Metric Selection for Evaluation of Human Supervisory Control Systems

DTIC Science & Technology

2009-12-01

finding a significant effect when there is none becomes more likely. The inflation of type I error due to multiple dependent variables can be handled...with multivariate analysis techniques, such as Multivariate Analysis of Variance (MANOVA) (Johnson & Wichern, 2002). However, it should be noted that...the few significant differences among many insignificant ones. The best way to avoid failure to identify significant differences is to design an

Linear, multivariable robust control with a mu perspective

NASA Technical Reports Server (NTRS)

Packard, Andy; Doyle, John; Balas, Gary

1993-01-01

The structured singular value is a linear algebra tool developed to study a particular class of matrix perturbation problems arising in robust feedback control of multivariable systems. These perturbations are called linear fractional, and are a natural way to model many types of uncertainty in linear systems, including state-space parameter uncertainty, multiplicative and additive unmodeled dynamics uncertainty, and coprime factor and gap metric uncertainty. The structured singular value theory provides a natural extension of classical SISO robustness measures and concepts to MIMO systems. The structured singular value analysis, coupled with approximate synthesis methods, make it possible to study the tradeoff between performance and uncertainty that occurs in all feedback systems. In MIMO systems, the complexity of the spatial interactions in the loop gains make it difficult to heuristically quantify the tradeoffs that must occur. This paper examines the role played by the structured singular value (and its computable bounds) in answering these questions, as well as its role in the general robust, multivariable control analysis and design problem.

Hypothyroidism among SLE patients: Case-control study.

PubMed

Watad, Abdulla; Mahroum, Naim; Whitby, Aaron; Gertel, Smadar; Comaneshter, Doron; Cohen, Arnon D; Amital, Howard

2016-05-01

The prevalence of hypothyroidism in SLE patients varies considerably and early reports were mainly based on small cohorts. To investigate the association between SLE and hypothyroidism. Patients with SLE were compared with age and sex-matched controls regarding the proportion of hypothyroidism in a case-control study. Chi-square and t-tests were used for univariate analysis and a logistic regression model was used for multivariate analysis. The study was performed utilizing the medical database of Clalit Health Services. The study included 5018 patients with SLE and 25,090 age and sex-matched controls. The proportion of hypothyroidism in patients with SLE was increased compared with the prevalence in controls (15.58% and 5.75%, respectively, P<0.001). In a multivariate analysis, SLE was associated with hypothyroidism (odds ratio 2.644, 95% confidence interval 2.405-2.908). Patients with SLE have a greater proportion of hypothyroidism than matched controls. Therefore, physicians treating patients with SLE should be aware of the possibility of thyroid dysfunction. Copyright © 2016 Elsevier B.V. All rights reserved.

Characterizing multivariate decoding models based on correlated EEG spectral features

PubMed Central

McFarland, Dennis J.

2013-01-01

Objective Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Methods Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). Results The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Conclusions Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. Significance While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. PMID:23466267

Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions

PubMed Central

2013-01-01

Background Recently, one of the greatest challenges in genome-wide association studies is to detect gene-gene and/or gene-environment interactions for common complex human diseases. Ritchie et al. (2001) proposed multifactor dimensionality reduction (MDR) method for interaction analysis. MDR is a combinatorial approach to reduce multi-locus genotypes into high-risk and low-risk groups. Although MDR has been widely used for case-control studies with binary phenotypes, several extensions have been proposed. One of these methods, a generalized MDR (GMDR) proposed by Lou et al. (2007), allows adjusting for covariates and applying to both dichotomous and continuous phenotypes. GMDR uses the residual score of a generalized linear model of phenotypes to assign either high-risk or low-risk group, while MDR uses the ratio of cases to controls. Methods In this study, we propose multivariate GMDR, an extension of GMDR for multivariate phenotypes. Jointly analysing correlated multivariate phenotypes may have more power to detect susceptible genes and gene-gene interactions. We construct generalized estimating equations (GEE) with multivariate phenotypes to extend generalized linear models. Using the score vectors from GEE we discriminate high-risk from low-risk groups. We applied the multivariate GMDR method to the blood pressure data of the 7,546 subjects from the Korean Association Resource study: systolic blood pressure (SBP) and diastolic blood pressure (DBP). We compare the results of multivariate GMDR for SBP and DBP to the results from separate univariate GMDR for SBP and DBP, respectively. We also applied the multivariate GMDR method to the repeatedly measured hypertension status from 5,466 subjects and compared its result with those of univariate GMDR at each time point. Results Results from the univariate GMDR and multivariate GMDR in two-locus model with both blood pressures and hypertension phenotypes indicate best combinations of SNPs whose interaction has significant association with risk for high blood pressures or hypertension. Although the test balanced accuracy (BA) of multivariate analysis was not always greater than that of univariate analysis, the multivariate BAs were more stable with smaller standard deviations. Conclusions In this study, we have developed multivariate GMDR method using GEE approach. It is useful to use multivariate GMDR with correlated multiple phenotypes of interests. PMID:24565370

Multivariate analysis in the pharmaceutical industry: enabling process understanding and improvement in the PAT and QbD era.

PubMed

Ferreira, Ana P; Tobyn, Mike

2015-01-01

In the pharmaceutical industry, chemometrics is rapidly establishing itself as a tool that can be used at every step of product development and beyond: from early development to commercialization. This set of multivariate analysis methods allows the extraction of information contained in large, complex data sets thus contributing to increase product and process understanding which is at the core of the Food and Drug Administration's Process Analytical Tools (PAT) Guidance for Industry and the International Conference on Harmonisation's Pharmaceutical Development guideline (Q8). This review is aimed at providing pharmaceutical industry professionals an introduction to multivariate analysis and how it is being adopted and implemented by companies in the transition from "quality-by-testing" to "quality-by-design". It starts with an introduction to multivariate analysis and the two methods most commonly used: principal component analysis and partial least squares regression, their advantages, common pitfalls and requirements for their effective use. That is followed with an overview of the diverse areas of application of multivariate analysis in the pharmaceutical industry: from the development of real-time analytical methods to definition of the design space and control strategy, from formulation optimization during development to the application of quality-by-design principles to improve manufacture of existing commercial products.

Epidemiologic methods in clinical trials.

PubMed

Rothman, K J

1977-04-01

Epidemiologic methods developed to control confounding in non-experimental studies are equally applicable for experiments. In experiments, most confounding is usually controlled by random allocation of subjects to treatment groups, but randomization does not preclude confounding except for extremely large studies, the degree of confounding expected being inversely related to the size of the treatment groups. In experiments, as in non-experimental studies, the extent of confounding for each risk indicator should be assessed, and if sufficiently large, controlled. Confounding is properly assessed by comparing the unconfounded effect estimate to the crude effect estimate; a common error is to assess confounding by statistical tests of significance. Assessment of confounding involves its control as a prerequisite. Control is most readily and cogently achieved by stratification of the data, though with many factors to control simultaneously, multivariate analysis or a combination of multivariate analysis and stratification might be necessary.

Chemical Discrimination of Cortex Phellodendri amurensis and Cortex Phellodendri chinensis by Multivariate Analysis Approach.

PubMed

Sun, Hui; Wang, Huiyu; Zhang, Aihua; Yan, Guangli; Han, Ying; Li, Yuan; Wu, Xiuhong; Meng, Xiangcai; Wang, Xijun

2016-01-01

As herbal medicines have an important position in health care systems worldwide, their current assessment, and quality control are a major bottleneck. Cortex Phellodendri chinensis (CPC) and Cortex Phellodendri amurensis (CPA) are widely used in China, however, how to identify species of CPA and CPC has become urgent. In this study, multivariate analysis approach was performed to the investigation of chemical discrimination of CPA and CPC. Principal component analysis showed that two herbs could be separated clearly. The chemical markers such as berberine, palmatine, phellodendrine, magnoflorine, obacunone, and obaculactone were identified through the orthogonal partial least squared discriminant analysis, and were identified tentatively by the accurate mass of quadruple-time-of-flight mass spectrometry. A total of 29 components can be used as the chemical markers for discrimination of CPA and CPC. Of them, phellodenrine is significantly higher in CPC than that of CPA, whereas obacunone and obaculactone are significantly higher in CPA than that of CPC. The present study proves that multivariate analysis approach based chemical analysis greatly contributes to the investigation of CPA and CPC, and showed that the identified chemical markers as a whole should be used to discriminate the two herbal medicines, and simultaneously the results also provided chemical information for their quality assessment. Multivariate analysis approach was performed to the investigate the herbal medicineThe chemical markers were identified through multivariate analysis approachA total of 29 components can be used as the chemical markers. UPLC-Q/TOF-MS-based multivariate analysis method for the herbal medicine samples Abbreviations used: CPC: Cortex Phellodendri chinensis, CPA: Cortex Phellodendri amurensis, PCA: Principal component analysis, OPLS-DA: Orthogonal partial least squares discriminant analysis, BPI: Base peaks ion intensity.

Practical robustness measures in multivariable control system analysis. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Lehtomaki, N. A.

1981-01-01

The robustness of the stability of multivariable linear time invariant feedback control systems with respect to model uncertainty is considered using frequency domain criteria. Available robustness tests are unified under a common framework based on the nature and structure of model errors. These results are derived using a multivariable version of Nyquist's stability theorem in which the minimum singular value of the return difference transfer matrix is shown to be the multivariable generalization of the distance to the critical point on a single input, single output Nyquist diagram. Using the return difference transfer matrix, a very general robustness theorem is presented from which all of the robustness tests dealing with specific model errors may be derived. The robustness tests that explicitly utilized model error structure are able to guarantee feedback system stability in the face of model errors of larger magnitude than those robustness tests that do not. The robustness of linear quadratic Gaussian control systems are analyzed.

Spectroscopic analysis and control

DOEpatents

Tate; , James D.; Reed, Christopher J.; Domke, Christopher H.; Le, Linh; Seasholtz, Mary Beth; Weber, Andy; Lipp, Charles

2017-04-18

Apparatus for spectroscopic analysis which includes a tunable diode laser spectrometer having a digital output signal and a digital computer for receiving the digital output signal from the spectrometer, the digital computer programmed to process the digital output signal using a multivariate regression algorithm. In addition, a spectroscopic method of analysis using such apparatus. Finally, a method for controlling an ethylene cracker hydrogenator.

Extending Inferential Group Analysis in Type 2 Diabetic Patients with Multivariate GLM Implemented in SPM8.

PubMed

Ferreira, Fábio S; Pereira, João M S; Duarte, João V; Castelo-Branco, Miguel

2017-01-01

Although voxel based morphometry studies are still the standard for analyzing brain structure, their dependence on massive univariate inferential methods is a limiting factor. A better understanding of brain pathologies can be achieved by applying inferential multivariate methods, which allow the study of multiple dependent variables, e.g. different imaging modalities of the same subject. Given the widespread use of SPM software in the brain imaging community, the main aim of this work is the implementation of massive multivariate inferential analysis as a toolbox in this software package. applied to the use of T1 and T2 structural data from diabetic patients and controls. This implementation was compared with the traditional ANCOVA in SPM and a similar multivariate GLM toolbox (MRM). We implemented the new toolbox and tested it by investigating brain alterations on a cohort of twenty-eight type 2 diabetes patients and twenty-six matched healthy controls, using information from both T1 and T2 weighted structural MRI scans, both separately - using standard univariate VBM - and simultaneously, with multivariate analyses. Univariate VBM replicated predominantly bilateral changes in basal ganglia and insular regions in type 2 diabetes patients. On the other hand, multivariate analyses replicated key findings of univariate results, while also revealing the thalami as additional foci of pathology. While the presented algorithm must be further optimized, the proposed toolbox is the first implementation of multivariate statistics in SPM8 as a user-friendly toolbox, which shows great potential and is ready to be validated in other clinical cohorts and modalities.

Extending Inferential Group Analysis in Type 2 Diabetic Patients with Multivariate GLM Implemented in SPM8

PubMed Central

Ferreira, Fábio S.; Pereira, João M.S.; Duarte, João V.; Castelo-Branco, Miguel

2017-01-01

Background: Although voxel based morphometry studies are still the standard for analyzing brain structure, their dependence on massive univariate inferential methods is a limiting factor. A better understanding of brain pathologies can be achieved by applying inferential multivariate methods, which allow the study of multiple dependent variables, e.g. different imaging modalities of the same subject. Objective: Given the widespread use of SPM software in the brain imaging community, the main aim of this work is the implementation of massive multivariate inferential analysis as a toolbox in this software package. applied to the use of T1 and T2 structural data from diabetic patients and controls. This implementation was compared with the traditional ANCOVA in SPM and a similar multivariate GLM toolbox (MRM). Method: We implemented the new toolbox and tested it by investigating brain alterations on a cohort of twenty-eight type 2 diabetes patients and twenty-six matched healthy controls, using information from both T1 and T2 weighted structural MRI scans, both separately – using standard univariate VBM - and simultaneously, with multivariate analyses. Results: Univariate VBM replicated predominantly bilateral changes in basal ganglia and insular regions in type 2 diabetes patients. On the other hand, multivariate analyses replicated key findings of univariate results, while also revealing the thalami as additional foci of pathology. Conclusion: While the presented algorithm must be further optimized, the proposed toolbox is the first implementation of multivariate statistics in SPM8 as a user-friendly toolbox, which shows great potential and is ready to be validated in other clinical cohorts and modalities. PMID:28761571

Characterizing multivariate decoding models based on correlated EEG spectral features.

PubMed

McFarland, Dennis J

2013-07-01

Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Wind Turbine Load Mitigation based on Multivariable Robust Control and Blade Root Sensors

NASA Astrophysics Data System (ADS)

Díaz de Corcuera, A.; Pujana-Arrese, A.; Ezquerra, J. M.; Segurola, E.; Landaluze, J.

2014-12-01

This paper presents two H∞ multivariable robust controllers based on blade root sensors' information for individual pitch angle control. The wind turbine of 5 MW defined in the Upwind European project is the reference non-linear model used in this research work, which has been modelled in the GH Bladed 4.0 software package. The main objective of these controllers is load mitigation in different components of wind turbines during power production in the above rated control zone. The first proposed multi-input multi-output (MIMO) individual pitch H" controller mitigates the wind effect on the tower side-to-side acceleration and reduces the asymmetrical loads which appear in the rotor due to its misalignment. The second individual pitch H" multivariable controller mitigates the loads on the three blades reducing the wind effect on the bending flapwise and edgewise momentums in the blades. The designed H" controllers have been validated in GH Bladed and an exhaustive analysis has been carried out to calculate fatigue load reduction on wind turbine components, as well as to analyze load mitigation in some extreme cases.

On the Numerical Formulation of Parametric Linear Fractional Transformation (LFT) Uncertainty Models for Multivariate Matrix Polynomial Problems

NASA Technical Reports Server (NTRS)

Belcastro, Christine M.

1998-01-01

Robust control system analysis and design is based on an uncertainty description, called a linear fractional transformation (LFT), which separates the uncertain (or varying) part of the system from the nominal system. These models are also useful in the design of gain-scheduled control systems based on Linear Parameter Varying (LPV) methods. Low-order LFT models are difficult to form for problems involving nonlinear parameter variations. This paper presents a numerical computational method for constructing and LFT model for a given LPV model. The method is developed for multivariate polynomial problems, and uses simple matrix computations to obtain an exact low-order LFT representation of the given LPV system without the use of model reduction. Although the method is developed for multivariate polynomial problems, multivariate rational problems can also be solved using this method by reformulating the rational problem into a polynomial form.

Multivariate Radiological-Based Models for the Prediction of Future Knee Pain: Data from the OAI

PubMed Central

Galván-Tejada, Jorge I.; Celaya-Padilla, José M.; Treviño, Victor; Tamez-Peña, José G.

2015-01-01

In this work, the potential of X-ray based multivariate prognostic models to predict the onset of chronic knee pain is presented. Using X-rays quantitative image assessments of joint-space-width (JSW) and paired semiquantitative central X-ray scores from the Osteoarthritis Initiative (OAI), a case-control study is presented. The pain assessments of the right knee at the baseline and the 60-month visits were used to screen for case/control subjects. Scores were analyzed at the time of pain incidence (T-0), the year prior incidence (T-1), and two years before pain incidence (T-2). Multivariate models were created by a cross validated elastic-net regularized generalized linear models feature selection tool. Univariate differences between cases and controls were reported by AUC, C-statistics, and ODDs ratios. Univariate analysis indicated that the medial osteophytes were significantly more prevalent in cases than controls: C-stat 0.62, 0.62, and 0.61, at T-0, T-1, and T-2, respectively. The multivariate JSW models significantly predicted pain: AUC = 0.695, 0.623, and 0.620, at T-0, T-1, and T-2, respectively. Semiquantitative multivariate models predicted paint with C-stat = 0.671, 0.648, and 0.645 at T-0, T-1, and T-2, respectively. Multivariate models derived from plain X-ray radiography assessments may be used to predict subjects that are at risk of developing knee pain. PMID:26504490

Controlled pattern imputation for sensitivity analysis of longitudinal binary and ordinal outcomes with nonignorable dropout.

PubMed

Tang, Yongqiang

2018-04-30

The controlled imputation method refers to a class of pattern mixture models that have been commonly used as sensitivity analyses of longitudinal clinical trials with nonignorable dropout in recent years. These pattern mixture models assume that participants in the experimental arm after dropout have similar response profiles to the control participants or have worse outcomes than otherwise similar participants who remain on the experimental treatment. In spite of its popularity, the controlled imputation has not been formally developed for longitudinal binary and ordinal outcomes partially due to the lack of a natural multivariate distribution for such endpoints. In this paper, we propose 2 approaches for implementing the controlled imputation for binary and ordinal data based respectively on the sequential logistic regression and the multivariate probit model. Efficient Markov chain Monte Carlo algorithms are developed for missing data imputation by using the monotone data augmentation technique for the sequential logistic regression and a parameter-expanded monotone data augmentation scheme for the multivariate probit model. We assess the performance of the proposed procedures by simulation and the analysis of a schizophrenia clinical trial and compare them with the fully conditional specification, last observation carried forward, and baseline observation carried forward imputation methods. Copyright © 2018 John Wiley & Sons, Ltd.

A multiplexed analysis approach identifies new association of inflammatory proteins in patients with overactive bladder

PubMed Central

Ma, Emily; Vetter, Joel; Bliss, Laura; Lai, H. Henry; Mysorekar, Indira U.

2016-01-01

Overactive bladder (OAB) is a common debilitating bladder condition with unknown etiology and limited diagnostic modalities. Here, we explored a novel high-throughput and unbiased multiplex approach with cellular and molecular components in a well-characterized patient cohort to identify biomarkers that could be reliably used to distinguish OAB from controls or provide insights into underlying etiology. As a secondary analysis, we determined whether this method could discriminate between OAB and other chronic bladder conditions. We analyzed plasma samples from healthy volunteers (n = 19) and patients diagnosed with OAB, interstitial cystitis/bladder pain syndrome (IC/BPS), or urinary tract infections (UTI; n = 51) for proinflammatory, chemokine, cytokine, angiogenesis, and vascular injury factors using Meso Scale Discovery (MSD) analysis and urinary cytological analysis. Wilcoxon rank-sum tests were used to perform univariate and multivariate comparisons between patient groups (controls, OAB, IC/BPS, and UTI). Multivariate logistic regression models were fit for each MSD analyte on 1) OAB patients and controls, 2) OAB and IC/BPS patients, and 3) OAB and UTI patients. Age, race, and sex were included as independent variables in all multivariate analysis. Receiver operating characteristic (ROC) curves were generated to determine the diagnostic potential of a given analyte. Our findings demonstrate that five analytes, i.e., interleukin 4, TNF-α, macrophage inflammatory protein-1β, serum amyloid A, and Tie2 can reliably differentiate OAB relative to controls and can be used to distinguish OAB from the other conditions. Together, our pilot study suggests a molecular imbalance in inflammatory proteins may contribute to OAB pathogenesis. PMID:27029431

A Comparison of Multivariable Control Design Techniques for a Turbofan Engine Control

NASA Technical Reports Server (NTRS)

Garg, Sanjay; Watts, Stephen R.

1995-01-01

This paper compares two previously published design procedures for two different multivariable control design techniques for application to a linear engine model of a jet engine. The two multivariable control design techniques compared were the Linear Quadratic Gaussian with Loop Transfer Recovery (LQG/LTR) and the H-Infinity synthesis. The two control design techniques were used with specific previously published design procedures to synthesize controls which would provide equivalent closed loop frequency response for the primary control loops while assuring adequate loop decoupling. The resulting controllers were then reduced in order to minimize the programming and data storage requirements for a typical implementation. The reduced order linear controllers designed by each method were combined with the linear model of an advanced turbofan engine and the system performance was evaluated for the continuous linear system. Included in the performance analysis are the resulting frequency and transient responses as well as actuator usage and rate capability for each design method. The controls were also analyzed for robustness with respect to structured uncertainties in the unmodeled system dynamics. The two controls were then compared for performance capability and hardware implementation issues.

Multivariate interactive digital analysis system /MIDAS/ - A new fast multispectral recognition system

NASA Technical Reports Server (NTRS)

Kriegler, F.; Marshall, R.; Lampert, S.; Gordon, M.; Cornell, C.; Kistler, R.

1973-01-01

The MIDAS system is a prototype, multiple-pipeline digital processor mechanizing the multivariate-Gaussian, maximum-likelihood decision algorithm operating at 200,000 pixels/second. It incorporates displays and film printer equipment under control of a general purpose midi-computer and possesses sufficient flexibility that operational versions of the equipment may be subsequently specified as subsets of the system.

A correlate of HIV-1 control consisting of both innate and adaptive immune parameters best predicts viral load by multivariable analysis in HIV-1 infected viremic controllers and chronically-infected non-controllers.

PubMed

Tomescu, Costin; Liu, Qin; Ross, Brian N; Yin, Xiangfan; Lynn, Kenneth; Mounzer, Karam C; Kostman, Jay R; Montaner, Luis J

2014-01-01

HIV-1 infected viremic controllers maintain durable viral suppression below 2000 copies viral RNA/ml without anti-retroviral therapy (ART), and the immunological factor(s) associated with host control in presence of low but detectable viral replication are of considerable interest. Here, we utilized a multivariable analysis to identify which innate and adaptive immune parameters best correlated with viral control utilizing a cohort of viremic controllers (median 704 viral RNA/ml) and non-controllers (median 21,932 viral RNA/ml) that were matched for similar CD4+ T cell counts in the absence of ART. We observed that HIV-1 Gag-specific CD8+ T cell responses were preferentially targeted over Pol-specific responses in viremic controllers (p = 0.0137), while Pol-specific responses were positively associated with viral load (rho = 0.7753, p = 0.0001, n = 23). Viremic controllers exhibited significantly higher NK and plasmacytoid dendritic cells (pDC) frequency as well as retained expression of the NK CD16 receptor and strong target cell-induced NK cell IFN-gamma production compared to non-controllers (p<0.05). Despite differences in innate and adaptive immune function however, both viremic controllers (p<0.05) and non-controller subjects (p<0.001) exhibited significantly increased CD8+ T cell activation and spontaneous NK cell degranulation compared to uninfected donors. Overall, we identified that a combination of innate (pDC frequency) and adaptive (Pol-specific CD8+ T cell responses) immune parameters best predicted viral load (R2 = 0.5864, p = 0.0021, n = 17) by a multivariable analysis. Together, this data indicates that preferential Gag-specific over Pol-specific CD8+ T cell responses along with a retention of functional innate subsets best predict host control over viral replication in HIV-1 infected viremic controllers compared to chronically-infected non-controllers.

FREQ: A computational package for multivariable system loop-shaping procedures

NASA Technical Reports Server (NTRS)

Giesy, Daniel P.; Armstrong, Ernest S.

1989-01-01

Many approaches in the field of linear, multivariable time-invariant systems analysis and controller synthesis employ loop-sharing procedures wherein design parameters are chosen to shape frequency-response singular value plots of selected transfer matrices. A software package, FREQ, is documented for computing within on unified framework many of the most used multivariable transfer matrices for both continuous and discrete systems. The matrices are evaluated at user-selected frequency-response values, and singular values against frequency. Example computations are presented to demonstrate the use of the FREQ code.

Multivariate approaches for stability control of the olive oil reference materials for sensory analysis - part I: framework and fundamentals.

PubMed

Valverde-Som, Lucia; Ruiz-Samblás, Cristina; Rodríguez-García, Francisco P; Cuadros-Rodríguez, Luis

2018-02-09

Virgin olive oil is the only food product for which sensory analysis is regulated to classify it in different quality categories. To harmonize the results of the sensorial method, the use of standards or reference materials is crucial. The stability of sensory reference materials is required to enable their suitable control, aiming to confirm that their specific target values are maintained on an ongoing basis. Currently, such stability is monitored by means of sensory analysis and the sensory panels are in the paradoxical situation of controlling the standards that are devoted to controlling the panels. In the present study, several approaches based on similarity analysis are exploited. For each approach, the specific methodology to build a proper multivariate control chart to monitor the stability of the sensory properties is explained and discussed. The normalized Euclidean and Mahalanobis distances, the so-called nearness and hardiness indices respectively, have been defined as new similarity indices to range the values from 0 to 1. Also, the squared mean from Hotelling's T 2 -statistic and Q 2 -statistic has been proposed as another similarity index. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

TU-FG-201-05: Varian MPC as a Statistical Process Control Tool

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carver, A; Rowbottom, C

Purpose: Quality assurance in radiotherapy requires the measurement of various machine parameters to ensure they remain within permitted values over time. In Truebeam release 2.0 the Machine Performance Check (MPC) was released allowing beam output and machine axis movements to be assessed in a single test. We aim to evaluate the Varian Machine Performance Check (MPC) as a tool for Statistical Process Control (SPC). Methods: Varian’s MPC tool was used on three Truebeam and one EDGE linac for a period of approximately one year. MPC was commissioned against independent systems. After this period the data were reviewed to determine whethermore » or not the MPC was useful as a process control tool. Analyses on individual tests were analysed using Shewhart control plots, using Matlab for analysis. Principal component analysis was used to determine if a multivariate model was of any benefit in analysing the data. Results: Control charts were found to be useful to detect beam output changes, worn T-nuts and jaw calibration issues. Upper and lower control limits were defined at the 95% level. Multivariate SPC was performed using Principal Component Analysis. We found little evidence of clustering beyond that which might be naively expected such as beam uniformity and beam output. Whilst this makes multivariate analysis of little use it suggests that each test is giving independent information. Conclusion: The variety of independent parameters tested in MPC makes it a sensitive tool for routine machine QA. We have determined that using control charts in our QA programme would rapidly detect changes in machine performance. The use of control charts allows large quantities of tests to be performed on all linacs without visual inspection of all results. The use of control limits alerts users when data are inconsistent with previous measurements before they become out of specification. A. Carver has received a speaker’s honorarium from Varian.« less

Pretreatment health behaviors predict survival among patients with head and neck squamous cell carcinoma.

PubMed

Duffy, Sonia A; Ronis, David L; McLean, Scott; Fowler, Karen E; Gruber, Stephen B; Wolf, Gregory T; Terrell, Jeffrey E

2009-04-20

Our prior work has shown that the health behaviors of head and neck cancer patients are interrelated and are associated with quality of life; however, other than smoking, the relationship between health behaviors and survival is unclear. A prospective cohort study was conducted to determine the relationship between five pretreatment health behaviors (smoking, alcohol, diet, physical activity, and sleep) and all-cause survival among 504 head and neck cancer patients. Smoking status was the strongest predictor of survival, with both current smokers (hazard ratio [HR] = 2.4; 95% CI, 1.3 to 4.4) and former smokers (HR = 2.0; 95% CI, 1.2 to 3.5) showing significant associations with poor survival. Problem drinking was associated with survival in the univariate analysis (HR = 1.4; 95% CI, 1.0 to 2.0) but lost significance when controlling for other factors. Low fruit intake was negatively associated with survival in the univariate analysis only (HR = 1.6; 95% CI, 1.1 to 2.1), whereas vegetable intake was not significant in either univariate or multivariate analyses. Although physical activity was associated with survival in the univariate analysis (HR = 0.95; 95% CI, 0.93 to 0.97), it was not significant in the multivariate model. Sleep was not significantly associated with survival in either univariate or multivariate analysis. Control variables that were also independently associated with survival in the multivariate analysis were age, education, tumor site, cancer stage, and surgical treatment. Variation in selected pretreatment health behaviors (eg, smoking, fruit intake, and physical activity) in this population is associated with variation in survival.

Input-output oriented computation algorithms for the control of large flexible structures

NASA Technical Reports Server (NTRS)

Minto, K. D.

1989-01-01

An overview is given of work in progress aimed at developing computational algorithms addressing two important aspects in the control of large flexible space structures; namely, the selection and placement of sensors and actuators, and the resulting multivariable control law design problem. The issue of sensor/actuator set selection is particularly crucial to obtaining a satisfactory control design, as clearly a poor choice will inherently limit the degree to which good control can be achieved. With regard to control law design, the researchers are driven by concerns stemming from the practical issues associated with eventual implementation of multivariable control laws, such as reliability, limit protection, multimode operation, sampling rate selection, processor throughput, etc. Naturally, the burden imposed by dealing with these aspects of the problem can be reduced by ensuring that the complexity of the compensator is minimized. Our approach to these problems is based on extensions to input/output oriented techniques that have proven useful in the design of multivariable control systems for aircraft engines. In particular, researchers are exploring the use of relative gain analysis and the condition number as a means of quantifying the process of sensor/actuator selection and placement for shape control of a large space platform.

MGAS: a powerful tool for multivariate gene-based genome-wide association analysis.

PubMed

Van der Sluis, Sophie; Dolan, Conor V; Li, Jiang; Song, Youqiang; Sham, Pak; Posthuma, Danielle; Li, Miao-Xin

2015-04-01

Standard genome-wide association studies, testing the association between one phenotype and a large number of single nucleotide polymorphisms (SNPs), are limited in two ways: (i) traits are often multivariate, and analysis of composite scores entails loss in statistical power and (ii) gene-based analyses may be preferred, e.g. to decrease the multiple testing problem. Here we present a new method, multivariate gene-based association test by extended Simes procedure (MGAS), that allows gene-based testing of multivariate phenotypes in unrelated individuals. Through extensive simulation, we show that under most trait-generating genotype-phenotype models MGAS has superior statistical power to detect associated genes compared with gene-based analyses of univariate phenotypic composite scores (i.e. GATES, multiple regression), and multivariate analysis of variance (MANOVA). Re-analysis of metabolic data revealed 32 False Discovery Rate controlled genome-wide significant genes, and 12 regions harboring multiple genes; of these 44 regions, 30 were not reported in the original analysis. MGAS allows researchers to conduct their multivariate gene-based analyses efficiently, and without the loss of power that is often associated with an incorrectly specified genotype-phenotype models. MGAS is freely available in KGG v3.0 (http://statgenpro.psychiatry.hku.hk/limx/kgg/download.php). Access to the metabolic dataset can be requested at dbGaP (https://dbgap.ncbi.nlm.nih.gov/). The R-simulation code is available from http://ctglab.nl/people/sophie_van_der_sluis. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Assessment of trace elements levels in patients with Type 2 diabetes using multivariate statistical analysis.

PubMed

Badran, M; Morsy, R; Soliman, H; Elnimr, T

2016-01-01

The trace elements metabolism has been reported to possess specific roles in the pathogenesis and progress of diabetes mellitus. Due to the continuous increase in the population of patients with Type 2 diabetes (T2D), this study aims to assess the levels and inter-relationships of fast blood glucose (FBG) and serum trace elements in Type 2 diabetic patients. This study was conducted on 40 Egyptian Type 2 diabetic patients and 36 healthy volunteers (Hospital of Tanta University, Tanta, Egypt). The blood serum was digested and then used to determine the levels of 24 trace elements using an inductive coupled plasma mass spectroscopy (ICP-MS). Multivariate statistical analysis depended on correlation coefficient, cluster analysis (CA) and principal component analysis (PCA), were used to analysis the data. The results exhibited significant changes in FBG and eight of trace elements, Zn, Cu, Se, Fe, Mn, Cr, Mg, and As, levels in the blood serum of Type 2 diabetic patients relative to those of healthy controls. The statistical analyses using multivariate statistical techniques were obvious in the reduction of the experimental variables, and grouping the trace elements in patients into three clusters. The application of PCA revealed a distinct difference in associations of trace elements and their clustering patterns in control and patients group in particular for Mg, Fe, Cu, and Zn that appeared to be the most crucial factors which related with Type 2 diabetes. Therefore, on the basis of this study, the contributors of trace elements content in Type 2 diabetic patients can be determine and specify with correlation relationship and multivariate statistical analysis, which confirm that the alteration of some essential trace metals may play a role in the development of diabetes mellitus. Copyright © 2015 Elsevier GmbH. All rights reserved.

Biostatistics Series Module 10: Brief Overview of Multivariate Methods.

PubMed

Hazra, Avijit; Gogtay, Nithya

2017-01-01

Multivariate analysis refers to statistical techniques that simultaneously look at three or more variables in relation to the subjects under investigation with the aim of identifying or clarifying the relationships between them. These techniques have been broadly classified as dependence techniques, which explore the relationship between one or more dependent variables and their independent predictors, and interdependence techniques, that make no such distinction but treat all variables equally in a search for underlying relationships. Multiple linear regression models a situation where a single numerical dependent variable is to be predicted from multiple numerical independent variables. Logistic regression is used when the outcome variable is dichotomous in nature. The log-linear technique models count type of data and can be used to analyze cross-tabulations where more than two variables are included. Analysis of covariance is an extension of analysis of variance (ANOVA), in which an additional independent variable of interest, the covariate, is brought into the analysis. It tries to examine whether a difference persists after "controlling" for the effect of the covariate that can impact the numerical dependent variable of interest. Multivariate analysis of variance (MANOVA) is a multivariate extension of ANOVA used when multiple numerical dependent variables have to be incorporated in the analysis. Interdependence techniques are more commonly applied to psychometrics, social sciences and market research. Exploratory factor analysis and principal component analysis are related techniques that seek to extract from a larger number of metric variables, a smaller number of composite factors or components, which are linearly related to the original variables. Cluster analysis aims to identify, in a large number of cases, relatively homogeneous groups called clusters, without prior information about the groups. The calculation intensive nature of multivariate analysis has so far precluded most researchers from using these techniques routinely. The situation is now changing with wider availability, and increasing sophistication of statistical software and researchers should no longer shy away from exploring the applications of multivariate methods to real-life data sets.

Hyperthyroidism association with SLE, lessons from real-life data--A case-control study.

PubMed

Watad, Abdulla; Cohen, Arnon D; Comaneshter, Doron; Tekes-Manova, Dorit; Amital, Howard

2016-01-01

Despite the frequently encountered association between thyroid disease and systemic lupus erythematosus (SLE) is well known, it is of surprise that only several reports compromised of small population size support this observation. To investigate the association of comorbid SLE and hyperthyroidism. Using the database of the largest health maintenance organization (HMO) in Israel, the Clalit Health Services, we searched for the co-existence of SLE and hyperthyroidism. Patients with SLE were compared with age- and sex-matched controls regarding the prevalence of hyperthyroidism in a case-control study. Chi-square and t-tests were used for univariate analysis and a logistic regression model was used for multivariate analysis. The study included 5018 patients with SLE and 25,090 age- and sex- matched controls. The prevalence of hyperthyroidism in patients with SLE was increased compared with the prevalence in controls (2.59% and 0.91%, respectively, p < 0.001). In a multivariate analysis, SLE was associated with hyperthyroidism (odds ratio 2.52, 95% confidence interval 2.028-3.137). Patients with SLE have a greater prevalence of hyperthyroidism than matched controls. Therefore, physicians treating patients with SLE should be aware of this possibility of this thyroid dysfunction.

Control-group feature normalization for multivariate pattern analysis of structural MRI data using the support vector machine.

PubMed

Linn, Kristin A; Gaonkar, Bilwaj; Satterthwaite, Theodore D; Doshi, Jimit; Davatzikos, Christos; Shinohara, Russell T

2016-05-15

Normalization of feature vector values is a common practice in machine learning. Generally, each feature value is standardized to the unit hypercube or by normalizing to zero mean and unit variance. Classification decisions based on support vector machines (SVMs) or by other methods are sensitive to the specific normalization used on the features. In the context of multivariate pattern analysis using neuroimaging data, standardization effectively up- and down-weights features based on their individual variability. Since the standard approach uses the entire data set to guide the normalization, it utilizes the total variability of these features. This total variation is inevitably dependent on the amount of marginal separation between groups. Thus, such a normalization may attenuate the separability of the data in high dimensional space. In this work we propose an alternate approach that uses an estimate of the control-group standard deviation to normalize features before training. We study our proposed approach in the context of group classification using structural MRI data. We show that control-based normalization leads to better reproducibility of estimated multivariate disease patterns and improves the classifier performance in many cases. Copyright © 2016 Elsevier Inc. All rights reserved.

Multivariate statistical process control (MSPC) using Raman spectroscopy for in-line culture cell monitoring considering time-varying batches synchronized with correlation optimized warping (COW).

PubMed

Liu, Ya-Juan; André, Silvère; Saint Cristau, Lydia; Lagresle, Sylvain; Hannas, Zahia; Calvosa, Éric; Devos, Olivier; Duponchel, Ludovic

2017-02-01

Multivariate statistical process control (MSPC) is increasingly popular as the challenge provided by large multivariate datasets from analytical instruments such as Raman spectroscopy for the monitoring of complex cell cultures in the biopharmaceutical industry. However, Raman spectroscopy for in-line monitoring often produces unsynchronized data sets, resulting in time-varying batches. Moreover, unsynchronized data sets are common for cell culture monitoring because spectroscopic measurements are generally recorded in an alternate way, with more than one optical probe parallelly connecting to the same spectrometer. Synchronized batches are prerequisite for the application of multivariate analysis such as multi-way principal component analysis (MPCA) for the MSPC monitoring. Correlation optimized warping (COW) is a popular method for data alignment with satisfactory performance; however, it has never been applied to synchronize acquisition time of spectroscopic datasets in MSPC application before. In this paper we propose, for the first time, to use the method of COW to synchronize batches with varying durations analyzed with Raman spectroscopy. In a second step, we developed MPCA models at different time intervals based on the normal operation condition (NOC) batches synchronized by COW. New batches are finally projected considering the corresponding MPCA model. We monitored the evolution of the batches using two multivariate control charts based on Hotelling's T 2 and Q. As illustrated with results, the MSPC model was able to identify abnormal operation condition including contaminated batches which is of prime importance in cell culture monitoring We proved that Raman-based MSPC monitoring can be used to diagnose batches deviating from the normal condition, with higher efficacy than traditional diagnosis, which would save time and money in the biopharmaceutical industry. Copyright © 2016 Elsevier B.V. All rights reserved.

The MIDAS processor. [Multivariate Interactive Digital Analysis System for multispectral scanner data

NASA Technical Reports Server (NTRS)

Kriegler, F. J.; Gordon, M. F.; Mclaughlin, R. H.; Marshall, R. E.

1975-01-01

The MIDAS (Multivariate Interactive Digital Analysis System) processor is a high-speed processor designed to process multispectral scanner data (from Landsat, EOS, aircraft, etc.) quickly and cost-effectively to meet the requirements of users of remote sensor data, especially from very large areas. MIDAS consists of a fast multipipeline preprocessor and classifier, an interactive color display and color printer, and a medium scale computer system for analysis and control. The system is designed to process data having as many as 16 spectral bands per picture element at rates of 200,000 picture elements per second into as many as 17 classes using a maximum likelihood decision rule.

Medial prefrontal aberrations in major depressive disorder revealed by cytoarchitectonically informed voxel-based morphometry

PubMed Central

Bludau, Sebastian; Bzdok, Danilo; Gruber, Oliver; Kohn, Nils; Riedl, Valentin; Sorg, Christian; Palomero-Gallagher, Nicola; Müller, Veronika I.; Hoffstaedter, Felix; Amunts, Katrin; Eickhoff, Simon B.

2017-01-01

Objective The heterogeneous human frontal pole has been identified as a node in the dysfunctional network of major depressive disorder. The contribution of the medial (socio-affective) versus lateral (cognitive) frontal pole to major depression pathogenesis is currently unclear. The present study performs morphometric comparison of the microstructurally informed subdivisions of human frontal pole between depressed patients and controls using both uni- and multivariate statistics. Methods Multi-site voxel- and region-based morphometric MRI analysis of 73 depressed patients and 73 matched controls without psychiatric history. Frontal pole volume was first compared between depressed patients and controls by subdivision-wise classical morphometric analysis. In a second approach, frontal pole volume was compared by subdivision-naive multivariate searchlight analysis based on support vector machines. Results Subdivision-wise morphometric analysis found a significantly smaller medial frontal pole in depressed patients with a negative correlation of disease severity and duration. Histologically uninformed multivariate voxel-wise statistics provided converging evidence for structural aberrations specific to the microstructurally defined medial area of the frontal pole in depressed patients. Conclusions Across disparate methods, we demonstrated subregion specificity in the left medial frontal pole volume in depressed patients. Indeed, the frontal pole was shown to structurally and functionally connect to other key regions in major depression pathology like the anterior cingulate cortex and the amygdala via the uncinate fasciculus. Present and previous findings consolidate the left medial portion of the frontal pole as particularly altered in major depression. PMID:26621569

Identifying Pleiotropic Genes in Genome-Wide Association Studies for Multivariate Phenotypes with Mixed Measurement Scales

PubMed Central

Williams, L. Keoki; Buu, Anne

2017-01-01

We propose a multivariate genome-wide association test for mixed continuous, binary, and ordinal phenotypes. A latent response model is used to estimate the correlation between phenotypes with different measurement scales so that the empirical distribution of the Fisher’s combination statistic under the null hypothesis is estimated efficiently. The simulation study shows that our proposed correlation estimation methods have high levels of accuracy. More importantly, our approach conservatively estimates the variance of the test statistic so that the type I error rate is controlled. The simulation also shows that the proposed test maintains the power at the level very close to that of the ideal analysis based on known latent phenotypes while controlling the type I error. In contrast, conventional approaches–dichotomizing all observed phenotypes or treating them as continuous variables–could either reduce the power or employ a linear regression model unfit for the data. Furthermore, the statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that conducting a multivariate test on multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests. The proposed method also offers a new approach to analyzing the Fagerström Test for Nicotine Dependence as multivariate phenotypes in genome-wide association studies. PMID:28081206

Effect of altered sensory conditions on multivariate descriptors of human postural sway

NASA Technical Reports Server (NTRS)

Kuo, A. D.; Speers, R. A.; Peterka, R. J.; Horak, F. B.; Peterson, B. W. (Principal Investigator)

1998-01-01

Multivariate descriptors of sway were used to test whether altered sensory conditions result not only in changes in amount of sway but also in postural coordination. Eigenvalues and directions of eigenvectors of the covariance of shnk and hip angles were used as a set of multivariate descriptors. These quantities were measured in 14 healthy adult subjects performing the Sensory Organization test, which disrupts visual and somatosensory information used for spatial orientation. Multivariate analysis of variance and discriminant analysis showed that resulting sway changes were at least bivariate in character, with visual and somatosensory conditions producing distinct changes in postural coordination. The most significant changes were found when somatosensory information was disrupted by sway-referencing of the support surface (P = 3.2 x 10(-10)). The resulting covariance measurements showed that subjects not only swayed more but also used increased hip motion analogous to the hip strategy. Disruption of vision, by either closing the eyes or sway-referencing the visual surround, also resulted in altered sway (P = 1.7 x 10(-10)), with proportionately more motion of the center of mass than with platform sway-referencing. As shown by discriminant analysis, an optimal univariate measure could explain at most 90% of the behavior due to altered sensory conditions. The remaining 10%, while smaller, are highly significant changes in posture control that depend on sensory conditions. The results imply that normal postural coordination of the trunk and legs requires both somatosensory and visual information and that each sensory modality makes a unique contribution to posture control. Descending postural commands are multivariate in nature, and the motion at each joint is affected uniquely by input from multiple sensors.

Pretreatment Health Behaviors Predict Survival Among Patients With Head and Neck Squamous Cell Carcinoma

PubMed Central

Duffy, Sonia A.; Ronis, David L.; McLean, Scott; Fowler, Karen E.; Gruber, Stephen B.; Wolf, Gregory T.; Terrell, Jeffrey E.

2009-01-01

Purpose Our prior work has shown that the health behaviors of head and neck cancer patients are interrelated and are associated with quality of life; however, other than smoking, the relationship between health behaviors and survival is unclear. Patients and Methods A prospective cohort study was conducted to determine the relationship between five pretreatment health behaviors (smoking, alcohol, diet, physical activity, and sleep) and all-cause survival among 504 head and neck cancer patients. Results Smoking status was the strongest predictor of survival, with both current smokers (hazard ratio [HR] = 2.4; 95% CI, 1.3 to 4.4) and former smokers (HR = 2.0; 95% CI, 1.2 to 3.5) showing significant associations with poor survival. Problem drinking was associated with survival in the univariate analysis (HR = 1.4; 95% CI, 1.0 to 2.0) but lost significance when controlling for other factors. Low fruit intake was negatively associated with survival in the univariate analysis only (HR = 1.6; 95% CI, 1.1 to 2.1), whereas vegetable intake was not significant in either univariate or multivariate analyses. Although physical activity was associated with survival in the univariate analysis (HR = 0.95; 95% CI, 0.93 to 0.97), it was not significant in the multivariate model. Sleep was not significantly associated with survival in either univariate or multivariate analysis. Control variables that were also independently associated with survival in the multivariate analysis were age, education, tumor site, cancer stage, and surgical treatment. Conclusion Variation in selected pretreatment health behaviors (eg, smoking, fruit intake, and physical activity) in this population is associated with variation in survival. PMID:19289626

Multiple Hypothesis Testing for Experimental Gingivitis Based on Wilcoxon Signed Rank Statistics

PubMed Central

Preisser, John S.; Sen, Pranab K.; Offenbacher, Steven

2011-01-01

Dental research often involves repeated multivariate outcomes on a small number of subjects for which there is interest in identifying outcomes that exhibit change in their levels over time as well as to characterize the nature of that change. In particular, periodontal research often involves the analysis of molecular mediators of inflammation for which multivariate parametric methods are highly sensitive to outliers and deviations from Gaussian assumptions. In such settings, nonparametric methods may be favored over parametric ones. Additionally, there is a need for statistical methods that control an overall error rate for multiple hypothesis testing. We review univariate and multivariate nonparametric hypothesis tests and apply them to longitudinal data to assess changes over time in 31 biomarkers measured from the gingival crevicular fluid in 22 subjects whereby gingivitis was induced by temporarily withholding tooth brushing. To identify biomarkers that can be induced to change, multivariate Wilcoxon signed rank tests for a set of four summary measures based upon area under the curve are applied for each biomarker and compared to their univariate counterparts. Multiple hypothesis testing methods with choice of control of the false discovery rate or strong control of the family-wise error rate are examined. PMID:21984957

A Versatile Cell Death Screening Assay Using Dye-Stained Cells and Multivariate Image Analysis.

PubMed

Collins, Tony J; Ylanko, Jarkko; Geng, Fei; Andrews, David W

2015-11-01

A novel dye-based method for measuring cell death in image-based screens is presented. Unlike conventional high- and medium-throughput cell death assays that measure only one form of cell death accurately, using multivariate analysis of micrographs of cells stained with the inexpensive mix, red dye nonyl acridine orange, and a nuclear stain, it was possible to quantify cell death induced by a variety of different agonists even without a positive control. Surprisingly, using a single known cytotoxic agent as a positive control for training a multivariate classifier allowed accurate quantification of cytotoxicity for mechanistically unrelated compounds enabling generation of dose-response curves. Comparison with low throughput biochemical methods suggested that cell death was accurately distinguished from cell stress induced by low concentrations of the bioactive compounds Tunicamycin and Brefeldin A. High-throughput image-based format analyses of more than 300 kinase inhibitors correctly identified 11 as cytotoxic with only 1 false positive. The simplicity and robustness of this dye-based assay makes it particularly suited to live cell screening for toxic compounds.

A Versatile Cell Death Screening Assay Using Dye-Stained Cells and Multivariate Image Analysis

PubMed Central

Collins, Tony J.; Ylanko, Jarkko; Geng, Fei

2015-01-01

Abstract A novel dye-based method for measuring cell death in image-based screens is presented. Unlike conventional high- and medium-throughput cell death assays that measure only one form of cell death accurately, using multivariate analysis of micrographs of cells stained with the inexpensive mix, red dye nonyl acridine orange, and a nuclear stain, it was possible to quantify cell death induced by a variety of different agonists even without a positive control. Surprisingly, using a single known cytotoxic agent as a positive control for training a multivariate classifier allowed accurate quantification of cytotoxicity for mechanistically unrelated compounds enabling generation of dose–response curves. Comparison with low throughput biochemical methods suggested that cell death was accurately distinguished from cell stress induced by low concentrations of the bioactive compounds Tunicamycin and Brefeldin A. High-throughput image-based format analyses of more than 300 kinase inhibitors correctly identified 11 as cytotoxic with only 1 false positive. The simplicity and robustness of this dye-based assay makes it particularly suited to live cell screening for toxic compounds. PMID:26422066

Implementation Challenges for Multivariable Control: What You Did Not Learn in School

NASA Technical Reports Server (NTRS)

Garg, Sanjay

2008-01-01

Multivariable control allows controller designs that can provide decoupled command tracking and robust performance in the presence of modeling uncertainties. Although the last two decades have seen extensive development of multivariable control theory and example applications to complex systems in software/hardware simulations, there are no production flying systems aircraft or spacecraft, that use multivariable control. This is because of the tremendous challenges associated with implementation of such multivariable control designs. Unfortunately, the curriculum in schools does not provide sufficient time to be able to provide an exposure to the students in such implementation challenges. The objective of this paper is to share the lessons learned by a practitioner of multivariable control in the process of applying some of the modern control theory to the Integrated Flight Propulsion Control (IFPC) design for an advanced Short Take-Off Vertical Landing (STOVL) aircraft simulation.

Analysis of Exhaled Breath Volatile Organic Compounds in Inflammatory Bowel Disease: A Pilot Study.

PubMed

Hicks, Lucy C; Huang, Juzheng; Kumar, Sacheen; Powles, Sam T; Orchard, Timothy R; Hanna, George B; Williams, Horace R T

2015-09-01

Distinguishing between the inflammatory bowel diseases [IBD], Crohn's disease [CD] and ulcerative colitis [UC], is important for determining management and prognosis. Selected ion flow tube mass spectrometry [SIFT-MS] may be used to analyse volatile organic compounds [VOCs] in exhaled breath: these may be altered in disease states, and distinguishing breath VOC profiles can be identified. The aim of this pilot study was to identify, quantify, and analyse VOCs present in the breath of IBD patients and controls, potentially providing insights into disease pathogenesis and complementing current diagnostic algorithms. SIFT-MS breath profiling of 56 individuals [20 UC, 18 CD, and 18 healthy controls] was undertaken. Multivariate analysis included principal components analysis and partial least squares discriminant analysis with orthogonal signal correction [OSC-PLS-DA]. Receiver operating characteristic [ROC] analysis was performed for each comparative analysis using statistically significant VOCs. OSC-PLS-DA modelling was able to distinguish both CD and UC from healthy controls and from one other with good sensitivity and specificity. ROC analysis using combinations of statistically significant VOCs [dimethyl sulphide, hydrogen sulphide, hydrogen cyanide, ammonia, butanal, and nonanal] gave integrated areas under the curve of 0.86 [CD vs healthy controls], 0.74 [UC vs healthy controls], and 0.83 [CD vs UC]. Exhaled breath VOC profiling was able to distinguish IBD patients from controls, as well as to separate UC from CD, using both multivariate and univariate statistical techniques. Copyright © 2015 European Crohn’s and Colitis Organisation (ECCO). Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Identifying ADHD children using hemodynamic responses during a working memory task measured by functional near-infrared spectroscopy.

PubMed

Gu, Yue; Miao, Shuo; Han, Junxia; Liang, Zhenhu; Ouyang, Gaoxiang; Yang, Jian; Li, Xiaoli

2018-06-01

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting children and adults. Previous studies found that functional near-infrared spectroscopy (fNIRS) can reveal significant group differences in several brain regions between ADHD children and healthy controls during working memory tasks. This study aimed to use fNIRS activation patterns to identify ADHD children from healthy controls. FNIRS signals from 25 ADHD children and 25 healthy controls performing the n-back task were recorded; then, multivariate pattern analysis was used to discriminate ADHD individuals from healthy controls, and classification performance was evaluated for significance by the permutation test. The results showed that 86.0% ([Formula: see text]) of participants can be correctly classified in leave-one-out cross-validation. The most discriminative brain regions included the bilateral dorsolateral prefrontal cortex, inferior medial prefrontal cortex, right posterior prefrontal cortex, and right temporal cortex. This study demonstrated that, in a small sample, multivariate pattern analysis can effectively identify ADHD children from healthy controls based on fNIRS signals, which argues for the potential utility of fNIRS in future assessments.

Kenyan female sex workers' use of female-controlled nonbarrier modern contraception: do they use condoms less consistently?

PubMed

Yam, Eileen A; Okal, Jerry; Musyoki, Helgar; Muraguri, Nicholas; Tun, Waimar; Sheehy, Meredith; Geibel, Scott

2016-03-01

To examine whether nonbarrier modern contraceptive use is associated with less consistent condom use among Kenyan female sex workers (FSWs). Researchers recruited 579 FSWs using respondent-driven sampling. We conducted multivariate logistic regression to examine the association between consistent condom use and female-controlled nonbarrier modern contraceptive use. A total of 98.8% reported using male condoms in the past month, and 64.6% reported using female-controlled nonbarrier modern contraception. In multivariate analysis, female-controlled nonbarrier modern contraceptive use was not associated with decreased condom use with clients or nonpaying partners. Consistency of condom use is not compromised when FSWs use available female-controlled nonbarrier modern contraception. FSWs should be encouraged to use condoms consistently, whether or not other methods are used simultaneously. Copyright © 2016 Elsevier Inc. All rights reserved.

Studying the Relationship between Children's Self-Control and Academic Achievement: An Application of Second-Order Growth Curve Model Analysis.

ERIC Educational Resources Information Center

Kim, Sooyeon; Murry, Velma McBride; Brody, Gene H.

The functional relationships between developmental change in children's self-control and academic achievement were examined using longitudinal family data. Multivariate latent growth models (LGM) were specified to determine whether the rate of growth in academic achievement changes as a function of developmental change in self-control. Data came…

Voxelwise multivariate analysis of multimodality magnetic resonance imaging

PubMed Central

Naylor, Melissa G.; Cardenas, Valerie A.; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin

2015-01-01

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remains a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. PMID:23408378

Estimating the net effect of progesterone elevation on the day of hCG on live birth rates after IVF: a cohort analysis of 3296 IVF cycles.

PubMed

Venetis, Christos A; Kolibianakis, Efstratios M; Bosdou, Julia K; Lainas, George T; Sfontouris, Ioannis A; Tarlatzis, Basil C; Lainas, Tryfon G

2015-03-01

What is the proper way of assessing the effect of progesterone elevation (PE) on the day of hCG on live birth in women undergoing fresh embryo transfer after in vitro fertilization (IVF) using GnRH analogues and gonadotrophins? This study indicates that a multivariable approach, where the effect of the most important confounders is controlled for, can lead to markedly different results regarding the association between PE on the day of hCG and live birth rates after IVF when compared with the bivariate analysis that has been typically used in the relevant literature up to date. PE on the day of hCG is associated with decreased pregnancy rates in fresh IVF cycles. Evidence for this comes from observational studies that mostly failed to control for potential confounders. This is a retrospective analysis of a cohort of fresh IVF/intracytoplasmic sperm injection cycles (n = 3296) performed in a single IVF centre during the period 2001-2013. Patients in whom ovarian stimulation was performed with gonadotrophins and GnRH analogues. Natural cycles and cycles where stimulation involved the administration of clomiphene were excluded. In order to reflect routine clinical practice, no other exclusion criteria were imposed on this dataset. The primary outcome measure for this study was live birth defined as the delivery of a live infant after 24 weeks of gestation. We compared the association between PE on the day of hCG (defined as P > 1.5 ng/ml) and live birth rates calculated by simple bivariate analyses with that derived from multivariable logistic regression. The multivariable analysis controlled for female age, number of oocytes retrieved, number of embryos transferred, developmental stage of embryos at transfer (cleavage versus blastocyst), whether at least one good-quality embryo was transferred, the woman's body mass index, the total dose of FSH administered during ovarian stimulation and the type of GnRH analogues used (agonists versus antagonists) during ovarian stimulation. In addition, an interaction analysis was performed in order to assess whether the ovarian response (<6, 6-18, >18 oocytes) has a moderating effect on the association of PE on the day of hCG with live birth rates after IVF. Live birth rates were not significantly different between cycles with and those without PE when a bivariate analysis was performed [odds ratio (OR): 0.78, 95% confidence interval (CI): 0.56-1.09]. However, when a multivariable analysis was performed, controlling for the effect of the aforementioned confounders, live birth rates (OR: 0.68, 95% CI: 0.48-0.97) were significantly decreased in the group with PE on the day of hCG. The number of oocytes retrieved was the most potent confounder, causing a 29.4% reduction in the OR for live birth between the two groups compared. Furthermore, a moderating effect of ovarian response on the association between PE and live birth rates was not supported in the present analysis since no interaction was detected between PE and the type of ovarian response (<6, 6-18, >18 oocytes). This is a retrospective analysis of data collected during a 12-year period, and although the effect of the most important confounders was controlled for in the multivariable analysis, the presence of residual bias cannot be excluded. This analysis highlights the need for a multivariable approach when researchers or clinicians aim to evaluate the impact of PE on pregnancy rates in their own clinical setting. Failure to do so might explain why many past studies have failed to identify the detrimental effect of PE in fresh IVF cycles. None. © The Author 2015. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Motivational Profiles of Adult Learners

ERIC Educational Resources Information Center

Rothes, Ana; Lemos, Marina S.; Gonçalves, Teresa

2017-01-01

This study investigated profiles of autonomous and controlled motivation and their effects in a sample of 188 adult learners from two Portuguese urban areas. Using a person-centered approach, results of cluster analysis and multivariate analysis of covariance revealed four motivational groups with different effects in self-efficacy, engagement,…

An efficient genome-wide association test for multivariate phenotypes based on the Fisher combination function.

PubMed

Yang, James J; Li, Jia; Williams, L Keoki; Buu, Anne

2016-01-05

In genome-wide association studies (GWAS) for complex diseases, the association between a SNP and each phenotype is usually weak. Combining multiple related phenotypic traits can increase the power of gene search and thus is a practically important area that requires methodology work. This study provides a comprehensive review of existing methods for conducting GWAS on complex diseases with multiple phenotypes including the multivariate analysis of variance (MANOVA), the principal component analysis (PCA), the generalizing estimating equations (GEE), the trait-based association test involving the extended Simes procedure (TATES), and the classical Fisher combination test. We propose a new method that relaxes the unrealistic independence assumption of the classical Fisher combination test and is computationally efficient. To demonstrate applications of the proposed method, we also present the results of statistical analysis on the Study of Addiction: Genetics and Environment (SAGE) data. Our simulation study shows that the proposed method has higher power than existing methods while controlling for the type I error rate. The GEE and the classical Fisher combination test, on the other hand, do not control the type I error rate and thus are not recommended. In general, the power of the competing methods decreases as the correlation between phenotypes increases. All the methods tend to have lower power when the multivariate phenotypes come from long tailed distributions. The real data analysis also demonstrates that the proposed method allows us to compare the marginal results with the multivariate results and specify which SNPs are specific to a particular phenotype or contribute to the common construct. The proposed method outperforms existing methods in most settings and also has great applications in GWAS on complex diseases with multiple phenotypes such as the substance abuse disorders.

F100 multivariable control synthesis program: Evaluation of a multivariable control using a real-time engine simulation

NASA Technical Reports Server (NTRS)

Szuch, J. R.; Soeder, J. F.; Seldner, K.; Cwynar, D. S.

1977-01-01

The design, evaluation, and testing of a practical, multivariable, linear quadratic regulator control for the F100 turbofan engine were accomplished. NASA evaluation of the multivariable control logic and implementation are covered. The evaluation utilized a real time, hybrid computer simulation of the engine. Results of the evaluation are presented, and recommendations concerning future engine testing of the control are made. Results indicated that the engine testing of the control should be conducted as planned.

Metabolic phenotyping of urine for discriminating alcohol-dependent from social drinkers and alcohol-naive subjects.

PubMed

Mostafa, Hamza; Amin, Arwa M; Teh, Chin-Hoe; Murugaiyah, Vikneswaran; Arif, Nor Hayati; Ibrahim, Baharudin

2016-12-01

Alcohol-dependence (AD) is a ravaging public health and social problem. AD diagnosis depends on questionnaires and some biomarkers, which lack specificity and sensitivity, however, often leading to less precise diagnosis, as well as delaying treatment. This represents a great burden, not only on AD individuals but also on their families. Metabolomics using nuclear magnetic resonance spectroscopy (NMR) can provide novel techniques for the identification of novel biomarkers of AD. These putative biomarkers can facilitate early diagnosis of AD. To identify novel biomarkers able to discriminate between alcohol-dependent, non-AD alcohol drinkers and controls using metabolomics. Urine samples were collected from 30 alcohol-dependent persons who did not yet start AD treatment, 54 social drinkers and 60 controls, who were then analysed using NMR. Data analysis was done using multivariate analysis including principal component analysis (PCA) and orthogonal partial least square-discriminate analysis (OPLS-DA), followed by univariate and multivariate logistic regression to develop the discriminatory model. The reproducibility was done using intraclass correlation coefficient (ICC). The OPLS-DA revealed significant discrimination between AD and other groups with sensitivity 86.21%, specificity 97.25% and accuracy 94.93%. Six biomarkers were significantly associated with AD in the multivariate logistic regression model. These biomarkers were cis-aconitic acid, citric acid, alanine, lactic acid, 1,2-propanediol and 2-hydroxyisovaleric acid. The reproducibility of all biomarkers was excellent (0.81-1.0). This study revealed that metabolomics analysis of urine using NMR identified AD novel biomarkers which can discriminate AD from social drinkers and controls with high accuracy. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Factors Controlling Sediment Load in The Central Anatolia Region of Turkey: Ankara River Basin.

PubMed

Duru, Umit; Wohl, Ellen; Ahmadi, Mehdi

2017-05-01

Better understanding of the factors controlling sediment load at a catchment scale can facilitate estimation of soil erosion and sediment transport rates. The research summarized here enhances understanding of correlations between potential control variables on suspended sediment loads. The Soil and Water Assessment Tool was used to simulate flow and sediment at the Ankara River basin. Multivariable regression analysis and principal component analysis were then performed between sediment load and controlling variables. The physical variables were either directly derived from a Digital Elevation Model or from field maps or computed using established equations. Mean observed sediment rate is 6697 ton/year and mean sediment yield is 21 ton/y/km² from the gage. Soil and Water Assessment Tool satisfactorily simulated observed sediment load with Nash-Sutcliffe efficiency, relative error, and coefficient of determination (R²) values of 0.81, -1.55, and 0.93, respectively in the catchment. Therefore, parameter values from the physically based model were applied to the multivariable regression analysis as well as principal component analysis. The results indicate that stream flow, drainage area, and channel width explain most of the variability in sediment load among the catchments. The implications of the results, efficient siltation management practices in the catchment should be performed to stream flow, drainage area, and channel width.

Factors Controlling Sediment Load in The Central Anatolia Region of Turkey: Ankara River Basin

NASA Astrophysics Data System (ADS)

Duru, Umit; Wohl, Ellen; Ahmadi, Mehdi

2017-05-01

Better understanding of the factors controlling sediment load at a catchment scale can facilitate estimation of soil erosion and sediment transport rates. The research summarized here enhances understanding of correlations between potential control variables on suspended sediment loads. The Soil and Water Assessment Tool was used to simulate flow and sediment at the Ankara River basin. Multivariable regression analysis and principal component analysis were then performed between sediment load and controlling variables. The physical variables were either directly derived from a Digital Elevation Model or from field maps or computed using established equations. Mean observed sediment rate is 6697 ton/year and mean sediment yield is 21 ton/y/km² from the gage. Soil and Water Assessment Tool satisfactorily simulated observed sediment load with Nash-Sutcliffe efficiency, relative error, and coefficient of determination ( R²) values of 0.81, -1.55, and 0.93, respectively in the catchment. Therefore, parameter values from the physically based model were applied to the multivariable regression analysis as well as principal component analysis. The results indicate that stream flow, drainage area, and channel width explain most of the variability in sediment load among the catchments. The implications of the results, efficient siltation management practices in the catchment should be performed to stream flow, drainage area, and channel width.

Beer fermentation: monitoring of process parameters by FT-NIR and multivariate data analysis.

PubMed

Grassi, Silvia; Amigo, José Manuel; Lyndgaard, Christian Bøge; Foschino, Roberto; Casiraghi, Ernestina

2014-07-15

This work investigates the capability of Fourier-Transform near infrared (FT-NIR) spectroscopy to monitor and assess process parameters in beer fermentation at different operative conditions. For this purpose, the fermentation of wort with two different yeast strains and at different temperatures was monitored for nine days by FT-NIR. To correlate the collected spectra with °Brix, pH and biomass, different multivariate data methodologies were applied. Principal component analysis (PCA), partial least squares (PLS) and locally weighted regression (LWR) were used to assess the relationship between FT-NIR spectra and the abovementioned process parameters that define the beer fermentation. The accuracy and robustness of the obtained results clearly show the suitability of FT-NIR spectroscopy, combined with multivariate data analysis, to be used as a quality control tool in the beer fermentation process. FT-NIR spectroscopy, when combined with LWR, demonstrates to be a perfectly suitable quantitative method to be implemented in the production of beer. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multivariate information-theoretic measures reveal directed information structure and task relevant changes in fMRI connectivity.

PubMed

Lizier, Joseph T; Heinzle, Jakob; Horstmann, Annette; Haynes, John-Dylan; Prokopenko, Mikhail

2011-02-01

The human brain undertakes highly sophisticated information processing facilitated by the interaction between its sub-regions. We present a novel method for interregional connectivity analysis, using multivariate extensions to the mutual information and transfer entropy. The method allows us to identify the underlying directed information structure between brain regions, and how that structure changes according to behavioral conditions. This method is distinguished in using asymmetric, multivariate, information-theoretical analysis, which captures not only directional and non-linear relationships, but also collective interactions. Importantly, the method is able to estimate multivariate information measures with only relatively little data. We demonstrate the method to analyze functional magnetic resonance imaging time series to establish the directed information structure between brain regions involved in a visuo-motor tracking task. Importantly, this results in a tiered structure, with known movement planning regions driving visual and motor control regions. Also, we examine the changes in this structure as the difficulty of the tracking task is increased. We find that task difficulty modulates the coupling strength between regions of a cortical network involved in movement planning and between motor cortex and the cerebellum which is involved in the fine-tuning of motor control. It is likely these methods will find utility in identifying interregional structure (and experimentally induced changes in this structure) in other cognitive tasks and data modalities.

Predicting worsening asthma control following the common cold

PubMed Central

Walter, Michael J.; Castro, Mario; Kunselman, Susan J.; Chinchilli, Vernon M; Reno, Melissa; Ramkumar, Thiruvamoor P.; Avila, Pedro C.; Boushey, Homer A.; Ameredes, Bill T.; Bleecker, Eugene R.; Calhoun, William J.; Cherniack, Reuben M.; Craig, Timothy J.; Denlinger, Loren C.; Israel, Elliot; Fahy, John V.; Jarjour, Nizar N.; Kraft, Monica; Lazarus, Stephen C.; Lemanske, Robert F.; Martin, Richard J.; Peters, Stephen P.; Ramsdell, Joe W.; Sorkness, Christine A.; Rand Sutherland, E.; Szefler, Stanley J.; Wasserman, Stephen I.; Wechsler, Michael E.

2008-01-01

The asthmatic response to the common cold is highly variable and early characteristics that predict worsening of asthma control following a cold have not been identified. In this prospective multi-center cohort study of 413 adult subjects with asthma, we used the mini-Asthma Control Questionnaire (mini-ACQ) to quantify changes in asthma control and the Wisconsin Upper Respiratory Symptom Survey-21 (WURSS-21) to measure cold severity. Univariate and multivariable models examined demographic, physiologic, serologic, and cold-related characteristics for their relationship to changes in asthma control following a cold. We observed a clinically significant worsening of asthma control following a cold (increase in mini-ACQ of 0.69 ± 0.93). Univariate analysis demonstrated season, center location, cold length, and cold severity measurements all associated with a change in asthma control. Multivariable analysis of the covariates available within the first 2 days of cold onset revealed the day 2 and the cumulative sum of the day 1 and 2 WURSS-21 scores were significant predictors for the subsequent changes in asthma control. In asthmatic subjects the cold severity measured within the first 2 days can be used to predict subsequent changes in asthma control. This information may help clinicians prevent deterioration in asthma control following a cold. PMID:18768579

Eating Disorders: Explanatory Variables in Caucasian and Hispanic College Women

ERIC Educational Resources Information Center

Aviña, Vanessa; Day, Susan X.

2016-01-01

The authors explored Hispanic and Caucasian college women's (N = 264) behavioral and attitudinal symptoms of eating disorders after controlling for body mass index and internalization of the thinness ideal, as well as the roles of ethnicity and ethnic identity in symptomatology. Correlational analysis, multivariate analysis of variance, and…

Performance of Modified Test Statistics in Covariance and Correlation Structure Analysis under Conditions of Multivariate Nonnormality.

ERIC Educational Resources Information Center

Fouladi, Rachel T.

2000-01-01

Provides an overview of standard and modified normal theory and asymptotically distribution-free covariance and correlation structure analysis techniques and details Monte Carlo simulation results on Type I and Type II error control. Demonstrates through the simulation that robustness and nonrobustness of structure analysis techniques vary as a…

On Restructurable Control System Theory

NASA Technical Reports Server (NTRS)

Athans, M.

1983-01-01

The state of stochastic system and control theory as it impacts restructurable control issues is addressed. The multivariable characteristics of the control problem are addressed. The failure detection/identification problem is discussed as a multi-hypothesis testing problem. Control strategy reconfiguration, static multivariable controls, static failure hypothesis testing, dynamic multivariable controls, fault-tolerant control theory, dynamic hypothesis testing, generalized likelihood ratio (GLR) methods, and adaptive control are discussed.

Using Science Activities To Internalize Locus of Control. Final Report.

ERIC Educational Resources Information Center

Rowland, Paul McD.

This project was designed to investigate the effect of the use of cause-and-effect activities in the science curriculum on the locus of control of the learner. The purpose of this research is to find the effect of the activities on the learner's locus of control and attitude toward science at grades 7 through 10. A multivariate analysis of…

Vibration Attenuation of the NASA Langley Evolutionary Structure Experiment Using H(infinity) and Structured Singular Value (mu) Robust Multivariable Control Techniques

NASA Technical Reports Server (NTRS)

Balas, Gary J.

1996-01-01

This final report summarizes the research results under NASA Contract NAG-1-1254 from May, 1991 - April, 1995. The main contribution of this research are in the areas of control of flexible structures, model validation, optimal control analysis and synthesis techniques, and use of shape memory alloys for structural damping.

Towards better process understanding: chemometrics and multivariate measurements in manufacturing of solid dosage forms.

PubMed

Matero, Sanni; van Den Berg, Frans; Poutiainen, Sami; Rantanen, Jukka; Pajander, Jari

2013-05-01

The manufacturing of tablets involves many unit operations that possess multivariate and complex characteristics. The interactions between the material characteristics and process related variation are presently not comprehensively analyzed due to univariate detection methods. As a consequence, current best practice to control a typical process is to not allow process-related factors to vary i.e. lock the production parameters. The problem related to the lack of sufficient process understanding is still there: the variation within process and material properties is an intrinsic feature and cannot be compensated for with constant process parameters. Instead, a more comprehensive approach based on the use of multivariate tools for investigating processes should be applied. In the pharmaceutical field these methods are referred to as Process Analytical Technology (PAT) tools that aim to achieve a thorough understanding and control over the production process. PAT includes the frames for measurement as well as data analyzes and controlling for in-depth understanding, leading to more consistent and safer drug products with less batch rejections. In the optimal situation, by applying these techniques, destructive end-product testing could be avoided. In this paper the most prominent multivariate data analysis measuring tools within tablet manufacturing and basic research on operations are reviewed. Copyright © 2013 Wiley Periodicals, Inc.

Robust Nonlinear Feedback Control of Aircraft Propulsion Systems

NASA Technical Reports Server (NTRS)

Garrard, William L.; Balas, Gary J.; Litt, Jonathan (Technical Monitor)

2001-01-01

This is the final report on the research performed under NASA Glen grant NASA/NAG-3-1975 concerning feedback control of the Pratt & Whitney (PW) STF 952, a twin spool, mixed flow, after burning turbofan engine. The research focussed on the design of linear and gain-scheduled, multivariable inner-loop controllers for the PW turbofan engine using H-infinity and linear, parameter-varying (LPV) control techniques. The nonlinear turbofan engine simulation was provided by PW within the NASA Rocket Engine Transient Simulator (ROCETS) simulation software environment. ROCETS was used to generate linearized models of the turbofan engine for control design and analysis as well as the simulation environment to evaluate the performance and robustness of the controllers. Comparison between the H-infinity, and LPV controllers are made with the baseline multivariable controller and developed by Pratt & Whitney engineers included in the ROCETS simulation. Simulation results indicate that H-infinity and LPV techniques effectively achieve desired response characteristics with minimal cross coupling between commanded values and are very robust to unmodeled dynamics and sensor noise.

A Study on Aircraft Engine Control Systems for Integrated Flight and Propulsion Control

NASA Astrophysics Data System (ADS)

Yamane, Hideaki; Matsunaga, Yasushi; Kusakawa, Takeshi

A flyable FADEC system engineering model incorporating Integrated Flight and Propulsion Control (IFPC) concept is developed for a highly maneuverable aircraft and a fighter-class engine. An overview of the FADEC system and functional assignments for its components such as the Engine Control Unit (ECU) and the Integrated Control Unit (ICU) are described. Overall system reliability analysis, convex analysis and multivariable controller design for the engine, fault detection/redundancy management, and response characteristics of a fuel system are addressed. The engine control performance of the FADEC is demonstrated by hardware-in-the-loop simulation for fast acceleration and thrust transient characteristics.

Evaluation of statistical protocols for quality control of ecosystem carbon dioxide fluxes

Treesearch

Jorge F. Perez-Quezada; Nicanor Z. Saliendra; William E. Emmerich; Emilio A. Laca

2007-01-01

The process of quality control of micrometeorological and carbon dioxide (CO2) flux data can be subjective and may lack repeatability, which would undermine the results of many studies. Multivariate statistical methods and time series analysis were used together and independently to detect and replace outliers in CO2 flux...

[Temporary employment and health: a multivariate analysis of occupational injury risk by job tenure].

PubMed

Bena, Antonella; Giraudo, Massimiliano

2013-01-01

To study the relationship between job tenure and injury risk, controlling for individual factors and company characteristics. Analysis of incidence and injury risk by job tenure, controlling for gender, age, nationality, economic activity, firm size. Sample of 7% of Italian workers registered in the INPS (National Institute of Social Insurance) database. Private sector employees who worked as blue collars or apprentices. First-time occupational injuries, all occupational injuries, serious occupational injuries. Our findings show an increase in injury risk among those who start a new job and an inverse relationship between job tenure and injury risk. Multivariate analysis confirm these results. Recommendations for improving this situation include the adoption of organizational models that provide periods of mentoring from colleagues already in the company and the assignment to simple and not much hazardous tasks. The economic crisis may exacerbate this problem: it is important for Italy to improve the systems of monitoring relations between temporary employment and health.

F100 Multivariable Control Synthesis Program. Computer Implementation of the F100 Multivariable Control Algorithm

NASA Technical Reports Server (NTRS)

Soeder, J. F.

1983-01-01

As turbofan engines become more complex, the development of controls necessitate the use of multivariable control techniques. A control developed for the F100-PW-100(3) turbofan engine by using linear quadratic regulator theory and other modern multivariable control synthesis techniques is described. The assembly language implementation of this control on an SEL 810B minicomputer is described. This implementation was then evaluated by using a real-time hybrid simulation of the engine. The control software was modified to run with a real engine. These modifications, in the form of sensor and actuator failure checks and control executive sequencing, are discussed. Finally recommendations for control software implementations are presented.

Regional magnetic resonance imaging measures for multivariate analysis in Alzheimer's disease and mild cognitive impairment.

PubMed

Westman, Eric; Aguilar, Carlos; Muehlboeck, J-Sebastian; Simmons, Andrew

2013-01-01

Automated structural magnetic resonance imaging (MRI) processing pipelines are gaining popularity for Alzheimer's disease (AD) research. They generate regional volumes, cortical thickness measures and other measures, which can be used as input for multivariate analysis. It is not clear which combination of measures and normalization approach are most useful for AD classification and to predict mild cognitive impairment (MCI) conversion. The current study includes MRI scans from 699 subjects [AD, MCI and controls (CTL)] from the Alzheimer's disease Neuroimaging Initiative (ADNI). The Freesurfer pipeline was used to generate regional volume, cortical thickness, gray matter volume, surface area, mean curvature, gaussian curvature, folding index and curvature index measures. 259 variables were used for orthogonal partial least square to latent structures (OPLS) multivariate analysis. Normalisation approaches were explored and the optimal combination of measures determined. Results indicate that cortical thickness measures should not be normalized, while volumes should probably be normalized by intracranial volume (ICV). Combining regional cortical thickness measures (not normalized) with cortical and subcortical volumes (normalized with ICV) using OPLS gave a prediction accuracy of 91.5 % when distinguishing AD versus CTL. This model prospectively predicted future decline from MCI to AD with 75.9 % of converters correctly classified. Normalization strategy did not have a significant effect on the accuracies of multivariate models containing multiple MRI measures for this large dataset. The appropriate choice of input for multivariate analysis in AD and MCI is of great importance. The results support the use of un-normalised cortical thickness measures and volumes normalised by ICV.

Multivariable regression analysis of list experiment data on abortion: results from a large, randomly-selected population based study in Liberia.

PubMed

Moseson, Heidi; Gerdts, Caitlin; Dehlendorf, Christine; Hiatt, Robert A; Vittinghoff, Eric

2017-12-21

The list experiment is a promising measurement tool for eliciting truthful responses to stigmatized or sensitive health behaviors. However, investigators may be hesitant to adopt the method due to previously untestable assumptions and the perceived inability to conduct multivariable analysis. With a recently developed statistical test that can detect the presence of a design effect - the absence of which is a central assumption of the list experiment method - we sought to test the validity of a list experiment conducted on self-reported abortion in Liberia. We also aim to introduce recently developed multivariable regression estimators for the analysis of list experiment data, to explore relationships between respondent characteristics and having had an abortion - an important component of understanding the experiences of women who have abortions. To test the null hypothesis of no design effect in the Liberian list experiment data, we calculated the percentage of each respondent "type," characterized by response to the control items, and compared these percentages across treatment and control groups with a Bonferroni-adjusted alpha criterion. We then implemented two least squares and two maximum likelihood models (four total), each representing different bias-variance trade-offs, to estimate the association between respondent characteristics and abortion. We find no clear evidence of a design effect in list experiment data from Liberia (p = 0.18), affirming the first key assumption of the method. Multivariable analyses suggest a negative association between education and history of abortion. The retrospective nature of measuring lifetime experience of abortion, however, complicates interpretation of results, as the timing and safety of a respondent's abortion may have influenced her ability to pursue an education. Our work demonstrates that multivariable analyses, as well as statistical testing of a key design assumption, are possible with list experiment data, although with important limitations when considering lifetime measures. We outline how to implement this methodology with list experiment data in future research.

Voxelwise multivariate analysis of multimodality magnetic resonance imaging.

PubMed

Naylor, Melissa G; Cardenas, Valerie A; Tosun, Duygu; Schuff, Norbert; Weiner, Michael; Schwartzman, Armin

2014-03-01

Most brain magnetic resonance imaging (MRI) studies concentrate on a single MRI contrast or modality, frequently structural MRI. By performing an integrated analysis of several modalities, such as structural, perfusion-weighted, and diffusion-weighted MRI, new insights may be attained to better understand the underlying processes of brain diseases. We compare two voxelwise approaches: (1) fitting multiple univariate models, one for each outcome and then adjusting for multiple comparisons among the outcomes and (2) fitting a multivariate model. In both cases, adjustment for multiple comparisons is performed over all voxels jointly to account for the search over the brain. The multivariate model is able to account for the multiple comparisons over outcomes without assuming independence because the covariance structure between modalities is estimated. Simulations show that the multivariate approach is more powerful when the outcomes are correlated and, even when the outcomes are independent, the multivariate approach is just as powerful or more powerful when at least two outcomes are dependent on predictors in the model. However, multiple univariate regressions with Bonferroni correction remain a desirable alternative in some circumstances. To illustrate the power of each approach, we analyze a case control study of Alzheimer's disease, in which data from three MRI modalities are available. Copyright © 2013 Wiley Periodicals, Inc.

Leptospira Exposure and Gardeners: A Case-Control Seroprevalence Study

PubMed Central

Alvarado-Esquivel, Cosme; Hernandez-Tinoco, Jesus; Sanchez-Anguiano, Luis Francisco; Ramos-Nevarez, Agar; Cerrillo-Soto, Sandra Margarita; Guido-Arreola, Carlos Alberto

2016-01-01

Background Leptospira can be found in soil. However, it is unclear whether occupational exposure to soil may represent a risk for Leptospira infection in humans. Therefore, we sought to determine the association of Leptospira IgG seroprevalence with the occupation of gardener, and to determine the epidemiological characteristics of gardeners associated with Leptospira exposure. Methods We performed a case-control study in 168 gardeners and 168 age- and gender-matched control subjects without gardening occupation in Durango City, Mexico. The seroprevalence of anti-Leptospira IgG antibodies in cases and controls was determined using an enzyme immunoassay. Bivariate and multivariate analyses were used to assess the association of Leptospira exposure and the characteristics of the gardeners. Results Anti-Leptospira IgG antibodies were found in 10 (6%) of 168 gardeners and in 15 (8.9%) of 168 control subjects (odds ratio (OR): 0.64; 95% confidence interval (CI): 0.28 - 1.48; P = 0.40). Multivariate analysis showed that Leptospira seropositivity was positively associated with female gender (OR: 5.82; 95% CI: 1.11 - 30.46; P = 0.03), and negatively associated with eating while working (OR: 0.21; 95% CI: 0.05 - 0.87; P = 0.03). In addition, multivariate analysis showed that high anti-Leptospira levels were associated with consumption of boar meat (OR: 28.00; 95% CI: 1.20 - 648.80; P = 0.03). Conclusions This is the first case-control study of Leptospira exposure in gardeners. Results do not support an association of Leptospira exposure with the occupation of gardener. However, further studies to confirm the lack of this association are needed. The potential role of consumption of boar meat in Leptospira infection deserves further investigation. PMID:26668679

Identifying ADHD children using hemodynamic responses during a working memory task measured by functional near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Gu, Yue; Miao, Shuo; Han, Junxia; Liang, Zhenhu; Ouyang, Gaoxiang; Yang, Jian; Li, Xiaoli

2018-06-01

Objective. Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting children and adults. Previous studies found that functional near-infrared spectroscopy (fNIRS) can reveal significant group differences in several brain regions between ADHD children and healthy controls during working memory tasks. This study aimed to use fNIRS activation patterns to identify ADHD children from healthy controls. Approach. FNIRS signals from 25 ADHD children and 25 healthy controls performing the n-back task were recorded; then, multivariate pattern analysis was used to discriminate ADHD individuals from healthy controls, and classification performance was evaluated for significance by the permutation test. Main results. The results showed that 86.0% (p<0.001 ) of participants can be correctly classified in leave-one-out cross-validation. The most discriminative brain regions included the bilateral dorsolateral prefrontal cortex, inferior medial prefrontal cortex, right posterior prefrontal cortex, and right temporal cortex. Significance. This study demonstrated that, in a small sample, multivariate pattern analysis can effectively identify ADHD children from healthy controls based on fNIRS signals, which argues for the potential utility of fNIRS in future assessments.

Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes.

PubMed

Achana, Felix A; Cooper, Nicola J; Bujkiewicz, Sylwia; Hubbard, Stephanie J; Kendrick, Denise; Jones, David R; Sutton, Alex J

2014-07-21

Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes. The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations. Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on outcomes not directly considered by the studies included in the analysis. Accounting for the dependency between outcomes in a multivariate meta-analysis may or may not improve the precision of effect estimates from a network meta-analysis compared to analysing each outcome separately.

Bayesian inference on risk differences: an application to multivariate meta-analysis of adverse events in clinical trials.

PubMed

Chen, Yong; Luo, Sheng; Chu, Haitao; Wei, Peng

2013-05-01

Multivariate meta-analysis is useful in combining evidence from independent studies which involve several comparisons among groups based on a single outcome. For binary outcomes, the commonly used statistical models for multivariate meta-analysis are multivariate generalized linear mixed effects models which assume risks, after some transformation, follow a multivariate normal distribution with possible correlations. In this article, we consider an alternative model for multivariate meta-analysis where the risks are modeled by the multivariate beta distribution proposed by Sarmanov (1966). This model have several attractive features compared to the conventional multivariate generalized linear mixed effects models, including simplicity of likelihood function, no need to specify a link function, and has a closed-form expression of distribution functions for study-specific risk differences. We investigate the finite sample performance of this model by simulation studies and illustrate its use with an application to multivariate meta-analysis of adverse events of tricyclic antidepressants treatment in clinical trials.

Chemometric techniques on the analysis of Raman spectra of serum blood samples of breast cancer patients

NASA Astrophysics Data System (ADS)

Rocha-Osornio, L. N.; Pichardo-Molina, J. L.; Barbosa-Garcia, O.; Frausto-Reyes, C.; Araujo-Andrade, C.; Huerta-Franco, R.; Gutiérrez-Juárez, G.

2008-02-01

Raman spectroscopy and Multivariate methods were used to study serum blood samples of control and breast cancer patients. Blood samples were obtained from 11 patients and 12 controls from the central region of Mexico. Our results show that principal component analysis is able to discriminate serum sample of breast cancer patients from those of control group, also the loading vectors of PCA plotted as a function of Raman shift shown which bands permitted to make the maximum discrimination between both groups of samples.

Hydrochemical evolution and groundwater flow processes in the Galilee and Eromanga basins, Great Artesian Basin, Australia: a multivariate statistical approach.

PubMed

Moya, Claudio E; Raiber, Matthias; Taulis, Mauricio; Cox, Malcolm E

2015-03-01

The Galilee and Eromanga basins are sub-basins of the Great Artesian Basin (GAB). In this study, a multivariate statistical approach (hierarchical cluster analysis, principal component analysis and factor analysis) is carried out to identify hydrochemical patterns and assess the processes that control hydrochemical evolution within key aquifers of the GAB in these basins. The results of the hydrochemical assessment are integrated into a 3D geological model (previously developed) to support the analysis of spatial patterns of hydrochemistry, and to identify the hydrochemical and hydrological processes that control hydrochemical variability. In this area of the GAB, the hydrochemical evolution of groundwater is dominated by evapotranspiration near the recharge area resulting in a dominance of the Na-Cl water types. This is shown conceptually using two selected cross-sections which represent discrete groundwater flow paths from the recharge areas to the deeper parts of the basins. With increasing distance from the recharge area, a shift towards a dominance of carbonate (e.g. Na-HCO3 water type) has been observed. The assessment of hydrochemical changes along groundwater flow paths highlights how aquifers are separated in some areas, and how mixing between groundwater from different aquifers occurs elsewhere controlled by geological structures, including between GAB aquifers and coal bearing strata of the Galilee Basin. The results of this study suggest that distinct hydrochemical differences can be observed within the previously defined Early Cretaceous-Jurassic aquifer sequence of the GAB. A revision of the two previously recognised hydrochemical sequences is being proposed, resulting in three hydrochemical sequences based on systematic differences in hydrochemistry, salinity and dominant hydrochemical processes. The integrated approach presented in this study which combines different complementary multivariate statistical techniques with a detailed assessment of the geological framework of these sedimentary basins, can be adopted in other complex multi-aquifer systems to assess hydrochemical evolution and its geological controls. Copyright © 2014 Elsevier B.V. All rights reserved.

Assessment of changes of vector borne diseases with wetland characteristics using multivariate analysis.

PubMed

Sheela, A M; Sarun, S; Justus, J; Vineetha, P; Sheeja, R V

2015-04-01

Vector borne diseases are a threat to human health. Little attention has been paid to the prevention of these diseases. We attempted to identify the significant wetland characteristics associated with the spread of chikungunya, dengue fever and malaria in Kerala, a tropical region of South West India using multivariate analyses (hierarchical cluster analysis, factor analysis and multiple regression). High/medium turbid coastal lagoons and inland water-logged wetlands with aquatic vegetation have significant effect on the incidence of chikungunya while dengue influenced by high turbid coastal beaches and malaria by medium turbid coastal beaches. The high turbidity in water is due to the urban waste discharge namely sewage, sullage and garbage from the densely populated cities and towns. The large extent of wetland is low land area favours the occurrence of vector borne diseases. Hence the provision of pollution control measures at source including soil erosion control measures is vital. The identification of vulnerable zones favouring the vector borne diseases will help the authorities to control pollution especially from urban areas and prevent these vector borne diseases. Future research should cover land use cover changes, climatic factors, seasonal variations in weather and pollution factors favouring the occurrence of vector borne diseases.

Evaluation of an F100 multivariable control using a real-time engine simulation

NASA Technical Reports Server (NTRS)

Szuch, J. R.; Skira, C.; Soeder, J. F.

1977-01-01

A multivariable control design for the F100 turbofan engine was evaluated, as part of the F100 multivariable control synthesis (MVCS) program. The evaluation utilized a real-time, hybrid computer simulation of the engine and a digital computer implementation of the control. Significant results of the evaluation are presented and recommendations concerning future engine testing of the control are made.

Processes and subdivisions in diogenites, a multivariate statistical analysis

NASA Technical Reports Server (NTRS)

Harriott, T. A.; Hewins, R. H.

1984-01-01

Multivariate statistical techniques used on diogenite orthopyroxene analyses show the relationships that occur within diogenites and the two orthopyroxenite components (class I and II) in the polymict diogenite Garland. Cluster analysis shows that only Peckelsheim is similar to Garland class I (Fe-rich) and the other diogenites resemble Garland class II. The unique diogenite Y 75032 may be related to type I by fractionation. Factor analysis confirms the subdivision and shows that Fe does not correlate with the weakly incompatible elements across the entire pyroxene composition range, indicating that igneous fractionation is not the process controlling total diogenite composition variation. The occurrence of two groups of diogenites is interpreted as the result of sampling or mixing of two main sequences of orthopyroxene cumulates with slightly different compositions.

[Risk factors for anorexia in children].

PubMed

Liu, Wei-Xiao; Lang, Jun-Feng; Zhang, Qin-Feng

2016-11-01

To investigate the risk factors for anorexia in children, and to reduce the prevalence of anorexia in children. A questionnaire survey and a case-control study were used to collect the general information of 150 children with anorexia (case group) and 150 normal children (control group). Univariate analysis and multivariate logistic stepwise regression analysis were performed to identify the risk factors for anorexia in children. The results of the univariate analysis showed significant differences between the case and control groups in the age in months when supplementary food were added, feeding pattern, whether they liked meat, vegetables and salty food, whether they often took snacks and beverages, whether they liked to play while eating, and whether their parents asked them to eat food on time (P<0.05). The results of the multivariate logistic regression analysis showed that late addition of supplementary food (OR=5.408), high frequency of taking snacks and/or drinks (OR=11.813), and eating while playing (OR=6.654) were major risk factors for anorexia in children. Liking of meat (OR=0.093) and vegetables (OR=0.272) and eating on time required by parents (OR=0.079) were protective factors against anorexia in children. Timely addition of supplementary food, a proper diet, and development of children's proper eating and living habits can reduce the incidence of anorexia in children.

Sensitivity analysis of automatic flight control systems using singular value concepts

NASA Technical Reports Server (NTRS)

Herrera-Vaillard, A.; Paduano, J.; Downing, D.

1985-01-01

A sensitivity analysis is presented that can be used to judge the impact of vehicle dynamic model variations on the relative stability of multivariable continuous closed-loop control systems. The sensitivity analysis uses and extends the singular-value concept by developing expressions for the gradients of the singular value with respect to variations in the vehicle dynamic model and the controller design. Combined with a priori estimates of the accuracy of the model, the gradients are used to identify the elements in the vehicle dynamic model and controller that could severely impact the system's relative stability. The technique is demonstrated for a yaw/roll damper stability augmentation designed for a business jet.

Multivariate data analysis and machine learning in Alzheimer's disease with a focus on structural magnetic resonance imaging.

PubMed

Falahati, Farshad; Westman, Eric; Simmons, Andrew

2014-01-01

Machine learning algorithms and multivariate data analysis methods have been widely utilized in the field of Alzheimer's disease (AD) research in recent years. Advances in medical imaging and medical image analysis have provided a means to generate and extract valuable neuroimaging information. Automatic classification techniques provide tools to analyze this information and observe inherent disease-related patterns in the data. In particular, these classifiers have been used to discriminate AD patients from healthy control subjects and to predict conversion from mild cognitive impairment to AD. In this paper, recent studies are reviewed that have used machine learning and multivariate analysis in the field of AD research. The main focus is on studies that used structural magnetic resonance imaging (MRI), but studies that included positron emission tomography and cerebrospinal fluid biomarkers in addition to MRI are also considered. A wide variety of materials and methods has been employed in different studies, resulting in a range of different outcomes. Influential factors such as classifiers, feature extraction algorithms, feature selection methods, validation approaches, and cohort properties are reviewed, as well as key MRI-based and multi-modal based studies. Current and future trends are discussed.

Water quality analysis of the Rapur area, Andhra Pradesh, South India using multivariate techniques

NASA Astrophysics Data System (ADS)

Nagaraju, A.; Sreedhar, Y.; Thejaswi, A.; Sayadi, Mohammad Hossein

2017-10-01

The groundwater samples from Rapur area were collected from different sites to evaluate the major ion chemistry. The large number of data can lead to difficulties in the integration, interpretation, and representation of the results. Two multivariate statistical methods, hierarchical cluster analysis (HCA) and factor analysis (FA), were applied to evaluate their usefulness to classify and identify geochemical processes controlling groundwater geochemistry. Four statistically significant clusters were obtained from 30 sampling stations. This has resulted two important clusters viz., cluster 1 (pH, Si, CO3, Mg, SO4, Ca, K, HCO3, alkalinity, Na, Na + K, Cl, and hardness) and cluster 2 (EC and TDS) which are released to the study area from different sources. The application of different multivariate statistical techniques, such as principal component analysis (PCA), assists in the interpretation of complex data matrices for a better understanding of water quality of a study area. From PCA, it is clear that the first factor (factor 1), accounted for 36.2% of the total variance, was high positive loading in EC, Mg, Cl, TDS, and hardness. Based on the PCA scores, four significant cluster groups of sampling locations were detected on the basis of similarity of their water quality.

Control Charts When the Observations Are Correlated.

DTIC Science & Technology

1987-05-01

l7 D-AiB6 388 CONTROL CHARTS WHEN THE OBSERVATIONS ARE CORRELATED(J) i/iPITTSBURGH UNIV PA CENTER FOR KULTIVARIATE ANALYSIS P R KRISHNAIAH ET AL MAY... Krishnaiah and B. Q. Miao F-49620-85-C-0008 S. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENT. PROJECT. TASK AREA II WORK UNIT NUMBERS... Krishnaiah and B.Q. Miao Center for Multivariate Analysis University of Pittsburgh N DTIC E L 1Zk-, -I- OCT0 11987 Play 1987 Technical Report No. 87-09

Potential of non-invasive esophagus cancer detection based on urine surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Huang, Shaohua; Wang, Lan; Chen, Weisheng; Feng, Shangyuan; Lin, Juqiang; Huang, Zufang; Chen, Guannan; Li, Buhong; Chen, Rong

2014-11-01

Non-invasive esophagus cancer detection based on urine surface-enhanced Raman spectroscopy (SERS) analysis was presented. Urine SERS spectra were measured on esophagus cancer patients (n = 56) and healthy volunteers (n = 36) for control analysis. Tentative assignments of the urine SERS spectra indicated some interesting esophagus cancer-specific biomolecular changes, including a decrease in the relative content of urea and an increase in the percentage of uric acid in the urine of esophagus cancer patients compared to that of healthy subjects. Principal component analysis (PCA) combined with linear discriminant analysis (LDA) was employed to analyze and differentiate the SERS spectra between normal and esophagus cancer urine. The diagnostic algorithms utilizing a multivariate analysis method achieved a diagnostic sensitivity of 89.3% and specificity of 83.3% for separating esophagus cancer samples from normal urine samples. These results from the explorative work suggested that silver nano particle-based urine SERS analysis coupled with PCA-LDA multivariate analysis has potential for non-invasive detection of esophagus cancer.

Multivariate analysis in thoracic research.

PubMed

Mengual-Macenlle, Noemí; Marcos, Pedro J; Golpe, Rafael; González-Rivas, Diego

2015-03-01

Multivariate analysis is based in observation and analysis of more than one statistical outcome variable at a time. In design and analysis, the technique is used to perform trade studies across multiple dimensions while taking into account the effects of all variables on the responses of interest. The development of multivariate methods emerged to analyze large databases and increasingly complex data. Since the best way to represent the knowledge of reality is the modeling, we should use multivariate statistical methods. Multivariate methods are designed to simultaneously analyze data sets, i.e., the analysis of different variables for each person or object studied. Keep in mind at all times that all variables must be treated accurately reflect the reality of the problem addressed. There are different types of multivariate analysis and each one should be employed according to the type of variables to analyze: dependent, interdependence and structural methods. In conclusion, multivariate methods are ideal for the analysis of large data sets and to find the cause and effect relationships between variables; there is a wide range of analysis types that we can use.

A framework for multivariate data-based at-site flood frequency analysis: Essentiality of the conjugal application of parametric and nonparametric approaches

NASA Astrophysics Data System (ADS)

Vittal, H.; Singh, Jitendra; Kumar, Pankaj; Karmakar, Subhankar

2015-06-01

In watershed management, flood frequency analysis (FFA) is performed to quantify the risk of flooding at different spatial locations and also to provide guidelines for determining the design periods of flood control structures. The traditional FFA was extensively performed by considering univariate scenario for both at-site and regional estimation of return periods. However, due to inherent mutual dependence of the flood variables or characteristics [i.e., peak flow (P), flood volume (V) and flood duration (D), which are random in nature], analysis has been further extended to multivariate scenario, with some restrictive assumptions. To overcome the assumption of same family of marginal density function for all flood variables, the concept of copula has been introduced. Although, the advancement from univariate to multivariate analyses drew formidable attention to the FFA research community, the basic limitation was that the analyses were performed with the implementation of only parametric family of distributions. The aim of the current study is to emphasize the importance of nonparametric approaches in the field of multivariate FFA; however, the nonparametric distribution may not always be a good-fit and capable of replacing well-implemented multivariate parametric and multivariate copula-based applications. Nevertheless, the potential of obtaining best-fit using nonparametric distributions might be improved because such distributions reproduce the sample's characteristics, resulting in more accurate estimations of the multivariate return period. Hence, the current study shows the importance of conjugating multivariate nonparametric approach with multivariate parametric and copula-based approaches, thereby results in a comprehensive framework for complete at-site FFA. Although the proposed framework is designed for at-site FFA, this approach can also be applied to regional FFA because regional estimations ideally include at-site estimations. The framework is based on the following steps: (i) comprehensive trend analysis to assess nonstationarity in the observed data; (ii) selection of the best-fit univariate marginal distribution with a comprehensive set of parametric and nonparametric distributions for the flood variables; (iii) multivariate frequency analyses with parametric, copula-based and nonparametric approaches; and (iv) estimation of joint and various conditional return periods. The proposed framework for frequency analysis is demonstrated using 110 years of observed data from Allegheny River at Salamanca, New York, USA. The results show that for both univariate and multivariate cases, the nonparametric Gaussian kernel provides the best estimate. Further, we perform FFA for twenty major rivers over continental USA, which shows for seven rivers, all the flood variables followed nonparametric Gaussian kernel; whereas for other rivers, parametric distributions provide the best-fit either for one or two flood variables. Thus the summary of results shows that the nonparametric method cannot substitute the parametric and copula-based approaches, but should be considered during any at-site FFA to provide the broadest choices for best estimation of the flood return periods.

The Gendered Monitoring of Juvenile Delinquents: A Test of Power-Control Theory Using a Retrospective Cohort Study

ERIC Educational Resources Information Center

Schulze, Corina; Bryan, Valerie

2017-01-01

Through the framework of power-control theory (PCT), we provide a model of juvenile offending that places the gendered-raced treatment of juveniles central to the analysis. We test the theory using a unique sample that is predominately African American, poor, and composed entirely of juvenile offenders. Multivariate models compare the predictive…

Chronic osteomyelitis correlates with increased risk of acute pancreatitis in a case-control study in Taiwan.

PubMed

Lai, Shih-Wei; Lai, Hsueh-Chou; Lin, Cheng-Li; Liao, Kuan-Fu; Tseng, Chun-Hung

2015-07-01

The objective of this study was to examine the relationship between chronic osteomyelitis and acute pancreatitis in Taiwan. This was a population-based case-control study utilizing the database of the Taiwan National Health Insurance Program. We identified 7678 cases aged 20-84 with newly diagnosed acute pancreatitis during the period of 1998 to 2011. From the same database, 30,712 subjects without diagnosis of acute pancreatitis were selected as controls. The cases and controls were matched with sex, age and index year of diagnosing acute pancreatitis. The odds ratio with 95% confidence interval of acute pancreatitis associated with chronic osteomyelitis was examined by the multivariable unconditional logistic regression analysis. After adjustment for multiple confounders, the multivariable analysis showed that the adjusted odds ratio of acute pancreatitis was 1.93 for subjects with chronic osteomyelitis (95% confidence interval 1.01, 3.69), when compared with subjects without chronic osteomyelitis. Chronic osteomyelitis correlates with increased risk of acute pancreatitis. Patients with chronic osteomyelitis should be carefully monitored about the risk of acute pancreatitis. Copyright © 2015 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

A Quality by Design approach to investigate tablet dissolution shift upon accelerated stability by multivariate methods.

PubMed

Huang, Jun; Goolcharran, Chimanlall; Ghosh, Krishnendu

2011-05-01

This paper presents the use of experimental design, optimization and multivariate techniques to investigate root-cause of tablet dissolution shift (slow-down) upon stability and develop control strategies for a drug product during formulation and process development. The effectiveness and usefulness of these methodologies were demonstrated through two application examples. In both applications, dissolution slow-down was observed during a 4-week accelerated stability test under 51°C/75%RH storage condition. In Application I, an experimental design was carried out to evaluate the interactions and effects of the design factors on critical quality attribute (CQA) of dissolution upon stability. The design space was studied by design of experiment (DOE) and multivariate analysis to ensure desired dissolution profile and minimal dissolution shift upon stability. Multivariate techniques, such as multi-way principal component analysis (MPCA) of the entire dissolution profiles upon stability, were performed to reveal batch relationships and to evaluate the impact of design factors on dissolution. In Application II, an experiment was conducted to study the impact of varying tablet breaking force on dissolution upon stability utilizing MPCA. It was demonstrated that the use of multivariate methods, defined as Quality by Design (QbD) principles and tools in ICH-Q8 guidance, provides an effective means to achieve a greater understanding of tablet dissolution upon stability. Copyright © 2010 Elsevier B.V. All rights reserved.

Salting-out assisted liquid-liquid extraction and partial least squares regression to assay low molecular weight polycyclic aromatic hydrocarbons leached from soils and sediments

NASA Astrophysics Data System (ADS)

Bressan, Lucas P.; do Nascimento, Paulo Cícero; Schmidt, Marcella E. P.; Faccin, Henrique; de Machado, Leandro Carvalho; Bohrer, Denise

2017-02-01

A novel method was developed to determine low molecular weight polycyclic aromatic hydrocarbons in aqueous leachates from soils and sediments using a salting-out assisted liquid-liquid extraction, synchronous fluorescence spectrometry and a multivariate calibration technique. Several experimental parameters were controlled and the optimum conditions were: sodium carbonate as the salting-out agent at concentration of 2 mol L- 1, 3 mL of acetonitrile as extraction solvent, 6 mL of aqueous leachate, vortexing for 5 min and centrifuging at 4000 rpm for 5 min. The partial least squares calibration was optimized to the lowest values of root mean squared error and five latent variables were chosen for each of the targeted compounds. The regression coefficients for the true versus predicted concentrations were higher than 0.99. Figures of merit for the multivariate method were calculated, namely sensitivity, multivariate detection limit and multivariate quantification limit. The selectivity was also evaluated and other polycyclic aromatic hydrocarbons did not interfere in the analysis. Likewise, high performance liquid chromatography was used as a comparative methodology, and the regression analysis between the methods showed no statistical difference (t-test). The proposed methodology was applied to soils and sediments of a Brazilian river and the recoveries ranged from 74.3% to 105.8%. Overall, the proposed methodology was suitable for the targeted compounds, showing that the extraction method can be applied to spectrofluorometric analysis and that the multivariate calibration is also suitable for these compounds in leachates from real samples.

Correlative and multivariate analysis of increased radon concentration in underground laboratory.

PubMed

Maletić, Dimitrije M; Udovičić, Vladimir I; Banjanac, Radomir M; Joković, Dejan R; Dragić, Aleksandar L; Veselinović, Nikola B; Filipović, Jelena

2014-11-01

The results of analysis using correlative and multivariate methods, as developed for data analysis in high-energy physics and implemented in the Toolkit for Multivariate Analysis software package, of the relations of the variation of increased radon concentration with climate variables in shallow underground laboratory is presented. Multivariate regression analysis identified a number of multivariate methods which can give a good evaluation of increased radon concentrations based on climate variables. The use of the multivariate regression methods will enable the investigation of the relations of specific climate variable with increased radon concentrations by analysis of regression methods resulting in 'mapped' underlying functional behaviour of radon concentrations depending on a wide spectrum of climate variables. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Using Time Series Analysis to Predict Cardiac Arrest in a PICU.

PubMed

Kennedy, Curtis E; Aoki, Noriaki; Mariscalco, Michele; Turley, James P

2015-11-01

To build and test cardiac arrest prediction models in a PICU, using time series analysis as input, and to measure changes in prediction accuracy attributable to different classes of time series data. Retrospective cohort study. Thirty-one bed academic PICU that provides care for medical and general surgical (not congenital heart surgery) patients. Patients experiencing a cardiac arrest in the PICU and requiring external cardiac massage for at least 2 minutes. None. One hundred three cases of cardiac arrest and 109 control cases were used to prepare a baseline dataset that consisted of 1,025 variables in four data classes: multivariate, raw time series, clinical calculations, and time series trend analysis. We trained 20 arrest prediction models using a matrix of five feature sets (combinations of data classes) with four modeling algorithms: linear regression, decision tree, neural network, and support vector machine. The reference model (multivariate data with regression algorithm) had an accuracy of 78% and 87% area under the receiver operating characteristic curve. The best model (multivariate + trend analysis data with support vector machine algorithm) had an accuracy of 94% and 98% area under the receiver operating characteristic curve. Cardiac arrest predictions based on a traditional model built with multivariate data and a regression algorithm misclassified cases 3.7 times more frequently than predictions that included time series trend analysis and built with a support vector machine algorithm. Although the final model lacks the specificity necessary for clinical application, we have demonstrated how information from time series data can be used to increase the accuracy of clinical prediction models.

Multivariate Methods for Meta-Analysis of Genetic Association Studies.

PubMed

Dimou, Niki L; Pantavou, Katerina G; Braliou, Georgia G; Bagos, Pantelis G

2018-01-01

Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.

Family Influences on College Students' Occupational Identity

ERIC Educational Resources Information Center

Berrios-Allison, Ana C.

2005-01-01

The occupational identity statuses of 232 college students were analyzed by examining their family emotional environment and the identity control processes that drive career decision making. Results of multivariate analysis showed that each family differentiation construct, family tolerance for connectedness, and separateness explained significant…

Sensor failure and multivariable control for airbreathing propulsion systems. Ph.D. Thesis - Dec. 1979 Final Report

NASA Technical Reports Server (NTRS)

Behbehani, K.

1980-01-01

A new sensor/actuator failure analysis technique for turbofan jet engines was developed. Three phases of failure analysis, namely detection, isolation, and accommodation are considered. Failure detection and isolation techniques are developed by utilizing the concept of Generalized Likelihood Ratio (GLR) tests. These techniques are applicable to both time varying and time invariant systems. Three GLR detectors are developed for: (1) hard-over sensor failure; (2) hard-over actuator failure; and (3) brief disturbances in the actuators. The probability distribution of the GLR detectors and the detectability of sensor/actuator failures are established. Failure type is determined by the maximum of the GLR detectors. Failure accommodation is accomplished by extending the Multivariable Nyquest Array (MNA) control design techniques to nonsquare system designs. The performance and effectiveness of the failure analysis technique are studied by applying the technique to a turbofan jet engine, namely the Quiet Clean Short Haul Experimental Engine (QCSEE). Single and multiple sensor/actuator failures in the QCSEE are simulated and analyzed and the effects of model degradation are studied.

Estimation and Psychometric Analysis of Component Profile Scores via Multivariate Generalizability Theory

ERIC Educational Resources Information Center

Grochowalski, Joseph H.

2015-01-01

Component Universe Score Profile analysis (CUSP) is introduced in this paper as a psychometric alternative to multivariate profile analysis. The theoretical foundations of CUSP analysis are reviewed, which include multivariate generalizability theory and constrained principal components analysis. Because CUSP is a combination of generalizability…

Multivariable polynomial fitting of controlled single-phase nonlinear load of input current total harmonic distortion

NASA Astrophysics Data System (ADS)

Sikora, Roman; Markiewicz, Przemysław; Pabjańczyk, Wiesława

2018-04-01

The power systems usually include a number of nonlinear receivers. Nonlinear receivers are the source of disturbances generated to the power system in the form of higher harmonics. The level of these disturbances describes the total harmonic distortion coefficient THD. Its value depends on many factors. One of them are the deformation and change in RMS value of supply voltage. A modern LED luminaire is a nonlinear receiver as well. The paper presents the results of the analysis of the influence of change in RMS value of supply voltage and the level of dimming of the tested luminaire on the value of the current THD. The analysis was made using a mathematical model based on multivariable polynomial fitting.

Fermentanomics: Relating quality attributes of a monoclonal antibody to cell culture process variables and raw materials using multivariate data analysis.

PubMed

Rathore, Anurag S; Kumar Singh, Sumit; Pathak, Mili; Read, Erik K; Brorson, Kurt A; Agarabi, Cyrus D; Khan, Mansoor

2015-01-01

Fermentanomics is an emerging field of research and involves understanding the underlying controlled process variables and their effect on process yield and product quality. Although major advancements have occurred in process analytics over the past two decades, accurate real-time measurement of significant quality attributes for a biotech product during production culture is still not feasible. Researchers have used an amalgam of process models and analytical measurements for monitoring and process control during production. This article focuses on using multivariate data analysis as a tool for monitoring the internal bioreactor dynamics, the metabolic state of the cell, and interactions among them during culture. Quality attributes of the monoclonal antibody product that were monitored include glycosylation profile of the final product along with process attributes, such as viable cell density and level of antibody expression. These were related to process variables, raw materials components of the chemically defined hybridoma media, concentration of metabolites formed during the course of the culture, aeration-related parameters, and supplemented raw materials such as glucose, methionine, threonine, tryptophan, and tyrosine. This article demonstrates the utility of multivariate data analysis for correlating the product quality attributes (especially glycosylation) to process variables and raw materials (especially amino acid supplements in cell culture media). The proposed approach can be applied for process optimization to increase product expression, improve consistency of product quality, and target the desired quality attribute profile. © 2015 American Institute of Chemical Engineers.

Metabolomic Analysis of Overactive Bladder in Male Patients: Identification of Potential Metabolite Biomarkers.

PubMed

Shimura, Hiroshi; Mitsui, Takahiko; Kira, Satoru; Ihara, Tatsuya; Sawada, Norifumi; Nakagomi, Hiroshi; Miyamoto, Tatsuya; Tsuchiya, Sachiko; Kanda, Mie; Takeda, Masayuki

2018-05-09

To identify metabolites that are associated with an overactive bladder (OAB) using metabolomics. A total of 58 male patients without apparent neurologic disease completed 24-hour bladder diaries of their micturition behavior and International Prostate Symptom Score (IPSS) for the assessment of micturition behavior and lower urinary tract symptoms. Urgency was defined as an IPSS urgency score of ≥2 (OAB group), and patients with IPSS urgency scores of ≤1 belonged to the control group. A comprehensive study of plasma metabolites was also conducted using capillary electrophoresis time-of-flight mass spectrometry. Metabolite levels were compared between the control and OAB groups using the Mann-Whitney U test. Potential metabolite biomarkers were selected using multivariate logistic regression analysis. Of the 58 subjects, the control and OAB groups consisted of 32 and 26 male patients, respectively. Nocturnal urinary volume, 24-hour micturition frequency, nocturnal micturition frequency, and the nocturia index were significantly higher in the OAB group. Metabolomic analysis revealed 60 metabolites in the subjects' plasma. The levels of 11 metabolites differed between the control and OAB groups. Multivariate analysis showed that an increased glutamate level and reduced arginine, glutamine, and inosine monophosphate levels are significantly associated with OAB in male patients. Reduced levels of asparagine and hydroxyproline could also be associated with OAB. Urgency is associated with abnormal metabolism. Analyses of amino acid profiles might aid the search for new treatment targets for OAB. Copyright © 2018 Elsevier Inc. All rights reserved.

Arterial compression of the retro-olivary sulcus of the medulla in essential hypertension: a multivariate analysis.

PubMed

Coffee, Robert E; Nicholas, Joyce S; Egan, Brent M; Rumboldt, Zoran; D'Agostino, Sabino; Patel, Sunil J

2005-11-01

Pulsatile arterial compression (AC) of the ventrolateral medulla (VLM) has been postulated to cause neurogenically mediated essential hypertension (EHTN). We aimed to establish whether the association between AC of specifically the retro-olivary sulcus (ROS) of the VLM and EHTN was significant, while controlling for other risks associated with EHTN. Case-control study. Posterior fossa magnetic resonance imaging scans of 131 subjects, including 58 subjects with EHTN and 73 normotensives, were reviewed to determine the presence of AC in the ROS. The history of other risk factors for EHTN was obtained by reviewing medical records. Multivariate logistic regression analysis of these data shows a significant association between AC in the ROS (right and/or left) and EHTN [odds ratio (OR) = 3.03, 95% confidence interval (CI) = 1.30, 7.06]. This analysis was done controlling for other known EHTN risk factors such as age, race, sex, diabetes, and obesity. A secondary analysis also controlling for these variables shows that AC of both the right and left ROS are independently associated with EHTN (right AC: OR = 5.04, 95% CI = 1.33, 19.17; left AC: OR = 3.39, 95% CI = 1.20, 9.60). In this retrospective study of subjects with EHTN and normotensive controls that had undergone magnetic resonance imaging of the posterior fossa, AC of the ROS on either side of the medulla is a significant independent risk factor in EHTN. Further studies are required to determine whether this is true for the general population of patients with neurogenically mediated EHTN.

Stability and Performance Robustness Assessment of Multivariable Control Systems

DTIC Science & Technology

1993-04-01

00- STABILITY AND PERFORMANCE ROBUSTNESS ASSESSMENT OF MULTIVARIABLE CONTROL SYSTEMS Asok Ray , Jenny I. Shen, and Chen-Kuo Weng Mechanical...Office of Naval Research Assessment of Multivariable Control Systems Grant No. N00014-90-J- 1513 6. AUTHOR(S) (Extension) Professor Asok Ray , Dr...20 The Pennsylvania State University University Park, PA 16802 (20 for Professor Asok Ray ) Naval Postgraduate School

Design of multivariable feedback control systems via spectral assignment. [as applied to aircraft flight control

NASA Technical Reports Server (NTRS)

Liberty, S. R.; Mielke, R. R.; Tung, L. J.

1981-01-01

Applied research in the area of spectral assignment in multivariable systems is reported. A frequency domain technique for determining the set of all stabilizing controllers for a single feedback loop multivariable system is described. It is shown that decoupling and tracking are achievable using this procedure. The technique is illustrated with a simple example.

Multivariate analysis of the impacts of the turbine fuel JP-4 in a microcosm toxicity test with implications for the evaluation of ecosystem dynamics and risk assessment.

PubMed

Landis, W G; Matthews, R A; Markiewicz, A J; Matthews, G B

1993-12-01

Turbine fuels are often the only aviation fuel available in most of the world. Turbine fuels consist of numerous constituents with varying water solubilities, volatilities and toxicities. This study investigates the toxicity of the water soluble fraction (WSF) of JP-4 using the Standard Aquatic Microcosm (SAM). Multivariate analysis of the complex data, including the relatively new method of nonmetric clustering, was used and compared to more traditional analyses. Particular emphasis is placed on ecosystem dynamics in multivariate space.The WSF is prepared by vigorously mixing the fuel and the SAM microcosm media in a separatory funnel. The water phase, which contains the water-soluble fraction of JP-4 is then collected. The SAM experiment was conducted using concentrations of 0.0, 1.5 and 15% WSF. The WSF is added on day 7 of the experiments by removing 450 ml from each microcosm including the controls, then adding the appropriate amount of toxicant solution and finally bringing the final volume to 3 L with microcosm media. Analysis of the WSF was performed by purge and trap gas chromatography. The organic constituents of the WSF were not recoverable from the water column within several days of the addition of the toxicant. However, the impact of the WSF on the microcosm was apparent. In the highest initial concentration treatment group an algal bloom ensued, generated by the apparent toxicity of the WSF of JP-4 to the daphnids. As the daphnid populations recovered the algal populations decreased to control values. Multivariate methods clearly demonstrated this initial impact along with an additional oscillation seperating the four treatment groups in the latter segment of the experiment. Apparent recovery may be an artifact of the projections used to describe the multivariate data. The variables that were most important in distinguishing the four groups shifted during the course of the 63 day experiment. Even this simple microcosm exhibited a variety of dynamics, with implications for biomonitoring schemes and ecological risk assessments.

Analysis of Prognostic Factors and Patterns of Recurrence in Patients With Pathologic Stage III Endometrial Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patel, Samir; Portelance, Lorraine; Gilbert, Lucy

2007-08-01

Purpose: To retrospectively assess prognostic factors and patterns of recurrence in patients with pathologic Stage III endometrial cancer. Methods and Materials: Between 1989 and 2003, 107 patients with pathologic International Federation of Gynecology and Obstetrics Stage III endometrial adenocarcinoma confined to the pelvis were treated at our institution. Adjuvant radiotherapy (RT) was delivered to 68 patients (64%). The influence of multiple patient- and treatment-related factors on pelvic and distant control and overall survival (OS) was evaluated. Results: Median follow-up for patients at risk was 41 months. Five-year actuarial OS was significantly improved in patients treated with adjuvant RT (68%) comparedmore » with those with resection alone (50%; p = 0.029). Age, histology, grade, uterine serosal invasion, adnexal involvement, number of extrauterine sites, and treatment with adjuvant RT predicted for improved survival in univariate analysis. Multivariate analysis revealed that grade, uterine serosal invasion, and treatment with adjuvant RT were independent predictors of survival. Five-year actuarial pelvic control was improved significantly with the delivery of adjuvant RT (74% vs. 49%; p = 0.011). Depth of myometrial invasion and treatment with adjuvant RT were independent predictors of pelvic control in multivariate analysis. Conclusions: Multiple prognostic factors predicting for the outcome of pathologic Stage III endometrial cancer patients were identified in this analysis. In particular, delivery of adjuvant RT seems to be a significant independent predictor for improved survival and pelvic control, suggesting that pelvic RT should be routinely considered in the management of these patients.« less

Multivariate meta-analysis: potential and promise.

PubMed

Jackson, Dan; Riley, Richard; White, Ian R

2011-09-10

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day 'Multivariate meta-analysis' event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd.

Cocaine dependence and thalamic functional connectivity: a multivariate pattern analysis.

PubMed

Zhang, Sheng; Hu, Sien; Sinha, Rajita; Potenza, Marc N; Malison, Robert T; Li, Chiang-Shan R

2016-01-01

Cocaine dependence is associated with deficits in cognitive control. Previous studies demonstrated that chronic cocaine use affects the activity and functional connectivity of the thalamus, a subcortical structure critical for cognitive functioning. However, the thalamus contains nuclei heterogeneous in functions, and it is not known how thalamic subregions contribute to cognitive dysfunctions in cocaine dependence. To address this issue, we used multivariate pattern analysis (MVPA) to examine how functional connectivity of the thalamus distinguishes 100 cocaine-dependent participants (CD) from 100 demographically matched healthy control individuals (HC). We characterized six task-related networks with independent component analysis of fMRI data of a stop signal task and employed MVPA to distinguish CD from HC on the basis of voxel-wise thalamic connectivity to the six independent components. In an unbiased model of distinct training and testing data, the analysis correctly classified 72% of subjects with leave-one-out cross-validation (p < 0.001), superior to comparison brain regions with similar voxel counts (p < 0.004, two-sample t test). Thalamic voxels that form the basis of classification aggregate in distinct subclusters, suggesting that connectivities of thalamic subnuclei distinguish CD from HC. Further, linear regressions provided suggestive evidence for a correlation of the thalamic connectivities with clinical variables and performance measures on the stop signal task. Together, these findings support thalamic circuit dysfunction in cognitive control as an important neural marker of cocaine dependence.

Adult males with haemophilia have a different macrovascular and microvascular endothelial function profile compared with healthy controls.

PubMed

Sun, H; Yang, M; Fung, M; Chan, S; Jawi, M; Anderson, T; Poon, M-C; Jackson, S

2017-09-01

Endothelial function has been identified as an independent predictor of cardiovascular risk in the general population. It is unclear if the haemophilia population has a different endothelial function profile compared to the healthy population. This prospective study aims to assess if there is a difference in endothelial function between haemophilia patients and healthy controls, and the impact of endothelial function on vascular outcomes in the haemophilia population. Baseline cardiovascular risk factors and endothelial function were presented. Adult males with haemophilia A or B recruited from the British Columbia and Southern Alberta haemophilia treatment centres were matched to healthy male controls by age and cardiovascular risk factors. Macrovascular endothelial function was assessed by brachial artery flow-mediated dilation (FMD) and nitroglycerin-mediated dilation (NMD), and microvascular endothelial function was assessed by hyperaemic velocity time integral (VTI). Multivariable linear regression was used to assess the association between haemophilia and endothelial function. A total of 81 patients with haemophilia and 243 controls were included. Patients with haemophilia had a similar FMD and NMD compared to controls, although haemophilia was associated with higher FMD on multivariable analysis. Haemophilia was associated with significantly lower VTI on univariate and multivariable analyses, regardless of haemophilia type and severity. Adult males with haemophilia appear to have lower microvascular endothelial function compared to healthy controls. Future studies to assess the impact of endothelial dysfunction on cardiovascular events in the haemophilia population are needed. © 2017 John Wiley & Sons Ltd.

Network meta-analysis of multiple outcome measures accounting for borrowing of information across outcomes

PubMed Central

2014-01-01

Background Network meta-analysis (NMA) enables simultaneous comparison of multiple treatments while preserving randomisation. When summarising evidence to inform an economic evaluation, it is important that the analysis accurately reflects the dependency structure within the data, as correlations between outcomes may have implication for estimating the net benefit associated with treatment. A multivariate NMA offers a framework for evaluating multiple treatments across multiple outcome measures while accounting for the correlation structure between outcomes. Methods The standard NMA model is extended to multiple outcome settings in two stages. In the first stage, information is borrowed across outcomes as well across studies through modelling the within-study and between-study correlation structure. In the second stage, we make use of the additional assumption that intervention effects are exchangeable between outcomes to predict effect estimates for all outcomes, including effect estimates on outcomes where evidence is either sparse or the treatment had not been considered by any one of the studies included in the analysis. We apply the methods to binary outcome data from a systematic review evaluating the effectiveness of nine home safety interventions on uptake of three poisoning prevention practices (safe storage of medicines, safe storage of other household products, and possession of poison centre control telephone number) in households with children. Analyses are conducted in WinBUGS using Markov Chain Monte Carlo (MCMC) simulations. Results Univariate and the first stage multivariate models produced broadly similar point estimates of intervention effects but the uncertainty around the multivariate estimates varied depending on the prior distribution specified for the between-study covariance structure. The second stage multivariate analyses produced more precise effect estimates while enabling intervention effects to be predicted for all outcomes, including intervention effects on outcomes not directly considered by the studies included in the analysis. Conclusions Accounting for the dependency between outcomes in a multivariate meta-analysis may or may not improve the precision of effect estimates from a network meta-analysis compared to analysing each outcome separately. PMID:25047164

Combining microwave resonance technology to multivariate data analysis as a novel PAT tool to improve process understanding in fluid bed granulation.

PubMed

Lourenço, Vera; Herdling, Thorsten; Reich, Gabriele; Menezes, José C; Lochmann, Dirk

2011-08-01

A set of 192 fluid bed granulation batches at industrial scale were in-line monitored using microwave resonance technology (MRT) to determine moisture, temperature and density of the granules. Multivariate data analysis techniques such as multiway partial least squares (PLS), multiway principal component analysis (PCA) and multivariate batch control charts were applied onto collected batch data sets. The combination of all these techniques, along with off-line particle size measurements, led to significantly increased process understanding. A seasonality effect could be put into evidence that impacted further processing through its influence on the final granule size. Moreover, it was demonstrated by means of a PLS that a relation between the particle size and the MRT measurements can be quantitatively defined, highlighting a potential ability of the MRT sensor to predict information about the final granule size. This study has contributed to improve a fluid bed granulation process, and the process knowledge obtained shows that the product quality can be built in process design, following Quality by Design (QbD) and Process Analytical Technology (PAT) principles. Copyright © 2011. Published by Elsevier B.V.

Chromatography methods and chemometrics for determination of milk fat adulterants

NASA Astrophysics Data System (ADS)

Trbović, D.; Petronijević, R.; Đorđević, V.

2017-09-01

Milk and milk-based products are among the leading food categories according to reported cases of food adulteration. Although many authentication problems exist in all areas of the food industry, adequate control methods are required to evaluate the authenticity of milk and milk products in the dairy industry. Moreover, gas chromatography (GC) analysis of triacylglycerols (TAGs) or fatty acid (FA) profiles of milk fat (MF) in combination with multivariate statistical data processing have been used to detect adulterations of milk and dairy products with foreign fats. The adulteration of milk and butter is a major issue for the dairy industry. The major adulterants of MF are vegetable oils (soybean, sunflower, groundnut, coconut, palm and peanut oil) and animal fat (cow tallow and pork lard). Multivariate analysis enables adulterated MF to be distinguished from authentic MF, while taking into account many analytical factors. Various multivariate analysis methods have been proposed to quantitatively detect levels of adulterant non-MFs, with multiple linear regression (MLR) seemingly the most suitable. There is a need for increased use of chemometric data analyses to detect adulterated MF in foods and for their expanded use in routine quality assurance testing.

Multivariable control theory applied to hierarchial attitude control for planetary spacecraft

NASA Technical Reports Server (NTRS)

Boland, J. S., III; Russell, D. W.

1972-01-01

Multivariable control theory is applied to the design of a hierarchial attitude control system for the CARD space vehicle. The system selected uses reaction control jets (RCJ) and control moment gyros (CMG). The RCJ system uses linear signal mixing and a no-fire region similar to that used on the Skylab program; the y-axis and z-axis systems which are coupled use a sum and difference feedback scheme. The CMG system uses the optimum steering law and the same feedback signals as the RCJ system. When both systems are active the design is such that the torques from each system are never in opposition. A state-space analysis was made of the CMG system to determine the general structure of the input matrices (steering law) and feedback matrices that will decouple the axes. It is shown that the optimum steering law and proportional-plus-rate feedback are special cases. A derivation of the disturbing torques on the space vehicle due to the motion of the on-board television camera is presented. A procedure for computing an upper bound on these torques (given the system parameters) is included.

Multivariate approach to quantitative analysis of Aphis gossypii Glover (Hemiptera: Aphididae) and their natural enemy populations at different cotton spacings.

PubMed

Malaquias, José B; Ramalho, Francisco S; Dos S Dias, Carlos T; Brugger, Bruno P; S Lira, Aline Cristina; Wilcken, Carlos F; Pachú, Jéssica K S; Zanuncio, José C

2017-02-09

The relationship between pests and natural enemies using multivariate analysis on cotton in different spacing has not been documented yet. Using multivariate approaches is possible to optimize strategies to control Aphis gossypii at different crop spacings because the possibility of a better use of the aphid sampling strategies as well as the conservation and release of its natural enemies. The aims of the study were (i) to characterize the temporal abundance data of aphids and its natural enemies using principal components, (ii) to analyze the degree of correlation between the insects and between groups of variables (pests and natural enemies), (iii) to identify the main natural enemies responsible for regulating A. gossypii populations, and (iv) to investigate the similarities in arthropod occurrence patterns at different spacings of cotton crops over two seasons. High correlations in the occurrence of Scymnus rubicundus with aphids are shown through principal component analysis and through the important role the species plays in canonical correlation analysis. Clustering the presence of apterous aphids matches the pattern verified for Chrysoperla externa at the three different spacings between rows. Our results indicate that S. rubicundus is the main candidate to regulate the aphid populations in all spacings studied.

Multivariate approach to quantitative analysis of Aphis gossypii Glover (Hemiptera: Aphididae) and their natural enemy populations at different cotton spacings

PubMed Central

Malaquias, José B.; Ramalho, Francisco S.; dos S. Dias, Carlos T.; Brugger, Bruno P.; S. Lira, Aline Cristina; Wilcken, Carlos F.; Pachú, Jéssica K. S.; Zanuncio, José C.

2017-01-01

The relationship between pests and natural enemies using multivariate analysis on cotton in different spacing has not been documented yet. Using multivariate approaches is possible to optimize strategies to control Aphis gossypii at different crop spacings because the possibility of a better use of the aphid sampling strategies as well as the conservation and release of its natural enemies. The aims of the study were (i) to characterize the temporal abundance data of aphids and its natural enemies using principal components, (ii) to analyze the degree of correlation between the insects and between groups of variables (pests and natural enemies), (iii) to identify the main natural enemies responsible for regulating A. gossypii populations, and (iv) to investigate the similarities in arthropod occurrence patterns at different spacings of cotton crops over two seasons. High correlations in the occurrence of Scymnus rubicundus with aphids are shown through principal component analysis and through the important role the species plays in canonical correlation analysis. Clustering the presence of apterous aphids matches the pattern verified for Chrysoperla externa at the three different spacings between rows. Our results indicate that S. rubicundus is the main candidate to regulate the aphid populations in all spacings studied. PMID:28181503

Natural history definition and a suggested clinical approach to Buerger's disease: a case-control study with survival analysis.

PubMed

Fazeli, Bahare; Ravari, Hassan; Assadi, Reza

2012-08-01

The aim of this study was first to describe the natural history of Buerger's disease (BD) and then to discuss a clinical approach to this disease based on multivariate analysis. One hundred eight patients who corresponded with Shionoya's criteria were selected from 2000 to 2007 for this study. Major amputation was considered the ultimate adverse event. Survival analyses were performed by Kaplan-Meier curves. Independent variables including gender, duration of smoking, number of cigarettes smoked per day, minor amputation events and type of treatments, were determined by multivariate Cox regression analysis. The recorded data demonstrated that BD may present in four forms, including relapsing-remitting (75%), secondary progressive (4.6%), primary progressive (14.2%) and benign BD (6.2%). Most of the amputations occurred due to relapses within the six years after diagnosis of BD. In multivariate analysis, duration of smoking of more than 20 years had a significant relationship with further major amputation among patients with BD. Smoking cessation programs with experienced psychotherapists are strongly recommended for those areas in which Buerger's disease is common. Patients who have smoked for more than 20 years should be encouraged to quit smoking, but should also be recommended for more advanced treatment for limb salvage.

Multivariate approach to quantitative analysis of Aphis gossypii Glover (Hemiptera: Aphididae) and their natural enemy populations at different cotton spacings

NASA Astrophysics Data System (ADS)

Malaquias, José B.; Ramalho, Francisco S.; Dos S. Dias, Carlos T.; Brugger, Bruno P.; S. Lira, Aline Cristina; Wilcken, Carlos F.; Pachú, Jéssica K. S.; Zanuncio, José C.

2017-02-01

The relationship between pests and natural enemies using multivariate analysis on cotton in different spacing has not been documented yet. Using multivariate approaches is possible to optimize strategies to control Aphis gossypii at different crop spacings because the possibility of a better use of the aphid sampling strategies as well as the conservation and release of its natural enemies. The aims of the study were (i) to characterize the temporal abundance data of aphids and its natural enemies using principal components, (ii) to analyze the degree of correlation between the insects and between groups of variables (pests and natural enemies), (iii) to identify the main natural enemies responsible for regulating A. gossypii populations, and (iv) to investigate the similarities in arthropod occurrence patterns at different spacings of cotton crops over two seasons. High correlations in the occurrence of Scymnus rubicundus with aphids are shown through principal component analysis and through the important role the species plays in canonical correlation analysis. Clustering the presence of apterous aphids matches the pattern verified for Chrysoperla externa at the three different spacings between rows. Our results indicate that S. rubicundus is the main candidate to regulate the aphid populations in all spacings studied.

FGWAS: Functional genome wide association analysis.

PubMed

Huang, Chao; Thompson, Paul; Wang, Yalin; Yu, Yang; Zhang, Jingwen; Kong, Dehan; Colen, Rivka R; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-10-01

Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs. Copyright © 2017 Elsevier Inc. All rights reserved.

Multivariate Models for Normal and Binary Responses in Intervention Studies

ERIC Educational Resources Information Center

Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen

2016-01-01

Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…

Multivariate functional response regression, with application to fluorescence spectroscopy in a cervical pre-cancer study.

PubMed

Zhu, Hongxiao; Morris, Jeffrey S; Wei, Fengrong; Cox, Dennis D

2017-07-01

Many scientific studies measure different types of high-dimensional signals or images from the same subject, producing multivariate functional data. These functional measurements carry different types of information about the scientific process, and a joint analysis that integrates information across them may provide new insights into the underlying mechanism for the phenomenon under study. Motivated by fluorescence spectroscopy data in a cervical pre-cancer study, a multivariate functional response regression model is proposed, which treats multivariate functional observations as responses and a common set of covariates as predictors. This novel modeling framework simultaneously accounts for correlations between functional variables and potential multi-level structures in data that are induced by experimental design. The model is fitted by performing a two-stage linear transformation-a basis expansion to each functional variable followed by principal component analysis for the concatenated basis coefficients. This transformation effectively reduces the intra-and inter-function correlations and facilitates fast and convenient calculation. A fully Bayesian approach is adopted to sample the model parameters in the transformed space, and posterior inference is performed after inverse-transforming the regression coefficients back to the original data domain. The proposed approach produces functional tests that flag local regions on the functional effects, while controlling the overall experiment-wise error rate or false discovery rate. It also enables functional discriminant analysis through posterior predictive calculation. Analysis of the fluorescence spectroscopy data reveals local regions with differential expressions across the pre-cancer and normal samples. These regions may serve as biomarkers for prognosis and disease assessment.

Feasibility Study on the Use of On-line Multivariate Statistical Process Control for Safeguards Applications in Natural Uranium Conversion Plants

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ladd-Lively, Jennifer L

2014-01-01

The objective of this work was to determine the feasibility of using on-line multivariate statistical process control (MSPC) for safeguards applications in natural uranium conversion plants. Multivariate statistical process control is commonly used throughout industry for the detection of faults. For safeguards applications in uranium conversion plants, faults could include the diversion of intermediate products such as uranium dioxide, uranium tetrafluoride, and uranium hexafluoride. This study was limited to a 100 metric ton of uranium (MTU) per year natural uranium conversion plant (NUCP) using the wet solvent extraction method for the purification of uranium ore concentrate. A key component inmore » the multivariate statistical methodology is the Principal Component Analysis (PCA) approach for the analysis of data, development of the base case model, and evaluation of future operations. The PCA approach was implemented through the use of singular value decomposition of the data matrix where the data matrix represents normal operation of the plant. Component mole balances were used to model each of the process units in the NUCP. However, this approach could be applied to any data set. The monitoring framework developed in this research could be used to determine whether or not a diversion of material has occurred at an NUCP as part of an International Atomic Energy Agency (IAEA) safeguards system. This approach can be used to identify the key monitoring locations, as well as locations where monitoring is unimportant. Detection limits at the key monitoring locations can also be established using this technique. Several faulty scenarios were developed to test the monitoring framework after the base case or normal operating conditions of the PCA model were established. In all of the scenarios, the monitoring framework was able to detect the fault. Overall this study was successful at meeting the stated objective.« less

Structural brain connectivity and cognitive ability differences: A multivariate distance matrix regression analysis.

PubMed

Ponsoda, Vicente; Martínez, Kenia; Pineda-Pardo, José A; Abad, Francisco J; Olea, Julio; Román, Francisco J; Barbey, Aron K; Colom, Roberto

2017-02-01

Neuroimaging research involves analyses of huge amounts of biological data that might or might not be related with cognition. This relationship is usually approached using univariate methods, and, therefore, correction methods are mandatory for reducing false positives. Nevertheless, the probability of false negatives is also increased. Multivariate frameworks have been proposed for helping to alleviate this balance. Here we apply multivariate distance matrix regression for the simultaneous analysis of biological and cognitive data, namely, structural connections among 82 brain regions and several latent factors estimating cognitive performance. We tested whether cognitive differences predict distances among individuals regarding their connectivity pattern. Beginning with 3,321 connections among regions, the 36 edges better predicted by the individuals' cognitive scores were selected. Cognitive scores were related to connectivity distances in both the full (3,321) and reduced (36) connectivity patterns. The selected edges connect regions distributed across the entire brain and the network defined by these edges supports high-order cognitive processes such as (a) (fluid) executive control, (b) (crystallized) recognition, learning, and language processing, and (c) visuospatial processing. This multivariate study suggests that one widespread, but limited number, of regions in the human brain, supports high-level cognitive ability differences. Hum Brain Mapp 38:803-816, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Centralized PI control for high dimensional multivariable systems based on equivalent transfer function.

PubMed

Luan, Xiaoli; Chen, Qiang; Liu, Fei

2014-09-01

This article presents a new scheme to design full matrix controller for high dimensional multivariable processes based on equivalent transfer function (ETF). Differing from existing ETF method, the proposed ETF is derived directly by exploiting the relationship between the equivalent closed-loop transfer function and the inverse of open-loop transfer function. Based on the obtained ETF, the full matrix controller is designed utilizing the existing PI tuning rules. The new proposed ETF model can more accurately represent the original processes. Furthermore, the full matrix centralized controller design method proposed in this paper is applicable to high dimensional multivariable systems with satisfactory performance. Comparison with other multivariable controllers shows that the designed ETF based controller is superior with respect to design-complexity and obtained performance. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Assessment of need of patients with schizophrenia: a study in Vellore, India.

PubMed

Ernest, Sharmila; Nagarajan, Guru; Jacob, K S

2013-12-01

and aims: There is a dearth of studies investigating the prevalence and factors associated with unmet needs in people with schizophrenia from low- and middle-income countries. We aimed to study prevalence and risk factors for unmet need. A case-control study design was employed. One hundred and one (101) consecutive patients attending a psychiatric hospital were assessed using Camberwell Assessment of Need Short version (CANSAS) and Positive and Negative Syndrome Scale (PANSS). Multivariate analysis was employed to adjust for confounders. The majority of patients had many unmet needs. These unmet needs were significantly associated with lower education, poverty and persistent psychopathology on multivariate analysis. Unmet needs are associated with poverty, lower education and persistent psychopathology. There is a need to manage unmet needs, in addition to addressing psychopathology and poverty.

Deconstructing multivariate decoding for the study of brain function.

PubMed

Hebart, Martin N; Baker, Chris I

2017-08-04

Multivariate decoding methods were developed originally as tools to enable accurate predictions in real-world applications. The realization that these methods can also be employed to study brain function has led to their widespread adoption in the neurosciences. However, prior to the rise of multivariate decoding, the study of brain function was firmly embedded in a statistical philosophy grounded on univariate methods of data analysis. In this way, multivariate decoding for brain interpretation grew out of two established frameworks: multivariate decoding for predictions in real-world applications, and classical univariate analysis based on the study and interpretation of brain activation. We argue that this led to two confusions, one reflecting a mixture of multivariate decoding for prediction or interpretation, and the other a mixture of the conceptual and statistical philosophies underlying multivariate decoding and classical univariate analysis. Here we attempt to systematically disambiguate multivariate decoding for the study of brain function from the frameworks it grew out of. After elaborating these confusions and their consequences, we describe six, often unappreciated, differences between classical univariate analysis and multivariate decoding. We then focus on how the common interpretation of what is signal and noise changes in multivariate decoding. Finally, we use four examples to illustrate where these confusions may impact the interpretation of neuroimaging data. We conclude with a discussion of potential strategies to help resolve these confusions in interpreting multivariate decoding results, including the potential departure from multivariate decoding methods for the study of brain function. Copyright © 2017. Published by Elsevier Inc.

Changes in the proportion of facility-based deliveries and related maternal health services among the poor in rural Jhang, Pakistan: results from a demand-side financing intervention.

PubMed

Agha, Sohail

2011-11-30

Demand-side financing projects are now being implemented in many developing countries, yet evidence showing that they reach the poor is scanty. A maternal health voucher scheme provided voucher-paid services in Jhang, a predominantly rural district of Pakistan, during 2010. A pre-test/post-test quasi-experimental design was used to assess the changes in the proportion of facility-based deliveries and related maternal health services among the poor. Household interviews were conducted with randomly selected women in the intervention and control union councils, before and after the intervention.A strong outreach model was used. Voucher promoters were given basic training in identification of poor women using the Poverty Scorecard for Pakistan, in the types of problems women could face during delivery, and in the promotion of antenatal care (ANC), institutional delivery and postnatal care (PNC). Voucher booklets valued at Rs. 4,000 ($48), including three ANC visits, a PNC visit, an institutional delivery, and a postnatal family planning visit, were sold for Rs. 100 ($1.2) to low-income women targeted by project outreach workers. Women suffering from complications were referred to emergency obstetric care services.Analysis was conducted at the bivariate and the multivariate levels. At the multivariate level, logistic regression analysis was conducted to determine whether the increase in institutional delivery was greater among poor women (defined for this study as women in the fourth or fifth quintiles) relative to non-poor women (defined for this study as women in the first quintile) in the intervention union councils compared to the control union councils. Bivariate analysis showed significant increases in the institutional delivery rate among women in the fourth or fifth wealth quintiles in the intervention union councils but no significant changes in this indicator among women in the same wealth quintiles in the control union councils. Multivariate analysis showed that the increase in institutional delivery among poor women relative to non-poor women was significantly greater in the intervention compared to the control union councils. Demand-side financing projects using vouchers can be an effective way of reducing inequities in institutional delivery.

Multivariable Techniques for High-Speed Research Flight Control Systems

NASA Technical Reports Server (NTRS)

Newman, Brett A.

1999-01-01

This report describes the activities and findings conducted under contract with NASA Langley Research Center. Subject matter is the investigation of suitable multivariable flight control design methodologies and solutions for large, flexible high-speed vehicles. Specifically, methodologies are to address the inner control loops used for stabilization and augmentation of a highly coupled airframe system possibly involving rigid-body motion, structural vibrations, unsteady aerodynamics, and actuator dynamics. Design and analysis techniques considered in this body of work are both conventional-based and contemporary-based, and the vehicle of interest is the High-Speed Civil Transport (HSCT). Major findings include: (1) control architectures based on aft tail only are not well suited for highly flexible, high-speed vehicles, (2) theoretical underpinnings of the Wykes structural mode control logic is based on several assumptions concerning vehicle dynamic characteristics, and if not satisfied, the control logic can break down leading to mode destabilization, (3) two-loop control architectures that utilize small forward vanes with the aft tail provide highly attractive and feasible solutions to the longitudinal axis control challenges, and (4) closed-loop simulation sizing analyses indicate the baseline vane model utilized in this report is most likely oversized for normal loading conditions.

The explanatory role of relationship power and control in domestic violence against women in Nicaragua: a feminist psychology analysis.

PubMed

Grose, Rose Grace; Grabe, Shelly

2014-08-01

This study offers a feminist psychology analysis of various aspects of relationship power and control and their relative explanatory contribution to understanding physical, psychological, and sexual violence against women. Findings from structured interviews with 345 women from rural Nicaragua (M age = 44) overwhelmingly demonstrate that measures of power and control reflecting interpersonal relationship dynamics have the strongest predictive power for explaining violence when compared in multivariate analyses to several of the more commonly used measures. These findings have implications for future research and the evaluation of interventions designed to decrease levels of violence against women. © The Author(s) 2014.

Neurodevelopmental Status and Adaptive Behaviors in Preschool Children with Chronic Kidney Disease

ERIC Educational Resources Information Center

Duquette, Peter J.; Hooper, Stephen R.; Icard, Phil F.; Hower, Sarah J.; Mamak, Eva G.; Wetherington, Crista E.; Gipson, Debbie S.

2009-01-01

This study examines the early neurodevelopmental function of infants and preschool children who have chronic kidney disease (CKD). Fifteen patients with CKD are compared to a healthy control group using the "Mullen Scales of Early Learning" (MSEL) and the "Vineland Adaptive Behavior Scale" (VABS). Multivariate analysis reveals…

Disfluency in Spasmodic Dysphonia: A Multivariate Analysis.

ERIC Educational Resources Information Center

Cannito, Michael P.; Burch, Annette Renee; Watts, Christopher; Rappold, Patrick W.; Hood, Stephen B.; Sherrard, Kyla

1997-01-01

This study examined visual analog scaling judgments of disfluency by normal listeners in response to oral reading by 20 adults with spasmodic dysphonia (SD) and nondysphonic controls. Findings suggest that although dysfluency is not a defining feature of SD, it does contribute significantly to the overall clinical impression of severity of the…

Multivariate meta-analysis: Potential and promise

PubMed Central

Jackson, Dan; Riley, Richard; White, Ian R

2011-01-01

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21268052

Spatial characterization of dissolved trace elements and heavy metals in the upper Han River (China) using multivariate statistical techniques.

PubMed

Li, Siyue; Zhang, Quanfa

2010-04-15

A data matrix (4032 observations), obtained during a 2-year monitoring period (2005-2006) from 42 sites in the upper Han River is subjected to various multivariate statistical techniques including cluster analysis, principal component analysis (PCA), factor analysis (FA), correlation analysis and analysis of variance to determine the spatial characterization of dissolved trace elements and heavy metals. Our results indicate that waters in the upper Han River are primarily polluted by Al, As, Cd, Pb, Sb and Se, and the potential pollutants include Ba, Cr, Hg, Mn and Ni. Spatial distribution of trace metals indicates the polluted sections mainly concentrate in the Danjiang, Danjiangkou Reservoir catchment and Hanzhong Plain, and the most contaminated river is in the Hanzhong Plain. Q-model clustering depends on geographical location of sampling sites and groups the 42 sampling sites into four clusters, i.e., Danjiang, Danjiangkou Reservoir region (lower catchment), upper catchment and one river in headwaters pertaining to water quality. The headwaters, Danjiang and lower catchment, and upper catchment correspond to very high polluted, moderate polluted and relatively low polluted regions, respectively. Additionally, PCA/FA and correlation analysis demonstrates that Al, Cd, Mn, Ni, Fe, Si and Sr are controlled by natural sources, whereas the other metals appear to be primarily controlled by anthropogenic origins though geogenic source contributing to them. 2009 Elsevier B.V. All rights reserved.

Non-fragile multivariable PID controller design via system augmentation

NASA Astrophysics Data System (ADS)

Liu, Jinrong; Lam, James; Shen, Mouquan; Shu, Zhan

2017-07-01

In this paper, the issue of designing non-fragile H∞ multivariable proportional-integral-derivative (PID) controllers with derivative filters is investigated. In order to obtain the controller gains, the original system is associated with an extended system such that the PID controller design can be formulated as a static output-feedback control problem. By taking the system augmentation approach, the conditions with slack matrices for solving the non-fragile H∞ multivariable PID controller gains are established. Based on the results, linear matrix inequality -based iterative algorithms are provided to compute the controller gains. Simulations are conducted to verify the effectiveness of the proposed approaches.

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model’s parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated. PMID:27537692

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.

Effect of sexual steroids on boar kinematic sperm subpopulations.

PubMed

Ayala, E M E; Aragón, M A

2017-11-01

Here, we show the effects of sexual steroids, progesterone, testosterone, or estradiol on motility parameters of boar sperm. Sixteen commercial seminal doses, four each of four adult boars, were analyzed using computer assisted sperm analysis (CASA). Mean values of motility parameters were analyzed by bivariate and multivariate statistics. Principal component analysis (PCA), followed by hierarchical clustering, was applied on data of motility parameters, provided automatically as intervals by the CASA system. Effects of sexual steroids were described in the kinematic subpopulations identified from multivariate statistics. Mean values of motility parameters were not significantly changed after addition of sexual steroids. Multivariate graphics showed that sperm subpopulations were not sensitive to the addition of either testosterone or estradiol, but sperm subpopulations responsive to progesterone were found. Distribution of motility parameters were wide in controls but sharpened at distinct concentrations of progesterone. We conclude that kinematic sperm subpopulations responsive to progesterone are present in boar semen, and these subpopulations are masked in evaluations of mean values of motility parameters. © 2017 International Society for Advancement of Cytometry. © 2017 International Society for Advancement of Cytometry.

Dose-dependent effect of mammographic breast density on the risk of contralateral breast cancer.

PubMed

Chowdhury, Marzana; Euhus, David; O'Donnell, Maureen; Onega, Tracy; Choudhary, Pankaj K; Biswas, Swati

2018-07-01

Increased mammographic breast density is a significant risk factor for breast cancer. It is not clear if it is also a risk factor for the development of contralateral breast cancer. The data were obtained from Breast Cancer Surveillance Consortium and included women diagnosed with invasive breast cancer or ductal carcinoma in situ between ages 18 and 88 and years 1995 and 2009. Each case of contralateral breast cancer was matched with three controls based on year of first breast cancer diagnosis, race, and length of follow-up. A total of 847 cases and 2541 controls were included. The risk factors included in the study were mammographic breast density, age of first breast cancer diagnosis, family history of breast cancer, anti-estrogen treatment, hormone replacement therapy, menopausal status, and estrogen receptor status, all from the time of first breast cancer diagnosis. Both univariate analysis and multivariate conditional logistic regression analysis were performed. In the final multivariate model, breast density, family history of breast cancer, and anti-estrogen treatment remained significant with p values less than 0.01. Increasing breast density had a dose-dependent effect on the risk of contralateral breast cancer. Relative to 'almost entirely fat' category of breast density, the adjusted odds ratios (and p values) in the multivariate analysis for 'scattered density,' 'heterogeneously dense,' and 'extremely dense' categories were 1.65 (0.036), 2.10 (0.002), and 2.32 (0.001), respectively. Breast density is an independent and significant risk factor for development of contralateral breast cancer. This risk factor should contribute to clinical decision making.

The discrimination of honey origin using melissopalynology and Raman spectroscopy techniques coupled with multivariate analysis.

PubMed

Corvucci, Francesca; Nobili, Lara; Melucci, Dora; Grillenzoni, Francesca-Vittoria

2015-02-15

Honey traceability to food quality is required by consumers and food control institutions. Melissopalynologists traditionally use percentages of nectariferous pollens to discriminate the botanical origin and the entire pollen spectrum (presence/absence, type and quantities and association of some pollen types) to determinate the geographical origin of honeys. To improve melissopalynological routine analysis, principal components analysis (PCA) was used. A remarkable and innovative result was that the most significant pollens for the traditional discrimination of the botanical and geographical origin of honeys were the same as those individuated with the chemometric model. The reliability of assignments of samples to honey classes was estimated through explained variance (85%). This confirms that the chemometric model properly describes the melissopalynological data. With the aim to improve honey discrimination, FT-microRaman spectrography and multivariate analysis were also applied. Well performing PCA models and good agreement with known classes were achieved. Encouraging results were obtained for botanical discrimination. Copyright © 2014 Elsevier Ltd. All rights reserved.

The impact of moderate wine consumption on the risk of developing prostate cancer.

PubMed

Vartolomei, Mihai Dorin; Kimura, Shoji; Ferro, Matteo; Foerster, Beat; Abufaraj, Mohammad; Briganti, Alberto; Karakiewicz, Pierre I; Shariat, Shahrokh F

2018-01-01

To investigate the impact of moderate wine consumption on the risk of prostate cancer (PCa). We focused on the differential effect of moderate consumption of red versus white wine. This study was a meta-analysis that includes data from case-control and cohort studies. A systematic search of Web of Science, Medline/PubMed, and Cochrane library was performed on December 1, 2017. Studies were deemed eligible if they assessed the risk of PCa due to red, white, or any wine using multivariable logistic regression analysis. We performed a formal meta-analysis for the risk of PCa according to moderate wine and wine type consumption (white or red). Heterogeneity between studies was assessed using Cochrane's Q test and I 2 statistics. Publication bias was assessed using Egger's regression test. A total of 930 abstracts and titles were initially identified. After removal of duplicates, reviews, and conference abstracts, 83 full-text original articles were screened. Seventeen studies (611,169 subjects) were included for final evaluation and fulfilled the inclusion criteria. In the case of moderate wine consumption: the pooled risk ratio (RR) for the risk of PCa was 0.98 (95% CI 0.92-1.05, p =0.57) in the multivariable analysis. Moderate white wine consumption increased the risk of PCa with a pooled RR of 1.26 (95% CI 1.10-1.43, p =0.001) in the multi-variable analysis. Meanwhile, moderate red wine consumption had a protective role reducing the risk by 12% (RR 0.88, 95% CI 0.78-0.999, p =0.047) in the multivariable analysis that comprised 222,447 subjects. In this meta-analysis, moderate wine consumption did not impact the risk of PCa. Interestingly, regarding the type of wine, moderate consumption of white wine increased the risk of PCa, whereas moderate consumption of red wine had a protective effect. Further analyses are needed to assess the differential molecular effect of white and red wine conferring their impact on PCa risk.

MIDAS, prototype Multivariate Interactive Digital Analysis System, phase 1. Volume 1: System description

NASA Technical Reports Server (NTRS)

Kriegler, F. J.

1974-01-01

The MIDAS System is described as a third-generation fast multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turnaround time and significant gains in throughput. The hardware and software are described. The system contains a mini-computer to control the various high-speed processing elements in the data path, and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating at 200,000 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation.

A multivariate model exploring the predictive value of demographic, adolescent, and family factors on glycemic control in adolescents with type 1 diabetes.

PubMed

Agarwal, Shivani; Jawad, Abbas F; Miller, Victoria A

2016-11-01

The current study examined how a comprehensive set of variables from multiple domains, including at the adolescent and family level, were predictive of glycemic control in adolescents with type 1 diabetes (T1D). Participants included 100 adolescents with T1D ages 10-16 yrs and their parents. Participants were enrolled in a longitudinal study about youth decision-making involvement in chronic illness management of which the baseline data were available for analysis. Bivariate associations with glycemic control (HbA1C) were tested. Hierarchical linear regression was implemented to inform the predictive model. In bivariate analyses, race, family structure, household income, insulin regimen, adolescent-reported adherence to diabetes self-management, cognitive development, adolescent responsibility for T1D management, and parent behavior during the illness management discussion were associated with HbA1c. In the multivariate model, the only significant predictors of HbA1c were race and insulin regimen, accounting for 17% of the variance. Caucasians had better glycemic control than other racial groups. Participants using pre-mixed insulin therapy and basal-bolus insulin had worse glycemic control than those on insulin pumps. This study shows that despite associations of adolescent and family-level variables with glycemic control at the bivariate level, only race and insulin regimen are predictive of glycemic control in hierarchical multivariate analyses. This model offers an alternative way to examine the relationship of demographic and psychosocial factors on glycemic control in adolescents with T1D. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Multivariate Regression Analysis and Slaughter Livestock,

DTIC Science & Technology

AGRICULTURE, *ECONOMICS), (*MEAT, PRODUCTION), MULTIVARIATE ANALYSIS, REGRESSION ANALYSIS , ANIMALS, WEIGHT, COSTS, PREDICTIONS, STABILITY, MATHEMATICAL MODELS, STORAGE, BEEF, PORK, FOOD, STATISTICAL DATA, ACCURACY

Atrial Fibrillation Management Strategies in Routine Clinical Practice: Insights from the International RealiseAF Survey

PubMed Central

Chiang, Chern-En; Naditch-Brûlé, Lisa; Brette, Sandrine; Silva-Cardoso, José; Gamra, Habib; Murin, Jan; Zharinov, Oleg J.; Steg, Philippe Gabriel

2016-01-01

Background Atrial fibrillation (AF) can be managed with rhythm- or rate-control strategies. There are few data from routine clinical practice on the frequency with which each strategy is used and their correlates in terms of patients’ clinical characteristics, AF control, and symptom burden. Methods RealiseAF was an international, cross-sectional, observational survey of 11,198 patients with AF. The aim of this analysis was to describe patient profiles and symptoms according to the AF management strategy used. A multivariate logistic regression identified factors associated with AF management strategy at the end of the visit. Results Among 10,497 eligible patients, 53.7% used a rate-control strategy, compared with 34.5% who used a rhythm-control strategy. In 11.8% of patients, no clear strategy was stated. The proportion of patients with AF-related symptoms (EHRA Class > = II) was 78.1% (n = 4396/5630) for those using a rate-control strategy vs. 67.8% for those using a rhythm-control strategy (p<0.001). Multivariate logistic regression analysis revealed that age <75 years or the paroxysmal or persistent form of AF favored the choice of a rhythm-control strategy. A change in strategy was infrequent, even in patients with European Heart Rhythm Association (EHRA) Class > = II. Conclusions In the RealiseAF routine clinical practice survey, rate control was more commonly used than rhythm control, and a change in strategy was uncommon, even in symptomatic patients. In almost 12% of patients, no clear strategy was stated. Physician awareness regarding optimal management strategies for AF may be improved. PMID:26800084

PHARYNGEAL SWALLOWING MECHANICS SECONDARY TO HEMISPHERIC STROKE

PubMed Central

May, Nelson H; Pisegna, Jessica M; Marchina, Sarah; Langmore, Susan E; Kumar, Sandeep; Pearson, William G

2016-01-01

Goals Computational Analysis of Swallowing Mechanics is a method that utilizes multivariate shape change analysis to uncover covariant elements of pharyngeal swallowing mechanics associated with impairment using videofluoroscopic swallowing studies. The goals of this preliminary study were to (1) characterize swallowing mechanics underlying stroke related dysphagia, (2) decipher the impact of left and right hemispheric stroke on pharyngeal swallowing mechanics, and (3) determine pharyngeal swallowing mechanics associated with penetration-aspiration status. Materials and Methods Videofluoroscopic swallowing studies of 18 dysphagic patients with hemispheric infarcts and age and gender matched controls were selected from well-controlled data sets. Patient data including laterality, and penetration-aspiration status was collected. Coordinates mapping muscle group action during swallowing were collected from videos. Multivariate morphometric analyses of coordinates associated with stroke, affected hemisphere, and penetration-aspiration status were performed. Findings Pharyngeal swallowing mechanics differed significantly in the following comparisons: stroke vs. controls (D=2.19, p<.0001); right hemispheric stroke vs. controls (D=3.64, p<.0001); left hemispheric stroke vs. controls (D=2.06, p<.0001); right hemispheric stroke vs. left hemispheric stroke (D=2.89, p<.0001); and penetration-aspiration vs. within normal limits (D=2.25, p<.0001). Differences in pharyngeal swallowing mechanics associated with each comparison were visualized using eigenvectors. Conclusion While current literature focuses on timing changes in stroke-related dysphagia, this data suggests that mechanical changes are also functionally important. Pharyngeal swallowing mechanics differed by affected hemisphere and penetration-aspiration status. Computational Analysis of Swallowing Mechanics can be used to identify patient specific swallowing impairment associated with stroke injury that could help guide rehabilitation strategies to improve swallowing outcomes. PMID:27913200

Outbreak of resistant Acinetobacter baumannii- measures and proposal for prevention and control.

PubMed

Romanelli, Roberta Maia de Castro; Jesus, Lenize Adriana de; Clemente, Wanessa Trindade; Lima, Stella Sala Soares; Rezende, Edna Maria; Coutinho, Rosane Luiza; Moreira, Ricardo Luiz Fontes; Neves, Francelli Aparecida Cordeiro; Brás, Nelma de Jesus

2009-10-01

Acinetobacter baumannii colonization and infection, frequent in Intensive Care Unit (ICU) patients, is commonly associated with high morbimortality. Several outbreaks due to multidrug-resistant (MDR) A. baumanii have been reported but few of them in Brazil. This study aimed to identify risk factors associated with colonization and infection by MDR and carbapenem-resistant A. baumannii strains isolated from patients admitted to the adult ICU at HC/UFMG. A case-control study was performed from January 2007 to June 2008. Cases were defined as patients colonized or infected by MDR/carbapenem-resistant A. baumannii, and controls were patients without MDR/carbapenem-resistant A. baumannii isolation, in a 1:2 proportion. For statistical analysis, due to changes in infection control guidelines, infection criteria and the notification process, this study was divided into two periods. During the first period analyzed, from January to December 2007, colonization or infection by MDR/carbapenem-resistant A. baumannii was associated with prior infection, invasive device utilization, prior carbapenem use and clinical severity. In the multivariate analysis, prior infection and mechanical ventilation proved to be statistically significant risk factors. Carbapenem use showed a tendency towards a statistical association. During the second study period, from January to June 2008, variables with a significant association with MDR/carbapenem-resistant A. baumannii colonization/infection were catheter utilization, carbapenem and third-generation cephalosporin use, hepatic transplantation, and clinical severity. In the multivariate analysis, only CVC use showed a statistical difference. Carbapenem and third-generation cephalosporin use displayed a tendency to be risk factors. Risk factors must be focused on infection control and prevention measures considering A. baumanni dissemination.

Perception of control, coping and psychological stress of infertile women undergoing IVF.

PubMed

Gourounti, Kleanthi; Anagnostopoulos, Fotios; Potamianos, Grigorios; Lykeridou, Katerina; Schmidt, Lone; Vaslamatzis, Grigorios

2012-06-01

The study aimed to examine: (i) the association between perception of infertility controllability and coping strategies; and (ii) the association between perception of infertility controllability and coping strategies to psychological distress, applying multivariate statistical techniques to control for the effects of demographic variables. This cross-sectional study included 137 women with fertility problems undergoing IVF in a public hospital. All participants completed questionnaires that measured fertility-related stress, state anxiety, depressive symptomatology, perception of control and coping strategies. Pearson's correlation coefficients were calculated between all study variables, followed by hierarchical multiple linear regression. Low perception of personal and treatment controllability was associated with frequent use of avoidance coping and high perception of treatment controllability was positively associated with problem-focused coping. Multivariate analysis showed that, when controlling for demographic factors, low perception of personal control and avoidance coping were positively associated with fertility-related stress and state anxiety, and problem-appraisal coping was negatively and significantly associated with fertility-related stress and depressive symptomatology scores. The findings of this study merit the understanding of the role of control perception and coping in psychological stress of infertile women to identify beforehand those women who might be at risk of experiencing high stress and in need of support. Copyright © 2012 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Predictors of Individual Tumor Local Control After Stereotactic Radiosurgery for Non-Small Cell Lung Cancer Brain Metastases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garsa, Adam A.; Badiyan, Shahed N.; DeWees, Todd

2014-10-01

Purpose: To evaluate local control rates and predictors of individual tumor local control for brain metastases from non-small cell lung cancer (NSCLC) treated with stereotactic radiosurgery (SRS). Methods and Materials: Between June 1998 and May 2011, 401 brain metastases in 228 patients were treated with Gamma Knife single-fraction SRS. Local failure was defined as an increase in lesion size after SRS. Local control was estimated using the Kaplan-Meier method. The Cox proportional hazards model was used for univariate and multivariate analysis. Receiver operating characteristic analysis was used to identify an optimal cutpoint for conformality index relative to local control. Amore » P value <.05 was considered statistically significant. Results: Median age was 60 years (range, 27-84 years). There were 66 cerebellar metastases (16%) and 335 supratentorial metastases (84%). The median prescription dose was 20 Gy (range, 14-24 Gy). Median overall survival from time of SRS was 12.1 months. The estimated local control at 12 months was 74%. On multivariate analysis, cerebellar location (hazard ratio [HR] 1.94, P=.009), larger tumor volume (HR 1.09, P<.001), and lower conformality (HR 0.700, P=.044) were significant independent predictors of local failure. Conformality index cutpoints of 1.4-1.9 were predictive of local control, whereas a cutpoint of 1.75 was the most predictive (P=.001). The adjusted Kaplan-Meier 1-year local control for conformality index ≥1.75 was 84% versus 69% for conformality index <1.75, controlling for tumor volume and location. The 1-year adjusted local control for cerebellar lesions was 60%, compared with 77% for supratentorial lesions, controlling for tumor volume and conformality index. Conclusions: Cerebellar tumor location, lower conformality index, and larger tumor volume were significant independent predictors of local failure after SRS for brain metastases from NSCLC. These results warrant further investigation in a prospective setting.« less

Multivariate pattern analysis reveals subtle brain anomalies relevant to the cognitive phenotype in neurofibromatosis type 1.

PubMed

Duarte, João V; Ribeiro, Maria J; Violante, Inês R; Cunha, Gil; Silva, Eduardo; Castelo-Branco, Miguel

2014-01-01

Neurofibromatosis Type 1 (NF1) is a common genetic condition associated with cognitive dysfunction. However, the pathophysiology of the NF1 cognitive deficits is not well understood. Abnormal brain structure, including increased total brain volume, white matter (WM) and grey matter (GM) abnormalities have been reported in the NF1 brain. These previous studies employed univariate model-driven methods preventing detection of subtle and spatially distributed differences in brain anatomy. Multivariate pattern analysis allows the combination of information from multiple spatial locations yielding a discriminative power beyond that of single voxels. Here we investigated for the first time subtle anomalies in the NF1 brain, using a multivariate data-driven classification approach. We used support vector machines (SVM) to classify whole-brain GM and WM segments of structural T1 -weighted MRI scans from 39 participants with NF1 and 60 non-affected individuals, divided in children/adolescents and adults groups. We also employed voxel-based morphometry (VBM) as a univariate gold standard to study brain structural differences. SVM classifiers correctly classified 94% of cases (sensitivity 92%; specificity 96%) revealing the existence of brain structural anomalies that discriminate NF1 individuals from controls. Accordingly, VBM analysis revealed structural differences in agreement with the SVM weight maps representing the most relevant brain regions for group discrimination. These included the hippocampus, basal ganglia, thalamus, and visual cortex. This multivariate data-driven analysis thus identified subtle anomalies in brain structure in the absence of visible pathology. Our results provide further insight into the neuroanatomical correlates of known features of the cognitive phenotype of NF1. Copyright © 2012 Wiley Periodicals, Inc.

Multivariate analysis of the cotton seed ionome reveals integrated genetic signatures of abiotic stress-response

USDA-ARS?s Scientific Manuscript database

To mitigate the effects of heat and drought stress, an understanding of the genetic control of physiological responses to these environmental conditions is needed. To this end, we evaluated an upland cotton (Gossypium hirsutum L.) mapping population under water-limited and well-watered conditions in...

The Effect of Shared versus Individual Reflection on Team Outcomes

ERIC Educational Resources Information Center

Domke-Damonte, Darla J.; Keels, J. Kay

2015-01-01

In this study, teams in a strategic management classroom were given one of two versions of an assignment related to the development of a team contract: independent individual reflections on desired team behaviors versus team-level reflections on desired behavioral norms. Results of a multivariate analysis of covariance, controlling for gender and…

Computed tomography findings associated with the risk for emergency ventral hernia repair.

PubMed

Mueck, Krislynn M; Holihan, Julie L; Mo, Jiandi; Flores-Gonzales, Juan R; Ko, Tien C; Kao, Lillian S; Liang, Mike K

2017-07-01

Conventional wisdom teaches that small hernia defects are more likely to incarcerate. We aim to identify radiographic features of ventral hernias associated with increased risk of bowel incarceration. We assessed all patients who underwent emergent ventral hernia repair for bowel complications from 2009 to 2015. Cases were matched 1:3 with elective controls. Computed tomography scans were reviewed to determine hernia characteristics. Univariate and multivariable analyses were performed to identify variables associated with emergent surgery. The cohort consisted of 88 patients and 264 controls. On univariate analysis, older age, higher ASA score, elevated BMI, ascites, larger hernias, small angle, and taller hernias were associated with emergent surgery. On multivariable analysis, morbid obesity, ascites, smaller angle, and taller hernias were independently associated with emergent surgery. The teaching that large defects do not incarcerate is inaccurate; bowel compromise occurs with ventral hernias of all sizes. Instead, taller height and smaller angle are associated with the need for emergent repair. Early elective repair should be considered for patients with hernia features concerning for increased risk of bowel compromise. Copyright © 2016 Elsevier Inc. All rights reserved.

The Irvine, Beatties, and Bresnahan (IBB) Forelimb Recovery Scale: An Assessment of Reliability and Validity

PubMed Central

Irvine, Karen-Amanda; Ferguson, Adam R.; Mitchell, Kathleen D.; Beattie, Stephanie B.; Lin, Amity; Stuck, Ellen D.; Huie, J. Russell; Nielson, Jessica L.; Talbott, Jason F.; Inoue, Tomoo; Beattie, Michael S.; Bresnahan, Jacqueline C.

2014-01-01

The IBB scale is a recently developed forelimb scale for the assessment of fine control of the forelimb and digits after cervical spinal cord injury [SCI; (1)]. The present paper describes the assessment of inter-rater reliability and face, concurrent and construct validity of this scale following SCI. It demonstrates that the IBB is a reliable and valid scale that is sensitive to severity of SCI and to recovery over time. In addition, the IBB correlates with other outcome measures and is highly predictive of biological measures of tissue pathology. Multivariate analysis using principal component analysis (PCA) demonstrates that the IBB is highly predictive of the syndromic outcome after SCI (2), and is among the best predictors of bio-behavioral function, based on strong construct validity. Altogether, the data suggest that the IBB, especially in concert with other measures, is a reliable and valid tool for assessing neurological deficits in fine motor control of the distal forelimb, and represents a powerful addition to multivariate outcome batteries aimed at documenting recovery of function after cervical SCI in rats. PMID:25071704

Multivariate calibration in Laser-Induced Breakdown Spectroscopy quantitative analysis: The dangers of a 'black box' approach and how to avoid them

NASA Astrophysics Data System (ADS)

Safi, A.; Campanella, B.; Grifoni, E.; Legnaioli, S.; Lorenzetti, G.; Pagnotta, S.; Poggialini, F.; Ripoll-Seguer, L.; Hidalgo, M.; Palleschi, V.

2018-06-01

The introduction of multivariate calibration curve approach in Laser-Induced Breakdown Spectroscopy (LIBS) quantitative analysis has led to a general improvement of the LIBS analytical performances, since a multivariate approach allows to exploit the redundancy of elemental information that are typically present in a LIBS spectrum. Software packages implementing multivariate methods are available in the most diffused commercial and open source analytical programs; in most of the cases, the multivariate algorithms are robust against noise and operate in unsupervised mode. The reverse of the coin of the availability and ease of use of such packages is the (perceived) difficulty in assessing the reliability of the results obtained which often leads to the consideration of the multivariate algorithms as 'black boxes' whose inner mechanism is supposed to remain hidden to the user. In this paper, we will discuss the dangers of a 'black box' approach in LIBS multivariate analysis, and will discuss how to overcome them using the chemical-physical knowledge that is at the base of any LIBS quantitative analysis.

Linear regression analysis and its application to multivariate chromatographic calibration for the quantitative analysis of two-component mixtures.

PubMed

Dinç, Erdal; Ozdemir, Abdil

2005-01-01

Multivariate chromatographic calibration technique was developed for the quantitative analysis of binary mixtures enalapril maleate (EA) and hydrochlorothiazide (HCT) in tablets in the presence of losartan potassium (LST). The mathematical algorithm of multivariate chromatographic calibration technique is based on the use of the linear regression equations constructed using relationship between concentration and peak area at the five-wavelength set. The algorithm of this mathematical calibration model having a simple mathematical content was briefly described. This approach is a powerful mathematical tool for an optimum chromatographic multivariate calibration and elimination of fluctuations coming from instrumental and experimental conditions. This multivariate chromatographic calibration contains reduction of multivariate linear regression functions to univariate data set. The validation of model was carried out by analyzing various synthetic binary mixtures and using the standard addition technique. Developed calibration technique was applied to the analysis of the real pharmaceutical tablets containing EA and HCT. The obtained results were compared with those obtained by classical HPLC method. It was observed that the proposed multivariate chromatographic calibration gives better results than classical HPLC.

Smoking prevalence and seizure control in Chinese males with epilepsy.

PubMed

Gao, Hui; Sander, Josemir W; Du, Xudong; Chen, Jiani; Zhu, Cairong; Zhou, Dong

2017-08-01

Smoking has a negative effect on most diseases, yet it is under-investigated in people with epilepsy; thus its role is not clear in the general population with epilepsy. We performed a retrospective pilot study on males with epilepsy to determine the smoking rate and its relationship with seizure control using univariate analysis to calculate odds ratios (ORs) and also used a multi-variate logistic regression model. The smoking rate in our sample of 278 individuals was 25.5%, which is lower than the general Chinese population smoking rate among males of 52.1%. We used two classifications: the first classified epilepsy as generalized, or by presumed topographic origin (temporal, frontal, parietal and occipital). The second classified the dominant seizure type of an individual as generalized tonic clonic seizure (GTCS), myoclonic seizure (MS), complex partial seizure (CPS), simple partial seizure (SPS), and secondary GTCS (sGTCS). The univariable analysis of satisfactory seizure control profile and smoking rate in both classifications showed a trend towards a beneficial effect of smoking although most were not statistically significant. Considering medication is an important confounding factor that would largely influence seizure control, we also conducted multi-variable analysis for both classifications with drug numbers and dosage. The result of our model also suggested that smoking is a protective factor. Our findings seem to suggest that smoking could have a potential role in seizure control although confounders need exploration particularly in view of the potential long term health effects. Replication in a much larger sample is needed as well as case control studies to elucidate this issue. Copyright © 2017 Elsevier Inc. All rights reserved.

Multivariate evaluation of the effectiveness of treatment efficacy of cypermethrin against sea lice (Lepeophtheirus salmonis) in Atlantic salmon (Salmo salar)

PubMed Central

2013-01-01

Background The sea louse Lepeophtheirus salmonis is the most important ectoparasite of farmed Atlantic salmon (Salmo salar) in Norwegian aquaculture. Control of sea lice is primarily dependent on the use of delousing chemotherapeutants, which are both expensive and toxic to other wildlife. The method most commonly used for monitoring treatment effectiveness relies on measuring the percentage reduction in the mobile stages of Lepeophtheirus salmonis only. However, this does not account for changes in the other sea lice stages and may result in misleading or incomplete interpretation regarding the effectiveness of treatment. With the aim of improving the evaluation of delousing treatments, we explored multivariate analyses of bath treatments using the topical pyrethroid, cypermethrin, in salmon pens at five Norwegian production sites. Results Conventional univariate analysis indicated reductions of over 90% in mobile stages at all sites. In contrast, multivariate analyses indicated differing treatment effectiveness between sites (p-value < 0.01) based on changes in the proportion and abundance of the chalimus and PAAM (pre-adult and adult males) stages. Low water temperatures and shortened intervals between sampling after treatment may account for the differences in the composition of chalimus and PAAM stage groups following treatment. Using multivariate analysis, such factors could be separated from those which were attributable to inadequate treatment or chemotherapeutant failure. Conclusions Multivariate analyses for evaluation of treatment effectiveness against multiple life cycle stages of L. salmonis yield additional information beyond that derivable from univariate methods. This can aid in the identification of causes of apparent treatment failure in salmon aquaculture. PMID:24354936

Multivariate statistical process control of a continuous pharmaceutical twin-screw granulation and fluid bed drying process.

PubMed

Silva, A F; Sarraguça, M C; Fonteyne, M; Vercruysse, J; De Leersnyder, F; Vanhoorne, V; Bostijn, N; Verstraeten, M; Vervaet, C; Remon, J P; De Beer, T; Lopes, J A

2017-08-07

A multivariate statistical process control (MSPC) strategy was developed for the monitoring of the ConsiGma™-25 continuous tablet manufacturing line. Thirty-five logged variables encompassing three major units, being a twin screw high shear granulator, a fluid bed dryer and a product control unit, were used to monitor the process. The MSPC strategy was based on principal component analysis of data acquired under normal operating conditions using a series of four process runs. Runs with imposed disturbances in the dryer air flow and temperature, in the granulator barrel temperature, speed and liquid mass flow and in the powder dosing unit mass flow were utilized to evaluate the model's monitoring performance. The impact of the imposed deviations to the process continuity was also evaluated using Hotelling's T 2 and Q residuals statistics control charts. The influence of the individual process variables was assessed by analyzing contribution plots at specific time points. Results show that the imposed disturbances were all detected in both control charts. Overall, the MSPC strategy was successfully developed and applied. Additionally, deviations not associated with the imposed changes were detected, mainly in the granulator barrel temperature control. Copyright © 2017 Elsevier B.V. All rights reserved.

Fibroblast Growth Factor 2-A Predictor of Outcome for Patients Irradiated for Stage II-III Non-Small-Cell Lung Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rades, Dirk, E-mail: Rades.Dirk@gmx.net; Setter, Cornelia; Dahl, Olav

2012-01-01

Purpose: The prognostic value of the tumor cell expression of the fibroblast growth factor 2 (FGF-2) in patients with non-small-cell lung cancer (NSCLC) is unclear. The present study investigated the effect of tumor cell expression of FGF-2 on the outcome of 60 patients irradiated for Stage II-III NSCLC. Methods and Materials: The effect of FGF-2 expression and 13 additional factors on locoregional control (LRC), metastasis-free survival (MFS), and overall survival (OS) were retrospectively evaluated. These additional factors included age, gender, Karnofsky performance status, histologic type, histologic grade, T and N category, American Joint Committee on Cancer stage, surgery, chemotherapy, pack-years,more » smoking during radiotherapy, and hemoglobin during radiotherapy. Locoregional failure was identified by endoscopy or computed tomography. Univariate analyses were performed with the Kaplan-Meier method and the Wilcoxon test and multivariate analyses with the Cox proportional hazard model. Results: On univariate analysis, improved LRC was associated with surgery (p = .017), greater hemoglobin levels (p = .036), and FGF-2 negativity (p <.001). On multivariate analysis of LRC, surgery (relative risk [RR], 2.44; p = .037), and FGF-2 expression (RR, 5.06; p <.001) maintained significance. On univariate analysis, improved MFS was associated with squamous cell carcinoma (p = .020), greater hemoglobin levels (p = .007), and FGF-2 negativity (p = .001). On multivariate analysis of MFS, the hemoglobin levels (RR, 2.65; p = .019) and FGF-2 expression (RR, 3.05; p = .004) were significant. On univariate analysis, improved OS was associated with a lower N category (p = .048), greater hemoglobin levels (p <.001), and FGF-2 negativity (p <.001). On multivariate analysis of OS, greater hemoglobin levels (RR, 4.62; p = .002) and FGF-2 expression (RR, 3.25; p = .002) maintained significance. Conclusions: Tumor cell expression of FGF-2 appeared to be an independent negative predictor of LRC, MFS, and OS.« less

Multivariate Tensor-based Morphometry on Surfaces: Application to Mapping Ventricular Abnormalities in HIV/AIDS

PubMed Central

Wang, Yalin; Zhang, Jie; Gutman, Boris; Chan, Tony F.; Becker, James T.; Aizenstein, Howard J.; Lopez, Oscar L.; Tamburo, Robert J.; Toga, Arthur W.; Thompson, Paul M.

2010-01-01

Here we developed a new method, called multivariate tensor-based surface morphometry (TBM), and applied it to study lateral ventricular surface differences associated with HIV/AIDS. Using concepts from differential geometry and the theory of differential forms, we created mathematical structures known as holomorphic one-forms, to obtain an efficient and accurate conformal parameterization of the lateral ventricular surfaces in the brain. The new meshing approach also provides a natural way to register anatomical surfaces across subjects, and improves on prior methods as it handles surfaces that branch and join at complex 3D junctions. To analyze anatomical differences, we computed new statistics from the Riemannian surface metrics - these retain multivariate information on local surface geometry. We applied this framework to analyze lateral ventricular surface morphometry in 3D MRI data from 11 subjects with HIV/AIDS and 8 healthy controls. Our method detected a 3D profile of surface abnormalities even in this small sample. Multivariate statistics on the local tensors gave better effect sizes for detecting group differences, relative to other TBM-based methods including analysis of the Jacobian determinant, the largest and smallest eigenvalues of the surface metric, and the pair of eigenvalues of the Jacobian matrix. The resulting analysis pipeline may improve the power of surface-based morphometry studies of the brain. PMID:19900560

Multivariate spatial models of excess crash frequency at area level: case of Costa Rica.

PubMed

Aguero-Valverde, Jonathan

2013-10-01

Recently, areal models of crash frequency have being used in the analysis of various area-wide factors affecting road crashes. On the other hand, disease mapping methods are commonly used in epidemiology to assess the relative risk of the population at different spatial units. A natural next step is to combine these two approaches to estimate the excess crash frequency at area level as a measure of absolute crash risk. Furthermore, multivariate spatial models of crash severity are explored in order to account for both frequency and severity of crashes and control for the spatial correlation frequently found in crash data. This paper aims to extent the concept of safety performance functions to be used in areal models of crash frequency. A multivariate spatial model is used for that purpose and compared to its univariate counterpart. Full Bayes hierarchical approach is used to estimate the models of crash frequency at canton level for Costa Rica. An intrinsic multivariate conditional autoregressive model is used for modeling spatial random effects. The results show that the multivariate spatial model performs better than its univariate counterpart in terms of the penalized goodness-of-fit measure Deviance Information Criteria. Additionally, the effects of the spatial smoothing due to the multivariate spatial random effects are evident in the estimation of excess equivalent property damage only crashes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

The Influence of Parental Self-Efficacy and Perceived Control on the Home Learning Environment of Young Children.

PubMed

Peacock-Chambers, Elizabeth; Martin, Justin T; Necastro, Kelly A; Cabral, Howard J; Bair-Merritt, Megan

2017-03-01

To: 1) examine sociodemographic factors associated with high parental self-efficacy and perceived control, and 2) determine how self-efficacy and control relate to the home learning environment (HLE), including whether they mediate the relationship between sociodemographic characteristics and HLE, among low-income parents of young children. Cross-sectional survey of English- and Spanish-speaking parents, 18 years of age and older, with children 15 to 36 months old, to assess parental self-efficacy, perceived control, HLE, and sociodemographic characteristics. Bivariate analysis identified sociodemographic predictors of high self-efficacy and control. Separate multivariate linear regression models were used to examine associations between self-efficacy, control, and the HLE. Formal path analysis was used to assess whether self-efficacy and control mediate the relationship between sociodemographic characteristics and HLE. Of 144 participants, 25% were white, 65% were immigrants, and 35% completed the survey in Spanish. US-born subjects, those who completed English surveys, or who had higher educational levels had significantly higher mean self-efficacy and perceived control scores (P < .05). Higher self-efficacy and perceived control were associated with a positive change in HLE score in separate multivariate models (self-efficacy β = .7 [95% confidence interval (CI), 0.5-0.9]; control β = .5 [95% CI, 0.2-0.8]). Self-efficacy acted as a mediator such that low self-efficacy explained part of the association between parental depressive symptoms, immigrant status, and less optimal HLE (P = .04 and < .001, respectively). High parental self-efficacy and perceived control positively influence HLEs of young children. Self-efficacy alone mediates the relationship between parental depressive symptoms, immigrant status, and less optimal early home learning. Copyright © 2016 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

Multivariate Cluster Analysis.

ERIC Educational Resources Information Center

McRae, Douglas J.

Procedures for grouping students into homogeneous subsets have long interested educational researchers. The research reported in this paper is an investigation of a set of objective grouping procedures based on multivariate analysis considerations. Four multivariate functions that might serve as criteria for adequate grouping are given and…

Modern CACSD using the Robust-Control Toolbox

NASA Technical Reports Server (NTRS)

Chiang, Richard Y.; Safonov, Michael G.

1989-01-01

The Robust-Control Toolbox is a collection of 40 M-files which extend the capability of PC/PRO-MATLAB to do modern multivariable robust control system design. Included are robust analysis tools like singular values and structured singular values, robust synthesis tools like continuous/discrete H(exp 2)/H infinity synthesis and Linear Quadratic Gaussian Loop Transfer Recovery methods and a variety of robust model reduction tools such as Hankel approximation, balanced truncation and balanced stochastic truncation, etc. The capabilities of the toolbox are described and illustated with examples to show how easily they can be used in practice. Examples include structured singular value analysis, H infinity loop-shaping and large space structure model reduction.

Pressure ulcer incidence and Braden subscales: Retrospective cohort analysis in general wards of a Portuguese hospital.

PubMed

Sardo, Pedro Miguel Garcez; Guedes, Jenifer Adriana Domingues; Alvarelhão, José Joaquim Marques; Machado, Paulo Alexandre Puga; Melo, Elsa Maria Oliveira Pinheiro

2018-05-01

To study the influence of Braden subscales scores (at the first pressure ulcer risk assessment) on pressure ulcer incidence using a univariate and a multivariate time to event analysis. Retrospective cohort analysis of electronic health record database from adult patients admitted without pressure ulcer(s) to medical and surgical wards of a Portuguese hospital during 2012. The hazard ratio of developing a pressure ulcer during the length of inpatient stay was calculated by univariate Cox regression for each variable of interest and by multivariate Cox regression for the Braden subscales that were statistically significant. This study included a sample of 6552 participants. During the length of stay, 153 participants developed (at least) one pressure ulcer, giving a pressure ulcer incidence of 2.3%. The univariate time to event analysis showed that all Braden subscales, except "nutrition", were associated with the development of pressure ulcer. By multivariate analysis the scores for "mobility" and "activity" were independently predictive of the development of pressure ulcer(s) for all participants. (Im)"mobility" (the lack of ability to change and control body position) and (in)"activity" (the limited degree of physical activity) were the major risk factors assessed by Braden Scale for pressure ulcer development during the length of inpatient stay. Thus, the greatest efforts in managing pressure ulcer risk should be on "mobility" and "activity", independently of the total Braden Scale score. Copyright © 2018 Tissue Viability Society. Published by Elsevier Ltd. All rights reserved.

Risk factors associated with gastric cancer in Mexico: education, breakfast and chili.

PubMed

Trujillo Rivera, Alejandro; Sampieri, Clara Luz; Morales Romero, Jaime; Montero, Hilda; Acosta Mesa, Héctor Gabriel; Cruz Ramírez, Nicandro; Novoa Del Toro, Elva María; León Córdoba, Kenneth

2018-06-01

the aim of the study was to use a validated questionnaire to identify factors associated with the development of gastric cancer (GC) in the Mexican population. the study included cases and controls that were paired by sex and ± 10 years of age at diagnosis. In relation to cases, 46 patients with a confirmed histopathological diagnosis of adenocarcinoma-type GC, as reported in the hospital records, were selected, and 46 blood bank donors from the same hospital were included as controls. The previously validated Questionnaire to Find Factors Associated with Gastric Cancer (QUFA-GC©) was used to collect data. Odds ratio (OR) and 95% confidence interval (IC) were estimated via univariate analysis (paired OR). Multivariate analysis was performed by logistic regression. A decision tree was constructed using the J48 algorithm. an association was found by univariate analysis between GC risk and a lack of formal education, having smoked for ≥ 10 years, eating rapidly, consuming very hot food and drinks, a non-suitable breakfast within two hours of waking, pickled food and capsaicin. In contrast, a protective association against GC was found with taking recreational exercise and consuming fresh fruit and vegetables. No association was found between the development of GC and having an income that reflected poverty, using a refrigerator, perception of the omission of breakfast and time period of alcoholism. In the final multivariate analysis model, having no formal education (OR = 17.47, 95% CI = 5.17-76.69), consuming a non-suitable breakfast within two hours of waking (OR = 8.99, 95% CI = 2.85-35.50) and the consumption of capsaicin ˃ 29.9 mg capsaicin per day (OR = 3.77, 95% CI = 1.21-13.11) were factors associated with GC. an association was found by multivariate analysis between the presence of GC and education, type of breakfast and the consumption of capsaicin. These variables are susceptible to intervention and can be identified via the QUFA-GC ©.

Fast Genome-Wide QTL Association Mapping on Pedigree and Population Data.

PubMed

Zhou, Hua; Blangero, John; Dyer, Thomas D; Chan, Kei-Hang K; Lange, Kenneth; Sobel, Eric M

2017-04-01

Since most analysis software for genome-wide association studies (GWAS) currently exploit only unrelated individuals, there is a need for efficient applications that can handle general pedigree data or mixtures of both population and pedigree data. Even datasets thought to consist of only unrelated individuals may include cryptic relationships that can lead to false positives if not discovered and controlled for. In addition, family designs possess compelling advantages. They are better equipped to detect rare variants, control for population stratification, and facilitate the study of parent-of-origin effects. Pedigrees selected for extreme trait values often segregate a single gene with strong effect. Finally, many pedigrees are available as an important legacy from the era of linkage analysis. Unfortunately, pedigree likelihoods are notoriously hard to compute. In this paper, we reexamine the computational bottlenecks and implement ultra-fast pedigree-based GWAS analysis. Kinship coefficients can either be based on explicitly provided pedigrees or automatically estimated from dense markers. Our strategy (a) works for random sample data, pedigree data, or a mix of both; (b) entails no loss of power; (c) allows for any number of covariate adjustments, including correction for population stratification; (d) allows for testing SNPs under additive, dominant, and recessive models; and (e) accommodates both univariate and multivariate quantitative traits. On a typical personal computer (six CPU cores at 2.67 GHz), analyzing a univariate HDL (high-density lipoprotein) trait from the San Antonio Family Heart Study (935,392 SNPs on 1,388 individuals in 124 pedigrees) takes less than 2 min and 1.5 GB of memory. Complete multivariate QTL analysis of the three time-points of the longitudinal HDL multivariate trait takes less than 5 min and 1.5 GB of memory. The algorithm is implemented as the Ped-GWAS Analysis (Option 29) in the Mendel statistical genetics package, which is freely available for Macintosh, Linux, and Windows platforms from http://genetics.ucla.edu/software/mendel. © 2016 WILEY PERIODICALS, INC.

Metabolic analysis of elicited cell suspension cultures of Cannabis sativa L. by (1)H-NMR spectroscopy.

PubMed

Pec, Jaroslav; Flores-Sanchez, Isvett Josefina; Choi, Young Hae; Verpoorte, Robert

2010-07-01

Cannabis sativa L. plants produce a diverse array of secondary metabolites. Cannabis cell cultures were treated with jasmonic acid (JA) and pectin as elicitors to evaluate their effect on metabolism from two cell lines using NMR spectroscopy and multivariate data analysis. According to principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA), the chloroform extract of the pectin-treated cultures were more different than control and JA-treated cultures; but in the methanol/water extract the metabolome of the JA-treated cells showed clear differences with control and pectin-treated cultures. Tyrosol, an antioxidant metabolite, was detected in cannabis cell cultures. The tyrosol content increased after eliciting with JA.

The effects of aminosalicylates or thiopurines on the risk of colorectal cancer in inflammatory bowel disease.

PubMed

Carrat, F; Seksik, P; Colombel, J-F; Peyrin-Biroulet, L; Beaugerie, L

2017-02-01

Whether aminosalicylates or thiopurines reduce the risk of colorectal cancer (CRC) in inflammatory bowel (IBD) disease is controversial. To assess simultaneously the chemopreventive effect of aminosalicylates or thiopurines in a case-control study nested in the CESAME observational cohort that enrolled consecutive patients with IBD between May 2004 and June 2005. Patients were followed up to December 2007. Study population comprised 144 case patients who developed CRC from the diagnosis of IBD (65 and 79 cases diagnosed, respectively, before and from 2004, starting year of the prospective observational period of CESAME) and 286 controls matched for gender, age, IBD subtype and year of diagnosis, and cumulative extent of colitis. Exposure to aminosalicylates or thiopurines was defined by an exposure to the treatment during the year of the diagnosis of cancer. The propensity of receiving 5-ASA and thiopurines was quantified by a composite score taking into account patient and IBD characteristics. The role of aminosalicylates or thiopurines was assessed by multivariate analysis. Propensity scores and the history of primary sclerosing cholangitis were entered into the multivariate model for adjustment. By multivariate analysis adjusted for propensity, a significant protective effect of exposure to drugs during the year of cancer was found for aminosalicylates (OR = 0.587, 95% CI: 0.367-0.937, P = 0.0257), but not for thiopurines (OR = 0.762, 95% CI: 0.432-1.343, P = 0.3468). In a case-control study nested in the CESAME cohort, a significant decrease in the risk of colorectal cancer in IBD was associated with exposure to aminosalicylates, not to thiopurines. © 2016 John Wiley & Sons Ltd.

Adjustment of automatic control systems of production facilities at coal processing plants using multivariant physico- mathematical models

NASA Astrophysics Data System (ADS)

Evtushenko, V. F.; Myshlyaev, L. P.; Makarov, G. V.; Ivushkin, K. A.; Burkova, E. V.

2016-10-01

The structure of multi-variant physical and mathematical models of control system is offered as well as its application for adjustment of automatic control system (ACS) of production facilities on the example of coal processing plant.

New evidence for involvement of ESR1 gene in susceptibility to Chinese migraine.

PubMed

An, Xingkai; Fang, Jie; Lin, Qing; Lu, Congxia; Ma, Qilin; Qu, Hongli

2017-01-01

Migraine is a common and disabling nervous system disease with a significant genetic predisposition. The sex hormones play an important role in the pathogenesis of migraine. However, the conclusions of the previous genetic relation studies are conflicting. The aim of this study is to determine whether variants in genes involved in estrogen receptor and estrogen hormone metabolism are related to Chinese migraine. By employing a case-control approach, 8 SNPs in the ESR1, ESR2, and CYP19A1 genes are studied in a cohort of 494 migraine cases and 533 controls. In addition, genotyping is performed using Sequenom MALDI-TOF mass spectrometry iPLEX platform. Univariate and multivariate analyses are carried out by logistic regression. The corresponding haplotypes are studied with the Haploview software and gene-gene interaction is assessed using the Generalized Multifactor Dimensionality Reduction (GMDR) analysis. There are significant differences in allelic distributions for rs2234693 and rs9340799 in ESR1 gene between patients with migraine and control subjects. Univariate logistic analysis shows that rs2234693 and rs9340799 are risk factors for migraine, but multivariate analysis reveals that only rs2234693 is significant associated with migraine. In the subgroup analysis, rs2234693 in ESR1 gene is found associated with menstrually related migraine. Further haplotypic analysis shows that rs2234693-rs9340799 TA haplotype serves as risk haplotype for migraine. The GMDR analysis identifies rs2234693 in ESR1 alone to be a crucial candidate in migraine susceptibility. This study is in agreement with the previous studies that variants in the ESR1 gene are associated with migraine suggesting that it plays a role in the migraine process.

Comparative forensic soil analysis of New Jersey state parks using a combination of simple techniques with multivariate statistics.

PubMed

Bonetti, Jennifer; Quarino, Lawrence

2014-05-01

This study has shown that the combination of simple techniques with the use of multivariate statistics offers the potential for the comparative analysis of soil samples. Five samples were obtained from each of twelve state parks across New Jersey in both the summer and fall seasons. Each sample was examined using particle-size distribution, pH analysis in both water and 1 M CaCl2 , and a loss on ignition technique. Data from each of the techniques were combined, and principal component analysis (PCA) and canonical discriminant analysis (CDA) were used for multivariate data transformation. Samples from different locations could be visually differentiated from one another using these multivariate plots. Hold-one-out cross-validation analysis showed error rates as low as 3.33%. Ten blind study samples were analyzed resulting in no misclassifications using Mahalanobis distance calculations and visual examinations of multivariate plots. Seasonal variation was minimal between corresponding samples, suggesting potential success in forensic applications. © 2014 American Academy of Forensic Sciences.

Quantifying the impact of between-study heterogeneity in multivariate meta-analyses

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2012-01-01

Measures that quantify the impact of heterogeneity in univariate meta-analysis, including the very popular I2 statistic, are now well established. Multivariate meta-analysis, where studies provide multiple outcomes that are pooled in a single analysis, is also becoming more commonly used. The question of how to quantify heterogeneity in the multivariate setting is therefore raised. It is the univariate R2 statistic, the ratio of the variance of the estimated treatment effect under the random and fixed effects models, that generalises most naturally, so this statistic provides our basis. This statistic is then used to derive a multivariate analogue of I2, which we call . We also provide a multivariate H2 statistic, the ratio of a generalisation of Cochran's heterogeneity statistic and its associated degrees of freedom, with an accompanying generalisation of the usual I2 statistic, . Our proposed heterogeneity statistics can be used alongside all the usual estimates and inferential procedures used in multivariate meta-analysis. We apply our methods to some real datasets and show how our statistics are equally appropriate in the context of multivariate meta-regression, where study level covariate effects are included in the model. Our heterogeneity statistics may be used when applying any procedure for fitting the multivariate random effects model. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22763950

Progress in multirate digital control system design

NASA Technical Reports Server (NTRS)

Berg, Martin C.; Mason, Gregory S.

1991-01-01

A new methodology for multirate sampled-data control design based on a new generalized control law structure, two new parameter-optimization-based control law synthesis methods, and a new singular-value-based robustness analysis method are described. The control law structure can represent multirate sampled-data control laws of arbitrary structure and dynamic order, with arbitrarily prescribed sampling rates for all sensors and update rates for all processor states and actuators. The two control law synthesis methods employ numerical optimization to determine values for the control law parameters. The robustness analysis method is based on the multivariable Nyquist criterion applied to the loop transfer function for the sampling period equal to the period of repetition of the system's complete sampling/update schedule. The complete methodology is demonstrated by application to the design of a combination yaw damper and modal suppression system for a commercial aircraft.

Analyzing Multiple Outcomes in Clinical Research Using Multivariate Multilevel Models

PubMed Central

Baldwin, Scott A.; Imel, Zac E.; Braithwaite, Scott R.; Atkins, David C.

2014-01-01

Objective Multilevel models have become a standard data analysis approach in intervention research. Although the vast majority of intervention studies involve multiple outcome measures, few studies use multivariate analysis methods. The authors discuss multivariate extensions to the multilevel model that can be used by psychotherapy researchers. Method and Results Using simulated longitudinal treatment data, the authors show how multivariate models extend common univariate growth models and how the multivariate model can be used to examine multivariate hypotheses involving fixed effects (e.g., does the size of the treatment effect differ across outcomes?) and random effects (e.g., is change in one outcome related to change in the other?). An online supplemental appendix provides annotated computer code and simulated example data for implementing a multivariate model. Conclusions Multivariate multilevel models are flexible, powerful models that can enhance clinical research. PMID:24491071

Approximate analysis for repeated eigenvalue problems with applications to controls-structure integrated design

NASA Technical Reports Server (NTRS)

Kenny, Sean P.; Hou, Gene J. W.

1994-01-01

A method for eigenvalue and eigenvector approximate analysis for the case of repeated eigenvalues with distinct first derivatives is presented. The approximate analysis method developed involves a reparameterization of the multivariable structural eigenvalue problem in terms of a single positive-valued parameter. The resulting equations yield first-order approximations to changes in the eigenvalues and the eigenvectors associated with the repeated eigenvalue problem. This work also presents a numerical technique that facilitates the definition of an eigenvector derivative for the case of repeated eigenvalues with repeated eigenvalue derivatives (of all orders). Examples are given which demonstrate the application of such equations for sensitivity and approximate analysis. Emphasis is placed on the application of sensitivity analysis to large-scale structural and controls-structures optimization problems.

Rapid quality assessment of Radix Aconiti Preparata using direct analysis in real time mass spectrometry.

PubMed

Zhu, Hongbin; Wang, Chunyan; Qi, Yao; Song, Fengrui; Liu, Zhiqiang; Liu, Shuying

2012-11-08

This study presents a novel and rapid method to identify chemical markers for the quality control of Radix Aconiti Preparata, a world widely used traditional herbal medicine. In the method, the samples with a fast extraction procedure were analyzed using direct analysis in real time mass spectrometry (DART MS) combined with multivariate data analysis. At present, the quality assessment approach of Radix Aconiti Preparata was based on the two processing methods recorded in Chinese Pharmacopoeia for the purpose of reducing the toxicity of Radix Aconiti and ensuring its clinical therapeutic efficacy. In order to ensure the safety and effectivity in clinical use, the processing degree of Radix Aconiti should be well controlled and assessed. In the paper, hierarchical cluster analysis and principal component analysis were performed to evaluate the DART MS data of Radix Aconiti Preparata samples in different processing times. The results showed that the well processed Radix Aconiti Preparata, unqualified processed and the raw Radix Aconiti could be clustered reasonably corresponding to their constituents. The loading plot shows that the main chemical markers having the most influence on the discrimination amongst the qualified and unqualified samples were mainly some monoester diterpenoid aconitines and diester diterpenoid aconitines, i.e. benzoylmesaconine, hypaconitine, mesaconitine, neoline, benzoylhypaconine, benzoylaconine, fuziline, aconitine and 10-OH-mesaconitine. The established DART MS approach in combination with multivariate data analysis provides a very flexible and reliable method for quality assessment of toxic herbal medicine. Copyright © 2012 Elsevier B.V. All rights reserved.

MIDAS, prototype Multivariate Interactive Digital Analysis System, phase 1. Volume 3: Wiring diagrams

NASA Technical Reports Server (NTRS)

Kriegler, F. J.; Christenson, D.; Gordon, M.; Kistler, R.; Lampert, S.; Marshall, R.; Mclaughlin, R.

1974-01-01

The Midas System is a third-generation, fast, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughput. The hardware and software generated in Phase I of the overall program are described. The system contains a mini-computer to control the various high-speed processing elements in the data path and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating at 2 x 100,000 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation. The MIDAS construction and wiring diagrams are given.

MIDAS, prototype Multivariate Interactive Digital Analysis System, Phase 1. Volume 2: Diagnostic system

NASA Technical Reports Server (NTRS)

Kriegler, F. J.; Christenson, D.; Gordon, M.; Kistler, R.; Lampert, S.; Marshall, R.; Mclaughlin, R.

1974-01-01

The MIDAS System is a third-generation, fast, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from present and projected sensors. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughout. The hardware and software generated in Phase I of the over-all program are described. The system contains a mini-computer to control the various high-speed processing elements in the data path and a classifier which implements an all-digital prototype multivariate-Gaussian maximum likelihood decision algorithm operating 2 x 105 pixels/sec. Sufficient hardware was developed to perform signature extraction from computer-compatible tapes, compute classifier coefficients, control the classifier operation, and diagnose operation. Diagnostic programs used to test MIDAS' operations are presented.

Magnetic resonance imaging and magnetic resonance spectroscopy for detection of early Alzheimer's disease.

PubMed

Westman, Eric; Wahlund, Lars-Olof; Foy, Catherine; Poppe, Michaela; Cooper, Allison; Murphy, Declan; Spenger, Christian; Lovestone, Simon; Simmons, Andrew

2011-01-01

Alzheimer's disease is the most common form of neurodegenerative disorder and early detection is of great importance if new therapies are to be effectively administered. We have investigated whether the discrimination between early Alzheimer's disease (AD) and elderly healthy control subjects can be improved by adding magnetic resonance spectroscopy (MRS) measures to magnetic resonance imaging (MRI) measures. In this study 30 AD patients and 36 control subjects were included. High resolution T1-weighted axial magnetic resonance images were obtained from each subject. Automated regional volume segmentation and cortical thickness measures were determined for the images. 1H MRS was acquired from the hippocampus and LCModel was used for metabolic quantification. Altogether, this yielded 58 different volumetric, cortical thickness and metabolite ratio variables which were used for multivariate analysis to distinguish between subjects with AD and Healthy controls. Combining MRI and MRS measures resulted in a sensitivity of 97% and a specificity of 94% compared to using MRI or MRS measures alone (sensitivity: 87%, 76%, specificity: 86%, 83% respectively). Adding the MRS measures to the MRI measures more than doubled the positive likelihood ratio from 6 to 17. Adding MRS measures to a multivariate analysis of MRI measures resulted in significantly better classification than using MRI measures alone. The method shows strong potential for discriminating between Alzheimer's disease and controls.

Multivariate causal attribution and cost-effectiveness of a national mass media campaign in the Philippines.

PubMed

Kincaid, D Lawrence; Do, Mai Phuong

2006-01-01

Cost-effectiveness analysis is based on a simple formula. A dollar estimate of the total cost to conduct a program is divided by the number of people estimated to have been affected by it in terms of some intended outcome. The direct, total costs of most communication campaigns are usually available. Estimating the amount of effect that can be attributed to the communication alone, however is problematical in full-coverage, mass media campaigns where the randomized control group design is not feasible. Single-equation, multiple regression analysis controls for confounding variables but does not adequately address the issue of causal attribution. In this article, multivariate causal attribution (MCA) methods are applied to data from a sample survey of 1,516 married women in the Philippines to obtain a valid measure of the number of new adopters of modern contraceptives that can be causally attributed to a national mass media campaign and to calculate its cost-effectiveness. The MCA analysis uses structural equation modeling to test the causal pathways and to test for endogeneity, biprobit analysis to test for direct effects of the campaign and endogeneity, and propensity score matching to create a statistically equivalent, matched control group that approximates the results that would have been obtained from a randomized control group design. The MCA results support the conclusion that the observed, 6.4 percentage point increase in modern contraceptive use can be attributed to the national mass media campaign and to its indirect effects on attitudes toward contraceptives. This net increase represented 348,695 new adopters in the population of married women at a cost of U.S. $1.57 per new adopter.

Predictors of Recurrence, Progression, and Retreatment in Basilar Tip Aneurysms: A Location-Controlled Analysis.

PubMed

Abecassis, Isaac Josh; Sen, Rajeev D; Barber, Jason; Shetty, Rakshith; Kelly, Cory M; Ghodke, Basavaraj V; Hallam, Danial K; Levitt, Michael R; Kim, Louis J; Sekhar, Laligam N

2018-06-14

Endovascular treatment of intracranial aneurysms is associated with higher rates of recurrence and retreatment, though contemporary rates and risk factors for basilar tip aneurysms (BTAs) are less well-described. To characterize progression, retreatement, and retreated progression of BTAs treated with microsurgical or endovascular interventions. We retrospectively reviewed records for 141 consecutive BTA patients. We included 158 anterior communicating artery (ACoA) and 118 middle cerebral artery (MCA) aneurysms as controls. Univariate and multivariate analyses were used to calculate rates of progression (recurrence of previously obliterated aneurysms and progression of known residual aneurysm dome or neck), retreatment, and retreated progression. Kaplan-Meier analysis was used to characterize 24-mo event rates for primary outcome prediction. Of 141 BTA patients, 62.4% were ruptured and 37.6% were unruptured. Average radiographical follow-up was 33 mo. Among ruptured aneurysms treated with clipping, there were 2 rehemorrhages due to recurrence (6.1%), and none in any other cohorts. Overall rates of progression (28.9%), retreatment (28.9%), and retreated progression (24.7%) were not significantly different between surgical and endovascular subgroups, though ruptured aneurysms had higher event rates. Multivariate modeling confirmed rupture status (P = .003, hazard ratio = 0.14) and aneurysm dome width (P = .005, hazard ratio = 1.23) as independent predictors of progression requiring retreatment. In a separate multivariate analysis with ACoA and MCA aneurysms, basilar tip location was an independent predictor of progression, retreatment, and retreated progression. BTAs have higher rates of progression and retreated progression than other aneurysm locations, independent of treatment modality. Rupture status and dome width are risk factors for progression requiring retreatment.

Community-acquired pneumonia in the elderly: A multivariate analysis of risk and prognostic factors.

PubMed

Riquelme, R; Torres, A; El-Ebiary, M; de la Bellacasa, J P; Estruch, R; Mensa, J; Fernández-Solá, J; Hernández, C; Rodriguez-Roisin, R

1996-11-01

To assess the risk and prognostic factors of community-acquired pneumonia occurring in the elderly (over age 65 yr) requiring hospitalization, two studies, case-control and cohort, were performed over an 8-mo period in a 1,000-bed university teaching hospital. We studied 101 patients with pneumonia (cases), age 78.5 +/- 7.9 yr (mean +/- SD). Each case was matched for sex, age (+/- 5 yr), and date of admission (+/- 2 d) with a control subject, without pneumonia during the preceding 3 yr, arriving at the emergency room. Etiologic diagnosis was obtained in 43 of 101 (42%) cases. The main microbial agents causing pneumonia were: Streptococcus pneumoniae (19 of 43, 44%), and Chlamydia pneumoniae (9 of 43, 21%). Gram-negative bacilli were uncommon (2 of 43, 5%). The multivariate analysis demonstrated that large-volume aspiration, and low serum albumin (< 30 mg/dl) were independent risk factors associated with the development of pneumonia. Crude mortality rate was 26% (26 of 101), while pneumonia-related mortality was 20% (20 of 101). The attributable mortality was 23% (odds ratio [OR]: 11.3; 95% confidence interval [CI]: 3.25 to 60.23; p < 0.0001). The multivariate analysis showed that patients had a worse prognosis if they were previously bedridden, had prior swallowing disorders, body temperature on admission was less than 37 degrees C, respiratory frequency was greater than 30/min or had three or more affected lobes on chest radiograph. Age by itself was not a significant factor related to prognosis. Among the significant risk factors, only nutritional status is probably amenable to medical intervention. The prognostic factors found in this study may help to identify, upon admission, those subjects at higher risk and who may require special observation.

Effects of intranasal oxytocin on symptoms of schizophrenia: A multivariate Bayesian meta-analysis.

PubMed

Williams, Donald R; Bürkner, Paul-Christian

2017-01-01

Schizophrenia is a heterogeneous disorder in which psychiatric symptoms are classified into two general subgroups-positive and negative symptoms. Current antipsychotic drugs are effective for treating positive symptoms, whereas negative symptoms are less responsive. Since the neuropeptide oxytocin (OT) has been shown to mediate social behavior in animals and humans, it has been used as an experimental therapeutic for treating schizophrenia and in particular negative symptoms which includes social deficits. Through eight randomized controlled trials (RCTs) and three meta-analyses, evidence for an effect of intranasal OT (IN-OT) has been inconsistent. We therefore conducted an updated meta-analysis that offers several advantages when compared to those done previously: (1) We used a multivariate analysis which allows for comparisons between symptoms and accounts for correlations between symptoms; (2) We controlled for baseline scores; (3) We used a fully Bayesian framework that allows for assessment of evidence in favor of the null hypothesis using Bayes factors; and (4) We addressed inconsistencies in the primary studies and previous meta-analyses. Eight RCTs (n=238) were included in the present study and we found that oxytocin did not improve any aspect of symptomology in schizophrenic patients and there was moderate evidence in favor of the null (no effect of oxytocin) for negative symptoms. Multivariate comparisons between symptom types revealed that oxytocin was not especially beneficial for treating negative symptoms. The effect size estimates were not moderated, publication bias was absent, and our estimates were robust to sensitivity analyses. These results suggest that IN-OT is not an effective therapeutic for schizophrenia. Copyright © 2016 Elsevier Ltd. All rights reserved.

Searching for forcing signatures in decadal patterns of shoreline change

NASA Astrophysics Data System (ADS)

Burningham, H.; French, J.

2016-12-01

Analysis of shoreline position at spatial scales of the order 10 - 100 km and at a multi-decadal time-scale has the potential to reveal regional coherence (or lack of) in the primary controls on shoreline tendencies and trends. Such information is extremely valuable for the evaluation of climate forcing on coastal behaviour. Segmenting a coast into discrete behaviour units based on these types of analyses is often subjective, however, and in the context of pervasive human interventions and alongshore variability in ocean climate, determining the most important controls on shoreline dynamics can be challenging. Multivariate analyses provide one means to resolve common behaviours across shoreline position datasets, thereby underpinning a more objective evaluation of possible coupling between shorelines at different scales. In an analysis of the Suffolk coast (eastern England) we explore the use of multivariate statistics to understand and classify mesoscale coastal behaviour. Suffolk comprises a relatively linear shoreline that shifts from east-facing in the north to southeast-facing in the south. Although primarily formed of a beach foreshore backed by cliffs or shingle barrier, the shoreline is punctuated at 3 locations by narrow tidal inlets with offset entrances that imply a persistent north to south sediment transport direction. Tidal regime decreases south to north from mesotidal (3.6m STR) to microtidal (1.9m STR), and the bimodal wave climate (northeast and southwest modes) presents complex local-scale variability in nearshore conditions. Shorelines exhibit a range of decadal behaviours from rapid erosion (up to 4m/yr) to quasi-stability that cannot be directly explained by the spatial organisation of contemporary landforms or coastal defences. A multivariate statistical approach to shoreline change analysis helps to define the key modes of change and determine the most likely forcing factors.

Detection of Leukemia with Blood Samples Using Raman Spectroscopy and Multivariate Analysis

NASA Astrophysics Data System (ADS)

Martínez-Espinosa, J. C.; González-Solís, J. L.; Frausto-Reyes, C.; Miranda-Beltrán, M. L.; Soria-Fregoso, C.; Medina-Valtierra, J.

2009-06-01

The use of Raman spectroscopy to analyze blood biochemistry and hence distinguish between normal and abnormal blood was investigated. Blood samples were obtained from 6 patients who were clinically diagnosed with leukemia and 6 healthy volunteers. The imprint was put under the microscope and several points were chosen for Raman measurement. All the spectra were collected by a confocal Raman micro-spectroscopy (Renishaw) with a NIR 830 nm laser. It is shown that the serum samples from patients with leukemia and from the control group can be discriminated when the multivariate statistical methods of principal component analysis (PCA) and linear discriminated analysis (LDA) are applied to their Raman spectra. The ratios of some band intensities were analyzed and some band ratios were significant and corresponded to proteins, phospholipids, and polysaccharides. The preliminary results suggest that Raman Spectroscopy could be a new technique to study the degree of damage to the bone marrow using just blood samples instead of biopsies, treatment very painful for patients.

Blackberry wines mineral and heavy metal content determination after dry ashing: multivariate data analysis as a tool for fruit wine quality control.

PubMed

Amidžić Klarić, Daniela; Klarić, Ilija; Mornar, Ana; Velić, Darko; Velić, Natalija

2015-08-01

This study brings out the data on the content of 21 mineral and heavy metal in 15 blackberry wines made of conventionally and organically grown blackberries. The objective of this study was to classify the blackberry wine samples based on their mineral composition and the applied cultivation method of the starting raw material by using chemometric analysis. The metal content of Croatian blackberry wine samples was determined by AAS after dry ashing. The comparison between an organic and conventional group of investigated blackberry wines showed statistically significant difference in concentrations of Si and Li, where the organic group contained higher concentrations of these compounds. According to multivariate data analysis, the model based on the original metal content data set finally included seven original variables (K, Fe, Mn, Cu, Ba, Cd and Cr) and gave a satisfactory separation of two applied cultivation methods of the starting raw material.

Simulation analysis of adaptive cruise prediction control

NASA Astrophysics Data System (ADS)

Zhang, Li; Cui, Sheng Min

2017-09-01

Predictive control is suitable for multi-variable and multi-constraint system control.In order to discuss the effect of predictive control on the vehicle longitudinal motion, this paper establishes the expected spacing model by combining variable pitch spacing and the of safety distance strategy. The model predictive control theory and the optimization method based on secondary planning are designed to obtain and track the best expected acceleration trajectory quickly. Simulation models are established including predictive and adaptive fuzzy control. Simulation results show that predictive control can realize the basic function of the system while ensuring the safety. The application of predictive and fuzzy adaptive algorithm in cruise condition indicates that the predictive control effect is better.

What matters? Assessing and developing inquiry and multivariable reasoning skills in high school chemistry

NASA Astrophysics Data System (ADS)

Daftedar Abdelhadi, Raghda Mohamed

Although the Next Generation Science Standards (NGSS) present a detailed set of Science and Engineering Practices, a finer grained representation of the underlying skills is lacking in the standards document. Therefore, it has been reported that teachers are facing challenges deciphering and effectively implementing the standards, especially with regards to the Practices. This analytical study assessed the development of high school chemistry students' (N = 41) inquiry, multivariable causal reasoning skills, and metacognition as a mediator for their development. Inquiry tasks based on concepts of element properties of the periodic table as well as reaction kinetics required students to conduct controlled thought experiments, make inferences, and declare predictions of the level of the outcome variable by coordinating the effects of multiple variables. An embedded mixed methods design was utilized for depth and breadth of understanding. Various sources of data were collected including students' written artifacts, audio recordings of in-depth observational groups and interviews. Data analysis was informed by a conceptual framework formulated around the concepts of coordinating theory and evidence, metacognition, and mental models of multivariable causal reasoning. Results of the study indicated positive change towards conducting controlled experimentation, making valid inferences and justifications. Additionally, significant positive correlation between metastrategic and metacognitive competencies, and sophistication of experimental strategies, signified the central role metacognition played. Finally, lack of consistency in indicating effective variables during the multivariable prediction task pointed towards the fragile mental models of multivariable causal reasoning the students had. Implications for teacher education, science education policy as well as classroom research methods are discussed. Finally, recommendations for developing reform-based chemistry curricula based on the Practices are presented.

Methods for presentation and display of multivariate data

NASA Technical Reports Server (NTRS)

Myers, R. H.

1981-01-01

Methods for the presentation and display of multivariate data are discussed with emphasis placed on the multivariate analysis of variance problems and the Hotelling T(2) solution in the two-sample case. The methods utilize the concepts of stepwise discrimination analysis and the computation of partial correlation coefficients.

A Primer on Multivariate Analysis of Variance (MANOVA) for Behavioral Scientists

ERIC Educational Resources Information Center

Warne, Russell T.

2014-01-01

Reviews of statistical procedures (e.g., Bangert & Baumberger, 2005; Kieffer, Reese, & Thompson, 2001; Warne, Lazo, Ramos, & Ritter, 2012) show that one of the most common multivariate statistical methods in psychological research is multivariate analysis of variance (MANOVA). However, MANOVA and its associated procedures are often not…

Successful Diabetic Control as Measured by Hemoglobin A1c is Associated with Lower Urine Risk Factors for Uric Acid Calculi.

PubMed

Maciolek, Kimberly A; Penniston, Kristina L; Jhagroo, R Allan; Best, Sara L

2018-06-13

To examine the association of glycemic control, including strict glycemic control, with 24-hour (24-h) urine risk factors for uric acid and calcium calculi. With IRB approval, we identified 183 stone formers (SFs) with 459 24-h urine collections. Hemoglobin A1c (HgbA1c) measures were obtained within 3 months of the urine collection. Collections were separated into normoglycemic (NG, HgbA1c<6.5) and hyperglycemic (HG, HgbA1c≥6.5) cohorts; 24-h urine parameters were compared. The NG cohort was further divided into patients with and without a history of diabetes type 2 (DM). Variables were analyzed using chi squared, Welch's t-test and multivariate linear regression to adjust for clustering, BMI, age, gender, thiazide and potassium citrate use. Patients in the HG group were older with higher BMI. Multivariate analysis of the total study population revealed that hyperglycemia correlated with lower pH, higher uric acid relative saturation (RS), lower brushite RS and higher citrate. NG SFs with and without a history of DM had similar risk factors for uric acid stone formation. Among NG SFs, those with DM had higher urine calcium (UCa) and calcium oxalate RS than those without DM. However, this difference may be related to other factors since neither parameter correlated with DM on multivariate regression (p>0.05). Successful glycemic control may be associated with reduced urinary risk factors for uric acid stone formation. Patients with well controlled DM had equivalent risk factors to those without DM. Glycemic control should be considered a target of the multidisciplinary medical management of stone disease.

Self-tuning multivariable pole placement control of a multizone crystal growth furnace

NASA Technical Reports Server (NTRS)

Batur, C.; Sharpless, R. B.; Duval, W. M. B.; Rosenthal, B. N.

1992-01-01

This paper presents the design and implementation of a multivariable self-tuning temperature controller for the control of lead bromide crystal growth. The crystal grows inside a multizone transparent furnace. There are eight interacting heating zones shaping the axial temperature distribution inside the furnace. A multi-input, multi-output furnace model is identified on-line by a recursive least squares estimation algorithm. A multivariable pole placement controller based on this model is derived and implemented. Comparison between single-input, single-output and multi-input, multi-output self-tuning controllers demonstrates that the zone-to-zone interactions can be minimized better by a multi-input, multi-output controller design. This directly affects the quality of crystal grown.

Overview of computational control research at UT Austin

NASA Technical Reports Server (NTRS)

Bong, Wie

1989-01-01

An overview of current research activities at UT Austin is presented to discuss certain technical issues in the following areas: (1) Computer-Aided Nonlinear Control Design: In this project, the describing function method is employed for the nonlinear control analysis and design of a flexible spacecraft equipped with pulse modulated reaction jets. INCA program has been enhanced to allow the numerical calculation of describing functions as well as the nonlinear limit cycle analysis capability in the frequency domain; (2) Robust Linear Quadratic Gaussian (LQG) Compensator Synthesis: Robust control design techniques and software tools are developed for flexible space structures with parameter uncertainty. In particular, an interactive, robust multivariable control design capability is being developed for INCA program; and (3) LQR-Based Autonomous Control System for the Space Station: In this project, real time implementation of LQR-based autonomous control system is investigated for the space station with time-varying inertias and with significant multibody dynamic interactions.

Risk factors for Staphylococcus aureus postpartum breast abscess.

PubMed

Branch-Elliman, Westyn; Golen, Toni H; Gold, Howard S; Yassa, David S; Baldini, Linda M; Wright, Sharon B

2012-01-01

Staphylococcus aureus (SA) breast abscesses are a complication of the postpartum period. Risk factors for postpartum SA breast abscesses are poorly defined, and literature is conflicting. Whether risk factors for methicillin-resistant SA (MRSA) and methicillin-susceptible SA (MSSA) infections differ is unknown. We describe novel risk factors associated with postpartum breast abscesses and the changing epidemiology of this infection. We conducted a cohort study with a nested case-control study (n = 216) involving all patients with culture-confirmed SA breast abscess among >30 000 deliveries at our academic tertiary care center from 2003 through 2010. Data were collected from hospital databases and through abstraction from medical records. All SA cases were compared with both nested controls and full cohort controls. A subanalysis was completed to determine whether risk factors for MSSA and MRSA breast abscess differ. Univariate analysis was completed using Student's t test, Wilcoxon rank-sum test, and analysis of variance, as appropriate. A multivariable stepwise logistic regression was used to determine final adjusted results for both the case-control and the cohort analyses. Fifty-four cases of culture-confirmed abscess were identified: 30 MRSA and 24 MSSA. Risk factors for postpartum SA breast abscess in multivariable analysis include in-hospital identification of a mother having difficulty breastfeeding (odds ratio, 5.00) and being a mother employed outside the home (odds ratio, 2.74). Risk factors did not differ between patients who developed MRSA and MSSA infections. MRSA is an increasingly important pathogen in postpartum women; risk factors for postpartum SA breast abscess have not changed with the advent of community-associated MRSA.

Does investor ownership of nursing homes compromise the quality of care?

PubMed

Harrington, C; Woolhandler, S; Mullan, J; Carrillo, H; Himmelstein, D U

2001-09-01

Two thirds of nursing homes are investor owned. This study examined whether investor ownership affects quality. We analyzed 1998 data from state inspections of 13,693 nursing facilities. We used a multivariate model and controlled for case mix, facility characteristics, and location. Investor-owned facilities averaged 5.89 deficiencies per home, 46.5% higher than nonprofit facilities and 43.0% higher than public facilities. In multivariate analysis, investor ownership predicted 0.679 additional deficiencies per home; chain ownership predicted an additional 0.633 deficiencies. Nurse staffing was lower at investor-owned nursing homes. Investor-owned nursing homes provide worse care and less nursing care than do not-for-profit or public homes.

Multivariate statistical analysis of a high rate biofilm process treating kraft mill bleach plant effluent.

PubMed

Goode, C; LeRoy, J; Allen, D G

2007-01-01

This study reports on a multivariate analysis of the moving bed biofilm reactor (MBBR) wastewater treatment system at a Canadian pulp mill. The modelling approach involved a data overview by principal component analysis (PCA) followed by partial least squares (PLS) modelling with the objective of explaining and predicting changes in the BOD output of the reactor. Over two years of data with 87 process measurements were used to build the models. Variables were collected from the MBBR control scheme as well as upstream in the bleach plant and in digestion. To account for process dynamics, a variable lagging approach was used for variables with significant temporal correlations. It was found that wood type pulped at the mill was a significant variable governing reactor performance. Other important variables included flow parameters, faults in the temperature or pH control of the reactor, and some potential indirect indicators of biomass activity (residual nitrogen and pH out). The most predictive model was found to have an RMSEP value of 606 kgBOD/d, representing a 14.5% average error. This was a good fit, given the measurement error of the BOD test. Overall, the statistical approach was effective in describing and predicting MBBR treatment performance.

Anger Expression Types and Interpersonal Problems in Nurses.

PubMed

Han, Aekyung; Won, Jongsoon; Kim, Oksoo; Lee, Sang E

2015-06-01

The purpose of this study was to investigate the anger expression types in nurses and to analyze the differences between the anger expression types and interpersonal problems. The data were collected from 149 nurses working in general hospitals with 300 beds or more in Seoul or Gyeonggi province, Korea. For anger expression type, the anger expression scale from the Korean State-Trait Anger Expression Inventory was used. For interpersonal problems, the short form of the Korean Inventory of Interpersonal Problems Circumplex Scales was used. Data were analyzed using descriptive statistics, cluster analysis, multivariate analysis of variance, and Duncan's multiple comparisons test. Three anger expression types in nurses were found: low-anger expression, anger-in, and anger-in/control type. From the results of multivariate analysis of variance, there were significant differences between anger expression types and interpersonal problems (Wilks lambda F = 3.52, p < .001). Additionally, anger-in/control type was found to have the most difficulty with interpersonal problems by Duncan's post hoc test (p < .050). Based on this research, the development of an anger expression intervention program for nurses is recommended to establish the means of expressing the suppressed emotions, which would help the nurses experience less interpersonal problems. Copyright © 2015. Published by Elsevier B.V.

Differential flatness properties and multivariable adaptive control of ovarian system dynamics

NASA Astrophysics Data System (ADS)

Rigatos, Gerasimos

2016-12-01

The ovarian system exhibits nonlinear dynamics which is modeled by a set of coupled nonlinear differential equations. The paper proposes adaptive fuzzy control based on differential flatness theory for the complex dynamics of the ovarian system. It is proven that the dynamic model of the ovarian system, having as state variables the LH and the FSH hormones and their derivatives, is a differentially flat one. This means that all its state variables and its control inputs can be described as differential functions of the flat output. By exploiting differential flatness properties the system's dynamic model is written in the multivariable linear canonical (Brunovsky) form, for which the design of a state feedback controller becomes possible. After this transformation, the new control inputs of the system contain unknown nonlinear parts, which are identified with the use of neurofuzzy approximators. The learning procedure for these estimators is determined by the requirement the first derivative of the closed-loop's Lyapunov function to be a negative one. Moreover, Lyapunov stability analysis shows that H-infinity tracking performance is succeeded for the feedback control loop and this assures improved robustness to the aforementioned model uncertainty as well as to external perturbations. The efficiency of the proposed adaptive fuzzy control scheme is confirmed through simulation experiments.

1H NMR Metabolomics Study of Spleen from C57BL/6 Mice Exposed to Gamma Radiation

PubMed Central

Xiao, X; Hu, M; Liu, M; Hu, JZ

2016-01-01

Due to the potential risk of accidental exposure to gamma radiation, it’s critical to identify the biomarkers of radiation exposed creatures. In the present study, NMR based metabolomics combined with multivariate data analysis to evaluate the metabolites changed in the C57BL/6 mouse spleen after 4 days whole body exposure to 3.0 Gy and 7.8 Gy gamma radiations. Principal component analysis (PCA) and orthogonal projection to latent structures analysis (OPLS) are employed for classification and identification potential biomarkers associated with gamma irradiation. Two different strategies for NMR spectral data reduction (i.e., spectral binning and spectral deconvolution) are combined with normalize to constant sum and unit weight before multivariate data analysis, respectively. The combination of spectral deconvolution and normalization to unit weight is the best way for identifying discriminatory metabolites between the irradiation and control groups. Normalized to the constant sum may achieve some pseudo biomarkers. PCA and OPLS results shown that the exposed groups can be well separated from the control group. Leucine, 2-aminobutyrate, valine, lactate, arginine, glutathione, 2-oxoglutarate, creatine, tyrosine, phenylalanine, π-methylhistidine, taurine, myoinositol, glycerol and uracil are significantly elevated while ADP is decreased significantly. These significantly changed metabolites are associated with multiple metabolic pathways and may be potential biomarkers in the spleen exposed to gamma irradiation. PMID:27019763

Analysis of association of clinical aspects and IL1B tagSNPs with severe preeclampsia.

PubMed

Leme Galvão, Larissa Paes; Menezes, Filipe Emanuel; Mendonca, Caio; Barreto, Ikaro; Alvim-Pereira, Claudia; Alvim-Pereira, Fabiano; Gurgel, Ricardo

2016-01-01

This study investigates the association between IL1B genotypes using a tag SNP (single polymorphism) approach, maternal and environmental factors in Brazilian women with severe preeclampsia. A case-control study with a total of 456 patients (169 preeclamptic women and 287 controls) was conducted in the two reference maternity hospitals of Sergipe state, Northeast Brazil. A questionnaire was administered and DNA was extracted to genotype the population for four tag SNPs of the IL1Beta: rs 1143643, rs 1143633, rs 1143634 and rs 1143630. Haplotype association analysis and p-values were calculated using the THESIAS test. Odds ratio (OR) estimation, confidence interval (CI) and multivariate logistic regression were performed. High pregestational body mass index (pre-BMI), first gestation, cesarean section, more than six medical visits, low level of consciousness on admission and TC and TT genotype in rs1143630 of IL1Beta showed association with the preeclamptic group in univariate analysis. After multivariate logistic regression pre-BMI, first gestation and low level of consciousness on admission remained associated. We identified an association between clinical variables and preeclampsia. Univariate analysis suggested that inflammatory process-related genes, such as IL1B, may be involved and should be targeted in further studies. The identification of the genetic background involved in preeclampsia host response modulation is mandatory in order to understand the preeclampsia process.

1H NMR metabolomics study of spleen from C57BL/6 mice exposed to gamma radiation

DOE PAGES

Xiao, Xiongjie; Hu, M.; Liu, M.; ...

2016-01-27

Due to the potential risk of accidental exposure to gamma radiation, it’s critical to identify the biomarkers of radiation exposed creatures. In the present study, NMR based metabolomics combined with multivariate data analysis to evaluate the metabolites changed in the C57BL/6 mouse spleen after 4 days whole body exposure to 3.0 Gy and 7.8 Gy gamma radiations. Principal component analysis (PCA) and orthogonal projection to latent structures analysis (OPLS) are employed for classification and identification potential biomarkers associated with gamma irradiation. Two different strategies for NMR spectral data reduction (i.e., spectral binning and spectral deconvolution) are combined with normalize tomore » constant sum and unit weight before multivariate data analysis, respectively. The combination of spectral deconvolution and normalization to unit weight is the best way for identifying discriminatory metabolites between the irradiation and control groups. Normalized to the constant sum may achieve some pseudo biomarkers. PCA and OPLS results shown that the exposed groups can be well separated from the control group. Leucine, 2-aminobutyrate, valine, lactate, arginine, glutathione, 2-oxoglutarate, creatine, tyrosine, phenylalanine, π-methylhistidine, taurine, myoinositol, glycerol and uracil are significantly elevated while ADP is decreased significantly. As a result, these significantly changed metabolites are associated with multiple metabolic pathways and may be potential biomarkers in the spleen exposed to gamma irradiation.« less

Patient satisfaction with intravenous acetaminophen: a pooled analysis of five randomized, placebo-controlled studies in the acute postoperative setting.

PubMed

Apfel, Christian C; Souza, Kimberly; Portillo, Juan; Dalal, Poorvi; Bergese, Sergio D

2015-01-01

Intravenous (IV) acetaminophen has been shown to reduce postoperative pain and opioid consumption, which may lead to increased patient satisfaction. To determine the effect IV acetaminophen has on patient satisfaction, a pooled analysis from methodologically homogenous studies was conducted. We obtained patient-level data from five randomized, placebo-controlled studies in adults undergoing elective surgery in which patient satisfaction was measured using a 4-point categorical rating scale. The primary endpoint was "excellent" satisfaction and the secondary endpoint was "good" or "excellent" satisfaction at 24 hr after first study drug administration. Bivariate analyses were conducted using the chi-square test and Student's t-test and multivariable analyses were conducted using logistic regression analysis. Patients receiving IV acetaminophen were more than twice as likely as those who received placebo to report "excellent" patient satisfaction ratings (32.3% vs. 15.9%, respectively). Of all variables that remained statistically significant in the multivariable analysis (i.e., type of surgery, duration of anesthesia, last pain rating, and opioid consumption), IV acetaminophen had the strongest positive effect on "excellent" patient satisfaction with an odds ratio of 2.76 (95% CI 1.81-4.23). Results for "excellent" or "good" satisfaction were similar. When given as part of a perioperative analgesic regimen, IV acetaminophen was associated with significantly improved patient satisfaction.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sole, Claudio V., E-mail: cvsole@uc.cl; School of Medicine, Complutense University, Madrid; Service of Radiation Oncology, Instituto de Radiomedicina, Santiago

Purpose: To perform a joint analysis of data from 3 contributing centers within the intraoperative electron-beam radiation therapy (IOERT)-Spanish program, to determine the potential of IOERT as an anticipated boost before external beam radiation therapy in the multidisciplinary treatment of pediatric extremity soft-tissue sarcomas. Methods and Materials: From June 1993 to May 2013, 62 patients (aged <21 years) with a histologic diagnosis of primary extremity soft-tissue sarcoma with absence of distant metastases, undergoing limb-sparing grossly resected surgery, external beam radiation therapy (median dose 40 Gy) and IOERT (median dose 10 Gy) were considered eligible for this analysis. Results: After a median follow-up ofmore » 66 months (range, 4-235 months), 10-year local control, disease-free survival, and overall survival was 85%, 76%, and 81%, respectively. In multivariate analysis after adjustment for other covariates, tumor size >5 cm (P=.04) and R1 margin status (P=.04) remained significantly associated with local relapse. In regard to overall survival only margin status (P=.04) retained association on multivariate analysis. Ten patients (16%) reported severe chronic toxicity events (all grade 3). Conclusions: An anticipated IOERT boost allowed for external beam radiation therapy dose reduction, with high local control and acceptably low toxicity rates. The combined radiosurgical approach needs to be tested in a prospective trial to confirm these results.« less

Pneumonia in multiple injured patients: a prospective controlled trial on early prediction using clinical and immunological parameters.

PubMed

Andermahr, J; Greb, A; Hensler, T; Helling, H J; Bouillon, B; Sauerland, S; Rehm, K E; Neugebauer, E

2002-05-01

In a prospective trial 266 multiple injured patients were included to evaluate clinical risk factors and immune parameters related to pneumonia. Clinical and humoral parameters were assessed and multivariate analysis performed. The multivariate analysis (odds ratio with 95% confidence interval (CI)) revealed male gender (3.65), traumatic brain injury (TBI) (2.52), thorax trauma (AIS(thorax) > or = 3) (2.05), antibiotic prophylaxis (1.30), injury severity score (ISS) (1.03 per ISS point) and the age (1.02 per year) as risk factors for pneumonia. The main pathogens were Acinetobacter Baumannii (40%) and Staphylococcus aureus (25%). A tendency towards higher Procalcitonin (PCT) and Interleukin (IL)-6 levels two days after trauma was observed for pneumonia patients. The immune parameters (PCT, IL-6, IL-10, soluble tumor necrosis factor p-55 and p-75) could not confirm the diagnosis of pneumonia earlier than the clinical parameters.

Statistical inferences for data from studies conducted with an aggregated multivariate outcome-dependent sample design

PubMed Central

Lu, Tsui-Shan; Longnecker, Matthew P.; Zhou, Haibo

2016-01-01

Outcome-dependent sampling (ODS) scheme is a cost-effective sampling scheme where one observes the exposure with a probability that depends on the outcome. The well-known such design is the case-control design for binary response, the case-cohort design for the failure time data and the general ODS design for a continuous response. While substantial work has been done for the univariate response case, statistical inference and design for the ODS with multivariate cases remain under-developed. Motivated by the need in biological studies for taking the advantage of the available responses for subjects in a cluster, we propose a multivariate outcome dependent sampling (Multivariate-ODS) design that is based on a general selection of the continuous responses within a cluster. The proposed inference procedure for the Multivariate-ODS design is semiparametric where all the underlying distributions of covariates are modeled nonparametrically using the empirical likelihood methods. We show that the proposed estimator is consistent and developed the asymptotically normality properties. Simulation studies show that the proposed estimator is more efficient than the estimator obtained using only the simple-random-sample portion of the Multivariate-ODS or the estimator from a simple random sample with the same sample size. The Multivariate-ODS design together with the proposed estimator provides an approach to further improve study efficiency for a given fixed study budget. We illustrate the proposed design and estimator with an analysis of association of PCB exposure to hearing loss in children born to the Collaborative Perinatal Study. PMID:27966260

Multivariable PID controller design tuning using bat algorithm for activated sludge process

NASA Astrophysics Data System (ADS)

Atikah Nor’Azlan, Nur; Asmiza Selamat, Nur; Mat Yahya, Nafrizuan

2018-04-01

The designing of a multivariable PID control for multi input multi output is being concerned with this project by applying four multivariable PID control tuning which is Davison, Penttinen-Koivo, Maciejowski and Proposed Combined method. The determination of this study is to investigate the performance of selected optimization technique to tune the parameter of MPID controller. The selected optimization technique is Bat Algorithm (BA). All the MPID-BA tuning result will be compared and analyzed. Later, the best MPID-BA will be chosen in order to determine which techniques are better based on the system performances in terms of transient response.

Multidisciplinary optimization of a controlled space structure using 150 design variables

NASA Technical Reports Server (NTRS)

James, Benjamin B.

1992-01-01

A general optimization-based method for the design of large space platforms through integration of the disciplines of structural dynamics and control is presented. The method uses the global sensitivity equations approach and is especially appropriate for preliminary design problems in which the structural and control analyses are tightly coupled. The method is capable of coordinating general purpose structural analysis, multivariable control, and optimization codes, and thus, can be adapted to a variety of controls-structures integrated design projects. The method is used to minimize the total weight of a space platform while maintaining a specified vibration decay rate after slewing maneuvers.

Multivariate Analysis and Machine Learning in Cerebral Palsy Research

PubMed Central

Zhang, Jing

2017-01-01

Cerebral palsy (CP), a common pediatric movement disorder, causes the most severe physical disability in children. Early diagnosis in high-risk infants is critical for early intervention and possible early recovery. In recent years, multivariate analytic and machine learning (ML) approaches have been increasingly used in CP research. This paper aims to identify such multivariate studies and provide an overview of this relatively young field. Studies reviewed in this paper have demonstrated that multivariate analytic methods are useful in identification of risk factors, detection of CP, movement assessment for CP prediction, and outcome assessment, and ML approaches have made it possible to automatically identify movement impairments in high-risk infants. In addition, outcome predictors for surgical treatments have been identified by multivariate outcome studies. To make the multivariate and ML approaches useful in clinical settings, further research with large samples is needed to verify and improve these multivariate methods in risk factor identification, CP detection, movement assessment, and outcome evaluation or prediction. As multivariate analysis, ML and data processing technologies advance in the era of Big Data of this century, it is expected that multivariate analysis and ML will play a bigger role in improving the diagnosis and treatment of CP to reduce mortality and morbidity rates, and enhance patient care for children with CP. PMID:29312134

Multivariate Analysis and Machine Learning in Cerebral Palsy Research.

PubMed

Zhang, Jing

2017-01-01

Cerebral palsy (CP), a common pediatric movement disorder, causes the most severe physical disability in children. Early diagnosis in high-risk infants is critical for early intervention and possible early recovery. In recent years, multivariate analytic and machine learning (ML) approaches have been increasingly used in CP research. This paper aims to identify such multivariate studies and provide an overview of this relatively young field. Studies reviewed in this paper have demonstrated that multivariate analytic methods are useful in identification of risk factors, detection of CP, movement assessment for CP prediction, and outcome assessment, and ML approaches have made it possible to automatically identify movement impairments in high-risk infants. In addition, outcome predictors for surgical treatments have been identified by multivariate outcome studies. To make the multivariate and ML approaches useful in clinical settings, further research with large samples is needed to verify and improve these multivariate methods in risk factor identification, CP detection, movement assessment, and outcome evaluation or prediction. As multivariate analysis, ML and data processing technologies advance in the era of Big Data of this century, it is expected that multivariate analysis and ML will play a bigger role in improving the diagnosis and treatment of CP to reduce mortality and morbidity rates, and enhance patient care for children with CP.

Awareness, treatment, control of diabetes mellitus and the risk factors: survey results from northeast China.

PubMed

Wang, Chang; Yu, Yaqin; Zhang, Xiangyang; Li, Yong; Kou, Changgui; Li, Bo; Tao, Yuchun; Zhen, Qing; He, Huan; Kanu, Joseph Sam; Huang, Xufeng; Han, Mei; Liu, Yawen

2014-01-01

The awareness, treatment and control of diabetes mellitus (DM) can effectively reflect on the social status of diabetes conditions. Although several researchers have investigated the awareness, treatment and control rates of diabetes mellitus in China, little is known about their association with risk factors. This study aims to examine the relationship between risk factors and awareness, treatment and control of diabetes mellitus in northeast China. A cross-sectional survey was conducted in 2012. Multistage stratified random cluster sampling design was used to select participants aged 18 to 79 years old. The analysis was based on a representative sample of 1,854 adult subjects. Multivariable logistic regression analysis was used to examine socio-demographic factors associated with the levels of awareness, treatment and control of diabetes mellitus. The awareness, treatment, and control rates of diabetes mellitus were 64.1%, 52.9% and 44.2%, respectively. In the multivariable logistic regression analysis, family history of diabetes was significantly positively associated with awareness (OR, 2.145; 95% CI, 1.600-2.875) and treatment (OR, 2.021; 95% CI, 1.559-2.619) of diabetes mellitus, while negatively associated with control (OR, 0.671; 95% CI, 0.529-0.951). Cigarette smokers and alcohol drinkers were less likely than non-smokers and non-drinkers to be aware of their blood glucose levels (OR, 0.895, 0.614; 95% CI, 0.659-1.216, 0.446-0.844, respectively). Participants who frequently exercise were more likely to be aware of their diabetic conditions than people who never or rarely exercise (OR, 2.003; 95% CI, 1.513-2.651). We found that the awareness and treatment of diabetes mellitus were positively associated with age and were high in participants with a family history of diabetes and those who exercise frequently, but low for cigarette smokers and alcohol drinkers. Participants with a family history of diabetes had their diabetic condition poorly controlled.

Multivariate data analysis on historical IPV production data for better process understanding and future improvements.

PubMed

Thomassen, Yvonne E; van Sprang, Eric N M; van der Pol, Leo A; Bakker, Wilfried A M

2010-09-01

Historical manufacturing data can potentially harbor a wealth of information for process optimization and enhancement of efficiency and robustness. To extract useful data multivariate data analysis (MVDA) using projection methods is often applied. In this contribution, the results obtained from applying MVDA on data from inactivated polio vaccine (IPV) production runs are described. Data from over 50 batches at two different production scales (700-L and 1,500-L) were available. The explorative analysis performed on single unit operations indicated consistent manufacturing. Known outliers (e.g., rejected batches) were identified using principal component analysis (PCA). The source of operational variation was pinpointed to variation of input such as media. Other relevant process parameters were in control and, using this manufacturing data, could not be correlated to product quality attributes. The gained knowledge of the IPV production process, not only from the MVDA, but also from digitalizing the available historical data, has proven to be useful for troubleshooting, understanding limitations of available data and seeing the opportunity for improvements. 2010 Wiley Periodicals, Inc.

Estimating an Effect Size in One-Way Multivariate Analysis of Variance (MANOVA)

ERIC Educational Resources Information Center

Steyn, H. S., Jr.; Ellis, S. M.

2009-01-01

When two or more univariate population means are compared, the proportion of variation in the dependent variable accounted for by population group membership is eta-squared. This effect size can be generalized by using multivariate measures of association, based on the multivariate analysis of variance (MANOVA) statistics, to establish whether…

Prognostic Value of External Beam Radiation Therapy in Patients Treated With Surgical Resection and Intraoperative Electron Beam Radiation Therapy for Locally Recurrent Soft Tissue Sarcoma: A Multicentric Long-Term Outcome Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Calvo, Felipe A.; School of Medicine, Complutense University, Madrid; Sole, Claudio V., E-mail: cvsole@uc.cl

Background: A joint analysis of data from centers involved in the Spanish Cooperative Initiative for Intraoperative Electron Radiotherapy was performed to investigate long-term outcomes of locally recurrent soft tissue sarcoma (LR-STS) patients treated with a multidisciplinary approach. Methods and Materials: Patients with a histologic diagnosis of LR-STS (extremity, 43%; trunk wall, 24%; retroperitoneum, 33%) and no distant metastases who underwent radical surgery and intraoperative electron radiation therapy (IOERT; median dose, 12.5 Gy) were considered eligible for participation in this study. In addition, 62% received external beam radiation therapy (EBRT; median dose, 50 Gy). Results: From 1986 to 2012, a totalmore » of 103 patients from 3 Spanish expert IOERT institutions were analyzed. With a median follow-up of 57 months (range, 2-311 months), 5-year local control (LC) was 60%. The 5-year IORT in-field control, disease-free survival (DFS), and overall survival were 73%, 43%, and 52%, respectively. In the multivariate analysis, no EBRT to treat the LR-STS (P=.02) and microscopically involved margin resection status (P=.04) retained significance in relation to LC. With regard to IORT in-field control, only not delivering EBRT to the LR-STS retained significance in the multivariate analysis (P=.03). Conclusion: This joint analysis revealed that surgical margin and EBRT affect LC but that, given the high risk of distant metastases, DFS remains modest. Intensified local treatment needs to be further tested in the context of more efficient concurrent, neoadjuvant, and adjuvant systemic therapy.« less

Assessment of cardio-respiratory interactions in preterm infants by bivariate autoregressive modeling and surrogate data analysis.

PubMed

Indic, Premananda; Bloch-Salisbury, Elisabeth; Bednarek, Frank; Brown, Emery N; Paydarfar, David; Barbieri, Riccardo

2011-07-01

Cardio-respiratory interactions are weak at the earliest stages of human development, suggesting that assessment of their presence and integrity may be an important indicator of development in infants. Despite the valuable research devoted to infant development, there is still a need for specifically targeted standards and methods to assess cardiopulmonary functions in the early stages of life. We present a new methodological framework for the analysis of cardiovascular variables in preterm infants. Our approach is based on a set of mathematical tools that have been successful in quantifying important cardiovascular control mechanisms in adult humans, here specifically adapted to reflect the physiology of the developing cardiovascular system. We applied our methodology in a study of cardio-respiratory responses for 11 preterm infants. We quantified cardio-respiratory interactions using specifically tailored multivariate autoregressive analysis and calculated the coherence as well as gain using causal approaches. The significance of the interactions in each subject was determined by surrogate data analysis. The method was tested in control conditions as well as in two different experimental conditions; with and without use of mild mechanosensory intervention. Our multivariate analysis revealed a significantly higher coherence, as confirmed by surrogate data analysis, in the frequency range associated with eupneic breathing compared to the other ranges. Our analysis validates the models behind our new approaches, and our results confirm the presence of cardio-respiratory coupling in early stages of development, particularly during periods of mild mechanosensory intervention, thus encouraging further application of our approach. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Application of reiteration of Hankel singular value decomposition in quality control

NASA Astrophysics Data System (ADS)

Staniszewski, Michał; Skorupa, Agnieszka; Boguszewicz, Łukasz; Michalczuk, Agnieszka; Wereszczyński, Kamil; Wicher, Magdalena; Konopka, Marek; Sokół, Maria; Polański, Andrzej

2017-07-01

Medical centres are obliged to store past medical records, including the results of quality assurance (QA) tests of the medical equipment, which is especially useful in checking reproducibility of medical devices and procedures. Analysis of multivariate time series is an important part of quality control of NMR data. In this work we proposean anomaly detection tool based on Reiteration of Hankel Singular Value Decomposition method. The presented method was compared with external software and authors obtained comparable results.

Structural Technology Evaluation and Analysis Program (STEAP). Delivery Order 0037: Prognosis-Based Control Reconfiguration for an Aircraft with Faulty Actuator to Enable Performance in a Degraded State

DTIC Science & Technology

2010-12-01

computers in 1953. HIL motion simulators were also built for the dynamic testing of vehicle com- ponents (e.g. suspensions, bodies ) with hydraulic or...complex, comprehensive mechanical systems can be simulated in real-time by parallel computers; examples include multi- body sys- tems, brake systems...hard constraints in a multivariable control framework. And the third aspect is the ability to perform online optimization. These aspects results in

Multivariate analysis of volatile compounds detected by headspace solid-phase microextraction/gas chromatography: A tool for sensory classification of cork stoppers.

PubMed

Prat, Chantal; Besalú, Emili; Bañeras, Lluís; Anticó, Enriqueta

2011-06-15

The volatile fraction of aqueous cork macerates of tainted and non-tainted agglomerate cork stoppers was analysed by headspace solid-phase microextraction (HS-SPME)/gas chromatography. Twenty compounds containing terpenoids, aliphatic alcohols, lignin-related compounds and others were selected and analysed in individual corks. Cork stoppers were previously classified in six different classes according to sensory descriptions including, 2,4,6-trichloroanisole taint and other frequent, non-characteristic odours found in cork. A multivariate analysis of the chromatographic data of 20 selected chemical compounds using linear discriminant analysis models helped in the differentiation of the a priori made groups. The discriminant model selected five compounds as the best combination. Selected compounds appear in the model in the following order; 2,4,6 TCA, fenchyl alcohol, 1-octen-3-ol, benzyl alcohol and benzothiazole. Unfortunately, not all six a priori differentiated sensory classes were clearly discriminated in the model, probably indicating that no measurable differences exist in the chromatographic data for some categories. The predictive analyses of a refined model in which two sensory classes were fused together resulted in a good classification. Prediction rates of control (non-tainted), TCA, musty-earthy-vegetative, vegetative and chemical descriptions were 100%, 100%, 85%, 67.3% and 100%, respectively, when the modified model was used. The multivariate analysis of chromatographic data will help in the classification of stoppers and provide a perfect complement to sensory analyses. Copyright © 2010 Elsevier Ltd. All rights reserved.

HPLC-TOF-MS and HPLC-MS/MS combined with multivariate analysis for the characterization and discrimination of phenolic profiles in nonfumigated and sulfur-fumigated rhubarb.

PubMed

Yan, Yan; Zhang, Qianqian; Feng, Fang

2016-07-01

Sulfur fumigation has recently been used during the postharvest handling of rhubarb to reduce the drying duration and control pests. However, a few reports question the effect of sulfur fumigation on the bioactive components of rhubarb, which is crucial for the quality evaluation of the herbal medicine. The bottleneck limiting the study comes from the complex compounds that exist in herb samples with diverse structural features, wide concentration range and the difficulty to obtain all the reference standards. In this study, an integrated strategy based on the highly effective separation and analysis by liquid chromatography coupled with diode-array detection and time-of-flight/triple-quadruple tandem mass spectrometry combined with multivariate analysis was established. 68 phenolic compounds that exist in nonfumigated and sulfur-fumigated herb samples of rhubarb were tentatively assigned based on their retention behavior, UV spectra, accurate molecular weight, and mass spectral fragments. Qualitative and semiquantitative comparison revealed a serious reduction of the majority of phenolic compounds in sulfur-fumigated rhubarb. Furthermore, multivariate analysis was applied to holistically discriminate nonfumigated from sulfur-fumigated rhubarb and explore the characteristic chemical markers. The established approach was specific and rapid for characterizing and screening sulfur-fumigated rhubarb among commercial samples and could be applied for the quality assessment of other sulfur-fumigated herbs. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Radiographical findings in patients with liver cirrhosis and hepatic encephalopathy.

PubMed

Elwir, Saleh; Hal, Hassan; Veith, Joshua; Schreibman, Ian; Kadry, Zakiyah; Riley, Thomas

2016-08-01

Hepatic encephalopathy is a common complication encountered in patients with liver cirrhosis. Hepatic encephalopathy is not reflected in the current liver transplant allocation system. Correlation was sought between hepatic encephalopathy with findings detected on radiographic imaging studies and the patient's clinical profile. A retrospective analysis was conducted of patients with cirrhosis, who presented for liver transplant evaluation in 2009 and 2010. Patients with hepatocellular carcinoma, ejection fraction less than 60% and who had a TIPS (transjugular intrahepatic portosystemic shunting) procedure or who did not complete the evaluation were excluded. Statistical analysis was performed and variables found to be significant on univariate analysis (P < 0.05) were analysed by a multivariate logistic regression model. A total of 117 patients met the inclusion criteria and were divided into a hepatic encephalopathy group (n = 58) and a control group (n = 59). Univariate analysis found that a smaller portal vein diameter, smaller liver antero-posterior diameter, liver nodularity and use of diuretics or centrally acting medications showed significant correlation with hepatic encephalopathy. This association was confirmed for smaller portal vein, use of diuretics and centrally acting medications in the multivariate analysis. A decrease in portal vein diameter was associated with increased risk of encephalopathy. Identifying patients with smaller portal vein diameter may warrant screening for encephalopathy by more advanced psychometric testing, and more aggressive control of constipation and other factors that may precipitate encephalopathy. © The Author(s) 2015. Published by Oxford University Press and the Digestive Science Publishing Co. Limited.

Profiling and classification of French propolis by combined multivariate data analysis of planar chromatograms and scanning direct analysis in real time mass spectra.

PubMed

Chasset, Thibaut; Häbe, Tim T; Ristivojevic, Petar; Morlock, Gertrud E

2016-09-23

Quality control of propolis is challenging, as it is a complex natural mixture of compounds, and thus, very difficult to analyze and standardize. Shown on the example of 30 French propolis samples, a strategy for an improved quality control was demonstrated in which high-performance thin-layer chromatography (HPTLC) fingerprints were evaluated in combination with selected mass signals obtained by desorption-based scanning mass spectrometry (MS). The French propolis sample extracts were separated by a newly developed reversed phase (RP)-HPTLC method. The fingerprints obtained by two different detection modes, i.e. after (1) derivatization and fluorescence detection (FLD) at UV 366nm and (2) scanning direct analysis in real time (DART)-MS, were analyzed by multivariate data analysis. Thus, RP-HPTLC-FLD and RP-HPTLC-DART-MS fingerprints were explored and the best classification was obtained using both methods in combination with pattern recognition techniques, such as principal component analysis. All investigated French propolis samples were divided in two types and characteristic patterns were observed. Phenolic compounds such as caffeic acid, p-coumaric acid, chrysin, pinobanksin, pinobanksin-3-acetate, galangin, kaempferol, tectochrysin and pinocembrin were identified as characteristic marker compounds of French propolis samples. This study expanded the research on the European poplar type of propolis and confirmed the presence of two botanically different types of propolis, known as the blue and orange types. Copyright © 2016 Elsevier B.V. All rights reserved.

The impact of moderate wine consumption on the risk of developing prostate cancer

PubMed Central

Ferro, Matteo; Foerster, Beat; Abufaraj, Mohammad; Briganti, Alberto; Karakiewicz, Pierre I; Shariat, Shahrokh F

2018-01-01

Objective To investigate the impact of moderate wine consumption on the risk of prostate cancer (PCa). We focused on the differential effect of moderate consumption of red versus white wine. Design This study was a meta-analysis that includes data from case–control and cohort studies. Materials and methods A systematic search of Web of Science, Medline/PubMed, and Cochrane library was performed on December 1, 2017. Studies were deemed eligible if they assessed the risk of PCa due to red, white, or any wine using multivariable logistic regression analysis. We performed a formal meta-analysis for the risk of PCa according to moderate wine and wine type consumption (white or red). Heterogeneity between studies was assessed using Cochrane’s Q test and I2 statistics. Publication bias was assessed using Egger’s regression test. Results A total of 930 abstracts and titles were initially identified. After removal of duplicates, reviews, and conference abstracts, 83 full-text original articles were screened. Seventeen studies (611,169 subjects) were included for final evaluation and fulfilled the inclusion criteria. In the case of moderate wine consumption: the pooled risk ratio (RR) for the risk of PCa was 0.98 (95% CI 0.92–1.05, p=0.57) in the multivariable analysis. Moderate white wine consumption increased the risk of PCa with a pooled RR of 1.26 (95% CI 1.10–1.43, p=0.001) in the multi-variable analysis. Meanwhile, moderate red wine consumption had a protective role reducing the risk by 12% (RR 0.88, 95% CI 0.78–0.999, p=0.047) in the multivariable analysis that comprised 222,447 subjects. Conclusions In this meta-analysis, moderate wine consumption did not impact the risk of PCa. Interestingly, regarding the type of wine, moderate consumption of white wine increased the risk of PCa, whereas moderate consumption of red wine had a protective effect. Further analyses are needed to assess the differential molecular effect of white and red wine conferring their impact on PCa risk. PMID:29713200

Design, evaluation and test of an electronic, multivariable control for the F100 turbofan engine

NASA Technical Reports Server (NTRS)

Skira, C. A.; Dehoff, R. L.; Hall, W. E., Jr.

1980-01-01

A digital, multivariable control design procedure for the F100 turbofan engine is described. The controller is based on locally linear synthesis techniques using linear, quadratic regulator design methods. The control structure uses an explicit model reference form with proportional and integral feedback near a nominal trajectory. Modeling issues, design procedures for the control law and the estimation of poorly measured variables are presented.

Mouse allergen, lung function, and atopy in Puerto Rican children.

PubMed

Forno, Erick; Cloutier, Michelle M; Datta, Soma; Paul, Kathryn; Sylvia, Jody; Calvert, Deanna; Thornton-Thompson, Sherell; Wakefield, Dorothy B; Brehm, John; Hamilton, Robert G; Alvarez, María; Colón-Semidey, Angel; Acosta-Pérez, Edna; Canino, Glorisa; Celedón, Juan C

2012-01-01

To examine the relation between mouse allergen exposure and asthma in Puerto Rican children. Mus m 1, Der p 1, Bla g 2, and Fel d 1 allergens were measured in dust samples from homes of Puerto Rican children with (cases) and without (controls) asthma in Hartford, CT (n = 449) and San Juan (SJ), Puerto Rico (n = 678). Linear or logistic regression was used for the multivariate analysis of mouse allergen (Mus m 1) and lung function (FEV(1) and FEV(1)/FVC) and allergy (total IgE and skin test reactivity (STR) to ≥1 allergen) measures. Homes in SJ had lower mouse allergen levels than those in Hartford. In multivariate analyses, mouse allergen was associated with higher FEV(1) in cases in Hartford (+70.6 ml, 95% confidence interval (CI) = 8.6-132.7 ml, P = 0.03) and SJ (+45.1 ml, 95% CI =  -0.5 to 90.6 ml, P = 0.05). In multivariate analyses of controls, mouse allergen was inversely associated with STR to ≥1 allergen in non-sensitized children (odds ratio [OR] for each log-unit increment in Mus m 1 = 0.7, 95% CI = 0.5-0.9, P<0.01). In a multivariate analysis including all children at both study sites, each log-increment in mouse allergen was positively associated with FEV(1) (+28.3 ml, 95% CI = 1.4-55.2 ml, P = 0.04) and inversely associated with STR to ≥1 allergen (OR for each log-unit increment in Mus m 1 = 0.8, 95% CI = 0.6-0.9, P<0.01). Mouse allergen is associated with a higher FEV(1) and lower odds of STR to ≥1 allergen in Puerto Rican children. This may be explained by the allergen itself or correlated microbial exposures.

Mouse Allergen, Lung Function, and Atopy in Puerto Rican Children

PubMed Central

Forno, Erick; Cloutier, Michelle M.; Datta, Soma; Paul, Kathryn; Sylvia, Jody; Calvert, Deanna; Thornton-Thompson, Sherell; Wakefield, Dorothy B.; Brehm, John; Hamilton, Robert G.; Alvarez, María; Colón-Semidey, Angel; Acosta-Pérez, Edna; Canino, Glorisa; Celedón, Juan C.

2012-01-01

Objective To examine the relation between mouse allergen exposure and asthma in Puerto Rican children. Methods Mus m 1, Der p 1, Bla g 2, and Fel d 1 allergens were measured in dust samples from homes of Puerto Rican children with (cases) and without (controls) asthma in Hartford, CT (n = 449) and San Juan (SJ), Puerto Rico (n = 678). Linear or logistic regression was used for the multivariate analysis of mouse allergen (Mus m 1) and lung function (FEV1 and FEV1/FVC) and allergy (total IgE and skin test reactivity (STR) to ≥1 allergen) measures. Results Homes in SJ had lower mouse allergen levels than those in Hartford. In multivariate analyses, mouse allergen was associated with higher FEV1 in cases in Hartford (+70.6 ml, 95% confidence interval (CI) = 8.6–132.7 ml, P = 0.03) and SJ (+45.1 ml, 95% CI =  −0.5 to 90.6 ml, P = 0.05). In multivariate analyses of controls, mouse allergen was inversely associated with STR to ≥1 allergen in non-sensitized children (odds ratio [OR] for each log-unit increment in Mus m 1 = 0.7, 95% CI = 0.5–0.9, P<0.01). In a multivariate analysis including all children at both study sites, each log-increment in mouse allergen was positively associated with FEV1 (+28.3 ml, 95% CI = 1.4–55.2 ml, P = 0.04) and inversely associated with STR to ≥1 allergen (OR for each log-unit increment in Mus m 1 = 0.8, 95% CI = 0.6–0.9, P<0.01). Conclusions Mouse allergen is associated with a higher FEV1 and lower odds of STR to ≥1 allergen in Puerto Rican children. This may be explained by the allergen itself or correlated microbial exposures. PMID:22815744

Application of the MNA design method to a nonlinear turbofan engine. [multivariable Nyquist array method

NASA Technical Reports Server (NTRS)

Leininger, G. G.

1981-01-01

Using nonlinear digital simulation as a representative model of the dynamic operation of the QCSEE turbofan engine, a feedback control system is designed by variable frequency design techniques. Transfer functions are generated for each of five power level settings covering the range of operation from approach power to full throttle (62.5% to 100% full power). These transfer functions are then used by an interactive control system design synthesis program to provide a closed loop feedback control using the multivariable Nyquist array and extensions to multivariable Bode diagrams and Nichols charts.

Edmonton obesity staging system among pediatric patients: a validation and obesogenic risk factor analysis.

PubMed

Grammatikopoulou, M G; Chourdakis, M; Gkiouras, K; Roumeli, P; Poulimeneas, D; Apostolidou, E; Chountalas, I; Tirodimos, I; Filippou, O; Papadakou-Lagogianni, S; Dardavessis, T

2018-01-08

The Edmonton Obesity Staging System for Pediatrics (EOSS-P) is a useful tool, delineating different obesity severity tiers associated with distinct treatment barriers. The aim of the study was to apply the EOSS-P on a Greek pediatric cohort and assess risk factors associated with each stage, compared to normal weight controls. A total of 361 children (2-14 years old), outpatients of an Athenian hospital, participated in this case-control study by forming two groups: the obese (n = 203) and the normoweight controls (n = 158). Anthropometry, blood pressure, blood and biochemical markers, comorbidities and obesogenic lifestyle parameters were recorded and the EOSS-P was applied. Validation of EOSS-P stages was conducted by juxtaposing them with IOTF-defined weight status. Obesogenic risk factors' analysis was conducted by constructing gender-and-age-adjusted (GA) and multivariate logistic models. The majority of obese children were stratified at stage 1 (46.0%), 17.0% were on stage 0, and 37.0% on stage 2. The validation analysis revealed that EOSS-P stages greater than 0 were associated with diastolic blood pressure and levels of glucose, cholesterol, LDL and ALT. Reduced obesity odds were observed among children playing outdoors and increased odds for every screen time hour, both in the GA and in the multivariate analyses (all P < 0.05). Although participation in sports > 2 times/week was associated with reduced obesity odds in the GA analysis (OR = 0.57, 95% CI = 0.33-0.98, P linear = 0.047), it lost its significance in the multivariate analysis (P linear = 0.145). Analogous results were recorded in the analyses of the abovementioned physical activity risk factors for the EOSS-P stages. Linear relationships were observed for fast-food consumption and IOTF-defined obesity and higher than 0 EOSS-P stages. Parental obesity status was associated with all EOSS-P stages and IOTF-defined obesity status. Few outpatients were healthy obese (stage 0), while the majority exhibited several comorbidities. Since each obesity tier entails different impacts to disease management, the study herein highlights modifiable factors facilitating descend to lower stages, and provides insight for designing tailored approaches tackling the high national pediatric obesity rates.

VEMAP phase 2 bioclimatic database. I. Gridded historical (20th century) climate for modeling ecosystem dynamics across the conterminous USA

Treesearch

Timothy G.F. Kittel; Nan. A. Rosenbloom; J.A. Royle; C. Daly; W.P. Gibson; H.H. Fisher; P. Thornton; D.N. Yates; S. Aulenbach; C. Kaufman; R. McKeown; Dominque Bachelet; David S. Schimel

2004-01-01

Analysis and simulation of biospheric responses to historical forcing require surface climate data that capture those aspects of climate that control ecological processes, including key spatial gradients and modes of temporal variability. We developed a multivariate, gridded historical climate dataset for the conterminous USA as a common input database for the...

Attitudes and exercise adherence: test of the Theories of Reasoned Action and Planned Behaviour.

PubMed

Smith, R A; Biddle, S J

1999-04-01

Three studies of exercise adherence and attitudes are reported that tested the Theory of Reasoned Action and the Theory of Planned Behaviour. In a prospective study of adherence to a private fitness club, structural equation modelling path analysis showed that attitudinal and social normative components of the Theory of Reasoned Action accounted for 13.1% of the variance in adherence 4 months later, although only social norm significantly predicted intention. In a second study, the Theory of Planned Behaviour was used to predict both physical activity and sedentary behaviour. Path analyses showed that attitude and perceived control, but not social norm, predicted total physical activity. Physical activity was predicted from intentions and control over sedentary behaviour. Finally, an intervention study with previously sedentary adults showed that intentions to be active measured at the start and end of a 10-week intervention were associated with the planned behaviour variables. A multivariate analysis of variance revealed no significant multivariate effects for time on the planned behaviour variables measured before and after intervention. Qualitative data provided evidence that participants had a positive experience on the intervention programme and supported the role of social normative factors in the adherence process.

1H NMR-based metabolic profiling for evaluating poppy seed rancidity and brewing.

PubMed

Jawień, Ewa; Ząbek, Adam; Deja, Stanisław; Łukaszewicz, Marcin; Młynarz, Piotr

2015-12-01

Poppy seeds are widely used in household and commercial confectionery. The aim of this study was to demonstrate the application of metabolic profiling for industrial monitoring of the molecular changes which occur during minced poppy seed rancidity and brewing processes performed on raw seeds. Both forms of poppy seeds were obtained from a confectionery company. Proton nuclear magnetic resonance (1H NMR) was applied as the analytical method of choice together with multivariate statistical data analysis. Metabolic fingerprinting was applied as a bioprocess control tool to monitor rancidity with the trajectory of change and brewing progressions. Low molecular weight compounds were found to be statistically significant biomarkers of these bioprocesses. Changes in concentrations of chemical compounds were explained relative to the biochemical processes and external conditions. The obtained results provide valuable and comprehensive information to gain a better understanding of the biology of rancidity and brewing processes, while demonstrating the potential for applying NMR spectroscopy combined with multivariate data analysis tools for quality control in food industries involved in the processing of oilseeds. This precious and versatile information gives a better understanding of the biology of these processes.

Pre-treatment plasma proteomic markers associated with survival in oesophageal cancer

PubMed Central

Kelly, P; Paulin, F; Lamont, D; Baker, L; Clearly, S; Exon, D; Thompson, A

2012-01-01

Background: The incidence of oesophageal adenocarcinoma is increasing worldwide but survival remains poor. Neoadjuvant chemotherapy can improve survival, but prognostic and predictive biomarkers are required. This study built upon preclinical approaches to identify prognostic plasma proteomic markers in oesophageal cancer. Methods: Plasma samples collected before and during the treatment of oesophageal cancer and non-cancer controls were analysed by surface-enhanced laser desorption/ionisation time-of-flight (SELDI-TOF) mass spectroscopy (MS). Protein peaks were identified by MS in tryptic digests of purified fractions. Associations between peak intensities obtained in the spectra and clinical endpoints (survival, disease-free survival) were tested by univariate (Fisher's exact test) and multivariate analysis (binary logistic regression). Results: Plasma protein peaks were identified that differed significantly (P<0.05, ANOVA) between the oesophageal cancer and control groups at baseline. Three peaks, confirmed as apolipoprotein A-I, serum amyloid A and transthyretin, in baseline (pre-treatment) samples were associated by univariate and multivariate analysis with disease-free survival and overall survival. Conclusion: Plasma proteins can be detected prior to treatment for oesophageal cancer that are associated with outcome and merit testing as prognostic and predictive markers of response to guide chemotherapy in oesophageal cancer. PMID:22294182

Pre-treatment plasma proteomic markers associated with survival in oesophageal cancer.

PubMed

Kelly, P; Paulin, F; Lamont, D; Baker, L; Clearly, S; Exon, D; Thompson, A

2012-02-28

The incidence of oesophageal adenocarcinoma is increasing worldwide but survival remains poor. Neoadjuvant chemotherapy can improve survival, but prognostic and predictive biomarkers are required. This study built upon preclinical approaches to identify prognostic plasma proteomic markers in oesophageal cancer. Plasma samples collected before and during the treatment of oesophageal cancer and non-cancer controls were analysed by surface-enhanced laser desorption/ionisation time-of-flight (SELDI-TOF) mass spectroscopy (MS). Protein peaks were identified by MS in tryptic digests of purified fractions. Associations between peak intensities obtained in the spectra and clinical endpoints (survival, disease-free survival) were tested by univariate (Fisher's exact test) and multivariate analysis (binary logistic regression). Plasma protein peaks were identified that differed significantly (P<0.05, ANOVA) between the oesophageal cancer and control groups at baseline. Three peaks, confirmed as apolipoprotein A-I, serum amyloid A and transthyretin, in baseline (pre-treatment) samples were associated by univariate and multivariate analysis with disease-free survival and overall survival. Plasma proteins can be detected prior to treatment for oesophageal cancer that are associated with outcome and merit testing as prognostic and predictive markers of response to guide chemotherapy in oesophageal cancer.

Identifying pleiotropic genes in genome-wide association studies from related subjects using the linear mixed model and Fisher combination function.

PubMed

Yang, James J; Williams, L Keoki; Buu, Anne

2017-08-24

A multivariate genome-wide association test is proposed for analyzing data on multivariate quantitative phenotypes collected from related subjects. The proposed method is a two-step approach. The first step models the association between the genotype and marginal phenotype using a linear mixed model. The second step uses the correlation between residuals of the linear mixed model to estimate the null distribution of the Fisher combination test statistic. The simulation results show that the proposed method controls the type I error rate and is more powerful than the marginal tests across different population structures (admixed or non-admixed) and relatedness (related or independent). The statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that applying the multivariate association test may facilitate identification of the pleiotropic genes contributing to the risk for alcohol dependence commonly expressed by four correlated phenotypes. This study proposes a multivariate method for identifying pleiotropic genes while adjusting for cryptic relatedness and population structure between subjects. The two-step approach is not only powerful but also computationally efficient even when the number of subjects and the number of phenotypes are both very large.

Gall bladder cancer and the role of dietary and lifestyle factors: a case-control study in a North Indian population.

PubMed

Panda, Dipanjan; Sharma, Atul; Shukla, Nootan K; Jaiswal, Richa; Dwivedi, Sadanand; Raina, Vinod; Mohanti, Bidhu K; Deo, Surya V; Patra, Somdatta

2013-09-01

Most patients with gall bladder cancer (GBC) present in the advanced stage with a poor response to therapy. Prevention or early detection is the best way to prevent death, but this requires identification of susceptible subgroups. Keeping this in mind, this study was carried out to evaluate the association between selected demographic, lifestyle, and dietary factors and GBC. A hospital-based case-control study was carried out at the All India Institute of Medical Sciences (New Delhi, India). Cases were defined as newly registered confirmed primary GBC patients. Controls were defined as healthy relatives of patients other than that of GBC. Data were collected from February 2008 to October 2009 using a semistructured interview schedule from both cases and controls. Analysis was carried out using SPSS version 15 and Epi-Info version 6. Factors found to be significant in the bivariate analysis were entered in a multivariate logistic regression analysis. A total of 122 cases and 122 controls were included in the study. There was no significant difference in age (P=0.06) and sex (P=0.66) between the cases and the controls. In the bivariate analysis, factors found to be significantly associated with GBC were illiteracy [odds ratio (OR) 8.00, P=0.000], lower socioeconomic status (OR 2.45, P=0.000), parity more than 3 (OR 9.06, P=0.000), age at first pregnancy less than 20 years (OR 2.03, P=0.018), and the use of nonliquefied petroleum gas cooking fuel (OR 4.17, P=0.000). Higher vitamin C intake had a protective effect (OR 0.33, P=0.004). In the multivariate analysis, education, intake of vitamin C, parity, and type of fuel used were significant factors. The risk factors for GBC that have been identified in the present study delineate a high-risk population group that can be targeted for preventive measures including improvement in socioeconomic status, education and lifestyle, and dietary intervention, and avoidance of the use of nonliquefied petroleum gas as cooking fuel.

Acoustic neuroma: potential risk factors and audiometric surveillance in the aluminium industry

PubMed Central

Taiwo, Oyebode; Galusha, Deron; Tessier-Sherman, Baylah; Kirsche, Sharon; Cantley, Linda; Slade, Martin D; Cullen, Mark R; Donoghue, A Michael

2014-01-01

Objectives To look for an association between acoustic neuroma (AN) and participation in a hearing conservation programme (HCP) and also for an association between AN and possible occupational risk factors in the aluminium industry. Methods We conducted a case–control analysis of a population of US aluminium production workers in 8 smelters and 43 other plants. Using insurance claims data, 97 cases of AN were identified between 1996 and 2009. Each was matched with four controls. Covariates included participation in a HCP, working in an aluminium smelter, working in an electrical job and hearing loss. Results In the bivariate analyses, covariates associated with AN were participation in the HCP (OR=1.72; 95% CI 1.09 to 2.69) and smelter work (OR=1.88; 95% CI 1.06 to 3.36). Electrical work was not significant (OR=1.60; 95% CI 0.65 to 3.94). Owing to high participation in the HCP in smelters, multivariate subanalyses were required. In the multivariate analyses, participation in the HCP was the only statistically significant risk factor for AN. In the multivariate analysis restricted to employees not working in a smelter, the OR was 1.81 (95% CI 1.04 to 3.17). Hearing loss, an indirect measure of in-ear noise dose, was not predictive of AN. Conclusions Our results suggest the incidental detection of previously undiagnosed tumours in workers who participated in the company-sponsored HCP. The increased medical surveillance among this population of workers most likely introduced detection bias, leading to the identification of AN cases that would have otherwise remained undetected. PMID:25015928

MIDAS, prototype Multivariate Interactive Digital Analysis System for large area earth resources surveys. Volume 1: System description

NASA Technical Reports Server (NTRS)

Christenson, D.; Gordon, M.; Kistler, R.; Kriegler, F.; Lampert, S.; Marshall, R.; Mclaughlin, R.

1977-01-01

A third-generation, fast, low cost, multispectral recognition system (MIDAS) able to keep pace with the large quantity and high rates of data acquisition from large regions with present and projected sensots is described. The program can process a complete ERTS frame in forty seconds and provide a color map of sixteen constituent categories in a few minutes. A principle objective of the MIDAS program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughput. The hardware and software generated in the overall program is described. The system contains a midi-computer to control the various high speed processing elements in the data path, a preprocessor to condition data, and a classifier which implements an all digital prototype multivariate Gaussian maximum likelihood or a Bayesian decision algorithm. Sufficient software was developed to perform signature extraction, control the preprocessor, compute classifier coefficients, control the classifier operation, operate the color display and printer, and diagnose operation.

Using a Grocery List Is Associated With a Healthier Diet and Lower BMI Among Very High-Risk Adults.

PubMed

Dubowitz, Tamara; Cohen, Deborah A; Huang, Christina Y; Beckman, Robin A; Collins, Rebecca L

2015-01-01

Examine whether use of a grocery list is associated with healthier diet and weight among food desert residents. Cross-sectional analysis of in-person interview data from randomly selected household food shoppers in 2 low-income, primarily African American urban neighborhoods in Pittsburgh, PA with limited access to healthy foods. Multivariate ordinary least-square regressions conducted among 1,372 participants and controlling for sociodemographic factors and other potential confounding variables indicated that although most of the sample (78%) was overweight or obese, consistently using a list was associated with lower body mass index (based on measured height and weight) (adjusted multivariant coefficient = 0.095) and higher dietary quality (based on the Healthy Eating Index-2005) (adjusted multivariant coefficient = 0.103) (P < .05). Shopping with a list may be a useful tool for low-income individuals to improve diet or decrease body mass index. Copyright © 2015 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Poor sleep quality has an adverse effect on childhood asthma control and lung function measures.

PubMed

Sheen, Youn Ho; Choi, Sun Hee; Jang, Sun Jung; Baek, Ji Hyeon; Jee, Hye Mi; Kim, Mi Ae; Chae, Kyu Young; Han, Man Yong

2017-08-01

It is unclear as to whether sleep respiratory breathing disorder (SRBD) is a risk factor for uncontrolled asthma in children. The aim of this study was therefore to investigate whether SRBD may have an adverse effect on childhood asthma control and lung function measures. This was a cross-sectional study of 220 children with well-controlled (n = 108), partly controlled (n = 92), and uncontrolled asthma (n = 20) according to the Global Initiative for Asthma guideline. SRBD was assessed using the Pediatric Sleep Questionnaire (PSQ). The association of SRBD with partly controlled/uncontrolled asthma was investigated on multivariate logistic regression analysis. Of 220 children with asthma, 43 (19.6%) had SRBD: well-controlled, 16.7% (18/108); partly controlled, 21.7% (20/92); and uncontrolled, 25.0% (5/20; P = 0.54). There was a significant difference in forced expiratory volume in 1 s/forced vital capacity (FEV 1 /FVC; P = 0.007) and childhood asthma control test (C-ACT) score (P < 0.001) according to asthma control status, but not in PSQ score (P = 0.18). Children with obstructive sleep apnea (PSQ >0.33) had a lower C-ACT score compared with controls (PSQ ≤0.33; 19.6 ± 5.1 vs 22.0 ± 4.2, P = 0.002). PSQ score was negatively correlated with FEV 1 /FVC (r = -0.16, P = 0.02). On multivariate logistic regression analysis, high PSQ score increased the odds of having partly controlled/uncontrolled asthma by 9.12 (95% CI: 1.04-79.72, P = 0.046) after adjusting for confounding factors. SRBD is an independent risk factor for partly controlled/uncontrolled asthma and has an adverse effect on lung function measures in children. Further research is warranted to determine whether the improvement of sleep quality may also enhance level of asthma control and lung function in children. © 2017 Japan Pediatric Society.

Pleiotropy Analysis of Quantitative Traits at Gene Level by Multivariate Functional Linear Models

PubMed Central

Wang, Yifan; Liu, Aiyi; Mills, James L.; Boehnke, Michael; Wilson, Alexander F.; Bailey-Wilson, Joan E.; Xiong, Momiao; Wu, Colin O.; Fan, Ruzong

2015-01-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai–Bartlett trace, Hotelling–Lawley trace, and Wilks’s Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. PMID:25809955

Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.

PubMed

Wang, Yifan; Liu, Aiyi; Mills, James L; Boehnke, Michael; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao; Wu, Colin O; Fan, Ruzong

2015-05-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. © 2015 WILEY PERIODICALS, INC.

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis.

PubMed

Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

2016-07-01

A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness.Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Code is available at https://github.com/aalto-ics-kepaco anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis

PubMed Central

Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J.; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T.; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

2016-01-01

Motivation: A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. Results: We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness. Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Availability and implementation: Code is available at https://github.com/aalto-ics-kepaco Contacts: anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153689

The influence of television and video game use on attention and school problems: a multivariate analysis with other risk factors controlled.

PubMed

Ferguson, Christopher J

2011-06-01

Research on youth mental health has increasingly indicated the importance of multivariate analyses of multiple risk factors for negative outcomes. Television and video game use have often been posited as potential contributors to attention problems, but previous studies have not always been well-controlled or used well-validated outcome measures. The current study examines the multivariate nature of risk factors for attention problems symptomatic of attention deficit hyperactivity disorder and poor school performance. A predominantly Hispanic population of 603 children (ages 10-14) and their parents/guardians responded to multiple behavioral measures. Outcome measures included parent and child reported attention problem behaviors on the Child Behavior Checklist (CBCL) as well as poor school performance as measured by grade point average (GPA). Results found that internal factors such as male gender, antisocial traits, family environment and anxiety best predicted attention problems. School performance was best predicted by family income. Television and video game use, whether total time spent using, or exposure to violent content specifically, did not predict attention problems or GPA. Television and video game use do not appear to be significant predictors of childhood attention problems. Intervention and prevention efforts may be better spent on other risk factors. Copyright © 2010 Elsevier Ltd. All rights reserved.

ABO and Rhesus blood groups and risk of endometriosis in a French Caucasian population of 633 patients living in the same geographic area.

PubMed

Borghese, Bruno; Chartier, Mélanie; Souza, Carlos; Santulli, Pietro; Lafay-Pillet, Marie-Christine; de Ziegler, Dominique; Chapron, Charles

2014-01-01

The identification of epidemiological factors increasing the risk of endometriosis could shorten the time to diagnosis. Specific blood groups may be more common in patients with endometriosis. We designed a cross-sectional study of 633 Caucasian women living in the same geographic area. Study group included 311 patients with histologically proven endometriosis. Control group included 322 patients without endometriosis as checked during surgery. Frequencies of ABO and Rhesus groups in the study and control groups were compared using univariate and multivariate analyses. We observed a higher proportion of Rh-negative women in the study group, as compared to healthy controls. Multivariate analysis showed that Rh-negative women are twice as likely to develop endometriosis (aOR = 1.90; 95% CI: 1.20-2.90). There was no significant difference in ABO group distribution between patients and controls. There was no difference when taking into account either the clinical forms (superficial endometriosis, endometrioma, and deep infiltration endometriosis) or the rAFS stages. Rh-negative women are twice as likely to develop endometriosis. Chromosome 1p, which contains the genes coding for the Rhesus, could also harbor endometriosis susceptibility genes.

[Association between hip fractures and risk factors for osteoporosis. Multivariate analysis].

PubMed

Masoni, Ana; Morosano, Mario; Tomat, María Florencia; Pezzotto, Stella M; Sánchez, Ariel

2007-01-01

In this observational, case-control study, 376 inpatients were evaluated in order to determine the association of risk factors (RF) and hip fracture; 151 patients had osteoporotic hip fracture (cases); the remaining were controls. Data were obtained from medical charts, and through a standardized questionnaire about RF. Mean age of the sample (+/- SD) was 80.6 +/- 8.1 years, without statistically significant difference between cases and controls; the female:male ratio was 3:1 in both groups. Fractured women were older than men (82.5 +/- 8.1 vs. 79.7 +/- 7.2 years, respectively; p < 0.01). Physical activity, intake of alcohol and tobacco, and sun exposure were low in all patients. Falls among cases happened predominantly at home (p < 0.001). Among female cases, time spent in household duties was a RF (p = 0.007), which was absent in males. In multivariate analysis, the following RF were significantly more frequent: Cognitive impairment (p = 0.001), and previous falls (p < 0.0001); whereas the following protective factors were significantly different from controls: Calcium intake during youth (p < 0.0001), current calcium intake (p < 0.0001), and mechanical aid for walking (p < 0.0001). Evaluation of RF and protective factors may contribute to diminish the probability of hip fracture, through a modification of personal habits, and measures to prevent falls among elderly adults. Present information can help to develop local and national population-based strategies to diminish the burden of hip fractures for the health system.

A nested case-control study of predictors for tuberculosis recurrence in a large UK Centre.

PubMed

Rosser, Andrew; Richardson, Matthew; Wiselka, Martin J; Free, Robert C; Woltmann, Gerrit; Mukamolova, Galina V; Pareek, Manish

2018-02-27

Tuberculosis (TB) recurrence represents a challenge to control programs. In low incidence countries, the prevailing risk factors leading to recurrence are poorly characterised. We conducted a nested case-control study using the Leicester TB service TBIT database. Cases were identified from database notifications between 1994 and 2014. Controls had one episode and were matched to cases on a ratio of two to one by the date of notification. Multiple imputation was used to account for missing data. Multivariate conditional logistic regression analysis was employed to identify clinical, sociodemographic and TB specific risk factors for recurrence. From a cohort of 4628 patients, 82 TB recurrences occurred (1.8%). Nineteen of 82 patients had paired isolates with MIRU-VNTR strain type profiles available, of which 84% were relapses and 16% reinfections. On multivariate analysis, smoking (OR 3.8; p = 0.04), grade 3/4 adverse drug reactions (OR 5.6; p = 0.02), ethnicity 'Indian subcontinent' (OR 8.5; p = <0.01), ethnicity 'other' (OR 31.2; p = 0.01) and receipt of immunosuppressants (OR 6.8; p = <0.01) were independent predictors of TB recurrence. Within this UK setting, the rate of TB recurrence was low, predominantly due to relapse. The identification of an elevated recurrence risk amongst the ethnic group contributing most cases to the national TB burden presents an opportunity to improve individual and population health.

Using Interactive Graphics to Teach Multivariate Data Analysis to Psychology Students

ERIC Educational Resources Information Center

Valero-Mora, Pedro M.; Ledesma, Ruben D.

2011-01-01

This paper discusses the use of interactive graphics to teach multivariate data analysis to Psychology students. Three techniques are explored through separate activities: parallel coordinates/boxplots; principal components/exploratory factor analysis; and cluster analysis. With interactive graphics, students may perform important parts of the…

Statistical inferences for data from studies conducted with an aggregated multivariate outcome-dependent sample design.

PubMed

Lu, Tsui-Shan; Longnecker, Matthew P; Zhou, Haibo

2017-03-15

Outcome-dependent sampling (ODS) scheme is a cost-effective sampling scheme where one observes the exposure with a probability that depends on the outcome. The well-known such design is the case-control design for binary response, the case-cohort design for the failure time data, and the general ODS design for a continuous response. While substantial work has been carried out for the univariate response case, statistical inference and design for the ODS with multivariate cases remain under-developed. Motivated by the need in biological studies for taking the advantage of the available responses for subjects in a cluster, we propose a multivariate outcome-dependent sampling (multivariate-ODS) design that is based on a general selection of the continuous responses within a cluster. The proposed inference procedure for the multivariate-ODS design is semiparametric where all the underlying distributions of covariates are modeled nonparametrically using the empirical likelihood methods. We show that the proposed estimator is consistent and developed the asymptotically normality properties. Simulation studies show that the proposed estimator is more efficient than the estimator obtained using only the simple-random-sample portion of the multivariate-ODS or the estimator from a simple random sample with the same sample size. The multivariate-ODS design together with the proposed estimator provides an approach to further improve study efficiency for a given fixed study budget. We illustrate the proposed design and estimator with an analysis of association of polychlorinated biphenyl exposure to hearing loss in children born to the Collaborative Perinatal Study. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Does Investor Ownership of Nursing Homes Compromise the Quality of Care?

PubMed Central

Harrington, Charlene; Woolhandler, Steffie; Mullan, Joseph; Carrillo, Helen; Himmelstein, David U.

2001-01-01

Objectives. Two thirds of nursing homes are investor owned. This study examined whether investor ownership affects quality. Methods. We analyzed 1998 data from state inspections of 13 693 nursing facilities. We used a multivariate model and controlled for case mix, facility characteristics, and location. Results. Investor-owned facilities averaged 5.89 deficiencies per home, 46.5% higher than nonprofit facilities and 43.0% higher than public facilities. In multivariate analysis, investor ownership predicted 0.679 additional deficiencies per home; chain ownership predicted an additional 0.633 deficiencies. Nurse staffing was lower at investor-owned nursing homes. Conclusions. Investor-owned nursing homes provide worse care and less nursing care than do not-for-profit or public homes. PMID:11527781

Multivariable control altitude demonstration on the F100 turbofan engine

NASA Technical Reports Server (NTRS)

Lehtinen, B.; Dehoff, R. L.; Hackney, R. D.

1979-01-01

The F100 Multivariable control synthesis (MVCS) program, was aimed at demonstrating the benefits of LGR synthesis theory in the design of a multivariable engine control system for operation throughout the flight envelope. The advantages of such procedures include: (1) enhanced performance from cross-coupled controls, (2) maximum use of engine variable geometry, and (3) a systematic design procedure that can be applied efficiently to new engine systems. The control system designed, under the MVCS program, for the Pratt & Whitney F100 turbofan engine is described. Basic components of the control include: (1) a reference value generator for deriving a desired equilibrium state and an approximate control vector, (2) a transition model to produce compatible reference point trajectories during gross transients, (3) gain schedules for producing feedback terms appropriate to the flight condition, and (4) integral switching logic to produce acceptable steady-state performance without engine operating limit exceedance.

Efficacy of tolvaptan in patients with refractory ascites in a clinical setting

PubMed Central

Ohki, Takamasa; Sato, Koki; Yamada, Tomoharu; Yamagami, Mari; Ito, Daisaku; Kawanishi, Koki; Kojima, Kentaro; Seki, Michiharu; Toda, Nobuo; Tagawa, Kazumi

2015-01-01

AIM: To elucidate the efficacies of tolvaptan (TLV) as a treatment for refractory ascites compared with conventional treatment. METHODS: We retrospectively enrolled 120 refractory ascites patients between January 1, 2009 and September 31, 2014. Sixty patients were treated with oral TLV at a starting dose of 3.75 mg/d in addition to sodium restriction (> 7 g/d), albumin infusion (10-20 g/wk), and standard diuretic therapy (20-60 mg/d furosemide and 25-50 mg/d spironolactone) and 60 patients with large volume paracentesis in addition to sodium restriction (less than 7 g/d), albumin infusion (10-20 g/wk), and standard diuretic therapy (20-120 mg/d furosemide and 25-150 mg/d spironolactone). Patient demographics and laboratory data, including liver function, were not matched due to the small number of patients. Continuous variables were analyzed by unpaired t-test or paired t-test. Fisher’s exact test was applied in cases comparing two nominal variables. We analyzed factors affecting clinical outcomes using receiver operating characteristic curves and multivariate regression analysis. We also used multivariate Cox’s proportional hazard regression analysis to elucidate the risk factors that contributed to the increased incidence of ascites. RESULTS: TLV was effective in 38 (63.3%) patients. The best cut-off values for urine output and reduced urine osmolality as measures of refractory ascites improvement were > 1800 mL within the first 24 h and > 30%, respectively. Multivariate regression analysis indicated that > 25% reduced urine osmolality [odds ratio (OR) = 20.7; P < 0.01] and positive hepatitis C viral antibodies (OR = 5.93; P = 0.05) were positively correlated with an improvement of refractory ascites, while the total bilirubin level per 1.0 mg/dL (OR = 0.57; P = 0.02) was negatively correlated with improvement. In comparing the TLV group and controls, only the serum sodium level was significantly lower in the TLV group (133 mEq/L vs 136 mEq/L; P = 0.02). However, there were no significant differences in the other parameters between the two groups. The cumulative incidence rate was significantly higher in the control group with a median incidence time of 30 d in the TLV group and 20 d in the control group (P = 0.01). Cox hazard proportional multivariate analysis indicated that the use of TLV (OR = 0.58; P < 0.01), uncontrolled liver neoplasms (OR = 1.92; P < 0.01), total bilirubin level per 1.0 mg/dL (OR = 1.10; P < 0.01), and higher sodium level per 1.0 mEq/L (OR = 0.94; P < 0.01) were independent factors that contributed to incidence. CONCLUSION: Administration of TLV results in better control of refractory ascites and reduced the incidence of additional invasive procedures or hospitalization compared with conventional ascites treatments. PMID:26140088

A power analysis for multivariate tests of temporal trend in species composition.

PubMed

Irvine, Kathryn M; Dinger, Eric C; Sarr, Daniel

2011-10-01

Long-term monitoring programs emphasize power analysis as a tool to determine the sampling effort necessary to effectively document ecologically significant changes in ecosystems. Programs that monitor entire multispecies assemblages require a method for determining the power of multivariate statistical models to detect trend. We provide a method to simulate presence-absence species assemblage data that are consistent with increasing or decreasing directional change in species composition within multiple sites. This step is the foundation for using Monte Carlo methods to approximate the power of any multivariate method for detecting temporal trends. We focus on comparing the power of the Mantel test, permutational multivariate analysis of variance, and constrained analysis of principal coordinates. We find that the power of the various methods we investigate is sensitive to the number of species in the community, univariate species patterns, and the number of sites sampled over time. For increasing directional change scenarios, constrained analysis of principal coordinates was as or more powerful than permutational multivariate analysis of variance, the Mantel test was the least powerful. However, in our investigation of decreasing directional change, the Mantel test was typically as or more powerful than the other models.

Rectal cancer delivery of radiotherapy in adequate time and with adequate dose is influenced by treatment center, treatment schedule, and gender and is prognostic parameter for local control: Results of study CAO/ARO/AIO-94

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fietkau, Rainer; Roedel, Claus; Hohenberger, Werner

2007-03-15

Purpose: The impact of the delivery of radiotherapy (RT) on treatment results in rectal cancer patients is unknown. Methods and Materials: The data from 788 patients with rectal cancer treated within the German CAO/AIO/ARO-94 phase III trial were analyzed concerning the impact of the delivery of RT (adequate RT: minimal radiation RT dose delivered, 4300 cGy for neoadjuvant RT or 4700 cGy for adjuvant RT; completion of RT in <44 days for neoadjuvant RT or <49 days for adjuvant RT) in different centers on the locoregional recurrence rate (LRR) and disease-free survival (DFS) at 5 years. The LRR, DFS, andmore » delivery of RT were analyzed as endpoints in multivariate analysis. Results: A significant difference was found between the centers and the delivery of RT. The overall delivery of RT was a prognostic factor for the LRR (no RT, 29.6% {+-} 7.8%; inadequate RT, 21.2% {+-} 5.6%; adequate RT, 6.8% {+-} 1.4%; p = 0.0001) and DFS (no RT, 55.1% {+-} 9.1%; inadequate RT, 57.4% {+-} 6.3%; adequate RT, 69.1% {+-} 2.3%; p = 0.02). Postoperatively, delivery of RT was a prognostic factor for LRR on multivariate analysis (together with pathologic stage) but not for DFS (independent parameters, pathologic stage and age). Preoperatively, on multivariate analysis, pathologic stage, but not delivery of RT, was an independent prognostic parameter for LRR and DFS (together with adequate chemotherapy). On multivariate analysis, the treatment center, treatment schedule (neoadjuvant vs. adjuvant RT), and gender were prognostic parameters for adequate RT. Conclusion: Delivery of RT should be regarded as a prognostic factor for LRR in rectal cancer and is influenced by the treatment center, treatment schedule, and patient gender.« less

Brain regions with abnormal network properties in severe epilepsy of Lennox-Gastaut phenotype: Multivariate analysis of task-free fMRI.

PubMed

Pedersen, Mangor; Curwood, Evan K; Archer, John S; Abbott, David F; Jackson, Graeme D

2015-11-01

Lennox-Gastaut syndrome, and the similar but less tightly defined Lennox-Gastaut phenotype, describe patients with severe epilepsy, generalized epileptic discharges, and variable intellectual disability. Our previous functional neuroimaging studies suggest that abnormal diffuse association network activity underlies the epileptic discharges of this clinical phenotype. Herein we use a data-driven multivariate approach to determine the spatial changes in local and global networks of patients with severe epilepsy of the Lennox-Gastaut phenotype. We studied 9 adult patients and 14 controls. In 20 min of task-free blood oxygen level-dependent functional magnetic resonance imaging data, two metrics of functional connectivity were studied: Regional homogeneity or local connectivity, a measure of concordance between each voxel to a focal cluster of adjacent voxels; and eigenvector centrality, a global connectivity estimate designed to detect important neural hubs. Multivariate pattern analysis of these data in a machine-learning framework was used to identify spatial features that classified disease subjects. Multivariate pattern analysis was 95.7% accurate in classifying subjects for both local and global connectivity measures (22/23 subjects correctly classified). Maximal discriminating features were the following: increased local connectivity in frontoinsular and intraparietal areas; increased global connectivity in posterior association areas; decreased local connectivity in sensory (visual and auditory) and medial frontal cortices; and decreased global connectivity in the cingulate cortex, striatum, hippocampus, and pons. Using a data-driven analysis method in task-free functional magnetic resonance imaging, we show increased connectivity in critical areas of association cortex and decreased connectivity in primary cortex. This supports previous findings of a critical role for these association cortical regions as a final common pathway in generating the Lennox-Gastaut phenotype. Abnormal function of these areas is likely to be important in explaining the intellectual problems characteristic of this disorder. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.

Fourier Transform Infrared Spectroscopy (FTIR) and Multivariate Analysis for Identification of Different Vegetable Oils Used in Biodiesel Production

PubMed Central

Mueller, Daniela; Ferrão, Marco Flôres; Marder, Luciano; da Costa, Adilson Ben; de Cássia de Souza Schneider, Rosana

2013-01-01

The main objective of this study was to use infrared spectroscopy to identify vegetable oils used as raw material for biodiesel production and apply multivariate analysis to the data. Six different vegetable oil sources—canola, cotton, corn, palm, sunflower and soybeans—were used to produce biodiesel batches. The spectra were acquired by Fourier transform infrared spectroscopy using a universal attenuated total reflectance sensor (FTIR-UATR). For the multivariate analysis principal component analysis (PCA), hierarchical cluster analysis (HCA), interval principal component analysis (iPCA) and soft independent modeling of class analogy (SIMCA) were used. The results indicate that is possible to develop a methodology to identify vegetable oils used as raw material in the production of biodiesel by FTIR-UATR applying multivariate analysis. It was also observed that the iPCA found the best spectral range for separation of biodiesel batches using FTIR-UATR data, and with this result, the SIMCA method classified 100% of the soybean biodiesel samples. PMID:23539030

Multivariate meta-analysis for non-linear and other multi-parameter associations

PubMed Central

Gasparrini, A; Armstrong, B; Kenward, M G

2012-01-01

In this paper, we formalize the application of multivariate meta-analysis and meta-regression to synthesize estimates of multi-parameter associations obtained from different studies. This modelling approach extends the standard two-stage analysis used to combine results across different sub-groups or populations. The most straightforward application is for the meta-analysis of non-linear relationships, described for example by regression coefficients of splines or other functions, but the methodology easily generalizes to any setting where complex associations are described by multiple correlated parameters. The modelling framework of multivariate meta-analysis is implemented in the package mvmeta within the statistical environment R. As an illustrative example, we propose a two-stage analysis for investigating the non-linear exposure–response relationship between temperature and non-accidental mortality using time-series data from multiple cities. Multivariate meta-analysis represents a useful analytical tool for studying complex associations through a two-stage procedure. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22807043

B-cell subset alterations and correlated factors in HIV-1 infection.

PubMed

Pensieroso, Simone; Galli, Laura; Nozza, Silvia; Ruffin, Nicolas; Castagna, Antonella; Tambussi, Giuseppe; Hejdeman, Bo; Misciagna, Donatella; Riva, Agostino; Malnati, Mauro; Chiodi, Francesca; Scarlatti, Gabriella

2013-05-15

During HIV-1 infection, the development, phenotype, and functionality of B cells are impaired. Transitional B cells and aberrant B-cell populations arise in blood, whereas a declined percentage of resting memory B cells is detected. Our study aimed at pinpointing the demographic, immunological, and viral factors driving these pathological findings, and the role of antiretroviral therapy in reverting these alterations. B-cell phenotype and correlating factors were evaluated. Variations in B-cell subsets were evaluated by flow cytometry in HIV-1-infected individuals naive to therapy, elite controllers, and patients treated with antiretroviral drugs (virological control or failure). Multivariable analysis was performed to identify variables independently associated with the B-cell alterations. Significant differences were observed among patients' groups in relation to all B-cell subsets. Resting memory B cells were preserved in patients naive to therapy and elite controllers, but reduced in treated patients. Individuals naive to therapy and experiencing multidrug failure, as well as elite controllers, had significantly higher levels of activated memory B cells compared to healthy controls. In the multivariate analysis, plasma viral load and nadir CD4 T cells independently correlated with major B-cell alterations. Coinfection with hepatitis C but not hepatitis B virus also showed an impact on specific B-cell subsets. Successful protracted antiretroviral treatment led to normalization of all B-cell subsets with exception of resting memory B cells. Our results indicate that viremia and nadir CD4 T cells are important prognostic markers of B-cell perturbations and provide evidence that resting memory B-cell depletion during chronic infection is not reverted upon successful antiretroviral therapy.

Upper esophageal sphincter (UES) metrics on high-resolution manometry (HRM) differentiate achalasia subtypes.

PubMed

Blais, P; Patel, A; Sayuk, G S; Gyawali, C P

2017-12-01

The upper esophageal sphincter (UES) reflexively responds to bolus presence within the esophageal lumen, therefore UES metrics can vary in achalasia. Within consecutive patients undergoing esophageal high-resolution manometry (HRM), 302 patients (58.2±1.0 year, 57% F) with esophageal outflow obstruction were identified, and compared to 16 asymptomatic controls (27.7±0.7 year, 56% F). Esophageal outflow obstruction was segregated into achalasia subtypes 1, 2, and 3, and esophagogastric junction outflow obstruction (EGJOO with intact peristalsis) using Chicago Classification v3.0. UES and lower esophageal sphincter (LES) metrics were compared between esophageal outflow obstruction and normal controls using univariate and multivariate analysis. Linear regression excluded multicollinearity of pressure metrics that demonstrated significant differences across individual subtype comparisons. LES integrated relaxation pressure (IRP) had utility in differentiating achalasia from controls (P<.0001), but no utility in segregating between subtypes (P=.27). In comparison to controls, patients collectively demonstrated univariate differences in UES mean basal pressure, relaxation time to nadir, recovery time, and residual pressure (UES-RP) (P≤.049). UES-RP was highest in type 2 achalasia (P<.0001 compared to other subtypes and controls). In multivariate analysis, only UES-RP retained significance in comparison between each of the subgroups (P≤.02 for each comparison). Intrabolus pressure was highest in type 3 achalasia; this demonstrated significant differences across some but not all subtype comparisons. Nadir UES-RP can differentiate achalasia subtypes within the esophageal outflow obstruction spectrum, with highest values in type 2 achalasia. This metric likely represents a surrogate marker for esophageal pressurization. © 2017 John Wiley & Sons Ltd.

Effect of Play-based Therapy on Meta-cognitive and Behavioral Aspects of Executive Function: A Randomized, Controlled, Clinical Trial on the Students With Learning Disabilities.

PubMed

Karamali Esmaili, Samaneh; Shafaroodi, Narges; Hassani Mehraban, Afsoon; Parand, Akram; Zarei, Masoume; Akbari-Zardkhaneh, Saeed

2017-01-01

Although the effect of educational methods on executive function (EF) is well known, training this function by a playful method is debatable. The current study aimed at investigating if a play-based intervention is effective on metacognitive and behavioral skills of EF in students with specific learning disabilities. In the current randomized, clinical trial, 49 subjects within the age range of 7 to 11 years with specific learning disabilities were randomly assigned into the intervention (25 subjects; mean age 8.5±1.33 years) and control (24 subjects; mean age 8.7±1.03 years) groups. Subjects in the intervention group received EF group training based on playing activities; subjects in the control group received no intervention. The behavior rating inventory of executive function (BRIEF) was administered to evaluate the behavioral and cognitive aspects of EF. The duration of the intervention was 6 hours per week for 9 weeks. Multivariate analysis of covariance was used to compare mean changes (before and after) in the BRIEF scores between the groups. The assumptions of multivariate analysis of covariance were examined. After controlling pre-test conditions, the intervention and control groups scored significantly differently on both the metacognition (P=0.002; effect size=0.20) and behavior regulation indices (P=0.01; effect size=0.12) of BRIEF. Play-based therapy is effective on the metacognitive and behavioral aspects of EF in students with specific learning disabilities. Professionals can use play-based therapy rather than educational approaches in clinical practice to enhance EF skills.

Analysis and control of the METC fluid bed gasifier. Final report (includes technical progress report for October 1994--January 1995), September 1994--September 1996

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1996-09-01

This document presents a modeling and control study of the Fluid Bed Gasification (FBG) unit at the Morgantown Energy Technology Center (METC). The work is performed under contract no. DE-FG21-94MC31384. The purpose of this study is to generate a simple FBG model from process data, and then use the model to suggest an improved control scheme which will improve operation of the gasifier. The work first developes a simple linear model of the gasifier, then suggests an improved gasifier pressure and MGCR control configuration, and finally suggests the use of a multivariable control strategy for the gasifier.

Digital controllers for VTOL aircraft

NASA Technical Reports Server (NTRS)

Stengel, R. F.; Broussard, J. R.; Berry, P. W.

1976-01-01

Using linear-optimal estimation and control techniques, digital-adaptive control laws have been designed for a tandem-rotor helicopter which is equipped for fully automatic flight in terminal area operations. Two distinct discrete-time control laws are designed to interface with velocity-command and attitude-command guidance logic, and each incorporates proportional-integral compensation for non-zero-set-point regulation, as well as reduced-order Kalman filters for sensor blending and noise rejection. Adaptation to flight condition is achieved with a novel gain-scheduling method based on correlation and regression analysis. The linear-optimal design approach is found to be a valuable tool in the development of practical multivariable control laws for vehicles which evidence significant coupling and insufficient natural stability.

Stereotactic radiosurgery of World Health Organization grade II and III intracranial meningiomas: treatment results on the basis of a 22-year experience.

PubMed

Pollock, Bruce E; Stafford, Scott L; Link, Michael J; Garces, Yolanda I; Foote, Robert L

2012-02-15

A study was undertaken to define the variables associated with tumor control and survival after single-session stereotactic radiosurgery (SRS) for patients with atypical and malignant intracranial meningiomas. Fifty patients with World Health Organization (WHO) grade II (n = 37) or grade III (n = 13) meningiomas underwent SRS from 1990 to 2008. Most tumors were located in the falx/parasagittal region or cerebral convexities (n = 35, 70%). Twenty patients (40%) had progressing tumors despite prior external beam radiation therapy (EBRT) (median dose, 54.0 grays [Gy]). The median treatment volume was 14.6 cm(3) ; the median tumor margin dose was 15.0 Gy. Seven patients (14%) received concurrent EBRT (median dose, 50.4 Gy). Follow-up (median, 38 months) was censored at last evaluation (n = 28) or death (n = 22). Tumor grade correlated with disease-specific survival (DSS) (hazard ratio [HR], 3.4; P = .008), local tumor control (HR, 2.4; P = .02), and progression-free survival (PFS) (HR, 2.6; P = .02) on univariate analysis, but not on multivariate analysis. Multivariate analysis showed that having failed EBRT and tumor volume >14.6 cm(3) were negative predictors of DSS and local control (HR, 3.0; P = .02 and HR, 4.4; P = .01; HR, 3.3; P = .001 and HR, 2.3; P = .02;, respectively). Having failed EBRT was a negative predictor of PFS (HR, 3.5; P = .002). Thirteen patients (26%) had radiation-related complications at a median of 6 months after radiosurgery. Tumor progression despite prior EBRT and larger tumor volume are negative predictors of tumor control and survival for patients having SRS for WHO grade II and III intracranial meningiomas. Copyright © 2011 American Cancer Society.

Association between control to target blood pressures and healthy lifestyle factors among Japanese hypertensive patients: longitudinal data analysis from Fukushima Research of Hypertension (FRESH).

PubMed

Yokokawa, Hirohide; Goto, Aya; Sanada, Hironobu; Watanabe, Tsuyoshi; Felder, Robin A; Jose, Pedro A; Yasumura, Seiji

2014-01-01

To determine success rates in controlling target blood pressures longitudinally by measuring several factors, including lifestyle characteristics associated with uncontrolled blood pressures for target treatment goals. This prospective observational cohort study (September 2008-September 2010) collected information on blood pressure control status and healthy lifestyle factors listed in Breslow's seven health practices through medical records and self-administered questionnaires from 884 of the 1264 Japanese hypertensive patients initially registered in the FRESH study. Multivariate analysis adjusted for associated factors was performed to estimate the association between lifestyle change and "uncontrolled blood pressures" at the final follow-up survey. Median age and proportion of men were 73 years and 39.1%, respectively. All survey failure rates were 37.6% among non-elderly patients (<65 years of age) without diabetes mellitus or chronic kidney disease, and 35.0% among patients with these diseases or myocardial infarction. Maintaining a healthy lifestyle was a protective factor against uncontrolled blood pressures in multivariate analysis. Obesity and smoking status were associated with uncontrolled blood pressures, and exercise frequency was borderline significance. The number of participants with healthy responses for these factors remained relatively low during follow up. Our study revealed low rates of controlled blood pressures, especially in non-elderly patients without diabetes mellitus or chronic kidney disease, and patients with these diseases or myocardial infarction. Our data indicate the need to maintain a healthy lifestyle, in particular, ideal body weight and adequate exercise frequency, for better hypertension management according to treatment guidelines. Copyright © 2013 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

The effects of age and gender on the relationship between HMGCR promoter-911 SNP (rs33761740) and serum lipids in patients with coronary heart disease.

PubMed

Akadam-Teker, Basak; Kurnaz, Ozlem; Coskunpinar, Ender; Daglar-Aday, Aynur; Kucukhuseyin, Ozlem; Cakmak, Huseyin Altug; Teker, Erhan; Bugra, Zehra; Ozturk, Oguz; Yilmaz-Aydogan, Hulya

2013-10-10

Hydroxymethylglutaryl-Coenzyme A Reductase (HMGCR) catalyzes the rate-limiting step of cholesterol biosynthesis. This enzyme is the target of the widely available cholesterol lowering statins. In this population-based case-control study, the frequencies of -911 C>A polymorphism (rs3761740) of the HMGCR gene in patients with coronary heart disease (CHD) and healthy subjects were investigated and the correlations between the different genotypes and hypercholesterolemia with cardiovascular risk factors were analyzed. The HMGCR genotypes were determined in 365 patients with CHD and 365 controls by PCR-RFLP assay. Anthropometric measurements were measured in all participants. There was no significant difference in the genotype frequencies of the HMGCR polymorphism between the male subjects of both patient and control groups, however, the HMGCR-CC genotype was found to be more frequent in female patients with CHD than female controls (p=0.002). The HMGCR-CC genotype showed higher total-cholesterol (TC) and LDL-cholesterol (LDL-C) levels than the CA+AA genotypes in male CHD patients (p=0.018). Due to this significant sex interaction, a multivariate analysis was conducted on the patient group. In the multivariate logistic regression analysis, the HMGCR-CC genotype was significantly associated with age<55 (OR=2.837, p=0.001) and TC ≥ 5.18 mmol/L (OR=1.970, p=0.027) in male subjects. However, this association was not observed in female patients (p>0.05). This analysis confirmed that the HMGCR-CC genotype was associated with elevated TC levels in male CHD patients with age<55 years. These results suggest that age and sex modify the contribution of the HMGCR-911 polymorphism to fasting serum TC, LDL-C levels and risk of CHD. © 2013.

The Potential of Multivariate Analysis in Assessing Students' Attitude to Curriculum Subjects

ERIC Educational Resources Information Center

Gaotlhobogwe, Michael; Laugharne, Janet; Durance, Isabelle

2011-01-01

Background: Understanding student attitudes to curriculum subjects is central to providing evidence-based options to policy makers in education. Purpose: We illustrate how quantitative approaches used in the social sciences and based on multivariate analysis (categorical Principal Components Analysis, Clustering Analysis and General Linear…

A multivariate pattern analysis study of the HIV-related white matter anatomical structural connections alterations

NASA Astrophysics Data System (ADS)

Tang, Zhenchao; Liu, Zhenyu; Li, Ruili; Cui, Xinwei; Li, Hongjun; Dong, Enqing; Tian, Jie

2017-03-01

It's widely known that HIV infection would cause white matter integrity impairments. Nevertheless, it is still unclear that how the white matter anatomical structural connections are affected by HIV infection. In the current study, we employed a multivariate pattern analysis to explore the HIV-related white matter connections alterations. Forty antiretroviraltherapy- naïve HIV patients and thirty healthy controls were enrolled. Firstly, an Automatic Anatomical Label (AAL) atlas based white matter structural network, a 90 × 90 FA-weighted matrix, was constructed for each subject. Then, the white matter connections deprived from the structural network were entered into a lasso-logistic regression model to perform HIV-control group classification. Using leave one out cross validation, a classification accuracy (ACC) of 90% (P=0.002) and areas under the receiver operating characteristic curve (AUC) of 0.96 was obtained by the classification model. This result indicated that the white matter anatomical structural connections contributed greatly to HIV-control group classification, providing solid evidence that the white matter connections were affected by HIV infection. Specially, 11 white matter connections were selected in the classification model, mainly crossing the regions of frontal lobe, Cingulum, Hippocampus, and Thalamus, which were reported to be damaged in previous HIV studies. This might suggest that the white matter connections adjacent to the HIV-related impaired regions were prone to be damaged.

Maternal Dietary Nutrient Intake and Its Association  with Preterm Birth: A Case-control Study in Beijing,  China.

PubMed

Zhang, Yan; Zhou, Hong; Perkins, Anthony; Wang, Yan; Sun, Jing

2017-03-01

This study aimed to evaluate dietary nutrient intake among Chinese pregnant women by comparison with Chinese Dietary Reference Intakes (DRIs) and to explore the association between dietary nutrients and preterm birth. A case-control design was conducted in Beijing with 130 preterm delivery mothers in case group and 381 term delivery mothers in control group. Information on mothers' diet was collected using a food frequency questionnaire, and nutrients and energy intakes were subsequently calculated based on DRIs. Multivariate analysis of variance was used to compare the differences between term and preterm groups in relation to dietary nutrients. Dietary nutrient intakes were imbalanced in both groups compared with Chinese DRIs. Preterm delivery mothers had a lower level of fat and vitamin E intake than term delivery mothers (p < 0.05). Multivariate analysis showed lower vitamin E intake in preterm delivery mothers with a prepregnancy BMI < 18.5 kg/m2 (p < 0.05) and higher carbohydrate intake in preterm delivery mothers with prepregnancy BMI ≥ 24 kg/m2 (p < 0.05). An imbalanced diet in both groups and low level of dietary intakes of fat and vitamin E in preterm group suggest health education measures should be taken to improve the dietary quality of pregnant women, especially for those with an abnormal prepregnancy BMI.

Development of upper tract stones in patients with congenital neurogenic bladder.

PubMed

Stephany, Heidi A; Clayton, Douglass B; Tanaka, Stacy T; Thomas, John C; Pope, John C; Brock, John W; Adams, Mark C

2014-02-01

Patients with neurogenic bladder are at increased risk of developing upper tract stones. We hypothesized that patients with lower urinary tract stone disease are at greater risk of developing upper tract stones. We performed a 10-year retrospective case-control study of patients with neurogenic bladder to determine the association between bladder and upper tract stones. Independent risk factors for upper tract stones were assessed. Cases and controls were matched 1:1. Univariable analysis was performed by Fisher's exact test and the Mann-Whitney U test. Multivariable logistic regression was performed. 52 cases and controls were identified. Cases were significantly more likely to be non-ambulatory, have bowel-urinary tract interposition, thoracic level dysraphism, and history of bladder stones. On multivariable analysis, independent predictors of stone formation were male sex (OR 2.82; p = 0.02), dysraphism involving the thoracic spine (OR 3.37; p = 0.014) bowel-urinary tract interposition (OR 2.611; p = 0.038), and a history of bladder stones (OR 3.57; p = 0.015). Patients with neurogenic bladder are at increased risk for upper tract stones. The presence of bladder stones may herald the development of upper tract stones. The predictors of stone disease identified should guide prospective studies to better understand the natural history of upper tract stone development in this population. Copyright © 2013 Journal of Pediatric Urology Company. Published by Elsevier Ltd. All rights reserved.

Multivariate Analysis of the Cotton Seed Ionome Reveals a Shared Genetic Architecture

PubMed Central

Pauli, Duke; Ziegler, Greg; Ren, Min; Jenks, Matthew A.; Hunsaker, Douglas J.; Zhang, Min; Baxter, Ivan; Gore, Michael A.

2018-01-01

To mitigate the effects of heat and drought stress, a better understanding of the genetic control of physiological responses to these environmental conditions is needed. To this end, we evaluated an upland cotton (Gossypium hirsutum L.) mapping population under water-limited and well-watered conditions in a hot, arid environment. The elemental concentrations (ionome) of seed samples from the population were profiled in addition to those of soil samples taken from throughout the field site to better model environmental variation. The elements profiled in seeds exhibited moderate to high heritabilities, as well as strong phenotypic and genotypic correlations between elements that were not altered by the imposed irrigation regimes. Quantitative trait loci (QTL) mapping results from a Bayesian classification method identified multiple genomic regions where QTL for individual elements colocalized, suggesting that genetic control of the ionome is highly interrelated. To more fully explore this genetic architecture, multivariate QTL mapping was implemented among groups of biochemically related elements. This analysis revealed both additional and pleiotropic QTL responsible for coordinated control of phenotypic variation for elemental accumulation. Machine learning algorithms that utilized only ionomic data predicted the irrigation regime under which genotypes were evaluated with very high accuracy. Taken together, these results demonstrate the extent to which the seed ionome is genetically interrelated and predictive of plant physiological responses to adverse environmental conditions. PMID:29437829

Two-sample tests and one-way MANOVA for multivariate biomarker data with nondetects.

PubMed

Thulin, M

2016-09-10

Testing whether the mean vector of a multivariate set of biomarkers differs between several populations is an increasingly common problem in medical research. Biomarker data is often left censored because some measurements fall below the laboratory's detection limit. We investigate how such censoring affects multivariate two-sample and one-way multivariate analysis of variance tests. Type I error rates, power and robustness to increasing censoring are studied, under both normality and non-normality. Parametric tests are found to perform better than non-parametric alternatives, indicating that the current recommendations for analysis of censored multivariate data may have to be revised. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A non-iterative extension of the multivariate random effects meta-analysis.

PubMed

Makambi, Kepher H; Seung, Hyunuk

2015-01-01

Multivariate methods in meta-analysis are becoming popular and more accepted in biomedical research despite computational issues in some of the techniques. A number of approaches, both iterative and non-iterative, have been proposed including the multivariate DerSimonian and Laird method by Jackson et al. (2010), which is non-iterative. In this study, we propose an extension of the method by Hartung and Makambi (2002) and Makambi (2001) to multivariate situations. A comparison of the bias and mean square error from a simulation study indicates that, in some circumstances, the proposed approach perform better than the multivariate DerSimonian-Laird approach. An example is presented to demonstrate the application of the proposed approach.

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden” Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method. PMID:20454705

A refined method for multivariate meta-analysis and meta-regression.

PubMed

Jackson, Daniel; Riley, Richard D

2014-02-20

Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing and deriving a confidence interval for the average effect. We have found that a refined method for univariate meta-analysis, which applies a scaling factor to the estimated effects' standard error, provides more accurate inference. We explain how to extend this method to the multivariate scenario and show that our proposal for refined multivariate meta-analysis and meta-regression can provide more accurate inferences than the more conventional approach. We explain how our proposed approach can be implemented using standard output from multivariate meta-analysis software packages and apply our methodology to two real examples. Copyright © 2013 John Wiley & Sons, Ltd.

Information on co-morbidities collected by history is useful for assigning Otitis Media risk to children.

PubMed

Casselbrant, Margaretha L; Mandel, Ellen M; Doyle, William J

2016-06-01

Determine if a 2-Step multivariate analysis of historical symptom/sign data for comorbid diseases can abstract high-level constructs useful in assigning a child's "risk" for different Otitis Media expressions. Seventeen items related to the symptom/sign expression of hypothesized Otitis Media comorbidities were collected by history on 141 3-year-old children. Using established criteria, the children were assigned to 1 of 3 groups: Control (no significant past Otitis Media, n=45), Chronic Otitis Media with Effusion (n=45) and Recurrent Acute Otitis Media (n=51). Principal Component Analysis was used to identify factors representing the non-redundant shared information among related items and Discriminant Analysis operating on those factors was used to estimate the best predictor equation for pairwise group assignments. Six multivariate factors representing the assignable comorbidities of frequent colds, nasal allergy, gastroesophageal disease (specific and general), nasal congestion and asthma were identified and explained 81% of the variance in the 17 items. Discriminant Analysis showed that, for the Control-Chronic Otitis Media with Effusion comparison, a combination of 3 factors and, for the Control-Recurrent Acute Otitis Media comparison, a combination of 2 factors had assignment accuracies of 74% and 68%, respectively. For the contrast between the two disease expressions, a 2-factor combination had an assignment accuracy of 61%. These results show that this analytic methodology can abstract high-level constructs, comorbidities, from low-level data, symptom/sign scores, support a linkage between certain comorbidities and Otitis Media risk and suggest that specific comorbidity combinations contain information relevant to assigning the risk for different Otitis Media expressions. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A modified case-control study of cryptosporidiosis (using non-Cryptosporidium-infected enteric cases as controls) in a community setting.

PubMed

Pintar, K D M; Pollari, F; Waltner-Toews, D; Charron, D F; McEwen, S A; Fazil, A; Nesbitt, A

2009-12-01

Data from the first sentinel site (Waterloo Region, Ontario) of the Canadian Integrated Enteric Disease Surveillance System (C-EnterNet) were used in a secondary-based case-control study of laboratory-confirmed Cryptosporidium infections to study the role of various exposure factors. The incidence of cryptosporidiosis in Waterloo Region was almost double both the provincial and national rates. Persons ill with one of nine other enteric infections (amoebiasis, campylobacteriosis, cyclosporiasis, giardiasis, listeriosis, salmonellosis, shigellosis, verotoxigenic E. coli infections, yersiniosis) captured by the surveillance system were used as the control group. Of 1204 cases of enteric illness in the sentinel area between April 2005 and December 2007, 36 cases and 803 controls were selected after excluding outbreak and international travel-related cases. Univariable analyses (Pearson chi2 and Fisher's exact tests) and multivariable logistic regression were performed. Results of the multivariable analysis found that cryptosporidiosis was associated with swimming in a lake or river (OR 2.9, 95% CI 1.2-7.4), drinking municipal water (a potential surrogate for urban respondents vs. rural) (OR 2.4, 95% CI 1.04-5.7), and having a family member with a diarrhoeal illness (OR 2.9, 95% CI 1.3-6.4).

Modeling in the quality by design environment: Regulatory requirements and recommendations for design space and control strategy appointment.

PubMed

Djuris, Jelena; Djuric, Zorica

2017-11-30

Mathematical models can be used as an integral part of the quality by design (QbD) concept throughout the product lifecycle for variety of purposes, including appointment of the design space and control strategy, continual improvement and risk assessment. Examples of different mathematical modeling techniques (mechanistic, empirical and hybrid) in the pharmaceutical development and process monitoring or control are provided in the presented review. In the QbD context, mathematical models are predominantly used to support design space and/or control strategies. Considering their impact to the final product quality, models can be divided into the following categories: high, medium and low impact models. Although there are regulatory guidelines on the topic of modeling applications, review of QbD-based submission containing modeling elements revealed concerns regarding the scale-dependency of design spaces and verification of models predictions at commercial scale of manufacturing, especially regarding real-time release (RTR) models. Authors provide critical overview on the good modeling practices and introduce concepts of multiple-unit, adaptive and dynamic design space, multivariate specifications and methods for process uncertainty analysis. RTR specification with mathematical model and different approaches to multivariate statistical process control supporting process analytical technologies are also presented. Copyright © 2017 Elsevier B.V. All rights reserved.

Identifying the hydrochemical characteristics of rivers and groundwater by multivariate statistical analysis in the Sanjiang Plain, China

NASA Astrophysics Data System (ADS)

Cao, Yingjie; Tang, Changyuan; Song, Xianfang; Liu, Changming; Zhang, Yinghua

2016-06-01

Two multivariate statistical technologies, factor analysis (FA) and discriminant analysis (DA), are applied to study the river and groundwater hydrochemistry and its controlling processes in the Sanjiang Plain of the northeast China. Factor analysis identifies five factors which account for 79.65 % of the total variance in the dataset. Four factors bearing specific meanings as the river and groundwater hydrochemistry controlling processes are divided into two groups, the "natural hydrochemistry evolution" group and the "pollution" group. The "natural hydrochemistry evolution" group includes the salinity factor (factor 1) caused by rock weathering and the residence time factor (factor 2) reflecting the groundwater traveling time. The "pollution" group represents the groundwater quality deterioration due to geogenic pollution caused by elevated Fe and Mn (factor 3) and elevated nitrate (NO3 -) introduced by human activities such as agriculture exploitations (factor 5). The hydrochemical difference and hydraulic connection among rivers (surface water, SW), shallow groundwater (SG) and deep groundwater (DG) group are evaluated by the factor scores obtained from FA and DA (Fisher's method). It is showed that the river water is characterized as low salinity and slight pollution, and the shallow groundwater has the highest salinity and severe pollution. The SW is well separated from SG and DG by Fisher's discriminant function, but the SG and DG can not be well separated showing their hydrochemical similarities, and emphasize hydraulic connections between SG and DG.

Radiotherapy for T1-2N0 glottic cancer: a multivariate analysis of predictive factors for the long-term outcome in 1050 patients and a prospective assessment of quality of life and voice handicap index in a subset of 233 patients.

PubMed

Al-Mamgani, A; van Rooij, P H; Woutersen, D P; Mehilal, R; Tans, L; Monserez, D; Baatenburg de Jong, R J

2013-08-01

To evaluate the outcomes of patients with early stage glottic cancer (GC) treated with radiotherapy (RT). The current study report on a retrospective analysis of oncologic outcome of 1050 patients with T1-2N0 glottic cancer treated with radiotherapy. Prospective assessment of quality of life (QoL) and voice handicap index (VHI) was performed in all patients treated from 2006 onwards (n = 233). Local control (LC), regional control (RC), disease-free survival (DFS), overall survival (OS), quality of life and voice handicap index. After a median follow-up of 90 months (range 3-309), the actuarial rates of local control, regional control, disease-free survival and overall survival were 85%, 99%, 84% and 81% at 5 years and 82%, 98%, 80% and 61% at 10 years, respectively. On multivariate analysis, T2 tumours, smoking after radiotherapy and conventional radiation scheme correlated significantly with poor local control. Patients who continued smoking after radiotherapy had also significantly lower overall survival rates (OR 4.3, P < 0.001). Hypothyroidism was reported in 18% of patients. Slight and temporary deterioration of quality of life scores was reported. Patient-reported xerostomia and dysphagia at 48 months were -7.1 and -6.5, compared with baseline, respectively. Voice handicap index improved significantly from 37 at baseline to 18 at 48 months. Patients with T2b and those who continued smoking had significantly worse voice handicap index. In the current study, excellent outcome with good quality of life and voice handicap index scores were reported. T2 tumours, in particular T2b, and continuing smoking after radiotherapy correlated significantly with poor local control and worse voice handicap index. © 2013 John Wiley & Sons Ltd.

Multivariate missing data in hydrology - Review and applications

NASA Astrophysics Data System (ADS)

Ben Aissia, Mohamed-Aymen; Chebana, Fateh; Ouarda, Taha B. M. J.

2017-12-01

Water resources planning and management require complete data sets of a number of hydrological variables, such as flood peaks and volumes. However, hydrologists are often faced with the problem of missing data (MD) in hydrological databases. Several methods are used to deal with the imputation of MD. During the last decade, multivariate approaches have gained popularity in the field of hydrology, especially in hydrological frequency analysis (HFA). However, treating the MD remains neglected in the multivariate HFA literature whereas the focus has been mainly on the modeling component. For a complete analysis and in order to optimize the use of data, MD should also be treated in the multivariate setting prior to modeling and inference. Imputation of MD in the multivariate hydrological framework can have direct implications on the quality of the estimation. Indeed, the dependence between the series represents important additional information that can be included in the imputation process. The objective of the present paper is to highlight the importance of treating MD in multivariate hydrological frequency analysis by reviewing and applying multivariate imputation methods and by comparing univariate and multivariate imputation methods. An application is carried out for multiple flood attributes on three sites in order to evaluate the performance of the different methods based on the leave-one-out procedure. The results indicate that, the performance of imputation methods can be improved by adopting the multivariate setting, compared to mean substitution and interpolation methods, especially when using the copula-based approach.

Development of Pattern Recognition Techniques for the Evaluation of Toxicant Impacts to Multispecies Systems

DTIC Science & Technology

1993-06-18

the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and clustering methods...rule rather than the exception. In the Standardized Aquatic Microcosm and the Mixed Flask Culture (MFC) microcosms, multivariate analysis and...experiments using two microcosm protocols. We use nonmetric clustering, a multivariate pattern recognition technique developed by Matthews and Heame (1991

Determinants of elevated healthcare utilization in patients with COPD.

PubMed

Simon-Tuval, Tzahit; Scharf, Steven M; Maimon, Nimrod; Bernhard-Scharf, Barbara J; Reuveni, Haim; Tarasiuk, Ariel

2011-01-13

Chronic obstructive pulmonary disease (COPD) imparts a substantial economic burden on western health systems. Our objective was to analyze the determinants of elevated healthcare utilization among patients with COPD in a single-payer health system. Three-hundred eighty-nine adults with COPD were matched 1:3 to controls by age, gender and area of residency. Total healthcare cost 5 years prior recruitment and presence of comorbidities were obtained from a computerized database. Health related quality of life (HRQoL) indices were obtained using validated questionnaires among a subsample of 177 patients. Healthcare utilization was 3.4-fold higher among COPD patients compared with controls (p < 0.001). The "most-costly" upper 25% of COPD patients (n = 98) consumed 63% of all costs. Multivariate analysis revealed that independent determinants of being in the "most costly" group were (OR; 95% CI): age-adjusted Charlson Comorbidity Index (1.09; 1.01-1.2), history of: myocardial infarct (2.87; 1.5-5.5), congestive heart failure (3.52; 1.9-6.4), mild liver disease (3.83; 1.3-11.2) and diabetes (2.02; 1.1-3.6). Bivariate analysis revealed that cost increased as HRQoL declined and severity of airflow obstruction increased but these were not independent determinants in a multivariate analysis. Comorbidity burden determines elevated utilization for COPD patients. Decision makers should prioritize scarce health care resources to a better care management of the "most costly" patients.

The impact of multiple endpoint dependency on Q and I(2) in meta-analysis.

PubMed

Thompson, Christopher Glen; Becker, Betsy Jane

2014-09-01

A common assumption in meta-analysis is that effect sizes are independent. When correlated effect sizes are analyzed using traditional univariate techniques, this assumption is violated. This research assesses the impact of dependence arising from treatment-control studies with multiple endpoints on homogeneity measures Q and I(2) in scenarios using the unbiased standardized-mean-difference effect size. Univariate and multivariate meta-analysis methods are examined. Conditions included different overall outcome effects, study sample sizes, numbers of studies, between-outcomes correlations, dependency structures, and ways of computing the correlation. The univariate approach used typical fixed-effects analyses whereas the multivariate approach used generalized least-squares (GLS) estimates of a fixed-effects model, weighted by the inverse variance-covariance matrix. Increased dependence among effect sizes led to increased Type I error rates from univariate models. When effect sizes were strongly dependent, error rates were drastically higher than nominal levels regardless of study sample size and number of studies. In contrast, using GLS estimation to account for multiple-endpoint dependency maintained error rates within nominal levels. Conversely, mean I(2) values were not greatly affected by increased amounts of dependency. Last, we point out that the between-outcomes correlation should be estimated as a pooled within-groups correlation rather than using a full-sample estimator that does not consider treatment/control group membership. Copyright © 2014 John Wiley & Sons, Ltd.

Risk models for post-endoscopic retrograde cholangiopancreatography pancreatitis (PEP): smoking and chronic liver disease are predictors of protection against PEP.

PubMed

DiMagno, Matthew J; Spaete, Joshua P; Ballard, Darren D; Wamsteker, Erik-Jan; Saini, Sameer D

2013-08-01

We investigated which variables independently associated with protection against or development of postendoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) and severity of PEP. Subsequently, we derived predictive risk models for PEP. In a case-control design, 6505 patients had 8264 ERCPs, 211 patients had PEP, and 22 patients had severe PEP. We randomly selected 348 non-PEP controls. We examined 7 established- and 9 investigational variables. In univariate analysis, 7 variables predicted PEP: younger age, female sex, suspected sphincter of Oddi dysfunction (SOD), pancreatic sphincterotomy, moderate-difficult cannulation (MDC), pancreatic stent placement, and lower Charlson score. Protective variables were current smoking, former drinking, diabetes, and chronic liver disease (CLD, biliary/transplant complications). Multivariate analysis identified seven independent variables for PEP, three protective (current smoking, CLD-biliary, CLD-transplant/hepatectomy complications) and 4 predictive (younger age, suspected SOD, pancreatic sphincterotomy, MDC). Pre- and post-ERCP risk models of 7 variables have a C-statistic of 0.74. Removing age (seventh variable) did not significantly affect the predictive value (C-statistic of 0.73) and reduced model complexity. Severity of PEP did not associate with any variables by multivariate analysis. By using the newly identified protective variables with 3 predictive variables, we derived 2 risk models with a higher predictive value for PEP compared to prior studies.

Hypnotherapy and Test Anxiety: Two Cognitive-Behavioral Constructs. The Effects of Hypnosis in Reducing Test Anxiety and Improving Academic Achievement in College Students.

ERIC Educational Resources Information Center

Sapp, Marty

A two-group randomized multivariate analysis of covariance (MANCOVA) was used to investigate the effects of cognitive-behavioral hypnosis in reducing test anxiety and improving academic performance in comparison to a Hawthorne control group. Subjects were enrolled in a rigorous introductory psychology course which covered an entire text in one…

A microcomputer-based whole-body counter for personnel routine monitoring.

PubMed

Chou, H P; Tsai, T M; Lan, C Y

1993-05-01

The paper describes a cost-effective NaI(Tl) whole-body counter developed for routine examinations of worker intakes at an isotope production facility. Signal processing, data analysis and system operation are microcomputer-controlled for minimum human interactions. The pulse height analyzer is developed as an microcomputer add-on card for easy manipulation. The scheme for radionuclide analysis is aimed for fast running according to a knowledge base established from background samples and phantom experiments in conjunction with a multivariate regression analysis. Long-term stability and calibration with standards and in vivo measurements are reported.

Multivariate analysis for scanning tunneling spectroscopy data

NASA Astrophysics Data System (ADS)

Yamanishi, Junsuke; Iwase, Shigeru; Ishida, Nobuyuki; Fujita, Daisuke

2018-01-01

We applied principal component analysis (PCA) to two-dimensional tunneling spectroscopy (2DTS) data obtained on a Si(111)-(7 × 7) surface to explore the effectiveness of multivariate analysis for interpreting 2DTS data. We demonstrated that several components that originated mainly from specific atoms at the Si(111)-(7 × 7) surface can be extracted by PCA. Furthermore, we showed that hidden components in the tunneling spectra can be decomposed (peak separation), which is difficult to achieve with normal 2DTS analysis without the support of theoretical calculations. Our analysis showed that multivariate analysis can be an additional powerful way to analyze 2DTS data and extract hidden information from a large amount of spectroscopic data.

Robust multivariate nonparametric tests for detection of two-sample location shift in clinical trials

PubMed Central

Jiang, Xuejun; Guo, Xu; Zhang, Ning; Wang, Bo

2018-01-01

This article presents and investigates performance of a series of robust multivariate nonparametric tests for detection of location shift between two multivariate samples in randomized controlled trials. The tests are built upon robust estimators of distribution locations (medians, Hodges-Lehmann estimators, and an extended U statistic) with both unscaled and scaled versions. The nonparametric tests are robust to outliers and do not assume that the two samples are drawn from multivariate normal distributions. Bootstrap and permutation approaches are introduced for determining the p-values of the proposed test statistics. Simulation studies are conducted and numerical results are reported to examine performance of the proposed statistical tests. The numerical results demonstrate that the robust multivariate nonparametric tests constructed from the Hodges-Lehmann estimators are more efficient than those based on medians and the extended U statistic. The permutation approach can provide a more stringent control of Type I error and is generally more powerful than the bootstrap procedure. The proposed robust nonparametric tests are applied to detect multivariate distributional difference between the intervention and control groups in the Thai Healthy Choices study and examine the intervention effect of a four-session motivational interviewing-based intervention developed in the study to reduce risk behaviors among youth living with HIV. PMID:29672555

Data-Driven Nonlinear Subspace Modeling for Prediction and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Ping; Song, Heda; Wang, Hong

Blast furnace (BF) in ironmaking is a nonlinear dynamic process with complicated physical-chemical reactions, where multi-phase and multi-field coupling and large time delay occur during its operation. In BF operation, the molten iron temperature (MIT) as well as Si, P and S contents of molten iron are the most essential molten iron quality (MIQ) indices, whose measurement, modeling and control have always been important issues in metallurgic engineering and automation field. This paper develops a novel data-driven nonlinear state space modeling for the prediction and control of multivariate MIQ indices by integrating hybrid modeling and control techniques. First, to improvemore » modeling efficiency, a data-driven hybrid method combining canonical correlation analysis and correlation analysis is proposed to identify the most influential controllable variables as the modeling inputs from multitudinous factors would affect the MIQ indices. Then, a Hammerstein model for the prediction of MIQ indices is established using the LS-SVM based nonlinear subspace identification method. Such a model is further simplified by using piecewise cubic Hermite interpolating polynomial method to fit the complex nonlinear kernel function. Compared to the original Hammerstein model, this simplified model can not only significantly reduce the computational complexity, but also has almost the same reliability and accuracy for a stable prediction of MIQ indices. Last, in order to verify the practicability of the developed model, it is applied in designing a genetic algorithm based nonlinear predictive controller for multivariate MIQ indices by directly taking the established model as a predictor. Industrial experiments show the advantages and effectiveness of the proposed approach.« less

Long working hours and skipping breakfast concomitant with late evening meals are associated with suboptimal glycemic control among young male Japanese patients with type 2 diabetes.

PubMed

Azami, Yasushi; Funakoshi, Mitsuhiko; Matsumoto, Hisashi; Ikota, Akemi; Ito, Koichi; Okimoto, Hisashi; Shimizu, Nobuaki; Tsujimura, Fumihiro; Fukuda, Hiroshi; Miyagi, Chozi; Osawa, Sayaka; Osawa, Ryo; Miura, Jiro

2018-04-17

To assess the associations of working conditions, eating habits and glycemic control among young Japanese workers with type 2 diabetes. This hospital- and clinic-based prospective study included 352 male and 126 female working patients with diabetes aged 20-40 years. Data were obtained from June to July 2012 and June to July 2013. Logistic regression analysis was used to estimate multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for suboptimal glycemic control (glycosylated hemoglobin level of ≥7%) obtained from June to July 2013. Multivariable logistic regression analysis showed that disease duration of ≥10 years (OR 2.43, 95% CI 1.02-5.80), glycosylated hemoglobin level of ≥7% in 2012 (OR 8.50, 95% CI 4.90-14.80), skipping breakfast and late evening meals (OR 2.50, 95% CI 1.25-5.00) and working ≥60 h/week (OR 2.92, 95% CI 1.16-7.40) were predictive of suboptimal glycemic control in male workers, whereas a glycosylated hemoglobin level of ≥7% in 2012 (OR 17.96, 95% CI 5.93-54.4), oral hyperglycemic agent therapy (OR 12.49, 95% CI 2.75-56.86) and insulin therapy (OR 11.60, 95% CI 2.35-57.63) were predictive of suboptimal glycemic control in female workers. Working ≥60 h/week and habitual skipping breakfast concomitant with late evening meals might affect the ability of young male workers with type 2 diabetes to achieve and maintain glycemic control. © 2018 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.

Factors related to clinical pregnancy after vitrified-warmed embryo transfer: a retrospective and multivariate logistic regression analysis of 2313 transfer cycles.

PubMed

Shi, Wenhao; Zhang, Silin; Zhao, Wanqiu; Xia, Xue; Wang, Min; Wang, Hui; Bai, Haiyan; Shi, Juanzi

2013-07-01

What factors does multivariate logistic regression show to be significantly associated with the likelihood of clinical pregnancy in vitrified-warmed embryo transfer (VET) cycles? Assisted hatching (AH) and if the reason to freeze embryos was to avoid the risk of ovarian hyperstimulation syndrome (OHSS) were significantly positively associated with a greater likelihood of clinical pregnancy. Single factor analysis has shown AH, number of embryos transferred and the reason of freezing for OHSS to be positively and damaged blastomere to be negatively significantly associated with the chance of clinical pregnancy after VET. It remains unclear what factors would be significant after multivariate analysis. The study was a retrospective analysis of 2313 VET cycles from 1481 patients performed between January 2008 and April 2012. A multivariate logistic regression analysis was performed to identify the factors to affect clinical pregnancy outcome of VET. There were 22 candidate variables selected based on clinical experiences and the literature. With the thresholds of α entry = α removal= 0.05 for both variable entry and variable removal, eight variables were chosen to contribute the multivariable model by the bootstrap stepwise variable selection algorithm (n = 1000). Eight variables were age at controlled ovarian hyperstimulation (COH), reason for freezing, AH, endometrial thickness, damaged blastomere, number of embryos transferred, number of good-quality embryos, and blood presence on transfer catheter. A descriptive comparison of the relative importance was accomplished by the proportion of explained variation (PEV). Among the reasons for freezing, the OHSS group showed a higher OR than the surplus embryo group when compared with other reasons for VET groups (OHSS versus Other, OR: 2.145; CI: 1.4-3.286; Surplus embryos versus Other, OR: 1.152; CI: 0.761-1.743) and high PEV (marginal 2.77%, P = 0.2911; partial 1.68%; CI of area under receptor operator characteristic curve (ROC): 0.5576-0.6000). AH also showed a high OR (OR: 2.105, CI: 1.554-2.85) and high PEV (marginal 1.97%; partial 1.02%; CI of area under ROC: 0.5344-0.5647). The number of good-quality embryos showed the highest marginal PEV and partial PEV (marginal 3.91%, partial 2.28%; CI of area under ROC: 0.5886-0.6343). This was a retrospective multivariate analysis of the data obtained in 5 years from a single IVF center. Repeated cycles in the same woman were treated as independent observations, which could introduce bias. Results are based on clinical pregnancy and not live births. Prospective analysis of a larger data set from a multicenter study based on live births is necessary to confirm the findings. Paying attention to the quality of embryos, the number of good embryos, AH and the reasons for freezing that are associated with clinical pregnancy after VET will assist the improvement of success rates.

Identifying HIV associated neurocognitive disorder using large-scale Granger causality analysis on resting-state functional MRI

NASA Astrophysics Data System (ADS)

DSouza, Adora M.; Abidin, Anas Z.; Leistritz, Lutz; Wismüller, Axel

2017-02-01

We investigate the applicability of large-scale Granger Causality (lsGC) for extracting a measure of multivariate information flow between pairs of regional brain activities from resting-state functional MRI (fMRI) and test the effectiveness of these measures for predicting a disease state. Such pairwise multivariate measures of interaction provide high-dimensional representations of connectivity profiles for each subject and are used in a machine learning task to distinguish between healthy controls and individuals presenting with symptoms of HIV Associated Neurocognitive Disorder (HAND). Cognitive impairment in several domains can occur as a result of HIV infection of the central nervous system. The current paradigm for assessing such impairment is through neuropsychological testing. With fMRI data analysis, we aim at non-invasively capturing differences in brain connectivity patterns between healthy subjects and subjects presenting with symptoms of HAND. To classify the extracted interaction patterns among brain regions, we use a prototype-based learning algorithm called Generalized Matrix Learning Vector Quantization (GMLVQ). Our approach to characterize connectivity using lsGC followed by GMLVQ for subsequent classification yields good prediction results with an accuracy of 87% and an area under the ROC curve (AUC) of up to 0.90. We obtain a statistically significant improvement (p<0.01) over a conventional Granger causality approach (accuracy = 0.76, AUC = 0.74). High accuracy and AUC values using our multivariate method to connectivity analysis suggests that our approach is able to better capture changes in interaction patterns between different brain regions when compared to conventional Granger causality analysis known from the literature.

Assessment of water quality parameters using multivariate analysis for Klang River basin, Malaysia.

PubMed

Mohamed, Ibrahim; Othman, Faridah; Ibrahim, Adriana I N; Alaa-Eldin, M E; Yunus, Rossita M

2015-01-01

This case study uses several univariate and multivariate statistical techniques to evaluate and interpret a water quality data set obtained from the Klang River basin located within the state of Selangor and the Federal Territory of Kuala Lumpur, Malaysia. The river drains an area of 1,288 km(2), from the steep mountain rainforests of the main Central Range along Peninsular Malaysia to the river mouth in Port Klang, into the Straits of Malacca. Water quality was monitored at 20 stations, nine of which are situated along the main river and 11 along six tributaries. Data was collected from 1997 to 2007 for seven parameters used to evaluate the status of the water quality, namely dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solids, ammoniacal nitrogen, pH, and temperature. The data were first investigated using descriptive statistical tools, followed by two practical multivariate analyses that reduced the data dimensions for better interpretation. The analyses employed were factor analysis and principal component analysis, which explain 60 and 81.6% of the total variation in the data, respectively. We found that the resulting latent variables from the factor analysis are interpretable and beneficial for describing the water quality in the Klang River. This study presents the usefulness of several statistical methods in evaluating and interpreting water quality data for the purpose of monitoring the effectiveness of water resource management. The results should provide more straightforward data interpretation as well as valuable insight for managers to conceive optimum action plans for controlling pollution in river water.

Nitrate source identification in groundwater of multiple land-use areas by combining isotopes and multivariate statistical analysis: A case study of Asopos basin (Central Greece).

PubMed

Matiatos, Ioannis

2016-01-15

Nitrate (NO3) is one of the most common contaminants in aquatic environments and groundwater. Nitrate concentrations and environmental isotope data (δ(15)N-NO3 and δ(18)O-NO3) from groundwater of Asopos basin, which has different land-use types, i.e., a large number of industries (e.g., textile, metal processing, food, fertilizers, paint), urban and agricultural areas and livestock breeding facilities, were analyzed to identify the nitrate sources of water contamination and N-biogeochemical transformations. A Bayesian isotope mixing model (SIAR) and multivariate statistical analysis of hydrochemical data were used to estimate the proportional contribution of different NO3 sources and to identify the dominant factors controlling the nitrate content of the groundwater in the region. The comparison of SIAR and Principal Component Analysis showed that wastes originating from urban and industrial zones of the basin are mainly responsible for nitrate contamination of groundwater in these areas. Agricultural fertilizers and manure likely contribute to groundwater contamination away from urban fabric and industrial land-use areas. Soil contribution to nitrate contamination due to organic matter is higher in the south-western part of the area far from the industries and the urban settlements. The present study aims to highlight the use of environmental isotopes combined with multivariate statistical analysis in locating sources of nitrate contamination in groundwater leading to a more effective planning of environmental measures and remediation strategies in river basins and water bodies as defined by the European Water Frame Directive (Directive 2000/60/EC).

A comparative study of multivariable robustness analysis methods as applied to integrated flight and propulsion control

NASA Technical Reports Server (NTRS)

Schierman, John D.; Lovell, T. A.; Schmidt, David K.

1993-01-01

Three multivariable robustness analysis methods are compared and contrasted. The focus of the analysis is on system stability and performance robustness to uncertainty in the coupling dynamics between two interacting subsystems. Of particular interest is interacting airframe and engine subsystems, and an example airframe/engine vehicle configuration is utilized in the demonstration of these approaches. The singular value (SV) and structured singular value (SSV) analysis methods are compared to a method especially well suited for analysis of robustness to uncertainties in subsystem interactions. This approach is referred to here as the interacting subsystem (IS) analysis method. This method has been used previously to analyze airframe/engine systems, emphasizing the study of stability robustness. However, performance robustness is also investigated here, and a new measure of allowable uncertainty for acceptable performance robustness is introduced. The IS methodology does not require plant uncertainty models to measure the robustness of the system, and is shown to yield valuable information regarding the effects of subsystem interactions. In contrast, the SV and SSV methods allow for the evaluation of the robustness of the system to particular models of uncertainty, and do not directly indicate how the airframe (engine) subsystem interacts with the engine (airframe) subsystem.

Multivariate Analysis of Schools and Educational Policy.

ERIC Educational Resources Information Center

Kiesling, Herbert J.

This report describes a multivariate analysis technique that approaches the problems of educational production function analysis by (1) using comparable measures of output across large experiments, (2) accounting systematically for differences in socioeconomic background, and (3) treating the school as a complete system in which different…

Minia, Egypt: Principal Component Analysis

PubMed

Abdelrehim, Marwa G; Mahfouz, Eman M; Ewis, Ashraf A; Seedhom, Amany E; Afifi, Hassan M; Shebl, Fatma M

2018-02-26

Background: Pancreatic cancer (PC) is a serious and rapidly progressing malignancy. Identifying risk factors including dietary elements is important to develop preventive strategies. This study focused on possible links between diet and PC. Methods: We conducted a case-control study including all PC patients diagnosed at Minia Cancer Center and controls from general population from June 2014 to December 2015. Dietary data were collected directly through personal interviews. Principal component analysis (PCA) was performed to identify dietary groups. The data were analyzed using crude odds ratios (ORs) and multivariable logistic regression with adjusted ORs and 95% confidence intervals (CIs). Results: A total of 75 cases and 149 controls were included in the study. PCA identified six dietary groups, labeled as cereals and grains, vegetables, proteins, dairy products, fruits, and sugars. Bivariate analysis showed that consumption of vegetables, fruits, sugars, and total energy intake were associated with change in PC risk. In multivariable-adjusted models comparing highest versus lowest levels of intake, we observed significant lower odds of PC in association with vegetable intake (OR 0.24; 95% CI, 0.07-0.85, P=0.012) and a higher likelihood with the total energy intake (OR 9.88; 95% CI, 2.56-38.09, P<0.0001). There was also a suggested link between high fruit consumption and reduced odds of PC. Conclusions: The study supports the association between dietary factors and the odds of PC development in Egypt. It was found that higher energy intake is associated with an increase in likelihood of PC, while increased vegetable consumption is associated with a lower odds ratio. Creative Commons Attribution License

Location in the right hemi-colon is an independent risk factor for delayed post-polypectomy hemorrhage: a multi-center case-control study.

PubMed

Buddingh, K Tim; Herngreen, Thomas; Haringsma, Jelle; van der Zwet, Wil C; Vleggaar, Frank P; Breumelhof, Ronald; Ter Borg, Frank

2011-06-01

Delayed hemorrhage is an infrequent, but serious complication of colonoscopic polypectomy. Large size is the only polyp-related factor that has been unequivocally proven to increase the risk of delayed bleeding. It has been suggested that location in the right hemi-colon is also a risk factor. The objective of this study was to determine whether polyp location is an independent risk factor for delayed post-polypectomy hemorrhage. A retrospective case-control study was conducted in two university hospitals and two community hospitals. Thirty-nine cases and 117 controls were identified. In multivariate analysis, size and location were found to be independent polyp-related risk factors for delayed type hemorrhage. The risk increased by 13% for every 1 mm increase in polyp diameter (odds ratio (OR) 1.13, 95% confidence interval (CI) 1.05-1.20, P<0.001). Polyps located in the right hemi-colon had an OR of 4.67 (1.88-11.61, P=0.001) for delayed hemorrhage. Polyps in the cecum seemed to be especially at high risk in univariate analysis (OR 13.82, 95% CI 2.66-71.73), but this could not be assessed in multivariate analysis as the number of cases was too small. Polyp type (sessile or pedunculated) was not a risk factor. Polyp location in the right hemi-colon seems to be an independent and substantial risk factor for delayed post-polypectomy hemorrhage. A low threshold for preventive hemostatic measures is advised when removing polyps from this region.

Vectored Thrust Digital Flight Control for Crew Escape. Volume 2.

DTIC Science & Technology

1985-12-01

no. 24. Lecrique, J., A. Rault, M. Tessier and J.L. Testud (1978), - "Multivariable Regulation of a Thermal Power Plant Steam Generator," presented...and Extended Kalman Observers," presented at the Conf. Decision and Control, San Diego, CA. Testud , J.L. (1977), Commande Numerique Multivariable du

Tables of Optimal Allocations of Observations for Comparing Treatments with a Control.

DTIC Science & Technology

1981-01-01

variatevpp v ,p,P t-distribution (p-variate Itl-distribution) with d.f. v and equal corre- lations p = N /C (N ); tables of t are given by Krishnaiah and1 0 1...values of (tp,/) 2 tabulated for selected -d and 1-a by Krishnaiah and Armitage (1965). Entries for v = 60 1.. the tables of Hahn and Hendrickson (1971...with a Control," Multivariate Analysis - II (Ed. P.R. Krishnaiah ), New York: Academic Press, 463-473. Bechhofer, R.E. and Nocturne, D.J. (1972), "Optimal

Multivariate pattern analysis of fMRI data reveals deficits in distributed representations in schizophrenia

PubMed Central

Yoon, Jong H.; Tamir, Diana; Minzenberg, Michael J.; Ragland, J. Daniel; Ursu, Stefan; Carter, Cameron S.

2009-01-01

Background Multivariate pattern analysis is an alternative method of analyzing fMRI data, which is capable of decoding distributed neural representations. We applied this method to test the hypothesis of the impairment in distributed representations in schizophrenia. We also compared the results of this method with traditional GLM-based univariate analysis. Methods 19 schizophrenia and 15 control subjects viewed two runs of stimuli--exemplars of faces, scenes, objects, and scrambled images. To verify engagement with stimuli, subjects completed a 1-back matching task. A multi-voxel pattern classifier was trained to identify category-specific activity patterns on one run of fMRI data. Classification testing was conducted on the remaining run. Correlation of voxel-wise activity across runs evaluated variance over time in activity patterns. Results Patients performed the task less accurately. This group difference was reflected in the pattern analysis results with diminished classification accuracy in patients compared to controls, 59% and 72% respectively. In contrast, there was no group difference in GLM-based univariate measures. In both groups, classification accuracy was significantly correlated with behavioral measures. Both groups showed highly significant correlation between inter-run correlations and classification accuracy. Conclusions Distributed representations of visual objects are impaired in schizophrenia. This impairment is correlated with diminished task performance, suggesting that decreased integrity of cortical activity patterns is reflected in impaired behavior. Comparisons with univariate results suggest greater sensitivity of pattern analysis in detecting group differences in neural activity and reduced likelihood of non-specific factors driving these results. PMID:18822407

Application of advanced control techniques to aircraft propulsion systems

NASA Technical Reports Server (NTRS)

Lehtinen, B.

1984-01-01

Two programs are described which involve the application of advanced control techniques to the design of engine control algorithms. Multivariable control theory is used in the F100 MVCS (multivariable control synthesis) program to design controls which coordinate the control inputs for improved engine performance. A systematic method for handling a complex control design task is given. Methods of analytical redundancy are aimed at increasing the control system reliability. The F100 DIA (detection, isolation, and accommodation) program, which investigates the uses of software to replace or augment hardware redundancy for certain critical engine sensor, is described.

Practical Methods for the Compensation and Control of Multivariable Systems.

DTIC Science & Technology

1982-04-01

a constant gain element gji . To be more specific, let us consider a linear multivariable system whose dynamical behavior is specified by a (pxm...controllable via uk if Yi is fed back to uj via an arbitrary gain gji , as depicted in the figure below? It might be noted that only the outputs and inputs...modes controllable via uk(s) before feedback will remain -19- controllable via uk(s) irrespective of gji (although certain of these uk controllable

Evaluation of 2 whole-brain radiotherapy schedules and prognostic factors for brain metastases in breast cancer patients.

PubMed

Rades, Dirk; Lohynska, Radka; Veninga, Theo; Stalpers, Lukas J A; Schild, Steven E

2007-12-01

The majority of breast cancer patients with brain metastases receive whole-brain radiotherapy (WBRT) and have a survival of only a few months. A short WBRT regimen would be preferable if it provides survival that is similar to that achieved with longer programs. This retrospective study compared survival and local control within the brain resulting from short-course WBRT with longer programs in 207 breast cancer patients. Sixty-nine patients treated with 5 fractions of 4 grays (Gy) each given within 5 days were compared with 138 patients treated with 10 fractions of 3 Gy each given over 2 weeks or 20 fractions of 2 Gy each given over 4 weeks. Six additional potential prognostic factors were investigated: age, Karnofsky performance score (KPS), number of brain metastases, the presence of extracranial metastases, interval from tumor diagnosis to WBRT, and recursive partitioning analysis (RPA) class. On univariate analysis, the WBRT regimen was not found to be associated with survival (P=.254) or local control (P=.397). Improved survival was associated with a KPS>70 (P<.001), single brain metastasis (P=.023), the absence of extracranial metastases (P<.001), and lower RPA class (P<.001). On multivariate analysis, which was performed without RPA class because this is a confounding variable, KPS (relative risk [RR] of 4.00; P<.001) and the presence of extracranial metastases (RR of 1.54; P=.024) maintained statistical significance. On univariate analysis, local control was associated with KPS (P<.001) and RPA class (P<.001). On multivariate analysis, local control was found to be associated with a KPS>70 (RR of 5.75; P<.001). Short-course WBRT with 5 fractions of 4 Gy each resulted in survival and local control that were similar to longer programs in breast cancer patients with brain metastases. The dose of 5 fractions of 4 Gy each appears preferable for the majority of these patients because it is less time consuming and more convenient. Copyright (c) 2007 American Cancer Society.

Control of maglev vehicles with aerodynamic and guideway disturbances

NASA Technical Reports Server (NTRS)

Flueckiger, Karl; Mark, Steve; Caswell, Ruth; Mccallum, Duncan

1994-01-01

A modeling, analysis, and control design methodology is presented for maglev vehicle ride quality performance improvement as measured by the Pepler Index. Ride quality enhancement is considered through active control of secondary suspension elements and active aerodynamic surfaces mounted on the train. To analyze and quantify the benefits of active control, the authors have developed a five degree-of-freedom lumped parameter model suitable for describing a large class of maglev vehicles, including both channel and box-beam guideway configurations. Elements of this modeling capability have been recently employed in studies sponsored by the U.S. Department of Transportation (DOT). A perturbation analysis about an operating point, defined by vehicle and average crosswind velocities, yields a suitable linearized state space model for multivariable control system analysis and synthesis. Neglecting passenger compartment noise, the ride quality as quantified by the Pepler Index is readily computed from the system states. A statistical analysis is performed by modeling the crosswind disturbances and guideway variations as filtered white noise, whereby the Pepler Index is established in closed form through the solution to a matrix Lyapunov equation. Data is presented which indicates the anticipated ride quality achieved through various closed-loop control arrangements.

Multivariate analysis of the immune response to a vaccine as an alternative to the repetition of animal challenge studies for vaccines with demonstrated efficacy.

PubMed

Chapat, Ludivine; Hilaire, Florence; Bouvet, Jérome; Pialot, Daniel; Philippe-Reversat, Corinne; Guiot, Anne-Laure; Remolue, Lydie; Lechenet, Jacques; Andreoni, Christine; Poulet, Hervé; Day, Michael J; De Luca, Karelle; Cariou, Carine; Cupillard, Lionel

2017-07-01

The assessment of vaccine combinations, or the evaluation of the impact of minor modifications of one component in well-established vaccines, requires animal challenges in the absence of previously validated correlates of protection. As an alternative, we propose conducting a multivariate analysis of the specific immune response to the vaccine. This approach is consistent with the principles of the 3Rs (Refinement, Reduction and Replacement) and avoids repeating efficacy studies based on infectious challenges in vivo. To validate this approach, a set of nine immunological parameters was selected in order to characterize B and T lymphocyte responses against canine rabies virus and to evaluate the compatibility between two canine vaccines, an inactivated rabies vaccine (RABISIN ® ) and a combined vaccine (EURICAN ® DAPPi-Lmulti) injected at two different sites in the same animals. The analysis was focused on the magnitude and quality of the immune response. The multi-dimensional picture given by this 'immune fingerprint' was used to assess the impact of the concomitant injection of the combined vaccine on the immunogenicity of the rabies vaccine. A principal component analysis fully discriminated the control group from the groups vaccinated with RABISIN ® alone or RABISIN ® +EURICAN ® DAPPi-Lmulti and confirmed the compatibility between the rabies vaccines. This study suggests that determining the immune fingerprint, combined with a multivariate statistical analysis, is a promising approach to characterizing the immunogenicity of a vaccine with an established record of efficacy. It may also avoid the need to repeat efficacy studies involving challenge infection in case of minor modifications of the vaccine or for compatibility studies. Copyright © 2017 Elsevier B.V. All rights reserved.

The structural equation analysis of childhood abuse, adult stressful life events, and temperaments in major depressive disorders and their influence on refractoriness

PubMed Central

Toda, Hiroyuki; Inoue, Takeshi; Tsunoda, Tomoya; Nakai, Yukiei; Tanichi, Masaaki; Tanaka, Teppei; Hashimoto, Naoki; Nakato, Yasuya; Nakagawa, Shin; Kitaichi, Yuji; Mitsui, Nobuyuki; Boku, Shuken; Tanabe, Hajime; Nibuya, Masashi; Yoshino, Aihide; Kusumi, Ichiro

2015-01-01

Background Previous studies have shown the interaction between heredity and childhood stress or life events on the pathogenesis of a major depressive disorder (MDD). In this study, we tested our hypothesis that childhood abuse, affective temperaments, and adult stressful life events interact and influence the diagnosis of MDD. Patients and methods A total of 170 healthy controls and 98 MDD patients were studied using the following self-administered questionnaire surveys: the Patient Health Questionnaire-9 (PHQ-9), the Life Experiences Survey, the Temperament Evaluation of the Memphis, Pisa, Paris, and San Diego Autoquestionnaire, and the Child Abuse and Trauma Scale (CATS). The data were analyzed with univariate analysis, multivariable analysis, and structural equation modeling. Results The neglect scores of the CATS indirectly predicted the diagnosis of MDD through cyclothymic and anxious temperament scores of the Temperament Evaluation of the Memphis, Pisa, Paris, and San Diego Autoquestionnaire in the structural equation modeling. Two temperaments – cyclothymic and anxious – directly predicted the diagnosis of MDD. The validity of this result was supported by the results of the stepwise multivariate logistic regression analysis as follows: three factors – neglect, cyclothymic, and anxious temperaments – were significant predictors of MDD. Neglect and the total CATS scores were also predictors of remission vs treatment-resistance in MDD patients independently of depressive symptoms. Limitations The sample size was small for the comparison between the remission and treatment-resistant groups in MDD patients in multivariable analysis. Conclusion This study suggests that childhood abuse, especially neglect, indirectly predicted the diagnosis of MDD through increased affective temperaments. The important role as a mediator of affective temperaments in the effect of childhood abuse on MDD was suggested. PMID:26316754

Multivariate statistical analysis: Principles and applications to coorbital streams of meteorite falls

NASA Technical Reports Server (NTRS)

Wolf, S. F.; Lipschutz, M. E.

1993-01-01

Multivariate statistical analysis techniques (linear discriminant analysis and logistic regression) can provide powerful discrimination tools which are generally unfamiliar to the planetary science community. Fall parameters were used to identify a group of 17 H chondrites (Cluster 1) that were part of a coorbital stream which intersected Earth's orbit in May, from 1855 - 1895, and can be distinguished from all other H chondrite falls. Using multivariate statistical techniques, it was demonstrated that a totally different criterion, labile trace element contents - hence thermal histories - or 13 Cluster 1 meteorites are distinguishable from those of 45 non-Cluster 1 H chondrites. Here, we focus upon the principles of multivariate statistical techniques and illustrate their application using non-meteoritic and meteoritic examples.

Quality Reporting of Multivariable Regression Models in Observational Studies: Review of a Representative Sample of Articles Published in Biomedical Journals.

PubMed

Real, Jordi; Forné, Carles; Roso-Llorach, Albert; Martínez-Sánchez, Jose M

2016-05-01

Controlling for confounders is a crucial step in analytical observational studies, and multivariable models are widely used as statistical adjustment techniques. However, the validation of the assumptions of the multivariable regression models (MRMs) should be made clear in scientific reporting. The objective of this study is to review the quality of statistical reporting of the most commonly used MRMs (logistic, linear, and Cox regression) that were applied in analytical observational studies published between 2003 and 2014 by journals indexed in MEDLINE.Review of a representative sample of articles indexed in MEDLINE (n = 428) with observational design and use of MRMs (logistic, linear, and Cox regression). We assessed the quality of reporting about: model assumptions and goodness-of-fit, interactions, sensitivity analysis, crude and adjusted effect estimate, and specification of more than 1 adjusted model.The tests of underlying assumptions or goodness-of-fit of the MRMs used were described in 26.2% (95% CI: 22.0-30.3) of the articles and 18.5% (95% CI: 14.8-22.1) reported the interaction analysis. Reporting of all items assessed was higher in articles published in journals with a higher impact factor.A low percentage of articles indexed in MEDLINE that used multivariable techniques provided information demonstrating rigorous application of the model selected as an adjustment method. Given the importance of these methods to the final results and conclusions of observational studies, greater rigor is required in reporting the use of MRMs in the scientific literature.

Militarism and mortality. An international analysis of arms spending and infant death rates.

PubMed

Woolhandler, S; Himmelstein, D U

1985-06-15

Examination of data from 141 countries showed that infant mortality rates for 1979 were positively correlated with the proportion of gross national product devoted to military spending (r = 0.23, p less than 0.01) and negatively correlated with indicators of economic development, health resources, and social spending. In a multivariate analysis controlling for per caput gross national product, arms spending remained a significant positive predictor of infant mortality rate (p less than 0.0001), while the proportion of the population with access to clean water, the number of teachers per head, and caloric consumption per head were negative predictors. The multivariate model accounted for much of the observed variance in infant mortality rate (R2 = 0.78, p less than 0.0001), and showed good fit to similar data for the year 1972 (R2 = 0.80, p less than 0.0001). The model was also predictive of infant mortality rates in subgroup analysis of underdeveloped, middle developed, and developed nations. Analysis of time trends confirmed that an increase in military spending presages a poor record of improvement in infant mortality rate. These findings support the hypothesis that arms spending is causally related to infant mortality.

Prevalence and risk factors for scrub typhus in South India.

PubMed

Trowbridge, Paul; P, Divya; Premkumar, Prasanna S; Varghese, George M

2017-05-01

To determine the prevalence and risk factors of scrub typhus in Tamil Nadu, South India. We performed a clustered seroprevalence study of the areas around Vellore. All participants completed a risk factor survey, with seropositive and seronegative participants acting as cases and controls, respectively, in a risk factor analysis. After univariate analysis, variables found to be significant underwent multivariate analysis. Of 721 people participating in this study, 31.8% tested seropositive. By univariate analysis, after accounting for clustering, having a house that was clustered with other houses, having a fewer rooms in a house, having fewer people living in a household, defecating outside, female sex, age >60 years, shorter height, lower weight, smaller body mass index and smaller mid-upper arm circumference were found to be significantly associated with seropositivity. After multivariate regression modelling, living in a house clustered with other houses, female sex and age >60 years were significantly associated with scrub typhus exposure. Overall, scrub typhus is much more common than previously thought. Previously described individual environmental and habitual risk factors seem to have less importance in South India, perhaps because of the overall scrub typhus-conducive nature of the environment in this region. © 2017 John Wiley & Sons Ltd.

Prematurity and fetal lung response after tracheal occlusion in fetuses with severe congenital diaphragmatic hernia.

PubMed

Sananes, Nicolas; Rodo, Carlota; Peiro, Jose Luis; Britto, Ingrid Schwach Werneck; Sangi-Haghpeykar, Haleh; Favre, Romain; Joal, Arnaud; Gaudineau, Adrien; Silva, Marcos Marques da; Tannuri, Uenis; Zugaib, Marcelo; Carreras, Elena; Ruano, Rodrigo

2016-09-01

To evaluate the independent association of fetal pulmonary response and prematurity to postnatal outcomes after fetal tracheal occlusion for congenital diaphragmatic hernia. Fetal pulmonary response, prematurity (<37 weeks at delivery) and extreme prematurity (<32 weeks at delivery) were evaluated and compared between survivors and non-survivors at 6 months of life. Multivariable analysis was conducted with generalized linear mixed models for variables significantly associated with survival in univariate analysis. Eighty-four infants were included, of whom 40 survived (47.6%) and 44 died (52.4%). Univariate analysis demonstrated that survival was associated with greater lung response (p=0.006), and the absence of extreme preterm delivery (p=0.044). In multivariable analysis, greater pulmonary response after FETO was an independent predictor of survival (aOR 1.87, 95% CI 1.08-3.33, p=0.023), whereas the presence of extreme prematurity was not statistically associated with mortality after controlling for fetal pulmonary response (aOR 0.52, 95% CI 0.12-2.30, p=0.367). Fetal pulmonary response after FETO is the most important factor associated with survival, independently from the gestational age at delivery.

Multivariate Optimization for Extraction of Pyrethroids in Milk and Validation for GC-ECD and CG-MS/MS Analysis

PubMed Central

Zanchetti Meneghini, Leonardo; Rübensam, Gabriel; Claudino Bica, Vinicius; Ceccon, Amanda; Barreto, Fabiano; Flores Ferrão, Marco; Bergold, Ana Maria

2014-01-01

A simple and inexpensive method based on solvent extraction followed by low temperature clean-up was applied for determination of seven pyrethroids residues in bovine raw milk using gas chromatography coupled to tandem mass spectrometry (GC-MS/MS) and gas chromatography with electron-capture detector (GC-ECD). Sample extraction procedure was established through the evaluation of seven different extraction protocols, evaluated in terms of analyte recovery and cleanup efficiency. Sample preparation optimization was based on Doehlert design using fifteen runs with three different variables. Response surface methodologies and polynomial analysis were used to define the best extraction conditions. Method validation was carried out based on SANCO guide parameters and assessed by multivariate analysis. Method performance was considered satisfactory since mean recoveries were between 87% and 101% for three distinct concentrations. Accuracy and precision were lower than ±20%, and led to no significant differences (p < 0.05) between results obtained by GC-ECD and GC-MS/MS techniques. The method has been applied to routine analysis for determination of pyrethroid residues in bovine raw milk in the Brazilian National Residue Control Plan since 2013, in which a total of 50 samples were analyzed. PMID:25380457

A system to build distributed multivariate models and manage disparate data sharing policies: implementation in the scalable national network for effectiveness research.

PubMed

Meeker, Daniella; Jiang, Xiaoqian; Matheny, Michael E; Farcas, Claudiu; D'Arcy, Michel; Pearlman, Laura; Nookala, Lavanya; Day, Michele E; Kim, Katherine K; Kim, Hyeoneui; Boxwala, Aziz; El-Kareh, Robert; Kuo, Grace M; Resnic, Frederic S; Kesselman, Carl; Ohno-Machado, Lucila

2015-11-01

Centralized and federated models for sharing data in research networks currently exist. To build multivariate data analysis for centralized networks, transfer of patient-level data to a central computation resource is necessary. The authors implemented distributed multivariate models for federated networks in which patient-level data is kept at each site and data exchange policies are managed in a study-centric manner. The objective was to implement infrastructure that supports the functionality of some existing research networks (e.g., cohort discovery, workflow management, and estimation of multivariate analytic models on centralized data) while adding additional important new features, such as algorithms for distributed iterative multivariate models, a graphical interface for multivariate model specification, synchronous and asynchronous response to network queries, investigator-initiated studies, and study-based control of staff, protocols, and data sharing policies. Based on the requirements gathered from statisticians, administrators, and investigators from multiple institutions, the authors developed infrastructure and tools to support multisite comparative effectiveness studies using web services for multivariate statistical estimation in the SCANNER federated network. The authors implemented massively parallel (map-reduce) computation methods and a new policy management system to enable each study initiated by network participants to define the ways in which data may be processed, managed, queried, and shared. The authors illustrated the use of these systems among institutions with highly different policies and operating under different state laws. Federated research networks need not limit distributed query functionality to count queries, cohort discovery, or independently estimated analytic models. Multivariate analyses can be efficiently and securely conducted without patient-level data transport, allowing institutions with strict local data storage requirements to participate in sophisticated analyses based on federated research networks. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Machtay, Mitchell, E-mail: mitchell.machtay@uhhospitals.org; Moughan, Jennifer; Farach, Andrew

Purpose: Concurrent chemoradiation therapy (CCRT) for squamous cell carcinoma of the head and neck (SCCHN) increases local tumor control but at the expense of increased toxicity. We recently showed that several clinical/pretreatment factors were associated with the occurrence of severe late toxicity. This study evaluated the potential relationship between radiation dose delivered to the pharyngeal wall and toxicity. Methods and Materials: This was an analysis of long-term survivors from 3 previously reported Radiation Therapy Oncology Group (RTOG) trials of CCRT for locally advanced SCCHN (RTOG trials 91-11, 97-03, and 99-14). Severe late toxicity was defined in this secondary analysis asmore » chronic grade 3-4 pharyngeal/laryngeal toxicity and/or requirement for a feeding tube {>=}2 years after registration and/or potential treatment-related death (eg, pneumonia) within 3 years. Radiation dosimetry (2-dimensional) analysis was performed centrally at RTOG headquarters to estimate doses to 4 regions of interest along the pharyngeal wall (superior oropharynx, inferior oropharynx, superior hypopharynx, and inferior hypopharynx). Case-control analysis was performed with a multivariate logistic regression model that included pretreatment and treatment potential factors. Results: A total of 154 patients were evaluable for this analysis, 71 cases (patients with severe late toxicities) and 83 controls; thus, 46% of evaluable patients had a severe late toxicity. On multivariate analysis, significant variables correlated with the development of severe late toxicity, including older age (odds ratio, 1.062 per year; P=.0021) and radiation dose received by the inferior hypopharynx (odds ratio, 1.023 per Gy; P=.016). The subgroup of patients receiving {<=}60 Gy to the inferior hypopharynx had a 40% rate of severe late toxicity compared with 56% for patients receiving >60 Gy. Oropharyngeal dose was not associated with this outcome. Conclusions: Severe late toxicity following CCRT is common in long-term survivors. Age is the most significant factor, but hypopharyngeal dose also was associated.« less

An Improved Method to Control the Critical Parameters of a Multivariable Control System

NASA Astrophysics Data System (ADS)

Subha Hency Jims, P.; Dharmalingam, S.; Wessley, G. Jims John

2017-10-01

The role of control systems is to cope with the process deficiencies and the undesirable effect of the external disturbances. Most of the multivariable processes are highly iterative and complex in nature. Aircraft systems, Modern Power Plants, Refineries, Robotic systems are few such complex systems that involve numerous critical parameters that need to be monitored and controlled. Control of these important parameters is not only tedious and cumbersome but also is crucial from environmental, safety and quality perspective. In this paper, one such multivariable system, namely, a utility boiler has been considered. A modern power plant is a complex arrangement of pipework and machineries with numerous interacting control loops and support systems. In this paper, the calculation of controller parameters based on classical tuning concepts has been presented. The controller parameters thus obtained and employed has controlled the critical parameters of a boiler during fuel switching disturbances. The proposed method can be applied to control the critical parameters like elevator, aileron, rudder, elevator trim rudder and aileron trim, flap control systems of aircraft systems.

Influences on parental acceptance of HPV vaccination in demonstration projects in Uganda and Vietnam.

PubMed

Galagan, Sean R; Paul, Proma; Menezes, Lysander; LaMontagne, D Scott

2013-06-26

This study investigates the effect of communication strategies on human papillomavirus (HPV) vaccine uptake in HPV vaccine demonstration projects in Uganda and Vietnam. Secondary analysis was conducted on data from surveys of a representative sample of parents and guardians of girls eligible for HPV vaccine, measuring three-dose coverage achieved in demonstration projects in 2008-2010. Univariate and multivariate logistic regression analysis calculated the unadjusted and adjusted odds of receiving at least one dose of HPV vaccine depending on exposure to community influencers; information, education, and communication (IEC) channels; and demographic factors. This study found that exposure to community influencers was associated with HPV vaccine uptake in a multivariate model controlling for other factors. Exposure to non-interactive IEC channels was only marginally associated with HPV vaccine uptake. These results underscore the need of HPV vaccine programs in low- and middle-income countries to involve and utilize key community influencers and stakeholders to maximize HPV vaccine uptake. Copyright © 2013 Elsevier Ltd. All rights reserved.

The Impact of Asking Intention or Self-Prediction Questions on Subsequent Behavior

PubMed Central

Wood, Chantelle; Conner, Mark; Miles, Eleanor; Sandberg, Tracy; Taylor, Natalie; Godin, Gaston; Sheeran, Paschal

2015-01-01

The current meta-analysis estimated the magnitude of the impact of asking intention and self-prediction questions on rates of subsequent behavior, and examined mediators and moderators of this question–behavior effect (QBE). Random-effects meta-analysis on 116 published tests of the effect indicated that intention/prediction questions have a small positive effect on behavior (d+ = 0.24). Little support was observed for attitude accessibility, cognitive dissonance, behavioral simulation, or processing fluency explanations of the QBE. Multivariate analyses indicated significant effects of social desirability of behavior/behavior domain (larger effects for more desirable and less risky behaviors), difficulty of behavior (larger effects for easy-to-perform behaviors), and sample type (larger effects among student samples). Although this review controls for co-occurrence of moderators in multivariate analyses, future primary research should systematically vary moderators in fully factorial designs. Further primary research is also needed to unravel the mechanisms underlying different variants of the QBE. PMID:26162771

Multivariate analysis of heavy metal contents in soils, sediments and water in the region of Meknes (central Morocco).

PubMed

Tahri, M; Benyaïch, F; Bounakhla, M; Bilal, E; Gruffat, J J; Moutte, J; Garcia, D

2005-03-01

Concentrations of Al, Fe, Cr, Cu, Ni, Pb and Zn in soils, sediments and water samples collected along the Oued Boufekrane river (Meknes, central Morocco) were determined. In soils, a homogeneous distribution of metal concentrations was observed throughout the study area except for Pb, which presents high enrichment at sites located at the vicinity of a main highway. In sediments, high enrichment, with respect to upstream sites, were observed downstream of the city of Meknes for Al, Cr, Fe and Ni and inside the city for Cu, Zn and Pb. In water samples, the metal contents showed to correlate with their homologues in sediments suggesting that the metal contents in water and sediments have identical origins. Descriptive statistics and multivariate analysis (principal factor method, PFM) were used to assist the interpretation of elemental data. This allowed the determination of the correlations between the metals and the identification of three main factor loadings controlling the metal variability in soils and sediments.

Designing a risk-based surveillance program for Mycobacterium avium ssp. paratuberculosis in Norwegian dairy herds using multivariate statistical process control analysis.

PubMed

Whist, A C; Liland, K H; Jonsson, M E; Sæbø, S; Sviland, S; Østerås, O; Norström, M; Hopp, P

2014-11-01

Surveillance programs for animal diseases are critical to early disease detection and risk estimation and to documenting a population's disease status at a given time. The aim of this study was to describe a risk-based surveillance program for detecting Mycobacterium avium ssp. paratuberculosis (MAP) infection in Norwegian dairy cattle. The included risk factors for detecting MAP were purchase of cattle, combined cattle and goat farming, and location of the cattle farm in counties containing goats with MAP. The risk indicators included production data [culling of animals >3 yr of age, carcass conformation of animals >3 yr of age, milk production decrease in older lactating cows (lactations 3, 4, and 5)], and clinical data (diarrhea, enteritis, or both, in animals >3 yr of age). Except for combined cattle and goat farming and cattle farm location, all data were collected at the cow level and summarized at the herd level. Predefined risk factors and risk indicators were extracted from different national databases and combined in a multivariate statistical process control to obtain a risk assessment for each herd. The ordinary Hotelling's T(2) statistic was applied as a multivariate, standardized measure of difference between the current observed state and the average state of the risk factors for a given herd. To make the analysis more robust and adapt it to the slowly developing nature of MAP, monthly risk calculations were based on data accumulated during a 24-mo period. Monitoring of these variables was performed to identify outliers that may indicate deviance in one or more of the underlying processes. The highest-ranked herds were scattered all over Norway and clustered in high-density dairy cattle farm areas. The resulting rankings of herds are being used in the national surveillance program for MAP in 2014 to increase the sensitivity of the ongoing surveillance program in which 5 fecal samples for bacteriological examination are collected from 25 dairy herds. The use of multivariate statistical process control for selection of herds will be beneficial when a diagnostic test suitable for mass screening is available and validated on the Norwegian cattle population, thus making it possible to increase the number of sampled herds. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Gain-scheduling multivariable LPV control of an irrigation canal system.

PubMed

Bolea, Yolanda; Puig, Vicenç

2016-07-01

The purpose of this paper is to present a multivariable linear parameter varying (LPV) controller with a gain scheduling Smith Predictor (SP) scheme applicable to open-flow canal systems. This LPV controller based on SP is designed taking into account the uncertainty in the estimation of delay and the variation of plant parameters according to the operating point. This new methodology can be applied to a class of delay systems that can be represented by a set of models that can be factorized into a rational multivariable model in series with left/right diagonal (multiple) delays, such as, the case of irrigation canals. A multiple pool canal system is used to test and validate the proposed control approach. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Multi-variant study of obesity risk genes in African Americans: The Jackson Heart Study.

PubMed

Liu, Shijian; Wilson, James G; Jiang, Fan; Griswold, Michael; Correa, Adolfo; Mei, Hao

2016-11-30

Genome-wide association study (GWAS) has been successful in identifying obesity risk genes by single-variant association analysis. For this study, we designed steps of analysis strategy and aimed to identify multi-variant effects on obesity risk among candidate genes. Our analyses were focused on 2137 African American participants with body mass index measured in the Jackson Heart Study and 657 common single nucleotide polymorphisms (SNPs) genotyped at 8 GWAS-identified obesity risk genes. Single-variant association test showed that no SNPs reached significance after multiple testing adjustment. The following gene-gene interaction analysis, which was focused on SNPs with unadjusted p-value<0.10, identified 6 significant multi-variant associations. Logistic regression showed that SNPs in these associations did not have significant linear interactions; examination of genetic risk score evidenced that 4 multi-variant associations had significant additive effects of risk SNPs; and haplotype association test presented that all multi-variant associations contained one or several combinations of particular alleles or haplotypes, associated with increased obesity risk. Our study evidenced that obesity risk genes generated multi-variant effects, which can be additive or non-linear interactions, and multi-variant study is an important supplement to existing GWAS for understanding genetic effects of obesity risk genes. Copyright © 2016 Elsevier B.V. All rights reserved.

COMT Val158Met polymorphism is associated with post-traumatic stress disorder and functional outcome following mild traumatic brain injury

PubMed Central

Winkler, Ethan A.; Yue, John K.; Ferguson, Adam R.; Temkin, Nancy R.; Stein, Murray B.; Barber, Jason; Yuh, Esther L.; Sharma, Sourabh; Satris, Gabriela G.; McAllister, Thomas W.; Rosand, Jonathan; Sorani, Marco D.; Lingsma, Hester F.; Tarapore, Phiroz E.; Burchard, Esteban G.; Hu, Donglei; Eng, Celeste; Wang, Kevin K.W.; Mukherjee, Pratik; Okonkwo, David O.; Diaz-Arrastia, Ramon; Manley, Geoffrey T.

2017-01-01

Mild traumatic brain injury (mTBI) results in variable clinical trajectories and outcomes. The source of variability remains unclear, but may involve genetic variations, such as single nucleotide polymorphisms (SNPs). A SNP in catechol-o-methyltransferase (COMT) is suggested to influence development of post-traumatic stress disorder (PTSD), but its role in TBI remains unclear. Here, we utilize the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study to investigate whether the COMT Val158Met polymorphism is associated with PTSD and global functional outcome as measured by the PTSD Checklist – Civilian Version and Glasgow Outcome Scale Extended (GOSE), respectively. Results in 93 predominately Caucasian subjects with mTBI show that the COMT Met158 allele is associated with lower incidence of PTSD (univariate odds ratio (OR) of 0.25, 95% CI [0.09–0.69]) and higher GOSE scores (univariate OR 2.87, 95% CI [1.20–6.86]) 6-months following injury. The COMT Val158Met genotype and PTSD association persists after controlling for race (multivariable OR of 0.29, 95% CI [0.10–0.83]) and pre-existing psychiatric disorders/substance abuse (multivariable OR of 0.32, 95% CI [0.11–0.97]). PTSD emerged as a strong predictor of poorer outcome on GOSE (multivariable OR 0.09, 95% CI [0.03–0.26]), which persists after controlling for age, GCS, and race. When accounting for PTSD in multivariable analysis, the association of COMT genotype and GOSE did not remain significant (multivariable OR 1.73, 95% CI [0.69–4.35]). Whether COMT genotype indirectly influences global functional outcome through PTSD remains to be determined and larger studies in more diverse populations are needed to confirm these findings. PMID:27769642

COMT Val158Met polymorphism is associated with post-traumatic stress disorder and functional outcome following mild traumatic brain injury.

PubMed

Winkler, Ethan A; Yue, John K; Ferguson, Adam R; Temkin, Nancy R; Stein, Murray B; Barber, Jason; Yuh, Esther L; Sharma, Sourabh; Satris, Gabriela G; McAllister, Thomas W; Rosand, Jonathan; Sorani, Marco D; Lingsma, Hester F; Tarapore, Phiroz E; Burchard, Esteban G; Hu, Donglei; Eng, Celeste; Wang, Kevin K W; Mukherjee, Pratik; Okonkwo, David O; Diaz-Arrastia, Ramon; Manley, Geoffrey T

2017-01-01

Mild traumatic brain injury (mTBI) results in variable clinical trajectories and outcomes. The source of variability remains unclear, but may involve genetic variations, such as single nucleotide polymorphisms (SNPs). A SNP in catechol-o-methyltransferase (COMT) is suggested to influence development of post-traumatic stress disorder (PTSD), but its role in TBI remains unclear. Here, we utilize the Transforming Research and Clinical Knowledge in Traumatic Brain Injury Pilot (TRACK-TBI Pilot) study to investigate whether the COMT Val 158 Met polymorphism is associated with PTSD and global functional outcome as measured by the PTSD Checklist - Civilian Version and Glasgow Outcome Scale Extended (GOSE), respectively. Results in 93 predominately Caucasian subjects with mTBI show that the COMT Met 158 allele is associated with lower incidence of PTSD (univariate odds ratio (OR) of 0.25, 95% CI [0.09-0.69]) and higher GOSE scores (univariate OR 2.87, 95% CI [1.20-6.86]) 6-months following injury. The COMT Val 158 Met genotype and PTSD association persists after controlling for race (multivariable OR of 0.29, 95% CI [0.10-0.83]) and pre-existing psychiatric disorders/substance abuse (multivariable OR of 0.32, 95% CI [0.11-0.97]). PTSD emerged as a strong predictor of poorer outcome on GOSE (multivariable OR 0.09, 95% CI [0.03-0.26]), which persists after controlling for age, GCS, and race. When accounting for PTSD in multivariable analysis, the association of COMT genotype and GOSE did not remain significant (multivariable OR 1.73, 95% CI [0.69-4.35]). Whether COMT genotype indirectly influences global functional outcome through PTSD remains to be determined and larger studies in more diverse populations are needed to confirm these findings. Copyright © 2016 Elsevier Ltd. All rights reserved.

On the potential for the Partial Triadic Analysis to grasp the spatio-temporal variability of groundwater hydrochemistry

NASA Astrophysics Data System (ADS)

Gourdol, L.; Hissler, C.; Pfister, L.

2012-04-01

The Luxembourg sandstone aquifer is of major relevance for the national supply of drinking water in Luxembourg. The city of Luxembourg (20% of the country's population) gets almost 2/3 of its drinking water from this aquifer. As a consequence, the study of both the groundwater hydrochemistry, as well as its spatial and temporal variations, are considered as of highest priority. Since 2005, a monitoring network has been implemented by the Water Department of Luxembourg City, with a view to a more sustainable management of this strategic water resource. The data collected to date forms a large and complex dataset, describing spatial and temporal variations of many hydrochemical parameters. The data treatment issue is tightly connected to this kind of water monitoring programs and complex databases. Standard multivariate statistical techniques, such as principal components analysis and hierarchical cluster analysis, have been widely used as unbiased methods for extracting meaningful information from groundwater quality data and are now classically used in many hydrogeological studies, in particular to characterize temporal or spatial hydrochemical variations induced by natural and anthropogenic factors. But these classical multivariate methods deal with two-way matrices, usually parameters/sites or parameters/time, while often the dataset resulting from qualitative water monitoring programs should be seen as a datacube parameters/sites/time. Three-way matrices, such as the one we propose here, are difficult to handle and to analyse by classical multivariate statistical tools and thus should be treated with approaches dealing with three-way data structures. One possible analysis approach consists in the use of partial triadic analysis (PTA). The PTA was previously used with success in many ecological studies but never to date in the domain of hydrogeology. Applied to the dataset of the Luxembourg Sandstone aquifer, the PTA appears as a new promising statistical instrument for hydrogeologists, in particular to characterize temporal and spatial hydrochemical variations induced by natural and anthropogenic factors. This new approach for groundwater management offers potential for 1) identifying a common multivariate spatial structure, 2) untapping the different hydrochemical patterns and explaining their controlling factors and 3) analysing the temporal variability of this structure and grasping hydrochemical changes.

A tool for classifying individuals with chronic back pain: using multivariate pattern analysis with functional magnetic resonance imaging data.

PubMed

Callan, Daniel; Mills, Lloyd; Nott, Connie; England, Robert; England, Shaun

2014-01-01

Chronic pain is one of the most prevalent health problems in the world today, yet neurological markers, critical to diagnosis of chronic pain, are still largely unknown. The ability to objectively identify individuals with chronic pain using functional magnetic resonance imaging (fMRI) data is important for the advancement of diagnosis, treatment, and theoretical knowledge of brain processes associated with chronic pain. The purpose of our research is to investigate specific neurological markers that could be used to diagnose individuals experiencing chronic pain by using multivariate pattern analysis with fMRI data. We hypothesize that individuals with chronic pain have different patterns of brain activity in response to induced pain. This pattern can be used to classify the presence or absence of chronic pain. The fMRI experiment consisted of alternating 14 seconds of painful electric stimulation (applied to the lower back) with 14 seconds of rest. We analyzed contrast fMRI images in stimulation versus rest in pain-related brain regions to distinguish between the groups of participants: 1) chronic pain and 2) normal controls. We employed supervised machine learning techniques, specifically sparse logistic regression, to train a classifier based on these contrast images using a leave-one-out cross-validation procedure. We correctly classified 92.3% of the chronic pain group (N = 13) and 92.3% of the normal control group (N = 13) by recognizing multivariate patterns of activity in the somatosensory and inferior parietal cortex. This technique demonstrates that differences in the pattern of brain activity to induced pain can be used as a neurological marker to distinguish between individuals with and without chronic pain. Medical, legal and business professionals have recognized the importance of this research topic and of developing objective measures of chronic pain. This method of data analysis was very successful in correctly classifying each of the two groups.

A Tool for Classifying Individuals with Chronic Back Pain: Using Multivariate Pattern Analysis with Functional Magnetic Resonance Imaging Data

PubMed Central

Callan, Daniel; Mills, Lloyd; Nott, Connie; England, Robert; England, Shaun

2014-01-01

Chronic pain is one of the most prevalent health problems in the world today, yet neurological markers, critical to diagnosis of chronic pain, are still largely unknown. The ability to objectively identify individuals with chronic pain using functional magnetic resonance imaging (fMRI) data is important for the advancement of diagnosis, treatment, and theoretical knowledge of brain processes associated with chronic pain. The purpose of our research is to investigate specific neurological markers that could be used to diagnose individuals experiencing chronic pain by using multivariate pattern analysis with fMRI data. We hypothesize that individuals with chronic pain have different patterns of brain activity in response to induced pain. This pattern can be used to classify the presence or absence of chronic pain. The fMRI experiment consisted of alternating 14 seconds of painful electric stimulation (applied to the lower back) with 14 seconds of rest. We analyzed contrast fMRI images in stimulation versus rest in pain-related brain regions to distinguish between the groups of participants: 1) chronic pain and 2) normal controls. We employed supervised machine learning techniques, specifically sparse logistic regression, to train a classifier based on these contrast images using a leave-one-out cross-validation procedure. We correctly classified 92.3% of the chronic pain group (N = 13) and 92.3% of the normal control group (N = 13) by recognizing multivariate patterns of activity in the somatosensory and inferior parietal cortex. This technique demonstrates that differences in the pattern of brain activity to induced pain can be used as a neurological marker to distinguish between individuals with and without chronic pain. Medical, legal and business professionals have recognized the importance of this research topic and of developing objective measures of chronic pain. This method of data analysis was very successful in correctly classifying each of the two groups. PMID:24905072

Risk Factors for Urinary Tract Infections in Cardiac Surgical Patients

PubMed Central

Gillen, Jacob R.; Isbell, James M.; Michaels, Alex D.; Lau, Christine L.

2015-01-01

Abstract Background: Risk factors for catheter-associated urinary tract infections (CAUTIs) in patients undergoing non-cardiac surgical procedures have been well documented. However, the variables associated with CAUTIs in the cardiac surgical population have not been clearly defined. Therefore, the purpose of this study was to investigate risk factors associated with CAUTIs in patients undergoing cardiac procedures. Methods: All patients undergoing cardiac surgery at a single institution from 2006 through 2012 (4,883 patients) were reviewed. Patients with U.S. Centers for Disease Control (CDC) criteria for CAUTI were identified from the hospital's Quality Assessment database. Pre-operative, operative, and post-operative patient factors were evaluated. Univariate and multivariable analyses were used to identify significant correlations between perioperative characteristics and CAUTIs. Results: There were 55 (1.1%) documented CAUTIs in the study population. On univariate analysis, older age, female gender, diabetes mellitus, cardiogenic shock, urgent or emergent operation, packed red blood cell (PRBC) units transfused, and intensive care unit length of stay (ICU LOS) were all significantly associated with CAUTI [p<0.05]. On multivariable logistic regression, older age, female gender, diabetes mellitus, and ICU LOS remained significantly associated with CAUTI. Additionally, there was a significant association between CAUTI and 30-d mortality on univariate analysis. However, when controlling for common predictors of operative mortality on multivariable analysis, CAUTI was no longer associated with mortality. Conclusions: There are several identifiable risk factors for CAUTI in patients undergoing cardiac procedures. CAUTI is not independently associated with increased mortality, but it does serve as a marker of sicker patients more likely to die from other comorbidities or complications. Therefore, awareness of the high-risk nature of these patients should lead to increased diligence and may help to improve peri-operative outcomes. Recognizing patients at high risk for CAUTI may lead to improved measures to decrease CAUTI rates within this population. PMID:26115336

Risk Factors for Urinary Tract Infections in Cardiac Surgical Patients.

PubMed

Gillen, Jacob R; Isbell, James M; Michaels, Alex D; Lau, Christine L; Sawyer, Robert G

2015-10-01

Risk factors for catheter-associated urinary tract infections (CAUTIs) in patients undergoing non-cardiac surgical procedures have been well documented. However, the variables associated with CAUTIs in the cardiac surgical population have not been clearly defined. Therefore, the purpose of this study was to investigate risk factors associated with CAUTIs in patients undergoing cardiac procedures. All patients undergoing cardiac surgery at a single institution from 2006 through 2012 (4,883 patients) were reviewed. Patients with U.S. Centers for Disease Control (CDC) criteria for CAUTI were identified from the hospital's Quality Assessment database. Pre-operative, operative, and post-operative patient factors were evaluated. Univariate and multivariable analyses were used to identify significant correlations between perioperative characteristics and CAUTIs. There were 55 (1.1%) documented CAUTIs in the study population. On univariate analysis, older age, female gender, diabetes mellitus, cardiogenic shock, urgent or emergent operation, packed red blood cell (PRBC) units transfused, and intensive care unit length of stay (ICU LOS) were all significantly associated with CAUTI [p<0.05]. On multivariable logistic regression, older age, female gender, diabetes mellitus, and ICU LOS remained significantly associated with CAUTI. Additionally, there was a significant association between CAUTI and 30-d mortality on univariate analysis. However, when controlling for common predictors of operative mortality on multivariable analysis, CAUTI was no longer associated with mortality. There are several identifiable risk factors for CAUTI in patients undergoing cardiac procedures. CAUTI is not independently associated with increased mortality, but it does serve as a marker of sicker patients more likely to die from other comorbidities or complications. Therefore, awareness of the high-risk nature of these patients should lead to increased diligence and may help to improve peri-operative outcomes. Recognizing patients at high risk for CAUTI may lead to improved measures to decrease CAUTI rates within this population.

Acoustic neuroma: potential risk factors and audiometric surveillance in the aluminium industry.

PubMed

Taiwo, Oyebode; Galusha, Deron; Tessier-Sherman, Baylah; Kirsche, Sharon; Cantley, Linda; Slade, Martin D; Cullen, Mark R; Donoghue, A Michael

2014-09-01

To look for an association between acoustic neuroma (AN) and participation in a hearing conservation programme (HCP) and also for an association between AN and possible occupational risk factors in the aluminium industry. We conducted a case-control analysis of a population of US aluminium production workers in 8 smelters and 43 other plants. Using insurance claims data, 97 cases of AN were identified between 1996 and 2009. Each was matched with four controls. Covariates included participation in a HCP, working in an aluminium smelter, working in an electrical job and hearing loss. In the bivariate analyses, covariates associated with AN were participation in the HCP (OR=1.72; 95% CI 1.09 to 2.69) and smelter work (OR=1.88; 95% CI 1.06 to 3.36). Electrical work was not significant (OR=1.60; 95% CI 0.65 to 3.94). Owing to high participation in the HCP in smelters, multivariate subanalyses were required. In the multivariate analyses, participation in the HCP was the only statistically significant risk factor for AN. In the multivariate analysis restricted to employees not working in a smelter, the OR was 1.81 (95% CI 1.04 to 3.17). Hearing loss, an indirect measure of in-ear noise dose, was not predictive of AN. Our results suggest the incidental detection of previously undiagnosed tumours in workers who participated in the company-sponsored HCP. The increased medical surveillance among this population of workers most likely introduced detection bias, leading to the identification of AN cases that would have otherwise remained undetected. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Heritability of somatotype components from early adolescence into young adulthood: a multivariate analysis on a longitudinal twin study.

PubMed

Peeters, M W; Thomis, M A; Claessens, A L; Loos, R J F; Maes, H H M; Lysens, R; Vanden Eynde, B; Vlietinck, R; Beunen, G

2003-01-01

Several studies with different designs have attempted to estimate the heritability of somatotype components. However they often ignore the covariation between the three components as well as possible sex and age effects. Shared environmental factors are not always controlled for. This study explores the pattern of genetic and environmental determination of the variation in Heath-Carter somatotype components from early adolescence into young adulthood. Data from the Leuven Longitudinal Twin Study, a longitudinal sample of Belgian same-aged twins followed from 10 to 18 years (n = 105 pairs, equally divided over five zygosity groups), is entered into a multivariate path analysis. Thus the covariation between the somatotype components is taken into account, gender heterogeneity can be tested, common environmental influences can be distinguished from genetic effects and age effects are controlled for. Heritability estimates from 10 to 18 years range from 0.21 to 0.88, 0.46 to 0.76 and 0.16 to 0.73 for endomorphy, mesomorphy and ectomorphy in boys. In girls, heritability estimates range from 0.76 to 0.89, 0.36 to 0.57 and 0.57 to 0.76 for the respective somatotype components. Sex differences are significant from 14 years onwards. More than half of the variance in all somatotype components for both sexes at all time points is explained by factors the three components have in common. The finding of substantial genetic influence on the variability of somatotype components is further supported. The need to consider somatotype as a whole is stressed as well as the need for sex- and perhaps age-specific analyses. Further multivariate analyses are needed to confirm the present findings.

Use of chemometrics to compare NIR and HPLC for the simultaneous determination of drug levels in fixed-dose combination tablets employed in tuberculosis treatment.

PubMed

Teixeira, Kelly Sivocy Sampaio; da Cruz Fonseca, Said Gonçalves; de Moura, Luís Carlos Brigido; de Moura, Mario Luís Ribeiro; Borges, Márcia Herminia Pinheiro; Barbosa, Euzébio Guimaraes; De Lima E Moura, Túlio Flávio Accioly

2018-02-05

The World Health Organization recommends that TB treatment be administered using combination therapy. The methodologies for quantifying simultaneously associated drugs are highly complex, being costly, extremely time consuming and producing chemical residues harmful to the environment. The need to seek alternative techniques that minimize these drawbacks is widely discussed in the pharmaceutical industry. Therefore, the objective of this study was to develop and validate a multivariate calibration model in association with the near infrared spectroscopy technique (NIR) for the simultaneous determination of rifampicin, isoniazid, pyrazinamide and ethambutol. These models allow the quality control of these medicines to be optimized using simple, fast, low-cost techniques that produce no chemical waste. In the NIR - PLS method, spectra readings were acquired in the 10,000-4000cm -1 range using an infrared spectrophotometer (IRPrestige - 21 - Shimadzu) with a resolution of 4cm -1 , 20 sweeps, under controlled temperature and humidity. For construction of the model, the central composite experimental design was employed on the program Statistica 13 (StatSoft Inc.). All spectra were treated by computational tools for multivariate analysis using partial least squares regression (PLS) on the software program Pirouette 3.11 (Infometrix, Inc.). Variable selections were performed by the QSAR modeling program. The models developed by NIR in association with multivariate analysis provided good prediction of the APIs for the external samples and were therefore validated. For the tablets, however, the slightly different quantitative compositions of excipients compared to the mixtures prepared for building the models led to results that were not statistically similar, despite having prediction errors considered acceptable in the literature. Copyright © 2017 Elsevier B.V. All rights reserved.

Instrumental Neutron Activation Analysis and Multivariate Statistics for Pottery Provenance

NASA Astrophysics Data System (ADS)

Glascock, M. D.; Neff, H.; Vaughn, K. J.

2004-06-01

The application of instrumental neutron activation analysis and multivariate statistics to archaeological studies of ceramics and clays is described. A small pottery data set from the Nasca culture in southern Peru is presented for illustration.

A systems theoretic approach to analysis and control of mammalian circadian dynamics

PubMed Central

Abel, John H.; Doyle, Francis J.

2016-01-01

The mammalian circadian clock is a complex multi-scale, multivariable biological control system. In the past two decades, methods from systems engineering have led to numerous insights into the architecture and functionality of this system. In this review, we examine the mammalian circadian system through a process systems lens. We present a mathematical framework for examining the cellular circadian oscillator, and show recent extensions for understanding population-scale dynamics. We provide an overview of the routes by which the circadian system can be systemically manipulated, and present in silico proof of concept results for phase resetting of the clock via model predictive control. PMID:28496287

A Study of Effects of MultiCollinearity in the Multivariable Analysis

PubMed Central

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; (Peter) He, Qinghua; Lillard, James W.

2015-01-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables. PMID:25664257

A Study of Effects of MultiCollinearity in the Multivariable Analysis.

PubMed

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; Peter He, Qinghua; Lillard, James W

2014-10-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables.

Multivariable control of a twin lift helicopter system using the LQG/LTR design methodology

NASA Technical Reports Server (NTRS)

Rodriguez, A. A.; Athans, M.

1986-01-01

Guidelines for developing a multivariable centralized automatic flight control system (AFCS) for a twin lift helicopter system (TLHS) are presented. Singular value ideas are used to formulate performance and stability robustness specifications. A linear Quadratic Gaussian with Loop Transfer Recovery (LQG/LTR) design is obtained and evaluated.

Controlled Multivariate Evaluation of Open Education: Application of a Critical Model.

ERIC Educational Resources Information Center

Sewell, Alan F.; And Others

This paper continues previous reports of a controlled multivariate evaluation of a junior high school open-education program. A new method of estimating program objectives and implementation is presented, together with the nature and degree of obtained student outcomes. Open-program students were found to approve more highly of their learning…

Model transformations for state-space self-tuning control of multivariable stochastic systems

NASA Technical Reports Server (NTRS)

Shieh, Leang S.; Bao, Yuan L.; Coleman, Norman P.

1988-01-01

The design of self-tuning controllers for multivariable stochastic systems is considered analytically. A long-division technique for finding the similarity transformation matrix and transforming the estimated left MFD to the right MFD is developed; the derivation is given in detail, and the procedures involved are briefly characterized.

Multivariable model predictive control design of reactive distillation column for Dimethyl Ether production

NASA Astrophysics Data System (ADS)

Wahid, A.; Putra, I. G. E. P.

2018-03-01

Dimethyl ether (DME) as an alternative clean energy has attracted a growing attention in the recent years. DME production via reactive distillation has potential for capital cost and energy requirement savings. However, combination of reaction and distillation on a single column makes reactive distillation process a very complex multivariable system with high non-linearity of process and strong interaction between process variables. This study investigates a multivariable model predictive control (MPC) based on two-point temperature control strategy for the DME reactive distillation column to maintain the purities of both product streams. The process model is estimated by a first order plus dead time model. The DME and water purity is maintained by controlling a stage temperature in rectifying and stripping section, respectively. The result shows that the model predictive controller performed faster responses compared to conventional PI controller that are showed by the smaller ISE values. In addition, the MPC controller is able to handle the loop interactions well.

Localization of genes involved in the metabolic syndrome using multivariate linkage analysis.

PubMed

Olswold, Curtis; de Andrade, Mariza

2003-12-31

There are no well accepted criteria for the diagnosis of the metabolic syndrome. However, the metabolic syndrome is identified clinically by the presence of three or more of these five variables: larger waist circumference, higher triglyceride levels, lower HDL-cholesterol concentrations, hypertension, and impaired fasting glucose. We use sets of two or three variables, which are available in the Framingham Heart Study data set, to localize genes responsible for this syndrome using multivariate quantitative linkage analysis. This analysis demonstrates the applicability of using multivariate linkage analysis and how its use increases the power to detect linkage when genes are involved in the same disease mechanism.

Evaluation of an F100 multivariable control using a real-time engine simulation

NASA Technical Reports Server (NTRS)

Szuch, J. R.; Soeder, J. F.; Skira, C.

1977-01-01

The control evaluated has been designed for the F100-PW-100 turbofan engine. The F100 engine represents the current state-of-the-art in aircraft gas turbine technology. The control makes use of a multivariable, linear quadratic regulator. The evaluation procedure employed utilized a real-time hybrid computer simulation of the F100 engine and an implementation of the control logic on the NASA LeRC digital computer/controller. The results of the evaluation indicated that the control logic and its implementation will be capable of controlling the engine throughout its operating range.

Multivariate frequency domain analysis of protein dynamics

NASA Astrophysics Data System (ADS)

Matsunaga, Yasuhiro; Fuchigami, Sotaro; Kidera, Akinori

2009-03-01

Multivariate frequency domain analysis (MFDA) is proposed to characterize collective vibrational dynamics of protein obtained by a molecular dynamics (MD) simulation. MFDA performs principal component analysis (PCA) for a bandpass filtered multivariate time series using the multitaper method of spectral estimation. By applying MFDA to MD trajectories of bovine pancreatic trypsin inhibitor, we determined the collective vibrational modes in the frequency domain, which were identified by their vibrational frequencies and eigenvectors. At near zero temperature, the vibrational modes determined by MFDA agreed well with those calculated by normal mode analysis. At 300 K, the vibrational modes exhibited characteristic features that were considerably different from the principal modes of the static distribution given by the standard PCA. The influences of aqueous environments were discussed based on two different sets of vibrational modes, one derived from a MD simulation in water and the other from a simulation in vacuum. Using the varimax rotation, an algorithm of the multivariate statistical analysis, the representative orthogonal set of eigenmodes was determined at each vibrational frequency.

Imaging of polysaccharides in the tomato cell wall with Raman microspectroscopy

PubMed Central

2014-01-01

Background The primary cell wall of fruits and vegetables is a structure mainly composed of polysaccharides (pectins, hemicelluloses, cellulose). Polysaccharides are assembled into a network and linked together. It is thought that the percentage of components and of plant cell wall has an important influence on mechanical properties of fruits and vegetables. Results In this study the Raman microspectroscopy technique was introduced to the visualization of the distribution of polysaccharides in cell wall of fruit. The methodology of the sample preparation, the measurement using Raman microscope and multivariate image analysis are discussed. Single band imaging (for preliminary analysis) and multivariate image analysis methods (principal component analysis and multivariate curve resolution) were used for the identification and localization of the components in the primary cell wall. Conclusions Raman microspectroscopy supported by multivariate image analysis methods is useful in distinguishing cellulose and pectins in the cell wall in tomatoes. It presents how the localization of biopolymers was possible with minimally prepared samples. PMID:24917885

A refined method for multivariate meta-analysis and meta-regression

PubMed Central

Jackson, Daniel; Riley, Richard D

2014-01-01

Making inferences about the average treatment effect using the random effects model for meta-analysis is problematic in the common situation where there is a small number of studies. This is because estimates of the between-study variance are not precise enough to accurately apply the conventional methods for testing and deriving a confidence interval for the average effect. We have found that a refined method for univariate meta-analysis, which applies a scaling factor to the estimated effects’ standard error, provides more accurate inference. We explain how to extend this method to the multivariate scenario and show that our proposal for refined multivariate meta-analysis and meta-regression can provide more accurate inferences than the more conventional approach. We explain how our proposed approach can be implemented using standard output from multivariate meta-analysis software packages and apply our methodology to two real examples. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:23996351

Comparison of the clinical efficacy between single-agent and dual-agent concurrent chemoradiotherapy in the treatment of unresectable esophageal squamous cell carcinoma: a multicenter retrospective analysis.

PubMed

Li, Jie; Gong, Youling; Diao, Peng; Huang, Qingmei; Wen, Yixue; Lin, Binwei; Cai, Hongwei; Tian, Honggang; He, Bing; Ji, Lanlan; Guo, Ping; Miao, Jidong; Du, Xiaobo

2018-01-22

Some Chinese patients with esophageal squamous cell carcinomaare often treated with single-agent concurrent chemoradiotherapy. However, no results have been reported from randomized controlled clinical trials comparing single-agent with double-agent concurrent chemoradiotherapy. It therefore remains unclear whether these regimens are equally clinically effective. In this study, we retrospectively analyzed and compared the therapeutic effects of single-agent and double-agent concurrent chemoradiotherapy in patients with unresectable esophageal squamous cell carcinoma. This study enrolled 168 patients who received definitive concurrent chemoradiotherapy for locally advanced unresectable esophageal squamous carcinoma at 10 hospitals between 2010 and 2015. We evaluated survival time and toxicity. The Kaplan-Meier method was used to estimate survival data. The log-rank test was used in univariate analysis A Cox proportional hazards regression model was used to conduct a multivariate analysis of the effects of prognostic factors on survival. In this study, 100 (59.5%) and 68 patients (40.5%) received single-agent and dual-agent combination chemoradiotherapy, respectively. The estimate 5-year progression-free survival (PFS) rate and overall survival (OS) rate of dual-agent therapy was higher than that of single-agent therapy (52.5% and 40.9%, 78.2% and 60.7%, respectively), but there were no significant differences (P = 0.367 and 0.161, respectively). Multivariate analysis showed that sex, age,and radiotherapy dose had no significant effects on OS or PFS. Only disease stage was associated with OS and PFS in the multivariable analysis (P = 0.006 and 0.003, respectively). In dual-agent group, the incidence of acute toxicity and the incidence of 3 and4 grade toxicity were higher than single-agent group. The 5-year PFS and OS rates of dual-agent therapy were higher than those of single-agent concurrent chemoradiotherapy for patients with unresectable esophageal squamous cell carcinoma; however, there were no significant differences in univariate analysis and multivariable analysis. Single-agent concurrent chemotherapy had less toxicity than a double-drug regimen. Therefore, we suggest that single therapis not inferior to dual therapy y. In the future, we aim to confirm our hypothesis through a prospective randomized study.

Exploring Raman spectroscopy for the evaluation of glaucomatous retinal changes

NASA Astrophysics Data System (ADS)

Wang, Qi; Grozdanic, Sinisa D.; Harper, Matthew M.; Hamouche, Nicolas; Kecova, Helga; Lazic, Tatjana; Yu, Chenxu

2011-10-01

Glaucoma is a chronic neurodegenerative disease characterized by apoptosis of retinal ganglion cells and subsequent loss of visual function. Early detection of glaucoma is critical for the prevention of permanent structural damage and irreversible vision loss. Raman spectroscopy is a technique that provides rapid biochemical characterization of tissues in a nondestructive and noninvasive fashion. In this study, we explored the potential of using Raman spectroscopy for detection of glaucomatous changes in vitro. Raman spectroscopic imaging was conducted on retinal tissues of dogs with hereditary glaucoma and healthy control dogs. The Raman spectra were subjected to multivariate discriminant analysis with a support vector machine algorithm, and a classification model was developed to differentiate disease tissues versus healthy tissues. Spectroscopic analysis of 105 retinal ganglion cells (RGCs) from glaucomatous dogs and 267 RGCs from healthy dogs revealed spectroscopic markers that differentiated glaucomatous specimens from healthy controls. Furthermore, the multivariate discriminant model differentiated healthy samples and glaucomatous samples with good accuracy [healthy 89.5% and glaucomatous 97.6% for the same breed (Basset Hounds); and healthy 85.0% and glaucomatous 85.5% for different breeds (Beagles versus Basset Hounds)]. Raman spectroscopic screening can be used for in vitro detection of glaucomatous changes in retinal tissue with a high specificity.

Understanding perception of active noise control system through multichannel EEG analysis.

PubMed

Bagha, Sangeeta; Tripathy, R K; Nanda, Pranati; Preetam, C; Das, Debi Prasad

2018-06-01

In this Letter, a method is proposed to investigate the effect of noise with and without active noise control (ANC) on multichannel electroencephalogram (EEG) signal. The multichannel EEG signal is recorded during different listening conditions such as silent, music, noise, ANC with background noise and ANC with both background noise and music. The multiscale analysis of EEG signal of each channel is performed using the discrete wavelet transform. The multivariate multiscale matrices are formulated based on the sub-band signals of each EEG channel. The singular value decomposition is applied to the multivariate matrices of multichannel EEG at significant scales. The singular value features at significant scales and the extreme learning machine classifier with three different activation functions are used for classification of multichannel EEG signal. The experimental results demonstrate that, for ANC with noise and ANC with noise and music classes, the proposed method has sensitivity values of 75.831% ( p < 0.001 ) and 99.31% ( p < 0.001 ), respectively. The method has an accuracy value of 83.22% for the classification of EEG signal with music and ANC with music as stimuli. The important finding of this study is that by the introduction of ANC, music can be better perceived by the human brain.

Longitudinal analysis of physical activity, fluid intake, and graft function among kidney transplant recipients

PubMed Central

Gordon, Elisa J.; Prohaska, Thomas R.; Gallant, Mary P.; Sehgal, Ashwini R.; Strogatz, David; Yucel, Recai; Conti, David; Siminoff, Laura A.

2010-01-01

Summary Self-care is recommended to kidney transplant recipients as a vital component to maintain long-term graft function. However, little is known about the effects of physical activity, fluid intake, and smoking history on graft function. This longitudinal study examined the relationship between self-care practices on graft function among 88 new kidney transplant recipients in Chicago, IL and Albany, NY between 2005 and 2008. Participants were interviewed, completed surveys, and medical charts were abstracted. Physical activity, fluid intake, and smoking history at baseline were compared with changes in estimated glomerular filtration rate (eGFR) (every 6 months up to 1 year) using bivariate and multivariate regression analysis, while controlling for sociodemographic and clinical transplant variables. Multivariate analyses revealed that greater physical activity was significantly (P < 0.05) associated with improvement in GFR at 6 months; while greater physical activity, absence of smoking history, and nonwhite ethnicity were significant (P < 0.05) predictors of improvement in GFR at 12 months. These results suggest that increasing physical activity levels in kidney recipients may be an effective behavioral measure to help ensure graft functioning. Our findings suggest the need for a randomized controlled trial of exercise, fluid intake, and smoking history on GFR beyond 12 months. PMID:19619168

Longitudinal analysis of physical activity, fluid intake, and graft function among kidney transplant recipients.

PubMed

Gordon, Elisa J; Prohaska, Thomas R; Gallant, Mary P; Sehgal, Ashwini R; Strogatz, David; Yucel, Recai; Conti, David; Siminoff, Laura A

2009-10-01

Self-care is recommended to kidney transplant recipients as a vital component to maintain long-term graft function. However, little is known about the effects of physical activity, fluid intake, and smoking history on graft function. This longitudinal study examined the relationship between self-care practices on graft function among 88 new kidney transplant recipients in Chicago, IL and Albany, NY between 2005 and 2008. Participants were interviewed, completed surveys, and medical charts were abstracted. Physical activity, fluid intake, and smoking history at baseline were compared with changes in estimated glomerular filtration rate (eGFR) (every 6 months up to 1 year) using bivariate and multivariate regression analysis, while controlling for sociodemographic and clinical transplant variables. Multivariate analyses revealed that greater physical activity was significantly (P < 0.05) associated with improvement in GFR at 6 months; while greater physical activity, absence of smoking history, and nonwhite ethnicity were significant (P < 0.05) predictors of improvement in GFR at 12 months. These results suggest that increasing physical activity levels in kidney recipients may be an effective behavioral measure to help ensure graft functioning. Our findings suggest the need for a randomized controlled trial of exercise, fluid intake, and smoking history on GFR beyond 12 months.

Exploring Raman spectroscopy for the evaluation of glaucomatous retinal changes.

PubMed

Wang, Qi; Grozdanic, Sinisa D; Harper, Matthew M; Hamouche, Nicolas; Kecova, Helga; Lazic, Tatjana; Yu, Chenxu

2011-10-01

Glaucoma is a chronic neurodegenerative disease characterized by apoptosis of retinal ganglion cells and subsequent loss of visual function. Early detection of glaucoma is critical for the prevention of permanent structural damage and irreversible vision loss. Raman spectroscopy is a technique that provides rapid biochemical characterization of tissues in a nondestructive and noninvasive fashion. In this study, we explored the potential of using Raman spectroscopy for detection of glaucomatous changes in vitro. Raman spectroscopic imaging was conducted on retinal tissues of dogs with hereditary glaucoma and healthy control dogs. The Raman spectra were subjected to multivariate discriminant analysis with a support vector machine algorithm, and a classification model was developed to differentiate disease tissues versus healthy tissues. Spectroscopic analysis of 105 retinal ganglion cells (RGCs) from glaucomatous dogs and 267 RGCs from healthy dogs revealed spectroscopic markers that differentiated glaucomatous specimens from healthy controls. Furthermore, the multivariate discriminant model differentiated healthy samples and glaucomatous samples with good accuracy [healthy 89.5% and glaucomatous 97.6% for the same breed (Basset Hounds); and healthy 85.0% and glaucomatous 85.5% for different breeds (Beagles versus Basset Hounds)]. Raman spectroscopic screening can be used for in vitro detection of glaucomatous changes in retinal tissue with a high specificity.

Laser-induced breakdown spectroscopy-based investigation and classification of pharmaceutical tablets using multivariate chemometric analysis

PubMed Central

Myakalwar, Ashwin Kumar; Sreedhar, S.; Barman, Ishan; Dingari, Narahara Chari; Rao, S. Venugopal; Kiran, P. Prem; Tewari, Surya P.; Kumar, G. Manoj

2012-01-01

We report the effectiveness of laser-induced breakdown spectroscopy (LIBS) in probing the content of pharmaceutical tablets and also investigate its feasibility for routine classification. This method is particularly beneficial in applications where its exquisite chemical specificity and suitability for remote and on site characterization significantly improves the speed and accuracy of quality control and assurance process. Our experiments reveal that in addition to the presence of carbon, hydrogen, nitrogen and oxygen, which can be primarily attributed to the active pharmaceutical ingredients, specific inorganic atoms were also present in all the tablets. Initial attempts at classification by a ratiometric approach using oxygen to nitrogen compositional values yielded an optimal value (at 746.83 nm) with the least relative standard deviation but nevertheless failed to provide an acceptable classification. To overcome this bottleneck in the detection process, two chemometric algorithms, i.e. principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA), were implemented to exploit the multivariate nature of the LIBS data demonstrating that LIBS has the potential to differentiate and discriminate among pharmaceutical tablets. We report excellent prospective classification accuracy using supervised classification via the SIMCA algorithm, demonstrating its potential for future applications in process analytical technology, especially for fast on-line process control monitoring applications in the pharmaceutical industry. PMID:22099648

Environmental factors associated with Crohn's disease in India.

PubMed

Pugazhendhi, Srinivasan; Sahu, Manoj Kumar; Subramanian, Venkataraman; Pulimood, Anna; Ramakrishna, Balakrishnan S

2011-12-01

The frequency of diagnosis of Crohn's disease (CD) in India is increasing. This case-control study was designed to detect associations of environmental and dietary factors with the diagnosis of CD. In 200 consecutive patients with CD and 200 control subjects without gastrointestinal disease, environmental hygiene exposures in childhood and in the past one year, and dietary preferences were recorded using a questionnaire. Univariate and multivariate analyses were done. In univariate analysis, CD showed positive association with urban residence (at birth and current), availability of protected drinking water (childhood and current), availability of piped water in the house (childhood and current), and strict vegetarian dietary habit, and negative association with regular fish consumption and presence of cattle in the house compound. Multivariate analysis showed that regular fish consumption (OR 0.52, 95% CI 0.33-0.80, p = 0.003), and presence of cattle in the house compound currently (OR 0.57, 95% CI 0.35-0.92, p = 0.023) were significant protective associations, whereas use of safe drinking water was positively associated (OR 1.59, 95% CI 1.02-2.47, p = 0.042) with the disease. Occurrence of CD was associated with dietary and environmental exposures, which indicate that diet and hygiene may influence the development of this disease.

The Impact of ART on the Economic Outcomes of People Living with HIV/AIDS.

PubMed

Nannungi, Annet; Wagner, Glenn; Ghosh-Dastidar, Bonnie

2013-01-01

Background. Clinical benefits of ART are well documented, but less is known about its effects on economic outcomes such as work status and income in sub-Saharan Africa. Methods. Data were examined from 482 adult clients entering HIV care (257 starting ART; 225 not yet eligible for ART) in Kampala, Uganda. Self-reported data on work status and income were assessed at baseline, months 6 and 12. Multivariate analysis examined the effects of ART over time, controlling for change in physical health functioning and baseline covariates. Results. Fewer ART patients worked at baseline compared to non-ART patients (25.5% versus 34.2%); 48.8% of those not working at baseline were now working at month 6, and 50% at month 12, with similar improvement in both the ART and non-ART groups. However, multivariate analysis revealed that the ART group experienced greater improvement over time. Average weekly income did not differ between the groups at baseline nor change significantly over time, among those who were working; being male gender and having any secondary education were predictive of higher income. Conclusions. ART was associated with greater improvement in work status, even after controlling for change in physical health functioning, suggesting other factors associated with ART may influence work.

Effects of valproate on the carotid artery intima-media thickness in epileptics.

PubMed

Luo, Xinming; Zhang, Ming; Deng, Liying; Zhao, Jing

2015-01-01

The objective was to explore the effects of valproate (VPA) on the carotid artery intima-media thickness (CA-IMT) in epileptics. A total of 30 epileptic patients treated with VPA was included as disease group, while 33 healthy people who matched general basic demographic details were the control group. The IMTs of the left and right carotids of the both groups were measured, and the average CA-IMT was calculated. The IMT-related risk factors were acquired for the univariate and multivariate analysis. The bilateral carotid and average CA-IMTs of the disease group were significantly higher than the control group (P < 0.001). The multivariant gradual regressive analysis screened out two CA-IMT-related factors, namely the disease duration and the drug administration duration were positively correlated with the average CA-IMT. The epileptic patients with disease course of more than 3 years had much higher average CA-IMT than that of the epileptics with ≤3 years disease (P < 0.001). The average CA-IMT of the patients with VPA-administration duration >1 year was also higher than that of the patients with VPA-administration duration <1 year, while the difference was not statistically significant (P = 0.196). The average CA-IMT of the epileptic patients treated with VPA was higher than that of healthy people.

Tuning algorithms for fractional order internal model controllers for time delay processes

NASA Astrophysics Data System (ADS)

Muresan, Cristina I.; Dutta, Abhishek; Dulf, Eva H.; Pinar, Zehra; Maxim, Anca; Ionescu, Clara M.

2016-03-01

This paper presents two tuning algorithms for fractional-order internal model control (IMC) controllers for time delay processes. The two tuning algorithms are based on two specific closed-loop control configurations: the IMC control structure and the Smith predictor structure. In the latter, the equivalency between IMC and Smith predictor control structures is used to tune a fractional-order IMC controller as the primary controller of the Smith predictor structure. Fractional-order IMC controllers are designed in both cases in order to enhance the closed-loop performance and robustness of classical integer order IMC controllers. The tuning procedures are exemplified for both single-input-single-output as well as multivariable processes, described by first-order and second-order transfer functions with time delays. Different numerical examples are provided, including a general multivariable time delay process. Integer order IMC controllers are designed in each case, as well as fractional-order IMC controllers. The simulation results show that the proposed fractional-order IMC controller ensures an increased robustness to modelling uncertainties. Experimental results are also provided, for the design of a multivariable fractional-order IMC controller in a Smith predictor structure for a quadruple-tank system.

An analysis of fracture trace patterns in areas of flat-lying sedimentary rocks for the detection of buried geologic structure. [Kansas and Texas

NASA Technical Reports Server (NTRS)

Podwysocki, M. H.

1974-01-01

Two study areas in a cratonic platform underlain by flat-lying sedimentary rocks were analyzed to determine if a quantitative relationship exists between fracture trace patterns and their frequency distributions and subsurface structural closures which might contain petroleum. Fracture trace lengths and frequency (number of fracture traces per unit area) were analyzed by trend surface analysis and length frequency distributions also were compared to a standard Gaussian distribution. Composite rose diagrams of fracture traces were analyzed using a multivariate analysis method which grouped or clustered the rose diagrams and their respective areas on the basis of the behavior of the rays of the rose diagram. Analysis indicates that the lengths of fracture traces are log-normally distributed according to the mapping technique used. Fracture trace frequency appeared higher on the flanks of active structures and lower around passive reef structures. Fracture trace log-mean lengths were shorter over several types of structures, perhaps due to increased fracturing and subsequent erosion. Analysis of rose diagrams using a multivariate technique indicated lithology as the primary control for the lower grouping levels. Groupings at higher levels indicated that areas overlying active structures may be isolated from their neighbors by this technique while passive structures showed no differences which could be isolated.

SEM-PLS Analysis of Inhibiting Factors of Cost Performance for Large Construction Projects in Malaysia: Perspective of Clients and Consultants

PubMed Central

Memon, Aftab Hameed; Rahman, Ismail Abdul

2014-01-01

This study uncovered inhibiting factors to cost performance in large construction projects of Malaysia. Questionnaire survey was conducted among clients and consultants involved in large construction projects. In the questionnaire, a total of 35 inhibiting factors grouped in 7 categories were presented to the respondents for rating significant level of each factor. A total of 300 questionnaire forms were distributed. Only 144 completed sets were received and analysed using advanced multivariate statistical software of Structural Equation Modelling (SmartPLS v2). The analysis involved three iteration processes where several of the factors were deleted in order to make the model acceptable. The result of the analysis found that R 2 value of the model is 0.422 which indicates that the developed model has a substantial impact on cost performance. Based on the final form of the model, contractor's site management category is the most prominent in exhibiting effect on cost performance of large construction projects. This finding is validated using advanced techniques of power analysis. This vigorous multivariate analysis has explicitly found the significant category which consists of several causative factors to poor cost performance in large construction projects. This will benefit all parties involved in construction projects for controlling cost overrun. PMID:24693227

SEM-PLS analysis of inhibiting factors of cost performance for large construction projects in Malaysia: perspective of clients and consultants.

PubMed

Memon, Aftab Hameed; Rahman, Ismail Abdul

2014-01-01

This study uncovered inhibiting factors to cost performance in large construction projects of Malaysia. Questionnaire survey was conducted among clients and consultants involved in large construction projects. In the questionnaire, a total of 35 inhibiting factors grouped in 7 categories were presented to the respondents for rating significant level of each factor. A total of 300 questionnaire forms were distributed. Only 144 completed sets were received and analysed using advanced multivariate statistical software of Structural Equation Modelling (SmartPLS v2). The analysis involved three iteration processes where several of the factors were deleted in order to make the model acceptable. The result of the analysis found that R(2) value of the model is 0.422 which indicates that the developed model has a substantial impact on cost performance. Based on the final form of the model, contractor's site management category is the most prominent in exhibiting effect on cost performance of large construction projects. This finding is validated using advanced techniques of power analysis. This vigorous multivariate analysis has explicitly found the significant category which consists of several causative factors to poor cost performance in large construction projects. This will benefit all parties involved in construction projects for controlling cost overrun.

Laryngospasm during emergency department ketamine sedation: a case-control study.

PubMed

Green, Steven M; Roback, Mark G; Krauss, Baruch

2010-11-01

The objective of this study was to assess predictors of emergency department (ED) ketamine-associated laryngospasm using case-control techniques. We performed a matched case-control analysis of a sample of 8282 ED ketamine sedations (including 22 occurrences of laryngospasm) assembled from 32 prior published series. We sequentially studied the association of each of 7 clinical variables with laryngospasm by assigning 4 controls to each case while matching for the remaining 6 variables. We then used univariate statistics and conditional logistic regression to analyze the matched sets. We found no statistical association of age, dose, oropharyngeal procedure, underlying physical illness, route, or coadministered anticholinergics with laryngospasm. Coadministered benzodiazepines showed a borderline association in the multivariate but not univariate analysis that was considered anomalous. This case-control analysis of the largest available sample of ED ketamine-associated laryngospasm did not demonstrate evidence of association with age, dose, or other clinical factors. Such laryngospasm seems to be idiosyncratic, and accordingly, clinicians administering ketamine must be prepared for its rapid identification and management. Given no evidence that they decrease the risk of laryngospasm, coadministered anticholinergics seem unnecessary.

Treatment of salivary gland neoplasms with fast neutron radiotherapy.

PubMed

Douglas, James G; Koh, Wui-jin; Austin-Seymour, Mary; Laramore, George E

2003-09-01

To evaluate the efficacy of fast neutron radiotherapy for the treatment of salivary gland neoplasms. Retrospective analysis. University of Washington Cancer Center, Neutron Facility, Seattle. The medical records of 279 patients treated with curative intent using fast neutron radiotherapy at the University of Washington Cancer Center were reviewed. Of the 279 patients, 263 had evidence of gross residual disease at the time of treatment (16 had no evidence of gross residual disease), 141 had tumors of a major salivary gland, and 138 had tumors of minor salivary glands. The median follow-up period was 36 months (range, 1-142 months). Local-regional control, cause-specific survival, and freedom from metastasis. The 6-year actuarial cause-specific survival rate was 67%. Multivariate analysis revealed that low group stage (I-II) disease, minor salivary sites, lack of skull base invasion, and primary disease were associated with a statistically significant improvement in cause-specific survival. The 6-year actuarial local-regional control rate was 59%. Multivariate analysis revealed size 4 cm or smaller, lack of base of skull invasion, prior surgical resection, and no previous radiotherapy to have a statistically significant improved local-regional control. Sixteen patients without evidence of gross residual disease had a 100% 6-year actuarial local-regional control. The 6-year actuarial freedom from metastasis rate was 64%. Factors associated with decreased development of systemic metastases included negative lymph nodes at the time of treatment and lack of base of skull involvement. The 6-year actuarial rate of development of grade 3 or 4 long-term toxicity (using the Radiation Therapy Oncology Group and European Organization for Research on the Treatment of Cancer criteria) was 10%. No patient experienced grade 5 toxic effects. Neuron radiotherapy is an effective treatment for patients with salivary gland neoplasms who have gross residual disease and achieves excellent local-regional control in patients without evidence of gross disease.

Leptospira Exposure and Waste Pickers: A Case-Control Seroprevalence Study in Durango, Mexico.

PubMed

Alvarado-Esquivel, Cosme; Hernandez-Tinoco, Jesus; Sanchez-Anguiano, Luis Francisco; Ramos-Nevarez, Agar; Cerrillo-Soto, Sandra Margarita; Guido-Arreola, Carlos Alberto

2015-08-01

Infection with Leptospira may occur by contact with Leptospira-infected animals. Waste pickers are in contact with rodents and dogs while picking in the garbage. Whether waste pickers are at risk for Leptospira infection is largely unknown. This study was aimed to determine the association of Leptospira IgG seroprevalence with the occupation of waste picking, and to determine the epidemiological characteristics of the waste pickers with Leptospira exposure. Through a case-control study, we determined the seroprevalence of anti-Leptospira IgG antibodies in 90 waste pickers and 90 age- and gender-matched control subjects in Durango City, Mexico using an enzyme immunoassay. Data were analyzed by bivariate and multivariate analyses. The prevalence of anti-Leptospira IgG antibodies was similar in waste pickers (4/90: 4.4%) to that in control subjects (5/90: 5.6%) (P = 1.00). Bivariate analysis showed that Leptospira exposure in waste pickers was associated with increasing age (P = 0.009), no education (P = 0.008), and consumption of rat meat (P = 0.04). However, these associations were no longer found by multivariate analysis. Leptospira exposure in waste pickers was not associated with health status, duration in the activity, wearing hand gloves and facemasks, history of injuries with sharp material of the garbage, or contact with animals or soil. This is the first study about Leptospira exposure in waste pickers. Results suggest that waste pickers are not at increasing risk for Leptospira exposure in Durango City, Mexico. Further research with a larger sample size to elucidate the association of Leptospira exposure with waste picking activity is needed.

A matrix-based method of moments for fitting the multivariate random effects model for meta-analysis and meta-regression

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2013-01-01

Multivariate meta-analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of moments for estimating the between-study covariance matrix with the properties that (1) it allows for either complete or incomplete outcomes and (2) it allows for covariates through meta-regression. Further, for complete data, it is invariant to linear transformations. Our method reduces to the usual univariate method of moments, proposed by DerSimonian and Laird, in a single dimension. We illustrate our method and compare it with some of the alternatives using a simulation study and a real example. PMID:23401213

Patient compliance with antihypertensive medication.

PubMed Central

Hershey, J C; Morton, B G; Davis, J B; Reichgott, M J

1980-01-01

Self-reported medication taking compliance behavior of 132 high blood pressure patients was analyzed using an expanded version of the health belief model. Subjects were selected through random sampling procedures from regular hypertension program sessions at a large urban hospital. A questionnaire was constructed to measure the model components, and interviews were conducted with each patient. Bivariate analysis showed that control over health matters, dependence on providers, perceived barriers, duration of treatment, and others' nonconfirming experience were significantly related to compliance (p < .05). Log-linear multivariate analysis revealed that three of these five variables--control over health matters, perceived barriers, and duration of treatment--contributed independently to patient compliance. Self-reported medication taking was significantly related to blood pressure control (p < .02). These data provide the basis for developing interventions for providers to facilitate the medication taking behavior of clinic patients. PMID:7416325

Epidemiology and risk factors for typhoid fever in Central Division, Fiji, 2014-2017: A case-control study.

PubMed

Prasad, Namrata; Jenkins, Aaron P; Naucukidi, Lanieta; Rosa, Varanisese; Sahu-Khan, Aalisha; Kama, Mike; Jenkins, Kylie M; Jenney, Adam W J; Jack, Susan J; Saha, Debasish; Horwitz, Pierre; Jupiter, Stacy D; Strugnell, Richard A; Mulholland, E Kim; Crump, John A

2018-06-01

Typhoid fever is endemic in Fiji, with high reported annual incidence. We sought to identify the sources and modes of transmission of typhoid fever in Fiji with the aim to inform disease control. We identified and surveyed patients with blood culture-confirmed typhoid fever from January 2014 through January 2017. For each typhoid fever case we matched two controls by age interval, gender, ethnicity, and residential area. Univariable and multivariable analysis were used to evaluate associations between exposures and risk for typhoid fever. We enrolled 175 patients with typhoid fever and 349 controls. Of the cases, the median (range) age was 29 (2-67) years, 86 (49%) were male, and 84 (48%) lived in a rural area. On multivariable analysis, interrupted water availability (odds ratio [OR] = 2.17; 95% confidence interval [CI] 1.18-4.00), drinking surface water in the last 2 weeks (OR = 3.61; 95% CI 1.44-9.06), eating unwashed produce (OR = 2.69; 95% CI 1.48-4.91), and having an unimproved or damaged sanitation facility (OR = 4.30; 95% CI 1.14-16.21) were significantly associated with typhoid fever. Frequent handwashing after defecating (OR = 0.57; 95% CI 0.35-0.93) and using soap for handwashing (OR = 0.61; 95% CI 0.37-0.95) were independently associated with a lower odds of typhoid fever. Poor sanitation facilities appear to be a major source of Salmonella Typhi in Fiji, with transmission by drinking contaminated surface water and consuming unwashed produce. Improved sanitation facilities and protection of surface water sources and produce from contamination by human feces are likely to contribute to typhoid control in Fiji.

Pharyngeal Swallowing Mechanics Secondary to Hemispheric Stroke.

PubMed

May, Nelson H; Pisegna, Jessica M; Marchina, Sarah; Langmore, Susan E; Kumar, Sandeep; Pearson, William G

2017-05-01

Computational analysis of swallowing mechanics (CASM) is a method that utilizes multivariate shape change analysis to uncover covariant elements of pharyngeal swallowing mechanics associated with impairment using videofluoroscopic swallowing studies. The goals of this preliminary study were to (1) characterize swallowing mechanics underlying stroke-related dysphagia, (2) decipher the impact of left and right hemispheric strokes on pharyngeal swallowing mechanics, and (3) determine pharyngeal swallowing mechanics associated with penetration-aspiration status. Videofluoroscopic swallowing studies of 18 dysphagic patients with hemispheric infarcts and age- and gender-matched controls were selected from well-controlled data sets. Patient data including laterality and penetration-aspiration status were collected. Coordinates mapping muscle group action during swallowing were collected from videos. Multivariate morphometric analyses of coordinates associated with stroke, affected hemisphere, and penetration-aspiration status were performed. Pharyngeal swallowing mechanics differed significantly in the following comparisons: stroke versus controls (D = 2.19, P < .0001), right hemispheric stroke versus controls (D = 3.64, P < .0001), left hemispheric stroke versus controls (D = 2.06, P < .0001), right hemispheric stroke versus left hemispheric stroke (D = 2.89, P < .0001), and penetration-aspiration versus within normal limits (D = 2.25, P < .0001). Differences in pharyngeal swallowing mechanics associated with each comparison were visualized using eigenvectors. Whereas current literature focuses on timing changes in stroke-related dysphagia, these data suggest that mechanical changes are also functionally important. Pharyngeal swallowing mechanics differed by the affected hemisphere and the penetration-aspiration status. CASM can be used to identify patient-specific swallowing impairment associated with stroke injury that could help guide rehabilitation strategies to improve swallowing outcomes. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Insulin resistance, diabetes mellitus and thyroid dysfunction in patients with palmoplantar pustulosis: a case-controlled study.

PubMed

Ataş, Hatice; Gönül, Müzeyyen

2017-06-01

Palmoplantar pustulosis (PPP) is a chronic pustular inflammatory skin disease; however, its pathogenesis is not well understood. Several factors, such as genetics, tobacco use and autoimmune issues, may contribute to this disease. This research was conducted to investigate the relationships between insulin resistance, thyroid disease and PPP. Thirty-three patients with PPP and 27 age- and gender-matched controls were analysed for their smoking histories, thyroid function tests, anti-thyroid peroxidase antibody (anti-TPO) levels, fasting glucose, fasting insulin levels and the homeostatic model assessment (HOMA) index for insulin resistance. We found significant differences between the PPP and control groups according to their tobacco use and anti-TPO levels ( p = 0.009 and p = 0.009, respectively). The proportion of tobacco use was 90% in the PPP patients and 63% in the controls. Gender and tobacco use were predictive risk factors for PPP in the multivariate analysis ( OR = 141.7, p < 0.0001 and OR = 147.6, p = 0.006, respectively). An anti-TPO level > 35 U/ml and the presence of a thyroid abnormality were independent risk factors in the univariate, but not the multivariate analysis ( OR = 4.2, p = 0.025 and OR = 5.4, p = 0.004, respectively). A moderate correlation between the gender and anti-TPO level was found ( r = 0.361, p = 0.039); however, the fasting glucose, insulin and HOMA index were not significant between the PPP and control groups. Female gender and smoking were the most important risk factors for PPP; however, the increase in the anti-TPO level may be related to the predominance of females afflicted with this disease. Additional studies are necessary to clarify the relationships between PPP, thyroid disease and diabetes mellitus.

Development of the Nasopharyngeal Microbiota in Infants with Cystic Fibrosis.

PubMed

Prevaes, Sabine M P J; de Winter-de Groot, Karin M; Janssens, Hettie M; de Steenhuijsen Piters, Wouter A A; Tramper-Stranders, Gerdien A; Wyllie, Anne L; Hasrat, Raiza; Tiddens, Harm A; van Westreenen, Mireille; van der Ent, Cornelis K; Sanders, Elisabeth A M; Bogaert, Debby

2016-03-01

Cystic fibrosis (CF) is characterized by early structural lung disease caused by pulmonary infections. The nasopharynx of infants is a major ecological reservoir of potential respiratory pathogens. To investigate the development of nasopharyngeal microbiota profiles in infants with CF compared with those of healthy control subjects during the first 6 months of life. We conducted a prospective cohort study, from the time of diagnosis onward, in which we collected questionnaires and 324 nasopharynx samples from 20 infants with CF and 45 age-matched healthy control subjects. Microbiota profiles were characterized by 16S ribosomal RNA-based sequencing. We observed significant differences in microbial community composition (P < 0.0002 by permutational multivariate analysis of variance) and development between groups. In infants with CF, early Staphylococcus aureus and, to a lesser extent, Corynebacterium spp. and Moraxella spp. dominance were followed by a switch to Streptococcus mitis predominance after 3 months of age. In control subjects, Moraxella spp. enrichment occurred throughout the first 6 months of life. In a multivariate analysis, S. aureus, S. mitis, Corynebacterium accolens, and bacilli were significantly more abundant in infants with CF, whereas Moraxella spp., Corynebacterium pseudodiphtericum and Corynebacterium propinquum and Haemophilus influenzae were significantly more abundant in control subjects, after correction for age, antibiotic use, and respiratory symptoms. Antibiotic use was independently associated with increased colonization of gram-negative bacteria such as Burkholderia spp. and members of the Enterobacteriaceae bacteria family and reduced colonization of potential beneficial commensals. From diagnosis onward, we observed distinct patterns of nasopharyngeal microbiota development in infants with CF under 6 months of age compared with control subjects and a marked effect of antibiotic therapy leading toward a gram-negative microbial composition.

Robustness analysis of an air heating plant and control law by using polynomial chaos

DOE Office of Scientific and Technical Information (OSTI.GOV)

Colón, Diego; Ferreira, Murillo A. S.; Bueno, Átila M.

2014-12-10

This paper presents a robustness analysis of an air heating plant with a multivariable closed-loop control law by using the polynomial chaos methodology (MPC). The plant consists of a PVC tube with a fan in the air input (that forces the air through the tube) and a mass flux sensor in the output. A heating resistance warms the air as it flows inside the tube, and a thermo-couple sensor measures the air temperature. The plant has thus two inputs (the fan's rotation intensity and heat generated by the resistance, both measured in percent of the maximum value) and two outputsmore » (air temperature and air mass flux, also in percent of the maximal value). The mathematical model is obtained by System Identification techniques. The mass flux sensor, which is nonlinear, is linearized and the delays in the transfer functions are properly approximated by non-minimum phase transfer functions. The resulting model is transformed to a state-space model, which is used for control design purposes. The multivariable robust control design techniques used is the LQG/LTR, and the controllers are validated in simulation software and in the real plant. Finally, the MPC is applied by considering some of the system's parameters as random variables (one at a time, and the system's stochastic differential equations are solved by expanding the solution (a stochastic process) in an orthogonal basis of polynomial functions of the basic random variables. This method transforms the stochastic equations in a set of deterministic differential equations, which can be solved by traditional numerical methods (That is the MPC). Statistical data for the system (like expected values and variances) are then calculated. The effects of randomness in the parameters are evaluated in the open-loop and closed-loop pole's positions.« less

The combination of ovarian volume and outline has better diagnostic accuracy than prostate-specific antigen (PSA) concentrations in women with polycystic ovarian syndrome (PCOs).

PubMed

Bili, Eleni; Bili, Authors Eleni; Dampala, Kaliopi; Iakovou, Ioannis; Tsolakidis, Dimitrios; Giannakou, Anastasia; Tarlatzis, Basil C

2014-08-01

The aim of this study was to determine the performance of prostate specific antigen (PSA) and ultrasound parameters, such as ovarian volume and outline, in the diagnosis of polycystic ovary syndrome (PCOS). This prospective, observational, case-controlled study included 43 women with PCOS, and 40 controls. Between day 3 and 5 of the menstrual cycle, fasting serum samples were collected and transvaginal ultrasound was performed. The diagnostic performance of each parameter [total PSA (tPSA), total-to-free PSA ratio (tPSA:fPSA), ovarian volume, ovarian outline] was estimated by means of receiver operating characteristic (ROC) analysis, along with area under the curve (AUC), threshold, sensitivity, specificity as well as positive (+) and negative (-) likelihood ratios (LRs). Multivariate logistical regression models, using ovarian volume and ovarian outline, were constructed. The tPSA and tPSA:fPSA ratio resulted in AUC of 0.74 and 0.70, respectively, with moderate specificity/sensitivity and insufficient LR+/- values. In the multivariate logistic regression model, the combination of ovarian volume and outline had a sensitivity of 97.7% and a specificity of 97.5% in the diagnosis of PCOS, with +LR and -LR values of 39.1 and 0.02, respectively. In women with PCOS, tPSA and tPSA:fPSA ratio have similar diagnostic performance. The use of a multivariate logistic regression model, incorporating ovarian volume and outline, offers very good diagnostic accuracy in distinguishing women with PCOS patients from controls. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Determination of awareness in patients with severe brain injury using EEG power spectral analysis

PubMed Central

Goldfine, Andrew M.; Victor, Jonathan D.; Conte, Mary M.; Bardin, Jonathan C.; Schiff, Nicholas D.

2011-01-01

Objective To determine whether EEG spectral analysis could be used to demonstrate awareness in patients with severe brain injury. Methods We recorded EEG from healthy controls and three patients with severe brain injury, ranging from minimally conscious state (MCS) to locked-in-state (LIS), while they were asked to imagine motor and spatial navigation tasks. We assessed EEG spectral differences from 4 to 24 Hz with univariate comparisons (individual frequencies) and multivariate comparisons (patterns across the frequency range). Results In controls, EEG spectral power differed at multiple frequency bands and channels during performance of both tasks compared to a resting baseline. As patterns of signal change were inconsistent between controls, we defined a positive response in patient subjects as consistent spectral changes across task performances. One patient in MCS and one in LIS showed evidence of motor imagery task performance, though with patterns of spectral change different from the controls. Conclusion EEG power spectral analysis demonstrates evidence for performance of mental imagery tasks in healthy controls and patients with severe brain injury. Significance EEG power spectral analysis can be used as a flexible bedside tool to demonstrate awareness in brain-injured patients who are otherwise unable to communicate. PMID:21514214

Does tip-of-the-tongue for proper names discriminate amnestic mild cognitive impairment?

PubMed

Juncos-Rabadán, Onésimo; Facal, David; Lojo-Seoane, Cristina; Pereiro, Arturo X

2013-04-01

Difficulty in retrieving people's names is very common in the early stages of Alzheimer's disease and mild cognitive impairment. Such difficulty is often observed as the tip-of-the-tongue (TOT) phenomenon. The main aim of this study was to explore whether a famous people's naming task that elicited the TOT state can be used to discriminate between amnestic mild cognitive impairment (aMCI) patients and normal controls. Eighty-four patients with aMCI and 106 normal controls aged over 50 years performed a task involving naming 50 famous people shown in pictures. Univariate and multivariate regression analyses were used to study the relationships between aMCI and semantic and phonological measures in the TOT paradigm. Univariate regression analyses revealed that all TOT measures significantly predicted aMCI. Multivariate analysis of all these measures correctly classified 70% of controls (specificity) and 71.6% of aMCI patients (sensitivity), with an AUC (area under curve ROC) value of 0.74, but only the phonological measure remained significant. This classification value was similar to that obtained with the Semantic verbal fluency test. TOTs for proper names may effectively discriminate aMCI patients from normal controls through measures that represent one of the naming processes affected, that is, phonological access.

Multivariate analyses of peripheral blood leukocyte transcripts distinguish Alzheimer's, Parkinson's, control, and those at risk for developing Alzheimer's.

PubMed

Delvaux, Elaine; Mastroeni, Diego; Nolz, Jennifer; Chow, Nienwen; Sabbagh, Marwan; Caselli, Richard J; Reiman, Eric M; Marshall, Frederick J; Coleman, Paul D

2017-10-01

The need for a reliable, simple, and inexpensive blood test for Alzheimer's disease (AD) suitable for use in a primary care setting is widely recognized. This has led to a large number of publications describing blood tests for AD, which have, for the most part, not been replicable. We have chosen to examine transcripts expressed by the cellular, leukocyte compartment of blood. We have used hypothesis-based cDNA arrays and quantitative PCR to quantify the expression of selected sets of genes followed by multivariate analyses in multiple independent samples. Rather than a single study with no replicates, we chose an experimental design in which there were multiple replicates using different platforms and different sample populations. We have divided 177 blood samples and 27 brain samples into multiple replicates to demonstrate the ability to distinguish early clinical AD (Clinical Dementia Rating scale 0.5), Parkinson's disease (PD), and cognitively unimpaired APOE4 homozygotes, as well as to determine persons at risk for future cognitive impairment with significant accuracy. We assess our methods in a training/test set and also show that the variables we use distinguish AD, PD, and control brain. Importantly, we describe the variability of the weights assigned to individual transcripts in multivariate analyses in repeated studies and suggest that the variability we describe may be the cause of inability to repeat many earlier studies. Our data constitute a proof of principle that multivariate analysis of the transcriptome related to cell stress and inflammation of peripheral blood leukocytes has significant potential as a minimally invasive and inexpensive diagnostic tool for diagnosis and early detection of risk for AD. Copyright © 2017 Elsevier Inc. All rights reserved.

Crayfish: a newly recognized vehicle for vibrio infections.

PubMed

Bean, N H; Maloney, E K; Potter, M E; Korazemo, P; Ray, B; Taylor, J P; Seigler, S; Snowden, J

1998-10-01

We conducted a 1-year case-control study of sporadic vibrio infections to identify risk factors related to consumption of seafood products in two coastal areas of Louisiana and Texas. Twenty-six persons with sporadic vibrio infections and 77 matched controls were enrolled. Multivariate analysis revealed that crayfish (P < 0.025) and raw oysters (P < 0.009) were independently associated with illness. Species-specific analysis revealed an association between consumption of cooked crayfish and Vibrio parahemolyticus infection (OR 9.24, P < 0.05). No crayfish consumption was reported by persons with V. vulnificus infection. Although crayfish had been suspected as a vehicle for foodborne disease, this is the first time to our knowledge that consumption of cooked crayfish has been demonstrated to be associated with vibrio infection.

Multivariate time series analysis of neuroscience data: some challenges and opportunities.

PubMed

Pourahmadi, Mohsen; Noorbaloochi, Siamak

2016-04-01

Neuroimaging data may be viewed as high-dimensional multivariate time series, and analyzed using techniques from regression analysis, time series analysis and spatiotemporal analysis. We discuss issues related to data quality, model specification, estimation, interpretation, dimensionality and causality. Some recent research areas addressing aspects of some recurring challenges are introduced. Copyright © 2015 Elsevier Ltd. All rights reserved.

Data analysis techniques

NASA Technical Reports Server (NTRS)

Park, Steve

1990-01-01

A large and diverse number of computational techniques are routinely used to process and analyze remotely sensed data. These techniques include: univariate statistics; multivariate statistics; principal component analysis; pattern recognition and classification; other multivariate techniques; geometric correction; registration and resampling; radiometric correction; enhancement; restoration; Fourier analysis; and filtering. Each of these techniques will be considered, in order.

Chemical structure of wood charcoal by infrared spectroscopy and multivariate analysis

Treesearch

Nicole Labbe; David Harper; Timothy Rials; Thomas Elder

2006-01-01

In this work, the effect of temperature on charcoal structure and chemical composition is investigated for four tree species. Wood charcoal carbonized at various temperatures is analyzed by mid infrared spectroscopy coupled with multivariate analysis and by thermogravimetric analysis to characterize the chemical composition during the carbonization process. The...

Multivariate analysis: greater insights into complex systems

USDA-ARS?s Scientific Manuscript database

Many agronomic researchers measure and collect multiple response variables in an effort to understand the more complex nature of the system being studied. Multivariate (MV) statistical methods encompass the simultaneous analysis of all random variables (RV) measured on each experimental or sampling ...

Cooperative control theory and integrated flight and propulsion control

NASA Technical Reports Server (NTRS)

Schmidt, David K.; Schierman, John D.

1995-01-01

The major contribution of this research was the exposition of the fact that airframe and engine interactions could be present, and their effects could include loss of stability and performance of the control systems. Also, the significance of two directional, as opposed to one-directional, coupling was identified and explained. A multivariable stability and performance analysis methodology was developed, and applied to several candidate aircraft configurations. In these example evaluations, the significance of these interactions was underscored. Also exposed was the fact that with interactions present along with some integrated control approaches, the engine command/limiting logic (which represents an important nonlinear component of the engine control system) can impact closed-loop airframe/engine system stability. Finally, a brief investigation of control-law synthesis techniques appropriate for the class of systems was pursued, and it was determined that multivariable techniques, including model-following formulations of LQG and/or H infinity methods, showed promise. However, for practical reasons, decentralized control architectures are preferred, which is an architecture incompatible with these synthesis methods. The major contributions of the second phase of the grant was the development of conditions under which no decentralized controller could achieve closed loop system requirements on stability and/or performance. Sought were conditions that depended only on properties of the plant and the requirement, and independent of any particular control law or synthesis approach. Therefore, they could be applied a priori, before synthesis of a candidate control law. Under this grant, such conditions were found regarding stability, and encouraging initial results were obtained regarding performance.

Multivariate analysis of progressive thermal desorption coupled gas chromatography-mass spectrometry.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van Benthem, Mark Hilary; Mowry, Curtis Dale; Kotula, Paul Gabriel

Thermal decomposition of poly dimethyl siloxane compounds, Sylgard{reg_sign} 184 and 186, were examined using thermal desorption coupled gas chromatography-mass spectrometry (TD/GC-MS) and multivariate analysis. This work describes a method of producing multiway data using a stepped thermal desorption. The technique involves sequentially heating a sample of the material of interest with subsequent analysis in a commercial GC/MS system. The decomposition chromatograms were analyzed using multivariate analysis tools including principal component analysis (PCA), factor rotation employing the varimax criterion, and multivariate curve resolution. The results of the analysis show seven components related to offgassing of various fractions of siloxanes that varymore » as a function of temperature. Thermal desorption coupled with gas chromatography-mass spectrometry (TD/GC-MS) is a powerful analytical technique for analyzing chemical mixtures. It has great potential in numerous analytic areas including materials analysis, sports medicine, in the detection of designer drugs; and biological research for metabolomics. Data analysis is complicated, far from automated and can result in high false positive or false negative rates. We have demonstrated a step-wise TD/GC-MS technique that removes more volatile compounds from a sample before extracting the less volatile compounds. This creates an additional dimension of separation before the GC column, while simultaneously generating three-way data. Sandia's proven multivariate analysis methods, when applied to these data, have several advantages over current commercial options. It also has demonstrated potential for success in finding and enabling identification of trace compounds. Several challenges remain, however, including understanding the sources of noise in the data, outlier detection, improving the data pretreatment and analysis methods, developing a software tool for ease of use by the chemist, and demonstrating our belief that this multivariate analysis will enable superior differentiation capabilities. In addition, noise and system artifacts challenge the analysis of GC-MS data collected on lower cost equipment, ubiquitous in commercial laboratories. This research has the potential to affect many areas of analytical chemistry including materials analysis, medical testing, and environmental surveillance. It could also provide a method to measure adsorption parameters for chemical interactions on various surfaces by measuring desorption as a function of temperature for mixtures. We have presented results of a novel method for examining offgas products of a common PDMS material. Our method involves utilizing a stepped TD/GC-MS data acquisition scheme that may be almost totally automated, coupled with multivariate analysis schemes. This method of data generation and analysis can be applied to a number of materials aging and thermal degradation studies.« less

Remote Multivariable Control Design Using a Competition Game

ERIC Educational Resources Information Center

Atanasijevic-Kunc, M.; Logar, V.; Karba, R.; Papic, M.; Kos, A.

2011-01-01

In this paper, some approaches to teaching multivariable control design are discussed, with special attention being devoted to a step-by-step transition to e-learning. The approach put into practice and presented here is developed through design projects, from which one is chosen as a competition game and is realized using the E-CHO system,…

Clostridium difficile infection is associated with graft loss in solid organ transplant recipients.

PubMed

Cusini, A; Béguelin, C; Stampf, S; Boggian, K; Garzoni, C; Koller, M; Manuel, O; Meylan, P; Mueller, N J; Hirsch, H H; Weisser, M; Berger, C; van Delden, C

2018-01-19

Clostridium difficile infection (CDI) is a leading cause of infectious diarrhea in solid organ transplant recipients (SOT). We aimed to assess incidence, risk factors, and outcome of CDI within the Swiss Transplant Cohort Study (STCS). We performed a case-control study of SOT recipients in the STCS diagnosed with CDI between May 2008 and August 2013. We matched 2 control subjects per case by age at transplantation, sex, and transplanted organ. A multivariable analysis was performed using conditional logistic regression to identify risk factors and evaluate outcome of CDI. Two thousand one hundred fifty-eight SOT recipients, comprising 87 cases of CDI and 174 matched controls were included. The overall CDI rate per 10 000 patient days was 0.47 (95% confidence interval ([CI] 0.38-0.58), with the highest rate in lung (1.48, 95% CI 0.93-2.24). In multivariable analysis, proven infections (hazard ratio [HR] 2.82, 95% CI 1.29-6.19) and antibiotic treatments (HR 4.51, 95% CI 2.03-10.0) during the preceding 3 months were independently associated with the development of CDI. Despite mild clinical presentations, recipients acquiring CDI posttransplantation had an increased risk of graft loss (HR 2.24, 95% CI 1.15-4.37; P = .02). These findings may help to improve the management of SOT recipients. © 2018 The American Society of Transplantation and the American Society of Transplant Surgeons.

Hyperconnectivity in juvenile myoclonic epilepsy: a network analysis.

PubMed

Caeyenberghs, K; Powell, H W R; Thomas, R H; Brindley, L; Church, C; Evans, J; Muthukumaraswamy, S D; Jones, D K; Hamandi, K

2015-01-01

Juvenile myoclonic epilepsy (JME) is a common idiopathic (genetic) generalized epilepsy (IGE) syndrome characterized by impairments in executive and cognitive control, affecting independent living and psychosocial functioning. There is a growing consensus that JME is associated with abnormal function of diffuse brain networks, typically affecting frontal and fronto-thalamic areas. Using diffusion MRI and a graph theoretical analysis, we examined bivariate (network-based statistic) and multivariate (global and local) properties of structural brain networks in patients with JME (N = 34) and matched controls. Neuropsychological assessment was performed in a subgroup of 14 patients. Neuropsychometry revealed impaired visual memory and naming in JME patients despite a normal full scale IQ (mean = 98.6). Both JME patients and controls exhibited a small world topology in their white matter networks, with no significant differences in the global multivariate network properties between the groups. The network-based statistic approach identified one subnetwork of hyperconnectivity in the JME group, involving primary motor, parietal and subcortical regions. Finally, there was a significant positive correlation in structural connectivity with cognitive task performance. Our findings suggest that structural changes in JME patients are distributed at a network level, beyond the frontal lobes. The identified subnetwork includes key structures in spike wave generation, along with primary motor areas, which may contribute to myoclonic jerks. We conclude that analyzing the affected subnetworks may provide new insights into understanding seizure generation, as well as the cognitive deficits observed in JME patients.

Hyperconnectivity in juvenile myoclonic epilepsy: A network analysis

PubMed Central

Caeyenberghs, K.; Powell, H.W.R.; Thomas, R.H.; Brindley, L.; Church, C.; Evans, J.; Muthukumaraswamy, S.D.; Jones, D.K.; Hamandi, K.

2014-01-01

Objective Juvenile myoclonic epilepsy (JME) is a common idiopathic (genetic) generalized epilepsy (IGE) syndrome characterized by impairments in executive and cognitive control, affecting independent living and psychosocial functioning. There is a growing consensus that JME is associated with abnormal function of diffuse brain networks, typically affecting frontal and fronto-thalamic areas. Methods Using diffusion MRI and a graph theoretical analysis, we examined bivariate (network-based statistic) and multivariate (global and local) properties of structural brain networks in patients with JME (N = 34) and matched controls. Neuropsychological assessment was performed in a subgroup of 14 patients. Results Neuropsychometry revealed impaired visual memory and naming in JME patients despite a normal full scale IQ (mean = 98.6). Both JME patients and controls exhibited a small world topology in their white matter networks, with no significant differences in the global multivariate network properties between the groups. The network-based statistic approach identified one subnetwork of hyperconnectivity in the JME group, involving primary motor, parietal and subcortical regions. Finally, there was a significant positive correlation in structural connectivity with cognitive task performance. Conclusions Our findings suggest that structural changes in JME patients are distributed at a network level, beyond the frontal lobes. The identified subnetwork includes key structures in spike wave generation, along with primary motor areas, which may contribute to myoclonic jerks. We conclude that analyzing the affected subnetworks may provide new insights into understanding seizure generation, as well as the cognitive deficits observed in JME patients. PMID:25610771

Multivariable speed synchronisation for a parallel hybrid electric vehicle drivetrain

NASA Astrophysics Data System (ADS)

Alt, B.; Antritter, F.; Svaricek, F.; Schultalbers, M.

2013-03-01

In this article, a new drivetrain configuration of a parallel hybrid electric vehicle is considered and a novel model-based control design strategy is given. In particular, the control design covers the speed synchronisation task during a restart of the internal combustion engine. The proposed multivariable synchronisation strategy is based on feedforward and decoupled feedback controllers. The performance and the robustness properties of the closed-loop system are illustrated by nonlinear simulation results.

Integrated GIS and multivariate statistical analysis for regional scale assessment of heavy metal soil contamination: A critical review.

PubMed

Hou, Deyi; O'Connor, David; Nathanail, Paul; Tian, Li; Ma, Yan

2017-12-01

Heavy metal soil contamination is associated with potential toxicity to humans or ecotoxicity. Scholars have increasingly used a combination of geographical information science (GIS) with geostatistical and multivariate statistical analysis techniques to examine the spatial distribution of heavy metals in soils at a regional scale. A review of such studies showed that most soil sampling programs were based on grid patterns and composite sampling methodologies. Many programs intended to characterize various soil types and land use types. The most often used sampling depth intervals were 0-0.10 m, or 0-0.20 m, below surface; and the sampling densities used ranged from 0.0004 to 6.1 samples per km 2 , with a median of 0.4 samples per km 2 . The most widely used spatial interpolators were inverse distance weighted interpolation and ordinary kriging; and the most often used multivariate statistical analysis techniques were principal component analysis and cluster analysis. The review also identified several determining and correlating factors in heavy metal distribution in soils, including soil type, soil pH, soil organic matter, land use type, Fe, Al, and heavy metal concentrations. The major natural and anthropogenic sources of heavy metals were found to derive from lithogenic origin, roadway and transportation, atmospheric deposition, wastewater and runoff from industrial and mining facilities, fertilizer application, livestock manure, and sewage sludge. This review argues that the full potential of integrated GIS and multivariate statistical analysis for assessing heavy metal distribution in soils on a regional scale has not yet been fully realized. It is proposed that future research be conducted to map multivariate results in GIS to pinpoint specific anthropogenic sources, to analyze temporal trends in addition to spatial patterns, to optimize modeling parameters, and to expand the use of different multivariate analysis tools beyond principal component analysis (PCA) and cluster analysis (CA). Copyright © 2017 Elsevier Ltd. All rights reserved.

LinkWinds: An Approach to Visual Data Analysis

NASA Technical Reports Server (NTRS)

Jacobson, Allan S.

1992-01-01

The Linked Windows Interactive Data System (LinkWinds) is a prototype visual data exploration and analysis system resulting from a NASA/JPL program of research into graphical methods for rapidly accessing, displaying and analyzing large multivariate multidisciplinary datasets. It is an integrated multi-application execution environment allowing the dynamic interconnection of multiple windows containing visual displays and/or controls through a data-linking paradigm. This paradigm, which results in a system much like a graphical spreadsheet, is not only a powerful method for organizing large amounts of data for analysis, but provides a highly intuitive, easy to learn user interface on top of the traditional graphical user interface.

Cancer screening delivery in persistent poverty rural counties.

PubMed

Bennett, Kevin J; Pumkam, Chaiporn; Bellinger, Jessica D; Probst, Janice C

2011-10-01

Rural populations are diagnosed with cancer at different rate and stages than nonrural populations, and race/ethnicity as well as the area-level income exacerbates the differences. The purpose of this analysis was to explore cancer screening rates across persistent poverty rural counties, with emphasis on nonwhite populations. The 2008 Behavioral Risk Factor Surveillance System was used, combined with data from the Area Resource File (analytic n = 309 937 unweighted, 196 344 347 weighted). Unadjusted analysis estimated screening rates for breast, cervical, and colorectal cancer. Multivariate analysis estimated the odds of screening, controlling for individual and county-level effects. Rural residents, particularly those in persistent poverty counties, were less likely to be screened than urban residents. More African Americans in persistent poverty rural counties reported not having mammography screening (18.3%) compared to 15.9% of urban African Americans. Hispanics had low screening rates across all service types. Multivariate analysis continued to find disparities in screening rates, after controlling for individual and county-level factors. African Americans in persistent poverty rural counties were more likely to be screened for both breast cancer (odds ratio, 1.44; 95% confidence interval, 1.12-1.85) and cervical cancer (1.46; 1.07-1.99) when compared with urban whites. Disparities in cancer screening rates exist across not only race/ethnicity but also county type. These disparities cannot be fully explained by either individual or county-level effects. Programs have been successful in improving screening rates for African American women and should be expanded to target other vulnerable women as well as other services such as colorectal cancer screening.

Resolving Identification Issues of Saraca asoca from Its Adulterant and Commercial Samples Using Phytochemical Markers

PubMed Central

Hegde, Satisha; Hegde, Harsha Vasudev; Jalalpure, Sunil Satyappa; Peram, Malleswara Rao; Pai, Sandeep Ramachandra; Roy, Subarna

2017-01-01

Saraca asoca (Roxb.) De Wilde (Ashoka) is a highly valued endangered medicinal tree species from Western Ghats of India. Besides treating cardiac and circulatory problems, S. asoca provides immense relief in gynecological disorders. Higher price and demand, in contrast to the smaller population size of the plant, have motivated adulteration with other plants such as Polyalthia longifolia (Sonnerat) Thwaites. The fundamental concerns in quality control of S. asoca arise due to its part of medicinal value (Bark) and the chemical composition. Phytochemical fingerprinting with proper selection of analytical markers is a promising method in addressing quality control issues. In the present study, high-performance liquid chromatography of phenolic compounds (gallic acid, catechin, and epicatechin) coupled to multivariate analysis was used. Five samples each of S. asoca, P. longifolia from two localities alongside five commercial market samples showed evidence of adulteration. Subsequently, multivariate hierarchical cluster analysis and principal component analysis was established to discriminate the adulterants of S. asoca. The proposed method ascertains identification of S. asoca from its putative adulterant P. longifolia and commercial market samples. The data generated may also serve as baseline data to form a quality standard for pharmacopoeias. SUMMARY Simultaneous quantification of gallic acid, catechin, epicatechin from Saraca asoca by high-performance liquid chromatographyDetection of S. asoca from adulterant and commercial samplesUse of analytical method along with a statistical tool for addressing quality issues. Abbreviations used: HPLC: High Performance Liquid Chromatography; RP-HPLC: Reverse Phase High Performance Liquid Chromatography; CAT: Catechin; EPI: Epicatechin; GA: Gallic acid; PCA: Principal Component Analysis. PMID:28808391

Comparison of connectivity analyses for resting state EEG data

NASA Astrophysics Data System (ADS)

Olejarczyk, Elzbieta; Marzetti, Laura; Pizzella, Vittorio; Zappasodi, Filippo

2017-06-01

Objective. In the present work, a nonlinear measure (transfer entropy, TE) was used in a multivariate approach for the analysis of effective connectivity in high density resting state EEG data in eyes open and eyes closed. Advantages of the multivariate approach in comparison to the bivariate one were tested. Moreover, the multivariate TE was compared to an effective linear measure, i.e. directed transfer function (DTF). Finally, the existence of a relationship between the information transfer and the level of brain synchronization as measured by phase synchronization value (PLV) was investigated. Approach. The comparison between the connectivity measures, i.e. bivariate versus multivariate TE, TE versus DTF, TE versus PLV, was performed by means of statistical analysis of indexes based on graph theory. Main results. The multivariate approach is less sensitive to false indirect connections with respect to the bivariate estimates. The multivariate TE differentiated better between eyes closed and eyes open conditions compared to DTF. Moreover, the multivariate TE evidenced non-linear phenomena in information transfer, which are not evidenced by the use of DTF. We also showed that the target of information flow, in particular the frontal region, is an area of greater brain synchronization. Significance. Comparison of different connectivity analysis methods pointed to the advantages of nonlinear methods, and indicated a relationship existing between the flow of information and the level of synchronization of the brain.

The influence of patient, caregiver, and family factors on symptoms of anxiety and depression in children and adolescents with intractable epilepsy.

PubMed

Puka, Klajdi; Widjaja, Elysa; Smith, Mary Lou

2017-02-01

The objective was to evaluate the association of caregiver and family factors with symptoms of anxiety and depression in children and adolescents with medically refractory localization-related epilepsy (i.e., failed at least two epilepsy medications). Forty-four children (ages 6-11years) and 65 adolescents (ages 12-18years) and their parents participated in this multicentered, observational, cross-sectional study. Univariable and multivariable linear regressions were used to evaluate the influence of multiple patient, caregiver, and family characteristics on self-reported symptoms of anxiety and depression in the children and adolescents. Among children, depressive symptoms were associated with a lower proportion of life with seizures (β=.344, p=.022), caregiver depression (β=.462, p=.002), poorer family relationships (β=.384, p=.010), and poorer family mastery and social support (β=.337, p=.025); in multivariable analysis, proportion of life with epilepsy and parental depression remained significant. No significant predictors of anxiety were found among children. Among adolescents, depressive symptoms were associated with caregiver unemployment (β=.345, p=.005) and anxiety (β=.359, p=.003), low household income (β=.321, p=.012), poorer family mastery and social support (β=.334, p=.007), and greater family demands (β=.326, p=.008); in multivariable analysis, caregiver unemployment and anxiety remained significant. Greater anxiety symptoms among adolescents were associated with females (β=.320, p=.009) and caregiver depression (β=.246, p=.048) and anxiety (β=.392, p=.001) and poorer family mastery and social support (β=.247, p=.047); in multivariable analysis, female sex and caregiver anxiety remained significant. These findings highlight the central role of caregiver psychopathology, which is amenable to intervention, on children and adolescents' symptoms of anxiety and depression. Addressing caregiver psychopathology may improve children and adolescents' quality of life even if seizure control is not attained. Copyright © 2016 Elsevier Inc. All rights reserved.

Apolipoprotein E Polymorphism and Left Ventricular Failure in Beta-Thalassemia: A Multivariate Meta-Analysis.

PubMed

Dimou, Niki L; Pantavou, Katerina G; Bagos, Pantelis G

2017-09-01

Apolipoprotein E (ApoE) is potentially a genetic risk factor for the development of left ventricular failure (LVF), the main cause of death in beta-thalassemia homozygotes. In the present study, we synthesize the results of independent studies examining the effect of ApoE on LVF development in thalassemic patients through a meta-analytic approach. However, all studies report more than one outcome, as patients are classified into three groups according to the severity of the symptoms and the genetic polymorphism. Thus, a multivariate meta-analytic method that addresses simultaneously multiple exposures and multiple comparison groups was developed. Four individual studies were included in the meta-analysis involving 613 beta-thalassemic patients and 664 controls. The proposed method that takes into account the correlation of log odds ratios (log(ORs)), revealed a statistically significant overall association (P-value  =  0.009), mainly attributed to the contrast of E4 versus E3 allele for patients with evidence (OR: 2.32, 95% CI: 1.19, 4.53) or patients with clinical and echocardiographic findings (OR: 3.34, 95% CI: 1.78, 6.26) of LVF. This study suggests that E4 is a genetic risk factor for LVF in beta-thalassemia major. The presented multivariate approach can be applied in several fields of research. © 2017 John Wiley & Sons Ltd/University College London.

Conic Sector Analysis of Hybrid Control Systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Thompson, P. M.

1982-01-01

A hybrid control system contains an analog plant and a hybrid (or sampled-data) compensator. In this thesis a new conic sector is determined which is constructive and can be used to: (1) determine closed loop stability, (2) analyze robustness with respect to modelling uncertainties, (3) analyze steady state response to commands, and (4) select the sample rate. The use of conic sectors allows the designer to treat hybrid control systems as though they were analog control systems. The center of the conic sector can be used as a rigorous linear time invariant approximation of the hybrid control system, and the radius places a bound on the errors of this approximation. The hybrid feedback system can be multivariable, and the sampler is assumed to be synchronous. Algorithms to compute the conic sector are presented. Several examples demonstrate how the conic sector analysis techniques are applied. Extensions to single loop multirate hybrid feedback systems are presented. Further extensions are proposed for multiloop multirate hybrid feedback system and for single rate systems with asynchronous sampling.

MULTIVARIATE CURVE RESOLUTION OF NMR SPECTROSCOPY METABONOMIC DATA

EPA Science Inventory

Sandia National Laboratories is working with the EPA to evaluate and develop mathematical tools for analysis of the collected NMR spectroscopy data. Initially, we have focused on the use of Multivariate Curve Resolution (MCR) also known as molecular factor analysis (MFA), a tech...

Understanding adaptive gait in lower-limb amputees: insights from multivariate analyses

PubMed Central

2013-01-01

Background In this paper we use multivariate statistical techniques to gain insights into how adaptive gait involving obstacle crossing is regulated in lower-limb amputees compared to able-bodied controls, with the aim of identifying underlying characteristics that differ between the two groups and consequently highlighting gait deficits in the amputees. Methods Eight unilateral trans-tibial amputees and twelve able-bodied controls completed adaptive gait trials involving negotiating various height obstacles; with amputees leading with their prosthetic limb. Spatiotemporal variables that are regularly used to quantify how gait is adapted when crossing obstacles were determined and subsequently analysed using multivariate statistical techniques. Results and discussion There were fundamental differences in the adaptive gait between the two groups. Compared to controls, amputees had a reduced approach velocity, reduced foot placement distance before and after the obstacle and reduced foot clearance over it, and reduced lead-limb knee flexion during the step following crossing. Logistic regression analysis highlighted the variables that best distinguished between the gait of the two groups and multiple regression analysis (with approach velocity as a controlling factor) helped identify what gait adaptations were driving the differences seen in these variables. Getting closer to the obstacle before crossing it appeared to be a strategy to ensure the heel of the lead-limb foot passed over the obstacle prior to the foot being lowered to the ground. Despite adopting such a heel clearance strategy, the lead-foot was positioned closer to the obstacle following crossing, which was likely a result of a desire to attain a limb/foot angle and orientation at instant of landing that minimised loads on the residuum (as evidenced by the reduced lead-limb knee flexion during the step following crossing). These changes in foot placement meant the foot was in a different part of swing at point of crossing and this explains why foot clearance was considerably reduced in amputees. Conclusions These results highlight that trans-tibial amputees use quite different gait adaptations to cross obstacles compared with controls (at least when leading with their prosthetic limb), indicating they are governed by different constraints; seemingly related to how they land on/load their prosthesis after crossing the obstacle. PMID:23958032

Metastatic Melanoma Induced Metabolic Changes in C57BL/6J Mouse Stomach Measured by 1H NMR Spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, M; Wang, Xiliang

Melanoma is a malignant tumor of melanocytes with high capability of invasion and rapid metastasis to other organs. Malignant melanoma is the most common metastatic malignancy found in gastrointestinal tract (GI). To the best of our knowledge, previous studies of melanoma in gastrointestinal tract are all clinical case reports. In this work, 1H NMR-based metabolomics approach is used to investigate the metabolite profiles differences of stomach tissue extracts of metastatic B16-F10 melanoma in C57BL/6J mouse and search for specific metabolite biomarker candidates. Principal Component Analysis (PCA), an unsupervised multivariate data analysis method, is used to detect possible outliers, while Orthogonalmore » Projection to Latent Structure (OPLS), a supervised multivariate data analysis method, is employed to evaluate important metabolites responsible for discriminating the control and the melanoma groups. Both PCA and OPLS results reveal that the melanoma group can be well separated from its control group. Among the 50 identified metabolites, it is found that the concentrations of 19 metabolites are statistically and significantly changed with the levels of O-phosphocholine and hypoxanthine down-regulated while the levels of isoleucine, leucine, valine, isobutyrate, threonine, cadaverine, alanine, glutamate, glutamine, methionine, citrate, asparagine, tryptophan, glycine, serine, uracil, and formate up-regulated in the melanoma group. These significantly changed metabolites are associated with multiple biological pathways and may be potential biomarkers for metastatic melanoma in stomach.« less

Metastatic Melanoma Induced Metabolic Changes in C57BL/6J Mouse Stomach Measured by 1H NMR Spectroscopy

DOE PAGES

Hu, M; Wang, Xiliang

2014-12-05

Melanoma is a malignant tumor of melanocytes with high capability of invasion and rapid metastasis to other organs. Malignant melanoma is the most common metastatic malignancy found in gastrointestinal tract (GI). To the best of our knowledge, previous studies of melanoma in gastrointestinal tract are all clinical case reports. In this work, 1H NMR-based metabolomics approach is used to investigate the metabolite profiles differences of stomach tissue extracts of metastatic B16-F10 melanoma in C57BL/6J mouse and search for specific metabolite biomarker candidates. Principal Component Analysis (PCA), an unsupervised multivariate data analysis method, is used to detect possible outliers, while Orthogonalmore » Projection to Latent Structure (OPLS), a supervised multivariate data analysis method, is employed to evaluate important metabolites responsible for discriminating the control and the melanoma groups. Both PCA and OPLS results reveal that the melanoma group can be well separated from its control group. Among the 50 identified metabolites, it is found that the concentrations of 19 metabolites are statistically and significantly changed with the levels of O-phosphocholine and hypoxanthine down-regulated while the levels of isoleucine, leucine, valine, isobutyrate, threonine, cadaverine, alanine, glutamate, glutamine, methionine, citrate, asparagine, tryptophan, glycine, serine, uracil, and formate up-regulated in the melanoma group. These significantly changed metabolites are associated with multiple biological pathways and may be potential biomarkers for metastatic melanoma in stomach.« less

Drunk driving detection based on classification of multivariate time series.

PubMed

Li, Zhenlong; Jin, Xue; Zhao, Xiaohua

2015-09-01

This paper addresses the problem of detecting drunk driving based on classification of multivariate time series. First, driving performance measures were collected from a test in a driving simulator located in the Traffic Research Center, Beijing University of Technology. Lateral position and steering angle were used to detect drunk driving. Second, multivariate time series analysis was performed to extract the features. A piecewise linear representation was used to represent multivariate time series. A bottom-up algorithm was then employed to separate multivariate time series. The slope and time interval of each segment were extracted as the features for classification. Third, a support vector machine classifier was used to classify driver's state into two classes (normal or drunk) according to the extracted features. The proposed approach achieved an accuracy of 80.0%. Drunk driving detection based on the analysis of multivariate time series is feasible and effective. The approach has implications for drunk driving detection. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

Metabolomics Approach to Male Lower Urinary Tract Symptoms: Identification of Possible Biomarkers and Potential Targets for New Treatments.

PubMed

Mitsui, Takahiko; Kira, Satoru; Ihara, Tatsuya; Sawada, Norifumi; Nakagomi, Hiroshi; Miyamoto, Tatsuya; Shimura, Hiroshi; Yokomichi, Hiroshi; Takeda, Masayuki

2018-05-01

We identified metabolites using a metabolomics approach and investigated the association between these metabolites and lower urinary tract symptoms. We used a 24-hour bladder diary and I-PSS (International Prostate Symptom Score) to assess micturition behavior and lower urinary tract symptoms in 58 male patients without apparent neurological disease. Lower urinary tract symptoms were defined as a total I-PSS score of 8 or greater. Patients with a score of 7 or less were placed in the control group. A comprehensive study of plasma metabolites was also performed by capillary electrophoresis time-of-flight mass spectrometry. Metabolites were compared between the lower urinary tract symptoms and control groups using the Mann-Whitney U test. Biomarkers of male lower urinary tract symptoms from the metabolites were analyzed using multivariable logistic regression analysis to determine the OR. Of the 58 men 32 were in the lower urinary tract symptoms group and the remaining 26 were in the control group. The 24-hour bladder diary showed that nocturnal urine volume, 24-hour micturition frequency, nocturnal micturition frequency and the nocturia index were significantly higher in the lower urinary tract symptoms group. Metabolomics analysis identified 60 metabolites from patient plasma. Multivariate analysis revealed that increased glutamate and decreased arginine, asparagine and inosine monophosphate were significantly associated with lower urinary tract symptoms in males. Decreases in citrulline and glutamine could also be associated with male lower urinary tract symptoms. Male lower urinary tract symptoms may develop due to abnormal metabolic processes in some pathways. Potential new treatments for lower urinary tract symptoms can be developed by identifying changes in the amino acid profiles. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Transition from LDR to HDR brachytherapy for cervical cancer: Evaluation of tumor control, survival, and toxicity.

PubMed

Romano, K D; Pugh, K J; Trifiletti, D M; Libby, B; Showalter, T N

In 2012, our institution transitioned from low-dose-rate (LDR) brachytherapy to high dose-rate (HDR) brachytherapy. We report clinical outcomes after brachytherapy for cervical cancer at our institution over a continuous 10-year period. From 2004 to 2014, 258 women (184 LDR and 74 HDR) were treated with tandem and ovoid brachytherapy in the multidisciplinary management of International Federation of Gynecology and Obstetrics Stages IA-IVB cervical cancer. Clinical and treatment-related prognostic factors including age, stage, smoking status, relevant doses, and toxicity data were recorded. Median followup for the LDR and HDR groups was 46 months and 12 months, respectively. The majority of patients (92%) received external beam radiotherapy as well as concurrent chemotherapy (83%) before the start of brachytherapy. For all stages, the 1-year local control and overall survival (OS) rates were comparable between the LDR and HDR groups (87% vs. 81%, p = 0.12; and 75% vs. 85%, p = 0.16), respectively. Factors associated with OS on multivariate analysis include age, stage, and nodal involvement. On multivariate analysis, severe toxicity (acute or chronic) was higher with HDR than LDR (24% vs. 10%, p = 0.04). Additional prognostic factors associated with increased severe toxicity include former/current smokers and total dose to lymph nodes. This comparative retrospective analysis of a large cohort of women treated with brachytherapy demonstrates no significant difference in OS or local control between the LDR and HDR. Acute and chronic toxicity increased shortly after the implementation of HDR, highlighting the importance of continued refinement of HDR methods, including integrating advanced imaging. Copyright © 2016 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

A case-control study to identify risk factors for totally implantable central venous port-related bloodstream infection.

PubMed

Lee, Guk Jin; Hong, Sook Hee; Roh, Sang Young; Park, Sa Rah; Lee, Myung Ah; Chun, Hoo Geun; Hong, Young Seon; Kang, Jin Hyoung; Kim, Sang Il; Kim, Youn Jeong; Chun, Ho Jong; Oh, Jung Suk

2014-07-01

To date, the risk factors for central venous port-related bloodstream infection (CVPBSI) in solid cancer patients have not been fully elucidated. We conducted this study in order to determine the risk factors for CVP-BSI in patients with solid cancer. A total of 1,642 patients with solid cancer received an implantable central venous port for delivery of chemotherapy between October 2008 and December 2011 in a single center. CVP-BSI was diagnosed in 66 patients (4%). We selected a control group of 130 patients, who were individually matched with respect to age, sex, and catheter insertion time. CVP-BSI occurred most frequently between September and November (37.9%). The most common pathogen was gram-positive cocci (n=35, 53.0%), followed by fungus (n=14, 21.2%). Multivariate analysis identified monthly catheter-stay as a risk factor for CVP-BSI (p=0.000), however, its risk was lower in primary gastrointestinal cancer than in other cancer (p=0.002). Initial metastatic disease and long catheter-stay were statistically significant factors affecting catheter life span (p=0.005 and p=0.000). Results of multivariate analysis showed that recent transfusion was a risk factor for mortality in patients with CVP-BSI (p=0.047). In analysis of the results with respect to risk factors, prolonged catheter-stay should be avoided as much as possible. It is necessary to be cautious of CVP-BSI in metastatic solid cancer, especially non-gastrointestinal cancer. In addition, avoidance of unnecessary transfusion is essential in order to reduce the mortality of CVP-BSI. Finally, considering the fact that confounding factors may have affected the results, conduct of a well-designed prospective controlled study is warranted.

The choice of prior distribution for a covariance matrix in multivariate meta-analysis: a simulation study.

PubMed

Hurtado Rúa, Sandra M; Mazumdar, Madhu; Strawderman, Robert L

2015-12-30

Bayesian meta-analysis is an increasingly important component of clinical research, with multivariate meta-analysis a promising tool for studies with multiple endpoints. Model assumptions, including the choice of priors, are crucial aspects of multivariate Bayesian meta-analysis (MBMA) models. In a given model, two different prior distributions can lead to different inferences about a particular parameter. A simulation study was performed in which the impact of families of prior distributions for the covariance matrix of a multivariate normal random effects MBMA model was analyzed. Inferences about effect sizes were not particularly sensitive to prior choice, but the related covariance estimates were. A few families of prior distributions with small relative biases, tight mean squared errors, and close to nominal coverage for the effect size estimates were identified. Our results demonstrate the need for sensitivity analysis and suggest some guidelines for choosing prior distributions in this class of problems. The MBMA models proposed here are illustrated in a small meta-analysis example from the periodontal field and a medium meta-analysis from the study of stroke. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data

PubMed Central

Hebart, Martin N.; Görgen, Kai; Haynes, John-Dylan

2015-01-01

The multivariate analysis of brain signals has recently sparked a great amount of interest, yet accessible and versatile tools to carry out decoding analyses are scarce. Here we introduce The Decoding Toolbox (TDT) which represents a user-friendly, powerful and flexible package for multivariate analysis of functional brain imaging data. TDT is written in Matlab and equipped with an interface to the widely used brain data analysis package SPM. The toolbox allows running fast whole-brain analyses, region-of-interest analyses and searchlight analyses, using machine learning classifiers, pattern correlation analysis, or representational similarity analysis. It offers automatic creation and visualization of diverse cross-validation schemes, feature scaling, nested parameter selection, a variety of feature selection methods, multiclass capabilities, and pattern reconstruction from classifier weights. While basic users can implement a generic analysis in one line of code, advanced users can extend the toolbox to their needs or exploit the structure to combine it with external high-performance classification toolboxes. The toolbox comes with an example data set which can be used to try out the various analysis methods. Taken together, TDT offers a promising option for researchers who want to employ multivariate analyses of brain activity patterns. PMID:25610393

A simplified dynamic model of the T700 turboshaft engine

NASA Technical Reports Server (NTRS)

Duyar, Ahmet; Gu, Zhen; Litt, Jonathan S.

1992-01-01

A simplified open-loop dynamic model of the T700 turboshaft engine, valid within the normal operating range of the engine, is developed. This model is obtained by linking linear state space models obtained at different engine operating points. Each linear model is developed from a detailed nonlinear engine simulation using a multivariable system identification and realization method. The simplified model may be used with a model-based real time diagnostic scheme for fault detection and diagnostics, as well as for open loop engine dynamics studies and closed loop control analysis utilizing a user generated control law.

Evaluation of risk factors for perforated peptic ulcer.

PubMed

Yamamoto, Kazuki; Takahashi, Osamu; Arioka, Hiroko; Kobayashi, Daiki

2018-02-15

The aim of this study was to evaluate the prediction factors for perforated peptic ulcer (PPU). At St. Luke's International Hospital in Tokyo, Japan, a case control study was performed between August 2004 and March 2016. All patients diagnosed with PPU were included. As control subjects, patients with age, sex and date of CT scan corresponding to those of the PPU subjects were included in the study at a proportion of 2 controls for every PPU subject. All data such as past medical histories, physical findings, and laboratory data were collected through chart reviews. Univariate analyses and multivariate analyses with logistic regression were conducted, and receiver operating characteristic curves (ROCs) were calculated to show validity. Sensitivity analyses were performed to confirm results using a stepwise method and conditional logistic regression. A total of 408 patients were included in this study; 136 were a group of patients with PPU, and 272 were a control group. Univariate analysis showed statistical significance in many categories. Four different models of multivariate analyses were conducted, and significant differences were found for muscular defense and a history of peptic ulcer disease (PUD) in all models. The conditional forced-entry analysis of muscular defense showed an odds ratio (OR) of 23.8 (95% confidence interval [CI]: 5.70-100.0), and the analysis of PUD history showed an OR of 6.40 (95% CI: 1.13-36.2). The sensitivity analysis showed consistent results, with an OR of 23.8-366.2 for muscular defense and an OR of 3.67-7.81 for PUD history. The area under the curve (AUC) of all models was high enough to confirm the results. However, anticoagulants, known risk factors for PUD, did not increase the risk for PPU in our study. The conditional forced-entry analysis of anticoagulant use showed an OR of 0.85 (95% CI: 0.03-22.3). The evaluation of prediction factors and development of a prediction rule for PPU may help our decision making in performing a CT scan for patients with acute abdominal pain.

Depressive symptoms in HIV-infected and seronegative control subjects in Cameroon: Effect of age, education and gender

PubMed Central

Kanmogne, Georgette D.; Qiu, Fang; Ntone, Félicien E.; Fonsah, Julius Y.; Njamnshi, Dora M.; Kuate, Callixte T.; Doh, Roland F.; Kengne, Anne M.; Tagny, Claude T.; Nchindap, Emilienne; Kenmogne, Léopoldine; Mbanya, Dora; Cherner, Mariana; Heaton, Robert K.; Njamnshi, Alfred K.

2017-01-01

Depression is a leading cause of HIV/AIDS disease burden; it worsens health outcomes and quality of life. Addressing this problem requires accurate quantification of the extra burden of depression to HIV/AIDS in a given population, and knowledge of the baseline depression prevalence in the general population. There has been no previous study of depression in the general Cameroonian population. The current study attempts to address that important need. We used the Beck Depression Inventory-II to assess the prevalence and severity of depressive symptoms in 270 HIV-infected and seronegative Cameroonians. Univariate analyses showed a trend toward higher depressive symptoms among cases, compared to controls (p = 0.055), and among older subjects (>40 years), compared to younger subjects (≤40 years) (p = 0.059). Analysis of depression severity showed that 33.73% of cases had moderate-to-severe depressive symptoms, compared to 19.8% of controls (p<0.01). However, multivariable negative binomial regression analyses showed no effect of age, HIV status, CD4 levels, viral loads, ART, or opportunistic infections on the risk of depressive symptoms. Both univariate and multivariable regression analyses showed significantly higher risk of depressive symptoms among females compared to males; this was significant for both female controls and female cases. Female cases had significantly higher CD4 cell counts and lower viral loads, compared to males. Both univariate and multivariable regression analyses showed that lower education (≤10 years) was associated with increased risk of depressive symptoms. This study shows a high prevalence of depressive symptoms among seronegative controls and HIV-infected Cameroonians. Integrating care for mental disorders such as depression into primary health care and existing HIV/AIDS treatment programs in Cameroon may improve the wellbeing of the general population and could lower the HIV/AIDS burden. PMID:28231258

Depressive symptoms in HIV-infected and seronegative control subjects in Cameroon: Effect of age, education and gender.

PubMed

Kanmogne, Georgette D; Qiu, Fang; Ntone, Félicien E; Fonsah, Julius Y; Njamnshi, Dora M; Kuate, Callixte T; Doh, Roland F; Kengne, Anne M; Tagny, Claude T; Nchindap, Emilienne; Kenmogne, Léopoldine; Mbanya, Dora; Cherner, Mariana; Heaton, Robert K; Njamnshi, Alfred K

2017-01-01

Depression is a leading cause of HIV/AIDS disease burden; it worsens health outcomes and quality of life. Addressing this problem requires accurate quantification of the extra burden of depression to HIV/AIDS in a given population, and knowledge of the baseline depression prevalence in the general population. There has been no previous study of depression in the general Cameroonian population. The current study attempts to address that important need. We used the Beck Depression Inventory-II to assess the prevalence and severity of depressive symptoms in 270 HIV-infected and seronegative Cameroonians. Univariate analyses showed a trend toward higher depressive symptoms among cases, compared to controls (p = 0.055), and among older subjects (>40 years), compared to younger subjects (≤40 years) (p = 0.059). Analysis of depression severity showed that 33.73% of cases had moderate-to-severe depressive symptoms, compared to 19.8% of controls (p<0.01). However, multivariable negative binomial regression analyses showed no effect of age, HIV status, CD4 levels, viral loads, ART, or opportunistic infections on the risk of depressive symptoms. Both univariate and multivariable regression analyses showed significantly higher risk of depressive symptoms among females compared to males; this was significant for both female controls and female cases. Female cases had significantly higher CD4 cell counts and lower viral loads, compared to males. Both univariate and multivariable regression analyses showed that lower education (≤10 years) was associated with increased risk of depressive symptoms. This study shows a high prevalence of depressive symptoms among seronegative controls and HIV-infected Cameroonians. Integrating care for mental disorders such as depression into primary health care and existing HIV/AIDS treatment programs in Cameroon may improve the wellbeing of the general population and could lower the HIV/AIDS burden.

Comparative Analysis of the Volatile Components of Agrimonia eupatoria from Leaves and Roots by Gas Chromatography-Mass Spectrometry and Multivariate Curve Resolution

PubMed Central

Feng, Xiao-Liang; He, Yun-biao; Liang, Yi-Zeng; Wang, Yu-Lin; Huang, Lan-Fang; Xie, Jian-Wei

2013-01-01

Gas chromatography-mass spectrometry and multivariate curve resolution were applied to the differential analysis of the volatile components in Agrimonia eupatoria specimens from different plant parts. After extracted with water distillation method, the volatile components in Agrimonia eupatoria from leaves and roots were detected by GC-MS. Then the qualitative and quantitative analysis of the volatile components in the main root of Agrimonia eupatoria was completed with the help of subwindow factor analysis resolving two-dimensional original data into mass spectra and chromatograms. 68 of 87 separated constituents in the total ion chromatogram of the volatile components were identified and quantified, accounting for about 87.03% of the total content. Then, the common peaks in leaf were extracted with orthogonal projection resolution method. Among the components determined, there were 52 components coexisting in the studied samples although the relative content of each component showed difference to some extent. The results showed a fair consistency in their GC-MS fingerprint. It was the first time to apply orthogonal projection method to compare different plant parts of Agrimonia eupatoria, and it reduced the burden of qualitative analysis as well as the subjectivity. The obtained results proved the combined approach powerful for the analysis of complex Agrimonia eupatoria samples. The developed method can be used to further study and quality control of Agrimonia eupatoria. PMID:24286016

Comparative Analysis of the Volatile Components of Agrimonia eupatoria from Leaves and Roots by Gas Chromatography-Mass Spectrometry and Multivariate Curve Resolution.

PubMed

Feng, Xiao-Liang; He, Yun-Biao; Liang, Yi-Zeng; Wang, Yu-Lin; Huang, Lan-Fang; Xie, Jian-Wei

2013-01-01

Gas chromatography-mass spectrometry and multivariate curve resolution were applied to the differential analysis of the volatile components in Agrimonia eupatoria specimens from different plant parts. After extracted with water distillation method, the volatile components in Agrimonia eupatoria from leaves and roots were detected by GC-MS. Then the qualitative and quantitative analysis of the volatile components in the main root of Agrimonia eupatoria was completed with the help of subwindow factor analysis resolving two-dimensional original data into mass spectra and chromatograms. 68 of 87 separated constituents in the total ion chromatogram of the volatile components were identified and quantified, accounting for about 87.03% of the total content. Then, the common peaks in leaf were extracted with orthogonal projection resolution method. Among the components determined, there were 52 components coexisting in the studied samples although the relative content of each component showed difference to some extent. The results showed a fair consistency in their GC-MS fingerprint. It was the first time to apply orthogonal projection method to compare different plant parts of Agrimonia eupatoria, and it reduced the burden of qualitative analysis as well as the subjectivity. The obtained results proved the combined approach powerful for the analysis of complex Agrimonia eupatoria samples. The developed method can be used to further study and quality control of Agrimonia eupatoria.

Moving beyond Univariate Post-Hoc Testing in Exercise Science: A Primer on Descriptive Discriminate Analysis

ERIC Educational Resources Information Center

Barton, Mitch; Yeatts, Paul E.; Henson, Robin K.; Martin, Scott B.

2016-01-01

There has been a recent call to improve data reporting in kinesiology journals, including the appropriate use of univariate and multivariate analysis techniques. For example, a multivariate analysis of variance (MANOVA) with univariate post hocs and a Bonferroni correction is frequently used to investigate group differences on multiple dependent…

An approach to multivariable control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

The paper presents simple schemes for multivariable control of multiple-joint robot manipulators in joint and Cartesian coordinates. The joint control scheme consists of two independent multivariable feedforward and feedback controllers. The feedforward controller is the minimal inverse of the linearized model of robot dynamics and contains only proportional-double-derivative (PD2) terms - implying feedforward from the desired position, velocity and acceleration. This controller ensures that the manipulator joint angles track any reference trajectories. The feedback controller is of proportional-integral-derivative (PID) type and is designed to achieve pole placement. This controller reduces any initial tracking error to zero as desired and also ensures that robust steady-state tracking of step-plus-exponential trajectories is achieved by the joint angles. Simple and explicit expressions of computation of the feedforward and feedback gains are obtained based on the linearized model of robot dynamics. This leads to computationally efficient schemes for either on-line gain computation or off-line gain scheduling to account for variations in the linearized robot model due to changes in the operating point. The joint control scheme is extended to direct control of the end-effector motion in Cartesian space. Simulation results are given for illustration.

Determinants of quality of life of patients with heart failure and iron deficiency treated with ferric carboxymaltose: FAIR-HF sub-analysis.

PubMed

Gutzwiller, Florian S; Pfeil, Alena M; Comin-Colet, Josep; Ponikowski, Piotr; Filippatos, Gerasimos; Mori, Claudio; Braunhofer, Peter G; Szucs, Thomas D; Schwenkglenks, Matthias; Anker, Stefan D

2013-10-09

Heart failure (HF) is a burden to patients and health care systems. The objectives of HF treatment are to improve health related quality of life (HRQoL) and reduce mortality and morbidity. We aimed to evaluate determinants of health-related quality of life (HRQoL) in patients with iron deficiency and HF treated with intravenous (i.v.) iron substitution or placebo. A randomised, double-blind, placebo-controlled trial (n = 459) in iron-deficient chronic heart failure (CHF) patients with or without anaemia studied clinical and HRQoL benefits of i.v. iron substitution using ferric carboxymaltose (FCM) over a 24-week trial period. Multivariate analysis was carried out with various clinical variables as independent variables and HRQoL measures as dependent variables. Mean change from baseline of European Quality of Life - 5 Dimensions (EQ-5D) (value set-based) utilities (on a 0 to 100 scale) at week 24 was 8.91 (i.v. iron) and 0.68 (placebo; p < 0.01). In a multivariate analysis excluding baseline HRQoL, a higher exercise tolerance and i.v. iron substitution positively influenced HRQoL, whereas impaired renal function and a history of stroke had a negative effect. The level of HRQoL was also influenced by country of residence. When baseline HRQoL was factored in, the multivariate model remained stable. In this study, i.v. iron substitution, exercise tolerance, stroke, country of residence and renal function influenced measures of HRQoL in patients with heart failure and iron deficiency. © 2013.

Personality traits in the differentiation of major depressive disorder and bipolar disorder during a depressive episode.

PubMed

Araujo, Jaciana Marlova Gonçalves; dos Passos, Miguel Bezerra; Molina, Mariane Lopez; da Silva, Ricardo Azevedo; Souza, Luciano Dias de Mattos

2016-02-28

The aim of this study was to determine the differences in personality traits between individuals with Major Depressive Disorder (MDD) and Bipolar Disorder (BD) during a depressive episode, when it can be hard to differentiate them. Data on personality traits (NEO-FFI), mental disorders (Mini International Neuropsychiatric Interview Plus) and socioeconomic variables were collected from 245 respondents who were in a depressive episode. Individuals with MDD (183) and BD (62) diagnosis were compared concerning personality traits, clinical aspects and socioeconomic variables through bivariate analyses (chi-square and ANOVA) and multivariate analysis (logistic regression). There were no differences in the prevalence of the disorders between socioeconomic and clinical variables. As for the personality traits, only the difference in Agreeableness was statistically significant. Considering the control of suicide risk, gender and anxiety comorbidity in the multivariate analysis, the only variable that remained associated was Agreeableness, with an increase in MDD cases. The brief version of the NEO inventories (NEO-FFI) does not allow for the analysis of personality facets. During a depressive episode, high levels of Agreeableness can indicate that MDD is a more likely diagnosis than BD. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Cohort comparisons: emotional well-being among adolescents and older adults

PubMed Central

Momtaz, Yadollah Abolfathi; Hamid, Tengku Aizan; Ibrahim, Rahimah

2014-01-01

Background There are several negative stereotypes about older adults that have negatively influenced people’s attitude about aging. The present study compared emotional well-being between older adults and adolescents. Methods Data for this study came from 1,403 community-dwelling elderly persons and 1,190 secondary school students and were obtained from two national cross-sectional surveys. Emotional well-being was measured using the World Health Organization-Five Well-Being Index. Data analysis was conducted using a multivariate analysis of covariance with SPSS software version 20 (IBM Corporation, Armonk, NY, USA). Results Elderly people significantly scored higher levels of emotional well-being (mean, 62.3; standard deviation, 22.55) than younger people (mean, 57.9; standard deviation, 18.46; t, 5.32; P≤0.001). The findings from the multivariate analysis of covariance revealed a significant difference between older adults and younger people in emotional well-being [F(3, 2587)=120.21; P≤0.001; η2=0.122] after controlling for sex. Conclusion Contrary to negative stereotypes about aging, our findings show a higher level of emotional well-being among older adults compared with younger people. PMID:24872683

Investigating the Moisture Content of Polyamide 6 by Raman-Microscopy and Multivariate Data Analysis

NASA Astrophysics Data System (ADS)

Lechner, Tobias; Noack, Kristina; Thöne, Manuel; Amend, Philipp; Schmidt, Michael; Will, Stefan

Thermal malleability of thermoplastics results in a high product diversity in various industry sectors. However, industrial applications require a constant and high component quality. Hence, material processing such as laser welding has to consider that, e.g., the moisture content of thermoplastics influences the mechanical properties such as the tensile strength. Moreover, water evaporates during laser welding and can form pores and defects. Thus, there is a large need for non-invasive material inspection before processing. To that end, we developed a methodology based on Raman-microscopy and multivariate data analysis (MVD) to determine the moisture content of polyamide (MCP). Further, the impact of the MCP on the mechanical properties was verified. For samples with a defined variation of the MCP, xyz-Raman-scans were carried out and analysed using MVD. For reference purposes, the samples were weighted and tensile tests were performed. An evaluation by means of partial least squares regression analysis (PLSR) resulted in a prediction of the MCP with a correlation coefficient >98%. Consequently, Raman-microscopy shows large potential for developing new techniques for inspection and quality control of plastics before processing. Dedicated to Professor Alfred Leipertz on the occasion of his 70th birthday.

Impact of loneliness and depression on mortality: results from the Longitudinal Ageing Study Amsterdam.

PubMed

Holwerda, Tjalling J; van Tilburg, Theo G; Deeg, Dorly J H; Schutter, Natasja; Van, Rien; Dekker, Jack; Stek, Max L; Beekman, Aartjan T F; Schoevers, Robert A

2016-08-01

Loneliness is highly prevalent among older people, has serious health consequences and is an important predictor of mortality. Loneliness and depression may unfavourably interact with each other over time but data on this topic are scarce. To determine whether loneliness is associated with excess mortality after 19 years of follow-up and whether the joint effect with depression confers further excess mortality. Different aspects of loneliness were measured with the De Jong Gierveld scale and depression with the Centre for Epidemiologic Studies Depression Scale in a cohort of 2878 people aged 55-85 with 19 years of follow-up. Excess mortality hypotheses were tested with Kaplan-Meier and Cox proportional hazard analyses controlling for potential confounders. At follow-up loneliness and depression were associated with excess mortality in older men and women in bivariate analysis but not in multivariate analysis. In multivariate analysis, severe depression was associated with excess mortality in men who were lonely but not in women. Loneliness and depression are important predictors of early death in older adults. Severe depression has a strong association with excess mortality in older men who were lonely, indicating a lethal combination in this group. © The Royal College of Psychiatrists 2016.

Groundwater flow and hydrogeochemical evolution in the Jianghan Plain, central China

NASA Astrophysics Data System (ADS)

Gan, Yiqun; Zhao, Ke; Deng, Yamin; Liang, Xing; Ma, Teng; Wang, Yanxin

2018-05-01

Hydrogeochemical analysis and multivariate statistics were applied to identify flow patterns and major processes controlling the hydrogeochemistry of groundwater in the Jianghan Plain, which is located in central Yangtze River Basin (central China) and characterized by intensive surface-water/groundwater interaction. Although HCO3-Ca-(Mg) type water predominated in the study area, the 457 (21 surface water and 436 groundwater) samples were effectively classified into five clusters by hierarchical cluster analysis. The hydrochemical variations among these clusters were governed by three factors from factor analysis. Major components (e.g., Ca, Mg and HCO3) in surface water and groundwater originated from carbonate and silicate weathering (factor 1). Redox conditions (factor 2) influenced the geogenic Fe and As contamination in shallow confined groundwater. Anthropogenic activities (factor 3) primarily caused high levels of Cl and SO4 in surface water and phreatic groundwater. Furthermore, the factor score 1 of samples in the shallow confined aquifer gradually increased along the flow paths. This study demonstrates that enhanced information on hydrochemistry in complex groundwater flow systems, by multivariate statistical methods, improves the understanding of groundwater flow and hydrogeochemical evolution due to natural and anthropogenic impacts.

Multivariate meta-analysis using individual participant data

PubMed Central

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2016-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment–covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. PMID:26099484

Risk factors associated with the community-acquired colonization of extended-spectrum beta-lactamase (ESBL) positive Escherichia Coli. an exploratory case-control study.

PubMed

Leistner, Rasmus; Meyer, Elisabeth; Gastmeier, Petra; Pfeifer, Yvonne; Eller, Christoph; Dem, Petra; Schwab, Frank

2013-01-01

The number of extended-spectrum beta-lactamase (ESBL) positive (+) Escherichia coli is increasing worldwide. In contrast with many other multidrug-resistant bacteria, it is suspected that they predominantly spread within the community. The objective of this study was to assess factors associated with community-acquired colonization of ESBL (+) E. coli. We performed a matched case-control study at the Charité University Hospital Berlin between May 2011 and January 2012. Cases were defined as patients colonized with community-acquired ESBL (+) E. coli identified <72 h after hospital admission. Controls were patients that carried no ESBL-positive bacteria but an ESBL-negative E.coli identified <72 h after hospital admission. Two controls per case were chosen from potential controls according to admission date. Case and control patients completed a questionnaire assessing nutritional habits, travel habits, household situation and language most commonly spoken at home (mother tongue). An additional rectal swab was obtained together with the questionnaire to verify colonization status. Genotypes of ESBL (+) E. coli strains were determined by PCR and sequencing. Risk factors associated with ESBL (+) E. coli colonization were analyzed by a multivariable conditional logistic regression analysis. We analyzed 85 cases and 170 controls, respectively. In the multivariable analysis, speaking an Asian language most commonly at home (OR = 13.4, CI 95% 3.3-53.8; p<0.001) and frequently eating pork (≥ 3 meals per week) showed to be independently associated with ESBL colonization (OR = 3.5, CI 95% 1.8-6.6; p<0.001). The most common ESBL genotypes were CTX-M-1 with 44% (n = 37), CTX-M-15 with 28% (n = 24) and CTX-M-14 with 13% (n = 11). An Asian mother tongue and frequently consuming certain types of meat like pork can be independently associated with the colonization of ESBL-positive bacteria. We found neither frequent consumption of poultry nor previous use of antibiotics to be associated with ESBL colonization.

Nonspecific ST-T changes associated with unsatisfactory blood pressure control among adults with hypertension in China: Evidence from the CSPTT study.

PubMed

Bao, Huihui; Cai, Huaxiu; Zhao, Yan; Huang, Xiao; Fan, Fangfang; Zhang, Chunyan; Li, Juxiang; Chen, Jing; Hong, Kui; Li, Ping; Wu, Yanqing; Wu, Qinhua; Wang, Binyan; Xu, Xiping; Li, Yigang; Huo, Yong; Cheng, Xiaoshu

2017-03-01

Nonspecific ST-segment and T-wave (ST-T) changes represent one of the most prevalent electrocardiographic abnormalities in hypertensive patients. However, a limited number of studies have investigated the association between nonspecific ST-T changes and unsatisfactory blood pressure (BP) control in adults with hypertension.The study population comprised 15,038 hypertensive patients, who were selected from 20,702 participants in the China Stroke Primary Prevention Trial. The subjects were examined with electrocardiogram test at the initial visit in order to monitor baseline heart activity. According to the results of the electrocardiogram (defined by Minnesota coding), the subjects were divided into 2 groups: ST-T abnormal and ST-T normal. Unsatisfactory BP control was defined as systolic BP ≥140 mm Hg or diastolic BP ≥90 mm Hg following antihypertensive treatment during the 4.5-year follow-up period. Multivariate analysis was used to analyze the association between nonspecific ST-T abnormalities and unsatisfactory BP control.Nonspecific ST-T changes were common in hypertensive adults (approximately 8.5% in the study), and more prevalent in women (10.3%) and diabetic patients (13.9%). The unsatisfactory BP control rate was high in the total population (47.0%), notably in the ST-T abnormal group (55.5%). The nonspecific ST-T abnormal group exhibited a significantly greater rate of unsatisfactory BP control (odds ratio [OR] 1.20, 95% confidence interval [CI] [1.06, 1.36], P = 0.005]), independent of traditional risk factors, as demonstrated by multivariate regression analysis. Notable differences were further observed in male subjects (OR 1.51, 95% CI [1.17, 1.94], P = 0.002) and in patients with comorbid diabetes (OR 1.47, 95% CI [1.04, 2.07], P = 0.029).Greater rates of unsatisfactory BP control in hypertensive patients with electrocardiographic nonspecific ST-T abnormalities were observed, notably in the subcategories of the male subjects and the diabetic patients.

Non-uniform multivariate embedding to assess the information transfer in cardiovascular and cardiorespiratory variability series.

PubMed

Faes, Luca; Nollo, Giandomenico; Porta, Alberto

2012-03-01

The complexity of the short-term cardiovascular control prompts for the introduction of multivariate (MV) nonlinear time series analysis methods to assess directional interactions reflecting the underlying regulatory mechanisms. This study introduces a new approach for the detection of nonlinear Granger causality in MV time series, based on embedding the series by a sequential, non-uniform procedure, and on estimating the information flow from one series to another by means of the corrected conditional entropy. The approach is validated on short realizations of linear stochastic and nonlinear deterministic processes, and then evaluated on heart period, systolic arterial pressure and respiration variability series measured from healthy humans in the resting supine position and in the upright position after head-up tilt. Copyright © 2011 Elsevier Ltd. All rights reserved.

The role of middle-class status in payday loan borrowing: a multivariate approach.

PubMed

Lim, Younghee; Bickham, Trey; Broussard, Julia; Dinecola, Cassie M; Gregory, Alethia; Weber, Brittany E

2014-10-01

Payday loans refer to small-dollar, high-interest, short-term loans usually extended to lower-income consumers. Despite much research to the contrary, the payday loan industry asserts that it primarily serves middle-class Americans. This article discusses the authors' investigation of the industry's claim, by analyzing data from a U.S. bankruptcy court serving a Southern district. Results of the multivariate binary logistic regression analysis showed that, controlling for various sociodemographic and economic variables, two middle-class indicators--home-ownership and annual income at or greater than the median income--are associated with a decreased likelihood of using payday loans. The article concludes with a discussion of the implications of the results for social work practice and advocacy in regard to financial capability, particularly asset development, income maintenance, and payday loan regulation.

Hybrid least squares multivariate spectral analysis methods

DOEpatents

Haaland, David M.

2002-01-01

A set of hybrid least squares multivariate spectral analysis methods in which spectral shapes of components or effects not present in the original calibration step are added in a following estimation or calibration step to improve the accuracy of the estimation of the amount of the original components in the sampled mixture. The "hybrid" method herein means a combination of an initial classical least squares analysis calibration step with subsequent analysis by an inverse multivariate analysis method. A "spectral shape" herein means normally the spectral shape of a non-calibrated chemical component in the sample mixture but can also mean the spectral shapes of other sources of spectral variation, including temperature drift, shifts between spectrometers, spectrometer drift, etc. The "shape" can be continuous, discontinuous, or even discrete points illustrative of the particular effect.

Directly observed treatment is associated with reduced default among foreign tuberculosis patients in Thailand.

PubMed

Kapella, B K; Anuwatnonthakate, A; Komsakorn, S; Moolphate, S; Charusuntonsri, P; Limsomboon, P; Wattanaamornkiat, W; Nateniyom, S; Varma, J K

2009-02-01

Thailand's Tuberculosis (TB) Active Surveillance Network in four provinces in Thailand. As treatment default is common in mobile and foreign populations, we evaluated risk factors for default among non-Thai TB patients in Thailand. Observational cohort study using TB program data. Analysis was restricted to patients with an outcome categorized as cured, completed, failure or default. We used multivariate analysis to identify factors associated with default, including propensity score analysis, to adjust for factors associated with receiving directly observed treatment (DOT). During October 2004-September 2006, we recorded data for 14359 TB patients, of whom 995 (7%) were non-Thais. Of the 791 patients analyzed, 313 (40%) defaulted. In multivariate analysis, age>or=45 years (RR 1.47, 95%CI 1.25-1.74), mobility (RR 2.36, 95%CI 1.77-3.14) and lack of DOT (RR 2.29, 95%CI 1.45-3.61) were found to be significantly associated with default among non-Thais. When controlling for propensity to be assigned DOT, the risk of default remained increased in those not assigned DOT (RR 1.99, 95%CI 1.03-3.85). In non-Thai TB patients, DOT was the only modifiable factor associated with default. Using DOT may help improve TB treatment outcomes in non-Thai TB patients.

Multispectral UV imaging for surface analysis of MUPS tablets with special focus on the pellet distribution.

PubMed

Novikova, Anna; Carstensen, Jens M; Rades, Thomas; Leopold, Prof Dr Claudia S

2016-12-30

In the present study the applicability of multispectral UV imaging in combination with multivariate image analysis for surface evaluation of MUPS tablets was investigated with respect to the differentiation of the API pellets from the excipients matrix, estimation of the drug content as well as pellet distribution, and influence of the coating material and tablet thickness on the predictive model. Different formulations consisting of coated drug pellets with two coating polymers (Aquacoat ® ECD and Eudragit ® NE 30 D) at three coating levels each were compressed to MUPS tablets with various amounts of coated pellets and different tablet thicknesses. The coated drug pellets were clearly distinguishable from the excipients matrix using a partial least squares approach regardless of the coating layer thickness and coating material used. Furthermore, the number of the detected drug pellets on the tablet surface allowed an estimation of the true drug content in the respective MUPS tablet. In addition, the pellet distribution in the MUPS formulations could be estimated by UV image analysis of the tablet surface. In conclusion, this study revealed that UV imaging in combination with multivariate image analysis is a promising approach for the automatic quality control of MUPS tablets during the manufacturing process. Copyright © 2016 Elsevier B.V. All rights reserved.

Multivariate statistical analysis of heavy metal concentration in soils of Yelagiri Hills, Tamilnadu, India--spectroscopical approach.

PubMed

Chandrasekaran, A; Ravisankar, R; Harikrishnan, N; Satapathy, K K; Prasad, M V R; Kanagasabapathy, K V

2015-02-25

Anthropogenic activities increase the accumulation of heavy metals in the soil environment. Soil pollution significantly reduces environmental quality and affects the human health. In the present study soil samples were collected at different locations of Yelagiri Hills, Tamilnadu, India for heavy metal analysis. The samples were analyzed for twelve selected heavy metals (Mg, Al, K, Ca, Ti, Fe, V, Cr, Mn, Co, Ni and Zn) using energy dispersive X-ray fluorescence (EDXRF) spectroscopy. Heavy metals concentration in soil were investigated using enrichment factor (EF), geo-accumulation index (Igeo), contamination factor (CF) and pollution load index (PLI) to determine metal accumulation, distribution and its pollution status. Heavy metal toxicity risk was assessed using soil quality guidelines (SQGs) given by target and intervention values of Dutch soil standards. The concentration of Ni, Co, Zn, Cr, Mn, Fe, Ti, K, Al, Mg were mainly controlled by natural sources. Multivariate statistical methods such as correlation matrix, principal component analysis and cluster analysis were applied for the identification of heavy metal sources (anthropogenic/natural origin). Geo-statistical methods such as kirging identified hot spots of metal contamination in road areas influenced mainly by presence of natural rocks. Copyright © 2014 Elsevier B.V. All rights reserved.

Role of Surgical Services in Profitability of Hospitals in California: An Analysis of Office of Statewide Health Planning and Development Annual Financial Data.

PubMed

Moazzez, Ashkan; de Virgilio, Christian

2016-10-01

With constant changes in health-care laws and payment methods, profitability, and financial sustainability of hospitals are of utmost importance. The purpose of this study is to determine the relationship between surgical services and hospital profitability. The Office of Statewide Health Planning and Development annual financial databases for the years 2009 to 2011 were used for this study. The hospitals' characteristics and income statement elements were extracted for statistical analysis using bivariate and multivariate linear regression. A total of 989 financial records of 339 hospitals were included. On bivariate analysis, the number of inpatient and ambulatory operating rooms (ORs), the number of cases done both as inpatient and outpatient in each OR, and the average minutes used in inpatient ORs were significantly related with the net income of the hospital. On multivariate regression analysis, when controlling for hospitals' payer mix and the study year, only the number of inpatient cases done in the inpatient ORs (β = 832, P = 0.037), and the number of ambulatory ORs (β = 1,485, 466, P = 0.001) were significantly related with the net income of the hospital. These findings suggest that hospitals can maximize their profitability by diverting and allocating outpatient surgeries to ambulatory ORs, to allow for more inpatient surgeries.

Ultraviolet spectroscopy combined with ultra-fast liquid chromatography and multivariate statistical analysis for quality assessment of wild Wolfiporia extensa from different geographical origins.

PubMed

Li, Yan; Zhang, Ji; Jin, Hang; Liu, Honggao; Wang, Yuanzhong

2016-08-05

A quality assessment system comprised of a tandem technique of ultraviolet (UV) spectroscopy and ultra-fast liquid chromatography (UFLC) aided by multivariate analysis was presented for the determination of geographic origin of Wolfiporia extensa collected from five regions in Yunnan Province of China. Characteristic UV spectroscopic fingerprints of samples were determined based on its methanol extract. UFLC was applied for the determination of pachymic acid (a biomarker) presented in individual test samples. The spectrum data matrix and the content of pachymic acid were integrated and analyzed by partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA). The results showed that chemical properties of samples were clearly dominated by the epidermis and inner part as well as geographical origins. The relationships among samples obtained from these five regions have been also presented. Moreover, an interesting finding implied that geographical origins had much greater influence on the chemical properties of epidermis compared with that of the inner part. This study demonstrated that a rapid tool for accurate discrimination of W. extensa by UV spectroscopy and UFLC could be available for quality control of complicated medicinal mushrooms. Copyright © 2016 Elsevier B.V. All rights reserved.

Robust tracking control of a magnetically suspended rigid body

NASA Technical Reports Server (NTRS)

Lim, Kyong B.; Cox, David E.

1994-01-01

This study is an application of H-infinity and micro-synthesis for designing robust tracking controllers for the Large Angle Magnetic Suspension Test Facility. The modeling, design, analysis, simulation, and testing of a control law that guarantees tracking performance under external disturbances and model uncertainties is investigated. The type of uncertainties considered and the tracking performance metric used is discussed. This study demonstrates the tradeoff between tracking performance at low frequencies and robustness at high frequencies. Two sets of controllers were designed and tested. The first set emphasized performance over robustness, while the second set traded off performance for robustness. Comparisons of simulation and test results are also included. Current simulation and experimental results indicate that reasonably good robust tracking performance can be attained for this system using multivariable robust control approach.

Preliminary identification of unicellular algal genus by using combined confocal resonance Raman spectroscopy with PCA and DPLS analysis

NASA Astrophysics Data System (ADS)

He, Shixuan; Xie, Wanyi; Zhang, Ping; Fang, Shaoxi; Li, Zhe; Tang, Peng; Gao, Xia; Guo, Jinsong; Tlili, Chaker; Wang, Deqiang

2018-02-01

The analysis of algae and dominant alga plays important roles in ecological and environmental fields since it can be used to forecast water bloom and control its potential deleterious effects. Herein, we combine in vivo confocal resonance Raman spectroscopy with multivariate analysis methods to preliminary identify the three algal genera in water blooms at unicellular scale. Statistical analysis of characteristic Raman peaks demonstrates that certain shifts and different normalized intensities, resulting from composition of different carotenoids, exist in Raman spectra of three algal cells. Principal component analysis (PCA) scores and corresponding loading weights show some differences from Raman spectral characteristics which are caused by vibrations of carotenoids in unicellular algae. Then, discriminant partial least squares (DPLS) classification method is used to verify the effectiveness of algal identification with confocal resonance Raman spectroscopy. Our results show that confocal resonance Raman spectroscopy combined with PCA and DPLS could handle the preliminary identification of dominant alga for forecasting and controlling of water blooms.

Qualitative and quantitative analysis of milk for the detection of adulteration by Laser Induced Breakdown Spectroscopy (LIBS).

PubMed

Moncayo, S; Manzoor, S; Rosales, J D; Anzano, J; Caceres, J O

2017-10-01

The present work focuses on the development of a fast and cost effective method based on Laser Induced Breakdown Spectroscopy (LIBS) to the quality control, traceability and detection of adulteration in milk. Two adulteration cases have been studied; a qualitative analysis for the discrimination between different milk blends and quantification of melamine in adulterated toddler milk powder. Principal Component Analysis (PCA) and neural networks (NN) have been used to analyze LIBS spectra obtaining a correct classification rate of 98% with a 100% of robustness. For the quantification of melamine, two methodologies have been developed; univariate analysis using CN emission band and multivariate calibration NN model obtaining correlation coefficient (R 2 ) values of 0.982 and 0.999 respectively. The results of the use of LIBS technique coupled with chemometric analysis are discussed in terms of its potential use in the food industry to perform the quality control of this dairy product. Copyright © 2017 Elsevier Ltd. All rights reserved.

Validation of a new modal performance measure for flexible controllers design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simo, J.B.; Tahan, S.A.; Kamwa, I.

1996-05-01

A new modal performance measure for power system stabilizer (PSS) optimization is proposed in this paper. The new method is based on modifying the square envelopes of oscillating modes, in order to take into account their damping ratios while minimizing the performance index. This criteria is applied to flexible controllers optimal design, on a multi-input-multi-output (MIMO) reduced-order model of a prototype power system. The multivariable model includes four generators, each having one input and one output. Linear time-response simulation and transient stability analysis with a nonlinear package confirm the superiority of the proposed criteria and illustrate its effectiveness in decentralizedmore » control.« less

Power analysis for multivariate and repeated measures designs: a flexible approach using the SPSS MANOVA procedure.

PubMed

D'Amico, E J; Neilands, T B; Zambarano, R

2001-11-01

Although power analysis is an important component in the planning and implementation of research designs, it is often ignored. Computer programs for performing power analysis are available, but most have limitations, particularly for complex multivariate designs. An SPSS procedure is presented that can be used for calculating power for univariate, multivariate, and repeated measures models with and without time-varying and time-constant covariates. Three examples provide a framework for calculating power via this method: an ANCOVA, a MANOVA, and a repeated measures ANOVA with two or more groups. The benefits and limitations of this procedure are discussed.

Association between statin therapy and tendon rupture: a case-control study.

PubMed

Beri, Abhimanyu; Dwamena, Francesca C; Dwamena, Ben A

2009-05-01

Although case reports of a possible association between statin therapy and tendon rupture have been published, no analytical studies exploring this relationship have been reported. We conducted a case-control study using the electronic medical records at Michigan State University from 2002 to 2007 to assess whether statin use is a risk factor for tendon rupture. We compared exposure to statins in 93 cases of tendon rupture with similar exposure in 279 sex- and age-matched controls. Exposure to statins was defined as documentation in the electronic medical record of statin use in the 12 months preceding tendon rupture. For controls, the exposure period was defined as 1 year preceding the last office visit. We used a multivariate logistic regression model, controlling for diabetes, renal disease, rheumatologic disease, and steroid use, to calculate the adjusted odds ratios (ORs). There was no significant difference between cases and controls in the rates of statin use, with either univariate [OR = 1.0, 95% confidence interval (CI) 0.54-1.84] or multivariate analyses (OR = 1.10, 95% CI 0.57-2.13). Based on predetermined subgroup analyses, statin exposure was found to be a significant risk factor for tendon rupture in women (adjusted OR = 3.76, 95% CI 1.11-12.75) but not in men (adjusted OR = 0.66, 95% CI 0.29-1.51). In conclusion, we found no overall association between statin use and tendon rupture, but subgroup analysis suggested that women with tendon rupture were more likely to be on statins.

Multi-Sample Cluster Analysis Using Akaike’s Information Criterion.

DTIC Science & Technology

1982-12-20

of Likelihood Criteria for I)fferent Hypotheses," in P. A. Krishnaiah (Ed.), Multivariate Analysis-Il, New York: Academic Press. [5] Fisher, R. A...Methods of Simultaneous Inference in MANOVA," in P. R. Krishnaiah (Ed.), rultivariate Analysis-Il, New York: Academic Press. [8) Kendall, M. G. (1966...1982), Applied Multivariate Statisti- cal-Analysis, Englewood Cliffs: Prentice-Mall, Inc. [1U] Krishnaiah , P. R. (1969), "Simultaneous Test

Identifying localized and scale-specific multivariate controls of soil organic matter variations using multiple wavelet coherence.

PubMed

Zhao, Ruiying; Biswas, Asim; Zhou, Yin; Zhou, Yue; Shi, Zhou; Li, Hongyi

2018-06-23

Environmental factors have shown localized and scale-dependent controls over soil organic matter (SOM) distribution in the landscape. Previous studies have explored the relationships between SOM and individual controlling factors; however, few studies have indicated the combined control from multiple environmental factors. In this study, we compared the localized and scale-dependent univariate and multivariate controls of SOM along two long transects (northeast, NE transect and north, N transect) from China. Bivariate wavelet coherence (BWC) between SOM and individual factors and multiple wavelet coherence (MWC) between SOM and factor combinations were calculated. Average wavelet coherence (AWC) and percent area of significant coherence (PASC) were used to assess the relative dominance of individual and a combination of factors to explain SOM variations at different scales and locations. The results showed that (in BWC analysis) mean annual temperature (MAT) with the largest AWC (0.39) and PASC (16.23%) was the dominant factor in explaining SOM variations along the NE transect. The topographic wetness index (TWI) was the dominant factor (AWC = 0.39 and PASC = 20.80%) along the N transect. MWC identified the combination of Slope, net primary production (NPP) and mean annual precipitation (MAP) as the most important combination in explaining SOM variations along the NE transect with a significant increase in AWC and PASC at different scales and locations (e.g. AWC = 0.91 and PASC = 58.03% at all scales). The combination of TWI, NPP and normalized difference vegetation index (NDVI) was the most influential along the N transect (AWC = 0.83 and PASC = 32.68% at all scales). The results indicated that the combined controls of environmental factors on SOM variations at different scales and locations in a large area can be identified by MWC. This is promising for a better understanding of the multivariate controls in SOM variations at larger spatial scales and may improve the capability of digital soil mapping. Copyright © 2018 Elsevier B.V. All rights reserved.

Enhancing vehicle cornering limit through sideslip and yaw rate control

NASA Astrophysics Data System (ADS)

Lu, Qian; Gentile, Pierangelo; Tota, Antonio; Sorniotti, Aldo; Gruber, Patrick; Costamagna, Fabio; De Smet, Jasper

2016-06-01

Fully electric vehicles with individually controlled drivetrains can provide a high degree of drivability and vehicle safety, all while increasing the cornering limit and the 'fun-to-drive' aspect. This paper investigates a new approach on how sideslip control can be integrated into a continuously active yaw rate controller to extend the limit of stable vehicle cornering and to allow sustained high values of sideslip angle. The controllability-related limitations of integrated yaw rate and sideslip control, together with its potential benefits, are discussed through the tools of multi-variable feedback control theory and non-linear phase-plane analysis. Two examples of integrated yaw rate and sideslip control systems are presented and their effectiveness is experimentally evaluated and demonstrated on a four-wheel-drive fully electric vehicle prototype. Results show that the integrated control system allows safe operation at the vehicle cornering limit at a specified sideslip angle independent of the tire-road friction conditions.

Advanced multivariable control of a turboexpander plant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Altena, D.; Howard, M.; Bullin, K.

1998-12-31

This paper describes an application of advanced multivariable control on a natural gas plant and compares its performance to the previous conventional feed-back control. This control algorithm utilizes simple models from existing plant data and/or plant tests to hold the process at the desired operating point in the presence of disturbances and changes in operating conditions. The control software is able to accomplish this due to effective handling of process variable interaction, constraint avoidance and feed-forward of measured disturbances. The economic benefit of improved control lies in operating closer to the process constraints while avoiding significant violations. The South Texasmore » facility where this controller was implemented experienced reduced variability in process conditions which increased liquids recovery because the plant was able to operate much closer to the customer specified impurity constraint. An additional benefit of this implementation of multivariable control is the ability to set performance criteria beyond simple setpoints, including process variable constraints, relative variable merit and optimizing use of manipulated variables. The paper also details the control scheme applied to the complex turboexpander process and some of the safety features included to improve reliability.« less

Docking and multivariate methods to explore HIV-1 drug-resistance: a comparative analysis

NASA Astrophysics Data System (ADS)

Almerico, Anna Maria; Tutone, Marco; Lauria, Antonino

2008-05-01

In this paper we describe a comparative analysis between multivariate and docking methods in the study of the drug resistance to the reverse transcriptase and the protease inhibitors. In our early papers we developed a simple but efficient method to evaluate the features of compounds that are less likely to trigger resistance or are effective against mutant HIV strains, using the multivariate statistical procedures PCA and DA. In the attempt to create a more solid background for the prediction of susceptibility or resistance, we carried out a comparative analysis between our previous multivariate approach and molecular docking study. The intent of this paper is not only to find further support to the results obtained by the combined use of PCA and DA, but also to evidence the structural features, in terms of molecular descriptors, similarity, and energetic contributions, derived from docking, which can account for the arising of drug-resistance against mutant strains.

SUGGESTIONS FOR OPTIMIZED PLANNING OF MULTIVARIATE MONITORING OF ATMOSPHERIC POLLUTION

EPA Science Inventory

Recent work in factor analysis of multivariate data sets has shown that variables with little signal should not be included in the factor analysis. Work also shows that rotational ambiguity is reduced if sources impacting a receptor have both large and small contributions. Thes...

Multivariate Meta-Analysis Using Individual Participant Data

ERIC Educational Resources Information Center

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2015-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is…

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol lowering drugs

PubMed Central

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G.; Shah, Arvind K.; Lin, Jianxin

2013-01-01

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data (IPD) in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the Deviance Information Criterion (DIC) is used to select the best transformation model. Since the model is quite complex, a novel Monte Carlo Markov chain (MCMC) sampling scheme is developed to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol lowering drugs where the goal is to jointly model the three dimensional response consisting of Low Density Lipoprotein Cholesterol (LDL-C), High Density Lipoprotein Cholesterol (HDL-C), and Triglycerides (TG) (LDL-C, HDL-C, TG). Since the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately: however, a multivariate approach would be more appropriate since these variables are correlated with each other. A detailed analysis of these data is carried out using the proposed methodology. PMID:23580436

Bayesian inference for multivariate meta-analysis Box-Cox transformation models for individual patient data with applications to evaluation of cholesterol-lowering drugs.

PubMed

Kim, Sungduk; Chen, Ming-Hui; Ibrahim, Joseph G; Shah, Arvind K; Lin, Jianxin

2013-10-15

In this paper, we propose a class of Box-Cox transformation regression models with multidimensional random effects for analyzing multivariate responses for individual patient data in meta-analysis. Our modeling formulation uses a multivariate normal response meta-analysis model with multivariate random effects, in which each response is allowed to have its own Box-Cox transformation. Prior distributions are specified for the Box-Cox transformation parameters as well as the regression coefficients in this complex model, and the deviance information criterion is used to select the best transformation model. Because the model is quite complex, we develop a novel Monte Carlo Markov chain sampling scheme to sample from the joint posterior of the parameters. This model is motivated by a very rich dataset comprising 26 clinical trials involving cholesterol-lowering drugs where the goal is to jointly model the three-dimensional response consisting of low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C), and triglycerides (TG) (LDL-C, HDL-C, TG). Because the joint distribution of (LDL-C, HDL-C, TG) is not multivariate normal and in fact quite skewed, a Box-Cox transformation is needed to achieve normality. In the clinical literature, these three variables are usually analyzed univariately; however, a multivariate approach would be more appropriate because these variables are correlated with each other. We carry out a detailed analysis of these data by using the proposed methodology. Copyright © 2013 John Wiley & Sons, Ltd.

Association between Low-density lipoprotein cholesterol and occipital periventricular hyperintensities in a group of Chinese patients: an observational study.

PubMed

Duan, Dazhi; Shen, Lin; Cui, Chun; Shu, Tongsheng; Zheng, Jian

2017-02-27

While occipital periventricular hyperintensities (OPVHs) are among the most common mild white matter hyperintensities, the clinical factors associated with OPVHs remain unclear. In this study, we investigated the role of clinical factors in development of pure OPVHs. This study included 97 patients with OPVHs and 73 healthy controls. Univariate analysis of clinical factors in OPVH patients and controls was followed by binomial logistic regression analysis to identify clinical factors significantly associated with OPVHs. Univariate analysis indicated that age, total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and apolipoprotein-B (Apo-B) levels differed significantly between the OPVH patients and controls (p < 0.05). Age and gender were correlated with OPVH scores (p < 0.05), while LDL-C, triglycerides, Apo-B and TC were anti-correlated with OPVHs scores (p < 0.05). Multivariate analysis indicated that LDL-C is negatively correlated with OPVHs (p < 0.05), and age is positively correlated with OPVHs (p < 0.001). In summary, LDL-C was negatively and age was positively associated with OPVHs among Chinese patients in a hospital.

Recent applications of multivariate data analysis methods in the authentication of rice and the most analyzed parameters: A review.

PubMed

Maione, Camila; Barbosa, Rommel Melgaço

2018-01-24

Rice is one of the most important staple foods around the world. Authentication of rice is one of the most addressed concerns in the present literature, which includes recognition of its geographical origin and variety, certification of organic rice and many other issues. Good results have been achieved by multivariate data analysis and data mining techniques when combined with specific parameters for ascertaining authenticity and many other useful characteristics of rice, such as quality, yield and others. This paper brings a review of the recent research projects on discrimination and authentication of rice using multivariate data analysis and data mining techniques. We found that data obtained from image processing, molecular and atomic spectroscopy, elemental fingerprinting, genetic markers, molecular content and others are promising sources of information regarding geographical origin, variety and other aspects of rice, being widely used combined with multivariate data analysis techniques. Principal component analysis and linear discriminant analysis are the preferred methods, but several other data classification techniques such as support vector machines, artificial neural networks and others are also frequently present in some studies and show high performance for discrimination of rice.

Genes@Work: an efficient algorithm for pattern discovery and multivariate feature selection in gene expression data.

PubMed

Lepre, Jorge; Rice, J Jeremy; Tu, Yuhai; Stolovitzky, Gustavo

2004-05-01

Despite the growing literature devoted to finding differentially expressed genes in assays probing different tissues types, little attention has been paid to the combinatorial nature of feature selection inherent to large, high-dimensional gene expression datasets. New flexible data analysis approaches capable of searching relevant subgroups of genes and experiments are needed to understand multivariate associations of gene expression patterns with observed phenotypes. We present in detail a deterministic algorithm to discover patterns of multivariate gene associations in gene expression data. The patterns discovered are differential with respect to a control dataset. The algorithm is exhaustive and efficient, reporting all existent patterns that fit a given input parameter set while avoiding enumeration of the entire pattern space. The value of the pattern discovery approach is demonstrated by finding a set of genes that differentiate between two types of lymphoma. Moreover, these genes are found to behave consistently in an independent dataset produced in a different laboratory using different arrays, thus validating the genes selected using our algorithm. We show that the genes deemed significant in terms of their multivariate statistics will be missed using other methods. Our set of pattern discovery algorithms including a user interface is distributed as a package called Genes@Work. This package is freely available to non-commercial users and can be downloaded from our website (http://www.research.ibm.com/FunGen).

Autologous Doping with Cryopreserved Red Blood Cells – Effects on Physical Performance and Detection by Multivariate Statistics

PubMed Central

Malm, Christer B.; Khoo, Nelson S.; Granlund, Irene; Lindstedt, Emilia; Hult, Andreas

2016-01-01

The discovery of erythropoietin (EPO) simplified blood doping in sports, but improved detection methods, for EPO has forced cheating athletes to return to blood transfusion. Autologous blood transfusion with cryopreserved red blood cells (RBCs) is the method of choice, because no valid method exists to accurately detect such event. In endurance sports, it can be estimated that elite athletes improve performance by up to 3% with blood doping, regardless of method. Valid detection methods for autologous blood doping is important to maintain credibility of athletic performances. Recreational male (N = 27) and female (N = 11) athletes served as Transfusion (N = 28) and Control (N = 10) subjects in two different transfusion settings. Hematological variables and physical performance were measured before donation of 450 or 900 mL whole blood, and until four weeks after re-infusion of the cryopreserved RBC fraction. Blood was analyzed for transferrin, iron, Hb, EVF, MCV, MCHC, reticulocytes, leucocytes and EPO. Repeated measures multivariate analysis of variance (MANOVA) and pattern recognition using Principal Component Analysis (PCA) and Orthogonal Projections of Latent Structures (OPLS) discriminant analysis (DA) investigated differences between Control and Transfusion groups over time. Significant increase in performance (15 ± 8%) and VO2max (17 ± 10%) (mean ± SD) could be measured 48 h after RBC re-infusion, and remained increased for up to four weeks in some subjects. In total, 533 blood samples were included in the study (Clean = 220, Transfused = 313). In response to blood transfusion, the largest change in hematological variables occurred 48 h after blood donation, when Control and Transfused groups could be separated with OPLS-DA (R2 = 0.76/Q2 = 0.59). RBC re-infusion resulted in the best model (R2 = 0.40/Q2 = 0.10) at the first sampling point (48 h), predicting one false positive and one false negative. Over all, a 25% and 86% false positives ratio was achieved in two separate trials. In conclusions, autologous re-infusion of RBCs increased VO2max and performance as hypothesized, but hematological profiling by multivariate statistics could not reach the WADA stipulated false positive ratio of <0.001% at any time point investigated. A majority of samples remained within limits of normal individual variation at all times. PMID:27284981

Metabolomics analysis of follicular fluid in women with ovarian endometriosis undergoing in vitro fertilization.

PubMed

Karaer, Abdullah; Tuncay, Gorkem; Mumcu, Akın; Dogan, Berat

2018-05-28

The purpose of this study was to investigate whether a change in the follicular fluid metabolomics profile due to endometrioma is identifiable. Twelve women with ovarian endometriosis (aged<40 years, with a body mass index [BMI] of <30 kg/m 2 ) and 12 age- and BMI-matched controls (women with infertility purely due to a male factor) underwent ovarian stimulation for intracytoplasmic sperm injection (ICSI). Follicular fluid samples were collected from both of groups at the time of oocyte retrieval for ICSI. Next, nuclear magnetic resonance (NMR) spectroscopy was performed for the collected follicular fluids. The metabolic compositions of the follicular fluids were then compared using univariate and multivariate statistical analyses of NMR data. Univariate and multivariate statistical analyses of NMR data showed that the metabolomic profiles of the follicular fluids obtained from the women with ovarian endometriosis were distinctly different from those obtained from the control group. In comparison with the controls, the follicular fluids of the women with ovarian endometriosis had statistically significant elevated levels of lactate, β-glucose, pyruvate, and valine. We conclude that the levels of lactate, β-glucose, pyruvate, and valine in the follicular fluid of the women with endometrioma were higher than those of the controls. ASRM: American Society for Reproductive Medicine; BMI: body mass index; CPMG: Carr-Purcell-Meiboom-Gill; E 2 : estradiol; ESHRE: European Society of Human Reproduction and Embryology; ERETIC: electronic to access in vivo concentration; FF: follicular fluid; FSH: follicle-stimulating hormone; hCG: human chorionic gonadotropin; HEPES: 2-hydroxyethyl-1-piperazineethanesulfonic acid; ICSI: intracytoplasmic sperm injection; IVF: in vitro fertilization; NMR: nuclear magnetic resonance spectroscopy; PCA: principal component analysis; PCOS: polycystic ovary syndrome; PLS-DA: partial least squares discriminant analysis; ppm: parts per million; PULCON: pulse length-based concentration determination; TSP: 3-(trimethylsilyl)-1-propanesulfonic acid sodium salt; VIP: variable importance in projection.

The association between Chiari malformation Type I, spinal syrinx, and scoliosis.

PubMed

Strahle, Jennifer; Smith, Brandon W; Martinez, Melaine; Bapuraj, J Rajiv; Muraszko, Karin M; Garton, Hugh J L; Maher, Cormac O

2015-06-01

OBJECT Chiari malformation Type I (CM-I) is often found in patients with scoliosis. Most previous reports of CM-I and scoliosis have focused on patients with CM-I and a spinal syrinx. The relationship between CM-I and scoliosis in the absence of a syrinx has never been defined clearly. The authors sought to determine if there is an independent association between CM-I and scoliosis when controlling for syrinx status. METHODS The medical records of 14,118 consecutive patients aged ≤ 18 years who underwent brain or cervical spine MRI at a single institution in an 11-year span were reviewed to identify patients with CM-I, scoliosis, and/or syrinx. The relationship between CM-I and scoliosis was analyzed by using multivariate regression analysis and controlling for age, sex, CM-I status, and syrinx status. RESULTS In this cohort, 509 patients had CM-I, 1740 patients had scoliosis, and 243 patients had a spinal syrinx. The presence of CM-I, the presence of syrinx, older age, and female sex were each significantly associated with scoliosis in the univariate analysis. In the multivariate regression analysis, older age (OR 1.02 [95% CI 1.01-1.03]; p < 0.0001), female sex (OR 1.71 [95% CI 1.54-1.90]; p < 0.0001), and syrinx (OR 9.08 [95% CI 6.82-12.10]; p < 0.0001) were each independently associated with scoliosis. CM-I was not independently associated with scoliosis when controlling for these other variables (OR 0.99 [95% CI 0.79-1.29]; p = 0.9). CONCLUSIONS A syrinx was independently associated with scoliosis in a large pediatric population undergoing MRI. CM-I was not independently associated with scoliosis when controlling for age, sex, and syrinx status. Because CM-I is not independently associated with scoliosis, scoliosis should not necessarily be considered a symptom of low cerebellar tonsil position in patients without a syrinx.

Sample size calculations for case-control studies

Cancer.gov

This R package can be used to calculate the required samples size for unconditional multivariate analyses of unmatched case-control studies. The sample sizes are for a scalar exposure effect, such as binary, ordinal or continuous exposures. The sample sizes can also be computed for scalar interaction effects. The analyses account for the effects of potential confounder variables that are also included in the multivariate logistic model.

Proceedings of the Workshop on Multivariable Control Systems Held at Wright-Patterson AFB, OH, on 3 December 1982.

DTIC Science & Technology

1983-09-01

promising method of af- craft multivariable flight controller design. Like any ne.! design technique, there is still more to learn about the r.~ cd...M4atix - Feedback Gain Ma trix - Fandom ’htrix Z - Number of Outputs L1 - Roll Moment • : ’ - 7oll Moment with Inertia TrML 523 a.. Symbols m - Number of

Lipid Abnormalities in Type 2 Diabetes Mellitus Patients with Overt Nephropathy

PubMed Central

Viswanathan, Vijay

2017-01-01

Background Diabetic nephropathy is a major complication of diabetes and an established risk factor for cardiovascular events. Lipid abnormalities occur in patients with diabetic nephropathy, which further increase their risk for cardiovascular events. We compared the degree of dyslipidemia among type 2 diabetes mellitus (T2DM) subjects with and without nephropathy and analyzed the factors associated with nephropathy among them. Methods In this retrospective study, T2DM patients with overt nephropathy were enrolled in the study group (n=89) and without nephropathy were enrolled in the control group (n=92). Both groups were matched for age and duration of diabetes. Data on total cholesterol (TC), triglycerides (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), urea and creatinine were collected from the case sheets. TG/HDL-C ratio, a surrogate marker for small, dense, LDL particles (sdLDL) and estimated glomerular filtration rate (eGFR) were calculated using equations. Multivariate analysis was done to determine the factors associated with eGFR. Results Dyslipidemia was present among 56.52% of control subjects and 75.28% of nephropathy subjects (P=0.012). The percentage of subjects with atherogenic dyslipidemia (high TG+low HDL-C+sdLDL) was 14.13 among controls and 14.61 among nephropathy subjects. Though serum creatinine was not significantly different, mean eGFR value was significantly lower among nephropathy patients (P=0.002). Upon multivariate analysis, it was found that TC (P=0.007) and HDL-C (P=0.06) were associated with eGFR among our study subjects. Conclusion Our results show that dyslipidemia was highly prevalent among subjects with nephropathy. Regular screening for dyslipidemia may be beneficial in controlling the risk for adverse events among diabetic nephropathy patients. PMID:28447439

Prevalence and determinants of albuminuria in a cohort of diabetic patients in Lebanon.

PubMed

Taleb, Nadine; Salti, Haytham; Al-Mokaddam, Mona; Merheb, Marie; Salti, Ibrahim; Nasrallah, Mona

2008-01-01

Few data are available on the extent of albuminuria in diabetic populations in the Middle East generally and in Lebanon specifically. We conducted this study to determine the prevalence of albuminuria and its major risk factors in a cohort of diabetic patients in Lebanon. Diabetic patients followed in the outpatient department at the American University of Beirut Medical Center (AUBMC) were included in a prospective observational study. AUBMC is a tertiary referral center and the outpatient department typically handles patients of low socioeconomic status with advanced disease. Patients were classified according to their urinary albumin-to-creatinine ratio (ACR) as having normoalbuminuria (ACR<30 mg/g creatinine), microalbuminuria (ACR=30 to <300 mg/g creatinine), or macroalbuminuria (ACR > or =300 mg/g creatinine). The three groups were compared to analyze the association between albuminuria and its risk factors. In addition, independent predictors of albuminuria were determined using multivariate logistic regression and presented as an odds ratio. Microalbuminuria and macroalbuminuria were present in 33.3% and 12.7% of 222 patients (mean age 56.4 years, mean deviation of diabetes 8.6 years, 58.7% women, 43.8% obese), respectively. Factors significantly associated with microalbuminuria included glycemic control, insulin use, and total and LDL cholesterol. Those associated with macroalbuminuria included in addition to glycemic control and insulin use, duration of diabetes, hypertension, elevated mean arterial pressure (MAP), and presence of neuropathy, retinopathy and peripheral vascular disease by bivariate analysis. Only glycemic control was an independent risk factor for both in addition to MAP and retinopathy for macroalbuminuria by multivariate analysis. Albuminuria is highly prevalent among this cohort of diabetic patients in Lebanon. Both glycemic control and blood pressure need to be better targeted in its management.

Leptospira Exposure and Waste Pickers: A Case-Control Seroprevalence Study in Durango, Mexico

PubMed Central

Alvarado-Esquivel, Cosme; Hernandez-Tinoco, Jesus; Sanchez-Anguiano, Luis Francisco; Ramos-Nevarez, Agar; Cerrillo-Soto, Sandra Margarita; Guido-Arreola, Carlos Alberto

2015-01-01

Background Infection with Leptospira may occur by contact with Leptospira-infected animals. Waste pickers are in contact with rodents and dogs while picking in the garbage. Whether waste pickers are at risk for Leptospira infection is largely unknown. This study was aimed to determine the association of Leptospira IgG seroprevalence with the occupation of waste picking, and to determine the epidemiological characteristics of the waste pickers with Leptospira exposure. Methods Through a case-control study, we determined the seroprevalence of anti-Leptospira IgG antibodies in 90 waste pickers and 90 age- and gender-matched control subjects in Durango City, Mexico using an enzyme immunoassay. Data were analyzed by bivariate and multivariate analyses. Results The prevalence of anti-Leptospira IgG antibodies was similar in waste pickers (4/90: 4.4%) to that in control subjects (5/90: 5.6%) (P = 1.00). Bivariate analysis showed that Leptospira exposure in waste pickers was associated with increasing age (P = 0.009), no education (P = 0.008), and consumption of rat meat (P = 0.04). However, these associations were no longer found by multivariate analysis. Leptospira exposure in waste pickers was not associated with health status, duration in the activity, wearing hand gloves and facemasks, history of injuries with sharp material of the garbage, or contact with animals or soil. Conclusions This is the first study about Leptospira exposure in waste pickers. Results suggest that waste pickers are not at increasing risk for Leptospira exposure in Durango City, Mexico. Further research with a larger sample size to elucidate the association of Leptospira exposure with waste picking activity is needed. PMID:26124911

Relationship Between Serum Zinc Level and Metabolic Syndrome: A Meta-Analysis of Observational Studies.

PubMed

Zhang, Yi; Zhang, Dian-Zhong

2018-05-10

This research sought to summarize the evidence regarding the relationship between serum zinc level and metabolic syndrome (MetS). The electronic databases of PubMed, Web of Science, and Embase were searched up to October 2017 for observational studies on the association between serum zinc level and MetS. The standard mean difference (SMD) and its corresponding 95% confidence interval (CI) of the serum zinc level for MetS versus control participants were calculated. In addition, the pooled odds ratio (OR) and relative risk (RR) of MetS for the highest versus lowest category of serum zinc level, as well as their corresponding 95% CI, were also calculated. A total of 11 observational studies (8 cross-sectional, 1 case-control, and 2 cohort studies) were included in this meta-analysis. The combined SMD demonstrated that the serum zinc level in MetS was higher than that in control participants (SMD = 0.11; 95% CI, 0.03-0.19; p = 0.009). Moreover, the overall multivariable-adjusted RR showed that the increased serum zinc level was associated with a higher risk of MetS (RR = 1.82; 95% CI, 1.33-2.50; p < 0.001). On the contrary, the overall multivariable-adjusted OR showed that there was no significant relationship between serum zinc level and MetS (OR = 1.00; 95% CI, 0.99-1.01; p = 0.841). Although the serum zinc level in participants with MetS was significantly higher than that in control ones, the existing evidence was still insufficient to conclude a definite relationship between serum zinc level and MetS. More well-designed prospective cohort studies are needed to elaborate the concerned issues further.

Influence of socioeconomic aspects on lymphatic filariasis: A case-control study in Andhra Pradesh, India.

PubMed

Mutheneni, Srinivasa Rao; Upadhyayula, Suryanaryana Murty; Kumaraswamy, Sriram; Kadiri, Madhusudhan Rao; Nagalla, Balakrishna

2016-01-01

Lymphatic filariasis (LF) is a major public health problem in India. The objective of the study was to assess the impact of socioeconomic conditions on LF in Chittoor district of Andhra Pradesh, India. A survey was carried out from 2004 to 2007 during which, an epidemiological and socioeconomic data were collected and analysed. The microfilaria (mf) positive samples were taken as cases and matched with control group by sex and age (1:1) for case-control study. Bivariate and multivariate logistic regression was used to identify the potential risk factors for filariasis. Using principal component analysis (PCA), a socioeconomic index was developed and the data/scores were classified into low, medium and high categories. In total 5,133 blood smears were collected, of which 77 samples were found positive for microfilaria (1.52%). Multivariate analysis showed that the risk of filariasis was higher in groups of people with income < ₹1000 per month [OR = 2.752 (95%CI, 0.435-17.429)]; ₹ 1000-3000 per month [3.079 (0.923-0.275)]; people living in tiled house structure [1.641 (0.534-5.048)], with kutcha (uncemented) drainage system [19.427 (2.985- 126.410)], respondents who did not implemented mosquito avoidance measures [1.737 (0.563-5.358)]; and in people who were not aware about prevention and control of filariasis [1.042 (0.368-2.956)]. PCA showed that respondents with low (41.6%) and medium (33.8%) socioeconomic status are more prone to filariasis (p=0.036). The cross sectional study showed that the population with low and medium socioeconomic status are at higher risk of filariasis. The identified socioeconomic risk factors can be used as a guideline for improving the conditions for effective management of filariasis.

Identification of Reliable Components in Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS): a Data-Driven Approach across Metabolic Processes.

PubMed

Motegi, Hiromi; Tsuboi, Yuuri; Saga, Ayako; Kagami, Tomoko; Inoue, Maki; Toki, Hideaki; Minowa, Osamu; Noda, Tetsuo; Kikuchi, Jun

2015-11-04

There is an increasing need to use multivariate statistical methods for understanding biological functions, identifying the mechanisms of diseases, and exploring biomarkers. In addition to classical analyses such as hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis, various multivariate strategies, including independent component analysis, non-negative matrix factorization, and multivariate curve resolution, have recently been proposed. However, determining the number of components is problematic. Despite the proposal of several different methods, no satisfactory approach has yet been reported. To resolve this problem, we implemented a new idea: classifying a component as "reliable" or "unreliable" based on the reproducibility of its appearance, regardless of the number of components in the calculation. Using the clustering method for classification, we applied this idea to multivariate curve resolution-alternating least squares (MCR-ALS). Comparisons between conventional and modified methods applied to proton nuclear magnetic resonance ((1)H-NMR) spectral datasets derived from known standard mixtures and biological mixtures (urine and feces of mice) revealed that more plausible results are obtained by the modified method. In particular, clusters containing little information were detected with reliability. This strategy, named "cluster-aided MCR-ALS," will facilitate the attainment of more reliable results in the metabolomics datasets.

Higher levels of s-RANKL and osteoprotegerin in children and adolescents with type 1 diabetes mellitus may indicate increased osteoclast signaling and predisposition to lower bone mass: a multivariate cross-sectional analysis.

PubMed

Tsentidis, C; Gourgiotis, D; Kossiva, L; Doulgeraki, A; Marmarinos, A; Galli-Tsinopoulou, A; Karavanaki, K

2016-04-01

Simultaneous lower bone mineral density, metabolic bone markers, parathyroid hormone (PTH), magnesium, insulin-like growth factor 1 (IGF1), and higher levels of total soluble receptor activator of nuclear factor-kappa B ligand (s-RANKL), osteoprotegerin (OPG), and alkaline phosphatase (ALP) are indicative of lower osteoblast and increased osteoclast signaling in children and adolescents with type 1 diabetes mellitus, predisposing to adult osteopenia and osteoporosis. Type 1 diabetes mellitus (T1DM) is a risk factor for reduced bone mass, disrupting several bone metabolic pathways. We aimed at identifying association patterns between bone metabolic markers, particularly OPG, s-RANKL, and bone mineral density (BMD) in T1DM children and adolescents, in order to study possible underlying pathophysiologic mechanisms of bone loss. We evaluated 40 children and adolescents with T1DM (mean ± SD age 13.04 ± 3.53 years, T1DM duration 5.15 ± 3.33 years) and 40 healthy age- and gender-matched controls (aged12.99 ± 3.3 years). OPG, s-RANKL, osteocalcin, C-telopeptide cross-links (CTX), IGF1, electrolytes, PTH, and total 25(OH)D were measured, and total body along with lumbar spine BMD were evaluated with dual energy X-ray absorptiometry (DXA). Multivariate regression and factor analysis were performed after classic inference. Patients had significantly lower BMD, with lower bone turnover markers, PTH, magnesium, and IGF1 than controls, indicating lower osteoblast signaling. Higher levels of total s-RANKL, OPG, and total ALP were observed in patients, with log(s-RANKL) and OPG correlation found only in controls, possibly indicating increased osteoclast signaling in patients. Coupling of bone resorption and formation was observed in both groups. Multivariate regression confirmed simultaneous lower bone turnover, IGF1, magnesium, and higher total s-RANKL, OPG, and ALP in patients, while factor analysis indicated possible activation of RANK/RANKL/OPG system in patients and its association with magnesium and IGF1. Patients with longer disease duration or worse metabolic control had lower BMD. T1DM children and adolescents have impaired bone metabolism which seems to be multifactorial. Reduced osteoblast and increased osteoclast signaling, resulting from multiple simultaneous disturbances, could lead to reduced peak bone accrual in early adulthood, predisposing to adult osteopenia and osteoporosis.

Multi-application controls: Robust nonlinear multivariable aerospace controls applications

NASA Technical Reports Server (NTRS)

Enns, Dale F.; Bugajski, Daniel J.; Carter, John; Antoniewicz, Bob

1994-01-01

This viewgraph presentation describes the general methodology used to apply Honywell's Multi-Application Control (MACH) and the specific application to the F-18 High Angle-of-Attack Research Vehicle (HARV) including piloted simulation handling qualities evaluation. The general steps include insertion of modeling data for geometry and mass properties, aerodynamics, propulsion data and assumptions, requirements and specifications, e.g. definition of control variables, handling qualities, stability margins and statements for bandwidth, control power, priorities, position and rate limits. The specific steps include choice of independent variables for least squares fits to aerodynamic and propulsion data, modifications to the management of the controls with regard to integrator windup and actuation limiting and priorities, e.g. pitch priority over roll, and command limiting to prevent departures and/or undesirable inertial coupling or inability to recover to a stable trim condition. The HARV control problem is characterized by significant nonlinearities and multivariable interactions in the low speed, high angle-of-attack, high angular rate flight regime. Systematic approaches to the control of vehicle motions modeled with coupled nonlinear equations of motion have been developed. This paper will discuss the dynamic inversion approach which explicity accounts for nonlinearities in the control design. Multiple control effectors (including aerodynamic control surfaces and thrust vectoring control) and sensors are used to control the motions of the vehicles in several degrees-of-freedom. Several maneuvers will be used to illustrate performance of MACH in the high angle-of-attack flight regime. Analytical methods for assessing the robust performance of the multivariable control system in the presence of math modeling uncertainty, disturbances, and commands have reached a high level of maturity. The structured singular value (mu) frequency response methodology is presented as a method for analyzing robust performance and the mu-synthesis method will be presented as a method for synthesizing a robust control system. The paper concludes with the author's expectations regarding future applications of robust nonlinear multivariable controls.

Nutritional Intervention: A Secondary Analysis of Its Effect on Malnourished Colombian Pre-Schoolers.

ERIC Educational Resources Information Center

Bejar, Isaac I.

1981-01-01

Effects of nutritional supplementation on physical development of malnourished children was analyzed by univariate and multivariate methods for the analysis of repeated measures. Results showed that the nutritional treatment was successful, but it was necessary to resort to the multivariate approach. (Author/GK)

A Multivariate Descriptive Model of Motivation for Orthodontic Treatment.

ERIC Educational Resources Information Center

Hackett, Paul M. W.; And Others

1993-01-01

Motivation for receiving orthodontic treatment was studied among 109 young adults, and a multivariate model of the process is proposed. The combination of smallest scale analysis and Partial Order Scalogram Analysis by base Coordinates (POSAC) illustrates an interesting methodology for health treatment studies and explores motivation for dental…

Exploring Pattern of Socialisation Conditions and Human Development by Nonlinear Multivariate Analysis.

ERIC Educational Resources Information Center

Grundmann, Matthias

Following the assumptions of ecological socialization research, adequate analysis of socialization conditions must take into account the multilevel and multivariate structure of social factors that impact on human development. This statement implies that complex models of family configurations or of socialization factors are needed to explain the…

Univariate Analysis of Multivariate Outcomes in Educational Psychology.

ERIC Educational Resources Information Center

Hubble, L. M.

1984-01-01

The author examined the prevalence of multiple operational definitions of outcome constructs and an estimate of the incidence of Type I error rates when univariate procedures were applied to multiple variables in educational psychology. Multiple operational definitions of constructs were advocated and wider use of multivariate analysis was…

Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM

ERIC Educational Resources Information Center

Warner, Rebecca M.

2007-01-01

This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…

Evaluation of Meterorite Amono Acid Analysis Data Using Multivariate Techniques

NASA Technical Reports Server (NTRS)

McDonald, G.; Storrie-Lombardi, M.; Nealson, K.

1999-01-01

The amino acid distributions in the Murchison carbonaceous chondrite, Mars meteorite ALH84001, and ice from the Allan Hills region of Antarctica are shown, using a multivariate technique known as Principal Component Analysis (PCA), to be statistically distinct from the average amino acid compostion of 101 terrestrial protein superfamilies.

MULTIVARIATE ANALYSIS ON LEVELS OF SELECTED METALS, PARTICULATE MATTER, VOC, AND HOUSEHOLD CHARACTERISTICS AND ACTIVITIES FROM THE MIDWESTERN STATES NHEXAS

EPA Science Inventory

Microenvironmental and biological/personal monitoring information were collected during the National Human Exposure Assessment Survey (NHEXAS), conducted in the six states comprising U.S. EPA Region Five. They have been analyzed by multivariate analysis techniques with general ...

Multivariate meta-analysis: a robust approach based on the theory of U-statistic.

PubMed

Ma, Yan; Mazumdar, Madhu

2011-10-30

Meta-analysis is the methodology for combining findings from similar research studies asking the same question. When the question of interest involves multiple outcomes, multivariate meta-analysis is used to synthesize the outcomes simultaneously taking into account the correlation between the outcomes. Likelihood-based approaches, in particular restricted maximum likelihood (REML) method, are commonly utilized in this context. REML assumes a multivariate normal distribution for the random-effects model. This assumption is difficult to verify, especially for meta-analysis with small number of component studies. The use of REML also requires iterative estimation between parameters, needing moderately high computation time, especially when the dimension of outcomes is large. A multivariate method of moments (MMM) is available and is shown to perform equally well to REML. However, there is a lack of information on the performance of these two methods when the true data distribution is far from normality. In this paper, we propose a new nonparametric and non-iterative method for multivariate meta-analysis on the basis of the theory of U-statistic and compare the properties of these three procedures under both normal and skewed data through simulation studies. It is shown that the effect on estimates from REML because of non-normal data distribution is marginal and that the estimates from MMM and U-statistic-based approaches are very similar. Therefore, we conclude that for performing multivariate meta-analysis, the U-statistic estimation procedure is a viable alternative to REML and MMM. Easy implementation of all three methods are illustrated by their application to data from two published meta-analysis from the fields of hip fracture and periodontal disease. We discuss ideas for future research based on U-statistic for testing significance of between-study heterogeneity and for extending the work to meta-regression setting. Copyright © 2011 John Wiley & Sons, Ltd.

Sequence of Radiotherapy and Chemotherapy in Breast Cancer After Breast-Conserving Surgery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jobsen, Jan J., E-mail: J.Jobsen@mst.nl; Palen, Job van der; Department of Research Methodology, Measurement and Data Analysis, Faculty of Behavioural Science, University of Twente

2012-04-01

Purpose: The optimal sequence of radiotherapy and chemotherapy in breast-conserving therapy is unknown. Methods and Materials: From 1983 through 2007, a total of 641 patients with 653 instances of breast-conserving therapy (BCT), received both chemotherapy and radiotherapy and are the basis of this analysis. Patients were divided into three groups. Groups A and B comprised patients treated before 2005, Group A radiotherapy first and Group B chemotherapy first. Group C consisted of patients treated from 2005 onward, when we had a fixed sequence of radiotherapy first, followed by chemotherapy. Results: Local control did not show any differences among the threemore » groups. For distant metastasis, no difference was shown between Groups A and B. Group C, when compared with Group A, showed, on univariate and multivariate analyses, a significantly better distant metastasis-free survival. The same was noted for disease-free survival. With respect to disease-specific survival, no differences were shown on multivariate analysis among the three groups. Conclusion: Radiotherapy, as an integral part of the primary treatment of BCT, should be administered first, followed by adjuvant chemotherapy.« less

Prediction of Gestational Diabetes through NMR Metabolomics of Maternal Blood.

PubMed

Pinto, Joana; Almeida, Lara M; Martins, Ana S; Duarte, Daniela; Barros, António S; Galhano, Eulália; Pita, Cristina; Almeida, Maria do Céu; Carreira, Isabel M; Gil, Ana M

2015-06-05

Metabolic biomarkers of pre- and postdiagnosis gestational diabetes mellitus (GDM) were sought, using nuclear magnetic resonance (NMR) metabolomics of maternal plasma and corresponding lipid extracts. Metabolite differences between controls and disease were identified through multivariate analysis of variable selected (1)H NMR spectra. For postdiagnosis GDM, partial least squares regression identified metabolites with higher dependence on normal gestational age evolution. Variable selection of NMR spectra produced good classification models for both pre- and postdiagnostic GDM. Prediagnosis GDM was accompanied by cholesterol increase and minor increases in lipoproteins (plasma), fatty acids, and triglycerides (extracts). Small metabolite changes comprised variations in glucose (up regulated), amino acids, betaine, urea, creatine, and metabolites related to gut microflora. Most changes were enhanced upon GDM diagnosis, in addition to newly observed changes in low-Mw compounds. GDM prediction seems possible exploiting multivariate profile changes rather than a set of univariate changes. Postdiagnosis GDM is successfully classified using a 26-resonance plasma biomarker. Plasma and extracts display comparable classification performance, the former enabling direct and more rapid analysis. Results and putative biochemical hypotheses require further confirmation in larger cohorts of distinct ethnicities.

Síndrome metabólico y otros factores asociados a gonartrosis.

PubMed

Charles-Lozoya, Sergio; Treviño-Báez, Joaquín Darío; Ramos-Rivera, Jesús Alejandro; Rangel-Flores, Jesús María; Tamez-Montes, Juan Carlos; Brizuela-Ventura, Jesús Miguel

2017-01-01

To evaluate whether an association exists between gonarthrosis and metabolic syndrome X (MS) as well as other potential risk factors. Comparative cross-sectional study of 310 patients evaluated by pathology of knee grouped in patients with gonarthrosis and without it. Sociodemographic, anthropometric and laboratory data was obtained. Gonarthrosis was defined as a ≥ 2 score in Kellgren-Lawrence radiological scale, and MS was assessed using the International Diabetes Federation criteria. Odds ratio and logistic regression were used for bivariate and multivariate analysis respectively. The prevalence of MS in patients who had gonarthrosis was 79.9%, statistically higher than in patients without gonarthrosis (p = 0.001). Other factors that had a statistically higher frequency in this group included diabetes mellitus (p = 0.02) and hypertension (p = 0.02). Multivariate analysis revealed MS had an association with a higher prevalence of gonarthrosis (p = 0.003), while high density lipoproteins (p = 0.02) was associated with a lower prevalence. MS and its related alterations are associated to gonarthrosis; their adequate control could prevent patients from developing the disease. Copyright: © 2017 SecretarÍa de Salud

Classical least squares multivariate spectral analysis

DOEpatents

Haaland, David M.

2002-01-01

An improved classical least squares multivariate spectral analysis method that adds spectral shapes describing non-calibrated components and system effects (other than baseline corrections) present in the analyzed mixture to the prediction phase of the method. These improvements decrease or eliminate many of the restrictions to the CLS-type methods and greatly extend their capabilities, accuracy, and precision. One new application of PACLS includes the ability to accurately predict unknown sample concentrations when new unmodeled spectral components are present in the unknown samples. Other applications of PACLS include the incorporation of spectrometer drift into the quantitative multivariate model and the maintenance of a calibration on a drifting spectrometer. Finally, the ability of PACLS to transfer a multivariate model between spectrometers is demonstrated.

Self-declared stock ownership and association with positive trial outcome in randomized controlled trials with binary outcomes published in general medical journals: a cross-sectional study.

PubMed

Falk Delgado, Alberto; Falk Delgado, Anna

2017-07-26

Describe the prevalence and types of conflicts of interest (COI) in published randomized controlled trials (RCTs) in general medical journals with a binary primary outcome and assess the association between conflicts of interest and favorable outcome. Parallel-group RCTs with a binary primary outcome published in three general medical journals during 2013-2015 were identified. COI type, funding source, and outcome were extracted. Binomial logistic regression model was performed to assess association between COI and funding source with outcome. A total of 509 consecutive parallel-group RCTs were included in the study. COI was reported in 74% in mixed funded RCTs and in 99% in for-profit funded RCTs. Stock ownership was reported in none of the non-profit RCTs, in 7% of mixed funded RCTs, and in 50% of for-profit funded RCTs. Mixed-funded RCTs had employees from the funding company in 11% and for-profit RCTs in 76%. Multivariable logistic regression revealed that stock ownership in the funding company among any of the authors was associated with a favorable outcome (odds ratio = 3.53; 95% confidence interval = 1.59-7.86; p < 0.01). COI in for-profit funded RCTs is extensive, because the factors related to COI are not fully independent, a multivariable analysis should be cautiously interpreted. However, after multivariable adjustment only stock ownership from the funding company among authors is associated with a favorable outcome.

Mapping as a visual health communication tool: promises and dilemmas.

PubMed

Parrott, Roxanne; Hopfer, Suellen; Ghetian, Christie; Lengerich, Eugene

2007-01-01

In the era of evidence-based public health promotion and planning, the use of maps as a form of evidence to communicate about the multiple determinants of cancer is on the rise. Geographic information systems and mapping technologies make future proliferation of this strategy likely. Yet disease maps as a communication form remain largely unexamined. This content analysis considers the presence of multivariate information, credibility cues, and the communication function of publicly accessible maps for cancer control activities. Thirty-six state comprehensive cancer control plans were publicly available in July 2005 and were reviewed for the presence of maps. Fourteen of the 36 state cancer plans (39%) contained map images (N = 59 static maps). A continuum of map inter activity was observed, with 10 states having interactive mapping tools available to query and map cancer information. Four states had both cancer plans with map images and interactive mapping tools available to the public on their Web sites. Of the 14 state cancer plans that depicted map images, two displayed multivariate data in a single map. Nine of the 10 states with interactive mapping capability offered the option to display multivariate health risk messages. The most frequent content category mapped was cancer incidence and mortality, with stage at diagnosis infrequently available. The most frequent communication function served by the maps reviewed was redundancy, as maps repeated information contained in textual forms. The social and ethical implications for communicating about cancer through the use of visual geographic representations are discussed.

Return Difference Feedback Design for Robust Uncertainty Tolerance in Stochastic Multivariable Control Systems.

DTIC Science & Technology

1984-07-01

34robustness" analysis for multiloop feedback systems. Reference [55] describes a simple method based on the Perron - Frobenius Theory of non-negative...Viewpoint, " Operator Theory : Advances and Applications, 12, pp. 277-302, 1984. - E. A. Jonckheere, "New Bound on the Sensitivity -- of the Solution of...Reidel, Dordrecht, Holland, 1984. M. G. Safonov, "Comments on Singular Value Theory in Uncertain Feedback Systems, " to appear IEEE Trans. on Automatic

Metabolic profiling of human lung cancer blood plasma using 1H NMR spectroscopy

NASA Astrophysics Data System (ADS)

Kokova, Daria; Dementeva, Natalia; Kotelnikov, Oleg; Ponomaryova, Anastasia; Cherdyntseva, Nadezhda; Kzhyshkowska, Juliya

2017-11-01

Lung cancer (both small cell and non-small cell) is the second most common cancer in both men and women. The article represents results of evaluating of the plasma metabolic profiles of 100 lung cancer patients and 100 controls to investigate significant metabolites using 400 MHz 1H NMR spectrometer. The results of multivariate statistical analysis show that a medium-field NMR spectrometer can obtain the data which are already sufficient for clinical metabolomics.

Analysis of the Risk Factors for Aerobic Vaginitis: A Case-Control Study.

PubMed

Geng, Nv; Wu, Wenjuan; Fan, Aiping; Han, Cha; Wang, Chen; Wang, Yingmei; Xue, Fengxia

2015-06-09

Aerobic vaginitis (AV) is a newly defined clinical entity which may interfere with women's reproductive health and have negative effects on pregnancy. This study was to identify the risk factors for AV. Participants in this case-control study included healthy women and women with AV. All participants completed a standardized questionnaire covering sociodemographic factors, sexual behaviors, personal hygiene habits and health behaviors. Uni- and multivariate logistic regression analyses were used for statistical evaluation. A total of 290 women of reproductive age were enrolled. In the multivariate analysis, unmarried status (odds ratio [OR] 2.606, 95% confidence interval [CI] 1.257-5.402), use of an intrauterine device (OR 4.989, 95% CI 1.922-12.952), long-term use of antibiotics (OR 11.176, 95% CI 1.363-91.666) and frequent vaginal douching (OR 4.689, 95% CI 1.363-16.135) were independent risk factors for AV. On the contrary, consistent condom use (OR 0.546, 95% CI 0.301-0.991) and college-level education or above (OR 0.255, 95% CI 0.131-0.497) were independent protective factors. Measures that may be considered to prevent AV include enhancing education to improve women's knowledge related to reproductive health, especially unmarried women, encouraging them to consistently use condoms as a contraceptive method, to avoid long-term use of antibiotics and to stop frequent vaginal douching. © 2015 S. Karger AG, Basel.

Expression and clinical significance of PIWIL2 in hilar cholangiocarcinoma tissues and cell lines.

PubMed

Chen, Y J; Xiong, X F; Wen, S Q; Tian, L; Cheng, W L; Qi, Y Q

2015-06-26

The objective of this study was to explore the relationship between PIWI-like protein 2 (PIWIL2) and clinicopathological charac-teristics and prognosis after radical resection. To accomplish this, we analyzed PIWIL2 expression in hilar cholangiocarcinoma tissues and cell lines. PIWIL2 expression was detected by immunohistochemistry in 41 hilar cholangiocarcinoma samples and 10 control tissues. Western blotting and immunocytofluorescence were used to investigate PIWIL2 expression in the cholangiocarcinoma cell line QBC939 and the bile duct epithelial cell line HIBEpic. Univariate and multivariate surviv-al analyses were performed using the Kaplan-Meier method for hilar cholangiocarcinoma patients who underwent radical resection. PIWIL2 expression was significantly higher in the hilar cholangiocarcinoma tissues and QBC939 cells than in control tissues and HIBEpic cells, respectively (P < 0.05). Poorly and moderately differentiated cholan-giocarcinoma tissues had significantly higher PIWIL2 expression than well-differentiated tissues (P < 0.05). Univariate analysis demonstrated that high PIWIL2 expression was associated with shorter survival time after radical resection (P < 0.05). Multivariate analysis showed that PI-WIL2 expression was an independent prognostic factor after radical re-section of hilar cholangiocarcinoma (P < 0.05). PIWIL2 expression was also associated with tumor-node-metastasis stage and differentiation. PIWIL2 was an independent prognostic factor after radical resection of hilar cholangiocarcinoma.

Sensory cortex hyperexcitability predicts short survival in amyotrophic lateral sclerosis.

PubMed

Shimizu, Toshio; Bokuda, Kota; Kimura, Hideki; Kamiyama, Tsutomu; Nakayama, Yuki; Kawata, Akihiro; Isozaki, Eiji; Ugawa, Yoshikazu

2018-05-01

To investigate somatosensory cortex excitability and its relationship to survival prognosis in patients with amyotrophic lateral sclerosis (ALS). A total of 145 patients with sporadic ALS and 73 healthy control participants were studied. We recorded compound muscle action potential and sensory nerve action potential of the median nerve and the median nerve somatosensory evoked potential (SEP), and we measured parameters, including onset-to-peak amplitude of N13 and N20 and peak-to-peak amplitude between N20 and P25 (N20p-P25p). Clinical prognostic factors, including ALS Functional Rating Scale-Revised, were evaluated. We followed up patients until the endpoints (death or tracheostomy) and analyzed factors associated with survival using multivariate analysis in the Cox proportional hazard model. Compared to controls, patients with ALS showed a larger amplitude of N20p-P25p in the median nerve SEP. Median survival time after examination was shorter in patients with N20p-P25p ≥8 μV (0.82 years) than in those with N20p-P25p <8 μV (1.68 years, p = 0.0002, log-rank test). Multivariate analysis identified a larger N20p-P25p amplitude as a factor that was independently associated with shorter survival ( p = 0.002). Sensory cortex hyperexcitability predicts short survival in patients with ALS. © 2018 American Academy of Neurology.

[Compliancy of pre-exposure prophylaxis for HIV infection in men who have sex with men in Chengdu].

PubMed

Xu, J Y; Mou, Y C; Ma, Y L; Zhang, J Y

2017-05-10

Objective: To evaluate the compliancy of HIV pre-exposure prophylaxis (PrEP) in men who have sex with men (MSM) in Chengdu, Sichuan province, and explore the influencing factors. Methods: From 1 July 2013 to 30 September 2015, a random, open, multi-center and parallel control intervention study was conducted in 328 MSM enrolled by non-probability sampling in Chengdu. The MSM were divided into 3 groups randomly, i.e. daily group, intermittent group (before and after exposure) and control group. Clinical follow-up and questionnaire survey were carried out every 3 months. Their PrEP compliances were evaluated respectively and multivariate logistic regression analysis was conducted to identify the related factors. Results: A total of 141 MSM were surveyed, in whom 59(41.8 % ) had good PrEP compliancy. The PrEP compliancy rate was 69.0 % in daily group, higher than that in intermittent group (14.3 % ), the difference had significance ( χ (2)=45.29, P <0.001). Multivariate logistic analysis indicated that type of PrEP was the influencing factors of PrEP compliancy. Compared with daily group, the intermittent group had worse PrEP compliancy ( OR =0.07, 95 %CI : 0.03-0.16). Conclusion: The PrEP compliance of the MSM in this study was poor, the compliancy would be influenced by the type of PrEP.

Advanced qualification of pharmaceutical excipient suppliers by multiple analytics and multivariate analysis combined.

PubMed

Hertrampf, A; Müller, H; Menezes, J C; Herdling, T

2015-11-10

Pharmaceutical excipients have different functions within a drug formulation, consequently they can influence the manufacturability and/or performance of medicinal products. Therefore, critical to quality attributes should be kept constant. Sometimes it may be necessary to qualify a second supplier, but its product will not be completely equal to the first supplier product. To minimize risks of not detecting small non-similarities between suppliers and to detect lot-to-lot variability for each supplier, multivariate data analysis (MVA) can be used as a more powerful alternative to classical quality control that uses one-parameter-at-a-time monitoring. Such approach is capable of supporting the requirements of a new guideline by the European Parliament and Council (2015/C-95/02) demanding appropriate quality control strategies for excipients based on their criticality and supplier risks in ensuring quality, safety and function. This study compares calcium hydrogen phosphate from two suppliers. It can be assumed that both suppliers use different manufacturing processes. Therefore, possible chemical and physical differences were investigated by using Raman spectroscopy, laser diffraction and X-ray powder diffraction. Afterwards MVA was used to extract relevant information from each analytical technique. Both CaHPO4 could be discriminated by their supplier. The gained knowledge allowed to specify an enhanced strategy for second supplier qualification. Copyright © 2015 Elsevier B.V. All rights reserved.

Increased prevalence of third-degree atrioventricular block in patients with type II diabetes mellitus.

PubMed

Movahed, Mohammad-Reza; Hashemzadeh, Mehrtash; Jamal, M Mazen

2005-10-01

Diabetes mellitus (DM) is a major risk for cardiovascular disease and mortality. There is some evidence that third-degree atrioventricular (AV) block occurs more commonly in patients with DM. In this study, we evaluated any possible association between DM and third-degree AV block using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes in a very large inpatient database. We used patient treatment files containing discharge diagnoses using ICD-9 codes of inpatient treatment from all Veterans Health Administration hospitals. The cohort was stratified using the ICD-9-CM code for DM (n = 293,124), a control group with hypertension but no DM (n = 552,623), and the ICD-9 code for third-degree AV block (426.0) and smoking (305.1, V15.82). We performed multivariate analysis adjusting for coronary artery disease, congestive heart failure, smoking, and hyperlipidemia. Continuous and binary variables were analyzed using chi2 and Fisher exact tests. Third-degree AV block diagnosis was present in 3,240 of DM patients (1.1%) vs 3,367 patients (0.6%) in the control group. Using multivariate analysis, DM remained strongly associated with third-degree AV block (odds ratio, 3.1; 95% confidential interval, 3.0 to 3.3; p < 0.0001). Third-degree AV block occurs significantly more in patients with DM. This finding may, in part, explain the high cardiovascular mortality in DM patients.

Prevention of post procedural acute kidney injury in the catheterization laboratory in a real-world population.

PubMed

Chorin, Ehud; Ben-Assa, Eyal; Konigstein, Maayan; Rofe, May-Tal; Hochstadt, Aviram; Galli, Naama; Schnapper, Michael; Arbel, Yaron; Rabey, Ilan; Shoshan, Jeremy Ben; Halkin, Amir; Herz, Itzhak; Finkelstein, Ariel; Bazan, Samuel; Keren, Gad; Banai, Shmuel

2017-01-01

Radiologists and cardiologists have a remarkably different approach to the clinical importance and to the need for prophylactic treatment of contrast-induced acute kidney injury (CI-AKI). To evaluate the efficacy of forced diuresis with matched controlled hydration (FMH) in a real-world, high risk population. This is an investigator-driven, single-center, retrospective analysis of prospectively collected data. A total of 150 consecutive patients undergoing coronary angiography, angioplasty or TAVR who were treated with FMH were compared to a matched historical control cohort. In the FMH treated patients, eGFR improved following the procedure from 37ml/min per 1.73m 2 at baseline to 39ml/min per 1.73m 2 (p<0.001); the net creatinine decreased from 1.85mg/dl to 1.78mg/dl (p<0.001). Among the matched control group, eGFR deteriorated from a baseline value of 36.7ml/min per 1.73m 2 to 33.2ml/min per 1.73m 2 post procedurally (p<0.001); the net creatinine increased from 1.88mg/dl to 2.14mg/dl (p<0.001). The incidence of post procedural AKI was substantially lower in the FMH treated group (2.7%) compared to the control group (26.7%). By multivariable analysis FMH treatment was independently correlated with reduced incidence of post procedural AKI compared with the control group (OR 0.06, p<0.001). Contrast volume did not correlate with AKI in neither univariate nor multivariate analyses. In patients undergoing coronary angiography, angioplasty or TAVR, who are considered high risk to develop post procedural AKI, forced diuresis with matched controlled hydration resulted in a significant net creatinine decrease, eGFR increase and a decrease in the incidence of AKI. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.