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Sample records for clinical parameters predicting

  1. Clinical parameters predictive of malignancy of thyroid follicular neoplasms

    International Nuclear Information System (INIS)

    Needle aspiration biopsy is commonly employed in the evaluation of thyroid nodules. Unfortunately, the cytologic finding of a 'follicular neoplasm' does not distinguish between a thyroid adenoma and a follicular cancer. The purpose of this study was to identify clinical parameters that characterize patients with an increased risk of having a thyroid follicular cancer who preoperatively have a 'follicular neoplasm' identified by needle aspiration biopsy. A total of 395 patients initially treated at Vancouver General Hospital and the British Columbia Cancer Agency between the years of 1965 and 1985 were identified and their data were entered into a computer database. Patients with thyroid adenomas were compared to patients with follicular cancer using the chi-square test and Student's t-test. Statistically significant parameters that distinguished patients at risk of having a thyroid cancer (p less than 0.05) included age greater than 50 years, nodule size greater than 3 cm, and a history of neck irradiation. Sex, family history of goiter or neoplasm, alcohol and tobacco use, and use of exogenous estrogen were not significant parameters. Patients can be identified preoperatively to be at an increased risk of having a follicular cancer and accordingly appropriate surgical resection can be planned

  2. Multidetector-CT angiography in pulmonary embolism - can image parameters predict clinical outcome?

    Energy Technology Data Exchange (ETDEWEB)

    Heyer, Christoph M.; Lemburg, Stefan P.; Nicolas, Volkmar; Roggenland, Daniela [Berufsgenossenschaftliches Universitaetsklinikum Bergmannsheil GmbH, Ruhr-University of Bochum, Institute of Diagnostic Radiology, Interventional Radiology and Nuclear Medicine, Bochum (Germany); Knoop, Heiko [Berufsgenossenschaftliches Universitaetsklinikum Bergmannsheil GmbH, Medical Clinic III - Pneumology, Allergology, and Sleep Medicine, Bochum (Germany); Holland-Letz, Tim [Ruhr-University of Bochum, Department of Medical Informatics, Biometry and Epidemiology, Bochum (Germany)

    2011-09-15

    To assess if pulmonary CT angiography (CTA) can predict outcome in patients with pulmonary embolism (PE). Retrospective analysis of CTA studies of patients with PE and documentation of pulmonary artery (PA)/aorta ratio, right ventricular (RV)/left ventricular (LV) ratio, superior vena cava (SVC) diameter, pulmonary obstruction index (POI), ventricular septal bowing (VSB), venous contrast reflux (VCR), pulmonary infarction and pleural effusion. Furthermore, duration of total hospital stay, necessity for/duration of ICU therapy, necessity for mechanical ventilation and mortality were recorded. Comparison was performed by logistic/linear regression analysis with significance at 5%. 152 patients were investigated. Mean duration of hospital stay was 21 {+-} 24 days. 66 patients were admitted to the ICU; 20 received mechanical ventilation. Mean duration of ICU therapy was 3 {+-} 8 days. Mortality rate was 8%. Significant positive associations of POI, VCR and pulmonary infarction with necessity for ICU therapy were shown. VCR was significantly associated with necessity for mechanical ventilation and duration of ICU treatment. Pleural effusions were significantly associated with duration of total hospital stay whereas the RV/LV ratio correlated with mortality. Selected CTA findings showed significant associations with the clinical course of PE and may thus be used as predictive parameters. (orig.)

  3. Multidetector-CT angiography in pulmonary embolism - can image parameters predict clinical outcome?

    International Nuclear Information System (INIS)

    To assess if pulmonary CT angiography (CTA) can predict outcome in patients with pulmonary embolism (PE). Retrospective analysis of CTA studies of patients with PE and documentation of pulmonary artery (PA)/aorta ratio, right ventricular (RV)/left ventricular (LV) ratio, superior vena cava (SVC) diameter, pulmonary obstruction index (POI), ventricular septal bowing (VSB), venous contrast reflux (VCR), pulmonary infarction and pleural effusion. Furthermore, duration of total hospital stay, necessity for/duration of ICU therapy, necessity for mechanical ventilation and mortality were recorded. Comparison was performed by logistic/linear regression analysis with significance at 5%. 152 patients were investigated. Mean duration of hospital stay was 21 ± 24 days. 66 patients were admitted to the ICU; 20 received mechanical ventilation. Mean duration of ICU therapy was 3 ± 8 days. Mortality rate was 8%. Significant positive associations of POI, VCR and pulmonary infarction with necessity for ICU therapy were shown. VCR was significantly associated with necessity for mechanical ventilation and duration of ICU treatment. Pleural effusions were significantly associated with duration of total hospital stay whereas the RV/LV ratio correlated with mortality. Selected CTA findings showed significant associations with the clinical course of PE and may thus be used as predictive parameters. (orig.)

  4. How to develop, validate, and compare clinical prediction models involving radiological parameters: Study design and statistical methods

    Energy Technology Data Exchange (ETDEWEB)

    Han, Kyung Hwa; Choi, Byoung Wook [Dept. of Radiology, and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul (Korea, Republic of); Song, Ki Jun [Dept. of Biostatistics and Medical Informatics, Yonsei University College of Medicine, Seoul (Korea, Republic of)

    2016-06-15

    Clinical prediction models are developed to calculate estimates of the probability of the presence/occurrence or future course of a particular prognostic or diagnostic outcome from multiple clinical or non-clinical parameters. Radiologic imaging techniques are being developed for accurate detection and early diagnosis of disease, which will eventually affect patient outcomes. Hence, results obtained by radiological means, especially diagnostic imaging, are frequently incorporated into a clinical prediction model as important predictive parameters, and the performance of the prediction model may improve in both diagnostic and prognostic settings. This article explains in a conceptual manner the overall process of developing and validating a clinical prediction model involving radiological parameters in relation to the study design and statistical methods. Collection of a raw dataset; selection of an appropriate statistical model; predictor selection; evaluation of model performance using a calibration plot, Hosmer-Lemeshow test and c-index; internal and external validation; comparison of different models using c-index, net reclassification improvement, and integrated discrimination improvement; and a method to create an easy-to-use prediction score system will be addressed. This article may serve as a practical methodological reference for clinical researchers.

  5. Thyroid Hormones, Autoantibodies, Ultrasonography, and Clinical Parameters for Predicting Thyroid Cancer

    Science.gov (United States)

    He, Lin-zheng; Zeng, Tian-shu; Pu, Lin; Pan, Shi-xiu; Xia, Wen-fang; Chen, Lu-lu

    2016-01-01

    Our objective was to evaluate thyroid nodule malignancy prediction using thyroid function tests, autoantibodies, ultrasonographic imaging, and clinical data. We conducted a retrospective cohort study in 1400 patients with nodular thyroid disease (NTD). The thyroid stimulating hormone (TSH) concentration was significantly higher in patients with differentiated thyroid cancer (DTC) versus benign thyroid nodular disease (BTND) (p = 0.004). The receiver operating characteristic curve of TSH showed an AUC of 0.58 (95% CI 0.53–0.62, p = 0.001), sensitivity of 74%, and specificity of 57% at a cut-off of 1.59 mIU/L. There was an incremental increase in TSH concentration along with the increasing tumor size (p < 0.001). Thyroglobulin antibody (TgAb) concentration was associated with an increased risk of malignancy (p = 0.029), but this association was lost when the effect of TSH was taken into account (p = 0.11). Thyroid ultrasonographic characteristics, including fewer than three nodules, hypoechoic appearance, solid component, poorly defined margin, intranodular or peripheral-intranodular flow, and punctate calcification, can be used to predict the risk of thyroid cancer. In conclusion, our study suggests that preoperative serum TSH concentration, age, and ultrasonographic features can be used to predict the risk of malignancy in patients with NTD. PMID:27313612

  6. Benefit of combining quantitative cardiac CT parameters with troponin I for predicting right ventricular dysfunction and adverse clinical events in patients with acute pulmonary embolism

    International Nuclear Information System (INIS)

    Objective: To prospectively evaluate the diagnostic accuracy of quantitative cardiac CT parameters alone and in combination with troponin I for the assessment of right ventricular dysfunction (RVD) and adverse clinical events in patients with acute pulmonary embolism (PE). Materials and results: This prospective study had institutional review board approval and was HIPAA compliant. In total 83 patients with confirmed PE underwent echocardiography and troponin I serum level measurements within 24 h. Three established cardiac CT measurements for the assessment of RVD were obtained (RV/LVaxial, RV/LV4-CH, and RV/LVvolume). CT measurements and troponin I serum levels were correlated with RVD found on echocardiography and adverse clinical events according to Management Strategies and Prognosis in Pulmonary Embolism Trial-3 (MAPPET-3 criteria. 31 of 83 patients with PE had RVD on echocardiography and 39 of 83 patients had adverse clinical events. A RV/LVvolume ratio > 1.43 showed the highest area under the curve (AUC) (0.65) for the prediction of adverse clinical events when compared to RV/LVaxial, RV/LV4Ch and troponin I. The AUC for the detection of RVD of RV/LVaxial, RV/LV4Ch, RV/LVvolume, and troponin I were 0.86, 0.86, 0.92, and 0.69, respectively. Combination of RV/LVaxial, RV/LV4Ch, RV/LVvolume with troponin I increased the AUC to 0.87, 0.87 and 0.93, respectively. Conclusion: A combination of cardiac CT parameters and troponin I measurements improves the diagnostic accuracy for detecting RVD and predicting adverse clinical events if compared to either test alone.

  7. The accuracy of a clinical parameters-based scoring system to predict spontaneous intracranial hemorrhage in children under one year old

    Directory of Open Access Journals (Sweden)

    Harris Alfan

    2015-05-01

    Full Text Available Background Previous studies show that most children aged less than 1 year had intracranial hemorrhage without any history of trauma. The sign and symptoms of spontaneous intracranial hemorrhage (SIH in children varies. To minimize morbidity and mortality, early detection and accurate diagnosis are required. Head CT scans area widely used for diagnosing SIH. Unfortunately, not all health facilities in Indonesia have CT scans. Objective To determine the accuracy of a clinical parameters-based scoring system in predicting spontaneous intracranial hemorrhage (SIH in children under one year old. Methods This diagnostic study included children aged under one year who were admitted to Mohammad Hoesin Hospital, Palembang. Patients who showed any signs of increased intracranial pressure were recruited. Data were collected from medical records from January 2007 to September 2013. Through the use of logistic regression analysis, clinical parameters showing significant relationships with computerized tomography (CT-scan confirmed SIH were selected as predictors. Each predictor was given a score based on an adjusted ratio. The cut-off point of the total scores from all patients was determined using a receiver operating curve (ROC analysis. The accuracy of the total scores was calculated using a 2x2 validity test. Results Of the 186 children included in this study, 98 (52.7% had SIH and 93 (94.8% were under 3 month-old. The predictors for SIH used included age (>3 months: score 0; 1-3 months: score 3, gender (female: score 0; male: score 1, pallor (no: score 0; yes: score 1, bulging fontanel (no: score 0; yes: score 1, pupil (isocoria: score 0; anisocoria: score 2 and history of shaken baby (no: score 0; yes: score 3. The ROC analysis showed that the area under the curve (AUC was 95.3% with a cut-off point of 4.5, had a sensitivity of 88.7% and a specificity of 93.1% Conclusion This scoring system based on clinical parameters hadgood accuracy for predicting

  8. Predicting Engine Parameters using the Optical Spectrum

    Data.gov (United States)

    National Aeronautics and Space Administration — The Optical Plume Anomaly Detection (OPAD) system is under development to predict engine anomalies and engine parameters of the Space Shuttle's Main Engine (SSME)....

  9. Clinicopathologic and gene expression parameters predict liver cancer prognosis

    Directory of Open Access Journals (Sweden)

    Hao Ke

    2011-11-01

    Full Text Available Abstract Background The prognosis of hepatocellular carcinoma (HCC varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and gene expression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model. Methods Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and gene expression data (from both tissue types in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction. Results HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, gene expression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis. Conclusion When applied individually, clinicopathologic parameters and gene expression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of gene expression on the processes of tumorigenesis and clinical outcome.

  10. Predictive value of PSA velocity over early clinical and pathological parameters in patients with localized prostate cancer who undergo radical retropubic prostatectomy

    Directory of Open Access Journals (Sweden)

    Martinez Carlos A.L.

    2004-01-01

    Full Text Available OBJECTIVES: To analyze the behavior of the prostate specific antigen velocity (PSAV in localized prostate adenocarcinoma. MATERIALS AND METHODS: We conducted a retrospective study of 500 men who had localized prostate adenocarcinoma, who underwent radical retropubic prostatectomy between January 1986 and December 1999. The PSAV was calculated for each patient and subsequently, the values were correlated with 5 groups: age, initial PSA value, clinical stage, tumor volume and Gleason score. RESULTS: The behavior of PSAV presented statistic significance with an increment between 1.3 ng/mL and 9.6 ng/mL, ranging from 38.6% and 59.8% when compared with the initial PSA value (p < 0.0001, clinical stage (p = 0.0002, tumor volume (p < 0.0001 and Gleason score (p = 0.0009. CONCLUSION: PSAV up to 2.5 ng/mL/year is associated with factors of good prognosis, such as initial PSA below 10 mg/mL, clinical stage T1, tumor volume below 20% and Gleason score lower than 7.

  11. The clot burden score, the Boston Acute Stroke Imaging Scale, the cerebral blood volume ASPECTS, and two novel imaging parameters in the prediction of clinical outcome of ischemic stroke patients receiving intravenous thrombolytic therapy

    Energy Technology Data Exchange (ETDEWEB)

    Sillanpaa, Niko; Hakomaki, Jari; Lahteela, Arto; Dastidar, Prasun; Soimakallio, Seppo [Tampere University Hospital, Medical Imaging Center, Tampere (Finland); Saarinen, Jukka T.; Numminen, Heikki; Elovaara, Irina [Tampere University Hospital, Department of Neurology, Tampere (Finland); Rusanen, Harri [Oulu University Hospital, Department of Neurology, Oulu (Finland)

    2012-07-15

    Recently two classification methods based on the location and the extent of thrombosis detected with CT angiography have been introduced: the Boston Acute Stroke Imaging Scale (BASIS) and the clot burden score (CBS). We studied the performance of BASIS and CBS in predicting good clinical outcome (mRS {<=}2 at 90 days) in an acute (<3 h) stroke cohort treated with intravenous thrombolytic therapy. Eighty-three consecutive patients who underwent multimodal CT were analyzed. Binary logistic regression model was used to assess how BASIS, CBS, and cerebral blood volume (CBV) ASPECTS predict favorable clinical outcome. Diagnostic sensitivities and specificities were calculated and compared. Patients with low CBS and CBV ASPECTS scores and major strokes according to BASIS had significantly higher admission NIHSS scores, larger perfusion defects, and more often poor clinical outcome. In logistic regression analysis, CBV ASPECTS, CBS and BASIS were significantly associated with the clinical outcome. The performance of BASIS improved when patients with thrombosis of the M2 segment of the middle cerebral artery were classified as having minor stroke (M1-BASIS). In the anterior circulation, the sum of CBS and CBV ASPECTS (CBSV) proved to be the most robust predictor of favorable outcome. CBV ASPECTS and CBS had high sensitivity but moderate to poor specificity while BASIS was only moderately sensitive and specific. CBS, BASIS, and CBV ASPECTS are statistically robust and sensitive but unspecific predictors of good clinical outcome. Two new derived imaging parameters, CBSV and M1-BASIS, share these properties and may have increased prognostic value. (orig.)

  12. Vertebral Geometry Parameters Can Predict Fractures

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    P Tofighi

    2007-08-01

    Full Text Available Background: The aim of this study was to investigate vertebral geometry changes and determine cutoff value of vertebral height to predict fractures. Methods: In a cross-sectional study, 280 postmenopausal women recruited .In all subjects bone mineral density and radiog¬raphy of the lumbar spine performed. Lateral radiographs were evaluated for identification of vertebral fractures, using a validated semiquantitative method. T-score of vertebral height was calculated based on data extracted from Iranian Multi¬center Osteoporosis Study. ROC curve used to determine cut off value of vertebral height T-score to predict fractures. Results: The mean of age and BMI were 55.34±8.7 years and 27.73±5 kg/m2, respectively. Among osteoporotic women, 59.8% had one or more vertebral fractures and 23.8% had at least 2 fractures. In fracture group the T-score of spine and femur BMD was lower than the others. The mean of vertebral height in women without fractures was 12.94±0.6 cm, and in the patient with 4 or more fractures was12.3, thus every fracture accompany with 1.2% decreases in the height of vertebrae. The prevalence of vertebral fracture in osteoporotic patients was 71.4% and in healthy cases 39.5%. Better estimation of vertebral height T score in ROC curve was less than -0.7.The sensitivity and specificity of the cut off value were 81.3% and 52.9%, respectively. Conclusion: Vertebral fractures are common fractures in postmenopausal women. There was a correlation between verte¬bral height and fractures. Vertebral geometric parameters especially height T score can be used for fracture screening.

  13. Vertebral Geometry Parameters Can Predict Fractures

    Directory of Open Access Journals (Sweden)

    P Tofighi

    2007-01-01

    Conclusion: Vertebral fractures are common fractures in postmenopausal women. There was a correlation between verte¬bral height and fractures. Vertebral geometric parameters especially height T score can be used for fracture screening.

  14. Clinical studies of biomarkers in suicide prediction

    OpenAIRE

    Jokinen, Jussi

    2007-01-01

    Suicide is a major clinical problem in psychiatry and suicidal behaviours can be seen as a nosological entity per se. Predicting suicide is difficult due to its low base-rate and the limited specificity of clinical predictors. Prospective biological studies suggest that dysfunctions in the hypothalamo pituitary adrenal (HPA) axis and the serotonergic system have predictive power for suicide in mood disorders. Suicide attempt is the most robust clinical predictor making suici...

  15. Representative parameter of immunostimulatory ginseng polysaccharide to predict radioprotection

    Energy Technology Data Exchange (ETDEWEB)

    Son, Hyeog Jin; Shim, Ji Young; Ahn, Ji Yeon; Yun, Yeon Sook; Song, Jie Young [Korea Institute of Radiological and Medical Sciences, Seoul (Korea, Republic of)

    2008-09-15

    According to the increase in the use of radiotherapy to cancer patients, many approaches have been tried to develop new agents for the protection of surrounding normal tissues. However, it is still few applied in the clinic as a radioprotector. We aim to find a representative parameter for radioprotection to easily predict the activity of in vivo experiment from the results of in vitro screening. The polysaccharide extracted from Panax ginseng was used in this study because the immunostimulator has been regarded as one of the radioprotective agent category and was already reported having a promising radioprotective activity through the increase of hematopoietic cells and the production of several cytokines. Mitogenic activity, AK cells activity and nitric oxide production were monitored for the in vitro immunological assay, and endogenous Colony-Forming Unit (e-CFU) was measured as in vivo radioprotective parameter. The immunological activity was increased by the galactose contents of ginseng polysaccharide dependently. The result of this study suggests that mitogenic activity of splenocytes demonstrated a good correlation with in vivo radioprotective effect, and may be used as a representative parameter to screen the candidates for radioprotector.

  16. Meta-analysis of clinical prediction models

    NARCIS (Netherlands)

    Debray, T.P.A.

    2013-01-01

    The past decades there has been a clear shift from implicit to explicit diagnosis and prognosis. This includes appreciation of clinical -diagnostic and prognostic- prediction models, which is likely to increase with the introduction of fully computerized patient records. Prediction models aim to pro

  17. Singular Parameter Prediction Algorithm for Bistable Neural Systems.

    Science.gov (United States)

    Durand, Dominique M; Jahangiri, Anila

    2010-04-01

    An algorithm is presented to predict the intensity and timing of a singular single stimulus required to switch the state of a bistable system from repetitive activity to a stable point. The algorithm is first tested on a modified Hodgkin-Huxley model to predict the parameters of a stimulus capable of annihilating the spontaneously occurring repetitive action potentials. Elevation of the potassium equilibrium potential causes oscillations in the V, m, h and n parameters and generates periodic activity. Equations describing the time-varying behavior of these parameters can be used to predict the pulse width, coupling interval and intensity of a single anodic pulse applied between two consecutive action potentials to suppress the activity. The algorithm was then applied to predict the singular parameters of quasi-periodic epileptiform activity generated in the hippocampus slice preparation exposed to high-potassium concentrations. The results indicate that a stimulus with the estimated parameters was able to either completely annihilate the action potentials in the HH model or predict the region of unpredictable latencies. Therefore this algorithm is capable a predicting singular parameters accurately when the model is known. In the case of an experimental system where the equations of the system are not known, the algorithm predicted parameters in the range of those observed experimentally. Therefore, the algorithm could reduce significantly the amount of time required to find the singular parameters of experimental bistable systems normally obtained by a systematic exploration of the parameter space. In particular, this algorithm could be useful to predict the singular parameters of quasi periodic epileptiform activity leading to the suppression of this activity if the system is bistable. PMID:21866209

  18. Radiogenomics: predicting clinical normal tissue radiosensitivity

    DEFF Research Database (Denmark)

    Alsner, Jan

    2006-01-01

    of subcutaneous fibrosis in breast cancer patients will be presented and discussed in relation to possible future studies in radiogenomics. One important and necessary basis for future studies is the collection of carefully designed clinical studies with the accrual of very large numbers of patients (the ESTRO......Studies on the genetic basis of normal tissue radiosensitivity, or  'radiogenomics', aims at predicting clinical radiosensitivity and optimize treatment from individual genetic profiles. Several studies have now reported links between variations in certain genes related to the biological response...... to radiation injury and risk of normal tissue morbidity in cancer patients treated with radiotherapy. However, after these initial association studies including few genes, we are still far from being able to predict clinical radiosensitivity on an individual level. Recent data from our own studies on risk...

  19. Tsunami Prediction and Earthquake Parameters Estimation in the Red Sea

    KAUST Repository

    Sawlan, Zaid A

    2012-12-01

    Tsunami concerns have increased in the world after the 2004 Indian Ocean tsunami and the 2011 Tohoku tsunami. Consequently, tsunami models have been developed rapidly in the last few years. One of the advanced tsunami models is the GeoClaw tsunami model introduced by LeVeque (2011). This model is adaptive and consistent. Because of different sources of uncertainties in the model, observations are needed to improve model prediction through a data assimilation framework. Model inputs are earthquake parameters and topography. This thesis introduces a real-time tsunami forecasting method that combines tsunami model with observations using a hybrid ensemble Kalman filter and ensemble Kalman smoother. The filter is used for state prediction while the smoother operates smoothing to estimate the earthquake parameters. This method reduces the error produced by uncertain inputs. In addition, state-parameter EnKF is implemented to estimate earthquake parameters. Although number of observations is small, estimated parameters generates a better tsunami prediction than the model. Methods and results of prediction experiments in the Red Sea are presented and the prospect of developing an operational tsunami prediction system in the Red Sea is discussed.

  20. Clinical prediction rule for nonmelanoma skin cancer

    Directory of Open Access Journals (Sweden)

    John Alexander Nova

    2015-01-01

    Full Text Available Background: Skin cancer is the most frequent neoplasia in the world. Even though ultraviolet radiation is the main cause, established prevention campaigns have not proved to be effective for controlling the incidence of this disease. Objective: To develop clinical prediction rules based on medical consultation and a questionnaire to estimate the risk of developing nonmelanoma skin cancer. Methods: This study was developed in several steps. They were: Identifying risk factors that could be possible predictors of nonmelanoma skin cancer; their clinical validation; developing a prediction rule using logistic regression; and collecting information from 962 patients in a case and control design (481 cases and 481 controls. We developed independent prediction rules for basal cell and squamous cell carcinomas. Finally, we evaluated reliability for each of the variables. Results: The variables that made up the final prediction rule were: Family history of skin cancer, history of outdoor work, age, phototypes 1-3 and the presence of poikiloderma of civatte, actinic keratosis and conjunctivitis in band. Prediction rules specificity was 87% for basal cell carcinomas and 92% for squamous cell carcinomas. Inter- and intra-observer reliability was good except for the conjunctivitis in band variable. Conclusions: The prediction rules let us calculate the individual risk of developing basal cell carcinoma and squamous cell carcinoma. This is an economic easy-to-apply tool that could be useful in primary and secondary prevention of skin cancer.

  1. Solar flare prediction using highly stressed longitudinal magnetic field parameters

    Institute of Scientific and Technical Information of China (English)

    Xin Huang; Hua-Ning Wang

    2013-01-01

    Three new longitudinal magnetic field parameters are extracted from SOHO/MDI magnetograms to characterize properties of the stressed magnetic field in active regions,and their flare productivities are calculated for 1055 active regions.We find that the proposed parameters can be used to distinguish flaring samples from non-flaring samples.Using the long-term accumulated MDI data,we build the solar flare prediction model by using a data mining method.Furthermore,the decision boundary,which is used to divide flaring from non-flaring samples,is determined by the decision tree algorithm.Finally,the performance of the prediction model is evaluated by 10-fold cross validation technology.We conclude that an efficient solar flare prediction model can be built by the proposed longitudinal magnetic field parameters with the data mining method.

  2. Using string invariants for prediction searching for optimal parameters

    Science.gov (United States)

    Bundzel, Marek; Kasanický, Tomáš; Pinčák, Richard

    2016-02-01

    We have developed a novel prediction method based on string invariants. The method does not require learning but a small set of parameters must be set to achieve optimal performance. We have implemented an evolutionary algorithm for the parametric optimization. We have tested the performance of the method on artificial and real world data and compared the performance to statistical methods and to a number of artificial intelligence methods. We have used data and the results of a prediction competition as a benchmark. The results show that the method performs well in single step prediction but the method's performance for multiple step prediction needs to be improved. The method works well for a wide range of parameters.

  3. Parameter variations in prediction skill optimization at ECMWF

    Science.gov (United States)

    Ollinaho, P.; Bechtold, P.; Leutbecher, M.; Laine, M.; Solonen, A.; Haario, H.; Järvinen, H.

    2013-11-01

    Algorithmic numerical weather prediction (NWP) skill optimization has been tested using the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). We report the results of initial experimentation using importance sampling based on model parameter estimation methodology targeted for ensemble prediction systems, called the ensemble prediction and parameter estimation system (EPPES). The same methodology was earlier proven to be a viable concept in low-order ordinary differential equation systems, and in large-scale atmospheric general circulation models (ECHAM5). Here we show that prediction skill optimization is possible even in the context of a system that is (i) of very high dimensionality, and (ii) carefully tuned to very high skill. We concentrate on four closure parameters related to the parameterizations of sub-grid scale physical processes of convection and formation of convective precipitation. We launch standard ensembles of medium-range predictions such that each member uses different values of the four parameters, and make sequential statistical inferences about the parameter values. Our target criterion is the squared forecast error of the 500 hPa geopotential height at day three and day ten. The EPPES methodology is able to converge towards closure parameter values that optimize the target criterion. Therefore, we conclude that estimation and cost function-based tuning of low-dimensional static model parameters is possible despite the very high dimensional state space, as well as the presence of stochastic noise due to initial state and physical tendency perturbations. The remaining question before EPPES can be considered as a generally applicable tool in model development is the correct formulation of the target criterion. The one used here is, in our view, very selective. Considering the multi-faceted question of improving forecast model performance, a more general target criterion should be developed

  4. PREDICTION OF LEAF SPRING PARAMETERS USING ARTIFICIAL NEURAL NETWORKS

    OpenAIRE

    Dr.D.V.V.KRISHNA PRASAD; J.P.KARTHIK

    2013-01-01

    In this paper an attempt is made to predict the optimum design parameters using artificial neural networks. For this static and dynamic analysis on various leaf spring configuration is carried out by ANSYS and is used as training data for neural network. Training data includes cross section of the leaf, load on the leaf spring, stresses, displacement and natural frequencies. By creating a network using thickness and width of the leaf, load on the leaf spring as input parameters and stresses, ...

  5. A THEORETIC METHOD TO PREDICT POLYMER SOLUBILITY PARAMETERS

    Institute of Scientific and Technical Information of China (English)

    Qing Ji; Bao-fu Qiao; De-lu Zhao

    2007-01-01

    A partition function and a complete thermodynamic description for pure polymer fluids have been investigated based on a self-avoid-walk lattice model.Caused by the introduction of Gibbs distribution into the Flory-Huggins theory.the partition function and the thermodynamic description depicted their dependence on temperature well.In the present study,we applied the theory to calculate polymer solubility parameters.The polymer solubility parameters predicted by our theory are well consistent with the experiment values.

  6. Prediction of Electrochemical Machining Process Parameters using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Hoda Hosny Abuzied

    2012-01-01

    Full Text Available Electrochemical machining (ECM is a non-traditional machining process used mainly to cut hard or difficult to cut metals, where the application of a more traditional process is not convenient. It offers several special advantages including higher machining rate, better precision and control, and a wider range of materials that can be machined. A suitable selection of machining parameters for the ECM process relies heavily on the operator’s technologies and experience because of their numerous and diverse range. Machining parameters provided by the machine tool builder cannot meet the operator’s requirements. So, artificial neural networks were introduced as an efficient approach to predict the values of resulting surface roughness and material removal rate. Many researchers usedartificial neural networks (ANN in improvement of ECM process and also in other nontraditional machining processes as well be seen in later sections. The present study is, initiated to predict values of some of resulting process parameters such as metal removal rate(MRR, and surface roughness (Ra using artificial neural networks based on variation of certain predominant parameters of an electrochemical broaching process such as applied voltage, feed rate and electrolyte flow rate. ANN was found to be an efficient approach as it reduced time & effort required to predict material removal rate & surface roughness if they were found experimentally using trial & error method. To validate the proposed approach the predicted values of surface roughness and material removal rate were compared with a previously obtained ones from the experimental work.

  7. Nondestructive prediction of pork freshness parameters using multispectral scattering images

    Science.gov (United States)

    Tang, Xiuying; Li, Cuiling; Peng, Yankun; Chao, Kuanglin; Wang, Mingwu

    2012-05-01

    Optical technology is an important and immerging technology for non-destructive and rapid detection of pork freshness. This paper studied on the possibility of using multispectral imaging technique and scattering characteristics to predict the freshness parameters of pork meat. The pork freshness parameters selected for prediction included total volatile basic nitrogen (TVB-N), color parameters (L *, a *, b *), and pH value. Multispectral scattering images were obtained from pork sample surface by a multispectral imaging system developed by ourselves; they were acquired at the selected narrow wavebands whose center wavelengths were 517,550, 560, 580, 600, 760, 810 and 910nm. In order to extract scattering characteristics from multispectral images at multiple wavelengths, a Lorentzian distribution (LD) function with four parameters (a: scattering asymptotic value; b: scattering peak; c: scattering width; d: scattering slope) was used to fit the scattering curves at the selected wavelengths. The results show that the multispectral imaging technique combined with scattering characteristics is promising for predicting the freshness parameters of pork meat.

  8. Prediction of interest rate using CKLS model with stochastic parameters

    Energy Technology Data Exchange (ETDEWEB)

    Ying, Khor Chia [Faculty of Computing and Informatics, Multimedia University, Jalan Multimedia, 63100 Cyberjaya, Selangor (Malaysia); Hin, Pooi Ah [Sunway University Business School, No. 5, Jalan Universiti, Bandar Sunway, 47500 Subang Jaya, Selangor (Malaysia)

    2014-06-19

    The Chan, Karolyi, Longstaff and Sanders (CKLS) model is a popular one-factor model for describing the spot interest rates. In this paper, the four parameters in the CKLS model are regarded as stochastic. The parameter vector φ{sup (j)} of four parameters at the (J+n)-th time point is estimated by the j-th window which is defined as the set consisting of the observed interest rates at the j′-th time point where j≤j′≤j+n. To model the variation of φ{sup (j)}, we assume that φ{sup (j)} depends on φ{sup (j−m)}, φ{sup (j−m+1)},…, φ{sup (j−1)} and the interest rate r{sub j+n} at the (j+n)-th time point via a four-dimensional conditional distribution which is derived from a [4(m+1)+1]-dimensional power-normal distribution. Treating the (j+n)-th time point as the present time point, we find a prediction interval for the future value r{sub j+n+1} of the interest rate at the next time point when the value r{sub j+n} of the interest rate is given. From the above four-dimensional conditional distribution, we also find a prediction interval for the future interest rate r{sub j+n+d} at the next d-th (d≥2) time point. The prediction intervals based on the CKLS model with stochastic parameters are found to have better ability of covering the observed future interest rates when compared with those based on the model with fixed parameters.

  9. Different Vocal Parameters Predict Perceptions of Dominance and Attractiveness.

    Science.gov (United States)

    Hodges-Simeon, Carolyn R; Gaulin, Steven J C; Puts, David A

    2010-12-01

    Low mean fundamental frequency (F(0)) in men's voices has been found to positively influence perceptions of dominance by men and attractiveness by women using standardized speech. Using natural speech obtained during an ecologically valid social interaction, we examined relationships between multiple vocal parameters and dominance and attractiveness judgments. Male voices from an unscripted dating game were judged by men for physical and social dominance and by women in fertile and non-fertile menstrual cycle phases for desirability in short-term and long-term relationships. Five vocal parameters were analyzed: mean F(0) (an acoustic correlate of vocal fold size), F(0) variation, intensity (loudness), utterance duration, and formant dispersion (D(f), an acoustic correlate of vocal tract length). Parallel but separate ratings of speech transcripts served as controls for content. Multiple regression analyses were used to examine the independent contributions of each of the predictors. Physical dominance was predicted by low F(0) variation and physically dominant word content. Social dominance was predicted only by socially dominant word content. Ratings of attractiveness by women were predicted by low mean F(0), low D(f), high intensity, and attractive word content across cycle phase and mating context. Low D(f) was perceived as attractive by fertile-phase women only. We hypothesize that competitors and potential mates may attend more strongly to different components of men's voices because of the different types of information these vocal parameters provide.

  10. Clinical predictive factors of pathologic tumor response

    Energy Technology Data Exchange (ETDEWEB)

    Choi, Chi Hwan; Kim, Won Dong; Lee, Sang Jeon; Park, Woo Yoon [Chungbuk National University College of Medicine, Cheongju (Korea, Republic of)

    2012-09-15

    The aim of this study was to identify clinical predictive factors for tumor response after preoperative chemoradiotherapy (CRT) in rectal cancer. The study involved 51 patients who underwent preoperative CRT followed by surgery between January 2005 and February 2012. Radiotherapy was delivered to the whole pelvis at a dose of 45 Gy in 25 fractions, followed by a boost of 5.4 Gy in 3 fractions to the primary tumor with 5 fractions per week. Three different chemotherapy regimens were used. Tumor responses to preoperative CRT were assessed in terms of tumor downstaging and pathologic complete response (ypCR). Statistical analyses were performed to identify clinical factors associated with pathologic tumor response. Tumor downstaging was observed in 28 patients (54.9%), whereas ypCR was observed in 6 patients (11.8%). Multivariate analysis found that predictors of downstaging was pretreatment relative lymphocyte count (p = 0.023) and that none of clinical factors was significantly associated with ypCR. Pretreatment relative lymphocyte count (%) has a significant impact on the pathologic tumor response (tumor downstaging) after preoperative CRT for locally advanced rectal cancer. Enhancement of lymphocyte-mediated immune reactions may improve the effect of preoperative CRT for rectal cancer.

  11. Researches on High Accuracy Prediction Methods of Earth Orientation Parameters

    Science.gov (United States)

    Xu, X. Q.

    2015-09-01

    The Earth rotation reflects the coupling process among the solid Earth, atmosphere, oceans, mantle, and core of the Earth on multiple spatial and temporal scales. The Earth rotation can be described by the Earth's orientation parameters, which are abbreviated as EOP (mainly including two polar motion components PM_X and PM_Y, and variation in the length of day ΔLOD). The EOP is crucial in the transformation between the terrestrial and celestial reference systems, and has important applications in many areas such as the deep space exploration, satellite precise orbit determination, and astrogeodynamics. However, the EOP products obtained by the space geodetic technologies generally delay by several days to two weeks. The growing demands for modern space navigation make high-accuracy EOP prediction be a worthy topic. This thesis is composed of the following three aspects, for the purpose of improving the EOP forecast accuracy. (1) We analyze the relation between the length of the basic data series and the EOP forecast accuracy, and compare the EOP prediction accuracy for the linear autoregressive (AR) model and the nonlinear artificial neural network (ANN) method by performing the least squares (LS) extrapolations. The results show that the high precision forecast of EOP can be realized by appropriate selection of the basic data series length according to the required time span of EOP prediction: for short-term prediction, the basic data series should be shorter, while for the long-term prediction, the series should be longer. The analysis also showed that the LS+AR model is more suitable for the short-term forecasts, while the LS+ANN model shows the advantages in the medium- and long-term forecasts. (2) We develop for the first time a new method which combines the autoregressive model and Kalman filter (AR+Kalman) in short-term EOP prediction. The equations of observation and state are established using the EOP series and the autoregressive coefficients

  12. Using neural networks for prediction of nuclear parameters

    International Nuclear Information System (INIS)

    Dating from 1943, the earliest work on artificial neural networks (ANN), when Warren Mc Cullock and Walter Pitts developed a study on the behavior of the biological neuron, with the goal of creating a mathematical model. Some other work was done until after the 80 witnessed an explosion of interest in ANNs, mainly due to advances in technology, especially microelectronics. Because ANNs are able to solve many problems such as approximation, classification, categorization, prediction and others, they have numerous applications in various areas, including nuclear. Nodal method is adopted as a tool for analyzing core parameters such as boron concentration and pin power peaks for pressurized water reactors. However, this method is extremely slow when it is necessary to perform various core evaluations, for example core reloading optimization. To overcome this difficulty, in this paper a model of Multi-layer Perceptron (MLP) artificial neural network type backpropagation will be trained to predict these values. The main objective of this work is the development of Multi-layer Perceptron (MLP) artificial neural network capable to predict, in very short time, with good accuracy, two important parameters used in the core reloading problem - Boron Concentration and Power Peaking Factor. For the training of the neural networks are provided loading patterns and nuclear data used in cycle 19 of Angra 1 nuclear power plant. Three models of networks are constructed using the same input data and providing the following outputs: 1- Boron Concentration and Power Peaking Factor, 2 - Boron Concentration and 3 - Power Peaking Factor. (author)

  13. Using neural networks for prediction of nuclear parameters

    Energy Technology Data Exchange (ETDEWEB)

    Pereira Filho, Leonidas; Souto, Kelling Cabral, E-mail: leonidasmilenium@hotmail.com, E-mail: kcsouto@bol.com.br [Instituto Federal de Educacao, Ciencia e Tecnologia do Rio de Janeiro (IFRJ), Rio de Janeiro, RJ (Brazil); Machado, Marcelo Dornellas, E-mail: dornemd@eletronuclear.gov.br [Eletrobras Termonuclear S.A. (GCN.T/ELETRONUCLEAR), Rio de Janeiro, RJ (Brazil). Gerencia de Combustivel Nuclear

    2013-07-01

    Dating from 1943, the earliest work on artificial neural networks (ANN), when Warren Mc Cullock and Walter Pitts developed a study on the behavior of the biological neuron, with the goal of creating a mathematical model. Some other work was done until after the 80 witnessed an explosion of interest in ANNs, mainly due to advances in technology, especially microelectronics. Because ANNs are able to solve many problems such as approximation, classification, categorization, prediction and others, they have numerous applications in various areas, including nuclear. Nodal method is adopted as a tool for analyzing core parameters such as boron concentration and pin power peaks for pressurized water reactors. However, this method is extremely slow when it is necessary to perform various core evaluations, for example core reloading optimization. To overcome this difficulty, in this paper a model of Multi-layer Perceptron (MLP) artificial neural network type backpropagation will be trained to predict these values. The main objective of this work is the development of Multi-layer Perceptron (MLP) artificial neural network capable to predict, in very short time, with good accuracy, two important parameters used in the core reloading problem - Boron Concentration and Power Peaking Factor. For the training of the neural networks are provided loading patterns and nuclear data used in cycle 19 of Angra 1 nuclear power plant. Three models of networks are constructed using the same input data and providing the following outputs: 1- Boron Concentration and Power Peaking Factor, 2 - Boron Concentration and 3 - Power Peaking Factor. (author)

  14. Clinical parameters associated with periodontitis in untreated persons

    NARCIS (Netherlands)

    Lembariti, BS; Van't Hof, MA; Pilot, T; Van Palenstein-Helderman, WH

    1997-01-01

    The purpose of this study was to investigate the relationship between clinical parameters and periodontitis in a population receiving no regular prophylactic dental care. From a sample of 164 adult rural and urban Tanzanian subjects aged between 30 and 44 years, 16% were identified with periodontiti

  15. Clinical and blood gasometric parameters during Vaquejada competition

    Directory of Open Access Journals (Sweden)

    Silvana S.B. Arruda

    2015-11-01

    Full Text Available ABSTRACT: Clinical and complementary analysis are good alternatives to evaluate physiological demand in performance horses. The aim of this study was to assess whether the physical effort variation of the three-day Vaquejada competition (a Brazilian form of bullfighting reflected in clinical and blood gasometric changes. During the competition eight sprints have been performed on the first day (D1, eight on the second (D2 and three on the last one (D3. Ten horses were evaluated by checking heart and respiratory rates and collecting blood samples for use in portable chemistry analyzer. Through that, it was assessed potential of hydrogen ion (pH, carbon dioxide pressure (pCO2, bicarbonate (HCO3- and titratable base concentration (cBase. Evaluations were carried with resting of at least twenty hours, before physical activity (D0, as control parameter, and up to thirty minutes after each sprint. Clinical parameters have increased on D1, D2 and D3, when compared to D0, which demonstrated the increased demand for substrate and oxygen to the cells.. Blood gasometric trial showed reductions of all variables, most marked between D1 and D2. It was verified less alteration of all clinical and blood gasometric parameters in D3 against D0. We concluded that the change effort between days of competition influenced the clinical and blood gas parameters, demonstrating appropriate physiological response. The data were presented as mean and standard error of the mean (mean ± SEM obtained in different days. Normality was confirmed by the Kolmogorov-Sminov test and data were compared by one-way ANOVA, followed by post-test Holm-Sidak (GraphPad Prism 2.6 for Windows, GraphPad Software, San Diego, CA, USA. P≤0.05 was considered as statistically significant.

  16. Predicting Endometrium Receptivity with Parameters of Spiral Artery Blood Flow

    Institute of Scientific and Technical Information of China (English)

    GONG Xuehao; LI Quanshui; ZHANG Qingping; ZHU Guijin

    2005-01-01

    Summary: In order To evaluate whether the parameters of spiral artery blood flow, as measured by transvaginal color Doppler, may be used to assess endometrium receptivity prior to embryo transfer (ET), a retrospective study of 94 infertile women who had undergone ART treatments with different outcomes (pregnant or nonpregnant) was done. Subendometrial blood flow was evaluated. The resistance index (RI), systolic/diastolic ratio (S/D) and pulsatility index (PI) were significantly lower in those who achieved pregnancy as compared with those who did not: 0.62±0.04 vs 0.68±0.04 (P<0.001), 2.66±0.33 vs 3.19±0.39 (P<0.01) and 1.15±0.17 vs 1.34±0.22 (P<0.05), respectively. Furthermore, when RI>0.72, PI>1.6, and S/D>3.6, no pregnancy occurred. These data suggest that the parameters of spiral artery blood flow could be used as a new assay in predicting endometrial receptivity before ET.

  17. Use of Feedback in Clinical Prediction

    Science.gov (United States)

    Schroeder, Harold E.

    1972-01-01

    Results indicated that predictive accuracy is greater when feedback is applied to the basis for the prediction than when applied to gut" impressions. Judges forming hypotheses were also able to learn from experience. (Author)

  18. Toward the Real-Time Tsunami Parameters Prediction

    Science.gov (United States)

    Lavrentyev, Mikhail; Romanenko, Alexey; Marchuk, Andrey

    2013-04-01

    Today, a wide well-developed system of deep ocean tsunami detectors operates over the Pacific. Direct measurements of tsunami-wave time series are available. However, tsunami-warning systems fail to predict basic parameters of tsunami waves on time. Dozens examples could be provided. In our view, the lack of computational power is the main reason of these failures. At the same time, modern computer technologies such as, GPU (graphic processing unit) and FPGA (field programmable gates array), can dramatically improve data processing performance, which may enhance timely tsunami-warning prediction. Thus, it is possible to address the challenge of real-time tsunami forecasting for selected geo regions. We propose to use three new techniques in the existing tsunami warning systems to achieve real-time calculation of tsunami wave parameters. First of all, measurement system (DART buoys location, e.g.) should be optimized (both in terms of wave arriving time and amplitude parameter). The corresponding software application exists today and is ready for use [1]. We consider the example of the coastal line of Japan. Numerical tests show that optimal installation of only 4 DART buoys (accounting the existing sea bed cable) will reduce the tsunami wave detection time to only 10 min after an underwater earthquake. Secondly, as was shown by this paper authors, the use of GPU/FPGA technologies accelerates the execution of the MOST (method of splitting tsunami) code by 100 times [2]. Therefore, tsunami wave propagation over the ocean area 2000*2000 km (wave propagation simulation: time step 10 sec, recording each 4th spatial point and 4th time step) could be calculated at: 3 sec with 4' mesh 50 sec with 1' mesh 5 min with 0.5' mesh The algorithm to switch from coarse mesh to the fine grain one is also available. Finally, we propose the new algorithm for tsunami source parameters determination by real-time processing the time series, obtained at DART. It is possible to approximate

  19. Predicting Fundamental Stellar Parameters From Photometric Light Curves

    Science.gov (United States)

    Miller, Adam; Richards, J.; Bloom, J. S.; a larger Team

    2014-01-01

    We present a new machine-learning-based framework for the prediction of the fundamental stellar parameters, Teff, log g, and [Fe/H], based on the photometric light curves of variable stellar sources. The method was developed following a systematic spectroscopic survey of stellar variability. Variable sources were selected from repeated Sloan Digital Sky Survey (SDSS) observations of Stripe 82, and spectroscopic observations were obtained with Hectospec on the 6.5-m Multi-Mirror Telescope. In sum, spectra were obtained for ~9000 stellar variables (including ~3000 from the SDSS archive), for which we measured Teff, log g, and [Fe/H] using the Segue Stellar Parameters Pipeline (SSPP). Examining the full sample of ~67k variables in Stripe 82, we show that the vast majority of photometric variables are consistent with main-sequence stars, even after restricting the search to high galactic latitudes. From the spectroscopic sample we confirm that most of these stellar variables are G and K dwarfs, though there is a bias in the output of the SSPP that prevents the identification of M type variables. We are unable to identify the dominant source of variability for these stars, but eclipsing systems and/or star spots are the most likely explanation. We develop a machine-learning model that can determine Teff, log g, and [Fe/H] without obtaining a spectrum. Instead, the random-forest-regression model uses SDSS color information and light-curve features to infer stellar properties. We detail how the feature set is pruned and the model is optimized to produce final predictions of Teff, log g, and [Fe/H] with a typical scatter of 165 K, 0.42 dex, and 0.33 dex, respectively. We further show that for the subset of variables with at least 50 observations in the g band the typical scatter reduces to 75 K, 0.19 dex, and 0.16 dex, respectively. We consider these results an important step on the path to the efficient and optimal extraction of information from future time

  20. Functional clinical typology of the foot and kinematic gait parameters

    Directory of Open Access Journals (Sweden)

    Jitka Marenčáková

    2016-06-01

    Full Text Available Background: The foot plays a key role in a standing posture, walking and running performance. Changes in its structure or function may alter upper segments of kinematic chain which can lead to formation of musculoskeletal disorders. Although functional clinical typology provides a complex view of foot kinesiology there is a lack of knowledge and evidence about influences of different foot types on human gait. Objective: The aim of the study was to analyse differences of kinematic gait parameters of lower extremity joints and pelvis between functional clinical foot types in healthy young men. Methods: Three-dimensional kinematic analysis by the Vicon Motion Capture MX System device in synchronization with 2 Kistler force platforms was used to obtain kinematic data from 18 healthy men (mean age 23.2 ± 1.9 years. The functional clinical foot type was clinically examined and sorted into 3 basic foot type groups - forefoot varus (FFvar, rearfoot varus (RFvar and forefoot valgus (FFvalg. Peak angular values and range of an angular displacement in all of three movement planes were analysed for pelvis, hip, knee and ankle joint. For statistical analysis of kinematic gait parameters differences between foot types Mann Whitney U test at a statistical significance level p < .05 and Cohen's coefficient d for effect size were used. Results: This study showed that functional clinical foot type can affect kinematic parameters of gait in the joints of the lower limb and pelvis. Significant differences were presented in the FFvar in comparison with other two foot type groups with middle and high size of effect. The most alterations were observed in pelvis area and in a sagittal plane of movement. Nevertheless, significant differences between FFvalg and RFvar foot types were not noticed. Conclusions: Functional clinical foot typology provides one of the possible methods to describe foot structure and function. Our results showed that foot type could

  1. Combining clinical variables to optimize prediction of antidepressant treatment outcomes.

    Science.gov (United States)

    Iniesta, Raquel; Malki, Karim; Maier, Wolfgang; Rietschel, Marcella; Mors, Ole; Hauser, Joanna; Henigsberg, Neven; Dernovsek, Mojca Zvezdana; Souery, Daniel; Stahl, Daniel; Dobson, Richard; Aitchison, Katherine J; Farmer, Anne; Lewis, Cathryn M; McGuffin, Peter; Uher, Rudolf

    2016-07-01

    The outcome of treatment with antidepressants varies markedly across people with the same diagnosis. A clinically significant prediction of outcomes could spare the frustration of trial and error approach and improve the outcomes of major depressive disorder through individualized treatment selection. It is likely that a combination of multiple predictors is needed to achieve such prediction. We used elastic net regularized regression to optimize prediction of symptom improvement and remission during treatment with escitalopram or nortriptyline and to identify contributing predictors from a range of demographic and clinical variables in 793 adults with major depressive disorder. A combination of demographic and clinical variables, with strong contributions from symptoms of depressed mood, reduced interest, decreased activity, indecisiveness, pessimism and anxiety significantly predicted treatment outcomes, explaining 5-10% of variance in symptom improvement with escitalopram. Similar combinations of variables predicted remission with area under the curve 0.72, explaining approximately 15% of variance (pseudo R(2)) in who achieves remission, with strong contributions from body mass index, appetite, interest-activity symptom dimension and anxious-somatizing depression subtype. Escitalopram-specific outcome prediction was more accurate than generic outcome prediction, and reached effect sizes that were near or above a previously established benchmark for clinical significance. Outcome prediction on the nortriptyline arm did not significantly differ from chance. These results suggest that easily obtained demographic and clinical variables can predict therapeutic response to escitalopram with clinically meaningful accuracy, suggesting a potential for individualized prescription of this antidepressant drug. PMID:27089522

  2. Using Kalman Filtering to Predict Time-Varying Parameters in a Model Predicting Baroreflex Regulation During Head-Up Tilt.

    Science.gov (United States)

    Matzuka, Brett; Mehlsen, Jesper; Tran, Hien; Olufsen, Mette Sofie

    2015-08-01

    The cardiovascular control system is continuously engaged to maintain homeostasis, but it is known to fail in a large cohort of patients suffering from orthostatic intolerance. Numerous clinical studies have been put forward to understand how the system fails, yet noninvasive clinical data are sparse, typical studies only include measurements of heart rate and blood pressure, as a result it is difficult to determine what mechanisms that are impaired. It is known, that blood pressure regulation is mediated by changes in heart rate, vascular resistance, cardiac contractility, and a number of other factors. Given that numerous factors contribute to changing these quantities, it is difficult to devise a physiological model describing how they change in time. One way is to build a model that allows these controlled quantities to change and to compare dynamics between subject groups. To do so, it requires more knowledge of how these quantities change for healthy subjects. This study compares two methods predicting time-varying changes in cardiac contractility and vascular resistance during head-up tilt. Similar to the study by Williams et al. [51], the first method uses piecewise linear splines, while the second uses the ensemble transform Kalman filter (ETKF) [1], [11], [12], [33]. In addition, we show that the delayed rejection adaptive Metropolis (DRAM) algorithm can be used for predicting parameter uncertainties within the spline methodology, which is compared with the variability obtained with the ETKF. While the spline method is easier to set up, this study shows that the ETKF has a significantly shorter computational time. Moreover, while uncertainty of predictions can be augmented to spline predictions using DRAM, these are readily available with the ETKF. PMID:25769142

  3. Nonlinear Time Series Prediction Using LS-SVM with Chaotic Mutation Evolutionary Programming for Parameter Optimization

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Nonlinear time series prediction is studied by using an improved least squares support vector machine (LSSVM) regression based on chaotic mutation evolutionary programming (CMEP) approach for parameter optimization.We analyze how the prediction error varies with different parameters (σ, γ) in LS-SVM. In order to select appropriate parameters for the prediction model, we employ CMEP algorithm. Finally, Nasdaq stock data are predicted by using this LS-SVM regression based on CMEP, and satisfactory results are obtained.

  4. A clinical prediction rule for histological chorioamnionitis in preterm newborns.

    Directory of Open Access Journals (Sweden)

    Jasper V Been

    Full Text Available BACKGROUND: Histological chorioamnionitis (HC is an intrauterine inflammatory process highly associated with preterm birth and adverse neonatal outcome. HC is often clinically silent and diagnosed postnatally by placental histology. Earlier identification could facilitate treatment individualisation to improve outcome in preterm newborns. AIM: Develop a clinical prediction rule at birth for HC and HC with fetal involvement (HCF in preterm newborns. METHODS: Clinical data and placental pathology were obtained from singleton preterm newborns (gestational age ≤ 32.0 weeks born at Erasmus UMC Rotterdam from 2001 to 2003 (derivation cohort; n = 216 or Máxima MC Veldhoven from 2009 to 2010 (validation cohort; n = 206. HC and HCF prediction rules were developed with preference for high sensitivity using clinical variables available at birth. RESULTS: HC and HCF were present in 39% and 24% in the derivation cohort and in 44% and 22% in the validation cohort, respectively. HC was predicted with 87% accuracy, yielding an area under ROC curve of 0.95 (95%CI = 0.92-0.98, a positive predictive value of 80% (95%CI = 74-84%, and a negative predictive value of 93% (95%CI = 88-96%. Corresponding figures for HCF were: accuracy 83%, area under ROC curve 0.92 (95%CI = 0.88-0.96, positive predictive value 59% (95%CI = 52-62%, and negative predictive value 97% (95%CI = 93-99%. External validation expectedly resulted in some loss of test performance, preferentially affecting positive predictive rather than negative predictive values. CONCLUSION: Using a clinical prediction rule composed of clinical variables available at birth, HC and HCF could be predicted with good test characteristics in preterm newborns. Further studies should evaluate the clinical value of these rules to guide early treatment individualisation.

  5. Pharmacogenetics : the science of predictive clinical pharmacology

    OpenAIRE

    Fenech, Anthony G; Grech, Godfrey

    2014-01-01

    The study of pharmacogenetics has expanded from what were initially casual family-based clinical drug response observations, to a fully-fledged science with direct therapeutic applications, all within a time-span of less than 60 years. A wide spectrum of polymorphisms, located within several genes, are now recognised to influence the pharmacokinetics and pharmacodynamics of the majority of drugs within our therapeutic armamentarium. This information forms the basis for the new development of ...

  6. Clinical refinement of the automatic lung parameter estimator (ALPE).

    Science.gov (United States)

    Thomsen, Lars P; Karbing, Dan S; Smith, Bram W; Murley, David; Weinreich, Ulla M; Kjærgaard, Søren; Toft, Egon; Thorgaard, Per; Andreassen, Steen; Rees, Stephen E

    2013-06-01

    The automatic lung parameter estimator (ALPE) method was developed in 2002 for bedside estimation of pulmonary gas exchange using step changes in inspired oxygen fraction (FIO₂). Since then a number of studies have been conducted indicating the potential for clinical application and necessitating systems evolution to match clinical application. This paper describes and evaluates the evolution of the ALPE method from a research implementation (ALPE1) to two commercial implementations (ALPE2 and ALPE3). A need for dedicated implementations of the ALPE method was identified: one for spontaneously breathing (non-mechanically ventilated) patients (ALPE2) and one for mechanically ventilated patients (ALPE3). For these two implementations, design issues relating to usability and automation are described including the mixing of gasses to achieve FIO₂ levels, and the automatic selection of FIO₂. For ALPE2, these improvements are evaluated against patients studied using the system. The major result is the evolution of the ALPE method into two dedicated implementations, namely ALPE2 and ALPE3. For ALPE2, the usability and automation of FIO₂ selection has been evaluated in spontaneously breathing patients showing that variability of gas delivery is 0.3 % (standard deviation) in 1,332 breaths from 20 patients. Also for ALPE2, the automated FIO2 selection method was successfully applied in 287 patient cases, taking 7.2 ± 2.4 min and was shown to be safe with only one patient having SpO₂ < 86 % when the clinician disabled the alarms. The ALPE method has evolved into two practical, usable systems targeted at clinical application, namely ALPE2 for spontaneously breathing patients and ALPE3 for mechanically ventilated patients. These systems may promote the exploration of the use of more detailed descriptions of pulmonary gas exchange in clinical practice.

  7. Predicting hospital-acquired infections by scoring system with simple parameters.

    Directory of Open Access Journals (Sweden)

    Ying-Jui Chang

    Full Text Available BACKGROUND: Hospital-acquired infections (HAI are associated with increased attributable morbidity, mortality, prolonged hospitalization, and economic costs. A simple, reliable prediction model for HAI has great clinical relevance. The objective of this study is to develop a scoring system to predict HAI that was derived from Logistic Regression (LR and validated by Artificial Neural Networks (ANN simultaneously. METHODOLOGY/PRINCIPAL FINDINGS: A total of 476 patients from all the 806 HAI inpatients were included for the study between 2004 and 2005. A sample of 1,376 non-HAI inpatients was randomly drawn from all the admitted patients in the same period of time as the control group. External validation of 2,500 patients was abstracted from another academic teaching center. Sixteen variables were extracted from the Electronic Health Records (EHR and fed into ANN and LR models. With stepwise selection, the following seven variables were identified by LR models as statistically significant: Foley catheterization, central venous catheterization, arterial line, nasogastric tube, hemodialysis, stress ulcer prophylaxes and systemic glucocorticosteroids. Both ANN and LR models displayed excellent discrimination (area under the receiver operating characteristic curve [AUC]: 0.964 versus 0.969, p = 0.507 to identify infection in internal validation. During external validation, high AUC was obtained from both models (AUC: 0.850 versus 0.870, p = 0.447. The scoring system also performed extremely well in the internal (AUC: 0.965 and external (AUC: 0.871 validations. CONCLUSIONS: We developed a scoring system to predict HAI with simple parameters validated with ANN and LR models. Armed with this scoring system, infectious disease specialists can more efficiently identify patients at high risk for HAI during hospitalization. Further, using parameters either by observation of medical devices used or data obtained from EHR also provided good prediction

  8. Evaluation of measurement parameters in clinical cerebral MR angiography

    International Nuclear Information System (INIS)

    A three-dimensional MR angiography technique was developed in patients and volunteers that can produce clinically useful studies of the cerebral vasculature with multiple views possible from a single data set acquisition. A low-flip angle, three-dimensional fast imaging with steady precessing sequence was found to provide the optimal vessel/soft-tissue contrast related to the tissues' relaxation parameters and inflow. The inflowing unsaturated spins and vessel orientation made an axial acquisition most effective. The flow-related phase dispersion could be largelly corrected with the appropriate orientation, strength, order, and combination of refocusing gradients with the shortest possible echo times. Reduced voxel size also affected the phase dispersion due to motion and field inhomogeneities. Postprocessing yielded projection images of vessels throughout the three-dimensional volume

  9. Translating biological parameters into clinically useful diagnostic tests.

    Science.gov (United States)

    Arfken, Cynthia L; Carney, Stuart; Boutros, Nash N

    2009-08-01

    Psychiatry has lagged behind other specialties in developing diagnostic laboratory tests for the purpose of confirming or ruling out a diagnosis. Biological research into the pathophysiology of psychiatric disorders has, however, yielded some highly replicable abnormalities that have the potential for development into clinically useful diagnostic tests. To achieve this goal, a process for systematic translation must be developed and implemented. Building on our previous work, we review a proposed process using four clearly defined steps. We conclude that biological parameters currently face challenges in their pathways to becoming diagnostic tests because of both the premature release and premature abandonment of tests. Attention to a systematic translation process aided by these principles may help to avoid these problems.

  10. Nutritional screening: control of clinical undernutrition with analytical parameters

    Directory of Open Access Journals (Sweden)

    José Ignacio de Ulíbarri Pérez

    2014-04-01

    Full Text Available Objective: To update the system for nutritional screening. The high prevalence of nutritional unstability that causes the Clinical Undernutrition (CU, especially within the hospitals and assisted residencies, makes it necessary to use screening tools for the constant control of undernutrition to combat it during its development. CU is not so much due to a nutritional deficiency but to the illness and its treatments. However, the screening systems currently used are aimed at detecting an already established undernutrition rather than at detecting any nutritional risk that may be present. The metabolic changes of the nutritional status that have a trophopathic effect, can be easily and automatically detected in plasma, which allows to make the necessary changes in treatments that might be too aggressive, as well as to apply nutritional support according to each case. The manual screening systems can detect those somatic changes typical of undernutrition only after many days or weeks, which might be too late. Plasma albumin is a very reliable parameter for nutritional control. A lowered amount of it, due to whatever reason, is a clear sign of a possible deficit as well as of a nutritional risk suffered by the cell way before the somatic signs of undernutrition will become apparent. A fast detection of nutritional risk, anticipating undernutrition, offers prognostic abilities, which makes screening tools based on analytic parameters the most useful, ergonomic, reliable and efficient system for nutritional screening and prognosis in the clinical practice. Conclusion: It is necessary to update some concepts, to leave behind old myths and to choose modern screening systems that have proven to be efficient. This is the only way achieving the dream of controlling CU among ill and vulnerable patients.

  11. Reporting and Methods in Clinical Prediction Research: A Systematic Review

    OpenAIRE

    Bouwmeester, W; Zuithoff, NP; Mallett, S.; Geerlings, MI; Vergouwe, Y.; Steyerberg, EW; Altman, DG; Moons, KG

    2012-01-01

    Editors' Summary Background There are often times in our lives when we would like to be able to predict the future. Is the stock market going to go up, for example, or will it rain tomorrow? Being able predict future health is also important, both to patients and to physicians, and there is an increasing body of published clinicalprediction research.” Diagnostic prediction research investigates the ability of variables or test results to predict the presence or absence of a specific diagnos...

  12. Clinical Prediction Rules for Physical Therapy Interventions: A Systematic Review

    OpenAIRE

    Beneciuk, Jason M.; Bishop, Mark D; George, Steven Z.

    2009-01-01

    Background and Purpose: Clinical prediction rules (CPRs) involving physical therapy interventions have been published recently. The quality of the studies used to develop the CPRs was not previously considered, a fact that has potential implications for clinical applications and future research. The purpose of this systematic review was to determine the quality of published CPRs developed for physical therapy interventions.

  13. Predictive data mining in clinical medicine: Current issues and guidelines

    OpenAIRE

    Bellazzi, Riccado; Zupan, Blaz

    2008-01-01

    BACKGROUND: The widespread availability of new computational methods and tools for data analysis and predictive modeling requires medical informatics researchers and practitioners to systematically select the most appropriate strategy to cope with clinical prediction problems. In particular, the collection of methods known as 'data mining' offers methodological and technical solutions to deal with the analysis of medical data and construction of prediction models. A large variety of these met...

  14. BAYESIAN PREDICTION FOR THE TWO-PARAMETER EXPONENTIAL DISTRIBUTION BASED ON TYPE Ⅱ DOUBLY CENSORING

    Institute of Scientific and Technical Information of China (English)

    LiYanling; ZhaoXuanmin; XieWenxian

    2005-01-01

    The two-parameter exponential distribution is proposed to be an underlying model, and prediction bounds for future observations are obtained by using Bayesian approach. Prediction intervals are derived for unobserved lifetimes in one-sample prediction and twosample prediction based on type Ⅱ doubly censored samples. A numerical example is given to illustrate the procedures,prediction intervals are investigated via Monte Carlo method,and the accuracy of prediction intervals is presented.

  15. Trend modelling of wave parameters and application in onboard prediction of ship responses

    DEFF Research Database (Denmark)

    Montazeri, Najmeh; Nielsen, Ulrik Dam; Jensen, J. Juncher

    2015-01-01

    This paper presents a trend analysis for prediction of sea state parameters onboard shipsduring voyages. Given those parameters, a JONSWAP model and also the transfer functions, prediction of wave induced ship responses are thus made. The procedure is tested with full-scale data of an in-service ......This paper presents a trend analysis for prediction of sea state parameters onboard shipsduring voyages. Given those parameters, a JONSWAP model and also the transfer functions, prediction of wave induced ship responses are thus made. The procedure is tested with full-scale data of an in...

  16. Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy

    OpenAIRE

    Jinlin Cao; Ping Yuan; Luming Wang; Yiqing Wang; Honghai Ma; Xiaoshuai Yuan; Wang Lv; Jian Hu

    2016-01-01

    The aim of this study was to construct an effective clinical nomogram for predicting the survival of esophageal cancer patients after esophagectomy. We identified esophageal cancer patients (n = 4,281) who underwent esophagectomy between 1988 and 2007 from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database. Clinically significant parameters for survival were used to construct a nomogram based on Cox regression analyses. The model was validated using bootstrap resamp...

  17. Cervical Vertebral Body's Volume as a New Parameter for Predicting the Skeletal Maturation Stages

    Science.gov (United States)

    Choi, Youn-Kyung; Kim, Jinmi; Maki, Koutaro; Ko, Ching-Chang

    2016-01-01

    This study aimed to determine the correlation between the volumetric parameters derived from the images of the second, third, and fourth cervical vertebrae by using cone beam computed tomography with skeletal maturation stages and to propose a new formula for predicting skeletal maturation by using regression analysis. We obtained the estimation of skeletal maturation levels from hand-wrist radiographs and volume parameters derived from the second, third, and fourth cervical vertebrae bodies from 102 Japanese patients (54 women and 48 men, 5–18 years of age). We performed Pearson's correlation coefficient analysis and simple regression analysis. All volume parameters derived from the second, third, and fourth cervical vertebrae exhibited statistically significant correlations (P < 0.05). The simple regression model with the greatest R-square indicated the fourth-cervical-vertebra volume as an independent variable with a variance inflation factor less than ten. The explanation power was 81.76%. Volumetric parameters of cervical vertebrae using cone beam computed tomography are useful in regression models. The derived regression model has the potential for clinical application as it enables a simple and quantitative analysis to evaluate skeletal maturation level. PMID:27340668

  18. Cervical Vertebral Body’s Volume as a New Parameter for Predicting the Skeletal Maturation Stages

    Directory of Open Access Journals (Sweden)

    Youn-Kyung Choi

    2016-01-01

    Full Text Available This study aimed to determine the correlation between the volumetric parameters derived from the images of the second, third, and fourth cervical vertebrae by using cone beam computed tomography with skeletal maturation stages and to propose a new formula for predicting skeletal maturation by using regression analysis. We obtained the estimation of skeletal maturation levels from hand-wrist radiographs and volume parameters derived from the second, third, and fourth cervical vertebrae bodies from 102 Japanese patients (54 women and 48 men, 5–18 years of age. We performed Pearson’s correlation coefficient analysis and simple regression analysis. All volume parameters derived from the second, third, and fourth cervical vertebrae exhibited statistically significant correlations (P<0.05. The simple regression model with the greatest R-square indicated the fourth-cervical-vertebra volume as an independent variable with a variance inflation factor less than ten. The explanation power was 81.76%. Volumetric parameters of cervical vertebrae using cone beam computed tomography are useful in regression models. The derived regression model has the potential for clinical application as it enables a simple and quantitative analysis to evaluate skeletal maturation level.

  19. Wear prediction on total ankle replacement effect of design parameters

    CERN Document Server

    Saad, Amir Putra Bin Md; Harun, Muhamad Noor; Kadir, Mohammed Rafiq Abdul

    2016-01-01

    This book develops and analyses computational wear simulations of the total ankle replacement for the stance phase of gait cycle. The emphasis is put on the relevant design parameters. The book presents a model consisting of three components; tibial, bearing and talar representing their physiological functions.

  20. Computer programme for prediction steel parameters after heat treatment

    OpenAIRE

    J. Trzaska; L.A Dobrzanski; A. Jagiełło

    2007-01-01

    Purpose: The purpose of this paper is presentation of the computer program for calculating the Continuous Cooling Transformation diagrams for constructional and engineering steels.Design/methodology/approach: The computer program uses the artificial neural networks for prediction steel properties after heat treatment. Input data are chemical composition and austenitizing temperature. Results of calculation consist of temperature of the beginning and the end of transformation...

  1. Different Vocal Parameters Predict Perceptions of Dominance and Attractiveness

    OpenAIRE

    Hodges-Simeon, Carolyn R.; Gaulin, Steven J.; Puts, David A.

    2010-01-01

    Low mean fundamental frequency (F 0) in men’s voices has been found to positively influence perceptions of dominance by men and attractiveness by women using standardized speech. Using natural speech obtained during an ecologically valid social interaction, we examined relationships between multiple vocal parameters and dominance and attractiveness judgments. Male voices from an unscripted dating game were judged by men for physical and social dominance and by women in fert...

  2. A model for estimating body shape biological age based on clinical parameters associated with body composition

    Directory of Open Access Journals (Sweden)

    Bae CY

    2012-12-01

    might be a novel approach to variation in body shape that is due to aging. We assume that our estimation model would be used as an adjunctive measure in easily predicting differences in body shape with the use of clinical parameters that are commonly used to assess the status of obesity in a clinical setting.Keywords: chronological age, body shape, biological age

  3. DYNAMICALLY EVOLVING CLINICAL PRACTICES AND IMPLICATIONS FOR PREDICTING MEDICAL DECISIONS

    Science.gov (United States)

    CHEN, JONATHAN H; GOLDSTEIN, MARY K; ASCH, STEVEN M; ALTMAN, RUSS B

    2015-01-01

    Automatically data-mining clinical practice patterns from electronic health records (EHR) can enable prediction of future practices as a form of clinical decision support (CDS). Our objective is to determine the stability of learned clinical practice patterns over time and what implication this has when using varying longitudinal historical data sources towards predicting future decisions. We trained an association rule engine for clinical orders (e.g., labs, imaging, medications) using structured inpatient data from a tertiary academic hospital. Comparing top order associations per admission diagnosis from training data in 2009 vs. 2012, we find practice variability from unstable diagnoses with rank biased overlap (RBO)0.6. Predicting admission orders for future (2013) patients with associations trained on recent (2012) vs. older (2009) data improved accuracy evaluated by area under the receiver operating characteristic curve (ROC-AUC) 0.89 to 0.92, precision at ten (positive predictive value of the top ten predictions against actual orders) 30% to 37%, and weighted recall (sensitivity) at ten 2.4% to 13%, (P<10−10). Training with more longitudinal data (2009-2012) was no better than only using recent (2012) data. Secular trends in practice patterns likely explain why smaller but more recent training data is more accurate at predicting future practices. PMID:26776186

  4. Insomnia Complaint Versus Sleep Diary Parameters: Predictions of Suicidal Ideation.

    Science.gov (United States)

    Woosley, Julie A; Lichstein, Kenneth L; Taylor, Daniel J; Riedel, Brant W; Bush, Andrew J

    2016-02-01

    The purpose of this study was to determine which aspects of insomnia best predict suicidal ideation (SI). Participants were grouped according to whether they complained of insomnia and whether their sleep would be characterized as poor or good by applying quantitative criteria for insomnia to their sleep diary data. Analyses revealed that insomnia complaint was more strongly associated with SI than was poor sleep. These findings suggest that patients who complain of insomnia, regardless of the presence or absence of poor sleep, may be at greater risk for suicide than those who are content with their sleep.

  5. Toward the Computational Prediction of Muon Sites and Interaction Parameters

    Science.gov (United States)

    Bonfà, Pietro; De Renzi, Roberto

    2016-09-01

    The rapid developments of computational quantum chemistry methods and supercomputing facilities motivate the renewed interest in the analysis of the muon/electron interactions in μSR experiments with ab initio approaches. Modern simulation methods seem to be able to provide the answers to the frequently asked questions of many μSR experiments: where is the muon? Is it a passive probe? What are the interaction parameters governing the muon-sample interaction? In this review we describe some of the approaches used to provide quantitative estimations of the aforementioned quantities and we provide the reader with a short discussion on the current developments in this field.

  6. Evaluation of clinical, biochemical and hematological parameters in macrocytic anemia

    Directory of Open Access Journals (Sweden)

    Aarthi Kannan

    2016-07-01

    Results: Primary bone marrow disorders were the most common cause of macrocytosis (46%. The other causes in decreasing order of frequency were megaloblastic anaemia (38%, hemolytic anemia (6%, drug induced (5%, alcoholism and liver disease (4% and idiopathic thrombocytopenic purpura (1%. There was a significant difference in the mean values of MCV and serum LDH between megaloblastic and non and ndash; megaloblastic macrocytosis. When serum LDH >1345.2 IU/L or MCV>121fl (criterion values of ROC curve with reticulocyte count <2% was taken as criteria, the sensitivity was 92.1% and specificity was 93.5% for diagnosing megaloblastic anemia. Conclusions: Systematic evaluation of macrocytosis will help us to distinguish megaloblastic and non and ndash; megaloblastic macrocytosis. The blood and biochemical parameters especially CBC, RC, and serum LDH along with supporting clinical features help us in diagnosing megaloblastic anemia in a setup where vitamin and metabolite levels are difficult to obtain. [Int J Res Med Sci 2016; 4(7.000: 2670-2678

  7. Clinical and Biochemical Parameters of Children and Adolescents Applying Pesticides

    Directory of Open Access Journals (Sweden)

    O Hendy

    2010-06-01

    Full Text Available Background: The primary agricultural product in Egypt is the cotton crop. Children and adolescents work seasonally in the cotton fields applying pesticides.Objectives: To examine the effect of pesticide exposure on clinical and biochemical parameters in children and adolescents applying pesticides.Methods: Male children currently applying pesticides and aged between 9 and 19 years (n = 50 were recruited for this study. They were asked to complete work, health, and exposure questionnaires; examined for any medical and neurological problems with particular attention to sensory and motor functions including cranial nerves, sensory and motor system, and reflexes. From each participant, a blood sample was taken to measure acetylcholinesterase activity, and liver and kidney functions. Children who have never worked in agriculture (n = 50, matched on age, education, and socioeconomic status were also studied and served as controls.Results: More neuromuscular disorders were identified in pesticide applicators than controls. A significant lower level of acetylcholinesterase was found in the applicator group compared to the controls. There was also a significant difference in hematological, renal and hepatic indices in the exposed children compared to the control children. Working more days in the current season and also working more years as a pesticide applicator were both associated with an increase in the prevalence of neuromuscular abnormalities and significant changes in the laboratory tests.Conclusion: Children and adolescent pesticide applicators working in farms of Egypt are at risk of developing serious health problems similar to those of adults.

  8. Predictive parameters of survival in hemodialysis patients with restless leg syndrome

    Directory of Open Access Journals (Sweden)

    Radojica V Stolic

    2014-01-01

    Full Text Available Restless leg syndrome (RLS affects the quality of life and survival in patients on hemodialysis (HD. The aim of this study was to determine the characteristics and survival parameters in patients on HD with RLS. This study was a non-randomized clinical study involving 204 patients on HD, of whom 71 were female and 133 were male. Symptoms of RLS were defined as positive responses to four questions comprising the criteria of RLS. We recorded the outcome of treatment, biochemical analyses, demographic, sexual, anthropometric and clinical characteristics in all study patients. Patients with RLS who completed the study had a significantly higher body mass index and lower intima-media thickness and flow through the arteriovenous fistula. Among patients with RLS who died, there were more smokers as well as higher incidences of cardiovascular disease and diabetes mellitus. Among patients with RLS who survived, there were a greater number of patients with preserved diuresis and receiving erythropoietin therapy. Patients who completed the study had significantly higher levels of hemoglobin, creatinine, serum iron and transferrin satura-tion. Diabetes mellitus (B = 1.802; P = 0.002 and low Kt/V (B = -5.218; P = 0.001 were major predictive parameters for survival.

  9. Molecular physicochemical parameters predicting antioxidant activity of Brazilian natural products

    Directory of Open Access Journals (Sweden)

    Luciana Scotti

    2009-12-01

    Full Text Available Reactive oxygen species (ROS are capable of oxidizing cellular proteins, nucleic acids and lipids, contributing to cellular aging, mutagenesis, carcinogenesis, coronary heart and neurodegenerative diseases. Free radicals-scavenging by phenolic compounds occurs by the transfer of one electron followed by the H-abstraction. In order to evaluate the antioxidant activity of a series of seventeen phenolic compounds extracted from Brazilian flora (Chimarrhis turbinata and Arrabidea samydoides, some physicochemical parameters (heat formation of the neutral, radical, and cationic compounds; orbitals' energies; ClogP; ΔH OX; and ΔHf were calculated. Considering the results from the calculated descriptors, the molecules 10a-f can be classified as having a higher antioxidant activity.

  10. Predictive parameters of infectiologic complications in patients after TIPSS; Praediktive Parameter infektiologischer Komplikationen bei Patienten nach TIPSS-Anlage

    Energy Technology Data Exchange (ETDEWEB)

    Cohnen, M.; Saleh, A.; Moedder, U. [Institut fuer Diagnostische Radiologie, Universitaetsklinikum Duesseldorf (Germany); Luethen, R.; Bode, J.; Haeussinger, D. [Klinik fuer Gastroenterologie, Hepatologie und Infektiologie, Universitaetsklinikum Duesseldorf (Germany); Daeubener, W. [Institut fuer Mikrobiologie und Virologie, Universitaetsklinikum Duesseldorf (Germany)

    2003-02-01

    Aim To define predictive parameters of a complicated clinical course after the TIPSS procedure. Blood cultures were drawn prospectively in 41 patients from a central line and from the portal venous blood before stent placement as well as from the central line 20 min after intervention. C-reactive proteine (CRP) (mg/dl) and white blood cell count (WBC,/{mu}l) on the day of TIPSS-procedure (d0), the first (d1) and seven (d7) days after TIPSS were compared in patients with a complicated clinical course (spontaneous bacterial peritonitis, pneumonia, sepsis; group I) to patients without clinical complications (group II) Group I showed a significant increase in CRP (d0: 1.8{+-}1.0; d1: 3.2{+-}1.5; d7: 4.3{+-}3.2), and white blood cell count (d0: 7700{+-}2600; d1: 10800{+-}2800; d7: 7500{+-}1800) on the first day after TIPSS-procedure in comparison to group II (CRP: d0: 1.6{+-}0.6; d1: 1.8{+-}1.0; d7: 1.9{+-}0.6. WBC: d0: 6900{+-}1500; d1: 8000{+-}1600; d7: 7600{+-}1400).Microbiological analysis showed in 12% skin or oral flora in the last sample. The course of CRP and WBC-count during the first week after TIPSS procedure may indicate patients with a potential risk of a complicated clinical course. (orig.) [German] Fragestellung Definition praediktiver Parameter infektiologischer Komplikationen bei Patienten nach TIPSS-Anlage.Methodik Bei 41 Patienten wurden Blutproben prospektiv vor intrahepatischer Stentanlage zentralvenoes und portalvenoes sowie 20 min postinterventionell erneut zentralvenoes entnommen und mikrobiologisch analysiert. C-reaktives Protein (CRP) (mg/dl) und Leukozytenzahl (/{mu}l) wurden am Interventionstag (d0), am 1. (d1) sowie 7 Tage (d7) postinterventionell bestimmt. Patienten mit kompliziertem Verlauf (spontane bakterielle Peritonitis,Pneumonie, Sepsis; Gruppe 1) wurden von Patienten ohne klinische Komplikationen (Gruppe 2) unterschieden.Ergebnisse Gruppe 1 wies einen signifikanten Anstieg des CRP (d0: 1,8{+-}1,0; d1: 3,2{+-}1,5; d7: 4,3{+-}3,2) und

  11. Brain Connectivity Predicts Placebo Response across Chronic Pain Clinical Trials

    Science.gov (United States)

    Tétreault, Pascal; Mansour, Ali; Vachon-Presseau, Etienne; Schnitzer, Thomas J.; Apkarian, A. Vania

    2016-01-01

    Placebo response in the clinical trial setting is poorly understood and alleged to be driven by statistical confounds, and its biological underpinnings are questioned. Here we identified and validated that clinical placebo response is predictable from resting-state functional magnetic-resonance-imaging (fMRI) brain connectivity. This also led to discovering a brain region predicting active drug response and demonstrating the adverse effect of active drug interfering with placebo analgesia. Chronic knee osteoarthritis (OA) pain patients (n = 56) underwent pretreatment brain scans in two clinical trials. Study 1 (n = 17) was a 2-wk single-blinded placebo pill trial. Study 2 (n = 39) was a 3-mo double-blinded randomized trial comparing placebo pill to duloxetine. Study 3, which was conducted in additional knee OA pain patients (n = 42), was observational. fMRI-derived brain connectivity maps in study 1 were contrasted between placebo responders and nonresponders and compared to healthy controls (n = 20). Study 2 validated the primary biomarker and identified a brain region predicting drug response. In both studies, approximately half of the participants exhibited analgesia with placebo treatment. In study 1, right midfrontal gyrus connectivity best identified placebo responders. In study 2, the same measure identified placebo responders (95% correct) and predicted the magnitude of placebo’s effectiveness. By subtracting away linearly modeled placebo analgesia from duloxetine response, we uncovered in 6/19 participants a tendency of duloxetine enhancing predicted placebo response, while in another 6/19, we uncovered a tendency for duloxetine to diminish it. Moreover, the approach led to discovering that right parahippocampus gyrus connectivity predicts drug analgesia after correcting for modeled placebo-related analgesia. Our evidence is consistent with clinical placebo response having biological underpinnings and shows that the method can also reveal that active

  12. Estimation of boundary parameters and prediction of transmission loss based upon ray acoustics

    Institute of Scientific and Technical Information of China (English)

    GUO Yuhong; FAN Minyi; HUI Junying

    2000-01-01

    Estimation of boundary parameters and prediction of transmission loss using a coherent channel model based upon ray acoustics and sound propagation data collected in field experiments are presented. Comparison between the prediction results and the experiment data indicates that the adopted sound propagation model is valuable, both selection and estimation methods on boundary parameters are reasonable, and the prediction performance of transmission loss is favorable.

  13. Prediction Model of Interval Grey Numbers with a Real Parameter and Its Application

    OpenAIRE

    Bo Zeng; Chuan Li; Xue-Yu Zhou; Xian-Jun Long

    2014-01-01

    Grey prediction models have become common methods which are widely employed to solve the problems with “small examples and poor information.” However, modeling objects of existing grey prediction models are limited to the homogenous data sequences which only contain the same data type. This paper studies the methodology of building prediction models of interval grey numbers that are grey heterogeneous data sequence, with a real parameter. Firstly, the position of the real parameter in an inte...

  14. Computer programme for prediction steel parameters after heat treatment

    Directory of Open Access Journals (Sweden)

    J. Trzaska

    2007-10-01

    Full Text Available Purpose: The purpose of this paper is presentation of the computer program for calculating the Continuous Cooling Transformation diagrams for constructional and engineering steels.Design/methodology/approach: The computer program uses the artificial neural networks for prediction steel properties after heat treatment. Input data are chemical composition and austenitizing temperature. Results of calculation consist of temperature of the beginning and the end of transformation in the cooling rate function, the volume fraction of structural components and hardness of steel cooled from austenitizing temperature with a fixed rate.Findings: The algorithm can be use in designing new chemical compositions of steels with assumed hardness after heat treatment.Research limitations/implications: The created method for designing chemical compositions is limited by ranges of mass concentrations of elements. The methodology demonstrated in the paper makes possibility to add new steels to the system.Practical implications: The method may be used in computer steel selection systems for machines parts manufactured from constructional or engineering steels subjected to heat treatment.Originality/value: The presented computer program can be used for selecting steel with required structure after heat treatment.

  15. Analysis and prediction of the alpha-function parameters used in cubic equations of state

    DEFF Research Database (Denmark)

    Privata, Romain; Viscontea, Maxime; Zazoua-Khames, Anis;

    2015-01-01

    evidenced and fixed. A new class of purely predictive alpha functions was derived by applying group-contribution (GC) methods to the prediction of alpha function parameters. The interest of such an approach is discussed and compared to another predictive approach (use of generalized alpha functions coupled...

  16. Prediction of Superconductivity for Oxides Based on Structural Parameters and Artificial Neural Network Method

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Superconductive properties for oxides were predicted by artificial neural network (ANN) method with structural and chemical parameters as inputs. The predicted properties include superconductivity for oxides, distributed ranges of the superconductive transition temperature (Tc) for complex oxides, and Tc values for cuprate superconductors. The calculated results indicated that the adjusted ANN can be used to predict superconductive properties for unknown oxides.

  17. Predicting parameters of degradation succession processes of Tibetan Kobresia grasslands

    Science.gov (United States)

    Lin, L.; Li, Y. K.; Xu, X. L.; Zhang, F. W.; Du, Y. G.; Liu, S. L.; Guo, X. W.; Cao, G. M.

    2015-11-01

    In the past two decades, increasing human activity (i.e., overgrazing) in the Tibetan Plateau has strongly influenced plant succession processes, resulting in the degradation of alpine grasslands. Therefore, it is necessary to diagnose the degree of degradation to enable implementation of appropriate management for sustainable exploitation and protection of alpine grasslands. Here, we investigated environmental factors and plant functional group (PFG) quantity factors during the alpine grassland succession processes. Principal component analysis (PCA) was used to identify the parameters indicative of degradation. We divided the entire degradation process into six stages. PFG types shifted from rhizome bunchgrasses to rhizome plexus and dense-plexus grasses during the degradation process. Leguminosae and Gramineae plants were replaced by sedges during the advanced stages of degradation. The PFGs were classified into two reaction groups: the grazing-sensitive group, containing Kobresia humilis Mey, and Gramineae and Leguminosae plants, and the grazing-insensitive group, containing Kobresia pygmaea Clarke. The first group was correlated with live root biomass in the surface soil (0-10 cm), whereas the second group was strongly correlated with mattic epipedon thickness and K. pygmaea characteristics. The degree of degradation of alpine meadows may be delineated by development of mattic epipedon and PFG composition. Thus, meadows could be easily graded and their use adjusted based on our scaling system, which would help prevent irreversible degradation of important grasslands. Because relatively few environmental factors are investigated, this approach can save time and labor to formulate a conservation management plan for degraded alpine meadows.

  18. Optimal Parameter Tuning in a Predictive Nonlinear Control Method for a Mobile Robot

    Directory of Open Access Journals (Sweden)

    D. Hazry

    2006-01-01

    Full Text Available This study contributes to a new optimal parameter tuning in a predictive nonlinear control method for stable trajectory straight line tracking with a non-holonomic mobile robot. In this method, the focus lies in finding the optimal parameter estimation and to predict the path that the mobile robot will follow for stable trajectory straight line tracking system. The stability control contains three parameters: 1 deflection parameter for the traveling direction of the mobile robot 2 deflection parameter for the distance across traveling direction of the mobile robot and 3 deflection parameter for the steering angle of the mobile robot . Two hundred and seventy three experimental were performed and the results have been analyzed and described herewith. It is found that by using a new optimal parameter tuning in a predictive nonlinear control method derived from the extension of kinematics model, the movement of the mobile robot is stabilized and adhered to the reference posture

  19. Parameter optimization of parenchymal texture analysis for prediction of false-positive recalls from screening mammography

    Science.gov (United States)

    Ray, Shonket; Keller, Brad M.; Chen, Jinbo; Conant, Emily F.; Kontos, Despina

    2016-03-01

    This work details a methodology to obtain optimal parameter values for a locally-adaptive texture analysis algorithm that extracts mammographic texture features representative of breast parenchymal complexity for predicting falsepositive (FP) recalls from breast cancer screening with digital mammography. The algorithm has two components: (1) adaptive selection of localized regions of interest (ROIs) and (2) Haralick texture feature extraction via Gray- Level Co-Occurrence Matrices (GLCM). The following parameters were systematically varied: mammographic views used, upper limit of the ROI window size used for adaptive ROI selection, GLCM distance offsets, and gray levels (binning) used for feature extraction. Each iteration per parameter set had logistic regression with stepwise feature selection performed on a clinical screening cohort of 474 non-recalled women and 68 FP recalled women; FP recall prediction was evaluated using area under the curve (AUC) of the receiver operating characteristic (ROC) and associations between the extracted features and FP recall were assessed via odds ratios (OR). A default instance of mediolateral (MLO) view, upper ROI size limit of 143.36 mm (2048 pixels2), GLCM distance offset combination range of 0.07 to 0.84 mm (1 to 12 pixels) and 16 GLCM gray levels was set. The highest ROC performance value of AUC=0.77 [95% confidence intervals: 0.71-0.83] was obtained at three specific instances: the default instance, upper ROI window equal to 17.92 mm (256 pixels2), and gray levels set to 128. The texture feature of sum average was chosen as a statistically significant (p<0.05) predictor and associated with higher odds of FP recall for 12 out of 14 total instances.

  20. On-time clinical phenotype prediction based on narrative reports

    Science.gov (United States)

    Bejan, Cosmin A.; Vanderwende, Lucy; Evans, Heather L.; Wurfel, Mark M.; Yetisgen-Yildiz, Meliha

    2013-01-01

    In this paper we describe a natural language processing system which is able to predict whether or not a patient exhibits a specific phenotype using the information extracted from the narrative reports associated with the patient. Furthermore, the phenotypic annotations from our report dataset were performed at the report level which allows us to perform the prediction of the clinical phenotype at any point in time during the patient hospitalization period. Our experiments indicate that an important factor in achieving better results for this problem is to determine how much information to extract from the patient reports in the time interval between the patient admission time and the current prediction time. PMID:24551325

  1. Predicting postoperative mortality after colorectal surgery : a novel clinical model

    NARCIS (Netherlands)

    van der Sluis, F. J.; Espin, E.; Vallribera, F.; de Bock, G. H.; Hoekstra, H. J.; van Leeuwen, B. L.; Engel, A. F.

    2014-01-01

    Aim The aim of this study was to develop and externally validate a clinically, practical and discriminative prediction model designed to estimate in-hospital mortality of patients undergoing colorectal surgery. Method All consecutive patients who underwent elective or emergency colorectal surgery fr

  2. Influence and prediction of hot deformation parameters on microstructure of Ti-15-3 alloy

    Institute of Scientific and Technical Information of China (English)

    李萍; 薛克敏; 吕炎; 谭建荣

    2002-01-01

    The effect of hot processing parameters on the microstructure of Ti-15-3 alloy after solution treatment was studied by isothermal compression test and metallurgical analysis. Predicting models for the relations between equivalent grain size and recrystallized grain volume percent with strain,strain rate and temperature have been developed with an artificial neural network method. The coincidence of predicted results with measured ones shows that the neural network can predict the influence of hot deformation parameters on the microstructure of Ti-15-3 alloy after solution treatment successfully. These studies are significant for determining hot-forging processing parameters of Ti-15-3 alloy.

  3. [Clinical probability of PE: should we use a clinical prediction rule?].

    Science.gov (United States)

    Le Gal, G; Righini, M; Perrier, A

    2008-12-01

    The determination of the clinical pretest probability using clinical prediction models is an important step in the assessment of patients with suspected pulmonary embolism (PE). It helps establish which test or sequence of tests can effectively corroborate or safely rule out PE. For example, it has been demonstrated that it is safe to withhold anticoagulant therapy in patients with negative d-dimer results and low pretest probability at initial presentation. Clinical probability will also increase the diagnostic yield of ventilation perfusion lung scan. Compared with clinical gestalt, clinical prediction rules provide a standardized and more reproducible estimate of a patient's probability of having a PE. Clinical prediction models combine aspects of the history and physical examination to categorize a patient's probability of having a disease. The models classify patients as having a low, moderate, or high likelihood of having PE. Clinical prediction models have been validated and are well established for the diagnosis of PE in symptomatic patients. They allow all physicians, whatever their expertise, to reliably determine the clinical pretest probability of PE, and thus safely manage their patients using diagnostic and therapeutic algorithms. PMID:19084205

  4. Probabilistic Fatigue Life Prediction of Turbine Disc Considering Model Parameter Uncertainty

    Science.gov (United States)

    He, Liping; Yu, Le; Zhu, Shun-Peng; Ding, Liangliang; Huang, Hong-Zhong

    2016-06-01

    Aiming to improve the predictive ability of Walker model for fatigue life prediction and taking the turbine disc alloy GH4133 as the application example, this paper investigates a new approach for probabilistic fatigue life prediction when considering parameter uncertainty inherent in the life prediction model. Firstly, experimental data are used to update the model parameters using Bayes' theorem, so as to obtain the posterior probability distribution functions of two parameters of the Walker model, as well to achieve the probabilistic life prediction model for turbine disc. During the updating process, Markov Chain Monte Carlo (MCMC) technique is used to generate samples of the given distribution and estimating the parameters distinctly. After that, the turbine disc life is predicted using the probabilistic Walker model based on Monte Carlo simulation technique. The experimental results indicate that: (1) after using the small sample test data obtained from turbine disc, parameter uncertainty of the Walker model can be quantified and the corresponding probabilistic model for fatigue life prediction can be established using Bayes' theorem; (2) there exists obvious dispersion of life data for turbine disc when predicting fatigue life in practical engineering application.

  5. Effects of soil hydraulic and transport parameter uncertainty on predictions of solute transport in large lysimeters

    Science.gov (United States)

    Advanced numerical simulation models can potentially help improve guidelines for irrigation and salinity management. Many simulation model parameters have considerable uncertainty, and ideally that uncertainty should be reflected in model predictions and recommendations. In this work, we investiga...

  6. SVM model for estimating the parameters of the probability-integral method of predicting mining subsidence

    Institute of Scientific and Technical Information of China (English)

    ZHANG Hua; WANG Yun-jia; LI Yong-feng

    2009-01-01

    A new mathematical model to estimate the parameters of the probability-integral method for mining subsidence prediction is proposed. Based on least squares support vector machine (LS-SVM) theory, it is capable of improving the precision and reliability of mining subsidence prediction. Many of the geological and mining factors involved are related in a nonlinear way. The new model is based on statistical theory (SLT) and empirical risk minimization (ERM) principles. Typical data collected from observation stations were used for the learning and training samples. The calculated results from the LS-SVM model were compared with the prediction results of a back propagation neural network (BPNN) model. The results show that the parameters were more precisely predicted by the LS-SVM model than by the BPNN model. The LS-SVM model was faster in computation and had better generalized performance. It provides a highly effective method for calculating the predicting parameters of the probability-integral method.

  7. Idiopathic normal pressure hydrocephalus: diagnostic and predictive value of clinical testing, lumbar drainage, and CSF dynamics.

    Science.gov (United States)

    Mahr, Cynthia V; Dengl, Markus; Nestler, Ulf; Reiss-Zimmermann, Martin; Eichner, Gerrit; Preuß, Matthias; Meixensberger, Jürgen

    2016-09-01

    OBJECTIVE The aim of the study was to analyze the diagnostic and predictive values of clinical tests, CSF dynamics, and intracranial pulsatility tests, compared with external lumbar drainage (ELD), for shunt response in patients with idiopathic normal pressure hydrocephalus (iNPH). METHODS Sixty-eight consecutive patients with suspected iNPH were prospectively evaluated. Preoperative assessment included clinical tests, overnight intracranial pressure (ICP) monitoring, lumbar infusion test (LIFT), and ELD for 24-72 hours. Simple and multiple linear regression analyses were conducted to identify predictive parameters concerning the outcome after shunt therapy. RESULTS Positive response to ELD correctly predicted improvement after CSF diversion in 87.9% of the patients. A Mini-Mental State Examination (MMSE) value below 21 was associated with nonresponse after shunt insertion (specificity 93%, sensitivity 67%). Resistance to outflow of CSF (ROut) > 12 mm Hg/ml/min was false negative in 21% of patients. Intracranial pulsatility parameters yielded different results in various parameters (correlation coefficient between pulse amplitude and ICP, slow wave amplitude, and mean ICP) but did not correlate to outcome. In multiple linear regression analysis, a calculation of presurgical MMSE versus the value after ELD, ROut, and ICP amplitude quotient during LIFT was significantly associated with outcome (p = 0.04). CONCLUSIONS Despite a multitude of invasive tests, presurgical clinical testing and response to ELD yielded the best prediction for improvement of symptoms following surgery. The complication rate of invasive testing was 5.4%. Multiple and simple linear regression analyses indicated that outcome can only be predicted by a combination of parameters, in accordance with a multifactorial pathogenesis of iNPH. PMID:26824377

  8. A practical approach to parameter estimation applied to model predicting heart rate regulation

    DEFF Research Database (Denmark)

    Olufsen, Mette; Ottesen, Johnny T.

    2013-01-01

    Mathematical models have long been used for prediction of dynamics in biological systems. Recently, several efforts have been made to render these models patient specific. One way to do so is to employ techniques to estimate parameters that enable model based prediction of observed quantities. Kn...

  9. Modeling of Mixolab Profiles by Nonlinear Curve Fitting and Prediction of Breadmaking Parameters

    Science.gov (United States)

    Prediction of breadmaking parameters is a crucial step in wheat quality evaluation for breeders and end-users. This research was performed to investigate the association of flour breadmaking parameters with mixing characteristics and the rheological property of dough subjected to thermal constraint....

  10. Prediction of Liquid-Liquid Equilibrium Using the Group Solubility Parameter Model

    Institute of Scientific and Technical Information of China (English)

    ZHAO Mo; CHEN Fuming

    2005-01-01

    The group solubility parameter (GSP) model was used to analyze the liquid-liquid equilibrium (LLE) of ternary and quaternary systems. The GSP parameters are divided into four dimensions representing the four major intermolecular forces. The values of the parameters were determined by regression using the nonlinear SIMPLEX optimization method to fit the LLE data of 548 ternary and 26 quaternary systems selected from the literature. LLE predictions of 8 ternary systems were then made using the fit parameters. Comparison of the results with predictions using the modified UNIFAC model shows that the GSP model has less adjustable parameters to achieve a similar accuracy and that the parameter values are easily acquired by analysis of available data.

  11. Vehicle Dynamic Prediction Systems with On-Line Identification of Vehicle Parameters and Road Conditions

    OpenAIRE

    Ling-Yuan Hsu; Tsung-Lin Chen

    2012-01-01

    This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficie...

  12. Using Kalman filtering to predict time-varying parameters in a model predicting baroreflex regulation during head-up tilt

    DEFF Research Database (Denmark)

    Matzuka, Brett; Mehlsen, Jesper; Tran, Hien;

    2015-01-01

    , while the second uses the ensemble transform Kalman filter (ETKF) [1], [12], [13], [35]. In addition, we show that the delayed rejection adaptive Metropolis (DRAM) algorithm can be used for predicting parameter uncertainties within the spline methodology, which is compared with the variability obtained...

  13. Development of an algorithm to predict comfort of wheelchair fit based on clinical measures.

    Science.gov (United States)

    Kon, Keisuke; Hayakawa, Yasuyuki; Shimizu, Shingo; Nosaka, Toshiya; Tsuruga, Takeshi; Matsubara, Hiroyuki; Nomura, Tomohiro; Murahara, Shin; Haruna, Hirokazu; Ino, Takumi; Inagaki, Jun; Kobayashi, Toshiki

    2015-09-01

    [Purpose] The purpose of this study was to develop an algorithm to predict the comfort of a subject seated in a wheelchair, based on common clinical measurements and without depending on verbal communication. [Subjects] Twenty healthy males (mean age: 21.5 ± 2 years; height: 171 ± 4.3 cm; weight: 56 ± 12.3 kg) participated in this study. [Methods] Each experimental session lasted for 60 min. The clinical measurements were obtained under 4 conditions (good posture, with and without a cushion; bad posture, with and without a cushion). Multiple regression analysis was performed to determine the relationship between a visual analogue scale and exercise physiology parameters (respiratory and metabolism), autonomic nervous parameters (heart rate, blood pressure, and salivary amylase level), and 3D-coordinate posture parameters (good or bad posture). [Results] For the equation (algorithm) to predict the visual analogue scale score, the adjusted multiple correlation coefficient was 0.72, the residual standard deviation was 1.2, and the prediction error was 12%. [Conclusion] The algorithm developed in this study could predict the comfort of healthy male seated in a wheelchair with 72% accuracy. PMID:26504299

  14. Cytokines and signaling molecules predict clinical outcomes in sepsis.

    Directory of Open Access Journals (Sweden)

    Christopher D Fjell

    Full Text Available INTRODUCTION: Inflammatory response during sepsis is incompletely understood due to small sample sizes and variable timing of measurements following the onset of symptoms. The vasopressin in septic shock trial (VASST compared the addition of vasopressin to norepinephrine alone in patients with septic shock. During this study plasma was collected and 39 cytokines measured in a 363 patients at both baseline (before treatment and 24 hours. Clinical features relating to both underlying health and the acute organ dysfunction induced by the severe infection were collected during the first 28 days of admission. HYPOTHESIS: Cluster analysis of cytokines identifies subgroups of patients at differing risk of death and organ failure. METHODS: Circulating cytokines and other signaling molecules were measured using a Luminex multi-bead analyte detection system. Hierarchical clustering was performed on plasma values to create patient subgroups. Enrichment analysis identified clinical outcomes significantly different according to these chemically defined patient subgroups. Logistic regression was performed to assess the importance of cytokines for predicting patient subgroups. RESULTS: Plasma levels at baseline produced three subgroups of patients, while 24 hour levels produced two subgroups. Using baseline cytokine data, one subgroup of 47 patients showed a high level of enrichment for severe septic shock, coagulopathy, renal failure, and risk of death. Using data at 24 hours, a larger subgroup of 81 patients that largely encompassed the 47 baseline subgroup patients had a similar enrichment profile. Measurement of two cytokines, IL2 and CSF2 and their product were sufficient to classify patients into these subgroups that defined clinical risks. CONCLUSIONS: A distinct pattern of cytokine levels measured early in the course of sepsis predicts disease outcome. Subpopulations of patients have differing clinical outcomes that can be predicted accurately from

  15. Toward an Efficient Prediction of Solar Flares: Which Parameters, and How?

    Directory of Open Access Journals (Sweden)

    Manolis K. Georgoulis

    2013-11-01

    Full Text Available Solar flare prediction has become a forefront topic in contemporary solar physics, with numerous published methods relying on numerous predictive parameters, that can even be divided into parameter classes. Attempting further insight, we focus on two popular classes of flare-predictive parameters, namely multiscale (i.e., fractal and multifractal and proxy (i.e., morphological parameters, and we complement our analysis with a study of the predictive capability of fundamental physical parameters (i.e., magnetic free energy and relative magnetic helicity. Rather than applying the studied parameters to a comprehensive statistical sample of flaring and non-flaring active regions, that was the subject of our previous studies, the novelty of this work is their application to an exceptionally long and high-cadence time series of the intensely eruptive National Oceanic and Atmospheric Administration (NOAA active region (AR 11158, observed by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. Aiming for a detailed study of the temporal evolution of each parameter, we seek distinctive patterns that could be associated with the four largest flares in the AR in the course of its five-day observing interval. We find that proxy parameters only tend to show preflare impulses that are practical enough to warrant subsequent investigation with sufficient statistics. Combining these findings with previous results, we conclude that: (i carefully constructed, physically intuitive proxy parameters may be our best asset toward an efficient future flare-forecasting; and (ii the time series of promising parameters may be as important as their instantaneous values. Value-based prediction is the only approach followed so far. Our results call for novel signal and/or image processing techniques to efficiently utilize combined amplitude and temporal-profile information to optimize the inferred solar-flare probabilities.

  16. Efficiency of Calatonia on clinical parameters in the immediate post-surgery period: a clinical study

    Directory of Open Access Journals (Sweden)

    Elaine Ferreira Lasaponari

    2013-09-01

    Full Text Available OBJECTIVE: to assess the efficiency of the Calatonia technique about clinical parameters and pain in the immediate post-surgical phase. METHOD: a randomised study was carried out with 116 patients subjected to a cholecystectomy, by laparoscopy, divided into an experimental group (58 patients and a placebo group (58 patients. The experimental group received the Calatonia technique, while the placebo was only subjected to non-intentional touches. RESULTS: The placebo group and the experimental group were considered homogeneous in terms of the variables: sex, age, physical status classification, duration of surgical procedures and also the time spent recovering in the Post-Anaesthetic Recovery Room. The only variable to show a statistically significant difference was the axillary temperature of the body. In relation to pain, the experimental group showed significant results, and hence it is possible to deduce that the relaxation caused by the Calatonia technique brought some relief of the general situation of pain. CONCLUSION: The application of Calatonia can take up the function of a resource complementary to assistance in the period immediately after surgery. Brazilian Register of Clinical Trials, UTN U1111-1129-9629.

  17. Prediction model of atmospheric refractive index structure parameter in coastal area

    Science.gov (United States)

    Wang, Hongxing; Li, Bifeng; Wu, Xiaojun; Liu, Chuanhui; Hu, Zhihui; Xu, Pengfei

    2015-09-01

    In this paper, we focus on the prediction of atmospheric refractive index structure parameter (?) in coastal area using the routine meteorological parameters. Based on the micrometeorology, macrometeorology and Monin-Obukhov similarity theory, three modified prediction models of ? are presented in combination with the long-term observation data of ? and meteorological parameters in coastal city, respectively. For different weather, the applicable cases of three ? prediction models are comparatively analysed and their applicable effects are comprehensively evaluated. The results indicate that the modified micrometeorology model of ? shows better applicability for overcast sky, the offshore macrometeorology model of ? displays better predictability for sunny day and the offshore Thiermann model provides better availability for overcast sky, cloudy day, overcast to sunny or sunny to overcast day.

  18. Bankruptcy prediction using SVM models with a new approach to combine features selection and parameter optimisation

    Science.gov (United States)

    Zhou, Ligang; Keung Lai, Kin; Yen, Jerome

    2014-03-01

    Due to the economic significance of bankruptcy prediction of companies for financial institutions, investors and governments, many quantitative methods have been used to develop effective prediction models. Support vector machine (SVM), a powerful classification method, has been used for this task; however, the performance of SVM is sensitive to model form, parameter setting and features selection. In this study, a new approach based on direct search and features ranking technology is proposed to optimise features selection and parameter setting for 1-norm and least-squares SVM models for bankruptcy prediction. This approach is also compared to the SVM models with parameter optimisation and features selection by the popular genetic algorithm technique. The experimental results on a data set with 2010 instances show that the proposed models are good alternatives for bankruptcy prediction.

  19. Development of computer code for determining prediction parameters of radionuclide migration in soil layer

    International Nuclear Information System (INIS)

    A computer code (MIGSTEM-FIT) has been developed to determine the prediction parameters, retardation factor, water flow velocity, dispersion coefficient, etc., of radionuclide migration in soil layer from the concentration distribution of radionuclide in soil layer or in effluent. In this code, the solution of the predicting equation for radionuclide migration is compared with the concentration distribution measured, and the most adequate values of parameter can be determined by the flexible tolerance method. The validity of finite differential method, which was one of the method to solve the predicting equation, was confirmed by comparison with the analytical solution, and also the validity of fitting method was confirmed by the fitting of the concentration distribution calculated from known parameters. From the examination about the error, it was found that the error of the parameter obtained by using this code was smaller than that of the concentration distribution measured. (author)

  20. Host genetics predict clinical deterioration in HCV-related cirrhosis.

    Directory of Open Access Journals (Sweden)

    Lindsay Y King

    Full Text Available Single nucleotide polymorphisms (SNPs in the epidermal growth factor (EGF, rs4444903, patatin-like phospholipase domain-containing protein 3 (PNPLA3, rs738409 genes, and near the interleukin-28B (IL28B, rs12979860 gene are linked to treatment response, fibrosis, and hepatocellular carcinoma (HCC in chronic hepatitis C. Whether these SNPs independently or in combination predict clinical deterioration in hepatitis C virus (HCV-related cirrhosis is unknown. We genotyped SNPs in EGF, PNPLA3, and IL28B from liver tissue from 169 patients with biopsy-proven HCV cirrhosis. We estimated risk of clinical deterioration, defined as development of ascites, encephalopathy, variceal hemorrhage, HCC, or liver-related death using Cox proportional hazards modeling. During a median follow-up of 6.6 years, 66 of 169 patients experienced clinical deterioration. EGF non-AA, PNPLA3 non-CC, and IL28B non-CC genotypes were each associated with increased risk of clinical deterioration in age, sex, and race-adjusted analysis. Only EGF non-AA genotype was independently associated with increased risk of clinical deterioration (hazard ratio [HR] 2.87; 95% confidence interval [CI] 1.31-6.25 after additionally adjusting for bilirubin, albumin, and platelets. Compared to subjects who had 0-1 unfavorable genotypes, the HR for clinical deterioration was 1.79 (95%CI 0.96-3.35 for 2 unfavorable genotypes and 4.03 (95%CI 2.13-7.62 for unfavorable genotypes for all three loci (Ptrend<0.0001. In conclusion, among HCV cirrhotics, EGF non-AA genotype is independently associated with increased risk for clinical deterioration. Specific PNPLA3 and IL28B genotypes also appear to be associated with clinical deterioration. These SNPs have potential to identify patients with HCV-related cirrhosis who require more intensive monitoring for decompensation or future therapies preventing disease progression.

  1. The relationships between preoperative urodynamic parameters and clinical outcomes in urinary stress incontinence

    Directory of Open Access Journals (Sweden)

    Yaşar Bozkurt

    2008-12-01

    Full Text Available The aim of present study was to evaluate the influence of urodynamic parameters on preoperative and postoperative clinical pictures in stress incontinence.Charts of patients, who were operated for stress incontinence using autologous rectus fascia sling between March 1999 and January 2005 in Tepecik Training and Research Hospital Urology Clinic, were evaluated retrospectively.A total of 41 patients were divided into two subgroups as, pure (10 patients and mixed stress incontinence (31 patients groups. Mean age of patients was 50.4 (33-70 years. Fifteen patients had intrinsic sphincter insufficiency (ISI. Mixed incontinence group had lower volume for first sensation and more detrusor overactivity than pure group. ISI did not alter the success of operation. Urodynamically no relationship was found between detrusor pressure and postoperative postvoiding residual urine (P>0.05.In conclusion, urodynamic evaluation before surgery was not related to preoperative and postoperative clinical picture of patients, but first sensation of bladder is only predictive for the success in fascial sling surgery.

  2. Extended cross-section adjustment method to improve the prediction accuracy of core parameters

    International Nuclear Information System (INIS)

    An extended cross-section adjustment method has been developed to improve the prediction accuracy of target core parameters. The present method is on the basis of a cross-section adjustment method which minimizes the uncertainties of target core parameters under the conditions that integral experimental data are given. The present method enables us to enhance the prediction accuracy better than the conventional cross-section adjustment method by taking into account the target core parameters, as well as the extended bias factor method. In addition, it is proved that the present method is equivalent to the extended bias factor method when only one target core parameter is taken into account. The present method is implemented in an existing cross-section adjustment solver. Numerical calculations verify the derived formulation and demonstrate an applicability of an adjusted cross-section set which is specialized for the target core parameters. (author)

  3. Prediction of chemical, physical and sensory data from process parameters for frozen cod using multivariate analysis

    DEFF Research Database (Denmark)

    Bechmann, Iben Ellegaard; Jensen, H.S.; Bøknæs, Niels;

    1998-01-01

    Physical, chemical and sensory quality parameters were determined for 115 cod (Gadus morhua) samples stored under varying frozen storage conditions. Five different process parameters (period of frozen storage, frozen storage. temperature, place of catch, season for catching and state of rigor) were....... PLS models that were able to predict the physical, chemical and sensory quality parameters from the process parameters of the frozen raw material were generated. The prediction abilities of the PLS models were good enough to give reasonable results even when the process parameters were characterised...... by ones and zeroes only. These results illustrate the application of multivariate analysis as an effective strategy for improving the quality of frozen fish products. (C) 1998 Society of Chemical Industry...

  4. Clinical prediction rules for failed nonoperative reduction of intussusception

    Science.gov (United States)

    Khorana, Jiraporn; Patumanond, Jayanton; Ukarapol, Nuthapong; Laohapensang, Mongkol; Visrutaratna, Pannee; Singhavejsakul, Jesda

    2016-01-01

    Purpose The nonoperative reduction of intussusception in children can be performed safely if there are no contraindications. Many risk factors associated with failed reduction were defined. The aim of this study was to develop a scoring system for predicting the failure of nonoperative reduction using various determinants. Patients and methods The data were collected from Chiang Mai University Hospital and Siriraj Hospital from January 2006 to December 2012. Inclusion criteria consisted of patients with intussusception aged 0–15 years with no contraindications for nonoperative reduction. The clinical prediction rules were developed using significant risk factors from the multivariable analysis. Results A total of 170 patients with intussusception were included in the study. In the final analysis model, 154 patients were used for identifying the significant risk factors of failure of reduction. Ten factors clustering by the age of 3 years were identified and used for developing the clinical prediction rules, and the factors were as follows: body weight 48 hours (RR =1.26, P37.8°C (RR =1.51, P<0.001), palpable mass (RR =1.26, P<0.001), location of mass (left over right side RR =1.48, P<0.001), ultrasound showed poor prognostic signs (RR =1.35, P<0.001), and the method of reduction (hydrostatic over pneumatic, RR =1.34, P=0.023). Prediction scores ranged from 0 to 16. A high-risk group (scores 12–16) predicted a greater chance of reduction failure (likelihood ratio of positive [LR+] =18.22, P<0.001). A low-risk group (score 0–11) predicted a lower chance of reduction failure (LR+ =0.79, P<0.001). The performance of the scoring model was 80.68% (area under the receiver operating characteristic curve). Conclusion This scoring guideline was used to predict the results of nonoperative reduction and forecast the prognosis of the failed reduction. The usefulness of these prediction scores is for informing the parents before the reduction. This scoring system can be

  5. Vehicle dynamic prediction systems with on-line identification of vehicle parameters and road conditions.

    Science.gov (United States)

    Hsu, Ling-Yuan; Chen, Tsung-Lin

    2012-01-01

    This paper presents a vehicle dynamics prediction system, which consists of a sensor fusion system and a vehicle parameter identification system. This sensor fusion system can obtain the six degree-of-freedom vehicle dynamics and two road angles without using a vehicle model. The vehicle parameter identification system uses the vehicle dynamics from the sensor fusion system to identify ten vehicle parameters in real time, including vehicle mass, moment of inertial, and road friction coefficients. With above two systems, the future vehicle dynamics is predicted by using a vehicle dynamics model, obtained from the parameter identification system, to propagate with time the current vehicle state values, obtained from the sensor fusion system. Comparing with most existing literatures in this field, the proposed approach improves the prediction accuracy both by incorporating more vehicle dynamics to the prediction system and by on-line identification to minimize the vehicle modeling errors. Simulation results show that the proposed method successfully predicts the vehicle dynamics in a left-hand turn event and a rollover event. The prediction inaccuracy is 0.51% in a left-hand turn event and 27.3% in a rollover event.

  6. Clinical presentation and outcome prediction of clinical, serological, and histopathological classification schemes in ANCA-associated vasculitis with renal involvement.

    Science.gov (United States)

    Córdova-Sánchez, Bertha M; Mejía-Vilet, Juan M; Morales-Buenrostro, Luis E; Loyola-Rodríguez, Georgina; Uribe-Uribe, Norma O; Correa-Rotter, Ricardo

    2016-07-01

    Several classification schemes have been developed for anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), with actual debate focusing on their clinical and prognostic performance. Sixty-two patients with renal biopsy-proven AAV from a single center in Mexico City diagnosed between 2004 and 2013 were analyzed and classified under clinical (granulomatosis with polyangiitis [GPA], microscopic polyangiitis [MPA], renal limited vasculitis [RLV]), serological (proteinase 3 anti-neutrophil cytoplasmic antibodies [PR3-ANCA], myeloperoxidase anti-neutrophil cytoplasmic antibodies [MPO-ANCA], ANCA negative), and histopathological (focal, crescenteric, mixed-type, sclerosing) categories. Clinical presentation parameters were compared at baseline between classification groups, and the predictive value of different classification categories for disease and renal remission, relapse, renal, and patient survival was analyzed. Serological classification predicted relapse rate (PR3-ANCA hazard ratio for relapse 2.93, 1.20-7.17, p = 0.019). There were no differences in disease or renal remission, renal, or patient survival between clinical and serological categories. Histopathological classification predicted response to therapy, with a poorer renal remission rate for sclerosing group and those with less than 25 % normal glomeruli; in addition, it adequately delimited 24-month glomerular filtration rate (eGFR) evolution, but it did not predict renal nor patient survival. On multivariate models, renal replacement therapy (RRT) requirement (HR 8.07, CI 1.75-37.4, p = 0.008) and proteinuria (HR 1.49, CI 1.03-2.14, p = 0.034) at presentation predicted renal survival, while age (HR 1.10, CI 1.01-1.21, p = 0.041) and infective events during the induction phase (HR 4.72, 1.01-22.1, p = 0.049) negatively influenced patient survival. At present, ANCA-based serological classification may predict AAV relapses, but neither clinical nor serological

  7. Soil Parameter Identification for Wheel-terrain Interaction Dynamics and Traversability Prediction

    Institute of Scientific and Technical Information of China (English)

    Suksun Hutangkabodee; Yahya Hashem Zweiri; Lakmal Dasarath Seneviratne; Kaspar Althoefer

    2006-01-01

    This paper presents a novel technique for identifying soil parameters for a wheeled vehicle traversing unknown terrain. The identified soil parameters are required for predicting vehicle drawbar pull and wheel drive torque, which in turn can be used for traversability prediction, traction control, and performance optimization of a wheeled vehicle on unknown terrain. The proposed technique is based on the Newton Raphson method. An approximated form of a wheel-soil interaction model based on Composite Simpson's Rule is employed for this purpose. The key soil parameters to be identified are internal friction angle, shear deformation modulus, and lumped pressure-sinkage coefficient. The fourth parameter, cohesion, is not too relevant to vehicle drawbar pull, and is assigned an average value during the identification process. Identified parameters are compared with known values, and shown to be in agreement. The identification method is relatively fast and robust.The identified soil parameters can effectively be used to predict drawbar pull and wheel drive torque with good accuracy.The use of identified soil parameters to design a traversability criterion for wheeled vehicles traversing unknown terrain is presented.

  8. Prediction Model of Battery State of Charge and Control Parameter Optimization for Electric Vehicle

    Directory of Open Access Journals (Sweden)

    Bambang Wahono

    2015-07-01

    Full Text Available This paper presents the construction of a battery state of charge (SOC prediction model and the optimization method of the said model to appropriately control the number of parameters in compliance with the SOC as the battery output objectives. Research Centre for Electrical Power and Mechatronics, Indonesian Institute of Sciences has tested its electric vehicle research prototype on the road, monitoring its voltage, current, temperature, time, vehicle velocity, motor speed, and SOC during the operation. Using this experimental data, the prediction model of battery SOC was built. Stepwise method considering multicollinearity was able to efficiently develops the battery prediction model that describes the multiple control parameters in relation to the characteristic values such as SOC. It was demonstrated that particle swarm optimization (PSO succesfully and efficiently calculated optimal control parameters to optimize evaluation item such as SOC based on the model.

  9. Identification and prediction of diabetic sensorimotor polyneuropathy using individual and simple combinations of nerve conduction study parameters.

    Directory of Open Access Journals (Sweden)

    Alanna Weisman

    Full Text Available OBJECTIVE: Evaluation of diabetic sensorimotor polyneuropathy (DSP is hindered by the need for complex nerve conduction study (NCS protocols and lack of predictive biomarkers. We aimed to determine the performance of single and simple combinations of NCS parameters for identification and future prediction of DSP. MATERIALS AND METHODS: 406 participants (61 with type 1 diabetes and 345 with type 2 diabetes with a broad spectrum of neuropathy, from none to severe, underwent NCS to determine presence or absence of DSP for cross-sectional (concurrent validity analysis. The 109 participants without baseline DSP were re-evaluated for its future onset (predictive validity. Performance of NCS parameters was compared by area under the receiver operating characteristic curve (AROC. RESULTS: At baseline there were 246 (60% Prevalent Cases. After 3.9 years mean follow-up, 25 (23% of the 109 Prevalent Controls that were followed became Incident DSP Cases. Threshold values for peroneal conduction velocity and sural amplitude potential best identified Prevalent Cases (AROC 0.90 and 0.83, sensitivity 80 and 83%, specificity 89 and 72%, respectively. Baseline tibial F-wave latency, peroneal conduction velocity and the sum of three lower limb nerve conduction velocities (sural, peroneal, and tibial best predicted 4-year incidence (AROC 0.79, 0.79, and 0.85; sensitivity 79, 70, and 81%; specificity 63, 74 and 77%, respectively. DISCUSSION: Individual NCS parameters or their simple combinations are valid measures for identification and future prediction of DSP. Further research into the predictive roles of tibial F-wave latencies, peroneal conduction velocity, and sum of conduction velocities as markers of incipient nerve injury is needed to risk-stratify individuals for clinical and research protocols.

  10. Predictable Outcomes with Porcelain Laminate Veneers: A Clinical Report.

    Science.gov (United States)

    Pimentel, Welson; Teixeira, Marcelo Lucchesi; Costa, Priscila Paganini; Jorge, Mônica Zacharias; Tiossi, Rodrigo

    2016-06-01

    This clinical report describes how to achieve predictable outcomes for anterior teeth esthetic restorations with porcelain laminate veneers by associating the digital planning and design of the restoration with interim restorations. The previous digital smile design of the restoration eliminates the communication barrier with the patient and assists the clinician throughout patient treatment. Interim restorations (diagnostic mock-ups) further enhance communication with the patient and prevent unnecessary tooth reduction for conservative tooth preparation. Adequate communication between patient and clinician contributes to successful definitive restorations and patient satisfaction with the final esthetic outcome.

  11. Predictions of the marviken subcooled critical mass flux using the critical flow scaling parameters

    Energy Technology Data Exchange (ETDEWEB)

    Park, Choon Kyung; Chun, Se Young; Cho, Seok; Yang, Sun Ku; Chung, Moon Ki [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1997-12-31

    A total of 386 critical flow data points from 19 runs of 27 runs in the Marviken Test were selected and compared with the predictions by the correlations based on the critical flow scaling parameters. The results show that the critical mass flux in the very large diameter pipe can be also characterized by two scaling parameters such as discharge coefficient and dimensionless subcooling (C{sub d,ref} and {Delta}{Tau}{sup *} {sub sub}). The agreement between the measured data and the predictions are excellent. 8 refs., 8 figs. 1 tab. (Author)

  12. Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation

    Directory of Open Access Journals (Sweden)

    Gergely Takács

    2014-01-01

    Full Text Available This paper presents an adaptive-predictive vibration control system using extended Kalman filtering for the joint estimation of system states and model parameters. A fixed-free cantilever beam equipped with piezoceramic actuators serves as a test platform to validate the proposed control strategy. Deflection readings taken at the end of the beam have been used to reconstruct the position and velocity information for a second-order state-space model. In addition to the states, the dynamic system has been augmented by the unknown model parameters: stiffness, damping constant, and a voltage/force conversion constant, characterizing the actuating effect of the piezoceramic transducers. The states and parameters of this augmented system have been estimated in real time, using the hybrid extended Kalman filter. The estimated model parameters have been applied to define the continuous state-space model of the vibrating system, which in turn is discretized for the predictive controller. The model predictive control algorithm generates state predictions and dual-mode quadratic cost prediction matrices based on the updated discrete state-space models. The resulting cost function is then minimized using quadratic programming to find the sequence of optimal but constrained control inputs. The proposed active vibration control system is implemented and evaluated experimentally to investigate the viability of the control method.

  13. Evaluation of multivariate linear regression and artificial neural networks in prediction of water quality parameters.

    Science.gov (United States)

    Zare Abyaneh, Hamid

    2014-01-01

    This paper examined the efficiency of multivariate linear regression (MLR) and artificial neural network (ANN) models in prediction of two major water quality parameters in a wastewater treatment plant. Biochemical oxygen demand (BOD) and chemical oxygen demand (COD) as well as indirect indicators of organic matters are representative parameters for sewer water quality. Performance of the ANN models was evaluated using coefficient of correlation (r), root mean square error (RMSE) and bias values. The computed values of BOD and COD by model, ANN method and regression analysis were in close agreement with their respective measured values. Results showed that the ANN performance model was better than the MLR model. Comparative indices of the optimized ANN with input values of temperature (T), pH, total suspended solid (TSS) and total suspended (TS) for prediction of BOD was RMSE = 25.1 mg/L, r = 0.83 and for prediction of COD was RMSE = 49.4 mg/L, r = 0.81. It was found that the ANN model could be employed successfully in estimating the BOD and COD in the inlet of wastewater biochemical treatment plants. Moreover, sensitive examination results showed that pH parameter have more effect on BOD and COD predicting to another parameters. Also, both implemented models have predicted BOD better than COD.

  14. Parameter estimation techniques and uncertainty in ground water flow model predictions

    International Nuclear Information System (INIS)

    Quantification of uncertainty in predictions of nuclear waste repository performance is a requirement of Nuclear Regulatory Commission regulations governing the licensing of proposed geologic repositories for high-level radioactive waste disposal. One of the major uncertainties in these predictions is in estimating the ground-water travel time of radionuclides migrating from the repository to the accessible environment. The cause of much of this uncertainty has been attributed to a lack of knowledge about the hydrogeologic properties that control the movement of radionuclides through the aquifers. A major reason for this lack of knowledge is the paucity of data that is typically available for characterizing complex ground-water flow systems. Because of this, considerable effort has been put into developing parameter estimation techniques that infer property values in regions where no measurements exist. Currently, no single technique has been shown to be superior or even consistently conservative with respect to predictions of ground-water travel time. This work was undertaken to compare a number of parameter estimation techniques and to evaluate how differences in the parameter estimates and the estimation errors are reflected in the behavior of the flow model predictions. That is, we wished to determine to what degree uncertainties in flow model predictions may be affected simply by the choice of parameter estimation technique used. 3 refs., 2 figs

  15. Application of GA–SVM method with parameter optimization for landslide development prediction

    OpenAIRE

    X. Z. LI; Kong, J. M.

    2014-01-01

    Prediction of the landslide development process is always a hot issue in landslide research. So far, many methods for landslide displacement series prediction have been proposed. The support vector machine (SVM) has been proved to be a novel algorithm with good performance. However, the performance strongly depends on the right selection of the parameters (C and γ) of the SVM model. In this study, we present an application of genetic algorithm and support vector machine (GA–...

  16. Comparison between turbinoplasty and endoscopic turbinectomy: Efficacy and clinical parameters

    Directory of Open Access Journals (Sweden)

    Rodrigues, Marcos Marques

    2011-10-01

    Full Text Available Introduction: Nasal Obstruction is a common symptom and affects 25% of the population. The inferior turbinate hypertrophy is the main cause of nasal obstruction. In the failure of clinical control, a surgical procedure to reduce the size of the inferior turbinate is indicated. Objective: Compare the improvement of life quality in late postoperative of Turbinectomy and turbinoplasty. Method: Study of a retrospective case series. 24 patients were submitted to a nasal surgery of turbinectomy or turbinoplasty in 2007. The patients were invited to an interview in august of 2008. The patients were evaluated in the following items: Postoperative NOSE scale, morbidity in postoperative, bleeding and quantity of crusts in postoperative. Results: 24 patients attended for the evaluation. The main variable analyzed was the difference between NOSE scales in late pre and post operative. There was no statistically significant by the test in the variables studied. Discussion: In the evaluation of the various types of surgical treatment of the inferior turbinate, literature shows similar results to our study, finding similar results between many surgical techniques in the improvement of the nasal obstruction and in mucociliary activity. Conclusion: There are no evidence in the literature and in our sample of the superiority of a technique of surgical treatment in the inferior turbinate under other treatments.

  17. Prediction Model of Interval Grey Numbers with a Real Parameter and Its Application

    Directory of Open Access Journals (Sweden)

    Bo Zeng

    2014-01-01

    Full Text Available Grey prediction models have become common methods which are widely employed to solve the problems with “small examples and poor information.” However, modeling objects of existing grey prediction models are limited to the homogenous data sequences which only contain the same data type. This paper studies the methodology of building prediction models of interval grey numbers that are grey heterogeneous data sequence, with a real parameter. Firstly, the position of the real parameter in an interval grey number sequence is discussed, and the real number is expanded into an interval grey number by adopting the method of grey generation. On this basis, a prediction model of interval grey number with a real parameter is deduced and built. Finally, this novel model is successfully applied to forecast the concentration of organic pollutant DDT in the atmosphere. The analysis and research results in this paper extend the object of grey prediction from homogenous data sequence to grey heterogeneous data sequence. Those research findings are of positive significance in terms of enriching and improving the theory system of grey prediction models.

  18. Semi-quantitative parameter analysis of DCE-MRI revisited: monte-carlo simulation, clinical comparisons, and clinical validation of measurement errors in patients with type 2 neurofibromatosis.

    Directory of Open Access Journals (Sweden)

    Alan Jackson

    Full Text Available PURPOSE: To compare semi-quantitative (SQ and pharmacokinetic (PK parameters for analysis of dynamic contrast enhanced MR data (DCE-MRI and investigate error-propagation in SQ parameters. METHODS: Clinical data was collected from five patients with type 2-neurofibromatosis (NF2 receiving anti-angiogenic therapy for rapidly growing vestibular schwannoma (VS. There were 7 VS and 5 meningiomas. Patients were scanned prior to therapy and at days 3 and 90 of treatment. Data was collected using a dual injection technique to permit direct comparison of SQ and PK parameters. Monte Carlo modeling was performed to assess potential measurement errors in SQ parameters in persistent, washout, and weakly enhancing tissues. The simulation predictions for five semi-quantitative parameters were tested using the clinical DCE-MRI data. RESULTS: In VS, SQ parameters and Ktrans showed close correlation and demonstrated similar therapy induced reductions. In meningioma, only the denoised Signal Enhancement Ratio (Rse1/se2(DN showed a significant therapy induced reduction (p<0.05. Simulation demonstrated: 1 Precision of SQ metrics normalized to the pre-contrast-baseline values (MSErel and ∑MSErel is improved by use of an averaged value from multiple baseline scans; 2 signal enhancement ratio Rmse1/mse2 shows considerable susceptibility to noise; 3 removal of outlier values to produce a new parameter, Rmse1/mse2(DN, improves precision and sensitivity to therapy induced changes. Direct comparison of in-vivo analysis with Monte Carlo simulation supported the simulation predicted error distributions of semi-quantitative metrics. CONCLUSION: PK and SQ parameters showed similar sensitivity to anti-angiogenic therapy induced changes in VS. Modeling studies confirmed the benefits of averaging baseline signal from multiple images for normalized SQ metrics and demonstrated poor noise tolerance in the widely used signal enhancement ratio, which is corrected by removal of

  19. Prediction of outcome utilizing both physiological and biochemical parameters in severe head injury.

    Science.gov (United States)

    Low, David; Kuralmani, Vellaisamy; Ng, See Kiong; Lee, Kah Keow; Ng, Ivan; Ang, Beng Ti

    2009-08-01

    Traumatic brain injury is a major socioeconomic burden, and the use of statistical models to predict outcomes after head injury can help to allocate limited health resources. Earlier prediction models analyzing admission data have been used to achieve prediction accuracies of up to 80%. Our aim was to design statistical models utilizing a combination of both physiological and biochemical variables obtained from multimodal monitoring in the neurocritical care setting as a complement to earlier models. We used decision tree and logistic regression analysis on variables including intracranial pressure (ICP), mean arterial pressure (MAP), cerebral perfusion pressure (CPP), and pressure reactivity index (PRx), as well as multimodal monitoring parameters to assess brain tissue oxygenation (PbtO(2)), and microdialysis parameters to predict outcomes based on a dichotomized Glasgow Outcome Score. Further analysis was carried out on various subgroup combinations of physiological and biochemical parameters. The reliability of the head injury models was assessed using a 10-fold cross-validation technique. In addition, the confusion matrix was also used to assess the sensitivity, specificity, and the F-ratio. In all, 2,413 time series records were extracted from 26 patients treated at our neurocritical care unit over a 1-year period. Decision tree analysis was found to be superior to logistic regression analysis in predictive accuracy of outcome. The combined use of microdialysis variables and PbtO(2), in addition to ICP, MAP, and CPP was found have the best predictive accuracy. The use of physiological and biochemical variables based on a decision tree analysis model has shown to provide an improvement in predictive accuracy compared with other previous models. The potential application is for outcome prediction in the multivariate setting of advanced multimodality monitoring, and validates the use of multimodal monitoring in the neurocritical care setting to have a potential

  20. Formalized prediction of clinically significant prostate cancer: is it possible?

    Institute of Scientific and Technical Information of China (English)

    Carvell T Nguyen; Michael W Kattan

    2012-01-01

    Greater understanding of the biology and epidemiology of prostate cancer in the last several decades have led to significant advances in its management.Prostate cancer is now detected in greater numbers at lower stages of disease and is amenable to multiple forms of efficacious treatment.However,there is a lack of conclusive data demonstrating a definitive mortality benefit from this earlier diagnosis and treatment of prostate cancer.It is likely due to the treatment of a large proportion of indolent cancers that would have had little adverse impact on health or lifespan if left alone.Due to this overtreatment phenomenon,active surveillance with delayed intervention is gaining traction as a viable management approach in contemporary practice.The ability to distinguish clinically insignificant cancers from those with a high risk of progression and/or lethality is critical to the appropriate selection of patients for surveillance protocols versus immediate intervention.This chapter will review the ability of various prediction models,including risk groupings and nomograms,to predict indolent disease and determine their role in the contemporary management of clinically localized prostate cancer.

  1. Hydrological model parameter dimensionality is a weak measure of prediction uncertainty

    Directory of Open Access Journals (Sweden)

    S. Pande

    2015-04-01

    Full Text Available This paper shows that instability of hydrological system representation in response to different pieces of information and associated prediction uncertainty is a function of model complexity. After demonstrating the connection between unstable model representation and model complexity, complexity is analyzed in a step by step manner. This is done measuring differences between simulations of a model under different realizations of input forcings. Algorithms are then suggested to estimate model complexity. Model complexities of the two model structures, SAC-SMA (Sacramento Soil Moisture Accounting and its simplified version SIXPAR (Six Parameter Model, are computed on resampled input data sets from basins that span across the continental US. The model complexities for SIXPAR are estimated for various parameter ranges. It is shown that complexity of SIXPAR increases with lower storage capacity and/or higher recession coefficients. Thus it is argued that a conceptually simple model structure, such as SIXPAR, can be more complex than an intuitively more complex model structure, such as SAC-SMA for certain parameter ranges. We therefore contend that magnitudes of feasible model parameters influence the complexity of the model selection problem just as parameter dimensionality (number of parameters does and that parameter dimensionality is an incomplete indicator of stability of hydrological model selection and prediction problems.

  2. Application of fuzzy inference system in the prediction of wave parameters

    Energy Technology Data Exchange (ETDEWEB)

    Kazeminezhad, M.H.; Etemad-Shahidi, A.; Mousavi, S.J. [Iran Univ. of Science and Technology, Structure and Hydrostructure Research Center, Tehran (Iran)

    2005-10-01

    Wave prediction is one of the most important issues in coastal and ocean engineering studies. In this study, the performance of Adaptive-Network-Based Fuzzy Inference System (ANFIS) and Coastal Engineering Manual (CEM) methods for predicting wave parameters were investigated. The data set used in this study comprises fetch-limited wave data and over water wind data gathered from deep-water location in Lake Ontario. The data set of year 2002 was used to develop the ANFIS models as wave predictor models. The data set of year 2003 was then used to test the developed ANFIS models and also the CEM method. Results indicate that ANFIS outperforms the CEM method in terms of prediction capability as the scatter index of predictions of ANFIS is less than that of CEM method. In particular, the CEM method overestimates the significant wave height and underestimates the peak spectral period, while ANFIS results in more accurate predictions. (Author)

  3. The Importance of the Range Parameter for Estimation and Prediction in Geostatistics

    CERN Document Server

    Kaufman, Cari

    2011-01-01

    Two canonical problems in geostatistics are estimating the parameters in a specified family of stochastic process models and predicting the process at new locations. A number of asymptotic results for these problems over a fixed spatial domain indicate that, for a Gaussian process with Mat\\'ern covariance function, one can fix the range parameter controlling the rate of decay of the process and obtain results that are asymptotically equivalent to the case that the range parameter is known. We discuss why these results do not always provide the appropriate intuition for finite samples. Moreover, we prove that a number of these asymptotic results may be extended to the case that the variance and range parameters are jointly estimated via maximum likelihood or maximum tapered likelihood. Our simulation results show that performance on a variety of metrics is improved and asymptotic approximations are applicable for smaller sample sizes when the range parameter is estimated. These effects are particularly apparen...

  4. Nomogram including pretherapeutic parameters for prediction of survival after SIRT of hepatic metastases from colorectal cancer

    International Nuclear Information System (INIS)

    Pre-therapeutic prediction of outcome is important for clinicians and patients in determining whether selective internal radiation therapy (SIRT) is indicated for hepatic metastases of colorectal cancer (CRC). Pre-therapeutic characteristics of 100 patients with colorectal liver metastases (CRLM) treated by radioembolization were analyzed to develop a nomogram for predicting survival. Prognostic factors were selected by univariate Cox regression analysis and subsequent tested by multivariate analysis for predicting patient survival. The nomogram was validated with reference to an external patient cohort (n = 25) from the Bonn University Department of Nuclear Medicine. Of the 13 parameters tested, four were independently associated with reduced patient survival in multivariate analysis. These parameters included no liver surgery before SIRT (HR:1.81, p = 0.014), CEA serum level ≥ 150 ng/ml (HR:2.08, p = 0.001), transaminase toxicity level ≥2.5 x upper limit of normal (HR:2.82, p = 0.001), and summed computed tomography (CT) size of the largest two liver lesions ≥10 cm (HR:2.31, p < 0.001). The area under the receiver-operating characteristic curve for our prediction model was 0.83 for the external patient cohort, indicating superior performance of our multivariate model compared to a model ignoring covariates. The nomogram developed in our study entailing four pre-therapeutic parameters gives good prediction of patient survival post SIRT. (orig.)

  5. Nomogram including pretherapeutic parameters for prediction of survival after SIRT of hepatic metastases from colorectal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Fendler, Wolfgang Peter [Ludwig-Maximilians-University of Munich, Department of Nuclear Medicine, Munich (Germany); Klinik und Poliklinik fuer Nuklearmedizin, Munich (Germany); Ilhan, Harun [Ludwig-Maximilians-University of Munich, Department of Nuclear Medicine, Munich (Germany); Paprottka, Philipp M. [Ludwig-Maximilians-University of Munich, Department of Clinical Radiology, Munich (Germany); Jakobs, Tobias F. [Hospital Barmherzige Brueder, Department of Diagnostic and Interventional Radiology, Munich (Germany); Heinemann, Volker [Ludwig-Maximilians-University of Munich, Department of Internal Medicine III, Munich (Germany); Ludwig-Maximilians-University of Munich, Comprehensive Cancer Center, Munich (Germany); Bartenstein, Peter; Haug, Alexander R. [Ludwig-Maximilians-University of Munich, Department of Nuclear Medicine, Munich (Germany); Ludwig-Maximilians-University of Munich, Comprehensive Cancer Center, Munich (Germany); Khalaf, Feras [University Hospital Bonn, Department of Nuclear Medicine, Bonn (Germany); Ezziddin, Samer [Saarland University Medical Center, Department of Nuclear Medicine, Homburg (Germany); Hacker, Marcus [Vienna General Hospital, Department of Nuclear Medicine, Vienna (Austria)

    2015-09-15

    Pre-therapeutic prediction of outcome is important for clinicians and patients in determining whether selective internal radiation therapy (SIRT) is indicated for hepatic metastases of colorectal cancer (CRC). Pre-therapeutic characteristics of 100 patients with colorectal liver metastases (CRLM) treated by radioembolization were analyzed to develop a nomogram for predicting survival. Prognostic factors were selected by univariate Cox regression analysis and subsequent tested by multivariate analysis for predicting patient survival. The nomogram was validated with reference to an external patient cohort (n = 25) from the Bonn University Department of Nuclear Medicine. Of the 13 parameters tested, four were independently associated with reduced patient survival in multivariate analysis. These parameters included no liver surgery before SIRT (HR:1.81, p = 0.014), CEA serum level ≥ 150 ng/ml (HR:2.08, p = 0.001), transaminase toxicity level ≥2.5 x upper limit of normal (HR:2.82, p = 0.001), and summed computed tomography (CT) size of the largest two liver lesions ≥10 cm (HR:2.31, p < 0.001). The area under the receiver-operating characteristic curve for our prediction model was 0.83 for the external patient cohort, indicating superior performance of our multivariate model compared to a model ignoring covariates. The nomogram developed in our study entailing four pre-therapeutic parameters gives good prediction of patient survival post SIRT. (orig.)

  6. Conditioning rainfall-runoff model parameter space to reduce prediction uncertainty in ungauged basins

    Science.gov (United States)

    Visessri, S.; Mcintyre, N.

    2012-04-01

    Prediction of streamflow for ungauged basins is associated with large uncertainty arising from input data, model structure, and parameter values. This paper investigates how conditioning the prior parameter space using regionalised indices of streamflow affects the prediction uncertainty for ungauged basins. The main concept used is filtering out the rainfall-runoff model parameter sets that do not give estimates of streamflow indices close to the regionalised values. These values are calculated based on regression equations, and associated Gaussian error distributions, constructed from the relationship between physical catchment properties and streamflow indices at gauged sites. The performance of the model is measured by 1-NSE and 1-log(NSE) for high and low flow fitting accordingly, calculated on daily and on monthly intervals. Ability to capture streamflow and reduction in prediction uncertainty is judged by reliability and sharpness. The case study is the upper Ping River in Thailand and the spatially lumped IHACRES model is used. Using the range defined by the regression at 95% confidence level of rainfall-runoff elasticity and base flow index to condition the prior parameter space is useful for reducing streamflow prediction uncertainty. The reliability obtained from conditioned parameter space is high, 73-99%, but the sharpness is low, 7-31%. It is suggested in this study that concurrently reaching the high sharpness and reliability is difficult, maybe due to poor data quality and high spatial variability of daily rainfall in this tropical region. The model usually overestimates peak flow throughout the period of simulation. The prior range of parameter values also contributes to the performance of the model but in this case rather wide prior parameter ranges are needed to accommodate all possible parameter values for all subcatchments which have various physical characteristics. The use of runoff coefficient to reduce uncertainty in streamflow prediction

  7. Prediction of Permeation Resistance of Protective Gloves, etc. from Solubility Parameters

    DEFF Research Database (Denmark)

    Henriksen, H. Risvig; Madsen, Jørgen Øgaard

    1997-01-01

    ). A starting point was the authoritative conclusion (Coletta et al., 1978), that permeation in protective clothing could not be predicted. As a spin off, the predictive concept indicated that new types of polymers sometimes should be incorporated to reach a reasonable (long) breakthrough time and (low......) permation rate (Henriksen 1982, 91, 92, 93, Henriksen et al., 1986,). Concrete products were designed and the new materials are today applied by several companies. Many researchers were inspired. In this presentation experience with practical prediction from the concept developed (MAXIPARDIF) is summarized...... and a new method to estimate of the 3D parameters for protective garment polymers is suggested. Some 3D parameters calculated this way are presented....

  8. Predictability of malaria parameters in Sahel under the S4CAST Model.

    Science.gov (United States)

    Diouf, Ibrahima; Rodríguez-Fonseca, Belen; Deme, Abdoulaye; Cisse, Moustapha; Ndione, Jaques-Andre; Gaye, Amadou; Suárez-Moreno, Roberto

    2016-04-01

    An extensive literature exists documenting the ENSO impacts on infectious diseases, including malaria. Other studies, however, have already focused on cholera, dengue and Rift Valley Fever. This study explores the seasonal predictability of malaria outbreaks over Sahel from previous SSTs of Pacific and Atlantic basins. The SST may be considered as a source of predictability due to its direct influence on rainfall and temperature, thus also other related variables like malaria parameters. In this work, the model has been applied to the study of predictability of the Sahelian malaria parameters from the leading MCA covariability mode in the framework of climate and health issue. The results of this work will be useful for decision makers to better access to climate forecasts and application on malaria transmission risk.

  9. Prevalence of herpesviruses in gingivitis and chronic periodontitis: relationship to clinical parameters and effect of treatment

    OpenAIRE

    Rucha Shah; Dhoom Singh Mehta

    2016-01-01

    Background: Assess the prevalence of herpesviruses in healthy subjects, gingivitis, and chronic periodontitis patients, to assess the relationship between the prevalence of herpesviruses and periodontal clinical parameters, and to evaluate the effect of phase-I therapy on the level of viral detection. Materials and Methods: Hundred patients consisting of 20 healthy subjects, 40 gingivitis, and 40 chronic periodontitis were included in the study. Clinical parameters recorded included plaque in...

  10. Prediction of data stream parameters in atmospheric turbulent wireless communication links

    Science.gov (United States)

    Tiker, A.; Yarkoni, N.; Blaunstein, N.; Zilberman, A.; Kopeika, N.

    2007-01-01

    A unified approach for calculation of information data stream parameters in the atmospheric optical communication channel is presented based on irradiance fluctuations of optical wave propagation through turbulence and on a generalized Ricean K-parameter distribution. The effects of turbulence are described via the well-known Kolmogorov scheme of turbulent structure relaxation in terms of stochastic scintillation theory described by the gamma-gamma distribution along with measurements of the values of the refractive index structure parameter, Cn 2. The relation between the Ricean parameter K and the signal scintillation parameter σI 2 is considered to develop a unified description of the corresponding probability density function (pdf) of signal fading within an atmospheric wireless communication link. Through the corresponding pdf and parameter K, signal data stream parameters such as the signal-to-noise ratio (SNR), bit error rate (BER), and capacity of the optical atmospheric channel (C) are estimated. Such an approach permits the reliable prediction of the effects of fading caused by different levels of turbulence and agrees with experimental data observed at different atmospheric levels, at the heights of both 100-200 m and above 1-2 km. It is shown that at heights of 100-200 m, effects of fading, caused by turbulence, occur much more frequently than those at the heights of 1-2 km. Data stream parameters such as channel capacity, SNR, and spectral efficiency become stronger at higher altitudes, while at the same time the BER becomes relatively negligible.

  11. Predictive value of semen parameters and age of the couple in pregnancy outcome after Intrauterine insemination

    Directory of Open Access Journals (Sweden)

    Marjan Sabbaghian

    2013-11-01

    Full Text Available Background: Intrauterine insemination (IUI is one the most common methods in infertility treatment, but its efficiency in infertile couples with male factor is controversial. This study is a retrospective study about correlation between semen parameters and male and female age with successful rate of IUI in patients attending to Royan Institute.Methods: A total of 998 consecutive couples in a period of 6 months undergoing IUI were included. They were classified into two groups: couples with successful and unsuccessful pregnancy. Main outcome was clinical pregnancy. Data about male and female ages and semen analysis including concentration, total sperm motility, class A motility, class B motility, class A+B motility and normal morphology was extracted from patients’ records. Semen samples were collected by masturbation or coitus after 2 to 7 days of abstinence. Their female partners were reported to have no chronic medi-cal conditions and have normal menstrual cycles.Results: One hundred and fifty seven of total 998 cycles (15.7% achieved pregnancy. The average of female age in successful and unsuccessful group was 28.95±4.19 and 30.00±4.56 years, respectively. Mean of male age was 33.97±4.85 years in successful group and 34.44±4.62 years in unsuccessful group. In successful and unsuccessful groups, average of sperm concentration was 53.62±38.45 and 46.26±26.59 (million sperm/ml, normal morphology of sperm was 8.98±4.31 (% and 8.68±4.81 (%, sperm total motility was 47.24±18.92 (% and 43.70±20.22 (% and total motile sperm count was 80.10±63.61 million and 78.57±68.22 million, respectively.Conclusion: There was no significant difference in mean of females’ age and males’ age between successful and unsuccessful groups (P<0.05. In addition, there was no significant difference in semen parameters including concentration, total sperm motility, class A motility, class B motility, class A+B motility and normal morphology between two

  12. Parametric computation predicts a multiplicative interaction between synaptic strength parameters that controls properties of gamma oscillations

    Directory of Open Access Journals (Sweden)

    Jordan eChambers

    2012-07-01

    Full Text Available Gamma oscillations are thought to be critical for a number of behavioural functions, they occur in many regions of the brain and through a variety of mechanisms. Fast repetitive bursting (FRB neurons in layer 2 of the cortex are able to drive gamma oscillations over long periods of time. Even though the oscillation is driven by FRB neurons, strong feedback within the rest of the cortex must modulate properties of the oscillation such as frequency and power. We used a highly detailed model of the cortex to determine how a cohort of 33 parameters controlling synaptic drive might modulate gamma oscillation properties. We were interested in determining not just the effects of parameters individually, but we also wanted to reveal interactions between parameters beyond additive effects. To prevent a combinatorial explosion in parameter combinations that might need to be simulated, we used a fractional factorial design that estimated the effects of individual parameters and two parameter interactions. This experiment required only 4096 model runs. We found that the largest effects on both gamma power and frequency came from a complex interaction between efficacy of synaptic connections from layer 2 inhibitory neurons to layer 2 excitatory neurons and the parameter for the reciprocal connection. As well as the effect of the individual parameters determining synaptic efficacy, there was multiplicative an interaction between these parameters beyond the additive effects of the parameters alone. The magnitude of this effect was similar to that of the individual parameters, predicting that it is physiologically important in setting gamma oscillation properties.

  13. PREDICTION OF CLINICAL EFFICIENCY OF SIMVASTATIN TREATMENT IN PATIENTS WITH RHEUMATOID ARTHRITIS

    Directory of Open Access Journals (Sweden)

    I. V. Shirinsky

    2009-01-01

    Full Text Available Abstract. Treatment with statins results in reduction of disease activity in one-third of patients with rheumatoid arthritis (RA. The aim of this study was to assess some factors that may predict clinical response to simvastatin therapy before starting the treatment. We evaluated an association of treatment efficacy with baseline clinical and laboratory parameters including disease activity measures, cytokine profiles in sera and culture supernatants of peripheral blood mononuclear cells. Thirty-three patients with active RA were enrolled in the study. The patients were treated with simvastatin at 40 mg/day for three months. Eleven patients (33% developed a moderate response according to EULAR criteria. It was shown that serum IL-10 concentrations was higher in responders, and positively correlated with clinical response to simvastatin. We carried out a receiver operating characteristic curve (ROC analysis in order to assess the accuracy of serum IL-10 for the predicting of EULAR response development. The cut-off threshold corresponding to the highest sensitivity (89% and specificity (62% was a value of 6.5 pg/ml. In conclusion, the performance characteristics of serum IL-10 measurement proved to be good enough to predict EULAR response to simvastatin therapy in RA patients.

  14. Effects of time-averaging climate parameters on predicted multicompartmental fate of pesticides and POPs.

    Science.gov (United States)

    Lammel, Gerhard

    2004-01-01

    With the aim to investigate the justification of time-averaging of climate parameters in multicompartment modelling the effects of various climate parameters and different modes of entry on the predicted substances' total environmental burdens and the compartmental fractions were studied. A simple, non-steady state zero-dimensional (box) mass-balance model of intercompartmental mass exchange which comprises four compartments was used for this purpose. Each two runs were performed, one temporally unresolved (time-averaged conditions) and a time-resolved (hourly or higher) control run. In many cases significant discrepancies are predicted, depending on the substance and on the parameter. We find discrepancies exceeding 10% relative to the control run and up to an order of magnitude for prediction of the total environmental burden from neglecting seasonalities of the soil and ocean temperatures and the hydroxyl radical concentration in the atmosphere and diurnalities of atmospheric mixing depth and the hydroxyl radical concentration in the atmosphere. Under some conditions it was indicated that substance sensitivity could be explained by the magnitude of the sink terms in the compartment(s) with parameters varying. In general, however, any key for understanding substance sensitivity seems not be linked in an easy manner to the properties of the substance, to the fractions of its burden or to the sink terms in either of the compartments with parameters varying. Averaging of diurnal variability was found to cause errors of total environmental residence time of different sign for different substances. The effects of time-averaging of several parameters are in general not additive but synergistic as well as compensatory effects occur. An implication of these findings is that the ranking of substances according to persistence is sensitive to time resolution on the scale of hours to months. As a conclusion it is recommended to use high temporal resolution in multi

  15. Recursive Parameter Method for Computing the Predicting Function of the Multivariable ARMAX Model

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    New method for computing the predicting function of the ARMAX model is proposed. The proposed method constructs a set of schemes for recursively computing the parameters in predicting function of the ARMAX model. In contrast to the existing method, that only gives results for the special case of the ARX model, the method presented is suitable not only for an SISO system, but also for an MIMO system. For the SISO system, the method presented here is even more convenient than the exisiting ones.

  16. Conditioning rainfall-runoff model parameters to reduce prediction uncertainty in ungauged basins

    Science.gov (United States)

    Visessri, S.; McIntyre, N.; Maksimovic, C.

    2012-12-01

    Conditioning rainfall-runoff model parameters in ungauged catchments in Thailand presents problems common to ungauged basins involving data availability, data quality, and rainfall-runoff model suitability, which all contribute to prediction uncertainty. This paper attempts to improve the estimation of streamflow in ungauged basins and reduce associated uncertainties using the approaches of conditioning the prior parameter space. 35 catchments from the upper Ping River basin, Thailand are selected as a case study. The catchments have a range of attributes e.g. catchment sizes 20-6350 km2, elevations 632-1529 m above sea level. and annual rainfall 846-1447 mm/year. For each catchment, three indices - rainfall-runoff elasticity, base flow index and runoff coefficient - are calculated using the observed rainfall-runoff data and regression equations relating these indices to the catchment attributes are identified. Uncertainty in expected indices is defined by the regression error distribution, approximated by a Gaussian model. The IHACRES model is applied for simulating streamflow. The IHACRES parameters are randomly sampled from their presumed prior parameter space. For each sampled parameter set, the streamflow and hence the three indices are modelled. The parameter sets are conditioned on the probability distributions of the regionalised indices, allowing ensemble predictions to be made. The objective function, NSE, calculated for daily and weekly time steps from the water years 1995-2000, is used to assess model performance. Ability to capture observed streamflow and the precision of the estimate is evaluated using reliability and sharpness measures. Similarity in modelled and expected indices contributes to good objective function values. Using only the regionalised runoff coefficient to condition the model yields better NSE values compared to using either only the rainfall-runoff elasticity or only the base flow index. Conditioning on the runoff coefficient

  17. Prediction of HAZ grain size in welding of ultra fine grained steel with different parameters

    Institute of Scientific and Technical Information of China (English)

    Zhao Hongyun; Zhang Hongtao; Li Dongqing; Wang Guodong

    2010-01-01

    The temperature field and thermal cycling curve in the heat-affected zone during welding 400 MPa ultra fine grained steel by plasma arc were simulated using finite element method.The principle of grain growth kinetics was used to predict the grain size in the heat-affected zone under different welding parameters.The simulation results show that the growing tendency of HAZ grain could be controlled by adjusting the welding parameters,but the growth of HAZ grain could not be eliminated at all.The HAZ grain size became small with increasing of the cooling rate and added with increasing of welding current,arc voltage and welding speed.

  18. Predicting future conflict between team-members with parameter-free models of social networks

    OpenAIRE

    Rovira-Asenjo, Núria; Gumí, Tània; Sales-Pardo, Marta; Guimerà, Roger

    2014-01-01

    Despite the well-documented benefits of working in teams, teamwork also results in communication, coordination and management costs, and may lead to personal conflict between team members. In a context where teams play an increasingly important role, it is of major importance to understand conflict and to develop diagnostic tools to avert it. Here, we investigate empirically whether it is possible to quantitatively predict future conflict in small teams using parameter-free models of social n...

  19. Predicting Nitrate Concentration in Groundwater Resources using Lumped-Parameter Model: Case Study in Qazvin Plain

    OpenAIRE

    R.S Hajimirmohammad Ali; H Karyab

    2016-01-01

    Background and Objective: The concentration of nitrate, factors affecting the balance sheet, and the changes in an aquifer is of utmost importance. Because modeling is an efficient method to predict the concentration of ions in water resources, in this study using lumped-parameter model and Monte Carlo simulation model, the nitrate concentrations in groundwater resources of Qazvin Plain were estimated and analyzed. Materials and Methods: A total of 19 wells in different climates of saline...

  20. Predicting the Flory-Huggins χ Parameter for Polymers with Stiffness Mismatch from Molecular Dynamics Simulations

    OpenAIRE

    Daniel J. Kozuch; Wenlin Zhang; Milner, Scott T.

    2016-01-01

    The Flory–Huggins χ parameter describes the excess free energy of mixing and governs phase behavior for polymer blends and block copolymers. For chemically-distinct nonpolar polymers, the value of χ is dominated by the mismatch in cohesive energy densities of the monomers. For blends of chemically-similar polymers, the entropic portion of χ, arising from non-ideal local packing, becomes more significant. Using polymer field theory, Fredrickson et al. predicted that a difference in backbone st...

  1. Multi-Variable Model-Based Parameter Estimation Model for Antenna Radiation Pattern Prediction

    Science.gov (United States)

    Deshpande, Manohar D.; Cravey, Robin L.

    2002-01-01

    A new procedure is presented to develop multi-variable model-based parameter estimation (MBPE) model to predict far field intensity of antenna. By performing MBPE model development procedure on a single variable at a time, the present method requires solution of smaller size matrices. The utility of the present method is demonstrated by determining far field intensity due to a dipole antenna over a frequency range of 100-1000 MHz and elevation angle range of 0-90 degrees.

  2. Alternative Schemes of Predicting Lepton Mixing Parameters from Discrete Flavor and CP Symmetry

    CERN Document Server

    Lu, Jun-Nan

    2016-01-01

    We suggest two alternative schemes to predict lepton mixing angles as well as $CP$ violating phases from a discrete flavor symmetry group combined with $CP$ symmetry. In the first scenario, the flavor and $CP$ symmetry is broken to the residual groups of the structure $Z_2\\times CP$ in the neutrino and charged lepton sectors. The resulting lepton mixing matrix depends on two free parameters $\\theta_{\

  3. A New Least Squares Support Vector Machines Ensemble Model for Aero Engine Performance Parameter Chaotic Prediction

    OpenAIRE

    Dangdang Du; Xiaoliang Jia; Chaobo Hao

    2016-01-01

    Aiming at the nonlinearity, chaos, and small-sample of aero engine performance parameters data, a new ensemble model, named the least squares support vector machine (LSSVM) ensemble model with phase space reconstruction (PSR) and particle swarm optimization (PSO), is presented. First, to guarantee the diversity of individual members, different single kernel LSSVMs are selected as base predictors, and they also output the primary prediction results independently. Then, all the primary predicti...

  4. Correlations between Plasma Levels of Anionic Uremic Toxins and Clinical Parameters in Hemodialysis Patients.

    Science.gov (United States)

    Ichimura, Yuichi; Takamatsu, Hiroyuki; Ideuchi, Hideki; Oda, Masako; Takeda, Kiyotaka; Saitoh, Hiroshi

    2016-01-01

    When the kidney is seriously impaired, various uremic toxins (UTs) accumulate in the body, often exerting unfavorable effects on physiological functions and drug pharmacokinetics. To prevent this, it is important to determine plasma UT levels accurately in chronic kidney disease patients. Although attempts to predict plasma UT levels using biomarkers have been made, the correlation between UT levels and the markers is not yet fully understood. In this study, we assessed the correlations among plasma levels of indoxyl sulfate (IS), indoleacetic acid (IA), and 3-carboxy-4-methyl-5-propyl-2-furanpropionic acid (CMPF) in 20 hemodialysis patients and evaluated the relationship between the plasma levels of UTs and clinical parameters, such as serum creatinine (Scr), blood urea nitrogen, and estimated glomerular filtration rate (eGFR), with special focus on IS. There were no correlations among the plasma levels of the three UTs before and immediately after hemodialysis. However, a significant correlation was observed between plasma IS levels and Scr before hemodialysis (r=0.643, p=0.002), with the correlation becoming much stronger when using the data obtained immediately after hemodialysis (r=0.744, pScr values, although the precise mechanism behind the correlation remains to be clarified. PMID:27477735

  5. The predicted influence of climate change on lesser prairie-chicken reproductive parameters

    Science.gov (United States)

    Grisham, Blake A.; Boal, Clint W.; Haukos, David A.; Davis, Dawn M.; Boydston, Kathy K.; Dixon, Charles; Heck, Willard R.

    2013-01-01

    The Southern High Plains is anticipated to experience significant changes in temperature and precipitation due to climate change. These changes may influence the lesser prairie-chicken (Tympanuchus pallidicinctus) in positive or negative ways. We assessed the potential changes in clutch size, incubation start date, and nest survival for lesser prairie-chickens for the years 2050 and 2080 based on modeled predictions of climate change and reproductive data for lesser prairie-chickens from 2001–2011 on the Southern High Plains of Texas and New Mexico. We developed 9 a priori models to assess the relationship between reproductive parameters and biologically relevant weather conditions. We selected weather variable(s) with the most model support and then obtained future predicted values from climatewizard.org. We conducted 1,000 simulations using each reproductive parameter’s linear equation obtained from regression calculations, and the future predicted value for each weather variable to predict future reproductive parameter values for lesser prairie-chickens. There was a high degree of model uncertainty for each reproductive value. Winter temperature had the greatest effect size for all three parameters, suggesting a negative relationship between above-average winter temperature and reproductive output. The above-average winter temperatures are correlated to La Niña events, which negatively affect lesser prairie-chickens through resulting drought conditions. By 2050 and 2080, nest survival was predicted to be below levels considered viable for population persistence; however, our assessment did not consider annual survival of adults, chick survival, or the positive benefit of habitat management and conservation, which may ultimately offset the potentially negative effect of drought on nest survival.

  6. A simple methodology for predicting laser-weld properties from material and laser parameters

    International Nuclear Information System (INIS)

    In laser material processing, understanding the laser interaction and the effect of processing parameters on this interaction is fundamental to any process if the system is to be optimized. Expanding this to different materials or other laser systems with different beam characteristics makes this interaction more complex and difficult to resolve. This work presents a relatively simple physical model to understand these interactions in terms of mean surface enthalpy values derived from both material parameters and laser parameters. From these fundamental properties the melt depth and width for any material can be predicted using a simple theory. By considering the mean enthalpy of the surface, the transition from conduction limited melting to keyholing can also be accurately predicted. The theory is compared to experimental results and the predicted and observed data are shown to correspond well for these experimental results as well as for published results for stainless steel and for a range of metals. The results suggest that it is important to keep the Fourier number of the weld much smaller than one to make it efficient. It is also discussed that the surface enthalpy could be used to prodict other effects in the weld such as porosity and material expulsion.

  7. Prediction of Aqueous Solubility for 209 Polychlorinated Diphenyl Ethers from Molecular Structural Parameters by DFT Method

    Institute of Scientific and Technical Information of China (English)

    XIE Ya-Jie; LIU Hong-Xia; WANG Zun-Yao; ZHU Li-Dan

    2008-01-01

    Optimized calculations of 209 polychlorinated diphenyl ethers (PCDEs) and diphenyl ethers were carried out at the B3LYP/6-31G* level with the Gaussian 98 program. Based on the theoretical linear solvation energy relationship (TLSER) model, the obtained structural parameters were taken as theoretical descriptors to establish the novel QSPR model for predicting aqueous solubility (-lgSw) of PCDEs. The model obtained in this work contains two variables: mean molecular polarizability (α) and the most positive partial charge on a hydrogen atom (qH+), of which R2 = 0.9606 and SD = 0.32. And the results of cross-validation test also show that the model exhibits optimum stability and better predictive power. Moreover, the predictive power of the new model is better than that of MCIs method.

  8. A New Least Squares Support Vector Machines Ensemble Model for Aero Engine Performance Parameter Chaotic Prediction

    Directory of Open Access Journals (Sweden)

    Dangdang Du

    2016-01-01

    Full Text Available Aiming at the nonlinearity, chaos, and small-sample of aero engine performance parameters data, a new ensemble model, named the least squares support vector machine (LSSVM ensemble model with phase space reconstruction (PSR and particle swarm optimization (PSO, is presented. First, to guarantee the diversity of individual members, different single kernel LSSVMs are selected as base predictors, and they also output the primary prediction results independently. Then, all the primary prediction results are integrated to produce the most appropriate prediction results by another particular LSSVM—a multiple kernel LSSVM, which reduces the dependence of modeling accuracy on kernel function and parameters. Phase space reconstruction theory is applied to extract the chaotic characteristic of input data source and reconstruct the data sample, and particle swarm optimization algorithm is used to obtain the best LSSVM individual members. A case study is employed to verify the effectiveness of presented model with real operation data of aero engine. The results show that prediction accuracy of the proposed model improves obviously compared with other three models.

  9. Predictive value of CASA parameters in IUI with frozen donor sperm.

    Science.gov (United States)

    Freour, Thomas; Jean, Miguel; Mirallie, Sophie; Langlois, Marie-Laure; Dubourdieu, Sophie; Barriere, Paul

    2009-10-01

    The objective of this study was to determine if characteristics of sperm motion determined by computer-aided semen analysis (CASA) after thawing and preparation on discontinuous gradient could predict pregnancy outcome after intrauterine insemination (IUI) from frozen donor sperm. A retrospective analysis of 100 non-selected women undergoing 171 consecutive donor insemination cycles was conducted between January 2006 and April 2007. Semen samples from all donors were analysed after thawing and density gradient preparation. Women who became pregnant and those who did not were comparable in terms of age, ovarian stimulation regimen and indication of IUI with donor semen. Pregnancy rate per cycle was 21.8%, and pregnancy occurred after 2.5 IUI cycles on average. Motility parameters of sperm measured by CASA (VAP, VCL, VSL, LIN, STR, and ALH) and total spermatozoa concentration after preparation on discontinuous gradient showed no difference in both groups. Progressive and total motile spermatozoa concentration, as well as progressive and total motile percentages was significantly higher in pregnancy group. The receiver operating characteristic (ROC) curve analysis showed that total motile percentage >17% and motile concentration >0.9 x 10(6)/mL best predicted pregnancy. In a multivariate analysis, only total motility percentage was able to predict pregnancy. Sperm motility parameters of frozen-thawed prepared donor sperm obtained by CASA do not seem to predict pregnancy in IUI cycles. Total motile and progressive percentages and concentrations remain the best prognostic elements for pregnancy in IUI with donor semen.

  10. Development of Health Parameter Model for Risk Prediction of CVD Using SVM.

    Science.gov (United States)

    Unnikrishnan, P; Kumar, D K; Poosapadi Arjunan, S; Kumar, H; Mitchell, P; Kawasaki, R

    2016-01-01

    Current methods of cardiovascular risk assessment are performed using health factors which are often based on the Framingham study. However, these methods have significant limitations due to their poor sensitivity and specificity. We have compared the parameters from the Framingham equation with linear regression analysis to establish the effect of training of the model for the local database. Support vector machine was used to determine the effectiveness of machine learning approach with the Framingham health parameters for risk assessment of cardiovascular disease (CVD). The result shows that while linear model trained using local database was an improvement on Framingham model, SVM based risk assessment model had high sensitivity and specificity of prediction of CVD. This indicates that using the health parameters identified using Framingham study, machine learning approach overcomes the low sensitivity and specificity of Framingham model. PMID:27594895

  11. Estimating unknown input parameters when implementing the NGA ground-motion prediction equations in engineering practice

    Science.gov (United States)

    Kaklamanos, James; Baise, Laurie G.; Boore, David M.

    2011-01-01

    The ground-motion prediction equations (GMPEs) developed as part of the Next Generation Attenuation of Ground Motions (NGA-West) project in 2008 are becoming widely used in seismic hazard analyses. However, these new models are considerably more complicated than previous GMPEs, and they require several more input parameters. When employing the NGA models, users routinely face situations in which some of the required input parameters are unknown. In this paper, we present a framework for estimating the unknown source, path, and site parameters when implementing the NGA models in engineering practice, and we derive geometrically-based equations relating the three distance measures found in the NGA models. Our intent is for the content of this paper not only to make the NGA models more accessible, but also to help with the implementation of other present or future GMPEs.

  12. Analyzing model uncertainty in predicted surface fluxes resulting from prescribed soil and vegetation parameters

    Science.gov (United States)

    Jankov, M.; Prochaka, L.; Mölders, N.

    2003-12-01

    The atmosphere and land-surface continuously interact, for which the surface affects current weather and climate. The biosphere-soil system plays an important role because it is the media in those interactions. The processes that describe those interactions are the exchange of momentuum, heat, water vapor, and matter. To include these processes at the soil-biosphere-atmosphere interface in atmospheric models they have to be parameterized. The different vegetation and soil types are realized by prescribed plant physiological and soil physical parameters (e.g. soil hydraulic conductivity, soil thermal conductivity, porosity, pore-size distribution index, leaf area index, albedo and emissivity of the foliage and soil, minimum stomatal resistance, canopy height, etc.) in these parameterizations. The parameters can vary even among the same soil or plant type. The order of magnitude of those variations can be as much as the mean values of the parameters themselves. In order to improve weather prediction the model uncertainty, caused by the necessity to prescribe parameters, has to be minimized. To asses the errors uncertainty analysis with respect to the prescribed parameters is carried out using the Gaussian Error Propagation method. We use the PennState/NCAR mesoscale meteorological model MM5 coupled with the Oregon State University land surface model (OSULSM) as the test-platform. The Gaussian Error Propagation technique provides error bars for the fluxes simulated by MM5. Moreover, the technique can point out which parameters contribute the most to the error, and should be replaced in future model development. Our preliminary results show that throughout the domain errors were at low or moderate levels. The highest errors predicted appear to be associated with scarcely vegetated, sandy clay loam areas and areas covered by ice and snow.

  13. Dynamic Contrast-Enhanced MRI of Cervical Cancers: Temporal Percentile Screening of Contrast Enhancement Identifies Parameters for Prediction of Chemoradioresistance

    International Nuclear Information System (INIS)

    Purpose: To systematically screen the tumor contrast enhancement of locally advanced cervical cancers to assess the prognostic value of two descriptive parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Methods and Materials: This study included a prospectively collected cohort of 81 patients who underwent DCE-MRI with gadopentetate dimeglumine before chemoradiotherapy. The following descriptive DCE-MRI parameters were extracted voxel by voxel and presented as histograms for each time point in the dynamic series: normalized relative signal increase (nRSI) and normalized area under the curve (nAUC). The first to 100th percentiles of the histograms were included in a log-rank survival test, resulting in p value and relative risk maps of all percentile–time intervals for each DCE-MRI parameter. The maps were used to evaluate the robustness of the individual percentile–time pairs and to construct prognostic parameters. Clinical endpoints were locoregional control and progression-free survival. The study was approved by the institutional ethics committee. Results: The p value maps of nRSI and nAUC showed a large continuous region of percentile–time pairs that were significantly associated with locoregional control (p < 0.05). These parameters had prognostic impact independent of tumor stage, volume, and lymph node status on multivariate analysis. Only a small percentile–time interval of nRSI was associated with progression-free survival. Conclusions: The percentile–time screening identified DCE-MRI parameters that predict long-term locoregional control after chemoradiotherapy of cervical cancer.

  14. Predictive significance of standardized uptake value parameters of FDG-PET in patients with non-small cell lung carcinoma

    Energy Technology Data Exchange (ETDEWEB)

    Duan, X-Y.; Wang, W.; Li, M.; Li, Y.; Guo, Y-M. [PET-CT Center, The First Affiliated Hospital of Xi' an, Jiaotong University, Xi' an, Shaanxi (China)

    2015-02-03

    {sup 18}F-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) is widely used to diagnose and stage non-small cell lung cancer (NSCLC). The aim of this retrospective study was to evaluate the predictive ability of different FDG standardized uptake values (SUVs) in 74 patients with newly diagnosed NSCLC. {sup 18}F-FDG PET/CT scans were performed and different SUV parameters (SUV{sub max}, SUV{sub avg}, SUV{sub T/L}, and SUV{sub T/A}) obtained, and their relationship with clinical characteristics were investigated. Meanwhile, correlation and multiple stepwise regression analyses were performed to determine the primary predictor of SUVs for NSCLC. Age, gender, and tumor size significantly affected SUV parameters. The mean SUVs of squamous cell carcinoma were higher than those of adenocarcinoma. Poorly differentiated tumors exhibited higher SUVs than well-differentiated ones. Further analyses based on the pathologic type revealed that the SUV{sub max}, SUV{sub avg}, and SUV{sub T/L} of poorly differentiated adenocarcinoma tumors were higher than those of moderately or well-differentiated tumors. Among these four SUV parameters, SUV{sub T/L} was the primary predictor for tumor differentiation. However, in adenocarcinoma, SUV{sub max} was the determining factor for tumor differentiation. Our results showed that these four SUV parameters had predictive significance related to NSCLC tumor differentiation; SUV{sub T/L} appeared to be most useful overall, but SUV{sub max} was the best index for adenocarcinoma tumor differentiation.

  15. Multi-output ANN Model for Prediction of Seven Meteorological Parameters in a Weather Station

    Science.gov (United States)

    Raza, Khalid; Jothiprakash, V.

    2014-12-01

    The meteorological parameters plays a vital role for determining various water demand in the water resource systems, planning, management and operation. Thus, accurate prediction of meteorological variables at different spatial and temporal intervals is the key requirement. Artificial Neural Network (ANN) is one of the most widely used data driven modelling techniques with lots of good features like, easy applications, high accuracy in prediction and to predict the multi-output complex non-linear relationships. In this paper, a Multi-input Multi-output (MIMO) ANN model has been developed and applied to predict seven important meteorological parameters, such as maximum temperature, minimum temperature, relative humidity, wind speed, sunshine hours, dew point temperature and evaporation concurrently. Several types of ANN, such as multilayer perceptron, generalized feedforward neural network, radial basis function and recurrent neural network with multi hidden layer and varying number of neurons at the hidden layer, has been developed, trained, validated and tested. From the results, it is found that the recurrent MIMO-ANN having 28 neurons in a single hidden layer, trained using hyperbolic tangent transfer function with a learning rate of 0.3 and momentum factor of 0.7 performed well over the other types of MIMO-ANN models. The MIMO ANN model performed well for all parameters with higher correlation and other performance indicators except for sunshine hours. Due to erratic nature, the importance of each of the input over the output through sensitivity analysis indicated that relative humidity has highest influence while others have equal influence over the output.

  16. Clinical Nomogram for Predicting Survival of Esophageal Cancer Patients after Esophagectomy

    Science.gov (United States)

    Cao, Jinlin; Yuan, Ping; Wang, Luming; Wang, Yiqing; Ma, Honghai; Yuan, Xiaoshuai; Lv, Wang; Hu, Jian

    2016-01-01

    The aim of this study was to construct an effective clinical nomogram for predicting the survival of esophageal cancer patients after esophagectomy. We identified esophageal cancer patients (n = 4,281) who underwent esophagectomy between 1988 and 2007 from the Surveillance, Epidemiology, and End Results (SEER) 18 registries database. Clinically significant parameters for survival were used to construct a nomogram based on Cox regression analyses. The model was validated using bootstrap resampling and a Chinese cohort (n = 145). A total of 4,109 patients from the SEER database were included for analysis. The multivariate analyses showed that the factors of age, race, histology, tumor site, tumor size, grade and depth of invasion, and the numbers of metastases and retrieved nodes were independent prognostic factors. All of these factors were selected into the nomogram. The nomogram showed a clear prognostic superiority over the seventh AJCC-TNM classification (C-index: SEER cohort, 0.716 vs 0.693, respectively; P nomogram predicted the probabilities of 3- and 5-year survival, which corresponded closely with the actual survival rates. This novel prognostic model may improve clinicians’ abilities to predict individualized survival and to make treatment recommendations. PMID:27215834

  17. Analyzing the effects of geological and parameter uncertainty on prediction of groundwater head and travel time

    Directory of Open Access Journals (Sweden)

    X. He

    2013-08-01

    Full Text Available Uncertainty of groundwater model predictions has in the past mostly been related to uncertainty in the hydraulic parameters, whereas uncertainty in the geological structure has not been considered to the same extent. Recent developments in theoretical methods for quantifying geological uncertainty have made it possible to consider this factor in groundwater modeling. In this study we have applied the multiple-point geostatistical method (MPS integrated in the Stanford Geostatistical Modeling Software (SGeMS for exploring the impact of geological uncertainty on groundwater flow patterns for a site in Denmark. Realizations from the geostatistical model were used as input to a groundwater model developed from Modular three-dimensional finite-difference ground-water model (MODFLOW within the Groundwater Modeling System (GMS modeling environment. The uncertainty analysis was carried out in three scenarios involving simulation of groundwater head distribution and travel time. The first scenario implied 100 stochastic geological models all assigning the same hydraulic parameters for the same geological units. In the second scenario the same 100 geological models were subjected to model optimization, where the hydraulic parameters for each of them were estimated by calibration against observations of hydraulic head and stream discharge. In the third scenario each geological model was run with 216 randomized sets of parameters. The analysis documented that the uncertainty on the conceptual geological model was as significant as the uncertainty related to the embedded hydraulic parameters.

  18. Cardiac magnetic resonance imaging parameters as surrogate endpoints in clinical trials of acute myocardial infarction

    OpenAIRE

    Gutberlet Matthias; Lurz Philipp; Fuernau Georg; de Waha Suzanne; Eitel Ingo; Desch Steffen; Schuler Gerhard; Thiele Holger

    2011-01-01

    Abstract Cardiac magnetic resonance (CMR) offers a variety of parameters potentially suited as surrogate endpoints in clinical trials of acute myocardial infarction such as infarct size, myocardial salvage, microvascular obstruction or left ventricular volumes and ejection fraction. The present article reviews each of these parameters with regard to the pathophysiological basis, practical aspects, validity, reliability and its relative value (strengths and limitations) as compared to competit...

  19. Prediction of water quality parameters from SAR images by using multivariate and texture analysis models

    Science.gov (United States)

    Shareef, Muntadher A.; Toumi, Abdelmalek; Khenchaf, Ali

    2014-10-01

    Remote sensing is one of the most important tools for monitoring and assisting to estimate and predict Water Quality parameters (WQPs). The traditional methods used for monitoring pollutants are generally relied on optical images. In this paper, we present a new approach based on the Synthetic Aperture Radar (SAR) images which we used to map the region of interest and to estimate the WQPs. To achieve this estimation quality, the texture analysis is exploited to improve the regression models. These models are established and developed to estimate six common concerned water quality parameters from texture parameters extracted from Terra SAR-X data. In this purpose, the Gray Level Cooccurrence Matrix (GLCM) is used to estimate several regression models using six texture parameters such as contrast, correlation, energy, homogeneity, entropy and variance. For each predicted model, an accuracy value is computed from the probability value given by the regression analysis model of each parameter. In order to validate our approach, we have used tow dataset of water region for training and test process. To evaluate and validate the proposed model, we applied it on the training set. In the last stage, we used the fuzzy K-means clustering to generalize the water quality estimation on the whole of water region extracted from segmented Terra SAR-X image. Also, the obtained results showed that there are a good statistical correlation between the in situ water quality and Terra SAR-X data, and also demonstrated that the characteristics obtained by texture analysis are able to monitor and predicate the distribution of WQPs in large rivers with high accuracy.

  20. Association rule mining based study for identification of clinical parameters akin to occurrence of brain tumor

    OpenAIRE

    Dipankar SENGUPTA; Sood, Meemansa; Vijayvargia, Poorvika; Hota, Sunil; Naik, Pradeep K

    2013-01-01

    Healthcare sector is generating a large amount of information corresponding to diagnosis, disease identification and treatment of an individual. Mining knowledge and providing scientific decision-making for the diagnosis & treatment of disease from the clinical dataset is therefore increasingly becoming necessary. Aim of this study was to assess the applicability of knowledge discovery in brain tumor data warehouse, applying data mining techniques for investigation of clinical parameters that...

  1. 四参数疲劳定寿方法%Four-parameter life prediction method

    Institute of Scientific and Technical Information of China (English)

    宁向荣; 陈伟; 蔡显新; 廖学军; 米栋

    2012-01-01

    对直升机传动系统采用的一种疲劳定寿方法——四参数法进行了研究:首先介绍了四参数应力一循环(S—N)曲线,然后详细介绍了通过材料平均S—N曲线获取构件安全S—N曲线的步骤以及直升机传动系统四参数疲劳定寿的程序和方法,研究了定寿流程中的各个技术细节.同时介绍了传动系统机匣疲劳试验中的多路协调加载技术以及某传动系统尾减机匣(TGB)的全尺寸疲劳试验情况.最后采用四参数疲劳定寿方法,根据某传动系统尾减机匣全尺寸疲劳试验结果和飞行实测载荷谱,对尾减机匣进行了安全寿命评估.该实例分析表明:四参数疲劳定寿方法为一种有效、可靠的寿命评估方法,具有推广价值.%Four-parameter life prediction method for helicopter transmission system was studied. Four-parameter stress-number of cycles (S-N) curve was presented first, and then, the derivation of helicopter transmission component safe S-N curve from material mean S-N curve and the scheme for the component life prediction were introduced in detail. Multi-load coordinating loading technology in fatigue test and a tail gear box (TGB) casing full-scale fatigue test were introduced at the same time. Finally, according to the full-scale fatigue test result and flight load survey data, applying the four-parameter life prediction method, the TGB casing life prediction was performed, which indicates that four-parameter life prediction method is a reliable and effective method and is worth to be generalized.

  2. Predictive value of routine hematological and biochemical parameters on 30-day fatality in acute stroke

    Directory of Open Access Journals (Sweden)

    Bhatia R

    2004-04-01

    Full Text Available OBJECTIVE: This prospective study was planned to study the prognostic value of routine clinical, hematological and biochemical parameters, including platelet aggregation in patients of acute stroke, on fatality occurring during the first 30 days. MATERIAL AND METHODS: In this study 116 consecutive patients (77 males and 39 females of stroke (within 72 hours of onset were included. After clinical evaluation and neuroimaging, blood investigations, hemoglobin, total leukocyte count, platelet count, platelet aggregation, erythrocyte sedimentation rate (ESR, blood sugar, urea, creatinine, sodium, potassium, serum cholesterol, serum bilirubin, aspartate aminotransferase (SGOT, alanine aminotransferase (SGPT, albumin, and globulin estimations were performed. The patients were followed up for a maximum period of 30 days from the onset of stroke, and patients who expired were grouped as ′expired′ and the rest as ′survivors′. Logistic regression analysis was carried out among the significant parameters to identify independent predictors of 30-day fatality. RESULTS: Univariate analysis demonstrated that among hematological parameters, high total leukocyte count and ESR, at admission, correlated significantly with an undesirable outcome during the initial 30 days. Among biochemical parameters, elevated urea, creatinine, serum transaminases (SGOT and SGPT and globulin levels correlated significantly with death. Logistic regression analysis demonstrated that a low Glasgow Coma Scale (GCS score along with biochemical parameters such as high serum creatinine, SGPT, ESR and total leukocyte count correlated with death. CONCLUSION: Impaired consciousness, high total leukocyte count, raised ESR, elevated creatinine and SGPT levels, estimated within 24 hours of hospitalization, are the most important indicators of 30-day mortality in patients with first-time ischemic stroke.

  3. Lumped Parameter Modeling as a Predictive Tool for a Battery Status Monitor

    Energy Technology Data Exchange (ETDEWEB)

    Jon P. Christophersen; Chester G. Motloch; Chinh D. Ho; John L. Morrison; Ronald C. Fenton; Vincent S. Battaglia; Tien Q. Duong

    2003-10-01

    The Advanced Technology Development Program is currently evaluating the performance of the second generation of lithium-ion cells (i.e., Gen 2 cells). Both the Gen 2 Baseline and Variant C cells are tested in accordance with the cell-specific test plan, and are removed at roughly equal power fade increments and sent for destructive diagnostic analysis. The diagnostic laboratories did not need all test cells for analysis, and returned five spare cells to the Idaho National Engineering and Environmental Laboratory (INEEL). INEEL used these cells for special pulse testing at various duty cycles, amplitudes, and durations to investigate the usefulness of the lumped parameter model (LPM) as a predictive tool in a battery status monitor (BSM). The LPM is a simplified linear model that accurately predicts the voltage response during certain pulse conditions. A database of parameter trends should enable dynamic predictions of state-of-charge and state-of-health conditions during in-vehicle pulsing. This information could be used by the BSM to provide accurate information to the vehicle control system.

  4. Neural network predictions of acoustical parameters in multi-purpose performance halls.

    Science.gov (United States)

    Cheung, L Y; Tang, S K

    2013-09-01

    A detailed binaural sound measurement was carried out in two multi-purpose performance halls of different seating capacities and designs in Hong Kong in the present study. The effectiveness of using neural network in the predictions of the acoustical properties using a limited number of measurement points was examined. The root-mean-square deviation from measurements, statistical parameter distribution matching, and the results of a t-test for vanishing mean difference between simulations and measurements were adopted as the evaluation criteria for the neural network performance. The audience locations relative to the sound source were used as the inputs to the neural network. Results show that the neural network training scheme using nine uniformly located measurement points in each specific hall area is the best choice regardless of the hall setting and design. It is also found that the neural network prediction of hall spaciousness does not require a large amount of training data, but the accuracy of the reverberance related parameter predictions increases with increasing volume of training data.

  5. ECG dispersion mapping predicts clinical deterioration, measured by increase in the Simple Clinical Score.

    LENUS (Irish Health Repository)

    Kellett, J

    2012-01-01

    Objective: ECG dispersion mapping (ECG-DM) is a novel technique that reports abnormal ECG microalternations. We report the ability of ECG-DM to predict clinical deterioration of acutely ill medical patients, as measured by an increase in the Simple Clinical Score (SCS) the day after admission to hospital. Methods: 453 acutely ill medical patients (mean age 69.7 +\\/- 14.0 years) had the SCS recorded and ECGDM performed immediately after admission to hospital. Results: 46 patients had an SCS increase 20.8 +\\/- 7.6 hours after admission. Abnormal micro-alternations during left ventricular re-polarization had the highest association with SCS increase (p=0.0005). Logistic regression showed that only nursing home residence and abnormal micro-alternations during re-polarization of the left ventricle were independent predictors of SCS increase with an odds ratio of 2.84 and 3.01, respectively. Conclusion: ECG-DM changes during left ventricular re-polarization are independent predictors of clinical deterioration the day after hospital admission.

  6. Endometrial thickness, Caucasian ethnicity, and age predict clinical pregnancy following fresh blastocyst embryo transfer: a retrospective cohort

    Directory of Open Access Journals (Sweden)

    Santoro Nanette

    2009-04-01

    Full Text Available Abstract Background In-vitro fertilization (IVF with blastocyst as opposed to cleavage stage embryos has been advocated to improve success rates. Limited information exists on which to predict which patients undergoing blastocyst embryo transfer (BET will achieve pregnancy. This study's objective was to evaluate the predictive value of patient and cycle characteristics for clinical pregnancy following fresh BET. Methods This was a retrospective cohort study from 2003–2007 at an academic assisted reproductive program. 114 women with infertility underwent fresh IVF with embryo transfer. We studied patients undergoing transfer of embryos at the blastocyst stage of development. Our main outcome of interest was clinical pregnancy. Clinical pregnancy and its associations with patient characteristics (age, body mass index, FSH, ethnicity and cycle parameters (thickness of endometrial stripe, number eggs, available cleaving embryos, number blastocysts available, transferred, and cryopreserved, and embryo quality were examined using Student's T test and Mann-Whitney-U tests as appropriate. Multivariable logistic regression models were created to determine independent predictors of CP following BET. Receiver Operating Characteristic analyses were used to determine the optimal thickness of endometrial stripe for predicting clinical pregnancy. Results Patients achieving clinical pregnancy demonstrated a thicker endometrial stripe and were younger preceding embryo transfer. On multivariable logistic regression analyses, Caucasian ethnicity (OR 2.641, 95% CI 1.054–6.617, thickness of endometrial stripe, (OR 1.185, 95% CI 1.006–1.396 and age (OR 0.879, 95% CI 0.789–0.980 predicted clinical pregnancy. By receiver operating characteristic analysis, endometrial stripe ≥ 9.4 mm demonstrated a sensitivity of 83% for predicting clinical pregnancy following BET. Conclusion In a cohort of patients undergoing fresh BET, thicker endometrial stripe, Caucasian

  7. A combined clinical and biomarker approach to predict diuretic response in acute heart failure

    NARCIS (Netherlands)

    Ter Maaten, Jozine M; Valente, Mattia A E; Metra, Marco; Bruno, Noemi; O'Connor, Christopher M; Ponikowski, Piotr; Teerlink, John R; Cotter, Gad; Davison, Beth; Cleland, John G; Givertz, Michael M; Bloomfield, Daniel M; Dittrich, Howard C; van Veldhuisen, Dirk J; Hillege, Hans L; Damman, Kevin; Voors, Adriaan A

    2015-01-01

    BACKGROUND: Poor diuretic response in acute heart failure is related to poor clinical outcome. The underlying mechanisms and pathophysiology behind diuretic resistance are incompletely understood. We evaluated a combined approach using clinical characteristics and biomarkers to predict diuretic resp

  8. Quantifying uncertainties in streamflow predictions through signature based inference of hydrological model parameters

    Science.gov (United States)

    Fenicia, Fabrizio; Reichert, Peter; Kavetski, Dmitri; Albert, Calro

    2016-04-01

    The calibration of hydrological models based on signatures (e.g. Flow Duration Curves - FDCs) is often advocated as an alternative to model calibration based on the full time series of system responses (e.g. hydrographs). Signature based calibration is motivated by various arguments. From a conceptual perspective, calibration on signatures is a way to filter out errors that are difficult to represent when calibrating on the full time series. Such errors may for example occur when observed and simulated hydrographs are shifted, either on the "time" axis (i.e. left or right), or on the "streamflow" axis (i.e. above or below). These shifts may be due to errors in the precipitation input (time or amount), and if not properly accounted in the likelihood function, may cause biased parameter estimates (e.g. estimated model parameters that do not reproduce the recession characteristics of a hydrograph). From a practical perspective, signature based calibration is seen as a possible solution for making predictions in ungauged basins. Where streamflow data are not available, it may in fact be possible to reliably estimate streamflow signatures. Previous research has for example shown how FDCs can be reliably estimated at ungauged locations based on climatic and physiographic influence factors. Typically, the goal of signature based calibration is not the prediction of the signatures themselves, but the prediction of the system responses. Ideally, the prediction of system responses should be accompanied by a reliable quantification of the associated uncertainties. Previous approaches for signature based calibration, however, do not allow reliable estimates of streamflow predictive distributions. Here, we illustrate how the Bayesian approach can be employed to obtain reliable streamflow predictive distributions based on signatures. A case study is presented, where a hydrological model is calibrated on FDCs and additional signatures. We propose an approach where the likelihood

  9. Dealing with missing predictor values when applying clinical prediction models.

    NARCIS (Netherlands)

    Janssen, K.J.; Vergouwe, Y.; Donders, A.R.T.; Harrell Jr, F.E.; Chen, Q.; Grobbee, D.E.; Moons, K.G.

    2009-01-01

    BACKGROUND: Prediction models combine patient characteristics and test results to predict the presence of a disease or the occurrence of an event in the future. In the event that test results (predictor) are unavailable, a strategy is needed to help users applying a prediction model to deal with suc

  10. Rorschach Prediction of Success in Clinical Training: A Second Look

    Science.gov (United States)

    Carlson, Rae

    1969-01-01

    A Rorschach Index based on ego-psychological conceptualization of an optimal personality picture predicted for 155 trainees was compared with predictions from the Miller Analogies Test (MAT) and the Strong Vocational Interest Blank (SVIB). The Index predicted success and failure more effectively. (Author)

  11. Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care

    Science.gov (United States)

    Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care, a 2010 workshop sponsored by the Epidemiology and Genomics Research Program.

  12. Predicting Nitrate Concentration in Groundwater Resources using Lumped-Parameter Model: Case Study in Qazvin Plain

    Directory of Open Access Journals (Sweden)

    R.S Hajimirmohammad Ali

    2016-03-01

    Full Text Available Background and Objective: The concentration of nitrate, factors affecting the balance sheet, and the changes in an aquifer is of utmost importance. Because modeling is an efficient method to predict the concentration of ions in water resources, in this study using lumped-parameter model and Monte Carlo simulation model, the nitrate concentrations in groundwater resources of Qazvin Plain were estimated and analyzed. Materials and Methods: A total of 19 wells in different climates of saline watershed in Qazvin Plain were selected and entry and exit routes of nitrate to these sources were analyzed using lumped-parameter model.  Finally, Monte Carlo simulation was used to determine the probability of the estimated nitrate concentration in aquifer. Results: Application of lumped-parameter model for a part of a part of groundwater resources in Qazvin Plain watershed predicted the nitrate concentration in the range of 8.12 to 15.94 mg/l.   The maximum concentration was estimated in cold-dry climate with 12.8±0.04 mg/L. Moreover, it was found that the difference between the estimated nitrate concentration and factors affecting its concentration in different climates was significant (p<0.05. Conclusion: Despite the predicted concentrations of nitrate in the study area were in accordance with the Iran national standard for drinking purposes, the cumulative probability of Monte Carlo simulation showed that the possible violation of nitrate from the safe limit of 10 mg/l in the study area is 90% (p = 0.005.

  13. Predicting trace organic compound attenuation with spectroscopic parameters in powdered activated carbon processes.

    Science.gov (United States)

    Ziska, Austin D; Park, Minkyu; Anumol, Tarun; Snyder, Shane A

    2016-08-01

    The removal of trace organic compounds (TOrCs) is of growing interest in water research and society. Powdered activated carbon (PAC) has been proven to be an effective method of removal for TOrCs in water, with the degree of effectiveness depending on dosage, contact time, and activated carbon type. In this study, the attenuation of TOrCs in three different secondary wastewater effluents using four PAC materials was studied in order to elucidate the effectiveness and efficacy of PAC for TOrC removal. With the notable exception of hydrochlorothiazide, all 14 TOrC indicators tested in this study exhibited a positive correlation of removal rate with their log Dow values, demonstrating that the main adsorption mechanism was hydrophobic interaction. As a predictive model, the modified Chick-Watson model, often used for the prediction of microorganism inactivation by disinfectants, was applied. The applied model exhibited good predictive power for TOrC attenuation by PAC in wastewater. In addition, surrogate models based upon spectroscopic measurements including UV absorbance at 254 nm and total fluorescence were applied to predict TOrC removal by PAC. The surrogate model was found to provide an excellent prediction of TOrC attenuation for all combinations of water quality and PAC type included in this study. The success of spectrometric parameters as surrogates in predicting TOrC attenuation by PAC are particularly useful because of their potential application in real-time on-line sensor monitoring and process control at full-scale water treatment plants, which could lead to significantly reduced operator response times and PAC operational optimization. PMID:27174829

  14. Analysis Of Clinical, Haematological And Biochemical Parameters In Patients With Infectious Mononucleosis

    Directory of Open Access Journals (Sweden)

    Canović Petar

    2015-12-01

    Full Text Available Primary infection with Epstein-Barr virus (EBV usually occurs in early childhood and often does not present clinical symptoms. More than 90% of adults are infected with this virus. A primary infection that occurs in adolescence or adulthood is usually clinically presented as infectious mononucleosis with a triad of symptoms: fever, lymphadenopathy and pharyngitis. Our retrospective study included 51 patients with a median age of 17 (9-23 years and serologically confirmed infectious mononucleosis. All patients with infectious mononucleosis were treated at the Clinic for Infectious Diseases at the Clinical Center in Kragujevac during 2013. We analysed the clinical, haematological and laboratory parameters of patients. The aspartate-aminotransferase levels were increased in 40 patients, with a mean value of 116.24 (±93.22; the alanine-aminotransferase levels were increased in 44 patients, with a mean value of 189.24 (±196.69. Lymphadenopathy was the most common clinical feature upon admission in 49 patients (96%; 38 patients (74.5% had splenomegaly, and 20 (39% had hepatomegaly. Twenty-six patients (51% had leukocytosis with lymphocytosis, while 15 (75% of the 20 who had a normal leukocyte count also had lymphocytosis. In the present study, we updated the clinical, haematological and laboratory parameters, which may lead to the establishment of an accurate diagnosis and promote further treatment of the patients.

  15. A new model to predict weak-lensing peak counts II. Parameter constraint strategies

    CERN Document Server

    Lin, Chieh-An

    2015-01-01

    Peak counts have been shown to be an excellent tool to extract the non-Gaussian part of the weak lensing signal. Recently, we developped a fast stochastic forward model to predict weak-lensing peak counts. Our model is able to reconstruct the underlying distribution of observables for analyses. In this work, we explore and compare various strategies for constraining parameter using our model, focusing on the matter density $\\Omega_\\mathrm{m}$ and the density fluctuation amplitude $\\sigma_8$. First, we examine the impact from the cosmological dependency of covariances (CDC). Second, we perform the analysis with the copula likelihood, a technique which makes a weaker assumption compared to the Gaussian likelihood. Third, direct, non-analytic parameter estimations are applied using the full information of the distribution. Fourth, we obtain constraints with approximate Bayesian computation (ABC), an efficient, robust, and likelihood-free algorithm based on accept-reject sampling. We find that neglecting the CDC ...

  16. A Bayesian Approach for Parameter Estimation and Prediction using a Computationally Intensive Model

    CERN Document Server

    Higdon, Dave; Schunck, Nicolas; Sarich, Jason; Wild, Stefan M

    2014-01-01

    Bayesian methods have been very successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best fit of a physics-based model $\\eta(\\theta)$ where $\\theta$ denotes the uncertain, best input setting. Hence the statistical model is of the form $y = \\eta(\\theta) + \\epsilon$, where $\\epsilon$ accounts for measurement, and possibly other error sources. When non-linearity is present in $\\eta(\\cdot)$, the resulting posterior distribution for the unknown parameters in the Bayesian formulation is typically complex and non-standard, requiring computationally demanding computational approaches such as Markov chain Monte Carlo (MCMC) to produce multivariate draws from the posterior. While quite generally applicable, MCMC requires thousands, or even millions of evaluations of the physics model $\\eta(\\cdot)$. This is problematic if the model takes hours or days to evaluate. To overcome this computational bottleneck, we pr...

  17. An Effective Approach Based on Response Surface Methodology for Predicting Friction Welding Parameters

    Science.gov (United States)

    Celik, Sare; Deniz Karaoglan, Aslan; Ersozlu, Ismail

    2016-03-01

    The joining of dissimilar metals is one of the most essential necessities of industries. Manufacturing by the joint of alloy steel and normal carbon steel is used in production, because it decreases raw material cost. The friction welding process parameters such as friction pressure, friction time, upset pressure, upset time and rotating speed play the major roles in determining the strength and microstructure of the joints. In this study, response surface methodology (RSM), which is a well-known design of experiments approach, is used for modeling the mathematical relation between the responses (tensile strength and maximum temperature), and the friction welding parameters with minimum number of experiments. The results show that RSM is an effective method for this type of problems for developing models and prediction.

  18. Chest X-rays and associated clinical parameters in pulmonary Tubercolosis cases from the National Tubercolosis Program, Mumbai, India

    Directory of Open Access Journals (Sweden)

    Yatin N. Dholakia

    2012-01-01

    Full Text Available The study was carried out in pulmonary tuberculosis (PTB patients from the local Tuberculosis control programme, Mumbai, India. It examined features of chest X-rays and their correlation with clinical parameters for possible application in suspected multidrug resistant TB (MDRTB and to predict outcome in new and treatment failure PTB cases. X-ray features (infiltrate, cavitation, miliary shadows, pleural effusion, mediastinal lymphadenopathy and extent of lesions were analyzed to identify associations with biological/clinical parameters through univariate and multivariate logistic regression. Failures demonstrated associations between extensive lesions and high glycosylated hemoglobin (GHb levels (P=0.028 and male gender (P=0.03. An association was also detected between cavitation and MDR (P=0.048. In new cases, bilateral cavities were associated with MDR (P=0.018 and male gender (P=0.01, low body mass index with infiltrates (P=0.008, and smoking with cavitation (P=0.0238. Strains belonging to the Manu1 spoligotype were associated with mild lesions (P=0.002. Poor outcome showed borderline significance with extensive lesions at onset (P=0.053. Furthermore, amongst new cases, smoking, the Central Asian Strain (CAS spoligotype and high GHb were associated with cavitation, whereas only CAS spoligotypes and high GHb were associated with extensive lesions. The study highlighted associations between certain clinical parameters and X-ray evidence which support the potential of X-rays to predict TB, MDRTB and poor outcome. The use of Xrays as an additional tool to shorten diagnostic delay and shortlist MDR suspects amongst nonresponders to TB treatment should be explored in a setting with limited resources coping with a high MDR case load such as Mumbai.

  19. The Chaotic Prediction for Aero-Engine Performance Parameters Based on Nonlinear PLS Regression

    Directory of Open Access Journals (Sweden)

    Chunxiao Zhang

    2012-01-01

    Full Text Available The prediction of the aero-engine performance parameters is very important for aero-engine condition monitoring and fault diagnosis. In this paper, the chaotic phase space of engine exhaust temperature (EGT time series which come from actual air-borne ACARS data is reconstructed through selecting some suitable nearby points. The partial least square (PLS based on the cubic spline function or the kernel function transformation is adopted to obtain chaotic predictive function of EGT series. The experiment results indicate that the proposed PLS chaotic prediction algorithm based on biweight kernel function transformation has significant advantage in overcoming multicollinearity of the independent variables and solve the stability of regression model. Our predictive NMSE is 16.5 percent less than that of the traditional linear least squares (OLS method and 10.38 percent less than that of the linear PLS approach. At the same time, the forecast error is less than that of nonlinear PLS algorithm through bootstrap test screening.

  20. Use of remote sensing derived parameters in a crop model for biomass prediction of hay crop

    Science.gov (United States)

    El Hajj, Mohammad; Baghdadi, Nicolas; Cheviron, Bruno; Belaud, Gilles; Zribi, Mehrez

    2016-04-01

    Pre-harvest yield forecasting is a critical challenge for producers, especially for large agricultural areas. During previous decades, numerous crop models were developed to predict crop growth and yield at daily time, most often for wheat or maize, and also for grasslands. Crop models require several input parameters that describe soil properties (e.g. field capacity), plant characteristics (e.g. maximal rooting depth) and management options (e.g. sowing dates, irrigation and harvest dates), which are referred to as the soil, plant and management families of parameters. Remote sensing technology has been extensively applied to identify spatially distributed values of some of the accessible parameters in the soil, plant and management families. The aim of this study was to address the feasibility, merits and limitations of forcing remote-sensing-derived parameters (LAI values, harvest and irrigation dates) in the PILOTE crop model, targeting the Total Dry Matter (TDM) of hay crops. Results show that optical images are suitable to feed PILOTE with LAI values without inducing significant errors on the predicted Total Dry Matter (TDM) values (Root Mean Square Error "RMSE" = 0.41 t/ha and Mean Absolute Percentage Error "MAPE" = 22%). Moreover, optical images with revisit times lower than 16 days are adequate to feed PILOTE with remotely sensed harvest dates (RMSE PILOTE with noisy irrigation dates that were estimated from SAR images also enabled reliable model predictions, at least when attaching a random uncertainty of "only" 3 days to the real known irrigation dates. The case of one or several undetected irrigations has also been explored, with the expected conclusion that undetected irrigations significantly affect model predictions only in dry periods. For the tested soil properties and climatic conditions, a maximum underestimation of TDM of approximately 1.55 t/ha (reference TDM of 3.43 t/ha) was observed in the second crop growth cycle when ignoring two

  1. Comparison of two non-linear prediction techniques for estimation of some intact rock parameters

    Science.gov (United States)

    Yagiz, Saffet; Sezer, Ebru; Gokceoglu, Candan

    2010-05-01

    Traditionally, some regression techniques have been used for prediction of some rock properties using their physical and index parameters. For this purpose, numerous models and empirical equations have been proposed in the literature to predict the uniaxial compressive strength (UCS) and the elasticity modules (E) of intact rocks. Two of the powerful modeling techniques for this purpose is that the non-linear multivariable regression (NLMR) and the artificial neural networks (ANN). The aim of the study is to develop some models to predict the UCS and E of rocks using predictive tools. Further, to investigate whether two-cycle or four-cycle slake durability index as an input parameter into the models demonstrates better characterization capacity for carbonate rocks, and also, to introduce two new performance ranking approaches via performance index and degree of consistency to select the best predictor among the developed models, complex and their rank cannot be solved by using a simple ranking approach introduced previously in the literature. To obtain these purposes, seven type of carbonate rocks was collected from quarries in the southwestern Turkey and their properties including the uniaxial compressive strength, the Schmidt hammer, effective porosity, dry unit weight, P-wave velocity, the modulus of elasticity, and both two and four-cycle of slake durability indices were determined for establishing a dataset used for construction of the models. As a result of this study, it is found that four-cycle slake durability index exhibits more characterization capacity for carbonate rock in the models in comparison with two-cycle slake durability index. Also, the ANN models having two outputs (UCS and E) exhibit more accurate estimation capacity than the NLMR models. In addition, newly introduced performance ranking index and degree of consistency may be accepted as useful indicators to be considered to obtain the performance ranking of complex models. Consequently

  2. The influence of estimated body segment parameters on predicted joint kinetics during diplegic cerebral palsy gait.

    Science.gov (United States)

    Kiernan, D; Walsh, M; O'Sullivan, R; O'Brien, T; Simms, C K

    2014-01-01

    Inverse Dynamic calculations are routinely used in joint moment and power estimates during gait with anthropometric data often taken from published sources. Many biomechanical analyses have highlighted the need to obtain subject-specific anthropometric data (e.g. Mass, Centre of Mass, Moments of Inertia) yet the types of imaging techniques required to achieve this are not always available in the clinical setting. Differences in anthropometric sets have been shown to affect the reactive force and moment calculations in normal subjects but the effect on a paediatric diplegic cerebral palsy group has not been investigated. The aim of this study was to investigate the effect of using different anthropometric sets on predicted sagittal plane moments during normal and diplegic cerebral palsy gait. Three published anthropometric sets were applied to the reactive force and moment calculations of 14 Cerebral Palsy and 14 Control subjects. Statistically significant differences were found when comparing the different anthropometric sets but variability in the resulting sagittal plane moment calculations between sets was low (0.01-0.07 Nm/kg). In addition, the GDI-Kinetic, used as an outcome variable to assess whether differences were clinically meaningful, indicated no clinically meaningful difference between sets. The results suggest that the effects of using different anthropometric sets on the kinetic profiles of normal and diplegic cerebral palsy subjects are clinically insignificant.

  3. Identification of Clinical and Genetic Parameters Associated with Hidradenitis Suppurativa in Inflammatory Bowel Disease

    NARCIS (Netherlands)

    Janse, Ineke C; Koldijk, Marjolein J; Spekhorst, Lieke M; Vila, Arnau Vich; Weersma, Rinse K; Dijkstra, Gerard; Horváth, Barbara

    2016-01-01

    BACKGROUND: Hidradenitis suppurativa (HS) has recently been associated with inflammatory bowel disease (IBD). The objective of this study is to investigate the prevalence of HS in IBD and to identify clinical and genetic parameters associated with HS in IBD. METHODS: A questionnaire, validated for H

  4. New evidence-based adaptive clinical trial methods for optimally integrating predictive biomarkers into oncology clinical development programs

    Institute of Scientific and Technical Information of China (English)

    Robert A.Beckman; Cong Chen

    2013-01-01

    Predictive biomarkers are important to the future of oncology; they can be used to identify patient populations who will benefit from therapy,increase the value of cancer medicines,and decrease the size and cost of clinical trials while increasing their chance of success.But predictive biomarkers do not always work.When unsuccessful,they add cost,complexity,and time to drug development.This perspective describes phases 2 and 3 development methods that efficiently and adaptively check the ability of a biomarker to predict clinical outcomes.In the end,the biomarker is emphasized to the extent that it can actually predict.

  5. Comparison of clinical and paraclinical parameters as tools for early diagnosis of classical swine fever

    DEFF Research Database (Denmark)

    Lohse, Louise; Uttenthal, Åse; Nielsen, Jens

    Comparison of clinical and paraclinical parameters as tools for early diagnosis of classical swine fever. Louise Lohse, Åse Uttenthal, Jens Nielsen. National Veterinary Institute, Division of Virology, Lindholm, Technical University of Denmark. Introduction: In order to limit the far-reaching socio......-economic as well as the animal welfare consequences of an outbreak of classical swine fever (CSF), early diagnosis is essential. However, host-virus interactions strongly influence the course of CSF disease, and the clinical feature is not clear, thus complicating the diagnostic perspective. At the National...... Veterinary Institute, in Denmark, we are conducting a series of animal experiments under standardized conditions in order to investigate new parameters of clinical as well as paraclinical nature that holds the potential as diagnostic tools to improve early detection of CSF. In three recent studies, weaned...

  6. CLINICAL DATABASE ANALYSIS USING DMDT BASED PREDICTIVE MODELLING

    Directory of Open Access Journals (Sweden)

    Srilakshmi Indrasenan

    2013-04-01

    Full Text Available In recent years, predictive data mining techniques play a vital role in the field of medical informatics. These techniques help the medical practitioners in predicting various classes which is useful in prediction treatment. One of such major difficulty is prediction of survival rate in breast cancer patients. Breast cancer is a common disease these days and fighting against it is a tough battle for both the surgeons and the patients. To predict the survivability rate in breast cancer patients which helps the medical practitioner to select the type of treatment a predictive data mining technique called Diversified Multiple Decision Tree (DMDT classification is used. Additionally, to avoid difficulties from the outlier and skewed data, it is also proposed to perform the improvement of training space by outlier filtering and over sampling. As a result, this novel approach gives the survivability rate of the cancer patients based on which the medical practitioners can choose the type of treatment.

  7. Clinical prediction of 5-year survival in systemic sclerosis

    DEFF Research Database (Denmark)

    Fransen, Julie Munk; Popa-Diaconu, D; Hesselstrand, R;

    2011-01-01

    Systemic sclerosis (SSc) is associated with a significant reduction in life expectancy. A simple prognostic model to predict 5-year survival in SSc was developed in 1999 in 280 patients, but it has not been validated in other patients. The predictions of a prognostic model are usually less accurate...... in other patients, especially from other centres or countries. A study was undertaken to validate the prognostic model to predict 5-year survival in SSc in other centres throughout Europe....

  8. Prediction trajectory of moving target based on parameter identify in RLS filtering with forget factor

    Science.gov (United States)

    Yin, Yili; Tian, Yan; Li, Zhang

    2015-10-01

    A moving target should be missing from a photoelectric theodolite tracker, when the clouds and other special conditions encountered in the course of a theodolite tracking a moving object, and this condition should cause the interruption of tracking process. In view of this problem, an algorithm based on the frame of parameter identification and rolling prediction to trajectory was presented to predicting the target trajectory when it missing. Firstly, the article makes a specification of photoelectric theodolite and it operating mechanism detailed. The reasons of flying target imaging disappear from the field of theodolite telescope and the traditional solution to this problem, the least square curve fitting of trajectory quadratic function of time, were narrated secondly. The algorithm based on recursive least square with forget factor, identify the parameters of target motion using the data of position from single theodolite, then the forecasting trajectory of moving targets was presented afterwards ,in the filtering approach of past data rolling smooth with the weight of last procedure. By simulation with tracking moving targets synthetic corner from a real tracking routine of photoelectric theodolite, the algorithm was testified, and the simulation of curve fitting a quadratic function of time was compared at the last part.

  9. Prediction of Radionuclide transfer based on soil parameters: application to vulnerability studies

    International Nuclear Information System (INIS)

    The multi factorial character of the radiocaesium and radiostrontium soil-to-plan transfer, which depends on the radionuclide level in the soil solution amplified by a plant factor, prevents from establishing univariate relationships between transfer factors and soil and/or plant parameters. The plant factor is inversely proportional to the level of competitive species in the soil solution (Ca and Mg, for radiostrontium, and K and NH4 for radiocaesium). Radionuclide level in soil solution depends on the radionuclide available fraction and its distribution coefficient. For radiostrontium, this may be obtained from the Cationic Exchange Capacity (CEC), whereas for radiocaesium the Specific Interception Potential should be calculate, both corrected by the concentrations of the competitive species and selectivity coefficients. Therefore, the transfer factor eventually depends on soil solution composition, the available fraction and the number of sorption sites, as well as on the plant factor. For a given plant, a relative sequence of transfer can be set up based solely on soil parameters, since the plant factor is cancelled. This prediction model has been compared with transfer data from experiments with Mediterranean, mineral soils, contaminated with a thermo generated aerosol, and with podzolic and organic soils, contaminated by the Chernobyl fallout. These studies revealed that it was possible to predict a relative scale of transfer for any type of soil, also allowing a scale of soil vulnerability to radiostrontium and radiocaesium contamination to be set up. (Author)

  10. Mapping of ionospheric parameters for space weather predictions: A concise review

    Institute of Scientific and Technical Information of China (English)

    Y. KAMIDE; A. IEDA

    2008-01-01

    Reviewing brieflythe recent progress in a joint program of specifying the polar ionosphere primarily on the basis of ground magnetometer data, this paper em-phasizes the importance of processing data from around the world in real time for space weather predictions. The output parameters from the program include ionospheric electric fields and currents and field-aligned currents. These real-time records are essential for running computer simulations under realistic boundary conditions and thus for making numerical predictions of space weather efficient as reliable as possible. Data from individual ground magnetometers as well as from the solar wind are collected and are used as input for the KRM and AMIE mag-netogram-inversion algorithms, through which the two-dimensional distribution of the ionospheric parameters is calculated. One of the goals of the program is to specify the solar-terrestrial environment in terms of ionospheric processes and to provide the scientific community with more than what geomagnetic activity Indices and statistical models indicate.

  11. Mapping of ionospheric parameters for space weather predictions: A concise review

    Institute of Scientific and Technical Information of China (English)

    Y.; KAMIDE; A.; IEDA

    2008-01-01

    Reviewing briefly the recent progress in a joint program of specifying the polar ionosphere primarily on the basis of ground magnetometer data, this paper em-phasizes the importance of processing data from around the world in real time for space weather predictions. The output parameters from the program include ionospheric electric fields and currents and field-aligned currents. These real-time records are essential for running computer simulations under realistic boundary conditions and thus for making numerical predictions of space weather efficient as reliable as possible. Data from individual ground magnetometers as well as from the solar wind are collected and are used as input for the KRM and AMIE mag-netogram-inversion algorithms, through which the two-dimensional distribution of the ionospheric parameters is calculated. One of the goals of the program is to specify the solar-terrestrial environment in terms of ionospheric processes and to provide the scientific community with more than what geomagnetic activity indices and statistical models indicate.

  12. Forecasting of Real Thunderstorms based on Electric Parameters Calculations in Numerical Weather Prediction Models

    Science.gov (United States)

    Dementyeva, Svetlana; Ilin, Nikolay; Shatalina, Maria; Mareev, Evgeny

    2016-04-01

    Now-casting and long-term forecasting of lightning flashes occurrence are urgent problems from different points of view. There are several approaches to predicting lightning activity using indirect non-electrical parameters based on the relationship of lightning flashes with vertical fluxes of solid-phased hydrometeors but for more explicit forecasting of the lightning flashes occurrence electric processes should be considered. In addition, a factor playing a key role for now-casting of lightning activity is the earliness. We have proposed an algorithm, which makes the process of thunderstorms prediction automatic (due to automatic start of the electric parameters calculation) and quick (due to the use of simplified methods). Our forecasting was based on the use of Weather Research and Forecasting (WRF) model, which does not include the electrification processes, but it was supplemented with two modules. The first is an algorithm, which allows us to select thunderstorm events indirectly. It is based on such characteristics of thunderclouds and thunderstorms as radar reflectivity, duration and area and provides us with information about an approximate beginning and duration of the thunderstorm. The second module is a method for electric parameters calculations, which we have proposed before. It was suggested that the non-inductive mechanism of charge generation and separation plays a key role in the thundercloud electrification processes. Also charge densities of solid-phased hydrometeors are assumed to be proportional to their mass in elementary air volume. According to the models by Saunders and Takahashi, particles change the sign of charge while getting into the lower part of thundercloud from the upper and vice versa. Electric neutrality in the vertical air column was supposed in the course of vertical charge separation due to collisions between falling graupels and carried upward ice crystals. Electric potential (and consequently electric field) can be found

  13. Incidence and clinical vital parameters in primary ketosis of Murrah buffaloes

    Directory of Open Access Journals (Sweden)

    Ankit Kumar

    2015-09-01

    Full Text Available Aim: The present study was undertaken to ascertain the incidence and clinical vital parameters in cases of primary ketosis in Murrah buffaloes brought to teaching veterinary clinical complex, Lala Lajpat Rai University of Veterinary and Animal Sciences, Hisar and from adjoining villages of the district Hisar, Haryana, India. Materials and Methods: The investigation was conducted on 24 clinical cases (out of total 145 screened of primary ketosis. The diagnosis was confirmed on the basis of clinical signs and significantly positive two tests for ketone bodies in urine (Rothera’s and Keto-Diastix strip test. Data collected were statistically analyzed using independent Student’s t-test. Results: Overall incidence of disease in these areas was found to be 16.55% and all the animals were recently parturited (mean: 1.42±0.14 month, on an average in their third lactation (mean: 2.38±0.30 and exhibited clinical signs such as selective anorexia (refusal to feed on concentrate diet, drastic reduction in milk yield (mean: 64.4±5.35%, ketotic odor from urine, breath, and milk and rapid loss of body condition. All the clinical vital parameters in ketotic buffaloes (body temperature, heart rate, respiration rate, and rumen movements were within normal range. Conclusion: Primary ketosis in Murrah buffaloes was the most common seen in the third lactation, within the first 2 months after parturition with characteristics clinical signs and no variability in vital parameters. The disease has severe effect on the production status of affected animal.

  14. Impact of Hybrid Intelligent Computing in Identifying Constructive Weather Parameters for Modeling Effective Rainfall Prediction

    Directory of Open Access Journals (Sweden)

    M. Sudha

    2015-12-01

    Full Text Available Uncertain atmosphere is a prevalent factor affecting the existing prediction approaches. Rough set and fuzzy set theories as proposed by Pawlak and Zadeh have become an effective tool for handling vagueness and fuzziness in the real world scenarios. This research work describes the impact of Hybrid Intelligent System (HIS for strategic decision support in meteorology. In this research a novel exhaustive search based Rough set reduct Selection using Genetic Algorithm (RSGA is introduced to identify the significant input feature subset. The proposed model could identify the most effective weather parameters efficiently than other existing input techniques. In the model evaluation phase two adaptive techniques were constructed and investigated. The proposed Artificial Neural Network based on Back Propagation learning (ANN-BP and Adaptive Neuro Fuzzy Inference System (ANFIS was compared with existing Fuzzy Unordered Rule Induction Algorithm (FURIA, Structural Learning Algorithm on Vague Environment (SLAVE and Particle Swarm OPtimization (PSO. The proposed rainfall prediction models outperformed when trained with the input generated using RSGA. A meticulous comparison of the performance indicates ANN-BP model as a suitable HIS for effective rainfall prediction. The ANN-BP achieved 97.46% accuracy with a nominal misclassification rate of 0.0254 %.

  15. Changes in Predicted Muscle Coordination with Subject-Specific Muscle Parameters for Individuals after Stroke

    Directory of Open Access Journals (Sweden)

    Brian A. Knarr

    2014-01-01

    Full Text Available Muscle weakness is commonly seen in individuals after stroke, characterized by lower forces during a maximal volitional contraction. Accurate quantification of muscle weakness is paramount when evaluating individual performance and response to after stroke rehabilitation. The objective of this study was to examine the effect of subject-specific muscle force and activation deficits on predicted muscle coordination when using musculoskeletal models for individuals after stroke. Maximum force generating ability and central activation ratio of the paretic plantar flexors, dorsiflexors, and quadriceps muscle groups were obtained using burst superimposition for four individuals after stroke with a range of walking speeds. Two models were created per subject: one with generic and one with subject-specific activation and maximum isometric force parameters. The inclusion of subject-specific muscle data resulted in changes in the model-predicted muscle forces and activations which agree with previously reported compensation patterns and match more closely the timing of electromyography for the plantar flexor and hamstring muscles. This was the first study to create musculoskeletal simulations of individuals after stroke with subject-specific muscle force and activation data. The results of this study suggest that subject-specific muscle force and activation data enhance the ability of musculoskeletal simulations to accurately predict muscle coordination in individuals after stroke.

  16. Prediction and optimization of friction welding parameters for super duplex stainless steel (UNS S32760) joints

    International Nuclear Information System (INIS)

    Highlights: • Corrosion resistance and impact strength – predicted by response surface methodology. • Burn off length has highest significance on corrosion resistance. • Friction force is a strong determinant in changing impact strength. • Pareto front points generated by genetic algorithm aid to fix input control variable. • Pareto front will be a trade-off between corrosion resistance and impact strength. - Abstract: Friction welding finds widespread industrial use as a mass production process for joining materials. Friction welding process allows welding of several materials that are extremely difficult to fusion weld. Friction welding process parameters play a significant role in making good quality joints. To produce a good quality joint it is important to set up proper welding process parameters. This can be done by employing optimization techniques. This paper presents a multi objective optimization method for optimizing the process parameters during friction welding process. The proposed method combines the response surface methodology (RSM) with an intelligent optimization algorithm, i.e. genetic algorithm (GA). Corrosion resistance and impact strength of friction welded super duplex stainless steel (SDSS) (UNS S32760) joints were investigated considering three process parameters: friction force (F), upset force (U) and burn off length (B). Mathematical models were developed and the responses were adequately predicted. Direct and interaction effects of process parameters on responses were studied by plotting graphs. Burn off length has high significance on corrosion current followed by upset force and friction force. In the case of impact strength, friction force has high significance followed by upset force and burn off length. Multi objective optimization for maximizing the impact strength and minimizing the corrosion current (maximizing corrosion resistance) was carried out using GA with the RSM model. The optimization procedure resulted in

  17. Predictive Models for Different Roughness Parameters During Machining Process of Peek Composites Using Response Surface Methodology

    Directory of Open Access Journals (Sweden)

    Mata-Cabrera Francisco

    2013-10-01

    Full Text Available Polyetheretherketone (PEEK composite belongs to a group of high performance thermoplastic polymers and is widely used in structural components. To improve the mechanical and tribological properties, short fibers are added as reinforcement to the material. Due to its functional properties and potential applications, it’s impor- tant to investigate the machinability of non-reinforced PEEK (PEEK, PEEK rein- forced with 30% of carbon fibers (PEEK CF30, and reinforced PEEK with 30% glass fibers (PEEK GF30 to determine the optimal conditions for the manufacture of the parts. The present study establishes the relationship between the cutting con- ditions (cutting speed and feed rate and the roughness (Ra , Rt , Rq , Rp , by develop- ing second order mathematical models. The experiments were planned as per full factorial design of experiments and an analysis of variance has been performed to check the adequacy of the models. These state the adequacy of the derived models to obtain predictions for roughness parameters within ranges of parameters that have been investigated during the experiments. The experimental results show that the most influence of the cutting parameters is the feed rate, furthermore, proved that glass fiber reinforcements produce a worse machinability.

  18. Denoising of arterial and venous Doppler signals using discrete wavelet transform: effect on clinical parameters.

    Science.gov (United States)

    Tokmakçi, Mahmut; Erdoğan, Nuri

    2009-05-01

    In this paper, the effects of a wavelet transform based denoising strategy on clinical Doppler parameters are analyzed. The study scheme included: (a) Acquisition of arterial and venous Doppler signals by sampling the audio output of an ultrasound scanner from 20 healthy volunteers, (b) Noise reduction via decomposition of the signals through discrete wavelet transform, (c) Spectral analysis of noisy and noise-free signals with short time Fourier transform, (d) Curve fitting to spectrograms, (e) Calculation of clinical Doppler parameters, (f) Statistical comparison of parameters obtained from noisy and noise-free signals. The decomposition level was selected as the highest level at which the maximum power spectral density and its corresponding frequency were preserved. In all subjects, noise-free spectrograms had smoother trace with less ripples. In both arterial and venous spectrograms, denoising resulted in a significant decrease in the maximum (systolic) and mean frequency, with no statistical difference in the minimum (diastolic) frequency. In arterial signals, this leads to a significant decrease in the calculated parameters such as Systolic/Diastolic Velocity Ratio, Resistivity Index, Pulsatility Index and Acceleration Time. Acceleration Index did not change significantly. Despite a successful denoising, the effects of wavelet decomposition on high frequency components in the Doppler signal should be challenged by comparison with reference data, or, through clinical investigations. PMID:19470316

  19. Correlation of alkaline phosphatase activity to clinical parameters of inflammation in smokers suffering from chronic periodontitis

    Science.gov (United States)

    Grover, Vishakha; Malhotra, Ranjan; Kapoor, Anoop; Bither, Rupika; Sachdeva, Sonia

    2016-01-01

    Context: Current clinical periodontal diagnostic techniques emphasize the assessment of clinical and radiographic signs of periodontal diseases which can provide a measure of history of disease. Hence, new methodologies for early identification and determination of periodontal disease activity need to be explored which will eventually result in expedited treatment. Aim: To evaluate the correlation of alkaline phosphatase (ALP) activity in gingival crevicular fluid (GCF) to clinical parameters of periodontal inflammation in smokers with chronic periodontitis. Materials and Methods: Study population included 15 smoker male patients in the age group of 35–55 years suffering from moderate generalized chronic periodontitis with history of smoking present. Following parameters were evaluated at baseline, 1 month and 3 months after scaling and root planing: plaque index, bleeding index, probing pocket depth (PD), relative attachment level (RAL), and GCF ALP activity. Statistical Analysis Used: Independent variables for measurements over time were analyzed by using Wilcoxon signed rank test. Results: A statistically significant reduction in all the clinical parameters and GCF ALP activity was observed from baseline to 1 month and 3 months. A correlation was observed between change in GCF ALP activity and PD reduction as well as gain in RAL at 3 months. Conclusion: The present study emphasizes that total ALP activity could be used as a marker for periodontal disease activity in smokers. Estimation of changes in the levels of this enzyme has a potential to aid in the detection of progression of periodontal disease and monitoring the response to periodontal therapy. PMID:27563197

  20. Correlation of alkaline phosphatase activity to clinical parameters of inflammation in smokers suffering from chronic periodontitis

    Directory of Open Access Journals (Sweden)

    Vishakha Grover

    2016-01-01

    Full Text Available Context: Current clinical periodontal diagnostic techniques emphasize the assessment of clinical and radiographic signs of periodontal diseases which can provide a measure of history of disease. Hence, new methodologies for early identification and determination of periodontal disease activity need to be explored which will eventually result in expedited treatment. Aim: To evaluate the correlation of alkaline phosphatase (ALP activity in gingival crevicular fluid (GCF to clinical parameters of periodontal inflammation in smokers with chronic periodontitis. Materials and Methods: Study population included 15 smoker male patients in the age group of 35–55 years suffering from moderate generalized chronic periodontitis with history of smoking present. Following parameters were evaluated at baseline, 1 month and 3 months after scaling and root planing: plaque index, bleeding index, probing pocket depth (PD, relative attachment level (RAL, and GCF ALP activity. Statistical Analysis Used: Independent variables for measurements over time were analyzed by using Wilcoxon signed rank test. Results: A statistically significant reduction in all the clinical parameters and GCF ALP activity was observed from baseline to 1 month and 3 months. A correlation was observed between change in GCF ALP activity and PD reduction as well as gain in RAL at 3 months. Conclusion: The present study emphasizes that total ALP activity could be used as a marker for periodontal disease activity in smokers. Estimation of changes in the levels of this enzyme has a potential to aid in the detection of progression of periodontal disease and monitoring the response to periodontal therapy.

  1. Predictive value of clinical history compared with urodynamic study in 1,179 women

    Directory of Open Access Journals (Sweden)

    Jorge Milhem Haddad

    2016-02-01

    Full Text Available SUMMARY Objective: to determine the positive predictive value of clinical history in comparison with urodynamic study for the diagnosis of urinary incontinence. Methods: retrospective analysis comparing clinical history and urodynamic evaluation of 1,179 women with urinary incontinence. The urodynamic study was considered the gold standard, whereas the clinical history was the new test to be assessed. This was established after analyzing each method as the gold standard through the difference between their positive predictive values. Results: the positive predictive values of clinical history compared with urodynamic study for diagnosis of stress urinary incontinence, overactive bladder and mixed urinary incontinence were, respectively, 37% (95% CI 31-44, 40% (95% CI 33-47 and 16% (95% CI 14-19. Conclusion: we concluded that the positive predictive value of clinical history was low compared with urodynamic study for urinary incontinence diagnosis. The positive predictive value was low even among women with pure stress urinary incontinence.

  2. Approaches to highly parameterized inversion: A guide to using PEST for model-parameter and predictive-uncertainty analysis

    Science.gov (United States)

    Doherty, John E.; Hunt, Randall J.; Tonkin, Matthew J.

    2010-01-01

    Analysis of the uncertainty associated with parameters used by a numerical model, and with predictions that depend on those parameters, is fundamental to the use of modeling in support of decisionmaking. Unfortunately, predictive uncertainty analysis with regard to models can be very computationally demanding, due in part to complex constraints on parameters that arise from expert knowledge of system properties on the one hand (knowledge constraints) and from the necessity for the model parameters to assume values that allow the model to reproduce historical system behavior on the other hand (calibration constraints). Enforcement of knowledge and calibration constraints on parameters used by a model does not eliminate the uncertainty in those parameters. In fact, in many cases, enforcement of calibration constraints simply reduces the uncertainties associated with a number of broad-scale combinations of model parameters that collectively describe spatially averaged system properties. The uncertainties associated with other combinations of parameters, especially those that pertain to small-scale parameter heterogeneity, may not be reduced through the calibration process. To the extent that a prediction depends on system-property detail, its postcalibration variability may be reduced very little, if at all, by applying calibration constraints; knowledge constraints remain the only limits on the variability of predictions that depend on such detail. Regrettably, in many common modeling applications, these constraints are weak. Though the PEST software suite was initially developed as a tool for model calibration, recent developments have focused on the evaluation of model-parameter and predictive uncertainty. As a complement to functionality that it provides for highly parameterized inversion (calibration) by means of formal mathematical regularization techniques, the PEST suite provides utilities for linear and nonlinear error-variance and uncertainty analysis in

  3. A biometric approach to predictable treatment of clinical crown discrepancies.

    Science.gov (United States)

    Chu, Stephen J

    2007-08-01

    Dental professionals have long been guided by mathematical principles when interpreting aesthetic and tooth proportions for their patients. While many acknowledge that such principles are merely launch points for a smile design or reconstructive procedure, their existence appears to indicate practitioners' desire for predictable, objective, and reproducible means of achieving success in aesthetic dentistry. This article introduces innovative aesthetic measurement gauges as a means of objectively quantifying tooth size discrepancies and enabling the clinician to perform aesthetic restorative dentistry with success and predictability.

  4. Islet Oxygen Consumption Rate (OCR) Dose Predicts Insulin Independence in Clinical Islet Autotransplantation

    OpenAIRE

    Papas, Klearchos K; Bellin, Melena D.; Sutherland, David E. R.; Suszynski, Thomas M.; Kitzmann, Jennifer P.; Avgoustiniatos, Efstathios S.; Gruessner, Angelika C.; Mueller, Kathryn R.; Beilman, Gregory J.; Balamurugan, Appakalai N.; Gopalakrishnan Loganathan; Colton, Clark K.; Maria Koulmanda; Weir, Gordon C.; Josh J Wilhelm

    2015-01-01

    Background: Reliable in vitro islet quality assessment assays that can be performed routinely, prospectively, and are able to predict clinical transplant outcomes are needed. In this paper we present data on the utility of an assay based on cellular oxygen consumption rate (OCR) in predicting clinical islet autotransplant (IAT) insulin independence (II). IAT is an attractive model for evaluating characterization assays regarding their utility in predicting II due to an absence of confounding ...

  5. Towards clinical application: repetitive sensor position re-calibration for improved reliability of gait parameters.

    Science.gov (United States)

    Hamacher, Daniel; Hamacher, Dennis; Taylor, William R; Singh, Navrag B; Schega, Lutz

    2014-04-01

    While camera-based motion tracking systems are considered to be the gold standard for kinematic analysis, these systems are not practical in clinical practice. However, the collection of gait parameters using inertial sensors is feasible in clinical settings and less expensive, but suffers from drift error that excludes accurate analyses. The goal of this study was to apply a combination of repetitive sensor position re-calibration techniques in order to improve the intra-day and inter-day reliability of gait parameters using inertial sensors. Kinematic data of nineteen healthy elderly individuals were captured twice within the first day and once on a second day after one week using inertial sensors fixed on the subject's forefoot during gait. Parameters of walking speed, minimum foot clearance (MFC), minimum toe clearance (MTC), stride length, stance time and swing time, as well as their corresponding measures of variability were calculated. Intra-day and inter-day differences were rated using intra-class correlation coefficients (ICC(3,1)), as well as the bias and limits of agreement. The results indicate excellent reliability for all intra-day and inter-day mean parameters (ICC: MFC 0.83-stride length 0.99). While good to excellent reliability was observed during intra-day parameters of variability (ICC: walking speed 0.71-MTC 0.98), corresponding inter-day reliability ranged from poor to excellent (ICC: walking speed 0.32-MTC 0.95). In conclusion, the system is suitable for reliable measurement of mean temporo-spatial parameters and the variability of MFC and MTC. However, the system's accuracy needs to be improved before remaining parameters of variability can reliably be collected.

  6. Prediction efficiency of the hydrographical parameters as related to distribution patterns of the Pleuromamma species in the Indian Ocean

    Digital Repository Service at National Institute of Oceanography (India)

    Jayalakshmy, K.V.; Saraswathy, M.

    . Multiple regression model of P. indica abundance on the parameters: temperature, salinity, dissolved oxygen and phosphate-phosphorus could explain more than 85% of the variation in the predicted abundance, while those of 8 species obtained from...

  7. On-Line Flutter Prediction Tool for Wind Tunnel Flutter Testing using Parameter Varying Estimation Methodology Project

    Data.gov (United States)

    National Aeronautics and Space Administration — ZONA Technology, Inc. (ZONA) proposes to develop an on-line flutter prediction tool using the parameter varying estimation (PVE) methodology, called the PVE...

  8. On-Line Flutter Prediction Tool for Wind Tunnel Flutter Testing using Parameter Varying Estimation Methodology Project

    Data.gov (United States)

    National Aeronautics and Space Administration — ZONA Technology, Inc. (ZONA) proposes to develop an on-line flutter prediction tool for wind tunnel model using the parameter varying estimation (PVE) technique to...

  9. Comparison of statistical and clinical predictions of functional outcome after ischemic stroke.

    Directory of Open Access Journals (Sweden)

    Douglas D Thompson

    Full Text Available To determine whether the predictions of functional outcome after ischemic stroke made at the bedside using a doctor's clinical experience were more or less accurate than the predictions made by clinical prediction models (CPMs.A prospective cohort study of nine hundred and thirty one ischemic stroke patients recruited consecutively at the outpatient, inpatient and emergency departments of the Western General Hospital, Edinburgh between 2002 and 2005. Doctors made informal predictions of six month functional outcome on the Oxford Handicap Scale (OHS. Patients were followed up at six months with a validated postal questionnaire. For each patient we calculated the absolute predicted risk of death or dependence (OHS≥3 using five previously described CPMs. The specificity of a doctor's informal predictions of OHS≥3 at six months was good 0.96 (95% CI: 0.94 to 0.97 and similar to CPMs (range 0.94 to 0.96; however the sensitivity of both informal clinical predictions 0.44 (95% CI: 0.39 to 0.49 and clinical prediction models (range 0.38 to 0.45 was poor. The prediction of the level of disability after stroke was similar for informal clinical predictions (ordinal c-statistic 0.74 with 95% CI 0.72 to 0.76 and CPMs (range 0.69 to 0.75. No patient or clinician characteristic affected the accuracy of informal predictions, though predictions were more accurate in outpatients.CPMs are at least as good as informal clinical predictions in discriminating between good and bad functional outcome after ischemic stroke. The place of these models in clinical practice has yet to be determined.

  10. Proposed parameters of specific rain attenuation prediction for Free Space Optics link operating in tropical region

    Science.gov (United States)

    Suriza, A. Z.; Md Rafiqul, Islam; Wajdi, A. K.; Naji, A. W.

    2013-03-01

    As the demand for higher and unlimited bandwidth for communication channel is increased, Free Space Optics (FSO) is a good alternative solution. As it is protocol transparent, easy to install, cost effective and have capabilities like fiber optics, its demand rises very fast. Weather condition, however is the limiting factor for FSO link. In the temperate region the major blockage for FSO link feasibility is fog. In the tropical region high rainfall rate is expected to be the major drawback of FSO link availability. Rain attenuation is the most significant to influence FSO link availability in tropical region. As for now the available k and α values are developed using data from temperate regions. Therefore, the objective of this paper is to propose new parameters for specific rain attenuation prediction model that represents tropical weather condition. The proposed values are derived from data measured in Malaysia and using methods recommended by ITU-R.

  11. Predicting future conflict between team-members with parameter-free models of social networks

    Science.gov (United States)

    Rovira-Asenjo, Núria; Gumí, Tània; Sales-Pardo, Marta; Guimerà, Roger

    2013-06-01

    Despite the well-documented benefits of working in teams, teamwork also results in communication, coordination and management costs, and may lead to personal conflict between team members. In a context where teams play an increasingly important role, it is of major importance to understand conflict and to develop diagnostic tools to avert it. Here, we investigate empirically whether it is possible to quantitatively predict future conflict in small teams using parameter-free models of social network structure. We analyze data of conflict appearance and resolution between 86 team members in 16 small teams, all working in a real project for nine consecutive months. We find that group-based models of complex networks successfully anticipate conflict in small teams whereas micro-based models of structural balance, which have been traditionally used to model conflict, do not.

  12. Predicting future conflict between team-members with parameter-free models of social networks

    CERN Document Server

    Rovira-Asenjo, Nuria; Sales-Pardo, Marta; Guimera, Roger

    2014-01-01

    Despite the well-documented benefits of working in teams, teamwork also results in communication, coordination and management costs, and may lead to personal conflict between team members. In a context where teams play an increasingly important role, it is of major importance to understand conflict and to develop diagnostic tools to avert it. Here, we investigate empirically whether it is possible to quantitatively predict future conflict in small teams using parameter-free models of social network structure. We analyze data of conflict appearance and resolution between 86 team members in 16 small teams, all working in a real project for nine consecutive months. We find that group-based models of complex networks successfully anticipate conflict in small teams whereas micro-based models of structural balance, which have been traditionally used to model conflict, do not.

  13. Pressure Ulcers in Adults: Prediction and Prevention. Clinical Practice Guideline Number 3.

    Science.gov (United States)

    Agency for Health Care Policy and Research (DHHS/PHS), Rockville, MD.

    This package includes a clinical practice guideline, quick reference guide for clinicians, and patient's guide to predicting and preventing pressure ulcers in adults. The clinical practice guideline includes the following: overview of the incidence and prevalence of pressure ulcers; clinical practice guideline (introduction, risk assessment tools…

  14. Prediction of ground motion parameters for the volcanic area of Mount Etna

    Science.gov (United States)

    Tusa, Giuseppina; Langer, Horst

    2016-01-01

    Ground motion prediction equations (GMPEs) have been derived for peak ground acceleration (PGA), velocity (PGV), and 5 % damped spectral acceleration (PSA) at frequencies between 0.1 and 10 Hz for the volcanic area of Mt. Etna. The dataset consists of 91 earthquakes with epicentral distances between 0.5 and 100 km. Given the specific characteristics of the area, we divided our data set into two groups: shallow events (SE, focal depth 5 km). The range of magnitude covered by the SE and the DE is 3.0 ≤ M L ≤ 4.3 and 3.0 ≤ M L ≤ 4.8, respectively. Signals of DE typically have more high frequencies than those of SE. These differences are clearly reflected in the empirical GMPEs of the two event groups. Empirical GMPEs were estimated considering several functional forms: Sabetta and Pugliese (Bull Seism Soc Am 77:1491-1513, 1987) (SP87), Ambraseys et al. (Earth Eng Struct Dyn 25:371-400, 1996) (AMB96), and Boore and Atkinson (Earth Spectra 24:99-138, 2008) (BA2008). From ANOVA, we learn that most of the errors in our GMPEs can be attributed to unmodeled site effects, whereas errors related to event parameters are limited. For DE, BA2008 outperforms the simpler models SP87 or AMB96. For SE, the simple SP87 is preferable considering the Bayesian Information Criterion since it proves more stable with respect to confidence and gives very similar or even lower prediction errors during cross-validation than the BA2008 model. We compared our results to relationships derived for Italy (ITA10, Bindi et al. Bull Earth Eng 99:2471-2488, 2011). For SE, the main differences are observed for distances greater than about 5 km for both horizontal and vertical PGAs. Conversely, for DE the ITA10 heavily overestimates the peak ground parameters for short distances.

  15. The prediction of Fe Mössbauer parameters by the density functional theory: a benchmark study.

    Science.gov (United States)

    Bochevarov, Arteum D; Friesner, Richard A; Lippard, Stephen J

    2010-11-01

    We report the performance of eight density functionals (B3LYP, BPW91, OLYP, O3LYP, M06, M06-2X, PBE, and SVWN5) in two Gaussian basis sets (Wachters and Partridge-1 on iron atoms; cc-pVDZ on the rest of atoms) for the prediction of the isomer shift (IS) and the quadrupole splitting (QS) parameters of Mössbauer spectroscopy. Two sources of geometry (density functional theory-optimized and X-ray) are used. Our data set consists of 31 iron-containing compounds (35 signals), the Mössbauer spectra of which were determined at liquid helium temperature and where the X-ray geometries are known. Our results indicate that the larger and uncontracted Partridge-1 basis set produces slightly more accurate linear correlations of electronic density used for the prediction of IS and noticeably more accurate results for the QS parameter. We confirm and discuss the earlier observation of Noodleman and co-workers that different oxidation states of iron produce different IS calibration lines. The B3LYP and O3LYP functionals have the lowest errors for either IS or QS. BPW91, OLYP, PBE, and M06 have a mixed success whereas SVWN5 and M06-2X demonstrate the worst performance. Finally, our calibrations and conclusions regarding the best functional to compute the Mössbauer characteristics are applied to candidate structures for the peroxo and Q intermediates of the enzyme methane monooxygenase hydroxylase (MMOH), and compared to experimental data in the literature. PMID:21258606

  16. Dose-volumetric parameters for predicting hypothyroidism after radiotherapy for head and neck cancer

    International Nuclear Information System (INIS)

    To investigate predictors affecting the development of hypothyroidism after radiotherapy for head and neck cancer, focusing on radiation dose-volumetric parameters, and to determine the appropriate radiation dose-volumetric threshold of radiation-induced hypothyroidism. A total of 114 patients with head and neck cancer whose radiotherapy fields included the thyroid gland were analysed. The purpose of the radiotherapy was either definitive (n=81) or post-operative (n=33). Thyroid function was monitored before starting radiotherapy and after completion of radiotherapy at 1 month, 6 months, 1 year and 2 years. A diagnosis of hypothyroidism was based on a thyroid stimulating hormone value greater than the maximum value of laboratory range, regardless of symptoms. In all patients, dose volumetric parameters were analysed. Median follow-up duration was 25 months (range; 6-38). Forty-six percent of the patients were diagnosed as hypothyroidism after a median time of 8 months (range; 1-24). There were no significant differences in the distribution of age, gender, surgery, radiotherapy technique and chemotherapy between the euthyroid group and the hypothyroid group. In univariate analysis, the mean dose and V35-V50 results were significantly associated with hypothyroidism. The V45 is the only variable that independently contributes to the prediction of hypothyroidism in multivariate analysis and V45 of 50% was a threshold value. If V45 was <50%, the cumulative incidence of hypothyroidism at 1 year was 22.8%, whereas the incidence was 56.1% if V45 was ≥50%. (P=0.034). The V45 may predict risk of developing hypothyroidism after radiotherapy for head and neck cancer, and a V45 of 50% can be a useful dose-volumetric threshold of radiation-induced hypothyroidism. (author)

  17. Analysis of clinical and morphological parameters in patients with vulvar melanoma

    Directory of Open Access Journals (Sweden)

    E. V. Korzhevskaya

    2011-01-01

    Full Text Available The purpose of this study was to estimate the value of and to reveal the specific features of clinical and morphological parameters in pa- tients with vulvar melanoma. The study was based on the data obtained from the analysis of 40 vulvar melanoma patients treated at the N.N. Blokhin Russian Cancer Research Institute in the period January 1980 to December 2010.

  18. Prediction of pyrolysis kinetic parameters from biomass constituents based on simplex-lattice mixture design☆

    Institute of Scientific and Technical Information of China (English)

    Panusit Sungsuk; Sasiporn Chayaporn; Sasithorn Sunphorka; Prapan Kuchonthara; Pornpote Piumsomboon; Benjapon Chalermsinsuwan

    2016-01-01

    The aim of this study is to determine the effect of the main chemical components of biomass:cel ulose, hemicel-lulose and lignin, on chemical kinetics of biomass pyrolysis. The experiments were designed based on a simplex-lattice mixture design. The pyrolysis was observed by using a thermogravimetric analyzer. The curves obtained from the employed analytical method fit the experimental data (R2 N 0.9). This indicated that this method has the potential to determine the kinetic parameters such as the activation energy (Ea), frequency factor (A) and re-action order (n) for each point of the experimental design. The results obtained from the simplex-lattice mixture design indicated that cellulose had a significant effect on Ea and A, and the interaction between cellulose and lignin had an important effect on the reaction order, n. The proposed models were then proved to be useful for predicting pyrolysis behavior in real biomass and so could be used as a simple approximation for predicting the overall trend of chemical reaction kinetics.

  19. Antioxidant defense parameters as predictive biomarkers for fermentative capacity of active dried wine yeast.

    Science.gov (United States)

    Gamero-Sandemetrio, Esther; Gómez-Pastor, Rocío; Matallana, Emilia

    2014-08-01

    The production of active dried yeast (ADY) is a common practice in industry for the maintenance of yeast starters and as a means of long term storage. The process, however, causes multiple cell injuries, with oxidative damage being one of the most important stresses. Consequentially, dehydration tolerance is a highly appreciated property in yeast for ADY production. In this study we analyzed the cellular redox environment in three Saccharomyces cerevisiae wine strains, which show markedly different fermentative capacities after dehydration. To measure/quantify the effect of dehydration on the S. cerevisiae strains, we used: (i) fluorescent probes; (ii) antioxidant enzyme activities; (ii) intracellular damage; (iii) antioxidant metabolites; and (iv) gene expression, to select a minimal set of biochemical parameters capable of predicting desiccation tolerance in wine yeasts. Our results show that naturally enhanced antioxidant defenses prevent oxidative damage after wine yeast biomass dehydration and improve fermentative capacity. Based on these results we chose four easily assayable parameters/biomarkers for the selection of industrial yeast strains of interest for ADY production: trehalose and glutathione levels, and glutathione reductase and catalase enzymatic activities. Yeast strains selected in accordance with this process display high levels of trehalose, low levels of oxidized glutathione, a high induction of glutathione reductase activity, as well as a high basal level and sufficient induction of catalase activity, which are properties inherent in superior ADY strains.

  20. Torque rheological parameters to predict pellet quality in extrusion-spheronization.

    Science.gov (United States)

    Soh, J L P; Liew, C V; Heng, P W S

    2006-06-01

    This study explored the feasibility of predicting the quality of microcrystalline cellulose (MCC) pellets prepared by extrusion-spheronization using torque rheological characterization. Rheological properties of eleven MCC grades as well as their binary mixtures with lactose (3:7) at various water contents were determined using a mixer torque rheometer (MTR). Derived torque parameters were: maximum torque and cumulative energy of mixing (CEM). CEM values of MCC powders (CEM((MCC))) could be attributed to their physical properties such as crystallinity, V(low P) and V(total) (volumes of mercury intruded in their pores at low pressure and the total intrusion volume), bulk and tapped densities. For both MCC powders and their binary mixtures, strong correlation was observed between their torque parameters and the properties of their pellets formed with 30 and 35% (w/w) water. Since this relationship was valid over a broad water content range, rheological assessment for pre-formulation purposes need not be performed at optimized water contents. These results demonstrated the usefulness of torque rheometry as an effective means of comparing and evaluating MCC grades especially when substitution of equivalent grades is encountered. In so doing, the tedious and expensive pre-production (pre-formulation and optimization) work can be considerably reduced. PMID:16574352

  1. Antioxidant defense parameters as predictive biomarkers for fermentative capacity of active dried wine yeast.

    Science.gov (United States)

    Gamero-Sandemetrio, Esther; Gómez-Pastor, Rocío; Matallana, Emilia

    2014-08-01

    The production of active dried yeast (ADY) is a common practice in industry for the maintenance of yeast starters and as a means of long term storage. The process, however, causes multiple cell injuries, with oxidative damage being one of the most important stresses. Consequentially, dehydration tolerance is a highly appreciated property in yeast for ADY production. In this study we analyzed the cellular redox environment in three Saccharomyces cerevisiae wine strains, which show markedly different fermentative capacities after dehydration. To measure/quantify the effect of dehydration on the S. cerevisiae strains, we used: (i) fluorescent probes; (ii) antioxidant enzyme activities; (ii) intracellular damage; (iii) antioxidant metabolites; and (iv) gene expression, to select a minimal set of biochemical parameters capable of predicting desiccation tolerance in wine yeasts. Our results show that naturally enhanced antioxidant defenses prevent oxidative damage after wine yeast biomass dehydration and improve fermentative capacity. Based on these results we chose four easily assayable parameters/biomarkers for the selection of industrial yeast strains of interest for ADY production: trehalose and glutathione levels, and glutathione reductase and catalase enzymatic activities. Yeast strains selected in accordance with this process display high levels of trehalose, low levels of oxidized glutathione, a high induction of glutathione reductase activity, as well as a high basal level and sufficient induction of catalase activity, which are properties inherent in superior ADY strains. PMID:24644263

  2. Performance of respiratory pattern parameters in classifiers for predict weaning process.

    Science.gov (United States)

    Chaparro, Javier A; Giraldo, Beatriz F; Caminal, Pere; Benito, Salvador

    2012-01-01

    Weaning trials process of patients in intensive care units is a complex clinical procedure. 153 patients under extubation process (T-tube test) were studied: 94 patients with successful trials (group S), 38 patients who failed to maintain spontaneous breathing and were reconnected (group F), and 21 patients with successful test but that had to be reintubated before 48 hours (group R). The respiratory pattern of each patient was characterized through the following time series: inspiratory time (T(I)), expiratory time (T(E)), breathing cycle duration (T(Tot)), tidal volume (V(T)), inspiratory fraction (T(I)/T(Tot)), half inspired flow (V(T)/T(I)), and rapid shallow index (f/V(T)), where ƒ is respiratory rate. Using techniques as autoregressive models (AR), autoregressive moving average models (ARMA) and autoregressive models with exogenous input (ARX), the most relevant parameters of the respiratory pattern were obtained. We proposed the evaluation of these parameters using classifiers as logistic regression (LR), linear discriminant analysis (LDA), support vector machines (SVM) and classification and regression tree (CART) to discriminate between patients from groups S, F and R. An accuracy of 93% (98% sensitivity and 82% specificity) has been obtained using CART classification. PMID:23366890

  3. A new model to predict weak-lensing peak counts. II. Parameter constraint strategies

    Science.gov (United States)

    Lin, Chieh-An; Kilbinger, Martin

    2015-11-01

    Context. Peak counts have been shown to be an excellent tool for extracting the non-Gaussian part of the weak lensing signal. Recently, we developed a fast stochastic forward model to predict weak-lensing peak counts. Our model is able to reconstruct the underlying distribution of observables for analysis. Aims: In this work, we explore and compare various strategies for constraining a parameter using our model, focusing on the matter density Ωm and the density fluctuation amplitude σ8. Methods: First, we examine the impact from the cosmological dependency of covariances (CDC). Second, we perform the analysis with the copula likelihood, a technique that makes a weaker assumption than does the Gaussian likelihood. Third, direct, non-analytic parameter estimations are applied using the full information of the distribution. Fourth, we obtain constraints with approximate Bayesian computation (ABC), an efficient, robust, and likelihood-free algorithm based on accept-reject sampling. Results: We find that neglecting the CDC effect enlarges parameter contours by 22% and that the covariance-varying copula likelihood is a very good approximation to the true likelihood. The direct techniques work well in spite of noisier contours. Concerning ABC, the iterative process converges quickly to a posterior distribution that is in excellent agreement with results from our other analyses. The time cost for ABC is reduced by two orders of magnitude. Conclusions: The stochastic nature of our weak-lensing peak count model allows us to use various techniques that approach the true underlying probability distribution of observables, without making simplifying assumptions. Our work can be generalized to other observables where forward simulations provide samples of the underlying distribution.

  4. Serum parameters predict the severity of ultrasonographicifndingsinnon-alcoholic fatty liver disease

    Institute of Scientific and Technical Information of China (English)

    Mohsen Razavizade; Raika Jamali; Abbas Arj; Hamidreza Talari

    2012-01-01

    BACKGROUND: Controversy exists about the correlation between liver ultrasonography and serum parameters for evaluating the severity of liver involvement in non-alcoholic fatty liver disease (NAFLD). This study was designed to determine the association between liver ultrasonography staging in NAFLD and serum parameters correlated with disease severity in previous studies; and set optimal cut-off points for those serum parameters correlated with NAFLD staging at ultrasonography, in order to differentiate ultrasonographic groups (USGs). METHODS: This cross-sectional study evaluated outpatients with evidence of NAFLD in ultrasonography referred to a general hospital. Those with positive viral markers, abnormal serum ceruloplasmin or gamma-globulin concentrations were excluded. A radiologist performed the ultrasonography staging and stratiifed the patients into mild, moderate, and severe groups. Fasting serum alanine aminotransferase (ALT), aspartate aminotransferase, alkaline phosphatase, triglyceride (TG), high and low density lipoprotein (HDL, LDL), and cholesterol were checked. RESULTS:Two hundred and forty-ifve patients with a mean age (±standard deviation) of 41.63(±11.46) years were included. There were no signiifcant differences when mean laboratory concentrations were compared between moderate and severe USGs. Therefore, these groups were combined to create revised USGs ("mild"versus"moderate or severe"). There were associations between the revised USGs, and ALT, TG, HDL levels, and diabetes mellitus [odds ratios=2.81 (95%conifdence interval (CI):1.37-5.76), 2.48 (95%CI:1.29-4.78), 0.36 (95%CI:0.18-0.74), and 5.65 (95%CI:2.86-11.16) respectively;all P values CONCLUSIONS: Serum ALT, TG, and HDL concentrations seem to be associated with the staging by liver ultrasonography in NAFLD. They might be used to predict the staging of liver ultrasonography in these patients.

  5. Predicting the wheel rolling resistance regarding important motion parameters using the artificial neural network

    Directory of Open Access Journals (Sweden)

    F Gheshlaghi

    2016-04-01

    the analytical and statistical methods. It is expected that the neural network can more accurately predict the rolling resistance. In this study, the neural network for experimental data was trained and the relationship among some parameters of velocity, dynamic load and tire pressure and rolling resistance were evaluated. Materials and Methods: The soil bin and single wheel tester of Biosystem Engineering Mechanics Department of Urmia University was used in this study. This soil bin has 24 m length, 2 m width and 1 m depth including a single-wheel tester and the carrier. Tester consists of four horizontal arms and a vertical arm to vertical load. The S-shaped load cells were employed in horizontal arms with a load capacity of 200 kg and another 500 kg in the vertical arm was embedded. The tire used in this study was a general pneumatic tire (Good year 9.5L-14, 6 ply In this study, artificial neural networks were used for optimizing the rolling resistance by 35 neurons, 6 inputs and 1 output choices. Comparison of neural network models according to the mean square error and correlation coefficient was used. In addition, 60% of the data on training, 20% on test and finally 20% of the credits was allocated to the validation and Output parameter of the neural network model has determined the tire rolling resistance. Finally, this study predicts the effects of changing parameters of tire pressure, vertical load and velocity on rolling resistance using a trained neural network. Results and Discussion: Based on obtained error of Levenberg- Marquardt algorithm, neural network with 35 neurons in the hidden layer with sigmoid tangent function and one neuron in the output layer with linear actuator function were selected. The regression coefficient of tested network is 0.92 which seems acceptable, considering the complexity of the studied process. Some of the input parameters to the network are speed, pressure and vertical load which their relationship with the rolling

  6. Parameter definition using vibration prediction software leads to significant drilling performance improvements

    Energy Technology Data Exchange (ETDEWEB)

    Amorim, Dalmo; Hanley, Chris Hanley; Fonseca, Isaac; Santos, Juliana [National Oilwell Varco, Houston TX (United States); Leite, Daltro J.; Borella, Augusto; Gozzi, Danilo [Petroleo Brasileiro S.A. (PETROBRAS), Rio de Janeiro, RJ (Brazil)

    2012-07-01

    field monitoring. Vibration prediction diminishes the importance of trial-and-error procedures such as drill-off tests, which are valid only for short sections. It also solves an existing lapse in Mechanical Specific Energy (MSE) real-time drilling control programs applying the theory of Teale, which states that a drilling system is perfectly efficient when it spends the exact energy to overcome the in situ rock strength. Using the proprietary software tool this paper will examine the resonant vibration modes that may be initiated while drilling with different BHA's and drill string designs, showing that the combination of a proper BHA design along with the correct selection of input parameters results in an overall improvement to drilling efficiency. Also, being the BHA predictively analyzed, it will be reduced the potential for vibration or stress fatigue in the drill string components, leading to a safer operation. In the recent years there has been an increased focus on vibration detection, analysis, and mitigation techniques, where new technologies, like the Drilling Dynamics Data Recorders (DDDR), may provide the capability to capture high frequency dynamics data at multiple points along the drilling system. These tools allow the achievement of drilling performance improvements not possible before, opening a whole new array of opportunities for optimization and for verification of predictions calculated by the drill string dynamics modeling software tool. The results of this study will identify how the dynamics from the drilling system, interacting with formation, directly relate to inefficiencies and to the possible solutions to mitigate drilling vibrations in order to improve drilling performance. Software vibration prediction and downhole measurements can be used for non-drilling operations like drilling out casing or reaming, where extremely high vibration levels - devastating to the cutting structure of the bit before it has even touched bottom - have

  7. Somatic cell count distributions during lactation predict clinical mastitis

    NARCIS (Netherlands)

    Green, M.J.; Green, L.E.; Schukken, Y.H.; Bradley, A.J.; Peeler, E.J.; Barkema, H.W.; Haas, de Y.; Collis, V.J.; Medley, G.F.

    2004-01-01

    This research investigated somatic cell count (SCC) records during lactation, with the purpose of identifying distribution characteristics (mean and measures of variation) that were most closely associated with clinical mastitis. Three separate data sets were used, one containing quarter SCC (n = 14

  8. The Prediction of Academic and Clinical Performance in Medical School

    Science.gov (United States)

    Gough, Harrison G.; Hall, Wallace B.

    1975-01-01

    A study of medical student performance showed the clinical performance factor more or less unpredictable from aptitude and premedical academic achievement indices while the academic performance factor was forecast with acceptable accuracy by equations based on the Medical College Admissions Test and premedical grade point average. (JT)

  9. Prediction of the date, magnitude and affected area of impending strong earthquakes using integration of multi precursors earthquake parameters

    OpenAIRE

    M. R. Saradjian; Akhoondzadeh, M

    2011-01-01

    Usually a precursor alone might not be useful as an accurate, precise, and stand-alone criteria for the earthquake parameters prediction. Therefore it is more appropriate to exploit parameters extracted from a variety of individual precursors so that their simultaneous integration would reduce the parameters's uncertainty.

    In our previous studies, five strong earthquakes which happened in the Samoa Islands, Sichuan (China), L'Aquila (Italy), Borujerd (Iran) and Zarand (Ir...

  10. An Integrative Pathway-based Clinical-genomic Model for Cancer Survival Prediction.

    Science.gov (United States)

    Chen, Xi; Wang, Lily; Ishwaran, Hemant

    2010-09-01

    Prediction models that use gene expression levels are now being proposed for personalized treatment of cancer, but building accurate models that are easy to interpret remains a challenge. In this paper, we describe an integrative clinical-genomic approach that combines both genomic pathway and clinical information. First, we summarize information from genes in each pathway using Supervised Principal Components (SPCA) to obtain pathway-based genomic predictors. Next, we build a prediction model based on clinical variables and pathway-based genomic predictors using Random Survival Forests (RSF). Our rationale for this two-stage procedure is that the underlying disease process may be influenced by environmental exposure (measured by clinical variables) and perturbations in different pathways (measured by pathway-based genomic variables), as well as their interactions. Using two cancer microarray datasets, we show that the pathway-based clinical-genomic model outperforms gene-based clinical-genomic models, with improved prediction accuracy and interpretability.

  11. Prevalence of herpesviruses in gingivitis and chronic periodontitis: relationship to clinical parameters and effect of treatment

    Directory of Open Access Journals (Sweden)

    Rucha Shah

    2016-01-01

    Full Text Available Background: Assess the prevalence of herpesviruses in healthy subjects, gingivitis, and chronic periodontitis patients, to assess the relationship between the prevalence of herpesviruses and periodontal clinical parameters, and to evaluate the effect of phase-I therapy on the level of viral detection. Materials and Methods: Hundred patients consisting of 20 healthy subjects, 40 gingivitis, and 40 chronic periodontitis were included in the study. Clinical parameters recorded included plaque index, gingival index, sulcus bleeding index, probing depth, and clinical attachment level. The gingivitis and chronic periodontitis patients received phase-I periodontal therapy including oral hygiene instructions, full mouth scaling for gingivitis patients and scaling and root planing for chronic periodontitis patients. Gingival crevicular fluid (GCF was collected, and the presence of herpes simplex virus-1 (HSV-1, HSV-2, cytomegalovirus, and Epstein–Barr virus (EBV was analyzed using polymerase chain reaction (PCR. Recording of periodontal parameters as well as GCF collection was performed at baseline and 6 weeks postphase-I therapy. Results: At baseline, the levels of HSV-1 and EBV detection were lower in healthy controls as compared to gingivitis (P < 0.05 and chronic periodontitis cases (P < 0.001. Phase-I therapy led to reduction in the amount of HSV-1 and EBV in gingivitis patients (P < 0.05 and for HSV-1, human cytomegalovirus and EBV in chronic periodontitis patients (P < 0.05 in comparison to baseline. The prevalence of EBV in chronic periodontitis patients was positively associated with increased gingival index, probing depth and loss of clinical attachment (P < 0.05. Conclusions: Higher prevalence of HSV-1 and EBV viruses in GCF of gingivitis and chronic periodontitis suggests a strong association between these viruses and periodontal diseases and periodontal therapy can lead to a reduction in herpesviruses at infected sites.

  12. Are clinical parameters sufficient to model gait patterns in patients with cerebral palsy using a multilinear approach?

    Science.gov (United States)

    Bonnefoy-Mazure, Alice; Sagawa, Yoshisama; Pomero, Vincent; Lascombes, Pierre; De Coulon, Geraldo; Armand, Stéphane

    2016-01-01

    The aim of this study was to evaluate whether clinical parameters are sufficient using, a multilinear regression model, to reproduce the sagittal plane joint angles (hip, knee, and ankle) in cerebral palsy gait. A total of 154 patients were included. The two legs were considered (308 observations). Thirty-six clinical parameters were used as regressors (range of motion, muscle strength, and spasticity of the lower). From the clinical gait analysis, the joint angles of the sagittal plane were selected. Results showed that clinical parameter does not provide sufficient information to recover joint angles and/or that the multilinear regression model is not an appropriate solution.

  13. Predicting CYP2C19 catalytic parameters for enantioselective oxidations using artificial neural networks and a chirality code.

    Science.gov (United States)

    Hartman, Jessica H; Cothren, Steven D; Park, Sun-Ha; Yun, Chul-Ho; Darsey, Jerry A; Miller, Grover P

    2013-07-01

    Cytochromes P450 (CYP for isoforms) play a central role in biological processes especially metabolism of chiral molecules; thus, development of computational methods to predict parameters for chiral reactions is important for advancing this field. In this study, we identified the most optimal artificial neural networks using conformation-independent chirality codes to predict CYP2C19 catalytic parameters for enantioselective reactions. Optimization of the neural networks required identifying the most suitable representation of structure among a diverse array of training substrates, normalizing distribution of the corresponding catalytic parameters (k(cat), K(m), and k(cat)/K(m)), and determining the best topology for networks to make predictions. Among different structural descriptors, the use of partial atomic charges according to the CHelpG scheme and inclusion of hydrogens yielded the most optimal artificial neural networks. Their training also required resolution of poorly distributed output catalytic parameters using a Box-Cox transformation. End point leave-one-out cross correlations of the best neural networks revealed that predictions for individual catalytic parameters (k(cat) and K(m)) were more consistent with experimental values than those for catalytic efficiency (k(cat)/K(m)). Lastly, neural networks predicted correctly enantioselectivity and comparable catalytic parameters measured in this study for previously uncharacterized CYP2C19 substrates, R- and S-propranolol. Taken together, these seminal computational studies for CYP2C19 are the first to predict all catalytic parameters for enantioselective reactions using artificial neural networks and thus provide a foundation for expanding the prediction of cytochrome P450 reactions to chiral drugs, pollutants, and other biologically active compounds.

  14. Association of IL-8 (-251 A/T Gene Polymorphism with Clinical Parameters and Chronic Periodontitis

    Directory of Open Access Journals (Sweden)

    Hengameh Khosropanah

    2013-01-01

    Full Text Available Objective: To investigate the correlation between IL-8 (-251 A/T gene polymorphism and susceptibility to chronic periodontitis as well as different clinical parameters and severity of the condition in patients referred to dental school, Shiraz University of Medical Sciences, Shiraz, Iran.Materials and Methods: In this randomized cross sectional study, 227 non-smoking patients with chronic periodontitis (test and 40 healthy individuals (control were enrolled in this experiment and the following clinical parameters were employed in the study: Periodontal Pocket Depth (PPD, Clinical Attachment Level (CAL and Bone Loss (BL. All participants underwent the PCR (Polymerase Chain Reaction test to detect 251 A/T Single Nucleotide Polymorphism of IL8 gene.Results: No significant correlation was perceived between different genotypes of IL-8 and the severity of the periodontal condition (P= 0.164, neither did we detect any substantial association between different IL-8 genotypes and the mean PPD (P=0.525, CAL (P=0.151, BL (P=0.255, PI (P=0.087, BOP (P=0.265 and the average number of teeth (P=0.931.Conclusion: The results implied that there was no explicit correlation between 251 (A/T IL-8 gene polymorphism and the severity of the chronic periodontal disease or to the susceptibility to it.

  15. Validity of Sildenafil Test in Patients with Pulmonary Arterial Hypertension Associated with Congenital Heart Disease According to Clinical and Echocardiographic Parameters

    OpenAIRE

    Akbar Shahmohammadi; Paridokht Nakhostin Davari; Mohammad Yusof Aarabi Mogaddam; Akbar Molaei; Mahmood Meraji

    2009-01-01

    Background: Pulmonary arterial hypertension is a complication of most congenital heart diseases. We sought to assess the effect of sildenafil on patients suffering from pulmonary arterial hypertension in association with congenital heart disease on the basis of clinical and echocardiographic parameters and compare the catheterization and treatment results so as to evaluate the predictive value of sildenafil on the operability of patients. Methods: After primary echocardiography, 21 patients w...

  16. DNA Methylation-Guided Prediction of Clinical Failure in High-Risk Prostate Cancer.

    Directory of Open Access Journals (Sweden)

    Kirill Litovkin

    Full Text Available Prostate cancer (PCa is a very heterogeneous disease with respect to clinical outcome. This study explored differential DNA methylation in a priori selected genes to diagnose PCa and predict clinical failure (CF in high-risk patients.A quantitative multiplex, methylation-specific PCR assay was developed to assess promoter methylation of the APC, CCND2, GSTP1, PTGS2 and RARB genes in formalin-fixed, paraffin-embedded tissue samples from 42 patients with benign prostatic hyperplasia and radical prostatectomy specimens of patients with high-risk PCa, encompassing training and validation cohorts of 147 and 71 patients, respectively. Log-rank tests, univariate and multivariate Cox models were used to investigate the prognostic value of the DNA methylation.Hypermethylation of APC, CCND2, GSTP1, PTGS2 and RARB was highly cancer-specific. However, only GSTP1 methylation was significantly associated with CF in both independent high-risk PCa cohorts. Importantly, trichotomization into low, moderate and high GSTP1 methylation level subgroups was highly predictive for CF. Patients with either a low or high GSTP1 methylation level, as compared to the moderate methylation groups, were at a higher risk for CF in both the training (Hazard ratio [HR], 3.65; 95% CI, 1.65 to 8.07 and validation sets (HR, 4.27; 95% CI, 1.03 to 17.72 as well as in the combined cohort (HR, 2.74; 95% CI, 1.42 to 5.27 in multivariate analysis.Classification of primary high-risk tumors into three subtypes based on DNA methylation can be combined with clinico-pathological parameters for a more informative risk-stratification of these PCa patients.

  17. Utilizing observations of vegetation patterns to infer ecosystem parameters and test model predictions

    Science.gov (United States)

    Penny, G.; Daniels, K. E.; Thompson, S. E.

    2012-12-01

    Periodic vegetation patterns arise globally in arid and semi-arid environments, and are believed to indicate competing positive and negative feedbacks between resource availability and plant uptake at different length scales. The patterns have become the object of two separate research themes, one focusing on observation of ecosystem properties and vegetation morphology, and another focusing on the development of theoretical models and descriptions of pattern behavior. Given the growing body of work in both directions, there is a compelling need to unify both strands of research by bringing together observations of large-scale pattern morphology with predictions made by various models. Previous attempts have employed spectral analysis on pattern images and inverse modeling on one-dimensional transects of patterns images, yet have not made a concerted effort to rigorously confront predictions with observational data in two dimensions. This study makes the first steps towards unification, utilizing high resolution landscape-scale images of vegetation patterns over multiple years at five different locations, including Niger, Central Mexico, Baja California, Texas, and Australia. Initial analyses of the observed patterns reveal considerable departures from the idealized morphologies predicted by models. Pattern wavelengths, while clustered around a local average, vary through space and are frequently altered by pattern defects such as missing or broken bands. While often locally homogeneous, pattern orientation also varies through space, allowing the correlations between landscape features and changes in local pattern morphology to be explored. Stationarity of the pattern can then be examined by comparing temporal changes in morphology with local climatic fluctuations. Ultimately, by identifying homogeneous regions of coherent pattern, inversion approaches can be applied to infer model parameters and build links between observable pattern and landscape features and the

  18. Ethics and epistemology of accurate prediction in clinical research.

    Science.gov (United States)

    Hey, Spencer Phillips

    2015-07-01

    All major research ethics policies assert that the ethical review of clinical trial protocols should include a systematic assessment of risks and benefits. But despite this policy, protocols do not typically contain explicit probability statements about the likely risks or benefits involved in the proposed research. In this essay, I articulate a range of ethical and epistemic advantages that explicit forecasting would offer to the health research enterprise. I then consider how some particular confidence levels may come into conflict with the principles of ethical research.

  19. Prenatal prediction of pulmonary hypoplasia: clinical, biometric, and Doppler velocity correlates

    NARCIS (Netherlands)

    J.A.M. Laudij (Jacqueline); D. Tibboel (Dick); S.G.F. Robben (Simon); R.R. de Krijger (Ronald); M.A.J. de Ridder (Maria); J.W. Wladimiroff (Juriy)

    2002-01-01

    textabstractOBJECTIVES: To determine the value of pulmonary artery Doppler velocimetry relative to fetal biometric indices and clinical correlates in the prenatal prediction of lethal lung hypoplasia (LH) in prolonged (>1 week) oligohydramnios. METHODS: Forty-two singleton pregnanc

  20. Do clinical prediction models improve concordance of treatment decisions in reproductive medicine?

    NARCIS (Netherlands)

    J.W. van der Steeg; P. Steures; M.J.C. Eijkemans; J.D.F. Habbema; P.M.M. Bossuyt; P.G.A. Hompes; F. van der Veen; B.W.J. Mol

    2006-01-01

    Objective To assess whether the use of clinical prediction models improves concordance between gynaecologists with respect to treatment decisions in reproductive medicine. Design We constructed 16 vignettes of subfertile couples by varying fertility history, postcoital test, sperm motility, follicle

  1. Prediction of the thermal dynamic parameters fluctuation of coolant system of the IBR-2M reactor using neural networks

    International Nuclear Information System (INIS)

    This paper presents an artificial neural network method for long-term prediction of the thermal dynamic parameters of primary coolant circuit of the IBR-2M reactor. The main goal is to predict the temperature and liquid sodium flow rate through the core and thermal power. It is shown that the prediction can reduce three times the effects of slow reactivity fluctuations in power and decrease the requirements for the automatic power stabilization system. Nonlinear autoregressive neural network (NAR) with local feedback connection has been considered. The results of prediction error ~ 5% coincide with the experimental ones.

  2. Predicting Relapse in Patients With Medulloblastoma by Integrating Evidence From Clinical and Genomic Features

    NARCIS (Netherlands)

    P. Tamayo; Y.J. Cho; A. Tsherniak; H. Greulich; L. Ambrogio; N. Schouten-van Meeteren; T. Zhou; A. Buxton; M. Kool; M. Meyerson; S.L. Pomeroy; J.P. Mesirov

    2011-01-01

    Purpose Despite significant progress in the molecular understanding of medulloblastoma, stratification of risk in patients remains a challenge. Focus has shifted from clinical parameters to molecular markers, such as expression of specific genes and selected genomic abnormalities, to improve accurac

  3. Locus heterogeneity for Waardenburg syndrome is predictive of clinical subtypes

    Energy Technology Data Exchange (ETDEWEB)

    Farrer, L.A.; Hoth, C. [Boston Univ. School of Medicine, MA (United States); Arnos, K.S. [Galludet Univ., Washington, DC (United States); Asher, J.H. Jr.; Friedman, T.B. [Michigan State Univ., East Lansing, MI (United States); Grundfast, K.M.; Lalwani, A.K. [National Institute on Deafness and Other Communication Disorders, Bethesda, MD (United States); Greenberg, J. [Univ. of Cape Town (South Africa); Diehl, S.R. [and others

    1994-10-01

    Waardenburg syndrome (WS) is a dominantly inherited and clinically variable syndrome of deafness, pigmentary changes, and distinctive facial features. Clinically, WS type I (WS1) is differentiated from WS type II (WS2) by the high frequency of dystopia canthorum in the family. In some families, WS is caused by mutations in the PAX3 gene on chromosome 2q. We have typed microsatellite markers within and flanking PAX3 in 41 WS1 kindreds and 26 WS2 kindreds in order to estimate the proportion of families with probable mutations in PAX3 and to study the relationship between phenotypic and genotypic heterogeneity. Evaluation of heterogeneity in location scores obtained by multilocus analysis indicated that WS is linked to PAX3 in 60% of all WS families and in 100% of WS1 families. None of the WS2 families were linked. In those families in which equivocal lod scores (between -2 and +1) were found, PAX3 mutations have been identified in 5 of the 15 WS1 families but in none of the 4 WS2 families. Although preliminary studies do not suggest any association between the phenotype and the molecular pathology in 20 families with known PAX3 mutations and in four patients with chromosomal abnormalities in the vicinity of PAX3, the presence of dystopia in multiple family members is a reliable indicator for identifying families likely to have a defect in PAX3. 59 refs., 3 figs., 5 tabs.

  4. Modeling and predicting seasonal influenza transmission in warm regions using climatological parameters.

    Directory of Open Access Journals (Sweden)

    Radina P Soebiyanto

    Full Text Available BACKGROUND: Influenza transmission is often associated with climatic factors. As the epidemic pattern varies geographically, the roles of climatic factors may not be unique. Previous in vivo studies revealed the direct effect of winter-like humidity on air-borne influenza transmission that dominates in regions with temperate climate, while influenza in the tropics is more effectively transmitted through direct contact. METHODOLOGY/PRINCIPAL FINDINGS: Using time series model, we analyzed the role of climatic factors on the epidemiology of influenza transmission in two regions characterized by warm climate: Hong Kong (China and Maricopa County (Arizona, USA. These two regions have comparable temperature but distinctly different rainfall. Specifically we employed Autoregressive Integrated Moving Average (ARIMA model along with climatic parameters as measured from ground stations and NASA satellites. Our studies showed that including the climatic variables as input series result in models with better performance than the univariate model where the influenza cases depend only on its past values and error signal. The best model for Hong Kong influenza was obtained when Land Surface Temperature (LST, rainfall and relative humidity were included as input series. Meanwhile for Maricopa County we found that including either maximum atmospheric pressure or mean air temperature gave the most improvement in the model performances. CONCLUSIONS/SIGNIFICANCE: Our results showed that including the environmental variables generally increases the prediction capability. Therefore, for countries without advanced influenza surveillance systems, environmental variables can be used for estimating influenza transmission at present and in the near future.

  5. Predictive Blood Chemistry Parameters for Pansteatitis-Affected Mozambique Tilapia (Oreochromis mossambicus)

    Science.gov (United States)

    Chapman, Robert W.; Somerville, Stephen E.; Guillette, Matthew P.; Botha, Hannes; Hoffman, Andre; Luus-Powell, Wilmien J.; Smit, Willem J.; Lebepe, Jeffrey; Myburgh, Jan; Govender, Danny; Tucker, Jonathan; Boggs, Ashley S. P.

    2016-01-01

    One of the largest river systems in South Africa, the Olifants River, has experienced significant changes in water quality due to anthropogenic activities. Since 2005, there have been various “outbreaks” of the inflammatory disease pansteatitis in several vertebrate species. Large-scale pansteatitis-related mortality events have decimated the crocodile population at Lake Loskop and decreased the population at Kruger National Park. Most pansteatitis-related diagnoses within the region are conducted post-mortem by either gross pathology or histology. The application of a non-lethal approach to assess the prevalence and pervasiveness of pansteatitis in the Olifants River region would be of great importance for the development of a management plan for this disease. In this study, several plasma-based biomarkers accurately classified pansteatitis in Mozambique tilapia (Oreochromis mossambicus) collected from Lake Loskop using a commercially available benchtop blood chemistry analyzer combined with data interpretation via artificial neural network analysis. According to the model, four blood chemistry parameters (calcium, sodium, total protein and albumin), in combination with total length, diagnose pansteatitis to a predictive accuracy of 92 percent. In addition, several morphometric traits (total length, age, weight) were also associated with pansteatitis. On-going research will focus on further evaluating the use of blood chemistry to classify pansteatitis across different species, trophic levels, and within different sites along the Olifants River. PMID:27115488

  6. Predictive Blood Chemistry Parameters for Pansteatitis-Affected Mozambique Tilapia (Oreochromis mossambicus.

    Directory of Open Access Journals (Sweden)

    John A Bowden

    Full Text Available One of the largest river systems in South Africa, the Olifants River, has experienced significant changes in water quality due to anthropogenic activities. Since 2005, there have been various "outbreaks" of the inflammatory disease pansteatitis in several vertebrate species. Large-scale pansteatitis-related mortality events have decimated the crocodile population at Lake Loskop and decreased the population at Kruger National Park. Most pansteatitis-related diagnoses within the region are conducted post-mortem by either gross pathology or histology. The application of a non-lethal approach to assess the prevalence and pervasiveness of pansteatitis in the Olifants River region would be of great importance for the development of a management plan for this disease. In this study, several plasma-based biomarkers accurately classified pansteatitis in Mozambique tilapia (Oreochromis mossambicus collected from Lake Loskop using a commercially available benchtop blood chemistry analyzer combined with data interpretation via artificial neural network analysis. According to the model, four blood chemistry parameters (calcium, sodium, total protein and albumin, in combination with total length, diagnose pansteatitis to a predictive accuracy of 92 percent. In addition, several morphometric traits (total length, age, weight were also associated with pansteatitis. On-going research will focus on further evaluating the use of blood chemistry to classify pansteatitis across different species, trophic levels, and within different sites along the Olifants River.

  7. Predictive Blood Chemistry Parameters for Pansteatitis-Affected Mozambique Tilapia (Oreochromis mossambicus).

    Science.gov (United States)

    Bowden, John A; Cantu, Theresa M; Chapman, Robert W; Somerville, Stephen E; Guillette, Matthew P; Botha, Hannes; Hoffman, Andre; Luus-Powell, Wilmien J; Smit, Willem J; Lebepe, Jeffrey; Myburgh, Jan; Govender, Danny; Tucker, Jonathan; Boggs, Ashley S P; Guillette, Louis J

    2016-01-01

    One of the largest river systems in South Africa, the Olifants River, has experienced significant changes in water quality due to anthropogenic activities. Since 2005, there have been various "outbreaks" of the inflammatory disease pansteatitis in several vertebrate species. Large-scale pansteatitis-related mortality events have decimated the crocodile population at Lake Loskop and decreased the population at Kruger National Park. Most pansteatitis-related diagnoses within the region are conducted post-mortem by either gross pathology or histology. The application of a non-lethal approach to assess the prevalence and pervasiveness of pansteatitis in the Olifants River region would be of great importance for the development of a management plan for this disease. In this study, several plasma-based biomarkers accurately classified pansteatitis in Mozambique tilapia (Oreochromis mossambicus) collected from Lake Loskop using a commercially available benchtop blood chemistry analyzer combined with data interpretation via artificial neural network analysis. According to the model, four blood chemistry parameters (calcium, sodium, total protein and albumin), in combination with total length, diagnose pansteatitis to a predictive accuracy of 92 percent. In addition, several morphometric traits (total length, age, weight) were also associated with pansteatitis. On-going research will focus on further evaluating the use of blood chemistry to classify pansteatitis across different species, trophic levels, and within different sites along the Olifants River.

  8. Parameters That May Be Used for Predicting Failure during Endoscopic Retrograde Cholangiopancreatography

    Directory of Open Access Journals (Sweden)

    Emre Balik

    2013-01-01

    Full Text Available Aim. Endoscopic retrograde cholangiopancreatography (ERCP is frequently used for the diagnosis and treatment of hepatic, biliary tract, and pancreatic disorders. However, failure during cannulation necessitates other interventions. The aim of this study was to establish parameters that can be used to predict failure during ERCP. Methods. A total of 5884 ERCP procedures performed on 5079 patients, between 1991 and 2006, were retrospectively evaluated. Results. Cannulation was possible in 4482 (88.2% patients. For each one-year increase in age, the cannulation failure rate increased by 1.01-fold (. A history of previous hepatic biliary tract surgery caused the cannulation failure rate to decrease by 0.487-fold (. A tumor infiltrating the ampulla, the presence of pathology obstructing the gastrointestinal passage, and peptic ulcer increased the failure rate by 78-, 28-, and 3.47-fold, respectively (. Conclusions.Patient gender and duodenal diverticula do not influence the success of cannulation during ERCP. Billroth II and Roux-en-Y gastrojejunostomy surgeries, a benign or malignant obstruction of the gastrointestinal system, and duodenal ulcers decrease the cannulation success rate, whereas a history of previous hepatic biliary tract surgery increases it. Although all endoscopists had equal levels of experience, statistically significant differences were detected among them.

  9. Study on the Influence of the Work Hardening Models Constitutive Parameters Identification in the Springback Prediction

    Science.gov (United States)

    Oliveira, M. C.; Alves, J. L.; Chaparro, B. M.; Menezes, L. F.

    2005-08-01

    The main goal of this work is to determine the influence of the work hardening model in the numerical prediction of springback. This study will be performed according with the specifications of the first phase of the "Benchmark 3" of the Numisheet'2005 Conference: the "Channel Draw". Several work hardening constitutive models are used in order to allow a better description of the different material mechanical behavior. Two are classical pure isotropic hardening models described by a power law (Swift) or a Voce type saturation equation. Those two models were also combined with a non-linear (Lemaître and Chaboche) kinematic hardening rule. The final one is the Teodosiu microstructural hardening model. The study is performed for two commonly used steels of the automotive industry: mild (DC06) and dual phase (DP600) steels. The mechanical characterization, as well as the constitutive parameters identification of each work hardening models, was performed by LPMTM, based on an appropriate set of experimental data such as uniaxial tensile tests, monotonic and Bauschinger simple shear tests and orthogonal strain path tests, all at various orientations with respect to the rolling direction. All the simulations were carried out with the CEMUC's home code DD3IMP (contraction of `Deep Drawing 3-D IMPlicit code').

  10. Predictive Blood Chemistry Parameters for Pansteatitis-Affected Mozambique Tilapia (Oreochromis mossambicus).

    Science.gov (United States)

    Bowden, John A; Cantu, Theresa M; Chapman, Robert W; Somerville, Stephen E; Guillette, Matthew P; Botha, Hannes; Hoffman, Andre; Luus-Powell, Wilmien J; Smit, Willem J; Lebepe, Jeffrey; Myburgh, Jan; Govender, Danny; Tucker, Jonathan; Boggs, Ashley S P; Guillette, Louis J

    2016-01-01

    One of the largest river systems in South Africa, the Olifants River, has experienced significant changes in water quality due to anthropogenic activities. Since 2005, there have been various "outbreaks" of the inflammatory disease pansteatitis in several vertebrate species. Large-scale pansteatitis-related mortality events have decimated the crocodile population at Lake Loskop and decreased the population at Kruger National Park. Most pansteatitis-related diagnoses within the region are conducted post-mortem by either gross pathology or histology. The application of a non-lethal approach to assess the prevalence and pervasiveness of pansteatitis in the Olifants River region would be of great importance for the development of a management plan for this disease. In this study, several plasma-based biomarkers accurately classified pansteatitis in Mozambique tilapia (Oreochromis mossambicus) collected from Lake Loskop using a commercially available benchtop blood chemistry analyzer combined with data interpretation via artificial neural network analysis. According to the model, four blood chemistry parameters (calcium, sodium, total protein and albumin), in combination with total length, diagnose pansteatitis to a predictive accuracy of 92 percent. In addition, several morphometric traits (total length, age, weight) were also associated with pansteatitis. On-going research will focus on further evaluating the use of blood chemistry to classify pansteatitis across different species, trophic levels, and within different sites along the Olifants River. PMID:27115488

  11. The importance of the preoperative clinical parameters and the intraoperative electrophysiological monitoring in brachial plexus surgery

    Directory of Open Access Journals (Sweden)

    Leandro Pretto Flores

    2011-08-01

    Full Text Available OBJECTIVE: The study aims to demonstrate the impact of some preoperative clinical parameters on the functional outcome of patients sustaining brachial plexus injuries, and to trace some commentaries about the use of intraoperative monitoring techniques. METHOD: A retrospective study one hundred cases of brachial plexus surgery. The analysis regarding postoperative outcomes was performed by comparing the average of the final result of the surgery for each studied cohort. RESULTS: Direct electrical stimulation was used in all patients, EMG in 59%, SEPs in 37% and evoked NAPs in 19% of the cases. Patients in whom the motor function of the hand was totally or partially preserved before surgery, and those in whom surgery was delayed less than 6 months demonstrated significant (p<0.05 better outcomes. CONCLUSION: The preoperative parameters associated to favorable outcomes in reconstruction of the brachial plexus are a good post-traumatic status of the hand and a short interval between injury and surgery.

  12. Influence of Clinical and Pathologic Parameters on Prognosis of Cervical Carcinoma in China

    Institute of Scientific and Technical Information of China (English)

    LUPing; LIANGQiudong; ZHENGQuanqing

    2003-01-01

    Objective: To explore the influence of clinical and pathologic parameters on the prognosis of squamous cell carcinoma and adenocarcinoma. Methods: 702 cases of cervical carcinoma were retrospec-tively studied. Cox regression model was informed in multi-variable analysis. Results: The retrospective analysis showed that 630 out of 702 cases of cervical carcinoma were squamous cell carcinoma, cumulative rate 89.4% and 72 case were adenocarcinoma, cumulative rate 10.6% respectively. The 5-year survival rate was lower for patients with adenocarcinoma than for patients with squamous cell carcinoma (58.3% vs 57.3%), but there was no significant difference. Cox regression model showed that the variable into equation for squamous cell carcinoma included tumor grade of differentiation, lymph node metastasis and FIGO stage, but only lymph node metastasis and FIGO stage for adenocarcinoma. Conclusion: FIGO stage and lymph node metastasis was independent parameter evaluating prognosis of cervical carcinoma.

  13. Evaluation of clinical parameters and lesions in pig organs during post-weaning period

    OpenAIRE

    Mejía Medina, Julián; Rincón Ruiz, Juan; Gutiérrez Vergara, Cristian; Correa Londoño, Guillermo; López Herrera, Albeiro; Parra Suescún, Jaime

    2012-01-01

    To evaluate the effect of early weaning on clinical parameters, development and occurrence of lesions in organs of systemic importance, and weight gain in pigs evaluations were carried out. The experiment was conducted in the San Pablo Production Research Center of the Universidad Nacional de Colombia (Medellín). We used 16 weaned pigs at 21 days of age. The animals were fed for 10 days with a basal diet (milk). Four pigs were slaughtered on days 1, 5, 7 and 10 post-weaning and samples of int...

  14. Human intoxication with paralytic shellfish toxins: clinical parameters and toxin analysis in plasma and urine.

    Science.gov (United States)

    García, Carlos; Lagos, Marcelo; Truan, Dominique; Lattes, Karinna; Véjar, Omar; Chamorro, Beatriz; Iglesias, Verónica; Andrinolo, Darío; Lagos, Néstor

    2005-01-01

    This study reports the data recorded from four patients intoxicated with shellfish during the summer 2002, after consuming ribbed mussels (Aulacomya ater) with paralytic shellfish toxin contents of 8,066 +/- 61.37 microg/100 gr of tissue. Data associated with clinical variables and paralytic shellfish toxins analysis in plasma and urine of the intoxicated patients are shown. For this purpose, the evolution of respiratory frequency, arterial blood pressure and heart rate of the poisoned patients were followed and recorded. The clinical treatment to reach a clinically stable condition and return to normal physiological parameters was a combination of hydration with saline solution supplemented with Dobutamine (vasoactive drug), Furosemide (diuretic) and Ranitidine (inhibitor of acid secretion). The physiological condition of patients began to improve after four hours of clinical treatment, and a stable condition was reached between 12 to 24 hours. The HPLC-FLD analysis showed only the GTX3/GTX2 epimers in the blood and urine samples. Also, these epimers were the only paralytic shellfish toxins found in the shellfish extract sample. PMID:16238098

  15. Association between magnesium-deficient status and anthropometric and clinical-nutritional parameters in posmenopausal women

    Directory of Open Access Journals (Sweden)

    Beatriz López-González

    2014-03-01

    Full Text Available Background: During menopause occurs weight gain and bone loss occurs due to the hormone decline during this period and other factors such as nutrition. Magnesium deficiency suggests a risk factor for obesity and osteoporosis. Objective: To evaluate the clinical and nutritional magnesium status in a population of postmenopausal women, assessing intake and serum levels of magnesium in the study population and correlation with anthropometric parameters such as body mass index (BMI and body fat, and biochemical parameters associated. Subjects and Method: The study involved 78 healthy women aged 44-76, with postmenopausal status, from the province of Grenade, Spain. The sample was divided into two age groups: group 1, aged 58. Anthropometric parameters were recorded and nutritional intake was assessed by 72-hour recall, getting the RDAs through Nutriber® program. To assess the biochemical parameters was performed a blood sample was taken. Magnesium was analyzed by flame atomic absorption spectrophotometry (FAAS in erythrocyte and plasma wet-mineralized samples. Results: Our results show that 37.85% of the total subjects have an overweight status. Magnesium intake found in our population is insufficient in 36% of women, while plasma magnesium deficiency corresponds to 23% of the population and 72% of women have deficient levels of magnesium in erythrocyte. Positive correlations were found between magnesium intake and dietary intake of calcium, of phosphorus, and with prealbumin plasma levels, as well as with a lower waist / hip ratio. Magnesium levels in erythrocyte were correlated with lower triglycerides and urea values. Conclusion: It is important to control and monitor the nutritional status of magnesium in postmenopausal -women to prevent nutritional alterations and possible clinical and chronic degenerative diseases associated with magnesium deficiency and with menopause.

  16. How electrodiagnosis predicts clinical outcome of focal peripheral nerve lesions.

    Science.gov (United States)

    Robinson, Lawrence R

    2015-09-01

    This article reviews the electrodiagnostic (EDX) prognostic factors for focal traumatic and nontraumatic peripheral nerve injuries. Referring physicians and patients often benefit from general and nerve-specific prognostic information from the EDX consultant. Knowing the probable outcome from a nerve injury allows the referring physician to choose the best treatment options for his/her patients. Nerve injuries are variable in their mechanism, location, and pathophysiology. The general effects of the injuries on nerve and muscle are well known, but more research is needed for nerve-specific information. Several factors currently known to influence prognosis include: nature of the nerve trauma, amount of axon loss, recruitment in muscles supplied by the nerve, the extent of demyelination, and the distance to reinnervate functional muscles. This article reviews these general concepts and also nerve-specific EDX measures that predict outcome after focal neuropathies.

  17. Prognostic and Predictive Biomarkers in Colorectal Cancer. From the Preclinical Setting to Clinical Practice.

    Science.gov (United States)

    Maurel, Joan; Postigo, Antonio

    2015-01-01

    Colorectal cancer (CRC) is the second largest cause of cancer mortality in Western countries, mostly due to metastasis. Understanding the natural history and prognostic factors in patients with metastatic CRC (mCRC) is essential for the optimal design of clinical trials. The main prognostic factors currently used in clinical practice are related to tumor behavior (e.g., white blood counts, levels of lactate dehydrogenase, levels of alkaline phosphatase) disease extension (e.g., presence of extrahepatic spread, number of organs affected) and general functional status (e.g., performance status as defined by the Eastern Cooperative Oncology Group). However, these parameters are not always sufficient to establish appropriate therapeutic strategies. First-line therapy in mCRC combines conventional chemotherapy (CHT) (e.g., FOLFOX, FOLFIRI, CAPOX) with a number of agents targeted to specific signaling pathways (TA) (e.g., panitumumab and cetuximab for cases KRAS/NRAS WT, and bevacizumab). Although the response rate to this combination regime exceeds 50%, progression of the disease is almost universal and only less than 10% of patients are free of disease at 2 years. Current clinical trials with second and third line therapy include new TA, such as tyrosin-kinase receptors inhibitors (MET, HER2, IGF-1R), inhibitors of BRAF, MEK, PI3K, AKT, mTORC, NOTCH and JAK1/JAK2, immunotherapy modulators and check point inhibitors (anti-PD-L1 and anti- PD1). Despite the identification of multiple prognostic and predictive biomarkers and signatures, it is still unclear how expression of many of these biomarkers is modulated by CHT and/or TA, thus potentially affecting response to treatment. In this review we analyzed how certain biomarkers in tumor cells and microenvironment influence the response to new TA and immune-therapies strategies in mCRC pre-treated patients. PMID:26452385

  18. Testing life history predictions in a long-lived seabird: a population matrix approach with improved parameter estimation

    Science.gov (United States)

    Doherty, P.F., Jr.; Schreiber, E.A.; Nichols, J.D.; Hines, J.E.; Link, W.A.; Schenk, G.A.; Schreiber, R.W.

    2004-01-01

    Life history theory and associated empirical generalizations predict that population growth rate (lambda) in long-lived animals should be most sensitive to adult survival; the rates to which lambda is most sensitive should be those with the smallest temporal variances; and stochastic environmental events should most affect the rates to which lambda is least sensitive. To date, most analyses attempting to examine these predictions have been inadequate, their validity being called into question by problems in estimating parameters, problems in estimating the variability of parameters, and problems in measuring population sensitivities to parameters. We use improved methodologies in these three areas and test these life-history predictions in a population of red-tailed tropicbirds (Phaethon rubricauda). We support our first prediction that lambda is most sensitive to survival rates. However the support for the second prediction that these rates have the smallest temporal variance was equivocal. Previous support for the second prediction may be an artifact of a high survival estimate near the upper boundary of 1 and not a result of natural selection canalizing variances alone. We did not support our third prediction that effects of environmental stochasticity (El Ni?o) would most likely be detected in vital rates to which lambda was least sensitive and which are thought to have high temporal variances. Comparative data-sets on other seabirds, within and among orders, and in other locations, are needed to understand these environmental effects.

  19. Predicting the activity coefficients of free-solvent for concentrated globular protein solutions using independently determined physical parameters.

    Directory of Open Access Journals (Sweden)

    Devin W McBride

    Full Text Available The activity coefficient is largely considered an empirical parameter that was traditionally introduced to correct the non-ideality observed in thermodynamic systems such as osmotic pressure. Here, the activity coefficient of free-solvent is related to physically realistic parameters and a mathematical expression is developed to directly predict the activity coefficients of free-solvent, for aqueous protein solutions up to near-saturation concentrations. The model is based on the free-solvent model, which has previously been shown to provide excellent prediction of the osmotic pressure of concentrated and crowded globular proteins in aqueous solutions up to near-saturation concentrations. Thus, this model uses only the independently determined, physically realizable quantities: mole fraction, solvent accessible surface area, and ion binding, in its prediction. Predictions are presented for the activity coefficients of free-solvent for near-saturated protein solutions containing either bovine serum albumin or hemoglobin. As a verification step, the predictability of the model for the activity coefficient of sucrose solutions was evaluated. The predicted activity coefficients of free-solvent are compared to the calculated activity coefficients of free-solvent based on osmotic pressure data. It is observed that the predicted activity coefficients are increasingly dependent on the solute-solvent parameters as the protein concentration increases to near-saturation concentrations.

  20. Predicting the activity coefficients of free-solvent for concentrated globular protein solutions using independently determined physical parameters.

    Science.gov (United States)

    McBride, Devin W; Rodgers, Victor G J

    2013-01-01

    The activity coefficient is largely considered an empirical parameter that was traditionally introduced to correct the non-ideality observed in thermodynamic systems such as osmotic pressure. Here, the activity coefficient of free-solvent is related to physically realistic parameters and a mathematical expression is developed to directly predict the activity coefficients of free-solvent, for aqueous protein solutions up to near-saturation concentrations. The model is based on the free-solvent model, which has previously been shown to provide excellent prediction of the osmotic pressure of concentrated and crowded globular proteins in aqueous solutions up to near-saturation concentrations. Thus, this model uses only the independently determined, physically realizable quantities: mole fraction, solvent accessible surface area, and ion binding, in its prediction. Predictions are presented for the activity coefficients of free-solvent for near-saturated protein solutions containing either bovine serum albumin or hemoglobin. As a verification step, the predictability of the model for the activity coefficient of sucrose solutions was evaluated. The predicted activity coefficients of free-solvent are compared to the calculated activity coefficients of free-solvent based on osmotic pressure data. It is observed that the predicted activity coefficients are increasingly dependent on the solute-solvent parameters as the protein concentration increases to near-saturation concentrations.

  1. Should I Pack My Umbrella? Clinical versus Statistical Prediction of Mental Health Decisions

    Science.gov (United States)

    Aegisdottir, Stefania; Spengler, Paul M.; White, Michael J.

    2006-01-01

    In this rejoinder, the authors respond to the insightful commentary of Strohmer and Arm, Chwalisz, and Hilton, Harris, and Rice about the meta-analysis on statistical versus clinical prediction techniques for mental health judgments. The authors address issues including the availability of statistical prediction techniques for real-life psychology…

  2. Parameter definition using vibration prediction software leads to significant drilling performance improvements

    Energy Technology Data Exchange (ETDEWEB)

    Amorim, Dalmo; Hanley, Chris Hanley; Fonseca, Isaac; Santos, Juliana [National Oilwell Varco, Houston TX (United States); Leite, Daltro J.; Borella, Augusto; Gozzi, Danilo [Petroleo Brasileiro S.A. (PETROBRAS), Rio de Janeiro, RJ (Brazil)

    2012-07-01

    field monitoring. Vibration prediction diminishes the importance of trial-and-error procedures such as drill-off tests, which are valid only for short sections. It also solves an existing lapse in Mechanical Specific Energy (MSE) real-time drilling control programs applying the theory of Teale, which states that a drilling system is perfectly efficient when it spends the exact energy to overcome the in situ rock strength. Using the proprietary software tool this paper will examine the resonant vibration modes that may be initiated while drilling with different BHA's and drill string designs, showing that the combination of a proper BHA design along with the correct selection of input parameters results in an overall improvement to drilling efficiency. Also, being the BHA predictively analyzed, it will be reduced the potential for vibration or stress fatigue in the drill string components, leading to a safer operation. In the recent years there has been an increased focus on vibration detection, analysis, and mitigation techniques, where new technologies, like the Drilling Dynamics Data Recorders (DDDR), may provide the capability to capture high frequency dynamics data at multiple points along the drilling system. These tools allow the achievement of drilling performance improvements not possible before, opening a whole new array of opportunities for optimization and for verification of predictions calculated by the drill string dynamics modeling software tool. The results of this study will identify how the dynamics from the drilling system, interacting with formation, directly relate to inefficiencies and to the possible solutions to mitigate drilling vibrations in order to improve drilling performance. Software vibration prediction and downhole measurements can be used for non-drilling operations like drilling out casing or reaming, where extremely high vibration levels - devastating to the cutting structure of the bit before it has even touched bottom - have

  3. Critical appraisal of clinical prediction rules that aim to optimize treatment selection for musculoskeletal conditions

    NARCIS (Netherlands)

    T.R. Stanton (Tasha); M.J. Hancock (Mark J.); C. Maher (Chris); B.W. Koes (Bart)

    2010-01-01

    textabstractBackground. Clinical prediction rules (CPRs) for treatment selection in musculoskeletal conditions have become increasingly popular. Purpose. The purposes of this review are: (1) to critically appraise studies evaluating CPRs and (2) to consider the clinical utility and stage of developm

  4. Clinical significance of sleep bruxism on several occlusal and functional parameters.

    Science.gov (United States)

    Ommerborn, Michelle A; Giraki, Maria; Schneider, Christine; Fuck, Lars Michael; Zimmer, Stefan; Franz, Matthias; Raab, Wolfgang Hans-michael; Schaefer, Ralf

    2010-10-01

    The aim of this study was to evaluate the association between various functional and occlusal parameters and sleep bruxism. Thirty-nine (39) sleep bruxism patients and 30 controls participated in this investigation. The assessment of sleep bruxism was performed using the Bruxcore Bruxism-Monitoring Device (BBMD) combined with a new computer-based analyzing method. Sixteen functional and/or occlusal parameters were recorded. With a mean slide of 0.95 mm in the sleep bruxism group and a mean slide of 0.42 mm in the control group (Mann Whitney U test; p<0.003), results solely demonstrated a significant group difference regarding the length of a slide from centric occlusion to maximum intercuspation. The results suggest that the slightly pronounced slide could be of clinical importance in the development of increased wear facets in patients with current sleep bruxism activity. Following further evaluation including polysomnographic recordings, the BBMD combined with this new analyzing technique seems to be a clinically feasible instrument that allows the practitioner to quantify abrasion over a short period. PMID:21032978

  5. Use of clinical movement screening tests to predict injury in sport

    OpenAIRE

    Chimera, Nicole J.; Warren, Meghan

    2016-01-01

    Clinical movement screening tests are gaining popularity as a means to determine injury risk and to implement training programs to prevent sport injury. While these screens are being used readily in the clinical field, it is only recently that some of these have started to gain attention from a research perspective. This limits applicability and poses questions to the validity, and in some cases the reliability, of the clinical movement tests as they relate to injury prediction, intervention,...

  6. Predicting pressure ulcers: cases missed using a new clinical prediction rule.

    NARCIS (Netherlands)

    Schoonhoven, L.; Grobbee, D.E.; Bousema, M.T.; Buskens, E.

    2005-01-01

    AIM: The aim of this paper is to report a study describing patients with pressure ulcers that were incorrectly classified as 'not at risk' by the prediction rule and comparing them with patients who were correctly classified as 'not at risk'. BACKGROUND: Patients admitted to hospital are at risk of

  7. Combining Physical and Biologic Parameters to Predict Radiation-Induced Lung Toxicity in Patients With Non-Small-Cell Lung Cancer Treated With Definitive Radiation Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Stenmark, Matthew H. [Department of Radiation Oncology, University of Michigan Medical Center, Ann Arbor, Michigan (United States); Cai Xuwei [Department of Radiation Oncology, University of Michigan Medical Center, Ann Arbor, Michigan (United States); Radiation Oncology, Shanghai Cancer Hospital, Fudan University, Shanghai (China); Shedden, Kerby [Department of Biostatistics, University of Michigan Medical Center, Ann Arbor, Michigan (United States); Hayman, James A. [Department of Radiation Oncology, University of Michigan Medical Center, Ann Arbor, Michigan (United States); Yuan Shuanghu [Department of Radiation Oncology, University of Michigan Medical Center, Ann Arbor, Michigan (United States); Radiation Oncology, Shangdong Cancer Hospital, Jinan (China); Ritter, Timothy [Veterans Affairs Medical Center, Ann Arbor, Michigan (United States); Ten Haken, Randall K.; Lawrence, Theodore S. [Department of Radiation Oncology, University of Michigan Medical Center, Ann Arbor, Michigan (United States); Kong Fengming, E-mail: fengkong@med.umich.edu [Department of Radiation Oncology, University of Michigan Medical Center, Ann Arbor, Michigan (United States); Veterans Affairs Medical Center, Ann Arbor, Michigan (United States)

    2012-10-01

    Purpose: To investigate the plasma dynamics of 5 proinflammatory/fibrogenic cytokines, including interleukin-1beta (IL-1{beta}), IL-6, IL-8, tumor necrosis factor alpha (TNF-{alpha}), and transforming growth factor beta1 (TGF-{beta}1) to ascertain their value in predicting radiation-induced lung toxicity (RILT), both individually and in combination with physical dosimetric parameters. Methods and Materials: Treatments of patients receiving definitive conventionally fractionated radiation therapy (RT) on clinical trial for inoperable stages I-III lung cancer were prospectively evaluated. Circulating cytokine levels were measured prior to and at weeks 2 and 4 during RT. The primary endpoint was symptomatic RILT, defined as grade 2 and higher radiation pneumonitis or symptomatic pulmonary fibrosis. Minimum follow-up was 18 months. Results: Of 58 eligible patients, 10 (17.2%) patients developed RILT. Lower pretreatment IL-8 levels were significantly correlated with development of RILT, while radiation-induced elevations of TGF-ss1 were weakly correlated with RILT. Significant correlations were not found for any of the remaining 3 cytokines or for any clinical or dosimetric parameters. Using receiver operator characteristic curves for predictive risk assessment modeling, we found both individual cytokines and dosimetric parameters were poor independent predictors of RILT. However, combining IL-8, TGF-ss1, and mean lung dose into a single model yielded an improved predictive ability (P<.001) compared to either variable alone. Conclusions: Combining inflammatory cytokines with physical dosimetric factors may provide a more accurate model for RILT prediction. Future study with a larger number of cases and events is needed to validate such findings.

  8. Dosemetric Parameters Predictive of Rib Fractures after Proton Beam Therapy for Early-Stage Lung Cancer.

    Science.gov (United States)

    Ishikawa, Yojiro; Nakamura, Tatsuya; Kato, Takahiro; Kadoya, Noriyuki; Suzuki, Motohisa; Azami, Yusuke; Hareyama, Masato; Kikuchi, Yasuhiro; Jingu, Keiichi

    2016-01-01

    Proton beam therapy (PBT) is the preferred modality for early-stage lung cancer. Compared with X-ray therapy, PBT offers good dose concentration as revealed by the characteristics of the Bragg peak. Rib fractures (RFs) after PBT lead to decreased quality of life for patients. However, the incidence of and the risk factors for RFs after PBT have not yet been clarified. We therefore explored the relationship between irradiated rib volume and RFs after PBT for early-stage lung cancer. The purpose of this study was to investigate the incidence and the risk factors for RFs following PBT for early-stage lung cancer. We investigated 52 early-stage lung cancer patients and analyzed a total of 215 irradiated ribs after PBT. Grade 2 RFs occurred in 12 patients (20 ribs); these RFs were symptomatic without displacement. No patient experienced more severe RFs. The median time to grade 2 RFs development was 17 months (range: 9-29 months). The three-year incidence of grade 2 RFs was 30.2%. According to the analysis comparing radiation dose and rib volume using receiver operating characteristic curves, we demonstrated that the volume of ribs receiving more than 120 Gy3 (relative biological effectiveness (RBE)) was more than 3.7 cm(3) at an area under the curve of 0.81, which increased the incidence of RFs after PBT (P < 0.001). In this study, RFs were frequently observed following PBT for early-stage lung cancer. We demonstrated that the volume of ribs receiving more than 120 Gy3 (RBE) was the most significant parameter for predicting RFs. PMID:27087118

  9. Debris-flows scale predictions based on basin spatial parameters calculated from Remote Sensing images in Wenchuan earthquake area

    International Nuclear Information System (INIS)

    Debris flow is a common hazard in the Wenchuan earthquake area. Collapse and Landslide Regions (CLR), caused by earthquakes, could be located from Remote Sensing images. CLR are the direct material source regions for debris flow. The Spatial Distribution of Collapse and Landslide Regions (SDCLR) strongly impact debris-flow formation. In order to depict SDCLR, we referred to Strahler's Hypsometric analysis method and developed 3 functional models to depict SDCLR quantitatively. These models mainly depict SDCLR relative to altitude, basin mouth and main gullies of debris flow. We used the integral of functions as the spatial parameters of SDCLR and these parameters were employed during the process of debris-flows scale predictions. Grouping-occurring debris-flows triggered by the rainstorm, which occurred on September 24th 2008 in Beichuan County, Sichuan province China, were selected to build the empirical equations for debris-flows scale predictions. Given the existing data, only debris-flows runout zone parameters (Max. runout distance L and Lateral width B) were estimated in this paper. The results indicate that the predicted results were more accurate when the spatial parameters were used. Accordingly, we suggest spatial parameters of SDCLR should be considered in the process of debris-flows scale prediction and proposed several strategies to prevent debris flow in the future

  10. QSAR Studies of Copper Azamacrocycles and Thiosemicarbazones: MM3 Parameter Development and Prediction of Biological Properties

    OpenAIRE

    Wolohan, Peter; Yoo, Jeongsoo; Welch, Michael J.; Reichert, David E.

    2005-01-01

    Genetic algorithms (GA) were used to develop specific copper metal-ligand force field parameters for the MM3 force field, from a combination of crystallographic structures and ab initio calculations. These new parameters produced results in good agreement with experiment and previously reported copper metal-ligand parameters for the AMBER force field. The MM3 parameters were then used to develop several Quantitative Structure Activity Relationship (QSAR) models. A successful QSAR for predicti...

  11. Predicting the Activity Coefficients of Free-Solvent for Concentrated Globular Protein Solutions Using Independently Determined Physical Parameters

    OpenAIRE

    McBride, Devin W; Rodgers, Victor G. J.

    2013-01-01

    The activity coefficient is largely considered an empirical parameter that was traditionally introduced to correct the non-ideality observed in thermodynamic systems such as osmotic pressure. Here, the activity coefficient of free-solvent is related to physically realistic parameters and a mathematical expression is developed to directly predict the activity coefficients of free-solvent, for aqueous protein solutions up to near-saturation concentrations. The model is based on the free-solvent...

  12. Prognosis after Acute Myocardial Infarction as Predicted by C-reactive Protein and Clinical Variables

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    Angelo Modica MD, PhD

    2013-02-01

    Full Text Available Background:Raised concentrations of C-reactive protein (CRP have been reported to be strongly related to an adverse long term prognosis in patients with acute myocardial infarction (AMI. However, adjustments for clinical variables as well as interaction between variables have been incomplete. The aims of this study were to examine the predictive value of baseline concentrations of CRP for mortality after adjustment for important clinical variables and to compare the clinical usefulness of CRP with easily available clinical variables in the prediction of long term survival.Methods:Five hundred and thirty-one patients with AMI were included. A blood sample for CRP was obtained on admission. All patients were followed for a minimum of two years and death of any cause was recorded as the study end point.Results:In logistic regression analysis, the interaction term Age by Killip class > 1, the variable glomerular filtration rate as well as the interaction term Age by Atrial fibrillation were retained. The resulting model correctly predicted death or not in 81% of the patients. CRP did not contribute to the final model.Conclusions:CRP does not independently predict long-term mortality after an AMI after adjustments for clinical variables and interaction. CRP has no value beyond clinical variables in predicting death after AMI.

  13. A novel method for the measurement of linear body segment parameters during clinical gait analysis.

    Science.gov (United States)

    Geil, Mark D

    2013-09-01

    Clinical gait analysis is a valuable tool for the understanding of motion disorders and treatment outcomes. Most standard models used in gait analysis rely on predefined sets of body segment parameters that must be measured on each individual. Traditionally, these parameters are measured using calipers and tape measures. The process can be time consuming and is prone to several sources of error. This investigation explored a novel method for rapid recording of linear body segment parameters using magnetic-field based digital calipers commonly used for a different purpose in prosthetics and orthotics. The digital method was found to be comparable to traditional in all linear measures and data capture was significantly faster with the digital method, with mean time savings for 10 measurements of 2.5 min. Digital calipers only record linear distances, and were less accurate when diameters were used to approximate limb circumferences. Experience in measuring BSPs is important, as an experienced measurer was significantly faster than a graduate student and showed less difference between methods. Comparing measurement of adults vs. children showed greater differences with adults, and some method-dependence. If the hardware is available, digital caliper measurement of linear BSPs is accurate and rapid.

  14. PREDICTING OUTCOME AND SEVERITY IN ACUTE ORGANOPHOSPHOROUS POISONING WITH CLINICAL SCORING AND SERUM CHOLINESTERASE LEVELS

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    Basavaraj R

    2014-11-01

    Full Text Available BACKGROUND AND OBJECTIVES: Organophosphorus compound poisoning is the most common medico toxic emergency in India the increase in pesticide use in agriculture has paralleled the increase in the use of these products for deliberate self-warm. Respiratory failure is the most common complication of OP poisoning leading to death. Early recognition and prompt ventilator support may improve survival. Owing to limited availability of resources, all OP poisoning patients are not managed in ICUs in Indian setup. It is therefore important that clinical features and criteria to predict the need for ventilator support be identified at initial examination. Hence this study was undertaken to assess the severity of organophosphorus compound poisoning both clinically by using Peradeniya scoring and by estimating serum choline esterase levels. METHODS: Cross sectional study was done at basaveswar teaching and general hospital attached to MR Medical College. Cases with history of exposure to organophosphorus compound within previous 24 hours were chosen after applying inclusion and exclusion criteria. Patients were evaluated for Peradeniya OP poisoning scale and serum cholinesterase levels for assessment of severity of poisoning. Serum cholinesterase levels and Peradeniya OP poisoning scale were studied to predict the need for ventilator support. The results were analyzed using Chi-square test. STATISTICAL ANALYSIS: It was done using pearson’s chi square test. RESULTS: In this study requirement of ventilator support was seen in 36% of patients. Mortality in our study was 18%. Only 15.6% of patients with mild grade of poisoning according to Peradeniya OP poisoning scale required ventilator support, whereas 84.4% did not require ventilator support. Most of patients with moderate (70.6% and severe poisoning (100% according to Peradeniya OP poisoning scale required ventilator support. 93.7% of patients with serum cholinesterase levels more than 50% did not require

  15. Evaluation of Clinical and Ultrasonographic Parameters in Psoriatic Arthritis Patients Treated with Adalimumab: A Retrospective Study

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    M. Teoli

    2012-01-01

    Full Text Available Objectives. The aim of this study was to evaluate clinical and US-PD parameters in PsA during adalimumab treatment. Methods. A retrospective study has been conducted in forty patients affected by moderate-to-severe peripheral PsA. Clinical, laboratory, and US-PD evaluations were performed at baseline, after 4, 12, and 24 weeks of treatment. They included erythrocyte sedimentation rate (ESR, C-reactive protein (CRP, visual analogue scale (VAS, Health Assessment Questionnaire (HAQ modified for Spondyloarthritis, Psoriasis Area Severity Index (PASI score, the 28-joint Disease Activity Score (DAS 28, and US-PD assessment. US-PD findings were scored according to a semiquantitative scale (ranging 0–3 for synovial proliferation (SP, joint effusion (SE, bone erosions (BE, and PD. Results. Data obtained for clinical, laboratory findings and US-PD evaluation showed statistical significant improvement in all the measures performed except for BE. A significant parallel decrease in SE, SP, and PD values were demonstrated. Conclusion. This study demonstrated that US-PD is a valid technique in monitoring the response to adalimumab in moderate-to-severe PsA.

  16. On the Effect of Unit-Cell Parameters in Predicting the Elastic Response of Wood-Plastic Composites

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    Fatemeh Alavi

    2013-01-01

    Full Text Available This paper presents a study on the effect of unit-cell geometrical parameters in predicting elastic properties of a typical wood plastic composite (WPC. The ultimate goal was obtaining the optimal values of representative volume element (RVE parameters to accurately predict the mechanical behavior of the WPC. For each unit cell, defined by a given combination of the above geometrical parameters, finite element simulation in ABAQUS was carried out, and the corresponding stress-strain curve was obtained. A uniaxial test according to ASTM D638-02a type V was performed on the composite specimen. Modulus of elasticity was determined using hyperbolic tangent function, and the results were compared to the sets of finite element analyses. Main effects of RVE parameters and their interactions were demonstrated and discussed, specially regarding the inclusion of two adjacent wood particles within one unit cell of the material. Regression analysis was performed to mathematically model the RVE parameter effects and their interactions over the modulus of elasticity response. The model was finally employed in an optimization analysis to arrive at an optimal set of RVE parameters that minimizes the difference between the predicted and experimental moduli of elasticity.

  17. Clinical and MRI models predicting amyloid deposition in progressive aphasia and apraxia of speech

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    Jennifer L. Whitwell

    2016-01-01

    Full Text Available Beta-amyloid (Aβ deposition can be observed in primary progressive aphasia (PPA and progressive apraxia of speech (PAOS. While it is typically associated with logopenic PPA, there are exceptions that make predicting Aβ status challenging based on clinical diagnosis alone. We aimed to determine whether MRI regional volumes or clinical data could help predict Aβ deposition. One hundred and thirty-nine PPA (n = 97; 15 agrammatic, 53 logopenic, 13 semantic and 16 unclassified and PAOS (n = 42 subjects were prospectively recruited into a cross-sectional study and underwent speech/language assessments, 3.0 T MRI and C11-Pittsburgh Compound B PET. The presence of Aβ was determined using a 1.5 SUVR cut-point. Atlas-based parcellation was used to calculate gray matter volumes of 42 regions-of-interest across the brain. Penalized binary logistic regression was utilized to determine what combination of MRI regions, and what combination of speech and language tests, best predicts Aβ (+ status. The optimal MRI model and optimal clinical model both performed comparably in their ability to accurately classify subjects according to Aβ status. MRI accurately classified 81% of subjects using 14 regions. Small left superior temporal and inferior parietal volumes and large left Broca's area volumes were particularly predictive of Aβ (+ status. Clinical scores accurately classified 83% of subjects using 12 tests. Phonological errors and repetition deficits, and absence of agrammatism and motor speech deficits were particularly predictive of Aβ (+ status. In comparison, clinical diagnosis was able to accurately classify 89% of subjects. However, the MRI model performed well in predicting Aβ deposition in unclassified PPA. Clinical diagnosis provides optimum prediction of Aβ status at the group level, although regional MRI measurements and speech and language testing also performed well and could have advantages in predicting Aβ status in unclassified

  18. Clinical and MRI models predicting amyloid deposition in progressive aphasia and apraxia of speech.

    Science.gov (United States)

    Whitwell, Jennifer L; Weigand, Stephen D; Duffy, Joseph R; Strand, Edythe A; Machulda, Mary M; Senjem, Matthew L; Gunter, Jeffrey L; Lowe, Val J; Jack, Clifford R; Josephs, Keith A

    2016-01-01

    Beta-amyloid (Aβ) deposition can be observed in primary progressive aphasia (PPA) and progressive apraxia of speech (PAOS). While it is typically associated with logopenic PPA, there are exceptions that make predicting Aβ status challenging based on clinical diagnosis alone. We aimed to determine whether MRI regional volumes or clinical data could help predict Aβ deposition. One hundred and thirty-nine PPA (n = 97; 15 agrammatic, 53 logopenic, 13 semantic and 16 unclassified) and PAOS (n = 42) subjects were prospectively recruited into a cross-sectional study and underwent speech/language assessments, 3.0 T MRI and C11-Pittsburgh Compound B PET. The presence of Aβ was determined using a 1.5 SUVR cut-point. Atlas-based parcellation was used to calculate gray matter volumes of 42 regions-of-interest across the brain. Penalized binary logistic regression was utilized to determine what combination of MRI regions, and what combination of speech and language tests, best predicts Aβ (+) status. The optimal MRI model and optimal clinical model both performed comparably in their ability to accurately classify subjects according to Aβ status. MRI accurately classified 81% of subjects using 14 regions. Small left superior temporal and inferior parietal volumes and large left Broca's area volumes were particularly predictive of Aβ (+) status. Clinical scores accurately classified 83% of subjects using 12 tests. Phonological errors and repetition deficits, and absence of agrammatism and motor speech deficits were particularly predictive of Aβ (+) status. In comparison, clinical diagnosis was able to accurately classify 89% of subjects. However, the MRI model performed well in predicting Aβ deposition in unclassified PPA. Clinical diagnosis provides optimum prediction of Aβ status at the group level, although regional MRI measurements and speech and language testing also performed well and could have advantages in predicting Aβ status in unclassified PPA subjects

  19. Applying dynamic parameters to predict hemodynamic response to volume expansion in spontaneously breathing patients with septic shock.

    Science.gov (United States)

    Lanspa, Michael J; Grissom, Colin K; Hirshberg, Eliotte L; Jones, Jason P; Brown, Samuel M

    2013-02-01

    Volume expansion is a mainstay of therapy in septic shock, although its effect is difficult to predict using conventional measurements. Dynamic parameters, which vary with respiratory changes, appear to predict hemodynamic response to fluid challenge in mechanically ventilated, paralyzed patients. Whether they predict response in patients who are free from mechanical ventilation is unknown. We hypothesized that dynamic parameters would be predictive in patients not receiving mechanical ventilation. This is a prospective, observational, pilot study. Patients with early septic shock and who were not receiving mechanical ventilation received 10-mL/kg volume expansion (VE) at their treating physician's discretion after initial resuscitation in the emergency department. We used transthoracic echocardiography to measure vena cava collapsibility index and aortic velocity variation before VE. We used a pulse contour analysis device to measure stroke volume variation (SVV). Cardiac index was measured immediately before and after VE using transthoracic echocardiography. Hemodynamic response was defined as an increase in cardiac index 15% or greater. Fourteen patients received VE, five of whom demonstrated a hemodynamic response. Vena cava collapsibility index and SVV were predictive (area under the curve = 0.83, 0.92, respectively). Optimal thresholds were calculated: vena cava collapsibility index, 15% or greater (positive predictive value, 62%; negative predictive value, 100%; P = 0.03); SVV, 17% or greater (positive predictive value 100%, negative predictive value 82%, P = 0.03). Aortic velocity variation was not predictive. Vena cava collapsibility index and SVV predict hemodynamic response to fluid challenge patients with septic shock who are not mechanically ventilated. Optimal thresholds differ from those described in mechanically ventilated patients.

  20. Genomic Copy Number Variations in the Genomes of Leukocytes Predict Prostate Cancer Clinical Outcomes.

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    Yan P Yu

    Full Text Available Accurate prediction of prostate cancer clinical courses remains elusive. In this study, we performed whole genome copy number analysis on leukocytes of 273 prostate cancer patients using Affymetrix SNP6.0 chip. Copy number variations (CNV were found across all chromosomes of the human genome. An average of 152 CNV fragments per genome was identified in the leukocytes from prostate cancer patients. The size distributions of CNV in the genome of leukocytes were highly correlative with prostate cancer aggressiveness. A prostate cancer outcome prediction model was developed based on large size ratio of CNV from the leukocyte genomes. This prediction model generated an average prediction rate of 75.2%, with sensitivity of 77.3% and specificity of 69.0% for prostate cancer recurrence. When combined with Nomogram and the status of fusion transcripts, the average prediction rate was improved to 82.5% with sensitivity of 84.8% and specificity of 78.2%. In addition, the leukocyte prediction model was 62.6% accurate in predicting short prostate specific antigen doubling time. When combined with Gleason's grade, Nomogram and the status of fusion transcripts, the prediction model generated a correct prediction rate of 77.5% with 73.7% sensitivity and 80.1% specificity. To our knowledge, this is the first study showing that CNVs in leukocyte genomes are predictive of clinical outcomes of a human malignancy.

  1. Evaluation of the Cerebral State Index in Cats under Isoflurane Anaesthesia: Dose-Effect Relationship and Prediction of Clinical Signs

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    Joana R. Sousa

    2014-01-01

    Full Text Available The performance of the cerebral state index (CSI in reflecting different levels of isoflurane anaesthesia was evaluated in ten cats subjected to four end-tidal isoflurane concentrations (EtIso, each maintained for 15 minutes (0.8%, 1.2%, 1.6%, or 2.0% EtIso. The CSI, hemodynamic data, ocular reflexes, and eye position were recorded for each EtIso concentration. Pharmacodynamic analysis of CSI with EtIso was performed, as well as prediction probability analysis with a clinical scale based on the eye reflexes. The CSI values showed great variability. Between all parameters, burst suppression ratio showed the better fitting with the sigmoidal concentration-effect model (R2=0.93 followed by CSI (R2=0.82 and electromyographic activity (R2=0.79. EtIso was the variable with better prediction of the clinical scale of anaesthesia (prediction probability value of 0.94. Although the CSI values decrease with increasing isoflurane concentrations, the huge variability in CSI values may be a strong limitation for its use in cats and it seems to be no better than EtIso as a predictor of clinical signs.

  2. Correlation between olfactory dysfunction and various clinical parameters in patients with multiple sclerosis

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    Kostić Jelena

    2009-01-01

    Full Text Available Background/Aim. Multiple sclerosis (MS is a chronic inflammatory disease of the central nervous system (CNS characterized by myelin destruction and axon loss. Among various clinical manifestations of MS cognitive disorders are frequent. Olfactory disorders are also noticed but they are rarely considered in clinical practice. The aim of the present study was to examine frequency of olfactory dysfunction in patients with MS and its relationship to clinical parameters. Methods. Our study comprised 61 consecutive patients with definite MS who were hospitalized at the Department for Multiple Sclerosis and Other Immune- Mediated Disorders of CNS, Institute of Neurology, Clinical Center of Serbia, Belgrade, and 45 gender-, age- and education-matched healthy voluntaries. The Pocket Smell Test (PST was used for examination of olfactory function. Cognitive functions were analyzed using the tests from the Brief Battery of Neuropsychological Tests: Paced Auditory Serial Addition Test 3-minute Version (PASAT 3', Word List Generation (WLG and Symbol Digit Modalities Test (SDMT. Results. Olfactory dysfunction was found in 26 (43% MS patients and 5 (11% controls (p = 0.001. Statistically significant positive correlation was found only between PST score and WLG scores (r = 0.297, p = 0.030. In comparison with the previously published normative values, our subjects with MS had decrease in the mean indices of the PASAT 3' in 28%, SDMT in 51% and WLG in 90% of the subjects. Conclusion. Olfactory dysfunction is frequent in our population of patients with MS. This disturbance correlates with the impairment of cognitive functions in these patients.

  3. High-throughput screening using patient-derived tumor xenografts to predict clinical trial drug response.

    Science.gov (United States)

    Gao, Hui; Korn, Joshua M; Ferretti, Stéphane; Monahan, John E; Wang, Youzhen; Singh, Mallika; Zhang, Chao; Schnell, Christian; Yang, Guizhi; Zhang, Yun; Balbin, O Alejandro; Barbe, Stéphanie; Cai, Hongbo; Casey, Fergal; Chatterjee, Susmita; Chiang, Derek Y; Chuai, Shannon; Cogan, Shawn M; Collins, Scott D; Dammassa, Ernesta; Ebel, Nicolas; Embry, Millicent; Green, John; Kauffmann, Audrey; Kowal, Colleen; Leary, Rebecca J; Lehar, Joseph; Liang, Ying; Loo, Alice; Lorenzana, Edward; Robert McDonald, E; McLaughlin, Margaret E; Merkin, Jason; Meyer, Ronald; Naylor, Tara L; Patawaran, Montesa; Reddy, Anupama; Röelli, Claudia; Ruddy, David A; Salangsang, Fernando; Santacroce, Francesca; Singh, Angad P; Tang, Yan; Tinetto, Walter; Tobler, Sonja; Velazquez, Roberto; Venkatesan, Kavitha; Von Arx, Fabian; Wang, Hui Qin; Wang, Zongyao; Wiesmann, Marion; Wyss, Daniel; Xu, Fiona; Bitter, Hans; Atadja, Peter; Lees, Emma; Hofmann, Francesco; Li, En; Keen, Nicholas; Cozens, Robert; Jensen, Michael Rugaard; Pryer, Nancy K; Williams, Juliet A; Sellers, William R

    2015-11-01

    Profiling candidate therapeutics with limited cancer models during preclinical development hinders predictions of clinical efficacy and identifying factors that underlie heterogeneous patient responses for patient-selection strategies. We established ∼1,000 patient-derived tumor xenograft models (PDXs) with a diverse set of driver mutations. With these PDXs, we performed in vivo compound screens using a 1 × 1 × 1 experimental design (PDX clinical trial or PCT) to assess the population responses to 62 treatments across six indications. We demonstrate both the reproducibility and the clinical translatability of this approach by identifying associations between a genotype and drug response, and established mechanisms of resistance. In addition, our results suggest that PCTs may represent a more accurate approach than cell line models for assessing the clinical potential of some therapeutic modalities. We therefore propose that this experimental paradigm could potentially improve preclinical evaluation of treatment modalities and enhance our ability to predict clinical trial responses.

  4. Strategies for automatic online treatment plan reoptimization using clinical treatment planning system: A planning parameters study

    Energy Technology Data Exchange (ETDEWEB)

    Li, Taoran; Wu, Qiuwen; Zhang, You; Vergalasova, Irina; Lee, W. Robert; Yin, Fang-Fang; Wu, Q. Jackie [Duke Medical Physics Graduate Program, Duke University, Durham, North Carolina 27705 and Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27710 (United States)

    2013-11-15

    Purpose: Adaptive radiation therapy for prostate cancer using online reoptimization provides an improved control of interfractional anatomy variations. However, the clinical implementation of online reoptimization is currently limited by the low efficiency of current strategies and the difficulties associated with integration into the current treatment planning system. This study investigates the strategies for performing fast (∼2 min) automatic online reoptimization with a clinical fluence-map-based treatment planning system; and explores the performance with different input parameters settings: dose-volume histogram (DVH) objective settings, starting stage, and iteration number (in the context of real time planning).Methods: Simulated treatments of 10 patients were reoptimized daily for the first week of treatment (5 fractions) using 12 different combinations of optimization strategies. Options for objective settings included guideline-based RTOG objectives, patient-specific objectives based on anatomy on the planning CT, and daily-CBCT anatomy-based objectives adapted from planning CT objectives. Options for starting stages involved starting reoptimization with and without the original plan's fluence map. Options for iteration numbers were 50 and 100. The adapted plans were then analyzed by statistical modeling, and compared both in terms of dosimetry and delivery efficiency.Results: All online reoptimized plans were finished within ∼2 min with excellent coverage and conformity to the daily target. The three input parameters, i.e., DVH objectives, starting stage, and iteration number, contributed to the outcome of optimization nearly independently. Patient-specific objectives generally provided better OAR sparing compared to guideline-based objectives. The benefit in high-dose sparing from incorporating daily anatomy into objective settings was positively correlated with the relative change in OAR volumes from planning CT to daily CBCT. The use of the

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

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    Vernon J Lee

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

  6. Late gadolinium enhancement cardiovascular magnetic resonance predicts clinical worsening in patients with pulmonary hypertension

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    Freed Benjamin H

    2012-02-01

    Full Text Available Abstract Background Late gadolinium enhancement (LGE occurs at the right ventricular (RV insertion point (RVIP in patients with pulmonary hypertension (PH and has been shown to correlate with cardiovascular magnetic resonance (CMR derived RV indices. However, the prognostic role of RVIP-LGE and other CMR-derived parameters of RV function are not well established. Our aim was to evaluate the predictive value of contrast-enhanced CMR in patients with PH. Methods RV size, ejection fraction (RVEF, and the presence of RVIP-LGE were determined in 58 patients with PH referred for CMR. All patients underwent right heart catheterization, exercise testing, and N-terminal pro-brain natriuretic peptide (NT-proBNP evaluation; results of which were included in the final analysis if performed within 4 months of the CMR study. Patients were followed for the primary endpoint of time to clinical worsening (death, decompensated right ventricular heart failure, initiation of prostacyclin, or lung transplantation. Results Overall, 40/58 (69% of patients had RVIP-LGE. Patients with RVIP- LGE had larger right ventricular volume index, lower RVEF, and higher mean pulmonary artery pressure (mPAP, all p Conclusions The presence of RVIP-LGE in patients with PH is a marker for more advanced disease and poor prognosis. In addition, this study reveals for the first time that CMR-derived RVEF is an independent non-invasive imaging predictor of adverse outcomes in this patient population.

  7. Role of parameter errors in the spring predictability barrier for ENSO events in the Zebiak-Cane model

    Science.gov (United States)

    Yu, Liang; Mu, Mu; Yu, Yanshan

    2014-05-01

    The impact of both initial and parameter errors on the spring predictability barrier (SPB) is investigated using the Zebiak-Cane model (ZC model). Previous studies have shown that initial errors contribute more to the SPB than parameter errors in the ZC model. Although parameter errors themselves are less important, there is a possibility that nonlinear interactions can occur between the two types of errors, leading to larger prediction errors compared with those induced by initial errors alone. In this case, the impact of parameter errors cannot be overlooked. In the present paper, the optimal combination of these two types of errors [i.e., conditional nonlinear optimal perturbation (CNOP) errors] is calculated to investigate whether this optimal error combination may cause a more notable SPB phenomenon than that caused by initial errors alone. Using the CNOP approach, the CNOP errors and CNOP-I errors (optimal errors when only initial errors are considered) are calculated and then three aspects of error growth are compared: (1) the tendency of the seasonal error growth; (2) the prediction error of the sea surface temperature anomaly; and (3) the pattern of error growth. All three aspects show that the CNOP errors do not cause a more significant SPB than the CNOP-I errors. Therefore, this result suggests that we could improve the prediction of the El Niño during spring by simply focusing on reducing the initial errors in this model.

  8. An approach to predicting bowing control parameter contours in violin performance

    OpenAIRE

    Maestre E.; Ramirez R.

    2010-01-01

    We present a machine learning approach to modeling bowing control parameter contours in violin performance. Using accurate sensing techniques we obtain relevant timbre-related bowing control parameters such as bow transversal velocity, bow pressing force, and bow-bridge distance of each performed note. Each performed note is represented by a curve parameter vector and a number of note classes are defined. The principal components of the data represented by the set of curve p...

  9. A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients

    Institute of Scientific and Technical Information of China (English)

    Jin-You Wang; Yao Zhu; Chao-Fu Wang; Shi-Lin Zhang; Bo Dai; Ding-Wei Ye

    2014-01-01

    Although several models have been developed to predict the probability of Gleason sum upgrading between biopsy and radical prostatectomy specimens, most of these models are restricted to prostate-specific antigen screening-detected prostate cancer. This study aimed to build a nomogram for the prediction of Gleason sum upgrading in clinical y diagnosed prostate cancer. The study cohort comprised 269 Chinese prostate cancer patients who underwent prostate biopsy with a minimum of 10 cores and were subsequently treated with radical prostatectomy. Of al included patients, 220 (81.8%) were referred with clinical symptoms. The prostate-specific antigen level, primary and secondary biopsy Gleason scores, and clinical T category were used in a multivariate logistic regression model to predict the probability of Gleason sum upgrading. The developed nomogram was validated internally. Gleason sum upgrading was observed in 90 (33.5%) patients. Our nomogram showed a bootstrap-corrected concordance index of 0.789 and good calibration using 4 readily available variables. The nomogram also demonstrated satisfactory statistical performance for predicting significant upgrading. External validation of the nomogram published by Chun et al. in our cohort showed a marked discordance between the observed and predicted probabilities of Gleason sum upgrading. In summary, a new nomogram to predict Gleason sum upgrading in clinically diagnosed prostate cancer was developed, and it demonstrated good statistical performance upon internal validation.

  10. A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients

    Directory of Open Access Journals (Sweden)

    Jin-You Wang

    2014-05-01

    Full Text Available Although several models have been developed to predict the probability of Gleason sum upgrading between biopsy and radical prostatectomy specimens, most of these models are restricted to prostate-specific antigen screening-detected prostate cancer. This study aimed to build a nomogram for the prediction of Gleason sum upgrading in clinically diagnosed prostate cancer. The study cohort comprised 269 Chinese prostate cancer patients who underwent prostate biopsy with a minimum of 10 cores and were subsequently treated with radical prostatectomy. Of all included patients, 220 (81.8% were referred with clinical symptoms. The prostate-specific antigen level, primary and secondary biopsy Gleason scores, and clinical T category were used in a multivariate logistic regression model to predict the probability of Gleason sum upgrading. The developed nomogram was validated internally. Gleason sum upgrading was observed in 90 (33.5% patients. Our nomogram showed a bootstrap-corrected concordance index of 0.789 and good calibration using 4 readily available variables. The nomogram also demonstrated satisfactory statistical performance for predicting significant upgrading. External validation of the nomogram published by Chun et al. in our cohort showed a marked discordance between the observed and predicted probabilities of Gleason sum upgrading. In summary, a new nomogram to predict Gleason sum upgrading in clinically diagnosed prostate cancer was developed, and it demonstrated good statistical performance upon internal validation.

  11. Predictive capacity of risk assessment scales and clinical judgment for pressure ulcers: a meta-analysis.

    Science.gov (United States)

    García-Fernández, Francisco Pedro; Pancorbo-Hidalgo, Pedro L; Agreda, J Javier Soldevilla

    2014-01-01

    A systematic review with meta-analysis was completed to determine the capacity of risk assessment scales and nurses' clinical judgment to predict pressure ulcer (PU) development. Electronic databases were searched for prospective studies on the validity and predictive capacity of PUs risk assessment scales published between 1962 and 2010 in English, Spanish, Portuguese, Korean, German, and Greek. We excluded gray literature sources, integrative review articles, and retrospective or cross-sectional studies. The methodological quality of the studies was assessed according to the guidelines of the Critical Appraisal Skills Program. Predictive capacity was measured as relative risk (RR) with 95% confidence intervals. When 2 or more valid original studies were found, a meta-analysis was conducted using a random-effect model and sensitivity analysis. We identified 57 studies, including 31 that included a validation study. We also retrieved 4 studies that tested clinical judgment as a risk prediction factor. Meta-analysis produced the following pooled predictive capacity indicators: Braden (RR = 4.26); Norton (RR = 3.69); Waterlow (RR = 2.66); Cubbin-Jackson (RR = 8.63); EMINA (RR = 6.17); Pressure Sore Predictor Scale (RR = 21.4); and clinical judgment (RR = 1.89). Pooled analysis of 11 studies found adequate risk prediction capacity in various clinical settings; the Braden, Norton, EMINA (mEntal state, Mobility, Incontinence, Nutrition, Activity), Waterlow, and Cubbin-Jackson scales showed the highest predictive capacity. The clinical judgment of nurses was found to achieve inadequate predictive capacity when used alone, and should be used in combination with a validated scale.

  12. Predictive indices of empirical clinical diagnosis of malaria among under-five febrile children attending paediatric outpatient clinic

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    Hassan A Elechi

    2015-01-01

    Full Text Available Background: Malaria has remained an important public health problem in Nigeria with children under 5 years of age bearing the greatest burden. Accurate and prompt diagnosis of malaria is an important element in the fight against the scourge. Due to the several limitations of microscopy, diagnosis of malaria has continued to be made based on clinical ground against several World Health Organization (WHO recommendations. Thus, we aim to assess the performance of empirical clinical diagnosis among febrile children under 5 years of age in a busy pediatric outpatient clinic. Materials and Methods: The study was a cross-sectional study. Children aged <5 years with fever or 72 h history of fever were recruited. Children on antimalarial prophylaxis or on treatment for malaria were excluded. Relevant information was obtained from the caregiver and clinical note of the child using interviewer administered questionnaire. Two thick and two thin films were made, stained, and read for each recruited child. Data was analysed using SPSS version 16. Results: Of the 433 children studied, 98 (22.6% were empirically diagnosed as having malaria and antimalarial drug prescribed. Twenty-three (23.5% of these children were confirmed by microscopy to have malaria parasitemia, while 75 (76.5% were negative for malaria parasitemia. Empirical clinical diagnosis show poor predictive indices with sensitivity of 19.2%, specificity of 76.0%, positive predictive value of 23.5% and negative predictive value of 71%. Conclusion and Recommendations: Empirical clinical diagnosis of malaria among the under-five children with symptoms suggestive of acute malaria is highly not reliable and hence the need to strengthen parasitological diagnosis.

  13. Correlation between serum adiponectin and clinical characteristics, biochemical parameters in Indian women with polycystic ovary syndrome

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    Sunita J Ramanand

    2014-01-01

    Full Text Available Background: Polycystic ovary syndrome (PCOS is a common disorder. PCOS women are at a high risk for insulin resistance and metabolic syndrome (MS. Adiponectin is positively related to insulin sensitivity. It has a preventive role in atherogenesis and MS. The present work was conducted to study the correlation between serum adiponectin levels and clinical characteristics and biochemical parameters in PCOS patients. Materials and Methods: A prospective study in 49 newly diagnosed (as per Rotterdam criteria Indian PCOS women was conducted. PCOS women were clinically examined and investigated for biochemical parameters. Results : The mean serum adiponectin was 12 ± 9.4 μg/mL (range 0.47-45. Hypoadiponectinemia (serum adiponectin <4 μg/mL was present in 22% patients. Age and adiponectin correlated significantly and inversely (r = −0.42, P = 0.027. Overweight/obese patients had lower mean adiponectin levels than normal weight (11.62 ± 9.5 vs 13.58 ± 9.5, P = 0.56. It was significantly lower in patients with acanthosis nigricans (AN as compared with those without AN (8.4 ± 5.9 vs 15 ± 11, P = 0.038. Hirsute patients showed lower mean adiponectin levels than nonhirsute (10 ± 7.3 vs 13 ± 10, P = 0.57. A positive, insignificant correlation was observed between serum adiponectin and cholesterol, low-density lipoprotein, follicle stimulating hormone (FSH, thyroid stimulating hormone, levels. A negative insignificant correlation existed between serum adiponectin and luteinizing hormone (LH, LH: FSH ratio, prolactin, dehydroepiandrosterone, testosterone, triglyceride, high-density lipoprotein, fasting blood glucose, fasting insulin, and Homeostasis Model Assessment. Conclusion: Hypoadiponectinemia is present in one-fifth of women with PCOS. Adiponectin levels decrease as age advances. Low levels of adiponectin possibly contributes to the development of dermal manifestation (AN of insulin resistance.

  14. Use of clinical movement screening tests to predict injury in sport.

    Science.gov (United States)

    Chimera, Nicole J; Warren, Meghan

    2016-04-18

    Clinical movement screening tests are gaining popularity as a means to determine injury risk and to implement training programs to prevent sport injury. While these screens are being used readily in the clinical field, it is only recently that some of these have started to gain attention from a research perspective. This limits applicability and poses questions to the validity, and in some cases the reliability, of the clinical movement tests as they relate to injury prediction, intervention, and prevention. This editorial will review the following clinical movement screening tests: Functional Movement Screen™, Star Excursion Balance Test, Y Balance Test, Drop Jump Screening Test, Landing Error Scoring System, and the Tuck Jump Analysis in regards to test administration, reliability, validity, factors that affect test performance, intervention programs, and usefulness for injury prediction. It is important to review the aforementioned factors for each of these clinical screening tests as this may help clinicians interpret the current body of literature. While each of these screening tests were developed by clinicians based on what appears to be clinical practice, this paper brings to light that this is a need for collaboration between clinicians and researchers to ensure validity of clinically meaningful tests so that they are used appropriately in future clinical practice. Further, this editorial may help to identify where the research is lacking and, thus, drive future research questions in regards to applicability and appropriateness of clinical movement screening tools. PMID:27114928

  15. Relationships between organohalogen contaminants and blood plasma clinical-chemical parameters in chicks of three raptor species from Northern Norway

    DEFF Research Database (Denmark)

    Sonne, Christian; Bustnes, Jan Ove; Herzke, Dorte;

    2010-01-01

    Organohalogen contaminants (OHCs) may affect various physiological parameters in birds including blood chemistry. We therefore examined blood plasma clinical-chemical parameters and OHCs in golden eagle, white-tailed eagle and goshawk chicks from Northern Norway. Correlation analyses on pooled data......:creatinine were significantly positively correlated to various OHCs (all: pbone...

  16. School based oral health promotional intervention: Effect on knowledge, practices and clinical oral health related parameters

    Directory of Open Access Journals (Sweden)

    Arjun Gauba

    2013-01-01

    Full Text Available Background: No organized school oral health program is existent in India. Aim: The aim of this study is to test the feasibility and efficacy of an economical school oral health promotional intervention with educational and preventive components. Settings and Design: School oral health promotional intervention carried out in one of the randomly selected school and evaluated through short duration prospective model. Materials and Methods: A total of 100 children with an age range of 10-12 years with no previous history of dental intervention were enrolled. Interventions comprised of oral health education (delivered through lecture and demonstrations by an undergraduate dental student and topical antibacterial therapy (fluoride varnish and povidone iodine. Outcomes consisted of Knowledge and practices (KAP regarding oral health, clinical oral health related parameters such as plaque index (PI, gingival index (GI and caries activity as per Modified Snyder′s test. These were reported at baseline, 3 weeks and 6 months follow-up examination by a calibrated examiner. Statistical Analysis: McNemar Bowker′s test, Student′s t-test, Pearson Chi-square tests were used. Results: Highly significant (P < 0.001 improvements in KAP scores, PI scores, GI scores and caries activity were reported at 3 weeks and 6 months follow-up examination. Conclusion: This small economical school oral health program positively influenced oral health related practices and parameters of oral health such as oral cleanliness, gingival health and caries activity.

  17. R-Peak Time: An Electrocardiographic Parameter with Multiple Clinical Applications.

    Science.gov (United States)

    Pérez-Riera, Andrés Ricardo; de Abreu, Luiz Carlos; Barbosa-Barros, Raimundo; Nikus, Kjell C; Baranchuk, Adrian

    2016-01-01

    In the 12-lead electrocardiogram (ECG), the time from the onset of the QRS complex (Q or R wave) to the apex or peak of R or to R' (when present), using indirect or semidirect surface unipolar precordial leads, bipolar limb leads or unipolar limb leads, is called ventricular activation time (VAT), R wave peak time (RWPT), R-peak time or intrinsicoid deflection (ID). The R-peak time in a specific ECG lead is the interval from the earliest onset of the QRS complex, preferably determined from multiple simultaneously recorded leads, to the peak (maximum) of the R wave or R' if present. Irrespective of the relative height of the R and R' waves, the R-peak time is measured to the second peak. The parameter corresponds to the time of the electrical activation occurring from the endocardium to the epicardium as reflected by the recording electrode located at a variable distance on the body surface, depending on the lead type: a unipolar precordial lead, a bipolar or unipolar limb lead. In normal conditions, the R-peak time for the thinner-walled right ventricle is measured from lead V1 or V2 and its upper limit of normal is 35 ms. The R-peak time for the left ventricle (LV) is measured from leads V5 to V6 and 45 ms is considered the upper limit of normal. In this manuscript, we review the clinical applications of this parameter.

  18. Colon cancer: association of histopathological parameters and patients' survival with clinical presentation.

    Science.gov (United States)

    Alexiusdottir, Kristin K; Snaebjornsson, Petur; Tryggvadottir, Laufey; Jonasson, Larus; Olafsdottir, Elinborg J; Björnsson, Einar Stefan; Möller, Pall Helgi; Jonasson, Jon G

    2013-10-01

    Available data correlating symptoms of colon cancer patients with the severity of the disease are very limited. In a population-based setting, we correlated information on symptoms of colon cancer patients with several pathological tumor parameters and survival. Information on all patients diagnosed with colon cancer in Iceland in 1995-2004 for this retrospective, population-based study was obtained from the Icelandic Cancer Registry. Information on symptoms of patients and blood hemoglobin was collected from patients' files. Pathological parameters were obtained from a previously performed standardized tumor review. A total of 768 patients entered this study; the median age was 73 years. Tumors in patients presenting at diagnosis with visible blood in stools were significantly more likely to be of lower grade, having pushing border, conspicuous peritumoral lymphocytic infiltration, and lower frequency of vessel invasion. Patients with abdominal pain and anemia were significantly more likely to have vessel invasion. Logistic regression showed that visible blood in stools was significantly associated with protecting pathological factors (OR range 0.38-0.83, p < 0.05). Tumors in patients presenting with abdominal pain were strongly associated with infiltrative margin and scarce peritumoral lymphocytic infiltration (OR = 1.95; 2.18 respectively, p < 0.05). Changes in bowel habits were strongly associated with vessel invasion (OR = 2.03, p < 0.05). Cox regression showed that blood in stools predicted survival (HR = 0.54). In conclusion, visible blood in stools correlates significantly with all the beneficial pathological parameters analyzed and with better survival of patients. Anemia, general symptoms, changes in bowel habits, acute symptoms, and abdominal pain correlate with more aggressive tumor characteristics and adverse outcome for patients.

  19. Comparison Between Pathogen Associated Laboratory and Clinical Parameters in Early-Onset Sepsis of the Newborn

    Science.gov (United States)

    Resch, Bernhard; B, Renoldner; N, Hofer

    2016-01-01

    Objectives: To identify laboratory and clinical characteristics of different pathogens associated with early-onset sepsis (EOS) of the newborn. Methods: Newborns with EOS were retrospectively analyzed regarding laboratory and clinical parameters associated with the identified pathogen. Results: We identified 125 newborns having diagnosis of culture proven EOS between 1993 and 2011. One hundred cases had diagnosis of group B streptococci (GBS) infection (80%), 11 had Escherichia coli (8.8%), eight enterococci (6.4%), and six other pathogens (4.8%). White blood cell count (WBC), immature to total neutrophil (IT) ratio, and C-reactive protein (CRP) values did not differ between groups within the first 72 hours of life. Presence of high (>30000/µL) and low (0.2 in GBS and E.coli EOS. High WBC were more common found than low WBC in all groups. Gram positive pathogens were more common found in late preterm and term infants (84%), and gram negative pathogens more common in very low birth weight infants (64%). E. coli was significantly associated with lower gestational age and birth weight, respectively. Conclusion: An abnormal IT-ratio was a more common finding than an abnormal WBC in GBS and E. coli EOS. E. coli was significantly associated with prematurity. PMID:27478518

  20. Evaluation of the suitability of free-energy minimization using nearest-neighbor energy parameters for RNA secondary structure prediction

    Directory of Open Access Journals (Sweden)

    Cobaugh Christian W

    2004-08-01

    Full Text Available Abstract Background A detailed understanding of an RNA's correct secondary and tertiary structure is crucial to understanding its function and mechanism in the cell. Free energy minimization with energy parameters based on the nearest-neighbor model and comparative analysis are the primary methods for predicting an RNA's secondary structure from its sequence. Version 3.1 of Mfold has been available since 1999. This version contains an expanded sequence dependence of energy parameters and the ability to incorporate coaxial stacking into free energy calculations. We test Mfold 3.1 by performing the largest and most phylogenetically diverse comparison of rRNA and tRNA structures predicted by comparative analysis and Mfold, and we use the results of our tests on 16S and 23S rRNA sequences to assess the improvement between Mfold 2.3 and Mfold 3.1. Results The average prediction accuracy for a 16S or 23S rRNA sequence with Mfold 3.1 is 41%, while the prediction accuracies for the majority of 16S and 23S rRNA structures tested are between 20% and 60%, with some having less than 20% prediction accuracy. The average prediction accuracy was 71% for 5S rRNA and 69% for tRNA. The majority of the 5S rRNA and tRNA sequences have prediction accuracies greater than 60%. The prediction accuracy of 16S rRNA base-pairs decreases exponentially as the number of nucleotides intervening between the 5' and 3' halves of the base-pair increases. Conclusion Our analysis indicates that the current set of nearest-neighbor energy parameters in conjunction with the Mfold folding algorithm are unable to consistently and reliably predict an RNA's correct secondary structure. For 16S or 23S rRNA structure prediction, Mfold 3.1 offers little improvement over Mfold 2.3. However, the nearest-neighbor energy parameters do work well for shorter RNA sequences such as tRNA or 5S rRNA, or for larger rRNAs when the contact distance between the base-pairs is less than 100 nucleotides.

  1. Capsaicin cough sensitivity and the association with clinical parameters in bronchiectasis.

    Directory of Open Access Journals (Sweden)

    Wei-jie Guan

    Full Text Available BACKGROUND: Cough hypersensitivity has been common among respiratory diseases. OBJECTIVE: To determine associations of capsaicin cough sensitivity and clinical parameters in adults with clinically stable bronchiectasis. METHODS: We recruited 135 consecutive adult bronchiectasis patients and 22 healthy subjects. History inquiry, sputum culture, spirometry, chest high-resolution computed tomography (HRCT, Leicester Cough Questionnaire scoring, Bronchiectasis Severity Index (BSI assessment and capsaicin inhalation challenge were performed. Cough sensitivity was measured as the capsaicin concentration eliciting at least 2 (C2 and 5 coughs (C5. RESULTS: Despite significant overlap between healthy subjects and bronchiectasis patients, both C2 and C5 were significantly lower in the latter group (all P<0.01. Lower levels of C5 were associated with a longer duration of bronchiectasis symptoms, worse HRCT score, higher 24-hour sputum volume, BSI and sputum purulence score, and sputum culture positive for P. aeruginosa. Determinants associated with increased capsaicin cough sensitivity, defined as C5 being 62.5 µmol/L or less, encompassed female gender (OR: 3.25, 95%CI: 1.35-7.83, P<0.01, HRCT total score between 7-12 (OR: 2.57, 95%CI: 1.07-6.173, P = 0.04, BSI between 5-8 (OR: 4.05, 95%CI: 1.48-11.06, P<0.01 and 9 or greater (OR: 4.38, 95%CI: 1.48-12.93, P<0.01. CONCLUSION: Capsaicin cough sensitivity is heightened in a subgroup of bronchiectasis patients and associated with the disease severity. Gender and disease severity, but not sputum purulence, are independent determinants of heightened capsaicin cough sensitivity. Current testing for cough sensitivity diagnosis may be limited because of overlap with healthy subjects but might provide an objective index for assessment of cough in future clinical trials.

  2. Vmax estimate from three-parameter critical velocity models: validity and impact on 800 m running performance prediction.

    Science.gov (United States)

    Bosquet, Laurent; Duchene, Antoine; Lecot, François; Dupont, Grégory; Leger, Luc

    2006-05-01

    The purpose of this study was to evaluate the validity of maximal velocity (Vmax) estimated from three-parameter systems models, and to compare the predictive value of two- and three-parameter models for the 800 m. Seventeen trained male subjects (VO2max=66.54+/-7.29 ml min(-1) kg(-1)) performed five randomly ordered constant velocity tests (CVT), a maximal velocity test (mean velocity over the last 10 m portion of a 40 m sprint) and a 800 m time trial (V 800 m). Five systems models (two three-parameter and three two-parameter) were used to compute V max (three-parameter models), critical velocity (CV), anaerobic running capacity (ARC) and V800m from times to exhaustion during CVT. Vmax estimates were significantly lower than (0.19Critical velocity (CV) alone explained 40-62% of the variance in V800m. Combining CV with other parameters of each model to produce a calculated V800m resulted in a clear improvement of this relationship (0.83parameter models had a better association (0.93parameter models (0.83parameter models appear to have a better predictive value for short duration events such as the 800 m, the fact the Vmax is not associated with the ability it is supposed to reflect suggests that they are more empirical than systems models.

  3. Relative role of parameter vs. climate uncertainty for predictions of future Southeastern U.S. pine carbon cycling

    Science.gov (United States)

    Jersild, A.; Thomas, R. Q.; Brooks, E.; Teskey, R. O.; Wynne, R. H.; Arthur, D.; Gonzalez, C.; Thomas, V. A.; Fox, T. D.; Smallman, L.

    2015-12-01

    Predictions of the how forest productivity and carbon sequestration will respond to climate change are essential for assisting land managers in adapting to future climate. However, current predictions can include considerable uncertainty that is often not well quantified. To address the need for better quantification of uncertainty, we calculated and compared parameter and climate prediction uncertainty for predictions of Southeastern U.S. pine forest productivity. We used a Metropolis-Hastings Markov Chain Monte Carlo-based data assimilation technique to fuse regionally widespread and diverse datasets with the Physiological Principles Predicting Growth model (3PG) model. The datasets incorporated include biomass observations from forest research plots that are part of the Pine Integrated Network: Education, Mitigation, and Adaptation project (PINEMAP) project, photosynthesis and evaporation observations from loblolly pine Ameriflux sites, and productivity responses to elevated CO2 from the Duke Free Air C site. These spatially and temporally diverse data sets give our unique analysis a more accurately measured uncertainty by constraining complimentary components of the model. In our analysis, parameter uncertainty was quantified using simulations that integrate across the posterior parameter distributions, while climate model uncertainty was quantified using downscaled RCP 8.5 simulations from twenty different CMIP5 climate models. Overall, we found that the uncertainty in future productivity of Southeastern U.S. managed pine forests that was associated with parameterization is comparable to the uncertainty associated with climate simulations. Our results indicate that reducing parameterization in ecosystem model development can improve future predictions of forest productivity and carbon sequestration, but uncertainties in future climate predictions also need to be properly quantified and communicated to forest owners and managers.

  4. Clinical algorithm for improved prediction of ambulation and patient stratification after incomplete spinal cord injury.

    Science.gov (United States)

    Zörner, Björn; Blanckenhorn, Wolf U; Dietz, Volker; Curt, Armin

    2010-01-01

    The extent of ambulatory recovery after motor incomplete spinal cord injury (miSCI) differs considerably amongst affected persons. This makes individual outcome prediction difficult and leads to increased within-group variation in clinical trials. The aims of this study on subjects with miSCI were: (1) to rank the strongest single predictors and predictor combinations of later walking capacity; (2) to develop a reliable algorithm for clinical prediction; and (3) to identify subgroups with only limited recovery of walking function. Correlation and logistic regression analyses were performed on a dataset of 90 subjects with tetra- or paraparesis, recruited in a prospective European multicenter study. Eleven measures obtained in the subacute injury period, including clinical examination, tibial somatosensory evoked potentials (tSSEP), and demographic factors, were related to ambulatory outcome (WISCI II, 6minWT) 6 months after injury. The lower extremity motor score (LEMS) alone and in combination was identified as most predictive for later walking capacity in miSCI. Ambulatory outcome of subjects with tetraparesis was correctly predicted for 92% (WISCI II) or 100% (6minWT) of the cases when LEMS was combined with either tSSEP or the ASIA Impairment Scale, respectively. For individuals with paraparesis, prediction was less distinct, mainly due to low prediction rates for individuals with poor walking outcome. A clinical algorithm was generated that allowed for the identification of a subgroup composed of individuals with tetraparesis and poor ambulatory recovery. These data provide evidence that a combination of predictors enables a reliable prediction of walking function and early patient stratification for clinical trials in miSCI.

  5. Research on predicting prosodic parameters for Chinese synthesis by data mining approach

    Institute of Scientific and Technical Information of China (English)

    WANG Wei; CAI Lianhong

    2003-01-01

    Prosodic control is an important part of speech synthesis system. Prosodic pa-rameters choice right or wrong influences the quality of synthetic speech directly. At present,text to speech system has less effective describe to reflect data relationships in the corpus. Anew research approach - data mining technology to discover those relationships by associationrules modeling is presented. And a new algorithm for generating association rules of prosodicparameters including pitch parameters and duration parameters from corpus is developed. Theoutput rules improve the correctness of syllable choice in text to speech system.

  6. GliomaPredict: a clinically useful tool for assigning glioma patients to specific molecular subtypes

    Directory of Open Access Journals (Sweden)

    Fine Howard A

    2010-07-01

    Full Text Available Abstract Background Advances in generating genome-wide gene expression data have accelerated the development of molecular-based tumor classification systems. Tools that allow the translation of such molecular classification schemas from research into clinical applications are still missing in the emerging era of personalized medicine. Results We developed GliomaPredict as a computational tool that allows the fast and reliable classification of glioma patients into one of six previously published stratified subtypes based on sets of extensively validated classifiers derived from hundreds of glioma transcriptomic profiles. Our tool utilizes a principle component analysis (PCA-based approach to generate a visual representation of the analyses, quantifies the confidence of the underlying subtype assessment and presents results as a printable PDF file. GliomaPredict tool is implemented as a plugin application for the widely-used GenePattern framework. Conclusions GliomaPredict provides a user-friendly, clinically applicable novel platform for instantly assigning gene expression-based subtype in patients with gliomas thereby aiding in clinical trial design and therapeutic decision-making. Implemented as a user-friendly diagnostic tool, we expect that in time GliomaPredict, and tools like it, will become routinely used in translational/clinical research and in the clinical care of patients with gliomas.

  7. Nomograms for the Prediction of Pathologic Stage of Clinically Localized Prostate Cancer in Korean Men

    OpenAIRE

    Song, Cheryn; Kang, Taejin; Ro, Jae Y.; Lee, Moo-Song; Kim, Choung-Soo; Ahn, Hanjong

    2005-01-01

    We analyzed the prostate cancer data of 317 Korean men with clinically localized prostate cancer who underwent radical prostatectomy at Asan Medical Center between June 1990 and November 2003 to construct nomograms predicting the pathologic stage of these tumors, and compared the outcome with preexisting nomograms. Multinomial log-linear regression was performed for the simultaneous prediction of organ-confined disease (OCD), extracapsular extension (ECE), seminal vesicle invasion (SVI) and l...

  8. A nomogram to predict Gleason sum upgrading of clinically diagnosed localized prostate cancer among Chinese patients

    OpenAIRE

    Jin-You Wang; Yao Zhu; Chao-Fu Wang; Shi-Lin Zhang; Bo Dai; Ding-Wei Ye

    2014-01-01

    Although several models have been developed to predict the probability of Gleason sum upgrading between biopsy and radical prostatectomy specimens, most of these models are restricted to prostate-specific antigen screening-detected prostate cancer. This study aimed to build a nomogram for the prediction of Gleason sum upgrading in clinically diagnosed prostate cancer. The study cohort comprised 269 Chinese prostate cancer patients who underwent prostate biopsy with a minimum of 10 cores and w...

  9. Pulmonary embolism in intensive care unit: Predictive factors, clinical manifestations and outcome

    OpenAIRE

    Bahloul Mabrouk; Chaari Anis; Kallel Hatem; Abid Leila; Hamida Chokri Ben; Dammak Hassen; Rekik Noureddine; Mnif Jameleddine; Chelly Hedi; Bouaziz Mounir

    2010-01-01

    Objective : To determine predictive factors, clinical and demographics characteristics of patients with pulmonary embolism (PE) in ICU, and to identify factors associated with poor outcome in the hospital and in the ICU. Methods : During a four-year prospective study, a medical committee of six ICU physicians prospectively examined all available data for each patient in order to classify patients according to the level of clinical suspicion of pulmonary thromboembolism. During the study...

  10. Early seizures in patients with acute stroke: Frequency, predictive factors, and effect on clinical outcome

    OpenAIRE

    Andrea Alberti; Maurizio Paciaroni; Valeria Caso; Michele Venti; Francesco Palmerini; Giancarlo Agnelli

    2008-01-01

    Andrea Alberti, Maurizio Paciaroni, Valeria Caso, Michele Venti, Francesco Palmerini, Giancarlo AgnelliStroke Unit and Division of Internal and Cardiovascular Medicine, University of Perugia, Perugia, ItalyBackground: Early seizure (ES) may complicate the clinical course of patients with acute stroke. The aim of this study was to assess the rate of and the predictive factors for ES as well the effects of ES on the clinical outcome at hospital discharge in patients with first-ever stroke.Patie...

  11. A Well-Designed Parameter Estimation Method for Lifetime Prediction of Deteriorating Systems with Both Smooth Degradation and Abrupt Damage

    Directory of Open Access Journals (Sweden)

    Chuanqiang Yu

    2015-01-01

    Full Text Available Deteriorating systems, which are subject to both continuous smooth degradation and additional abrupt damages due to a shock process, can be often encountered in engineering. Modeling the degradation evolution and predicting the lifetime of this kind of systems are both interesting and challenging in practice. In this paper, we model the degradation trajectory of the deteriorating system by a random coefficient regression (RCR model with positive jumps, where the RCR part is used to model the continuous smooth degradation of the system and the jump part is used to characterize the abrupt damages due to random shocks. Based on a specified threshold level, the probability density function (PDF and cumulative distribution function (CDF of the lifetime can be derived analytically. The unknown parameters associated with the derived lifetime distributions can be estimated via a well-designed parameter estimation procedure on the basis of the available degradation recordings of the deteriorating systems. An illustrative example is finally provided to demonstrate the implementation and superiority of the newly proposed lifetime prediction method. The experimental results reveal that our proposed lifetime prediction method with the dedicated parameter estimation strategy can get more accurate lifetime predictions than the rival model in literature.

  12. Applying Theoretical Approach for Predicting the Selective Calcium Channel Blockers Pharmacological Parameter by Biopartitioning Micellar Chromatography

    Institute of Scientific and Technical Information of China (English)

    WANG Su-Min; YANG Geng-Liang; LI Zhi-Wei; LIU Hai-Yan; GUO Hui-Juan

    2006-01-01

    The usefulness of biopartitioning micellar chromatography (BMC) for predicting oral drug acute toxicity and apparent bioavailability was demonstrated. A logarithmic model (an LD50 model) and the second order polynomial models (apparent bioavailability model) have been obtained using the retention data of the selective calcium channel blockers to predict pharmacological properties of compounds. The use of BMC is simple, reproducible and can provide key information about the acute toxicity and transport properties of new compounds during the drug discovery process.

  13. Three-tiered risk stratification model to predict progression in Barrett's esophagus using epigenetic and clinical features.

    Directory of Open Access Journals (Sweden)

    Fumiaki Sato

    Full Text Available Barrett's esophagus predisposes to esophageal adenocarcinoma. However, the value of endoscopic surveillance in Barrett's esophagus has been debated because of the low incidence of esophageal adenocarcinoma in Barrett's esophagus. Moreover, high inter-observer and sampling-dependent variation in the histologic staging of dysplasia make clinical risk assessment problematic. In this study, we developed a 3-tiered risk stratification strategy, based on systematically selected epigenetic and clinical parameters, to improve Barrett's esophagus surveillance efficiency.We defined high-grade dysplasia as endpoint of progression, and Barrett's esophagus progressor patients as Barrett's esophagus patients with either no dysplasia or low-grade dysplasia who later developed high-grade dysplasia or esophageal adenocarcinoma. We analyzed 4 epigenetic and 3 clinical parameters in 118 Barrett's esophagus tissues obtained from 35 progressor and 27 non-progressor Barrett's esophagus patients from Baltimore Veterans Affairs Maryland Health Care Systems and Mayo Clinic. Based on 2-year and 4-year prediction models using linear discriminant analysis (area under the receiver-operator characteristic (ROC curve: 0.8386 and 0.7910, respectively, Barrett's esophagus specimens were stratified into high-risk (HR, intermediate-risk (IR, or low-risk (LR groups. This 3-tiered stratification method retained both the high specificity of the 2-year model and the high sensitivity of the 4-year model. Progression-free survivals differed significantly among the 3 risk groups, with p = 0.0022 (HR vs. IR and p<0.0001 (HR or IR vs. LR. Incremental value analyses demonstrated that the number of methylated genes contributed most influentially to prediction accuracy.This 3-tiered risk stratification strategy has the potential to exert a profound impact on Barrett's esophagus surveillance accuracy and efficiency.

  14. Comparison of four clinical scores for the predicting lower limb deep venous thrombosis in Chinese patients

    Institute of Scientific and Technical Information of China (English)

    Li Zhua; Min Liu; Xiaojuan Guo; Jianguo Wang; Youmin Guo; Chen Wang; Hongxia Ma; Yulin Guo

    2008-01-01

    To evaluate Wells, Kahn, St.Andr é and Constans scores for the prediction of deep venous thrombosis in Chinese patients.Methods:One hundred and seventy-two patients, prospectively, blinded referred for evaluation with four clinical-score systems for suspected deep venous thrombosis, were examined by ultrasonography.Sensitivity, specificity, positive predictive value, nega- tive predictive value and receiver operation curves were calculated for four clinical scores.The difference between areas of the ROC curve for each of the scores was compared with others and reference line.Results:Forty-six of 172 patients had deep venous throm- bosis proven by sonography.The sensitivity, specificity, positive predictive value and negative predictive value for Wells score was 91.3%, 27.4% and 74.2% respectively, for Constans score; 95.7%, 34.9%, 34.9% and 95.7% respectively.Area under ROV curve of Constans with the reference line.Conclusion:Based on the results of our study, the sensitivity, negative prediction value and area under ROC Considering the aim of the clinical assessment, Constans score and Wells score are more efficient for Chinese hospitalized patients.

  15. Parameters extraction of photovoltaic module for long-term prediction using Artifical Bee Colony optimization

    OpenAIRE

    Garoudja, Elyes; Kara, Kamel; Chouder, Aissa; Silvestre Bergés, Santiago

    2015-01-01

    In this paper, a heuristic optimization approach based on Artificial Bee Colony (ABC) algorithm is applied to the extraction of the five electrical parameters of a photovoltaic (PV) module. The proposed approach has several interesting features such as no prior knowledge of the physical system and its convergence is not dependent on the initial conditions. The extracted parameters have been tested against several static IV characteristics of different PV modules from diff...

  16. Two-parameter Failure Model Improves Time-independent and Time-dependent Failure Predictions

    Energy Technology Data Exchange (ETDEWEB)

    Huddleston, R L

    2004-01-27

    A new analytical model for predicting failure under a generalized, triaxial stress state was developed by the author and initially reported in 1984. The model was validated for predicting failure under elevated-temperature creep-rupture conditions. Biaxial data for three alloy steels, Types 304 and 316 stainless steels and Inconel 600, demonstrated two to three orders of magnitude reduction in the scatter of predicted versus observed creep-rupture times as compared to the classical failure models of Mises, Tresca, and Rankine. In 1990, the new model was incorporated into American Society of Mechanical Engineers (ASME) Code Case N47-29 for design of components operating under creep-rupture conditions. The current report provides additional validation of the model for predicting failure under time-independent conditions and also outlines a methodology for predicting failure under cyclic, time-dependent, creep-fatigue conditions. The later extension of the methodology may have the potential to improve failure predictions there as well. These results are relevant to most design applications, but they have special relevance to high-performance design applications such as components for high-pressure equipment, nuclear reactors, and jet engines.

  17. A Multi-Center Prospective Derivation and Validation of a Clinical Prediction Tool for Severe Clostridium difficile Infection.

    LENUS (Irish Health Repository)

    Na, Xi

    2015-04-23

    Prediction of severe clinical outcomes in Clostridium difficile infection (CDI) is important to inform management decisions for optimum patient care. Currently, treatment recommendations for CDI vary based on disease severity but validated methods to predict severe disease are lacking. The aim of the study was to derive and validate a clinical prediction tool for severe outcomes in CDI.

  18. Stochastic rainfall-runoff forecasting: parameter estimation, multi-step prediction, and evaluation of overflow risk

    DEFF Research Database (Denmark)

    Löwe, Roland; Mikkelsen, Peter Steen; Madsen, Henrik

    2014-01-01

    Probabilistic runoff forecasts generated by stochastic greybox models can be notably useful for the improvement of the decision-making process in real-time control setups for urban drainage systems because the prediction risk relationships in these systems are often highly nonlinear. To date, res...... in this analysis. In conclusion, further research must focus on the development of model structures that allow the proper separation of dry and wet weather uncertainties and simulate runoff uncertainties depending on the rainfall input.......Probabilistic runoff forecasts generated by stochastic greybox models can be notably useful for the improvement of the decision-making process in real-time control setups for urban drainage systems because the prediction risk relationships in these systems are often highly nonlinear. To date......, research has primarily focused on one-step-ahead flow predictions for identifying, estimating, and evaluating greybox models. For control purposes, however, stochastic predictions are required for longer forecast horizons and for the prediction of runoff volumes, rather than flows. This article therefore...

  19. Prediction of Clinical Deterioration in Hospitalized Adult Patients with Hematologic Malignancies Using a Neural Network Model

    Science.gov (United States)

    Hu, Scott B.; Wong, Deborah J. L.; Correa, Aditi; Li, Ning; Deng, Jane C.

    2016-01-01

    Introduction Clinical deterioration (ICU transfer and cardiac arrest) occurs during approximately 5–10% of hospital admissions. Existing prediction models have a high false positive rate, leading to multiple false alarms and alarm fatigue. We used routine vital signs and laboratory values obtained from the electronic medical record (EMR) along with a machine learning algorithm called a neural network to develop a prediction model that would increase the predictive accuracy and decrease false alarm rates. Design Retrospective cohort study. Setting The hematologic malignancy unit in an academic medical center in the United States. Patient Population Adult patients admitted to the hematologic malignancy unit from 2009 to 2010. Intervention None. Measurements and Main Results Vital signs and laboratory values were obtained from the electronic medical record system and then used as predictors (features). A neural network was used to build a model to predict clinical deterioration events (ICU transfer and cardiac arrest). The performance of the neural network model was compared to the VitalPac Early Warning Score (ViEWS). Five hundred sixty five consecutive total admissions were available with 43 admissions resulting in clinical deterioration. Using simulation, the neural network outperformed the ViEWS model with a positive predictive value of 82% compared to 24%, respectively. Conclusion We developed and tested a neural network-based prediction model for clinical deterioration in patients hospitalized in the hematologic malignancy unit. Our neural network model outperformed an existing model, substantially increasing the positive predictive value, allowing the clinician to be confident in the alarm raised. This system can be readily implemented in a real-time fashion in existing EMR systems. PMID:27532679

  20. Spatial extrapolation of light use efficiency model parameters to predict gross primary production

    Directory of Open Access Journals (Sweden)

    Karsten Schulz

    2011-12-01

    Full Text Available To capture the spatial and temporal variability of the gross primary production as a key component of the global carbon cycle, the light use efficiency modeling approach in combination with remote sensing data has shown to be well suited. Typically, the model parameters, such as the maximum light use efficiency, are either set to a universal constant or to land class dependent values stored in look-up tables. In this study, we employ the machine learning technique support vector regression to explicitly relate the model parameters of a light use efficiency model calibrated at several FLUXNET sites to site-specific characteristics obtained by meteorological measurements, ecological estimations and remote sensing data. A feature selection algorithm extracts the relevant site characteristics in a cross-validation, and leads to an individual set of characteristic attributes for each parameter. With this set of attributes, the model parameters can be estimated at sites where a parameter calibration is not possible due to the absence of eddy covariance flux measurement data. This will finally allow a spatially continuous model application. The performance of the spatial extrapolation scheme is evaluated with a cross-validation approach, which shows the methodology to be well suited to recapture the variability of gross primary production across the study sites.

  1. FEM and ANN combined approach for predicting pressure source parameters at Etna volcano

    Directory of Open Access Journals (Sweden)

    A. Di Stefano

    2010-05-01

    Full Text Available A hybrid approach for forward and inverse geophysical modeling, based on Artificial Neural Networks (ANN and Finite Element Method (FEM, is proposed in order to properly identify the parameters of volcanic pressure sources from geophysical observations at ground surface. The neural network is trained and tested with a set of patterns obtained by the solutions of numerical models based on FEM. The geophysical changes caused by magmatic pressure sources were computed developing a 3-D FEM model with the aim to include the effects of topography and medium heterogeneities at Etna volcano. ANNs are used to interpolate the complex non linear relation between geophysical observations and source parameters both for forward and inverse modeling. The results show that the combination of neural networks and FEM is a powerful tool for a straightforward and accurate estimation of source parameters in volcanic regions.

  2. Predicting effects of diffusion welding parameters on welded joint properties by artificial neural network

    Institute of Scientific and Technical Information of China (English)

    刘黎明; 祝美丽; 牛济泰; 张忠典

    2001-01-01

    The static model for metal matrix composites in diffusion welding was established by means of artificial neural network method. The model presents the relationship between weld joint properties and welding parameters such as welding temperature, welding pressure and welding time. Through simulating the diffusion welding process of SiCw/6061Al composite, the effects of welding parameters on the strength of welded joint was studied and optimal technical parameters was obtained. It is proved that this method has good fault-tolerant ability and versatility and can overcome the shortage of the general experiment. The established static model is in good agreement with the actual welding process, so it becomes a new path for studying the weldability of new material.

  3. Predicting neutrino parameters from SO(3) family symmetry and quark-lepton unification

    Energy Technology Data Exchange (ETDEWEB)

    King, Stephen F. [School of Physics and Astronomy, University of Southampton, Southampton, SO17 1BJ (United Kingdom)

    2005-08-01

    We show how the neutrino mixing angles and oscillation phase can be predicted from tri-bimaximal neutrino mixing, corrected by charged lepton mixing angles which are related to quark mixing angles via quark-lepton unification. The tri-bimaximal neutrino mixing can naturally originate from the see-saw mechanism via constrained sequential dominance (CSD), where CSD can result from the vacuum alignment of a non-abelian family symmetry such as SO(3). We construct a realistic model of quark and lepton masses and mixings based on SO(3) family symmetry with quark-lepton unification based on the Pati-Salam gauge group. The atmospheric angle is predicted to be approximately maximal {theta}{sub 23} = 45{sup 0}, corrected by the quark mixing angle {theta}{sub 23}{sup CKM} {approx} 2.4 deg., with the correction controlled by an undetermined phase in the quark sector. The solar angle is predicted by the tri-bimaximal complementarity relation: {theta}{sub 12}+(1/2{sup 1/2})({theta}{sub C}/3)cos ({delta}-{pi}) {approx} 35.26 deg., where {theta}{sub C} is the Cabibbo angle and {delta} is the neutrino oscillation phase. The reactor angle is predicted to be {theta}{sub 13} {approx} (1/2{sup 1/2})({theta}{sub C}/3) {approx} 3.06 deg. The MNS neutrino oscillation phase {delta} is predicted in terms of the solar angle to be cos ({delta}-{pi}) {approx} (35.26 deg.-{theta}{sub 12}{sup 0})/3.06 deg. These predictions can all be tested by future high precision neutrino oscillation experiments, thereby probing the nature of high energy quark-lepton unification.

  4. Lymphocytic Thyroiditis – is cytological grading significant? A correlation of grades with clinical, biochemical, ltrasonographic and radionuclide parameters

    Directory of Open Access Journals (Sweden)

    Dash Radharaman

    2007-01-01

    Full Text Available Abstract Background Clinical, biochemical, ultrasonographic, radionuclide and cytomorphological observations in Lymphocytic thyroiditis (LT, to define the cytological grading criteria on smears and correlation of grades with above parameters. Methods This prospective study was conducted on 76 patients attending the Fine needle aspiration cytology clinic of a tertiary care institute in North India. The various parameters like patients' clinical presentation, thyroid antimicrosomal antibodies, hormonal profiles, radionuclide thyroid scan and thyroid ultrasound were studied. Fine needle aspiration of thyroid gland and grading of thyroiditis was done on smears. The grades were correlated with above parameters and the correlation indices were evaluated statistically. Results Most of the patients were females (70, 92.11% who presented with a diffuse goiter (68, 89.47%. Hypothyroid features (56, 73.68% and elevated TSH (75, 98.68% were common, but radioiodide uptake was low or normal in majority of patients. Thyroid antimicrosomal antibody was elevated in 46/70 (65.71% patients. Cytomorphology in fine needle aspirates was diagnostic of lymphocytic thyroiditis in 75 (98.68% patients. Most of them had grade I/II disease by cytology. No correlation was observed between grades of cytomorphology and clinical, biochemical, ultrasonographic and radionuclide parameters. Conclusion Despite the availability of several tests for diagnosis of LT, FNAC remains the gold standard. The grades of thyroiditis at cytology however do not correlate with clinical, biochemical, radionuclide and ultrasonographic parameters.

  5. Hemogram parameters for predicting pulmonary embolism in patients with deep venous thrombosis

    Directory of Open Access Journals (Sweden)

    Kaya H

    2015-11-01

    Full Text Available Hakki Kaya, Recep KurtDepartment of Cardiology, Cumhuriyet University Medical School, Sivas, TurkeyWe read the article of Sevuk et al,1 published in the August 2015 issue of your journal, with great interest. The authors concluded that percentage change in serial measurements of mean platelet volume (MPV and platelet-distribution width (PDW is valuable in predicting the development of pulmonary thromboembolism in patients with a previous history of deep venous thrombosis (DVT. In a similar study conducted by Braekkan et al2 (Tromsø Study, MPV on admission was shown to predict pulmonary thromboembolism.  Read the original paper here

  6. DYNAMIC PRODUCTION PREDICTION AND PARAMETER IDENTIFICATION FOR GAS WELL WITH VERTICAL FRACTURE

    Institute of Scientific and Technical Information of China (English)

    郭大立; 刘慈群; 赵金洲

    2002-01-01

    In order to devoid the hard work and factitious error in selecting charts while analyzing and interpreting hydraulic fracturing fracture parameters, on the basis of the nonDarcy flow factor, this paper put out the non-Darcy flow mathematical model of real gas in the formation and fracture, established the production history automatic matching model to identify fracture parameters, and offered the numerical solutions of those models, which took the variation of fracture conductivity in production process. These results offered a precise and reliable method to understand formation, analyze and evaluate the fracturing treatment quality of gas well.

  7. Handbook of parameter values for the prediction of radionuclide transfer in temperate environments

    International Nuclear Information System (INIS)

    This Handbook has been prepared in response to a widely expressed interest in having a convenient and authoritative reference for radionuclide transfer parameter values used in biospheric assessment models. It draws on data from North America and Europe, much of which was collected through projects of the International Union of Radioecologists (IUR) and the Commission of European Communities (CEC) over the last decade. It is intended to supplement existing IAEA publications on environmental assessment methodology, primarily Generic Models and Parameters for Assessing the Environmental Transfer of Radionuclides from Routine Releases, IAEA Safety Series No. 57 (1982). 219 refs, 3 figs, 32 tabs

  8. Predictive Validity of DSM-IV Oppositional Defiant and Conduct Disorders in Clinically Referred Preschoolers

    Science.gov (United States)

    Keenan, Kate; Boeldt, Debra; Chen, Diane; Coyne, Claire; Donald, Radiah; Duax, Jeanne; Hart, Katherine; Perrott, Jennifer; Strickland, Jennifer; Danis, Barbara; Hill, Carri; Davis, Shante; Kampani, Smita; Humphries, Marisha

    2011-01-01

    Background: Diagnostic validity of oppositional defiant and conduct disorders (ODD and CD) for preschoolers has been questioned based on concerns regarding the ability to differentiate normative, transient disruptive behavior from clinical symptoms. Data on concurrent validity have accumulated, but predictive validity is limited. Predictive…

  9. Clinical prediction of occupational and non-specific low back pain

    Directory of Open Access Journals (Sweden)

    Ingrid Tolosa-Guzmán

    2012-09-01

    Full Text Available Non-specific Occupational Low Back Pain (NOLBP is a health condition that generates a high absenteeism and disability. Due to multifactorial causes is difficult to determine accurate diagnosis and prognosis. The clinical prediction of NOLBP is identified as a series of models that integrate a multivariate analysis to determine early diagnosis, course, and occupational impact of this health condition. Objective: to identify predictor factors of NOLBP, and the type of material referred to in the scientific evidence and establish the scopes of the prediction. Materials and method: the title search was conducted in the databases PubMed, Science Direct, and Ebsco Springer, between 1985 and 2012. The selected articles were classified through a bibliometric analysis allowing to define the most relevant ones. Results: 101 titles met the established criteria, but only 43 met the purpose of the review. As for NOLBP prediction, the studies varied in relation to the factors for example: diagnosis, transition of lumbar pain from acute to chronic, absenteeism from work, disability and return to work. Conclusion: clinical prediction is considered as a strategic to determine course and prognostic of NOLBP, and to determine the characteristics that increase the risk of chronicity in workers with this health condition. Likewise, clinical prediction rules are tools that aim to facilitate decision making about the evaluation, diagnosis, prognosis and intervention for low back pain, which should incorporate risk factors of physical, psychological and social.

  10. Predicting tropical forest stand structure parameters from Fourier transform of very high-resolution remotely sensed canopy images

    OpenAIRE

    Couteron, Pierre; Pelissier, Raphaël; Nicolini, Eric,; Paget, P.

    2005-01-01

    1. Predicting stand structure parameters for tropical forests from remotely sensed data has numerous important applications, such as estimating above-ground biomass and carbon stocks and providing spatial information for forest mapping and management planning, as well as detecting potential ecological determinants of plant species distributions. As an alternative to direct measurement of physical attributes of the vegetation and individual tree crown delineation, we present a powerful holisti...

  11. COMPARISON OF ANN WITH RSM IN PREDICTING SURFACE ROUGHNESS WITH RESPECT TO PROCESS PARAMETERS IN Nd: YAG LASER DRILLING

    OpenAIRE

    ARINDAM MAJUMDER

    2010-01-01

    Micro machining is a ready solution towards the miniaturization of component and devices. The process parameters of low power pulse Nd:YAG laser machining such as pulse rate, pulse width, speed play a major role in deciding the surface quality. Two methods, response surface methodology (RSM) and artificial neural network (ANN) were used to predict the surface roughness of Nd:YAG laser drilled mild steel specimens. The experiments were conducted based on the three factors, three levels and cen...

  12. Prediction of the droughts in Indonesia with environmental parameters; Prediccion de sequias en Indonesia mediante la utilizacion de parametros medioambientales

    Energy Technology Data Exchange (ETDEWEB)

    Wasser, C.V.H.J.

    1994-12-31

    Every 5 or 10 years, the global climate is modified by the ``El Nino-Southern Oscillation`` (ENSO) oceanic-atmospheric system. This paper shows how data related with this system, combined with other environmental parameters, can be used to predict the intensity of the dry season in Indonesia. Foreseeing a possible short-fall of rain is very important for a country where the mayor part of its 190 million inhabitants depend on rice as their prime food source. (Author)

  13. Predicting dynamic knee joint load with clinical measures in people with medial knee osteoarthritis.

    Science.gov (United States)

    Hunt, Michael A; Bennell, Kim L

    2011-08-01

    Knee joint loading, as measured by the knee adduction moment (KAM), has been implicated in the pathogenesis of knee osteoarthritis (OA). Given that the KAM can only currently be accurately measured in the laboratory setting with sophisticated and expensive equipment, its utility in the clinical setting is limited. This study aimed to determine the ability of a combination of four clinical measures to predict KAM values. Three-dimensional motion analysis was used to calculate the peak KAM at a self-selected walking speed in 47 consecutive individuals with medial compartment knee OA and varus malalignment. Clinical predictors included: body mass; tibial angle measured using an inclinometer; walking speed; and visually observed trunk lean toward the affected limb during the stance phase of walking. Multiple linear regression was performed to predict KAM magnitudes using the four clinical measures. A regression model including body mass (41% explained variance), tibial angle (17% explained variance), and walking speed (9% explained variance) explained a total of 67% of variance in the peak KAM. Our study demonstrates that a set of measures easily obtained in the clinical setting (body mass, tibial alignment, and walking speed) can help predict the KAM in people with medial knee OA. Identifying those patients who are more likely to experience high medial knee loads could assist clinicians in deciding whether load-modifying interventions may be appropriate for patients, whilst repeated assessment of joint load could provide a mechanism to monitor disease progression or success of treatment.

  14. Prediction of the saturated hydraulic conductivity from Brooks and Corey’s water retention parameters

    NARCIS (Netherlands)

    P. Nasta; J.A. Vrugt; N. Romano

    2013-01-01

    Prediction of flow through variably saturated porous media requires accurate knowledge of the soil hydraulic properties, namely the water retention function (WRF) and the hydraulic conductivity function (HCF). Unfortunately, direct measurement of the HCF is time consuming and expensive. In this stud

  15. Prediction of the ease of subdivision of scored tablets from their physical parameters

    NARCIS (Netherlands)

    Van Der Steen, Koos C.; Frijlink, Henderik W.; Schipper, C. Maarten A.; Barends, Dirk M.

    2010-01-01

    At present, the ease of subdivision of scored tablets is estimated in vivo. In order to replace such in vivo testing and to develop a surrogate test which uses in vitro techniques, the association between physical parameters of scored tablets and their ease of subdivision was studied. The physical p

  16. House thermal model parameter estimation method for Model Predictive Control applications

    NARCIS (Netherlands)

    Leeuwen, van R.P.; Wit, de J.B.; Fink, J.; Smit, G.J.M.

    2015-01-01

    In this paper we investigate thermal network models with different model orders applied to various Dutch low-energy house types with high and low interior thermal mass and containing floor heating. Parameter estimations are performed by using data from TRNSYS simulations. The paper discusses results

  17. Discrete element modelling (DEM) input parameters: understanding their impact on model predictions using statistical analysis

    Science.gov (United States)

    Yan, Z.; Wilkinson, S. K.; Stitt, E. H.; Marigo, M.

    2015-09-01

    Selection or calibration of particle property input parameters is one of the key problematic aspects for the implementation of the discrete element method (DEM). In the current study, a parametric multi-level sensitivity method is employed to understand the impact of the DEM input particle properties on the bulk responses for a given simple system: discharge of particles from a flat bottom cylindrical container onto a plate. In this case study, particle properties, such as Young's modulus, friction parameters and coefficient of restitution were systematically changed in order to assess their effect on material repose angles and particle flow rate (FR). It was shown that inter-particle static friction plays a primary role in determining both final angle of repose and FR, followed by the role of inter-particle rolling friction coefficient. The particle restitution coefficient and Young's modulus were found to have insignificant impacts and were strongly cross correlated. The proposed approach provides a systematic method that can be used to show the importance of specific DEM input parameters for a given system and then potentially facilitates their selection or calibration. It is concluded that shortening the process for input parameters selection and calibration can help in the implementation of DEM.

  18. Mathcad computer applications predicting antenna parameters from antenna physical dimensions and ground characteristics

    OpenAIRE

    Gerry, Donald D.

    1993-01-01

    Approved for public release; distribution is unlimited. This report provides the documentation for a set of computer applications for the evaluation of antenna parameters. The applications are written for the Mathcad personal computer software for various antenna types listed in the thesis index. Antenna dimen Lieutenant Commander, United States Navy

  19. Clinical evaluation of an ionic tooth brush on oral hygiene status, gingival status, and microbial parameter

    Directory of Open Access Journals (Sweden)

    Deshmukh J

    2006-01-01

    Full Text Available It has long been recognised that the presence of dental plaque leads to gingivitis and periodontal disease, as well as dental caries. Today tooth brushing is the most widely accepted method of removing plaque. Hence this present clinical study was undertaken to evaluate the effectiveness of an ionic toothbrush on oral hygiene status. For this study, 20 dental students in the age group of 18-20 years were included. All the subjects after undergoing dental prophylaxis were then provided with ionic toothbrushes, either active (equipped with lithium battery or inactive (without lithium battery. Plaque index and gingival bleeding index were examined at 7th, 14th, and 21st day. Microbial assessment was done for detection of colony forming units (CFU from the plaque samples which were collected on 0 day and 21st day, both before brushing and after brushing. Results shown a significant reduction in all the parameters and the reduction was more significant in active and inactive ionic toothbrush users. It was concluded that both active and inactive ionic toothbrushes reduced the plaque index and gingival bleeding index scores significantly and active ionic tooth brushes were more effective as compared to inactive ionic toothbrushes. There was no soft tissue trauma following the use of both type of toothbrushes, which showed that ionic toothbrushes were equally safe for regular long-term use.

  20. [Comparison of clinical assessment and invasive evaluation of hemodynamic parameters in septic shock].

    Science.gov (United States)

    Vucić, N; Pilas, V

    1995-06-01

    The authors compare, in this prospective study, the accuracy of their own clinical assessment of hemodynamic parameters and severity of disease with the findings obtained by right heart catheterization in 50 patients with septic shock. The purpose of the study was to determine whether Swan-Ganz catheter insertion was necessary in all patients with septic shock. As soon as the diagnosis was established, the value of pulmonary capillary wedge pressure was estimated, as well as presence or absence of pathological uptake/supply dependency in all patients. The latter is an excellent indicator of severity of disease. The accurate assessment was noted in 27 (54%) patients (1. investigator), and in 30 (60%) patients (2. investigator). The sensitivity of detection of pathological uptake/supply dependency amounted to 53% and 65%; specificity was 73% and 79%, respectively. The therapy was altered in 21 patients (42%) after catheter insertion. The results were tested with chi2-test (p < 0.01). The findings of this study warrant catheter insertion in patients with septic shock. PMID:8649145

  1. Variations of clinical biochemical parameters of laying hens and broiler chickens fed aflatoxin-containing feed.

    Science.gov (United States)

    Fernandez, A; Verde, M T; Gascon, M; Ramos, J; Gomez, J; Luco, D F; Chavez, G

    1994-03-01

    Two groups of 32 laying hens (Hyssex Brown) and two groups of 32 23-day-old (Hybro) broiler chickens were fed 2.5 and 5 parts/10(6) of aflatoxin in their diet for 4, 8, 16 and 32 days; 16 hens and 32 chicks were maintained as control groups (0 parts/10(6)). After the intoxication period, a clearance period was established of 1, 2, 4 and 8 days. Relative weights of liver and kidneys significantly increased in intoxicated hens, but not in broiler chickens. Histological lesions in both types of bird consisted of hepatic cell vacuolation with fatty infiltration. There was a significant decrease (Phens, cholesterol levels were not significantly (P> 0.05) different from control values, but triglyceride levels decreased (PAST) serum levels remained normal, whereas alanino aminotransferase (ALT) activity decreased in both intoxicated groups. The activity of serum lactic dehydrogenase (LDH) and gammaglutamil transferase (GGT) increased significantly. In intoxicated broiler chickens, aflatoxins did not alter (P> 0.05) the biochemical parameters studied, except that the serum calcium concentration was lower in the 5 parts/10(6) group. These data indicated that in intoxicated laying hens, a severe clinical biochemical alteration was produced, and that this together with the hepatic lesions observed in hens and broilers may aid disease diagnosis.

  2. Association between Bone Mineral Density and Clinical Parameters in Traumatic Brain Injury Patients

    Directory of Open Access Journals (Sweden)

    Murat Ersöz,

    2016-04-01

    Full Text Available Objective: Determine the association between the bone mineral density and traumatic brain injury (TBI. Materials and Methods: Twenty-two patients with TBI included to the study. Dual energy X-ray absorptiometry measurements which determines the femur neck and L1-4 vertebrate T scores in patients was performed via Lunar Prodigy DPX system. Clinical parameters such as types of involvements (plegia, upper-lower extremity spasticity values, presence of heterotypic ossification, ambulation levels were determined and their relations with femur neck and L1-4 vertebrate T scores were examined with Mann-Whitney U Test. Results: In the comparison of sub groups of type of plegia (tetraplegic/hemi-paraplegic, lower extremity spasticity values [Ascworth score 0/1-2-3-4, presence of heterotopic ossification no statistically significant (p>0.05 difference was found in the femur neck and L1-4 vertebrate T scores. On the other hand, in the subgroups determined according to ambulatory levels of the patients (confined to bed-wheelchair/ ambulated (orthesis-hand support-independent] significant difference was observed in the femur neck T scores (p=0.044. Femur neck T scores were significantly high in ambulated patients (p=0.044. Conclusion: In TBI cases ambulation level is a factor which significantly affect bone mineral density. It is necessary to ambulate patients with potential as soon as possible and to plan alternative approaches in patient could not be ambulated.

  3. Simple blood tests as predictive markers of disease severity and clinical condition in patients with venous insufficiency.

    Science.gov (United States)

    Karahan, Oguz; Yavuz, Celal; Kankilic, Nazim; Demirtas, Sinan; Tezcan, Orhan; Caliskan, Ahmet; Mavitas, Binali

    2016-09-01

    Chronic venous insufficiency (CVI) is a progressive inflammatory disease. Because of its inflammatory nature, several circulating markers were investigated for predicting disease progression. We aimed to investigate simple inflammatory blood markers as predictors of clinical class and disease severity in patients with CVI. Eighty patients with CVI were divided into three groups according to clinical class (grade 1, 2 and 3) and score of disease severity (mild, moderate and severe). The basic inflammatory blood markers [neutrophil, lymphocyte, mean platelet volume (MPV), white blood cell (WBC), platelet, albumin, D-dimer, fibrinogen, fibrinogen to albumin ratio, and neutrophil to lymphocyte ratio] were investigated in each group. Serum neutrophil, lymphocyte, MPV, platelet count, D-dimer and neutrophil to lymphocyte ratio levels were similar among the groups (P > 0.05). Although the serum WBC levels were significant in the clinical severity groups (P < 0.05), it was useless to separate each severity class. However, albumin, fibrinogen and the fibrinogen to albumin ratio were significant predictors of clinical class and disease severity. Especially, the fibrinogen to albumin ratio was detected as an independent indicator for a clinical class and disease severity with high sensitivity and specificity (75% sensitivity and 87.5% specificity for clinical class and 90% sensitivity and 88.3% specificity for disease severity). Serum fibrinogen and albumin levels can be useful parameters to determine clinical class and disease severity in patients with CVI. Moreover, the fibrinogen to albumin ratio is a more sensitive and specific predictor of the progression of CVI. PMID:26650463

  4. Semen molecular and cellular features: these parameters can reliably predict subsequent ART outcome in a goat model

    Directory of Open Access Journals (Sweden)

    Mereu Paolo

    2009-11-01

    Full Text Available Abstract Currently, the assessment of sperm function in a raw or processed semen sample is not able to reliably predict sperm ability to withstand freezing and thawing procedures and in vivo fertility and/or assisted reproductive biotechnologies (ART outcome. The aim of the present study was to investigate which parameters among a battery of analyses could predict subsequent spermatozoa in vitro fertilization ability and hence blastocyst output in a goat model. Ejaculates were obtained by artificial vagina from 3 adult goats (Capra hircus aged 2 years (A, B and C. In order to assess the predictive value of viability, computer assisted sperm analyzer (CASA motility parameters and ATP intracellular concentration before and after thawing and of DNA integrity after thawing on subsequent embryo output after an in vitro fertility test, a logistic regression analysis was used. Individual differences in semen parameters were evident for semen viability after thawing and DNA integrity. Results of IVF test showed that spermatozoa collected from A and B lead to higher cleavage rates (0

  5. Influence of precision of emission characteristic parameters on model prediction error of VOCs/formaldehyde from dry building material.

    Directory of Open Access Journals (Sweden)

    Wenjuan Wei

    Full Text Available Mass transfer models are useful in predicting the emissions of volatile organic compounds (VOCs and formaldehyde from building materials in indoor environments. They are also useful for human exposure evaluation and in sustainable building design. The measurement errors in the emission characteristic parameters in these mass transfer models, i.e., the initial emittable concentration (C 0, the diffusion coefficient (D, and the partition coefficient (K, can result in errors in predicting indoor VOC and formaldehyde concentrations. These errors have not yet been quantitatively well analyzed in the literature. This paper addresses this by using modelling to assess these errors for some typical building conditions. The error in C 0, as measured in environmental chambers and applied to a reference living room in Beijing, has the largest influence on the model prediction error in indoor VOC and formaldehyde concentration, while the error in K has the least effect. A correlation between the errors in D, K, and C 0 and the error in the indoor VOC and formaldehyde concentration prediction is then derived for engineering applications. In addition, the influence of temperature on the model prediction of emissions is investigated. It shows the impact of temperature fluctuations on the prediction errors in indoor VOC and formaldehyde concentrations to be less than 7% at 23±0.5°C and less than 30% at 23±2°C.

  6. Improving prediction of vapor-liquid equilibrium with modified HVOS-PR-UNIFAC model by revision of group interaction parameters

    Institute of Scientific and Technical Information of China (English)

    XUE Rong-shu; LI Yan-jiao; WANG Xiao-qing; TAN Shi-yu; WEI Shun-an

    2007-01-01

    Quantitative description of vapor-liquid equilibrium is very useful for designing separation processes. In this study, we combined the Peng-Robinson equation and the Huron-Vidal-Orbey-Sandler mixing rule into a modified UNIFAC model for the improvement of predicting vapor-liquid equilibria. The predictions of vapor-liquid equilibria for 62 systems including alcoholalkane, alcohol-benzene, and amine-water systems demonstrate that the revised parameters remarkably improve the prediction accuracy for many systems. Especially for amine-water system, the mean deviation of components decreases from 0.094 to 0.021, and the mean deviation of pressure from 22.45% to 4.41%.

  7. Prediction of Flow Regimes and Thermal Hydraulic Parameters in Two-Phase Natural Circulation by RELAP5 and TRACE Codes

    Directory of Open Access Journals (Sweden)

    Viet-Anh Phung

    2015-01-01

    Full Text Available In earlier study we have demonstrated that RELAP5 can predict flow instability parameters (flow rate, oscillation period, temperature, and pressure in single channel tests in CIRCUS-IV facility. The main goals of this work are to (i validate RELAP5 and TRACE capabilities in prediction of two-phase flow instability and flow regimes and (ii assess the effect of improvement in flow regime identification on code predictions. Most of the results of RELAP5 and TRACE calculation are in reasonable agreement with experimental data from CIRCUS-IV. However, both codes misidentified instantaneous flow regimes which were observed in the test with high speed camera. One of the reasons for the incorrect identification of the flow regimes is the small tube flow regime transition model in RELAP5 and the combined bubbly-slug flow regime in TRACE. We found that calculation results are sensitive to flow regime boundaries of RELAP5 which were modified in order to match the experimental data on flow regimes. Although the flow regime became closer to the experimental one, other predicted thermal hydraulic parameters showed larger discrepancy with the experimental data than with the base case calculations where flow regimes were misidentified.

  8. Prediction and Optimization Approaches for Modeling and Selection of Optimum Machining Parameters in CNC down Milling Operation

    Directory of Open Access Journals (Sweden)

    Asaad A. Abdullah

    2014-04-01

    Full Text Available In this study, we suggested intelligent approach to predict and optimize the cutting parameters when down milling of 45# steel material with cutting tool PTHK- (Ø10*20C*10D*75L -4F-1.0R under dry condition. The experiments were performed statistically according to four factors with three levels in Taguchi experimental design method. Adaptive Neuro-fuzzy inference system is utilized to establish the relationship between the inputs and output parameter exploiting the Taguchi orthogonal array L27. The Particle Swarm Optimized-Adaptive Neuro-Fuzzy Inference System (PSOANFIS is suggested to select the best cutting parameters providing the lower surface through from the experimental data using ANFIS models to predict objective functions. The PSOANFIS optimization approach that improves the surface quality from 0.212 to 0.202, as well as the cutting time is also reduced from 7.5 to 4.78 sec according to machining parameters before and after optimization process. From these results, it can be readily achieved that the advanced study is trusted and suitable for solving other problems encountered in metal cutting operations and the same surface roughness.

  9. A Design of Experiment approach to predict product and process parameters for a spray dried influenza vaccine.

    Science.gov (United States)

    Kanojia, Gaurav; Willems, Geert-Jan; Frijlink, Henderik W; Kersten, Gideon F A; Soema, Peter C; Amorij, Jean-Pierre

    2016-09-25

    Spray dried vaccine formulations might be an alternative to traditional lyophilized vaccines. Compared to lyophilization, spray drying is a fast and cheap process extensively used for drying biologicals. The current study provides an approach that utilizes Design of Experiments for spray drying process to stabilize whole inactivated influenza virus (WIV) vaccine. The approach included systematically screening and optimizing the spray drying process variables, determining the desired process parameters and predicting product quality parameters. The process parameters inlet air temperature, nozzle gas flow rate and feed flow rate and their effect on WIV vaccine powder characteristics such as particle size, residual moisture content (RMC) and powder yield were investigated. Vaccine powders with a broad range of physical characteristics (RMC 1.2-4.9%, particle size 2.4-8.5μm and powder yield 42-82%) were obtained. WIV showed no significant loss in antigenicity as revealed by hemagglutination test. Furthermore, descriptive models generated by DoE software could be used to determine and select (set) spray drying process parameter. This was used to generate a dried WIV powder with predefined (predicted) characteristics. Moreover, the spray dried vaccine powders retained their antigenic stability even after storage for 3 months at 60°C. The approach used here enabled the generation of a thermostable, antigenic WIV vaccine powder with desired physical characteristics that could be potentially used for pulmonary administration. PMID:27523619

  10. Better estimation of protein-DNA interaction parameters improve prediction of functional sites

    Directory of Open Access Journals (Sweden)

    O'Flanagan Ruadhan A

    2008-12-01

    Full Text Available Abstract Background Characterizing transcription factor binding motifs is a common bioinformatics task. For transcription factors with variable binding sites, we need to get many suboptimal binding sites in our training dataset to get accurate estimates of free energy penalties for deviating from the consensus DNA sequence. One procedure to do that involves a modified SELEX (Systematic Evolution of Ligands by Exponential Enrichment method designed to produce many such sequences. Results We analyzed low stringency SELEX data for E. coli Catabolic Activator Protein (CAP, and we show here that appropriate quantitative analysis improves our ability to predict in vitro affinity. To obtain large number of sequences required for this analysis we used a SELEX SAGE protocol developed by Roulet et al. The sequences obtained from here were subjected to bioinformatic analysis. The resulting bioinformatic model characterizes the sequence specificity of the protein more accurately than those sequence specificities predicted from previous analysis just by using a few known binding sites available in the literature. The consequences of this increase in accuracy for prediction of in vivo binding sites (and especially functional ones in the E. coli genome are also discussed. We measured the dissociation constants of several putative CAP binding sites by EMSA (Electrophoretic Mobility Shift Assay and compared the affinities to the bioinformatics scores provided by methods like the weight matrix method and QPMEME (Quadratic Programming Method of Energy Matrix Estimation trained on known binding sites as well as on the new sites from SELEX SAGE data. We also checked predicted genome sites for conservation in the related species S. typhimurium. We found that bioinformatics scores based on SELEX SAGE data does better in terms of prediction of physical binding energies as well as in detecting functional sites. Conclusion We think that training binding site detection

  11. Clinical and Radiographic Factors Predicting Hearing Preservation Rates in Large Vestibular Schwannomas.

    Science.gov (United States)

    Mendelsohn, Daniel; Westerberg, Brian D; Dong, Charles; Akagami, Ryojo

    2016-06-01

    Objectives Postoperative hearing preservation rates for patients with large vestibular schwannomas range from 0 to 43%. The clinical and radiographic factors predicting hearing preservation in smaller vestibular schwannomas are well described; however, their importance in larger tumors is unclear. We investigated factors predicting hearing preservation in large vestibular schwannomas. Design Retrospective review. Setting Quaternary care academic center. Participants A total of 85 patients with unilateral vestibular schwannomas > 3 cm underwent retrosigmoid resections. Main Outcomes Measures Preoperative and postoperative serviceable hearing rates. Methods Clinical and radiographic data including preoperative and postoperative audiograms, preoperative symptoms, magnetic resonance imaging features, and postoperative facial weakness were analyzed. Results Hearing was preserved in 41% of patients (17 of 42) with preoperative serviceable hearing. Hypertension and diabetes increased the likelihood of preoperative hearing loss. Preoperative tinnitus predicted a lower likelihood of hearing preservation. No radiographic factors predicted hearing preservation; however, larger tumor size, smaller fourth ventricular width, and the presence of a cerebrospinal fluid cleft surrounding the tumor predicted postoperative facial weakness. Conclusion Systemic comorbidities may influence hearing loss preoperatively in patients with large vestibular schwannomas. The absence of tinnitus may reflect hearing reserve and propensity for hearing preservation. Preoperative radiographic features did not predict hearing preservation despite some associations with postoperative facial weakness. PMID:27175312

  12. Interleukin-1β level in peri-implant crevicular fluid and its correlation with the clinical and radiographic parameters

    Directory of Open Access Journals (Sweden)

    Aniruddha M Kajale

    2014-01-01

    Full Text Available Background and Objectives : Assessing only the clinical and radiographic parameters for evaluation of dental implants may not be enough as they often reflect extensive inflammatory changes in the periodontal tissues. As peri-implant crevicular fluid (PICF can give us a more prompt and objective measure of the disease activity, the purpose of this case series is to assess the peri-implant health status of single tooth dental implants not only clinically and radiographically but also biochemically. Materials and Methods: Thirteen patients were subjected to dental implants at single edentulous sites using a conventional surgical approach. At baseline, 6 months, and 12 months after implant placement, the clinical and radiographic parameters were recorded. Additionally, IL-1β in PICF was estimated using the ELISA kit at 6 th and 12 th month. Results: The clinical and radiographic parameters differed significantly around the implants at different time intervals with IL-1β levels showing highly significant differences between 6 months (31.79 ± 12.26 pg/μl and 12 months (113.09 ± 51.11 pg/μl. However, Spearman′s correlation coefficient showed no correlation with the clinical and radiographic parameters. Interpretation and Conclusion: Assessment of the various parameters confirmed that all the implants had a healthy peri-implant status. Although the levels of IL-1β in PICF were elevated at the 12 th month, they were well within the healthy range as observed by previous studies. This indicates that IL-1β, a biochemical marker, can be used as an adjunct to clinical and radiographic parameters in the assessment of EARLY inflammatory changes around implants.

  13. Prediction of operational parameters effect on coal flotation using artificial neural network

    Institute of Scientific and Technical Information of China (English)

    E. Jorjani; Sh. Mesroghli; S. Chehreh Chelgani

    2008-01-01

    Artificial neural network procedures were used to predict the combustible value (i.e. 100-Ash) and combustible recovery of coal flotation concentrate in different operational conditions. The pulp density, pH, rotation rate, coal particle size, dosage of collector, frother and conditioner were used as inputs to the network. Feed-forward artificial neural networks with 5-30-2-1 and 7-10-3-1 arrangements were capable to estimate the combustible value and combustible recovery of coal flotation concentrate respectively as the outputs. Quite satisfactory correlations of 1 and 0.91 in training and testing stages for combustible value and of 1 and 0.95 in training and testing stages for combustible recovery prediction were achieved. The proposed neural network models can be used to determine the most advantageous operational conditions for the expected concentrate assay and recovery in the coal flotation process.

  14. Simple measurements for prediction of drug release from polymer matrices - Solubility parameters and intrinsic viscosity

    DEFF Research Database (Denmark)

    Madsen, Claus G; Skov, Anders; Baldursdottir, Stefania;

    2015-01-01

    (dl-lactide-co-glycolide) (PLGA) were cast with bovine serum albumin (BSA) as a model drug using different solvents (acetone, dichloromethane, ethanol and water). The amount of released protein from the different matrices was correlated with the Hildebrand and Hansen solubility parameters of the solvents, and the intrinsic...... viscosity of the polymer solutions. Matrix microstructure was investigated by transmission and scanning electron microscopy (TEM and SEM). Polycaprolactone (PCL) matrices were used in a similar way to support the results for PLGA matrices. RESULTS: The maximum amount of BSA released and the release profile...... from PLGA matrices varied depending on the solvent used for casting. The maximum amount of released BSA decreased with higher intrinsic viscosity, and increased with solubility parameter difference between the solvent and polymer used. The solvent used also had an effect on the matrix microstructure...

  15. Future methane, hydroxyl, and their uncertainties: key climate and emission parameters for future predictions

    OpenAIRE

    Holmes, C. D.; Prather, M. J.; O.A. Søvde; Myhre, G.

    2012-01-01

    Accurate prediction of future methane abundances following a climate scenario requires understanding the lifetime changes driven by anthropogenic emissions, meteorological factors, and chemistry-climate feedbacks. Uncertainty in any of these influences or the underlying processes implies uncertainty in future abundance and radiative forcing. We simulate methane lifetime in three chemical transport models (CTMs) – UCI CTM, GEOS-Chem, and Oslo CTM3 – over the period 1997–2009 and compare the mo...

  16. Hemogram parameters for predicting pulmonary embolism in patients with deep venous thrombosis

    OpenAIRE

    Kaya H; Kurt R

    2015-01-01

    Hakki Kaya, Recep KurtDepartment of Cardiology, Cumhuriyet University Medical School, Sivas, TurkeyWe read the article of Sevuk et al,1 published in the August 2015 issue of your journal, with great interest. The authors concluded that percentage change in serial measurements of mean platelet volume (MPV) and platelet-distribution width (PDW) is valuable in predicting the development of pulmonary thromboembolism in patients with a previous history of deep venous thrombosis (DVT). In a similar...

  17. Parameter importance and uncertainty in predicting runoff pesticide reduction with filter strips.

    Science.gov (United States)

    Muñoz-Carpena, Rafael; Fox, Garey A; Sabbagh, George J

    2010-01-01

    Vegetative filter strips (VFS) are an environmental management tool used to reduce sediment and pesticide transport from surface runoff. Numerical models of VFS such as the Vegetative Filter Strip Modeling System (VFSMOD-W) are capable of predicting runoff, sediment, and pesticide reduction and can be useful tools to understand the effectiveness of VFS and environmental conditions under which they may be ineffective. However, as part of the modeling process, it is critical to identify input factor importance and quantify uncertainty in predicted runoff, sediment, and pesticide reductions. This research used state-of-the-art global sensitivity and uncertainty analysis tools, a screening method (Morris) and a variance-based method (extended Fourier Analysis Sensitivity Test), to evaluate VFSMOD-W under a range of field scenarios. The three VFS studies analyzed were conducted on silty clay loam and silt loam soils under uniform, sheet flow conditions and included atrazine, chlorpyrifos, cyanazine, metolachlor, pendimethalin, and terbuthylazine data. Saturated hydraulic conductivity was the most important input factor for predicting infiltration and runoff, explaining >75% of the total output variance for studies with smaller hydraulic loading rates ( approximately 100-150 mm equivalent depths) and approximately 50% for the higher loading rate ( approximately 280-mm equivalent depth). Important input factors for predicting sedimentation included hydraulic conductivity, average particle size, and the filter's Manning's roughness coefficient. Input factor importance for pesticide trapping was controlled by infiltration and, therefore, hydraulic conductivity. Global uncertainty analyses suggested a wide range of reductions for runoff (95% confidence intervals of 7-93%), sediment (84-100%), and pesticide (43-100%) . Pesticide trapping probability distributions fell between runoff and sediment reduction distributions as a function of the pesticides' sorption. Seemingly

  18. Genetic parameters for methane emissions predicted from milk mid-infrared spectra in dairy cows

    OpenAIRE

    Kandel, Purna Bhadra; Vanrobays, Marie-Laure; Vanlierde, Amélie; Dehareng, Frédéric; Froidmont, Eric; Dardenne, Pierre; Lewis, E; Buckley, F.; Deighton, MH; McParland, S.; Gengler, Nicolas; Soyeurt, Hélène

    2013-01-01

    Genetic selection of low methane (CH4) emitting animals is additive and permanent but the difficulties associated with individual CH4 measurement result in a paucity of records required to estimate genetic variability of CH4 traits. Recently, it was shown that direct quantification of CH4 emissions by mid-infrared spectroscopy (MIR) from milk. The CH4 prediction equation was developed using 452 SF6 CH4 measurements with associated milk spectra and the calibration equation wa...

  19. Prediction of radiation inactivation of presonicated a-amylase in terms of kinetic parameters

    International Nuclear Information System (INIS)

    Full text: In-vitro radiation inactivation of enzyme amylase denies display of optimum enzyme function owing to alterations in active site. Certain extent of enzyme activity seems to be protected in case of radiation inactivated enzyme, prior-exposed to ultrasonic frequencies. The present investigation, exploring trends of changes in kinetic parameters and its dependence on ultrasonic frequencies and gamma doses, will be discussed to highlight the functional status of active site under situation

  20. Computational prediction of the spectroscopic parameters of methanediol, an elusive molecule for interstellar detection

    Energy Technology Data Exchange (ETDEWEB)

    Barrientos, Carmen; Redondo, Pilar; Largo, Antonio [Departamento de Química Física y Química Inorgánica, Facultad de Ciencias, Universidad de Valladolid, Campus Miguel Delibes, Paseo de Belén 7, E-47011 Valladolid (Spain); Martínez, Henar, E-mail: alargo@qf.uva.es [Departamento de Química Orgánica, Escuela de Ingenierías Industriales, Universidad de Valladolid, Campus Esgueva, Paseo del Cauce 59, E-47011 Valladolid (Spain)

    2014-04-01

    The molecular structure of methanediol has been investigated by means of quantum chemical calculations. Two conformers, corresponding to C{sub 2} and C {sub s} symmetries, respectively, were considered. The C{sub 2} conformer is found to lie about 1.7 (at 298 K) or 2.3 (at 0 K) kcal mol{sup –1} below the C {sub s} conformer. Predictions for their rotational constants, vibrational frequencies, IR intensities, and dipole moments have been provided. The lowest-lying isomer has a very low dipole moment, around 0.03 D, whereas the C {sub s} conformer has a relatively high dipole moment, namely, 2.7 D. The barrier for the C {sub s} →C{sub 2} process is predicted to be around 0.7-1 kcal mol{sup –1}. Based on the energetic results the proportion of the C{sub s} conformer is likely to be negligible under low temperature conditions, such as in the interstellar medium. Therefore, it is predicted that detection by radioastronomy of methanediol would be rather unlikely.

  1. Predicting neutrino parameters from SO(3) family symmetry and quark-lepton unification

    CERN Document Server

    King, S F

    2005-01-01

    We show how the neutrino mixing angles and oscillation phase can be predicted from tri-bimaximal neutrino mixing, corrected by charged lepton mixing angles which are related to quark mixing angles via quark-lepton unification. The tri-bimaximal neutrino mixing can naturally originate from the see-saw mechanism via constrained sequential dominance (CSD), where CSD can result from the vacuum alignment of a non-Abelian family symmetry such as SO(3). We construct a realistic model of quark and lepton masses and mixings based on SO(3) family symmetry with quark-lepton unification based on the Pati-Salam gauge group. The atmospheric angle is predicted to be approximately maximal $\\theta_{23}= 45^\\circ$, corrected by the quark mixing angle $\\theta_{23}^{\\mathrm{CKM}}\\approx 2.4^\\circ$, with the correction controlled by an undetermined phase in the quark sector. The solar angle is predicted by the tri-bimaximal complementarity relation: $\\theta_{12}+ \\frac{1}{\\sqrt{2}}\\frac{\\theta_{\\mathrm{C}}}{3} \\cos (\\delta - \\pi)...

  2. Future methane, hydroxyl, and their uncertainties: key climate and emission parameters for future predictions

    Directory of Open Access Journals (Sweden)

    C. D. Holmes

    2012-08-01

    Full Text Available Accurate prediction of future methane abundances following a climate scenario requires understanding the lifetime changes driven by anthropogenic emissions, meteorological factors, and chemistry-climate feedbacks. Uncertainty in any of these influences or the underlying processes implies uncertainty in future abundance and radiative forcing. We simulate methane lifetime in multiple models over the period 1997–2009, adding sensitivity tests to determine key variables that drive the year-to-year variability. Across three atmospheric chemistry and transport models – UCI CTM, GEOS-Chem, and Oslo CTM3 – we find that temperature, water vapor, ozone column, biomass burning and lightning NOx are the dominant sources of interannual changes in methane lifetime. We also evaluate the model responses to forcings that have impacts on decadal time scales, such as methane feedback, and anthropogenic NOx emissions. In general, these different CTMs show similar sensitivities to the driving variables. We construct a parametric model that reproduces most of the interannual variability of each CTM and use it to predict methane lifetime from 1980 through 2100 following a specified emissions and climate scenario (RCP 8.5. The parametric model propagates uncertainties through all steps and provides a foundation for predicting methane abundances in any climate scenario. Our sensitivity tests also enable a new estimate of the methane global warming potential (GWP, accounting for stratospheric ozone effects, including those mediated by water vapor. We estimate the 100-yr GWP to be 32.

  3. Simple radiographic parameter predicts fracturing in metastatic femoral bone lesions: results from a randomised trial

    International Nuclear Information System (INIS)

    Background and purpose: In the randomised Dutch Bone Metastasis Study on the palliative effect of a single fraction (SF) of 8 Gy versus six fractions of 4 Gy on painful bone metastases, 14 fractures occurred in 102 patients with femoral metastases. Purpose of the present study was to identify lesional risk factors for fracturing and to evaluate the influence of the treatment schedule. Material and methods: Pretreatment radiographs of femoral metastases were collected. Three observers separately measured the lesions and scored radiographic characteristics. Results: Ten fractures occurred after median 7 weeks in 44 SF patients (23%) and four after median 20 weeks in 58 multiple fraction patients (7%) (UV, P=0.02). In 110 femoral metastases, an axial cortical involvement >30 mm significantly predicted fracturing (MV, P=0.02). Twelve out of 14 fractured lesions and 40 out of 96 non-fractured metastases had an axial cortical involvement >30 mm (negative predictive value, 97%). When correcting for the axial cortical involvement, the treatment schedule was not predictive anymore (MV, P=0.07). Conclusions: Fracturing of the femur mostly depended on the amount of axial cortical involvement of the metastasis. We recommend to treat femoral metastases with an axial cortical involvement ≤30 mm with an SF of 8 Gy for relief of pain. If the axial cortical involvement is >30 mm, prophylactic surgery should be performed to minimize the risk of pathological fracturing or, if the patient's condition is limited, irradiation to a higher total dose

  4. Predicting Global Solar Radiation Using an Artificial Neural Network Single-Parameter Model

    Directory of Open Access Journals (Sweden)

    Karoro Angela

    2011-01-01

    Full Text Available We used five years of global solar radiation data to estimate the monthly average of daily global solar irradiation on a horizontal surface based on a single parameter, sunshine hours, using the artificial neural network method. The station under the study is located in Kampala, Uganda at a latitude of 0.19°N, a longitude of 32.34°E, and an altitude of 1200 m above sea level. The five-year data was split into two parts in 2003–2006 and 2007-2008; the first part was used for training, and the latter was used for testing the neural network. Amongst the models tested, the feed-forward back-propagation network with one hidden layer (65 neurons and with the tangent sigmoid as the transfer function emerged as the more appropriate model. Results obtained using the proposed model showed good agreement between the estimated and actual values of global solar irradiation. A correlation coefficient of 0.963 was obtained with a mean bias error of 0.055 MJ/m2 and a root mean square error of 0.521 MJ/m2. The single-parameter ANN model shows promise for estimating global solar irradiation at places where monitoring stations are not established and stations where we have one common parameter (sunshine hours.

  5. PERSPECTIVES OF FACTORIAL ANALYSIS IN STUDYING ASSOCIATIONS BETWEEN IMMUNE SYSTEM PARAMETERS AND CLINICAL CHARACTERISTICS IN GASTRIC CANCER

    Directory of Open Access Journals (Sweden)

    I. G. Solovyeva

    2010-01-01

    Full Text Available  When studying functional features of immune system, a lot of quantitative and functional parameters are determined. A multifactorial analysis allows of detecting interdependent immunological parameters and defining them as significant factors. In present study, four factors are revealed, which are associated with certain clinical characteristics of gastric cancer (tumor invasion depth, lymph node status and distant metastases, tumor stage, histological type. The data obtained are of interest, with regard of systemic approach to functional studies of immune functions.

  6. Delayed heart rate recovery after treadmill test: comparison with clinical, exercise and myocardial perfusion parameters

    Energy Technology Data Exchange (ETDEWEB)

    Jeong, S.Y.; Seo, J. H.; Bae, J. H.; Ahn, B. C.; Lee, J.; Lee, K. B.; Chae, S. C [Kyungpook National University Hospital, Daegu (Korea, Republic of)

    2004-07-01

    Imbalance autonomic nervous tone are fundamental risk factors for cardiac death. Recent studies reported abnormal heart rate recovery(HRR) after the treadmill exercise test is a powerful predictor of significant excess mortality. To evaluate HRR as an index of coronary artery disease(CAD). we have compared perfusion defect. 252 patients(147 men) underwent exercise myocardial perfusion imaging were included. The value for HRR was defined as the decrease in heart rate from peak exercise to 1 minute after termination of exercise. Myocardial perfusion imaging was acquired at 1 hour after 740MBq {sup 99m}Tc-MIBI injection using dual head gamma camera(Vertex Plus, ADAC, USA). Summed stress score(SSS) and stress ejection fraction(sEF) were obtained from AutoQUANT program. 23 beats/min was defined as the lowest normal value for HRR. Patients were divided two groups: abnormal HRR(abHRR) and normal HRR(nHRR). We compared clinical(age, sex, pervious CAD history, DM, HTN), exercise test(exercise capacity, duration) and myocardial perfusion parameters(SSS, sEF) between two groups. Mean value of HRR was 50.814.2 beat/min. There were 25 patients(9.9%) with an abHRR. Patient with abHRR were generally in older age(61.59.2 vs 54.48.9yr), were more likely men(72 vs 56.8%), had a higher frequency of DM(16.7 vs 9%), HTN(52 vs 27.6%) and CAD history (28 vs 7%) compared to nHRR. In exercise and myocardial perfusion parameters, abHRR were showed more positive result(60 vs 30%), had short exercise duration(7.0{+-}3.0 vs 9.1{+-}2.7min) and small exercise capacity(7.2{+-}2.3 vs 10.0{+-}2.7Mets) compared to nHRR, had a higher frequency of CAD(76 vs 41.4%) and multivessel disease(25 vs 6.5%), had larger SSS(8.1{+-}8.8 vs 3.7{+-}6.3) and had smaller sEF(47.7{+-}14.3 vs 57.9{+-}10.3%) compared to nHRR. AbHRR was frequently found in patients with CAD, large myocardial perfusion defect and decreased LV function. It seems that the HRR may be considered a reliable index of the severity of CAD.

  7. EHRs Connect Research and Practice: Where Predictive Modeling, Artificial Intelligence, and Clinical Decision Support Intersect

    CERN Document Server

    Bennett, Casey; Selove, Rebecca

    2012-01-01

    Objectives: Electronic health records (EHRs) are only a first step in capturing and utilizing health-related data - the challenge is turning that data into useful information. Furthermore, EHRs are increasingly likely to include data relating to patient outcomes, functionality such as clinical decision support, and genetic information as well, and, as such, can be seen as repositories of increasingly valuable information about patients' health conditions and responses to treatment over time. Methods: We describe a case study of 423 patients treated by Centerstone within Tennessee and Indiana in which we utilized electronic health record data to generate predictive algorithms of individual patient treatment response. Multiple models were constructed using predictor variables derived from clinical, financial and geographic data. Results: For the 423 patients, 101 deteriorated, 223 improved and in 99 there was no change in clinical condition. Based on modeling of various clinical indicators at baseline, the high...

  8. Prediction of postoperative liver regeneration from clinical information using a data-led mathematical model

    Science.gov (United States)

    Yamamoto, Kimiyo N.; Ishii, Masatsugu; Inoue, Yoshihiro; Hirokawa, Fumitoshi; MacArthur, Ben D.; Nakamura, Akira; Haeno, Hiroshi; Uchiyama, Kazuhisa

    2016-01-01

    Although the capacity of the liver to recover its size after resection has enabled extensive liver resection, post-hepatectomy liver failure remains one of the most lethal complications of liver resection. Therefore, it is clinically important to discover reliable predictive factors after resection. In this study, we established a novel mathematical framework which described post-hepatectomy liver regeneration in each patient by incorporating quantitative clinical data. Using the model fitting to the liver volumes in series of computed tomography of 123 patients, we estimated liver regeneration rates. From the estimation, we found patients were divided into two groups: i) patients restored the liver to its original size (Group 1, n = 99); and ii) patients experienced a significant reduction in size (Group 2, n = 24). From discriminant analysis in 103 patients with full clinical variables, the prognosis of patients in terms of liver recovery was successfully predicted in 85–90% of patients. We further validated the accuracy of our model prediction using a validation cohort (prediction = 84–87%, n = 39). Our interdisciplinary approach provides qualitative and quantitative insights into the dynamics of liver regeneration. A key strength is to provide better prediction in patients who had been judged as acceptable for resection by current pragmatic criteria. PMID:27694914

  9. Search for morphological parameters influential for prediction of the mechanical characteristics of an austeno-ferritic duplex stainless steel

    International Nuclear Information System (INIS)

    Duplex stainless steels are commonly used (among others in nuclear industry) for their good properties. However these steels may 'age' in service condition at high temperatures. As their mechanical properties (Charpy impact toughness, resistance to ductile tearing) are often very scattered and tend to decrease after ageing, it has become essential to predict them with high precision. For this, we propose to explain a part of the scattering of the mechanical properties with measurable parameters in relation with the particularly complicated two-phase morphology. The two-phase and bi-percolated morphology of the ferrite and austenite phases is first characterised from the observation of 2D images and from the reconstitution of a 3D image. At the same time we precise the genesis of the formation's mechanisms of the structure (germination and growth of the austenitic phase in the solidified ferri tic one) in relation with the literature. The morphological characteristics so observed corresponding with classical notions of mathematical morphology, - size, covariance, connexity -, we use morphological operators to measure morphological variables by image analysis. We establish then a link between toughness and a parameter measuring fineness of the morphology. The lack of data for very aged steels prevent us from proposing a model of toughness which could take this parameter into consideration at these ageing states, for which it is properly the more crucial to obtain specially precise predictions. A mathematical mo del of the 3D structure of the steel is finally proposed. We choose an homogeneous Markov chain of 3D spatial processes, whose evolution in time mimes the solidification. The morphology of the microstructure is so summarised with 8 parameters. This model is liable to be coupled with a model of toughness, for which it would so enlarge the possibilities of prediction. It could also be used to simulate subsequently the damage and the rupture of two

  10. The effect of differential growth rates across plants on spectral predictions of physiological parameters.

    Directory of Open Access Journals (Sweden)

    Tal Rapaport

    Full Text Available Leaves of various ages and positions in a plant's canopy can present distinct physiological, morphological and anatomical characteristics, leading to complexities in selecting a single leaf for spectral representation of an entire plant. A fortiori, as growth rates between canopies differ, spectral-based comparisons across multiple plants--often based on leaves' position but not age--becomes an even more challenging mission. This study explores the effect of differential growth rates on the reflectance variability between leaves of different canopies, and its implication on physiological predictions made by widely-used spectral indices. Two distinct irrigation treatments were applied for one month, in order to trigger the formation of different growth rates between two groups of grapevines. Throughout the experiment, the plants were physiologically and morphologically monitored, while leaves from every part of their canopies were spectrally and histologically sampled. As the control vines were constantly developing new leaves, the water deficit plants were experiencing growth inhibition, resulting in leaves of different age at similar nodal position across the treatments. This modification of the age-position correlation was characterized by a near infrared reflectance difference between younger and older leaves, which was found to be exponentially correlated (R(2 = 0.98 to the age-dependent area of intercellular air spaces within the spongy parenchyma. Overall, the foliage of the control plant became more spectrally variable, creating complications for intra- and inter-treatment leaf-based comparisons. Of the derived indices, the Structure-Insensitive Pigment Index (SIPI was found indifferent to the age-position effect, allowing the treatments to be compared at any nodal position, while a Normalized Difference Vegetation Index (NDVI-based stomatal conductance prediction was substantially affected by differential growth rates. As various

  11. Future methane, hydroxyl, and their uncertainties: key climate and emission parameters for future predictions

    Directory of Open Access Journals (Sweden)

    C. D. Holmes

    2013-01-01

    Full Text Available Accurate prediction of future methane abundances following a climate scenario requires understanding the lifetime changes driven by anthropogenic emissions, meteorological factors, and chemistry-climate feedbacks. Uncertainty in any of these influences or the underlying processes implies uncertainty in future abundance and radiative forcing. We simulate methane lifetime in three chemical transport models (CTMs – UCI CTM, GEOS-Chem, and Oslo CTM3 – over the period 1997–2009 and compare the models' year-to-year variability against constraints from global methyl chloroform observations. Using sensitivity tests, we find that temperature, water vapor, stratospheric ozone column, biomass burning and lightning NOx are the dominant sources of interannual changes in methane lifetime in all three models. We also evaluate each model's response to forcings that have impacts on decadal time scales, such as methane feedback, and anthropogenic emissions. In general, these different CTMs show similar sensitivities to the driving variables. We construct a parametric model that reproduces most of the interannual variability of each CTM and use it to predict methane lifetime from 1980 through 2100 following a specified emissions and climate scenario (RCP 8.5. The parametric model propagates uncertainties through all steps and provides a foundation for predicting methane abundances in any climate scenario. Our sensitivity tests also enable a new estimate of the methane global warming potential (GWP, accounting for stratospheric ozone effects, including those mediated by water vapor. We estimate the 100-yr GWP to be 32, which is 25% larger than past assessments.

  12. Islet Oxygen Consumption Rate (OCR Dose Predicts Insulin Independence in Clinical Islet Autotransplantation.

    Directory of Open Access Journals (Sweden)

    Klearchos K Papas

    Full Text Available Reliable in vitro islet quality assessment assays that can be performed routinely, prospectively, and are able to predict clinical transplant outcomes are needed. In this paper we present data on the utility of an assay based on cellular oxygen consumption rate (OCR in predicting clinical islet autotransplant (IAT insulin independence (II. IAT is an attractive model for evaluating characterization assays regarding their utility in predicting II due to an absence of confounding factors such as immune rejection and immunosuppressant toxicity.Membrane integrity staining (FDA/PI, OCR normalized to DNA (OCR/DNA, islet equivalent (IE and OCR (viable IE normalized to recipient body weight (IE dose and OCR dose, and OCR/DNA normalized to islet size index (ISI were used to characterize autoislet preparations (n = 35. Correlation between pre-IAT islet product characteristics and II was determined using receiver operating characteristic analysis.Preparations that resulted in II had significantly higher OCR dose and IE dose (p<0.001. These islet characterization methods were highly correlated with II at 6-12 months post-IAT (area-under-the-curve (AUC = 0.94 for IE dose and 0.96 for OCR dose. FDA/PI (AUC = 0.49 and OCR/DNA (AUC = 0.58 did not correlate with II. OCR/DNA/ISI may have some utility in predicting outcome (AUC = 0.72.Commonly used assays to determine whether a clinical islet preparation is of high quality prior to transplantation are greatly lacking in sensitivity and specificity. While IE dose is highly predictive, it does not take into account islet cell quality. OCR dose, which takes into consideration both islet cell quality and quantity, may enable a more accurate and prospective evaluation of clinical islet preparations.

  13. Validation of Occupants’ Behaviour Models for Indoor Quality Parameter and Energy Consumption Prediction

    DEFF Research Database (Denmark)

    Fabi, Valentina; Sugliano, Martina; Andersen, Rune Korsholm;

    2015-01-01

    Occupants’ behaviour related to building control system plays a significant role to achieve thermal comfort and air quality in naturally-ventilated buildings. Generally, the published models of occupant's behavior are not validated, meaning that the predictive power has not yet been tested...... in a dynamic BEPS software and the obtained results in terms of temperature, relative humidity and CO2 concentration were compared to real measurements. Through this comparison it will be possible to verify the accuracy of the implemented behavioral models.The models were able to reproduce the general...

  14. Application of the L-M optimized algorithm to predicting blast vibration parameters

    Institute of Scientific and Technical Information of China (English)

    ZHANG Yi-feng; YAO Dao-ping; XIE Zhai-zhao; YANG Jiang-feng; YE You-quan

    2008-01-01

    @@ Currently, the regression empirical formula with vibration peak as the safety index of single blasting vibration is widely applied in blasting engineering circles throughout the world. Due to complex blasting mechanism and blasting medium environment as well as plural influencing factors, it is difficult that all these factors can be taken into consideration by using one regression empirical formula. In addition, due to the inherent limitations of regression analysis (e.g., requiring good data distribution and large amount of samples), the vibration prediction by empirical formula is not ideal (LI, 1997; CHEN, 2001; ZHANG, 2001).

  15. Seasonal dependence of the "forecast parameter" based on the EIA characteristics for the prediction of Equatorial Spread F (ESF

    Directory of Open Access Journals (Sweden)

    S. V. Thampi

    2008-06-01

    Full Text Available In an earlier study, Thampi et al. (2006 have shown that the strength and asymmetry of Equatorial Ionization Anomaly (EIA, obtained well ahead of the onset time of Equatorial Spread F (ESF have a definite role on the subsequent ESF activity, and a new "forecast parameter" has been identified for the prediction of ESF. This paper presents the observations of EIA strength and asymmetry from the Indian longitudes during the period from August 2005–March 2007. These observations are made using the line of sight Total Electron Content (TEC measured by a ground-based beacon receiver located at Trivandrum (8.5° N, 77° E, 0.5° N dip lat in India. It is seen that the seasonal variability of EIA strength and asymmetry are manifested in the latitudinal gradients obtained using the relative TEC measurements. As a consequence, the "forecast parameter" also displays a definite seasonal pattern. The seasonal variability of the EIA strength and asymmetry, and the "forecast parameter" are discussed in the present paper and a critical value for has been identified for each month/season. The likely "skill factor" of the new parameter is assessed using the data for a total of 122 days, and it is seen that when the estimated value of the "forecast parameter" exceeds the critical value, the ESF is seen to occur on more than 95% of cases.

  16. Association between Clinical and Doppler Echocardiographic Parameters with Sudden Death in Hemodialysis Patients

    Science.gov (United States)

    Barberato, Silvio Henrique; Bucharles, Sérgio Gardano Elias; Barberato, Marcia Ferreira Alves; Pecoits-Filho, Roberto

    2016-01-01

    Background: Sudden cardiac death (SCD) is the leading cause of death in maintenance hemodialysis (HD) patients, but there is little information about underlying risk factors. Objectives: Evaluate the association between clinical and echocardiographic variables with SCD on HD patients. Methods: Retrospective nested case-control study on chronic HD patients who were prospectively followed. The primary endpoint was SCD. Variables were compared by Student t test, Mann-Whitney or Chi-Square, and independent predictors of SCD were evidenced by multivariate logistic regression. Results: We followed 153 patients (50 ± 15 years, 58% men) for 23 ± 14 months and observed 35 deaths, 17 of which were SCD events. When compared to the control group (matched for gender, age, and body mass index) there were no differences regarding time on dialysis, traditional biochemical parameters, blood pressure, smoking, use of cardiovascular protective drugs, ejection fraction, left ventricular dimensions, and diastolic function indices. On the other hand, in the SCD group, we found a higher prevalence of previous heart failure, acute myocardial infarction and diabetes, greater left ventricular mass index, greater left atrial size and lower global myocardial performance. After multivariate logistic regression analysis, diabetes (OR = 2.6; CI = 1.3-7.5; p = 0.023) and left ventricular mass index ≥ 101 g/m2.7 (OR = 1.04; CI = 1.01-1.08; p = 0.028) showed independent association with SCD events. Conclusions: HD patients with diabetes mellitus and left ventricular hypertrophy appear to have the highest risk of SCD. Preventive and therapeutic strategies should be encouraged in addressing these risk factors to minimize the occurrence of SCD in HD patients. PMID:27411094

  17. Site-Dependent Differences in Clinical, Pathohistological, and Molecular Parameters in Metastatic Colon Cancer

    Directory of Open Access Journals (Sweden)

    Christoph Wilmanns, Sandra Steinhauer, Joachim Grossmann, Günther Ruf

    2009-01-01

    Full Text Available The purpose was to develop a metastatic score specific to the hepatic and peritoneal site in colorectal cancer patients from clinical, pathohistological and molecular markers potentially reflecting oncogenic activation (OA or epithelial-mesenchymal transition (EMT, where OA may reflect an activation and EMT the functional loss of certain genes. The primary tumour stage (OA, EMT, lymphonodal stage (OA, the presence of a lymphangiosis carcinomatosa (OA, histological grade (OA, EMT, and immunoblot extraction of E-cadherin (OA, EMT were differentially rated with zero to one or two points due to their potential contribution to each process and the resulting scores were validated in 27 colorectal cancer patients (three patients with pre-malignant adenomas, 16 with primaries and two with local recurrencies, three of which were metastatic to the peritoneum, six metastatic to the liver and two metastatic to both, the liver and the peritoneum, and five with hepatic secondaries, one of which at histology was metastatic to the peritoneum too. As a single parameter only the N-stage significantly contributed to OA (p<0.05. Median OA and EMT scores, however, were 3.5 and 2 in the case of primaries without further spread, 5 and 4 in those nodal positive, 5 and 4 in the case of peritoneal implants, 6 and 2 in the case of liver metastases, and 6.5 and 3 in the case of a simultaneous hepatic and peritoneal spread, respectively. These differences were significant when scores from patients with and without liver metastases (OA, p<0.002 or with peritoneal implants and isolated hepatic spread (EMT, p<0.01 were compared. The results suggest a site-specific contribution of OA and EMT to tumour progression in human colon cancer.

  18. Correlation between nutritional status and clinical parameters among Thalassaemic patients – A study of West Bengal

    Directory of Open Access Journals (Sweden)

    A. Jana

    2016-08-01

    Full Text Available Thalassaemia is the most common monogenic, autosomal recessive hereditary disorder. The severe forms of thalassaemia are associated with chronic transfusion dependent haemolytic anaemia. Normal growth is impeded due to nutritional deficiency, chronic anaemia as well as iron overload. The aim of this study is to focus the nutritional health status of transfusion dependent thalassaemia patients. This is a cross-sectional analysis of the records of the patients registered at Day Care unit of a City Hospital, Kolkata, India. Clinical history of each patient is collected from registered book of the hospital and body weights and height of the patients are taken from day care unit before starting the transfusion. Laboratory parameters like Pretransfusion Haemoglobin (Hb and Periodic Serum Ferritin are noted in respect of each patient. Z score for height, weight and Body Mass Index (BMI is also taken into consideration using WHO reference. Statistical analysis was carried out using Microsoft excel and SPSS16 Software. Out of 117 Bengali speaking patients 84 were from different Hindu caste families and the rest 33 were from the Muslim community. The mean age of studied patients’ population was 10.77 years (range 4 -20years. Major patients (81.1% suffer high level (>1000ng/ml of serum ferritin level due to not proper management of Pretransfusion haemoglobin and as well as not taken regular chelation. About two third (65.8% of studied population are noted to be short stature, 18.8% are thin and 23.9% are very thin (BMI Z score <-3. as well as regular chelation therapy is the central aspects to improve their proper growth Only 3 children are overweight. Height Z scores is significantly co related with mean serum ferritin level. Management of the disease is very important to control the nutritional health status of thalassaemic children. Proper knowledge of iron free food, optimum transfusion as well as regular chelation therapy is the central aspects to

  19. Prediction of human pharmacokinetics using physiologically based modeling: a retrospective analysis of 26 clinically tested drugs.

    Science.gov (United States)

    De Buck, Stefan S; Sinha, Vikash K; Fenu, Luca A; Nijsen, Marjoleen J; Mackie, Claire E; Gilissen, Ron A H J

    2007-10-01

    The aim of this study was to evaluate different physiologically based modeling strategies for the prediction of human pharmacokinetics. Plasma profiles after intravenous and oral dosing were simulated for 26 clinically tested drugs. Two mechanism-based predictions of human tissue-to-plasma partitioning (P(tp)) from physicochemical input (method Vd1) were evaluated for their ability to describe human volume of distribution at steady state (V(ss)). This method was compared with a strategy that combined predicted and experimentally determined in vivo rat P(tp) data (method Vd2). Best V(ss) predictions were obtained using method Vd2, providing that rat P(tp) input was corrected for interspecies differences in plasma protein binding (84% within 2-fold). V(ss) predictions from physicochemical input alone were poor (32% within 2-fold). Total body clearance (CL) was predicted as the sum of scaled rat renal clearance and hepatic clearance projected from in vitro metabolism data. Best CL predictions were obtained by disregarding both blood and microsomal or hepatocyte binding (method CL2, 74% within 2-fold), whereas strong bias was seen using both blood and microsomal or hepatocyte binding (method CL1, 53% within 2-fold). The physiologically based pharmacokinetics (PBPK) model, which combined methods Vd2 and CL2 yielded the most accurate predictions of in vivo terminal half-life (69% within 2-fold). The Gastroplus advanced compartmental absorption and transit model was used to construct an absorption-disposition model and provided accurate predictions of area under the plasma concentration-time profile, oral apparent volume of distribution, and maximum plasma concentration after oral dosing, with 74%, 70%, and 65% within 2-fold, respectively. This evaluation demonstrates that PBPK models can lead to reasonable predictions of human pharmacokinetics. PMID:17620347

  20. Predicting Ovarian Cancer Patients' Clinical Response to Platinum-Based Chemotherapy by Their Tumor Proteomic Signatures.

    Science.gov (United States)

    Yu, Kun-Hsing; Levine, Douglas A; Zhang, Hui; Chan, Daniel W; Zhang, Zhen; Snyder, Michael

    2016-08-01

    Ovarian cancer is the deadliest gynecologic malignancy in the United States with most patients diagnosed in the advanced stage of the disease. Platinum-based antineoplastic therapeutics is indispensable to treating advanced ovarian serous carcinoma. However, patients have heterogeneous responses to platinum drugs, and it is difficult to predict these interindividual differences before administering medication. In this study, we investigated the tumor proteomic profiles and clinical characteristics of 130 ovarian serous carcinoma patients analyzed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), predicted the platinum drug response using supervised machine learning methods, and evaluated our prediction models through leave-one-out cross-validation. Our data-driven feature selection approach indicated that tumor proteomics profiles contain information for predicting binarized platinum response (P drug responses as well as provided insights into the biological processes influencing the efficacy of platinum-based therapeutics. Our analytical approach is also extensible to predicting response to other antineoplastic agents or treatment modalities for both ovarian and other cancers. PMID:27312948

  1. Predicting reoffense in pedophilic child molesters by clinical diagnoses and risk assessment.

    Science.gov (United States)

    Eher, Reinhard; Olver, Mark E; Heurix, Isabelle; Schilling, Frank; Rettenberger, Martin

    2015-12-01

    A Diagnostic and Statistical Manual of Mental Disorders (DSM)-based diagnosis of pedophilia has so far failed to predict sexual reoffense in convicted child molesters, probably because of its broad and unspecific conceptualization. In this study, therefore, we investigated the prognostic value of the subtype exclusive pedophilia and a series of customary risk assessment instruments (SSPI, Static-99, Stable-2007, VRS:SO) and the PCL-R in a sample of prison released pedophilic sexual offenders. First, we examined the convergent validity of risk assessment instruments (N = 261). Then, we calculated the predictive accuracy of the measures and diagnosis for sexual recidivism by ROC analyses and subsequent Cox regression (N = 189). Also, predictive values with more clinical immediacy were calculated (sensitivity, specificity, PPV and NPV). The VRS:SO, the SSPI, and the Static-99 significantly predicted sexual recidivism, as did a diagnosis of exclusive pedophilia. Also, the VRS:SO predicted sexual reoffense significantly better than the Stable-2007, the Static-99/Stable-2007 combined score, and the PCL-R. When used combined, only the VRS:SO and a diagnosis of exclusive pedophilia added incremental validity to each other. Our findings support that the clinical diagnosis of an exclusive pedophilia based on DSM criteria and VRS:SO defined risk factors can reliably discriminate higher from lower risk offenders, even within the select subgroup of pedophilic child molesters. PMID:26146817

  2. Tsunami hazard warning and risk prediction based on inaccurate earthquake source parameters

    Directory of Open Access Journals (Sweden)

    K. Goda

    2015-12-01

    Full Text Available This study investigates the issues related to underestimation of the earthquake source parameters in the context of tsunami early warning and tsunami risk assessment. The magnitude of a very large event may be underestimated significantly during the early stage of the disaster, resulting in the issuance of incorrect tsunami warnings. Tsunamigenic events in the Tohoku region of Japan, where the 2011 tsunami occurred, are focused on as a case study to illustrate the significance of the problems. The effects of biases in the estimated earthquake magnitude on tsunami loss are investigated using a rigorous probabilistic tsunami loss calculation tool that can be applied to a range of earthquake magnitudes by accounting for uncertainties of earthquake source parameters (e.g. geometry, mean slip, and spatial slip distribution. The quantitative tsunami loss results provide with valuable insights regarding the importance of deriving accurate seismic information as well as the potential biases of the anticipated tsunami consequences. Finally, usefulness of rigorous tsunami risk assessment is discussed in defining critical hazard scenarios based on the potential consequences due to tsunami disasters.

  3. Effect of seasonal variation on adult clinical laboratory parameters in Rwanda, Zambia, and Uganda: implications for HIV biomedical prevention trials.

    Directory of Open Access Journals (Sweden)

    Eugene Ruzagira

    Full Text Available To investigate the effect of seasonal variation on adult clinical laboratory parameters in Rwanda, Zambia, and Uganda and determine its implications for HIV prevention and other clinical trials.Volunteers in a cross-sectional study to establish laboratory reference intervals were asked to return for a seasonal visit after the local season had changed from dry to rainy or vice versa. Volunteers had to be clinically healthy, not pregnant and negative for HIV, Hepatitis B and C, and syphilis infection at both visits. At each visit, blood was taken for measurement of hemoglobin, haematocrit, mean corpuscular volume, red blood cells, platelets, total white blood cells (WBC, neutrophils, lymphocytes, monocytes, eosinophils, basophils, CD4/CD8 T cells, aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, direct bilirubin, total bilirubin, total immunoglobulin gamma, total protein, creatinine, total amylase, creatine phosphokinase and lactate dehydrogenase (LDH. Consensus dry season reference intervals were applied to rainy season values (and vice versa and the proportion of 'out-of-range' values determined. Percentage differences between dry and rainy season parameter mean values were estimated.In this cohort of 903 volunteers, less than 10.0% of consensus parameter (except LDH values in one season were "out-of-range" in the other. Twenty-two (22 percent of rainy season LDH values fell outside of the consensus dry season interval with the higher values observed in the rainy season. Variability between consensus seasonal means ranged from 0.0% (total WBC, neutrophils, monocytes, basophils, and direct bilirubin to 40.0% (eosinophils. Within sites, the largest seasonal variations were observed for monocytes (Masaka, 11.5%, LDH (Lusaka, 21.7%, and basophils (Kigali, 22.2%.Seasonality had minimal impact on adult clinical laboratory parameter values in Rwanda, Zambia, and Uganda. Seasonal variation may not be an important factor in the

  4. A novel neural-inspired learning algorithm with application to clinical risk prediction.

    Science.gov (United States)

    Tay, Darwin; Poh, Chueh Loo; Kitney, Richard I

    2015-04-01

    Clinical risk prediction - the estimation of the likelihood an individual is at risk of a disease - is a coveted and exigent clinical task, and a cornerstone to the recommendation of life saving management strategies. This is especially important for individuals at risk of cardiovascular disease (CVD) given the fact that it is the leading causes of death in many developed counties. To this end, we introduce a novel learning algorithm - a key factor that influences the performance of machine learning-based prediction models - and utilities it to develop CVD risk prediction tool. This novel neural-inspired algorithm, called the Artificial Neural Cell System for classification (ANCSc), is inspired by mechanisms that develop the brain and empowering it with capabilities such as information processing/storage and recall, decision making and initiating actions on external environment. Specifically, we exploit on 3 natural neural mechanisms responsible for developing and enriching the brain - namely neurogenesis, neuroplasticity via nurturing and apoptosis - when implementing ANCSc algorithm. Benchmark testing was conducted using the Honolulu Heart Program (HHP) dataset and results are juxtaposed with 2 other algorithms - i.e. Support Vector Machine (SVM) and Evolutionary Data-Conscious Artificial Immune Recognition System (EDC-AIRS). Empirical experiments indicate that ANCSc algorithm (statistically) outperforms both SVM and EDC-AIRS algorithms. Key clinical markers identified by ANCSc algorithm include risk factors related to diet/lifestyle, pulmonary function, personal/family/medical history, blood data, blood pressure, and electrocardiography. These clinical markers, in general, are also found to be clinically significant - providing a promising avenue for identifying potential cardiovascular risk factors to be evaluated in clinical trials. PMID:25576352

  5. On the estimation of stellar parameters with uncertainty prediction from Generative Artificial Neural Networks: application to Gaia RVS simulated spectra

    Science.gov (United States)

    Dafonte, C.; Fustes, D.; Manteiga, M.; Garabato, D.; Álvarez, M. A.; Ulla, A.; Allende Prieto, C.

    2016-10-01

    Aims: We present an innovative artificial neural network (ANN) architecture, called Generative ANN (GANN), that computes the forward model, that is it learns the function that relates the unknown outputs (stellar atmospheric parameters, in this case) to the given inputs (spectra). Such a model can be integrated in a Bayesian framework to estimate the posterior distribution of the outputs. Methods: The architecture of the GANN follows the same scheme as a normal ANN, but with the inputs and outputs inverted. We train the network with the set of atmospheric parameters (Teff, log g, [Fe/H] and [α/ Fe]), obtaining the stellar spectra for such inputs. The residuals between the spectra in the grid and the estimated spectra are minimized using a validation dataset to keep solutions as general as possible. Results: The performance of both conventional ANNs and GANNs to estimate the stellar parameters as a function of the star brightness is presented and compared for different Galactic populations. GANNs provide significantly improved parameterizations for early and intermediate spectral types with rich and intermediate metallicities. The behaviour of both algorithms is very similar for our sample of late-type stars, obtaining residuals in the derivation of [Fe/H] and [α/ Fe] below 0.1 dex for stars with Gaia magnitude Grvs accounts for a number in the order of four million stars to be observed by the Radial Velocity Spectrograph of the Gaia satellite. Conclusions: Uncertainty estimation of computed astrophysical parameters is crucial for the validation of the parameterization itself and for the subsequent exploitation by the astronomical community. GANNs produce not only the parameters for a given spectrum, but a goodness-of-fit between the observed spectrum and the predicted one for a given set of parameters. Moreover, they allow us to obtain the full posterior distribution over the astrophysical parameters space once a noise model is assumed. This can be used for

  6. Prediction of Clinically Relevant Safety Signals of Nephrotoxicity through Plasma Metabolite Profiling

    Directory of Open Access Journals (Sweden)

    W. B. Mattes

    2013-01-01

    Full Text Available Addressing safety concerns such as drug-induced kidney injury (DIKI early in the drug pharmaceutical development process ensures both patient safety and efficient clinical development. We describe a unique adjunct to standard safety assessment wherein the metabolite profile of treated animals is compared with the MetaMap Tox metabolomics database in order to predict the potential for a wide variety of adverse events, including DIKI. To examine this approach, a study of five compounds (phenytoin, cyclosporin A, doxorubicin, captopril, and lisinopril was initiated by the Technology Evaluation Consortium under the auspices of the Drug Safety Executive Council (DSEC. The metabolite profiles for rats treated with these compounds matched established reference patterns in the MetaMap Tox metabolomics database indicative of each compound’s well-described clinical toxicities. For example, the DIKI associated with cyclosporine A and doxorubicin was correctly predicted by metabolite profiling, while no evidence for DIKI was found for phenytoin, consistent with its clinical picture. In some cases the clinical toxicity (hepatotoxicity, not generally seen in animal studies, was detected with MetaMap Tox. Thus metabolite profiling coupled with the MetaMap Tox metabolomics database offers a unique and powerful approach for augmenting safety assessment and avoiding clinical adverse events such as DIKI.

  7. Prediction of vapor-liquid equilibria of binary systems consisting of homogeneous components by using wilson equation with parameters estimated from pure-component properties

    OpenAIRE

    KOBUCHI,Shigetoshi; Takakura, Kei; Yonezawa, Setsuko; Fkuchi, Kenji; ARAI,Yasuhiko

    2013-01-01

    A simple method previously proposed for estimating Wilson parameters on the basis of solubility parameters and molar volumes given from group-contribution methods and normal boiling points of pure substances has been adopted to predict the vapor–liquid equilibria of binary systems consisting of homogeneous components. The prediction performances are examined and discussed.

  8. Physiologically-based pharmacokinetic modeling to predict the clinical pharmacokinetics of monoclonal antibodies.

    Science.gov (United States)

    Glassman, Patrick M; Balthasar, Joseph P

    2016-08-01

    Accurate prediction of the clinical pharmacokinetics of new therapeutic entities facilitates decision making during drug discovery, and increases the probability of success for early clinical trials. Standard strategies employed for predicting the pharmacokinetics of small-molecule drugs (e.g., allometric scaling) are often not useful for predicting the disposition monoclonal antibodies (mAbs), as mAbs frequently demonstrate species-specific non-linear pharmacokinetics that is related to mAb-target binding (i.e., target-mediated drug disposition, TMDD). The saturable kinetics of TMDD are known to be influenced by a variety of factors, including the sites of target expression (which determines the accessibility of target to mAb), the extent of target expression, the rate of target turnover, and the fate of mAb-target complexes. In most cases, quantitative information on the determinants of TMDD is not available during early phases of drug discovery, and this has complicated attempts to employ mechanistic mathematical models to predict the clinical pharmacokinetics of mAbs. In this report, we introduce a simple strategy, employing physiologically-based modeling, to predict mAb disposition in humans. The approach employs estimates of inter-antibody variability in rate processes of extravasation in tissues and fluid-phase endocytosis, estimates for target concentrations in tissues derived through use of categorical immunohistochemical scores, and in vitro measures of the turnover of target and target-mAb complexes. Monte Carlo simulations were performed for four mAbs (cetuximab, figitumumab, dalotuzumab, trastuzumab) directed against three targets (epidermal growth factor receptor, insulin-like growth factor receptor 1, human epidermal growth factor receptor 2). The proposed modeling strategy was able to predict well the pharmacokinetics of cetuximab, dalotuzumab, and trastuzumab at a range of doses, but trended towards underprediction of figitumumab concentrations

  9. Forest Parameter Prediction Using an Image-Based Point Cloud: A Comparison of Semi-ITC with ABA

    Directory of Open Access Journals (Sweden)

    Johannes Rahlf

    2015-11-01

    Full Text Available Image-based point clouds obtained using aerial photogrammetry share many characteristics with point clouds obtained by airborne laser scanning (ALS. Two approaches have been used to predict forest parameters from ALS: the area-based approach (ABA and the individual tree crown (ITC approach. In this article, we apply the semi-ITC approach, a variety of the ITC approach, on an image-based point cloud to predict forest parameters and compare the performance to the ABA. Norwegian National Forest Inventory sample plots on a site in southeastern Norway were used as the reference data. Tree crown objects were delineated using a watershed segmentation algorithm, and explanatory variables were calculated for each tree crown segment. A multivariate kNN model for timber volume, stem density, basal area and quadratic mean diameter with the semi-ITC approach produced RMSEs of 30%, 46%, 25%, 26%, respectively. The corresponding measures for the ABA were 30%, 51%, 26%, 35%, respectively. Univariate kNN models resulted in timber volume RMSEs of 25% for the semi-ITC approach and 22% for the ABA. A non-linear logistic regression model with the ABA produced an RMSE of 23%. Both approaches predicted timber volume with comparable precision and accuracy at the plot level. The multivariate kNN model was slightly more precise with the semi-ITC approach, while biases were larger

  10. External model validation of binary clinical risk prediction models in cardiovascular and thoracic surgery.

    Science.gov (United States)

    Hickey, Graeme L; Blackstone, Eugene H

    2016-08-01

    Clinical risk-prediction models serve an important role in healthcare. They are used for clinical decision-making and measuring the performance of healthcare providers. To establish confidence in a model, external model validation is imperative. When designing such an external model validation study, thought must be given to patient selection, risk factor and outcome definitions, missing data, and the transparent reporting of the analysis. In addition, there are a number of statistical methods available for external model validation. Execution of a rigorous external validation study rests in proper study design, application of suitable statistical methods, and transparent reporting.

  11. [Critical evaluation and predictive value of clinical presentation in out-patients with acute community-acquired pneumonia].

    Science.gov (United States)

    Mayaud, C; Fartoukh, M; Prigent, H; Parrot, A; Cadranel, J

    2006-01-01

    Diagnostic probability of community-acquired pneumonia (CAP) depends on data related to age and clinical and radiological findings. The critical evaluation of data in the literature leads to the following conclusions: 1) the prevalence of CAP in a given population with acute respiratory disease is 5% in outpatients and 10% in an emergency care unit. This could be as low as 2% in young people and even higher than 40% in hospitalized elderly patients; 2) the collection of clinical data is linked to the way the patient is examined and to the expertise of the clinician. The absolute lack of "vital signs" has a good negative predictive value in CAP; presence of unilateral crackles has a good positive predictive value; 3) there is a wide range of X-ray abnormalities: localized alveolar opacities; interstitial opacities, limited of diffused. The greatest radiological difficulties are encountered in old people with disorders including chronic respiratory or cardiac opacities and as a consequence of the high prevalence of bronchopneumonia episodes at this age; 4) among patients with lower respiratory tract (LRT) infections, the blood levels of leukocytes, CRP and procalcitonine are higher in CAP patients, mainly when their disease has a bacterial origin. Since you have not a threshold value reliably demonstrated in large populations with LRT infections or acute respiratory disease, presence or absence of these parameters could only be taken as a slight hint for a CAP diagnosis. PMID:17084571

  12. Prediction of qualitative parameters of slab steel ingot using numerical modelling

    Directory of Open Access Journals (Sweden)

    M. Tkadlečková

    2016-07-01

    Full Text Available The paper describes the verification of casting and solidification of heavy slab ingot weighing 40 t from tool steel by means of numerical modelling with use of a finite element method. The pre-processing, processing and post-processing phases of numerical modelling are outlined. Also, the problems with determination of the thermodynamic properties of materials and with determination of the heat transfer between the individual parts of the casting system are discussed. The final porosity, macrosegregation and the risk of cracks were predicted. The results allowed us to use the slab ingot instead of the conventional heavy steel ingot and to improve the ratio, the chamfer and the external shape of the wall of the new design of the slab ingot.

  13. Body mass index and other anthropometric parameters in patients with diffuse large B-cell lymphoma: physiopathological significance and predictive value in the immunochemotherapy era.

    Science.gov (United States)

    Sarkozy, Clémentine; Camus, Vincent; Tilly, Hervé; Salles, Gilles; Jardin, Fabrice

    2015-07-01

    Diffuse large B-cell lymphoma (DLBCL) is the most common form of aggressive non-Hodgkin lymphoma, accounting for 30-40% of newly diagnosed cases. Obesity is a well-defined risk factor for DLBCL. However, the impact of body mass index (BMI) on DLBCL prognosis is controversial. Recent studies suggest that skeletal muscle wasting (sarcopenia) or loss of fat mass can be detected by computed tomography (CT) images and is useful for predicting the clinical outcome in several types of cancer including DLBCL. Several hypotheses have been proposed to explain the differences in DLBCL outcome according to BMI or weight that include tolerance to treatment, inflammatory background and chemotherapy or rituximab metabolism. In this review, we summarize the available literature, addressing the impact and physiopathological relevance of simple anthropometric tools including BMI and tissue distribution measurements. We also discuss their relationship with other nutritional parameters and their potential role in the management of patients with DLBCL. PMID:25363401

  14. Prediction of changes in important physical parameters during composting of separated animal slurry solid fractions

    DEFF Research Database (Denmark)

    Chowdhury, Md Albarune; de Neergaard, Andreas; Jensen, Lars Stoumann

    2014-01-01

    Solid-liquid separation of animal slurry, with solid fractions used for composting, has gained interest recently. However, efficient composting of separated animal slurry solid fractions (SSFs) requires a better understanding of the process dynamics in terms of important physical parameters...... and their interacting physical relationships in the composting matrix. Here we monitored moisture content, bulk density, particle density and air-filled porosity (AFP) during composting of SSF collected from four commercially available solid-liquid separators. Composting was performed in laboratory-scale reactors...... for 30 days (d) under forced aeration and measurements were conducted on the solid samples at the beginning of composting and at 10-d intervals during composting. The results suggest that differences in initial physical properties of SSF influence the development of compost maximum temperatures (40...

  15. Parameter Identification for a New Circuit Model Aimed to Predict Body Water Volume

    Directory of Open Access Journals (Sweden)

    GHEORGHE, A.-G.

    2012-11-01

    Full Text Available Intracellular and extracellular water volumes in the human body have been computed using a sequence of models starting with a linear first order RC circuit (Cole model and finishing with the De Lorenzo model. This last model employs a fractional order impedance whose parameters are identified using the frequency characteristics of the impedance module and phase, the latter being not unique. While the Cole model has a two octaves frequency validity range, the De Lorenzo model can be used for three decades. A new linear RC model, valid for a three decades frequency range, is proposed. This circuit can be viewed as an extension of the Cole model for a larger frequency interval, unlike similar models proposed by the same authors.

  16. On better estimating and normalizing the relationship between clinical parameters: comparing respiratory modulations in the photoplethysmogram and blood pressure signal (DPOP versus PPV).

    Science.gov (United States)

    Addison, Paul S; Wang, Rui; Uribe, Alberto A; Bergese, Sergio D

    2015-01-01

    DPOP (ΔPOP or Delta-POP) is a noninvasive parameter which measures the strength of respiratory modulations present in the pulse oximeter waveform. It has been proposed as a noninvasive alternative to pulse pressure variation (PPV) used in the prediction of the response to volume expansion in hypovolemic patients. We considered a number of simple techniques for better determining the underlying relationship between the two parameters. It was shown numerically that baseline-induced signal errors were asymmetric in nature, which corresponded to observation, and we proposed a method which combines a least-median-of-squares estimator with the requirement that the relationship passes through the origin (the LMSO method). We further developed a method of normalization of the parameters through rescaling DPOP using the inverse gradient of the linear fitted relationship. We propose that this normalization method (LMSO-N) is applicable to the matching of a wide range of clinical parameters. It is also generally applicable to the self-normalizing of parameters whose behaviour may change slightly due to algorithmic improvements. PMID:25691912

  17. On Better Estimating and Normalizing the Relationship between Clinical Parameters: Comparing Respiratory Modulations in the Photoplethysmogram and Blood Pressure Signal (DPOP versus PPV

    Directory of Open Access Journals (Sweden)

    Paul S. Addison

    2015-01-01

    Full Text Available DPOP (ΔPOP or Delta-POP is a noninvasive parameter which measures the strength of respiratory modulations present in the pulse oximeter waveform. It has been proposed as a noninvasive alternative to pulse pressure variation (PPV used in the prediction of the response to volume expansion in hypovolemic patients. We considered a number of simple techniques for better determining the underlying relationship between the two parameters. It was shown numerically that baseline-induced signal errors were asymmetric in nature, which corresponded to observation, and we proposed a method which combines a least-median-of-squares estimator with the requirement that the relationship passes through the origin (the LMSO method. We further developed a method of normalization of the parameters through rescaling DPOP using the inverse gradient of the linear fitted relationship. We propose that this normalization method (LMSO-N is applicable to the matching of a wide range of clinical parameters. It is also generally applicable to the self-normalizing of parameters whose behaviour may change slightly due to algorithmic improvements.

  18. The effect of sugar-free chewing gum on plaque and clinical parameters of gingival inflammation: a systematic review

    NARCIS (Netherlands)

    R.S. Keukenmeester; D.E. Slot; M.S. Putt; G.A. van der Weijden

    2013-01-01

    Objective The aim of this study was to systematically review the current literature on the clinical effects of sugar-free chewing gum on plaque indices and parameters of gingival inflammation. Material and methods The MEDLINE-PubMed, Cochrane-CENTRAL and EMBASE databases were searched up to 20 April

  19. The effect of medicated, sugar-free chewing gum on plaque and clinical parameters of gingival inflammation: a systematic review

    NARCIS (Netherlands)

    R.S. Keukenmeester; D.E. Slot; M.S. Putt; G.A. van der Weijden

    2014-01-01

    Objective This study aimed to systematically review the present literature to establish the clinical effect of medicated, sugar-free chewing gum on plaque indices and parameters of gingival inflammation. Materials and methods MEDLINE-PubMed, Cochrane CENTRAL and EMBASE databases were searched up to

  20. Rhythmic 24-hour variations of frequently used clinical biochemical parameters in healthy young males - The Bispebjerg study of diurnal variations

    DEFF Research Database (Denmark)

    Sennels, Henriette P; Jørgensen, Henrik L; Gøtze, Jens Peter;

    2012-01-01

    Purpose. To evaluate the influence of time of day on the circulating concentrations of 14 frequently used clinical biochemical parameters in the Bispebjerg study of diurnal variations. Materials and methods. Venous blood samples were obtained under controlled environmental, activities and food...

  1. Predictive Power of the Baseline QRS Complex Duration for Clinical Response to Cardiac Resynchronisation Therapy

    Directory of Open Access Journals (Sweden)

    Ali Kazemisaeid

    2011-02-01

    Full Text Available Background: Determination of predictors of response to cardiac resynchronisation therapy (CRT in patients with moderate to severe heart failure accompanied by a ventricular dyssynchrony can play a major role in improving candidate selection for CRT.Objectives: We evaluated whether the baseline QRS duration could be used to discriminate responders from non-responders to CRT.Methods: Eighty three consecutive patients with moderate to severe heart failure and with successful implantation of a CRT device at our centre were included in the study. QRS durations were measured on 12-lead surface electrocardiogram before and 6 months after implantation of the CRT device, using the widest QRS complex in leads II, V1 and V6. Clinical response to CRT was defined as an improvement of ≥1 grade in NYHA class.Results: Optimal cut-off value to discriminate baseline QRS duration for predicting clinical response to CRT was identified at 152 ms, yielding a sensitivity of 73.3%, a specificity of 56.5% as well as positive and negative predictive values of 81.5% and 44.8%, respectively. The discriminatory pow- er of the baseline QRS duration for response to CRT assessed by the ROC curve was 0.6402 (95% CI: 0.4976 – 0.7829. Baseline QRS duration ≥ 152 ms could effectively predict clinical response to CRT after adjusting for covariates (OR = 3.743, p = 0.017.Conclusion: Baseline QRS duration can effectively predict clinical response to CRT and optimal cut-off value to discriminate baseline QRS duration for response to CRT is 152 ms.

  2. A Clinical Scoring System to Predict the Development of Bronchopulmonary Dysplasia

    OpenAIRE

    Gürsoy, Tuğba; Hayran, Mutlu; Derin, Hatice; Ovalı, Fahri

    2015-01-01

    ObjectiveThis study aims to develop a scoring system for the prediction of bronchopulmonary dysplasia (BPD). MethodsMedical records of 652 infants whose gestational age and birth weight were below 32 weeks and 1,500g, respectively, and who survived beyond 28th postnatal day were reviewed retrospectively. Logistic regression methods were used to determine the clinical and demographic risk factors within the first 72 hours of life associated with BPD, as well as the weights of these factors on ...

  3. Fusion of clinical and stochastic finite element data for hip fracture risk prediction.

    Science.gov (United States)

    Jiang, Peng; Missoum, Samy; Chen, Zhao

    2015-11-26

    Hip fracture affects more than 250,000 people in the US and 1.6 million worldwide per year. With an aging population, the development of reliable fracture risk models is therefore of prime importance. Due to the complexity of the hip fracture phenomenon, the use of clinical data only, as it is done traditionally, might not be sufficient to ensure an accurate and robust hip fracture prediction model. In order to increase the predictive ability of the risk model, the authors propose to supplement the clinical data with computational data from finite element models. The fusion of the two types of data is performed using deterministic and stochastic computational data. In the latter case, uncertainties in loading and material properties of the femur are accounted for and propagated through the finite element model. The predictive capability of a support vector machine (SVM) risk model constructed by combining clinical and finite element data was assessed using a Women׳s Health Initiative (WHI) dataset. The dataset includes common factors such as age and BMD as well as geometric factors obtained from DXA imaging. The fusion of computational and clinical data systematically leads to an increase in predictive ability of the SVM risk model as measured by the AUC metric. It is concluded that the largest gains in AUC are obtained by the stochastic approach. This gain decreases as the dimensionality of the problem increases: a 5.3% AUC improvement was achieved for a 9 dimensional problem involving geometric factors and weight while a 1.3% increase was obtained for a 20 dimensional case including geometric and conventional factors. PMID:26482733

  4. Evaluating clinical abdominal scoring system in predict- ing the necessity of laparotomy in blunt abdominal trauma

    Directory of Open Access Journals (Sweden)

    Erfantalab-Avini Peyman

    2011-06-01

    Full Text Available 【Abstract】 Objectives: Trauma is among the lead- ing causes of death. Medical management of blunt abdomi- nal trauma (BAT relies on judging patients for whom lap- arotomy is mandatory. This study aimed to determine BAT patients’ signs, as well as paraclinical data, and to clarify the accuracy, sensitivity, specificity, positive and negative predictive value of clinical abdominal scoring system (CASS, a new scoring system based on clinical signs, in predicting whether a BAT patient needs laparotomy or not. Methods: Totally 400 patients suspected of BAT that arrived at the emergency department of two university hos- pitals in Tehran from March 20, 2007 to March 19, 2009 were included in this study. They were evaluated for age, sex, type of trauma, systolic blood pressure, Glasgow coma scale (GCS, pulse rate, time of presentation after trauma, abdomi- nal clinical findings, respiratory rate, temperature, hemoglo- bin (Hb concentration, focused abdominal sonography in trauma (FAST and CASS. Results: Our measurements showed that CASS had an accuracy of 94%, sensitivity of 100%, specificity of 88%, positive predictive value of 90% and negative predictive value of 100% in determining the necessity of laparotomy in BAT patients. Moreover, in our analysis, systolic blood pressure, GCS, pulse rate, Hb concentration, time of presen- tation after trauma, abdominal clinical findings and FAST were also shown to be helpful in confirming the need for laparotomy (P<0.05. Conclusion: CASS is a promising scoring system in rapid detection of the need for laparotomy as well as in minimizing auxiliary expense for further evaluation in BAT patients, thus to promote the cost-benefit ratio and accu- racy of diagnosis. Key words: Abdominal injuries; Laparotomy; Patients; Wounds, nonpenetrating

  5. Blood coagulation parameters and platelet indices: changes in normal and preeclamptic pregnancies and predictive values for preeclampsia.

    Directory of Open Access Journals (Sweden)

    Lei Han

    Full Text Available Preeclampsia (PE is an obstetric disorder with high morbidity and mortality rates but without clear pathogeny. The dysfunction of the blood coagulation-fibrinolysis system is a salient characteristic of PE that varies in severity, and necessitates different treatments. Therefore, it is necessary to find suitable predictors for the onset and severity of PE.We aimed to evaluate blood coagulation parameters and platelet indices as potential predictors for the onset and severity of PE.Blood samples from 3 groups of subjects, normal pregnant women (n = 79, mild preeclampsia (mPE (n = 53 and severe preeclampsia (sPE (n = 42, were collected during early and late pregnancy. The levels of coagulative parameters and platelet indices were measured and compared among the groups. The receiver-operating characteristic (ROC curves of these indices were generated, and the area under the curve (AUC was calculated. The predictive values of the selected potential parameters were examined in binary regression analysis.During late pregnancy in the normal pregnancy group, the activated partial thromboplastin time (APTT, prothrombin time (PT, thrombin time (TT and platelet count decreased, while the fibrinogen level and mean platelet volume (MPV increased compared to early pregnancy (p<0.05. However, the PE patients presented with increased APTT, TT, MPV and D-dimer (DD during the third trimester. In the analysis of subjects with and without PE, TT showed the largest AUC (0.743 and high predictive value. In PE patients with different severities, MPV showed the largest AUC (0.671 and ideal predictive efficiency.Normal pregnancy causes a maternal physiological hypercoagulable state in late pregnancy. PE may trigger complex disorders in the endogenous coagulative pathways and consume platelets and FIB, subsequently activating thrombopoiesis and fibrinolysis. Thrombin time and MPV may serve as early monitoring markers for the onset and severity of PE

  6. Support vector machine to predict diesel engine performance and emission parameters fueled with nano-particles additive to diesel fuel

    Science.gov (United States)

    Ghanbari, M.; Najafi, G.; Ghobadian, B.; Mamat, R.; Noor, M. M.; Moosavian, A.

    2015-12-01

    This paper studies the use of adaptive Support Vector Machine (SVM) to predict the performance parameters and exhaust emissions of a diesel engine operating on nanodiesel blended fuels. In order to predict the engine parameters, the whole experimental data were randomly divided into training and testing data. For SVM modelling, different values for radial basis function (RBF) kernel width and penalty parameters (C) were considered and the optimum values were then found. The results demonstrate that SVM is capable of predicting the diesel engine performance and emissions. In the experimental step, Carbon nano tubes (CNT) (40, 80 and 120 ppm) and nano silver particles (40, 80 and 120 ppm) with nanostructure were prepared and added as additive to the diesel fuel. Six cylinders, four-stroke diesel engine was fuelled with these new blended fuels and operated at different engine speeds. Experimental test results indicated the fact that adding nano particles to diesel fuel, increased diesel engine power and torque output. For nano-diesel it was found that the brake specific fuel consumption (bsfc) was decreased compared to the net diesel fuel. The results proved that with increase of nano particles concentrations (from 40 ppm to 120 ppm) in diesel fuel, CO2 emission increased. CO emission in diesel fuel with nano-particles was lower significantly compared to pure diesel fuel. UHC emission with silver nano-diesel blended fuel decreased while with fuels that contains CNT nano particles increased. The trend of NOx emission was inverse compared to the UHC emission. With adding nano particles to the blended fuels, NOx increased compared to the net diesel fuel. The tests revealed that silver & CNT nano particles can be used as additive in diesel fuel to improve complete combustion of the fuel and reduce the exhaust emissions significantly.

  7. The north Jutland county diabetic retinopathy study (NCDRS) 2. Non-ophthalmic parameters and clinically significant macular oedema

    DEFF Research Database (Denmark)

    Knudsen, Lars Loumann; Lervang, Hans-Henrik; Lundbye-Christensen, Søren;

    2007-01-01

    subjects undergoing retinopathy screening in the county of North Jutland. The association between the presence of clinically significant macular oedema and blood-pressure, HbA1c, BMI, age, onset of diabetes, duration of diabetes, blood pressure reducing medication, lipid lowering medication, neuropathy......Background: The influence of non-ophthalmic parameters on the prevalence of clinically significant macular oedema has not been unambiguously established. The present study was initiated with the aim of clarification. Methods: This cross-sectional study comprised 656 type 1 and 328 type 2 diabetic......, and urinary albumin excretion was explored using multiple logistic regression analysis. Findings: We found no significant association between the presence of clinically significant macular oedema and any of the examined parameters in type 1 diabetic subjects. In type 2 diabetic subjects the duration...

  8. Integration of umbilical venous and arterial Doppler flow parameters for prediction of adverse perinatal outcome

    Directory of Open Access Journals (Sweden)

    Hebbar Shripad

    2015-01-01

    Full Text Available Background: Quantification of umbilical vein (UV blood flow rate and umbilical artery Doppler indices might be valuable in assessing fetuses at increased risk of perinatal complications as they receive their supply of oxygen and nutrients through this vessel. Previous studies have indicated that UV blood volume flow rate to umbilical artery pulsatility index (UAPI ratio (venous arterial index [VAI] evaluates both venous and arterial arm of fetal umbilical circulation and hence, can be adopted as a screening tool in management of high risk pregnancy. Objectives: To compare umbilical VAI with adverse perinatal outcome and also to evaluate its efficacy with other flow indices in determining perinatal outcome. Materials and Methods: Various Doppler indices such as normalized blood flow rate in UV (nUV, ml/kg estimated fetal weight/min, VAI (nUV/UAPI, umbilical artery resistance index (RI, UAPI, and systolic diastolic ratio were determined in 103 pregnant women within 2 weeks of the delivery. A risk score was devised using APGAR at 5 min, birth weight, preterm delivery, fetal distress, Neonatal Intensive Care Unit (NICU care, and perinatal death and this score was correlated with antenatal Doppler findings. Results: Subjects with low VAI were found to have a greater association with intrauterine growth restricted fetuses (28.5% and low liquor (35.7%, preterm deliveries (46.4%, lower mean birth weight (2.25 kg, higher NICU admission rates (32.1%. The unfavorable score was noticed in 25.2% of the neonates. They had lower VAI (156 vs. 241, UV diameter (6.2 mm vs. 7.8 mm, UV velocity (16.2 vs. 17.8, nUV (163.7 vs. 206.4, and higher PI (1.3 vs. 0.9. A cut-off of VAI of 105 ml/kg/min had sensitivity of 86.7% and a specificity of 93.5% for predicting poor perinatal outcome. Conclusion: VAI with a cut-off of 105 ml/kg/min can be used as an additional tool along with the other conventional Doppler indices in order to predict adverse fetal outcome.

  9. Pre-stimulation parameters predicting live birth after IVF in the long GnRH agonist protocol

    DEFF Research Database (Denmark)

    Pettersson, Göran; Andersen, Anders Nyboe; Broberg, Per;

    2010-01-01

    This retrospective study aimed to identify novel pre-stimulation parameters associated with live birth in IVF and to develop a model for prediction of the chances of live birth at an early phase of the treatment cycle. Data were collected from a randomized trial in couples with unexplained...... infertility, tubal factor, mild male factor or other reason for infertility. All women (n=731) had undergone an IVF cycle (no intracytoplasmic sperm injection) after stimulation with human menopausal gonadotrophin or follicle-stimulating hormone following the long gonadotrophin-releasing hormone agonist...

  10. Modeling and Predicting AD Progression by Regression Analysis of Sequential Clinical Data

    KAUST Repository

    Xie, Qing

    2016-02-23

    Alzheimer\\'s Disease (AD) is currently attracting much attention in elders\\' care. As the increasing availability of massive clinical diagnosis data, especially the medical images of brain scan, it is highly significant to precisely identify and predict the potential AD\\'s progression based on the knowledge in the diagnosis data. In this paper, we follow a novel sequential learning framework to model the disease progression for AD patients\\' care. Different from the conventional approaches using only initial or static diagnosis data to model the disease progression for different durations, we design a score-involved approach and make use of the sequential diagnosis information in different disease stages to jointly simulate the disease progression. The actual clinical scores are utilized in progress to make the prediction more pertinent and reliable. We examined our approach by extensive experiments on the clinical data provided by the Alzheimer\\'s Disease Neuroimaging Initiative (ADNI). The results indicate that the proposed approach is more effective to simulate and predict the disease progression compared with the existing methods.

  11. Endovascular Treatment of Malignant Superior Vena Cava Syndrome: Results and Predictive Factors of Clinical Efficacy

    Energy Technology Data Exchange (ETDEWEB)

    Fagedet, Dorothee, E-mail: DFagedet@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de medecine interne, Pole Pluridisciplinaire de Medecine (France); Thony, Frederic, E-mail: FThony@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de radiologie et imagerie medicale, Pole d' Imagerie (France); Timsit, Jean-Francois, E-mail: JFTimsit@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de reanimation, Pole Medecine Aiguee Communautaire (France); Rodiere, Mathieu, E-mail: MRodiere@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de radiologie et imagerie medicale, Pole d' Imagerie (France); Monnin-Bares, Valerie, E-mail: v-monnin@chu-montpellier.fr [CHRU Arnaud de Villeneuve, Imagerie Medicale Thoracique Cardiovasculaire (France); Ferretti, Gilbert R., E-mail: GFerretti@chu-grenoble.fr [CHU de Grenoble, Clinique universitaire de radiologie et imagerie medicale, Pole d' Imagerie (France); Vesin, Aurelien; Moro-Sibilot, Denis, E-mail: DMoro.pneumo@chu-grenoble.fr [University Grenoble 1 e Albert Bonniot Institute, Inserm U823 (France)

    2013-02-15

    To demonstrate the effectiveness of endovascular treatment (EVT) with self-expandable bare stents for malignant superior vena cava syndrome (SVCS) and to analyze predictive factors of EVT efficacy. Retrospective review of the 164 patients with malignant SVCS treated with EVT in our hospital from August 1992 to December 2007 and followed until February 2009. Endovascular treatment includes angioplasty before and after stent placement. We used self-expandable bare stents. We studied results of this treatment and looked for predictive factors of clinical efficacy, recurrence, and complications by statistical analysis. Endovascular treatment was clinically successful in 95% of cases, with an acceptable rate of early mortality (2.4%). Thrombosis of the superior vena cava was the only independent factor for EVT failure. The use of stents over 16 mm in diameter was a predictive factor for complications (P = 0.008). Twenty-one complications (12.8%) occurred during the follow-up period. Relapse occurred in 36 patients (21.9%), with effective restenting in 75% of cases. Recurrence of SVCS was significantly increased in cases of occlusion (P = 0.01), initial associated thrombosis (P = 0.006), or use of steel stents (P = 0.004). Long-term anticoagulant therapy did not influence the risk of recurrence or complications. In malignancy, EVT with self-expandable bare stents is an effective SVCS therapy. These results prompt us to propose treatment with stents earlier in the clinical course of patients with SVCS and to avoid dilatation greater than 16 mm.

  12. Microbial functional diversity enhances predictive models linking environmental parameters to ecosystem properties.

    Science.gov (United States)

    Powell, Jeff R; Welsh, Allana; Hallin, Sara

    2015-07-01

    Microorganisms drive biogeochemical processes, but linking these processes to real changes in microbial communities under field conditions is not trivial. Here, we present a model-based approach to estimate independent contributions of microbial community shifts to ecosystem properties. The approach was tested empirically, using denitrification potential as our model process, in a spatial survey of arable land encompassing a range of edaphic conditions and two agricultural production systems. Soil nitrate was the most important single predictor of denitrification potential (the change in Akaike's information criterion, corrected for sample size, ΔAIC(c) = 20.29); however, the inclusion of biotic variables (particularly the evenness and size of denitrifier communities [ΔAIC(c) = 12.02], and the abundance of one denitrifier genotype [ΔAIC(c) = 18.04]) had a substantial effect on model precision, comparable to the inclusion of abiotic variables (biotic R2 = 0.28, abiotic R2 = 0.50, biotic + abiotic R2 = 0.76). This approach provides a valuable tool for explicitly linking microbial communities to ecosystem functioning. By making this link, we have demonstrated that including aspects of microbial community structure and diversity in biogeochemical models can improve predictions of nutrient cycling in ecosystems and enhance our understanding of ecosystem functionality.

  13. A better parameter in predicting insulin resistance: Obesity plus elevated alanine aminotransferase

    Institute of Scientific and Technical Information of China (English)

    Ping-Hao Chen; Jong-Dar Chen; Yu-Cheng Lin

    2009-01-01

    AIM: To investigate the association of obesity and elevated alanine aminotransferase with insulin resistance and compare these factors with metabolic syndrome.METHODS: We enrolled a total of 1308 male workers aged from 22 to 63 years. Data was extracted from the workers’ periodic health check-ups in hospitals. All cases were from the community of northern Taiwan.This was a cross-sectional observational study from July to September in 2004. We grouped all cases into four groups, based on the quartile of homeostasis model assessment. The top fourth quartile group was defined as the group with insulin resistance. We performed multivariate logistic regression analysis for the odds ratio of the risk factors for insulin resistance.RESULTS: Compared with metabolic syndrome, the coexistence of both factors had a 4.3-fold (95% CI: 2.7-6.8) increased risk, which was more than metabolic syndrome with a 3.6-fold (95% CI: 2.6-5.0) increased risk. The two factors had a synergistic effect. The synergistic index of obesity and elevated alanine aminotransferase (ALT) was 2.1 (95% CI: 1.01-4.3).CONCLUSION: Obesity and elevated ALT are associatedwith insulin resistance. The effects are synergistic.Coexistence of them is better than metabolic syndrome in predicting insulin resistance.

  14. BAYESIAN PREDICTION OF GENETIC PARAMETERS IN Eucalyptus globulus CLONES UNDER WATER SUPPLY CONDITIONS

    Directory of Open Access Journals (Sweden)

    Freddy Mora

    2013-06-01

    Full Text Available http://dx.doi.org/10.5902/198050989297A Bayesian analysis of genetic parameters for growth traits at twelve months after planting was carried out in twenty nine Eucalyptus globulus clones in southern Chile. Two different environmental conditions were considered: 1 Non-irrigation and; 2 Plants were irrigated with a localized irrigation system. The Bayesian approach was performed using Gibbs sampling algorithm in a clone-environment interaction model. Inheritability values ​​were high in the water supply condition (posterior mode: H2=0.41, 0.36 and 0.39 for height, diameter and sectional area, respectively, while in the environment without irrigation, the inheritabilities were significantly lower, which was confirmed by the Bayesian credible intervals (95% probability. The posterior mode of the genetic correlation between sites was positive and high for all traits (r=0.7, 0.65 and 0.8, for height, diameter and sectional area, respectively and according to the credible interval, it was statistically different from zero, indicating a non-significant interaction.

  15. Study on meteorological parameters during pre-monsoon period at Trombay for environmental impact predictions

    International Nuclear Information System (INIS)

    Bhabha Atomic Research Centre, Trombay site is characterized by complex topography with approximately 330 meter hill at one side and the Arabian Sea at the other which at the eastern coast of Mumbai. A research reactor (DHRUVA) is located in the almost central part of the BARC site. During the operation of research reactor, it gives rise to the formation of fission product noble gases (FPNGs) and other radionuclides but are retained in the fuel matrix itself. Any minor defects in the fuel matrix may lead to the release of the activity to the environment after the filtration through the bank of the High Efficiency Particulate Activity (HEPA) filters. The various reactor components like shut off rods, pneumatic carrier facilities etc. are cooled by processed air that leads to the formation of activation products like 41Ar, which is discharged through the elevated stack. In case of release of gaseous radioactive effluents to the environment though much below permissible limits, exposure to the public may occur by various pathways. External exposure occurs during the passage of the radioactive plume. The doses at different locations due to dispersion of the released gaseous effluent activity can vary depending on the meteorological conditions and effect of topography. In order to estimate the public exposures due to the plume dispersion, the meteorological parameters like wind speed, wind direction and stability category are essential. The paper presents the conclusions from meteorological data for two consecutive years (2012-2013) for Trombay, Mumbai

  16. Parameters affecting the accuracy of oxide thickness prediction in thin metal-oxide-semiconductor structures

    Science.gov (United States)

    Mohaidat, J. M.; Ahmad-Bitar, Riyad N.

    2004-01-01

    On the basis of the solution of the time dependent Schrödinger equation within the framework of the effective mass theory, a complete quantum mechanical electron tunneling through a biased square potential model with abrupt interfaces was deduced. Barriers of 3 eV height and widths up to 140 Å were investigated. Current density-voltage ( J- V) curves were computed for Al/SiO 2/ n+Si structure. The computed J- V curves exhibited oscillations at applied voltages above (Fowler-Nordheim tunneling) and below (direct tunneling) 3 V. For oxide thickness estimation, the position of the oscillation extrema from this quantum mechanical model were fitted to a wave interference formula and showed excellent agreement for oxide layer widths less than 50 Å. However, a systematic deviation appeared for layers larger than 50 Å. We show that the electron energy distribution at the injection layer and the electron effective mass on layers other than the oxide layer are important parameters for accurate oxide thickness estimation.

  17. Density functional theoretical (DFT) study for the prediction of spectroscopic parameters of ClCCCN

    CERN Document Server

    Varadwaj, P R

    2005-01-01

    DFT and RHF level calculations in conjunction with three different of basis sets have been used to investigate the variations in the bond lengths, dipole moment and rotational constants, IR frequencies, IR intensities and rotational invariants of ClCCCN. The nuclear quadrupole constants of chlorine and nitrogen of ClCCCN have been calculated on the experimental r$_{s}$ structure as well as on the B3PW91/6-311++g(d,p) optimized geometry and are found to be within the scale length of the experimental uncertainty. Linear regression analysis between the B3LYP/6-311++g(d,p) level calculated and experimental B$_{o}$ values have been achieved for ClCCCN and BrCCCN. The slopes and intercepts obtained from the regression analysis were used to calculate the reasonable values of rotational constants of all the rare isotopic species of ClCCCN and BrCCCN as well having standard deviations $\\pm$0.048 MHz and $\\pm$0.015 MHz respectively. All the spectroscopic parameters obtained from DFT calculation shows satisfactory agree...

  18. Microsatellite Instability Predicts Clinical Outcome in Radiation-Treated Endometrioid Endometrial Cancer

    International Nuclear Information System (INIS)

    Purpose: To elucidate whether microsatellite instability (MSI) predicts clinical outcome in radiation-treated endometrioid endometrial cancer (EEC). Methods and Materials: A consecutive series of 93 patients with EEC treated with extrafascial hysterectomy and postoperative radiotherapy was studied. The median clinical follow-up of patients was 138 months, with a maximum of 232 months. Five quasimonomorphic mononucleotide markers (BAT-25, BAT-26, NR21, NR24, and NR27) were used for MSI classification. Results: Twenty-five patients (22%) were classified as MSI. Both in the whole series and in early stages (I and II), univariate analysis showed a significant association between MSI and poorer 10-year local disease-free survival, disease-free survival, and cancer-specific survival. In multivariate analysis, MSI was excluded from the final regression model in the whole series, but in early stages MSI provided additional significant predictive information independent of traditional prognostic and predictive factors (age, stage, grade, and vascular invasion) for disease-free survival (hazard ratio [HR] 3.25, 95% confidence interval [CI] 1.01-10.49; p = 0.048) and cancer-specific survival (HR 4.20, 95% CI 1.23-14.35; p = 0.022) and was marginally significant for local disease-free survival (HR 3.54, 95% CI 0.93-13.46; p = 0.064). Conclusions: These results suggest that MSI may predict radiotherapy response in early-stage EEC.

  19. Clinical picture and risk prediction of short-term mortality in cardiogenic shock

    DEFF Research Database (Denmark)

    Harjola, Veli-Pekka; Lassus, Johan; Sionis, Alessandro;

    2015-01-01

    AIMS: The aim of this study was to investigate the clinical picture and outcome of cardiogenic shock and to develop a risk prediction score for short-term mortality. METHODS AND RESULTS: The CardShock study was a multicentre, prospective, observational study conducted between 2010 and 2012....... Patients with either acute coronary syndrome (ACS) or non-ACS aetiologies were enrolled within 6 h from detection of cardiogenic shock defined as severe hypotension with clinical signs of hypoperfusion and/or serum lactate >2 mmol/L despite fluid resuscitation (n = 219, mean age 67, 74% men). Data...... on clinical presentation, management, and biochemical variables were compared between different aetiologies of shock. Systolic blood pressure was on average 78 mmHg (standard deviation 14 mmHg) and mean arterial pressure 57 (11) mmHg. The most common cause (81%) was ACS (68% ST-elevation myocardial infarction...

  20. Prediction of changes in important physical parameters during composting of separated animal slurry solid fractions.

    Science.gov (United States)

    Chowdhury, Md Albarune; de Neergaard, Andreas; Jensen, Lars Stoumann

    2014-01-01

    Solid-liquid separation of animal slurry, with solid fractions used for composting, has gained interest recently. However, efficient composting of separated animal slurry solid fractions (SSFs) requires a better understanding of the process dynamics in terms of important physical parameters and their interacting physical relationships in the composting matrix. Here we monitored moisture content, bulk density, particle density and air-filled porosity (AFP) during composting of SSF collected from four commercially available solid-liquid separators. Composting was performed in laboratory-scale reactors for 30 days (d) under forced aeration and measurements were conducted on the solid samples at the beginning of composting and at 10-d intervals during composting. The results suggest that differences in initial physical properties of SSF influence the development of compost maximum temperatures (40-70 degreeC). Depending on SSF, total wet mass and volume losses (expressed as % of initial value) were up to 37% and 34%, respectively. After 30 d of composting, relative losses of total solids varied from 17.9% to 21.7% and of volatile solids (VS) from 21.3% to 27.5%, depending on SSF. VS losses in all composts showed different dynamics as described by the first-order kinetic equation. The estimated component particle density of 1441 kg m-3 for VS and 2625 kg m-3 for fixed solids can be used to improve estimates of AFP for SSF within the range tested. The linear relationship between wet bulk density and AFP reported by previous researchers held true for SSF.

  1. Clinical implications of omics and systems medicine: focus on predictive and individualized treatment.

    Science.gov (United States)

    Benson, M

    2016-03-01

    Many patients with common diseases do not respond to treatment. This is a key challenge to modern health care, which causes both suffering and enormous costs. One important reason for the lack of treatment response is that common diseases are associated with altered interactions between thousands of genes, in combinations that differ between subgroups of patients who do or do not respond to a given treatment. Such subgroups, or even distinct disease entities, have been described recently in asthma, diabetes, autoimmune diseases and cancer. High-throughput techniques (omics) allow identification and characterization of such subgroups or entities. This may have important clinical implications, such as identification of diagnostic markers for individualized medicine, as well as new therapeutic targets for patients who do not respond to existing drugs. For example, whole-genome sequencing may be applied to more accurately guide treatment of neurodevelopmental diseases, or to identify drugs specifically targeting mutated genes in cancer. A study published in 2015 showed that 28% of hepatocellular carcinomas contained mutated genes that potentially could be targeted by drugs already approved by the US Food and Drug Administration. A translational study, which is described in detail, showed how combined omics, computational, functional and clinical studies could identify and validate a novel diagnostic and therapeutic candidate gene in allergy. Another important clinical implication is the identification of potential diagnostic markers and therapeutic targets for predictive and preventative medicine. By combining computational and experimental methods, early disease regulators may be identified and potentially used to predict and treat disease before it becomes symptomatic. Systems medicine is an emerging discipline, which may contribute to such developments through combining omics with computational, functional and clinical studies. The aims of this review are to provide

  2. TU-C-12A-09: Modeling Pathologic Response of Locally Advanced Esophageal Cancer to Chemo-Radiotherapy Using Quantitative PET/CT Features, Clinical Parameters and Demographics

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, H; Chen, W; Kligerman, S; D’Souza, W; Suntharalingam, M; Lu, W [University of Maryland School of Medicine, Baltimore, MD (United States); Tan, S [Huazhong University of Science and Technology, Wuhan (China); Kim, G [Duke University, High Point, NC (United States)

    2014-06-15

    Purpose: To develop predictive models using quantitative PET/CT features for the evaluation of tumor response to neoadjuvant chemo-radiotherapy (CRT) in patients with locally advanced esophageal cancer. Methods: This study included 20 patients who underwent tri-modality therapy (CRT + surgery) and had {sup 18}F-FDG PET/CT scans before initiation of CRT and 4-6 weeks after completion of CRT but prior to surgery. Four groups of tumor features were examined: (1) conventional PET/CT response measures (SUVmax, tumor diameter, etc.); (2) clinical parameters (TNM stage, histology, etc.) and demographics; (3) spatial-temporal PET features, which characterize tumor SUV intensity distribution, spatial patterns, geometry, and associated changes resulting from CRT; and (4) all features combined. An optimal feature set was identified with recursive feature selection and cross-validations. Support vector machine (SVM) and logistic regression (LR) models were constructed for prediction of pathologic tumor response to CRT, using cross-validations to avoid model over-fitting. Prediction accuracy was assessed via area under the receiver operating characteristic curve (AUC), and precision was evaluated via confidence intervals (CIs) of AUC. Results: When applied to the 4 groups of tumor features, the LR model achieved AUCs (95% CI) of 0.57 (0.10), 0.73 (0.07), 0.90 (0.06), and 0.90 (0.06). The SVM model achieved AUCs (95% CI) of 0.56 (0.07), 0.60 (0.06), 0.94 (0.02), and 1.00 (no misclassifications). Using spatial-temporal PET features combined with conventional PET/CT measures and clinical parameters, the SVM model achieved very high accuracy (AUC 1.00) and precision (no misclassifications), significantly better than using conventional PET/CT measures or clinical parameters and demographics alone. For groups with a large number of tumor features (groups 3 and 4), the SVM model achieved significantly higher accuracy than the LR model. Conclusion: The SVM model using all features

  3. Modeling Pathologic Response of Esophageal Cancer to Chemoradiation Therapy Using Spatial-Temporal {sup 18}F-FDG PET Features, Clinical Parameters, and Demographics

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Hao [Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland (United States); Tan, Shan [Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland (United States); Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan (China); Chen, Wengen; Kligerman, Seth [Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland (United States); Kim, Grace; D' Souza, Warren D.; Suntharalingam, Mohan [Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland (United States); Lu, Wei, E-mail: wlu@umm.edu [Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland (United States)

    2014-01-01

    Purpose: To construct predictive models using comprehensive tumor features for the evaluation of tumor response to neoadjuvant chemoradiation therapy (CRT) in patients with esophageal cancer. Methods and Materials: This study included 20 patients who underwent trimodality therapy (CRT + surgery) and underwent {sup 18}F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) both before and after CRT. Four groups of tumor features were examined: (1) conventional PET/CT response measures (eg, standardized uptake value [SUV]{sub max}, tumor diameter); (2) clinical parameters (eg, TNM stage, histology) and demographics; (3) spatial-temporal PET features, which characterize tumor SUV intensity distribution, spatial patterns, geometry, and associated changes resulting from CRT; and (4) all features combined. An optimal feature set was identified with recursive feature selection and cross-validations. Support vector machine (SVM) and logistic regression (LR) models were constructed for prediction of pathologic tumor response to CRT, cross-validations being used to avoid model overfitting. Prediction accuracy was assessed by area under the receiver operating characteristic curve (AUC), and precision was evaluated by confidence intervals (CIs) of AUC. Results: When applied to the 4 groups of tumor features, the LR model achieved AUCs (95% CI) of 0.57 (0.10), 0.73 (0.07), 0.90 (0.06), and 0.90 (0.06). The SVM model achieved AUCs (95% CI) of 0.56 (0.07), 0.60 (0.06), 0.94 (0.02), and 1.00 (no misclassifications). With the use of spatial-temporal PET features combined with conventional PET/CT measures and clinical parameters, the SVM model achieved very high accuracy (AUC 1.00) and precision (no misclassifications)—results that were significantly better than when conventional PET/CT measures or clinical parameters and demographics alone were used. For groups with many tumor features (groups 3 and 4), the SVM model achieved significantly higher

  4. Association between a composite score of pain sensitivity and clinical parameters in low-back pain

    DEFF Research Database (Denmark)

    O'Neill, Søren; Manniche, Claus; Graven-Nielsen, Thomas;

    2014-01-01

    A limited number of quantitative sensory pain tests (QST) were selected on the basis of ease of application and interpretation in a clinical setting. QST results were summarized as a composite score on a scale of zero to four which was deemed to facilitate clinical interpretation. The QST set...

  5. INFLUENCE OF PHYSIOTHERAPY ON CLINICAL AND IMMUNOLOGICAL PARAMETERS IN CHILDREN WITH JUVENILE RHEUMATOID ARTHRITIS

    OpenAIRE

    T.L. Nastausheva; L.T. Dmitrieva

    2008-01-01

    Clinical and immunological status has been evaluated in 85 children with juvenile rheumatoid arthritis (RA) before and after physiotherapeutic procedures: electrophoresis with dimexid and magnetotherapy. The control group of 31 children did not follow physiotherapeutic procedures. The following results were fixed: clinical indices and immunological status of children with juvenile rheumatoid arthritis have been changed in a larger degree in case of magnetotherapy.

  6. A novel metric for quantification of homogeneous and heterogeneous tumors in PET for enhanced clinical outcome prediction

    Science.gov (United States)

    Rahmim, Arman; Schmidtlein, C. Ross; Jackson, Andrew; Sheikhbahaei, Sara; Marcus, Charles; Ashrafinia, Saeed; Soltani, Madjid; Subramaniam, Rathan M.

    2016-01-01

    Oncologic PET images provide valuable information that can enable enhanced prognosis of disease. Nonetheless, such information is simplified significantly in routine clinical assessment to meet workflow constraints. Examples of typical FDG PET metrics include: (i) SUVmax, (2) total lesion glycolysis (TLG), and (3) metabolic tumor volume (MTV). We have derived and implemented a novel metric for tumor quantification, inspired in essence by a model of generalized equivalent uniform dose as used in radiation therapy. The proposed metric, denoted generalized effective total uptake (gETU), is attractive as it encompasses the abovementioned commonly invoked metrics, and generalizes them, for both homogeneous and heterogeneous tumors, using a single parameter a. We evaluated this new metric for improved overall survival (OS) prediction on two different baseline FDG PET/CT datasets: (a) 113 patients with squamous cell cancer of the oropharynx, and (b) 72 patients with locally advanced pancreatic adenocarcinoma. Kaplan-Meier survival analysis was performed, where the subjects were subdivided into two groups using the median threshold, from which the hazard ratios (HR) were computed in Cox proportional hazards regression. For the oropharyngeal cancer dataset, MTV, TLG, SUVmax, SUVmean and SUVpeak produced HR values of 1.86, 3.02, 1.34, 1.36 and 1.62, while the proposed gETU metric for a  = 0.25 (greater emphasis on volume information) enabled significantly enhanced OS prediction with HR  =  3.94. For the pancreatic cancer dataset, MTV, TLG, SUVmax, SUVmean and SUVpeak resulted in HR values of 1.05, 1.25, 1.42, 1.45 and 1.52, while gETU at a  = 3.2 (greater emphasis on SUV information) arrived at an improved HR value of 1.61. Overall, the proposed methodology allows placement of differing degrees of emphasis on tumor volume versus uptake for different types of tumors to enable enhanced clinical outcome prediction.

  7. Automated development of artificial neural networks for clinical purposes: Application for predicting the outcome of choledocholithiasis surgery.

    Science.gov (United States)

    Vukicevic, Arso M; Stojadinovic, Miroslav; Radovic, Milos; Djordjevic, Milena; Cirkovic, Bojana Andjelkovic; Pejovic, Tomislav; Jovicic, Gordana; Filipovic, Nenad

    2016-08-01

    Among various expert systems (ES), Artificial Neural Network (ANN) has shown to be suitable for the diagnosis of concurrent common bile duct stones (CBDS) in patients undergoing elective cholecystectomy. However, their application in practice remains limited since the development of ANNs represents a slow process that requires additional expertize from potential users. The aim of this study was to propose an ES for automated development of ANNs and validate its performances on the problem of prediction of CBDS. Automated development of the ANN was achieved by applying the evolutionary assembling approach, which assumes optimal configuring of the ANN parameters by using Genetic algorithm. Automated selection of optimal features for the ANN training was performed using a Backward sequential feature selection algorithm. The assessment of the developed ANN included the evaluation of predictive ability and clinical utility. For these purposes, we collected data from 303 patients who underwent surgery in the period from 2008 to 2014. The results showed that the total bilirubin, alanine aminotransferase, common bile duct diameter, number of stones, size of the smallest calculus, biliary colic, acute cholecystitis and pancreatitis had the best prognostic value of CBDS. Compared to the alternative approaches, the ANN obtained by the proposed ES had better sensitivity and clinical utility, which are considered to be the most important for the particular problem. Besides the fact that it enabled the development of ANNs with better performances, the proposed ES significantly reduced the complexity of ANNs' development compared to previous studies that required manual selection of optimal features and/or ANN configuration. Therefore, it is concluded that the proposed ES represents a robust and user-friendly framework that, apart from the prediction of CBDS, could advance and simplify the application of ANNs for solving a wider range of problems. PMID:27261565

  8. How do alternative root water uptake models affect the inverse estimation of soil hydraulic parameters and the prediction of evapotranspiration?

    Science.gov (United States)

    Gayler, Sebastian; Salima-Sultana, Daisy; Selle, Benny; Ingwersen, Joachim; Wizemann, Hans-Dieter; Högy, Petra; Streck, Thilo

    2016-04-01

    Soil water extraction by roots affects the dynamics and distribution of soil moisture and controls transpiration, which influences soil-vegetation-atmosphere feedback processes. Consequently, root water uptake requires close attention when predicting water fluxes across the land surface, e.g., in agricultural crop models or in land surface schemes of weather and climate models. The key parameters for a successful simultaneous simulation of soil moisture dynamics and evapotranspiration in Richards equation-based models are the soil hydraulic parameters, which describe the shapes of the soil water retention curve and the soil hydraulic conductivity curve. As measurements of these parameters are expensive and their estimation from basic soil data via pedotransfer functions is rather inaccurate, the values of the soil hydraulic parameters are frequently inversely estimated by fitting the model to measured time series of soil water content and evapotranspiration. It is common to simulate root water uptake and transpiration by simple stress functions, which describe from which soil layer water is absorbed by roots and predict when total crop transpiration is decreased in case of soil water limitations. As for most of the biogeophysical processes simulated in crop and land surface models, there exist several alternative functional relationships for simulating root water uptake and there is no clear reason for preferring one process representation over another. The error associated with alternative representations of root water uptake, however, contributes to structural model uncertainty and the choice of the root water uptake model may have a significant impact on the values of the soil hydraulic parameters estimated inversely. In this study, we use the agroecosystem model system Expert-N to simulate soil moisture dynamics and evapotranspiration at three agricultural field sites located in two contrasting regions in Southwest Germany (Kraichgau, Swabian Alb). The Richards

  9. SITE-94. Discrete-feature modelling of the Aespoe Site: 3. Predictions of hydrogeological parameters for performance assessment

    Energy Technology Data Exchange (ETDEWEB)

    Geier, J.E. [Golder Associates AB, Uppsala (Sweden)

    1996-12-01

    A 3-dimensional, discrete-feature hydrological model is developed. The model integrates structural and hydrologic data for the Aespoe site, on scales ranging from semi regional fracture zones to individual fractures in the vicinity of the nuclear waste canisters. Predicted parameters for the near field include fracture spacing, fracture aperture, and Darcy velocity at each of forty canister deposition holes. Parameters for the far field include discharge location, Darcy velocity, effective longitudinal dispersion coefficient and head gradient, flow porosity, and flow wetted surface, for each canister source that discharges to the biosphere. Results are presented in the form of statistical summaries for a total of 42 calculation cases, which treat a set of 25 model variants in various combinations. The variants for the SITE-94 Reference Case model address conceptual and parametric uncertainty related to the site-scale hydrogeologic model and its properties, the fracture network within the repository, effective semi regional boundary conditions for the model, and the disturbed-rock zone around the repository tunnels and shafts. Two calculation cases simulate hydrologic conditions that are predicted to occur during future glacial episodes. 30 refs.

  10. SITE-94. Discrete-feature modelling of the Aespoe Site: 3. Predictions of hydrogeological parameters for performance assessment

    International Nuclear Information System (INIS)

    A 3-dimensional, discrete-feature hydrological model is developed. The model integrates structural and hydrologic data for the Aespoe site, on scales ranging from semi regional fracture zones to individual fractures in the vicinity of the nuclear waste canisters. Predicted parameters for the near field include fracture spacing, fracture aperture, and Darcy velocity at each of forty canister deposition holes. Parameters for the far field include discharge location, Darcy velocity, effective longitudinal dispersion coefficient and head gradient, flow porosity, and flow wetted surface, for each canister source that discharges to the biosphere. Results are presented in the form of statistical summaries for a total of 42 calculation cases, which treat a set of 25 model variants in various combinations. The variants for the SITE-94 Reference Case model address conceptual and parametric uncertainty related to the site-scale hydrogeologic model and its properties, the fracture network within the repository, effective semi regional boundary conditions for the model, and the disturbed-rock zone around the repository tunnels and shafts. Two calculation cases simulate hydrologic conditions that are predicted to occur during future glacial episodes. 30 refs

  11. Clinical signs of pneumonia in children: association with and prediction of diagnosis by fuzzy sets theory

    Directory of Open Access Journals (Sweden)

    Pereira J.C.R.

    2004-01-01

    Full Text Available The present study compares the performance of stochastic and fuzzy models for the analysis of the relationship between clinical signs and diagnosis. Data obtained for 153 children concerning diagnosis (pneumonia, other non-pneumonia diseases, absence of disease and seven clinical signs were divided into two samples, one for analysis and other for validation. The former was used to derive relations by multi-discriminant analysis (MDA and by fuzzy max-min compositions (fuzzy, and the latter was used to assess the predictions drawn from each type of relation. MDA and fuzzy were closely similar in terms of prediction, with correct allocation of 75.7 to 78.3% of patients in the validation sample, and displaying only a single instance of disagreement: a patient with low level of toxemia was mistaken as not diseased by MDA and correctly taken as somehow ill by fuzzy. Concerning relations, each method provided different information, each revealing different aspects of the relations between clinical signs and diagnoses. Both methods agreed on pointing X-ray, dyspnea, and auscultation as better related with pneumonia, but only fuzzy was able to detect relations of heart rate, body temperature, toxemia and respiratory rate with pneumonia. Moreover, only fuzzy was able to detect a relationship between heart rate and absence of disease, which allowed the detection of six malnourished children whose diagnoses as healthy are, indeed, disputable. The conclusion is that even though fuzzy sets theory might not improve prediction, it certainly does enhance clinical knowledge since it detects relationships not visible to stochastic models.

  12. Acute pyelonephritis: role of enhanced CT scan in the prediction of clinical outcome

    Energy Technology Data Exchange (ETDEWEB)

    Jo, Byung June; Kim, Ki Whang; Yu, Jeong Sik; Kim, Jai Keun; Yoon, Sang Wook; Ha, Sung Kyu; Park, Chong Hoon [Yonsei Univ. College of Medicine, Seoul (Korea, Republic of)

    1997-04-01

    To correlate the CT findings of acute pyelonephritis with its outcome and with clinical data. Thirty five contrast enhanced CT scans in patients diagnosed as suffering from acute pyelonephritis were retrospectively analyzed. Findings based on the morphology of perfusion defect in the renal parenchyma were classified as normal, focal wedge, multifocal wedge, focal mass, or mixed form composed of wedge and mass. These findings were correlated with clinical data such as degree of fever, leukocytosis, the period after antibiotic treatment during which fever was reduced, and the presence of pyuria in each group Analysis was then performed. Perfusion defects were seen in 23 of 35 cases, and their morphology was classified as follow; focal wedge (n=2), multifocal wedge (n=8), focal mass (n=4), and mixed form (n=9). Twelve cases (34.3%) showed no perfusion defect. The duration of fever was significantly prolonged in patients with focal mass form (p < .05). There was no significant correlation between the morphology of perfusion defect, bilaterality, and other clinical factors. The present study shows that the clinical course of the focal mass form of perfusion defect, as seen on CT, is different from that of other types. CT could be effective in predicting clinical progress and the outcome of treatment in cases of acute pyelonephritis.

  13. Non-Responders to Intravenous Immunoglobulin and Coronary Artery Dilatation in Kawasaki Disease: Predictive Parameters in Korean Children

    Science.gov (United States)

    Kim, Bo Young; Kim, Dongwan; Kim, Yong Hyun; Ryoo, Eell; Sun, Yong Han; Jeon, In-sang; Jung, Mi-Jin; Cho, Hye Kyung; Tchah, Hann; Choi, Deok Young

    2016-01-01

    Background and Objectives In Kawasaki disease (KD), high dose intravenous immunoglobulin (IVIG) significantly lowers the coronary complications. However, some patients either do not respond to initial therapy or develop coronary complications. We aimed to identify the predictive factors for unresponsiveness to initial IVIG therapy and coronary artery dilatation (CAD; defined by Z-score≥2.5) in the acute phase and convalescent phase. Subjects and Methods A retrospective review was conducted of 703 patients with KD, admitted to Gachon University Gil Medical Center between January 2005 and June 2013. The patients were divided into two groups—IVIG responders vs. non-responders—based on the IVIG treatments, and presence of fever after treatment. Further, these groups were divided into two subgroups based on their CAD. Results Among the 703 patients with KD, the rate of non-responders to initial IVIG was 16.8%. Serum total bilirubin, platelet count, and neutrophil proportion were independent predictive parameters of unresponsiveness (p<0.05). CAD was found in 234 patients (33.3%) in the acute phase, and in 32 patients (4.6%) in the convalescent phase. Male gender, fever duration, serum C-reactive protein, and white blood cell count were related to CAD (p<0.05). CAD was detected more frequently in non-responders than in the responders (47.5% vs. 31.5%, p=0.001). Kobayashi, Egami, and Sano scoring systems applied to our study population reflected low sensitivities (28.0-33.9%). Conclusion Several independent parameters were related to unresponsiveness to the initial IVIG or CAD. These parameters might be helpful in establishing more focused and careful monitoring of high-risk KD patients in Korea.

  14. Evaluation of several FDG PET parameters for prediction of soft tissue tumour grade at primary diagnosis and recurrence

    Energy Technology Data Exchange (ETDEWEB)

    Fendler, Wolfgang P. [Ludwig-Maximilians-University of Munich, Department of Nuclear Medicine, Munich (Germany); Department of Nuclear Medicine, Munich (Germany); Chalkidis, Rebecca P.; Ilhan, Harun [Ludwig-Maximilians-University of Munich, Department of Nuclear Medicine, Munich (Germany); Knoesel, Thomas [Ludwig-Maximilians-University of Munich, Institute of Pathology, Munich (Germany); Herrmann, Ken [Julius-Maximilians-University of Wuerzburg, Department of Nuclear Medicine, Wuerzburg (Germany); Issels, Rolf D.; Lindner, Lars H. [Ludwig-Maximilians-University of Munich, Department of Internal Medicine III, Munich (Germany); Ludwig-Maximilians-University of Munich, Comprehensive Cancer Center, Munich (Germany); Bartenstein, Peter [Ludwig-Maximilians-University of Munich, Department of Nuclear Medicine, Munich (Germany); Ludwig-Maximilians-University of Munich, Comprehensive Cancer Center, Munich (Germany); Cyran, Clemens C. [Ludwig-Maximilians-University of Munich, Department of Clinical Radiology, Munich (Germany); Hacker, Marcus [Vienna General Hospital, Department of Nuclear Medicine, Vienna (Austria)

    2015-08-15

    This study evaluates the diagnostic accuracy of SUV-based parameters derived from [{sup 18} F]-2-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) in order to optimize non-invasive prediction of soft tissue tumour (STT) grade. One hundred and twenty-nine lesions from 123 patients who underwent FDG-PET for primary staging (n = 79) or assessment of recurrence (n = 44) of STT were analyzed retrospectively. Histopathology was the reference standard for tumour grading. Absolute values and tumour-to-liver ratios of several standardized uptake value (SUV) parameters were correlated with tumour grading. At primary diagnosis SUV{sub max}, SUV{sub peak}, SUV{sub max}/SUV{sub liver} and SUV{sub peak}/SUV{sub liver} showed good correlation with tumour grade. SUV{sub peak} (area under the receiver-operating-characteristic, AUC-ROC: 0.82) and SUV{sub peak}/SUV{sub liver} (AUC-ROC: 0.82) separated best between low grade (WHO intermediate, grade 1 sarcoma, and low risk gastrointestinal stromal tumours, GISTs) and high grade (grade 2/3 sarcoma and intermediate/high risk GISTs) lesions: optimal threshold for SUV{sub peak}/SUV{sub liver} was 2.4, which resulted in a sensitivity of 79 % and a specificity of 81 %. At disease recurrence, the AUC-ROC was <0.75 for each parameter. A tumour SUV{sub peak} of at least 2.4 fold mean liver uptake predicts high grade histopathology with good diagnostic accuracy at primary staging. At disease recurrence, FDG-PET does not reliably separate high and low grade lesions. (orig.)

  15. Effects Of Music Therapy On Clinical And Biochemical Parameters Of Metabolic Syndrome

    Directory of Open Access Journals (Sweden)

    Rajnee

    2011-12-01

    Full Text Available Background: Music therapy is a new approach being used for the management of metabolic abnormalities and stress related illness.Objective: To study the effect of Music therapy on various clinical and biochemical parameters of Metabolic Syndrome.Methods: This cross sectional study was carried out on 100 patients of metabolic syndrome selected randomly. These patients were divided into two equal groups after age, sex adjustment. In control group (group I 50 patients underwent the conventional treatment. 50 patients in study group were treated with supervised music protocol along with conventional treatment. The Body Mass Index, ;Waist-Hip ratio, Blood pressure, Fasting blood sugar were monitored weekly while HbA1c and lipid profile were determined at the baseline and after three months of exposure to music therapy. Statistical analysis was performed by employing student t- test.Results: In the study group there was a significant decrease in BMI (27.18±5.02 to 25.44±3.49 kg/m2, p<0.05, waist hip ratio (0.95±0.05 to 0.93±0.05 cm, p<0.05, Fasting blood sugar (196.00±47.80mg/ dl to152.00±16.19mg/dl , p<0.001, HbA1c (8.41±1.31% to 7.08±0.78 % p<0.001, Systolic Blood Pressure (151.00±12.10 to 136±9.04 mmHg p<0.001, Diastolic Blood Pressure (94±4.80 to 86.44±3.16 mmHg, p<0.01, Mean serum cholesterol (257.80±18.92 to 229.12±17.82mg/dl, p<0.001 and triglycerides (180.86±14.04 to 136.50±8.92mg/dl, p<0.001, LDL (167.97±14.40 to 140.20±15.41mg/dl, p<0.001, and VLDL (33.60±2.88 to 28.04±3.08mg/dl, p<0.001 and increase in HDL (33.32±3.38 to 39.71±3.41mg/dl, p<0.001, when compared with those of control group not receiving the music therapy along with the conventional treatment.Conclusion: The promising outcomes of Music therapy showed that it may be considered as a useful adjunct to conventional treatment in management of the metabolic syndrome. This study advocates music therapy to establish it from a general well being concepts to a

  16. Application of Optimized Neural Network Models for Prediction of Nuclear Magnetic Resonance Parameters in Carbonate Reservoir Rocks

    Directory of Open Access Journals (Sweden)

    Javad Ghiasi-Freez

    2015-05-01

    Full Text Available Neural network models are powerful tools for extracting the underlying dependency of a set of input/output data. However, the mentioned tools are in danger of sticking in local minima. The present study went to step forward by optimizing neural network models using three intelligent optimization algorithms, including genetic algorithm (GA, particle swarm optimization (PSO, and ant colony (AC, to eliminate the risk of being exposed to local minima. This strategy was capable of significantly improving the accuracy of a neural network by optimizing network parameters such as weights and biases. Nuclear magnetic resonance (NMR log measures some of the most useful characteristics of reservoir rock; the capabilities of the optimized models were used for prediction of nuclear magnetic resonance (NMR log parameters in a carbonate reservoir rock of Iran. Conventional porosity logs, which are the easily accessible tools compared to NMR log’s parameters, were introduced to the models as inputs while free fluid porosity and permeability, which were measured by NMR log, are desire outputs. The performance of three optimized models was verified by some unseen test data. The results show that PSO-based network and ACO-based network is the best and poorest method, respectively, in terms of accuracy; however, the convergence time of GA-based model is considerably smaller than PSO-based and GA-based models.

  17. Safety core parameters prediction in research reactors using artificial neural networks: A comparative study of various learning algorithms

    International Nuclear Information System (INIS)

    In recent years, Artificial Neural Networks (ANNs) were applied successfully as an advanced and promising tool for simulating several reactor physics parameters in nuclear engineering applications. The main objective in using such Artificial Intelligent (AI) methods, in the field of nuclear engineering, is to develop simple and 1st estimate models capable of simulating adequately, with reasonable error, important reactor physics parameters in relatively short time comparatively to time consuming and cumbersome reactor physics computer codes. The feasibility of this application has been demonstrated through a previous work done for a typical benchmark 10 Mw IAEA LEU (Low Enriched Uranium) core research reactor, using an adaptive learning rate procedure in a typical back-propagation algorithm in the training process. However, even tough the predictive results achieved are within ±0.7% for Keff and within ±8.5% for Pmax, the convergence time spent during the training phase were of about 36 and 24 hours, respectively for both cited parameters, on a small computational system (300 Mhz Pentium II PC). Hence, this paper suggests one of the suitable ways explored to speed up the training process and to improve neural networks performances by carrying out a comprehensive sensitivity studies on an iterative and multistage calculation process using Neural Network MATLAB Toolbox

  18. Combined Computational Approach Based on Density Functional Theory and Artificial Neural Networks for Predicting The Solubility Parameters of Fullerenes.

    Science.gov (United States)

    Perea, J Darío; Langner, Stefan; Salvador, Michael; Kontos, Janos; Jarvas, Gabor; Winkler, Florian; Machui, Florian; Görling, Andreas; Dallos, Andras; Ameri, Tayebeh; Brabec, Christoph J

    2016-05-19

    The solubility of organic semiconductors in environmentally benign solvents is an important prerequisite for the widespread adoption of organic electronic appliances. Solubility can be determined by considering the cohesive forces in a liquid via Hansen solubility parameters (HSP). We report a numerical approach to determine the HSP of fullerenes using a mathematical tool based on artificial neural networks (ANN). ANN transforms the molecular surface charge density distribution (σ-profile) as determined by density functional theory (DFT) calculations within the framework of a continuum solvation model into solubility parameters. We validate our model with experimentally determined HSP of the fullerenes C60, PC61BM, bisPC61BM, ICMA, ICBA, and PC71BM and through comparison with previously reported molecular dynamics calculations. Most excitingly, the ANN is able to correctly predict the dispersive contributions to the solubility parameters of the fullerenes although no explicit information on the van der Waals forces is present in the σ-profile. The presented theoretical DFT calculation in combination with the ANN mathematical tool can be easily extended to other π-conjugated, electronic material classes and offers a fast and reliable toolbox for future pathways that may include the design of green ink formulations for solution-processed optoelectronic devices. PMID:27070101

  19. Can dosimetric parameters predict acute hematologic toxicity in rectal cancer patients treated with intensity-modulated pelvic radiotherapy?

    International Nuclear Information System (INIS)

    To identify dosimetric parameters associated with acute hematologic toxicity (HT) in rectal cancer patients undergoing concurrent chemotherapy and intensity-modulated pelvic radiotherapy. Ninety-three rectal cancer patients receiving concurrent capecitabine and pelvic intensity-modulated radiation therapy (IMRT) were analyzed. Pelvic bone marrow (PBM) was contoured for each patient and divided into three subsites: lumbosacral spine (LSS), ilium, and lower pelvis (LP). The volume of each site receiving 5–40 Gy (V 5, V10, V15, V20, V30, and V40, respectively) as well as patient baseline clinical characteristics was calculated. The endpoint for hematologic toxicity was grade ≥ 2 (HT2+) leukopenia, neutropenia, anemia or thrombocytopenia. Logistic regression was used to analyze correlation between dosimetric parameters and grade ≥ 2 hematologic toxicity. Twenty-four in ninety-three patients experienced grade ≥ 2 hematologic toxicity. Only the dosimetric parameter V40 of lumbosacral spine was correlated with grade ≥ 2 hematologic toxicity. Increased pelvic lumbosacral spine V40 (LSS-V40) was associated with an increased grade ≥ 2 hematologic toxicity (p = 0.041). Patients with LSS-V40 ≥ 60 % had higher rates of grade ≥ 2 hematologic toxicity than did patients with lumbosacral spine V40 < 60 % (38.3 %, 18/47 vs.13 %, 6/46, p =0.005). On univariate and multivariate logistic regression analysis, lumbosacral spine V40 and gender was also the variable associated with grade ≥ 2 hematologic toxicity. Female patients were observed more likely to have grade ≥ 2 hematologic toxicity than male ones (46.9 %, 15/32 vs 14.8 %, 9/61, p =0.001). Lumbosacral spine -V40 was associated with clinically significant grade ≥ 2 hematologic toxicity. Keeping the lumbosacral spine -V40 < 60 % was associated with a 13 % risk of grade ≥ 2 hematologic toxicity in rectal cancer patients undergoing concurrent chemoradiotherapy

  20. Effects of organohalogen pollutants on haematological and urine clinical-chemical parameters in Greenland sledge dogs (Canis familiaris)

    DEFF Research Database (Denmark)

    Sonne, Christian; Dietz, Rune; Kirkegaard, Maja;

    2008-01-01

    and urine clinical-chemical parameters were measured and compared between the bitches and pups form the control and exposed cohorts. Based on existing reference intervals, Arctic mammals may have blood clinical-chemical endpoint levels that differ from comparable species at lower latitudes. The cortisol......:05) in the control group, while glucose was signi.cantly highest (ANCOVA: po0:05) in the exposed group. Furthermore, the blood cholesterol levels indicate that exposure via the diet to marine mammal blubber has a preventive effect on the development of cardiovascular diseases. We therefore suggest...

  1. INFLUENCE OF PHYSIOTHERAPY ON CLINICAL AND IMMUNOLOGICAL PARAMETERS IN CHILDREN WITH JUVENILE RHEUMATOID ARTHRITIS

    Directory of Open Access Journals (Sweden)

    T.L. Nastausheva

    2008-12-01

    Full Text Available Clinical and immunological status has been evaluated in 85 children with juvenile rheumatoid arthritis (RA before and after physiotherapeutic procedures: electrophoresis with dimexid and magnetotherapy. The control group of 31 children did not follow physiotherapeutic procedures. The following results were fixed: clinical indices and immunological status of children with juvenile rheumatoid arthritis have been changed in a larger degree in case of magnetotherapy.

  2. Predicting clinically unrecognized coronary artery disease: use of two- dimensional echocardiography

    Directory of Open Access Journals (Sweden)

    Nagueh Sherif F

    2009-03-01

    Full Text Available Abstract Background 2-D Echo is often performed in patients without history of coronary artery disease (CAD. We sought to determine echo features predictive of CAD. Methods 2-D Echo of 328 patients without known CAD performed within one year prior to stress myocardial SPECT and angiography were reviewed. Echo features examined were left ventricular and atrial enlargement, LV hypertrophy, wall motion abnormality (WMA, LV ejection fraction (EF 15% LV perfusion defect or multivessel distribution. Severe coronary artery stenosis (CAS was defined as left main, 3 VD or 2VD involving proximal LAD. Results The mean age was 62 ± 13 years, 59% men, 29% diabetic (DM and 148 (45% had > 2 risk factors. Pharmacologic stress was performed in 109 patients (33%. MPA was present in 200 pts (60% of which, 137 were high risk. CAS was present in 166 pts (51%, 75 were severe. Of 87 patients with WMA, 83% had MPA and 78% had CAS. Multivariate analysis identified age >65, male, inability to exercise, DM, WMA, MAC and AS as independent predictors of MPA and CAS. Independent predictors of high risk MPA and severe CAS were age, DM, inability to exercise and WMA. 2-D echo findings offered incremental value over clinical information in predicting CAD by angiography. (Chi square: 360 vs. 320 p = 0.02. Conclusion 2-D Echo was valuable in predicting presence of physiological and anatomical CAD in addition to clinical information.

  3. Early seizures in patients with acute stroke: Frequency, predictive factors, and effect on clinical outcome

    Directory of Open Access Journals (Sweden)

    Andrea Alberti

    2008-06-01

    Full Text Available Andrea Alberti, Maurizio Paciaroni, Valeria Caso, Michele Venti, Francesco Palmerini, Giancarlo AgnelliStroke Unit and Division of Internal and Cardiovascular Medicine, University of Perugia, Perugia, ItalyBackground: Early seizure (ES may complicate the clinical course of patients with acute stroke. The aim of this study was to assess the rate of and the predictive factors for ES as well the effects of ES on the clinical outcome at hospital discharge in patients with first-ever stroke.Patients and methods: A total of 638 consecutive patients with first-ever stroke (543 ischemic, 95 hemorrhagic, admitted to our Stroke Unit, were included in this prospective study. ES were defined as seizures occurring within 7 days from acute stroke. Patients with history of epilepsy were excluded.Results: Thirty-one patients (4.8% had ES. Seizures were significantly more common in patients with cortical involvement, severe and large stroke, and in patient with cortical hemorrhagic transformation of ischemic stroke. ES was not associated with an increase in adverse outcome (mortality and disability. After multivariate analysis, hemorrhagic transformation resulted as an independent predictive factor for ES (OR = 6.5; 95% CI: 1.95–22.61; p = 0.003.Conclusion: ES occur in about 5% of patients with acute stroke. In these patients hemorrhagic transformation is a predictive factor for ES. ES does not seem to be associated with an adverse outcome at hospital discharge after acute stroke.Keywords: seizures, stroke, cortical involvement, hemorrhagic transformation

  4. Early seizures in patients with acute stroke: Frequency, predictive factors, and effect on clinical outcome

    Science.gov (United States)

    Alberti, Andrea; Paciaroni, Maurizio; Caso, Valeria; Venti, Michele; Palmerini, Francesco; Agnelli, Giancarlo

    2008-01-01

    Background Early seizure (ES) may complicate the clinical course of patients with acute stroke. The aim of this study was to assess the rate of and the predictive factors for ES as well the effects of ES on the clinical outcome at hospital discharge in patients with first-ever stroke. Patients and methods A total of 638 consecutive patients with first-ever stroke (543 ischemic, 95 hemorrhagic), admitted to our Stroke Unit, were included in this prospective study. ES were defined as seizures occurring within 7 days from acute stroke. Patients with history of epilepsy were excluded. Results Thirty-one patients (4.8%) had ES. Seizures were significantly more common in patients with cortical involvement, severe and large stroke, and in patient with cortical hemorrhagic transformation of ischemic stroke. ES was not associated with an increase in adverse outcome (mortality and disability). After multivariate analysis, hemorrhagic transformation resulted as an independent predictive factor for ES (OR = 6.5; 95% CI: 1.95–22.61; p = 0.003). Conclusion ES occur in about 5% of patients with acute stroke. In these patients hemorrhagic transformation is a predictive factor for ES. ES does not seem to be associated with an adverse outcome at hospital discharge after acute stroke. PMID:18827922

  5. Biomarkers for predicting clinical response to immunosuppressive therapy in aplastic anemia.

    Science.gov (United States)

    Narita, Atsushi; Kojima, Seiji

    2016-08-01

    The decision to select hematopoietic stem cell transplantation (HSCT) or immunosuppressive therapy (IST) as initial therapy in acquired aplastic anemia (AA) is currently based on patient age and the availability of a human leukocyte antigen (HLA)-matched donor. Although IST is a promising treatment option, the ability to predict its long-term outcomes remains poor due to refractoriness, relapses, and the risk of clonal evolution. Several predictive biomarkers for response to IST have been posited, including age, gender, pre-treatment blood cell counts, cytokines, gene mutations, paroxysmal nocturnal hemoglobinuria (PNH), and telomere length (TL). While previous studies have provided substantial biological insights into the utility of IST, the prognostic power of the reported biomarkers is currently insufficient to contribute to clinical decision making. Recently, a large retrospective analysis proposed the combination of minor PNH clones and TL as an efficient predictor of IST response. Identification of a reliable predictor would provide a useful tool for determining the most appropriate treatment choice for AA patients, including up-front HSCT from HLA-matched unrelated donor. The present review summarizes studies evaluating the utility of biomarkers in predicting the clinical response to IST of patients with AA, and provides a baseline for prospective studies aimed at validating previously reported biomarkers. PMID:27091471

  6. The clinical factors′ prediction of increased intradialytic qt dispersion on the electrocardiograms of chronic hemodialysis patients

    Directory of Open Access Journals (Sweden)

    Dina Oktavia

    2013-01-01

    Full Text Available Ventricular arrhythmias and sudden death are common in patients on maintenance hemodialysis (HD. The increase in QT dispersion (QTd on the electrocardiogram (ECG reflects increased tendency for ventricular repolarization that predisposes to arrhythmias. The purpose of the study was to identify the clinical factors that may predict the increased intradialytic QTd and to assess differences in QTd before and after HD. Each of 61 chronic HD patients underwent 12-lead ECG and blood pressure (BP measurement before and every 1 h during a single HD session. The QT intervals were corrected for heart rate using Bazett′s formula. Intradialytic QTd increased in 30 (49% patients. There was no correlation between the increased QTd and the clinical factors including hypertension, pulse pressure, intradialytic hypotension, left ventricular hypertrophy, old myocardial infarct, diabetes mellitus, and nutritional status. The means of QT interval and QTd increased after HD session (from 382 ± 29 to 444 ± 26 ms, P <0.05; and from 74 ± 21 to 114 ± 53 ms, respectively, P <0.05. We conclude that the increased intradialytic QTd could not be predicted by any of the clinical factors evaluated in this study. There was significant difference in the means of QTd before and after HD session.

  7. A Panel of Cancer Testis Antigens and Clinical Risk Factors to Predict Metastasis in Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Ramyar Molania

    2014-01-01

    Full Text Available Colorectal cancer (CRC is the third common carcinoma with a high rate of mortality worldwide and several studies have investigated some molecular and clinicopathological markers for diagnosis and prognosis of its malignant phenotypes. The aim of this study is to evaluate expression frequency of PAGE4, SCP-1, and SPANXA/D cancer testis antigen (CTA genes as well as some clinical risk markers to predict liver metastasis of colorectal cancer patients. The expression frequency of PAGE4, SCP-1, and SPANXA/D cancer/testis antigen (CTA genes was obtained using reverse transcription polymerase chain reaction (RT-PCR assay in 90 colorectal tumor samples including both negative and positive liver metastasis tumors. Statistical analysis was performed to assess the association of three studied genes and clinical risk factors with CRC liver metastasis. The frequency of PAGE4 and SCP-1 genes expression was significantly higher in the primary tumours with liver metastasis when statistically compared with primary tumors with no liver metastasis (P<0.05. Among all clinical risk factors studied, the lymph node metastasis and the depth of invasion were statistically correlated with liver metastasis of CRC patients. In addition, using multiple logistic regression, we constructed a model based on PAGE4 and lymph node metastasis to predict liver metastasis of CRC.

  8. Predicting PTSD using the New York Risk Score with genotype data: potential clinical and research opportunities

    Directory of Open Access Journals (Sweden)

    Boscarino JA

    2013-04-01

    Full Text Available Joseph A Boscarino,1,2 H Lester Kirchner,3,4 Stuart N Hoffman,5 Porat M Erlich1,4 1Center for Health Research, Geisinger Clinic, Danville, 2Department of Psychiatry, Temple University School of Medicine, Philadelphia, 3Division of Medicine, Geisinger Clinic, Danville, 4Department of Medicine, Temple University School of Medicine, Philadelphia, 5Department of Neurology, Geisinger Clinic, Danville, PA, USA Background: We previously developed a post-traumatic stress disorder (PTSD screening instrument, ie, the New York PTSD Risk Score (NYPRS, that was effective in predicting PTSD. In the present study, we assessed a version of this risk score that also included genetic information. Methods: Utilizing diagnostic testing methods, we hierarchically examined different prediction variables identified in previous NYPRS research, including genetic risk-allele information, to assess lifetime and current PTSD status among a population of trauma-exposed adults. Results: We found that, in predicting lifetime PTSD, the area under the receiver operating characteristic curve (AUC for the Primary Care PTSD Screen alone was 0.865. When we added psychosocial predictors from the original NYPRS to the model, including depression, sleep disturbance, and a measure of health care access, the AUC increased to 0.902, which was a significant improvement (P = 0.0021. When genetic information was added in the form of a count of PTSD risk alleles located within FKBP, COMT, CHRNA5, and CRHR1 genetic loci (coded 0–6, the AUC increased to 0.920, which was also a significant improvement (P = 0.0178. The results for current PTSD were similar. In the final model for current PTSD with the psychosocial risk factors included, genotype resulted in a prediction weight of 17 for each risk allele present, indicating that a person with six risk alleles or more would receive a PTSD risk score of 17 × 6 = 102, the highest risk score for any of the predictors studied. Conclusion: Genetic

  9. Clinical prediction rules in Staphylococcus aureus bacteremia demonstrate the usefulness of reporting likelihood ratios in infectious diseases.

    Science.gov (United States)

    Bai, A D; Showler, A; Burry, L; Steinberg, M; Tomlinson, G A; Bell, C M; Morris, A M

    2016-09-01

    Infectious diseases specialists often use diagnostic tests to assess the probability of a disease based on knowledge of the diagnostic properties. It has become standard for published studies on diagnostic tests to report sensitivity, specificity and predictive values. Likelihood ratios are often omitted. We compared published clinical prediction rules in Staphylococcus aureus bacteremia to illustrate the importance of likelihood ratios. We performed a narrative review comparing published clinical prediction rules used for excluding endocarditis in S. aureus bacteremia. Of nine published clinical prediction rules, only three studies reported likelihood ratios. Many studies concluded that the clinical prediction rule could safely exclude endocarditis based on high sensitivity and high negative predictive value. Of the studies with similar high sensitivity and high negative predictive value, calculated negative likelihood ratios were able to differentiate and identify the best clinical prediction rule for excluding endocarditis. Compared to sensitivity, specificity and predictive values, likelihood ratios can be more directly used to interpret diagnostic test results to assist in ruling in or ruling out a disease. Therefore, a new standard should be set to include likelihood ratios in reporting of diagnostic tests in infectious diseases research. PMID:27357965

  10. Prediction of Water Quality Parameters Using Statistical Methods: A Case Study in a Specially Protected Area, Ankara, Turkey

    Science.gov (United States)

    Alp, E.; Yücel, Ö.; Özcan, Z.

    2014-12-01

    Turkey has been making many legal arrangements for sustainable water management during the harmonization process with the European Union. In order to make cost effective and efficient decisions, monitoring network in Turkey has been expanding. However, due to time and budget constraints, desired number of monitoring campaigns can not be carried. Hence, in this study, independent parameters that can be measured easily and quickly are used to estimate water quality parameters in Lake Mogan and Eymir using linear regression. Nonpoint sources are one of the major pollutant components in Eymir and Mogan lakes. In this paper, a correlation between easily measurable parameters, DO, temperature, electrical conductivity, pH, precipitation and dependent variables, TN, TP, COD, Chl-a, TSS, Total Coliform is investigated. Simple regression analysis is performed for each season in Eymir and Mogan lakes by using SPSS Statistical program using the water quality data collected between 2006-2012. Regression analysis demonstrated significant linear relationship between measured and simulated concentrations for TN (R2=0.86), TP (R2=0.85), TSS (R2=0.91), Chl-a (R2=0.94), COD (R2=0.99), T. Coliform (R2=0.97) which are the best results in each season for Eymir and Mogan Lakes. The overall results of this study shows that by using easily measurable parameters even in ungauged situation the water quality of lakes can be predicted. Moreover, the outputs obtained from the regression equations can be used as an input for water quality models such as phosphorus budget model which is used to calculate the required reduction in the external phosphorus load to Lake Mogan to meet the water quality standards.

  11. A clinical comparative study of anatomic parameters before and after total hip replacement on congenital dysplasia.

    Science.gov (United States)

    Huang, Ziqiang; Zhou, Yonggang; Chai, Wei; Ji, Weiping; Cui, Guopeng; Ma, Miaoqun; Zhu, Yin

    2016-07-01

    [Purpose] To study preoperative and postoperative hip circumference data of various types of congenital dysplasia of the hip treated with total hip replacement, including the femoral offset, femoral neck length, height, and hip abductor arm parameters. [Subjects and Methods] This study included seventy-eight cases of congenital dysplasia of the hip (I-III type). Furthermore, four parameters were measured, including the preoperative and postoperative femoral offset. Statistical data analysis was performed using the SPSS 13.0 software. [Results] The femoral offset was 33.3 ± 8.4 mm (preoperative) and 39.1 ± 7.1 mm (postoperative). The femoral head height was 59.5 ± 8.7 mm (preoperative) and 68.8 ± 11.0 mm (postoperative). The femoral neck length was 50.8 ± 10.8 mm (preoperative) and 61.5 ± 10.4 mm (postoperative). The hip abductor arm was 54.3 ± 9.6 mm (preoperative) 64.7 ± 10.1 mm (postoperative). The preoperative and postoperative parameters showed statistical differences. Furthermore, no significant differences were evidenced when comparing the postoperative hip parameters with the normal data parameters. [Conclusion] Total hip replacement on congenital dysplasia of the hip could lead to the rebuilt of an almost normal physiological anatomy for each hip case (type I-III). PMID:27512242

  12. Retinopathy of Prematurity in Very Low Birth Weight Infants: Effects of Serum Vitamin A and Clinical Parameters

    OpenAIRE

    Esra Arun Özer; Özlem Sivaslı Gül; Gamze Men; Ekrem Talay; Sümer Sütçüoğlu; Ali Kanık; Ebru Türkoğlu; Zelal Kahramaner; Hese Coşar; Aydın Erdemir; Işın Yaprak

    2011-01-01

    Pur po se: Retinopathy of prematurity (ROP) is a proliferative vascular disease which affects premature newborns and occurs during vessel development. The pathogenesis of ROP is complex and includes oxidative damage to the developing retina. The aim of this study was to evaluate the relationship of ROP with serum vitamin A levels and clinical parameters in infants with a gestational age of ≤32 weeks and birth weight of ≤1500 grams. Ma te ri al and Met hod: Newborns admitted to Newbor...

  13. Predictor value of some clinical-biological parameters for the onset of depressive disorder in elderly patients with unstable angina

    OpenAIRE

    Cristina Moşuţan; George Săraci; Caius R. Duncea

    2012-01-01

    Abstract. Objective: To evaluate the potential predictor value of some parameters for the onset of depression after an episode of unstableangina in elderly. Material and Methods: We included 103 elderly patients who suffered an acute unstable angina episode. Clinical, laband imagistic data was recorded in the first week after admittance. Six month after unstable angina episode, patients were evaluated for thepresence of depression. Results: Univariate analysis showed statistically significant...

  14. Detection of human herpes viruses in patients with chronic and aggressive periodontitis and relationship between viruses and clinical parameters

    OpenAIRE

    Das, Sushma; Krithiga, G Shobha Prakash; Gopalakrishnan, S.

    2012-01-01

    Background and Aims: Recent microbiological researches have revealed the possible role of human cytomegalovirus (HCMV), Epstein barr virus (EBV), and herpes simplex virus (HSV-1 and HSV-2) in the etiopathogenesis of periodontal diseases. The present pilot study has been undertaken to detect the presence of these viruses in chronic periodontitis, aggressive periodontitis, and healthy individuals and to determine the relationship between these viruses and the clinical parameters. Materials and ...

  15. Diagnostic and prognostic accuracy of clinical and laboratory parameters in community-acquired pneumonia

    Directory of Open Access Journals (Sweden)

    Nusbaumer Charly

    2007-03-01

    Full Text Available Abstract Background Community-acquired pneumonia (CAP is the most frequent infection-related cause of death. The reference standard to diagnose CAP is a new infiltrate on chest radiograph in the presence of recently acquired respiratory signs and symptoms. This study aims to evaluate the diagnostic and prognostic accuracy of clinical signs and symptoms and laboratory biomarkers for CAP. Methods 545 patients with suspected lower respiratory tract infection, admitted to the emergency department of a university hospital were included in a pre-planned post-hoc analysis of two controlled intervention trials. Baseline assessment included history, clinical examination, radiography and measurements of procalcitonin (PCT, highly sensitive C-reactive protein (hsCRP and leukocyte count. Results Of the 545 patients, 373 had CAP, 132 other respiratory tract infections, and 40 other final diagnoses. The AUC of a clinical model including standard clinical signs and symptoms (i.e. fever, cough, sputum production, abnormal chest auscultation and dyspnea to diagnose CAP was 0.79 [95% CI, 0.75–0.83]. This AUC was significantly improved by including PCT and hsCRP (0.92 [0.89–0.94]; p Conclusion PCT, and to a lesser degree hsCRP, improve the accuracy of currently recommended approaches for the diagnosis of CAP, thereby complementing clinical signs and symptoms. PCT is useful in the severity assessment of CAP.

  16. ESTABLISHMENT OF ECHOCARDIOGRAPHIC PARAMETERS OF CLINICALLY HEALTHY FLORIDA MANATEES (TRICHECHUS MANATUS LATIROSTRIS).

    Science.gov (United States)

    Gerlach, Trevor J; Estrada, Amara H; Sosa, Ivan S; Powell, Melanie; Lamb, Kenneth E; Ball, Ray L; de Wit, Martine; Walsh, Mike T

    2015-06-01

    A standardized echocardiographic technique was recently established for the Florida manatee (Trichechus manatus latirostris). There are no available published data on normal echocardiographic parameters in any Sirenian species. The purpose of this study was to report reference parameters for various echocardiographic measurements. These parameters are intended to serve as a comparison for future research into the prevalence of cardiac diseases in the manatee and to aid in diagnosing animals with suspected cardiac disease in rehabilitation facilities. Annual health assessments of free-ranging manatees in Crystal River National Wildlife Refuge, Florida, and pre-release health assessments of rehabilitated manatees at Tampa's Lowry Park Zoo permitted comparison of echocardiographic measurements in adult (n=14), subadult (n=7), and calf (n=8) animals under manual restraint. PMID:26056870

  17. ESTABLISHMENT OF ECHOCARDIOGRAPHIC PARAMETERS OF CLINICALLY HEALTHY FLORIDA MANATEES (TRICHECHUS MANATUS LATIROSTRIS).

    Science.gov (United States)

    Gerlach, Trevor J; Estrada, Amara H; Sosa, Ivan S; Powell, Melanie; Lamb, Kenneth E; Ball, Ray L; de Wit, Martine; Walsh, Mike T

    2015-06-01

    A standardized echocardiographic technique was recently established for the Florida manatee (Trichechus manatus latirostris). There are no available published data on normal echocardiographic parameters in any Sirenian species. The purpose of this study was to report reference parameters for various echocardiographic measurements. These parameters are intended to serve as a comparison for future research into the prevalence of cardiac diseases in the manatee and to aid in diagnosing animals with suspected cardiac disease in rehabilitation facilities. Annual health assessments of free-ranging manatees in Crystal River National Wildlife Refuge, Florida, and pre-release health assessments of rehabilitated manatees at Tampa's Lowry Park Zoo permitted comparison of echocardiographic measurements in adult (n=14), subadult (n=7), and calf (n=8) animals under manual restraint.

  18. Preoperative MRI findings predict two-year postoperative clinical outcome in lumbar spinal stenosis.

    Directory of Open Access Journals (Sweden)

    Pekka Kuittinen

    Full Text Available To study the predictive value of preoperative magnetic resonance imaging (MRI findings for the two-year postoperative clinical outcome in lumbar spinal stenosis (LSS.84 patients (mean age 63±11 years, male 43% with symptoms severe enough to indicate LSS surgery were included in this prospective observational single-center study. Preoperative MRI of the lumbar spine was performed with a 1.5-T unit. The imaging protocol conformed to the requirements of the American College of Radiology for the performance of MRI of the adult spine. Visual and quantitative assessment of MRI was performed by one experienced neuroradiologist. At the two-year postoperative follow-up, functional ability was assessed with the Oswestry Disability Index (ODI 0-100% and treadmill test (0-1000 m, pain symptoms with the overall Visual Analogue Scale (VAS 0-100 mm, and specific low back pain (LBP and specific leg pain (LP separately with a numeric rating scale from 0-10 (NRS-11. Satisfaction with the surgical outcome was also assessed.Preoperative severe central stenosis predicted postoperatively lower LP, LBP, and VAS when compared in patients with moderate central stenosis (p<0.05. Moreover, severe stenosis predicted higher postoperative satisfaction (p = 0.029. Preoperative scoliosis predicted an impaired outcome in the ODI (p = 0.031 and lowered the walking distance in the treadmill test (p = 0.001. The preoperative finding of only one stenotic level in visual assessment predicted less postoperative LBP when compared with patients having 2 or more stenotic levels (p = 0.026. No significant differences were detected between quantitative measurements and the patient outcome.Routine preoperative lumbar spine MRI can predict the patient outcome in a two-year follow up in patients with LSS surgery. Severe central stenosis and one-level central stenosis are predictors of good outcome. Preoperative finding of scoliosis may indicate worse functional ability.

  19. Evaluation of Carotid Arterial Intima-Media Thickness (IMT and Its Relation to Clinical Parameters in Japanese Children

    Directory of Open Access Journals (Sweden)

    Tamura,Hiroko

    2011-02-01

    Full Text Available The aim of this study was to evaluate the carotid arterial intima-media thickness (IMT and its relation to clinical parameters in Japanese children. Fifty-two healthy children (39 boys and 13 girls, aged 6-14 years, were enrolled in this cross-sectional investigation study. IMT of the common carotid artery was determined using ultrasonography. We also investigated anthropometric parameters, blood pressure (BP, lifestyles and blood examinations. The mean value of IMT was 0.4±0.1mm, which was lower than the normal value (1.0mm in adults. IMT was positively correlated with age (r=0.340 and height (r=0.346 in boys, while it was positively correlated with body mass index (BMI (r=0.584 and diastolic BP (DBP (r=0.563 in girls. In addition, IMT was associated with sleeping hours and hours of watching television (TV by using stepwise regression analysis. In conclusion, IMT increased with aging, and it was linked to some clinical parameters of atherosclerosis and lifestyles in children. Therefore, this reference data will be helpful for future assessment of age-related change in Japanese children in clinical practice, and IMT might be a good predictor of atherosclerosis in Japanese children.

  20. Sensitivity, specificity and predictive value of blood cultures from cattle clinically suspected of bacterial endocarditis

    DEFF Research Database (Denmark)

    Houe, Hans; Eriksen, L.; Jungersen, Gregers;

    1993-01-01

    This study investigated the number of blood culture-positive cattle among 215 animals clinically suspected of having bacterial endocarditis. For animals that were necropsied, the sensitivity, specificity and predictive value of the diagnosis of endocarditis were calculated on the basis...... of the isolation of the causative bacteria from blood. Furthermore, it was investigated whether the glutaraldehyde coagulation time, total leucocyte count, per cent neutrophil granulocytes, pulse rate and duration of disease could help to discriminate endocarditis from other diseases. Among 138 animals necropsied...... the sensitivity, specificity and predictive value of blood cultivation were 70.7 per cent, 93.8 per cent and 89.1 per cent, respectively. None of the other measurements could be used to discriminate between endocarditis and non-endocarditis cases....

  1. Predictive Factors of Gastrointestinal Caustic Injury According to Clinical and Endoscopic Findings

    Directory of Open Access Journals (Sweden)

    Cherie Quingking

    2013-03-01

    Full Text Available Background: Ingestion of caustic substances is the main reason for referral to Philippines National Poison Management and Control Center among other causes of acute poisoning. Rapid assessment of severity of injury is important for treatment and prognosis of these cases. This study was aimed to investigate the correlation of clinical factors with severity of gastrointestinal (GI mucosal injury. Methods: In this retrospective study, a total of 105 patients were included. Patients were categorized into two groups including 35 patients with low grade and 70 patients with high grade GI injury to compare the predictive value of clinical findings. Results: Mean (SD age of patients was 27 (10 and 47% of patients were male. Oral burns (P

  2. An Update on Crown Lengthening. Part 2: Increasing Clinical Crown Height to Facilitate Predictable Restorations.

    Science.gov (United States)

    Kalsi, Harpoonam Jeet; Bomfim, Deborah Iola; Darbar, Ulpee

    2015-04-01

    This is the second paper in this two-part series. Paper one provided an overview of managing gingival tissue excess and paper two will focus on increasing clinical crown height to facilitate restorative treatment. Crown lengthening is a surgical procedure aimed at the removal of gingival tissue with or without adjunctive bone removal. The different types of procedure undertaken will be discussed over the two papers. In order to provide predictable restorations, care must be taken to ensure the integrity of the margins. If this is not taken into account it can lead to an impingement on the biologic width, which may in turn lead to chronic inflammation resulting in recession or the development of periodontal problems which can be hard to manage. Clinical Relevance: This paper aims to reinforce the need for thorough diagnosis and treatment planning and provides an overview of the various procedures that can be undertaken.

  3. Molecular biomarkers of colorectal cancer: prognostic and predictive tools for clinical practice

    Institute of Scientific and Technical Information of China (English)

    Wei-qin JIANG; Fang-fang FU; Yang-xia LI; Wei-bin WANG; Hao-hao WANG; Hai-ping JIANG; Li-song TENG

    2012-01-01

    Colorectal cancer remains one of the most common types of cancer and leading causes of cancer death worldwide.Although we have made steady progress in chemotherapy and targeted therapy,evidence suggests that the majority of patients undergoing drug therapy experience severe,debilitating,and even lethal adverse drug events which considerably outweigh the benefits.The identification of suitable biomarkers will allow clinicians to deliver the most appropriate drugs to specific patients and spare them ineffective and expensive treatments.Prognostic and predictive biomarkers have been the subjects of many published papers,but few have been widely incorporated into clinical practice.Here,we want to review recent biomarker data related to colorectal cancer,which may have been ready for clinical use.

  4. Optimal marker-strategy clinical trial design to detect predictive markers for targeted therapy.

    Science.gov (United States)

    Zang, Yong; Liu, Suyu; Yuan, Ying

    2016-07-01

    In developing targeted therapy, the marker-strategy design (MSD) provides an important approach to evaluate the predictive marker effect. This design first randomizes patients into non-marker-based or marker-based strategies. Patients allocated to the non-marker-based strategy are then further randomized to receive either the standard or targeted treatments, while patients allocated to the marker-based strategy receive treatments based on their marker statuses. Little research has been done on the statistical properties of the MSD, which has led to some widespread misconceptions and placed clinical researchers at high risk of using inefficient designs. In this article, we show that the commonly used between-strategy comparison has low power to detect the predictive effect and is valid only under a restrictive condition that the randomization ratio within the non-marker-based strategy matches the marker prevalence. We propose a Wald test that is generally valid and also uniformly more powerful than the between-strategy comparison. Based on that, we derive an optimal MSD that maximizes the power to detect the predictive marker effect by choosing the optimal randomization ratios between the two strategies and treatments. Our numerical study shows that using the proposed optimal designs can substantially improve the power of the MSD to detect the predictive marker effect. We use a lung cancer trial to illustrate the proposed optimal designs.

  5. Sputum biomarkers and the prediction of clinical outcomes in patients with cystic fibrosis.

    Directory of Open Access Journals (Sweden)

    Theodore G Liou

    Full Text Available Lung function, acute pulmonary exacerbations (APE, and weight are the best clinical predictors of survival in cystic fibrosis (CF; however, underlying mechanisms are incompletely understood. Biomarkers of current disease state predictive of future outcomes might identify mechanisms and provide treatment targets, trial endpoints and objective clinical monitoring tools. Such CF-specific biomarkers have previously been elusive. Using observational and validation cohorts comprising 97 non-transplanted consecutively-recruited adult CF patients at the Intermountain Adult CF Center, University of Utah, we identified biomarkers informative of current disease and predictive of future clinical outcomes. Patients represented the majority of sputum producers. They were recruited March 2004-April 2007 and followed through May 2011. Sputum biomarker concentrations were measured and clinical outcomes meticulously recorded for a median 5.9 (interquartile range 5.0 to 6.6 years to study associations between biomarkers and future APE and time-to-lung transplantation or death. After multivariate modeling, only high mobility group box-1 protein (HMGB-1, mean=5.84 [log ng/ml], standard deviation [SD] =1.75 predicted time-to-first APE (hazard ratio [HR] per log-unit HMGB-1=1.56, p-value=0.005, number of future APE within 5 years (0.338 APE per log-unit HMGB-1, p<0.001 by quasi-Poisson regression and time-to-lung transplantation or death (HR=1.59, p=0.02. At APE onset, sputum granulocyte macrophage colony stimulating factor (GM-CSF, mean 4.8 [log pg/ml], SD=1.26 was significantly associated with APE-associated declines in lung function (-10.8 FEV(1% points per log-unit GM-CSF, p<0.001 by linear regression. Evaluation of validation cohorts produced similar results that passed tests of mutual consistency. In CF sputum, high HMGB-1 predicts incidence and recurrence of APE and survival, plausibly because it mediates long-term airway inflammation. High APE-associated GM

  6. Per-beam, planar IMRT QA passing rates do not predict clinically relevant patient dose errors

    Energy Technology Data Exchange (ETDEWEB)

    Nelms, Benjamin E.; Zhen Heming; Tome, Wolfgang A. [Canis Lupus LLC and Department of Human Oncology, University of Wisconsin, Merrimac, Wisconsin 53561 (United States); Department of Medical Physics, University of Wisconsin, Madison, Wisconsin 53705 (United States); Departments of Human Oncology, Medical Physics, and Biomedical Engineering, University of Wisconsin, Madison, Wisconsin 53792 (United States)

    2011-02-15

    Purpose: The purpose of this work is to determine the statistical correlation between per-beam, planar IMRT QA passing rates and several clinically relevant, anatomy-based dose errors for per-patient IMRT QA. The intent is to assess the predictive power of a common conventional IMRT QA performance metric, the Gamma passing rate per beam. Methods: Ninety-six unique data sets were created by inducing four types of dose errors in 24 clinical head and neck IMRT plans, each planned with 6 MV Varian 120-leaf MLC linear accelerators using a commercial treatment planning system and step-and-shoot delivery. The error-free beams/plans were used as ''simulated measurements'' (for generating the IMRT QA dose planes and the anatomy dose metrics) to compare to the corresponding data calculated by the error-induced plans. The degree of the induced errors was tuned to mimic IMRT QA passing rates that are commonly achieved using conventional methods. Results: Analysis of clinical metrics (parotid mean doses, spinal cord max and D1cc, CTV D95, and larynx mean) vs IMRT QA Gamma analysis (3%/3 mm, 2/2, 1/1) showed that in all cases, there were only weak to moderate correlations (range of Pearson's r-values: -0.295 to 0.653). Moreover, the moderate correlations actually had positive Pearson's r-values (i.e., clinically relevant metric differences increased with increasing IMRT QA passing rate), indicating that some of the largest anatomy-based dose differences occurred in the cases of high IMRT QA passing rates, which may be called ''false negatives.'' The results also show numerous instances of false positives or cases where low IMRT QA passing rates do not imply large errors in anatomy dose metrics. In none of the cases was there correlation consistent with high predictive power of planar IMRT passing rates, i.e., in none of the cases did high IMRT QA Gamma passing rates predict low errors in anatomy dose metrics or vice versa

  7. Do clinical factors help to predict disease course in inflammatory bowel disease?

    Institute of Scientific and Technical Information of China (English)

    Edouard; Louis; Jacques; Belaiche; Catherine; Reenaers

    2010-01-01

    While therapeutic strategies able to change the natural history of the disease are developing,it is of major importance to have available predictive factors for aggressive disease to try and target these therapeutic strategies.Clinical predictors have probably been the most broadly studied.In both Crohn's disease(CD) and ulcerative colitis(UC),age at diagnosis,disease location and smoking habit are currently the strongest predictors of disease course.A younger age at onset is associated with more aggressive...

  8. Is correction necessary when clinically determining quantitative cerebral perfusion parameters from multi-slice dynamic susceptibility contrast MR studies?

    Science.gov (United States)

    Salluzzi, M.; Frayne, R.; Smith, M. R.

    2006-01-01

    Several groups have modified the standard singular value decomposition (SVD) algorithm to produce delay-insensitive cerebral blood flow (CBF) estimates from dynamic susceptibility contrast (DSC) perfusion studies. However, new dependences of CBF estimates on bolus arrival times and slice position in multi-slice studies have been recently recognized. These conflicting findings can be reconciled by accounting for several experimental and algorithmic factors. Using simulation and clinical studies, the non-simultaneous measurement of arterial and tissue concentration curves (relative slice position) in a multi-slice study is shown to affect time-related perfusion parameters, e.g. arterial-tissue-delay measurements. However, the current clinical impact of relative slice position on amplitude-related perfusion parameters, e.g. CBF, can be expected to be small unless any of the following conditions are present individually or in combination: (a) high concentration curve signal-to-noise ratios, (b) small tissue mean transit times, (c) narrow arterial input functions or (d) low temporal resolution of the DSC image sequence. Recent improvements in magnetic resonance (MR) technology can easily be expected to lead to scenarios where these effects become increasingly important sources of inaccuracy for all perfusion parameter estimates. We show that using Fourier interpolated (high temporal resolution) residue functions reduces the systematic error of the perfusion parameters obtained from multi-slice studies. Preliminary results associated with this paper were presented at ISMRM 12th Scientific Meeting and Exhibition, Kyoto, Japan, 2004.

  9. Predicting Complexation Thermodynamic Parameters of β-Cyclodextrin with Chiral Guests by Using Swarm Intelligence and Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Luckhana Lawtrakul

    2009-05-01

    Full Text Available The Particle Swarm Optimization (PSO and Support Vector Machines (SVMs approaches are used for predicting the thermodynamic parameters for the 1:1 inclusion complexation of chiral guests with β-cyclodextrin. A PSO is adopted for descriptor selection in the quantitative structure-property relationships (QSPR of a dataset of 74 chiral guests due to its simplicity, speed, and consistency. The modified PSO is then combined with SVMs for its good approximating properties, to generate a QSPR model with the selected features. Linear, polynomial, and Gaussian radial basis functions are used as kernels in SVMs. All models have demonstrated an impressive performance with R2 higher than 0.8.

  10. COMPARISON OF ANN WITH RSM IN PREDICTING SURFACE ROUGHNESS WITH RESPECT TO PROCESS PARAMETERS IN Nd: YAG LASER DRILLING

    Directory of Open Access Journals (Sweden)

    ARINDAM MAJUMDER

    2010-10-01

    Full Text Available Micro machining is a ready solution towards the miniaturization of component and devices. The process parameters of low power pulse Nd:YAG laser machining such as pulse rate, pulse width, speed play a major role in deciding the surface quality. Two methods, response surface methodology (RSM and artificial neural network (ANN were used to predict the surface roughness of Nd:YAG laser drilled mild steel specimens. The experiments were conducted based on the three factors, three levels and central composite face centered design with full replication technique and mathematical model was developed. Also a comparison has been done with between the result obtained throughresponse surface methodology (RSM and artificial neural network (ANN.

  11. Clinical and radiological parameters of patients with lung thromboembolism, diagnosed by high probability ventilation / perfusion scintigraphies

    International Nuclear Information System (INIS)

    Background: pulmonary embolism (PE) remains an elusive diagnosis, and still causes too many unexpected deaths. Because of this, noninvasive investigations are done when pulmonary embolism is suspected. Objective: to determine the clinical and x-rays findings in patients with diagnosis of pulmonary embolism by high probability ventilation/perfusion (V/Q) lung scan. Materials and methods: inpatient medical records of 91 patients with clinical suspected PE and high and low probability V/Q lung scan were analyzed (PIOPED criterion). Results: there were statistics correlation with four clinical findings: hemoptysis (p value=0,02, odds ratio=8,925), taquicardia (p value=0,02 odds ratio=3,5), chest pain (p value=0,01, odds ratio=1,87), and recent surgery (p value=0,02, odds ratio=2,762). The 70,7% chest x-rays were normal (p value < 0,001). Conclusion: the clinical and x-rays findings in patients with diagnosis of PE by high probability V/Q lung scan were: hemoptysis, taquicardia, chest pain, recent surgery and normal chest x-ray. This is important because would help to choose the patients in whom the V/Q lung scan will have the maximal performance (Au)

  12. Predictive capacity of sperm quality parameters and sperm subpopulations on field fertility after artificial insemination in sheep.

    Science.gov (United States)

    Santolaria, P; Vicente-Fiel, S; Palacín, I; Fantova, E; Blasco, M E; Silvestre, M A; Yániz, J L

    2015-12-01

    This study was designed to evaluate the relevance of several sperm quality parameters and sperm population structure on the reproductive performance after cervical artificial insemination (AI) in sheep. One hundred and thirty-nine ejaculates from 56 adult rams were collected using an artificial vagina, processed for sperm quality assessment and used to perform 1319 AI. Analyses of sperm motility by computer-assisted sperm analysis (CASA), sperm nuclear morphometry by computer-assisted sperm morphometry analysis (CASMA), membrane integrity by acridine orange-propidium iodide combination and sperm DNA fragmentation using the sperm chromatin dispersion test (SCD) were performed. Clustering procedures using the sperm kinematic and morphometric data resulted in the classification of spermatozoa into three kinematic and three morphometric sperm subpopulations. Logistic regression procedures were used, including fertility at AI as the dependent variable (measured by lambing, 0 or 1) and farm, year, month of AI, female parity, female lambing-treatment interval, ram, AI technician and sperm quality parameters (including sperm subpopulations) as independent factors. Sperm quality variables remaining in the logistic regression model were viability and VCL. Fertility increased for each one-unit increase in viability (by a factor of 1.01) and in VCL (by a factor of 1.02). Multiple linear regression analyses were also performed to analyze the factors possibly influencing ejaculate fertility (N=139). The analysis yielded a significant (P<0.05) relationship between sperm viability and ejaculate fertility. The discriminant ability of the different semen variables to predict field fertility was analyzed using receiver operating characteristic (ROC) curve analysis. Sperm viability and VCL showed significant, albeit limited, predictive capacity on field fertility (0.57 and 0.54 Area Under Curve, respectively). The distribution of spermatozoa in the different subpopulations was not

  13. Prediction of Mass Transfer Time Relaxation Parameter for Boiling Simulation on the Shell-Side of LNG Spiral Wound Heat Exchanger

    OpenAIRE

    Wu, Zhi-Yong; Cai, Wei-Hua; Qiu, Guo-Dong; Jiang, Yi-Qiang

    2014-01-01

    The objective of this present study is to propose an approach to predict mass transfer time relaxation parameter for boiling simulation on the shell-side of LNG spiral wound heat exchanger (SWHE). The numerical model for the shell-side of LNG SWHE was established. For propane and ethane, a predicted value of mass transfer time relaxation parameter was presented through the equivalent evaporation simulations and was validated by the Chisholm void fraction correlation recommended under various ...

  14. Correlated regions of cerebral blood flow with clinical parameters in Parkinson's disease. Comparison using 'Anatomy' and 'Talairach Daemon' software

    International Nuclear Information System (INIS)

    We assign the anatomical names of functional activation regions in the brain, based on the probabilistic cyto-architectonic atlas by Anatomy 1.7 from an analysis of correlations between regional cerebral blood flow (rCBF) and clinical parameters of the non-demented Parkinson's disease (PD) patients by statistical parametric mapping (SPM) 8. We evaluated Anatomy 1.7 of SPM toolbox compared to 'Talairach Daemon' (TD) Client 2.4.2 software. One hundred and thirty-six patients (mean age 60.0±9.09 years; 73 women and 63 men) with non-demented PD were selected. Tc-99m-HMPAO brain single-photon emission computed tomography (SPECT) scans were performed on the patients using a two-head gamma-camera. We analyzed the brain image of PD patients by SPM8 and found the anatomical names of correlated regions of rCBF perfusion with the clinical parameters using TD Client 2.4.2 and Anatomy 1.7. The SPM8 provided a correlation coefficient between clinical parameters and cerebral hypoperfusion by a simple regression method. To the clinical parameters were added age, duration of disease, education period, Hoehn and Yahr (H and Y) stage and Korean mini-mental state examination (K-MMSE) score. Age was correlated with cerebral perfusion in the Brodmann area (BA) 6 and BA 3b assigned by Anatomy 1.7 and BA 6 and pyramis in gray matter by TD Client 2.4.2 with p<0.001 uncorrected. Also, assigned significant correlated regions were found in the left and right lobules VI (Hem) with duration of disease, in left and right lobules VIIa crus I (Hem) with education, in left insula (Ig2), left and right lobules VI (Hem) with H and Y, and in BA 4a and 6 with K-MMSE score with p<0.05 uncorrected by Anatomy 1.7, respectively. Most areas of correlation were overlapped by two different anatomical labeling methods, but some correlation areas were found with different names. Age was the most significantly correlated clinical parameter with rCBF. TD Client found the exact anatomical name by the peak

  15. The predictability of renin-angiotensin-aldosterone system factors for clinical outcome in patients with acute decompensated heart failure.

    Science.gov (United States)

    Nakada, Yasuki; Takahama, Hiroyuki; Kanzaki, Hideaki; Sugano, Yasuo; Hasegawa, Takuya; Ohara, Takahiro; Amaki, Makoto; Funada, Akira; Yoshida, Akemi; Yasuda, Satoshi; Ogawa, Hisao; Anzai, Toshihisa

    2016-06-01

    Although counter-regulation between B-type natriuretic peptide (BNP) levels and renin-angiotensin-aldosterone system (RAAS) activation in heart failure (HF) has been suggested, whether the regulation is preserved in acute decompensated heart failure (ADHF) patients remains unclear. This study aimed to determine: (1) the relationship between RAAS activation and clinical outcomes in ADHF patients, and (2) the relationships between plasma BNP levels and degrees of activation in RAAS factors. This study included ADHF patients (n = 103, NYHA3-4, plasma BNP > 200 pg/ml). We studied the predictability of RAAS factors for cardiovascular events and the relationships between plasma BNP levels and the degrees of activation in RAAS factors, which were evaluated by plasma renin activity (PRA) and aldosterone concentration (PAC). PRA was a strong predictor of cardiovascular (CV) events over 1 year, even after accounting for plasma BNP levels (hazard ratio (HR): 1.04, CI [1.02-1.06], p analysis, p = 0.06). Cut-off value of PRA (5.3 ng/ml/h) was determined by AUC curve. Of the enrolled patients, higher PRA was found in 40 % of them. Although no correlation between the plasma BNP levels and PRA was found (p = 0.36), after adjusting for hemodynamic parameters, eGFR and medication, a correlation was found between them (p = 0.01). Elevated RAAS factors were found in a substantial number of ADHF patients with high plasma BNP levels in the association with hemodynamic state, which predicts poor clinical outcomes. The measurements of RAAS factors help to stratify ADHF patients at risk for further CV events. PMID:25964073

  16. Lyman-Kutcher-Burman NTCP model parameters for radiation pneumonitis and xerostomia based on combined analysis of published clinical data

    International Nuclear Information System (INIS)

    Knowledge of accurate parameter estimates is essential for incorporating normal tissue complication probability (NTCP) models into biologically based treatment planning. The purpose of this work is to derive parameter estimates for the Lyman-Kutcher-Burman (LKB) NTCP model using a combined analysis of multi-institutional toxicity data for the lung (radiation pneumonitis) and parotid gland (xerostomia). A series of published clinical datasets describing dose response for radiation pneumonitis (RP) and xerostomia were identified for this analysis. The data support the notion of large volume effect for the lung and parotid gland with the estimates of the n parameter being close to unity. Assuming that n = 1, the m and TD50 parameters of the LKB model were estimated by the maximum likelihood method from plots of complication rate as a function of mean organ dose. Ninety five percent confidence intervals for parameter estimates were obtained by the profile likelihood method. If daily fractions other than 2 Gy had been used in a published report, mean organ doses were converted to 2 Gy/fraction-equivalent doses using the linear-quadratic (LQ) formula with α/β = 3 Gy. The following parameter estimates were obtained for the endpoint of symptomatic RP when the lung is considered a paired organ: m = 0.41 (95% CI 0.38, 0.45) and TD50 = 29.9 Gy (95% CI 28.2, 31.8). When RP incidence was evaluated as a function of dose to the ipsilateral lung rather than total lung, estimates were m = 0.35 (95% CI 0.29, 0.43) and TD50 = 37.6 Gy (95% CI 34.6, 41.4). For xerostomia expressed as reduction in stimulated salivary flow below 25% within six months after radiotherapy, the following values were obtained: m = 0.53 (95% CI 0.45, 0.65) and TD50 = 31.4 Gy (95% CI 29.1, 34.0). Although a large number of parameter estimates for different NTCP models and critical structures exist and continue to appear in the literature, it is hard to justify the use of any single parameter set obtained at a

  17. Multiscale modeling of protein transport in silicon membrane nanochannels. Part 2. From molecular parameters to a predictive continuum diffusion model.

    Science.gov (United States)

    Amato, Francesco; Cosentino, Carlo; Pricl, Sabrina; Ferrone, Marco; Fermeglia, Maurizio; Cheng, Mark Ming-Cheng; Walczak, Robert; Ferrari, Mauro

    2006-12-01

    Transport and surface interactions of proteins in nanopore membranes play a key role in many processes of biomedical importance. Although the use of porous materials provides a large surface-to-volume ratio, the efficiency of the operations is often determined by transport behavior, and this is complicated by the fact that transport paths (i.e., the pores) are frequently of molecular dimensions. Under these conditions, a protein diffusion can be slower than predicted from Fick law. The main contribution of this paper is the development of a mathematical model of this phenomenon, whose parameters are computed via molecular modeling, as described Part 1. Our multiscale modeling methodology, validated by using experimental results related to the diffusion of lysozyme molecules, constitutes an "ab initio" recipe, for which no experimental data are needed to predict the protein release, and can be tailored in principle to match any different protein and any different surface, thus filling gap between the nano and the macroscale. PMID:17003963

  18. Elimination of the soil moisture effect on the spectra for reflectance prediction of soil salinity using external parameter orthogonalization method

    Science.gov (United States)

    Peng, Xiang; Xu, Chi; Zeng, Wenzhi; Wu, JingWei; Huang, JieSheng

    2016-01-01

    Soil salinization is a common desertification process, especially in arid lands. Hyperspectral remote sensing of salinized soil is favored for its advantages of being efficient and inexpensive. However, soil moisture often jointly has a great influence on the soil reflectance spectra under field conditions. It is a challenge to establish a model to eliminate the effect of soil moisture and quantitatively estimate the salinity contents of slightly and moderately salt-affected soil. A controlled laboratory experiment was conducted by way of continuously monitoring changes of soil moisture and salt content, which was mainly focused on the slightly and moderately salt-affected soil. We investigated the external parameter orthogonalization (EPO) method to remove the effect of soil moisture (4 to 36% in weight base) by preprocessing soil spectral reflectance and establishing the partial least squares regression after EPO preprocessing model (EPO-PLS) to predict soil salt content. Through comparing PLS with EPO-PLS model, R2 and ratio of prediction to deviation rose from 0.604 and 1.063, respectively, to 0.874 and 2.865 for validation data. Root mean square error and bias were, respectively, reduced from 1.163 and 0.141 g/100 g to 0.718 and 0.044 g/100 g. The performance of the model after EPO algorithm preprocessing was improved significantly.

  19. Strength development in concrete with wood ash blended cement and use of soft computing models to predict strength parameters

    Directory of Open Access Journals (Sweden)

    S. Chowdhury

    2015-11-01

    Full Text Available In this study, Wood Ash (WA prepared from the uncontrolled burning of the saw dust is evaluated for its suitability as partial cement replacement in conventional concrete. The saw dust has been acquired from a wood polishing unit. The physical, chemical and mineralogical characteristics of WA is presented and analyzed. The strength parameters (compressive strength, split tensile strength and flexural strength of concrete with blended WA cement are evaluated and studied. Two different water-to-binder ratio (0.4 and 0.45 and five different replacement percentages of WA (5%, 10%, 15%, 18% and 20% including control specimens for both water-to-cement ratio is considered. Results of compressive strength, split tensile strength and flexural strength showed that the strength properties of concrete mixture decreased marginally with increase in wood ash contents, but strength increased with later age. The XRD test results and chemical analysis of WA showed that it contains amorphous silica and thus can be used as cement replacing material. Through the analysis of results obtained in this study, it was concluded that WA could be blended with cement without adversely affecting the strength properties of concrete. Also using a new statistical theory of the Support Vector Machine (SVM, strength parameters were predicted by developing a suitable model and as a result, the application of soft computing in structural engineering has been successfully presented in this research paper.

  20. Strength development in concrete with wood ash blended cement and use of soft computing models to predict strength parameters.

    Science.gov (United States)

    Chowdhury, S; Maniar, A; Suganya, O M

    2015-11-01

    In this study, Wood Ash (WA) prepared from the uncontrolled burning of the saw dust is evaluated for its suitability as partial cement replacement in conventional concrete. The saw dust has been acquired from a wood polishing unit. The physical, chemical and mineralogical characteristics of WA is presented and analyzed. The strength parameters (compressive strength, split tensile strength and flexural strength) of concrete with blended WA cement are evaluated and studied. Two different water-to-binder ratio (0.4 and 0.45) and five different replacement percentages of WA (5%, 10%, 15%, 18% and 20%) including control specimens for both water-to-cement ratio is considered. Results of compressive strength, split tensile strength and flexural strength showed that the strength properties of concrete mixture decreased marginally with increase in wood ash contents, but strength increased with later age. The XRD test results and chemical analysis of WA showed that it contains amorphous silica and thus can be used as cement replacing material. Through the analysis of results obtained in this study, it was concluded that WA could be blended with cement without adversely affecting the strength properties of concrete. Also using a new statistical theory of the Support Vector Machine (SVM), strength parameters were predicted by developing a suitable model and as a result, the application of soft computing in structural engineering has been successfully presented in this research paper. PMID:26644928

  1. Estimation and Prediction of Bioconcentration Factors of Nonionic Organic Chemicals in Fish by Electrotopological State Indices and Structural Parameter

    Institute of Scientific and Technical Information of China (English)

    FENG Chang-Jun; YANG Wei-Hua; MU Lai-Long

    2008-01-01

    Based on the characteristics of atom types, Hall's electrotopological state indices (En) are calculated for 165 nonionic organic compounds. On the basis of the characteristics of substituent and conjugated matrix, a novel molecular structure parameter (G) is defined and calcu- lated for 165 molecules in this paper. En and G show good structural selectivity for organic molecules. G, a satisfactory relationship between bioconcentration factor (BCF) and En, is expressed as: lgBCF = -0.283 + 1.246G + 0.079E42 + 0.351E9 - 0.063E17 (n' = 122, R = 0.967, F = 425.636, s = 0.394), which could provide estimation and prediction for the lgBCF of nonionic organic chemicals. Furthermore, the model is examined to validate overall robustness with Jackknife tests, and the independent variables in model do not exist cross correlation with VIF. All these regression results show that the new parameter G and electrotopological state index have good rationality and efficiency. It is concluded that the En and G will be used widely in quantitative structure-property/activity relationship (QSPR/QSAR) research.

  2. Strength development in concrete with wood ash blended cement and use of soft computing models to predict strength parameters.

    Science.gov (United States)

    Chowdhury, S; Maniar, A; Suganya, O M

    2015-11-01

    In this study, Wood Ash (WA) prepared from the uncontrolled burning of the saw dust is evaluated for its suitability as partial cement replacement in conventional concrete. The saw dust has been acquired from a wood polishing unit. The physical, chemical and mineralogical characteristics of WA is presented and analyzed. The strength parameters (compressive strength, split tensile strength and flexural strength) of concrete with blended WA cement are evaluated and studied. Two different water-to-binder ratio (0.4 and 0.45) and five different replacement percentages of WA (5%, 10%, 15%, 18% and 20%) including control specimens for both water-to-cement ratio is considered. Results of compressive strength, split tensile strength and flexural strength showed that the strength properties of concrete mixture decreased marginally with increase in wood ash contents, but strength increased with later age. The XRD test results and chemical analysis of WA showed that it contains amorphous silica and thus can be used as cement replacing material. Through the analysis of results obtained in this study, it was concluded that WA could be blended with cement without adversely affecting the strength properties of concrete. Also using a new statistical theory of the Support Vector Machine (SVM), strength parameters were predicted by developing a suitable model and as a result, the application of soft computing in structural engineering has been successfully presented in this research paper.

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

    NARCIS (Netherlands)

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

    2013-01-01

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

  4. Factors predicting suicidal ideation in the preceding 12 months among patients attending a community psychiatric outpatient clinic.

    LENUS (Irish Health Repository)

    Anyansi, Tochukwu E

    2013-06-01

    Predictive factors are used to alert the clinician to the necessity of carrying out a suicide risk assessment in those patients whose demographic and clinical characteristics suggest the possibility of suicide.

  5. Developing a clinical utility framework to evaluate prediction models in radiogenomics

    Science.gov (United States)

    Wu, Yirong; Liu, Jie; Munoz del Rio, Alejandro; Page, David C.; Alagoz, Oguzhan; Peissig, Peggy; Onitilo, Adedayo A.; Burnside, Elizabeth S.

    2015-03-01

    Combining imaging and genetic information to predict disease presence and behavior is being codified into an emerging discipline called "radiogenomics." Optimal evaluation methodologies for radiogenomics techniques have not been established. We aim to develop a clinical decision framework based on utility analysis to assess prediction models for breast cancer. Our data comes from a retrospective case-control study, collecting Gail model risk factors, genetic variants (single nucleotide polymorphisms-SNPs), and mammographic features in Breast Imaging Reporting and Data System (BI-RADS) lexicon. We first constructed three logistic regression models built on different sets of predictive features: (1) Gail, (2) Gail+SNP, and (3) Gail+SNP+BI-RADS. Then, we generated ROC curves for three models. After we assigned utility values for each category of findings (true negative, false positive, false negative and true positive), we pursued optimal operating points on ROC curves to achieve maximum expected utility (MEU) of breast cancer diagnosis. We used McNemar's test to compare the predictive performance of the three models. We found that SNPs and BI-RADS features augmented the baseline Gail model in terms of the area under ROC curve (AUC) and MEU. SNPs improved sensitivity of the Gail model (0.276 vs. 0.147) and reduced specificity (0.855 vs. 0.912). When additional mammographic features were added, sensitivity increased to 0.457 and specificity to 0.872. SNPs and mammographic features played a significant role in breast cancer risk estimation (p-value < 0.001). Our decision framework comprising utility analysis and McNemar's test provides a novel framework to evaluate prediction models in the realm of radiogenomics.

  6. Prognostic value of metabolic parameters and clinical impact of {sup 18}F-fluorocholine PET/CT in biochemical recurrent prostate cancer

    Energy Technology Data Exchange (ETDEWEB)

    Colombie, M.; Bailly, C.; Rusu, D.; Rousseau, N. [Institut de Cancerologie de l' Ouest Rene Gauducheau, Nuclear Medicine, 44805 Nantes-St Herblain Cedex (France); Campion, L. [ICO Cancer Center, Statistics, Saint-Herblain (France); Nantes University, Nantes-Angers Cancer Research Center, INSERM U892-CNRS UMR 6299, Nantes (France); Rousseau, T. [Urologic Clinic Nantes-Atlantis, Saint Herblain (France); Mathieu, C. [University Hospital, Nuclear Medicine, Nantes (France); Ferrer, L. [ICO Cancer Center, Physics, Saint-Herblain (France); Kraeber-Bodere, F. [Institut de Cancerologie de l' Ouest Rene Gauducheau, Nuclear Medicine, 44805 Nantes-St Herblain Cedex (France); University Hospital, Nuclear Medicine, Nantes (France); Nantes University, Nantes-Angers Cancer Research Center, INSERM U892-CNRS UMR 6299, Nantes (France); Rousseau, C. [Institut de Cancerologie de l' Ouest Rene Gauducheau, Nuclear Medicine, 44805 Nantes-St Herblain Cedex (France); Nantes University, Nantes-Angers Cancer Research Center, INSERM U892-CNRS UMR 6299, Nantes (France)

    2015-11-15

    To evaluate the therapeutic impact of {sup 18}F-fluorocholine (FCH) PET/CT in biochemical recurrent prostate cancer (PC) and to investigate the value of quantitative FCH PET/CT parameters in predicting progression-free survival (PFS). This retrospective study included 172 consecutive patients with PC who underwent FCH PET/CT for biochemical recurrence. Mean rising PSA was 10.7 ± 35.0 ng/ml. Patients with positive FCH PET were classified into three groups: those with uptake only in the prostatic bed, those with locoregional disease, and those with distant metastases. Referring physicians were asked to indicate the hypothetical therapeutic strategy with and without the FCH PET/CT results. Clinical variables and PET parameters including SUVmax, SUVpeak, SUVmean, total lesion choline kinase activity (TLCKA) and standardized added metabolic activity (SAM) were recorded and a multivariate analysis was performed to determine the factors independently predicting PFS. In 137 of the 172 patients, the FCH PET/CT scan was positive, and of these, 29.9 % (41/137) had prostatic recurrence, 42.3 % (58/137) had pelvic lymph node recurrence with or without prostatic recurrence, and 27.7 % (38/137) had distant metastases. The FCH PET/CT result led to a change in treatment plan in 43.6 % (75/172) of the 172 patients. Treatment was changed in 49.6 % (68/137) of those with a positive FCH PET/CT scan and in 20 % (7/35) of those with a negative FCH PET/CT scan. After a median follow-up of 29.3 months (95 % CI 18.9 - 45.9 months), according to multivariate analysis age <70 years, SAM ≥23 and SUVmean ≥3 were parameters independently predicting PFS. A nomogram constructed using the three parameters showed 49 months of PFS in patients with the best scores (0 or 1) and only 11 months in patients with a poor score (score 3). This study indicates that a positive FCH PET result in PC patients with biochemical recurrence predicts a shorter PFS and confirms the major impact of the FCH PET

  7. Clinical evaluation of nares-vocal cord distance and its correlation with various external body parameters

    Directory of Open Access Journals (Sweden)

    Bhuwan Sareen

    2015-01-01

    Full Text Available Background and Aims: The optimal visualisation of vocal cords during fibreoptic intubation may be utilised for the nares-vocal cord distance (NVD estimation. The present study was conducted to measure NVD and to correlate with various external body parameters. Methods: This study was conducted on 50 males and 50 females. We measured NVD and analysed its relationship with height, nares to tragus of ear distance (NED, nares to angle of mandible distance (NMD, sternal length (SL, thyro-mental distance (TMD, sterno-mental distance (SMD and arm span (AS. Results: The mean NVD of the males was 18.5 ± 1.5 cm, and that of the females was 15.9 ± 1.1 cm. The relationship between the NVD and body height (males P = 0.001, r = 0.463, females P = 0.000, r = 0.555, SL (males P = 0.000, r = 0.463, females P < 0.000, r = 0.801 or AS (males P = 0.000, r = 0.561, females P = 0.000, r = 0.499 showed a significant correlation but NED, NMD, TMD, SMD did not. After combining male and female groups, (n = 100, the correlation of NVD with external body parameters is as follows SL (r = 0.887, height (r = 0.791, AS (r = 0.769, weight (r = 0.531, SMD (r = 0.466, NED (r = 0.459, NMD (r = 0.391, TMD (r = 0.379. Conclusion: The relationship of NVD to external body parameters had strong correlation in all parameters in the combined group; whereas when gender was taken into consideration NVD correlated significantly only with SL, height and AS.

  8. Can clinical colour vision tests be used to predict the results of the Farnsworth lantern test?

    Science.gov (United States)

    Cole, B L; Maddocks, J D

    1998-11-01

    Clinicians usually do not have access to a lantern test when making an occupational assessment of the ability of a person with defective colour vision to recognise signal light colours: they must rely on the results of ordinary clinical tests. While all colour vision defectives fail the Holmes Wright Type B lantern test and most fail the Holmes Wright Type A lantern, 35% of colour vision defectives pass the Farnsworth lantern. Can clinical tests predict who will pass and fail the Farnsworth lantern? We find that a pass (less than two or more diametrical crossings) at the Farnsworth Panel D 15 Dichotomous test has a sensitivity of 0.67 and specificity of 0.94 in predicting a pass or fail at the Farnsworth lantern test: a Nagel range of > 10 has a sensitivity of 0.87 and a specificity of 0.57. We conclude that neither the D 15 nor the Nagel Anomaloscope matching range are satisfactory predictors of performance on the Farnsworth Lantern.

  9. Predicting the risk of suicide by analyzing the text of clinical notes.

    Directory of Open Access Journals (Sweden)

    Chris Poulin

    Full Text Available We developed linguistics-driven prediction models to estimate the risk of suicide. These models were generated from unstructured clinical notes taken from a national sample of U.S. Veterans Administration (VA medical records. We created three matched cohorts: veterans who committed suicide, veterans who used mental health services and did not commit suicide, and veterans who did not use mental health services and did not commit suicide during the observation period (n = 70 in each group. From the clinical notes, we generated datasets of single keywords and multi-word phrases, and constructed prediction models using a machine-learning algorithm based on a genetic programming framework. The resulting inference accuracy was consistently 65% or more. Our data therefore suggests that computerized text analytics can be applied to unstructured medical records to estimate the risk of suicide. The resulting system could allow clinicians to potentially screen seemingly healthy patients at the primary care level, and to continuously evaluate the suicide risk among psychiatric patients.

  10. Integration of noninvasive prenatal prediction of fetal blood group into clinical prenatal care.

    Science.gov (United States)

    Clausen, Frederik Banch

    2014-05-01

    Incompatibility of red blood cell blood group antigens between a pregnant woman and her fetus can cause maternal immunization and, consequently, hemolytic disease of the fetus and newborn. Noninvasive prenatal testing of cell-free fetal DNA can be used to assess the risk of hemolytic disease of the fetus and newborn to fetuses of immunized women. Prediction of the fetal RhD type has been very successful and is now integrated into clinical practice to assist in the management of the pregnancies of RhD immunized women. In addition, noninvasive prediction of the fetal RhD type can be applied to guide targeted prenatal prophylaxis, thus avoiding unnecessary exposure to anti-D in pregnant women. The analytical aspect of noninvasive fetal RHD typing is very robust and accurate, and its routine utilization has demonstrated high sensitivities for fetal RHD detection. A high compliance with administering anti-D is essential for obtaining a clinical effect. Noninvasive fetal typing of RHC/c, RHE/e, and KEL may become more widely used in the future. PMID:24431264

  11. Knee shape might predict clinical outcome after an anterior cruciate ligament rupture.

    Science.gov (United States)

    Eggerding, V; van Kuijk, K S R; van Meer, B L; Bierma-Zeinstra, S M A; van Arkel, E R A; Reijman, M; Waarsing, J H; Meuffels, D E

    2014-06-01

    We have investigated whether shape of the knee can predict the clinical outcome of patients after an anterior cruciate ligament rupture. We used statistical shape modelling to measure the shape of the knee joint of 182 prospectively followed patients on lateral and Rosenberg view radiographs of the knee after a rupture of the anterior cruciate ligament. Subsequently, we associated knee shape with the International Knee Documentation Committee subjective score at two years follow-up. The mean age of patients was 31 years (21 to 51), the majority were male (n = 121) and treated operatively (n = 135). We found two modes (shape variations) that were significantly associated with the subjective score at two years: one for the operatively treated group (p = 0.002) and one for the non-operatively treated group (p = 0.003). Operatively treated patients who had higher subjective scores had a smaller intercondylar notch and a smaller width of the intercondylar eminence. Non-operatively treated patients who scored higher on the subjective score had a more pyramidal intercondylar notch as opposed to one that was more dome-shaped. We conclude that the shape of the femoral notch and the intercondylar eminence is predictive of clinical outcome two years after a rupture of the anterior cruciate ligament.

  12. Clinical manifestations that predict abnormal brain computed tomography (CT in children with minor head injury

    Directory of Open Access Journals (Sweden)

    Nesrin Alharthy

    2015-01-01

    Full Text Available Background: Computed tomography (CT used in pediatric pediatrics brain injury (TBI to ascertain neurological manifestations. Nevertheless, this practice is associated with adverse effects. Reports in the literature suggest incidents of morbidity and mortality in children due to exposure to radiation. Hence, it is found imperative to search for a reliable alternative. Objectives: The aim of this study is to find a reliable clinical alternative to detect an intracranial injury without resorting to the CT. Materials and Methods: Retrospective cross-sectional study was undertaken in patients (1-14 years with blunt head injury and having a Glasgow Coma Scale (GCS of 13-15 who had CT performed on them. Using statistical analysis, the correlation between clinical examination and positive CT manifestation is analyzed for different age-groups and various mechanisms of injury. Results: No statistically significant association between parameteres such as Loss of Consciousness, ′fall′ as mechanism of injury, motor vehicle accidents (MVA, more than two discrete episodes of vomiting and the CT finding of intracranial injury could be noted. Analyzed data have led to believe that GCS of 13 at presentation is the only important clinical predictor of intracranial injury. Conclusion: Retrospective data, small sample size and limited number of factors for assessing clinical manifestation might present constraints on the predictive rule that was derived from this review. Such limitations notwithstanding, the decision to determine which patients should undergo neuroimaging is encouraged to be based on clinical judgments. Further analysis with higher sample sizes may be required to authenticate and validate findings.