leading to substantial errors in predicted

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

    PubMed

    Johnston, Ryne C; Zhou, Jing; Smith, Jeremy C; Parks, Jerry M

    2016-08-01

    Redox processes in complex transition metal-containing species are often intimately associated with changes in ligand protonation states and metal coordination number. A major challenge is therefore to develop consistent computational approaches for computing pH-dependent redox and ligand dissociation properties of organometallic species. Reduction of the Co center in the vitamin B12 derivative aquacobalamin can be accompanied by ligand dissociation, protonation, or both, making these properties difficult to compute accurately. We examine this challenge here by using density functional theory and continuum solvation to compute Co-ligand binding equilibrium constants (Kon/off), pKas, and reduction potentials for models of aquacobalamin in aqueous solution. We consider two models for cobalamin ligand coordination: the first follows the hexa, penta, tetra coordination scheme for Co(III), Co(II), and Co(I) species, respectively, and the second model features saturation of each vacant axial coordination site on Co(II) and Co(I) species with a single, explicit water molecule to maintain six directly interacting ligands or water molecules in each oxidation state. Comparing these two coordination schemes in combination with five dispersion-corrected density functionals, we find that the accuracy of the computed properties is largely independent of the scheme used, but including only a continuum representation of the solvent yields marginally better results than saturating the first solvation shell around Co throughout. PBE performs best, displaying balanced accuracy and superior performance overall, with RMS errors of 80 mV for seven reduction potentials, 2.0 log units for five pKas and 2.3 log units for two log Kon/off values for the aquacobalamin system. Furthermore, we find that the BP86 functional commonly used in corrinoid studies suffers from erratic behavior and inaccurate descriptions of Co-axial ligand binding, leading to substantial errors in predicted pKas and

  20. Stable and accurate hybrid finite volume methods based on pure convexity arguments for hyperbolic systems of conservation law

    NASA Astrophysics Data System (ADS)

    De Vuyst, Florian

    2004-01-01

    This exploratory work tries to present first results of a novel approach for the numerical approximation of solutions of hyperbolic systems of conservation laws. The objective is to define stable and "reasonably" accurate numerical schemes while being free from any upwind process and from any computation of derivatives or mean Jacobian matrices. That means that we only want to perform flux evaluations. This would be useful for "complicated" systems like those of two-phase models where solutions of Riemann problems are hard, see impossible to compute. For Riemann or Roe-like solvers, each fluid model needs the particular computation of the Jacobian matrix of the flux and the hyperbolicity property which can be conditional for some of these models makes the matrices be not R-diagonalizable everywhere in the admissible state space. In this paper, we rather propose some numerical schemes where the stability is obtained using convexity considerations. A certain rate of accuracy is also expected. For that, we propose to build numerical hybrid fluxes that are convex combinations of the second-order Lax-Wendroff scheme flux and the first-order modified Lax-Friedrichs scheme flux with an "optimal" combination rate that ensures both minimal numerical dissipation and good accuracy. The resulting scheme is a central scheme-like method. We will also need and propose a definition of local dissipation by convexity for hyperbolic or elliptic-hyperbolic systems. This convexity argument allows us to overcome the difficulty of nonexistence of classical entropy-flux pairs for certain systems. We emphasize the systematic feature of the method which can be fastly implemented or adapted to any kind of systems, with general analytical or data-tabulated equations of state. The numerical results presented in the paper are not superior to many existing state-of-the-art numerical methods for conservation laws such as ENO, MUSCL or central scheme of Tadmor and coworkers. The interest is rather

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

    PubMed

    Johnston, Ryne C; Zhou, Jing; Smith, Jeremy C; Parks, Jerry M

    2016-08-01

    Redox processes in complex transition metal-containing species are often intimately associated with changes in ligand protonation states and metal coordination number. A major challenge is therefore to develop consistent computational approaches for computing pH-dependent redox and ligand dissociation properties of organometallic species. Reduction of the Co center in the vitamin B12 derivative aquacobalamin can be accompanied by ligand dissociation, protonation, or both, making these properties difficult to compute accurately. We examine this challenge here by using density functional theory and continuum solvation to compute Co-ligand binding equilibrium constants (Kon/off), pKas, and reduction potentials for models of aquacobalamin in aqueous solution. We consider two models for cobalamin ligand coordination: the first follows the hexa, penta, tetra coordination scheme for Co(III), Co(II), and Co(I) species, respectively, and the second model features saturation of each vacant axial coordination site on Co(II) and Co(I) species with a single, explicit water molecule to maintain six directly interacting ligands or water molecules in each oxidation state. Comparing these two coordination schemes in combination with five dispersion-corrected density functionals, we find that the accuracy of the computed properties is largely independent of the scheme used, but including only a continuum representation of the solvent yields marginally better results than saturating the first solvation shell around Co throughout. PBE performs best, displaying balanced accuracy and superior performance overall, with RMS errors of 80 mV for seven reduction potentials, 2.0 log units for five pKas and 2.3 log units for two log Kon/off values for the aquacobalamin system. Furthermore, we find that the BP86 functional commonly used in corrinoid studies suffers from erratic behavior and inaccurate descriptions of Co-axial ligand binding, leading to substantial errors in predicted pKas and

  2. 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.

  3. Targeted Proteomics Enables Simultaneous Quantification of Folate Receptor Isoforms and Potential Isoform-based Diagnosis in Breast Cancer.

    PubMed

    Yang, Ting; Xu, Feifei; Fang, Danjun; Chen, Yun

    2015-11-17

    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.

  4. 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

  5. Differential diagnosis of Brucella abortus by real-time PCR based on a single-nucleotide polymorphisms.

    PubMed

    Kim, Ji-Yeon; Kang, Sung-Il; Lee, Jin Ju; Lee, Kichan; Sung, So-Ra; Erdenebaataar, Janchivdorj; Vanaabaatar, Batbaatar; Jung, Suk Chan; Park, Yong Ho; Yoo, Han-Sang; Her, Moon

    2016-05-01

    To diagnose brucellosis effectively, many genus- and species-specific detection methods based on PCR have been developed. With conventional PCR assays, real-time PCR techniques have been developed as rapid diagnostic tools. Among them, real-time PCR using hybridization probe (hybprobe) has been recommended for bacteria with high DNA homology among species, with which it is possible to make an accurate diagnosis by means of an amplification curve and melting peak analysis. A hybprobe for B. abortus was designed from a specific single-nucleotide polymorphism (SNP) on the fbaA gene. This probe only showed specific amplification of B. abortus from approximately the 14th cycle, given a melting peak at 69°C. The sensitivity of real-time PCR was revealed to be 20 fg/µl by 10-fold DNA dilution, and the detection limit was 4 CFU in clinical samples. This real-time PCR showed greater sensitivity than that of conventional PCR and previous real-time PCR based on Taqman probe. Therefore, this new real-time PCR assay could be helpful for differentiating B. abortus infection with rapidity and accuracy.

  6. Differential diagnosis of Brucella abortus by real-time PCR based on a single-nucleotide polymorphisms

    PubMed Central

    KIM, Ji-Yeon; KANG, Sung-Il; LEE, Jin Ju; LEE, Kichan; SUNG, So-Ra; ERDENEBAATAAR, Janchivdorj; VANAABAATAR, Batbaatar; JUNG, Suk Chan; PARK, Yong Ho; YOO, Han-Sang; HER, Moon

    2015-01-01

    To diagnose brucellosis effectively, many genus- and species-specific detection methods based on PCR have been developed. With conventional PCR assays, real-time PCR techniques have been developed as rapid diagnostic tools. Among them, real-time PCR using hybridization probe (hybprobe) has been recommended for bacteria with high DNA homology among species, with which it is possible to make an accurate diagnosis by means of an amplification curve and melting peak analysis. A hybprobe for B. abortus was designed from a specific single-nucleotide polymorphism (SNP) on the fbaA gene. This probe only showed specific amplification of B. abortus from approximately the 14th cycle, given a melting peak at 69°C. The sensitivity of real-time PCR was revealed to be 20 fg/µl by 10-fold DNA dilution, and the detection limit was 4 CFU in clinical samples. This real-time PCR showed greater sensitivity than that of conventional PCR and previous real-time PCR based on Taqman probe. Therefore, this new real-time PCR assay could be helpful for differentiating B. abortus infection with rapidity and accuracy. PMID:26666176

  7. A fault diagnosis approach for diesel engine valve train based on improved ITD and SDAG-RVM

    NASA Astrophysics Data System (ADS)

    Yu, Liu; Junhong, Zhang; Fengrong, Bi; Jiewei, Lin; Wenpeng, Ma

    2015-02-01

    Targeting the non-stationary characteristics of the vibration signals of a diesel engine valve train, and the limitation of the autoregressive (AR) model, a novel approach based on the improved intrinsic time-scale decomposition (ITD) and relevance vector machine (RVM) is proposed in this paper for the identification of diesel engine valve train faults. The approach mainly consists of three stages: First, prior to the feature extraction, non-uniform B-spline interpolation is introduced to the ITD method for the fitting of baseline signal, then the improved ITD is used to decompose the non-stationary signals into a set of stationary proper rotation components (PRCs). Second, the AR model is established for each PRC, and the first several AR coefficients together with the remnant variance of all PRCs are regarded as the fault feature vectors. Finally, a new separability based directed acyclic graph (SDAG) method is proposed to determine the structure of multi-class RVM, and the fault feature vectors are classified using the SDAG-RVM classifier to recognize the fault of the diesel engine valve train. The experimental results demonstrate that the proposed fault diagnosis approach can effectively extract the fault features and accurately identify the fault patterns.

  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

    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. 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

  10. 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.

  11. Mass Spectrometry-based Workflow for Accurate Quantification of Escherichia coli Enzymes: How Proteomics Can Play a Key Role in Metabolic Engineering*

    PubMed Central

    Trauchessec, Mathieu; Jaquinod, Michel; Bonvalot, Aline; Brun, Virginie; Bruley, Christophe; Ropers, Delphine; de Jong, Hidde; Garin, Jérôme; Bestel-Corre, Gwenaëlle; Ferro, Myriam

    2014-01-01

    Metabolic engineering aims to design high performance microbial strains producing compounds of interest. This requires systems-level understanding; genome-scale models have therefore been developed to predict metabolic fluxes. However, multi-omics data including genomics, transcriptomics, fluxomics, and proteomics may be required to model the metabolism of potential cell factories. Recent technological advances to quantitative proteomics have made mass spectrometry-based quantitative assays an interesting alternative to more traditional immuno-affinity based approaches. This has improved specificity and multiplexing capabilities. In this study, we developed a quantification workflow to analyze enzymes involved in central metabolism in Escherichia coli (E. coli). This workflow combined full-length isotopically labeled standards with selected reaction monitoring analysis. First, full-length 15N labeled standards were produced and calibrated to ensure accurate measurements. Liquid chromatography conditions were then optimized for reproducibility and multiplexing capabilities over a single 30-min liquid chromatography-MS analysis. This workflow was used to accurately quantify 22 enzymes involved in E. coli central metabolism in a wild-type reference strain and two derived strains, optimized for higher NADPH production. In combination with measurements of metabolic fluxes, proteomics data can be used to assess different levels of regulation, in particular enzyme abundance and catalytic rate. This provides information that can be used to design specific strains used in biotechnology. In addition, accurate measurement of absolute enzyme concentrations is key to the development of predictive kinetic models in the context of metabolic engineering. PMID:24482123

  12. Single nucleotide polymorphism-based microarray analysis for the diagnosis of hydatidiform moles

    PubMed Central

    XIE, YINGJUN; PEI, XIAOJUAN; DONG, YU; WU, HUIQUN; WU, JIANZHU; SHI, HUIJUAN; ZHUANG, XUYING; SUN, XIAOFANG; HE, JIALING

    2016-01-01

    In clinical diagnostics, single nucleotide polymorphism (SNP)-based microarray analysis enables the detection of copy number variations (CNVs), as well as copy number neutral regions, that are absent of heterozygosity throughout the genome. The aim of the present study was to evaluate the effectiveness and sensitivity of SNP-based microarray analysis in the diagnosis of hydatidiform mole (HM). By using whole-genome SNP microarray analysis, villous genotypes were detected, and the ploidy of villous tissue was determined to identify HMs. A total of 66 villous tissues and two twin tissues were assessed in the present study. Among these samples, 11 were triploid, one was tetraploid, 23 were abnormal aneuploidy, three were complete genome homozygosity, and the remaining ones were normal ploidy. The most noteworthy finding of the present study was the identification of six partial HMs and three complete HMs from those samples that were not identified as being HMs on the basis of the initial diagnosis of experienced obstetricians. This study has demonstrated that the application of an SNP-based microarray analysis was able to increase the sensitivity of diagnosis for HMs with partial and complete HMs, which makes the identification of these diseases at an early gestational age possible. PMID:27151252

  13. Accurate and easy-to-use assessment of contiguous DNA methylation sites based on proportion competitive quantitative-PCR and lateral flow nucleic acid biosensor.

    PubMed

    Xu, Wentao; Cheng, Nan; Huang, Kunlun; Lin, Yuehe; Wang, Chenguang; Xu, Yuancong; Zhu, Longjiao; Du, Dan; Luo, Yunbo

    2016-06-15

    Many types of diagnostic technologies have been reported for DNA methylation, but they require a standard curve for quantification or only show moderate accuracy. Moreover, most technologies have difficulty providing information on the level of methylation at specific contiguous multi-sites, not to mention easy-to-use detection to eliminate labor-intensive procedures. We have addressed these limitations and report here a cascade strategy that combines proportion competitive quantitative PCR (PCQ-PCR) and lateral flow nucleic acid biosensor (LFNAB), resulting in accurate and easy-to-use assessment. The P16 gene with specific multi-methylated sites, a well-studied tumor suppressor gene, was used as the target DNA sequence model. First, PCQ-PCR provided amplification products with an accurate proportion of multi-methylated sites following the principle of proportionality, and double-labeled duplex DNA was synthesized. Then, a LFNAB strategy was further employed for amplified signal detection via immune affinity recognition, and the exact level of site-specific methylation could be determined by the relative intensity of the test line and internal reference line. This combination resulted in all recoveries being greater than 94%, which are pretty satisfactory recoveries in DNA methylation assessment. Moreover, the developed cascades show significantly high usability as a simple, sensitive, and low-cost tool. Therefore, as a universal platform for sensing systems for the detection of contiguous multi-sites of DNA methylation without external standards and expensive instrumentation, this PCQ-PCR-LFNAB cascade method shows great promise for the point-of-care diagnosis of cancer risk and therapeutics.

  14. 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.

  15. 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.

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

    PubMed

    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. PMID:26429462

  17. Accurate kinematic measurement at interfaces between dissimilar materials using conforming finite-element-based digital image correlation

    NASA Astrophysics Data System (ADS)

    Tao, Ran; Moussawi, Ali; Lubineau, Gilles; Pan, Bing

    2016-06-01

    Digital image correlation (DIC) is now an extensively applied full-field measurement technique with subpixel accuracy. A systematic drawback of this technique, however, is the smoothening of the kinematic field (e.g., displacement and strains) across interfaces between dissimilar materials, where the deformation gradient is known to be large. This can become an issue when a high level of accuracy is needed, for example, in the interfacial region of composites or joints. In this work, we described the application of global conforming finite-element-based DIC technique to obtain precise kinematic fields at interfaces between dissimilar materials. Speckle images from both numerical and actual experiments processed by the described global DIC technique better captured sharp strain gradient at the interface than local subset-based DIC.

  18. NNLOPS accurate associated HW production

    NASA Astrophysics Data System (ADS)

    Astill, William; Bizon, Wojciech; Re, Emanuele; Zanderighi, Giulia

    2016-06-01

    We present a next-to-next-to-leading order accurate description of associated HW production consistently matched to a parton shower. The method is based on reweighting events obtained with the HW plus one jet NLO accurate calculation implemented in POWHEG, extended with the MiNLO procedure, to reproduce NNLO accurate Born distributions. Since the Born kinematics is more complex than the cases treated before, we use a parametrization of the Collins-Soper angles to reduce the number of variables required for the reweighting. We present phenomenological results at 13 TeV, with cuts suggested by the Higgs Cross section Working Group.

  19. A piecewise monotone subgradient algorithm for accurate L¹-TV based registration of physical slices with discontinuities in microscopy.

    PubMed

    Michalek, Jan; Capek, Martin

    2013-05-01

    Image registration tasks are often formulated in terms of minimization of a functional consisting of a data fidelity term penalizing the mismatch between the reference and the target image, and a term enforcing smoothness of shift between neighboring pairs of pixels (a min-sum problem). Most methods for deformable image registration use some form of interpolation between matching control points. The interpolation makes it impossible to account for isolated discontinuities in the deformation field that may appear, e.g., when a physical slice of a microscopy specimen is ruptured by the cutting tool. For registration of neighboring physical slices of microscopy specimens with discontinuities, Janácek proposed an L¹-distance data fidelity term and a total variation (TV) smoothness term, and used a graph-cut (GC) based iterative steepest descent algorithm for minimization. The L¹-TV functional is nonconvex; hence a steepest descent algorithm is not guaranteed to converge to the global minimum. Schlesinger presented transformation of max-sum problems to minimization of a dual quantity called problem power, which is--contrary to the original max-sum functional--convex. Based on Schlesinger's solution to max-sum problems we developed an algorithm for L¹-TV minimization by iterative multi-label steepest descent minimization of the convex dual problem. For Schlesinger's subgradient algorithm we proposed a novel step control heuristics that considerably enhances both speed and accuracy compared with standard step size strategies for subgradient methods. It is shown experimentally that our subgradient scheme achieves consistently better image registration than GC in terms of lower values both of the composite L¹-TV functional, and of its components, i.e., the L¹ distance of the images and the transformation smoothness TV, and yields visually acceptable results even in cases where the GC based algorithm fails. The new algorithm allows easy parallelization and can thus be

  20. A Novel Local Learning based Approach With Application to Breast Cancer Diagnosis

    SciTech Connect

    Xu, Songhua; Tourassi, Georgia

    2012-01-01

    The purpose of this study is to develop and evaluate a novel local learning-based approach for computer-assisted diagnosis of breast cancer. Our new local learning based algorithm using the linear logistic regression method as its base learner is described. Overall, our algorithm will perform its stochastic searching process until the total allowed computing time is used up by our random walk process in identifying the most suitable population subdivision scheme and their corresponding individual base learners. The proposed local learning-based approach was applied for the prediction of breast cancer given 11 mammographic and clinical findings reported by physicians using the BI-RADS lexicon. Our database consisted of 850 patients with biopsy confirmed diagnosis (290 malignant and 560 benign). We also compared the performance of our method with a collection of publicly available state-of-the-art machine learning methods. Predictive performance for all classifiers was evaluated using 10-fold cross validation and Receiver Operating Characteristics (ROC) analysis. Figure 1 reports the performance of 54 machine learning methods implemented in the machine learning toolkit Weka (version 3.0). We introduced a novel local learning-based classifier and compared it with an extensive list of other classifiers for the problem of breast cancer diagnosis. Our experiments show that the algorithm superior prediction performance outperforming a wide range of other well established machine learning techniques. Our conclusion complements the existing understanding in the machine learning field that local learning may capture complicated, non-linear relationships exhibited by real-world datasets.

  1. Quaternion-based unscented Kalman filter for accurate indoor heading estimation using wearable multi-sensor system.

    PubMed

    Yuan, Xuebing; Yu, Shuai; Zhang, Shengzhi; Wang, Guoping; Liu, Sheng

    2015-01-01

    Inertial navigation based on micro-electromechanical system (MEMS) inertial measurement units (IMUs) has attracted numerous researchers due to its high reliability and independence. The heading estimation, as one of the most important parts of inertial navigation, has been a research focus in this field. Heading estimation using magnetometers is perturbed by magnetic disturbances, such as indoor concrete structures and electronic equipment. The MEMS gyroscope is also used for heading estimation. However, the accuracy of gyroscope is unreliable with time. In this paper, a wearable multi-sensor system has been designed to obtain the high-accuracy indoor heading estimation, according to a quaternion-based unscented Kalman filter (UKF) algorithm. The proposed multi-sensor system including one three-axis accelerometer, three single-axis gyroscopes, one three-axis magnetometer and one microprocessor minimizes the size and cost. The wearable multi-sensor system was fixed on waist of pedestrian and the quadrotor unmanned aerial vehicle (UAV) for heading estimation experiments in our college building. The results show that the mean heading estimation errors are less 10° and 5° to multi-sensor system fixed on waist of pedestrian and the quadrotor UAV, respectively, compared to the reference path. PMID:25961384

  2. 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

  3. PETs: A Stable and Accurate Predictor of Protein-Protein Interacting Sites Based on Extremely-Randomized Trees.

    PubMed

    Xia, Bin; Zhang, Hong; Li, Qianmu; Li, Tao

    2015-12-01

    Protein-protein interaction (PPI) plays crucial roles in the performance of various biological processes. A variety of methods are dedicated to identify whether proteins have interaction residues, but it is often more crucial to recognize each amino acid. In practical applications, the stability of a prediction model is as important as its accuracy. However, random sampling, which is widely used in previous prediction models, often brings large difference between each training model. In this paper, a Predictor of protein-protein interaction sites based on Extremely-randomized Trees (PETs) is proposed to improve the prediction accuracy while maintaining the prediction stability. In PETs, a cluster-based sampling strategy is proposed to ensure the model stability: first, the training dataset is divided into subsets using specific features; second, the subsets are clustered using K-means; and finally the samples are selected from each cluster. Using the proposed sampling strategy, samples which have different types of significant features could be selected independently from different clusters. The evaluation shows that PETs is able to achieve better accuracy while maintaining a good stability. The source code and toolkit are available at https://github.com/BinXia/PETs.

  4. 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.

  5. Short-time matrix series based singular value decomposition for rolling bearing fault diagnosis

    NASA Astrophysics Data System (ADS)

    Cong, Feiyun; Chen, Jin; Dong, Guangming; Zhao, Fagang

    2013-01-01

    Rolling element bearing faults are among the main causes of rotating machines breakdown. It is important to distinguish the incipient fault before the bearings step into serious failure. Based on the traditional singular value decomposition (SVD) theory, short-time matrix series (STMS) and singular value ratio (SVR) are introduced to the vibration signal processing. The proposed signal processing method is called S-SVDR (STMS based SVD method using SVR) and it has been proved to have a good local identification capability in the rolling bearing fault diagnosis. The detailed description of applying S-SVDR methods to rolling bearing fault diagnosis is given through the artificial fault signal processing in experiment 1. In experiment 2, rolling element bearing accelerated life test is performed in Hangzhou Bearing Test & Research Center (HBRC). The experimental result shows that the incipient fault can be well detected through S-SVDR processing method. However, the envelope analysis of original signal cannot detect the fault due to the existence of signal interference. A conclusion can be made that the proposed S-SVDR method has a good effect on de-noising and eliminating the signal interference of rolling bearing for the fault diagnosis.

  6. Data-based hybrid tension estimation and fault diagnosis of cold rolling continuous annealing processes.

    PubMed

    Liu, Qiang; Chai, Tianyou; Wang, Hong; Qin, Si-Zhao Joe

    2011-12-01

    The continuous annealing process line (CAPL) of cold rolling is an important unit to improve the mechanical properties of steel strips in steel making. In continuous annealing processes, strip tension is an important factor, which indicates whether the line operates steadily. Abnormal tension profile distribution along the production line can lead to strip break and roll slippage. Therefore, it is essential to estimate the whole tension profile in order to prevent the occurrence of faults. However, in real annealing processes, only a limited number of strip tension sensors are installed along the machine direction. Since the effects of strip temperature, gas flow, bearing friction, strip inertia, and roll eccentricity can lead to nonlinear tension dynamics, it is difficult to apply the first-principles induced model to estimate the tension profile distribution. In this paper, a novel data-based hybrid tension estimation and fault diagnosis method is proposed to estimate the unmeasured tension between two neighboring rolls. The main model is established by an observer-based method using a limited number of measured tensions, speeds, and currents of each roll, where the tension error compensation model is designed by applying neural networks principal component regression. The corresponding tension fault diagnosis method is designed using the estimated tensions. Finally, the proposed tension estimation and fault diagnosis method was applied to a real CAPL in a steel-making company, demonstrating the effectiveness of the proposed method.

  7. Image-based computer-assisted diagnosis system for benign paroxysmal positional vertigo

    NASA Astrophysics Data System (ADS)

    Kohigashi, Satoru; Nakamae, Koji; Fujioka, Hiromu

    2005-04-01

    We develop the image based computer assisted diagnosis system for benign paroxysmal positional vertigo (BPPV) that consists of the balance control system simulator, the 3D eye movement simulator, and the extraction method of nystagmus response directly from an eye movement image sequence. In the system, the causes and conditions of BPPV are estimated by searching the database for record matching with the nystagmus response for the observed eye image sequence of the patient with BPPV. The database includes the nystagmus responses for simulated eye movement sequences. The eye movement velocity is obtained by using the balance control system simulator that allows us to simulate BPPV under various conditions such as canalithiasis, cupulolithiasis, number of otoconia, otoconium size, and so on. Then the eye movement image sequence is displayed on the CRT by the 3D eye movement simulator. The nystagmus responses are extracted from the image sequence by the proposed method and are stored in the database. In order to enhance the diagnosis accuracy, the nystagmus response for a newly simulated sequence is matched with that for the observed sequence. From the matched simulation conditions, the causes and conditions of BPPV are estimated. We apply our image based computer assisted diagnosis system to two real eye movement image sequences for patients with BPPV to show its validity.

  8. An Error Diagnosis Technique Based on Location Sets to Rectify Subcircuits

    NASA Astrophysics Data System (ADS)

    Shioki, Kosuke; Okada, Narumi; Ishihara, Toshiro; Hirose, Tetsuya; Kuroki, Nobutaka; Numa, Masahiro

    This paper presents an error diagnosis technique for incremental synthesis, called EXLLS (Extended X-algorithm for LUT-based circuit model based on Location sets to rectify Subcircuits), which rectifies five or more functional errors in the whole circuit based on location sets to rectify subcircuits. Conventional error diagnosis technique, called EXLIT, tries to rectify five or more functional errors based on incremental rectification for subcircuits. However, the solution depends on the selection and the order of modifications on subcircuits, which increases the number of locations to be changed. To overcome this problem, we propose EXLLS based on location sets to rectify subcircuits, which obtains two or more solutions by separating i) extraction of location sets to be rectified, and ii) rectification for the whole circuit based on the location sets. Thereby EXLLS can rectify five or more errors with fewer locations to change. Experimental results have shown that EXLLS reduces increase in the number of locations to be rectified with conventional technique by 90.1%.

  9. Remote Fault Information Acquisition and Diagnosis System of the Combine Harvester Based on LabVIEW

    NASA Astrophysics Data System (ADS)

    Chen, Jin; Wu, Pei; Xu, Kai

    Most combine harvesters have not be equipped with online fault diagnosis system. A fault information acquisition and diagnosis system of the Combine Harvester based on LabVIEW is designed, researched and developed. Using ARM development board, by collecting many sensors' signals, this system can achieve real-time measurement, collection, displaying and analysis of different parts of combine harvesters. It can also realize detection online of forward velocity, roller speed, engine temperature, etc. Meanwhile the system can judge the fault location. A new database function is added so that we can search the remedial measures to solve the faults and also we can add new faults to the database. So it is easy to take precautions against before the combine harvester breaking down then take measures to service the harvester.

  10. Livingstone Model-Based Diagnosis of Earth Observing One Infusion Experiment

    NASA Technical Reports Server (NTRS)

    Hayden, Sandra C.; Sweet, Adam J.; Christa, Scott E.

    2004-01-01

    The Earth Observing One satellite, launched in November 2000, is an active earth science observation platform. This paper reports on the progress of an infusion experiment in which the Livingstone 2 Model-Based Diagnostic engine is deployed on Earth Observing One, demonstrating the capability to monitor the nominal operation of the spacecraft under command of an on-board planner, and demonstrating on-board diagnosis of spacecraft failures. Design and development of the experiment, specification and validation of diagnostic scenarios, characterization of performance results and benefits of the model- based approach are presented.

  11. FastME 2.0: A Comprehensive, Accurate, and Fast Distance-Based Phylogeny Inference Program.

    PubMed

    Lefort, Vincent; Desper, Richard; Gascuel, Olivier

    2015-10-01

    FastME provides distance algorithms to infer phylogenies. FastME is based on balanced minimum evolution, which is the very principle of Neighbor Joining (NJ). FastME improves over NJ by performing topological moves using fast, sophisticated algorithms. The first version of FastME only included Nearest Neighbor Interchange. The new 2.0 version also includes Subtree Pruning and Regrafting, while remaining as fast as NJ and providing a number of facilities: Distance estimation for DNA and proteins with various models and options, bootstrapping, and parallel computations. FastME is available using several interfaces: Command-line (to be integrated in pipelines), PHYLIP-like, and a Web server (http://www.atgc-montpellier.fr/fastme/).

  12. FastME 2.0: A Comprehensive, Accurate, and Fast Distance-Based Phylogeny Inference Program

    PubMed Central

    Lefort, Vincent; Desper, Richard; Gascuel, Olivier

    2015-01-01

    FastME provides distance algorithms to infer phylogenies. FastME is based on balanced minimum evolution, which is the very principle of Neighbor Joining (NJ). FastME improves over NJ by performing topological moves using fast, sophisticated algorithms. The first version of FastME only included Nearest Neighbor Interchange. The new 2.0 version also includes Subtree Pruning and Regrafting, while remaining as fast as NJ and providing a number of facilities: Distance estimation for DNA and proteins with various models and options, bootstrapping, and parallel computations. FastME is available using several interfaces: Command-line (to be integrated in pipelines), PHYLIP-like, and a Web server (http://www.atgc-montpellier.fr/fastme/). PMID:26130081

  13. 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

    2013-04-01

    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.

  14. FastME 2.0: A Comprehensive, Accurate, and Fast Distance-Based Phylogeny Inference Program.

    PubMed

    Lefort, Vincent; Desper, Richard; Gascuel, Olivier

    2015-10-01

    FastME provides distance algorithms to infer phylogenies. FastME is based on balanced minimum evolution, which is the very principle of Neighbor Joining (NJ). FastME improves over NJ by performing topological moves using fast, sophisticated algorithms. The first version of FastME only included Nearest Neighbor Interchange. The new 2.0 version also includes Subtree Pruning and Regrafting, while remaining as fast as NJ and providing a number of facilities: Distance estimation for DNA and proteins with various models and options, bootstrapping, and parallel computations. FastME is available using several interfaces: Command-line (to be integrated in pipelines), PHYLIP-like, and a Web server (http://www.atgc-montpellier.fr/fastme/). PMID:26130081

  15. [Application of optimized parameters SVM based on photoacoustic spectroscopy method in fault diagnosis of power transformer].

    PubMed

    Zhang, Yu-xin; Cheng, Zhi-feng; Xu, Zheng-ping; Bai, Jing

    2015-01-01

    In order to solve the problems such as complex operation, consumption for the carrier gas and long test period in traditional power transformer fault diagnosis approach based on dissolved gas analysis (DGA), this paper proposes a new method which is detecting 5 types of characteristic gas content in transformer oil such as CH4, C2H2, C2H4, C2H6 and H2 based on photoacoustic Spectroscopy and C2H2/C2H4, CH4/H2, C2H4/C2H6 three-ratios data are calculated. The support vector machine model was constructed using cross validation method under five support vector machine functions and four kernel functions, heuristic algorithms were used in parameter optimization for penalty factor c and g, which to establish the best SVM model for the highest fault diagnosis accuracy and the fast computing speed. Particles swarm optimization and genetic algorithm two types of heuristic algorithms were comparative studied in this paper for accuracy and speed in optimization. The simulation result shows that SVM model composed of C-SVC, RBF kernel functions and genetic algorithm obtain 97. 5% accuracy in test sample set and 98. 333 3% accuracy in train sample set, and genetic algorithm was about two times faster than particles swarm optimization in computing speed. The methods described in this paper has many advantages such as simple operation, non-contact measurement, no consumption for the carrier gas, long test period, high stability and sensitivity, the result shows that the methods described in this paper can instead of the traditional transformer fault diagnosis by gas chromatography and meets the actual project needs in transformer fault diagnosis.

  16. An accurate projector gamma correction method for phase-measuring profilometry based on direct optical power detection

    NASA Astrophysics Data System (ADS)

    Liu, Miao; Yin, Shibin; Yang, Shourui; Zhang, Zonghua

    2015-10-01

    Digital projector is frequently applied to generate fringe pattern in phase calculation-based three dimensional (3D) imaging systems. Digital projector often works with camera in this kind of systems so the intensity response of a projector should be linear in order to ensure the measurement precision especially in Phase-Measuring Profilometry (PMP). Some correction methods are often applied to cope with the non-linear intensity response of the digital projector. These methods usually rely on camera and gamma function is often applied to compensate the non-linear response so the correction performance is restricted by the dynamic range of camera. In addition, the gamma function is not suitable to compensate the nonmonotonicity intensity response. This paper propose a gamma correction method by the precisely detecting the optical energy instead of using a plate and camera. A photodiode with high dynamic range and linear response is used to directly capture the light optical from the digital projector. After obtaining the real gamma curve precisely by photodiode, a gray level look-up table (LUT) is generated to correct the image to be projected. Finally, this proposed method is verified experimentally.

  17. 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.

  18. 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.

  19. How accurate are interpretations of curriculum-based measurement progress monitoring data? Visual analysis versus decision rules.

    PubMed

    Van Norman, Ethan R; Christ, Theodore J

    2016-10-01

    Curriculum based measurement of oral reading (CBM-R) is used to monitor the effects of academic interventions for individual students. Decisions to continue, modify, or terminate these interventions are made by interpreting time series CBM-R data. Such interpretation is founded upon visual analysis or the application of decision rules. The purpose of this study was to compare the accuracy of visual analysis and decision rules. Visual analysts interpreted 108 CBM-R progress monitoring graphs one of three ways: (a) without graphic aids, (b) with a goal line, or (c) with a goal line and a trend line. Graphs differed along three dimensions, including trend magnitude, variability of observations, and duration of data collection. Automated trend line and data point decision rules were also applied to each graph. Inferential analyses permitted the estimation of the probability of a correct decision (i.e., the student is improving - continue the intervention, or the student is not improving - discontinue the intervention) for each evaluation method as a function of trend magnitude, variability of observations, and duration of data collection. All evaluation methods performed better when students made adequate progress. Visual analysis and decision rules performed similarly when observations were less variable. Results suggest that educators should collect data for more than six weeks, take steps to control measurement error, and visually analyze graphs when data are variable. Implications for practice and research are discussed. PMID:27586069

  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. 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.

  2. An accurate method for energy spectrum reconstruction of Linac beams based on EPID measurements of scatter radiation

    NASA Astrophysics Data System (ADS)

    Juste, B.; Miró, R.; Verdú, G.; Santos, A.

    2014-06-01

    This work presents a methodology to reconstruct a Linac high energy photon spectrum beam. The method is based on EPID scatter images generated when the incident photon beam impinges onto a plastic block. The distribution of scatter radiation produced by this scattering object placed on the external EPID surface and centered at the beam field size was measured. The scatter distribution was also simulated for a series of monoenergetic identical geometry photon beams. Monte Carlo simulations were used to predict the scattered photons for monoenergetic photon beams at 92 different locations, with 0.5 cm increments and at 8.5 cm from the centre of the scattering material. Measurements were performed with the same geometry using a 6 MeV photon beam produced by the linear accelerator. A system of linear equations was generated to combine the polyenergetic EPID measurements with the monoenergetic simulation results. Regularization techniques were applied to solve the system for the incident photon spectrum. A linear matrix system, A×S=E, was developed to describe the scattering interactions and their relationship to the primary spectrum (S). A is the monoenergetic scatter matrix determined from the Monte Carlo simulations, S is the incident photon spectrum, and E represents the scatter distribution characterized by EPID measurement. Direct matrix inversion methods produce results that are not physically consistent due to errors inherent in the system, therefore Tikhonov regularization methods were applied to address the effects of these errors and to solve the system for obtaining a consistent bremsstrahlung spectrum.

  3. How accurate are interpretations of curriculum-based measurement progress monitoring data? Visual analysis versus decision rules.

    PubMed

    Van Norman, Ethan R; Christ, Theodore J

    2016-10-01

    Curriculum based measurement of oral reading (CBM-R) is used to monitor the effects of academic interventions for individual students. Decisions to continue, modify, or terminate these interventions are made by interpreting time series CBM-R data. Such interpretation is founded upon visual analysis or the application of decision rules. The purpose of this study was to compare the accuracy of visual analysis and decision rules. Visual analysts interpreted 108 CBM-R progress monitoring graphs one of three ways: (a) without graphic aids, (b) with a goal line, or (c) with a goal line and a trend line. Graphs differed along three dimensions, including trend magnitude, variability of observations, and duration of data collection. Automated trend line and data point decision rules were also applied to each graph. Inferential analyses permitted the estimation of the probability of a correct decision (i.e., the student is improving - continue the intervention, or the student is not improving - discontinue the intervention) for each evaluation method as a function of trend magnitude, variability of observations, and duration of data collection. All evaluation methods performed better when students made adequate progress. Visual analysis and decision rules performed similarly when observations were less variable. Results suggest that educators should collect data for more than six weeks, take steps to control measurement error, and visually analyze graphs when data are variable. Implications for practice and research are discussed.

  4. 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. PMID:23902112

  5. A two-parameter kinetic model based on a time-dependent activity coefficient accurately describes enzymatic cellulose digestion

    PubMed Central

    Kostylev, Maxim; Wilson, David

    2014-01-01

    Lignocellulosic biomass is a potential source of renewable, low-carbon-footprint liquid fuels. Biomass recalcitrance and enzyme cost are key challenges associated with the large-scale production of cellulosic fuel. Kinetic modeling of enzymatic cellulose digestion has been complicated by the heterogeneous nature of the substrate and by the fact that a true steady state cannot be attained. We present a two-parameter kinetic model based on the Michaelis-Menten scheme (Michaelis L and Menten ML. (1913) Biochem Z 49:333–369), but with a time-dependent activity coefficient analogous to fractal-like kinetics formulated by Kopelman (Kopelman R. (1988) Science 241:1620–1626). We provide a mathematical derivation and experimental support to show that one of the parameters is a total activity coefficient and the other is an intrinsic constant that reflects the ability of the cellulases to overcome substrate recalcitrance. The model is applicable to individual cellulases and their mixtures at low-to-medium enzyme loads. Using biomass degrading enzymes from a cellulolytic bacterium Thermobifida fusca we show that the model can be used for mechanistic studies of enzymatic cellulose digestion. We also demonstrate that it applies to the crude supernatant of the widely studied cellulolytic fungus Trichoderma reesei and can thus be used to compare cellulases from different organisms. The two parameters may serve a similar role to Vmax, KM, and kcat in classical kinetics. A similar approach may be applicable to other enzymes with heterogeneous substrates and where a steady state is not achievable. PMID:23837567

  6. 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.

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

    PubMed Central

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

    2015-01-01

    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. PMID:26078362

  8. A hybrid feature-based segmentation and classification system for the computer aided self-diagnosis of otitis media.

    PubMed

    Shie, Chuen-Kai; Chang, Hao-Ting; Fan, Fu-Cheng; Chen, Chung-Jung; Fang, Te-Yung; Wang, Pa-Chun

    2014-01-01

    We propose a novel hybrid otitis media (OM) computer aided detection (CAD) system, designed to aid in the self-diagnosis of various forms of OM. OM is a prevalent disease in both children and adults. Our system is able to differentiate normal ear from acute otitis media (AOM), otitis media with effusion (OME) and the multi-categories of chronic otitis media including perforation, retraction, cholesteatoma, etc. We propose a modified double active contour segmentation method designed for use with otoscope images, and enabled to handle user acquired data. To describe the visual symptoms (e.g., red, bulging, effusion, perforation, retraction, etc.) of otitis media accurately, we extract color, geometric and texture features by grid color moment, Gabor filter, local binary pattern and histogram of oriented gradients. A powerful classification structure based on Adaboost is used to select the most useful features and build a strong classifier. Our system achieves classification accuracy as high as 88.06% and is suitable for real use. In addition, some interesting observations about OM otoscope images are also discussed.

  9. A feasibility study for measuring accurate tendon displacements using an audio-based Fourier analysis of pulsed-wave Doppler ultrasound signals.

    PubMed

    Stegman, K J; Podhorodeski, R P; Park, E J

    2009-01-01

    The accuracy of Pulsed-Wave Doppler Ultrasound displacement measurements of a slow moving "tendon-like" string was investigated in this study. This was accomplished by estimating string displacements using an audio-based Fourier analysis of a Pulsed-Wave Doppler signal from a commercial ultrasound scanner. Our feasibility study showed that the proposed technique is much more accurate at estimating the actual string displacement in comparison to the scanner's onboard software. Furthermore, this study also shows that a real-time Doppler data acquisition from an ultrasound scanner is possible for the ultimate purpose of real-time biological tendon displacement monitoring.

  10. Are skinfold-based models accurate and suitable for assessing changes in body composition in highly trained athletes?

    PubMed

    Silva, Analiza M; Fields, David A; Quitério, Ana L; Sardinha, Luís B

    2009-09-01

    This study was designed to assess the usefulness of skinfold (SKF) equations developed by Jackson and Pollock (JP) and by Evans (Ev) in tracking body composition changes (relative fat mass [%FM], absolute fat mass [FM], and fat-free mass [FFM]) of elite male judo athletes before a competition using a 4-compartment (4C) model as the reference method. A total of 18 male, top-level (age: 22.6 +/- 2.9 yr) athletes were evaluated at baseline (weight: 73.4 +/- 7.9 kg; %FM4C: 7.0 +/- 3.3%; FM4C: 5.1 +/- 2.6 kg; and FFM4C: 68.3 +/- 7.3 kg) and before a competition (weight: 72.7 +/- 7.5 kg; %FM4C: 6.5 +/- 3.4%; FM4C: 4.8 +/- 2.6 kg; and FFM4C: 67.9 +/- 7.1 kg). Measures of body density assessed by air displacement plethysmography, bone mineral content by dual energy X-ray absorptiometry, and total-body water by bioelectrical impedance spectroscopy were used to estimate 4C model %FM, FM, and FFM. Seven SKF site models using both JP and Ev were used to estimate %FM, FM, and FFM along with the simplified Ev3SKF site. Changes in %FM, FM, and FFM were not significantly different from the 4C model. The regression model for the SKF in question and the reference method did not differ from the line of identity in estimating changes in %FM, FM, and FFM. The limits of agreement were similar, ranging from -3.4 to 3.6 for %FM, -2.7 to 2.5 kg for FM, and -2.5 to 2.7 kg for FFM. Considering the similar performance of both 7SKF- and 3SKF-based equations compared with the criterion method, these data indicate that either the 7- or 3-site SFK models are not valid to detect %FM, FM, and FFM changes of highly trained athletes. These results highlighted the inaccuracy of anthropometric models in tracking desired changes in body composition of elite male judo athletes before a competition.

  11. A decision tree – based method for the differential diagnosis of Aortic Stenosis from Mitral Regurgitation using heart sounds

    PubMed Central

    Pavlopoulos, Sotiris A; Stasis, Antonis CH; Loukis, Euripides N

    2004-01-01

    Background New technologies like echocardiography, color Doppler, CT, and MRI provide more direct and accurate evidence of heart disease than heart auscultation. However, these modalities are costly, large in size and operationally complex and therefore are not suitable for use in rural areas, in homecare and generally in primary healthcare set-ups. Furthermore the majority of internal medicine and cardiology training programs underestimate the value of cardiac auscultation and junior clinicians are not adequately trained in this field. Therefore efficient decision support systems would be very useful for supporting clinicians to make better heart sound diagnosis. In this study a rule-based method, based on decision trees, has been developed for differential diagnosis between "clear" Aortic Stenosis (AS) and "clear" Mitral Regurgitation (MR) using heart sounds. Methods For the purposes of our experiment we used a collection of 84 heart sound signals including 41 heart sound signals with "clear" AS systolic murmur and 43 with "clear" MR systolic murmur. Signals were initially preprocessed to detect 1st and 2nd heart sounds. Next a total of 100 features were determined for every heart sound signal and relevance to the differentiation between AS and MR was estimated. The performance of fully expanded decision tree classifiers and Pruned decision tree classifiers were studied based on various training and test datasets. Similarly, pruned decision tree classifiers were used to examine their differentiation capabilities. In order to build a generalized decision support system for heart sound diagnosis, we have divided the problem into sub problems, dealing with either one morphological characteristic of the heart-sound waveform or with difficult to distinguish cases. Results Relevance analysis on the different heart sound features demonstrated that the most relevant features are the frequency features and the morphological features that describe S1, S2 and the systolic

  12. Fault Tree Based Diagnosis with Optimal Test Sequencing for Field Service Engineers

    NASA Technical Reports Server (NTRS)

    Iverson, David L.; George, Laurence L.; Patterson-Hine, F. A.; Lum, Henry, Jr. (Technical Monitor)

    1994-01-01

    When field service engineers go to customer sites to service equipment, they want to diagnose and repair failures quickly and cost effectively. Symptoms exhibited by failed equipment frequently suggest several possible causes which require different approaches to diagnosis. This can lead the engineer to follow several fruitless paths in the diagnostic process before they find the actual failure. To assist in this situation, we have developed the Fault Tree Diagnosis and Optimal Test Sequence (FTDOTS) software system that performs automated diagnosis and ranks diagnostic hypotheses based on failure probability and the time or cost required to isolate and repair each failure. FTDOTS first finds a set of possible failures that explain exhibited symptoms by using a fault tree reliability model as a diagnostic knowledge to rank the hypothesized failures based on how likely they are and how long it would take or how much it would cost to isolate and repair them. This ordering suggests an optimal sequence for the field service engineer to investigate the hypothesized failures in order to minimize the time or cost required to accomplish the repair task. Previously, field service personnel would arrive at the customer site and choose which components to investigate based on past experience and service manuals. Using FTDOTS running on a portable computer, they can now enter a set of symptoms and get a list of possible failures ordered in an optimal test sequence to help them in their decisions. If facilities are available, the field engineer can connect the portable computer to the malfunctioning device for automated data gathering. FTDOTS is currently being applied to field service of medical test equipment. The techniques are flexible enough to use for many different types of devices. If a fault tree model of the equipment and information about component failure probabilities and isolation times or costs are available, a diagnostic knowledge base for that device can be

  13. [Multi-diagnosis space models of As stress in rice based on hyperspectral indices].

    PubMed

    Cao, Shi; Liu, Xiang-Nan; Liu, Mu-Xia

    2010-10-01

    High arsenic content in rice can influence the chlorophyll, water content and structure in their leaves, reduce the rate of photosynthesis and change their spectral features. Multiple models for diagnosing As contamination in rice based on spectral parameters were studied. Sixty samples belonging to mature rice in three different areas were scanned by ASD field pro3 for optical data. Arsenic reference values were obtained by atomic absorption spectrometry. First, correlation analysis was used between 9 hyperspectral indices and As content in rice, and three indices (PSNDa, fWBI, SIPI) were extracted to diagnose As contamination in rice, which were respectively sensitive to chlorophyll, water content and structure of leaves, then took the three indices to form a diagnosis spectral indices space (PSNDa-fWBI, PSNDa-SIPI, fWBI-SIPI) of As stress in rice. Second, principal component analysis and independent component analysis were also applied in these 9 hyperspectral indices, and two principal components (F1, F2) and two independent components(ICA1, ICA2) were extracted. These four components (F1, F2, ICA1, ICA2) were all correlated with As content in rice, and composed another two diagnosis spaces (F1-F2, ICA1-ICA2) for predicting As contamination. And these spaces composed a multiple diagnosis space model which diagnosed As contamination in rice of test area from different level, and showed a good result. PMID:21229762

  14. Socio-cultural and Knowledge-Based Barriers to Tuberculosis Diagnosis for Women in Bhopal, India

    PubMed Central

    McArthur, Evonne; Bali, Surya; Khan, Azim A.

    2016-01-01

    Background: In India, only one woman is diagnosed with tuberculosis (TB) for every 2.4 men. Previous studies have indicated gender disparities in care-seeking behavior and TB diagnosis; however, little is known about the specific barriers women face. Objectives: This study aimed to characterize socio-cultural and knowledge-based barriers that affected TB diagnosis for women in Bhopal, India. Materials and Methods: In-depth interviews were conducted with 13 affected women and 6 health-care workers. The Bhopal Diagnostic Microscopy Laboratory Register (n = 121) and the Bhopal district report (n = 261) were examined for diagnostic and care-seeking trends. Results: Women, especially younger women, faced socio-cultural barriers and stigma, causing many to hide their symptoms. Older women had little awareness about TB. Women often sought treatment from private practitioners, resulting in delayed diagnosis. Conclusions: Understanding these diagnostic and help-seeking behaviors barriers for women is critical for development of a gender-sensitive TB control program. PMID:26917876

  15. A Bayesian least squares support vector machines based framework for fault diagnosis and failure prognosis

    NASA Astrophysics Data System (ADS)

    Khawaja, Taimoor Saleem

    A high-belief low-overhead Prognostics and Health Management (PHM) system is desired for online real-time monitoring of complex non-linear systems operating in a complex (possibly non-Gaussian) noise environment. This thesis presents a Bayesian Least Squares Support Vector Machine (LS-SVM) based framework for fault diagnosis and failure prognosis in nonlinear non-Gaussian systems. The methodology assumes the availability of real-time process measurements, definition of a set of fault indicators and the existence of empirical knowledge (or historical data) to characterize both nominal and abnormal operating conditions. An efficient yet powerful Least Squares Support Vector Machine (LS-SVM) algorithm, set within a Bayesian Inference framework, not only allows for the development of real-time algorithms for diagnosis and prognosis but also provides a solid theoretical framework to address key concepts related to classification for diagnosis and regression modeling for prognosis. SVM machines are founded on the principle of Structural Risk Minimization (SRM) which tends to find a good trade-off between low empirical risk and small capacity. The key features in SVM are the use of non-linear kernels, the absence of local minima, the sparseness of the solution and the capacity control obtained by optimizing the margin. The Bayesian Inference framework linked with LS-SVMs allows a probabilistic interpretation of the results for diagnosis and prognosis. Additional levels of inference provide the much coveted features of adaptability and tunability of the modeling parameters. The two main modules considered in this research are fault diagnosis and failure prognosis. With the goal of designing an efficient and reliable fault diagnosis scheme, a novel Anomaly Detector is suggested based on the LS-SVM machines. The proposed scheme uses only baseline data to construct a 1-class LS-SVM machine which, when presented with online data is able to distinguish between normal behavior

  16. Computer-Based Image Analysis for Plus Disease Diagnosis in Retinopathy of Prematurity: Performance of the “i-ROP” System and Image Features Associated With Expert Diagnosis

    PubMed Central

    Ataer-Cansizoglu, Esra; Bolon-Canedo, Veronica; Campbell, J. Peter; Bozkurt, Alican; Erdogmus, Deniz; Kalpathy-Cramer, Jayashree; Patel, Samir; Jonas, Karyn; Chan, R. V. Paul; Ostmo, Susan; Chiang, Michael F.

    2015-01-01

    Purpose We developed and evaluated the performance of a novel computer-based image analysis system for grading plus disease in retinopathy of prematurity (ROP), and identified the image features, shapes, and sizes that best correlate with expert diagnosis. Methods A dataset of 77 wide-angle retinal images from infants screened for ROP was collected. A reference standard diagnosis was determined for each image by combining image grading from 3 experts with the clinical diagnosis from ophthalmoscopic examination. Manually segmented images were cropped into a range of shapes and sizes, and a computer algorithm was developed to extract tortuosity and dilation features from arteries and veins. Each feature was fed into our system to identify the set of characteristics that yielded the highest-performing system compared to the reference standard, which we refer to as the “i-ROP” system. Results Among the tested crop shapes, sizes, and measured features, point-based measurements of arterial and venous tortuosity (combined), and a large circular cropped image (with radius 6 times the disc diameter), provided the highest diagnostic accuracy. The i-ROP system achieved 95% accuracy for classifying preplus and plus disease compared to the reference standard. This was comparable to the performance of the 3 individual experts (96%, 94%, 92%), and significantly higher than the mean performance of 31 nonexperts (81%). Conclusions This comprehensive analysis of computer-based plus disease suggests that it may be feasible to develop a fully-automated system based on wide-angle retinal images that performs comparably to expert graders at three-level plus disease discrimination. Translational Relevance Computer-based image analysis, using objective and quantitative retinal vascular features, has potential to complement clinical ROP diagnosis by ophthalmologists. PMID:26644965

  17. Computer aided diagnosis based on medical image processing and artificial intelligence methods

    NASA Astrophysics Data System (ADS)

    Stoitsis, John; Valavanis, Ioannis; Mougiakakou, Stavroula G.; Golemati, Spyretta; Nikita, Alexandra; Nikita, Konstantina S.

    2006-12-01

    Advances in imaging technology and computer science have greatly enhanced interpretation of medical images, and contributed to early diagnosis. The typical architecture of a Computer Aided Diagnosis (CAD) system includes image pre-processing, definition of region(s) of interest, features extraction and selection, and classification. In this paper, the principles of CAD systems design and development are demonstrated by means of two examples. The first one focuses on the differentiation between symptomatic and asymptomatic carotid atheromatous plaques. For each plaque, a vector of texture and motion features was estimated, which was then reduced to the most robust ones by means of ANalysis of VAriance (ANOVA). Using fuzzy c-means, the features were then clustered into two classes. Clustering performances of 74%, 79%, and 84% were achieved for texture only, motion only, and combinations of texture and motion features, respectively. The second CAD system presented in this paper supports the diagnosis of focal liver lesions and is able to characterize liver tissue from Computed Tomography (CT) images as normal, hepatic cyst, hemangioma, and hepatocellular carcinoma. Five texture feature sets were extracted for each lesion, while a genetic algorithm based feature selection method was applied to identify the most robust features. The selected feature set was fed into an ensemble of neural network classifiers. The achieved classification performance was 100%, 93.75% and 90.63% in the training, validation and testing set, respectively. It is concluded that computerized analysis of medical images in combination with artificial intelligence can be used in clinical practice and may contribute to more efficient diagnosis.

  18. Computer-aided diagnosis of peripheral soft tissue masses based on ultrasound imaging.

    PubMed

    Chiou, Hong-Jen; Chen, Chih-Yen; Liu, Tzu-Chiang; Chiou, See-Ying; Wang, Hsin-Kai; Chou, Yi-Hong; Chiang, Huihua Kenny

    2009-07-01

    Medical ultrasound (US) has been widely used for distinguishing benign from malignant peripheral soft tissue tumors. However, diagnosis by US is subjective and depends on the experience of the radiologists. The rarity of peripheral soft tissue tumors can make them easily neglected and this frequently leads to delayed diagnosis, which results in a much higher death rate than with other tumors. In this paper, we developed a computer-aided diagnosis (CAD) system to diagnose peripheral soft tissue masses on US images. We retrospectively evaluated 49 cases of pathologically proven peripheral soft tissue masses (32 benign, 17 malignant). The proposed CAD system includes three main procedures: image pre-processing and region-of-interest (ROI) segmentation, feature extraction and statistics-based discriminant analysis (DA). We developed a depth-normalization factor (DNF) to compensate for the influence of the depth setting on the apparent size of the ROI. After image pre-processing and normalization, five features, namely area (A), boundary transition ratio (T), circularity (C), high intensity spots (H) and uniformity (U), were extracted from the US images. A DA function was then employed to analyze these features. A CAD algorithm was then devised for differentiating benign from malignant masses. The CAD system achieved an accuracy of 87.8%, a sensitivity of 88.2%, a specificity of 87.5%, a positive predictive value (PPV) 78.9% and a negative predictive value (NPV) 93.3%. These results indicate that the CAD system is valuable as a means of providing a second diagnostic opinion when radiologists carry out peripheral soft tissue mass diagnosis.

  19. A java-based application for differential diagnosis of hematopoietic neoplasms using immunophenotyping by flow cytometry.

    PubMed

    Nguyen, A N; Milam, J D; Johnson, K A; Banez, E I

    2000-07-01

    We describe the implementation of a Java-based application for differential diagnosis of hematopoietic neoplasms using immunophenotyping by flow cytometry. The current version of this Java applet includes the knowledge-base for 33 hematopoietic neoplasms and 43 diagnostic immunophenotyping markers. Java, a new object-oriented computing language, helps facilitate development of this applet, a platform-independent module that can be implemented on the World Wide Web. As the Web rapidly becomes more accessible to users around the world, Web-based software may eventually form the core of decision-support systems in clinical settings. Java-based applications, such as the one described in this paper, are expected to contribute significantly in this area.

  20. Computer-aided diagnosis of breast microcalcifications based on dual-tree complex wavelet transform

    PubMed Central

    2012-01-01

    Background Digital mammography is the most reliable imaging modality for breast carcinoma diagnosis and breast micro-calcifications is regarded as one of the most important signs on imaging diagnosis. In this paper, a computer-aided diagnosis (CAD) system is presented for breast micro-calcifications based on dual-tree complex wavelet transform (DT-CWT) to facilitate radiologists like double reading. Methods Firstly, 25 abnormal ROIs were extracted according to the center and diameter of the lesions manually and 25 normal ROIs were selected randomly. Then micro-calcifications were segmented by combining space and frequency domain techniques. We extracted three texture features based on wavelet (Haar, DB4, DT-CWT) transform. Totally 14 descriptors were introduced to define the characteristics of the suspicious micro-calcifications. Principal Component Analysis (PCA) was used to transform these descriptors to a compact and efficient vector expression. Support Vector Machine (SVM) classifier was used to classify potential micro-calcifications. Finally, we used the receiver operating characteristic (ROC) curve and free-response operating characteristic (FROC) curve to evaluate the performance of the CAD system. Results The results of SVM classifications based on different wavelets shows DT-CWT has a better performance. Compared with other results, DT-CWT method achieved an accuracy of 96% and 100% for the classification of normal and abnormal ROIs, and the classification of benign and malignant micro-calcifications respectively. In FROC analysis, our CAD system for clinical dataset detection achieved a sensitivity of 83.5% at a false positive per image of 1.85. Conclusions Compared with general wavelets, DT-CWT could describe the features more effectively, and our CAD system had a competitive performance. PMID:23253202

  1. Shorter sampling periods and accurate estimates of milk volume and components are possible for pasture based dairy herds milked with automated milking systems.

    PubMed

    Kamphuis, Claudia; Burke, Jennie K; Taukiri, Sarah; Petch, Susan-Fay; Turner, Sally-Anne

    2016-08-01

    Dairy cows grazing pasture and milked using automated milking systems (AMS) have lower milking frequencies than indoor fed cows milked using AMS. Therefore, milk recording intervals used for herd testing indoor fed cows may not be suitable for cows on pasture based farms. We hypothesised that accurate standardised 24 h estimates could be determined for AMS herds with milk recording intervals of less than the Gold Standard (48 hs), but that the optimum milk recording interval would depend on the herd average for milking frequency. The Gold Standard protocol was applied on five commercial dairy farms with AMS, between December 2011 and February 2013. From 12 milk recording test periods, involving 2211 cow-test days and 8049 cow milkings, standardised 24 h estimates for milk volume and milk composition were calculated for the Gold Standard protocol and compared with those collected during nine alternative sampling scenarios, including six shorter sampling periods and three in which a fixed number of milk samples per cow were collected. Results infer a 48 h milk recording protocol is unnecessarily long for collecting accurate estimates during milk recording on pasture based AMS farms. Collection of two milk samples only per cow was optimal in terms of high concordance correlation coefficients for milk volume and components and a low proportion of missed cow-test days. Further research is required to determine the effects of diurnal variations in milk composition on standardised 24 h estimates for milk volume and components, before a protocol based on a fixed number of samples could be considered. Based on the results of this study New Zealand have adopted a split protocol for herd testing based on the average milking frequency for the herd (NZ Herd Test Standard 8100:2015). PMID:27600967

  2. Diagnosis of disc herniation based on classifiers and features generated from spine MR images

    NASA Astrophysics Data System (ADS)

    Koh, Jaehan; Chaudhary, Vipin; Dhillon, Gurmeet

    2010-03-01

    In recent years the demand for an automated method for diagnosis of disc abnormalities has grown as more patients suffer from lumbar disorders and radiologists have to treat more patients reliably in a limited amount of time. In this paper, we propose and compare several classifiers that diagnose disc herniation, one of the common problems of the lumbar spine, based on lumbar MR images. Experimental results on a limited data set of 68 clinical cases with 340 lumbar discs show that our classifiers can diagnose disc herniation with 97% accuracy.

  3. Fault diagnosis in spur gears based on genetic algorithm and random forest

    NASA Astrophysics Data System (ADS)

    Cerrada, Mariela; Zurita, Grover; Cabrera, Diego; Sánchez, René-Vinicio; Artés, Mariano; Li, Chuan

    2016-03-01

    There are growing demands for condition-based monitoring of gearboxes, and therefore new methods to improve the reliability, effectiveness, accuracy of the gear fault detection ought to be evaluated. Feature selection is still an important aspect in machine learning-based diagnosis in order to reach good performance of the diagnostic models. On the other hand, random forest classifiers are suitable models in industrial environments where large data-samples are not usually available for training such diagnostic models. The main aim of this research is to build up a robust system for the multi-class fault diagnosis in spur gears, by selecting the best set of condition parameters on time, frequency and time-frequency domains, which are extracted from vibration signals. The diagnostic system is performed by using genetic algorithms and a classifier based on random forest, in a supervised environment. The original set of condition parameters is reduced around 66% regarding the initial size by using genetic algorithms, and still get an acceptable classification precision over 97%. The approach is tested on real vibration signals by considering several fault classes, one of them being an incipient fault, under different running conditions of load and velocity.

  4. Model-Based Diagnosis and Prognosis of a Water Recycling System

    NASA Technical Reports Server (NTRS)

    Roychoudhury, Indranil; Hafiychuk, Vasyl; Goebel, Kai Frank

    2013-01-01

    A water recycling system (WRS) deployed at NASA Ames Research Center s Sustainability Base (an energy efficient office building that integrates some novel technologies developed for space applications) will serve as a testbed for long duration testing of next generation spacecraft water recycling systems for future human spaceflight missions. This system cleans graywater (waste water collected from sinks and showers) and recycles it into clean water. Like all engineered systems, the WRS is prone to standard degradation due to regular use, as well as other faults. Diagnostic and prognostic applications will be deployed on the WRS to ensure its safe, efficient, and correct operation. The diagnostic and prognostic results can be used to enable condition-based maintenance to avoid unplanned outages, and perhaps extend the useful life of the WRS. Diagnosis involves detecting when a fault occurs, isolating the root cause of the fault, and identifying the extent of damage. Prognosis involves predicting when the system will reach its end of life irrespective of whether an abnormal condition is present or not. In this paper, first, we develop a physics model of both nominal and faulty system behavior of the WRS. Then, we apply an integrated model-based diagnosis and prognosis framework to the simulation model of the WRS for several different fault scenarios to detect, isolate, and identify faults, and predict the end of life in each fault scenario, and present the experimental results.

  5. Kinetic analyses and performance of a colloidal magnetic nanoparticle based immunoassay dedicated to allergy diagnosis.

    PubMed

    Teste, Bruno; Kanoufi, Frédéric; Descroix, Stéphanie; Poncet, Pascal; Georgelin, Thomas; Siaugue, Jean-Michel; Petr, Jan; Varenne, Anne; Hennion, Marie-Claire

    2011-07-01

    In this paper, we demonstrate the possibility to use magnetic nanoparticles as immunosupports for allergy diagnosis. Most immunoassays used for immunosupports and clinical diagnosis are based on a heterogeneous solid-phase system and suffer from mass-transfer limitation. The nanoparticles' colloidal behavior and magnetic properties bring the advantages of homogeneous immunoassay, i.e., species diffusion, and of heterogeneous immunoassay, i.e., easy separation of the immunocomplex and free forms, as well as analyte preconcentration. We thus developed a colloidal, non-competitive, indirect immunoassay using magnetic core-shell nanoparticles (MCSNP) as immunosupports. The feasibility of such an immunoassay was first demonstrated with a model antibody and described by comparing the immunocapture kinetics using macro (standard microtiter plate), micro (microparticles) and nanosupports (MCSNP). The influence of the nanosupport properties (surface chemistry, antigen density) and of the medium (ionic strength, counter ion nature) on the immunocapture efficiency and specificity was then investigated. The performances of this original MCSNP-based immunoassay were compared with a gold standard enzyme-linked immunosorbent assay (ELISA) using a microtiter plate. The capture rate of target IgG was accelerated 200-fold and a tenfold lower limit of detection was achieved. Finally, the MCSNP-based immunoassay was successfully applied to the detection of specific IgE from milk-allergic patient's sera with a lower LOD and a good agreement (CV < 6%) with the microtiter plate, confirming the great potential of this analytical platform in the field of immunodiagnosis.

  6. The Era of Molecular and Other Non-Culture-Based Methods in Diagnosis of Sepsis

    PubMed Central

    Mancini, Nicasio; Carletti, Silvia; Ghidoli, Nadia; Cichero, Paola; Burioni, Roberto; Clementi, Massimo

    2010-01-01

    Summary: Sepsis, a leading cause of morbidity and mortality throughout the world, is a clinical syndrome with signs and symptoms relating to an infectious event and the consequent important inflammatory response. From a clinical point of view, sepsis is a continuous process ranging from systemic inflammatory response syndrome (SIRS) to multiple-organ-dysfunction syndrome (MODS). Blood cultures are the current “gold standard” for diagnosis, and they are based on the detection of viable microorganisms present in blood. However, on some occasions, blood cultures have intrinsic limitations in terms of sensitivity and rapidity, and it is not expected that these drawbacks will be overcome by significant improvements in the near future. For these principal reasons, other approaches are therefore needed in association with blood culture to improve the overall diagnostic yield for septic patients. These considerations have represented the rationale for the development of highly sensitive and fast laboratory methods. This review addresses non-culture-based techniques for the diagnosis of sepsis, including molecular and other non-culture-based methods. In particular, the potential clinical role for the sensitive and rapid detection of bacterial and fungal DNA in the development of new diagnostic algorithms is discussed. PMID:20065332

  7. Sliding window and regression based cup detection in digital fundus images for glaucoma diagnosis.

    PubMed

    Xu, Yanwu; Xu, Dong; Lin, Stephen; Liu, Jiang; Cheng, Jun; Cheung, Carol Y; Aung, Tin; Wong, Tien Yin

    2011-01-01

    We propose a machine learning framework based on sliding windows for glaucoma diagnosis. In digital fundus photographs, our method automatically localizes the optic cup, which is the primary structural image cue for clinically identifying glaucoma. This localization uses a bundle of sliding windows of different sizes to obtain cup candidates in each disc image, then extracts from each sliding window a new histogram based feature that is learned using a group sparsity constraint. An epsilon-SVR (support vector regression) model based on non-linear radial basis function (RBF) kernels is used to rank each candidate, and final decisions are made with a non-maximal suppression (NMS) method. Tested on the large ORIGA(-light) clinical dataset, the proposed method achieves a 73.2% overlap ratio with manually-labeled ground-truth and a 0.091 absolute cup-to-disc ratio (CDR) error, a simple yet widely used diagnostic measure. The high accuracy of this framework on images from low-cost and widespread digital fundus cameras indicates much promise for developing practical automated/assisted glaucoma diagnosis systems. PMID:22003677

  8. Quantum dot-based nanosensors for diagnosis via enzyme activity measurement.

    PubMed

    Knudsen, Birgitta R; Jepsen, Morten Leth; Ho, Yi-Ping

    2013-05-01

    Enzymes are essential in the human body, and the disorder of enzymatic activities has been associated with many different diseases and stages of disease. Luminescent semiconductor nanocrystals, also known as quantum dots (QDs), have garnered great attention in molecular diagnostics. Owing to their superior optical properties, tunable and narrow emissions, stable brightness and long lifetime, QD-based enzyme activity measurement has demonstrated improved detection sensitivity, which is considered particularly valuable for early disease diagnosis. Recent studies have also shown that QD-based nanosensors are capable of probing multiple enzyme activities simultaneously. This review highlights the current development of QD-based nanosensors for enzyme detection. The enzyme-QD hybrid system, equipped with unique electronic, optical and catalytic properties, is envisioned as a potential solution in addressing challenges in diagnostics and therapeutics.

  9. Pompe Disease: Diagnosis and Management. Evidence-Based Guidelines from a Canadian Expert Panel.

    PubMed

    Tarnopolsky, Mark; Katzberg, Hans; Petrof, Basil J; Sirrs, Sandra; Sarnat, Harvey B; Myers, Kimberley; Dupré, Nicolas; Dodig, Dubravka; Genge, Angela; Venance, Shannon L; Korngut, Lawrence; Raiman, Julian; Khan, Aneal

    2016-07-01

    Pompe disease is a lysosomal storage disorder caused by a deficiency of the enzyme acid alpha-glucosidase. Patients have skeletal muscle and respiratory weakness with or without cardiomyopathy. The objective of our review was to systematically evaluate the quality of evidence from the literature to formulate evidence-based guidelines for the diagnosis and management of patients with Pompe disease. The literature review was conducted using published literature, clinical trials, cohort studies and systematic reviews. Cardinal treatment decisions produced seven management guidelines and were assigned a GRADE classification based on the quality of evidence in the published literature. In addition, six recommendations were made based on best clinical practices but with insufficient data to form a guideline. Studying outcomes in rare diseases is challenging due to the small number of patients, but this is in particular the reason why we believe that informed treatment decisions need to consider the quality of the evidence. PMID:27055517

  10. A GC/MS-based metabolomic approach for reliable diagnosis of phenylketonuria.

    PubMed

    Xiong, Xiyue; Sheng, Xiaoqi; Liu, Dan; Zeng, Ting; Peng, Ying; Wang, Yichao

    2015-11-01

    ), which showed that phenylacetic acid may be used as a reliable discriminator for the diagnosis of PKU. The low false positive rate (1-specificity, 0.064) can be eliminated or at least greatly reduced by simultaneously referring to other markers, especially phenylpyruvic acid, a unique marker in PKU. Additionally, this standard was obtained with high sensitivity and specificity in a less invasive manner for diagnosing PKU compared with the Phe/Tyr ratio. Therefore, we conclude that urinary metabolomic information based on the improved oximation-silylation method together with GC/MS may be reliable for the diagnosis and differential diagnosis of PKU.

  11. MR diffusion-weighted imaging-based subcutaneous tumour volumetry in a xenografted nude mouse model using 3D Slicer: an accurate and repeatable method

    PubMed Central

    Ma, Zelan; Chen, Xin; Huang, Yanqi; He, Lan; Liang, Cuishan; Liang, Changhong; Liu, Zaiyi

    2015-01-01

    Accurate and repeatable measurement of the gross tumour volume(GTV) of subcutaneous xenografts is crucial in the evaluation of anti-tumour therapy. Formula and image-based manual segmentation methods are commonly used for GTV measurement but are hindered by low accuracy and reproducibility. 3D Slicer is open-source software that provides semiautomatic segmentation for GTV measurements. In our study, subcutaneous GTVs from nude mouse xenografts were measured by semiautomatic segmentation with 3D Slicer based on morphological magnetic resonance imaging(mMRI) or diffusion-weighted imaging(DWI)(b = 0,20,800 s/mm2) . These GTVs were then compared with those obtained via the formula and image-based manual segmentation methods with ITK software using the true tumour volume as the standard reference. The effects of tumour size and shape on GTVs measurements were also investigated. Our results showed that, when compared with the true tumour volume, segmentation for DWI(P = 0.060–0.671) resulted in better accuracy than that mMRI(P < 0.001) and the formula method(P < 0.001). Furthermore, semiautomatic segmentation for DWI(intraclass correlation coefficient, ICC = 0.9999) resulted in higher reliability than manual segmentation(ICC = 0.9996–0.9998). Tumour size and shape had no effects on GTV measurement across all methods. Therefore, DWI-based semiautomatic segmentation, which is accurate and reproducible and also provides biological information, is the optimal GTV measurement method in the assessment of anti-tumour treatments. PMID:26489359

  12. CIMIDx: Prototype for a Cloud-Based System to Support Intelligent Medical Image Diagnosis With Efficiency

    PubMed Central

    2015-01-01

    Background The Internet has greatly enhanced health care, helping patients stay up-to-date on medical issues and general knowledge. Many cancer patients use the Internet for cancer diagnosis and related information. Recently, cloud computing has emerged as a new way of delivering health services but currently, there is no generic and fully automated cloud-based self-management intervention for breast cancer patients, as practical guidelines are lacking. Objective We investigated the prevalence and predictors of cloud use for medical diagnosis among women with breast cancer to gain insight into meaningful usage parameters to evaluate the use of generic, fully automated cloud-based self-intervention, by assessing how breast cancer survivors use a generic self-management model. The goal of this study was implemented and evaluated with a new prototype called “CIMIDx”, based on representative association rules that support the diagnosis of medical images (mammograms). Methods The proposed Cloud-Based System Support Intelligent Medical Image Diagnosis (CIMIDx) prototype includes two modules. The first is the design and development of the CIMIDx training and test cloud services. Deployed in the cloud, the prototype can be used for diagnosis and screening mammography by assessing the cancers detected, tumor sizes, histology, and stage of classification accuracy. To analyze the prototype’s classification accuracy, we conducted an experiment with data provided by clients. Second, by monitoring cloud server requests, the CIMIDx usage statistics were recorded for the cloud-based self-intervention groups. We conducted an evaluation of the CIMIDx cloud service usage, in which browsing functionalities were evaluated from the end-user’s perspective. Results We performed several experiments to validate the CIMIDx prototype for breast health issues. The first set of experiments evaluated the diagnostic performance of the CIMIDx framework. We collected medical information

  13. Enhanced characterization of solid solitary pulmonary nodules with Bayesian analysis-based computer-aided diagnosis

    PubMed Central

    Perandini, Simone; Soardi, Gian Alberto; Motton, Massimiliano; Augelli, Raffaele; Dallaserra, Chiara; Puntel, Gino; Rossi, Arianna; Sala, Giuseppe; Signorini, Manuel; Spezia, Laura; Zamboni, Federico; Montemezzi, Stefania

    2016-01-01

    The aim of this study was to prospectively assess the accuracy gain of Bayesian analysis-based computer-aided diagnosis (CAD) vs human judgment alone in characterizing solitary pulmonary nodules (SPNs) at computed tomography (CT). The study included 100 randomly selected SPNs with a definitive diagnosis. Nodule features at first and follow-up CT scans as well as clinical data were evaluated individually on a 1 to 5 points risk chart by 7 radiologists, firstly blinded then aware of Bayesian Inference Malignancy Calculator (BIMC) model predictions. Raters’ predictions were evaluated by means of receiver operating characteristic (ROC) curve analysis and decision analysis. Overall ROC area under the curve was 0.758 before and 0.803 after the disclosure of CAD predictions (P = 0.003). A net gain in diagnostic accuracy was found in 6 out of 7 readers. Mean risk class of benign nodules dropped from 2.48 to 2.29, while mean risk class of malignancies rose from 3.66 to 3.92. Awareness of CAD predictions also determined a significant drop on mean indeterminate SPNs (15 vs 23.86 SPNs) and raised the mean number of correct and confident diagnoses (mean 39.57 vs 25.71 SPNs). This study provides evidence supporting the integration of the Bayesian analysis-based BIMC model in SPN characterization.

  14. Diagnosis and treatment of melanoma. European consensus-based interdisciplinary guideline--Update 2012.

    PubMed

    Garbe, Claus; Peris, Ketty; Hauschild, Axel; Saiag, Philippe; Middleton, Mark; Spatz, Alan; Grob, Jean-Jacques; Malvehy, Josep; Newton-Bishop, Julia; Stratigos, Alexander; Pehamberger, Hubert; Eggermont, Alexander M

    2012-10-01

    Cutaneous melanoma (CM) is potentially the most dangerous form of skin tumour and causes 90% of skin cancer mortality. A unique collaboration of multi-disciplinary experts from the European Dermatology Forum (EDF), the European Association of Dermato-Oncology (EADO) and the European Organization of Research and Treatment of Cancer (EORTC) was formed to make recommendations on CM diagnosis and treatment, based on systematic literature reviews and the experts' experience. Diagnosis is made clinically and staging is based upon the AJCC system. CMs are excised with one to two centimetre safety margins. Sentinel lymph node dissection (SLND) is routinely offered as a staging procedure in patients with tumours more than 1mm in thickness, although there is as yet no clear survival benefit for this approach. Interferon-α treatment may be offered to patients with stage II and III melanoma as an adjuvant therapy, as this treatment increases at least the disease-free survival (DFS) and less clear the overall survival (OS) time. The treatment is however associated with significant toxicity. In distant metastasis, all options of surgical therapy have to be considered thoroughly. In the absence of surgical options, systemic treatment is indicated. BRAF inhibitors like vemurafenib for BRAF mutated patients as well as the CTLA-4 antibody ipilimumab offer new therapeutic opportunities apart from conventional chemotherapy. Therapeutic decisions in stage IV patients should be primarily made by an interdisciplinary oncology team ('tumour board'). PMID:22981501

  15. Optical and dielectric sensors based on antimicrobial peptides for microorganism diagnosis

    PubMed Central

    Silva, Rafael R.; Avelino, Karen Y. P. S.; Ribeiro, Kalline L.; Franco, Octavio L.; Oliveira, Maria D. L.; Andrade, Cesar A. S.

    2014-01-01

    Antimicrobial peptides (AMPs) are natural compounds isolated from a wide variety of organisms that include microorganisms, insects, amphibians, plants, and humans. These biomolecules are considered as part of the innate immune system and are known as natural antibiotics, presenting a broad spectrum of activities against bacteria, fungi, and/or viruses. Technological innovations have enabled AMPs to be utilized for the development of novel biodetection devices. Advances in nanotechnology, such as the synthesis of nanocomposites, nanoparticles, and nanotubes have permitted the development of nanostructured platforms with biocompatibility and greater surface areas for the immobilization of biocomponents, arising as additional tools for obtaining more efficient biosensors. Diverse AMPs have been used as biological recognition elements for obtaining biosensors with more specificity and lower detection limits, whose analytical response can be evaluated through electrochemical impedance and fluorescence spectroscopies. AMP-based biosensors have shown potential for applications such as supplementary tools for conventional diagnosis methods of microorganisms. In this review, conventional methods for microorganism diagnosis as well new strategies using AMPs for the development of impedimetric and fluorescent biosensors are highlighted. AMP-based biosensors show promise as methods for diagnosing infections and bacterial contaminations as well as applications in quality control for clinical analyses and microbiological laboratories. PMID:25191319

  16. Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer's disease.

    PubMed

    Bhateja, Vikrant; Moin, Aisha; Srivastava, Anuja; Bao, Le Nguyen; Lay-Ekuakille, Aimé; Le, Dac-Nhuong

    2016-07-01

    Computer based diagnosis of Alzheimer's disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer's disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics). PMID:27475574

  17. Improved automated diagnosis of misfire in internal combustion engines based on simulation models

    NASA Astrophysics Data System (ADS)

    Chen, Jian; Bond Randall, Robert

    2015-12-01

    In this paper, a new advance in the application of Artificial Neural Networks (ANNs) to the automated diagnosis of misfires in Internal Combustion engines(IC engines) is detailed. The automated diagnostic system comprises three stages: fault detection, fault localization and fault severity identification. Particularly, in the severity identification stage, separate Multi-Layer Perceptron networks (MLPs) with saturating linear transfer functions were designed for individual speed conditions, so they could achieve finer classification. In order to obtain sufficient data for the network training, numerical simulation was used to simulate different ranges of misfires in the engine. The simulation models need to be updated and evaluated using experimental data, so a series of experiments were first carried out on the engine test rig to capture the vibration signals for both normal condition and with a range of misfires. Two methods were used for the misfire diagnosis: one is based on the torsional vibration signals of the crankshaft and the other on the angular acceleration signals (rotational motion) of the engine block. Following the signal processing of the experimental and simulation signals, the best features were selected as the inputs to ANN networks. The ANN systems were trained using only the simulated data and tested using real experimental cases, indicating that the simulation model can be used for a wider range of faults for which it can still be considered valid. The final results have shown that the diagnostic system based on simulation can efficiently diagnose misfire, including location and severity.

  18. Enhanced characterization of solid solitary pulmonary nodules with Bayesian analysis-based computer-aided diagnosis

    PubMed Central

    Perandini, Simone; Soardi, Gian Alberto; Motton, Massimiliano; Augelli, Raffaele; Dallaserra, Chiara; Puntel, Gino; Rossi, Arianna; Sala, Giuseppe; Signorini, Manuel; Spezia, Laura; Zamboni, Federico; Montemezzi, Stefania

    2016-01-01

    The aim of this study was to prospectively assess the accuracy gain of Bayesian analysis-based computer-aided diagnosis (CAD) vs human judgment alone in characterizing solitary pulmonary nodules (SPNs) at computed tomography (CT). The study included 100 randomly selected SPNs with a definitive diagnosis. Nodule features at first and follow-up CT scans as well as clinical data were evaluated individually on a 1 to 5 points risk chart by 7 radiologists, firstly blinded then aware of Bayesian Inference Malignancy Calculator (BIMC) model predictions. Raters’ predictions were evaluated by means of receiver operating characteristic (ROC) curve analysis and decision analysis. Overall ROC area under the curve was 0.758 before and 0.803 after the disclosure of CAD predictions (P = 0.003). A net gain in diagnostic accuracy was found in 6 out of 7 readers. Mean risk class of benign nodules dropped from 2.48 to 2.29, while mean risk class of malignancies rose from 3.66 to 3.92. Awareness of CAD predictions also determined a significant drop on mean indeterminate SPNs (15 vs 23.86 SPNs) and raised the mean number of correct and confident diagnoses (mean 39.57 vs 25.71 SPNs). This study provides evidence supporting the integration of the Bayesian analysis-based BIMC model in SPN characterization. PMID:27648166

  19. Enhanced characterization of solid solitary pulmonary nodules with Bayesian analysis-based computer-aided diagnosis.

    PubMed

    Perandini, Simone; Soardi, Gian Alberto; Motton, Massimiliano; Augelli, Raffaele; Dallaserra, Chiara; Puntel, Gino; Rossi, Arianna; Sala, Giuseppe; Signorini, Manuel; Spezia, Laura; Zamboni, Federico; Montemezzi, Stefania

    2016-08-28

    The aim of this study was to prospectively assess the accuracy gain of Bayesian analysis-based computer-aided diagnosis (CAD) vs human judgment alone in characterizing solitary pulmonary nodules (SPNs) at computed tomography (CT). The study included 100 randomly selected SPNs with a definitive diagnosis. Nodule features at first and follow-up CT scans as well as clinical data were evaluated individually on a 1 to 5 points risk chart by 7 radiologists, firstly blinded then aware of Bayesian Inference Malignancy Calculator (BIMC) model predictions. Raters' predictions were evaluated by means of receiver operating characteristic (ROC) curve analysis and decision analysis. Overall ROC area under the curve was 0.758 before and 0.803 after the disclosure of CAD predictions (P = 0.003). A net gain in diagnostic accuracy was found in 6 out of 7 readers. Mean risk class of benign nodules dropped from 2.48 to 2.29, while mean risk class of malignancies rose from 3.66 to 3.92. Awareness of CAD predictions also determined a significant drop on mean indeterminate SPNs (15 vs 23.86 SPNs) and raised the mean number of correct and confident diagnoses (mean 39.57 vs 25.71 SPNs). This study provides evidence supporting the integration of the Bayesian analysis-based BIMC model in SPN characterization. PMID:27648166

  20. Multispectral medical image fusion in Contourlet domain for computer based diagnosis of Alzheimer's disease

    NASA Astrophysics Data System (ADS)

    Bhateja, Vikrant; Moin, Aisha; Srivastava, Anuja; Bao, Le Nguyen; Lay-Ekuakille, Aimé; Le, Dac-Nhuong

    2016-07-01

    Computer based diagnosis of Alzheimer's disease can be performed by dint of the analysis of the functional and structural changes in the brain. Multispectral image fusion deliberates upon fusion of the complementary information while discarding the surplus information to achieve a solitary image which encloses both spatial and spectral details. This paper presents a Non-Sub-sampled Contourlet Transform (NSCT) based multispectral image fusion model for computer-aided diagnosis of Alzheimer's disease. The proposed fusion methodology involves color transformation of the input multispectral image. The multispectral image in YIQ color space is decomposed using NSCT followed by dimensionality reduction using modified Principal Component Analysis algorithm on the low frequency coefficients. Further, the high frequency coefficients are enhanced using non-linear enhancement function. Two different fusion rules are then applied to the low-pass and high-pass sub-bands: Phase congruency is applied to low frequency coefficients and a combination of directive contrast and normalized Shannon entropy is applied to high frequency coefficients. The superiority of the fusion response is depicted by the comparisons made with the other state-of-the-art fusion approaches (in terms of various fusion metrics).

  1. Matrix-Similarity Based Loss Function and Feature Selection for Alzheimer's Disease Diagnosis

    PubMed Central

    Zhu, Xiaofeng; Suk, Heung-Il; Shen, Dinggang

    2015-01-01

    Recent studies on Alzheimer's Disease (AD) or its prodromal stage, Mild Cognitive Impairment (MCI), diagnosis presented that the tasks of identifying brain disease status and predicting clinical scores based on neuroimaging features were highly related to each other. However, these tasks were often conducted independently in the previous studies. Regarding the feature selection, to our best knowledge, most of the previous work considered a loss function defined as an element-wise difference between the target values and the predicted ones. In this paper, we consider the problems of joint regression and classification for AD/MCI diagnosis and propose a novel matrix-similarity based loss function that uses high-level information inherent in the target response matrix and imposes the information to be preserved in the predicted response matrix. The newly devised loss function is combined with a group lasso method for joint feature selection across tasks, i.e., clinical scores prediction and disease status identification. We conducted experiments on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, and showed that the newly devised loss function was effective to enhance the performances of both clinical score prediction and disease status identification, outperforming the state-of-the-art methods. PMID:26379415

  2. Evidence-based consensus on the diagnosis, prevention and management of hepatitis C virus disease

    PubMed Central

    Shaheen, Mahrukh Akbar; Idrees, Muhammad

    2015-01-01

    Hepatitis C virus (HCV) is a potent human pathogen and is one of the main causes of chronic hepatitis round the world. The present review describes the evidence-based consensus on the diagnosis, prevention and management of HCV disease. Various techniques, for the detection of anti-HCV immunoglobulin G immunoassays, detection of HCV RNA by identifying virus-specific molecules nucleic acid testings, recognition of core antigen for diagnosis of HCV, quantitative antigen assay, have been used to detect HCV RNA and core antigen. Advanced technologies such as nanoparticle-based diagnostic assays, loop-mediated isothermal amplification and aptamers and Ortho trak-C assay have also come to the front that provides best detection results with greater ease and specificity for detection of HCV. It is of immense importance to prevent this infection especially among the sexual partners, injecting drug users, mother-to-infant transmission of HCV, household contact, healthcare workers and people who get tattoos and piercing on their skin. Management of this infection is intended to eradicate it out of the body of patients. Management includes examining the treatment (efficacy and protection), assessment of hepatic condition before commencing therapy, controlling the parameters upon which dual and triple therapies work, monitoring the body after treatment and adjusting the co-factors. Examining the treatment in some special groups of people (HIV/HCV co-infected, hemodialysis patients, renal transplanted patients). PMID:25848486

  3. Enhanced characterization of solid solitary pulmonary nodules with Bayesian analysis-based computer-aided diagnosis.

    PubMed

    Perandini, Simone; Soardi, Gian Alberto; Motton, Massimiliano; Augelli, Raffaele; Dallaserra, Chiara; Puntel, Gino; Rossi, Arianna; Sala, Giuseppe; Signorini, Manuel; Spezia, Laura; Zamboni, Federico; Montemezzi, Stefania

    2016-08-28

    The aim of this study was to prospectively assess the accuracy gain of Bayesian analysis-based computer-aided diagnosis (CAD) vs human judgment alone in characterizing solitary pulmonary nodules (SPNs) at computed tomography (CT). The study included 100 randomly selected SPNs with a definitive diagnosis. Nodule features at first and follow-up CT scans as well as clinical data were evaluated individually on a 1 to 5 points risk chart by 7 radiologists, firstly blinded then aware of Bayesian Inference Malignancy Calculator (BIMC) model predictions. Raters' predictions were evaluated by means of receiver operating characteristic (ROC) curve analysis and decision analysis. Overall ROC area under the curve was 0.758 before and 0.803 after the disclosure of CAD predictions (P = 0.003). A net gain in diagnostic accuracy was found in 6 out of 7 readers. Mean risk class of benign nodules dropped from 2.48 to 2.29, while mean risk class of malignancies rose from 3.66 to 3.92. Awareness of CAD predictions also determined a significant drop on mean indeterminate SPNs (15 vs 23.86 SPNs) and raised the mean number of correct and confident diagnoses (mean 39.57 vs 25.71 SPNs). This study provides evidence supporting the integration of the Bayesian analysis-based BIMC model in SPN characterization.

  4. ALA-based fluorescent diagnosis of malignant oral lesions in the presence of bacterial porphyrin formation

    NASA Astrophysics Data System (ADS)

    Schleier, P.; Berndt, A.; Zinner, K.; Zenk, W.; Dietel, W.; Pfister, W.

    2006-02-01

    The aminolevulinic acid (5-ALA) -based fluorescence diagnosis has been found to be promising for an early detection and demarcation of superficial oral squamous cell carcinomas (OSCC). This method has previously demonstrated high sensitivity, however this clinical trial showed a specificity of approximately 62 %. This specificity was mainly restricted by tumor detection in the oral cavity in the presence of bacteria. After topical ALA application in the mouth of patients with previously diagnosed OSSC, red fluorescent areas were observed which did not correlate to confirm histological findings. Swabs and plaque samples were taken from 44 patients and cultivated microbiologically. Fluorescence was investigated (OMA-system) from 32 different bacteria strains found naturally in the oral cavity. After ALA incubation, 30 of 32 strains were found to synthesize fluorescent porphyrins, mainly Protoporphyrin IX. Also multiple fluorescent spectra were obtained having peak wavelengths of 636 nm and around 618 nm - 620 nm indicating synthesis of different porphyrins, such as the lipophylic Protoporphyrin IX (PpIX) and hydrophylic porphyrins (water soluble porphyrins, wsp). Of the 32 fluorescent bacterial strains, 18 produced wsp, often in combination with PpIX, and 5 produced solely wsp. These results clarify that ALA-based fluorescence diagnosis without consideration or suppression of bacteria fluorescence may lead to false-positive findings. It is necessary to suppress bacteria fluorescence with suitable antiseptics before starting the procedure. In this study, when specific antiseptic pre-treatment was performed bacterial associated fluorescence was significantly reduced.

  5. Combining Model-Based and Feature-Driven Diagnosis Approaches - A Case Study on Electromechanical Actuators

    NASA Technical Reports Server (NTRS)

    Narasimhan, Sriram; Roychoudhury, Indranil; Balaban, Edward; Saxena, Abhinav

    2010-01-01

    Model-based diagnosis typically uses analytical redundancy to compare predictions from a model against observations from the system being diagnosed. However this approach does not work very well when it is not feasible to create analytic relations describing all the observed data, e.g., for vibration data which is usually sampled at very high rates and requires very detailed finite element models to describe its behavior. In such cases, features (in time and frequency domains) that contain diagnostic information are extracted from the data. Since this is a computationally intensive process, it is not efficient to extract all the features all the time. In this paper we present an approach that combines the analytic model-based and feature-driven diagnosis approaches. The analytic approach is used to reduce the set of possible faults and then features are chosen to best distinguish among the remaining faults. We describe an implementation of this approach on the Flyable Electro-mechanical Actuator (FLEA) test bed.

  6. Optical and dielectric sensors based on antimicrobial peptides for microorganism diagnosis.

    PubMed

    Silva, Rafael R; Avelino, Karen Y P S; Ribeiro, Kalline L; Franco, Octavio L; Oliveira, Maria D L; Andrade, Cesar A S

    2014-01-01

    Antimicrobial peptides (AMPs) are natural compounds isolated from a wide variety of organisms that include microorganisms, insects, amphibians, plants, and humans. These biomolecules are considered as part of the innate immune system and are known as natural antibiotics, presenting a broad spectrum of activities against bacteria, fungi, and/or viruses. Technological innovations have enabled AMPs to be utilized for the development of novel biodetection devices. Advances in nanotechnology, such as the synthesis of nanocomposites, nanoparticles, and nanotubes have permitted the development of nanostructured platforms with biocompatibility and greater surface areas for the immobilization of biocomponents, arising as additional tools for obtaining more efficient biosensors. Diverse AMPs have been used as biological recognition elements for obtaining biosensors with more specificity and lower detection limits, whose analytical response can be evaluated through electrochemical impedance and fluorescence spectroscopies. AMP-based biosensors have shown potential for applications such as supplementary tools for conventional diagnosis methods of microorganisms. In this review, conventional methods for microorganism diagnosis as well new strategies using AMPs for the development of impedimetric and fluorescent biosensors are highlighted. AMP-based biosensors show promise as methods for diagnosing infections and bacterial contaminations as well as applications in quality control for clinical analyses and microbiological laboratories.

  7. Avoiding fractional electrons in subsystem DFT based ab-initio molecular dynamics yields accurate models for liquid water and solvated OH radical

    NASA Astrophysics Data System (ADS)

    Genova, Alessandro; Ceresoli, Davide; Pavanello, Michele

    2016-06-01

    In this work we achieve three milestones: (1) we present a subsystem DFT method capable of running ab-initio molecular dynamics simulations accurately and efficiently. (2) In order to rid the simulations of inter-molecular self-interaction error, we exploit the ability of semilocal frozen density embedding formulation of subsystem DFT to represent the total electron density as a sum of localized subsystem electron densities that are constrained to integrate to a preset, constant number of electrons; the success of the method relies on the fact that employed semilocal nonadditive kinetic energy functionals effectively cancel out errors in semilocal exchange-correlation potentials that are linked to static correlation effects and self-interaction. (3) We demonstrate this concept by simulating liquid water and solvated OH• radical. While the bulk of our simulations have been performed on a periodic box containing 64 independent water molecules for 52 ps, we also simulated a box containing 256 water molecules for 22 ps. The results show that, provided one employs an accurate nonadditive kinetic energy functional, the dynamics of liquid water and OH• radical are in semiquantitative agreement with experimental results or higher-level electronic structure calculations. Our assessments are based upon comparisons of radial and angular distribution functions as well as the diffusion coefficient of the liquid.

  8. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints.

    PubMed

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-02-24

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS-inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car.

  9. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints

    PubMed Central

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-01-01

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS–inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car. PMID:26927108

  10. An Accurate GPS-IMU/DR Data Fusion Method for Driverless Car Based on a Set of Predictive Models and Grid Constraints.

    PubMed

    Wang, Shiyao; Deng, Zhidong; Yin, Gang

    2016-01-01

    A high-performance differential global positioning system (GPS)  receiver with real time kinematics provides absolute localization for driverless cars. However, it is not only susceptible to multipath effect but also unable to effectively fulfill precise error correction in a wide range of driving areas. This paper proposes an accurate GPS-inertial measurement unit (IMU)/dead reckoning (DR) data fusion method based on a set of predictive models and occupancy grid constraints. First, we employ a set of autoregressive and moving average (ARMA) equations that have different structural parameters to build maximum likelihood models of raw navigation. Second, both grid constraints and spatial consensus checks on all predictive results and current measurements are required to have removal of outliers. Navigation data that satisfy stationary stochastic process are further fused to achieve accurate localization results. Third, the standard deviation of multimodal data fusion can be pre-specified by grid size. Finally, we perform a lot of field tests on a diversity of real urban scenarios. The experimental results demonstrate that the method can significantly smooth small jumps in bias and considerably reduce accumulated position errors due to DR. With low computational complexity, the position accuracy of our method surpasses existing state-of-the-arts on the same dataset and the new data fusion method is practically applied in our driverless car. PMID:26927108

  11. Rapid and accurate species and genomic species identification and exhaustive population diversity assessment of Agrobacterium spp. using recA-based PCR.

    PubMed

    Shams, M; Vial, L; Chapulliot, D; Nesme, X; Lavire, C

    2013-07-01

    Agrobacteria are common soil bacteria that interact with plants as commensals, plant growth promoting rhizobacteria or alternatively as pathogens. Indigenous agrobacterial populations are composites, generally with several species and/or genomic species and several strains per species. We thus developed a recA-based PCR approach to accurately identify and specifically detect agrobacteria at various taxonomic levels. Specific primers were designed for all species and/or genomic species of Agrobacterium presently known, including 11 genomic species of the Agrobacterium tumefaciens complex (G1-G9, G13 and G14, among which only G2, G4, G8 and G14 still received a Latin epithet: pusense, radiobacter, fabrum and nepotum, respectively), A. larrymoorei, A. rubi, R. skierniewicense, A. sp. 1650, and A. vitis, and for the close relative Allorhizobium undicola. Specific primers were also designed for superior taxa, Agrobacterium spp. and Rhizobiaceace. Primer specificities were assessed with target and non-target pure culture DNAs as well as with DNAs extracted from composite agrobacterial communities. In addition, we showed that the amplicon cloning-sequencing approach used with Agrobacterium-specific or Rhizobiaceae-specific primers is a way to assess the agrobacterial diversity of an indigenous agrobacterial population. Hence, the agrobacterium-specific primers designed in the present study enabled the first accurate and rapid identification of all species and/or genomic species of Agrobacterium, as well as their direct detection in environmental samples.

  12. A simple and accurate SNP scoring strategy based on typeIIS restriction endonuclease cleavage and matrix-assisted laser desorption/ionization mass spectrometry

    PubMed Central

    Hong, Sun Pyo; Ji, Seung Il; Rhee, Hwanseok; Shin, Soo Kyeong; Hwang, Sun Young; Lee, Seung Hwan; Lee, Soong Deok; Oh, Heung-Bum; Yoo, Wangdon; Kim, Soo-Ok

    2008-01-01

    Background We describe the development of a novel matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF)-based single nucleotide polymorphism (SNP) scoring strategy, termed Restriction Fragment Mass Polymorphism (RFMP) that is suitable for genotyping variations in a simple, accurate, and high-throughput manner. The assay is based on polymerase chain reaction (PCR) amplification and mass measurement of oligonucleotides containing a polymorphic base, to which a typeIIS restriction endonuclease recognition was introduced by PCR amplification. Enzymatic cleavage of the products leads to excision of oligonucleotide fragments representing base variation of the polymorphic site whose masses were determined by MALDI-TOF MS. Results The assay represents an improvement over previous methods because it relies on the direct mass determination of PCR products rather than on an indirect analysis, where a base-extended or fluorescent report tag is interpreted. The RFMP strategy is simple and straightforward, requiring one restriction digestion reaction following target amplification in a single vessel. With this technology, genotypes are generated with a high call rate (99.6%) and high accuracy (99.8%) as determined by independent sequencing. Conclusion The simplicity, accuracy and amenability to high-throughput screening analysis should make the RFMP assay suitable for large-scale genotype association study as well as clinical genotyping in laboratories. PMID:18538037

  13. Space-Based Diagnosis of Surface Ozone Sensitivity to Anthropogenic Emissions

    NASA Technical Reports Server (NTRS)

    Martin, Randall V.; Fiore, Arlene M.; VanDonkelaar, Aaron

    2004-01-01

    We present a novel capability in satellite remote sensing with implications for air pollution control strategy. We show that the ratio of formaldehyde columns to tropospheric nitrogen dioxide columns is an indicator of the relative sensitivity of surface ozone to emissions of nitrogen oxides (NO(x) = NO + NO2) and volatile organic compounds (VOCs). The diagnosis from these space-based observations is highly consistent with current under