Analysis of linear energy transfers and quality factors of charged particles produced by spontaneous fission neutrons from 252Cf and 244Pu in the human body.

PubMed

Endo, Akira; Sato, Tatsuhiko

2013-04-01

Absorbed doses, linear energy transfers (LETs) and quality factors of secondary charged particles in organs and tissues, generated via the interactions of the spontaneous fission neutrons from (252)Cf and (244)Pu within the human body, were studied using the Particle and Heavy Ion Transport Code System (PHITS) coupled with the ICRP Reference Phantom. Both the absorbed doses and the quality factors in target organs generally decrease with increasing distance from the source organ. The analysis of LET distributions of secondary charged particles led to the identification of the relationship between LET spectra and target-source organ locations. A comparison between human body-averaged mean quality factors and fluence-averaged radiation weighting factors showed that the current numerical conventions for the radiation weighting factors of neutrons, updated in ICRP103, and the quality factors for internal exposure are valid.

Predictors of postoperative outcomes of cubital tunnel syndrome treatments using multiple logistic regression analysis.

PubMed

Suzuki, Taku; Iwamoto, Takuji; Shizu, Kanae; Suzuki, Katsuji; Yamada, Harumoto; Sato, Kazuki

2017-05-01

This retrospective study was designed to investigate prognostic factors for postoperative outcomes for cubital tunnel syndrome (CubTS) using multiple logistic regression analysis with a large number of patients. Eighty-three patients with CubTS who underwent surgeries were enrolled. The following potential prognostic factors for disease severity were selected according to previous reports: sex, age, type of surgery, disease duration, body mass index, cervical lesion, presence of diabetes mellitus, Workers' Compensation status, preoperative severity, and preoperative electrodiagnostic testing. Postoperative severity of disease was assessed 2 years after surgery by Messina's criteria which is an outcome measure specifically for CubTS. Bivariate analysis was performed to select candidate prognostic factors for multiple linear regression analyses. Multiple logistic regression analysis was conducted to identify the association between postoperative severity and selected prognostic factors. Both bivariate and multiple linear regression analysis revealed only preoperative severity as an independent risk factor for poor prognosis, while other factors did not show any significant association. Although conflicting results exist regarding prognosis of CubTS, this study supports evidence from previous studies and concludes early surgical intervention portends the most favorable prognosis. Copyright © 2017 The Japanese Orthopaedic Association. Published by Elsevier B.V. All rights reserved.

Selection of higher order regression models in the analysis of multi-factorial transcription data.

PubMed

Prazeres da Costa, Olivia; Hoffman, Arthur; Rey, Johannes W; Mansmann, Ulrich; Buch, Thorsten; Tresch, Achim

2014-01-01

Many studies examine gene expression data that has been obtained under the influence of multiple factors, such as genetic background, environmental conditions, or exposure to diseases. The interplay of multiple factors may lead to effect modification and confounding. Higher order linear regression models can account for these effects. We present a new methodology for linear model selection and apply it to microarray data of bone marrow-derived macrophages. This experiment investigates the influence of three variable factors: the genetic background of the mice from which the macrophages were obtained, Yersinia enterocolitica infection (two strains, and a mock control), and treatment/non-treatment with interferon-γ. We set up four different linear regression models in a hierarchical order. We introduce the eruption plot as a new practical tool for model selection complementary to global testing. It visually compares the size and significance of effect estimates between two nested models. Using this methodology we were able to select the most appropriate model by keeping only relevant factors showing additional explanatory power. Application to experimental data allowed us to qualify the interaction of factors as either neutral (no interaction), alleviating (co-occurring effects are weaker than expected from the single effects), or aggravating (stronger than expected). We find a biologically meaningful gene cluster of putative C2TA target genes that appear to be co-regulated with MHC class II genes. We introduced the eruption plot as a tool for visual model comparison to identify relevant higher order interactions in the analysis of expression data obtained under the influence of multiple factors. We conclude that model selection in higher order linear regression models should generally be performed for the analysis of multi-factorial microarray data.

Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

PubMed

Cook, James P; Mahajan, Anubha; Morris, Andrew P

2017-02-01

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used for meta-analysis of GWAS of binary phenotypes, without loss of power, even in the presence of extreme case-control imbalance, provided that one of the following schemes is used: (i) effective sample size weighting of Z-scores or (ii) inverse-variance weighting of allelic effect sizes after conversion onto the log-odds scale. Our conclusions thus provide essential recommendations for the development of robust protocols for meta-analysis of binary phenotypes with linear models.

ADAPTION OF NONSTANDARD PIPING COMPONENTS INTO PRESENT DAY SEISMIC CODES

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

D. T. Clark; M. J. Russell; R. E. Spears

2009-07-01

With spiraling energy demand and flat energy supply, there is a need to extend the life of older nuclear reactors. This sometimes requires that existing systems be evaluated to present day seismic codes. Older reactors built in the 1960s and early 1970s often used fabricated piping components that were code compliant during their initial construction time period, but are outside the standard parameters of present-day piping codes. There are several approaches available to the analyst in evaluating these non-standard components to modern codes. The simplest approach is to use the flexibility factors and stress indices for similar standard components withmore » the assumption that the non-standard component’s flexibility factors and stress indices will be very similar. This approach can require significant engineering judgment. A more rational approach available in Section III of the ASME Boiler and Pressure Vessel Code, which is the subject of this paper, involves calculation of flexibility factors using finite element analysis of the non-standard component. Such analysis allows modeling of geometric and material nonlinearities. Flexibility factors based on these analyses are sensitive to the load magnitudes used in their calculation, load magnitudes that need to be consistent with those produced by the linear system analyses where the flexibility factors are applied. This can lead to iteration, since the magnitude of the loads produced by the linear system analysis depend on the magnitude of the flexibility factors. After the loading applied to the nonstandard component finite element model has been matched to loads produced by the associated linear system model, the component finite element model can then be used to evaluate the performance of the component under the loads with the nonlinear analysis provisions of the Code, should the load levels lead to calculated stresses in excess of Allowable stresses. This paper details the application of component-level finite element modeling to account for geometric and material nonlinear component behavior in a linear elastic piping system model. Note that this technique can be applied to the analysis of B31 piping systems.« less

A study of the effects of an experimental spiral physics curriculum taught to sixth grade girls and boys

NASA Astrophysics Data System (ADS)

Davis, Edith G.

The pilot study compared the effectiveness of using an experimental spiral physics curriculum to a traditional linear physics curriculum for sixth through eighth grades. The study also surveyed students' parents and principals about students' academic history and background as well as identified resilient children's attributes for academic success. The pilot study was used to help validate the testing instrument as well as help refine the complete study. The purpose of the complete study was to compare the effectiveness of using an experimental spiral physics curriculum and a traditional linear curriculum with sixth graders only; seventh and eighth graders were dropped in the complete study. The study also surveyed students' parents, teachers, and principals about students' academic history and background as well as identified resilient children's attributes for academic success. Both the experimental spiral physics curriculum and the traditional linear physics curriculum increased physics achievement; however, there was no statistically significant difference in effectiveness of teaching experimental spiral physics curriculum in the aggregated sixth grade group compared to the traditional linear physics curriculum. It is important to note that the majority of the subgroups studied did show statistically significant differences in effectiveness for the experimental spiral physics curriculum compared to the traditional linear physics curriculum. The Grounded Theory analysis of resilient student characteristics resulted in categories for future studies including the empathy factor ("E" factor), the tenacity factor ("T" factor), the relational factor ("R" factor), and the spiritual factor ("S" factor).

Identifying the Factors That Influence Change in SEBD Using Logistic Regression Analysis

ERIC Educational Resources Information Center

Camilleri, Liberato; Cefai, Carmel

2013-01-01

Multiple linear regression and ANOVA models are widely used in applications since they provide effective statistical tools for assessing the relationship between a continuous dependent variable and several predictors. However these models rely heavily on linearity and normality assumptions and they do not accommodate categorical dependent…

Comparison of Linear and Non-linear Regression Analysis to Determine Pulmonary Pressure in Hyperthyroidism.

PubMed

Scarneciu, Camelia C; Sangeorzan, Livia; Rus, Horatiu; Scarneciu, Vlad D; Varciu, Mihai S; Andreescu, Oana; Scarneciu, Ioan

2017-01-01

This study aimed at assessing the incidence of pulmonary hypertension (PH) at newly diagnosed hyperthyroid patients and at finding a simple model showing the complex functional relation between pulmonary hypertension in hyperthyroidism and the factors causing it. The 53 hyperthyroid patients (H-group) were evaluated mainly by using an echocardiographical method and compared with 35 euthyroid (E-group) and 25 healthy people (C-group). In order to identify the factors causing pulmonary hypertension the statistical method of comparing the values of arithmetical means is used. The functional relation between the two random variables (PAPs and each of the factors determining it within our research study) can be expressed by linear or non-linear function. By applying the linear regression method described by a first-degree equation the line of regression (linear model) has been determined; by applying the non-linear regression method described by a second degree equation, a parabola-type curve of regression (non-linear or polynomial model) has been determined. We made the comparison and the validation of these two models by calculating the determination coefficient (criterion 1), the comparison of residuals (criterion 2), application of AIC criterion (criterion 3) and use of F-test (criterion 4). From the H-group, 47% have pulmonary hypertension completely reversible when obtaining euthyroidism. The factors causing pulmonary hypertension were identified: previously known- level of free thyroxin, pulmonary vascular resistance, cardiac output; new factors identified in this study- pretreatment period, age, systolic blood pressure. According to the four criteria and to the clinical judgment, we consider that the polynomial model (graphically parabola- type) is better than the linear one. The better model showing the functional relation between the pulmonary hypertension in hyperthyroidism and the factors identified in this study is given by a polynomial equation of second degree where the parabola is its graphical representation.

Analysis of the shapes of hemocytes of Callista brevisiphonata in vitro (Bivalvia, Veneridae).

PubMed

Karetin, Yu A; Pushchin, I I

2015-08-01

Fractal formalism in conjunction with linear methods of image analysis is suitable for the comparative analysis of such "irregular" shapes (from the point of view of classical Euclidean geometry) as flattened amoeboid cells of invertebrates in vitro. Cell morphology of in vitro spreading hemocytes from the bivalve mollusc Callista brevisiphonata was analyzed using correlation, factor and cluster analysis. Four significantly different cell types were identified on the basis of 36 linear and nonlinear parameters. The analysis confirmed the adequacy of the selected methodology for numerical description of the shape and the adequacy of classification of nonlinear shapes of spread hemocytes belonging to the same species. Investigation has practical significance for the description of the morphology of cultured cells, since cell shape is a result of summation of a number of extracellular and intracellular factors. © 2015 International Society for Advancement of Cytometry.

Analysis of Nonlinear Dynamics in Linear Compressors Driven by Linear Motors

NASA Astrophysics Data System (ADS)

Chen, Liangyuan

2018-03-01

The analysis of dynamic characteristics of the mechatronics system is of great significance for the linear motor design and control. Steady-state nonlinear response characteristics of a linear compressor are investigated theoretically based on the linearized and nonlinear models. First, the influence factors considering the nonlinear gas force load were analyzed. Then, a simple linearized model was set up to analyze the influence on the stroke and resonance frequency. Finally, the nonlinear model was set up to analyze the effects of piston mass, spring stiffness, driving force as an example of design parameter variation. The simulating results show that the stroke can be obtained by adjusting the excitation amplitude, frequency and other adjustments, the equilibrium position can be adjusted by adjusting the DC input, and to make the more efficient operation, the operating frequency must always equal to the resonance frequency.

Slope stability analysis using limit equilibrium method in nonlinear criterion.

PubMed

Lin, Hang; Zhong, Wenwen; Xiong, Wei; Tang, Wenyu

2014-01-01

In slope stability analysis, the limit equilibrium method is usually used to calculate the safety factor of slope based on Mohr-Coulomb criterion. However, Mohr-Coulomb criterion is restricted to the description of rock mass. To overcome its shortcomings, this paper combined Hoek-Brown criterion and limit equilibrium method and proposed an equation for calculating the safety factor of slope with limit equilibrium method in Hoek-Brown criterion through equivalent cohesive strength and the friction angle. Moreover, this paper investigates the impact of Hoek-Brown parameters on the safety factor of slope, which reveals that there is linear relation between equivalent cohesive strength and weakening factor D. However, there are nonlinear relations between equivalent cohesive strength and Geological Strength Index (GSI), the uniaxial compressive strength of intact rock σ ci , and the parameter of intact rock m i . There is nonlinear relation between the friction angle and all Hoek-Brown parameters. With the increase of D, the safety factor of slope F decreases linearly; with the increase of GSI, F increases nonlinearly; when σ ci is relatively small, the relation between F and σ ci is nonlinear, but when σ ci is relatively large, the relation is linear; with the increase of m i , F decreases first and then increases.

Slope Stability Analysis Using Limit Equilibrium Method in Nonlinear Criterion

PubMed Central

Lin, Hang; Zhong, Wenwen; Xiong, Wei; Tang, Wenyu

2014-01-01

In slope stability analysis, the limit equilibrium method is usually used to calculate the safety factor of slope based on Mohr-Coulomb criterion. However, Mohr-Coulomb criterion is restricted to the description of rock mass. To overcome its shortcomings, this paper combined Hoek-Brown criterion and limit equilibrium method and proposed an equation for calculating the safety factor of slope with limit equilibrium method in Hoek-Brown criterion through equivalent cohesive strength and the friction angle. Moreover, this paper investigates the impact of Hoek-Brown parameters on the safety factor of slope, which reveals that there is linear relation between equivalent cohesive strength and weakening factor D. However, there are nonlinear relations between equivalent cohesive strength and Geological Strength Index (GSI), the uniaxial compressive strength of intact rock σ ci, and the parameter of intact rock m i. There is nonlinear relation between the friction angle and all Hoek-Brown parameters. With the increase of D, the safety factor of slope F decreases linearly; with the increase of GSI, F increases nonlinearly; when σ ci is relatively small, the relation between F and σ ci is nonlinear, but when σ ci is relatively large, the relation is linear; with the increase of m i, F decreases first and then increases. PMID:25147838

Analysis of linear and cyclic oligomers in polyamide-6 without sample preparation by liquid chromatography using the sandwich injection method. II. Methods of detection and quantification and overall long-term performance.

PubMed

Mengerink, Y; Peters, R; Kerkhoff, M; Hellenbrand, J; Omloo, H; Andrien, J; Vestjens, M; van der Wal, S

2000-05-05

By separating the first six linear and cyclic oligomers of polyamide-6 on a reversed-phase high-performance liquid chromatographic system after sandwich injection, quantitative determination of these oligomers becomes feasible. Low-wavelength UV detection of the different oligomers and selective post-column reaction detection of the linear oligomers with o-phthalic dicarboxaldehyde (OPA) and 3-mercaptopropionic acid (3-MPA) are discussed. A general methodology for quantification of oligomers in polymers was developed. It is demonstrated that the empirically determined group-equivalent absorption coefficients and quench factors are a convenient way of quantifying linear and cyclic oligomers of nylon-6. The overall long-term performance of the method was studied by monitoring a reference sample and the calibration factors of the linear and cyclic oligomers.

Discriminative analysis of non-linear brain connectivity for leukoaraiosis with resting-state fMRI

NASA Astrophysics Data System (ADS)

Lai, Youzhi; Xu, Lele; Yao, Li; Wu, Xia

2015-03-01

Leukoaraiosis (LA) describes diffuse white matter abnormalities on CT or MR brain scans, often seen in the normal elderly and in association with vascular risk factors such as hypertension, or in the context of cognitive impairment. The mechanism of cognitive dysfunction is still unclear. The recent clinical studies have revealed that the severity of LA was not corresponding to the cognitive level, and functional connectivity analysis is an appropriate method to detect the relation between LA and cognitive decline. However, existing functional connectivity analyses of LA have been mostly limited to linear associations. In this investigation, a novel measure utilizing the extended maximal information coefficient (eMIC) was applied to construct non-linear functional connectivity in 44 LA subjects (9 dementia, 25 mild cognitive impairment (MCI) and 10 cognitively normal (CN)). The strength of non-linear functional connections for the first 1% of discriminative power increased in MCI compared with CN and dementia, which was opposed to its linear counterpart. Further functional network analysis revealed that the changes of the non-linear and linear connectivity have similar but not completely the same spatial distribution in human brain. In the multivariate pattern analysis with multiple classifiers, the non-linear functional connectivity mostly identified dementia, MCI and CN from LA with a relatively higher accuracy rate than the linear measure. Our findings revealed the non-linear functional connectivity provided useful discriminative power in classification of LA, and the spatial distributed changes between the non-linear and linear measure may indicate the underlying mechanism of cognitive dysfunction in LA.

Analysis of facial motion patterns during speech using a matrix factorization algorithm

PubMed Central

Lucero, Jorge C.; Munhall, Kevin G.

2008-01-01

This paper presents an analysis of facial motion during speech to identify linearly independent kinematic regions. The data consists of three-dimensional displacement records of a set of markers located on a subject’s face while producing speech. A QR factorization with column pivoting algorithm selects a subset of markers with independent motion patterns. The subset is used as a basis to fit the motion of the other facial markers, which determines facial regions of influence of each of the linearly independent markers. Those regions constitute kinematic “eigenregions” whose combined motion produces the total motion of the face. Facial animations may be generated by driving the independent markers with collected displacement records. PMID:19062866

Internal and external environmental factors affecting the performance of hospital-based home nursing care.

PubMed

Noh, J-W; Kwon, Y-D; Yoon, S-J; Hwang, J-I

2011-06-01

Numerous studies on HNC services have been carried out by signifying their needs, efficiency and effectiveness. However, no study has ever been performed to determine the critical factors associated with HNC's positive results despite the deluge of positive studies on the service. This study included all of the 89 training hospitals that were practising HNC service in Korea as of November 2006. The input factors affecting the performance were classified as either internal or external environmental factors. This analysis was conducted to understand the impact that the corresponding factors had on performance. Data were analysed by using multiple linear regressions. The internal and external environment variables affected the performance of HNC based on univariate analysis. The meaningful variables were internal environmental factors. Specifically, managerial resource (the number of operating beds and the outpatient/inpatient ratio) were meaningful when the multiple linear regression analysis was performed. Indeed, the importance of organizational culture (the passion of HNC nurses) was significant. This study, considering the limited market size of Korea, illustrates that the critical factor for the development of hospital-led HNC lies with internal environmental factors rather than external ones. Among the internal environmental factors, the hospitals' managerial resource-related factors (specifically, the passion of nurses) were the most important contributing element. © 2011 The Authors. International Nursing Review © 2011 International Council of Nurses.

A Linear Variable-[theta] Model for Measuring Individual Differences in Response Precision

ERIC Educational Resources Information Center

Ferrando, Pere J.

2011-01-01

Models for measuring individual response precision have been proposed for binary and graded responses. However, more continuous formats are quite common in personality measurement and are usually analyzed with the linear factor analysis model. This study extends the general Gaussian person-fluctuation model to the continuous-response case and…

Modeling containment of large wildfires using generalized linear mixed-model analysis

Treesearch

Mark Finney; Isaac C. Grenfell; Charles W. McHugh

2009-01-01

Billions of dollars are spent annually in the United States to contain large wildland fires, but the factors contributing to suppression success remain poorly understood. We used a regression model (generalized linear mixed-model) to model containment probability of individual fires, assuming that containment was a repeated-measures problem (fixed effect) and...

CFORM- LINEAR CONTROL SYSTEM DESIGN AND ANALYSIS: CLOSED FORM SOLUTION AND TRANSIENT RESPONSE OF THE LINEAR DIFFERENTIAL EQUATION

NASA Technical Reports Server (NTRS)

Jamison, J. W.

1994-01-01

CFORM was developed by the Kennedy Space Center Robotics Lab to assist in linear control system design and analysis using closed form and transient response mechanisms. The program computes the closed form solution and transient response of a linear (constant coefficient) differential equation. CFORM allows a choice of three input functions: the Unit Step (a unit change in displacement); the Ramp function (step velocity); and the Parabolic function (step acceleration). It is only accurate in cases where the differential equation has distinct roots, and does not handle the case for roots at the origin (s=0). Initial conditions must be zero. Differential equations may be input to CFORM in two forms - polynomial and product of factors. In some linear control analyses, it may be more appropriate to use a related program, Linear Control System Design and Analysis (KSC-11376), which uses root locus and frequency response methods. CFORM was written in VAX FORTRAN for a VAX 11/780 under VAX VMS 4.7. It has a central memory requirement of 30K. CFORM was developed in 1987.

Relationship between linear type and fertility traits in Nguni cows.

PubMed

Zindove, T J; Chimonyo, M; Nephawe, K A

2015-06-01

The objective of the study was to assess the dimensionality of seven linear traits (body condition score, body stature, body length, heart girth, navel height, body depth and flank circumference) in Nguni cows using factor analysis and indicate the relationship between the extracted latent variables and calving interval (CI) and age at first calving (AFC). The traits were measured between December 2012 and November 2013 on 1559 Nguni cows kept under thornveld, succulent karoo, grassland and bushveld vegetation types. Low partial correlations (-0.04 to 0.51), high Kaiser statistic for measure of sampling adequacy scores and significance of the Bartlett sphericity test (P1. Factor 1 included body condition score, body depth, flank circumference and heart girth and represented body capacity of cows. Factor 2 included body length, body stature and navel height and represented frame size of cows. CI and AFC decreased linearly with increase of factor 1. There was a quadratic increase in AFC as factor 2 increased (P<0.05). It was concluded that the linear type traits under study can be grouped into two distinct factors, one linked to body capacity and the other to the frame size of the cows. Small-framed cows with large body capacities have shorter CI and AFC.

Quasi-likelihood generalized linear regression analysis of fatality risk data

DOT National Transportation Integrated Search

2009-01-01

Transportation-related fatality risks is a function of many interacting human, vehicle, and environmental factors. Statisitcally valid analysis of such data is challenged both by the complexity of plausable structural models relating fatality rates t...

Assessing risk factors for periodontitis using regression

NASA Astrophysics Data System (ADS)

Lobo Pereira, J. A.; Ferreira, Maria Cristina; Oliveira, Teresa

2013-10-01

Multivariate statistical analysis is indispensable to assess the associations and interactions between different factors and the risk of periodontitis. Among others, regression analysis is a statistical technique widely used in healthcare to investigate and model the relationship between variables. In our work we study the impact of socio-demographic, medical and behavioral factors on periodontal health. Using regression, linear and logistic models, we can assess the relevance, as risk factors for periodontitis disease, of the following independent variables (IVs): Age, Gender, Diabetic Status, Education, Smoking status and Plaque Index. The multiple linear regression analysis model was built to evaluate the influence of IVs on mean Attachment Loss (AL). Thus, the regression coefficients along with respective p-values will be obtained as well as the respective p-values from the significance tests. The classification of a case (individual) adopted in the logistic model was the extent of the destruction of periodontal tissues defined by an Attachment Loss greater than or equal to 4 mm in 25% (AL≥4mm/≥25%) of sites surveyed. The association measures include the Odds Ratios together with the correspondent 95% confidence intervals.

Pattern variation of fish fingerling abundance in the Na Thap Tidal river of Southern Thailand: 2005-2015

NASA Astrophysics Data System (ADS)

Donroman, T.; Chesoh, S.; Lim, A.

2018-04-01

This study aimed to investigate the variation patterns of fish fingerling abundance based on month, year and sampling site. Monthly collecting data set of the Na Thap tidal river of southern Thailand, were obtained from June 2005 to October 2015. The square root transformation was employed for maintaining the fingerling data normality. Factor analysis was applied for clustering number of fingerling species and multiple linear regression was used to examine the association between fingerling density and year, month and site. Results from factor analysis classified fingerling into 3 factors based on saline preference; saline water, freshwater and ubiquitous species. The results showed a statistically high significant relation between fingerling density, month, year and site. Abundance of saline water and ubiquitous fingerling density showed similar pattern. Downstream site presented highest fingerling density whereas almost of freshwater fingerling occurred in upstream. This finding confirmed that factor analysis and the general linear regression method can be used as an effective tool for predicting and monitoring wild fingerling density in order to sustain fish stock management.

Generalized Structured Component Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Takane, Yoshio

2004-01-01

We propose an alternative method to partial least squares for path analysis with components, called generalized structured component analysis. The proposed method replaces factors by exact linear combinations of observed variables. It employs a well-defined least squares criterion to estimate model parameters. As a result, the proposed method…

Factor Scores, Structure and Communality Coefficients: A Primer

ERIC Educational Resources Information Center

Odum, Mary

2011-01-01

(Purpose) The purpose of this paper is to present an easy-to-understand primer on three important concepts of factor analysis: Factor scores, structure coefficients, and communality coefficients. Given that statistical analyses are a part of a global general linear model (GLM), and utilize weights as an integral part of analyses (Thompson, 2006;…

INNOVATIVE INSTRUMENTATION AND ANALYSIS OF THE TEMPERATURE MEASUREMENT FOR HIGH TEMPERATURE GASIFICATION

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

Seong W. Lee

During this reporting period, the literature survey including the gasifier temperature measurement literature, the ultrasonic application and its background study in cleaning application, and spray coating process are completed. The gasifier simulator (cold model) testing has been successfully conducted. Four factors (blower voltage, ultrasonic application, injection time intervals, particle weight) were considered as significant factors that affect the temperature measurement. The Analysis of Variance (ANOVA) was applied to analyze the test data. The analysis shows that all four factors are significant to the temperature measurements in the gasifier simulator (cold model). The regression analysis for the case with the normalizedmore » room temperature shows that linear model fits the temperature data with 82% accuracy (18% error). The regression analysis for the case without the normalized room temperature shows 72.5% accuracy (27.5% error). The nonlinear regression analysis indicates a better fit than that of the linear regression. The nonlinear regression model's accuracy is 88.7% (11.3% error) for normalized room temperature case, which is better than the linear regression analysis. The hot model thermocouple sleeve design and fabrication are completed. The gasifier simulator (hot model) design and the fabrication are completed. The system tests of the gasifier simulator (hot model) have been conducted and some modifications have been made. Based on the system tests and results analysis, the gasifier simulator (hot model) has met the proposed design requirement and the ready for system test. The ultrasonic cleaning method is under evaluation and will be further studied for the gasifier simulator (hot model) application. The progress of this project has been on schedule.« less

TENSOR DECOMPOSITIONS AND SPARSE LOG-LINEAR MODELS

PubMed Central

Johndrow, James E.; Bhattacharya, Anirban; Dunson, David B.

2017-01-01

Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. We derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions. PMID:29332971

Prevalence of vitamin D deficiency and associated factors in women and newborns in the immediate postpartum period

PubMed Central

do Prado, Mara Rúbia Maciel Cardoso; Oliveira, Fabiana de Cássia Carvalho; Assis, Karine Franklin; Ribeiro, Sarah Aparecida Vieira; do Prado, Pedro Paulo; Sant'Ana, Luciana Ferreira da Rocha; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2015-01-01

Abstract Objective: To assess the prevalence of vitamin D deficiency and its associated factors in women and their newborns in the postpartum period. Methods: This cross-sectional study evaluated vitamin D deficiency/insufficiency in 226 women and their newborns in Viçosa (Minas Gerais, BR) between December 2011 and November 2012. Cord blood and venous maternal blood were collected to evaluate the following biochemical parameters: vitamin D, alkaline phosphatase, calcium, phosphorus and parathyroid hormone. Poisson regression analysis, with a confidence interval of 95%, was applied to assess vitamin D deficiency and its associated factors. Multiple linear regression analysis was performed to identify factors associated with 25(OH)D deficiency in the newborns and women from the study. The criteria for variable inclusion in the multiple linear regression model was the association with the dependent variable in the simple linear regression analysis, considering p<0.20. Significance level was α <5%. Results: From 226 women included, 200 (88.5%) were 20-44 years old; the median age was 28 years. Deficient/insufficient levels of vitamin D were found in 192 (85%) women and in 182 (80.5%) neonates. The maternal 25(OH)D and alkaline phosphatase levels were independently associated with vitamin D deficiency in infants. Conclusions: This study identified a high prevalence of vitamin D deficiency and insufficiency in women and newborns and the association between maternal nutritional status of vitamin D and their infants' vitamin D status. PMID:26100593

Dense grid sibling frames with linear phase filters

NASA Astrophysics Data System (ADS)

Abdelnour, Farras

2013-09-01

We introduce new 5-band dyadic sibling frames with dense time-frequency grid. Given a lowpass filter satisfying certain conditions, the remaining filters are obtained using spectral factorization. The analysis and synthesis filterbanks share the same lowpass and bandpass filters but have different and oversampled highpass filters. This leads to wavelets approximating shift-invariance. The filters are FIR, have linear phase, and the resulting wavelets have vanishing moments. The filters are designed using spectral factorization method. The proposed method leads to smooth limit functions with higher approximation order, and computationally stable filterbanks.

Comparing the Fit of Item Response Theory and Factor Analysis Models

ERIC Educational Resources Information Center

Maydeu-Olivares, Alberto; Cai, Li; Hernandez, Adolfo

2011-01-01

Linear factor analysis (FA) models can be reliably tested using test statistics based on residual covariances. We show that the same statistics can be used to reliably test the fit of item response theory (IRT) models for ordinal data (under some conditions). Hence, the fit of an FA model and of an IRT model to the same data set can now be…

Categorized or Continuous? Strength of an Association--And Linear Regression

ERIC Educational Resources Information Center

Drummond, Gordon B.; Vowler, Sarah L.

2012-01-01

In this article, the authors consider the possibility that groups could be different, because of the different conditions of a factor. This is as far as the analysis can extend: the consideration is restricted to groups characterized by the different category of the factor being considered. In many biological experiments, the factor considered may…

Attitudes Toward Seeking Professional Psychological Help: Factor Structure and Socio-Demographic Predictors

PubMed Central

Picco, Louisa; Abdin, Edimanysah; Chong, Siow Ann; Pang, Shirlene; Shafie, Saleha; Chua, Boon Yiang; Vaingankar, Janhavi A.; Ong, Lue Ping; Tay, Jenny; Subramaniam, Mythily

2016-01-01

Attitudes toward seeking professional psychological help (ATSPPH) are complex. Help seeking preferences are influenced by various attitudinal and socio-demographic factors and can often result in unmet needs, treatment gaps, and delays in help-seeking. The aims of the current study were to explore the factor structure of the ATSPPH short form (-SF) scale and determine whether any significant socio-demographic differences exist in terms of help-seeking attitudes. Data were extracted from a population-based survey conducted among Singapore residents aged 18–65 years. Respondents provided socio-demographic information and were administered the ATSPPH-SF. Weighted mean and standard error of the mean were calculated for continuous variables, and frequencies and percentages for categorical variables. Confirmatory factor analysis and exploratory factor analysis were performed to establish the validity of the factor structure of the ATSPPH-SF scale. Multivariable linear regressions were conducted to examine predictors of each of the ATSPPH-SF factors. The factor analysis revealed that the ATSPPH-SF formed three distinct dimensions: “Openness to seeking professional help,” “Value in seeking professional help,” and “Preference to cope on one's own.” Multiple linear regression analyses showed that age, ethnicity, marital status, education, and income were significantly associated with the ATSPPH-SF factors. Population subgroups that were less open to or saw less value in seeking psychological help should be targeted via culturally appropriate education campaigns and tailored and supportive interventions. PMID:27199794

Method for factor analysis of GC/MS data

DOEpatents

Van Benthem, Mark H; Kotula, Paul G; Keenan, Michael R

2012-09-11

The method of the present invention provides a fast, robust, and automated multivariate statistical analysis of gas chromatography/mass spectroscopy (GC/MS) data sets. The method can involve systematic elimination of undesired, saturated peak masses to yield data that follow a linear, additive model. The cleaned data can then be subjected to a combination of PCA and orthogonal factor rotation followed by refinement with MCR-ALS to yield highly interpretable results.

[Association between distribution of bacillary dysentery and meteorological factors in Beijing, 2004-2015].

PubMed

Du, Z; Zhang, J; Lu, J X; Lu, L P

2018-05-10

Objective: To analyze the distribution characteristics of bacillary dysentery in Beijing during 2004-2015 and evaluate the influence of meteorological factors on the temporal and spatial distribution of bacillary dysentery. Methods: The incidence data of bacterial dysentery and meteorological data in Beijing from 2004 to 2015 were collected. Descriptive epidemiological analysis was conducted to study the distribution characteristics of bacterial dysentery. Linear correlation analysis and multiple linear regression analysis were carried out to investigate the relationship between the incidence of bacillary dysentery and average precipitation, average air temperature, sunshine hours, average wind speed, average air pressure, gale and rain days. Results: A total of 280 704 cases of bacterial dysentery, including 36 deaths, were reported from 2004 to 2015 in Beijing, the average annual incidence was 130.15/100 000. The annual incidence peak was mainly between May and October, the cases occurred during this period accounted for 80.75 % of the total, and the incidence was highest in age group 0 year. The population distribution showed that most cases were children outside child care settings and students, and the sex ratio of the cases was 1.22∶1. The reported incidence of bacillary dysentery was positively associated with average precipitation, average air temperature and rain days with the correlation coefficients of 0.931, 0.878 and 0.888, but it was negatively associated with the average pressure, the correlation coefficient was -0.820. Multiple linear regression equation for fitting analysis of bacillary dysentery and meteorological factors was Y =3.792+0.162 X (1). Conclusion: The reported incidence of bacillary dysentery in Beijing was much higher than national level. The annual incidence peak was during July to August, and the average precipitation was an important meteorological factor influencing the incidence of bacillary dysentery.

Factors Affecting Online Groupwork Interest: A Multilevel Analysis

ERIC Educational Resources Information Center

Du, Jianxia; Xu, Jianzhong; Fan, Xitao

2013-01-01

The purpose of the present study is to examine the personal and contextual factors that may affect students' online groupwork interest. Using the data obtained from graduate students in an online course, both student- and group-level predictors for online groupwork interest were analyzed within the framework of hierarchical linear modeling…

Non-Linear Modeling of Growth Prerequisites in a Finnish Polytechnic Institution of Higher Education

ERIC Educational Resources Information Center

Nokelainen, Petri; Ruohotie, Pekka

2009-01-01

Purpose: This study aims to examine the factors of growth-oriented atmosphere in a Finnish polytechnic institution of higher education with categorical exploratory factor analysis, multidimensional scaling and Bayesian unsupervised model-based visualization. Design/methodology/approach: This study was designed to examine employee perceptions of…

Relative Velocity as a Metric for Probability of Collision Calculations

NASA Technical Reports Server (NTRS)

Frigm, Ryan Clayton; Rohrbaugh, Dave

2008-01-01

Collision risk assessment metrics, such as the probability of collision calculation, are based largely on assumptions about the interaction of two objects during their close approach. Specifically, the approach to probabilistic risk assessment can be performed more easily if the relative trajectories of the two close approach objects are assumed to be linear during the encounter. It is shown in this analysis that one factor in determining linearity is the relative velocity of the two encountering bodies, in that the assumption of linearity breaks down at low relative approach velocities. The first part of this analysis is the determination of the relative velocity threshold below which the assumption of linearity becomes invalid. The second part is a statistical study of conjunction interactions between representative asset spacecraft and the associated debris field environment to determine the likelihood of encountering a low relative velocity close approach. This analysis is performed for both the LEO and GEO orbit regimes. Both parts comment on the resulting effects to collision risk assessment operations.

[Approach to the Development of Mind and Persona].

PubMed

Sawaguchi, Toshiko

2018-01-01

To access medical specialists by health specialists working in the regional health field, the possibility of utilizing the voice approach for dissociative identity disorder (DID) patients as a health assessment for medical access (HAMA) was investigated. The first step is to investigate whether the plural personae in a single DID patient can be discriminated by voice analysis. Voices of DID patients including these with different personae were extracted from YouTube and were analysed using the software PRAAT with basic frequency, oral factors, chin factors and tongue factors. In addition, RAKUGO story teller voices made artificially and dramatically were analysed in the same manner. Quantitive and qualitative analysis method were carried out and nested logistic regression and a nested generalized linear model was developed. The voice from different personae in one DID patient could be visually and easily distinquished using basic frequency curve, cluster analysis and factor analysis. In the canonical analysis, only Roy's maximum root was <0.01. In the nested generalized linear model, the model using a standard deviation (SD) indicator fit best and some other possibilities are shown here. In DID patients, the short transition time among plural personae could guide to the risky situation such as suicide. So if the voice approach can show the time threshold of changes between the different personae, it would be useful as an Access Assessment in the form of a simple HAMA.

Geologic and mineral and water resources investigations in western Colorado using ERTS-1 data

NASA Technical Reports Server (NTRS)

Knepper, D. H., Jr. (Principal Investigator); Hutchinson, R. M.; Sawatzky, D. L.; Trexler, D. W.; Bruns, D. L.; Nicolais, S. M.

1973-01-01

The author has identified the following significant results. Topography was found to be the most important factor defining folds on ERTS-1 imagery of northwestern Colorado; tonal variations caused by rock reflectance and vegetation type and density are the next most important factors. Photo-linears mapped on ERTS-1 imagery of central Colorado correlate well with ground-measured joint and fracture trends. In addition, photo-linears have been successfully used to determine the location and distribution of metallic mineral deposits in the Colorado Mineral Belt. True color composites are best for general geologic analysis and false color composites prepared with positive/negative masks are useful for enhancing local geologic phenomena. During geologic analysis of any given area, ERTS-1 imagery from several different dates should be studied.

Serosal Laceration During Firing of Powered Linear Stapler Is a Predictor of Staple Malformation.

PubMed

Matsuzawa, Fumihiko; Homma, Shigenori; Yoshida, Tadashi; Konishi, Yuji; Shibasaki, Susumu; Ishikawa, Takahisa; Kawamura, Hideki; Takahashi, Norihiko; Iijima, Hiroaki; Taketomi, Akinobu

2017-12-01

Although several types of staplers have been developed, staple-line leaks have been a great problem in gastrointestinal surgery. Powered linear staplers were recently developed to further reduce the risk of tissue trauma during laparoscopic surgery. The aim of this study was to identify the factors that predict staple malformation and determine the effect of precompression and slow firing on the staple formation of this novel powered stapling method. Porcine stomachs were divided using an endoscopic powered linear stapler with gold reloads. We divided the specimens into 9 groups according to the precompression time (0/60/180 seconds) and firing time (0/60/180 seconds). The occurrence and length of laceration and the shape of the staples were evaluated. We examined the factors influencing successful stapling and investigated the key factors for staple malformation. Precompression significantly decreased the occurrence and length of serosal laceration. Precompression and slow firing significantly improved the optimal stapling formation rate. Univariate analysis showed that the precompression time (0 seconds), firing time (0 seconds), and presence of serosal laceration were significantly associated with a low optimal formation rate. Multivariate analysis showed that these three factors were associated independently with low optimal formation rate and that the presence of serosal laceration was the only factor that could be detected during the stapling procedure. We have shown that serosal laceration is a predictor of staple malformation and demonstrated the importance of precompression and slow stapling when using the powered stapling method.

Specific factors for prenatal lead exposure in the border area of China.

PubMed

Kawata, Kimiko; Li, Yan; Liu, Hao; Zhang, Xiao Qin; Ushijima, Hiroshi

2006-07-01

The objectives of this study are to examine the prevalence of increased blood lead concentrations in mothers and their umbilical cords, and to identify risk factors for prenatal lead exposure in Kunming city, Yunnan province, China. The study was conducted at two obstetrics departments, and 100 peripartum women were enrolled. The mean blood lead concentrations of the mothers and the umbilical cords were 67.3microg/l and 53.1microg/l, respectively. In multiple linear regression analysis, maternal occupational exposure, maternal consumption of homemade dehydrated vegetables and maternal habitation period in Kunming city were significantly associated with an increase of umbilical cord blood lead concentration. In addition, logistic regression analysis was used to assess the association of umbilical cord blood lead concentrations that possibly have adverse effects on brain development of newborns with each potential risk factor. Maternal frequent use of tableware with color patterns inside was significantly associated with higher cord blood lead concentration in addition to the three items in the multiple linear regression analysis. These points should be considered as specific recommendations for maternal and fetal lead exposure in this city.

The value of continuity: Refined isogeometric analysis and fast direct solvers

DOE PAGES

Garcia, Daniel; Pardo, David; Dalcin, Lisandro; ...

2016-08-24

Here, we propose the use of highly continuous finite element spaces interconnected with low continuity hyperplanes to maximize the performance of direct solvers. Starting from a highly continuous Isogeometric Analysis (IGA) discretization, we introduce C0-separators to reduce the interconnection between degrees of freedom in the mesh. By doing so, both the solution time and best approximation errors are simultaneously improved. We call the resulting method “refined Isogeometric Analysis (rIGA)”. To illustrate the impact of the continuity reduction, we analyze the number of Floating Point Operations (FLOPs), computational times, and memory required to solve the linear system obtained by discretizing themore » Laplace problem with structured meshes and uniform polynomial orders. Theoretical estimates demonstrate that an optimal continuity reduction may decrease the total computational time by a factor between p 2 and p 3, with pp being the polynomial order of the discretization. Numerical results indicate that our proposed refined isogeometric analysis delivers a speed-up factor proportional to p 2. In a 2D mesh with four million elements and p=5, the linear system resulting from rIGA is solved 22 times faster than the one from highly continuous IGA. In a 3D mesh with one million elements and p=3, the linear system is solved 15 times faster for the refined than the maximum continuity isogeometric analysis.« less

[Prevalence of vitamin D deficiency and associated factors in women and newborns in the immediate postpartum period].

PubMed

do Prado, Mara Rúbia Maciel Cardoso; Oliveira, Fabiana de Cássia Carvalho; Assis, Karine Franklin; Ribeiro, Sarah Aparecida Vieira; do Prado Junior, Pedro Paulo; Sant'Ana, Luciana Ferreira da Rocha; Priore, Silvia Eloiza; Franceschini, Sylvia do Carmo Castro

2015-01-01

To assess the prevalence of vitamin D deficiency and its associated factors in women and their newborns in the postpartum period. This cross-sectional study evaluated vitamin D deficiency/insufficiency in 226 women and their newborns in Viçosa (Minas Gerais, BR) between December 2011 and November 2012. Cord blood and venous maternal blood were collected to evaluate the following biochemical parameters: vitamin D, alkaline phosphatase, calcium, phosphorus and parathyroid hormone. Poisson regression analysis, with a confidence interval of 95% was applied to assess vitamin D deficiency and its associated factors. Multiple linear regression analysis was performed to identify factors associated with 25(OH)D deficiency in the newborns and women from the study. The criteria for variable inclusion in the multiple linear regression model was the association with the dependent variable in the simple linear regression analysis, considering p<0.20. Significance level was α<5%. From 226 women included, 200 (88.5%) were 20 to 44 years old; the median age was 28 years. Deficient/insufficient levels of vitamin D were found in 192 (85%) women and in 182 (80.5%) neonates. The maternal 25(OH)D and alkaline phosphatase levels were independently associated with vitamin D deficiency in infants. This study identified a high prevalence of vitamin D deficiency and insufficiency in women and newborns and the association between maternal nutritional status of vitamin D and their infants' vitamin D status. Copyright © 2015 Sociedade de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.

Using structural equation modeling for network meta-analysis.

PubMed

Tu, Yu-Kang; Wu, Yun-Chun

2017-07-14

Network meta-analysis overcomes the limitations of traditional pair-wise meta-analysis by incorporating all available evidence into a general statistical framework for simultaneous comparisons of several treatments. Currently, network meta-analyses are undertaken either within the Bayesian hierarchical linear models or frequentist generalized linear mixed models. Structural equation modeling (SEM) is a statistical method originally developed for modeling causal relations among observed and latent variables. As random effect is explicitly modeled as a latent variable in SEM, it is very flexible for analysts to specify complex random effect structure and to make linear and nonlinear constraints on parameters. The aim of this article is to show how to undertake a network meta-analysis within the statistical framework of SEM. We used an example dataset to demonstrate the standard fixed and random effect network meta-analysis models can be easily implemented in SEM. It contains results of 26 studies that directly compared three treatment groups A, B and C for prevention of first bleeding in patients with liver cirrhosis. We also showed that a new approach to network meta-analysis based on the technique of unrestricted weighted least squares (UWLS) method can also be undertaken using SEM. For both the fixed and random effect network meta-analysis, SEM yielded similar coefficients and confidence intervals to those reported in the previous literature. The point estimates of two UWLS models were identical to those in the fixed effect model but the confidence intervals were greater. This is consistent with results from the traditional pairwise meta-analyses. Comparing to UWLS model with common variance adjusted factor, UWLS model with unique variance adjusted factor has greater confidence intervals when the heterogeneity was larger in the pairwise comparison. The UWLS model with unique variance adjusted factor reflects the difference in heterogeneity within each comparison. SEM provides a very flexible framework for univariate and multivariate meta-analysis, and its potential as a powerful tool for advanced meta-analysis is still to be explored.

The Langley Stability and Transition Analysis Code (LASTRAC) : LST, Linear and Nonlinear PSE for 2-D, Axisymmetric, and Infinite Swept Wing Boundary Layers

NASA Technical Reports Server (NTRS)

Chang, Chau-Lyan

2003-01-01

During the past two decades, our understanding of laminar-turbulent transition flow physics has advanced significantly owing to, in a large part, the NASA program support such as the National Aerospace Plane (NASP), High-speed Civil Transport (HSCT), and Advanced Subsonic Technology (AST). Experimental, theoretical, as well as computational efforts on various issues such as receptivity and linear and nonlinear evolution of instability waves take part in broadening our knowledge base for this intricate flow phenomenon. Despite all these advances, transition prediction remains a nontrivial task for engineers due to the lack of a widely available, robust, and efficient prediction tool. The design and development of the LASTRAC code is aimed at providing one such engineering tool that is easy to use and yet capable of dealing with a broad range of transition related issues. LASTRAC was written from scratch based on the state-of-the-art numerical methods for stability analysis and modem software technologies. At low fidelity, it allows users to perform linear stability analysis and N-factor transition correlation for a broad range of flow regimes and configurations by using either the linear stability theory (LST) or linear parabolized stability equations (LPSE) method. At high fidelity, users may use nonlinear PSE to track finite-amplitude disturbances until the skin friction rise. Coupled with the built-in receptivity model that is currently under development, the nonlinear PSE method offers a synergistic approach to predict transition onset for a given disturbance environment based on first principles. This paper describes the governing equations, numerical methods, code development, and case studies for the current release of LASTRAC. Practical applications of LASTRAC are demonstrated for linear stability calculations, N-factor transition correlation, non-linear breakdown simulations, and controls of stationary crossflow instability in supersonic swept wing boundary layers.

Numerical Investigation of Crossflow Instability on the HIFiRE-5

NASA Astrophysics Data System (ADS)

Lakebrink, Matthew T.

Stability analysis was performed with the Langley Stability and Transition Analysis Code (LASTRAC) on a 38.1% scale model of the HIFiRE-5 elliptic-cone forebody to study crossflow-induced transition in hypersonic boundary layers. A resolution study consisting of three grids (30e6, 45e6, and 91e6 points) indicated that the fine grid was sufficiently resolved. Results were largely insensitive to grid resolution over the acreage and near the attachment line. The percent variation in second-mode properties along the semi-minor axis was less than 1% between the medium and fine grids. The variation in crossflow-wave properties was less than 0.04% between the medium and fine grids. Comparisons were made between crossflow-wave properties computed using quasi-parallel Linear Stability Theory (LST), the Linear Parabolized Stability Equations (LPSE), and surface marching or two-plane LPSE (2pLPSE). Sensitivity to marching path was also explored by performing analysis along Group-Velocity Lines (GVL) and Inviscid Streamlines (ISL). The wave properties were largely insensitive to analysis type and marching path, with the greatest variation near the attachment line. The LPSE-growth rates were as much as 20% greater than LST. Results from LPSE and 2pLPSE were similar except near the attachment line, where 2pLPSE growth rates were about 30% greater. Growth rates for crossflow and second-mode waves computed with 2pLPSE were compared to Spatial BiGlobal (SBG) analysis. Crossflow growth rates agreed well between 2pLPSE and SBG, indicating that the more expensive SBG approach is unnecessary for crossflow computation over the acreage. Second-mode growth rates along the attachment line had similar peak frequencies between the various methods, but 2pLPSE and LST growth rates were as much as 200% and 30% greater than SBG respectively. These results represent the first comparison between SBG and conventional techniques for crossflow waves, and help to define best practices for the use of each technique. Crossflow-wave computations were compared to measurements made by Dr. Matt Borg in the Boeing AFOSR Mach 6 Quiet Tunnel (BAM6QT). Linear analysis for wave angle, phase speed, peak frequency, and spanwise wavelength agreed well with the experiment for sufficiently low Reynolds numbers. The Reynolds number at which linear theory deviated from the test data was termed the 'linear limit'. A stationary-crossflow N-factor of 8.2 correlated well with the linear limit, as did a traveling-wave amplitude of about 1%. Experimental PSD data was used to identify the onset of turbulence at the downstream end of the model, and the associated stationary-crossflow N-factor based on LST was 9.4. Correlating to the linear limit provides a way to conservatively estimate crossflow-induced transition using LST. Evolution of the crossflow waves between the linear limit and the breakdown to turbulence was studied using Non-linear PSE (NPSE). By exciting a combination of stationary and traveling waves, naturally excited harmonics grew downstream of the linear limit to amplitudes of about 2% based on peak temperature. The wave angles of these harmonics agreed well with the test data. For reasons unknown, such agreement was not realized for phase speed. Initial-amplitude sweeps were performed for both stationary and traveling waves. Initial stationary-wave amplitude had a strong influence on the peak-harmonic amplitude and location of transition onset, while initial amplitude of the traveling-waves primarily influenced the location of transition onset. This is the first dataset from which detailed comparisons have been made between stability analysis and quiet tunnel data for crossflow waves in both the linear and non-linear stages of evolution. Several of these comparisons serve as validation of LASTRAC for crossflow-wave analysis. Finally, to aid the comparison of stability analysis to experimental data in general, the sensitivities of crossflow-wave evolution to small-yaw angles and changes in wall temperature were investigated. A yaw angle of 0.5 degrees resulted in a change in N-factor of about 1 between the same point on opposite halves of the geometry. A 15K increase in wall temperature led to a 0.1 increase in N-factor. These results, which are the first of their kind, highlight the sensitivity of crossflow waves to subtle changes in boundary conditions, and serve to emphasize the importance of high-quality test data for which flow conditions are recorded as precisely as possible.

Influencing factors of alexithymia in Chinese medical students: a cross-sectional study.

PubMed

Zhu, Yaxin; Luo, Ting; Liu, Jie; Qu, Bo

2017-04-04

A much higher prevalence of alexithymia has been reported in medical students compared with the general population, and alexithymia is a risk factor that increases vulnerability to mental disorders. Our aim was to evaluate the level of alexithymia in Chinese medical students and to explore its influencing factors. A cross-sectional study of 1,950 medical students at Shenyang Medical College was conducted in May 2014 to evaluate alexithymia in medical students using the Chinese version of the 20-item Toronto Alexithymia Scale (TAS-20). The reliability of the questionnaire was assessed by Cronbach's α coefficient and mean inter-item correlations. Confirmatory factor analysis (CFA) was used to evaluate construct validity. The relationships between alexithymia and influencing factors were examined using Student's t-test, analysis of variance, and multiple linear regression analysis. Statistical analysis was performed using SPSS 21.0. Of the 1,950 medical students, 1,886 (96.7%) completed questionnaires. Overall, Cronbach's α coefficient of the TAS-20 questionnaire was 0.868. The results of CFA showed that the original three-factor structure produced an acceptable fit to the data. By univariate analysis, gender, grade (academic year of study), smoking behavior, alcohol use, physical activity, history of living with parents during childhood, and childhood trauma were influencing factors of TAS-20 scores (p < 0.05). Multiple linear regression analysis showed that gender, physical activity, grade, living with parents, and childhood trauma also had statistically significant association with total TAS-20 score (p < 0.05). Gender, physical activity, grade, history of living with parents during childhood, and childhood trauma were all factors determining the level of alexithymia. To prevent alexithymia, it will be advisable to promote adequate physical activity and pay greater attention to male medical students and those who are in the final year of training.

Alternate Solution to Generalized Bernoulli Equations via an Integrating Factor: An Exact Differential Equation Approach

ERIC Educational Resources Information Center

Tisdell, C. C.

2017-01-01

Solution methods to exact differential equations via integrating factors have a rich history dating back to Euler (1740) and the ideas enjoy applications to thermodynamics and electromagnetism. Recently, Azevedo and Valentino presented an analysis of the generalized Bernoulli equation, constructing a general solution by linearizing the problem…

Young Children's Psychological Selves: Convergence with Maternal Reports of Child Personality

ERIC Educational Resources Information Center

Brown, Geoffrey L.; Mangelsdorf, Sarah C.; Agathen, Jean M.; Ho, Moon-Ho

2008-01-01

The present research examined five-year-old children's psychological self-concepts. Non-linear factor analysis was used to model the latent structure of the children's self-view questionnaire (CSVQ; Eder, 1990), a measure of children's self-concepts. The coherence and reliability of the emerging factor structure indicated that young children are…

Factors Predicting Science Achievement of Immigrant and Non-Immigrant Students: A Multilevel Analysis

ERIC Educational Resources Information Center

Areepattamannil, Shaljan; Kaur, Berinderjeet

2013-01-01

This study, employing hierarchical linear modeling (HLM), sought to investigate the student-level and school-level factors associated with the science achievement of immigrant and non-immigrant students among a national sample of 22,646 students from 896 schools in Canada. While student background characteristics such as home language, family…

The Effect of Sample Size on Parametric and Nonparametric Factor Analytical Methods

ERIC Educational Resources Information Center

Kalkan, Ömür Kaya; Kelecioglu, Hülya

2016-01-01

Linear factor analysis models used to examine constructs underlying the responses are not very suitable for dichotomous or polytomous response formats. The associated problems cannot be eliminated by polychoric or tetrachoric correlations in place of the Pearson correlation. Therefore, we considered parameters obtained from the NOHARM and FACTOR…

Effects of Initial Geometric Imperfections On the Non-Linear Response of the Space Shuttle Superlightweight Liquid-Oxygen Tank

NASA Technical Reports Server (NTRS)

Nemeth, Michael P.; Young, Richard D.; Collins, Timothy J.; Starnes, James H., Jr.

2002-01-01

The results of an analytical study of the elastic buckling and nonlinear behavior of the liquid-oxygen tank for the new Space Shuttle superlightweight external fuel tank are presented. Selected results that illustrate three distinctly different types of non-linear response phenomena for thin-walled shells which are subjected to combined mechanical and thermal loads are presented. These response phenomena consist of a bifurcation-type buckling response, a short-wavelength non-linear bending response and a non-linear collapse or "snap-through" response associated with a limit point. The effects of initial geometric imperfections on the response characteristics are emphasized. The results illustrate that the buckling and non-linear response of a geometrically imperfect shell structure subjected to complex loading conditions may not be adequately characterized by an elastic linear bifurcation buckling analysis, and that the traditional industry practice of applying a buckling-load knock-down factor can result in an ultraconservative design. Results are also presented that show that a fluid-filled shell can be highly sensitive to initial geometric imperfections, and that the use a buckling-load knock-down factor is needed for this case.

Quantifying the linear and nonlinear relations between the urban form fragmentation and the carbon emission distribution

NASA Astrophysics Data System (ADS)

Zuo, S.; Dai, S.; Ren, Y.; Yu, Z.

2017-12-01

Scientifically revealing the spatial heterogeneity and the relationship between the fragmentation of urban landscape and the direct carbon emissions are of great significance to land management and urban planning. In fact, the linear and nonlinear effects among the various factors resulted in the carbon emission spatial map. However, there is lack of the studies on the direct and indirect relations between the carbon emission and the city functional spatial form changes, which could not be reflected by the land use change. The linear strength and direction of the single factor could be calculated through the correlation and Geographically Weighted Regression (GWR) analysis, the nonlinear power of one factor and the interaction power of each two factors could be quantified by the Geodetector analysis. Therefore, we compared the landscape fragmentation metrics of the urban land cover and functional district patches to characterize the landscape form and then revealed the relations between the landscape fragmentation level and the direct the carbon emissions based on the three methods. The results showed that fragmentation decreased and the fragmented patches clustered at the coarser resolution. The direct CO2 emission density and the population density increased when the fragmentation level aggregated. The correlation analysis indicated the weak linear relation between them. The spatial variation of GWR output indicated the fragmentation indicator (MESH) had the positive influence on the carbon emission located in the relatively high emission region, and the negative effects regions accounted for the small part of the area. The Geodetector which explores the nonlinear relation identified the DIVISION and MESH as the most powerful direct factor for the land cover patches, NP and PD for the functional district patches, and the interactions between fragmentation indicator (MESH) and urban sprawl metrics (PUA and DIS) had the greatly increased explanation powers on the urban carbon emission. Overall, this study provides a framework to understand the relation between the urban landscape fragmentation and the carbon emission for the low carbon city construction planning in the other cities.

Impact of "JOBM": ISI Impact Factor Places the "Journal of Organizational Behavior Management" Third in Applied Psychology

ERIC Educational Resources Information Center

Hantula, Donald A.

2006-01-01

The ISI Impact Factor for "JOBM" is 1.793, placing it third in the JCR rankings for journals in applied psychology with a sharply accelerating linear trend over the past 5 years. This article reviews the Impact Factor and raises questions regarding its reliability and validity and then considers a citation analysis of "JOBM" in light of the…

Determination and analysis of non-linear index profiles in electron-beam-deposited MgOAl2O3ZrO2 ternary composite thin-film optical coatings

NASA Astrophysics Data System (ADS)

Sahoo, N. K.; Thakur, S.; Senthilkumar, M.; Das, N. C.

2005-02-01

Thickness-dependent index non-linearity in thin films has been a thought provoking as well as intriguing topic in the field of optical coatings. The characterization and analysis of such inhomogeneous index profiles pose several degrees of challenges to thin-film researchers depending upon the availability of relevant experimental and process-monitoring-related information. In the present work, a variety of novel experimental non-linear index profiles have been observed in thin films of MgOAl2O3ZrO2 ternary composites in solid solution under various electron-beam deposition parameters. Analysis and derivation of these non-linear spectral index profiles have been carried out by an inverse-synthesis approach using a real-time optical monitoring signal and post-deposition transmittance and reflection spectra. Most of the non-linear index functions are observed to fit polynomial equations of order seven or eight very well. In this paper, the application of such a non-linear index function has also been demonstrated in designing electric-field-optimized high-damage-threshold multilayer coatings such as normal- and oblique-incidence edge filters and a broadband beam splitter for p-polarized light. Such designs can also advantageously maintain the microstructural stability of the multilayer structure due to the low stress factor of the non-linear ternary composite layers.

Refinements of Stout’s Procedure for Assessing Latent Trait Unidimensionality

DTIC Science & Technology

1992-08-01

in the presence of guessing when coupled with many high-discriminating items. A revision of DIMTEST is proposed to overcome this limitation. Also, an...used for factor analysis. When guessing is present in the responses to items, however, linear factor analysis of tetrachoric correlations can produce...significance when d=1 and maintaining good power when d=2, even when the correlation between the abilities is as high as .7. The present study provides a

Understanding Child Stunting in India: A Comprehensive Analysis of Socio-Economic, Nutritional and Environmental Determinants Using Additive Quantile Regression

PubMed Central

Fenske, Nora; Burns, Jacob; Hothorn, Torsten; Rehfuess, Eva A.

2013-01-01

Background Most attempts to address undernutrition, responsible for one third of global child deaths, have fallen behind expectations. This suggests that the assumptions underlying current modelling and intervention practices should be revisited. Objective We undertook a comprehensive analysis of the determinants of child stunting in India, and explored whether the established focus on linear effects of single risks is appropriate. Design Using cross-sectional data for children aged 0–24 months from the Indian National Family Health Survey for 2005/2006, we populated an evidence-based diagram of immediate, intermediate and underlying determinants of stunting. We modelled linear, non-linear, spatial and age-varying effects of these determinants using additive quantile regression for four quantiles of the Z-score of standardized height-for-age and logistic regression for stunting and severe stunting. Results At least one variable within each of eleven groups of determinants was significantly associated with height-for-age in the 35% Z-score quantile regression. The non-modifiable risk factors child age and sex, and the protective factors household wealth, maternal education and BMI showed the largest effects. Being a twin or multiple birth was associated with dramatically decreased height-for-age. Maternal age, maternal BMI, birth order and number of antenatal visits influenced child stunting in non-linear ways. Findings across the four quantile and two logistic regression models were largely comparable. Conclusions Our analysis confirms the multifactorial nature of child stunting. It emphasizes the need to pursue a systems-based approach and to consider non-linear effects, and suggests that differential effects across the height-for-age distribution do not play a major role. PMID:24223839

Understanding child stunting in India: a comprehensive analysis of socio-economic, nutritional and environmental determinants using additive quantile regression.

PubMed

Fenske, Nora; Burns, Jacob; Hothorn, Torsten; Rehfuess, Eva A

2013-01-01

Most attempts to address undernutrition, responsible for one third of global child deaths, have fallen behind expectations. This suggests that the assumptions underlying current modelling and intervention practices should be revisited. We undertook a comprehensive analysis of the determinants of child stunting in India, and explored whether the established focus on linear effects of single risks is appropriate. Using cross-sectional data for children aged 0-24 months from the Indian National Family Health Survey for 2005/2006, we populated an evidence-based diagram of immediate, intermediate and underlying determinants of stunting. We modelled linear, non-linear, spatial and age-varying effects of these determinants using additive quantile regression for four quantiles of the Z-score of standardized height-for-age and logistic regression for stunting and severe stunting. At least one variable within each of eleven groups of determinants was significantly associated with height-for-age in the 35% Z-score quantile regression. The non-modifiable risk factors child age and sex, and the protective factors household wealth, maternal education and BMI showed the largest effects. Being a twin or multiple birth was associated with dramatically decreased height-for-age. Maternal age, maternal BMI, birth order and number of antenatal visits influenced child stunting in non-linear ways. Findings across the four quantile and two logistic regression models were largely comparable. Our analysis confirms the multifactorial nature of child stunting. It emphasizes the need to pursue a systems-based approach and to consider non-linear effects, and suggests that differential effects across the height-for-age distribution do not play a major role.

The association between meteorological factors and road traffic injuries: a case analysis from Shantou city, China

PubMed Central

Gao, Jinghong; Chen, Xiaojun; Woodward, Alistair; Liu, Xiaobo; Wu, Haixia; Lu, Yaogui; Li, Liping; Liu, Qiyong

2016-01-01

Few studies examined the associations of meteorological factors with road traffic injuries (RTIs). The purpose of the present study was to quantify the contributions of meteorological factors to RTI cases treated at a tertiary level hospital in Shantou city, China. A time-series diagram was employed to illustrate the time trends and seasonal variation of RTIs, and correlation analysis and multiple linear regression analysis were conducted to investigate the relationships between meteorological parameters and RTIs. RTIs followed a seasonal pattern as more cases occurred during summer and winter months. RTIs are positively correlated with temperature and sunshine duration, while negatively associated with wind speed. Temperature, sunshine hour and wind speed were included in the final linear model with regression coefficients of 0.65 (t = 2.36, P = 0.019), 2.23 (t = 2.72, P = 0.007) and −27.66 (t = −5.67, P < 0.001), respectively, accounting for 19.93% of the total variation of RTI cases. The findings can help us better understand the associations between meteorological factors and RTIs, and with potential contributions to the development and implementation of regional level evidence-based weather-responsive traffic management system in the future. PMID:27853316

MTF measurement and analysis of linear array HgCdTe infrared detectors

NASA Astrophysics Data System (ADS)

Zhang, Tong; Lin, Chun; Chen, Honglei; Sun, Changhong; Lin, Jiamu; Wang, Xi

2018-01-01

The slanted-edge technique is the main method for measurement detectors MTF, however this method is commonly used on planar array detectors. In this paper the authors present a modified slanted-edge method to measure the MTF of linear array HgCdTe detectors. Crosstalk is one of the major factors that degrade the MTF value of such an infrared detector. This paper presents an ion implantation guard-ring structure which was designed to effectively absorb photo-carriers that may laterally defuse between adjacent pixels thereby suppressing crosstalk. Measurement and analysis of the MTF of the linear array detectors with and without a guard-ring were carried out. The experimental results indicated that the ion implantation guard-ring structure effectively suppresses crosstalk and increases MTF value.

INNOVATIVE INSTRUMENTATION AND ANALYSIS OF THE TEMPERATURE MEASUREMENT FOR HIGH TEMPERATURE GASIFICATION

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

Seong W. Lee

2004-10-01

The systematic tests of the gasifier simulator on the clean thermocouple were completed in this reporting period. Within the systematic tests on the clean thermocouple, five (5) factors were considered as the experimental parameters including air flow rate, water flow rate, fine dust particle amount, ammonia addition and high/low frequency device (electric motor). The fractional factorial design method was used in the experiment design with sixteen (16) data sets of readings. Analysis of Variances (ANOVA) was applied to the results from systematic tests. The ANOVA results show that the un-balanced motor vibration frequency did not have the significant impact onmore » the temperature changes in the gasifier simulator. For the fine dust particles testing, the amount of fine dust particles has significant impact to the temperature measurements in the gasifier simulator. The effects of the air and water on the temperature measurements show the same results as reported in the previous report. The ammonia concentration was included as an experimental parameter for the reducing environment in this reporting period. The ammonia concentration does not seem to be a significant factor on the temperature changes. The linear regression analysis was applied to the temperature reading with five (5) factors. The accuracy of the linear regression is relatively low, which is less than 10% accuracy. Nonlinear regression was also conducted to the temperature reading with the same factors. Since the experiments were designed in two (2) levels, the nonlinear regression is not very effective with the dataset (16 readings). An extra central point test was conducted. With the data of the center point testing, the accuracy of the nonlinear regression is much better than the linear regression.« less

Applications of multivariate modeling to neuroimaging group analysis: A comprehensive alternative to univariate general linear model

PubMed Central

Chen, Gang; Adleman, Nancy E.; Saad, Ziad S.; Leibenluft, Ellen; Cox, RobertW.

2014-01-01

All neuroimaging packages can handle group analysis with t-tests or general linear modeling (GLM). However, they are quite hamstrung when there are multiple within-subject factors or when quantitative covariates are involved in the presence of a within-subject factor. In addition, sphericity is typically assumed for the variance–covariance structure when there are more than two levels in a within-subject factor. To overcome such limitations in the traditional AN(C)OVA and GLM, we adopt a multivariate modeling (MVM) approach to analyzing neuroimaging data at the group level with the following advantages: a) there is no limit on the number of factors as long as sample sizes are deemed appropriate; b) quantitative covariates can be analyzed together with within- subject factors; c) when a within-subject factor is involved, three testing methodologies are provided: traditional univariate testing (UVT)with sphericity assumption (UVT-UC) and with correction when the assumption is violated (UVT-SC), and within-subject multivariate testing (MVT-WS); d) to correct for sphericity violation at the voxel level, we propose a hybrid testing (HT) approach that achieves equal or higher power via combining traditional sphericity correction methods (Greenhouse–Geisser and Huynh–Feldt) with MVT-WS. PMID:24954281

Constrained Maximum Likelihood Estimation for Two-Level Mean and Covariance Structure Models

ERIC Educational Resources Information Center

Bentler, Peter M.; Liang, Jiajuan; Tang, Man-Lai; Yuan, Ke-Hai

2011-01-01

Maximum likelihood is commonly used for the estimation of model parameters in the analysis of two-level structural equation models. Constraints on model parameters could be encountered in some situations such as equal factor loadings for different factors. Linear constraints are the most common ones and they are relatively easy to handle in…

To bend or not to bend: electronic structural analysis of linear versus bent M-H-M interactions in dinickel bis(dialkylphosphino)methane complexes.

PubMed

Wilson, Zakiya S; Stanley, George G; Vicic, David A

2010-06-21

The M-H-M bonding in the dinuclear complexes Ni(2)(mu-H)(mu-P(2))(2)X(2) (P(2) = R(2)PCH(2)PR(2), R = iPr, Cy; X = Cl, Br) has been investigated. These dinickel A-frames were studied via density functional theory (DFT) calculations to analyze the factors that influence linear and bent M-H-M bonding. The DFT calculations indicate that the bent geometry is favored electronically, with ligand steric effects driving the formation of the linear M-H-M structures.

Response of dissolved trace metals to land use/land cover and their source apportionment using a receptor model in a subtropic river, China.

PubMed

Li, Siyue; Zhang, Quanfa

2011-06-15

Water samples were collected for determination of dissolved trace metals in 56 sampling sites throughout the upper Han River, China. Multivariate statistical analyses including correlation analysis, stepwise multiple linear regression models, and principal component and factor analysis (PCA/FA) were employed to examine the land use influences on trace metals, and a receptor model of factor analysis-multiple linear regression (FA-MLR) was used for source identification/apportionment of anthropogenic heavy metals in the surface water of the River. Our results revealed that land use was an important factor in water metals in the snow melt flow period and land use in the riparian zone was not a better predictor of metals than land use away from the river. Urbanization in a watershed and vegetation along river networks could better explain metals, and agriculture, regardless of its relative location, however slightly explained metal variables in the upper Han River. FA-MLR analysis identified five source types of metals, and mining, fossil fuel combustion, and vehicle exhaust were the dominant pollutions in the surface waters. The results demonstrated great impacts of human activities on metal concentrations in the subtropical river of China. Copyright © 2011 Elsevier B.V. All rights reserved.

Binding affinity toward human prion protein of some anti-prion compounds - Assessment based on QSAR modeling, molecular docking and non-parametric ranking.

PubMed

Kovačević, Strahinja; Karadžić, Milica; Podunavac-Kuzmanović, Sanja; Jevrić, Lidija

2018-01-01

The present study is based on the quantitative structure-activity relationship (QSAR) analysis of binding affinity toward human prion protein (huPrP C ) of quinacrine, pyridine dicarbonitrile, diphenylthiazole and diphenyloxazole analogs applying different linear and non-linear chemometric regression techniques, including univariate linear regression, multiple linear regression, partial least squares regression and artificial neural networks. The QSAR analysis distinguished molecular lipophilicity as an important factor that contributes to the binding affinity. Principal component analysis was used in order to reveal similarities or dissimilarities among the studied compounds. The analysis of in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) parameters was conducted. The ranking of the studied analogs on the basis of their ADMET parameters was done applying the sum of ranking differences, as a relatively new chemometric method. The main aim of the study was to reveal the most important molecular features whose changes lead to the changes in the binding affinities of the studied compounds. Another point of view on the binding affinity of the most promising analogs was established by application of molecular docking analysis. The results of the molecular docking were proven to be in agreement with the experimental outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

Collective Socialization and Child Conduct Problems: A Multilevel Analysis with an African American Sample

ERIC Educational Resources Information Center

Simons, Leslie Gordon; Simons, Ronald L.; Conger, Rand D.; Brody, Gene H.

2004-01-01

This article uses hierarchical linear modeling with a sample of African American children and their primary caregivers to examine the association between various community factors and child conduct problems. The analysis revealed a rather strong inverse association between level of collective socialization and conduct problems. This relationship…

Probability Distribution of Dose and Dose-Rate Effectiveness Factor for use in Estimating Risks of Solid Cancers From Exposure to Low-Let Radiation.

PubMed

Kocher, David C; Apostoaei, A Iulian; Hoffman, F Owen; Trabalka, John R

2018-06-01

This paper presents an analysis to develop a subjective state-of-knowledge probability distribution of a dose and dose-rate effectiveness factor for use in estimating risks of solid cancers from exposure to low linear energy transfer radiation (photons or electrons) whenever linear dose responses from acute and chronic exposure are assumed. A dose and dose-rate effectiveness factor represents an assumption that the risk of a solid cancer per Gy at low acute doses or low dose rates of low linear energy transfer radiation, RL, differs from the risk per Gy at higher acute doses, RH; RL is estimated as RH divided by a dose and dose-rate effectiveness factor, where RH is estimated from analyses of dose responses in Japanese atomic-bomb survivors. A probability distribution to represent uncertainty in a dose and dose-rate effectiveness factor for solid cancers was developed from analyses of epidemiologic data on risks of incidence or mortality from all solid cancers as a group or all cancers excluding leukemias, including (1) analyses of possible nonlinearities in dose responses in atomic-bomb survivors, which give estimates of a low-dose effectiveness factor, and (2) comparisons of risks in radiation workers or members of the public from chronic exposure to low linear energy transfer radiation at low dose rates with risks in atomic-bomb survivors, which give estimates of a dose-rate effectiveness factor. Probability distributions of uncertain low-dose effectiveness factors and dose-rate effectiveness factors for solid cancer incidence and mortality were combined using assumptions about the relative weight that should be assigned to each estimate to represent its relevance to estimation of a dose and dose-rate effectiveness factor. The probability distribution of a dose and dose-rate effectiveness factor for solid cancers developed in this study has a median (50th percentile) and 90% subjective confidence interval of 1.3 (0.47, 3.6). The harmonic mean is 1.1, which implies that the arithmetic mean of an uncertain estimate of the risk of a solid cancer per Gy at low acute doses or low dose rates of low linear energy transfer radiation is only about 10% less than the mean risk per Gy at higher acute doses. Data were also evaluated to define a low acute dose or low dose rate of low linear energy transfer radiation, i.e., a dose or dose rate below which a dose and dose-rate effectiveness factor should be applied in estimating risks of solid cancers.

Application of factor analysis of infrared spectra for quantitative determination of beta-tricalcium phosphate in calcium hydroxylapatite.

PubMed

Arsenyev, P A; Trezvov, V V; Saratovskaya, N V

1997-01-01

This work represents a method, which allows to determine phase composition of calcium hydroxylapatite basing on its infrared spectrum. The method uses factor analysis of the spectral data of calibration set of samples to determine minimal number of factors required to reproduce the spectra within experimental error. Multiple linear regression is applied to establish correlation between factor scores of calibration standards and their properties. The regression equations can be used to predict the property value of unknown sample. The regression model was built for determination of beta-tricalcium phosphate content in hydroxylapatite. Statistical estimation of quality of the model was carried out. Application of the factor analysis on spectral data allows to increase accuracy of beta-tricalcium phosphate determination and expand the range of determination towards its less concentration. Reproducibility of results is retained.

Alternate solution to generalized Bernoulli equations via an integrating factor: an exact differential equation approach

NASA Astrophysics Data System (ADS)

Tisdell, C. C.

2017-08-01

Solution methods to exact differential equations via integrating factors have a rich history dating back to Euler (1740) and the ideas enjoy applications to thermodynamics and electromagnetism. Recently, Azevedo and Valentino presented an analysis of the generalized Bernoulli equation, constructing a general solution by linearizing the problem through a substitution. The purpose of this note is to present an alternative approach using 'exact methods', illustrating that a substitution and linearization of the problem is unnecessary. The ideas may be seen as forming a complimentary and arguably simpler approach to Azevedo and Valentino that have the potential to be assimilated and adapted to pedagogical needs of those learning and teaching exact differential equations in schools, colleges, universities and polytechnics. We illustrate how to apply the ideas through an analysis of the Gompertz equation, which is of interest in biomathematical models of tumour growth.

Linear and nonlinear models for predicting fish bioconcentration factors for pesticides.

PubMed

Yuan, Jintao; Xie, Chun; Zhang, Ting; Sun, Jinfang; Yuan, Xuejie; Yu, Shuling; Zhang, Yingbiao; Cao, Yunyuan; Yu, Xingchen; Yang, Xuan; Yao, Wu

2016-08-01

This work is devoted to the applications of the multiple linear regression (MLR), multilayer perceptron neural network (MLP NN) and projection pursuit regression (PPR) to quantitative structure-property relationship analysis of bioconcentration factors (BCFs) of pesticides tested on Bluegill (Lepomis macrochirus). Molecular descriptors of a total of 107 pesticides were calculated with the DRAGON Software and selected by inverse enhanced replacement method. Based on the selected DRAGON descriptors, a linear model was built by MLR, nonlinear models were developed using MLP NN and PPR. The robustness of the obtained models was assessed by cross-validation and external validation using test set. Outliers were also examined and deleted to improve predictive power. Comparative results revealed that PPR achieved the most accurate predictions. This study offers useful models and information for BCF prediction, risk assessment, and pesticide formulation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effects of biomotor structures on performance of competitive gymnastics elements in elementary school male sixth-graders.

PubMed

Delas, Suncica; Zagorac, Nebojsa; Katić, Ratko

2008-06-01

In order to identify the biomotor systems that determine performance of competitive gymnastics elements in elementary school male sixth-graders, factor structures of morphological characteristics and basic motor abilities were determined first, followed by relations of the morphological-motor system factors obtained with a set of criterion variables evaluating specific motor skills in competitive gymnastics in 110 male children aged 12 years +/- 3 months. Factor analysis of 17 morphological measures produced three morphological factors: factor of mesoectoendomorphy (general morphological factor) and factor of pronounced endomorphy, i.e. excessive adipose tissue, along with low skeleton longitudinality. Factor analysis of 16 motor variables yielded four motor factors: factor of general motoricity; factor integrating leg flexibility and arm explosiveness; factor juxtaposing body flexibility and repetitive leg strength; and factor predominantly defining leg movement frequency. Three significant canonical correlations, i.e. linear combinations, explained the association between the set of six latent variables of the morphological and basic motor system, and five variables assessing the knowledge in competitive gymnastics. The first canonical linear combination was based on the favorable and predominant impact of the general motor factor (a system integrating leg explosiveness, whole body coordination, relative arm and trunk strength, and arm movement frequency), along with unfavorable effect of morphological factors on the gymnastics elements performance, squat vault and handstand in particular The relation of the second pair of canonical factors pointed to the effects of leg flexibility and arm explosiveness on the cartwheel and backward pullover mount performance, whereas the relation of the third pair of canonical factors showed a favorable impact of the general morphological factor and leg movement frequency regulator on the forward shoulderkip from increase, cartwheel and handstand performance.

Sufficient Forecasting Using Factor Models

PubMed Central

Fan, Jianqing; Xue, Lingzhou; Yao, Jiawei

2017-01-01

We consider forecasting a single time series when there is a large number of predictors and a possible nonlinear effect. The dimensionality was first reduced via a high-dimensional (approximate) factor model implemented by the principal component analysis. Using the extracted factors, we develop a novel forecasting method called the sufficient forecasting, which provides a set of sufficient predictive indices, inferred from high-dimensional predictors, to deliver additional predictive power. The projected principal component analysis will be employed to enhance the accuracy of inferred factors when a semi-parametric (approximate) factor model is assumed. Our method is also applicable to cross-sectional sufficient regression using extracted factors. The connection between the sufficient forecasting and the deep learning architecture is explicitly stated. The sufficient forecasting correctly estimates projection indices of the underlying factors even in the presence of a nonparametric forecasting function. The proposed method extends the sufficient dimension reduction to high-dimensional regimes by condensing the cross-sectional information through factor models. We derive asymptotic properties for the estimate of the central subspace spanned by these projection directions as well as the estimates of the sufficient predictive indices. We further show that the natural method of running multiple regression of target on estimated factors yields a linear estimate that actually falls into this central subspace. Our method and theory allow the number of predictors to be larger than the number of observations. We finally demonstrate that the sufficient forecasting improves upon the linear forecasting in both simulation studies and an empirical study of forecasting macroeconomic variables. PMID:29731537

Flexible modeling improves assessment of prognostic value of C-reactive protein in advanced non-small cell lung cancer.

PubMed

Gagnon, B; Abrahamowicz, M; Xiao, Y; Beauchamp, M-E; MacDonald, N; Kasymjanova, G; Kreisman, H; Small, D

2010-03-30

C-reactive protein (CRP) is gaining credibility as a prognostic factor in different cancers. Cox's proportional hazard (PH) model is usually used to assess prognostic factors. However, this model imposes a priori assumptions, which are rarely tested, that (1) the hazard ratio associated with each prognostic factor remains constant across the follow-up (PH assumption) and (2) the relationship between a continuous predictor and the logarithm of the mortality hazard is linear (linearity assumption). We tested these two assumptions of the Cox's PH model for CRP, using a flexible statistical model, while adjusting for other known prognostic factors, in a cohort of 269 patients newly diagnosed with non-small cell lung cancer (NSCLC). In the Cox's PH model, high CRP increased the risk of death (HR=1.11 per each doubling of CRP value, 95% CI: 1.03-1.20, P=0.008). However, both the PH assumption (P=0.033) and the linearity assumption (P=0.015) were rejected for CRP, measured at the initiation of chemotherapy, which kept its prognostic value for approximately 18 months. Our analysis shows that flexible modeling provides new insights regarding the value of CRP as a prognostic factor in NSCLC and that Cox's PH model underestimates early risks associated with high CRP.

Application of Exactly Linearized Error Transport Equations to AIAA CFD Prediction Workshops

NASA Technical Reports Server (NTRS)

Derlaga, Joseph M.; Park, Michael A.; Rallabhandi, Sriram

2017-01-01

The computational fluid dynamics (CFD) prediction workshops sponsored by the AIAA have created invaluable opportunities in which to discuss the predictive capabilities of CFD in areas in which it has struggled, e.g., cruise drag, high-lift, and sonic boom pre diction. While there are many factors that contribute to disagreement between simulated and experimental results, such as modeling or discretization error, quantifying the errors contained in a simulation is important for those who make decisions based on the computational results. The linearized error transport equations (ETE) combined with a truncation error estimate is a method to quantify one source of errors. The ETE are implemented with a complex-step method to provide an exact linearization with minimal source code modifications to CFD and multidisciplinary analysis methods. The equivalency of adjoint and linearized ETE functional error correction is demonstrated. Uniformly refined grids from a series of AIAA prediction workshops demonstrate the utility of ETE for multidisciplinary analysis with a connection between estimated discretization error and (resolved or under-resolved) flow features.

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.

Parental and Early Childhood Influences on Adolescent Obesity: A Longitudinal Study

ERIC Educational Resources Information Center

Chivers, Paola; Parker, Helen; Bulsara, Max; Beilin, Lawrence; Hands, Beth

2012-01-01

The influence of parental and early childhood factors on adolescent obesity was investigated using a longitudinal model of body mass index (BMI) from birth to 14 years. Trajectories of BMI using linear mixed model (LMM) analysis were used to investigate the influence of early parental and childhood factors on BMI at 14 years in the Raine birth…

What Do School Report Cards Really Tell Us? (An Analysis of the Relationships among Factors Commonly Reported in School District Report Cards).

ERIC Educational Resources Information Center

Bobbett, Gordon C.; And Others

The relationships among factors reported on school district (SD) report cards were studied for 121 Tennessee SDs. The report cards provided data on student outcomes (achievement test scores) and SD characteristics. Relationships were studied through linear regression, Pearson product moment correlation, and Guttman's partial correlation. Six…

Alcohol consumption and its related harms in The Netherlands since 1960: relationships with planned and unplanned factors.

PubMed

Knibbe, Ronald A; Derickx, Mieke; Allamani, Allaman; Massini, Giulia

2014-10-01

to establish which unplanned (social developments) and planned (alcohol policy measures) factors are related to per capita consumption and alcohol-related harms in the Netherlands. linear regression was used to establish which of the planned and unplanned factors were most strongly connected with alcohol consumption and harms. Artificial Neural Analysis (ANN) was used to inspect the interconnections between all variables. mothers age at birth was most strongly associated with increase in consumption. The ban on selling alcoholic beverages at petrol station was associated with a decrease in consumption. The linear regression of harms did not show any relation between alcohol policy measures and harms. The ANN-analyses indicate a very high interconnectedness between all variables allowing no causal inferences. Exceptions are the relation between price of beer and wine and the consumption of these beverages and the relation between a decrease in transport mortality and the increased use of breathalyzers tests and a restriction of paracommercial selling. unplanned factors are most strongly associated with per capita consumption and harms. ANN-analysis indicates that price of alcoholic beverages, breath testing, and restriction of sales may have had some influence. The study's limitations are noted.

Approximate Probabilistic Methods for Survivability/Vulnerability Analysis of Strategic Structures.

DTIC Science & Technology

1978-07-15

weapon yield, in kilotons; K = energy coupling factor; C = coefficient determined from linear regression; a, b = exponents determined from linear...hn(l + .582 00 = 0.54 In the case of the applied pressure, according to Perret and Bass (1975), the variabilities in the exponents a and b of Eq. 32...ATTN: WESSF, L. Ingram ATTN: ATC-T ATTN: Library ATTN: F. Brown BMD Systems Command ATTN: J. Strange Deoartment of the Army ATTN: BMDSC-H, N. Hurst

Stabilization and robustness of non-linear unity-feedback system - Factorization approach

NASA Technical Reports Server (NTRS)

Desoer, C. A.; Kabuli, M. G.

1988-01-01

The paper is a self-contained discussion of a right factorization approach in the stability analysis of the nonlinear continuous-time or discrete-time, time-invariant or time-varying, well-posed unity-feedback system S1(P, C). It is shown that a well-posed stable feedback system S1(P, C) implies that P and C have right factorizations. In the case where C is stable, P has a normalized right-coprime factorization. The factorization approach is used in stabilization and simultaneous stabilization results.

Simulating the effect of non-linear mode coupling in cosmological parameter estimation

NASA Astrophysics Data System (ADS)

Kiessling, A.; Taylor, A. N.; Heavens, A. F.

2011-09-01

Fisher Information Matrix methods are commonly used in cosmology to estimate the accuracy that cosmological parameters can be measured with a given experiment and to optimize the design of experiments. However, the standard approach usually assumes both data and parameter estimates are Gaussian-distributed. Further, for survey forecasts and optimization it is usually assumed that the power-spectrum covariance matrix is diagonal in Fourier space. However, in the low-redshift Universe, non-linear mode coupling will tend to correlate small-scale power, moving information from lower to higher order moments of the field. This movement of information will change the predictions of cosmological parameter accuracy. In this paper we quantify this loss of information by comparing naïve Gaussian Fisher matrix forecasts with a maximum likelihood parameter estimation analysis of a suite of mock weak lensing catalogues derived from N-body simulations, based on the SUNGLASS pipeline, for a 2D and tomographic shear analysis of a Euclid-like survey. In both cases, we find that the 68 per cent confidence area of the Ωm-σ8 plane increases by a factor of 5. However, the marginal errors increase by just 20-40 per cent. We propose a new method to model the effects of non-linear shear-power mode coupling in the Fisher matrix by approximating the shear-power distribution as a multivariate Gaussian with a covariance matrix derived from the mock weak lensing survey. We find that this approximation can reproduce the 68 per cent confidence regions of the full maximum likelihood analysis in the Ωm-σ8 plane to high accuracy for both 2D and tomographic weak lensing surveys. Finally, we perform a multiparameter analysis of Ωm, σ8, h, ns, w0 and wa to compare the Gaussian and non-linear mode-coupled Fisher matrix contours. The 6D volume of the 1σ error contours for the non-linear Fisher analysis is a factor of 3 larger than for the Gaussian case, and the shape of the 68 per cent confidence volume is modified. We propose that future Fisher matrix estimates of cosmological parameter accuracies should include mode-coupling effects.

Effects of biomotor structures on performance of competitive gymnastics elements in elementary school female sixth-graders.

PubMed

Delas, Suncica; Babin, Josip; Katić, Ratko

2007-12-01

In order to identify biomotor systems that determine performance of competitive gymnastics elements in elementary school female sixth-graders, factor structures of morphological characteristics and basic motor abilities were determined first, followed by relations of the morphological-motor system factors obtained with a set of criterion variables evaluating specific motor skills in competitive gymnastics in 126 female children aged 12 years +/- 3 months. Factor analysis of 17 morphological measures yielded three morphological factors: factor of mesoendomorphy and/or adipose body voluminosity; factor of longitudinal body dimensionality; and factor of transverse arm dimensionality. Factor analysis of 16 motor variables produced four motor factors: general motoricity factor (motor system); general speed factor; factor of explosive strength of throwing type (arm explosiveness); and factor of arm and leg flexibility. Three significant canonical correlations, i.e. linear combinations, explained the association between the set of seven latent variables of the morphological and basic motor system, and five variables evaluating the knowledge in competitive gymnastics. The first canonical linear combination was based on a favorable and predominant impact of the general motor factor (a system integrating whole body coordination, leg explosiveness, relative arm strength, arm movement frequency and body flexibility) on performance of gymnastics elements, cartwheel, handstand and backward pullover mount in particular, and to a lesser extent front scale and double leg pirouette for 180 degrees. The relation of the second pair of canonical factors additionally explained the role of transverse dimensionality of arm skeleton, arm flexibility and explosiveness in performing cartwheel and squat vault, whereas the relation of the third pair of canonical factors explained the unfavorable impact of adipose voluminosity on the performance of squat vault and backward pullover mount.

Parallel-vector solution of large-scale structural analysis problems on supercomputers

NASA Technical Reports Server (NTRS)

Storaasli, Olaf O.; Nguyen, Duc T.; Agarwal, Tarun K.

1989-01-01

A direct linear equation solution method based on the Choleski factorization procedure is presented which exploits both parallel and vector features of supercomputers. The new equation solver is described, and its performance is evaluated by solving structural analysis problems on three high-performance computers. The method has been implemented using Force, a generic parallel FORTRAN language.

Inverted Spring Pendulum Driven by a Periodic Force: Linear versus Nonlinear Analysis

ERIC Educational Resources Information Center

Arinstein, A.; Gitterman, M.

2008-01-01

We analyse the stability of the spring inverted pendulum with the vertical oscillations of the suspension point. An important factor in the stability analysis is the interaction between radial and oscillating modes. In addition to the small oscillations near the upper position, the nonlinearity of the problem leads to the appearance of limit-cycle…

Effective Use of Multimedia Presentations to Maximize Learning within High School Science Classrooms

ERIC Educational Resources Information Center

Rapp, Eric

2013-01-01

This research used an evidenced-based experimental 2 x 2 factorial design General Linear Model with Repeated Measures Analysis of Covariance (RMANCOVA). For this analysis, time served as the within-subjects factor while treatment group (i.e., static and signaling, dynamic and signaling, static without signaling, and dynamic without signaling)…

Four points function fitted and first derivative procedure for determining the end points in potentiometric titration curves: statistical analysis and method comparison.

PubMed

Kholeif, S A

2001-06-01

A new method that belongs to the differential category for determining the end points from potentiometric titration curves is presented. It uses a preprocess to find first derivative values by fitting four data points in and around the region of inflection to a non-linear function, and then locate the end point, usually as a maximum or minimum, using an inverse parabolic interpolation procedure that has an analytical solution. The behavior and accuracy of the sigmoid and cumulative non-linear functions used are investigated against three factors. A statistical evaluation of the new method using linear least-squares method validation and multifactor data analysis are covered. The new method is generally applied to symmetrical and unsymmetrical potentiometric titration curves, and the end point is calculated using numerical procedures only. It outperforms the "parent" regular differential method in almost all factors levels and gives accurate results comparable to the true or estimated true end points. Calculated end points from selected experimental titration curves compatible with the equivalence point category of methods, such as Gran or Fortuin, are also compared with the new method.

Langley Stability and Transition Analysis Code (LASTRAC) Version 1.2 User Manual

NASA Technical Reports Server (NTRS)

Chang, Chau-Lyan

2004-01-01

LASTRAC is a general-purposed, physics-based transition prediction code released by NASA for Laminar Flow Control studies and transition research. The design and development of the LASTRAC code is aimed at providing an engineering tool that is easy to use and yet capable of dealing with a broad range of transition related issues. It was written from scratch based on the state-of-the-art numerical methods for stability analysis and modern software technologies. At low fidelity, it allows users to perform linear stability analysis and N-factor transition correlation for a broad range of flow regimes and configurations by using either the linear stability theory or linear parabolized stability equations method. At high fidelity, users may use nonlinear PSE to track finite-amplitude disturbances until the skin friction rise. This document describes the governing equations, numerical methods, code development, detailed description of input/output parameters, and case studies for the current release of LASTRAC.

Intrinsic noise analysis and stochastic simulation on transforming growth factor beta signal pathway

NASA Astrophysics Data System (ADS)

Wang, Lu; Ouyang, Qi

2010-10-01

A typical biological cell lives in a small volume at room temperature; the noise effect on the cell signal transduction pathway may play an important role in its dynamics. Here, using the transforming growth factor-β signal transduction pathway as an example, we report our stochastic simulations of the dynamics of the pathway and introduce a linear noise approximation method to calculate the transient intrinsic noise of pathway components. We compare the numerical solutions of the linear noise approximation with the statistic results of chemical Langevin equations, and find that they are quantitatively in agreement with the other. When transforming growth factor-β dose decreases to a low level, the time evolution of noise fluctuation of nuclear Smad2—Smad4 complex indicates the abnormal enhancement in the transient signal activation process.

SU-E-T-627: Failure Modes and Effect Analysis for Monthly Quality Assurance of Linear Accelerator

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

Xie, J; Xiao, Y; Wang, J

2014-06-15

Purpose: To develop and implement a failure mode and effect analysis (FMEA) on routine monthly Quality Assurance (QA) tests (physical tests part) of linear accelerator. Methods: A systematic failure mode and effect analysis method was performed for monthly QA procedures. A detailed process tree of monthly QA was created and potential failure modes were defined. Each failure mode may have many influencing factors. For each factor, a risk probability number (RPN) was calculated from the product of probability of occurrence (O), the severity of effect (S), and detectability of the failure (D). The RPN scores are in a range ofmore » 1 to 1000, with higher scores indicating stronger correlation to a given influencing factor of a failure mode. Five medical physicists in our institution were responsible to discuss and to define the O, S, D values. Results: 15 possible failure modes were identified and all RPN scores of all influencing factors of these 15 failue modes were from 8 to 150, and the checklist of FMEA in monthly QA was drawn. The system showed consistent and accurate response to erroneous conditions. Conclusion: The influencing factors of RPN greater than 50 were considered as highly-correlated factors of a certain out-oftolerance monthly QA test. FMEA is a fast and flexible tool to develop an implement a quality management (QM) frame work of monthly QA, which improved the QA efficiency of our QA team. The FMEA work may incorporate more quantification and monitoring fuctions in future.« less

Multifactorial analysis of renal transplants reported to the United Network for Organ Sharing Registry: a 1994 update.

PubMed

Gjertson, D W

1994-01-01

1. From a multivariate log-linear analysis of 57,303 renal transplants between 1988 and 1994, the top 10 factors influencing one-year and 3-year cadaveric graft survival rates were ranked as follows: [table: see text] 2. Center effects accounted for 30% and 28% of all assignable variations in one-year and 3-year outcomes, respectively. Although center variation dominated 32 other variables, most factors were relatively independent of transplant center. 3. Novel to our own multifactorial analyses of the UNOS Kidney Transplant Registry were 6 pretransplant factors (recipient pretransplant dialysis, pregnancy, PRA technique, donor disposition and preservation, and ABO compatibility). Survival rates over the various combinations of these new factors were not significantly different. 4. For the first time in our multivariate analyses, 4 posttransplantation factors (delayed graft function, rejection episodes prior to discharge, induction and maintenance drug therapies) were included in the log-linear model. It is noteworthy that graft survival in both transplant periods was seriously imperiled following delayed graft function or rejection prior to discharge, yet the accounting for these pseudo-outcome variables did not alter the influence of the remaining 31 transplant factors. Finally, maintenance drug therapies strongly influenced short-term outcomes but did not influence long-term results, except for a noteworthy trend toward increased survival rates for FK506 therapy.

Product competitiveness analysis for e-commerce platform of special agricultural products

NASA Astrophysics Data System (ADS)

Wan, Fucheng; Ma, Ning; Yang, Dongwei; Xiong, Zhangyuan

2017-09-01

On the basis of analyzing the influence factors of the product competitiveness of the e-commerce platform of the special agricultural products and the characteristics of the analytical methods for the competitiveness of the special agricultural products, the price, the sales volume, the postage included service, the store reputation, the popularity, etc. were selected in this paper as the dimensionality for analyzing the competitiveness of the agricultural products, and the principal component factor analysis was taken as the competitiveness analysis method. Specifically, the web crawler was adopted to capture the information of various special agricultural products in the e-commerce platform ---- chi.taobao.com. Then, the original data captured thereby were preprocessed and MYSQL database was adopted to establish the information library for the special agricultural products. Then, the principal component factor analysis method was adopted to establish the analysis model for the competitiveness of the special agricultural products, and SPSS was adopted in the principal component factor analysis process to obtain the competitiveness evaluation factor system (support degree factor, price factor, service factor and evaluation factor) of the special agricultural products. Then, the linear regression method was adopted to establish the competitiveness index equation of the special agricultural products for estimating the competitiveness of the special agricultural products.

The Box-Cox power transformation on nursing sensitive indicators: Does it matter if structural effects are omitted during the estimation of the transformation parameter?

PubMed Central

2011-01-01

Background Many nursing and health related research studies have continuous outcome measures that are inherently non-normal in distribution. The Box-Cox transformation provides a powerful tool for developing a parsimonious model for data representation and interpretation when the distribution of the dependent variable, or outcome measure, of interest deviates from the normal distribution. The objectives of this study was to contrast the effect of obtaining the Box-Cox power transformation parameter and subsequent analysis of variance with or without a priori knowledge of predictor variables under the classic linear or linear mixed model settings. Methods Simulation data from a 3 × 4 factorial treatments design, along with the Patient Falls and Patient Injury Falls from the National Database of Nursing Quality Indicators (NDNQI®) for the 3rd quarter of 2007 from a convenience sample of over one thousand US hospitals were analyzed. The effect of the nonlinear monotonic transformation was contrasted in two ways: a) estimating the transformation parameter along with factors with potential structural effects, and b) estimating the transformation parameter first and then conducting analysis of variance for the structural effect. Results Linear model ANOVA with Monte Carlo simulation and mixed models with correlated error terms with NDNQI examples showed no substantial differences on statistical tests for structural effects if the factors with structural effects were omitted during the estimation of the transformation parameter. Conclusions The Box-Cox power transformation can still be an effective tool for validating statistical inferences with large observational, cross-sectional, and hierarchical or repeated measure studies under the linear or the mixed model settings without prior knowledge of all the factors with potential structural effects. PMID:21854614

The Box-Cox power transformation on nursing sensitive indicators: does it matter if structural effects are omitted during the estimation of the transformation parameter?

PubMed

Hou, Qingjiang; Mahnken, Jonathan D; Gajewski, Byron J; Dunton, Nancy

2011-08-19

Many nursing and health related research studies have continuous outcome measures that are inherently non-normal in distribution. The Box-Cox transformation provides a powerful tool for developing a parsimonious model for data representation and interpretation when the distribution of the dependent variable, or outcome measure, of interest deviates from the normal distribution. The objectives of this study was to contrast the effect of obtaining the Box-Cox power transformation parameter and subsequent analysis of variance with or without a priori knowledge of predictor variables under the classic linear or linear mixed model settings. Simulation data from a 3 × 4 factorial treatments design, along with the Patient Falls and Patient Injury Falls from the National Database of Nursing Quality Indicators (NDNQI® for the 3rd quarter of 2007 from a convenience sample of over one thousand US hospitals were analyzed. The effect of the nonlinear monotonic transformation was contrasted in two ways: a) estimating the transformation parameter along with factors with potential structural effects, and b) estimating the transformation parameter first and then conducting analysis of variance for the structural effect. Linear model ANOVA with Monte Carlo simulation and mixed models with correlated error terms with NDNQI examples showed no substantial differences on statistical tests for structural effects if the factors with structural effects were omitted during the estimation of the transformation parameter. The Box-Cox power transformation can still be an effective tool for validating statistical inferences with large observational, cross-sectional, and hierarchical or repeated measure studies under the linear or the mixed model settings without prior knowledge of all the factors with potential structural effects.

Use of factor scores for predicting body weight from linear body measurements in three South African indigenous chicken breeds.

PubMed

Malomane, Dorcus Kholofelo; Norris, David; Banga, Cuthbert B; Ngambi, Jones W

2014-02-01

Body weight and weight of body parts are of economic importance. It is difficult to directly predict body weight from highly correlated morphological traits through multiple regression. Factor analysis was carried out to examine the relationship between body weight and five linear body measurements (body length, body girth, wing length, shank thickness, and shank length) in South African Venda (VN), Naked neck (NN), and Potchefstroom koekoek (PK) indigenous chicken breeds, with a view to identify those factors that define body conformation. Multiple regression was subsequently performed to predict body weight, using orthogonal traits derived from the factor analysis. Measurements were obtained from 210 chickens, 22 weeks of age, 70 chickens per breed. High correlations were obtained between body weight and all body measurements except for wing length in PK. Two factors extracted after varimax rotation explained 91, 95, and 83% of total variation in VN, NN, and PK, respectively. Factor 1 explained 73, 90, and 64% in VN, NN, and PK, respectively, and was loaded on all body measurements except for wing length in VN and PK. In a multiple regression, these two factors accounted for 72% variation in body weight in VN, while only factor 1 accounted for 83 and 74% variation in body weight in NN and PK, respectively. The two factors could be used to define body size and conformation of these breeds. Factor 1 could predict body weight in all three breeds. Body measurements can be better selected jointly to improve body weight in these breeds.

The impact of intrinsic and extrinsic factors on the job satisfaction of dentists.

PubMed

Goetz, K; Campbell, S M; Broge, B; Dörfer, C E; Brodowski, M; Szecsenyi, J

2012-10-01

The Two-Factor Theory of job satisfaction distinguishes between intrinsic-motivation (i.e. recognition, responsibility) and extrinsic-hygiene (i.e. job security, salary, working conditions) factors. The presence of intrinsic-motivation facilitates higher satisfaction and performance, whereas the absences of extrinsic factors help mitigate against dissatisfaction. The consideration of these factors and their impact on dentists' job satisfaction is essential for the recruitment and retention of dentists. The objective of the study is to assess the level of job satisfaction of German dentists and the factors that are associated with it. This cross-sectional study was based on a job satisfaction survey. Data were collected from 147 dentists working in 106 dental practices. Job satisfaction was measured with the 10-item Warr-Cook-Wall job satisfaction scale. Organizational characteristics were measured with two items. Linear regression analyses were performed in which each of the nine items of the job satisfaction scale (excluding overall satisfaction) were handled as dependent variables. A stepwise linear regression analysis was performed with overall job satisfaction as the dependent outcome variable, the nine items of job satisfaction and the two items of organizational characteristics controlled for age and gender as predictors. The response rate was 95.0%. Dentists were satisfied with 'freedom of working method' and mostly dissatisfied with their 'income'. Both variables are extrinsic factors. The regression analyses identified five items that were significantly associated with each item of the job satisfaction scale: 'age', 'mean weekly working time', 'period in the practice', 'number of dentist's assistant' and 'working atmosphere'. Within the stepwise linear regression analysis the intrinsic factor 'opportunity to use abilities' (β = 0.687) showed the highest score of explained variance (R(2) = 0.468) regarding overall job satisfaction. With respect to the Two-Factor Theory of job satisfaction both components, intrinsic and extrinsic, are essential for dentists but the presence of intrinsic motivating factors like the opportunity to use abilities has most positive impact on job satisfaction. The findings of this study will be helpful for further activities to improve the working conditions of dentists and to ensure quality of care. © 2012 John Wiley & Sons A/S.

Public and Private School Distinction, Regional Development Differences, and Other Factors Influencing the Success of Primary School Students in Turkey

ERIC Educational Resources Information Center

Sulku, Seher Nur; Abdioglu, Zehra

2015-01-01

This study investigates the factors influencing the success of students in primary schools in Turkey. TIMSS 2011 data for Turkey, measuring the success of eighth-grade students in the field of mathematics, were used in an econometric analysis, performed using classical linear regression models. Two hundred thirty-nine schools participated in the…

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.

Deep data analysis via physically constrained linear unmixing: universal framework, domain examples, and a community-wide platform.

PubMed

Kannan, R; Ievlev, A V; Laanait, N; Ziatdinov, M A; Vasudevan, R K; Jesse, S; Kalinin, S V

2018-01-01

Many spectral responses in materials science, physics, and chemistry experiments can be characterized as resulting from the superposition of a number of more basic individual spectra. In this context, unmixing is defined as the problem of determining the individual spectra, given measurements of multiple spectra that are spatially resolved across samples, as well as the determination of the corresponding abundance maps indicating the local weighting of each individual spectrum. Matrix factorization is a popular linear unmixing technique that considers that the mixture model between the individual spectra and the spatial maps is linear. Here, we present a tutorial paper targeted at domain scientists to introduce linear unmixing techniques, to facilitate greater understanding of spectroscopic imaging data. We detail a matrix factorization framework that can incorporate different domain information through various parameters of the matrix factorization method. We demonstrate many domain-specific examples to explain the expressivity of the matrix factorization framework and show how the appropriate use of domain-specific constraints such as non-negativity and sum-to-one abundance result in physically meaningful spectral decompositions that are more readily interpretable. Our aim is not only to explain the off-the-shelf available tools, but to add additional constraints when ready-made algorithms are unavailable for the task. All examples use the scalable open source implementation from https://github.com/ramkikannan/nmflibrary that can run from small laptops to supercomputers, creating a user-wide platform for rapid dissemination and adoption across scientific disciplines.

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.

A practical guide to environmental association analysis in landscape genomics.

PubMed

Rellstab, Christian; Gugerli, Felix; Eckert, Andrew J; Hancock, Angela M; Holderegger, Rolf

2015-09-01

Landscape genomics is an emerging research field that aims to identify the environmental factors that shape adaptive genetic variation and the gene variants that drive local adaptation. Its development has been facilitated by next-generation sequencing, which allows for screening thousands to millions of single nucleotide polymorphisms in many individuals and populations at reasonable costs. In parallel, data sets describing environmental factors have greatly improved and increasingly become publicly accessible. Accordingly, numerous analytical methods for environmental association studies have been developed. Environmental association analysis identifies genetic variants associated with particular environmental factors and has the potential to uncover adaptive patterns that are not discovered by traditional tests for the detection of outlier loci based on population genetic differentiation. We review methods for conducting environmental association analysis including categorical tests, logistic regressions, matrix correlations, general linear models and mixed effects models. We discuss the advantages and disadvantages of different approaches, provide a list of dedicated software packages and their specific properties, and stress the importance of incorporating neutral genetic structure in the analysis. We also touch on additional important aspects such as sampling design, environmental data preparation, pooled and reduced-representation sequencing, candidate-gene approaches, linearity of allele-environment associations and the combination of environmental association analyses with traditional outlier detection tests. We conclude by summarizing expected future directions in the field, such as the extension of statistical approaches, environmental association analysis for ecological gene annotation, and the need for replication and post hoc validation studies. © 2015 John Wiley & Sons Ltd.

Analysis of Nuclear Factor-κB (NF-κB) Essential Modulator (NEMO) Binding to Linear and Lysine-linked Ubiquitin Chains and Its Role in the Activation of NF-κB*

PubMed Central

Kensche, Tobias; Tokunaga, Fuminori; Ikeda, Fumiyo; Goto, Eiji; Iwai, Kazuhiro; Dikic, Ivan

2012-01-01

Nuclear factor-κB (NF-κB) essential modulator (NEMO), a component of the inhibitor of κB kinase (IKK) complex, controls NF-κB signaling by binding to ubiquitin chains. Structural studies of NEMO provided a rationale for the specific binding between the UBAN (ubiquitin binding in ABIN and NEMO) domain of NEMO and linear (Met-1-linked) di-ubiquitin chains. Full-length NEMO can also interact with Lys-11-, Lys-48-, and Lys-63-linked ubiquitin chains of varying length in cells. Here, we show that purified full-length NEMO binds preferentially to linear ubiquitin chains in competition with lysine-linked ubiquitin chains of defined length, including long Lys-63-linked deca-ubiquitins. Linear di-ubiquitins were sufficient to activate both the IKK complex in vitro and to trigger maximal NF-κB activation in cells. In TNFα-stimulated cells, NEMO chimeras engineered to bind exclusively to Lys-63-linked ubiquitin chains mediated partial NF-κB activation compared with cells expressing NEMO that binds to linear ubiquitin chains. We propose that NEMO functions as a high affinity receptor for linear ubiquitin chains and a low affinity receptor for long lysine-linked ubiquitin chains. This phenomenon could explain quantitatively distinct NF-κB activation patterns in response to numerous cell stimuli. PMID:22605335

Convergence Estimates for Multidisciplinary Analysis and Optimization

NASA Technical Reports Server (NTRS)

Arian, Eyal

1997-01-01

A quantitative analysis of coupling between systems of equations is introduced. This analysis is then applied to problems in multidisciplinary analysis, sensitivity, and optimization. For the sensitivity and optimization problems both multidisciplinary and single discipline feasibility schemes are considered. In all these cases a "convergence factor" is estimated in terms of the Jacobians and Hessians of the system, thus it can also be approximated by existing disciplinary analysis and optimization codes. The convergence factor is identified with the measure for the "coupling" between the disciplines in the system. Applications to algorithm development are discussed. Demonstration of the convergence estimates and numerical results are given for a system composed of two non-linear algebraic equations, and for a system composed of two PDEs modeling aeroelasticity.

Quality of life in breast cancer patients--a quantile regression analysis.

PubMed

Pourhoseingholi, Mohamad Amin; Safaee, Azadeh; Moghimi-Dehkordi, Bijan; Zeighami, Bahram; Faghihzadeh, Soghrat; Tabatabaee, Hamid Reza; Pourhoseingholi, Asma

2008-01-01

Quality of life study has an important role in health care especially in chronic diseases, in clinical judgment and in medical resources supplying. Statistical tools like linear regression are widely used to assess the predictors of quality of life. But when the response is not normal the results are misleading. The aim of this study is to determine the predictors of quality of life in breast cancer patients, using quantile regression model and compare to linear regression. A cross-sectional study conducted on 119 breast cancer patients that admitted and treated in chemotherapy ward of Namazi hospital in Shiraz. We used QLQ-C30 questionnaire to assessment quality of life in these patients. A quantile regression was employed to assess the assocciated factors and the results were compared to linear regression. All analysis carried out using SAS. The mean score for the global health status for breast cancer patients was 64.92+/-11.42. Linear regression showed that only grade of tumor, occupational status, menopausal status, financial difficulties and dyspnea were statistically significant. In spite of linear regression, financial difficulties were not significant in quantile regression analysis and dyspnea was only significant for first quartile. Also emotion functioning and duration of disease statistically predicted the QOL score in the third quartile. The results have demonstrated that using quantile regression leads to better interpretation and richer inference about predictors of the breast cancer patient quality of life.

Development of parallel line analysis criteria for recombinant adenovirus potency assay and definition of a unit of potency.

PubMed

Ogawa, Yasushi; Fawaz, Farah; Reyes, Candice; Lai, Julie; Pungor, Erno

2007-01-01

Parameter settings of a parallel line analysis procedure were defined by applying statistical analysis procedures to the absorbance data from a cell-based potency bioassay for a recombinant adenovirus, Adenovirus 5 Fibroblast Growth Factor-4 (Ad5FGF-4). The parallel line analysis was performed with a commercially available software, PLA 1.2. The software performs Dixon outlier test on replicates of the absorbance data, performs linear regression analysis to define linear region of the absorbance data, and tests parallelism between the linear regions of standard and sample. Width of Fiducial limit, expressed as a percent of the measured potency, was developed as a criterion for rejection of the assay data and to significantly improve the reliability of the assay results. With the linear range-finding criteria of the software set to a minimum of 5 consecutive dilutions and best statistical outcome, and in combination with the Fiducial limit width acceptance criterion of <135%, 13% of the assay results were rejected. With these criteria applied, the assay was found to be linear over the range of 0.25 to 4 relative potency units, defined as the potency of the sample normalized to the potency of Ad5FGF-4 standard containing 6 x 10(6) adenovirus particles/mL. The overall precision of the assay was estimated to be 52%. Without the application of Fiducial limit width criterion, the assay results were not linear over the range, and an overall precision of 76% was calculated from the data. An absolute unit of potency for the assay was defined by using the parallel line analysis procedure as the amount of Ad5FGF-4 that results in an absorbance value that is 121% of the average absorbance readings of the wells containing cells not infected with the adenovirus.

Flexible modeling improves assessment of prognostic value of C-reactive protein in advanced non-small cell lung cancer

PubMed Central

Gagnon, B; Abrahamowicz, M; Xiao, Y; Beauchamp, M-E; MacDonald, N; Kasymjanova, G; Kreisman, H; Small, D

2010-01-01

Background: C-reactive protein (CRP) is gaining credibility as a prognostic factor in different cancers. Cox's proportional hazard (PH) model is usually used to assess prognostic factors. However, this model imposes a priori assumptions, which are rarely tested, that (1) the hazard ratio associated with each prognostic factor remains constant across the follow-up (PH assumption) and (2) the relationship between a continuous predictor and the logarithm of the mortality hazard is linear (linearity assumption). Methods: We tested these two assumptions of the Cox's PH model for CRP, using a flexible statistical model, while adjusting for other known prognostic factors, in a cohort of 269 patients newly diagnosed with non-small cell lung cancer (NSCLC). Results: In the Cox's PH model, high CRP increased the risk of death (HR=1.11 per each doubling of CRP value, 95% CI: 1.03–1.20, P=0.008). However, both the PH assumption (P=0.033) and the linearity assumption (P=0.015) were rejected for CRP, measured at the initiation of chemotherapy, which kept its prognostic value for approximately 18 months. Conclusion: Our analysis shows that flexible modeling provides new insights regarding the value of CRP as a prognostic factor in NSCLC and that Cox's PH model underestimates early risks associated with high CRP. PMID:20234363

Managerial and environmental factors in the continuity of mental health care across institutions.

PubMed

Greenberg, Greg A; Rosenheck, Robert A

2003-04-01

The authors examined the association of continuity of care with factors assumed to be under the control of health care administrators and environmental factors not under managerial control. The authors used a facility-level administrative data set for 139 Department of Veterans Affairs medical centers over a six-year period and supplemental data on environmental factors to conduct two types of analysis. First, simple correlations were used to examine bivariate associations between eight continuity-of-care measures and nine measures of the institutional environment and the social context. Second, to control for potential autocorrelation, multivariate hierarchical linear models with all nine independent measures were created. The strongest predictors of continuity of care were per capita outpatient expenditure and the degree of emphasis on outpatient care as measured by the percentage of all mental health expenditures devoted to outpatient care. The former was significantly associated with greater continuity of care on six of eight measures and the latter on seven of eight measures. The environmental factor of social capital (the degree of civic involvement and trust at the state level) was associated with greater continuity of care on five measures. The degree to which non-VA mental health services were funded in a state was unexpectedly found to be positively associated with greater continuity of care. In multivariate analysis using hierarchical linear modeling, significant relationships with continuity of care remained for per capita outpatient expenditures, overall outpatient emphasis, and social capital, but not for non-VA mental health funding. A linear term representing the year was positively and significantly associated with six of the eight examined continuity-of-care measures, indicating improvement in continuity of care for the period under study, although the explanation for this trend over time is unclear. Several factors potentially under managerial control are associated with increased mental health continuity of care.

Use of linear regression models to determine influence factors on the concentration levels of radon in occupied houses

NASA Astrophysics Data System (ADS)

Buermeyer, Jonas; Gundlach, Matthias; Grund, Anna-Lisa; Grimm, Volker; Spizyn, Alexander; Breckow, Joachim

2016-09-01

This work is part of the analysis of the effects of constructional energy-saving measures to radon concentration levels in dwellings performed on behalf of the German Federal Office for Radiation Protection. In parallel to radon measurements for five buildings, both meteorological data outside the buildings and the indoor climate factors were recorded. In order to access effects of inhabited buildings, the amount of carbon dioxide (CO2) was measured. For a statistical linear regression model, the data of one object was chosen as an example. Three dummy variables were extracted from the process of the CO2 concentration to provide information on the usage and ventilation of the room. The analysis revealed a highly autoregressive model for the radon concentration with additional influence by the natural environmental factors. The autoregression implies a strong dependency on a radon source since it reflects a backward dependency in time. At this point of the investigation, it cannot be determined whether the influence by outside factors affects the source of radon or the habitant’s ventilation behavior resulting in variation of the occurring concentration levels. In any case, the regression analysis might provide further information that would help to distinguish these effects. In the next step, the influence factors will be weighted according to their impact on the concentration levels. This might lead to a model that enables the prediction of radon concentration levels based on the measurement of CO2 in combination with environmental parameters, as well as the development of advices for ventilation.

Evaluation of beach cleanup effects using linear system analysis.

PubMed

Kataoka, Tomoya; Hinata, Hirofumi

2015-02-15

We established a method for evaluating beach cleanup effects (BCEs) based on a linear system analysis, and investigated factors determining BCEs. Here we focus on two BCEs: decreasing the total mass of toxic metals that could leach into a beach from marine plastics and preventing the fragmentation of marine plastics on the beach. Both BCEs depend strongly on the average residence time of marine plastics on the beach (τ(r)) and the period of temporal variability of the input flux of marine plastics (T). Cleanups on the beach where τ(r) is longer than T are more effective than those where τ(r) is shorter than T. In addition, both BCEs are the highest near the time when the remnants of plastics reach the local maximum (peak time). Therefore, it is crucial to understand the following three factors for effective cleanups: the average residence time, the plastic input period and the peak time. Copyright © 2014 Elsevier Ltd. All rights reserved.

Right-sizing statistical models for longitudinal data.

PubMed

Wood, Phillip K; Steinley, Douglas; Jackson, Kristina M

2015-12-01

Arguments are proposed that researchers using longitudinal data should consider more and less complex statistical model alternatives to their initially chosen techniques in an effort to "right-size" the model to the data at hand. Such model comparisons may alert researchers who use poorly fitting, overly parsimonious models to more complex, better-fitting alternatives and, alternatively, may identify more parsimonious alternatives to overly complex (and perhaps empirically underidentified and/or less powerful) statistical models. A general framework is proposed for considering (often nested) relationships between a variety of psychometric and growth curve models. A 3-step approach is proposed in which models are evaluated based on the number and patterning of variance components prior to selection of better-fitting growth models that explain both mean and variation-covariation patterns. The orthogonal free curve slope intercept (FCSI) growth model is considered a general model that includes, as special cases, many models, including the factor mean (FM) model (McArdle & Epstein, 1987), McDonald's (1967) linearly constrained factor model, hierarchical linear models (HLMs), repeated-measures multivariate analysis of variance (MANOVA), and the linear slope intercept (linearSI) growth model. The FCSI model, in turn, is nested within the Tuckerized factor model. The approach is illustrated by comparing alternative models in a longitudinal study of children's vocabulary and by comparing several candidate parametric growth and chronometric models in a Monte Carlo study. (c) 2015 APA, all rights reserved).

Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

2012-05-01

Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Assessment of the Uniqueness of Wind Tunnel Strain-Gage Balance Load Predictions

NASA Technical Reports Server (NTRS)

Ulbrich, N.

2016-01-01

A new test was developed to assess the uniqueness of wind tunnel strain-gage balance load predictions that are obtained from regression models of calibration data. The test helps balance users to gain confidence in load predictions of non-traditional balance designs. It also makes it possible to better evaluate load predictions of traditional balances that are not used as originally intended. The test works for both the Iterative and Non-Iterative Methods that are used in the aerospace testing community for the prediction of balance loads. It is based on the hypothesis that the total number of independently applied balance load components must always match the total number of independently measured bridge outputs or bridge output combinations. This hypothesis is supported by a control volume analysis of the inputs and outputs of a strain-gage balance. It is concluded from the control volume analysis that the loads and bridge outputs of a balance calibration data set must separately be tested for linear independence because it cannot always be guaranteed that a linearly independent load component set will result in linearly independent bridge output measurements. Simple linear math models for the loads and bridge outputs in combination with the variance inflation factor are used to test for linear independence. A highly unique and reversible mapping between the applied load component set and the measured bridge output set is guaranteed to exist if the maximum variance inflation factor of both sets is less than the literature recommended threshold of five. Data from the calibration of a six{component force balance is used to illustrate the application of the new test to real-world data.

Classification and regression tree analysis vs. multivariable linear and logistic regression methods as statistical tools for studying haemophilia.

PubMed

Henrard, S; Speybroeck, N; Hermans, C

2015-11-01

Haemophilia is a rare genetic haemorrhagic disease characterized by partial or complete deficiency of coagulation factor VIII, for haemophilia A, or IX, for haemophilia B. As in any other medical research domain, the field of haemophilia research is increasingly concerned with finding factors associated with binary or continuous outcomes through multivariable models. Traditional models include multiple logistic regressions, for binary outcomes, and multiple linear regressions for continuous outcomes. Yet these regression models are at times difficult to implement, especially for non-statisticians, and can be difficult to interpret. The present paper sought to didactically explain how, why, and when to use classification and regression tree (CART) analysis for haemophilia research. The CART method is non-parametric and non-linear, based on the repeated partitioning of a sample into subgroups based on a certain criterion. Breiman developed this method in 1984. Classification trees (CTs) are used to analyse categorical outcomes and regression trees (RTs) to analyse continuous ones. The CART methodology has become increasingly popular in the medical field, yet only a few examples of studies using this methodology specifically in haemophilia have to date been published. Two examples using CART analysis and previously published in this field are didactically explained in details. There is increasing interest in using CART analysis in the health domain, primarily due to its ease of implementation, use, and interpretation, thus facilitating medical decision-making. This method should be promoted for analysing continuous or categorical outcomes in haemophilia, when applicable. © 2015 John Wiley & Sons Ltd.

Extracting factors for interest rate scenarios

NASA Astrophysics Data System (ADS)

Molgedey, L.; Galic, E.

2001-04-01

Factor based interest rate models are widely used for risk managing purposes, for option pricing and for identifying and capturing yield curve anomalies. The movements of a term structure of interest rates are commonly assumed to be driven by a small number of orthogonal factors such as SHIFT, TWIST and BUTTERFLY (BOW). These factors are usually obtained by a Principal Component Analysis (PCA) of historical bond prices (interest rates). Although PCA diagonalizes the covariance matrix of either the interest rates or the interest rate changes, it does not use both covariance matrices simultaneously. Furthermore higher linear and nonlinear correlations are neglected. These correlations as well as the mean reverting properties of the interest rates become crucial, if one is interested in a longer time horizon (infrequent hedging or trading). We will show that Independent Component Analysis (ICA) is a more appropriate tool than PCA, since ICA uses the covariance matrix of the interest rates as well as the covariance matrix of the interest rate changes simultaneously. Additionally higher linear and nonlinear correlations may be easily incorporated. The resulting factors are uncorrelated for various time delays, approximately independent but nonorthogonal. This is in contrast to the factors obtained from the PCA, which are orthogonal and uncorrelated for identical times only. Although factors from the ICA are nonorthogonal, it is sufficient to consider only a few factors in order to explain most of the variation in the original data. Finally we will present examples that ICA based hedges outperforms PCA based hedges specifically if the portfolio is sensitive to structural changes of the yield curve.

Performance of an Axisymmetric Rocket Based Combined Cycle Engine During Rocket Only Operation Using Linear Regression Analysis

NASA Technical Reports Server (NTRS)

Smith, Timothy D.; Steffen, Christopher J., Jr.; Yungster, Shaye; Keller, Dennis J.

1998-01-01

The all rocket mode of operation is shown to be a critical factor in the overall performance of a rocket based combined cycle (RBCC) vehicle. An axisymmetric RBCC engine was used to determine specific impulse efficiency values based upon both full flow and gas generator configurations. Design of experiments methodology was used to construct a test matrix and multiple linear regression analysis was used to build parametric models. The main parameters investigated in this study were: rocket chamber pressure, rocket exit area ratio, injected secondary flow, mixer-ejector inlet area, mixer-ejector area ratio, and mixer-ejector length-to-inlet diameter ratio. A perfect gas computational fluid dynamics analysis, using both the Spalart-Allmaras and k-omega turbulence models, was performed with the NPARC code to obtain values of vacuum specific impulse. Results from the multiple linear regression analysis showed that for both the full flow and gas generator configurations increasing mixer-ejector area ratio and rocket area ratio increase performance, while increasing mixer-ejector inlet area ratio and mixer-ejector length-to-diameter ratio decrease performance. Increasing injected secondary flow increased performance for the gas generator analysis, but was not statistically significant for the full flow analysis. Chamber pressure was found to be not statistically significant.

Vitamin D insufficiency and subclinical atherosclerosis in non-diabetic males living with HIV.

PubMed

Portilla, Joaquín; Moreno-Pérez, Oscar; Serna-Candel, Carmen; Escoín, Corina; Alfayate, Rocio; Reus, Sergio; Merino, Esperanza; Boix, Vicente; Giner, Livia; Sánchez-Payá, José; Picó, Antonio

2014-01-01

Vitamin D insufficiency (VDI) has been associated with increased cardiovascular risk in the non-HIV population. This study evaluates the relationship among serum 25-hydroxyvitamin D [25(OH)D] levels, cardiovascular risk factors, adipokines, antiviral therapy (ART) and subclinical atherosclerosis in HIV-infected males. A cross-sectional study in ambulatory care was made in non-diabetic patients living with HIV. VDI was defined as 25(OH)D serum levels <75 nmol/L. Fasting lipids, glucose, inflammatory markers (tumour necrosis factor-α, interleukin-6, high-sensitivity C-reactive protein) and endothelial markers (plasminogen activator inhibitor-1, or PAI-I) were measured. The common carotid artery intima-media thickness (C-IMT) was determined. A multivariate logistic regression analysis was made to identify factors associated with the presence of VDI, while multivariate linear regression analysis was used to identify factors associated with common C-IMT. Eighty-nine patients were included (age 42 ± 8 years), 18.9% were in CDC (US Centers for Disease Control and Prevention) stage C and 75 were on ART. VDI was associated with ART exposure, sedentary lifestyle, higher triglycerides levels and PAI-I. In univariate analysis, VDI was associated with greater common C-IMT. The multivariate linear regression model, adjusted by confounding factors, revealed an independent association between common C-IMT and patient age, time of exposure to protease inhibitors (PIs) and impaired fasting glucose (IFG). In contrast, there were no independent associations between common C-IMT and VDI or inflammatory and endothelial markers. VDI was not independently associated with subclinical atherosclerosis in non-diabetic males living with HIV. Older age, a longer exposure to PIs, and IFG were independent factors associated with common C-IMT in this population.

Sarcopenia Impairs Prognosis of Patients with Hepatocellular Carcinoma: The Role of Liver Functional Reserve and Tumor-Related Factors in Loss of Skeletal Muscle Volume.

PubMed

Imai, Kenji; Takai, Koji; Watanabe, Satoshi; Hanai, Tatsunori; Suetsugu, Atsushi; Shiraki, Makoto; Shimizu, Masahito

2017-09-22

Sarcopenia impairs survival in patients with hepatocellular carcinoma (HCC). This study aimed to clarify the factors that contribute to decreased skeletal muscle volume in patients with HCC. The third lumbar vertebra skeletal muscle index (L3 SMI) in 351 consecutive patients with HCC was calculated to identify sarcopenia. Sarcopenia was defined as an L3 SMI value ≤ 29.0 cm²/m² for women and ≤ 36.0 cm²/m² for men. The factors affecting L3 SMI were analyzed by multiple linear regression analysis and tree-based models. Of the 351 HCC patients, 33 were diagnosed as having sarcopenia and showed poor prognosis compared with non-sarcopenia patients ( p = 0.007). However, this significant difference disappeared after the adjustments for age, sex, Child-Pugh score, maximum tumor size, tumor number, and the degree of portal vein invasion by propensity score matching analysis. Multiple linear regression analysis showed that age ( p = 0.015) and sex ( p < 0.0001) were significantly correlated with a decrease in L3 SMI. Tree-based models revealed that sex (female) is the most significant factor that affects L3 SMI. In male patients, L3 SMI was decreased by aging, increased Child-Pugh score (≥56 years), and enlarged tumor size (<56 years). Maintaining liver functional reserve and early diagnosis and therapy for HCC are vital to prevent skeletal muscle depletion and improve the prognosis of patients with HCC.

An exploratory analysis of treatment completion and client and organizational factors using hierarchical linear modeling.

PubMed

Woodward, Albert; Das, Abhik; Raskin, Ira E; Morgan-Lopez, Antonio A

2006-11-01

Data from the Alcohol and Drug Services Study (ADSS) are used to analyze the structure and operation of the substance abuse treatment industry in the United States. Published literature contains little systematic empirical analysis of the interaction between organizational characteristics and treatment outcomes. This paper addresses that deficit. It develops and tests a hierarchical linear model (HLM) to address questions about the empirical relationship between treatment inputs (industry costs, types and use of counseling and medical personnel, diagnosis mix, patient demographics, and the nature and level of services used in substance abuse treatment), and patient outcomes (retention and treatment completion rates). The paper adds to the literature by demonstrating a direct and statistically significant link between treatment completion and the organizational and staffing structure of the treatment setting. Related reimbursement issues, questions for future analysis, and limitations of the ADSS for this analysis are discussed.

The microcomputer scientific software series 3: general linear model--analysis of variance.

Treesearch

Harold M. Rauscher

1985-01-01

A BASIC language set of programs, designed for use on microcomputers, is presented. This set of programs will perform the analysis of variance for any statistical model describing either balanced or unbalanced designs. The program computes and displays the degrees of freedom, Type I sum of squares, and the mean square for the overall model, the error, and each factor...

Calculation of selective filters of a device for primary analysis of speech signals

NASA Astrophysics Data System (ADS)

Chudnovskii, L. S.; Ageev, V. M.

2014-07-01

The amplitude-frequency responses of filters for primary analysis of speech signals, which have a low quality factor and a high rolloff factor in the high-frequency range, are calculated using the linear theory of speech production and psychoacoustic measurement data. The frequency resolution of the filter system for a sinusoidal signal is 40-200 Hz. The modulation-frequency resolution of amplitude- and frequency-modulated signals is 3-6 Hz. The aforementioned features of the calculated filters are close to the amplitudefrequency responses of biological auditory systems at the level of the eighth nerve.

Large Spatial and Temporal Separations of Cause and Effect in Policy Making - Dealing with Non-linear Effects

NASA Astrophysics Data System (ADS)

McCaskill, John

There can be large spatial and temporal separation of cause and effect in policy making. Determining the correct linkage between policy inputs and outcomes can be highly impractical in the complex environments faced by policy makers. In attempting to see and plan for the probable outcomes, standard linear models often overlook, ignore, or are unable to predict catastrophic events that only seem improbable due to the issue of multiple feedback loops. There are several issues with the makeup and behaviors of complex systems that explain the difficulty many mathematical models (factor analysis/structural equation modeling) have in dealing with non-linear effects in complex systems. This chapter highlights those problem issues and offers insights to the usefulness of ABM in dealing with non-linear effects in complex policy making environments.

AN ENERGY SYSTEMS ANALYSIS OF CONSTRAINTS ON ECONOMIC DEVELOPMENT

EPA Science Inventory

There is a strong linear dependence of economic activity as measured by gross domestic product (GDP) on both the fossil fuel energy and the total emergy consumed by nations. Conceptual models of global and regional environmental systems were developed to examine the factors c...

Evaluation of Hepatic Steatosis by Using Acoustic Structure Quantification US in a Rat Model: Comparison with Pathologic Examination and MR Spectroscopy.

PubMed

Lee, Dong Ho; Lee, Jae Young; Lee, Kyung Bun; Han, Joon Koo

2017-11-01

Purpose To determine factors that significantly affect the focal disturbance (FD) ratio calculated with an acoustic structure quantification (ASQ) technique in a dietary-induced fatty liver disease rat model and to assess the diagnostic performance of the FD ratio in the assessment of hepatic steatosis by using histopathologic examination as a standard of reference. Materials and Methods Twenty-eight male F344 rats were fed a methionine-choline-deficient diet with a variable duration (3.5 days [half week] or 1, 2, 3, 4, 5, or 6 weeks; four rats in each group). A control group of four rats was maintained on a standard diet. At the end of each diet period, ASQ ultrasonography (US) and magnetic resonance (MR) spectroscopy were performed. Then, the rat was sacrificed and histopathologic examination of the liver was performed. Receiver operating characteristic curve analysis was performed to assess the diagnostic performance of the FD ratio in the evaluation of the degree of hepatic steatosis. The Spearman correlation coefficient was calculated to assess the correlation between the ordinal values, and multivariate linear regression analysis was used to identify significant determinant factors for the FD ratio. Results The diagnostic performance of the FD ratio in the assessment of the degree of hepatic steatosis (area under the receiver operating characteristic curve: 1.000 for 5%-33% steatosis, 0.981 for >33% to 66% steatosis, and 0.965 for >66% steatosis) was excellent and was comparable to that of MR spectroscopy. There was a strong negative linear correlation between the FD ratio and the estimated fat fraction at MR spectroscopy (Spearman ρ, -0.903; P < .001). Multivariate linear regression analysis showed that the degree of hepatic steatosis (P < .001) and fibrosis stage (P = .022) were significant factors affecting the FD ratio. Conclusion The FD ratio may potentially provide good diagnostic performance in the assessment of the degree of hepatic steatosis, with a strong negative linear correlation with the estimated fat fraction at MR spectroscopy. The degree of steatosis and stage of fibrosis at histopathologic examination were significant factors that affected the FD ratio. © RSNA, 2017 Online supplemental material is available for this article.

Analysis of a Single Hemodialysis on Phosphate Removal of the Internal Fistula Patients by Mathematical and Statistical Methods

PubMed Central

Yu, Qiyao; Bai, Yaling; Zhang, Junxia; Cui, Liwen; Zhang, Huiran; Xu, Jinsheng; Gao, Chao

2013-01-01

Chronic kidney disease related mineral and bone disease (CKD-MBD) is a worldwide challenge in hemodialysis patients. In china, the number of dialysis patients is growing but few data are available about their bone disorders. In the current study, we aimed to evaluate the effect of clinical factors on the serum phosphorus clearance in the 80 maintenance hemodialysis (MHD) patients. Six clinical factors were identified for their association with the serum phosphorus clearance using the analysis of Spearman's single linear correlation, including predialysis serum phosphate level, CRR, membrane surface area of the dialyzer, effective blood flow rate, the blood chamber volume, and hematocrit. In an overall multivariate analysis, pre-P, CRR, membrane SA, and Qb were identified as independent risk factors associated with the serum phosphorus clearance. In conclusion, HD could effectively clear serum phosphorus. The analysis of CRR might help to estimate serum phosphorus reduction ratio. PMID:24454542

Developing a Study Orientation Questionnaire in Mathematics for primary school students.

PubMed

Maree, Jacobus G; Van der Walt, Martha S; Ellis, Suria M

2009-04-01

The Study Orientation Questionnaire in Mathematics (Primary) is being developed as a diagnostic measure for South African teachers and counsellors to help primary school students improve their orientation towards the study of mathematics. In this study, participants were primary school students in the North-West Province of South Africa. During the standardisation in 2007, 1,013 students (538 boys: M age = 12.61; SD = 1.53; 555 girls: M age = 11.98; SD = 1.35; 10 missing values) were assessed. Factor analysis yielded three factors. Analysis also showed satisfactory reliability coefficients and item-factor correlations. Step-wise linear regression indicated that three factors (Mathematics anxiety, Study attitude in mathematics, and Study habits in mathematics) contributed significantly (R2 = .194) to predicting achievement in mathematics as measured by the Basic Mathematics Questionnaire (Primary).

Nursing Job Rotation Stress Scale development and psychometric evaluation.

PubMed

Huang, Shan; Lin, Yu-Hua; Kao, Chia-Chan; Yang, Hsing-Yu; Anne, Ya-Li; Wang, Cheng-Hua

2016-01-01

The aim of this study was to develop and assess the reliability and validity of the Nurse Job Rotation Stress Scale (NJRS). A convenience sampling method was utilized to recruit two groups of nurses (n = 150 and 253) from a 2751 bed medical center in southern Taiwan. The NJRS scale was developed and used to evaluate the NJRS. Explorative factor analysis revealed that three factors accounted for 74.11% of the explained variance. Confirmatory factor analysis validity testing supported the three factor structure and the construct validity. Cronbach's alpha for the 10 item model was 0.87 and had high linearity. The NJRS can be considered a reliable and valid scale for the measurement of nurse job rotation stress for nursing management and research purposes. © 2015 Japan Academy of Nursing Science.

Linear Combination Fitting (LCF)-XANES analysis of As speciation in selected mine-impacted materials

EPA Pesticide Factsheets

This table provides sample identification labels and classification of sample type (tailings, calcinated, grey slime). For each sample, total arsenic and iron concentrations determined by acid digestion and ICP analysis are provided along with arsenic in-vitro bioaccessibility (As IVBA) values to estimate arsenic risk. Lastly, the table provides linear combination fitting results from synchrotron XANES analysis showing the distribution of arsenic speciation phases present in each sample along with fitting error (R-factor).This dataset is associated with the following publication:Ollson, C., E. Smith, K. Scheckel, A. Betts, and A. Juhasz. Assessment of arsenic speciation and bioaccessibility in mine-impacted materials. Diana Aga, Wonyong Choi, Andrew Daugulis, Gianluca Li Puma, Gerasimos Lyberatos, and Joo Hwa Tay JOURNAL OF HAZARDOUS MATERIALS. Elsevier Science Ltd, New York, NY, USA, 313: 130-137, (2016).

The effect of changes in sea surface temperature on linear growth of Porites coral in Ambon Bay

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

Corvianawatie, Corry, E-mail: corvianawatie@students.itb.ac.id; Putri, Mutiara R., E-mail: mutiara.putri@fitb.itb.ac.id; Cahyarini, Sri Y., E-mail: yuda@geotek.lipi.go.id

Coral is one of the most important organisms in the coral reef ecosystem. There are several factors affecting coral growth, one of them is changes in sea surface temperature (SST). The purpose of this research is to understand the influence of SST variability on the annual linear growth of Porites coral taken from Ambon Bay. The annual coral linear growth was calculated and compared to the annual SST from the Extended Reconstructed Sea Surface Temperature version 3b (ERSST v3b) model. Coral growth was calculated by using Coral X-radiograph Density System (CoralXDS) software. Coral sample X-radiographs were used as input data.more » Chronology was developed by calculating the coral’s annual growth bands. A pair of high and low density banding patterns observed in the coral’s X-radiograph represent one year of coral growth. The results of this study shows that Porites coral extents from 2001-2009 and had an average growth rate of 1.46 cm/year. Statistical analysis shows that the annual coral linear growth declined by 0.015 cm/year while the annual SST declined by 0.013°C/year. SST and the annual linear growth of Porites coral in the Ambon Bay is insignificantly correlated with r=0.304 (n=9, p>0.05). This indicates that annual SST variability does not significantly influence the linear growth of Porites coral from Ambon Bay. It is suggested that sedimentation load, salinity, pH or other environmental factors may affect annual linear coral growth.« less

Critical analysis of commonly used fluorescence metrics to characterize dissolved organic matter.

PubMed

Korak, Julie A; Dotson, Aaron D; Summers, R Scott; Rosario-Ortiz, Fernando L

2014-02-01

The use of fluorescence spectroscopy for the analysis and characterization of dissolved organic matter (DOM) has gained widespread interest over the past decade, in part because of its ease of use and ability to provide bulk DOM chemical characteristics. However, the lack of standard approaches for analysis and data evaluation has complicated its use. This study utilized comparative statistics to systematically evaluate commonly used fluorescence metrics for DOM characterization to provide insight into the implications for data analysis and interpretation such as peak picking methods, carbon-normalized metrics and the fluorescence index (FI). The uncertainty associated with peak picking methods was evaluated, including the reporting of peak intensity and peak position. The linear relationship between fluorescence intensity and dissolved organic carbon (DOC) concentration was found to deviate from linearity at environmentally relevant concentrations and simultaneously across all peak regions. Comparative analysis suggests that the loss of linearity is composition specific and likely due to non-ideal intermolecular interactions of the DOM rather than the inner filter effects. For some DOM sources, Peak A deviated from linearity at optical densities a factor of 2 higher than that of Peak C. For carbon-normalized fluorescence intensities, the error associated with DOC measurements significantly decreases the ability to distinguish compositional differences. An in-depth analysis of FI determined that the metric is mostly driven by peak emission wavelength and less by emission spectra slope. This study also demonstrates that fluorescence intensity follows property balance principles, but the fluorescence index does not. Copyright © 2013 Elsevier Ltd. All rights reserved.

Some Statistics for Assessing Person-Fit Based on Continuous-Response Models

ERIC Educational Resources Information Center

Ferrando, Pere Joan

2010-01-01

This article proposes several statistics for assessing individual fit based on two unidimensional models for continuous responses: linear factor analysis and Samejima's continuous response model. Both models are approached using a common framework based on underlying response variables and are formulated at the individual level as fixed regression…

Identification of key factors affecting the water pollutant concentration in the sluice-controlled river reaches of the Shaying River in China via statistical analysis methods.

PubMed

Dou, Ming; Zhang, Yan; Zuo, Qiting; Mi, Qingbin

2015-08-01

The construction of sluices creates a strong disturbance in water environmental factors within a river. The change in water pollutant concentrations of sluice-controlled river reaches (SCRRs) is more complex than that of natural river segments. To determine the key factors affecting water pollutant concentration changes in SCRRs, river reaches near the Huaidian Sluice in the Shaying River of China were selected as a case study, and water quality monitoring experiments based on different regulating modes were implemented in 2009 and 2010. To identify the key factors affecting the change rates for the chemical oxygen demand of permanganate (CODMn) and ammonia nitrogen (NH3-N) concentrations in the SCRRs of the Huaidian Sluice, partial correlation analysis, principal component analysis and principal factor analysis were used. The results indicate four factors, i.e., the inflow quantity from upper reaches, opening size of sluice gates, water pollutant concentration from upper reaches, and turbidity before the sluice, which are the common key factors for the CODMn and NH3-N concentration change rates. Moreover, the dissolved oxygen before a sluice is a key factor for the permanganate concentration from CODMn change rate, and the water depth before a sluice is a key factor for the NH3-N concentration change rate. Multiple linear regressions between the water pollutant concentration change rate and key factors were established via multiple linear regression analyses, and the quantitative relationship between the CODMn and NH3-N concentration change rates and key affecting factors was analyzed. Finally, the mechanism of action for the key factors affecting the water pollutant concentration changes was analyzed. The results reveal that the inflow quantity from upper reaches, opening size of sluice gates, permanganate concentration from CODMn from upper reaches and dissolved oxygen before the sluice have a negative influence and the turbidity before the sluice has a positive influence on the permanganate concentration from CODMn change rates and that the opening size of sluice gates, NH3-N concentration from upper reaches, and water depth before the sluice have a negative influence and the inflow quantity from upper reaches and turbidity before the sluice have a positive influence on the NH3-N concentration change rates, which provides a scientific grounding for pollution control and sluice operations in SCRRs.

Three-dimensional analysis of surface crack-Hertzian stress field interaction

NASA Technical Reports Server (NTRS)

Ballarini, R.; Hsu, Y.

1989-01-01

The results are presented of a stress intensity factor analysis of semicircular surface cracks in the inner raceway of an engine bearing. The loading consists of a moving spherical Hertzian contact load and an axial stress due to rotation and shrink fit. A 3-D linear elastic Boundary Element Method code was developed to perform the stress analysis. The element library includes linear and quadratic isoparametric surface elements. Singular quarter point elements were employed to capture the square root displacement variation and the inverse square root stress singularity along the crack front. The program also possesses the capability to separate the whole domain into two subregions. This procedure enables one to solve nonsymmetric fracture mechanics problems without having to separate the crack surfaces a priori. A wide range of configuration parameters was investigated. The ratio of crack depth to bearing thickness was varied from one-sixtieth to one-fifth for several different locations of the Hertzian load. The stress intensity factors for several crack inclinations were also investigated. The results demonstrate the efficiency and accuracy of the Boundary Element Method. Moreover, the results can provide the basis for crack growth calculations and fatigue life prediction.

Plasma apelin levels, blood pressure and cardiovascular risk factors in a coastal Chinese population.

PubMed

Zhu, Pengli; Huang, Feng; Lin, Fan; Yuan, Yin; Chen, Falin; Li, Qiaowei

2013-11-01

To describe the relationship of plasma apelin levels with blood pressure in a coastal Chinese population. This cross-sectional study included a total of 1031 subjects from the coastal areas of China. One-way analysis of variance (ANOVA) and linear trend test, Pearson's correlation analysis, as well as multivariate linear regression analysis were used to evaluate the association between plasma apelin levels and blood pressure. Plasma apelin levels dropped with increasing quartiles of systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial blood pressure (MABP) (all P<0.001). SBP, DBP, and MABP values decreased as the apelin levels increased within the quartiles. After adjusting for age and gender, the significant differences in SBP, DBP, and MABP between the groups within the apelin quartiles remained (all P<0.05). A significant negative correlation between SBP, DBP, as well as MABP and apelin levels was observed (all P<0.01); even after adjusting for cardiovascular confounding factors, this negative correlation remained (all P<0.001). A negative correlation between plasma apelin levels and blood pressure was found in this 1000-population-based epidemiological study. Apelin may become a potential therapeutic target of anti-hypertensive treatment.

A single-degree-of-freedom model for non-linear soil amplification

USGS Publications Warehouse

Erdik, Mustafa Ozder

1979-01-01

For proper understanding of soil behavior during earthquakes and assessment of a realistic surface motion, studies of the large-strain dynamic response of non-linear hysteretic soil systems are indispensable. Most of the presently available studies are based on the assumption that the response of a soil deposit is mainly due to the upward propagation of horizontally polarized shear waves from the underlying bedrock. Equivalent-linear procedures, currently in common use in non-linear soil response analysis, provide a simple approach and have been favorably compared with the actual recorded motions in some particular cases. Strain compatibility in these equivalent-linear approaches is maintained by selecting values of shear moduli and damping ratios in accordance with the average soil strains, in an iterative manner. Truly non-linear constitutive models with complete strain compatibility have also been employed. The equivalent-linear approaches often raise some doubt as to the reliability of their results concerning the system response in high frequency regions. In these frequency regions the equivalent-linear methods may underestimate the surface motion by as much as a factor of two or more. Although studies are complete in their methods of analysis, they inevitably provide applications pertaining only to a few specific soil systems, and do not lead to general conclusions about soil behavior. This report attempts to provide a general picture of the soil response through the use of a single-degree-of-freedom non-linear-hysteretic model. Although the investigation is based on a specific type of nonlinearity and a set of dynamic soil properties, the method described does not limit itself to these assumptions and is equally applicable to other types of nonlinearity and soil parameters.

Parallel-vector computation for linear structural analysis and non-linear unconstrained optimization problems

NASA Technical Reports Server (NTRS)

Nguyen, D. T.; Al-Nasra, M.; Zhang, Y.; Baddourah, M. A.; Agarwal, T. K.; Storaasli, O. O.; Carmona, E. A.

1991-01-01

Several parallel-vector computational improvements to the unconstrained optimization procedure are described which speed up the structural analysis-synthesis process. A fast parallel-vector Choleski-based equation solver, pvsolve, is incorporated into the well-known SAP-4 general-purpose finite-element code. The new code, denoted PV-SAP, is tested for static structural analysis. Initial results on a four processor CRAY 2 show that using pvsolve reduces the equation solution time by a factor of 14-16 over the original SAP-4 code. In addition, parallel-vector procedures for the Golden Block Search technique and the BFGS method are developed and tested for nonlinear unconstrained optimization. A parallel version of an iterative solver and the pvsolve direct solver are incorporated into the BFGS method. Preliminary results on nonlinear unconstrained optimization test problems, using pvsolve in the analysis, show excellent parallel-vector performance indicating that these parallel-vector algorithms can be used in a new generation of finite-element based structural design/analysis-synthesis codes.

Non-linear effects of the built environment on automobile-involved pedestrian crash frequency: A machine learning approach.

PubMed

Ding, Chuan; Chen, Peng; Jiao, Junfeng

2018-03-01

Although a growing body of literature focuses on the relationship between the built environment and pedestrian crashes, limited evidence is provided about the relative importance of many built environment attributes by accounting for their mutual interaction effects and their non-linear effects on automobile-involved pedestrian crashes. This study adopts the approach of Multiple Additive Poisson Regression Trees (MAPRT) to fill such gaps using pedestrian collision data collected from Seattle, Washington. Traffic analysis zones are chosen as the analytical unit. The effects of various factors on pedestrian crash frequency investigated include characteristics the of road network, street elements, land use patterns, and traffic demand. Density and the degree of mixed land use have major effects on pedestrian crash frequency, accounting for approximately 66% of the effects in total. More importantly, some factors show clear non-linear relationships with pedestrian crash frequency, challenging the linearity assumption commonly used in existing studies which employ statistical models. With various accurately identified non-linear relationships between the built environment and pedestrian crashes, this study suggests local agencies to adopt geo-spatial differentiated policies to establish a safe walking environment. These findings, especially the effective ranges of the built environment, provide evidence to support for transport and land use planning, policy recommendations, and road safety programs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Healthcare Expenditures Associated with Depression Among Individuals with Osteoarthritis: Post-Regression Linear Decomposition Approach.

PubMed

Agarwal, Parul; Sambamoorthi, Usha

2015-12-01

Depression is common among individuals with osteoarthritis and leads to increased healthcare burden. The objective of this study was to examine excess total healthcare expenditures associated with depression among individuals with osteoarthritis in the US. Adults with self-reported osteoarthritis (n = 1881) were identified using data from the 2010 Medical Expenditure Panel Survey (MEPS). Among those with osteoarthritis, chi-square tests and ordinary least square regressions (OLS) were used to examine differences in healthcare expenditures between those with and without depression. Post-regression linear decomposition technique was used to estimate the relative contribution of different constructs of the Anderson's behavioral model, i.e., predisposing, enabling, need, personal healthcare practices, and external environment factors, to the excess expenditures associated with depression among individuals with osteoarthritis. All analysis accounted for the complex survey design of MEPS. Depression coexisted among 20.6 % of adults with osteoarthritis. The average total healthcare expenditures were $13,684 among adults with depression compared to $9284 among those without depression. Multivariable OLS regression revealed that adults with depression had 38.8 % higher healthcare expenditures (p < 0.001) compared to those without depression. Post-regression linear decomposition analysis indicated that 50 % of differences in expenditures among adults with and without depression can be explained by differences in need factors. Among individuals with coexisting osteoarthritis and depression, excess healthcare expenditures associated with depression were mainly due to comorbid anxiety, chronic conditions and poor health status. These expenditures may potentially be reduced by providing timely intervention for need factors or by providing care under a collaborative care model.

Operator Factorization and the Solution of Second-Order Linear Ordinary Differential Equations

ERIC Educational Resources Information Center

Robin, W.

2007-01-01

The theory and application of second-order linear ordinary differential equations is reviewed from the standpoint of the operator factorization approach to the solution of ordinary differential equations (ODE). Using the operator factorization approach, the general second-order linear ODE is solved, exactly, in quadratures and the resulting…

Non-Linearity in Wide Dynamic Range CMOS Image Sensors Utilizing a Partial Charge Transfer Technique.

PubMed

Shafie, Suhaidi; Kawahito, Shoji; Halin, Izhal Abdul; Hasan, Wan Zuha Wan

2009-01-01

The partial charge transfer technique can expand the dynamic range of a CMOS image sensor by synthesizing two types of signal, namely the long and short accumulation time signals. However the short accumulation time signal obtained from partial transfer operation suffers of non-linearity with respect to the incident light. In this paper, an analysis of the non-linearity in partial charge transfer technique has been carried, and the relationship between dynamic range and the non-linearity is studied. The results show that the non-linearity is caused by two factors, namely the current diffusion, which has an exponential relation with the potential barrier, and the initial condition of photodiodes in which it shows that the error in the high illumination region increases as the ratio of the long to the short accumulation time raises. Moreover, the increment of the saturation level of photodiodes also increases the error in the high illumination region.

Alcohol consumption and all-cause mortality.

PubMed

Duffy, J C

1995-02-01

Prospective studies of alcohol and mortality in middle-aged men almost universally find a U-shaped relationship between alcohol consumption and risk of mortality. This review demonstrates the extent to which different studies lead to different risk estimates, analyses the putative influence of abstention as a risk factor and uses available data to produce point and interval estimates of the consumption level apparently associated with minimum risk from two studies in the UK. Data from a number of studies are analysed by means of logistic-linear modelling, taking account of the possible influence of abstention as a special risk factor. Separate analysis of British data is performed. Logistic-linear modelling demonstrates large and highly significant differences between the studies considered in the relationship between alcohol consumption and all-cause mortality. The results support the identification of abstention as a special risk factor for mortality, but do not indicate that this alone explains the apparent U-shaped relationship. Separate analysis of two British studies indicates minimum risk of mortality in this population at a consumption level of about 26 (8.5 g) units of alcohol per week. The analysis supports the view that abstention may be a specific risk factor for all-cause mortality, but is not an adequate explanation of the apparent protective effect of alcohol consumption against all-cause mortality. Future analyses might better be performed on a case-by-case basis, using a change-point model to estimate the parameters of the relationship. The current misinterpretation of the sensible drinking level of 21 units per week for men in the UK as a limit is not justified, and the data suggest that alcohol consumption is a net preventive factor against premature death in this population.

Attitudes toward abortion among students at the University of Cape Coast, Ghana.

PubMed

Rominski, Sarah D; Darteh, Eugene; Dickson, Kwamena Sekyi; Munro-Kramer, Michelle

2017-03-01

This study aimed to describe the attitudes toward abortion of Ghanaian University students and to determine factors which are associated with supporting a woman's right to an abortion. This cross-sectional survey was administered to residential students at the University of Cape Coast. Participants were posed a series of 26 statements to determine to what extent they were supportive of abortion as a woman's right. An exploratory factor analysis was used to create a scale with the pertinent factors that relate to abortion attitudes and a multivariable linear regression model explored the relationships among significant variables noted during exploratory factor analysis. 1038 students completed the survey and these students had a generally negative view of abortion. Two factors emerged: (1) the Abortion as a Right scale consisted of five questions (α = .755) and (2) the Moral Objection to Abortion scale consisted of three questions (α = .740). In linear regression, being older (β = 1.9), sexually experienced (β = 1.2), having a boyfriend/girlfriend (β = 1.4), and knowing someone who has terminated a pregnancy (β = 1.1) were significantly associated with a more liberal view of a right to an abortion. This work supports the idea that students who have personal exposure to an abortion experience hold more liberal views on abortion than those who have not had a similar exposure. Copyright © 2016 Elsevier B.V. All rights reserved.

Fasting insulin levels and metabolic risk factors in type 2 diabetic patients at the first visit in Japan: a 10-year, nationwide, observational study (JDDM 28).

PubMed

Matsuba, Ikuro; Saito, Kazumi; Takai, Masahiko; Hirao, Koichi; Sone, Hirohito

2012-09-01

To investigate the relationship between fasting insulin levels and metabolic risk factors (MRFs) in type 2 diabetic patients at the first clinic/hospital visit in Japan over the years 2000 to 2009. In total, 4,798 drug-naive Japanese patients with type 2 diabetes were registered on their first clinic/hospital visits. Conventional clinical factors and fasting insulin levels were observed at baseline within the Japan Diabetes Clinical Data Management (JDDM) study between consecutive 2-year groups. Multiple linear regression analysis was performed using a model in which the dependent variable was fasting insulin values using various clinical explanatory variables. Fasting insulin levels were found to be decreasing from 2000 to 2009. Multiple linear regression analysis with the fasting insulin levels as the dependent variable showed that waist circumference (WC), BMI, mean blood pressure, triglycerides, and HDL cholesterol were significant, with WC and BMI as the main factors. ANCOVA after adjustment for age and fasting plasma glucose clearly shows the decreasing trend in fasting insulin levels and the increasing trend in BMI. During the 10-year observation period, the decreasing trend in fasting insulin was related to the slight increase in WC/BMI in type 2 diabetes. Low pancreatic β-cell reserve on top of a lifestyle background might be dependent on an increase in MRFs.

Fasting Insulin Levels and Metabolic Risk Factors in Type 2 Diabetic Patients at the First Visit in Japan

PubMed Central

Matsuba, Ikuro; Saito, Kazumi; Takai, Masahiko; Hirao, Koichi; Sone, Hirohito

2012-01-01

OBJECTIVE To investigate the relationship between fasting insulin levels and metabolic risk factors (MRFs) in type 2 diabetic patients at the first clinic/hospital visit in Japan over the years 2000 to 2009. RESEARCH DESIGN AND METHODS In total, 4,798 drug-naive Japanese patients with type 2 diabetes were registered on their first clinic/hospital visits. Conventional clinical factors and fasting insulin levels were observed at baseline within the Japan Diabetes Clinical Data Management (JDDM) study between consecutive 2-year groups. Multiple linear regression analysis was performed using a model in which the dependent variable was fasting insulin values using various clinical explanatory variables. RESULTS Fasting insulin levels were found to be decreasing from 2000 to 2009. Multiple linear regression analysis with the fasting insulin levels as the dependent variable showed that waist circumference (WC), BMI, mean blood pressure, triglycerides, and HDL cholesterol were significant, with WC and BMI as the main factors. ANCOVA after adjustment for age and fasting plasma glucose clearly shows the decreasing trend in fasting insulin levels and the increasing trend in BMI. CONCLUSIONS During the 10-year observation period, the decreasing trend in fasting insulin was related to the slight increase in WC/BMI in type 2 diabetes. Low pancreatic β-cell reserve on top of a lifestyle background might be dependent on an increase in MRFs. PMID:22665215

Short-term effects of meteorological factors on hand, foot and mouth disease among children in Shenzhen, China: Non-linearity, threshold and interaction.

PubMed

Zhang, Zhen; Xie, Xu; Chen, Xiliang; Li, Yuan; Lu, Yan; Mei, Shujiang; Liao, Yuxue; Lin, Hualiang

2016-01-01

Various meteorological factors have been associated with hand, foot and mouth disease (HFMD) among children; however, fewer studies have examined the non-linearity and interaction among the meteorological factors. A generalized additive model with a log link allowing Poisson auto-regression and over-dispersion was applied to investigate the short-term effects daily meteorological factors on children HFMD with adjustment of potential confounding factors. We found positive effects of mean temperature and wind speed, the excess relative risk (ERR) was 2.75% (95% CI: 1.98%, 3.53%) for one degree increase in daily mean temperature on lag day 6, and 3.93% (95% CI: 2.16% to 5.73%) for 1m/s increase in wind speed on lag day 3. We found a non-linear effect of relative humidity with thresholds with the low threshold at 45% and high threshold at 85%, within which there was positive effect, the ERR was 1.06% (95% CI: 0.85% to 1.27%) for 1 percent increase in relative humidity on lag day 5. No significant effect was observed for rainfall and sunshine duration. For the interactive effects, we found a weak additive interaction between mean temperature and relative humidity, and slightly antagonistic interaction between mean temperature and wind speed, and between relative humidity and wind speed in the additive models, but the interactions were not statistically significant. This study suggests that mean temperature, relative humidity and wind speed might be risk factors of children HFMD in Shenzhen, and the interaction analysis indicates that these meteorological factors might have played their roles individually. Copyright © 2015 Elsevier B.V. All rights reserved.

Stirling System Modeling for Space Nuclear Power Systems

NASA Technical Reports Server (NTRS)

Lewandowski, Edward J.; Johnson, Paul K.

2008-01-01

A dynamic model of a high-power Stirling convertor has been developed for space nuclear power systems modeling. The model is based on the Component Test Power Convertor (CTPC), a 12.5-kWe free-piston Stirling convertor. The model includes the fluid heat source, the Stirling convertor, output power, and heat rejection. The Stirling convertor model includes the Stirling cycle thermodynamics, heat flow, mechanical mass-spring damper systems, and the linear alternator. The model was validated against test data. Both nonlinear and linear versions of the model were developed. The linear version algebraically couples two separate linear dynamic models; one model of the Stirling cycle and one model of the thermal system, through the pressure factors. Future possible uses of the Stirling system dynamic model are discussed. A pair of commercially available 1-kWe Stirling convertors is being purchased by NASA Glenn Research Center. The specifications of those convertors may eventually be incorporated into the dynamic model and analysis compared to the convertor test data. Subsequent potential testing could include integrating the convertors into a pumped liquid metal hot-end interface. This test would provide more data for comparison to the dynamic model analysis.

Investigation of Periodic Nuclear Decay Data with Spectral Analysis Techniques

NASA Astrophysics Data System (ADS)

Javorsek, D.; Sturrock, P.; Buncher, J.; Fischbach, E.; Gruenwald, T.; Hoft, A.; Horan, T.; Jenkins, J.; Kerford, J.; Lee, R.; Mattes, J.; Morris, D.; Mudry, R.; Newport, J.; Petrelli, M.; Silver, M.; Stewart, C.; Terry, B.; Willenberg, H.

2009-12-01

We provide the results from a spectral analysis of nuclear decay experiments displaying unexplained periodic fluctuations. The analyzed data was from 56Mn decay reported by the Children's Nutrition Research Center in Houston, 32Si decay reported by an experiment performed at the Brookhaven National Laboratory, and 226Ra decay reported by an experiment performed at the Physikalisch-Technische-Bundesanstalt in Germany. All three data sets possess the same primary frequency mode consisting of an annual period. Additionally a spectral comparison of the local ambient temperature, atmospheric pressure, relative humidity, Earth-Sun distance, and the plasma speed and latitude of the heliospheric current sheet (HCS) was performed. Following analysis of these six possible causal factors, their reciprocals, and their linear combinations, a possible link between nuclear decay rate fluctuations and the linear combination of the HCS latitude and 1/R motivates searching for a possible mechanism with such properties.

Hierarchical Bayes approach for subgroup analysis.

PubMed

Hsu, Yu-Yi; Zalkikar, Jyoti; Tiwari, Ram C

2017-01-01

In clinical data analysis, both treatment effect estimation and consistency assessment are important for a better understanding of the drug efficacy for the benefit of subjects in individual subgroups. The linear mixed-effects model has been used for subgroup analysis to describe treatment differences among subgroups with great flexibility. The hierarchical Bayes approach has been applied to linear mixed-effects model to derive the posterior distributions of overall and subgroup treatment effects. In this article, we discuss the prior selection for variance components in hierarchical Bayes, estimation and decision making of the overall treatment effect, as well as consistency assessment of the treatment effects across the subgroups based on the posterior predictive p-value. Decision procedures are suggested using either the posterior probability or the Bayes factor. These decision procedures and their properties are illustrated using a simulated example with normally distributed response and repeated measurements.

Schistosomiasis Breeding Environment Situation Analysis in Dongting Lake Area

NASA Astrophysics Data System (ADS)

Li, Chuanrong; Jia, Yuanyuan; Ma, Lingling; Liu, Zhaoyan; Qian, Yonggang

2013-01-01

Monitoring environmental characteristics, such as vegetation, soil moisture et al., of Oncomelania hupensis (O. hupensis)’ spatial/temporal distribution is of vital importance to the schistosomiasis prevention and control. In this study, the relationship between environmental factors derived from remotely sensed data and the density of O. hupensis was analyzed by a multiple linear regression model. Secondly, spatial analysis of the regression residual was investigated by the semi-variogram method. Thirdly, spatial analysis of the regression residual and the multiple linear regression model were both employed to estimate the spatial variation of O. hupensis density. Finally, the approach was used to monitor and predict the spatial and temporal variations of oncomelania of Dongting Lake region, China. And the areas of potential O. hupensis habitats were predicted and the influence of Three Gorges Dam (TGB)project on the density of O. hupensis was analyzed.

A Framework for Integrating Qualitative and Quantitative Data in Knowledge, Attitude, and Practice Studies: A Case Study of Pesticide Usage in Eastern Uganda

PubMed Central

Muleme, James; Kankya, Clovice; Ssempebwa, John C.; Mazeri, Stella; Muwonge, Adrian

2017-01-01

Knowledge, attitude, and practice (KAP) studies guide the implementation of public health interventions (PHIs), and they are important tools for political persuasion. The design and implementation of PHIs assumes a linear KAP relationship, i.e., an awareness campaign results in the desirable societal behavioral change. However, there is no robust framework for testing this relationship before and after PHIs. Here, we use qualitative and quantitative data on pesticide usage to test this linear relationship, identify associated context specific factors as well as assemble a framework that could be used to guide and evaluate PHIs. We used data from a cross-sectional mixed methods study on pesticide usage. Quantitative data were collected using a structured questionnaire from 167 households representing 1,002 individuals. Qualitative data were collected from key informants and focus group discussions. Quantitative and qualitative data analysis was done in R 3.2.0 as well as qualitative thematic analysis, respectively. Our framework shows that a KAP linear relationship only existed for households with a low knowledge score, suggesting that an awareness campaign would only be effective for ~37% of the households. Context specific socioeconomic factors explain why this relationship does not hold for households with high knowledge scores. These findings are essential for developing targeted cost-effective and sustainable interventions on pesticide usage and other PHIs with context specific modifications. PMID:29276703

Comparative analysis of risk-based cleanup levels and associated remediation costs using linearized multistage model (cancer slope factor) vs. threshold approach (reference dose) for three chlorinated alkenes

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

Lawton, L.J.; Mihalich, J.P.

1995-12-31

The chlorinated alkenes 1,1-dichloroethene (1,1-DCE), tetrachloroethene (PCE), and trichloroethene (TCE) are common environmental contaminants found in soil and groundwater at hazardous waste sites. Recent assessment of data from epidemiology and mechanistic studies indicates that although exposure to 1,1-DCE, PCE, and TCE causes tumor formation in rodents, it is unlikely that these chemicals are carcinogenic to humans. Nevertheless, many state and federal agencies continue to regulate these compounds as carcinogens through the use of the linearized multistage model and resulting cancer slope factor (CSF). The available data indicate that 1,1-DCE, PCE, and TCE should be assessed using a threshold (i.e., referencemore » dose [RfD]) approach rather than a CSF. This paper summarizes the available metabolic, toxicologic, and epidemiologic data that question the use of the linear multistage model (and CSF) for extrapolation from rodents to humans. A comparative analysis of potential risk-based cleanup goals (RBGs) for these three compounds in soil is presented for a hazardous waste site. Goals were calculated using the USEPA CSFs and using a threshold (i.e., RfD) approach. Costs associated with remediation activities required to meet each set of these cleanup goals are presented and compared.« less

A Framework for Integrating Qualitative and Quantitative Data in Knowledge, Attitude, and Practice Studies: A Case Study of Pesticide Usage in Eastern Uganda.

PubMed

Muleme, James; Kankya, Clovice; Ssempebwa, John C; Mazeri, Stella; Muwonge, Adrian

2017-01-01

Knowledge, attitude, and practice (KAP) studies guide the implementation of public health interventions (PHIs), and they are important tools for political persuasion. The design and implementation of PHIs assumes a linear KAP relationship, i.e., an awareness campaign results in the desirable societal behavioral change. However, there is no robust framework for testing this relationship before and after PHIs. Here, we use qualitative and quantitative data on pesticide usage to test this linear relationship, identify associated context specific factors as well as assemble a framework that could be used to guide and evaluate PHIs. We used data from a cross-sectional mixed methods study on pesticide usage. Quantitative data were collected using a structured questionnaire from 167 households representing 1,002 individuals. Qualitative data were collected from key informants and focus group discussions. Quantitative and qualitative data analysis was done in R 3.2.0 as well as qualitative thematic analysis, respectively. Our framework shows that a KAP linear relationship only existed for households with a low knowledge score, suggesting that an awareness campaign would only be effective for ~37% of the households. Context specific socioeconomic factors explain why this relationship does not hold for households with high knowledge scores. These findings are essential for developing targeted cost-effective and sustainable interventions on pesticide usage and other PHIs with context specific modifications.

Fourier analysis of the SOR iteration

NASA Technical Reports Server (NTRS)

Leveque, R. J.; Trefethen, L. N.

1986-01-01

The SOR iteration for solving linear systems of equations depends upon an overrelaxation factor omega. It is shown that for the standard model problem of Poisson's equation on a rectangle, the optimal omega and corresponding convergence rate can be rigorously obtained by Fourier analysis. The trick is to tilt the space-time grid so that the SOR stencil becomes symmetrical. The tilted grid also gives insight into the relation between convergence rates of several variants.

Universality of qT resummation for electroweak boson production

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

Konychev, Anton V.; Nadolsky, Pavel M.

We perform a global analysis of transverse momentum distributions in Drell-Yan pair and Z boson production in order to investigate universality of nonperturbative contributions to the Collins-Soper-Sterman resummed form factor. Our fit made in an improved nonperturbative model suggests that the nonperturbative contributions follow universal nearly-linear dependence on the logarithm of the heavy boson invariant mass Q, which closely agrees with an estimate from the infrared renormalon analysis.

Universality of q{sub T} resummation for electroweak boson production.

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

Konychev, A. V.; Nadolsky, P. M.; High Energy Physics

We perform a global analysis of transverse momentum distributions in Drell-Yan pair and Z boson production in order to investigate universality of nonperturbative contributions to the Collins-Soper-Sterman resummed form factor. Our fit made in an improved nonperturbative model suggests that the nonperturbative contributions follow universal nearly-linear dependence on the logarithm of the heavy boson invariant mass Q, which closely agrees with an estimate from the infrared renormalon analysis.

New dual asymmetric CEC linear Fresnel concentrator for evacuated tubular receivers

NASA Astrophysics Data System (ADS)

Canavarro, Diogo; Chaves, Julio; Collares-Pereira, Manuel

2017-06-01

Linear Fresnel Reflector concentrators (LFR) are a potential solution for low-cost electricity production. Nevertheless in order to become more competitive with other CSP (Concentrated Solar Power) technologies, in particular with the Parabolic Trough concentrator, their overall solar to electricity efficiencies must increase. A possible path to achieve this goal is to increase the concentration factor, hence increasing the working temperatures for higher thermodynamic efficiency (more energy collection) and decrease the total number of rows of the solar field (less parasitic losses and corresponding cost reduction). This paper presents a dual asymmetric CEC-type (Compound Elliptical Concentrator) LFR (Linear Fresnel Concentrator) for evacuated tubular receivers. The concentrator is designed for a high concentration factor, presenting an asymmetric configuration enabling a very compact solution. The CEC-type secondary mirror is introduced to accommodate very high concentration values with a wide enough acceptance-angle (augmenting optical tolerances) for simple mechanical tracking solutions, achieving a higher CAP (Concentration Acceptance Product) in comparison with conventional LFR solutions. The paper presents an optical and thermal analysis of the concentrator using two different locations, Faro (Portugal) and Hurghada (Egypt).

Analyzing Response Times in Tests with Rank Correlation Approaches

ERIC Educational Resources Information Center

Ranger, Jochen; Kuhn, Jorg-Tobias

2013-01-01

It is common practice to log-transform response times before analyzing them with standard factor analytical methods. However, sometimes the log-transformation is not capable of linearizing the relation between the response times and the latent traits. Therefore, a more general approach to response time analysis is proposed in the current…

Determinants of Anabolic-Androgenic Steroid Risk Perceptions in Youth Populations: A Multivariate Analysis

ERIC Educational Resources Information Center

Denham, Bryan E.

2009-01-01

Grounded conceptually in social cognitive theory, this research examines how personal, behavioral, and environmental factors are associated with risk perceptions of anabolic-androgenic steroids. Ordinal logistic regression and logit log-linear models applied to data gathered from high-school seniors (N = 2,160) in the 2005 Monitoring the Future…

The Determinants of Child Health in Pakistan: An Economic Analysis

ERIC Educational Resources Information Center

Shehzad, Shafqat

2006-01-01

This paper estimates linear structural models using LISREL and employs MIMIC models to find out factors determining child health in Pakistan. A distinction has been made in permanent and transitory health states that lend support to Grossman's (1972) stock and flow concepts of health. The paper addresses the issue of health unobservability and…

Does Familism Lead to Increased Parental Monitoring?: Protective Factors for Coping with Risky Behaviors

ERIC Educational Resources Information Center

Romero, Andrea J.; Ruiz, Myrna

2007-01-01

We examined coping with risky behaviors (cigarettes, alcohol/drugs, yelling/ hitting, and anger), familism (family proximity and parental closeness) and parental monitoring (knowledge and discipline) in a sample of 56 adolescents (11-15 years old) predominantly of Mexican descent at two time points. Multiple linear regression analysis indicated…

U. S. Fourth Graders' Informational Text Comprehension: Indicators from NAEP

ERIC Educational Resources Information Center

Schugar, Heather R.; Dreher, Miriam Jean

2017-01-01

This study is a secondary analysis of reading data collected from over 165,000 fourth graders as part of the U.S. National Assessment of Educational Progress. Using hierarchical linear modelling, the authors investigated factors associated with students' informational text comprehension, including out-of-school reading engagement, and in-school…

Electronic Resource Expenditure and the Decline in Reference Transaction Statistics in Academic Libraries

ERIC Educational Resources Information Center

Dubnjakovic, Ana

2012-01-01

The current study investigates factors influencing increase in reference transactions in a typical week in academic libraries across the United States of America. Employing multiple regression analysis and general linear modeling, variables of interest from the "Academic Library Survey (ALS) 2006" survey (sample size 3960 academic libraries) were…

Conditional Covariance-Based Subtest Selection for DIMTEST

ERIC Educational Resources Information Center

Froelich, Amy G.; Habing, Brian

2008-01-01

DIMTEST is a nonparametric hypothesis-testing procedure designed to test the assumptions of a unidimensional and locally independent item response theory model. Several previous Monte Carlo studies have found that using linear factor analysis to select the assessment subtest for DIMTEST results in a moderate to severe loss of power when the exam…

Novel control modes to improve the performance of rectilinear ion trap mass spectrometer with dual pressure chambers

NASA Astrophysics Data System (ADS)

Huo, Xinming; Tang, Fei; Zhang, Xiaohua; Chen, Jin; Zhang, Yan; Guo, Cheng'an; Wang, Xiaohao

2016-10-01

The rectilinear ion trap (RIT) has gradually become one of the preferred mass analyzers for portable mass spectrometers because of its simple configuration. In order to enhance the performance, including sensitivity, quantitation capability, throughput, and resolution, a novel RIT mass spectrometer with dual pressure chambers was designed and characterized. The studied system constituted a quadrupole linear ion trap (QLIT) in the first chamber and a RIT in the second chamber. Two control modes are hereby proposed: Storage Quadrupole Linear Ion Trap-Rectilinear Ion Trap (SQLIT-RIT) mode, in which the QLIT was used at high pressure for ion storage and isolation, and the RIT was used for analysis; and Analysis Quadrupole Linear Ion Trap-Rectilinear Ion Trap (AQLIT-RIT) mode, in which the QLIT was used for ion storage and cooling. Subsequently, synchronous scanning and analysis were carried out by QLIT and RIT. In SQLIT-RIT mode, signal intensity was improved by a factor of 30; the limit of quantitation was reduced more than tenfold to 50 ng mL-1, and an optimal duty cycle of 96.4% was achieved. In AQLIT-RIT mode, the number of ions coexisting in the RIT was reduced, which weakened the space-charge effect and reduced the mass shift. Furthermore, the mass resolution was enhanced by a factor of 3. The results indicate that the novel control modes achieve satisfactory performance without adding any system complexity, which provides a viable pathway to guarantee good analytical performance in miniaturization of the mass spectrometer.

Principal component regression analysis with SPSS.

PubMed

Liu, R X; Kuang, J; Gong, Q; Hou, X L

2003-06-01

The paper introduces all indices of multicollinearity diagnoses, the basic principle of principal component regression and determination of 'best' equation method. The paper uses an example to describe how to do principal component regression analysis with SPSS 10.0: including all calculating processes of the principal component regression and all operations of linear regression, factor analysis, descriptives, compute variable and bivariate correlations procedures in SPSS 10.0. The principal component regression analysis can be used to overcome disturbance of the multicollinearity. The simplified, speeded up and accurate statistical effect is reached through the principal component regression analysis with SPSS.

Sexual Response Models: Toward a More Flexible Pattern of Women's Sexuality.

PubMed

Ferenidou, Fotini; Kirana, Paraskevi-Sofia; Fokas, Konstantinos; Hatzichristou, Dimitrios; Athanasiadis, Loukas

2016-09-01

Recent research suggests that none of the current theoretical models can sufficiently describe women's sexual response, because several factors and situations can influence this. To explore individual variations of a sexual model that describes women's sexual responses and to assess the association of endorsement of that model with sexual dysfunctions and reasons to engage in sexual activity. A sample of 157 randomly selected hospital employees completed self-administered questionnaires. Two models were developed: one merged the Master and Johnson model with the Kaplan model (linear) and the other was the Basson model (circular). Sexual function was evaluated by the Female Sexual Function Index and the Brief Sexual Symptom Checklist for Women. The Reasons for Having Sex Questionnaire was administered to investigate the reasons for which women have sex. Women reported that their current sexual experiences were at times consistent with the linear and circular models (66.9%), only the linear model (27%), only the circular model (5.4%), and neither model (0.7%). When the groups were reconfigured to the group that endorsed more than 5 of 10 sexual experiences, 64.3% of women endorsed the linear model, 20.4% chose the linear and circular models, 14.6% chose the circular model, and 0.7% selected neither. The Female Sexual Function Index, demographic factors, having sex for insecurity reasons, and sexual satisfaction correlated with the endorsement of a sexual response model. When these factors were entered in a stepwise logistic regression analysis, only the Female Sexual Function Index and having sex for insecurity reasons maintained a significant association with the sexual response model. The present study emphasizes the heterogeneity of female sexuality, with most of the sample reporting alternating between the linear and circular models. Sexual dysfunctions and having sex for insecurity reasons were associated with the Basson model. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Predicting Time to Hospital Discharge for Extremely Preterm Infants

PubMed Central

Hintz, Susan R.; Bann, Carla M.; Ambalavanan, Namasivayam; Cotten, C. Michael; Das, Abhik; Higgins, Rosemary D.

2010-01-01

As extremely preterm infant mortality rates have decreased, concerns regarding resource utilization have intensified. Accurate models to predict time to hospital discharge could aid in resource planning, family counseling, and perhaps stimulate quality improvement initiatives. Objectives For infants <27 weeks estimated gestational age (EGA), to develop, validate and compare several models to predict time to hospital discharge based on time-dependent covariates, and based on the presence of 5 key risk factors as predictors. Patients and Methods This was a retrospective analysis of infants <27 weeks EGA, born 7/2002-12/2005 and surviving to discharge from a NICHD Neonatal Research Network site. Time to discharge was modeled as continuous (postmenstrual age at discharge, PMAD), and categorical variables (“Early” and “Late” discharge). Three linear and logistic regression models with time-dependent covariate inclusion were developed (perinatal factors only, perinatal+early neonatal factors, perinatal+early+later factors). Models for Early and Late discharge using the cumulative presence of 5 key risk factors as predictors were also evaluated. Predictive capabilities were compared using coefficient of determination (R2) for linear models, and AUC of ROC curve for logistic models. Results Data from 2254 infants were included. Prediction of PMAD was poor, with only 38% of variation explained by linear models. However, models incorporating later clinical characteristics were more accurate in predicting “Early” or “Late” discharge (full models: AUC 0.76-0.83 vs. perinatal factor models: AUC 0.56-0.69). In simplified key risk factors models, predicted probabilities for Early and Late discharge compared favorably with observed rates. Furthermore, the AUC (0.75-0.77) were similar to those of models including the full factor set. Conclusions Prediction of Early or Late discharge is poor if only perinatal factors are considered, but improves substantially with knowledge of later-occurring morbidities. Prediction using a few key risk factors is comparable to full models, and may offer a clinically applicable strategy. PMID:20008430

Data mining-based coefficient of influence factors optimization of test paper reliability

NASA Astrophysics Data System (ADS)

Xu, Peiyao; Jiang, Huiping; Wei, Jieyao

2018-05-01

Test is a significant part of the teaching process. It demonstrates the final outcome of school teaching through teachers' teaching level and students' scores. The analysis of test paper is a complex operation that has the characteristics of non-linear relation in the length of the paper, time duration and the degree of difficulty. It is therefore difficult to optimize the coefficient of influence factors under different conditions in order to get text papers with clearly higher reliability with general methods [1]. With data mining techniques like Support Vector Regression (SVR) and Genetic Algorithm (GA), we can model the test paper analysis and optimize the coefficient of impact factors for higher reliability. It's easy to find that the combination of SVR and GA can get an effective advance in reliability from the test results. The optimal coefficient of influence factors optimization has a practicability in actual application, and the whole optimizing operation can offer model basis for test paper analysis.

Uremic Pruritus, Dialysis Adequacy, and Metabolic Profiles in Hemodialysis Patients: A Prospective 5-Year Cohort Study

PubMed Central

Chen, Hung-Yuan; Chiu, Yen-Ling; Hsu, Shih-Ping; Pai, Mei-Fen; Ju-YehYang; Lai, Chun-Fu; Lu, Hui-Min; Huang, Shu-Chen; Yang, Shao-Yu; Wen, Su-Yin; Chiu, Hsien-Ching; Hu, Fu-Chang; Peng, Yu-Sen; Jee, Shiou-Hwa

2013-01-01

Background Uremic pruritus is a common and intractable symptom in patients on chronic hemodialysis, but factors associated with the severity of pruritus remain unclear. This study aimed to explore the associations of metabolic factors and dialysis adequacy with the aggravation of pruritus. Methods We conducted a 5-year prospective cohort study on patients with maintenance hemodialysis. A visual analogue scale (VAS) was used to assess the intensity of pruritus. Patient demographic and clinical characteristics, laboratory parameters, dialysis adequacy (assessed by Kt/V), and pruritus intensity were recorded at baseline and follow-up. Change score analysis of the difference score of VAS between baseline and follow-up was performed using multiple linear regression models. The optimal threshold of Kt/V, which is associated with the aggravation of uremic pruritus, was determined by generalized additive models and receiver operating characteristic analysis. Results A total of 111 patients completed the study. Linear regression analysis showed that lower Kt/V and use of low-flux dialyzer were significantly associated with the aggravation of pruritus after adjusting for the baseline pruritus intensity and a variety of confounding factors. The optimal threshold value of Kt/V for pruritus was 1.5 suggested by both generalized additive models and receiver operating characteristic analysis. Conclusions Hemodialysis with the target of Kt/V ≥1.5 and use of high-flux dialyzer may reduce the intensity of pruritus in patients on chronic hemodialysis. Further clinical trials are required to determine the optimal dialysis dose and regimen for uremic pruritus. PMID:23940749

Demographic and clinical features related to perceived discrimination in schizophrenia.

PubMed

Fresán, Ana; Robles-García, Rebeca; Madrigal, Eduardo; Tovilla-Zarate, Carlos-Alfonso; Martínez-López, Nicolás; Arango de Montis, Iván

2018-04-01

Perceived discrimination contributes to the development of internalized stigma among those with schizophrenia. Evidence on demographic and clinical factors related to the perception of discrimination among this population is both contradictory and scarce in low- and middle-income countries. Accordingly, the main purpose of this study is to determine the demographic and clinical factors predicting the perception of discrimination among Mexican patients with schizophrenia. Two hundred and seventeen adults with paranoid schizophrenia completed an interview on their demographic status and clinical characteristics. Symptom severity was assessed using the Positive and Negative Syndrome Scale; and perceived discrimination using 13 items from the King's Internalized Stigma Scale. Bivariate linear associations were determined to identify the variables of interest to be included in a linear regression analysis. Years of education, age of illness onset and length of hospitalization were associated with discrimination. However, only age of illness onset and length of hospitalization emerged as predictors of perceived discrimination in the final regression analysis, with longer length of hospitalization being the independent variable with the greatest contribution. Fortunately, this is a modifiable factor regarding the perception of discrimination and self-stigma. Strategies for achieving this as part of community-based mental health care are also discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Pathway analysis of high-throughput biological data within a Bayesian network framework.

PubMed

Isci, Senol; Ozturk, Cengizhan; Jones, Jon; Otu, Hasan H

2011-06-15

Most current approaches to high-throughput biological data (HTBD) analysis either perform individual gene/protein analysis or, gene/protein set enrichment analysis for a list of biologically relevant molecules. Bayesian Networks (BNs) capture linear and non-linear interactions, handle stochastic events accounting for noise, and focus on local interactions, which can be related to causal inference. Here, we describe for the first time an algorithm that models biological pathways as BNs and identifies pathways that best explain given HTBD by scoring fitness of each network. Proposed method takes into account the connectivity and relatedness between nodes of the pathway through factoring pathway topology in its model. Our simulations using synthetic data demonstrated robustness of our approach. We tested proposed method, Bayesian Pathway Analysis (BPA), on human microarray data regarding renal cell carcinoma (RCC) and compared our results with gene set enrichment analysis. BPA was able to find broader and more specific pathways related to RCC. Accompanying BPA software (BPAS) package is freely available for academic use at http://bumil.boun.edu.tr/bpa.

Bias due to two-stage residual-outcome regression analysis in genetic association studies.

PubMed

Demissie, Serkalem; Cupples, L Adrienne

2011-11-01

Association studies of risk factors and complex diseases require careful assessment of potential confounding factors. Two-stage regression analysis, sometimes referred to as residual- or adjusted-outcome analysis, has been increasingly used in association studies of single nucleotide polymorphisms (SNPs) and quantitative traits. In this analysis, first, a residual-outcome is calculated from a regression of the outcome variable on covariates and then the relationship between the adjusted-outcome and the SNP is evaluated by a simple linear regression of the adjusted-outcome on the SNP. In this article, we examine the performance of this two-stage analysis as compared with multiple linear regression (MLR) analysis. Our findings show that when a SNP and a covariate are correlated, the two-stage approach results in biased genotypic effect and loss of power. Bias is always toward the null and increases with the squared-correlation between the SNP and the covariate (). For example, for , 0.1, and 0.5, two-stage analysis results in, respectively, 0, 10, and 50% attenuation in the SNP effect. As expected, MLR was always unbiased. Since individual SNPs often show little or no correlation with covariates, a two-stage analysis is expected to perform as well as MLR in many genetic studies; however, it produces considerably different results from MLR and may lead to incorrect conclusions when independent variables are highly correlated. While a useful alternative to MLR under , the two -stage approach has serious limitations. Its use as a simple substitute for MLR should be avoided. © 2011 Wiley Periodicals, Inc.

Tools for Basic Statistical Analysis

NASA Technical Reports Server (NTRS)

Luz, Paul L.

2005-01-01

Statistical Analysis Toolset is a collection of eight Microsoft Excel spreadsheet programs, each of which performs calculations pertaining to an aspect of statistical analysis. These programs present input and output data in user-friendly, menu-driven formats, with automatic execution. The following types of calculations are performed: Descriptive statistics are computed for a set of data x(i) (i = 1, 2, 3 . . . ) entered by the user. Normal Distribution Estimates will calculate the statistical value that corresponds to cumulative probability values, given a sample mean and standard deviation of the normal distribution. Normal Distribution from two Data Points will extend and generate a cumulative normal distribution for the user, given two data points and their associated probability values. Two programs perform two-way analysis of variance (ANOVA) with no replication or generalized ANOVA for two factors with four levels and three repetitions. Linear Regression-ANOVA will curvefit data to the linear equation y=f(x) and will do an ANOVA to check its significance.

An Analysis of Terrestrial and Aquatic Environmental Controls of Riverine Dissolved Organic Carbon in the Conterminous United States

DOE PAGES

Yang, Qichun; Zhang, Xuesong; Xu, Xingya; ...

2017-05-29

Riverine carbon cycling is an important, but insufficiently investigated component of the global carbon cycle. Analyses of environmental controls on riverine carbon cycling are critical for improved understanding of mechanisms regulating carbon processing and storage along the terrestrial-aquatic continuum. Here, we compile and analyze riverine dissolved organic carbon (DOC) concentration data from 1402 United States Geological Survey (USGS) gauge stations to examine the spatial variability and environmental controls of DOC concentrations in the United States (U.S.) surface waters. DOC concentrations exhibit high spatial variability, with an average of 6.42 ± 6.47 mg C/ L (Mean ± Standard Deviation). In general,more » high DOC concentrations occur in the Upper Mississippi River basin and the Southeastern U.S., while low concentrations are mainly distributed in the Western U.S. Single-factor analysis indicates that slope of drainage areas, wetlands, forests, percentage of first-order streams, and instream nutrients (such as nitrogen and phosphorus) pronouncedly influence DOC concentrations, but the explanatory power of each bivariate model is lower than 35%. Analyses based on the general multi-linear regression models suggest DOC concentrations are jointly impacted by multiple factors. Soil properties mainly show positive correlations with DOC concentrations; forest and shrub lands have positive correlations with DOC concentrations, but urban area and croplands demonstrate negative impacts; total instream phosphorus and dam density correlate positively with DOC concentrations. Notably, the relative importance of these environmental controls varies substantially across major U.S. water resource regions. In addition, DOC concentrations and environmental controls also show significant variability from small streams to large rivers, which may be caused by changing carbon sources and removal rates by river orders. In sum, our results reveal that general multi-linear regression analysis of twenty one terrestrial and aquatic environmental factors can partially explain (56%) the DOC concentration variation. In conclusion, this study highlights the complexity of the interactions among these environmental factors in determining DOC concentrations, thus calls for processes-based, non-linear methodologies to constrain uncertainties in riverine DOC cycling.« less

Linear degrees of freedom in speech production: analysis of cineradio- and labio-film data and articulatory-acoustic modeling.

PubMed

Beautemps, D; Badin, P; Bailly, G

2001-05-01

The following contribution addresses several issues concerning speech degrees of freedom in French oral vowels, stop, and fricative consonants based on an analysis of tongue and lip shapes extracted from cineradio- and labio-films. The midsagittal tongue shapes have been submitted to a linear decomposition where some of the loading factors were selected such as jaw and larynx position while four other components were derived from principal component analysis (PCA). For the lips, in addition to the more traditional protrusion and opening components, a supplementary component was extracted to explain the upward movement of both the upper and lower lips in [v] production. A linear articulatory model was developed; the six tongue degrees of freedom were used as the articulatory control parameters of the midsagittal tongue contours and explained 96% of the tongue data variance. These control parameters were also used to specify the frontal lip width dimension derived from the labio-film front views. Finally, this model was complemented by a conversion model going from the midsagittal to the area function, based on a fitting of the midsagittal distances and the formant frequencies for both vowels and consonants.

Experimental variability and data pre-processing as factors affecting the discrimination power of some chemometric approaches (PCA, CA and a new algorithm based on linear regression) applied to (+/-)ESI/MS and RPLC/UV data: Application on green tea extracts.

PubMed

Iorgulescu, E; Voicu, V A; Sârbu, C; Tache, F; Albu, F; Medvedovici, A

2016-08-01

The influence of the experimental variability (instrumental repeatability, instrumental intermediate precision and sample preparation variability) and data pre-processing (normalization, peak alignment, background subtraction) on the discrimination power of multivariate data analysis methods (Principal Component Analysis -PCA- and Cluster Analysis -CA-) as well as a new algorithm based on linear regression was studied. Data used in the study were obtained through positive or negative ion monitoring electrospray mass spectrometry (+/-ESI/MS) and reversed phase liquid chromatography/UV spectrometric detection (RPLC/UV) applied to green tea extracts. Extractions in ethanol and heated water infusion were used as sample preparation procedures. The multivariate methods were directly applied to mass spectra and chromatograms, involving strictly a holistic comparison of shapes, without assignment of any structural identity to compounds. An alternative data interpretation based on linear regression analysis mutually applied to data series is also discussed. Slopes, intercepts and correlation coefficients produced by the linear regression analysis applied on pairs of very large experimental data series successfully retain information resulting from high frequency instrumental acquisition rates, obviously better defining the profiles being compared. Consequently, each type of sample or comparison between samples produces in the Cartesian space an ellipsoidal volume defined by the normal variation intervals of the slope, intercept and correlation coefficient. Distances between volumes graphically illustrates (dis)similarities between compared data. The instrumental intermediate precision had the major effect on the discrimination power of the multivariate data analysis methods. Mass spectra produced through ionization from liquid state in atmospheric pressure conditions of bulk complex mixtures resulting from extracted materials of natural origins provided an excellent data basis for multivariate analysis methods, equivalent to data resulting from chromatographic separations. The alternative evaluation of very large data series based on linear regression analysis produced information equivalent to results obtained through application of PCA an CA. Copyright © 2016 Elsevier B.V. All rights reserved.

Crack Growth of a Titanium-Aluminide Alloy under Thermal-Mechanical Fatigue

DTIC Science & Technology

1988-12-01

the elastic-plastic fracture mechanics ( EPFM ) relations such as the J-integral or crack tip opening displacement (CTOD) must be used. Much more work...has been done in the area of LEFM, using stress intensity factor range AK as a correlating factor, than in EPFM . No matter which type of analysis is...thus obvious that a simple linear summation model such as Heil’s might not be applicable to this material. Other damage mechanisms were then investigated

Analysis on the Climate Change Characteristics of Dianchi Lake Basin under the Background of Global Warming

NASA Astrophysics Data System (ADS)

Zhenyu, Yu; Luo, Yi; Yang, Kun; Qiongfei, Deng

2017-05-01

Based on the data published by the State Statistical Bureau and the weather station data, the annual mean temperature, wind speed, humidity, light duration and precipitation of Dianchi Lake in 1990 ~ 2014 were analysed. Combined with the population The results show that the climatic changes in Dianchi Lake basin are related to the climatic change in the past 25 years, and the correlation between these factors and the main climatic factors are analysed by linear regression, Mann-Kendall test, cumulative anomaly, R/S and Morlet wavelet analysis. Population, housing construction area growth and other aspects of the correlation trends and changes in the process, revealing the population expansion and housing construction area growth on the climate of the main factors of the cycle tendency of significant impact.

Influence factors and forecast of carbon emission in China: structure adjustment for emission peak

NASA Astrophysics Data System (ADS)

Wang, B.; Cui, C. Q.; Li, Z. P.

2018-02-01

This paper introduced Principal Component Analysis and Multivariate Linear Regression Model to verify long-term balance relationships between Carbon Emissions and the impact factors. The integrated model of improved PCA and multivariate regression analysis model is attainable to figure out the pattern of carbon emission sources. Main empirical results indicate that among all selected variables, the role of energy consumption scale was largest. GDP and Population follow and also have significant impacts on carbon emission. Industrialization rate and fossil fuel proportion, which is the indicator of reflecting the economic structure and energy structure, have a higher importance than the factor of urbanization rate and the dweller consumption level of urban areas. In this way, some suggestions are put forward for government to achieve the peak of carbon emissions.

Factors Predicting a Good Symptomatic Outcome After Prostate Artery Embolisation (PAE).

PubMed

Maclean, D; Harris, M; Drake, T; Maher, B; Modi, S; Dyer, J; Somani, B; Hacking, N; Bryant, T

2018-02-26

As prostate artery embolisation (PAE) becomes an established treatment for benign prostatic obstruction, factors predicting good symptomatic outcome remain unclear. Pre-embolisation prostate size as a predictor is controversial with a handful of papers coming to conflicting conclusions. We aimed to investigate if an association existed in our patient cohort between prostate size and clinical benefit, in addition to evaluating percentage volume reduction as a predictor of symptomatic outcome following PAE. Prospective follow-up of 86 PAE patients at a single institution between June 2012 and January 2016 was conducted (mean age 64.9 years, range 54-80 years). Multiple linear regression analysis was performed to assess strength of association between clinical improvement (change in IPSS) and other variables, of any statistical correlation, through Pearson's bivariate analysis. No major procedural complications were identified and clinical success was achieved in 72.1% (n = 62) at 12 months. Initial prostate size and percentage reduction were found to have a significant association with clinical improvement. Multiple linear regression analysis (r 2  = 0.48) demonstrated that percentage volume reduction at 3 months (r = 0.68, p < 0.001) had the strongest correlation with good symptomatic improvement at 12 months after adjusting for confounding factors. Both the initial prostate size and percentage volume reduction at 3 months predict good symptomatic outcome at 12 months. These findings therefore aid patient selection and counselling to achieve optimal outcomes for men undergoing prostate artery embolisation.

Findings regarding the relationships between sociodemographic, psychological, comorbidity factors, and functional status, in geriatric inpatients.

PubMed

Capisizu, Ana; Aurelian, Sorina; Zamfirescu, Andreea; Omer, Ioana; Haras, Monica; Ciobotaru, Camelia; Onose, Liliana; Spircu, Tiberiu; Onose, Gelu

2015-01-01

To assess the impact of socio-demographic and comorbidity factors, and quantified depressive symptoms on disability in inpatients. Observational cross-sectional study, including a number of 80 elderly (16 men, 64 women; mean age 72.48 years; standard deviation 9.95 years) admitted in the Geriatrics Clinic of "St. Luca" Hospital, Bucharest, between May-July, 2012. We used the Functional Independence Measure, Geriatric Depression Scale and an array of socio-demographic and poly-pathology parameters. Statistical analysis included Wilcoxon and Kruskal-Wallis tests for ordinal variables, linear bivariate correlations, general linear model analysis, ANOVA. FIM scores were negatively correlated with age (R=-0.301; 95%CI=-0.439 -0.163; p=0.007); GDS scores had a statistically significant negative correlation (R=-0.322; 95% CI=-0.324 -0.052; p=0.004) with FIM scores. A general linear model, including other variables (gender, age, provenance, matrimonial state, living conditions, education, respectively number of chronic illnesses) as factors, found living conditions (p=0.027) and the combination of matrimonial state and gender (p=0.004) to significantly influence FIM scores. ANOVA showed significant differences in FIM scores stratified by the number of chronic diseases (p=0.035). Our study objectified the negative impact of depression on functional status; interestingly, education had no influence on FIM scores; living conditions and a combination of matrimonial state and gender had an important impact: patients with living spouses showed better functional scores than divorced/widowers; the number of chronic diseases also affected the FIM scores: lower in patients with significant polypathology. These findings should be considered when designing geriatric rehabilitation programs, especially for home--including skilled--cares.

Q estimation of seismic data using the generalized S-transform

NASA Astrophysics Data System (ADS)

Hao, Yaju; Wen, Xiaotao; Zhang, Bo; He, Zhenhua; Zhang, Rui; Zhang, Jinming

2016-12-01

Quality factor, Q, is a parameter that characterizes the energy dissipation during seismic wave propagation. The reservoir pore is one of the main factors that affect the value of Q. Especially, when pore space is filled with oil or gas, the rock usually exhibits a relative low Q value. Such a low Q value has been used as a direct hydrocarbon indicator by many researchers. The conventional Q estimation method based on spectral ratio suffers from the problem of waveform tuning; hence, many researchers have introduced time-frequency analysis techniques to tackle this problem. Unfortunately, the window functions adopted in time-frequency analysis algorithms such as continuous wavelet transform (CWT) and S-transform (ST) contaminate the amplitude spectra because the seismic signal is multiplied by the window functions during time-frequency decomposition. The basic assumption of the spectral ratio method is that there is a linear relationship between natural logarithmic spectral ratio and frequency. However, this assumption does not hold if we take the influence of window functions into consideration. In this paper, we first employ a recently developed two-parameter generalized S-transform (GST) to obtain the time-frequency spectra of seismic traces. We then deduce the non-linear relationship between natural logarithmic spectral ratio and frequency. Finally, we obtain a linear relationship between natural logarithmic spectral ratio and a newly defined parameter γ by ignoring the negligible second order term. The gradient of this linear relationship is 1/Q. Here, the parameter γ is a function of frequency and source wavelet. Numerical examples for VSP and post-stack reflection data confirm that our algorithm is capable of yielding accurate results. The Q-value results estimated from field data acquired in western China show reasonable comparison with oil-producing well location.

Stigma towards mental illness among medical and nursing students in Singapore: a cross-sectional study

PubMed Central

Chang, Sherilyn; Ong, Hui Lin; Seow, Esmond; Chua, Boon Yiang; Abdin, Edimansyah; Samari, Ellaisha; Chong, Siow Ann; Subramaniam, Mythily

2017-01-01

Objectives To assess stigma towards people with mental illness among Singapore medical and nursing students using the Opening Minds Stigma Scale for Health Care Providers (OMS-HC), and to examine the relationship of students’ stigmatising attitudes with sociodemographic and education factors. Design and setting Cross-sectional study conducted in Singapore Participants The study was conducted among 1002 healthcare (502 medical and 500 nursing) students during April to September 2016. Students had to be Singapore citizens or permanent residents and enrolled in public educational institutions to be included in the study. The mean (SD) age of the participants was 21.3 (3.3) years, with the majority being females (71.1%). 75.2% of the participants were Chinese, 14.1% were Malays, and 10.7% were either Indians or of other ethnicity. Methods Factor analysis was conducted to validate the OMS-HC scale in the study sample and to examine its factor structure. Descriptive statistics and multivariate linear regression were used to examine sociodemographic and education correlates. Results Factor analysis revealed a three-factor structure with 14 items. The factors were labelled as attitudes towards help-seeking and people with mental illness, social distance and disclosure. Multivariable linear regression analysis showed that medical students were found to be associated with lower total OMS-HC scores (P<0.05), less negative attitudes (P<0.001) and greater disclosure (P<0.05) than nursing students. Students who had a monthly household income of below S$4000 had more unfavourable attitudes than those with an income of SGD$10 000 and above (P<0.05). Having attended clinical placement was associated with more negative attitudes (P<0.05) among the students. Conclusion Healthcare students generally possessed positive attitudes towards help-seeking and persons with mental illness, though they preferred not to disclose their own mental health condition. Academic curriculum may need to enhance the component of mental health training, particularly on reducing stigma in certain groups of students. PMID:29208617

Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening

PubMed Central

Wang, Ke-Sheng; Liu, Xuefeng; Ategbole, Muyiwa; Xie, Xin; Liu, Ying; Xu, Chun; Xie, Changchun; Sha, Zhanxin

2017-01-01

Objective: Screening for colorectal cancer (CRC) can reduce disease incidence, morbidity, and mortality. However, few studies have investigated the urban-rural differences in social and behavioral factors influencing CRC screening. The objective of the study was to investigate the potential factors across urban-rural groups on the usage of CRC screening. Methods: A total of 38,505 adults (aged ≥40 years) were selected from the 2009 California Health Interview Survey (CHIS) data - the latest CHIS data on CRC screening. The weighted generalized linear mixed-model (WGLIMM) was used to deal with this hierarchical structure data. Weighted simple and multiple mixed logistic regression analyses in SAS ver. 9.4 were used to obtain the odds ratios (ORs) and their 95% confidence intervals (CIs). Results: The overall prevalence of CRC screening was 48.1% while the prevalence in four residence groups - urban, second city, suburban, and town/rural, were 45.8%, 46.9%, 53.7% and 50.1%, respectively. The results of WGLIMM analysis showed that there was residence effect (p<0.0001) and residence groups had significant interactions with gender, age group, education level, and employment status (p<0.05). Multiple logistic regression analysis revealed that age, race, marital status, education level, employment stats, binge drinking, and smoking status were associated with CRC screening (p<0.05). Stratified by residence regions, age and poverty level showed associations with CRC screening in all four residence groups. Education level was positively associated with CRC screening in second city and suburban. Infrequent binge drinking was associated with CRC screening in urban and suburban; while current smoking was a protective factor in urban and town/rural groups. Conclusions: Mixed models are useful to deal with the clustered survey data. Social factors and behavioral factors (binge drinking and smoking) were associated with CRC screening and the associations were affected by living areas such as urban and rural regions. PMID:28952708

Generalized Linear Mixed Model Analysis of Urban-Rural Differences in Social and Behavioral Factors for Colorectal Cancer Screening

PubMed

Wang, Ke-Sheng; Liu, Xuefeng; Ategbole, Muyiwa; Xie, Xin; Liu, Ying; Xu, Chun; Xie, Changchun; Sha, Zhanxin

2017-09-27

Objective: Screening for colorectal cancer (CRC) can reduce disease incidence, morbidity, and mortality. However, few studies have investigated the urban-rural differences in social and behavioral factors influencing CRC screening. The objective of the study was to investigate the potential factors across urban-rural groups on the usage of CRC screening. Methods: A total of 38,505 adults (aged ≥40 years) were selected from the 2009 California Health Interview Survey (CHIS) data - the latest CHIS data on CRC screening. The weighted generalized linear mixed-model (WGLIMM) was used to deal with this hierarchical structure data. Weighted simple and multiple mixed logistic regression analyses in SAS ver. 9.4 were used to obtain the odds ratios (ORs) and their 95% confidence intervals (CIs). Results: The overall prevalence of CRC screening was 48.1% while the prevalence in four residence groups - urban, second city, suburban, and town/rural, were 45.8%, 46.9%, 53.7% and 50.1%, respectively. The results of WGLIMM analysis showed that there was residence effect (p<0.0001) and residence groups had significant interactions with gender, age group, education level, and employment status (p<0.05). Multiple logistic regression analysis revealed that age, race, marital status, education level, employment stats, binge drinking, and smoking status were associated with CRC screening (p<0.05). Stratified by residence regions, age and poverty level showed associations with CRC screening in all four residence groups. Education level was positively associated with CRC screening in second city and suburban. Infrequent binge drinking was associated with CRC screening in urban and suburban; while current smoking was a protective factor in urban and town/rural groups. Conclusions: Mixed models are useful to deal with the clustered survey data. Social factors and behavioral factors (binge drinking and smoking) were associated with CRC screening and the associations were affected by living areas such as urban and rural regions. Creative Commons Attribution License

Analysis of factors that inhibiting implementation of Information Security Management System (ISMS) based on ISO 27001

NASA Astrophysics Data System (ADS)

Tatiara, R.; Fajar, A. N.; Siregar, B.; Gunawan, W.

2018-03-01

The purpose of this research is to determine multi factors that inhibiting the implementation of the ISMS based on ISO 2700. It is also to propose a follow-up recommendation on the factors that inhibit the implementation of the ISMS. Data collection is derived from questionnaires to 182 respondents from users in data center operation (DCO) at bca, Indonesian telecommunication international (telin), and data centre division at Indonesian Ministry of Health. We analysing data collection with multiple linear regression analysis and paired t-test. The results are multiple factors which inhibiting the implementation of the ISMS from the three organizations which has implement and operate the ISMS, ISMS documentation management, and continual improvement. From this research, we concluded that the processes of implementation in ISMS is the necessity of the role of all parties in succeeding the implementation of the ISMS continuously.

Linear mixed-effects modeling approach to FMRI group analysis

PubMed Central

Chen, Gang; Saad, Ziad S.; Britton, Jennifer C.; Pine, Daniel S.; Cox, Robert W.

2013-01-01

Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance–covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance–covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity for activation detection. The importance of hypothesis formulation is also illustrated in the simulations. Comparisons with alternative group analysis approaches and the limitations of LME are discussed in details. PMID:23376789

Linear mixed-effects modeling approach to FMRI group analysis.

PubMed

Chen, Gang; Saad, Ziad S; Britton, Jennifer C; Pine, Daniel S; Cox, Robert W

2013-06-01

Conventional group analysis is usually performed with Student-type t-test, regression, or standard AN(C)OVA in which the variance-covariance matrix is presumed to have a simple structure. Some correction approaches are adopted when assumptions about the covariance structure is violated. However, as experiments are designed with different degrees of sophistication, these traditional methods can become cumbersome, or even be unable to handle the situation at hand. For example, most current FMRI software packages have difficulty analyzing the following scenarios at group level: (1) taking within-subject variability into account when there are effect estimates from multiple runs or sessions; (2) continuous explanatory variables (covariates) modeling in the presence of a within-subject (repeated measures) factor, multiple subject-grouping (between-subjects) factors, or the mixture of both; (3) subject-specific adjustments in covariate modeling; (4) group analysis with estimation of hemodynamic response (HDR) function by multiple basis functions; (5) various cases of missing data in longitudinal studies; and (6) group studies involving family members or twins. Here we present a linear mixed-effects modeling (LME) methodology that extends the conventional group analysis approach to analyze many complicated cases, including the six prototypes delineated above, whose analyses would be otherwise either difficult or unfeasible under traditional frameworks such as AN(C)OVA and general linear model (GLM). In addition, the strength of the LME framework lies in its flexibility to model and estimate the variance-covariance structures for both random effects and residuals. The intraclass correlation (ICC) values can be easily obtained with an LME model with crossed random effects, even at the presence of confounding fixed effects. The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity for activation detection. The importance of hypothesis formulation is also illustrated in the simulations. Comparisons with alternative group analysis approaches and the limitations of LME are discussed in details. Published by Elsevier Inc.

IMPACT: Investigating the impact of Models of Practice for Allied health Care in subacuTe settings. A protocol for a quasi-experimental mixed methods study of cost effectiveness and outcomes for patients exposed to different models of allied health care.

PubMed

Coker, Freya; Williams, Cylie M; Taylor, Nicholas F; Caspers, Kirsten; McAlinden, Fiona; Wilton, Anita; Shields, Nora; Haines, Terry P

2018-05-10

This protocol considers three allied health staffing models across public health subacute hospitals. This quasi-experimental mixed-methods study, including qualitative process evaluation, aims to evaluate the impact of additional allied health services in subacute care, in rehabilitation and geriatric evaluation management settings, on patient, health service and societal outcomes. This health services research will analyse outcomes of patients exposed to different allied health models of care at three health services. Each health service will have a control ward (routine care) and an intervention ward (additional allied health). This project has two parts. Part 1: a whole of site data extraction for included wards. Outcome measures will include: length of stay, rate of readmissions, discharge destinations, community referrals, patient feedback and staff perspectives. Part 2: Functional Independence Measure scores will be collected every 2-3 days for the duration of 60 patient admissions.Data from part 1 will be analysed by linear regression analysis for continuous outcomes using patient-level data and logistic regression analysis for binary outcomes. Qualitative data will be analysed using a deductive thematic approach. For part 2, a linear mixed model analysis will be conducted using therapy service delivery and days since admission to subacute care as fixed factors in the model and individual participant as a random factor. Graphical analysis will be used to examine the growth curve of the model and transformations. The days since admission factor will be used to examine non-linear growth trajectories to determine if they lead to better model fit. Findings will be disseminated through local reports and to the Department of Health and Human Services Victoria. Results will be presented at conferences and submitted to peer-reviewed journals. The Monash Health Human Research Ethics committee approved this multisite research (HREC/17/MonH/144 and HREC/17/MonH/547). © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Quantitative analysis of crystalline pharmaceuticals in powders and tablets by a pattern-fitting procedure using X-ray powder diffraction data.

PubMed

Yamamura, S; Momose, Y

2001-01-16

A pattern-fitting procedure for quantitative analysis of crystalline pharmaceuticals in solid dosage forms using X-ray powder diffraction data is described. This method is based on a procedure for pattern-fitting in crystal structure refinement, and observed X-ray scattering intensities were fitted to analytical expressions including some fitting parameters, i.e. scale factor, peak positions, peak widths and degree of preferred orientation of the crystallites. All fitting parameters were optimized by the non-linear least-squares procedure. Then the weight fraction of each component was determined from the optimized scale factors. In the present study, well-crystallized binary systems, zinc oxide-zinc sulfide (ZnO-ZnS) and salicylic acid-benzoic acid (SA-BA), were used as the samples. In analysis of the ZnO-ZnS system, the weight fraction of ZnO or ZnS could be determined quantitatively in the range of 5-95% in the case of both powders and tablets. In analysis of the SA-BA systems, the weight fraction of SA or BA could be determined quantitatively in the range of 20-80% in the case of both powders and tablets. Quantitative analysis applying this pattern-fitting procedure showed better reproducibility than other X-ray methods based on the linear or integral intensities of particular diffraction peaks. Analysis using this pattern-fitting procedure also has the advantage that the preferred orientation of the crystallites in solid dosage forms can be also determined in the course of quantitative analysis.

Parallel Event Analysis Under Unix

NASA Astrophysics Data System (ADS)

Looney, S.; Nilsson, B. S.; Oest, T.; Pettersson, T.; Ranjard, F.; Thibonnier, J.-P.

The ALEPH experiment at LEP, the CERN CN division and Digital Equipment Corp. have, in a joint project, developed a parallel event analysis system. The parallel physics code is identical to ALEPH's standard analysis code, ALPHA, only the organisation of input/output is changed. The user may switch between sequential and parallel processing by simply changing one input "card". The initial implementation runs on an 8-node DEC 3000/400 farm, using the PVM software, and exhibits a near-perfect speed-up linearity, reducing the turn-around time by a factor of 8.

Determinants of linear growth in Malaysian children with cerebral palsy.

PubMed

Zainah, S H; Ong, L C; Sofiah, A; Poh, B K; Hussain, I H

2001-08-01

To compare the linear growth and nutritional parameters of a group of Malaysian children with cerebral palsy (CP) against a group of controls, and to determine the nutritional, medical and sociodemographic factors associated with poor growth in children with CP. The linear growth of 101 children with CP and of their healthy controls matched for age, sex and ethnicity was measured using upper-arm length (UAL). Nutritional parameters of weight, triceps skin-fold thickness and mid-arm circumference were also measured. Total caloric intake was assessed using a 24-h recall of a 3-day food intake and calculated as a percentage of the Recommended Daily Allowance. Multiple regression analysis was used to determine nutritional, medical and sociodemographic factors associated with poor growth (using z-scores of UAL) in children with CP. Compared with the controls, children with CP had significantly lower mean UAL measurements (difference between means -1.1, 95% confidence interval -1.65 to - 0.59), weight (difference between means -6.0, 95% CI -7.66 to -4.34), mid-arm circumference (difference between means -1.3, 95% CI -2.06 to -0.56) and triceps skin-fold thickness (difference between means -2.5, 95% CI -3.5 to -1.43). Factors associated with low z-scores of UAL were a lower percentage of median weight (P < 0.001), tube feeding (P < 0.001) and increasing age (P < 0.001). A large proportion of Malaysian children with CP have poor nutritional status and linear growth. Nutritional assessment and management at an early age might help this group of children achieve adequate growth.

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

Yang, Qichun; Zhang, Xuesong; Xu, Xingya

Riverine carbon cycling is an important, but insufficiently investigated component of the global carbon cycle. Analyses of environmental controls on riverine carbon cycling are critical for improved understanding of mechanisms regulating carbon processing and storage along the terrestrial-aquatic continuum. Here, we compile and analyze riverine dissolved organic carbon (DOC) concentration data from 1402 United States Geological Survey (USGS) gauge stations to examine the spatial variability and environmental controls of DOC concentrations in the United States (U.S.) surface waters. DOC concentrations exhibit high spatial variability, with an average of 6.42 ± 6.47 mg C/ L (Mean ± Standard Deviation). In general,more » high DOC concentrations occur in the Upper Mississippi River basin and the Southeastern U.S., while low concentrations are mainly distributed in the Western U.S. Single-factor analysis indicates that slope of drainage areas, wetlands, forests, percentage of first-order streams, and instream nutrients (such as nitrogen and phosphorus) pronouncedly influence DOC concentrations, but the explanatory power of each bivariate model is lower than 35%. Analyses based on the general multi-linear regression models suggest DOC concentrations are jointly impacted by multiple factors. Soil properties mainly show positive correlations with DOC concentrations; forest and shrub lands have positive correlations with DOC concentrations, but urban area and croplands demonstrate negative impacts; total instream phosphorus and dam density correlate positively with DOC concentrations. Notably, the relative importance of these environmental controls varies substantially across major U.S. water resource regions. In addition, DOC concentrations and environmental controls also show significant variability from small streams to large rivers, which may be caused by changing carbon sources and removal rates by river orders. In sum, our results reveal that general multi-linear regression analysis of twenty one terrestrial and aquatic environmental factors can partially explain (56%) the DOC concentration variation. In conclusion, this study highlights the complexity of the interactions among these environmental factors in determining DOC concentrations, thus calls for processes-based, non-linear methodologies to constrain uncertainties in riverine DOC cycling.« less

Correlates of early pregnancy serum brain-derived neurotrophic factor in a Peruvian population.

PubMed

Yang, Na; Levey, Elizabeth; Gelaye, Bizu; Zhong, Qiu-Yue; Rondon, Marta B; Sanchez, Sixto E; Williams, Michelle A

2017-12-01

Knowledge about factors that influence serum brain-derived neurotrophic factor (BDNF) concentrations during early pregnancy is lacking. The aim of the study is to examine the correlates of early pregnancy serum BDNF concentrations. A total of 982 women attending prenatal care clinics in Lima, Peru, were recruited in early pregnancy. Pearson's correlation coefficient was calculated to evaluate the relation between BDNF concentrations and continuous covariates. Analysis of variance and generalized linear models were used to compare the unadjusted and adjusted BDNF concentrations according to categorical variables. Multivariable linear regression models were applied to determine the factors that influence early pregnancy serum BDNF concentrations. In bivariate analysis, early pregnancy serum BDNF concentrations were positively associated with maternal age (r = 0.16, P < 0.001) and early pregnancy body mass index (BMI) (r = 0.17, P < 0.001), but inversely correlated with gestational age at sample collection (r = -0.21, P < 0.001) and C-reactive protein (CRP) concentrations (r = -0.07, P < 0.05). In the multivariable linear regression model, maternal age (β = 0.11, P = 0.001), early pregnancy BMI (β = 1.58, P < 0.001), gestational age at blood collection (β = -0.33, P < 0.001), and serum CRP concentrations (β = -0.57, P = 0.002) were significantly associated with early pregnancy serum BDNF concentrations. Participants with moderate antepartum depressive symptoms (Patient Health Questionnaire-9 (PHQ-9) score ≥ 10) had lower serum BDNF concentrations compared with participants with no/mild antepartum depressive symptoms (PHQ-9 score < 10). Maternal age, early pregnancy BMI, gestational age, and the presence of moderate antepartum depressive symptoms were statistically significantly associated with early pregnancy serum BDNF concentrations in low-income Peruvian women. Biological changes of CRP during pregnancy may affect serum BDNF concentrations.

Effects of Cerebral Blood Flow and Vessel Conditions on Speech Recognition in Patients With Postlingual Adult Cochlear Implant: Predictable Factors for the Efficacy of Cochlear Implant.

PubMed

Ishino, Takashi; Ragaee, Mahmoud Ali; Maruhashi, Tatsuya; Kajikawa, Masato; Higashi, Yukihito; Sonoyama, Toru; Takeno, Sachio; Hirakawa, Katsuhiro

Cochlear implantation (CI) has been the most successful procedure for restoring hearing in a patient with severe and profound hearing loss. However, possibly owing to the variable brain functions of each patient, its performance and the associated patient satisfaction are widely variable. The authors hypothesize that peripheral and cerebral circulation can be assessed by noninvasive and globally available methods, yielding superior presurgical predictive factors of the performance of CI in adult patients with postlingual hearing loss who are scheduled to undergo CI. Twenty-two adult patients with cochlear implants for postlingual hearing loss were evaluated using Doppler sonography measurement of the cervical arteries (reflecting cerebral blood flow), flow-mediated dilation (FMD; reflecting the condition of cerebral arteries), and their pre-/post-CI best score on a monosyllabic discrimination test (pre-/post-CI best monosyllabic discrimination [BMD] score). Correlations between post-CI BMD score and the other factors were examined using univariate analysis and stepwise multiple linear regression analysis. The prediction factors were calculated by examining the receiver-operating characteristic curve between post-CI BMD score and the significantly positively correlated factors. Age and duration of deafness had a moderately negative correlation. The mean velocity of the internal carotid arteries and FMD had a moderate-to-strong positive correlation with the post-CI BMD score in univariate analysis. Stepwise multiple linear regression analysis revealed that only FMD was significantly positively correlated with post-CI BMD score. Analysis of the receiver-operating characteristic curve showed that a FMD cutoff score of 1.8 significantly predicted post-CI BMD score. These data suggest that FMD is a convenient, noninvasive, and widely available tool for predicting the efficacy of cochlear implants. An FMD cutoff score of 1.8 could be a good index for determining whether patients will hear well with cochlear implants. It could also be used to predict whether cochlear implants will provide good speech recognition benefits to candidates, even if their speech discrimination is poor. This FMD index could become a useful predictive tool for candidates with poor speech discrimination to determine the efficacy of CI before surgery.

Comparing Linear Discriminant Function with Logistic Regression for the Two-Group Classification Problem.

ERIC Educational Resources Information Center

Fan, Xitao; Wang, Lin

The Monte Carlo study compared the performance of predictive discriminant analysis (PDA) and that of logistic regression (LR) for the two-group classification problem. Prior probabilities were used for classification, but the cost of misclassification was assumed to be equal. The study used a fully crossed three-factor experimental design (with…

Beyond the Black-White Test Score Gap: Latinos' Early School Experiences and Literacy Outcomes

ERIC Educational Resources Information Center

Delgado, Enilda A.; Stoll, Laurie Cooper

2015-01-01

Data from the Early Childhood Longitudinal Survey-Birth Cohort are used to analyze the factors that lead to the reading readiness of children who participate in nonparental care the year prior to kindergarten (N = 4,550), with a specific focus on Latino children (N = 800). Stepwise multiple linear regression analysis demonstrates that reading…

Stagnation in Mortality Decline among Elders in the Netherlands

ERIC Educational Resources Information Center

Janssen, Fanny; Nusselder, Wilma J.; Looman, Caspar W. N.; Mackenbach, Johan P.; Kunst, Anton E.

2003-01-01

Purpose: This study assesses whether the stagnation of old-age (80+) mortality decline observed in The Netherlands in the 1980s continued in the 1990s and determines which factors contributed to this stagnation. Emphasis is on the role of smoking. Design and Methods: Poisson regression analysis with linear splines was applied to total and…

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

Zhang, Ch.; Gao, X. W.; Sladek, J.

This paper reports our recent research works on crack analysis in continuously non-homogeneous and linear elastic functionally graded materials. A meshless boundary element method is developed for this purpose. Numerical examples are presented and discussed to demonstrate the efficiency and the accuracy of the present numerical method, and to show the effects of the material gradation on the crack-opening-displacements and the stress intensity factors.

Environmental Influences on Daily Emergency Admissions in Sickle-Cell Disease Patients

PubMed Central

Mekontso Dessap, Armand; Contou, Damien; Dandine-Roulland, Claire; Hemery, François; Habibi, Anoosha; Charles-Nelson, Anaïs; Galacteros, Frederic; Brun-Buisson, Christian; Maitre, Bernard; Katsahian, Sandrine

2014-01-01

Abstract Previous reports have suggested a role for weather conditions and air pollution on the variability of sickle cell disease (SCD) severity, but large-scale comprehensive epidemiological studies are lacking. In order to evaluate the influence of air pollution and climatic factors on emergency hospital admissions (EHA) in SCD patients, we conducted an 8-year observational retrospective study in 22 French university hospitals in Paris conurbation, using distributed lag non-linear models, a methodology able to flexibly describe simultaneously non-linear and delayed associations, with a multivariable approach. During the 2922 days of the study, there were 17,710 EHA, with a mean daily number of 6.1 ± 2.8. Most environmental factors were significantly correlated to each other. The risk of EHA was significantly associated with higher values of nitrogen dioxide, atmospheric particulate matters, and daily mean wind speed; and with lower values of carbon monoxide, ozone, sulfur dioxide, daily temperature (minimal, maximal, mean, and range), day-to-day mean temperature change, daily bright sunshine, and occurrence of storm. There was a lag effect for 12 of 15 environmental factors influencing hospitalization rate. Multivariate analysis identified carbon monoxide, day-to-day temperature change, and mean wind speed, along with calendar factors (weekend, summer season, and year) as independent factors associated with EHA. In conclusion, most weather conditions and air pollutants assessed were correlated to each other and influenced the rate of EHA in SCD patients. In multivariate analysis, lower carbon monoxide concentrations, day-to-day mean temperature drop and higher wind speed were associated with increased risk of EHA. PMID:25546672

Environmental influences on daily emergency admissions in sickle-cell disease patients.

PubMed

Mekontso Dessap, Armand; Contou, Damien; Dandine-Roulland, Claire; Hemery, François; Habibi, Anoosha; Charles-Nelson, Anaïs; Galacteros, Frederic; Brun-Buisson, Christian; Maitre, Bernard; Katsahian, Sandrine

2014-12-01

Previous reports have suggested a role for weather conditions and air pollution on the variability of sickle cell disease (SCD) severity, but large-scale comprehensive epidemiological studies are lacking. In order to evaluate the influence of air pollution and climatic factors on emergency hospital admissions (EHA) in SCD patients, we conducted an 8-year observational retrospective study in 22 French university hospitals in Paris conurbation, using distributed lag non-linear models, a methodology able to flexibly describe simultaneously non-linear and delayed associations, with a multivariable approach. During the 2922 days of the study, there were 17,710 EHA, with a mean daily number of 6.1 ± 2.8. Most environmental factors were significantly correlated to each other. The risk of EHA was significantly associated with higher values of nitrogen dioxide, atmospheric particulate matters, and daily mean wind speed; and with lower values of carbon monoxide, ozone, sulfur dioxide, daily temperature (minimal, maximal, mean, and range), day-to-day mean temperature change, daily bright sunshine, and occurrence of storm. There was a lag effect for 12 of 15 environmental factors influencing hospitalization rate. Multivariate analysis identified carbon monoxide, day-to-day temperature change, and mean wind speed, along with calendar factors (weekend, summer season, and year) as independent factors associated with EHA. In conclusion, most weather conditions and air pollutants assessed were correlated to each other and influenced the rate of EHA in SCD patients. In multivariate analysis, lower carbon monoxide concentrations, day-to-day mean temperature drop and higher wind speed were associated with increased risk of EHA.

Differences in Risk Factors for Rotator Cuff Tears between Elderly Patients and Young Patients.

PubMed

Watanabe, Akihisa; Ono, Qana; Nishigami, Tomohiko; Hirooka, Takahiko; Machida, Hirohisa

2018-02-01

It has been unclear whether the risk factors for rotator cuff tears are the same at all ages or differ between young and older populations. In this study, we examined the risk factors for rotator cuff tears using classification and regression tree analysis as methods of nonlinear regression analysis. There were 65 patients in the rotator cuff tears group and 45 patients in the intact rotator cuff group. Classification and regression tree analysis was performed to predict rotator cuff tears. The target factor was rotator cuff tears; explanatory variables were age, sex, trauma, and critical shoulder angle≥35°. In the results of classification and regression tree analysis, the tree was divided at age 64. For patients aged≥64, the tree was divided at trauma. For patients aged<64, the tree was divided at critical shoulder angle≥35°. The odds ratio for critical shoulder angle≥35° was significant for all ages (5.89), and for patients aged<64 (10.3) while trauma was only a significant factor for patients aged≥64 (5.13). Age, trauma, and critical shoulder angle≥35° were related to rotator cuff tears in this study. However, these risk factors showed different trends according to age group, not a linear relationship.

Caffeinated and decaffeinated coffee consumption and melanoma risk: a dose-response meta-analysis of prospective cohort studies.

PubMed

Micek, Agnieszka; Godos, Justyna; Lafranconi, Alessandra; Marranzano, Marina; Pajak, Andrzej

2018-06-01

To determine the association between total, caffeinated and decaffeinated coffee consumption and melanoma risk a dose-response meta-analysis on prospective cohort studies were performed. Eligible studies were identified searching PubMed and EMBASE databases from the earliest available online indexing year to March 2017. The dose-response relationship was assessed by random-effects meta-analysis and the shape of the exposure-outcome curve was modelled linearly and using restricted cubic splines. A total of seven studies eligible for meta-analysis were identified that comprised 1,418,779 participants and 9211 melanoma cases. A linear dose-response meta-analysis showed a significant association between total coffee consumption and melanoma risk. An increase in coffee consumption of one cup per day was associated with a 3% reduction in melanoma risk (RR 0.97; 95% CI 0.95-0.99). Our findings suggest that coffee intake may be inversely associated with incidence of melanoma. Nevertheless, further studies exploring also the role of confounding factors are needed to explain the heterogeneity among studies.

Factors influencing the postoperative use of analgesics in dogs and cats by Canadian veterinarians.

PubMed

Dohoo, S E; Dohoo, I R

1996-09-01

Four hundred and seventeen Canadian veterinarians were surveyed to determine their postoperative use of analgesics in dogs and cats following 6 categories of surgeries, and their opinion toward pain perception and perceived complications associated with the postoperative use of potent opioid analgesics. Three hundred and seventeen (76%) returned the questionnaire. An analgesic user was defined as a veterinarian who administers analgesics to at least 50% of dogs or 50% of cats following abdominal surgery, excluding ovariohysterectomy. The veterinarians responding exhibited a bimodal distribution of analgesic use, with 49.5% being defined as analgesic users. These veterinarians tended to use analgesics in 100% of animals following abdominal surgery. Veterinarians defined as analgesic nonusers rarely used postoperative analgesics following any abdominal surgery. Pain perception was defined as the average of pain rankings (on a scale of 1 to 10) following abdominal surgery, or the value for dogs or cats if the veterinarian worked with only 1 of the 2 species. Maximum concern about the risks associated with the postoperative use of potent opioid agonists was defined as the highest ranking assigned to any of the 7 risks evaluated in either dogs or cats. Logistic regression analysis identified the pain perception score and the maximum concern regarding the use of potent opioid agonists in the postoperative period as the 2 factors that distinguished analgesic users from analgesic nonusers. This model correctly classified 68% of veterinarians as analgesic users or nonusers. Linear regression analysis identified gender and the presence of an animal health technologist in the practice as the 2 factors that influenced pain perception by veterinarians. Linear regression analysis identified working with an animal health technologist, graduation within the past 10 years, and attendance at continuing education as factors that influenced maximum concern about the postoperative use of opioid agonists.

Intracultural Differences in Local Botanical Knowledge and Knowledge Loss among the Mexican Isthmus Zapotecs.

PubMed

Saynes-Vásquez, Alfredo; Vibrans, Heike; Vergara-Silva, Francisco; Caballero, Javier

2016-01-01

This study reports on the socio-demographic and locality factors that influence ethnobiological knowledge in three communities of Zapotec indigenous people of the Isthmus of Tehuantepec, Mexico. It uses local botanical nomenclature as a proxy for general ethnobiological knowledge. In each of these communities (one urban and two rural), 100 adult men were interviewed aided with a field herbarium. Fifty had a background in farming, and 50 worked in the secondary or tertiary sector as their main economic activity, totaling 300 interviews. Using a field herbarium with samples of 30 common and rare wild regional species, we documented visual recognition, knowledge of the local life form, generic and specific names and uses (five knowledge levels measuring knowledge depth). The relationship between sociodemographic variables and knowledge was analyzed with simple correlations. Differences between the three communities and the five knowledge levels were then evaluated with a discriminant analysis. A general linear analysis identified factors and covariables that influenced the observed differences. Differences between the groups with different economic activities were estimated with a t-test for independent samples. Most of the relationships found between sociodemographic variables and plant knowledge were expected: age and rurality were positively related with knowledge and years of formal schooling was negatively related. However, the somewhat less rural site had more traditional knowledge due to local circumstances. The general linear model explained 70-77% of the variation, a high value. It showed that economic activity was by far the most important factor influencing knowledge, by a factor of five. The interaction of locality and economic activity followed. The discriminant analysis assigned interviewees correctly to their localities in 94% of the cases, strengthening the evidence for intracultural variation. Both sociodemographic and historic intracultural differences heavily influence local knowledge.

Intracultural Differences in Local Botanical Knowledge and Knowledge Loss among the Mexican Isthmus Zapotecs

PubMed Central

Saynes-Vásquez, Alfredo; Vibrans, Heike; Vergara-Silva, Francisco; Caballero, Javier

2016-01-01

This study reports on the socio-demographic and locality factors that influence ethnobiological knowledge in three communities of Zapotec indigenous people of the Isthmus of Tehuantepec, Mexico. It uses local botanical nomenclature as a proxy for general ethnobiological knowledge. In each of these communities (one urban and two rural), 100 adult men were interviewed aided with a field herbarium. Fifty had a background in farming, and 50 worked in the secondary or tertiary sector as their main economic activity, totaling 300 interviews. Using a field herbarium with samples of 30 common and rare wild regional species, we documented visual recognition, knowledge of the local life form, generic and specific names and uses (five knowledge levels measuring knowledge depth). The relationship between sociodemographic variables and knowledge was analyzed with simple correlations. Differences between the three communities and the five knowledge levels were then evaluated with a discriminant analysis. A general linear analysis identified factors and covariables that influenced the observed differences. Differences between the groups with different economic activities were estimated with a t-test for independent samples. Most of the relationships found between sociodemographic variables and plant knowledge were expected: age and rurality were positively related with knowledge and years of formal schooling was negatively related. However, the somewhat less rural site had more traditional knowledge due to local circumstances. The general linear model explained 70–77% of the variation, a high value. It showed that economic activity was by far the most important factor influencing knowledge, by a factor of five. The interaction of locality and economic activity followed. The discriminant analysis assigned interviewees correctly to their localities in 94% of the cases, strengthening the evidence for intracultural variation. Both sociodemographic and historic intracultural differences heavily influence local knowledge. PMID:26986077

Investigation of charge weight and shock factor effect on non-linear transient structural response of rectangular plates subjected to underwater explosion (UNDEX) shock loading

NASA Astrophysics Data System (ADS)

Demir, Ozgur; Sahin, Abdurrahman; Yilmaz, Tamer

2012-09-01

Underwater explosion induced shock loads are capable of causing considerable structural damage. Investigations of the underwater explosion (UNDEX) effects on structures have seen continuous developments because of security risks. Most of the earlier experimental investigations were performed by military since the World War I. Subsequently; Cole [1] established mathematical relations for modeling underwater explosion shock loading, which were the outcome of many experimental investigations This study predicts and establishes the transient responses of a panel structure to underwater explosion shock loads using non-linear finite element code Ls-Dyna. Accordingly, in this study a new MATLAB code has been developed for predicting shock loading profile for different weight of explosive and different shock factors. Numerical analysis was performed for various test conditions and results are compared with Ramajeyathilagam's experimental study [8].

Measurement and Characterization of Concentrator Solar Cells II

NASA Technical Reports Server (NTRS)

Scheiman, Dave; Sater, Bernard L.; Chubb, Donald; Jenkins, Phillip; Snyder, Dave

2005-01-01

Concentrator solar cells are continuing to get more consideration for use in power systems. This interest is because concentrator systems can have a net lower cost per watt in solar cell materials plus ongoing improvements in sun-tracking technology. Quantitatively measuring the efficiency of solar cells under concentration is difficult. Traditionally, the light concentration on solar cells has been determined by using a ratio of the measured solar cell s short circuit current to that at one sun, this assumes that current changes proportionally with light intensity. This works well with low to moderate (<20 suns) concentration levels on "well-behaved" linear cells but does not apply when cells respond superlinearly, current increases faster than intensity, or sublinearly, current increases more slowly than intensity. This paper continues work on using view factors to determine the concentration level and linearity of the solar cell with mathematical view factor analysis and experimental results [1].

Monte Carlo modelling of Schottky diode for rectenna simulation

NASA Astrophysics Data System (ADS)

Bernuchon, E.; Aniel, F.; Zerounian, N.; Grimault-Jacquin, A. S.

2017-09-01

Before designing a detector circuit, the electrical parameters extraction of the Schottky diode is a critical step. This article is based on a Monte-Carlo (MC) solver of the Boltzmann Transport Equation (BTE) including different transport mechanisms at the metal-semiconductor contact such as image force effect or tunneling. The weight of tunneling and thermionic current is quantified according to different degrees of tunneling modelling. The I-V characteristic highlights the dependence of the ideality factor and the current saturation with bias. Harmonic Balance (HB) simulation on a rectifier circuit within Advanced Design System (ADS) software shows that considering non-linear ideality factor and saturation current for the electrical model of the Schottky diode does not seem essential. Indeed, bias independent values extracted in forward regime on I-V curve are sufficient. However, the non-linear series resistance extracted from a small signal analysis (SSA) strongly influences the conversion efficiency at low input powers.

A Double-Sided Linear Primary Permanent Magnet Vernier Machine

PubMed Central

2015-01-01

The purpose of this paper is to present a new double-sided linear primary permanent magnet (PM) vernier (DSLPPMV) machine, which can offer high thrust force, low detent force, and improved power factor. Both PMs and windings of the proposed machine are on the short translator, while the long stator is designed as a double-sided simple iron core with salient teeth so that it is very robust to transmit high thrust force. The key of this new machine is the introduction of double stator and the elimination of translator yoke, so that the inductance and the volume of the machine can be reduced. Hence, the proposed machine offers improved power factor and thrust force density. The electromagnetic performances of the proposed machine are analyzed including flux, no-load EMF, thrust force density, and inductance. Based on using the finite element analysis, the characteristics and performances of the proposed machine are assessed. PMID:25874250

A double-sided linear primary permanent magnet vernier machine.

PubMed

Du, Yi; Zou, Chunhua; Liu, Xianxing

2015-01-01

The purpose of this paper is to present a new double-sided linear primary permanent magnet (PM) vernier (DSLPPMV) machine, which can offer high thrust force, low detent force, and improved power factor. Both PMs and windings of the proposed machine are on the short translator, while the long stator is designed as a double-sided simple iron core with salient teeth so that it is very robust to transmit high thrust force. The key of this new machine is the introduction of double stator and the elimination of translator yoke, so that the inductance and the volume of the machine can be reduced. Hence, the proposed machine offers improved power factor and thrust force density. The electromagnetic performances of the proposed machine are analyzed including flux, no-load EMF, thrust force density, and inductance. Based on using the finite element analysis, the characteristics and performances of the proposed machine are assessed.

Perceptions of sexual partner safety.

PubMed

Masaro, C L; Dahinten, V S; Johnson, J; Ogilvie, G; Patrick, D M

2008-06-01

Many individuals select sexual partners based on assumed partner STI/HIV safety, yet few studies have investigated how these assumptions are formed. The objective of this research was to determine the extent to which partner safety beliefs were used to evaluate partner safety, and whether these beliefs influenced perceptions of personal STI/HIV risk. Participants (n = 317) recruited from an STI clinic completed a structured self-report questionnaire. A Partner Safety Beliefs Scale (PSBS) was developed to determine the factors that most influenced perceived partner safety. Exploratory factor analysis showed that a single factor accounted for 46% of the variance in the PSBS; with an internal consistency of 0.92. Linear regression was used to determine factors predictive of perceived personal STI/HIV risk. Participants endorsed statements indicating that knowing or trusting a sexual partner influences their beliefs about their partner's safety. Linear regression analysis indicated that education, income, number of sexual partners, and PSBS scores were significant predictors of perceived personal STI/HIV risk. The results of this study indicate that many individuals are relying on partner attributes and relationship characteristics when assessing the STI/HIV status of a sexual partner, and that this reliance is associated with a decreased perception of personal STI/HIV risk. Prevention campaigns need to acknowledge that people are likely to evaluate sexual partners whom they know and trust as safe. Dispelling erroneous beliefs about the ability to select safe partners is needed to promote safer sexual behavior.

Global sensitivity analysis for urban water quality modelling: Terminology, convergence and comparison of different methods

NASA Astrophysics Data System (ADS)

Vanrolleghem, Peter A.; Mannina, Giorgio; Cosenza, Alida; Neumann, Marc B.

2015-03-01

Sensitivity analysis represents an important step in improving the understanding and use of environmental models. Indeed, by means of global sensitivity analysis (GSA), modellers may identify both important (factor prioritisation) and non-influential (factor fixing) model factors. No general rule has yet been defined for verifying the convergence of the GSA methods. In order to fill this gap this paper presents a convergence analysis of three widely used GSA methods (SRC, Extended FAST and Morris screening) for an urban drainage stormwater quality-quantity model. After the convergence was achieved the results of each method were compared. In particular, a discussion on peculiarities, applicability, and reliability of the three methods is presented. Moreover, a graphical Venn diagram based classification scheme and a precise terminology for better identifying important, interacting and non-influential factors for each method is proposed. In terms of convergence, it was shown that sensitivity indices related to factors of the quantity model achieve convergence faster. Results for the Morris screening method deviated considerably from the other methods. Factors related to the quality model require a much higher number of simulations than the number suggested in literature for achieving convergence with this method. In fact, the results have shown that the term "screening" is improperly used as the method may exclude important factors from further analysis. Moreover, for the presented application the convergence analysis shows more stable sensitivity coefficients for the Extended-FAST method compared to SRC and Morris screening. Substantial agreement in terms of factor fixing was found between the Morris screening and Extended FAST methods. In general, the water quality related factors exhibited more important interactions than factors related to water quantity. Furthermore, in contrast to water quantity model outputs, water quality model outputs were found to be characterised by high non-linearity.

Perceptual distortion analysis of color image VQ-based coding

NASA Astrophysics Data System (ADS)

Charrier, Christophe; Knoblauch, Kenneth; Cherifi, Hocine

1997-04-01

It is generally accepted that a RGB color image can be easily encoded by using a gray-scale compression technique on each of the three color planes. Such an approach, however, fails to take into account correlations existing between color planes and perceptual factors. We evaluated several linear and non-linear color spaces, some introduced by the CIE, compressed with the vector quantization technique for minimum perceptual distortion. To study these distortions, we measured contrast and luminance of the video framebuffer, to precisely control color. We then obtained psychophysical judgements to measure how well these methods work to minimize perceptual distortion in a variety of color space.

Practical Session: Multiple Linear Regression

NASA Astrophysics Data System (ADS)

Clausel, M.; Grégoire, G.

2014-12-01

Three exercises are proposed to illustrate the simple linear regression. In the first one investigates the influence of several factors on atmospheric pollution. It has been proposed by D. Chessel and A.B. Dufour in Lyon 1 (see Sect. 6 of http://pbil.univ-lyon1.fr/R/pdf/tdr33.pdf) and is based on data coming from 20 cities of U.S. Exercise 2 is an introduction to model selection whereas Exercise 3 provides a first example of analysis of variance. Exercises 2 and 3 have been proposed by A. Dalalyan at ENPC (see Exercises 2 and 3 of http://certis.enpc.fr/~dalalyan/Download/TP_ENPC_5.pdf).

Linearity and sex-specificity of impact force prediction during a fall onto the outstretched hand using a single-damper-model.

PubMed

Kawalilak, C E; Lanovaz, J L; Johnston, J D; Kontulainen, S A

2014-09-01

To assess the linearity and sex-specificity of damping coefficients used in a single-damper-model (SDM) when predicting impact forces during the worst-case falling scenario from fall heights up to 25 cm. Using 3-dimensional motion tracking and an integrated force plate, impact forces and impact velocities were assessed from 10 young adults (5 males; 5 females), falling from planted knees onto outstretched arms, from a random order of drop heights: 3, 5, 7, 10, 15, 20, and 25 cm. We assessed the linearity and sex-specificity between impact forces and impact velocities across all fall heights using analysis of variance linearity test and linear regression, respectively. Significance was accepted at P<0.05. Association between impact forces and impact velocities up to 25 cm was linear (P=0.02). Damping coefficients appeared sex-specific (males: 627 Ns/m, R(2)=0.70; females: 421 Ns/m; R(2)=0.81; sex combined: 532 Ns/m, R(2)=0.61). A linear damping coefficient used in the SDM proved valid for predicting impact forces from fall heights up to 25 cm. RESULTS suggested the use of sex-specific damping coefficients when estimating impact force using the SDM and calculating the factor-of-risk for wrist fractures.

Time-domain induced polarization - an analysis of Cole-Cole parameter resolution and correlation using Markov Chain Monte Carlo inversion

NASA Astrophysics Data System (ADS)

Madsen, Line Meldgaard; Fiandaca, Gianluca; Auken, Esben; Christiansen, Anders Vest

2017-12-01

The application of time-domain induced polarization (TDIP) is increasing with advances in acquisition techniques, data processing and spectral inversion schemes. An inversion of TDIP data for the spectral Cole-Cole parameters is a non-linear problem, but by applying a 1-D Markov Chain Monte Carlo (MCMC) inversion algorithm, a full non-linear uncertainty analysis of the parameters and the parameter correlations can be accessed. This is essential to understand to what degree the spectral Cole-Cole parameters can be resolved from TDIP data. MCMC inversions of synthetic TDIP data, which show bell-shaped probability distributions with a single maximum, show that the Cole-Cole parameters can be resolved from TDIP data if an acquisition range above two decades in time is applied. Linear correlations between the Cole-Cole parameters are observed and by decreasing the acquisitions ranges, the correlations increase and become non-linear. It is further investigated how waveform and parameter values influence the resolution of the Cole-Cole parameters. A limiting factor is the value of the frequency exponent, C. As C decreases, the resolution of all the Cole-Cole parameters decreases and the results become increasingly non-linear. While the values of the time constant, τ, must be in the acquisition range to resolve the parameters well, the choice between a 50 per cent and a 100 per cent duty cycle for the current injection does not have an influence on the parameter resolution. The limits of resolution and linearity are also studied in a comparison between the MCMC and a linearized gradient-based inversion approach. The two methods are consistent for resolved models, but the linearized approach tends to underestimate the uncertainties for poorly resolved parameters due to the corresponding non-linear features. Finally, an MCMC inversion of 1-D field data verifies that spectral Cole-Cole parameters can also be resolved from TD field measurements.

Factors associated with motor performance among overweight and nonoverweight Tyrolean primary school children.

PubMed

Ruedl, Gerhard; Greier, Klaus; Kirschner, Werner; Kopp, Martin

2016-01-01

The increasing prevalence of overweight and obesity among children is often associated with motor deficits. Motor performance among children partly depends on modifiable factors, for example, weight status, electronic media use, sports club participation, and on nonmodifiable factors, for example, sex, age, migration background, or socio-economic status. To evaluate factors associated with motor performance among overweight and nonoverweight Tyrolean primary school children. Height, weight, and sport motor performance of primary school children were measured using the German motor performance test DMT 6-18. In addition, children were asked about migration background, sports club participation, and electronic media use in their room. A total of 304 children (48.7% girls) with a mean age of 8.0 ± 1.2 years were tested. In total, 61 (20.1%) children were overweight or obese. Regarding motor performance, nonoverweight children showed significantly higher total z-scores (106.8 ± 5.7 vs. 102.4 ± 6.8). For the total cohort, results of the multiple linear regression analysis (R (2) = 0.20) revealed that factors male sex (β = 0.12), nonoverweight children (β = 0.28), higher school grade (β = 0.23), sports club participation (β = 0.18),and > 2 weekly lessons of physical education (β = 0.26) were associated with an increased motor performance. For nonoverweight children results of the multiple linear regression analysis (R (2) = 0.09) found that a higher school grade (β = 0.17), sports club participation (β = 0.16),and more than 2 weekly lessons of physical education (β = 0.22) were associated with an increased motor performance. For the overweight children, results of the multiple linear regression analysis (R (2) = 0 .43) showed that no migration background (β = 0.23), a higher school grade (β = 0.55), sports club participation (β = 0.33) and more than 2 weekly lessons of physical education (β = 0.48) were associated with an increased motor performance. Regarding modifiable factors, motor performance among overweight and nonoverweight children is strongly associated with a higher number of weekly lessons in physical education. Therefore, daily lessons in physical education are strongly recommended to improve motor performance especially among overweight primary school children.

Unit Reynolds number, Mach number and pressure gradient effects on laminar-turbulent transition in two-dimensional boundary layers

NASA Astrophysics Data System (ADS)

Risius, Steffen; Costantini, Marco; Koch, Stefan; Hein, Stefan; Klein, Christian

2018-05-01

The influence of unit Reynolds number (Re_1=17.5× 106-80× 106 {m}^{-1}), Mach number (M= 0.35-0.77) and incompressible shape factor (H_{12} = 2.50-2.66) on laminar-turbulent boundary layer transition was systematically investigated in the Cryogenic Ludwieg-Tube Göttingen (DNW-KRG). For this investigation the existing two-dimensional wind tunnel model, PaLASTra, which offers a quasi-uniform streamwise pressure gradient, was modified to reduce the size of the flow separation region at its trailing edge. The streamwise temperature distribution and the location of laminar-turbulent transition were measured by means of temperature-sensitive paint (TSP) with a higher accuracy than attained in earlier measurements. It was found that for the modified PaLASTra model the transition Reynolds number (Re_{ {tr}}) exhibits a linear dependence on the pressure gradient, characterized by H_{12}. Due to this linear relation it was possible to quantify the so-called `unit Reynolds number effect', which is an increase of Re_{ {tr}} with Re_1. By a systematic variation of M, Re_1 and H_{12} in combination with a spectral analysis of freestream disturbances, a stabilizing effect of compressibility on boundary layer transition, as predicted by linear stability theory, was detected (`Mach number effect'). Furthermore, two expressions were derived which can be used to calculate the transition Reynolds number as a function of the amplitude of total pressure fluctuations, Re_1 and H_{12}. To determine critical N-factors, the measured transition locations were correlated with amplification rates, calculated by incompressible and compressible linear stability theory. By taking into account the spectral level of total pressure fluctuations at the frequency of the most amplified Tollmien-Schlichting wave at transition location, the scatter in the determined critical N-factors was reduced. Furthermore, the receptivity coefficients dependence on incidence angle of acoustic waves was used to correct the determined critical N-factors. Thereby, a found dependency of the determined critical N-factors on H_{12} decreased, leading to an average critical N-factor of about 9.5 with a standard deviation of σ ≈ 0.8.

CSOLNP: Numerical Optimization Engine for Solving Non-linearly Constrained Problems.

PubMed

Zahery, Mahsa; Maes, Hermine H; Neale, Michael C

2017-08-01

We introduce the optimizer CSOLNP, which is a C++ implementation of the R package RSOLNP (Ghalanos & Theussl, 2012, Rsolnp: General non-linear optimization using augmented Lagrange multiplier method. R package version, 1) alongside some improvements. CSOLNP solves non-linearly constrained optimization problems using a Sequential Quadratic Programming (SQP) algorithm. CSOLNP, NPSOL (a very popular implementation of SQP method in FORTRAN (Gill et al., 1986, User's guide for NPSOL (version 4.0): A Fortran package for nonlinear programming (No. SOL-86-2). Stanford, CA: Stanford University Systems Optimization Laboratory), and SLSQP (another SQP implementation available as part of the NLOPT collection (Johnson, 2014, The NLopt nonlinear-optimization package. Retrieved from http://ab-initio.mit.edu/nlopt)) are three optimizers available in OpenMx package. These optimizers are compared in terms of runtimes, final objective values, and memory consumption. A Monte Carlo analysis of the performance of the optimizers was performed on ordinal and continuous models with five variables and one or two factors. While the relative difference between the objective values is less than 0.5%, CSOLNP is in general faster than NPSOL and SLSQP for ordinal analysis. As for continuous data, none of the optimizers performs consistently faster than the others. In terms of memory usage, we used Valgrind's heap profiler tool, called Massif, on one-factor threshold models. CSOLNP and NPSOL consume the same amount of memory, while SLSQP uses 71 MB more memory than the other two optimizers.

Suppression of stimulated Brillouin scattering in optical fibers using a linearly chirped diode laser.

PubMed

White, J O; Vasilyev, A; Cahill, J P; Satyan, N; Okusaga, O; Rakuljic, G; Mungan, C E; Yariv, A

2012-07-02

The output of high power fiber amplifiers is typically limited by stimulated Brillouin scattering (SBS). An analysis of SBS with a chirped pump laser indicates that a chirp of 2.5 × 10(15) Hz/s could raise, by an order of magnitude, the SBS threshold of a 20-m fiber. A diode laser with a constant output power and a linear chirp of 5 × 10(15) Hz/s has been previously demonstrated. In a low-power proof-of-concept experiment, the threshold for SBS in a 6-km fiber is increased by a factor of 100 with a chirp of 5 × 10(14) Hz/s. A linear chirp will enable straightforward coherent combination of multiple fiber amplifiers, with electronic compensation of path length differences on the order of 0.2 m.

Nanoimaging of resonating hyperbolic polaritons in linear boron nitride antennas

PubMed Central

Alfaro-Mozaz, F. J.; Alonso-González, P.; Vélez, S.; Dolado, I.; Autore, M.; Mastel, S.; Casanova, F.; Hueso, L. E.; Li, P.; Nikitin, A. Y.; Hillenbrand, R.

2017-01-01

Polaritons in layered materials—including van der Waals materials—exhibit hyperbolic dispersion and strong field confinement, which makes them highly attractive for applications including optical nanofocusing, sensing and control of spontaneous emission. Here we report a near-field study of polaritonic Fabry–Perot resonances in linear antennas made of a hyperbolic material. Specifically, we study hyperbolic phonon–polaritons in rectangular waveguide antennas made of hexagonal boron nitride (h-BN, a prototypical van der Waals crystal). Infrared nanospectroscopy and nanoimaging experiments reveal sharp resonances with large quality factors around 100, exhibiting atypical modal near-field patterns that have no analogue in conventional linear antennas. By performing a detailed mode analysis, we can assign the antenna resonances to a single waveguide mode originating from the hybridization of hyperbolic surface phonon–polaritons (Dyakonov polaritons) that propagate along the edges of the h-BN waveguide. Our work establishes the basis for the understanding and design of linear waveguides, resonators, sensors and metasurface elements based on hyperbolic materials and metamaterials. PMID:28589941

Height and Weight Estimation From Anthropometric Measurements Using Machine Learning Regressions

PubMed Central

Fernandes, Bruno J. T.; Roque, Alexandre

2018-01-01

Height and weight are measurements explored to tracking nutritional diseases, energy expenditure, clinical conditions, drug dosages, and infusion rates. Many patients are not ambulant or may be unable to communicate, and a sequence of these factors may not allow accurate estimation or measurements; in those cases, it can be estimated approximately by anthropometric means. Different groups have proposed different linear or non-linear equations which coefficients are obtained by using single or multiple linear regressions. In this paper, we present a complete study of the application of different learning models to estimate height and weight from anthropometric measurements: support vector regression, Gaussian process, and artificial neural networks. The predicted values are significantly more accurate than that obtained with conventional linear regressions. In all the cases, the predictions are non-sensitive to ethnicity, and to gender, if more than two anthropometric parameters are analyzed. The learning model analysis creates new opportunities for anthropometric applications in industry, textile technology, security, and health care. PMID:29651366

Psychometric properties of the Intrinsic Motivation Inventory in a competitive sport setting: a confirmatory factor analysis.

PubMed

McAuley, E; Duncan, T; Tammen, V V

1989-03-01

The present study was designed to assess selected psychometric properties of the Intrinsic Motivation Inventory (IMI) (Ryan, 1982), a multidimensional measure of subjects' experience with regard to experimental tasks. Subjects (N = 116) competed in a basketball free-throw shooting game, following which they completed the IMI. The LISREL VI computer program was employed to conduct a confirmatory factor analysis to assess the tenability of a five factor hierarchical model representing four first-order factors or dimensions and a second-order general factor representing intrinsic motivation. Indices of model acceptability tentatively suggest that the sport data adequately fit the hypothesized five factor hierarchical model. Alternative models were tested but did not result in significant improvements in the goodness-of-fit indices, suggesting the proposed model to be the most accurate of the models tested. Coefficient alphas for the four dimensions and the overall scale indicated adequate reliability. The results are discussed with regard to the importance of accurate assessment of psychological constructs and the use of linear structural equations in confirming the factor structures of measures.

Factors associated with arterial stiffness in children aged 9-10 years

PubMed Central

Batista, Milena Santos; Mill, José Geraldo; Pereira, Taisa Sabrina Silva; Fernandes, Carolina Dadalto Rocha; Molina, Maria del Carmen Bisi

2015-01-01

OBJECTIVE To analyze the factors associated with stiffness of the great arteries in prepubertal children. METHODS This study with convenience sample of 231 schoolchildren aged 9-10 years enrolled in public and private schools in Vitória, ES, Southeastern Brazil, in 2010-2011. Anthropometric and hemodynamic data, blood pressure, and pulse wave velocity in the carotid-femoral segment were obtained. Data on current and previous health conditions were obtained by questionnaire and notes on the child’s health card. Multiple linear regression was applied to identify the partial and total contribution of the factors in determining the pulse wave velocity values. RESULTS Among the students, 50.2% were female and 55.4% were 10 years old. Among those classified in the last tertile of pulse wave velocity, 60.0% were overweight, with higher mean blood pressure, waist circumference, and waist-to-height ratio. Birth weight was not associated with pulse wave velocity. After multiple linear regression analysis, body mass index (BMI) and diastolic blood pressure remained in the model. CONCLUSIONS BMI was the most important factor in determining arterial stiffness in children aged 9-10 years. PMID:25902563

Statistical image quantification toward optimal scan fusion and change quantification

NASA Astrophysics Data System (ADS)

Potesil, Vaclav; Zhou, Xiang Sean

2007-03-01

Recent advance of imaging technology has brought new challenges and opportunities for automatic and quantitative analysis of medical images. With broader accessibility of more imaging modalities for more patients, fusion of modalities/scans from one time point and longitudinal analysis of changes across time points have become the two most critical differentiators to support more informed, more reliable and more reproducible diagnosis and therapy decisions. Unfortunately, scan fusion and longitudinal analysis are both inherently plagued with increased levels of statistical errors. A lack of comprehensive analysis by imaging scientists and a lack of full awareness by physicians pose potential risks in clinical practice. In this paper, we discuss several key error factors affecting imaging quantification, studying their interactions, and introducing a simulation strategy to establish general error bounds for change quantification across time. We quantitatively show that image resolution, voxel anisotropy, lesion size, eccentricity, and orientation are all contributing factors to quantification error; and there is an intricate relationship between voxel anisotropy and lesion shape in affecting quantification error. Specifically, when two or more scans are to be fused at feature level, optimal linear fusion analysis reveals that scans with voxel anisotropy aligned with lesion elongation should receive a higher weight than other scans. As a result of such optimal linear fusion, we will achieve a lower variance than naïve averaging. Simulated experiments are used to validate theoretical predictions. Future work based on the proposed simulation methods may lead to general guidelines and error lower bounds for quantitative image analysis and change detection.

Analysis of coals and biomass pyrolysis using the distributed activation energy model.

PubMed

Li, Zhengqi; Liu, Chunlong; Chen, Zhichao; Qian, Juan; Zhao, Wei; Zhu, Qunyi

2009-01-01

The thermal decomposition of coals and biomass was studied using thermogravimetric analysis with the distributed activation energy model. The integral method resulted in Datong bituminous coal conversions of 3-73% at activation energies of 100-486 kJ/mol. The corresponding frequency factors were e(19.5)-e(59.0)s(-1). Jindongnan lean coal conversions were 8-52% at activation energies of 100-462 kJ/mol. Their corresponding frequency factors were e(13.0)-e(55.8)s(-1). The conversion of corn-stalk skins were 1-84% at activation energies of 62-169 kJ/mol with frequency factors of e(10.8)-e(26.5)s(-1). Datong bituminous coal, Jindongnan lean coal and corn-stalk skins had approximate Gaussian distribution functions with linear ln k(0) to E relationships.

Non-parametric causality detection: An application to social media and financial data

NASA Astrophysics Data System (ADS)

Tsapeli, Fani; Musolesi, Mirco; Tino, Peter

2017-10-01

According to behavioral finance, stock market returns are influenced by emotional, social and psychological factors. Several recent works support this theory by providing evidence of correlation between stock market prices and collective sentiment indexes measured using social media data. However, a pure correlation analysis is not sufficient to prove that stock market returns are influenced by such emotional factors since both stock market prices and collective sentiment may be driven by a third unmeasured factor. Controlling for factors that could influence the study by applying multivariate regression models is challenging given the complexity of stock market data. False assumptions about the linearity or non-linearity of the model and inaccuracies on model specification may result in misleading conclusions. In this work, we propose a novel framework for causal inference that does not require any assumption about a particular parametric form of the model expressing statistical relationships among the variables of the study and can effectively control a large number of observed factors. We apply our method in order to estimate the causal impact that information posted in social media may have on stock market returns of four big companies. Our results indicate that social media data not only correlate with stock market returns but also influence them.

Design and comparative performance analysis of different chirping profiles of tanh apodized fiber Bragg grating and comparison with the dispersion compensation fiber for long-haul transmission system

NASA Astrophysics Data System (ADS)

Dar, Aasif Bashir; Jha, Rakesh Kumar

2017-03-01

Various dispersion compensation units are presented and evaluated in this paper. These dispersion compensation units include dispersion compensation fiber (DCF), DCF merged with fiber Bragg grating (FBG) (joint technique), and linear, square root, and cube root chirped tanh apodized FBG. For the performance evaluation 10 Gb/s NRZ transmission system over 100-km-long single-mode fiber is used. The three chirped FBGs are optimized individually to yield pulse width reduction percentage (PWRP) of 86.66, 79.96, 62.42% for linear, square root, and cube root, respectively. The DCF and Joint technique both provide a remarkable PWRP of 94.45 and 96.96%, respectively. The performance of optimized linear chirped tanh apodized FBG and DCF is compared for long-haul transmission system on the basis of quality factor of received signal. For both the systems maximum transmission distance is calculated such that quality factor is ≥ 6 at the receiver and result shows that performance of FBG is comparable to that of DCF with advantages of very low cost, small size and reduced nonlinear effects.

Investigation of Sunspot Area Varying with Sunspot Number

NASA Astrophysics Data System (ADS)

Li, K. J.; Li, F. Y.; Zhang, J.; Feng, W.

2016-11-01

The statistical relationship between sunspot area (SA) and sunspot number (SN) is investigated through analysis of their daily observation records from May 1874 to April 2015. For a total of 1607 days, representing 3 % of the total interval considered, either SA or SN had a value of zero while the other parameter did not. These occurrences most likely reflect the report of short-lived spots by a single observatory and subsequent averaging of zero values over multiple stations. The main results obtained are as follows: i) The number of spotless days around the minimum of a solar cycle is statistically negatively correlated with the maximum strength of solar activity of that cycle. ii) The probability distribution of SA generally decreases monotonically with SA, but the distribution of SN generally increases first, then it decreases as a whole. The different probability distribution of SA and SN should strengthen their non-linear relation, and the correction factor [k] in the definition of SN may be one of the factors that cause the non-linearity. iii) The non-linear relation of SA and SN indeed exists statistically, and it is clearer during the maximum epoch of a solar cycle.

Analysis of mortality data from the former USSR: age-period-cohort analysis.

PubMed

Willekens, F; Scherbov, S

1992-01-01

The objective of this article is to review research on age-period-cohort (APC) analysis of mortality and to trace the effects of contemporary and historical factors on mortality change in the former USSR. Several events in USSR history have exerted a lasting influence on its people. These influences may be captured by an APC model in which the period effects measure the impact of contemporary factors and the cohort effects the past history of individuals which cannot be attributed to age or stage in the life cycle. APC models are extensively applied in the study of mortality. This article presents the statistical theory of the APC models and shows that they belong to the family of generalized linear models. The parameters of the APC model may therefore be estimated by any package of loglinear analysis that allows for hybrid loglinear models.

Short-term, high-dose glucocorticoid treatment does not contribute to reduced bone mineral density in patients with multiple sclerosis.

PubMed

Olsson, A; Oturai, D B; Sørensen, P S; Oturai, P S; Oturai, A B

2015-10-01

Patients with multiple sclerosis (MS) are at increased risk of reduced bone mineral density (BMD). A contributing factor might be treatment with high-dose glucocorticoids (GCs). The objective of this paper is to assess bone mass in patients with MS and evaluate the importance of short-term, high-dose GC treatment and other risk factors that affect BMD in patients with MS. A total of 260 patients with MS received short-term high-dose GC treatment and had their BMD measured by dual x-ray absorptiometry. BMD was compared to a healthy age-matched reference population (Z-scores). Data regarding GCs, age, body mass index (BMI), serum 25(OH)D, disease duration and severity were collected retrospectively and analysed in a multiple linear regression analysis to evaluate the association between each risk factor and BMD. Osteopenia was present in 38% and osteoporosis in 7% of the study population. Mean Z-score was significantly below zero, indicating a decreased BMD in our MS patients. Multiple linear regression analysis showed no significant association between GCs and BMD. In contrast, age, BMI and disease severity were independently associated with both lumbar and femoral BMD. Reduced BMD was prevalent in patients with MS. GC treatment appears not to be the primary underlying cause of secondary osteoporosis in MS patients. © The Author(s), 2015.

A linear diode array (JFD-5) for match line in vivo dosimetry in photon and electron beams; evaluation for a chest wall irradiation technique.

PubMed

Essers, M; van Battum, L; Heijmen, B J

2001-11-01

In vivo dosimetry using thermoluminiscence detectors (TLD) is routinely performed in our institution to determine dose inhomogeneities in the match line region during chest wall irradiation. However, TLDs have some drawbacks: online in vivo dosimetry cannot be performed; generally, doses delivered by the contributing fields are not measured separately; measurement analysis is time consuming. To overcome these problems, the Joined Field Detector (JFD-5), a detector for match line in vivo dosimetry based on diodes, has been developed. This detector and its characteristics are presented. The JFD-5 is a linear array of 5 p-type diodes. The middle three diodes, used to measure the dose in the match line region, are positioned at 5-mm intervals. The outer two diodes, positioned at 3-cm distance from the central diode, are used to measure the dose in the two contributing fields. For three JFD-5 detectors, calibration factors for different energies, and sensitivity correction factors for non-standard field sizes, patient skin temperature, and oblique incidence have been determined. The accuracy of penumbra and match line dose measurements has been determined in phantom studies and in vivo. Calibration factors differ significantly between diodes and between photon and electron beams. However, conversion factors between energies can be applied. The correction factor for temperature is 0.35%/ degrees C, and for oblique incidence 2% at maximum. The penumbra measured with the JFD-5 agrees well with film and linear diode array measurements. JFD-5 in vivo match line dosimetry reproducibility was 2.0% (1 SD) while the agreement with TLD was 0.999+/-0.023 (1 SD). The JFD-5 can be used for accurate, reproducible, and fast on-line match line in vivo dosimetry.

Effect of the physicochemical parameters of benzimidazole molecules on their retention by a nonpolar sorbent from an aqueous acetonitrile solution

NASA Astrophysics Data System (ADS)

Shafigulin, R. V.; Safonova, I. A.; Bulanova, A. V.

2015-09-01

The effect of the structure of benzimidazoles on their chromatographic retention on octadecyl silica gel from an aqueous acetonitrile eluent was studied. One- and many-parameter correlation equations were obtained by linear regression analysis, and their prognostic potential in determining the retention factors of benzimidazoles under study was analyzed.

Response Rate and Teaching Effectiveness in Institutional Student Evaluation of Teaching: A Multiple Linear Regression Study

ERIC Educational Resources Information Center

Al-Maamari, Faisal

2015-01-01

It is important to consider the question of whether teacher-, course-, and student-related factors affect student ratings of instructors in Student Evaluation of Teaching (SET) in English Language Teaching (ELT). This paper reports on a statistical analysis of SET in two large EFL programmes at a university setting in the Sultanate of Oman. I…

Generalized linear models and point count data: statistical considerations for the design and analysis of monitoring studies

Treesearch

Nathaniel E. Seavy; Suhel Quader; John D. Alexander; C. John Ralph

2005-01-01

The success of avian monitoring programs to effectively guide management decisions requires that studies be efficiently designed and data be properly analyzed. A complicating factor is that point count surveys often generate data with non-normal distributional properties. In this paper we review methods of dealing with deviations from normal assumptions, and we focus...

Examining the Influence of Selected Factors on Perceived Co-Op Work-Term Quality from a Student Perspective

ERIC Educational Resources Information Center

Drewery, David; Nevison, Colleen; Pretti, T. Judene; Cormier, Lauren; Barclay, Sage; Pennaforte, Antoine

2016-01-01

This study discusses and tests a conceptual model of co-op work-term quality from a student perspective. Drawing from an earlier exploration of co-op students' perceptions of work-term quality, variables related to role characteristics, interpersonal dynamics, and organizational elements were used in a multiple linear regression analysis to…

Calibration sets and the accuracy of vibrational scaling factors: A case study with the X3LYP hybrid functional

NASA Astrophysics Data System (ADS)

Teixeira, Filipe; Melo, André; Cordeiro, M. Natália D. S.

2010-09-01

A linear least-squares methodology was used to determine the vibrational scaling factors for the X3LYP density functional. Uncertainties for these scaling factors were calculated according to the method devised by Irikura et al. [J. Phys. Chem. A 109, 8430 (2005)]. The calibration set was systematically partitioned according to several of its descriptors and the scaling factors for X3LYP were recalculated for each subset. The results show that the scaling factors are only significant up to the second digit, irrespective of the calibration set used. Furthermore, multivariate statistical analysis allowed us to conclude that the scaling factors and the associated uncertainties are independent of the size of the calibration set and strongly suggest the practical impossibility of obtaining vibrational scaling factors with more than two significant digits.

Calibration sets and the accuracy of vibrational scaling factors: a case study with the X3LYP hybrid functional.

PubMed

Teixeira, Filipe; Melo, André; Cordeiro, M Natália D S

2010-09-21

A linear least-squares methodology was used to determine the vibrational scaling factors for the X3LYP density functional. Uncertainties for these scaling factors were calculated according to the method devised by Irikura et al. [J. Phys. Chem. A 109, 8430 (2005)]. The calibration set was systematically partitioned according to several of its descriptors and the scaling factors for X3LYP were recalculated for each subset. The results show that the scaling factors are only significant up to the second digit, irrespective of the calibration set used. Furthermore, multivariate statistical analysis allowed us to conclude that the scaling factors and the associated uncertainties are independent of the size of the calibration set and strongly suggest the practical impossibility of obtaining vibrational scaling factors with more than two significant digits.

On the equivalence of case-crossover and time series methods in environmental epidemiology.

PubMed

Lu, Yun; Zeger, Scott L

2007-04-01

The case-crossover design was introduced in epidemiology 15 years ago as a method for studying the effects of a risk factor on a health event using only cases. The idea is to compare a case's exposure immediately prior to or during the case-defining event with that same person's exposure at otherwise similar "reference" times. An alternative approach to the analysis of daily exposure and case-only data is time series analysis. Here, log-linear regression models express the expected total number of events on each day as a function of the exposure level and potential confounding variables. In time series analyses of air pollution, smooth functions of time and weather are the main confounders. Time series and case-crossover methods are often viewed as competing methods. In this paper, we show that case-crossover using conditional logistic regression is a special case of time series analysis when there is a common exposure such as in air pollution studies. This equivalence provides computational convenience for case-crossover analyses and a better understanding of time series models. Time series log-linear regression accounts for overdispersion of the Poisson variance, while case-crossover analyses typically do not. This equivalence also permits model checking for case-crossover data using standard log-linear model diagnostics.

STUDYING THE POLARIZATION OF HARD X-RAY SOLAR FLARES WITH THE GAMMA RAY POLARIMETER EXPERIMENT (GRAPE)

NASA Astrophysics Data System (ADS)

Ertley, Camden

2014-01-01

The degree of linear polarization of hard X-rays (50-500 keV) can provide a better understanding of the particle acceleration mechanisms and the emission of radiation during solar flares. Difficulties in measuring the linear polarization has limited the ability of past experiments to place constraints on solar flare models. The Gamma RAy Polarimeter Experiment (GRAPE) is a balloon-borne Compton polarimeter designed to measure polarization in the 50 - 500 keV energy range. This energy range minimizes the thermal contamination that can potentially affect measurements at lower energies. This research focuses on the analysis of data acquired during the first high altitude balloon flight of the GRAPE payload in 2011. During this 26 hour balloon flight two M-class flares were observed. The analysis effort includes the development of a Monte Carlo simulation of the full instrument payload with the GEANT4 toolkit. The simulations were used in understanding the background environment, creating a response matrix for the deconvolution of the energy loss spectra, and determining the modulation factor for a 100% linearly polarized source. We report on the results from the polarization analysis of the solar flare data. The polarization and spectral data can be used to further our understanding of particle acceleration in the context of current solar flare models.

Correcting for population structure and kinship using the linear mixed model: theory and extensions.

PubMed

Hoffman, Gabriel E

2013-01-01

Population structure and kinship are widespread confounding factors in genome-wide association studies (GWAS). It has been standard practice to include principal components of the genotypes in a regression model in order to account for population structure. More recently, the linear mixed model (LMM) has emerged as a powerful method for simultaneously accounting for population structure and kinship. The statistical theory underlying the differences in empirical performance between modeling principal components as fixed versus random effects has not been thoroughly examined. We undertake an analysis to formalize the relationship between these widely used methods and elucidate the statistical properties of each. Moreover, we introduce a new statistic, effective degrees of freedom, that serves as a metric of model complexity and a novel low rank linear mixed model (LRLMM) to learn the dimensionality of the correction for population structure and kinship, and we assess its performance through simulations. A comparison of the results of LRLMM and a standard LMM analysis applied to GWAS data from the Multi-Ethnic Study of Atherosclerosis (MESA) illustrates how our theoretical results translate into empirical properties of the mixed model. Finally, the analysis demonstrates the ability of the LRLMM to substantially boost the strength of an association for HDL cholesterol in Europeans.

Schizophrenia with prominent catatonic features ('catatonic schizophrenia'). II. Factor analysis of the catatonic syndrome.

PubMed

Ungvari, Gabor S; Goggins, William; Leung, Siu-Kau; Gerevich, Jozsef

2007-03-30

Previous factor analyses of catatonia have yielded conflicting results for several reasons including small and/or diagnostically heterogeneous samples and incomparability or lack of standardized assessment. This study examined the factor structure of catatonia in a large, diagnostically homogenous sample of patients with chronic schizophrenia using standardized rating instruments. A random sample of 225 Chinese inpatients diagnosed with schizophrenia according to DSM-IV criteria were selected from the long-stay wards of a psychiatric hospital. They were assessed with a battery of rating scales measuring psychopathology, extrapyramidal motor status, and level of functioning. Catatonia was rated using the Bush-Francis Catatonia Rating Scale. Factor analysis using principal component analysis and Varimax rotation with Kaiser normalization was performed. Four factors were identified with Eigenvalues of 3.27, 2.58, 2.28 and 1.88. The percentage of variance explained by each of the four factors was 15.9%, 12.0%, 11.8% and 10.2% respectively, and together they explained 49.9% of the total variance. Factor 1 loaded on "negative/withdrawn" phenomena, Factor 2 on "automatic" phenomena, Factor 3 on "repetitive/echo" phenomena and Factor 4 on "agitated/resistive" phenomena. In multivariate linear regression analysis negative symptoms and akinesia were associated with 'negative' catatonic symptoms, antipsychotic doses and atypical antipsychotics with 'automatic' symptoms, length of current admission, severity of psychopathology and younger age at onset with 'repetitive' symptoms and age, poor functioning and severity of psychopathology with 'agitated' catatonic symptom scores. The results support recent findings that four main factors underlie catatonic signs/symptoms in chronic schizophrenia.

Bio-psychosocial factors are associated with pain intensity, physical functioning, and ability to work in female healthcare personnel with recurrent low back pain.

PubMed

Taulaniemi, Annika; Kuusinen, Lotta; Tokola, Kari; Kankaanpää, Markku; Suni, Jaana H

2017-08-31

To investigate associations of various bio-psychosocial factors with bodily pain, physical func-tioning, and ability to work in low back pain. Cross-sectional study. A total of 219 female healthcare workers with recurrent non-specific low back pain. Associations between several physical and psychosocial factors and: (i) bodily pain, (ii) physical functioning and (iii) ability to work were studied. Variables with statistically significant associations (p < 0.05) in bivariate analysis were set within a generalized linear model to analyse their relationship with each dependent variable. In generalized linear model analysis, perceived work-induced lumbar exertion (p < 0.001), multi-site pain (p <0.001) and work-related fear-avoidance beliefs (FAB-W) (p = 0.02) best explained bodily pain. Multi-site pain (p < 0.001), lumbar exertion (p = 0.005), FAB-W (p = 0.01) and physical performance in figure-of-eight running (p = 0.01) and modified push-ups (p = 0.05) best explained physical functioning; FAB-W (p <0.001), lumbar exertion (p = 0.003), depression (p = 0.01) and recovery after work (p = 0.03) best explained work ability. In bivariate analysis lumbar exertion was associated with poor physical performance. FAB-W and work-induced lumbar exertion were associated with levels of pain, physical functioning and ability to work. Poor physical performance capacity was associated with work-induced lumbar exertion. Interventions that aim to reduce fear-avoidance and increase fitness capacity might be beneficial.

Stress Induced in Periodontal Ligament under Orthodontic Loading (Part II): A Comparison of Linear Versus Non-Linear Fem Study.

PubMed

Hemanth, M; Deoli, Shilpi; Raghuveer, H P; Rani, M S; Hegde, Chatura; Vedavathi, B

2015-09-01

Simulation of periodontal ligament (PDL) using non-linear finite element method (FEM) analysis gives better insight into understanding of the biology of tooth movement. The stresses in the PDL were evaluated for intrusion and lingual root torque using non-linear properties. A three-dimensional (3D) FEM model of the maxillary incisors was generated using Solidworks modeling software. Stresses in the PDL were evaluated for intrusive and lingual root torque movements by 3D FEM using ANSYS software. These stresses were compared with linear and non-linear analyses. For intrusive and lingual root torque movements, distribution of stress over the PDL was within the range of optimal stress value as proposed by Lee, but was exceeding the force system given by Proffit as optimum forces for orthodontic tooth movement with linear properties. When same force load was applied in non-linear analysis, stresses were more compared to linear analysis and were beyond the optimal stress range as proposed by Lee for both intrusive and lingual root torque. To get the same stress as linear analysis, iterations were done using non-linear properties and the force level was reduced. This shows that the force level required for non-linear analysis is lesser than that of linear analysis.

What controls the stable isotope composition of precipitation in the Mekong Delta? A model-based statistical approach

NASA Astrophysics Data System (ADS)

Le Duy, Nguyen; Heidbüchel, Ingo; Meyer, Hanno; Merz, Bruno; Apel, Heiko

2018-02-01

This study analyzes the influence of local and regional climatic factors on the stable isotopic composition of rainfall in the Vietnamese Mekong Delta (VMD) as part of the Asian monsoon region. It is based on 1.5 years of weekly rainfall samples. In the first step, the isotopic composition of the samples is analyzed by local meteoric water lines (LMWLs) and single-factor linear correlations. Additionally, the contribution of several regional and local factors is quantified by multiple linear regression (MLR) of all possible factor combinations and by relative importance analysis. This approach is novel for the interpretation of isotopic records and enables an objective quantification of the explained variance in isotopic records for individual factors. In this study, the local factors are extracted from local climate records, while the regional factors are derived from atmospheric backward trajectories of water particles. The regional factors, i.e., precipitation, temperature, relative humidity and the length of backward trajectories, are combined with equivalent local climatic parameters to explain the response variables δ18O, δ2H, and d-excess of precipitation at the station of measurement. The results indicate that (i) MLR can better explain the isotopic variation in precipitation (R2 = 0.8) compared to single-factor linear regression (R2 = 0.3); (ii) the isotopic variation in precipitation is controlled dominantly by regional moisture regimes (˜ 70 %) compared to local climatic conditions (˜ 30 %); (iii) the most important climatic parameter during the rainy season is the precipitation amount along the trajectories of air mass movement; (iv) the influence of local precipitation amount and temperature is not significant during the rainy season, unlike the regional precipitation amount effect; (v) secondary fractionation processes (e.g., sub-cloud evaporation) can be identified through the d-excess and take place mainly in the dry season, either locally for δ18O and δ2H, or along the air mass trajectories for d-excess. The analysis shows that regional and local factors vary in importance over the seasons and that the source regions and transport pathways, and particularly the climatic conditions along the pathways, have a large influence on the isotopic composition of rainfall. Although the general results have been reported qualitatively in previous studies (proving the validity of the approach), the proposed method provides quantitative estimates of the controlling factors, both for the whole data set and for distinct seasons. Therefore, it is argued that the approach constitutes an advancement in the statistical analysis of isotopic records in rainfall that can supplement or precede more complex studies utilizing atmospheric models. Due to its relative simplicity, the method can be easily transferred to other regions, or extended with other factors. The results illustrate that the interpretation of the isotopic composition of precipitation as a recorder of local climatic conditions, as for example performed for paleorecords of water isotopes, may not be adequate in the southern part of the Indochinese Peninsula, and likely neither in other regions affected by monsoon processes. However, the presented approach could open a pathway towards better and seasonally differentiated reconstruction of paleoclimates based on isotopic records.

Determinants of stunting at 6, 12, 24 and 60 months and postnatal linear growth in Pakistani children.

PubMed

Saleemi, M A; Ashraf, R N; Mellander, L; Zaman, S

2001-11-01

A "nested" case-control design was used to identify cases from a longitudinally followed cohort of 1236 newborns registered during 1984-1987, living in three socioeconomically different areas. The children had a length <-2SDS (standard deviation scores) at 6, 12, 24 and 60 mo of age using the NCHS reference. The controls were matched for gender, area and month of birth. A logistic regression analysis was used for determining the risk factors for stunting at each age. Postnatal linear growth was also examined in these two groups of children and body size was compared with the NCHS reference and that of upper-middle-class children (n = 240). At 6 mo of age, prematurity and duration of breastfeeding showed a significant association with stunting. At 12 mo, maternal height, birthweight and stunting at 6 mo, while at 24 mo, stunting at 6, 12 and 18 mo were identified as important factors. At 60 mo, no other factors besides previous stunting could be identified. The mean height reached at 60 mo showed a deficit of 6 and 13 cm for the controls and the cases, respectively, compared to the NCHS reference. Twenty-eight percent of the children from the two poor areas who were stunted at 6 mo had improved by 60 mo of age. The risk factors for stunting varied at different ages, relating more to feeding at early ages and to previous stunting, predominantly at higher ages. The linear growth showed that faltering increased with age when cases and controls were treated separately. Recovery from stunting could also be demonstrated.

Performance analysis of an integrated GPS/inertial attitude determination system. M.S. Thesis - MIT

NASA Technical Reports Server (NTRS)

Sullivan, Wendy I.

1994-01-01

The performance of an integrated GPS/inertial attitude determination system is investigated using a linear covariance analysis. The principles of GPS interferometry are reviewed, and the major error sources of both interferometers and gyroscopes are discussed and modeled. A new figure of merit, attitude dilution of precision (ADOP), is defined for two possible GPS attitude determination methods, namely single difference and double difference interferometry. Based on this figure of merit, a satellite selection scheme is proposed. The performance of the integrated GPS/inertial attitude determination system is determined using a linear covariance analysis. Based on this analysis, it is concluded that the baseline errors (i.e., knowledge of the GPS interferometer baseline relative to the vehicle coordinate system) are the limiting factor in system performance. By reducing baseline errors, it should be possible to use lower quality gyroscopes without significantly reducing performance. For the cases considered, single difference interferometry is only marginally better than double difference interferometry. Finally, the performance of the system is found to be relatively insensitive to the satellite selection technique.

Linear Ordinary Differential Equations with Constant Coefficients. Revisiting the Impulsive Response Method Using Factorization

ERIC Educational Resources Information Center

Camporesi, Roberto

2011-01-01

We present an approach to the impulsive response method for solving linear constant-coefficient ordinary differential equations based on the factorization of the differential operator. The approach is elementary, we only assume a basic knowledge of calculus and linear algebra. In particular, we avoid the use of distribution theory, as well as of…

Interpreting the g loadings of intelligence test composite scores in light of Spearman's law of diminishing returns.

PubMed

Reynolds, Matthew R

2013-03-01

The linear loadings of intelligence test composite scores on a general factor (g) have been investigated recently in factor analytic studies. Spearman's law of diminishing returns (SLODR), however, implies that the g loadings of test scores likely decrease in magnitude as g increases, or they are nonlinear. The purpose of this study was to (a) investigate whether the g loadings of composite scores from the Differential Ability Scales (2nd ed.) (DAS-II, C. D. Elliott, 2007a, Differential Ability Scales (2nd ed.). San Antonio, TX: Pearson) were nonlinear and (b) if they were nonlinear, to compare them with linear g loadings to demonstrate how SLODR alters the interpretation of these loadings. Linear and nonlinear confirmatory factor analysis (CFA) models were used to model Nonverbal Reasoning, Verbal Ability, Visual Spatial Ability, Working Memory, and Processing Speed composite scores in four age groups (5-6, 7-8, 9-13, and 14-17) from the DAS-II norming sample. The nonlinear CFA models provided better fit to the data than did the linear models. In support of SLODR, estimates obtained from the nonlinear CFAs indicated that g loadings decreased as g level increased. The nonlinear portion for the nonverbal reasoning loading, however, was not statistically significant across the age groups. Knowledge of general ability level informs composite score interpretation because g is less likely to produce differences, or is measured less, in those scores at higher g levels. One implication is that it may be more important to examine the pattern of specific abilities at higher general ability levels. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Analysis and compensation for the effect of the catheter position on image intensities in intravascular optical coherence tomography

NASA Astrophysics Data System (ADS)

Liu, Shengnan; Eggermont, Jeroen; Wolterbeek, Ron; Broersen, Alexander; Busk, Carol A. G. R.; Precht, Helle; Lelieveldt, Boudewijn P. F.; Dijkstra, Jouke

2016-12-01

Intravascular optical coherence tomography (IVOCT) is an imaging technique that is used to analyze the underlying cause of cardiovascular disease. Because a catheter is used during imaging, the intensities can be affected by the catheter position. This work aims to analyze the effect of the catheter position on IVOCT image intensities and to propose a compensation method to minimize this effect in order to improve the visualization and the automatic analysis of IVOCT images. The effect of catheter position is modeled with respect to the distance between the catheter and the arterial wall (distance-dependent factor) and the incident angle onto the arterial wall (angle-dependent factor). A light transmission model incorporating both factors is introduced. On the basis of this model, the interaction effect of both factors is estimated with a hierarchical multivariant linear regression model. Statistical analysis shows that IVOCT intensities are significantly affected by both factors with p<0.001, as either aspect increases the intensity decreases. This effect differs for different pullbacks. The regression results were used to compensate for this effect. Experiments show that the proposed compensation method can improve the performance of the automatic bioresorbable vascular scaffold strut detection.

Stress analysis of ribbon parachutes

NASA Technical Reports Server (NTRS)

Reynolds, D. T.; Mullins, W. M.

1975-01-01

An analytical method has been developed for determining the internal load distribution for ribbon parachutes subjected to known riser and aerodynamic forces. Finite elements with non-linear elastic properties represent the parachute structure. This method is an extension of the analysis previously developed by the authors and implemented in the digital computer program CANO. The present analysis accounts for the effect of vertical ribbons in the solution for canopy shape and stress distribution. Parametric results are presented which relate the canopy stress distribution to such factors as vertical ribbon strength, number of gores, and gore shape in a ribbon parachute.

Linear ordinary differential equations with constant coefficients. Revisiting the impulsive response method using factorization

NASA Astrophysics Data System (ADS)

Camporesi, Roberto

2011-06-01

We present an approach to the impulsive response method for solving linear constant-coefficient ordinary differential equations based on the factorization of the differential operator. The approach is elementary, we only assume a basic knowledge of calculus and linear algebra. In particular, we avoid the use of distribution theory, as well as of the other more advanced approaches: Laplace transform, linear systems, the general theory of linear equations with variable coefficients and the variation of constants method. The approach presented here can be used in a first course on differential equations for science and engineering majors.

The isoform A of reticulon-4 (Nogo-A) in cerebrospinal fluid of primary brain tumor patients: influencing factors.

PubMed

Koper, Olga Martyna; Kamińska, Joanna; Milewska, Anna; Sawicki, Karol; Mariak, Zenon; Kemona, Halina; Matowicka-Karna, Joanna

2018-05-18

The influence of isoform A of reticulon-4 (Nogo-A), also known as neurite outgrowth inhibitor, on primary brain tumor development was reported. Therefore the aim was the evaluation of Nogo-A concentrations in cerebrospinal fluid (CSF) and serum of brain tumor patients compared with non-tumoral individuals. All serum results, except for two cases, obtained both in brain tumors and non-tumoral individuals, were below the lower limit of ELISA detection. Cerebrospinal fluid Nogo-A concentrations were significantly lower in primary brain tumor patients compared to non-tumoral individuals. The univariate linear regression analysis found that if white blood cell count increases by 1 × 10 3 /μL, the mean cerebrospinal fluid Nogo-A concentration value decreases 1.12 times. In the model of multiple linear regression analysis predictor variables influencing cerebrospinal fluid Nogo-A concentrations included: diagnosis, sex, and sodium level. The mean cerebrospinal fluid Nogo-A concentration value was 1.9 times higher for women in comparison to men. In the astrocytic brain tumor group higher sodium level occurs with lower cerebrospinal fluid Nogo-A concentrations. We found the opposite situation in non-tumoral individuals. Univariate linear regression analysis revealed, that cerebrospinal fluid Nogo-A concentrations change in relation to white blood cell count. In the created model of multiple linear regression analysis we found, that within predictor variables influencing CSF Nogo-A concentrations were diagnosis, sex, and sodium level. Results may be relevant to the search for cerebrospinal fluid biomarkers and potential therapeutic targets in primary brain tumor patients. Nogo-A concentrations were tested by means of enzyme-linked immunosorbent assay (ELISA).

Operational and customer relationship management considerations of electronic prescribing among pharmacists.

PubMed

Smith, Alan D; Motley, Darlene

2009-01-01

Technology in healthcare environments has increasingly become a vital way to communicate vital information in a safe, reliable, precise and secure manner. Healthcare is an arena that is constantly changing and very fast paced, but adoption of electronic prescribing (e-prescribing) has been comparatively slow and painful in the USA. Medical professionals need a system to communicate medications and diagnosis, with patients' safety as the major consideration, especially with the many complexities associated with drug-interactions and allergies. Via multivariate analysis and linear regression analysis, it was found that degree of e-prescribing acceptance is highly predictable by constructs of Technological Sophistication, Operational Factors and Maturity Factors, which are very stable ease-of-use variables derived from the TAM Model by Davis (1989).

Blood lead levels and risk factors in pregnant women from Durango, Mexico.

PubMed

La-Llave-León, Osmel; Estrada-Martínez, Sergio; Manuel Salas-Pacheco, José; Peña-Elósegui, Rocío; Duarte-Sustaita, Jaime; Candelas Rangel, Jorge-Luís; García Vargas, Gonzalo

2011-01-01

In this cross-sectional study the authors determined blood lead levels (BLLs) and some risk factors for lead exposure in pregnant women. Two hundred ninety-nine pregnant women receiving medical attention by the Secretary of Health, State of Durango, Mexico, participated in this study between 2007 and 2008. BLLs were evaluated with graphite furnace atomic absorption spectrometry. The authors used Student t test, 1-way analysis of variance (ANOVA), and linear regression as statistical treatments. BLLs ranged from 0.36 to 23.6 μg/dL (mean = 2.79 μg/dL, standard deviation = 2.14). Multivariate analysis showed that the main predictors of BLLs were working in a place where lead is used, using lead glazed pottery, and eating soil.

[Relationship between high-sensitivity C-reactive protein and obesity/metabolic syndrome in children].

PubMed

Chen, Fangfang; Wang, Wenpeng; Teng, Yue; Hou, Dongqing; Zhao, Xiaoyuan; Yang, Ping; Yan, Yinkun; Mi, Jie

2014-06-01

To explore the relationship between high-sensitivity C-reactive protein (hsCRP) and obesity/metabolic syndrome (MetS) related factors in children. 403 children aged 10-14 and born in Beijing were involved in this study. Height, weight, waist circumference, fat mass percentage (Fat%), blood pressure (BP), hsCRP, triglyceride (TG), total cholesterol (TC), fasting plasma glucose (FPG), high and low density lipoprotein cholesterol (HDL-C, LDL-C) were observed among these children. hsCRP was transformed with base 10 logarithm (lgCRP). MetS was defined according to the International Diabetes Federation 2007 definition. Associations between MetS related components and hsCRP were tested using partial correlation analysis, analysis of covariance and linear regression models. 1) lgCRP was positively correlated with BMI, waist circumference, Fat%,BP, FPG, LDL-C and TC while negatively correlated with HDL-C. With BMI under control, the relationships disappeared, but LDL-C (r = 0.102). 2) The distributions of lgCRP showed obvious differences in all the metabolic indices, in most groups, respectively. With BMI under control, close relationships between lgCRP and high blood pressure/high TG disappeared and the relationship with MetS weakened. 3) Through linear regression models, factors as waist circumference, BMI, Fat% were the strongest factors related to hsCRP, followed by systolic BP, HDL-C, diastolic BP, TG and LDL-C. With BMI under control, the relationships disappeared, but LDL-C(β = 0.045). hsCRP was correlated with child obesity, lipid metabolism and MetS. Waist circumference was the strongest factors related with hsCRP. Obesity was the strongest and the independent influencing factor of hsCRP.

Cement Leakage in Percutaneous Vertebral Augmentation for Osteoporotic Vertebral Compression Fractures: Analysis of Risk Factors.

PubMed

Xie, Weixing; Jin, Daxiang; Ma, Hui; Ding, Jinyong; Xu, Jixi; Zhang, Shuncong; Liang, De

2016-05-01

The risk factors for cement leakage were retrospectively reviewed in 192 patients who underwent percutaneous vertebral augmentation (PVA). To discuss the factors related to the cement leakage in PVA procedure for the treatment of osteoporotic vertebral compression fractures. PVA is widely applied for the treatment of osteoporotic vertebral fractures. Cement leakage is a major complication of this procedure. The risk factors for cement leakage were controversial. A retrospective review of 192 patients who underwent PVA was conducted. The following data were recorded: age, sex, bone density, number of fractured vertebrae before surgery, number of treated vertebrae, severity of the treated vertebrae, operative approach, volume of injected bone cement, preoperative vertebral compression ratio, preoperative local kyphosis angle, intraosseous clefts, preoperative vertebral cortical bone defect, and ratio and type of cement leakage. To study the correlation between each factor and cement leakage ratio, bivariate regression analysis was employed to perform univariate analysis, whereas multivariate linear regression analysis was employed to perform multivariate analysis. The study included 192 patients (282 treated vertebrae), and cement leakage occurred in 100 vertebrae (35.46%). The vertebrae with preoperative cortical bone defects generally exhibited higher cement leakage ratio, and the leakage is typically type C. Vertebrae with intact cortical bones before the procedure tend to experience type S leakage. Univariate analysis showed that patient age, bone density, number of fractured vertebrae before surgery, and vertebral cortical bone were associated with cement leakage ratio (P<0.05). Multivariate analysis showed that the main factors influencing bone cement leakage are bone density and vertebral cortical bone defect, with standardized partial regression coefficients of -0.085 and 0.144, respectively. High bone density and vertebral cortical bone defect are independent risk factors associated with bone cement leakage.

Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data.

PubMed

Ying, Gui-Shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

2017-04-01

To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field in the elderly. When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI -0.03 to 0.32D, p = 0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, p = 0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller p-values, while analysis of the worse eye provided larger p-values than mixed effects models and marginal models. In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision.

Selecting the correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm in bioanalytical LC-MS/MS assays and impacts of using incorrect weighting factors on curve stability, data quality, and assay performance.

PubMed

Gu, Huidong; Liu, Guowen; Wang, Jian; Aubry, Anne-Françoise; Arnold, Mark E

2014-09-16

A simple procedure for selecting the correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm in bioanalytical LC-MS/MS assays is reported. The correct weighting factor is determined by the relationship between the standard deviation of instrument responses (σ) and the concentrations (x). The weighting factor of 1, 1/x, or 1/x(2) should be selected if, over the entire concentration range, σ is a constant, σ(2) is proportional to x, or σ is proportional to x, respectively. For the first time, we demonstrated with detailed scientific reasoning, solid historical data, and convincing justification that 1/x(2) should always be used as the weighting factor for all bioanalytical LC-MS/MS assays. The impacts of using incorrect weighting factors on curve stability, data quality, and assay performance were thoroughly investigated. It was found that the most stable curve could be obtained when the correct weighting factor was used, whereas other curves using incorrect weighting factors were unstable. It was also found that there was a very insignificant impact on the concentrations reported with calibration curves using incorrect weighting factors as the concentrations were always reported with the passing curves which actually overlapped with or were very close to the curves using the correct weighting factor. However, the use of incorrect weighting factors did impact the assay performance significantly. Finally, the difference between the weighting factors of 1/x(2) and 1/y(2) was discussed. All of the findings can be generalized and applied into other quantitative analysis techniques using calibration curves with weighted least-squares regression algorithm.

Modified chloride diffusion model for concrete under the coupling effect of mechanical load and chloride salt environment

NASA Astrophysics Data System (ADS)

Lei, Mingfeng; Lin, Dayong; Liu, Jianwen; Shi, Chenghua; Ma, Jianjun; Yang, Weichao; Yu, Xiaoniu

2018-03-01

For the purpose of investigating lining concrete durability, this study derives a modified chloride diffusion model for concrete based on the odd continuation of boundary conditions and Fourier transform. In order to achieve this, the linear stress distribution on a sectional structure is considered, detailed procedures and methods are presented for model verification and parametric analysis. Simulation results show that the chloride diffusion model can reflect the effects of linear stress distribution of the sectional structure on the chloride diffusivity with reliable accuracy. Along with the natural environmental characteristics of practical engineering structures, reference value ranges of model parameters are provided. Furthermore, a chloride diffusion model is extended for the consideration of multi-factor coupling of linear stress distribution, chloride concentration and diffusion time. Comparison between model simulation and typical current research results shows that the presented model can produce better considerations with a greater universality.

Conditional parametric models for storm sewer runoff

NASA Astrophysics Data System (ADS)

Jonsdottir, H.; Nielsen, H. Aa; Madsen, H.; Eliasson, J.; Palsson, O. P.; Nielsen, M. K.

2007-05-01

The method of conditional parametric modeling is introduced for flow prediction in a sewage system. It is a well-known fact that in hydrological modeling the response (runoff) to input (precipitation) varies depending on soil moisture and several other factors. Consequently, nonlinear input-output models are needed. The model formulation described in this paper is similar to the traditional linear models like final impulse response (FIR) and autoregressive exogenous (ARX) except that the parameters vary as a function of some external variables. The parameter variation is modeled by local lines, using kernels for local linear regression. As such, the method might be referred to as a nearest neighbor method. The results achieved in this study were compared to results from the conventional linear methods, FIR and ARX. The increase in the coefficient of determination is substantial. Furthermore, the new approach conserves the mass balance better. Hence this new approach looks promising for various hydrological models and analysis.

Salicylic acid deposition from wash-off products: comparison of in vivo and porcine deposition models.

PubMed

Davies, M A

2015-10-01

Salicylic acid (SA) is a widely used active in anti-acne face wash products. Only about 1-2% of the total dose is actually deposited on skin during washing, and more efficient deposition systems are sought. The objective of this work was to develop an improved method, including data analysis, to measure deposition of SA from wash-off formulae. Full fluorescence excitation-emission matrices (EEMs) were acquired for non-invasive measurement of deposition of SA from wash-off products. Multivariate data analysis methods - parallel factor analysis and N-way partial least-squares regression - were used to develop and compare deposition models on human volunteers and porcine skin. Although both models are useful, there are differences between them. First, the range of linear response to dosages of SA was 60 μg cm(-2) in vivo compared to 25 μg cm(-2) on porcine skin. Second, the actual shape of the SA band was different between substrates. The methods employed in this work highlight the utility of the use of EEMs, in conjunction with multivariate analysis tools such as parallel factor analysis and multiway partial least-squares calibration, in determining sources of spectral variability in skin and quantification of exogenous species deposited on skin. The human model exhibited the widest range of linearity, but porcine model is still useful up to deposition levels of 25 μg cm(-2) or used with nonlinear calibration models. © 2015 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

An Investigation of Lower Urinary Tract Symptoms in Women Aged 40 and Over.

PubMed

Sever, Neziha; Oskay, Umran

2017-01-01

The objective of this study was to determine lower urinary tract symptoms (LUTS) and associated risk factors in women aged 40 years and over. The study was carried out with a total of 312 women. The data were collected between 1 January 2009 and 30 July 2010. As research instruments, an interview form of 19 questions that questioned personal characteristics and was developed by researchers, and the Bristol Female Lower Urinary Tract Symptoms (BFLUTS) Questionnaire evaluating lower urinary tract symptoms were used. Linear regression analysis was used to detect associated risk factors. The rates of urgency, urinary incontinence, nocturia, and frequency symptoms were 61.5, 52.2, 18.9, and 25%, respectively. BFLUTS total scores increased with age, but the present study has detected no statistically significant differences (P > 0.05). BFLUTS scores of the women demonstrated statistically significant differences according to several risk factors including menopause status (P = 0.03), presence of chronic illness (P = 0.000), medicine use (P = 0.000), recurrent urinary tract infections (P = 0.000), body mass index (BMI) (P = 0.004), delivery number (P = 0.005) and chronic constipation (P = 0.002). Multiple linear regression analysis determined that frequent urinary tract infections, presence of chronic illness, chronic constipation, BMI and number of deliveries were significantly related to LUTS development. The most common LUTS was urgency in women aged 40 years and older. Recurrent urinary tract infection was determined as the most significant risk factor for LUTS, followed by chronic illness, chronic constipation, higher BMI and parity. © 2015 Wiley Publishing Asia Pty Ltd.

A Fresh Look at Linear Ordinary Differential Equations with Constant Coefficients. Revisiting the Impulsive Response Method Using Factorization

ERIC Educational Resources Information Center

Camporesi, Roberto

2016-01-01

We present an approach to the impulsive response method for solving linear constant-coefficient ordinary differential equations of any order based on the factorization of the differential operator. The approach is elementary, we only assume a basic knowledge of calculus and linear algebra. In particular, we avoid the use of distribution theory, as…

HCMM hydrological analysis in Utah

NASA Technical Reports Server (NTRS)

Miller, A. W. (Principal Investigator)

1982-01-01

The feasibility of applying a linear model to HCMM data in hopes of obtaining an accurate linear correlation was investigated. The relationship among HCMM sensed data surface temperature and red reflectivity on Utah Lake and water quality factors including algae concentrations, algae type, and nutrient and turbidity concentrations was established and evaluated. Correlation (composite) images of day infrared and reflectance imagery were assessed to determine if remote sensing offers the capability of using masses of accurate and comprehensive data in calculating evaporation. The effects of algae on temperature and evaporation were studied and the possibility of using satellite thermal data to locate areas within Utah Lake where significant thermal sources exist and areas of near surface groundwater was examined.

Factors associated with perception of singing voice handicap.

PubMed

Cohen, Seth M; Noordzij, J Pieter; Garrett, C Gaelyn; Ossoff, Robert H

2008-04-01

This study will determine factors that influence the self-perceived handicap associated with singing voice problems. A prospective cohort. Singers presenting to a voice clinic prospectively completed the Singing Voice Handicap Index (SVHI) before evaluation and treatment. Demographic data, singing style, professional status, duration of symptoms, medical problems, and diagnosis were collected. Univariate and multivariate analysis was performed. One hundred seventy-one singers completed the SVHI. The duration of symptoms, being an amateur singer or singing teacher, benign vocal fold lesions, and neurologic voice disorders were associated with increased SVHI scores (P < 0.05, multiple linear regression). Age greater than 50 years and gospel singing were predictive of increased SVHI scores only on univariate analysis (P < 0.05, t test). Singers experience significant handicap as a result of their singing problems with certain factors associated with greater impairment. Targeting interventions at patients more severely affected may improve outcomes.

Understanding nurses' and physicians' fear of repercussions for reporting errors: clinician characteristics, organization demographics, or leadership factors?

PubMed

Castel, Evan S; Ginsburg, Liane R; Zaheer, Shahram; Tamim, Hala

2015-08-14

Identifying and understanding factors influencing fear of repercussions for reporting and discussing medical errors in nurses and physicians remains an important area of inquiry. Work is needed to disentangle the role of clinician characteristics from those of the organization-level and unit-level safety environments in which these clinicians work and learn, as well as probing the differing reporting behaviours of nurses and physicians. This study examines the influence of clinician demographics (age, gender, and tenure), organization demographics (teaching status, location of care, and province) and leadership factors (organization and unit leadership support for safety) on fear of repercussions, and does so for nurses and physicians separately. A cross-sectional analysis of 2319 nurse and 386 physician responders from three Canadian provinces to the Modified Stanford patient safety climate survey (MSI-06). Data were analyzed using exploratory factor analysis, multiple linear regression, and hierarchical linear regression. Age, gender, tenure, teaching status, and province were not significantly associated with fear of repercussions for nurses or physicians. Mental health nurses had poorer fear responses than their peers outside of these areas, as did community physicians. Strong organization and unit leadership support for safety explained the most variance in fear for both nurses and physicians. The absence of associations between several plausible factors including age, tenure and teaching status suggests that fear is a complex construct requiring more study. Substantially differing fear responses across locations of care indicate areas where interventions may be needed. In addition, since factors affecting fear of repercussions appear to be different for nurses and physicians, tailoring patient safety initiatives to each group may, in some instances, be fruitful. Although further investigation is needed to examine these and other factors in detail, supportive safety leadership appears to be central to reducing fear of reporting errors for both nurses and physicians.

Comparison of linear, skewed-linear, and proportional hazard models for the analysis of lambing interval in Ripollesa ewes.

PubMed

Casellas, J; Bach, R

2012-06-01

Lambing interval is a relevant reproductive indicator for sheep populations under continuous mating systems, although there is a shortage of selection programs accounting for this trait in the sheep industry. Both the historical assumption of small genetic background and its unorthodox distribution pattern have limited its implementation as a breeding objective. In this manuscript, statistical performances of 3 alternative parametrizations [i.e., symmetric Gaussian mixed linear (GML) model, skew-Gaussian mixed linear (SGML) model, and piecewise Weibull proportional hazard (PWPH) model] have been compared to elucidate the preferred methodology to handle lambing interval data. More specifically, flock-by-flock analyses were performed on 31,986 lambing interval records (257.3 ± 0.2 d) from 6 purebred Ripollesa flocks. Model performances were compared in terms of deviance information criterion (DIC) and Bayes factor (BF). For all flocks, PWPH models were clearly preferred; they generated a reduction of 1,900 or more DIC units and provided BF estimates larger than 100 (i.e., PWPH models against linear models). These differences were reduced when comparing PWPH models with different number of change points for the baseline hazard function. In 4 flocks, only 2 change points were required to minimize the DIC, whereas 4 and 6 change points were needed for the 2 remaining flocks. These differences demonstrated a remarkable degree of heterogeneity across sheep flocks that must be properly accounted for in genetic evaluation models to avoid statistical biases and suboptimal genetic trends. Within this context, all 6 Ripollesa flocks revealed substantial genetic background for lambing interval with heritabilities ranging between 0.13 and 0.19. This study provides the first evidence of the suitability of PWPH models for lambing interval analysis, clearly discarding previous parametrizations focused on mixed linear models.

Cognitive function and associated factors among older people in Taiwan: age and sex differences.

PubMed

Li, Cheng-Lun; Hsu, Hui-Chuan

2015-01-01

The aim of this study was to examine cognitive function and the risk and the protective factors by age and sex among Taiwanese older people. The data were from a nation-representative panel of older people in Taiwan. The participants completing both the 2003 and 2007 waves were included for analysis in this study (n=3228). Descriptive analysis and generalized linear model were applied, and the samples were stratified by age groups and by sex. The factors related to higher cognitive function at the intercept included being younger, male, higher education, and doing unpaid work. At the time slope, the age effect and physical function difficulties would reduce the cognitive function across time, while education and providing informational support would increase the cognitive function across time. There were age- and sex-differences in the factors related to cognitive function, particularly on the working status and social participation. Different health promotion strategies to target these populations should be accordingly developed. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Modified global and modified linear contrast stretching algorithms: new colour contrast enhancement techniques for microscopic analysis of malaria slide images.

PubMed

Abdul-Nasir, Aimi Salihah; Mashor, Mohd Yusoff; Mohamed, Zeehaida

2012-01-01

Malaria is one of the serious global health problem, causing widespread sufferings and deaths in various parts of the world. With the large number of cases diagnosed over the year, early detection and accurate diagnosis which facilitates prompt treatment is an essential requirement to control malaria. For centuries now, manual microscopic examination of blood slide remains the gold standard for malaria diagnosis. However, low contrast of the malaria and variable smears quality are some factors that may influence the accuracy of interpretation by microbiologists. In order to reduce this problem, this paper aims to investigate the performance of the proposed contrast enhancement techniques namely, modified global and modified linear contrast stretching as well as the conventional global and linear contrast stretching that have been applied on malaria images of P. vivax species. The results show that the proposed modified global and modified linear contrast stretching techniques have successfully increased the contrast of the parasites and the infected red blood cells compared to the conventional global and linear contrast stretching. Hence, the resultant images would become useful to microbiologists for identification of various stages and species of malaria.

Linear microbunching analysis for recirculation machines

DOE PAGES

Tsai, C. -Y.; Douglas, D.; Li, R.; ...

2016-11-28

Microbunching instability (MBI) has been one of the most challenging issues in designs of magnetic chicanes for short-wavelength free-electron lasers or linear colliders, as well as those of transport lines for recirculating or energy-recovery-linac machines. To quantify MBI for a recirculating machine and for more systematic analyses, we have recently developed a linear Vlasov solver and incorporated relevant collective effects into the code, including the longitudinal space charge, coherent synchrotron radiation, and linac geometric impedances, with extension of the existing formulation to include beam acceleration. In our code, we semianalytically solve the linearized Vlasov equation for microbunching amplification factor formore » an arbitrary linear lattice. In this study we apply our code to beam line lattices of two comparative isochronous recirculation arcs and one arc lattice preceded by a linac section. The resultant microbunching gain functions and spectral responses are presented, with some results compared to particle tracking simulation by elegant (M. Borland, APS Light Source Note No. LS-287, 2002). These results demonstrate clearly the impact of arc lattice design on the microbunching development. Lastly, the underlying physics with inclusion of those collective effects is elucidated and the limitation of the existing formulation is also discussed.« less

Phase space analysis in anisotropic optical systems

NASA Technical Reports Server (NTRS)

Rivera, Ana Leonor; Chumakov, Sergey M.; Wolf, Kurt Bernardo

1995-01-01

From the minimal action principle follows the Hamilton equations of evolution for geometric optical rays in anisotropic media. As in classical mechanics of velocity-dependent potentials, the velocity and the canonical momentum are not parallel, but differ by an anisotropy vector potential, similar to that of linear electromagnetism. Descartes' well known diagram for refraction is generalized and a factorization theorem holds for interfaces between two anisotropic media.

Calculation of the orientational linear and nonlinear correlation factors of polar liquids from the rotational Dean-Kawasaki equation.

PubMed

Déjardin, P M; Cornaton, Y; Ghesquière, P; Caliot, C; Brouzet, R

2018-01-28

A calculation of the Kirkwood and Piekara-Kielich correlation factors of polar liquids is presented using the forced rotational diffusion theory of Cugliandolo et al. [Phys. Rev. E 91, 032139 (2015)]. These correlation factors are obtained as a function of density and temperature. Our results compare reasonably well with the experimental temperature dependence of the linear dielectric constant of some simple polar liquids across a wide temperature range. A comparison of our results for the linear dielectric constant and the Kirkwood correlation factor with relevant numerical simulations of liquid water and methanol is given.

Effects of source shape on the numerical aperture factor with a geometrical-optics model.

PubMed

Wan, Der-Shen; Schmit, Joanna; Novak, Erik

2004-04-01

We study the effects of an extended light source on the calibration of an interference microscope, also referred to as an optical profiler. Theoretical and experimental numerical aperture (NA) factors for circular and linear light sources along with collimated laser illumination demonstrate that the shape of the light source or effective aperture cone is critical for a correct NA factor calculation. In practice, more-accurate results for the NA factor are obtained when a linear approximation to the filament light source shape is used in a geometric model. We show that previously measured and derived NA factors show some discrepancies because a circular rather than linear approximation to the filament source was used in the modeling.

A Factorization Approach to the Linear Regulator Quadratic Cost Problem

NASA Technical Reports Server (NTRS)

Milman, M. H.

1985-01-01

A factorization approach to the linear regulator quadratic cost problem is developed. This approach makes some new connections between optimal control, factorization, Riccati equations and certain Wiener-Hopf operator equations. Applications of the theory to systems describable by evolution equations in Hilbert space and differential delay equations in Euclidean space are presented.

Analysis of linear elasticity and non-linearity due to plasticity and material damage in woven and biaxial braided composites

NASA Astrophysics Data System (ADS)

Goyal, Deepak

Textile composites have a wide variety of applications in the aerospace, sports, automobile, marine and medical industries. Due to the availability of a variety of textile architectures and numerous parameters associated with each, optimal design through extensive experimental testing is not practical. Predictive tools are needed to perform virtual experiments of various options. The focus of this research is to develop a better understanding of linear elastic response, plasticity and material damage induced nonlinear behavior and mechanics of load flow in textile composites. Textile composites exhibit multiple scales of complexity. The various textile behaviors are analyzed using a two-scale finite element modeling. A framework to allow use of a wide variety of damage initiation and growth models is proposed. Plasticity induced non-linear behavior of 2x2 braided composites is investigated using a modeling approach based on Hill's yield function for orthotropic materials. The mechanics of load flow in textile composites is demonstrated using special non-standard postprocessing techniques that not only highlight the important details, but also transform the extensive amount of output data into comprehensible modes of behavior. The investigations show that the damage models differ from each other in terms of amount of degradation as well as the properties to be degraded under a particular failure mode. When compared with experimental data, predictions of some models match well for glass/epoxy composite whereas other's match well for carbon/epoxy composites. However, all the models predicted very similar response when damage factors were made similar, which shows that the magnitude of damage factors are very important. Full 3D as well as equivalent tape laminate predictions lie within the range of the experimental data for a wide variety of braided composites with different material systems, which validated the plasticity analysis. Conclusions about the effect of fiber type on the degree of plasticity induced non-linearity in a +/-25° braid depend on the measure of non-linearity. Investigations about the mechanics of load flow in textile composites bring new insights about the textile behavior. For example, the reasons for existence of transverse shear stress under uni-axial loading and occurrence of stress concentrations at certain locations were explained.

A fresh look at linear ordinary differential equations with constant coefficients. Revisiting the impulsive response method using factorization

NASA Astrophysics Data System (ADS)

Camporesi, Roberto

2016-01-01

We present an approach to the impulsive response method for solving linear constant-coefficient ordinary differential equations of any order based on the factorization of the differential operator. The approach is elementary, we only assume a basic knowledge of calculus and linear algebra. In particular, we avoid the use of distribution theory, as well as of the other more advanced approaches: Laplace transform, linear systems, the general theory of linear equations with variable coefficients and variation of parameters. The approach presented here can be used in a first course on differential equations for science and engineering majors.

A drift correction optimization technique for the reduction of the inter-measurement dispersion of isotope ratios measured using a multi-collector plasma mass spectrometer

NASA Astrophysics Data System (ADS)

Doherty, W.; Lightfoot, P. C.; Ames, D. E.

2014-08-01

The effects of polynomial interpolation and internal standardization drift corrections on the inter-measurement dispersion (statistical) of isotope ratios measured with a multi-collector plasma mass spectrometer were investigated using the (analyte, internal standard) isotope systems of (Ni, Cu), (Cu, Ni), (Zn, Cu), (Zn, Ga), (Sm, Eu), (Hf, Re) and (Pb, Tl). The performance of five different correction factors was compared using a (statistical) range based merit function ωm which measures the accuracy and inter-measurement range of the instrument calibration. The frequency distribution of optimal correction factors over two hundred data sets uniformly favored three particular correction factors while the remaining two correction factors accounted for a small but still significant contribution to the reduction of the inter-measurement dispersion. Application of the merit function is demonstrated using the detection of Cu and Ni isotopic fractionation in laboratory and geologic-scale chemical reactor systems. Solvent extraction (diphenylthiocarbazone (Cu, Pb) and dimethylglyoxime (Ni) was used to either isotopically fractionate the metal during extraction using the method of competition or to isolate the Cu and Ni from the sample (sulfides and associated silicates). In the best case, differences in isotopic composition of ± 3 in the fifth significant figure could be routinely and reliably detected for Cu65/63 and Ni61/62. One of the internal standardization drift correction factors uses a least squares estimator to obtain a linear functional relationship between the measured analyte and internal standard isotope ratios. Graphical analysis demonstrates that the points on these graphs are defined by highly non-linear parametric curves and not two linearly correlated quantities which is the usual interpretation of these graphs. The success of this particular internal standardization correction factor was found in some cases to be due to a fortuitous, scale dependent, parametric curve effect.

Stress concentration factors for circular, reinforced penetrations in pressurized cylindrical shells. Ph.D. Thesis - Virginia Univ.

NASA Technical Reports Server (NTRS)

Ramsey, J. W., Jr.

1975-01-01

The effect on stresses in a cylindrical shell with a circular penetration subject to internal pressure was investigated in thin, shallow linearly, elastic cylindrical shells. Results provide numerical predictions of peak stress concentration factors around nonreinforced and reinforced penetrations in pressurized cylindrical shells. Analytical results were correlated with published formulas, as well as theoretical and experimental results. An accuracy study was made of the finite element program for each of the configurations considered important in pressure vessel technology. A formula is developed to predict the peak stress concentration factor for analysis and/or design in conjunction with the ASME Boiler and Pressure Vessel Code.

Study on avalanche photodiode influence on heterodyne laser interferometer linearity

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

Budzyn, Grzegorz, E-mail: grzegorz.budzyn@pwr.wroc.pl; Podzorny, Tomasz

2016-06-28

In the paper we analyze factors reducing the possible accuracy of the heterodyne laser interferometers. The analysis is performed for the avalanche-photodiode input stages but is in main points valid also for stages with other type of photodetectors. Instrumental error originating from optical, electronic and digital signal processing factors is taken into consideration. We stress factors which are critical and those which can be neglected at certain accuracy requirements. In the work we prove that it is possible to reduce errors of the laser instrument below 1 nm point for multiaxial APD based interferometers by precise control of incident optical powermore » and the temperature of the photodiode.« less

[Clinical significance and distribution of BRCA genes mutation in sporadic high grade serous ovarian cancer].

PubMed

Liu, W L; Wang, Z Z; Zhao, J Z; Hou, Y Y; Wu, X X; Li, W; Dong, B; Tong, T T; Guo, Y J

2017-01-25

Objective: To investigate the mutations of BRCA genes in sporadic high grade serous ovarian cancer (HGSOC) and study its clinical significance. Methods: Sixty-eight patients between January 2015 and January 2016 from the Affiliated Cancer Hospital of Zhengzhou University were collected who were based on pathological diagnosis of ovarian cancer and had no reported family history, and all patients firstly hospitalized were untreated in other hospitals before. (1) The BRCA genes were detected by next-generation sequencing (NGS) method. (2) The serum tumor markers included carcinoembryonic antigen (CEA), CA(125), CA(199), and human epididymis protein 4 (HE4) were detected by the chemiluminescence methods, and their correlation was analyzed by Pearson linear correlation. Descriptive statistics and comparisons were performed using two-tailed t -tests, Pearson's chi square test, Fisher's exact tests or logistic regression analysis as appropriate to research the clinicopathologic features associated with BRCA mutations, including age, International Federation of Gynecology and Obstetrics (FIGO) stage, platinum-based chemotherapy sensitivity, distant metastases, serum tumor markers (STM) . Results: (1) Fifteen cases (22%, 15/68) BRCA mutations were identified (BRCA1: 11 cases; BRCA2: 4 cases), and four novel mutations were observed. (2) The levels of CEA, CA(199), and HE4 were lower in BRCA mutations compared to that in control group, while no significant differences were found ( P >0.05), but the level of CA(125) was much higher in BRCA mutation group than that in controls ( t =-3.536, P =0.003). Further linear regression analysis found that there was a significant linear correlation between CA(125) and HE4 group ( r =0.494, P <0.01), and the same correlation as CEA and CA(199) group ( r =0.897, P <0.01). (3) Single factor analysis showed that no significant differences were observed in onset age, FIGO stage, distant metastasis, and STM between BRCA(+) and BRCA(-) group ( P >0.05), while significant differences were found in CA(125) and sensitivity to platinum-based chemotherapy between the patients with BRCA mutation and wild type ( P <0.05). The multiple factors analysis showed that the high level of CA(125) was a independent risk factor of BRCA mutations in sporadic HGSOC ( P =0.007). Conclusion: The combination of CA(125) with BRCA have great clinical significance, the mutation of BRCA gene could guild the clinical chemotherapy regiments.

A New SEYHAN's Approach in Case of Heterogeneity of Regression Slopes in ANCOVA.

PubMed

Ankarali, Handan; Cangur, Sengul; Ankarali, Seyit

2018-06-01

In this study, when the assumptions of linearity and homogeneity of regression slopes of conventional ANCOVA are not met, a new approach named as SEYHAN has been suggested to use conventional ANCOVA instead of robust or nonlinear ANCOVA. The proposed SEYHAN's approach involves transformation of continuous covariate into categorical structure when the relationship between covariate and dependent variable is nonlinear and the regression slopes are not homogenous. A simulated data set was used to explain SEYHAN's approach. In this approach, we performed conventional ANCOVA in each subgroup which is constituted according to knot values and analysis of variance with two-factor model after MARS method was used for categorization of covariate. The first model is a simpler model than the second model that includes interaction term. Since the model with interaction effect has more subjects, the power of test also increases and the existing significant difference is revealed better. We can say that linearity and homogeneity of regression slopes are not problem for data analysis by conventional linear ANCOVA model by helping this approach. It can be used fast and efficiently for the presence of one or more covariates.

Effects of abiotic factors on ecosystem health of Taihu Lake, China based on eco-exergy theory

NASA Astrophysics Data System (ADS)

Wang, Ce; Bi, Jun; Fath, Brian D.

2017-02-01

A lake ecosystem is continuously exposed to environmental stressors with non-linear interrelationships between abiotic factors and aquatic organisms. Ecosystem health depicts the capacity of system to respond to external perturbations and still maintain structure and function. In this study, we explored the effects of abiotic factors on ecosystem health of Taihu Lake in 2013, China from a system-level perspective. Spatiotemporal heterogeneities of eco-exergy and specific eco-exergy served as thermodynamic indicators to represent ecosystem health in the lake. The results showed the plankton community appeared more energetic in May, and relatively healthy in Gonghu Bay with both higher eco-exergy and specific eco-exergy; a eutrophic state was likely discovered in Zhushan Bay with higher eco-exergy but lower specific eco-exergy. Gradient Boosting Machine (GBM) approach was used to explain the non-linear relationships between two indicators and abiotic factors. This analysis revealed water temperature, inorganic nutrients, and total suspended solids greatly contributed to the two indicators that increased. However, pH rise driven by inorganic carbon played an important role in undermining ecosystem health, particularly when pH was higher than 8.2. This implies that climate change with rising CO2 concentrations has the potential to aggravate eutrophication in Taihu Lake where high nutrient loads are maintained.

Effects of abiotic factors on ecosystem health of Taihu Lake, China based on eco-exergy theory

PubMed Central

Wang, Ce; Bi, Jun; Fath, Brian D.

2017-01-01

A lake ecosystem is continuously exposed to environmental stressors with non-linear interrelationships between abiotic factors and aquatic organisms. Ecosystem health depicts the capacity of system to respond to external perturbations and still maintain structure and function. In this study, we explored the effects of abiotic factors on ecosystem health of Taihu Lake in 2013, China from a system-level perspective. Spatiotemporal heterogeneities of eco-exergy and specific eco-exergy served as thermodynamic indicators to represent ecosystem health in the lake. The results showed the plankton community appeared more energetic in May, and relatively healthy in Gonghu Bay with both higher eco-exergy and specific eco-exergy; a eutrophic state was likely discovered in Zhushan Bay with higher eco-exergy but lower specific eco-exergy. Gradient Boosting Machine (GBM) approach was used to explain the non-linear relationships between two indicators and abiotic factors. This analysis revealed water temperature, inorganic nutrients, and total suspended solids greatly contributed to the two indicators that increased. However, pH rise driven by inorganic carbon played an important role in undermining ecosystem health, particularly when pH was higher than 8.2. This implies that climate change with rising CO2 concentrations has the potential to aggravate eutrophication in Taihu Lake where high nutrient loads are maintained. PMID:28220835

[Preliminary study on the effect of climate factors on pollen fertility in Platycodon grandiflorum].

PubMed

Shi, Feng-hua; Zhang, Lei; Wei, Jian-he

2011-06-01

To have a better utilization of male sterile lines in heterozygotic breeding of Platycodon grandiflorum and provide theoretical basis for Platycodon grandiflorum hyboridization. The pollen viability was detected by the means of aceto carmine dyeing, and the correlation analysis between climate factors of each anther development stage and pollen viability was estimated by Pearson coefficients. Pollen viability variation range of male-sterile line GP1BC1-12 was 0% - 27%. That of male-sterile line GP12BC4-10 and chifeng germplasm was respectively 1.3% - 17.9% and 75.9% - 98.5%. Further linear regression analysis between climate factors of each anther development stage and pollen viability indicated that the degree of sensitivity varied with different germplasm of Platycodon grandiflorum. Among three germplasm, male sterile line GP12BC4-10 was the most stable one to the climate factors, and the male-sterile line GP1BC1-12 was the most sensitive one. Temperature and solar irradiation are the most important climate factors to affect pollen viability in Platycodon grandflorum, and microspore mother cells stage (MMC) is its sensetive stage.

The Relationship Between Surface Curvature and Abdominal Aortic Aneurysm Wall Stress.

PubMed

de Galarreta, Sergio Ruiz; Cazón, Aitor; Antón, Raúl; Finol, Ender A

2017-08-01

The maximum diameter (MD) criterion is the most important factor when predicting risk of rupture of abdominal aortic aneurysms (AAAs). An elevated wall stress has also been linked to a high risk of aneurysm rupture, yet is an uncommon clinical practice to compute AAA wall stress. The purpose of this study is to assess whether other characteristics of the AAA geometry are statistically correlated with wall stress. Using in-house segmentation and meshing algorithms, 30 patient-specific AAA models were generated for finite element analysis (FEA). These models were subsequently used to estimate wall stress and maximum diameter and to evaluate the spatial distributions of wall thickness, cross-sectional diameter, mean curvature, and Gaussian curvature. Data analysis consisted of statistical correlations of the aforementioned geometry metrics with wall stress for the 30 AAA inner and outer wall surfaces. In addition, a linear regression analysis was performed with all the AAA wall surfaces to quantify the relationship of the geometric indices with wall stress. These analyses indicated that while all the geometry metrics have statistically significant correlations with wall stress, the local mean curvature (LMC) exhibits the highest average Pearson's correlation coefficient for both inner and outer wall surfaces. The linear regression analysis revealed coefficients of determination for the outer and inner wall surfaces of 0.712 and 0.516, respectively, with LMC having the largest effect on the linear regression equation with wall stress. This work underscores the importance of evaluating AAA mean wall curvature as a potential surrogate for wall stress.

Complete characterization of fourth-order symplectic integrators with extended-linear coefficients.

PubMed

Chin, Siu A

2006-02-01

The structure of symplectic integrators up to fourth order can be completely and analytically understood when the factorization (split) coefficients are related linearly but with a uniform nonlinear proportional factor. The analytic form of these extended-linear symplectic integrators greatly simplified proofs of their general properties and allowed easy construction of both forward and nonforward fourth-order algorithms with an arbitrary number of operators. Most fourth-order forward integrators can now be derived analytically from this extended-linear formulation without the use of symbolic algebra.

Adjustment of Adaptive Gain with Bounded Linear Stability Analysis to Improve Time-Delay Margin for Metrics-Driven Adaptive Control

NASA Technical Reports Server (NTRS)

Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje Srinvas

2009-01-01

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a linear damaged twin-engine generic transport model of aircraft. The analysis shows that the system with the adjusted adaptive gain becomes more robust to unmodeled dynamics or time delay.

Cointegration of output, capital, labor, and energy

NASA Astrophysics Data System (ADS)

Stresing, R.; Lindenberger, D.; Kã¼mmel, R.

2008-11-01

Cointegration analysis is applied to the linear combinations of the time series of (the logarithms of) output, capital, labor, and energy for Germany, Japan, and the USA since 1960. The computed cointegration vectors represent the output elasticities of the aggregate energy-dependent Cobb-Douglas function. The output elasticities give the economic weights of the production factors capital, labor, and energy. We find that they are for labor much smaller and for energy much larger than the cost shares of these factors. In standard economic theory output elasticities equal cost shares. Our heterodox findings support results obtained with LINEX production functions.

[The analysis of threshold effect using Empower Stats software].

PubMed

Lin, Lin; Chen, Chang-zhong; Yu, Xiao-dan

2013-11-01

In many studies about biomedical research factors influence on the outcome variable, it has no influence or has a positive effect within a certain range. Exceeding a certain threshold value, the size of the effect and/or orientation will change, which called threshold effect. Whether there are threshold effects in the analysis of factors (x) on the outcome variable (y), it can be observed through a smooth curve fitting to see whether there is a piecewise linear relationship. And then using segmented regression model, LRT test and Bootstrap resampling method to analyze the threshold effect. Empower Stats software developed by American X & Y Solutions Inc has a threshold effect analysis module. You can input the threshold value at a given threshold segmentation simulated data. You may not input the threshold, but determined the optimal threshold analog data by the software automatically, and calculated the threshold confidence intervals.

Major Depression and Acute Coronary Syndrome-Related Factors

PubMed Central

Figueiredo, Jose Henrique Cunha; Silva, Nelson Albuquerque de Souza e; Pereira, Basilio de Bragança; de Oliveira, Glaucia Maria Moraes

2017-01-01

Background Major Depressive Disorder (MDD) is one of the most common mental illnesses in psychiatry, being considered a risk factor for Acute Coronary Syndrome (ACS). Objective To assess the prevalence of MDD in ACS patients, as well as to analyze associated factors through the interdependence of sociodemographic, lifestyle and clinical variables. Methods Observational, descriptive, cross-sectional, case-series study conducted on patients hospitalized consecutively at the coronary units of three public hospitals in the city of Rio de Janeiro over a 24-month period. All participants answered a standardized questionnaire requesting sociodemographic, lifestyle and clinical data, as well as a structured diagnostic interview for the DSM-IV regarding ongoing major depressive episodes. A general log-linear model of multivariate analysis was employed to assess association and interdependence with a significance level of 5%. Results Analysis of 356 patients (229 men), with an average and median age of 60 years (SD ± 11.42, 27-89). We found an MDD point prevalence of 23%, and a significant association between MDD and gender, marital status, sedentary lifestyle, Killip classification, and MDD history. Controlling for gender, we found a statistically significant association between MDD and gender, age ≤ 60 years, sedentary lifestyle and MDD history. The log-linear model identified the variables MDD history, gender, sedentary lifestyle, and age ≤ 60 years as having the greatest association with MDD. Conclusion Distinct approaches are required to diagnose and treat MDD in young women with ACS, history of MDD, sedentary lifestyle, and who are not in stable relationships. PMID:28443957

Dolastatin 15, a mollusk linear peptide, and Celecoxib, a selective cyclooxygenase-2 inhibitor, prevent preneoplastic colonic lesions and induce apoptosis through inhibition of the regulatory transcription factor NF-κB and an inflammatory protein, iNOS.

PubMed

Piplani, Honit; Vaish, Vivek; Sanyal, Sankar Nath

2012-11-01

The marine ecosystem is a unique and enormously rich source of natural products with potential chemopreventive applications in cancer. In the present study, we explored the chemopreventive role and the molecular mechanism of Dolastatin, a linear peptide from an Indian Ocean mollusk, and Celecoxib, a well-established cyclooxygenase-2 (COX-2) inhibitor in an individual as well as in a combination regimen in 1,2-dimethylhydrazine dihydrochloride (DMH)-induced colon carcinogenesis in a rat model. After a 6-week treatment with DMH, morphological analysis revealed a marked occurrence of preneoplastic features in the colonic mucosa, whereas histologically well-characterized dysplasia and hyperplasia were observed in DMH-treated animals. Simultaneous administration of Celecoxib and Dolastatin reduced these features significantly. DMH treatment affected the number of apoptotic cells in colonic enterocytes, which reverted to the normal level with the use of Celecoxib and Dolastatin. Inflammation remains the dominant molecular mechanism in the development of multiple plaque lesions, the carcinogenic lesions in a DMH-induced process that may be mediated by COX-2. Western blot and immunofluorescence analysis revealed a higher expression of COX-2 and nuclear factor-κB, the transcription factors responsible for proinflammatory proteins such as TNFα, and also the inducible nitric oxide synthase in the DMH group, which was further recovered significantly with the use of Celecoxib and Dolastatin. In-silico molecular docking analysis of Dolastatin as a ligand with various regulatory proteins suggests that although the peptide failed to dock to COX-2, it successfully did so with inducible nitric oxide synthase, thereby indicating the potential of this inflammatory protein as a molecular anticancer target in colon carcinogenesis.

Comparison of the Chiron Quantiplex branched DNA (bDNA) assay and the Abbott Genostics solution hybridization assay for quantification of hepatitis B viral DNA.

PubMed

Kapke, G E; Watson, G; Sheffler, S; Hunt, D; Frederick, C

1997-01-01

Several assays for quantification of DNA have been developed and are currently used in research and clinical laboratories. However, comparison of assay results has been difficult owing to the use of different standards and units of measurements as well as differences between assays in dynamic range and quantification limits. Although a few studies have compared results generated by different assays, there has been no consensus on conversion factors and thorough analysis has been precluded by small sample size and limited dynamic range studied. In this study, we have compared the Chiron branched DNA (bDNA) and Abbott liquid hybridization assays for quantification of hepatitis B virus (HBV) DNA in clinical specimens and have derived conversion factors to facilitate comparison of assay results. Additivity and variance stabilizing (AVAS) regression, a form of non-linear regression analysis, was performed on assay results for specimens from HBV clinical trials. Our results show that there is a strong linear relationship (R2 = 0.96) between log Chiron and log Abbott assay results. Conversion factors derived from regression analyses were found to be non-constant and ranged from 6-40. Analysis of paired assay results below and above each assay's limit of quantification (LOQ) indicated that a significantly (P < 0.01) larger proportion of observations were below the Abbott assay LOQ but above the Chiron assay LOQ, indicating that the Chiron assay is significantly more sensitive than the Abbott assay. Testing of replicate specimens showed that the Chiron assay consistently yielded lower per cent coefficients of variance (% CVs) than the Abbott assay, indicating that the Chiron assay provides superior precision.

[Association between urinary microalbumin-to-creatinine ratio and brachial-ankle pulse wave velocity in hypertensive patients].

PubMed

Zhu, Hang; Xue, Hao; Wang, Guangyi; Fu, Zhenhong; Liu, Jie; Shi, Yajun

2015-04-01

To explore the association between urinary microalbumin-to-creatinine ratio (ACR) and brachial-ankle pulse wave velocity (baPWV) in hypertensive patients. A total of 877 primary hypertension patients were enrolled in this trial from September 2009 to December 2012, and were randomly recruited and patients were divided into normal ACR group (ACR < 30 mg/g, n = 723), micro-albuminuria group (30 mg/g ≤ ACR < 300 mg/g, n = 136) and macro-albuminuria group (ACR ≥ 300 mg/g, n = 18). baPWV was measure by automatic pulse wave velocity measuring system. The baPWV values in patients of micro-albuminuria group and macro-albuminuria group were significantly higher than in the normal ACR group (all P < 0.05). The baPWV value of macro-albuminuria group was significantly higher than in the micro-albuminuria group (P < 0.05). Linear correlation analysis revealed that ACR was positively correlated with baPWV (r = 0.413, P < 0.01). Multiple linear regression analysis showed that ACR independently correlated with baPWV in patients with primary hypertension (β = 0.29, R(2) = 0.112, P < 0.01) after adjusting for age, sex, body mass index, systolic blood pressure, diastolic blood pressure, blood glucose, total cholesterol, low density lipoprotein, high density lipoprotein and triglyceride. Using ACR < 30 mg/g and ACR ≥ 30 mg/g as dichotomous variable, binary logistic regression analysis showed that ACR ≥ 30 mg/g was also a risk factor of the ascending baPWV in primary hypertension patients (OR: 1.73, 95% CI: 1.62-2.98) after adjusting the traditional cardiovascular risk factors. ACR is positively correlated to baPWV in primary hypertension patients, and the ascending baPWV is a risk factor of early renal dysfunction in primary hypertension patients.

Awareness about basic life support and emergency medical services and its associated factors among students in a tertiary care hospital in South India.

PubMed

Aroor, Akshatha Rao; Saya, Rama Prakash; Attar, Nazir Rahim; Saya, Ganesh Kumar; Ravinanthanan, Manikandan

2014-07-01

The knowledge and skills about the basic life support (BLS) and the advanced life support are the most important determining factors of the cardiopulmonary resuscitation (CPR) success rates. To determine the level of awareness on BLS and skills among undergraduate and postgraduate students of medical and dental profession, as well as nursing students and interns in a tertiary care hospital. This descriptive cross-sectional study was conducted in a tertiary care hospital in South India. The awareness level on BLS and factors associated which include age, sex, level of training (undergraduate, internship, and postgraduate groups), course of study (nursing, dental, and medical groups), and previous exposure to BLS were assessed by using a structured questionnaire. The association of these variables with awareness level was assessed by independent t test, analysis of variance, and linear regression analysis. Among 520 study subjects, 229 were students, 171 were interns, and 120 were postgraduate students. The overall mean score of awareness was 4.16 ± 1.40 (score range: 0-10). Age, sex, level of training, course of study, and previous exposure to BLS were significantly associated with awareness level in univariate analysis (P < 0.05). Linear regression model also showed that all the above variables were significantly associated with awareness level (P < 0.05). About 322 (61.9%) subjects attributed lack of awareness about BLS to lack of available professional training. About 479 (92.1%) responded that BLS training should be a part of medical curriculum. Awareness level on BLS is below average indicating the importance of professional training at all levels in a tertiary care health institution.

Multifactor analysis and simulation of the surface runoff and soil infiltration at different slope gradients

NASA Astrophysics Data System (ADS)

Huang, J.; Kang, Q.; Yang, J. X.; Jin, P. W.

2017-08-01

The surface runoff and soil infiltration exert significant influence on soil erosion. The effects of slope gradient/length (SG/SL), individual rainfall amount/intensity (IRA/IRI), vegetation cover (VC) and antecedent soil moisture (ASM) on the runoff depth (RD) and soil infiltration (INF) were evaluated in a series of natural rainfall experiments in the South of China. RD is found to correlate positively with IRA, IRI, and ASM factors and negatively with SG and VC. RD decreased followed by its increase with SG and ASM, it increased with a further decrease with SL, exhibited a linear growth with IRA and IRI, and exponential drop with VC. Meanwhile, INF exhibits a positive correlation with SL, IRA and IRI and VC, and a negative one with SG and ASM. INF was going up and then down with SG, linearly rising with SL, IRA and IRI, increasing by a logit function with VC, and linearly falling with ASM. The VC level above 60% can effectively lower the surface runoff and significantly enhance soil infiltration. Two RD and INF prediction models, accounting for the above six factors, were constructed using the multiple nonlinear regression method. The verification of those models disclosed a high Nash-Sutcliffe coefficient and low root-mean-square error, demonstrating good predictability of both models.

Evolutionary profiles derived from the QR factorization of multiple structural alignments gives an economy of information.

PubMed

O'Donoghue, Patrick; Luthey-Schulten, Zaida

2005-02-25

We present a new algorithm, based on the multidimensional QR factorization, to remove redundancy from a multiple structural alignment by choosing representative protein structures that best preserve the phylogenetic tree topology of the homologous group. The classical QR factorization with pivoting, developed as a fast numerical solution to eigenvalue and linear least-squares problems of the form Ax=b, was designed to re-order the columns of A by increasing linear dependence. Removing the most linear dependent columns from A leads to the formation of a minimal basis set which well spans the phase space of the problem at hand. By recasting the problem of redundancy in multiple structural alignments into this framework, in which the matrix A now describes the multiple alignment, we adapted the QR factorization to produce a minimal basis set of protein structures which best spans the evolutionary (phase) space. The non-redundant and representative profiles obtained from this procedure, termed evolutionary profiles, are shown in initial results to outperform well-tested profiles in homology detection searches over a large sequence database. A measure of structural similarity between homologous proteins, Q(H), is presented. By properly accounting for the effect and presence of gaps, a phylogenetic tree computed using this metric is shown to be congruent with the maximum-likelihood sequence-based phylogeny. The results indicate that evolutionary information is indeed recoverable from the comparative analysis of protein structure alone. Applications of the QR ordering and this structural similarity metric to analyze the evolution of structure among key, universally distributed proteins involved in translation, and to the selection of representatives from an ensemble of NMR structures are also discussed.

Factors associated with health-related quality of life among operating engineers.

PubMed

Choi, Seung Hee; Redman, Richard W; Terrell, Jeffrey E; Pohl, Joanne M; Duffy, Sonia A

2012-11-01

Because health-related quality of life among blue-collar workers has not been well studied, the purpose of this study was to determine factors associated with health-related quality of life among Operating Engineers. With cross-sectional data from a convenience sample of 498 Operating Engineers, personal and health behavioral factors associated with health-related quality of life were examined. Multivariate linear regression analysis revealed that personal factors (older age, being married, more medical comorbidities, and depression) and behavioral factors (smoking, low fruit and vegetable intake, low physical activity, high body mass index, and low sleep quality) were associated with poor health-related quality of life. Operating Engineers are at risk for poor health-related quality of life. Underlying medical comorbidities and depression should be well managed. Worksite wellness programs addressing poor health behaviors may be beneficial.

Quantifying cognition and behavior in normal aging, mild cognitive impairment, and Alzheimer's disease

NASA Astrophysics Data System (ADS)

Giraldo, Diana L.; Sijbers, Jan; Romero, Eduardo

2017-11-01

The diagnosis of Alzheimer's disease (AD) and mild cognitive impairment (MCI) is based on neuropsychological evaluation of the patient. Different cognitive and memory functions are assessed by a battery of tests that are composed of items devised to specifically evaluate such upper functions. This work aims to identify and quantify the factors that determine the performance in neuropsychological evaluation by conducting an Exploratory Factor Analysis (EFA). For this purpose, using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), EFA was applied to 67 item scores taken from the baseline neuropsychological battery of the three phases of ADNI study. The found factors are directly related to specific brain functions such as memory, behavior, orientation, or verbal fluency. The identification of factors is followed by the calculation of factor scores given by weighted linear combinations of the items scores.

Linearization of digital derived rate algorithm for use in linear stability analysis

NASA Technical Reports Server (NTRS)

Graham, R. E.; Porada, T. W.

1985-01-01

The digital derived rate (DDR) algorithm is used to calculate the rate of rotation of the Centaur upper-stage rocket. The DDR is highly nonlinear algorithm, and classical linear stability analysis of the spacecraft cannot be performed without linearization. The performance of this rate algorithm is characterized by a gain and phase curve that drop off at the same frequency. This characteristic is desirable for many applications. A linearization technique for the DDR algorithm is investigated. The linearization method is described. Examples of the results of the linearization technique are illustrated, and the effects of linearization are described. A linear digital filter may be used as a substitute for performing classical linear stability analyses, while the DDR itself may be used in time response analysis.

Temporal dynamic of malaria in a suburban area along the Niger River.

PubMed

Sissoko, Mahamadou Soumana; Sissoko, Kourane; Kamate, Bourama; Samake, Yacouba; Goita, Siaka; Dabo, Abdoulaye; Yena, Mama; Dessay, Nadine; Piarroux, Renaud; Doumbo, Ogobara K; Gaudart, Jean

2017-10-23

Even if rainfall and temperature are factors classically associated to malaria, little is known about other meteorological factors, their variability and combinations related to malaria, in association with river height variations. Furthermore, in suburban area, urbanization and growing population density should be assessed in relation to these environmental factors. The aim of this study was to assess the impact of combined environmental, meteorological and hydrological factors on malaria incidence through time in the context of urbanization. Population observational data were prospectively collected. Clinical malaria was defined as the presence of parasites in addition to clinical symptoms. Meteorological and hydrological factors were measured daily. For each factors variation indices were estimated. Urbanization was yearly estimated assessing satellite imaging and field investigations. Principal component analysis was used for dimension reduction and factors combination. Lags between malaria incidences and the main components were assessed by cross-correlation functions. Generalized additive model was used to assess relative impact of different environmental components, taking into account lags, and modelling non-linear relationships. Change-point analysis was used to determine transmission periods within years. Malaria incidences were dominated by annual periodicity and varied through time without modification of the dynamic, with no impact of the urbanization. The main meteorological factor associated with malaria was a combination of evaporation, humidity and rainfall, with a lag of 3 months. The relationship between combined temperature factors showed a linear impact until reaching high temperatures limiting malaria incidence, with a lag 3.25 months. Height and variation of the river were related to malaria incidence (respectively 6 week lag and no lag). The study emphasizes no decreasing trend of malaria incidence despite accurate access to care and control strategies in accordance to international recommendations. Furthermore, no decreasing trend was showed despite the urbanization of the area. Malaria transmission remain increase 3 months after the beginning of the dry season. Addition to evaporation versus humidity/rainfall, nonlinear relationship for temperature and river height and variations have to be taken into account when implementing malaria control programmes.

Hydrodynamic Stability Analysis on Sheared Stratified Flow in a Convective Flow Environment

NASA Astrophysics Data System (ADS)

Xiao, Yuan; Lin, Wenxian; Armfiled, Steven; Kirkpatrick, Michael; He, Yinghe; Fluid Dynamics Research Group, James Cook University Team; Fluid Dynamics Research Group, University of Sydney Team

2014-11-01

A hydrodynamic stability analysis on the convective sheared boundary layer (SCBL) flow, where a sheared stratified flow and a thermally convective flow coexist, is carried out in this study. The linear unstable stratifications representing the convective flow are included in the TaylorGoldstein equations as an unstable factor Jb. A new unstable region corresponding to the convective instability, which is not present in pure sheared stratified flows, is found with the analysis. It is also found that the boundaries of the convective instability regions expand with increasing Jb and interact with the sheared stratified instability region. More results will be presented at the conference

State-variable analysis of non-linear circuits with a desk computer

NASA Technical Reports Server (NTRS)

Cohen, E.

1981-01-01

State variable analysis was used to analyze the transient performance of non-linear circuits on a desk top computer. The non-linearities considered were not restricted to any circuit element. All that is required for analysis is the relationship defining each non-linearity be known in terms of points on a curve.

Water conservation behavior in Australia.

PubMed

Dolnicar, Sara; Hurlimann, Anna; Grün, Bettina

2012-08-30

Ensuring a nation's long term water supply requires the use of both supply-sided approaches such as water augmentation through water recycling, and demand-sided approaches such as water conservation. Conservation behavior can only be increased if the key drivers of such behavior are understood. The aim of this study is to reveal the main drivers from a comprehensive pool of hypothesized factors. An empirical study was conducted with 3094 Australians. Data was analyzed using multivariate linear regression analysis and decision trees to determine which factors best predict self-reported water conservation behavior. Two key factors emerge: high level of pro-environmental behavior; and pro-actively seeking out information about water. A number of less influential factors are also revealed. Public communication strategy implications are derived. Copyright © 2012 Elsevier Ltd. All rights reserved.

Status of tuberculosis-related stigma and associated factors: a cross-sectional study in central China.

PubMed

Yin, Xiaoxv; Yan, Shijiao; Tong, Yeqing; Peng, Xin; Yang, Tingting; Lu, Zuxun; Gong, Yanhong

2018-02-01

Tuberculosis (TB) poses a significant challenge to public health worldwide. Stigma is a major obstacle to TB control by leading to delay in diagnosis and treatment non-adherence. This study aimed to evaluate the status of TB-related stigma and its associated factors among TB patients in China. Cross-sectional survey. Thus, 1342 TB patients were recruited from TB dispensaries in three counties in Hubei Province using a multistage sampling method and surveyed using a structured anonymous questionnaire including validated scales to measure TB-related stigma. A generalised linear regression model was used to identify the factors associated with TB-related stigma. The average score on the TB-related Stigma Scale was 9.33 (SD = 4.25). Generalised linear regression analysis revealed that knowledge about TB (ß = -0.18, P = 0.0025), family function (ß = -0.29, P < 0.0001) and doctor-patient communication (ß = -0.32, P = 0.0005) were negatively associated with TB-related stigma. TB-related stigma was high among TB patients in China. Interventions concentrating on reducing TB patients' stigma in China should focus on improving patients' family function and patients' knowledge about TB. © 2017 John Wiley & Sons Ltd.

Ultrasound measurement of peripheral endothelial dysfunction in type 2 diabetic patients: correlation with risk factors

PubMed Central

Bosevski, Marijan; Georgievska-Ismail, Ljubica

2010-01-01

The purpose of the study was to assess the endothelial dysfunction (ED) in type 2 diabetic patients ultrasonographicaly and estimate the correlation of ED with glycemia and other cardio-metabolic risk factors. 171 patient (age 60,0 + 8,5 years) with diagnosed type 2 diabetes and coronary artery disease (CAD) were randomly included in a cross sectional study. B-mode ultrasound system with a linear transducer of 7.5 MHz was used for evaluation of flow-mediated vasodilation in brachial artery (FMV). FMV was presented as a change of brachial artery diameter at rest and after limb ischemia, previously provoked by cuff inflation. Peripheral ED was found in 77,2% (132 patients). Multivariate logistic regression model defined: age (OR 1,071, 95% CI 1,003 1,143) and plasma cholesterol (OR 4,083 95%CI 1,080 17,017) as determinants for ED. Linear multivariate analysis presented duration of diabetes (Beta 0,173, Sig 0,024), and glycemia (Beta 0,132, Sig 0,044) to be associated independently with FMV value. Estimated factors influencing FMV might be potential therapeutic targets for presented endothelial dysfunction in type 2 diabetic patients with coronary artery disease. PMID:20507285

Social support for women of reproductive age and its predictors: a population-based study

PubMed Central

2012-01-01

Background Social support is an exchange of resources between at least two individuals perceived by the provider or recipient to be intended to promote the health of the recipient. Social support is a major determinant of health. The objective of this study was to determine the perceived social support and its associated sociodemographic factors among women of reproductive age. Methods This was a population-based cross-sectional study with multistage random cluster sampling of 1359 women of reproductive age. Data were collected using questionnaires on sociodemographic factors and perceived social support (PRQ85-Part 2). The relationship between the dependent variable (perceived social support) and the independent variables (sociodemographic characteristics) was analyzed using the multivariable linear regression model. Results The mean score of social support was 134.3 ± 17.9. Women scored highest in the “worth” dimension and lowest in the “social integration” dimension. Multivariable linear regression analysis indicated that the variables of education, spouse’s occupation, Sufficiency of income for expenses and primary support source were significantly related to the perceived social support. Conclusion Sociodemographic factors affect social support and could be considered in planning interventions to improve social support for Iranian women. PMID:22988834

An ecological analysis of pertussis disease in Minnesota, 2009-2013.

PubMed

Iroh Tam, P Y; Menk, J S; Hughes, J; Kulasingam, S L

2016-03-01

The increase in pertussis cases in Minnesota in the last decade has been mainly attributed to the switch from whole cell to acellular pertussis [as part of the diphtheria, tetanus and acellular pertussis vaccine (DTaP)]. It is unclear, however, to what degree community-level risk factors also contribute. Understanding these factors can help inform public health policy-makers about where else to target resources. We performed an ecological analysis within Minnesota to identify risk factors at the county level using a Bayesian Poisson generalized linear areal model to account for spatial dependence. Univariate analyses suggested an association between increased pertussis rates at the county level and white maternal ethnicity, being US born, urban counties and average household size. In the multivariable analysis, the rate of pertussis was 1·79 times greater for urban vs. rural counties and 4·75 times greater for counties with a one-person larger average household size. Pertussis rates in counties with higher (i.e. 4+DTaP) receipt in children were 0·97 times lower. Examining county-level factors associated with varying levels of pertussis may help identify those counties that would most benefit from targeted interventions and increased resource allocation.

Background recovery via motion-based robust principal component analysis with matrix factorization

NASA Astrophysics Data System (ADS)

Pan, Peng; Wang, Yongli; Zhou, Mingyuan; Sun, Zhipeng; He, Guoping

2018-03-01

Background recovery is a key technique in video analysis, but it still suffers from many challenges, such as camouflage, lighting changes, and diverse types of image noise. Robust principal component analysis (RPCA), which aims to recover a low-rank matrix and a sparse matrix, is a general framework for background recovery. The nuclear norm is widely used as a convex surrogate for the rank function in RPCA, which requires computing the singular value decomposition (SVD), a task that is increasingly costly as matrix sizes and ranks increase. However, matrix factorization greatly reduces the dimension of the matrix for which the SVD must be computed. Motion information has been shown to improve low-rank matrix recovery in RPCA, but this method still finds it difficult to handle original video data sets because of its batch-mode formulation and implementation. Hence, in this paper, we propose a motion-assisted RPCA model with matrix factorization (FM-RPCA) for background recovery. Moreover, an efficient linear alternating direction method of multipliers with a matrix factorization (FL-ADM) algorithm is designed for solving the proposed FM-RPCA model. Experimental results illustrate that the method provides stable results and is more efficient than the current state-of-the-art algorithms.

UFVA, A Combined Linear and Nonlinear Factor Analysis Program Package for Chemical Data Evaluation.

DTIC Science & Technology

1980-11-01

that one cluster consists of the monoterpenes and Isoprene; the second is of the sesquiterpenes. Compound 8 (Caryophyllene) should therefore belong to...two clusters very clearly (Fig. 6). Figure 6 The very similar fragmentation pattern of Isoprene and the monoterpenes is reflected by their close...13 of another set of 13 terpene components. These are Isoprene, four monoterpenes (Myrcene, Menthol, Camphene, Umbellulone), four sesquiterpenes

Sequence information gain based motif analysis.

PubMed

Maynou, Joan; Pairó, Erola; Marco, Santiago; Perera, Alexandre

2015-11-09

The detection of regulatory regions in candidate sequences is essential for the understanding of the regulation of a particular gene and the mechanisms involved. This paper proposes a novel methodology based on information theoretic metrics for finding regulatory sequences in promoter regions. This methodology (SIGMA) has been tested on genomic sequence data for Homo sapiens and Mus musculus. SIGMA has been compared with different publicly available alternatives for motif detection, such as MEME/MAST, Biostrings (Bioconductor package), MotifRegressor, and previous work such Qresiduals projections or information theoretic based detectors. Comparative results, in the form of Receiver Operating Characteristic curves, show how, in 70% of the studied Transcription Factor Binding Sites, the SIGMA detector has a better performance and behaves more robustly than the methods compared, while having a similar computational time. The performance of SIGMA can be explained by its parametric simplicity in the modelling of the non-linear co-variability in the binding motif positions. Sequence Information Gain based Motif Analysis is a generalisation of a non-linear model of the cis-regulatory sequences detection based on Information Theory. This generalisation allows us to detect transcription factor binding sites with maximum performance disregarding the covariability observed in the positions of the training set of sequences. SIGMA is freely available to the public at http://b2slab.upc.edu.

Analyzing Multilevel Factors Underlying Adolescent Smoking Behaviors: The Roles of Friendship Network, Family Relations, and School Environment.

PubMed

Kim, Harris H-S; Chun, JongSerl

2018-06-01

This study investigates the extent to which friendship network, family relations, and school context are related to adolescent cigarette smoking. Friendship network is measured in terms of delinquent peers; family relations in terms of parental supervision; and school environment in terms of objective (eg, antismoking policy) and subjective (eg, school attachment) characteristics. Findings are based on the secondary analysis of the health behavior in school-aged children, 2009-2010. Two-level hierarchical generalized linear models are estimated using hierarchical linear modeling 7. At the student level, ties to delinquent friends is significantly related to higher odds of smoking, while greater parental supervision is associated with lower odds. At the school level, antismoking policy and curriculum independently lower smoking behavior. Better within-class peer relations, greater school attachment, and higher academic performance are also negatively related to smoking. Last, the positive association between delinquent friends and smoking is weaker in schools with a formally enacted antismoking policy. However, this association is stronger in schools with better peer relations. Adolescent smoking behavior is embedded in a broader ecological setting. This research reveals that a proper understanding of it requires comprehensive analysis that incorporates factors measured at individual (student) and contextual (school) levels. © 2018, American School Health Association.

Rise time analysis of pulsed klystron-modulator for efficiency improvement of linear colliders

NASA Astrophysics Data System (ADS)

Oh, J. S.; Cho, M. H.; Namkung, W.; Chung, K. H.; Shintake, T.; Matsumoto, H.

2000-04-01

In linear accelerators, the periods during the rise and fall of a klystron-modulator pulse cannot be used to generate RF power. Thus, these periods need to be minimized to get high efficiency, especially in large-scale machines. In this paper, we present a simplified and generalized voltage rise time function of a pulsed modulator with a high-power klystron load using the equivalent circuit analysis method. The optimum pulse waveform is generated when this pulsed power system is tuned with a damping factor of ˜0.85. The normalized rise time chart presented in this paper allows one to predict the rise time and pulse shape of the pulsed power system in general. The results can be summarized as follows: The large distributed capacitance in the pulse tank and operating parameters, Vs× Tp , where Vs is load voltage and Tp is the pulse width, are the main factors determining the pulse rise time in the high-power RF system. With an RF pulse compression scheme, up to ±3% ripple of the modulator voltage is allowed without serious loss of compressor efficiency, which allows the modulator efficiency to be improved as well. The wiring inductance should be minimized to get the fastest rise time.

The psychobiological theory of temperament and character: comment on Farmer and Goldberg (2008).

PubMed

Cloninger, C Robert

2008-09-01

The revised Temperament and Character Inventory (TCI-R) is the third stage of development of a widely used multiscale personality inventory that began with the Tridimensional Personality Questionnaire (TPQ) and then the Temperament and Character Inventory (TCI). The author describes the third stage of the psychobiological theory of temperament and character; empirical tests of its predictions from genetics, neurobiology, psychosocial development, and clinical studies; and empirical findings that stimulated incremental changes in theory and test construction. Linear factor analysis is an inadequate method for evaluating the nonlinear and dynamical nature of the intrapsychic processes that influence human personality. Traits derived by factor analysis under the doubtful assumption of linearity are actually heterogeneous composites of rational and emotional processes that differ fundamentally in their underlying brain processes. The predictions of the psychobiological theory are strongly validated by extensive data from genetics, neurobiology, longitudinal studies of development, and clinical assessment. The distinction between temperament and character allows the TCI and TCI-R to outperform other popular personality inventories in distinguishing individuals with personality disorders from others and in describing the developmental path to well-being in terms of dynamical processes within the individual that are useful for both research and clinical practice. (c) 2008 APA, all rights reserved.

A systematic review of methodology: time series regression analysis for environmental factors and infectious diseases.

PubMed

Imai, Chisato; Hashizume, Masahiro

2015-03-01

Time series analysis is suitable for investigations of relatively direct and short-term effects of exposures on outcomes. In environmental epidemiology studies, this method has been one of the standard approaches to assess impacts of environmental factors on acute non-infectious diseases (e.g. cardiovascular deaths), with conventionally generalized linear or additive models (GLM and GAM). However, the same analysis practices are often observed with infectious diseases despite of the substantial differences from non-infectious diseases that may result in analytical challenges. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, systematic review was conducted to elucidate important issues in assessing the associations between environmental factors and infectious diseases using time series analysis with GLM and GAM. Published studies on the associations between weather factors and malaria, cholera, dengue, and influenza were targeted. Our review raised issues regarding the estimation of susceptible population and exposure lag times, the adequacy of seasonal adjustments, the presence of strong autocorrelations, and the lack of a smaller observation time unit of outcomes (i.e. daily data). These concerns may be attributable to features specific to infectious diseases, such as transmission among individuals and complicated causal mechanisms. The consequence of not taking adequate measures to address these issues is distortion of the appropriate risk quantifications of exposures factors. Future studies should pay careful attention to details and examine alternative models or methods that improve studies using time series regression analysis for environmental determinants of infectious diseases.

Phenotypic variation as an indicator of pesticide stress in gudgeon: Accounting for confounding factors in the wild.

PubMed

Shinn, Cândida; Blanchet, Simon; Loot, Géraldine; Lek, Sovan; Grenouillet, Gaël

2015-12-15

The response of organisms to environmental stress is currently used in the assessment of ecosystem health. Morphological changes integrate the multiple effects of one or several stress factors upon the development of the exposed organisms. In a natural environment, many factors determine the patterns of morphological differentiation between individuals. However, few studies have sought to distinguish and measure the independent effect of these factors (genetic diversity and structure, spatial structuring of populations, physical-chemical conditions, etc.). Here we investigated the relationship between pesticide levels measured at 11 sites sampled in rivers of the Garonne river basin (SW France) and morphological changes of a freshwater fish species, the gudgeon (Gobio gobio). Each individual sampled was genotyped using 8 microsatellite markers and their phenotype characterized via 17 morphological traits. Our analysis detected a link between population genetic structure (revealed by a Bayesian method) and morphometry (linear discriminant analysis) of the studied populations. We then developed an original method based on general linear models using distance matrices, an extension of the partial Mantel test beyond 3 matrices. This method was used to test the relationship between contamination (toxicity index) and morphometry (PST of morphometric traits), taking into account (1) genetic differentiation between populations (FST), (2) geographical distances between sites, (3) site catchment area, and (4) various physical-chemical parameters for each sampling site. Upon removal of confounding effects, 3 of the 17 morphological traits studied were significantly correlated with pesticide toxicity, suggesting a response of these traits to the anthropogenic stress. These results underline the importance of taking into account the different sources of phenotypic variability between organisms when identifying the stress factors involved. The separation and quantification of the independent effect of such factors provides an interesting outlook regarding the use of these evaluation metrics as indicators of ecosystem health. Copyright © 2015 Elsevier B.V. All rights reserved.

The impact of emphysema on dosimetric parameters for stereotactic body radiotherapy of the lung

PubMed Central

Ochiai, Satoru; Nomoto, Yoshihito; Yamashita, Yasufumi; Inoue, Tomoki; Murashima, Shuuichi; Hasegawa, Daisuke; Kurita, Yoshie; Watanabe, Yui; Toyomasu, Yutaka; Kawamura, Tomoko; Takada, Akinori; Noriko; Kobayashi, Shigeki; Sakuma, Hajime

2016-01-01

The purpose of this study was to evaluate the impact of emphysematous changes in lung on dosimetric parameters in stereotactic body radiation therapy (SBRT) for lung tumor. A total of 72 treatment plans were reviewed, and dosimetric factors [including homogeneity index (HI) and conformity index (CI)] were evaluated. Emphysematous changes in lung were observed in 43 patients (60%). Patients were divided into three groups according to the severity of emphysema: no emphysema (n = 29), mild emphysema (n = 22) and moderate to severe emphysema groups (n = 21). The HI (P < 0.001) and the CI (P = 0.029) were significantly different in accordance with the severity of emphysema in one-way analysis of variance (ANOVA). The HI value was significantly higher in the moderate to severe emphysema group compared with in the no emphysema (Tukey, P < 0.001) and mild emphysema groups (P = 0.002). The CI value was significantly higher in the moderate to severe emphysema group compared with in the no emphysema group (P = 0.044). In multiple linear regression analysis, the severity of emphysema (P < 0.001) and the mean material density of the lung within the PTV (P < 0.001) were significant factors for HI, and the mean density of the lung within the PTV (P = 0.005) was the only significant factor for CI. The mean density of the lung within the PTV was significantly different in accordance with the severity of emphysema (one-way ANOVA, P = 0.008) and the severity of emphysema (P < 0.001) was one of the significant factors for the density of the lung within the PTV in multiple linear regression analysis. Our results suggest that emphysematous changes in the lung significantly impact on several dosimetric parameters in SBRT, and they should be carefully evaluated before treatment planning. PMID:27380802

Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data

PubMed Central

Ying, Gui-shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

2017-01-01

Purpose To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. Methods We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field data in the elderly. Results When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI −0.03 to 0.32D, P=0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, P=0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller P-values, while analysis of the worse eye provided larger P-values than mixed effects models and marginal models. Conclusion In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision. PMID:28102741

Prediction of the space adaptation syndrome

NASA Technical Reports Server (NTRS)

Reschke, M. F.; Homick, J. L.; Ryan, P.; Moseley, E. C.

1984-01-01

The univariate and multivariate relationships of provocative measures used to produce motion sickness symptoms were described. Normative subjects were used to develop and cross-validate sets of linear equations that optimally predict motion sickness in parabolic flights. The possibility of reducing the number of measurements required for prediction was assessed. After describing the variables verbally and statistically for 159 subjects, a factor analysis of 27 variables was completed to improve understanding of the relationships between variables and to reduce the number of measures for prediction purposes. The results of this analysis show that none of variables are significantly related to the responses to parabolic flights. A set of variables was selected to predict responses to KC-135 flights. A series of discriminant analyses were completed. Results indicate that low, moderate, or severe susceptibility could be correctly predicted 64 percent and 53 percent of the time on original and cross-validation samples, respectively. Both the factor analysis and the discriminant analysis provided no basis for reducing the number of tests.

Simulation of Shear and Bending Cracking in RC Beam: Material Model and its Application to Impact

NASA Astrophysics Data System (ADS)

Mokhatar, S. N.; Sonoda, Y.; Zuki, S. S. M.; Kamarudin, A. F.; Noh, M. S. Md

2018-04-01

This paper presents a simple and reliable non-linear numerical analysis incorporated with fully Lagrangian method namely Smoothed Particle Hydrodynamics (SPH) to predict the impact response of the reinforced concrete (RC) beam under impact loading. The analysis includes the simulation of the effects of high mass low-velocity impact load falling on beam structures. Three basic ideas to present the localized failure of structural elements are: (1) the accurate strength of concrete and steel reinforcement during the short period (dynamic), Dynamic Increase Factor (DIF) has been employed for the effect of strain rate on the compression and tensile strength (2) linear pressure-sensitive yield criteria (Drucker-Prager type) with a new volume dependent Plane-Cap (PC) hardening in the pre-peak regime is assumed for the concrete, meanwhile, shear-strain energy criterion (Von-Mises) is applied to steel reinforcement (3) two kinds of constitutive equation are introduced to simulate the crushing and bending cracking of the beam elements. Then, these numerical analysis results were compared with the experimental test results.

Preliminary Analysis of an Oscillating Surge Wave Energy Converter with Controlled Geometry: Preprint

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

Tom, Nathan; Lawson, Michael; Yu, Yi-Hsiang

The aim of this paper is to present a novel wave energy converter device concept that is being developed at the National Renewable Energy Laboratory. The proposed concept combines an oscillating surge wave energy converter with active control surfaces. These active control surfaces allow for the device geometry to be altered, which leads to changes in the hydrodynamic properties. The device geometry will be controlled on a sea state time scale and combined with wave-to-wave power-take-off control to maximize power capture, increase capacity factor, and reduce design loads. The paper begins with a traditional linear frequency domain analysis of themore » device performance. Performance sensitivity to foil pitch angle, the number of activated foils, and foil cross section geometry is presented to illustrate the current design decisions; however, it is understood from previous studies that modeling of current oscillating wave energy converter designs requires the consideration of nonlinear hydrodynamics and viscous drag forces. In response, a nonlinear model is presented that highlights the shortcomings of the linear frequency domain analysis and increases the precision in predicted performance.« less

Influence of fracture network physical properties on stability criteria of density-driven flow in a dual-porosity system

NASA Astrophysics Data System (ADS)

Hassanzadeh, H.; Jafari Raad, S. M.

2017-12-01

Linear stability analysis is conducted to study the onset of buoyancy-driven convection involved in solubility trapping of CO2 into deep fractured aquifers. In this study, the effect of fracture network physical properties on the stability criteria in a brine-rich fractured porous layer is investigated using dual porosity concept for both single and variable matrix block size distributions. Linear stability analysis results show that both fracture interporosity flow and fracture storativity factors play an important role in the stability behavior of the system. It is shown that a diffusive boundary layer under the gravity field in a fractured rock with lower fracture storativity and/or higher fracture interporosity flow coefficient is more stable. We present scaling relations that relate the onset of convective instability in fractured aquifers. These findings improve our understanding of buoyancy driven flow in fractured aquifers and are particularly important in estimation of potential storage capacity, risk assessment, and storage sites characterization and screening.Keywords: CO2 sequestration; fractured rock; buoyancy-driven convection; stability analysis

Neighborhood adversity, ethnic diversity, and weak social cohesion and social networks predict high rates of maternal depressive symptoms: a critical realist ecological study in South Western Sydney, Australia.

PubMed

Eastwood, John Graeme; Kemp, Lynn Ann; Jalaludin, Bin Badrudin; Phung, Hai Ngoc

2013-01-01

The aim of the study reported here is to explore ecological covariate and latent variable associations with perinatal depressive symptoms in South Western Sydney for the purpose of informing subsequent theory generation of perinatal context, depression, and the developmental origins of health and disease. Mothers (n = 15,389) delivering in 2002 and 2003 were assessed at two to three weeks after delivery for risk factors for depressive symptoms. The binary outcome variables were Edinburgh Postnatal Depression Scale (EPDS)> 9 and > 12. Aggregated EPDS > 9 was analyzed for 101 suburbs. Suburb-level variables were drawn from the 2001 Australian Census, New South Wales Crime Statistics, and aggregated individual-level risk factors. Analysis included exploratory factor analysis, univariate and multivariate likelihood, and Bayesian linear regression with conditional autoregressive components. The exploratory factor analysis identified six factors: neighborhood adversity, social cohesion, health behaviors, housing quality, social services, and support networks. Variables associated with neighborhood adversity, social cohesion, social networks, and ethnic diversity were consistently associated with aggregated depressive symptoms. The findings support the theoretical proposition that neighborhood adversity causes maternal psychological distress and depression within the context of social buffers including social networks, social cohesion, and social services.

Calibrating Nonlinear Soil Material Properties for Seismic Analysis Using Soil Material Properties Intended for Linear Analysis

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

Spears, Robert Edward; Coleman, Justin Leigh

2015-08-01

Seismic analysis of nuclear structures is routinely performed using guidance provided in “Seismic Analysis of Safety-Related Nuclear Structures and Commentary (ASCE 4, 1998).” This document, which is currently under revision, provides detailed guidance on linear seismic soil-structure-interaction (SSI) analysis of nuclear structures. To accommodate the linear analysis, soil material properties are typically developed as shear modulus and damping ratio versus cyclic shear strain amplitude. A new Appendix in ASCE 4-2014 (draft) is being added to provide guidance for nonlinear time domain SSI analysis. To accommodate the nonlinear analysis, a more appropriate form of the soil material properties includes shear stressmore » and energy absorbed per cycle versus shear strain. Ideally, nonlinear soil model material properties would be established with soil testing appropriate for the nonlinear constitutive model being used. However, much of the soil testing done for SSI analysis is performed for use with linear analysis techniques. Consequently, a method is described in this paper that uses soil test data intended for linear analysis to develop nonlinear soil material properties. To produce nonlinear material properties that are equivalent to the linear material properties, the linear and nonlinear model hysteresis loops are considered. For equivalent material properties, the shear stress at peak shear strain and energy absorbed per cycle should match when comparing the linear and nonlinear model hysteresis loops. Consequently, nonlinear material properties are selected based on these criteria.« less

Cooperation without culture? The null effect of generalized trust on intentional homicide: a cross-national panel analysis, 1995-2009.

PubMed

Robbins, Blaine

2013-01-01

Sociologists, political scientists, and economists all suggest that culture plays a pivotal role in the development of large-scale cooperation. In this study, I used generalized trust as a measure of culture to explore if and how culture impacts intentional homicide, my operationalization of cooperation. I compiled multiple cross-national data sets and used pooled time-series linear regression, single-equation instrumental-variables linear regression, and fixed- and random-effects estimation techniques on an unbalanced panel of 118 countries and 232 observations spread over a 15-year time period. Results suggest that culture and large-scale cooperation form a tenuous relationship, while economic factors such as development, inequality, and geopolitics appear to drive large-scale cooperation.

Data analysis and calibration for a bulk-refractive-index-compensated surface plasmon resonance affinity sensor

NASA Astrophysics Data System (ADS)

Chinowsky, Timothy M.; Yee, Sinclair S.

2002-02-01

Surface plasmon resonance (SPR) affinity sensing, the problem of bulk refractive index (RI) interference in SPR sensing, and a sensor developed to overcome this problem are briefly reviewed. The sensor uses a design based on Texas Instruments' Spreeta SPR sensor to simultaneously measure both bulk and surface RI. The bulk RI measurement is then used to compensate the surface measurement and remove the effects of bulk RI interference. To achieve accurate compensation, robust data analysis and calibration techniques are necessary. Simple linear data analysis techniques derived from measurements of the sensor response were found to provide a versatile, low noise method for extracting measurements of bulk and surface refractive index from the raw sensor data. Automatic calibration using RI gradients was used to correct the linear estimates, enabling the sensor to produce accurate data even when the sensor has a complicated nonlinear response which varies with time. The calibration procedure is described, and the factors influencing calibration accuracy are discussed. Data analysis and calibration principles are illustrated with an experiment in which sucrose and detergent solutions are used to produce changes in bulk and surface RI, respectively.

Full-motion video analysis for improved gender classification

NASA Astrophysics Data System (ADS)

Flora, Jeffrey B.; Lochtefeld, Darrell F.; Iftekharuddin, Khan M.

2014-06-01

The ability of computer systems to perform gender classification using the dynamic motion of the human subject has important applications in medicine, human factors, and human-computer interface systems. Previous works in motion analysis have used data from sensors (including gyroscopes, accelerometers, and force plates), radar signatures, and video. However, full-motion video, motion capture, range data provides a higher resolution time and spatial dataset for the analysis of dynamic motion. Works using motion capture data have been limited by small datasets in a controlled environment. In this paper, we explore machine learning techniques to a new dataset that has a larger number of subjects. Additionally, these subjects move unrestricted through a capture volume, representing a more realistic, less controlled environment. We conclude that existing linear classification methods are insufficient for the gender classification for larger dataset captured in relatively uncontrolled environment. A method based on a nonlinear support vector machine classifier is proposed to obtain gender classification for the larger dataset. In experimental testing with a dataset consisting of 98 trials (49 subjects, 2 trials per subject), classification rates using leave-one-out cross-validation are improved from 73% using linear discriminant analysis to 88% using the nonlinear support vector machine classifier.

A multiphase non-linear mixed effects model: An application to spirometry after lung transplantation.

PubMed

Rajeswaran, Jeevanantham; Blackstone, Eugene H

2017-02-01

In medical sciences, we often encounter longitudinal temporal relationships that are non-linear in nature. The influence of risk factors may also change across longitudinal follow-up. A system of multiphase non-linear mixed effects model is presented to model temporal patterns of longitudinal continuous measurements, with temporal decomposition to identify the phases and risk factors within each phase. Application of this model is illustrated using spirometry data after lung transplantation using readily available statistical software. This application illustrates the usefulness of our flexible model when dealing with complex non-linear patterns and time-varying coefficients.

Advanced statistics: linear regression, part II: multiple linear regression.

PubMed

Marill, Keith A

2004-01-01

The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

Dimension Reduction With Extreme Learning Machine.

PubMed

Kasun, Liyanaarachchi Lekamalage Chamara; Yang, Yan; Huang, Guang-Bin; Zhang, Zhengyou

2016-08-01

Data may often contain noise or irrelevant information, which negatively affect the generalization capability of machine learning algorithms. The objective of dimension reduction algorithms, such as principal component analysis (PCA), non-negative matrix factorization (NMF), random projection (RP), and auto-encoder (AE), is to reduce the noise or irrelevant information of the data. The features of PCA (eigenvectors) and linear AE are not able to represent data as parts (e.g. nose in a face image). On the other hand, NMF and non-linear AE are maimed by slow learning speed and RP only represents a subspace of original data. This paper introduces a dimension reduction framework which to some extend represents data as parts, has fast learning speed, and learns the between-class scatter subspace. To this end, this paper investigates a linear and non-linear dimension reduction framework referred to as extreme learning machine AE (ELM-AE) and sparse ELM-AE (SELM-AE). In contrast to tied weight AE, the hidden neurons in ELM-AE and SELM-AE need not be tuned, and their parameters (e.g, input weights in additive neurons) are initialized using orthogonal and sparse random weights, respectively. Experimental results on USPS handwritten digit recognition data set, CIFAR-10 object recognition, and NORB object recognition data set show the efficacy of linear and non-linear ELM-AE and SELM-AE in terms of discriminative capability, sparsity, training time, and normalized mean square error.

Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs.

PubMed

Ganga, G M D; Esposto, K F; Braatz, D

2012-01-01

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

Identifying Plant Part Composition of Forest Logging Residue Using Infrared Spectral Data and Linear Discriminant Analysis

PubMed Central

Acquah, Gifty E.; Via, Brian K.; Billor, Nedret; Fasina, Oladiran O.; Eckhardt, Lori G.

2016-01-01

As new markets, technologies and economies evolve in the low carbon bioeconomy, forest logging residue, a largely untapped renewable resource will play a vital role. The feedstock can however be variable depending on plant species and plant part component. This heterogeneity can influence the physical, chemical and thermochemical properties of the material, and thus the final yield and quality of products. Although it is challenging to control compositional variability of a batch of feedstock, it is feasible to monitor this heterogeneity and make the necessary changes in process parameters. Such a system will be a first step towards optimization, quality assurance and cost-effectiveness of processes in the emerging biofuel/chemical industry. The objective of this study was therefore to qualitatively classify forest logging residue made up of different plant parts using both near infrared spectroscopy (NIRS) and Fourier transform infrared spectroscopy (FTIRS) together with linear discriminant analysis (LDA). Forest logging residue harvested from several Pinus taeda (loblolly pine) plantations in Alabama, USA, were classified into three plant part components: clean wood, wood and bark and slash (i.e., limbs and foliage). Five-fold cross-validated linear discriminant functions had classification accuracies of over 96% for both NIRS and FTIRS based models. An extra factor/principal component (PC) was however needed to achieve this in FTIRS modeling. Analysis of factor loadings of both NIR and FTIR spectra showed that, the statistically different amount of cellulose in the three plant part components of logging residue contributed to their initial separation. This study demonstrated that NIR or FTIR spectroscopy coupled with PCA and LDA has the potential to be used as a high throughput tool in classifying the plant part makeup of a batch of forest logging residue feedstock. Thus, NIR/FTIR could be employed as a tool to rapidly probe/monitor the variability of forest biomass so that the appropriate online adjustments to parameters can be made in time to ensure process optimization and product quality. PMID:27618901

Dose-effect relationships, epidemiological analysis and the derivation of low dose risk.

PubMed

Leenhouts, H P; Chadwick, K H

2011-03-01

This paper expands on our recent comments in a letter to this journal about the analysis of epidemiological studies and the determination of low dose RBE of low LET radiation (Chadwick and Leenhouts 2009 J. Radiol. Prot. 29 445-7). Using the assumption that radiation induced cancer arises from a somatic mutation (Chadwick and Leenhouts 2011 J. Radiol. Prot. 31 41-8) a model equation is derived to describe cancer induction as a function of dose. The model is described briefly, evidence is provided in support of it, and it is applied to a set of experimental animal data. The results are compared with a linear fit to the data as has often been done in epidemiological studies. The article presents arguments to support several related messages which are relevant to epidemiological analysis, the derivation of low dose risk and the weighting factor of sparsely ionising radiations. The messages are: (a) cancer incidence following acute exposure should, in principle, be fitted to a linear-quadratic curve with cell killing using all the data available; (b) the acute data are dominated by the quadratic component of dose; (c) the linear fit of any acute data will essentially be dependent on the quadratic component and will be unrelated to the effectiveness of the radiation at low doses; consequently, (d) the method used by ICRP to derive low dose risk from the atomic bomb survivor data means that it is unrelated to the effectiveness of the hard gamma radiation at low radiation doses; (e) the low dose risk value should, therefore, not be used as if it were representative for hard gamma rays to argue for an increased weighting factor for tritium and soft x-rays even though there are mechanistic reasons to expect this; (f) epidemiological studies of chronically exposed populations supported by appropriate cellular radiobiological studies have the best chance of revealing different RBE values for different sparsely ionising radiations.

Sources of variation for indoor nitrogen dioxide in rural residences of Ethiopia

PubMed Central

2009-01-01

Background Unprocessed biomass fuel is the primary source of indoor air pollution (IAP) in developing countries. The use of biomass fuel has been linked with acute respiratory infections. This study assesses sources of variations associated with the level of indoor nitrogen dioxide (NO2). Materials and methods This study examines household factors affecting the level of indoor pollution by measuring NO2. Repeated measurements of NO2 were made using a passive diffusive sampler. A Saltzman colorimetric method using a spectrometer calibrated at 540 nm was employed to analyze the mass of NO2 on the collection filter that was then subjected to a mass transfer equation to calculate the level of NO2 for the 24 hours of sampling duration. Structured questionnaire was used to collect data on fuel use characteristics. Data entry and cleaning was done in EPI INFO version 6.04, while data was analyzed using SPSS version 15.0. Analysis of variance, multiple linear regression and linear mixed model were used to isolate determining factors contributing to the variation of NO2 concentration. Results A total of 17,215 air samples were fully analyzed during the study period. Wood and crop were principal source of household energy. Biomass fuel characteristics were strongly related to indoor NO2 concentration in one-way analysis of variance. There was variation in repeated measurements of indoor NO2 over time. In a linear mixed model regression analysis, highland setting, wet season, cooking, use of fire events at least twice a day, frequency of cooked food items, and interaction between ecology and season were predictors of indoor NO2 concentration. The volume of the housing unit and the presence of kitchen showed little relevance in the level of NO2 concentration. Conclusion Agro-ecology, season, purpose of fire events, frequency of fire activities, frequency of cooking and physical conditions of housing are predictors of NO2 concentration. Improved kitchen conditions and ventilation are highly recommended. PMID:19922645

Unsupervised Bayesian linear unmixing of gene expression microarrays.

PubMed

Bazot, Cécile; Dobigeon, Nicolas; Tourneret, Jean-Yves; Zaas, Aimee K; Ginsburg, Geoffrey S; Hero, Alfred O

2013-03-19

This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene signatures, called factors, with random positive mixing coefficients, called factor scores, that specify the relative contribution of each signature to a specific sample. The particularity of the proposed method is that uBLU constrains the factor loadings to be non-negative and the factor scores to be probability distributions over the factors. Furthermore, it also provides estimates of the number of factors. A Gibbs sampling strategy is adopted here to generate random samples according to the posterior distribution of the factors, factor scores, and number of factors. These samples are then used to estimate all the unknown parameters. Firstly, the proposed uBLU method is applied to several simulated datasets with known ground truth and compared with previous factor decomposition methods, such as principal component analysis (PCA), non negative matrix factorization (NMF), Bayesian factor regression modeling (BFRM), and the gradient-based algorithm for general matrix factorization (GB-GMF). Secondly, we illustrate the application of uBLU on a real time-evolving gene expression dataset from a recent viral challenge study in which individuals have been inoculated with influenza A/H3N2/Wisconsin. We show that the uBLU method significantly outperforms the other methods on the simulated and real data sets considered here. The results obtained on synthetic and real data illustrate the accuracy of the proposed uBLU method when compared to other factor decomposition methods from the literature (PCA, NMF, BFRM, and GB-GMF). The uBLU method identifies an inflammatory component closely associated with clinical symptom scores collected during the study. Using a constrained model allows recovery of all the inflammatory genes in a single factor.

Modelling typhoid risk in Dhaka Metropolitan Area of Bangladesh: the role of socio-economic and environmental factors

PubMed Central

2013-01-01

Background Developing countries in South Asia, such as Bangladesh, bear a disproportionate burden of diarrhoeal diseases such as Cholera, Typhoid and Paratyphoid. These seem to be aggravated by a number of social and environmental factors such as lack of access to safe drinking water, overcrowdedness and poor hygiene brought about by poverty. Some socioeconomic data can be obtained from census data whilst others are more difficult to elucidate. This study considers a range of both census data and spatial data from other sources, including remote sensing, as potential predictors of typhoid risk. Typhoid data are aggregated from hospital admission records for the period from 2005 to 2009. The spatial and statistical structures of the data are analysed and Principal Axis Factoring is used to reduce the degree of co-linearity in the data. The resulting factors are combined into a Quality of Life index, which in turn is used in a regression model of typhoid occurrence and risk. Results The three Principal Factors used together explain 87% of the variance in the initial candidate predictors, which eminently qualifies them for use as a set of uncorrelated explanatory variables in a linear regression model. Initial regression result using Ordinary Least Squares (OLS) were disappointing, this was explainable by analysis of the spatial autocorrelation inherent in the Principal factors. The use of Geographically Weighted Regression caused a considerable increase in the predictive power of regressions based on these factors. The best prediction, determined by analysis of the Akaike Information Criterion (AIC) was found when the three factors were combined into a quality of life index, using a method previously published by others, and had a coefficient of determination of 73%. Conclusions The typhoid occurrence/risk prediction equation was used to develop the first risk map showing areas of Dhaka Metropolitan Area whose inhabitants are at greater or lesser risk of typhoid infection. This, coupled with seasonal information on typhoid incidence also reported in this paper, has the potential to advise public health professionals on developing prevention strategies such as targeted vaccination. PMID:23497202

Modelling typhoid risk in Dhaka metropolitan area of Bangladesh: the role of socio-economic and environmental factors.

PubMed

Corner, Robert J; Dewan, Ashraf M; Hashizume, Masahiro

2013-03-16

Developing countries in South Asia, such as Bangladesh, bear a disproportionate burden of diarrhoeal diseases such as cholera, typhoid and paratyphoid. These seem to be aggravated by a number of social and environmental factors such as lack of access to safe drinking water, overcrowdedness and poor hygiene brought about by poverty. Some socioeconomic data can be obtained from census data whilst others are more difficult to elucidate. This study considers a range of both census data and spatial data from other sources, including remote sensing, as potential predictors of typhoid risk. Typhoid data are aggregated from hospital admission records for the period from 2005 to 2009. The spatial and statistical structures of the data are analysed and principal axis factoring is used to reduce the degree of co-linearity in the data. The resulting factors are combined into a quality of life index, which in turn is used in a regression model of typhoid occurrence and risk. The three principal factors used together explain 87% of the variance in the initial candidate predictors, which eminently qualifies them for use as a set of uncorrelated explanatory variables in a linear regression model. Initial regression result using ordinary least squares (OLS) were disappointing, this was explainable by analysis of the spatial autocorrelation inherent in the principal factors. The use of geographically weighted regression caused a considerable increase in the predictive power of regressions based on these factors. The best prediction, determined by analysis of the Akaike information criterion (AIC) was found when the three factors were combined into a quality of life index, using a method previously published by others, and had a coefficient of determination of 73%. The typhoid occurrence/risk prediction equation was used to develop the first risk map showing areas of Dhaka metropolitan area whose inhabitants are at greater or lesser risk of typhoid infection. This, coupled with seasonal information on typhoid incidence also reported in this paper, has the potential to advise public health professionals on developing prevention strategies such as targeted vaccination.

Prevalence and Predisposing Factors for Depressive Status in Chinese Patients with Obstructive Sleep Apnoea: A Large-Sample Survey.

PubMed

Dai, Yaozhang; Li, Xuewu; Zhang, Xin; Wang, Sihua; Sang, Jianzhong; Tian, Xiufen; Cao, Hua

2016-01-01

Recently, there are few studies reporting on depressive status and obstructive sleep apnoea (OSA) in China. A large-sample survey was to be performed to explore the prevalence of depressive status and related factors in Chinese patients with OSA. From among a randomly-selected group of OSA patients, 1,327 met inclusion criteria. After screening with the Symptom Checklist 90 (SCL-90) and Self-Rating Depression Scale (SDS), patients were assigned to OSA without depressive status (control group, n = 698) and OSA with depressive status (n = 629) groups. Using chi-squared testing, the correlation analyses between the depressive status and OSA patient demographic and clinical variables were tested. Then depression-related risk factors in OSA patients were analysed using stepwise linear regression analysis. The effects of family and social factors on depressive status in OSA patients were investigated using Mann-Whitney U (one of nonparametric test). The prevalence of depressive status was 47.4% in OSA patients. Depressive status was significantly associated with female gender, single status, Family Burden Scale of Disease (FBS), Family APGAR Index (APGAR), apnoea-hypopnea index (AHI), and Perceived Social Support Scale (PSSS). Stepwise linear regression analysis further indicated that single status, hypoxemia, APGAR, AHI, PSSS, AHI, and FBS were all risk factors for depressive status in OSA patients. The total of the FBS score and three of its sub-factors scores (family daily activities, family relationships and mental health of family members) were higher, and the total of the APGAR score and two of its sub-factors scores (adaptability and affection) were lower in OSA with depressive status compared with the control group. Besides, the total score for the PSSS and scores for its two sub-factors (family support and social support) were all lower in OSA patients with depressive status than those of the control group. Depressive status has high comorbid rate in Chinese OSA patients and is significantly associated with single status, apnoea-hypopnea index, hypoxemia, family and social supports.

Prevalence and Predisposing Factors for Depressive Status in Chinese Patients with Obstructive Sleep Apnoea: A Large-Sample Survey

PubMed Central

Dai, Yaozhang; Li, Xuewu; Zhang, Xin; Wang, Sihua; Sang, Jianzhong; Tian, Xiufen; Cao, Hua

2016-01-01

Background and Objective Recently, there are few studies reporting on depressive status and obstructive sleep apnoea (OSA) in China. A large-sample survey was to be performed to explore the prevalence of depressive status and related factors in Chinese patients with OSA. Methods From among a randomly-selected group of OSA patients, 1,327 met inclusion criteria. After screening with the Symptom Checklist 90 (SCL-90) and Self-Rating Depression Scale (SDS), patients were assigned to OSA without depressive status (control group, n = 698) and OSA with depressive status (n = 629) groups. Using chi-squared testing, the correlation analyses between the depressive status and OSA patient demographic and clinical variables were tested. Then depression-related risk factors in OSA patients were analysed using stepwise linear regression analysis. The effects of family and social factors on depressive status in OSA patients were investigated using Mann-Whitney U (one of nonparametric test). Results The prevalence of depressive status was 47.4% in OSA patients. Depressive status was significantly associated with female gender, single status, Family Burden Scale of Disease (FBS), Family APGAR Index (APGAR), apnoea-hypopnea index (AHI), and Perceived Social Support Scale (PSSS). Stepwise linear regression analysis further indicated that single status, hypoxemia, APGAR, AHI, PSSS, AHI, and FBS were all risk factors for depressive status in OSA patients. The total of the FBS score and three of its sub-factors scores (family daily activities, family relationships and mental health of family members) were higher, and the total of the APGAR score and two of its sub-factors scores (adaptability and affection) were lower in OSA with depressive status compared with the control group. Besides, the total score for the PSSS and scores for its two sub-factors (family support and social support) were all lower in OSA patients with depressive status than those of the control group. Conclusions Depressive status has high comorbid rate in Chinese OSA patients and is significantly associated with single status, apnoea-hypopnea index, hypoxemia, family and social supports. PMID:26934192

The application of two-step linear temperature program to thermal analysis for monitoring the lipid induction of Nostoc sp. KNUA003 in large scale cultivation.

PubMed

Kang, Bongmun; Yoon, Ho-Sung

2015-02-01

Recently, microalgae was considered as a renewable energy for fuel production because its production is nonseasonal and may take place on nonarable land. Despite all of these advantages, microalgal oil production is significantly affected by environmental factors. Furthermore, the large variability remains an important problem in measurement of algae productivity and compositional analysis, especially, the total lipid content. Thus, there is considerable interest in accurate determination of total lipid content during the biotechnological process. For these reason, various high-throughput technologies were suggested for accurate measurement of total lipids contained in the microorganisms, especially oleaginous microalgae. In addition, more advanced technologies were employed to quantify the total lipids of the microalgae without a pretreatment. However, these methods are difficult to measure total lipid content in wet form microalgae obtained from large-scale production. In present study, the thermal analysis performed with two-step linear temeperature program was applied to measure heat evolved in temperature range from 310 to 351 °C of Nostoc sp. KNUA003 obtained from large-scale cultivation. And then, we examined the relationship between the heat evolved in 310-351 °C (HE) and total lipid content of the wet Nostoc cell cultivated in raceway. As a result, the linear relationship was determined between HE value and total lipid content of Nostoc sp. KNUA003. Particularly, there was a linear relationship of 98% between the HE value and the total lipid content of the tested microorganism. Based on this relationship, the total lipid content converted from the heat evolved of wet Nostoc sp. KNUA003 could be used for monitoring its lipid induction in large-scale cultivation. Copyright © 2014 Elsevier Inc. All rights reserved.

Adult weight gain and colorectal adenomas-a systematic review and meta-analysis.

PubMed

Schlesinger, S; Aleksandrova, K; Abar, L; Vieria, A R; Vingeliene, S; Polemiti, E; Stevens, C A T; Greenwood, D C; Chan, D S M; Aune, D; Norat, T

2017-06-01

Colorectal adenomas are known as precursors for the majority of colorectal carcinomas. While weight gain during adulthood has been identified as a risk factor for colorectal cancer, the association is less clear for colorectal adenomas. We conducted a systematic review and meta-analysis to quantify the evidence on this association. We searched Medline up to September 2016 to identify observational (prospective, cross-sectional and retrospective) studies on weight gain during adulthood and colorectal adenoma occurrence and recurrence. We conducted meta-analysis on high weight gain versus stable weight, linear and non-linear dose-response meta-analyses to analyze the association. Summary odds ratios (OR) and 95% confidence intervals (95% CI) were estimated using a random effects model. For colorectal adenoma occurrence, the summary OR was 1.39 (95% CI: 1.17-1.65; I2: 43%, N = 9 studies, cases = 5507) comparing high (midpoint: 17.4 kg) versus stable weight gain during adulthood and with each 5 kg weight gain the odds increased by 7% (2%-11%; I2: 65%, N = 7 studies). Although there was indication of non-linearity (Pnon-linearity < 0.001) there was an increased odds of colorectal adenoma throughout the whole range of weight gain. Three studies were identified investigating the association between weight gain and colorectal adenoma recurrence and data were limited to draw firm conclusions. Even a small amount of adult weight gain was related to a higher odds of colorectal adenoma occurrence. Our findings add to the benefits of weight control in adulthood regarding colorectal adenoma occurrence, which might be relevant for early prevention of colorectal cancer. © The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Expendable launch vehicle studies

NASA Technical Reports Server (NTRS)

Bainum, Peter M.; Reiss, Robert

1995-01-01

Analytical support studies of expendable launch vehicles concentrate on the stability of the dynamics during launch especially during or near the region of maximum dynamic pressure. The in-plane dynamic equations of a generic launch vehicle with multiple flexible bending and fuel sloshing modes are developed and linearized. The information from LeRC about the grids, masses, and modes is incorporated into the model. The eigenvalues of the plant are analyzed for several modeling factors: utilizing diagonal mass matrix, uniform beam assumption, inclusion of aerodynamics, and the interaction between the aerodynamics and the flexible bending motion. Preliminary PID, LQR, and LQG control designs with sensor and actuator dynamics for this system and simulations are also conducted. The initial analysis for comparison of PD (proportional-derivative) and full state feedback LQR Linear quadratic regulator) shows that the split weighted LQR controller has better performance than that of the PD. In order to meet both the performance and robustness requirements, the H(sub infinity) robust controller for the expendable launch vehicle is developed. The simulation indicates that both the performance and robustness of the H(sub infinity) controller are better than that for the PID and LQG controllers. The modelling and analysis support studies team has continued development of methodology, using eigensensitivity analysis, to solve three classes of discrete eigenvalue equations. In the first class, the matrix elements are non-linear functions of the eigenvector. All non-linear periodic motion can be cast in this form. Here the eigenvector is comprised of the coefficients of complete basis functions spanning the response space and the eigenvalue is the frequency. The second class of eigenvalue problems studied is the quadratic eigenvalue problem. Solutions for linear viscously damped structures or viscoelastic structures can be reduced to this form. Particular attention is paid to Maxwell and Kelvin models. The third class of problems consists of linear eigenvalue problems in which the elements of the mass and stiffness matrices are stochastic. dynamic structural response for which the parameters are given by probabilistic distribution functions, rather than deterministic values, can be cast in this form. Solutions for several problems in each class will be presented.

NLOphoric rigid pyrazino-phenanthroline donor-π-acceptor compounds: Investigation of structural and solvent effects on non-linear optical properties using computational methods

NASA Astrophysics Data System (ADS)

Kothavale, Shantaram; Katariya, Santosh; Sekar, Nagaiyan

2018-01-01

Rigid pyrazino-phenanthroline based donor-π-acceptor-π-auxiliary acceptor type compounds have been studied for their linear and non-linear optical properties. The non-linear optical (NLO) behavior of these dyes was studied by calculating the values of static α , β and γ using solvatochromic as well as computational methods. The results obtained by solvatochromic method are correlated theoretically with Density Functional Theory (DFT) using B3LYP/6-31G (d), CAM B3LYP/6-31 G(d), B3LYP/6-31++ g(d,P) and CAM B3LYP/6-31++ g(d,P) methods. The results reveal that, among all four computational methods CAM-B3LYP/6-31++ g(d,P) performs well for the calculation of linear polarizability (α) and first order hyperpolarizability (β), while CAM-B3LYP/6-31 g(d,P) for the calculation of second order hyperpolarizability (ϒ). Overall TPA depends on the molecular structure variation with increase in complexity and molecular weight, which implies that both the number of branches and the size of π-framework are important factors for the molecular TPA in this chromophoric system. Generalized Mulliken-Hush (GMH) analysis is performed to study the effective charge transfer from donor to acceptor.

Alcohol outlet density and assault: a spatial analysis.

PubMed

Livingston, Michael

2008-04-01

A large number of studies have found links between alcohol outlet densities and assault rates in local areas. This study tests a variety of specifications of this link, focusing in particular on the possibility of a non-linear relationship. Cross-sectional data on police-recorded assaults during high alcohol hours, liquor outlets and socio-demographic characteristics were obtained for 223 postcodes in Melbourne, Australia. These data were used to construct a series of models testing the nature of the relationship between alcohol outlet density and assault, while controlling for socio-demographic factors and spatial auto-correlation. Four types of relationship were examined: a normal linear relationship between outlet density and assault, a non-linear relationship with potential threshold or saturation densities, a relationship mediated by the socio-economic status of the neighbourhood and a relationship which takes into account the effect of outlets in surrounding neighbourhoods. The model positing non-linear relationships between outlet density and assaults was found to fit the data most effectively. An increasing accelerating effect for the density of hotel (pub) licences was found, suggesting a plausible upper limit for these licences in Melbourne postcodes. The study finds positive relationships between outlet density and assault rates and provides evidence that this relationship is non-linear and thus has critical values at which licensing policy-makers can impose density limits.

Hybrid PV/diesel solar power system design using multi-level factor analysis optimization

NASA Astrophysics Data System (ADS)

Drake, Joshua P.

Solar power systems represent a large area of interest across a spectrum of organizations at a global level. It was determined that a clear understanding of current state of the art software and design methods, as well as optimization methods, could be used to improve the design methodology. Solar power design literature was researched for an in depth understanding of solar power system design methods and algorithms. Multiple software packages for the design and optimization of solar power systems were analyzed for a critical understanding of their design workflow. In addition, several methods of optimization were studied, including brute force, Pareto analysis, Monte Carlo, linear and nonlinear programming, and multi-way factor analysis. Factor analysis was selected as the most efficient optimization method for engineering design as it applied to solar power system design. The solar power design algorithms, software work flow analysis, and factor analysis optimization were combined to develop a solar power system design optimization software package called FireDrake. This software was used for the design of multiple solar power systems in conjunction with an energy audit case study performed in seven Tibetan refugee camps located in Mainpat, India. A report of solar system designs for the camps, as well as a proposed schedule for future installations was generated. It was determined that there were several improvements that could be made to the state of the art in modern solar power system design, though the complexity of current applications is significant.

Factors that influence the efficacy of acarbose and metformin as initial therapy in Chinese patients with newly diagnosed type 2 diabetes: a subanalysis of the MARCH trial.

PubMed

Zhang, Jinping; Wang, Na; Xing, Xiaoyan; Yang, Zhaojun; Wang, Xin; Yang, Wenying

2016-01-01

To conduct a subanalysis of the randomized MARCH (Metformin and AcaRbose in Chinese as the initial Hypoglycemic treatment) trial to investigate whether specific characteristics are associated with the efficacy of either acarbose or metformin as initial therapy. A total of 657 type 2 diabetes patients who were randomly assigned to 48 weeks of therapy with either acarbose or metformin in the MARCH trial were divided into two groups based upon their hemoglobin A1c (HbA1c) levels at the end of follow-up: HbA1c <7% (<53 mmol/mol) and ≥7% (≥53 mmol/mol). Univariate, multivariate, and stepwise linear regression analyses were applied to identify the factors associated with treatment efficacy. Because this was a subanalysis, no measurement was performed. Univariate analysis showed that the efficacy of acarbose and metformin was influenced by HbA1c, fasting blood glucose (FBG), and 2 hour postprandial venous blood glucose (2hPPG) levels, as well as by changes in body mass index (BMI) (p ≤ 0.006). Multivariate analysis and stepwise linear regression analyses indicated that lower baseline 2hPPG values and greater changes in BMI were factors that positively influenced efficacy in both treatment groups (p ≤ 0.05). Stepwise regression model analysis also revealed that a lower baseline homeostasis model assessment-estimated insulin resistance (HOMA-IR) and higher serum insulin area under the curve (AUC) were factors positively influencing HbA1c normalization in all patients (p ≤ 0.032). Newly diagnosed type 2 diabetes patients with lower baseline 2hPPG and HOMA-IR values are more likely to achieve glucose control with acarbose or metformin treatment. Furthermore, the change in BMI after acarbose or metformin treatment is also a factor influencing HbA1c normalization. A prospective study with a larger sample size is necessary to confirm our results as well as measure β cell function and examine the influence of the patients' dietary habits.

Comparative Study on Code-based Linear Evaluation of an Existing RC Building Damaged during 1998 Adana-Ceyhan Earthquake

NASA Astrophysics Data System (ADS)

Toprak, A. Emre; Gülay, F. Gülten; Ruge, Peter

2008-07-01

Determination of seismic performance of existing buildings has become one of the key concepts in structural analysis topics after recent earthquakes (i.e. Izmit and Duzce Earthquakes in 1999, Kobe Earthquake in 1995 and Northridge Earthquake in 1994). Considering the need for precise assessment tools to determine seismic performance level, most of earthquake hazardous countries try to include performance based assessment in their seismic codes. Recently, Turkish Earthquake Code 2007 (TEC'07), which was put into effect in March 2007, also introduced linear and non-linear assessment procedures to be applied prior to building retrofitting. In this paper, a comparative study is performed on the code-based seismic assessment of RC buildings with linear static methods of analysis, selecting an existing RC building. The basic principles dealing the procedure of seismic performance evaluations for existing RC buildings according to Eurocode 8 and TEC'07 will be outlined and compared. Then the procedure is applied to a real case study building is selected which is exposed to 1998 Adana-Ceyhan Earthquake in Turkey, the seismic action of Ms = 6.3 with a maximum ground acceleration of 0.28 g It is a six-storey RC residential building with a total of 14.65 m height, composed of orthogonal frames, symmetrical in y direction and it does not have any significant structural irregularities. The rectangular shaped planar dimensions are 16.40 m×7.80 m = 127.90 m2 with five spans in x and two spans in y directions. It was reported that the building had been moderately damaged during the 1998 earthquake and retrofitting process was suggested by the authorities with adding shear-walls to the system. The computations show that the performing methods of analysis with linear approaches using either Eurocode 8 or TEC'07 independently produce similar performance levels of collapse for the critical storey of the structure. The computed base shear value according to Eurocode is much higher than the requirements of the Turkish Earthquake Code while the selected ground conditions represent the same characteristics. The main reason is that the ordinate of the horizontal elastic response spectrum for Eurocode 8 is increased by the soil factor. In TEC'07 force-based linear assessment, the seismic demands at cross-sections are to be checked with residual moment capacities; however, the chord rotations of primary ductile elements must be checked for Eurocode safety verifications. On the other hand, the demand curvatures from linear methods of analysis of Eurocode 8 together with TEC'07 are almost similar.

Combined cumulative sum (CUSUM) and chronological environmental analysis as a tool to improve the learning environment for linear-probe endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) trainees: a pilot study.

PubMed

Norisue, Yasuhiro; Tokuda, Yasuharu; Juarez, Mayrol; Uchimido, Ryo; Fujitani, Shigeki; Stoeckel, David A

2017-02-07

Cumulative sum (CUSUM) analysis can be used to continuously monitor the performance of an individual or process and detect deviations from a preset or standard level of achievement. However, no previous study has evaluated the utility of CUSUM analysis in facilitating timely environmental assessment and interventions to improve performance of linear-probe endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA). The aim of this study was to evaluate the usefulness of combined CUSUM and chronological environmental analysis as a tool to improve the learning environment for EBUS-TBNA trainees. This study was an observational chart review. To determine if performance was acceptable, CUSUM analysis was used to track procedural outcomes of trainees in EBUS-TBNA. To investigate chronological changes in the learning environment, multivariate logistic regression analysis was used to compare several indices before and after time points when significant changes occurred in proficiency. Presence of an additional attending bronchoscopist was inversely associated with nonproficiency (odds ratio, 0.117; 95% confidence interval, 0-0.749; P = 0.019). Other factors, including presence of an on-site cytopathologist and dose of sedatives used, were not significantly associated with duration of nonproficiency. Combined CUSUM and chronological environmental analysis may be useful in hastening interventions that improve performance of EBUS-TBNA.

Relative importance of habitat filtering and limiting similarity on species assemblages of alpine and subalpine plant communities.

PubMed

Takahashi, Koichi; Tanaka, Saeka

2016-11-01

This study examined how habitat filtering and limiting similarity affect species assemblages of alpine and subalpine plant communities along a slope gradient on Mt. Norikura in central Japan. Plant traits (plant height, individual leaf area, specific leaf area (SLA), leaf linearity, leaf nitrogen and chlorophyll concentrations) and abiotic environmental factors (elevation, slope inclination, ground surface texture, soil water, soil pH, soil nutrient concentrations of NH 4 -N and NO 3 -N) were examined. The metrics of variance, range, kurtosis and the standard deviation of neighbor distance divided by the range of traits present (SDNDr) were calculated for each plant trait to measure trait distribution patterns. Limiting similarity was detected only for chlorophyll concentration. By contrast, habitat filtering was detected for individual leaf area, SLA, leaf linearity, chlorophyll concentration. Abiotic environmental factors were summarized by the principal component analysis (PCA). The first PCA axis positively correlated with elevation and soil pH, and negatively correlated with sand cover, soil water, NH 4 -N and NO 3 -N concentrations. High values of the first PCA axis represent the wind-exposed upper slope with lower soil moisture and nutrient availabilities. Plant traits changed along the first PCA axis. Leaf area, SLA and chlorophyll concentration decreased, and leaf linearity increased with the first PCA axis. This study showed that the species assemblage of alpine and subalpine plants was determined mainly by habitat filtering, indicating that abiotic environmental factors are more important for species assemblage than interspecific competition. Therefore, only species adapting to abiotic environments can distribute to these environments.

Using hierarchical linear growth models to evaluate protective mechanisms that mediate science achievement

NASA Astrophysics Data System (ADS)

von Secker, Clare Elaine

The study of students at risk is a major topic of science education policy and discussion. Much research has focused on describing conditions and problems associated with the statistical risk of low science achievement among individuals who are members of groups characterized by problems such as poverty and social disadvantage. But outcomes attributed to these factors do not explain the nature and extent of mechanisms that account for differences in performance among individuals at risk. There is ample theoretical and empirical evidence that demographic differences should be conceptualized as social contexts, or collections of variables, that alter the psychological significance and social demands of life events, and affect subsequent relationships between risk and resilience. The hierarchical linear growth models used in this dissertation provide greater specification of the role of social context and the protective effects of attitude, expectations, parenting practices, peer influences, and learning opportunities on science achievement. While the individual influences of these protective factors on science achievement were small, their cumulative effect was substantial. Meta-analysis conducted on the effects associated with psychological and environmental processes that mediate risk mechanisms in sixteen social contexts revealed twenty-two significant differences between groups of students. Positive attitudes, high expectations, and more intense science course-taking had positive effects on achievement of all students, although these factors were not equally protective in all social contexts. In general, effects associated with authoritative parenting and peer influences were negative, regardless of social context. An evaluation comparing the performance and stability of hierarchical linear growth models with traditional repeated measures models is included as well.

[Influence of autoclave sterilization on dimensional stability and detail reproduction of 5 additional silicone impression materials].

PubMed

Xu, Tong-kai; Sun, Zhi-hui; Jiang, Yong

2012-03-01

To evaluate the dimensional stability and detail reproduction of five additional silicone impression materials after autoclave sterilization. Impressions were made on the ISO 4823 standard mold containing several marking lines, in five kinds of additional silicone. All the impressions were sterilized by high temperature and pressure (135 °C, 212.8 kPa) for 25 min. Linear measurements of pre-sterilization and post-sterilization were made with a measuring microscope. Statistical analysis utilized single-factor analysis with pair-wise comparison of mean values when appropriate. Hypothesis testing was conducted at alpha = 0.05. No significant difference was found between the pre-sterilization and post-sterilization conditions for all locations, and all the absolute valuse of linear rate of change less than 8%. All the sterilization by the autoclave did not affect the surfuce detail reproduction of the 5 impression materials. The dimensional stability and detail reproduction of the five additional silicone impression materials in the study was unaffected by autoclave sterilization.

The determination of trace lead in Chinese medicinal herbs by flow injection analysis in polyethyleneglycol medium

NASA Astrophysics Data System (ADS)

Gong, Aiqin; Zhu, Xiashi; Huang, Xiaoyan; Zhang, Yaqin

2008-01-01

In this work, a new flow injection analysis (FIA) for the determination of Pb 2+ in Chinese medicinal herbs was developed. In the buffer solution of borax-NaOH (pH 10.5), Pb 2+ reacted with 2-[(5-bromo-2-pyridyl)-azo]-5-(diethyl-amino)phenol (5-Br-PADAP) to form a complex. The experimental results showed that the sensitivity was enhanced in the presence of polyethyleneglycol-800 (PG-800). The main factors affecting the determination were investigated in detail. Under the optimum conditions, the linear range and detection limit is 0.0-0.3 μg/mL and 1.5 ng/mL (correlation coefficient r = 0.9996), respectively. The linear regression equation is A = -0.005 + 0.60 c (μg/mL). The sample throughout is 10 h -1. Foreign substrates effects were also investigated. The proposed method has been successfully applied to the determination of lead in reference material, goldthread and lepidium seed.

Improved application of independent component analysis to functional magnetic resonance imaging study via linear projection techniques.

PubMed

Long, Zhiying; Chen, Kewei; Wu, Xia; Reiman, Eric; Peng, Danling; Yao, Li

2009-02-01

Spatial Independent component analysis (sICA) has been widely used to analyze functional magnetic resonance imaging (fMRI) data. The well accepted implicit assumption is the spatially statistical independency of intrinsic sources identified by sICA, making the sICA applications difficult for data in which there exist interdependent sources and confounding factors. This interdependency can arise, for instance, from fMRI studies investigating two tasks in a single session. In this study, we introduced a linear projection approach and considered its utilization as a tool to separate task-related components from two-task fMRI data. The robustness and feasibility of the method are substantiated through simulation on computer data and fMRI real rest data. Both simulated and real two-task fMRI experiments demonstrated that sICA in combination with the projection method succeeded in separating spatially dependent components and had better detection power than pure model-based method when estimating activation induced by each task as well as both tasks.

Analysis of Instabilities in Non-Axisymmetric Hypersonic Boundary Layers Over Cones

NASA Technical Reports Server (NTRS)

Li, Fei; Choudhari, Meelan M.; Chang, Chau-Lyan; White, Jeffery A.

2010-01-01

Hypersonic flows over circular cones constitute one of the most important generic configurations for fundamental aerodynamic and aerothermodynamic studies. In this paper, numerical computations are carried out for Mach 6 flows over a 7-degree half-angle cone with two different flow incidence angles and a compression cone with a large concave curvature. Instability wave and transition-related flow physics are investigated using a series of advanced stability methods ranging from conventional linear stability theory (LST) and a higher-fidelity linear and nonlinear parabolized stability equations (PSE), to the 2D eigenvalue analysis based on partial differential equations. Computed N factor distribution pertinent to various instability mechanisms over the cone surface provides initial assessments of possible transition fronts and a guide to corresponding disturbance characteristics such as frequency and azimuthal wave numbers. It is also shown that strong secondary instability that eventually leads to transition to turbulence can be simulated very efficiently using a combination of advanced stability methods described above.

CMB and matter power spectra with non-linear dark-sector interactions

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

Marttens, R.F. vom; Casarini, L.; Zimdahl, W.

2017-01-01

An interaction between dark matter and dark energy, proportional to the product of their energy densities, results in a scaling behavior of the ratio of these densities with respect to the scale factor of the Robertson-Walker metric. This gives rise to a class of cosmological models which deviate from the standard model in an analytically tractable way. In particular, it becomes possible to quantify the role of potential dark-energy perturbations. We investigate the impact of this interaction on the structure formation process. Using the (modified) CAMB code we obtain the CMB spectrum as well as the linear matter power spectrum.more » It is shown that the strong degeneracy in the parameter space present in the background analysis is considerably reduced by considering Planck data. Our analysis is compatible with the ΛCDM model at the 2σ confidence level with a slightly preferred direction of the energy flow from dark matter to dark energy.« less

Gain optimization with non-linear controls

NASA Technical Reports Server (NTRS)

Slater, G. L.; Kandadai, R. D.

1984-01-01

An algorithm has been developed for the analysis and design of controls for non-linear systems. The technical approach is to use statistical linearization to model the non-linear dynamics of a system by a quasi-Gaussian model. A covariance analysis is performed to determine the behavior of the dynamical system and a quadratic cost function. Expressions for the cost function and its derivatives are determined so that numerical optimization techniques can be applied to determine optimal feedback laws. The primary application for this paper is centered about the design of controls for nominally linear systems but where the controls are saturated or limited by fixed constraints. The analysis is general, however, and numerical computation requires only that the specific non-linearity be considered in the analysis.

Piping benchmark problems. Volume 1. Dynamic analysis uniform support motion response spectrum method

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

Bezler, P.; Hartzman, M.; Reich, M.

1980-08-01

A set of benchmark problems and solutions have been developed for verifying the adequacy of computer programs used for dynamic analysis and design of nuclear piping systems by the Response Spectrum Method. The problems range from simple to complex configurations which are assumed to experience linear elastic behavior. The dynamic loading is represented by uniform support motion, assumed to be induced by seismic excitation in three spatial directions. The solutions consist of frequencies, participation factors, nodal displacement components and internal force and moment components. Solutions to associated anchor point motion static problems are not included.

Input-output characterization of an ultrasonic testing system by digital signal analysis

NASA Technical Reports Server (NTRS)

Karaguelle, H.; Lee, S. S.; Williams, J., Jr.

1984-01-01

The input/output characteristics of an ultrasonic testing system used for stress wave factor measurements were studied. The fundamentals of digital signal processing are summarized. The inputs and outputs are digitized and processed in a microcomputer using digital signal processing techniques. The entire ultrasonic test system, including transducers and all electronic components, is modeled as a discrete-time linear shift-invariant system. Then the impulse response and frequency response of the continuous time ultrasonic test system are estimated by interpolating the defining points in the unit sample response and frequency response of the discrete time system. It is found that the ultrasonic test system behaves as a linear phase bandpass filter. Good results were obtained for rectangular pulse inputs of various amplitudes and durations and for tone burst inputs whose center frequencies are within the passband of the test system and for single cycle inputs of various amplitudes. The input/output limits on the linearity of the system are determined.

Risk factors of autistic symptoms in children with ADHD.

PubMed

Kröger, Anne; Hänig, Susann; Seitz, Christiane; Palmason, Haukur; Meyer, Jobst; Freitag, Christine M

2011-12-01

Autistic symptoms are frequently observed in children with attention-deficit/hyperactivity disorder (ADHD), but their etiology remains unclear. The main aim of this study was to describe risk factors for increased autistic symptoms in children with ADHD without an autism or autism-spectrum diagnosis. Comorbid psychiatric disorders, developmental delay, current medication, prenatal biological and postnatal psychosocial risk factors as well as parental autistic traits were assessed in 205 children with ADHD. Linear regression models identified maternal autistic traits, current familial risk factors and hyperactive symptoms as predictors of autistic symptoms in children with ADHD. Findings are indicative of possible genetic as well as environmental risk factors mediating autistic symptoms in children with ADHD. An additional validity analysis by ROC, area under the curve (AUC), suggested a cut-off of 11 to differentiate between ADHD and high-functioning ASD by the Social Communication Questionnaire (SCQ).

The effect of broken stringers on the stress intensity factor for a uniformly stiffened sheet containing a crack

NASA Technical Reports Server (NTRS)

Poe, C. C., Jr.

1973-01-01

A linear elastic stress analysis was made of a centrally cracked sheet stiffened by riveted, uniformly spaced and sized stringers. The stress intensity factor for the sheet and the load concentration factor for the most highly loaded stringer were determined for various numbers of broken stringers. A broken stringer causes the stress intensity factor to be very high when the crack tip is near the broken stringer, but causes little effect when the crack tip extends beyond several intact stringers. A broken stringer also causes an increase in the load concentration factor of the adjacent stringers. The calculated residual strengths and fatigue-crack-growth lives of a stiffened aluminum sheet with a broken stringer were only slightly less than a sheet with all intact stringers, and were still much higher than those of an unstiffened sheet.

Design of experiments as a tool for LC-MS/MS method development for the trace analysis of the potentially genotoxic 4-dimethylaminopyridine impurity in glucocorticoids.

PubMed

Székely, Gy; Henriques, B; Gil, M; Ramos, A; Alvarez, C

2012-11-01

The present study reports on a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method development strategy supported by design of experiments (DoE) for the trace analysis of 4-dimethylaminopyridine (DMAP). The conventional approaches for development of LC-MS/MS methods are usually via trial and error, varying intentionally the experimental factors which is time consuming and interactions between experimental factors are not considered. The LC factors chosen for the DoE study include flow (F), gradient (G) and injection volume (V(inj)) while cone voltage (E(con)) and collision energy (E(col)) were chosen as MS parameters. All of the five factors were studied simultaneously. The method was optimized with respect to four responses: separation of peaks (Sep), peak area (A(peak)), length of the analysis (T) and the signal to noise ratio (S/N). A quadratic model, namely central composite face (CCF) featuring 29 runs was used instead of a less powerful linear model since the increase in the number of injections was insignificant. In order to determine the robustness of the method a new set of DoE experiments was carried out applying robustness around the optimal conditions was evaluated applying a fractional factorial of resolution III with 11 runs, wherein additional factors - such as column temperature and quadrupole resolution - were considered. The method utilizes a Phenomenex Gemini NX C-18 HPLC analytical column with electrospray ionization and a triple quadrupole mass detector in multiple reaction monitoring (MRM) mode, resulting in short analyses with a 10min runtime. Drawbacks of derivatization, namely incomplete reaction and time consuming sample preparation, have been avoided and the change from SIM to MRM mode resulted in increased sensitivity and lower LOQ. The DoE method development strategy led to a method allowing the trace analysis of DMAP at 0.5 ng/ml absolute concentration which corresponds to a 0.1 ppm limit of quantification in 5mg/ml mometasone furoate glucocorticoid. The obtained method was validated in a linear range of 0.1-10 ppm and presented a %RSD of 0.02% for system precision. Regarding DMAP recovery in mometasone furoate, spiked samples produced %recoveries between 83 and 113% in the range of 0.1-2 ppm. Copyright © 2012 Elsevier B.V. All rights reserved.

Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

PubMed Central

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

2017-01-01

Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

The parenting attitudes and the stress of mothers predict the asthmatic severity of their children: a prospective study.

PubMed

Nagano, Jun; Kakuta, Chikage; Motomura, Chikako; Odajima, Hiroshi; Sudo, Nobuyuki; Nishima, Sankei; Kubo, Chiharu

2010-10-07

To examine relationships between a mother's stress-related conditions and parenting attitudes and their children's asthmatic status. 274 mothers of an asthmatic child 2 to 12 years old completed a questionnaire including questions about their chronic stress/coping behaviors (the "Stress Inventory"), parenting attitudes (the "Ta-ken Diagnostic Test for Parent-Child Relationship, Parent Form"), and their children's disease status. One year later, a follow-up questionnaire was mailed to the mothers that included questions on the child's disease status. 223 mothers (81%) responded to the follow-up survey. After controlling for non-psychosocial factors including disease severity at baseline, multiple linear regression analysis followed by multiple logistic regression analysis found chronic irritation/anger and emotional suppression to be aggravating factors for children aged < 7 years; for children aged 7 and over, the mothers' egocentric behavior was a mitigating factor while interference was an aggravating factor. Different types of parental stress/coping behaviors and parenting styles may differently predict their children's asthmatic status, and such associations may change as children grow.

Total Ambient Dose Equivalent Buildup Factor Determination for Nbs04 Concrete.

PubMed

Duckic, Paulina; Hayes, Robert B

2018-06-01

Buildup factors are dimensionless multiplicative factors required by the point kernel method to account for scattered radiation through a shielding material. The accuracy of the point kernel method is strongly affected by the correspondence of analyzed parameters to experimental configurations, which is attempted to be simplified here. The point kernel method has not been found to have widespread practical use for neutron shielding calculations due to the complex neutron transport behavior through shielding materials (i.e. the variety of interaction mechanisms that neutrons may undergo while traversing the shield) as well as non-linear neutron total cross section energy dependence. In this work, total ambient dose buildup factors for NBS04 concrete are calculated in terms of neutron and secondary gamma ray transmission factors. The neutron and secondary gamma ray transmission factors are calculated using MCNP6™ code with updated cross sections. Both transmission factors and buildup factors are given in a tabulated form. Practical use of neutron transmission and buildup factors warrants rigorously calculated results with all associated uncertainties. In this work, sensitivity analysis of neutron transmission factors and total buildup factors with varying water content has been conducted. The analysis showed significant impact of varying water content in concrete on both neutron transmission factors and total buildup factors. Finally, support vector regression, a machine learning technique, has been engaged to make a model based on the calculated data for calculation of the buildup factors. The developed model can predict most of the data with 20% relative error.

Advanced Statistical Analyses to Reduce Inconsistency of Bond Strength Data.

PubMed

Minamino, T; Mine, A; Shintani, A; Higashi, M; Kawaguchi-Uemura, A; Kabetani, T; Hagino, R; Imai, D; Tajiri, Y; Matsumoto, M; Yatani, H

2017-11-01

This study was designed to clarify the interrelationship of factors that affect the value of microtensile bond strength (µTBS), focusing on nondestructive testing by which information of the specimens can be stored and quantified. µTBS test specimens were prepared from 10 noncarious human molars. Six factors of µTBS test specimens were evaluated: presence of voids at the interface, X-ray absorption coefficient of resin, X-ray absorption coefficient of dentin, length of dentin part, size of adhesion area, and individual differences of teeth. All specimens were observed nondestructively by optical coherence tomography and micro-computed tomography before µTBS testing. After µTBS testing, the effect of these factors on µTBS data was analyzed by the general linear model, linear mixed effects regression model, and nonlinear regression model with 95% confidence intervals. By the general linear model, a significant difference in individual differences of teeth was observed ( P < 0.001). A significantly positive correlation was shown between µTBS and length of dentin part ( P < 0.001); however, there was no significant nonlinearity ( P = 0.157). Moreover, a significantly negative correlation was observed between µTBS and size of adhesion area ( P = 0.001), with significant nonlinearity ( P = 0.014). No correlation was observed between µTBS and X-ray absorption coefficient of resin ( P = 0.147), and there was no significant nonlinearity ( P = 0.089). Additionally, a significantly positive correlation was observed between µTBS and X-ray absorption coefficient of dentin ( P = 0.022), with significant nonlinearity ( P = 0.036). A significant difference was also observed between the presence and absence of voids by linear mixed effects regression analysis. Our results showed correlations between various parameters of tooth specimens and µTBS data. To evaluate the performance of the adhesive more precisely, the effect of tooth variability and a method to reduce variation in bond strength values should also be considered.

Increased rates of authorship in radiology publications: a bibliometric analysis of 142,576 articles published worldwide by radiologists between 1991 and 2012.

PubMed

Chow, Daniel S; Ha, Richard; Filippi, Christopher G

2015-01-01

OBJECTIVE; There is evidence in academic medicine that the number of authors per paper has increased over time. The goal of this study was to quantitatively analyze authorship trends in the field of radiology over 20 years. A search of the National Library of Medicine MEDLINE database was conducted to identify articles published by radiology departments between 1991 and 2012. Country of origin, article study design, and journal impact factor were recorded. The increase in number of authors per paper was assessed by linear and nonlinear regression. Pearson correlation was used to assess the relation between journal impact factor and number of authors. A total of 142,576 articles and 699,257 authors were identified during the study period. The mean number of authors per paper displayed linear growth from 3.9 to 5.7 (p < 0.0001). The proportion of single authors declined from 11% in 1991 to 4.4% in 2012. The number of clinical trials increased in a linear pattern, review articles in an exponential pattern, and case reports in a logistic pattern (p < 0.0001 for each). Countries with the highest number of authors per paper were Japan, Italy, and Germany. The number of articles funded by the U.S. National Institutes of Health (NIH) displayed exponential growth and of non-NIH-funded articles displayed linear growth (p < 0.0001 for each). A negligible relation was observed between journal impact factor and number of authors (Pearson r = 0.1066). Radiology has had a steady increase in mean number of authors per paper since the early 1990s that has varied by study design. The increase is probably multi-factorial and includes components of author inflation and increasing complexity of research. Findings support the need for reemphasis of authorship criteria to preserve authorship value and accountability.

Efficient multitasking of Choleski matrix factorization on CRAY supercomputers

NASA Technical Reports Server (NTRS)

Overman, Andrea L.; Poole, Eugene L.

1991-01-01

A Choleski method is described and used to solve linear systems of equations that arise in large scale structural analysis. The method uses a novel variable-band storage scheme and is structured to exploit fast local memory caches while minimizing data access delays between main memory and vector registers. Several parallel implementations of this method are described for the CRAY-2 and CRAY Y-MP computers demonstrating the use of microtasking and autotasking directives. A portable parallel language, FORCE, is used for comparison with the microtasked and autotasked implementations. Results are presented comparing the matrix factorization times for three representative structural analysis problems from runs made in both dedicated and multi-user modes on both computers. CPU and wall clock timings are given for the parallel implementations and are compared to single processor timings of the same algorithm.

[Correlation research on contents of podophyllotoxin and total lignans in Sinopodophyllum hexandrum and ecological factors].

PubMed

Li, Min; Zhong, Guo-yue; Wu, Ao-lin; Zhang, Shou-wen; Jiang, Wei; Liang, Jian

2015-05-01

To explore the correlation between the ecological factors and the contents of podophyllotoxin and total lignans in root and rhizome of Sinopodophyllum hexandrum, podophyllotoxin in 87 samples (from 5 provinces) was determined by HPLC and total lignans by UV. A correlation and regression analysis was made by software SPSS 16.0 in combination with ecological factors (terrain, soil and climate). The content determination results showed a great difference between podophyllotoxin and total lignans, attaining 1.001%-6.230% and 5.350%-16.34%, respective. The correlation and regression analysis by SPSS showed a positive linear correlation between their contents, strong positive correlation between their contents, latitude and annual average rainfall within the sampling area, weak negative correlation with pH value and organic material in soil, weaker and stronger positive correlations with soil potassium, weak negative correlation with slope and annual average temperature and weaker positive correlation between the podophyllotoxin content and soil potassium.

Analysis of the effectiveness of fertilizer subsidy policy and its effect on rice production in Karanganyar Regency

NASA Astrophysics Data System (ADS)

Mulyadiana, A. T.; Marwanti, S.; Rahayu, W.

2018-03-01

The research aims to know the factors which affecting rice production, and to know the effectiveness of fertilizer subsidy policy on rice production in Karanganyar Regency. The fertilizer subsidy policy was based on four indicators of fertilizer subsidy namely exact price, exact place, exact time, and exact quantity. Data was analyzed using descriptive quantitative and qualitative and multiple linear regression. The result of research showed that fertilizer subsidy policy in Karanganyar Regency evaluated from four indicators was not effective because the distribution of fertilizer subsidy to farmers still experience some mistakes. The result of regression analysis showed that production factors such as land area, use of urea fertilizer, use of NPK fertilizer, and effectiveness of fertilizer subsidy policy had positive correlation and significant influence on rice production, while labor utilization and use of seeds factors had no significant effect on rice production in Karanganyar Regency. This means that if the fertilizer subsidy policy is more effective, rice production is also increased.

Solar cycle signal in air temperature in North America - Amplitude, gradient, phase and distribution

NASA Technical Reports Server (NTRS)

Currie, R. G.

1981-01-01

The considered investigation was motivated by three factors. One is related to an extension of single-channel MESA to multi-channel by Strand (1977), Morf et al. (1978), and Jones (1978). MESA is a high-resolution signal processing and spectrum analysis technique due to Burg (1975). The considered developments resulted in the discovery of the 11-year solar cycle signal in the change of the length of day by Currie (1980, 1981). They also led Currie (1981) to study the phase spectrum of the 11-year term in height H of sea level. The investigation tries to clarify the phase relations among the involved parameters. The second factor is connected with an application of the linear time domain technique used by Currie (1981) to temperature records to obtain more accurate information regarding the signal amplitude. The third factor of motivation is related to increases in the number of stations available for an analysis, the greater average length of the records, and the more accurate data set.

Factors contributing to Korean teachers' attitudes toward students with epilepsy.

PubMed

Lee, Sang-Ahm; Yim, Soo Bin; Rho, Young Il; Chu, Minkyung; Park, Hyeon Mi; Lee, Geun-ho; Park, Sung-Pa; Jung, Dae Soo

2011-02-01

We investigated factors contributing to teachers' attitudes toward students with epilepsy. Data were collected from 604 teachers in Korea. The questionnaire included the Scale of Attitudes Toward Persons with Epilepsy (ATPE) and a demographic and teaching experience survey. In stepwise linear regression analysis, ATPE Knowledge scores (P<0.001) and prior experience teaching a student with epilepsy (P=0.001) were identified as significant factors for ATPE Attitude scores. The ATPE Knowledge scores accounted for 50.1% of the variance in the Attitude scores, and experience teaching a student with epilepsy accounted only for 1.0%. Our finding that teachers' knowledge is the most important factor influencing teacher's attitudes toward epilepsy indicates that teachers should be provided with information about epilepsy universally, across geographic settings, educational levels, and experience levels. Copyright © 2010 Elsevier Inc. All rights reserved.

[Optimization of cultivation conditions in se-enriched Spirulina platensis].

PubMed

Huang, Zhi; Zheng, Wen-Jie; Guo, Bao-Jiang

2002-05-01

Orthogonal combination design was adopted in examining the Spirulina platensis (S. platensis) yield and the influence of four factors (Se content, Se-adding method, S content and NaHCO3 content) on algae growth. The results showed that Se content, Se-adding method and NaHCO3 content were key factors in cultivation conditions of Se-enriched S. platensis with the optimal combination being Se at 300 mg/L, Se-adding amount equally divided into three times and NaHCO3 at 16.8 g/L. Algae yield had a remarkable correlation with OD560 and floating rate by linear regression analysis. There was a corresponding relationship between effects of the four factors on algae yield and on OD560, floating rate too. In conclusion, OD560 and floating rate could be served as yield-forming factors.

Factors that determine self-reported immunosuppressant adherence in kidney transplant recipients: a correlational study.

PubMed

Weng, Li-Chueh; Yang, Ya-Chen; Huang, Hsiu-Li; Chiang, Yang-Jen; Tsai, Yu-Hsia

2017-01-01

To determine the factors related to immunosuppressant therapy adherence in kidney transplant recipients in Taiwan. Adherence to immunosuppressant treatment is critical after kidney transplantation. Thus, the factors associated with self-reported medication adherence in kidney transplant recipients warrant investigation. The study used a cross-sectional and correlation design. A convenience sample of 145 kidney transplant recipients was included. Structured questionnaires were used to collect data during 2012-2013. Multivariate linear regression was used to examine the factors related to immunosuppressant therapy adherence. Over half of the participants were female (54·5%), mean age was 45·5 years, and mean year after transplant was 7·4. The mean score for medication adherence was 29·73 (possible score range 7-35). The results of the multivariate linear regression analysis showed that gender (male), low income with a high school or college education, years after transplantation and concerns about medication taking were negatively associated with adherence. Medication self-efficacy was positively associated with adherence. Therapy-related factors, partnerships with healthcare professionals and having private healthcare insurance did not significantly relate to immunosuppressant therapy adherence. Kidney transplant recipients demonstrated a high level of adherence. Strategies to enhance patients' self-efficacy and alleviate concerns about medication may promote medication adherence. Male patients, those with a lower income and those with a higher education level, should be a focus of efforts to maintain adherence to the medication regimen. © 2016 John Wiley & Sons Ltd.

A Multiphase Non-Linear Mixed Effects Model: An Application to Spirometry after Lung Transplantation

PubMed Central

Rajeswaran, Jeevanantham; Blackstone, Eugene H.

2014-01-01

In medical sciences, we often encounter longitudinal temporal relationships that are non-linear in nature. The influence of risk factors may also change across longitudinal follow-up. A system of multiphase non-linear mixed effects model is presented to model temporal patterns of longitudinal continuous measurements, with temporal decomposition to identify the phases and risk factors within each phase. Application of this model is illustrated using spirometry data after lung transplantation using readily available statistical software. This application illustrates the usefulness of our flexible model when dealing with complex non-linear patterns and time varying coefficients. PMID:24919830

Phytotoxicity and accumulation of chromium in carrot plants and the derivation of soil thresholds for Chinese soils.

PubMed

Ding, Changfeng; Li, Xiaogang; Zhang, Taolin; Ma, Yibing; Wang, Xingxiang

2014-10-01

Soil environmental quality standards in respect of heavy metals for farmlands should be established considering both their effects on crop yield and their accumulation in the edible part. A greenhouse experiment was conducted to investigate the effects of chromium (Cr) on biomass production and Cr accumulation in carrot plants grown in a wide range of soils. The results revealed that carrot yield significantly decreased in 18 of the total 20 soils with Cr addition being the soil environmental quality standard of China. The Cr content of carrot grown in the five soils with pH>8.0 exceeded the maximum allowable level (0.5mgkg(-1)) according to the Chinese General Standard for Contaminants in Foods. The relationship between carrot Cr concentration and soil pH could be well fitted (R(2)=0.70, P<0.0001) by a linear-linear segmented regression model. The addition of Cr to soil influenced carrot yield firstly rather than the food quality. The major soil factors controlling Cr phytotoxicity and the prediction models were further identified and developed using path analysis and stepwise multiple linear regression analysis. Soil Cr thresholds for phytotoxicity meanwhile ensuring food safety were then derived on the condition of 10 percent yield reduction. Copyright © 2014 Elsevier Inc. All rights reserved.

A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty

NASA Astrophysics Data System (ADS)

Zhang, Chenglong; Guo, Ping

2017-10-01

The vague and fuzzy parametric information is a challenging issue in irrigation water management problems. In response to this problem, a generalized fuzzy credibility-constrained linear fractional programming (GFCCFP) model is developed for optimal irrigation water allocation under uncertainty. The model can be derived from integrating generalized fuzzy credibility-constrained programming (GFCCP) into a linear fractional programming (LFP) optimization framework. Therefore, it can solve ratio optimization problems associated with fuzzy parameters, and examine the variation of results under different credibility levels and weight coefficients of possibility and necessary. It has advantages in: (1) balancing the economic and resources objectives directly; (2) analyzing system efficiency; (3) generating more flexible decision solutions by giving different credibility levels and weight coefficients of possibility and (4) supporting in-depth analysis of the interrelationships among system efficiency, credibility level and weight coefficient. The model is applied to a case study of irrigation water allocation in the middle reaches of Heihe River Basin, northwest China. Therefore, optimal irrigation water allocation solutions from the GFCCFP model can be obtained. Moreover, factorial analysis on the two parameters (i.e. λ and γ) indicates that the weight coefficient is a main factor compared with credibility level for system efficiency. These results can be effective for support reasonable irrigation water resources management and agricultural production.

Development of a nearshore oscillating surge wave energy converter with variable geometry

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

Tom, N. M.; Lawson, M. J.; Yu, Y. H.

This paper presents an analysis of a novel wave energy converter concept that combines an oscillating surge wave energy converter (OSWEC) with control surfaces. The control surfaces allow for a variable device geometry that enables the hydrodynamic properties to be adapted with respect to structural loading, absorption range and power-take-off capability. The device geometry is adjusted on a sea state-to-sea state time scale and combined with wave-to-wave manipulation of the power take-off (PTO) to provide greater control over the capture efficiency, capacity factor, and design loads. This work begins with a sensitivity study of the hydrodynamic coefficients with respect tomore » device width, support structure thickness, and geometry. A linear frequency domain analysis is used to evaluate device performance in terms of absorbed power, foundation loads, and PTO torque. Previous OSWEC studies included nonlinear hydrodynamics, in response a nonlinear model that includes a quadratic viscous damping torque that was linearized via the Lorentz linearization. Inclusion of the quadratic viscous torque led to construction of an optimization problem that incorporated motion and PTO constraints. Results from this study found that, when transitioning from moderate-to-large sea states the novel OSWEC was capable of reducing structural loads while providing a near constant power output.« less

Noise suppression for the differential detection in nuclear magnetic resonance gyroscope

NASA Astrophysics Data System (ADS)

Yang, Dan; Zhou, Binquan; Chen, LinLin; Jia, YuChen; Lu, QiLin

2017-10-01

The nuclear magnetic resonance gyroscope is based on spin-exchange optical pumping of noble gases to detect and measure the angular velocity of the carrier, but it would be challenging to measure the precession signal of noble gas nuclei directly. To solve the problem, the primary detection method utilizes alkali atoms, the precession of nuclear magnetization modulates the alkali atoms at the Larmor frequency of nuclei, relatively speaking, and it is easier to detect the precession signal of alkali atoms. The precession frequency of alkali atoms is detected by the rotation angle of linearly polarized probe light; and differential detection method is commonly used in NMRG in order to detect the linearly polarized light rotation angle. Thus, the detection accuracy of differential detection system will affect the sensitivity of the NMRG. For the purpose of further improvement of the sensitivity level of the NMRG, this paper focuses on the aspects of signal detection, and aims to do an error analysis as well as an experimental research of the linearly light rotation angle detection. Through the theoretical analysis and the experimental illustration, we found that the extinction ratio σ2 and DC bias are the factors that will produce detective noise in the differential detection method.

Use of biopartitioning micellar chromatography and RP-HPLC for the determination of blood-brain barrier penetration of α-adrenergic/imidazoline receptor ligands, and QSPR analysis.

PubMed

Vucicevic, J; Popovic, M; Nikolic, K; Filipic, S; Obradovic, D; Agbaba, D

2017-03-01

For this study, 31 compounds, including 16 imidazoline/α-adrenergic receptor (IRs/α-ARs) ligands and 15 central nervous system (CNS) drugs, were characterized in terms of the retention factors (k) obtained using biopartitioning micellar and classical reversed phase chromatography (log k BMC and log k wRP , respectively). Based on the retention factor (log k wRP ) and slope of the linear curve (S) the isocratic parameter (φ 0 ) was calculated. Obtained retention factors were correlated with experimental log BB values for the group of examined compounds. High correlations were obtained between logarithm of biopartitioning micellar chromatography (BMC) retention factor and effective permeability (r(log k BMC /log BB): 0.77), while for RP-HPLC system the correlations were lower (r(log k wRP /log BB): 0.58; r(S/log BB): -0.50; r(φ 0 /P e ): 0.61). Based on the log k BMC retention data and calculated molecular parameters of the examined compounds, quantitative structure-permeability relationship (QSPR) models were developed using partial least squares, stepwise multiple linear regression, support vector machine and artificial neural network methodologies. A high degree of structural diversity of the analysed IRs/α-ARs ligands and CNS drugs provides wide applicability domain of the QSPR models for estimation of blood-brain barrier penetration of the related compounds.

Characterization of HPGe gamma spectrometric detectors systems for Instrumental Neutron Activation Analysis (INAA) at the Colombian Geological Survey

NASA Astrophysics Data System (ADS)

Sierra, O.; Parrado, G.; Cañón, Y.; Porras, A.; Alonso, D.; Herrera, D. C.; Peña, M.; Orozco, J.

2016-07-01

This paper presents the progress made by the Neutron Activation Analysis (NAA) laboratory at the Colombian Geological Survey (SGC in its Spanish acronym), towards the characterization of its gamma spectrometric systems for Instrumental Neutron Activation Analysis (INAA), with the aim of introducing corrections to the measurements by variations in sample geometry. Characterization includes the empirical determination of the interaction point of gamma radiation inside the Germanium crystal, through the application of a linear model and the use of a fast Monte Carlo N-Particle (MCNP) software to estimate correction factors for differences in counting efficiency that arise from variations in sample density between samples and standards.

Analysis of multi lobe journal bearings with surface roughness using finite difference method

NASA Astrophysics Data System (ADS)

PhaniRaja Kumar, K.; Bhaskar, SUdaya; Manzoor Hussain, M.

2018-04-01

Multi lobe journal bearings are used for high operating speeds and high loads in machines. In this paper symmetrical multi lobe journal bearings are analyzed to find out the effect of surface roughnessduring non linear loading. Using the fourth order RungeKutta method, time transient analysis was performed to calculate and plot the journal centre trajectories. Flow factor method is used to evaluate the roughness and the finite difference method (FDM) is used to predict the pressure distribution over the bearing surface. The Transient analysis is done on the multi lobe journal bearings for threedifferent surface roughness orientations. Longitudinal surface roughness is more effective when compared with isotopic and traverse surface roughness.

Factors associated to quality of life in active elderly.

PubMed

Alexandre, Tiago da Silva; Cordeiro, Renata Cereda; Ramos, Luiz Roberto

2009-08-01

To analyze whether quality of life in active, healthy elderly individuals is influenced by functional status and sociodemographic characteristics, as well as psychological parameters. Study conducted in a sample of 120 active elderly subjects recruited from two open universities of the third age in the cities of São Paulo and São José dos Campos (Southeastern Brazil) between May 2005 and April 2006. Quality of life was measured using the abbreviated Brazilian version of the World Health Organization Quality of Live (WHOQOL-bref) questionnaire. Sociodemographic, clinical and functional variables were measured through crossculturally validated assessments by the Mini Mental State Examination, Geriatric Depression Scale, Functional Reach, One-Leg Balance Test, Timed Up and Go Test, Six-Minute Walk Test, Human Activity Profile and a complementary questionnaire. Simple descriptive analyses, Pearson's correlation coefficient, Student's t-test for non-related samples, analyses of variance, linear regression analyses and variance inflation factor were performed. The significance level for all statistical tests was set at 0.05. Linear regression analysis showed an independent correlation without colinearity between depressive symptoms measured by the Geriatric Depression Scale and four domains of the WHOQOL-bref. Not having a conjugal life implied greater perception in the social domain; developing leisure activities and having an income over five minimum wages implied greater perception in the environment domain. Functional status had no influence on the Quality of Life variable in the analysis models in active elderly. In contrast, psychological factors, as assessed by the Geriatric Depression Scale, and sociodemographic characteristics, such as marital status, income and leisure activities, had an impact on quality of life.

A multiple linear regression analysis of factors affecting the simulated Basic Life Support (BLS) performance with Automated External Defibrillator (AED) in Flemish lifeguards.

PubMed

Iserbyt, Peter; Schouppe, Gilles; Charlier, Nathalie

2015-04-01

Research investigating lifeguards' performance of Basic Life Support (BLS) with Automated External Defibrillator (AED) is limited. Assessing simulated BLS/AED performance in Flemish lifeguards and identifying factors affecting this performance. Six hundred and sixteen (217 female and 399 male) certified Flemish lifeguards (aged 16-71 years) performed BLS with an AED on a Laerdal ResusciAnne manikin simulating an adult victim of drowning. Stepwise multiple linear regression analysis was conducted with BLS/AED performance as outcome variable and demographic data as explanatory variables. Mean BLS/AED performance for all lifeguards was 66.5%. Compression rate and depth adhered closely to ERC 2010 guidelines. Ventilation volume and flow rate exceeded the guidelines. A significant regression model, F(6, 415)=25.61, p<.001, ES=.38, explained 27% of the variance in BLS performance (R2=.27). Significant predictors were age (beta=-.31, p<.001), years of certification (beta=-.41, p<.001), time on duty per year (beta=-.25, p<.001), practising BLS skills (beta=.11, p=.011), and being a professional lifeguard (beta=-.13, p=.029). 71% of lifeguards reported not practising BLS/AED. Being young, recently certified, few days of employment per year, practising BLS skills and not being a professional lifeguard are factors associated with higher BLS/AED performance. Measures should be taken to prevent BLS/AED performances from decaying with age and longer certification. Refresher courses could include a formal skills test and lifeguards should be encouraged to practise their BLS/AED skills. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Perceived cognitive impairment in Chinese patients with breast cancer and its relationship with post-traumatic stress disorder symptoms and fatigue.

PubMed

Li, Jie; Yu, Lixiang; Long, Zhouting; Li, Yang; Cao, Fenglin

2015-06-01

Clinical reports have shown that adjuvant chemotherapy has a negative impact on perceived cognitive impairment (PCI) of patients with breast cancer; however, evidence concerning the effects of psychological factors such as post-traumatic stress disorder (PTSD) symptoms on PCI is limited, especially in relation to Chinese patients with breast cancer. This research investigated the associations between psychological factors and PCI in Chinese women with breast cancer. In total, 204 women with breast cancer were assessed for PCI, PTSD symptoms, fatigue, anxiety, and depression using self-report measures. Hierarchical linear regression was conducted to investigate the associations between the variables of interest and PCI. Two hundred and two women were included in the final analysis; two of those originally tested were excluded because of missing data. A univariate analysis showed that PCI was significantly related to education, PTSD symptoms (re-experience, avoidance, and hyperarousal), fatigue, depression, anxiety, and undergoing chemotherapy or radiotherapy. Hierarchical linear regression revealed that PTSD symptoms and fatigue (ΔR(2)  = 0.26, P < 0.001) independently accounted for PCI in Chinese women with breast cancer regardless of age, education level, chemotherapy and radiotherapy. Hyperarousal was the only contributing PTSD symptom to PCI (B = -1.24, SE = 0.33, β = -0.39, P < 0.001). Besides chemotherapy, PTSD symptoms, especially hyperarousal, and fatigue are important risk factors for significant PCI and are therefore worthy of further investigation. Copyright © 2014 John Wiley & Sons, Ltd.

Factors that influence standard automated perimetry test results in glaucoma: test reliability, technician experience, time of day, and season.

PubMed

Junoy Montolio, Francisco G; Wesselink, Christiaan; Gordijn, Marijke; Jansonius, Nomdo M

2012-10-09

To determine the influence of several factors on standard automated perimetry test results in glaucoma. Longitudinal Humphrey field analyzer 30-2 Swedish interactive threshold algorithm data from 160 eyes of 160 glaucoma patients were used. The influence of technician experience, time of day, and season on the mean deviation (MD) was determined by performing linear regression analysis of MD against time on a series of visual fields and subsequently performing a multiple linear regression analysis with the MD residuals as dependent variable and the factors mentioned above as independent variables. Analyses were performed with and without adjustment for the test reliability (fixation losses and false-positive and false-negative answers) and with and without stratification according to disease stage (baseline MD). Mean follow-up was 9.4 years, with on average 10.8 tests per patient. Technician experience, time of day, and season were associated with the MD. Approximately 0.2 dB lower MD values were found for inexperienced technicians (P < 0.001), tests performed after lunch (P < 0.001), and tests performed in the summer or autumn (P < 0.001). The effects of time of day and season appeared to depend on disease stage. Independent of these effects, the percentage of false-positive answers strongly influenced the MD with a 1 dB increase in MD per 10% increase in false-positive answers. Technician experience, time of day, season, and the percentage of false-positive answers have a significant influence on the MD of standard automated perimetry.

Factors associated with stress among adolescents in the city of Nawabshah, Pakistan.

PubMed

Parpio, Yasmin; Farooq, Salima; Gulzar, Saleema; Tharani, Ambreen; Javed, Fawad; Ali, Tazeen Saeed

2012-11-01

To identify the risk factors of stress among school-going adolescents in rural Nawabshah, Pakistan. The cross-sectional study was conducted in 2005, comprising 800 school-going children of 10-16 years of age in Nawabshah, through simple random sampling. Data was collected using a structured questionnaire to assess the potential risk factors of stress. A modified version of Perceived stress scale was utilized to measure stress level. SPSS 12 was used for statistical analysis, while multiple linear regression analysis was run to identify the factors associated with stress in the study population. Of the total, 529 (66%) children belonged to state-run schools while 271 (34%) were studying at private facilities. The mean age was 13.7+/-1.3 years. The level of stress was positively associated with the number of siblings, parental conflicts, the age of the mother and the number of rooms in the household. There was decreased level of stress among female adolescents (n=474; 59.3%) who had prior information about pubertal body changes than the boys (n=326; 40.8%). The study showed that stress among adolescents can be reduced by modifying socio-economic and demographic factors.

[Baseline correction of spectrum for the inversion of chlorophyll-a concentration in the turbidity water].

PubMed

Wei, Yu-Chun; Wang, Guo-Xiang; Cheng, Chun-Mei; Zhang, Jing; Sun, Xiao-Peng

2012-09-01

Suspended particle material is the main factor affecting remote sensing inversion of chlorophyll-a concentration (Chla) in turbidity water. According to the optical property of suspended material in water, the present paper proposed a linear baseline correction method to weaken the suspended particle contribution in the spectrum above turbidity water surface. The linear baseline was defined as the connecting line of reflectance from 450 to 750 nm, and baseline correction is that spectrum reflectance subtracts the baseline. Analysis result of field data in situ of Meiliangwan, Taihu Lake in April, 2011 and March, 2010 shows that spectrum linear baseline correction can improve the inversion precision of Chl a and produce the better model diagnoses. As the data in March, 2010, RMSE of band ratio model built by original spectrum is 4.11 mg x m(-3), and that built by spectrum baseline correction is 3.58 mg x m(-3). Meanwhile, residual distribution and homoscedasticity in the model built by baseline correction spectrum is improved obviously. The model RMSE of April, 2011 shows the similar result. The authors suggest that using linear baseline correction as the spectrum processing method to improve Chla inversion accuracy in turbidity water without algae bloom.

Perceived Social Ecological Factors Associated with Fruit and Vegetable Purchasing, Preparation, and Consumption among Young Adults

PubMed Central

Graham, Dan J.; Pelletier, Jennifer; Neumark-Sztainer, Dianne; Lust, Katherine; Laska, Melissa N.

2013-01-01

Most young adults do not consume recommended levels of fruits and vegetables (FV), and interventions to increase FV-related behaviors among this understudied population are needed. Therefore, it is important to identify correlates of FV intake among young adults to guide intervention development. This cross-sectional study utilized data from an online survey to identify factors related to young adults’ FV purchasing, preparation, and consumption, and to explore between-factor relationships using mediation analysis. In 2010, 1201 college students in Minnesota completed questionnaires assessing FV behaviors, as well as perceptions of FV-related individual, social, and environmental factors. Factor analysis identified questionnaire items assessing similar constructs. Seven factors were identified (personal barriers, FV knowledge, family, friends, neighborhood, access barriers, and campus) and evaluated for relationships with FV purchasing, preparation, and consumption using linear regression. Results revealed that perceived personal barriers (e.g., lacking cooking skills) were inversely related to all FV outcomes. Perception that family and friends eat healthfully and neighborhood access to FV were positively related to all outcomes. Individual-, social-, and environmental-level perceptions were related to purchasing, preparation, and consumption, and the effects of these factors were similar when accounting for mediated effects. Factors at all three levels and the ways in which these various factors operate together may be important to consider in future efforts to improve FV behaviors among young adults. PMID:23958116

Application of Bounded Linear Stability Analysis Method for Metrics-Driven Adaptive Control

NASA Technical Reports Server (NTRS)

Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje

2009-01-01

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics-driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a second order system that represents a pitch attitude control of a generic transport aircraft. The analysis shows that the system with the metrics-conforming variable adaptive gain becomes more robust to unmodeled dynamics or time delay. The effect of analysis time-window for BLSA is also evaluated in order to meet the stability margin criteria.

Factors Associated with Job Satisfaction among University Teachers in Northeastern Region of China: A Cross-Sectional Study.

PubMed

Pan, Bochen; Shen, Xue; Liu, Li; Yang, Yilong; Wang, Lie

2015-10-14

Teachers' job satisfaction is one of the key factors in institutional dynamics and is generally considered to be the primary variable by which the effectiveness of an organization's human resource is evaluated. The objectives of this study were to assess the level of job satisfaction among university teachers and to clarify the associated factors. A cross-sectional study was conducted between November 2013 and January 2014. Teachers from six universities in Shenyang, China were randomly sampled. The job satisfaction scale Minnesota Satisfaction Questionnaire (MSQ), perceived organizational support (POS), psychological capital questionnaire (PCQ-24), and effort-reward imbalance scale (ERI) together with questions about demographic and working factors were administered in questionnaires distributed to 1500 university teachers. Hierarchical linear regression analyses were performed to explore the related factors. 1210 effective responses were obtained (effective respondent rate 80.7%). The average score of overall job satisfaction was 69.71. Hierarchical linear regression analysis revealed that turnover intention, occupational stress and chronic disease all had negative impacts on job satisfaction, whereas perceived organizational support, psychological capital and higher monthly income were positively associated with job satisfaction among the university teachers. Age was also linked to the level of job satisfaction. All the variables explained 60.7% of the variance in job satisfaction. Chinese university teachers had a moderate level of job satisfaction. Demographic and working characteristics were associated factors for job satisfaction. Perceived organizational support showed the strongest association with job satisfaction. RESULTS of the study indicate that improving the perceived organizational support may increase the level of job satisfaction for university teachers.

A Systematic Review of Methodology: Time Series Regression Analysis for Environmental Factors and Infectious Diseases

PubMed Central

Imai, Chisato; Hashizume, Masahiro

2015-01-01

Background: Time series analysis is suitable for investigations of relatively direct and short-term effects of exposures on outcomes. In environmental epidemiology studies, this method has been one of the standard approaches to assess impacts of environmental factors on acute non-infectious diseases (e.g. cardiovascular deaths), with conventionally generalized linear or additive models (GLM and GAM). However, the same analysis practices are often observed with infectious diseases despite of the substantial differences from non-infectious diseases that may result in analytical challenges. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, systematic review was conducted to elucidate important issues in assessing the associations between environmental factors and infectious diseases using time series analysis with GLM and GAM. Published studies on the associations between weather factors and malaria, cholera, dengue, and influenza were targeted. Findings: Our review raised issues regarding the estimation of susceptible population and exposure lag times, the adequacy of seasonal adjustments, the presence of strong autocorrelations, and the lack of a smaller observation time unit of outcomes (i.e. daily data). These concerns may be attributable to features specific to infectious diseases, such as transmission among individuals and complicated causal mechanisms. Conclusion: The consequence of not taking adequate measures to address these issues is distortion of the appropriate risk quantifications of exposures factors. Future studies should pay careful attention to details and examine alternative models or methods that improve studies using time series regression analysis for environmental determinants of infectious diseases. PMID:25859149

Psychometric evaluation of the revised Illness Perception Questionnaire (IPQ-R) in cancer patients: confirmatory factor analysis and Rasch analysis.

PubMed

Ashley, Laura; Smith, Adam B; Keding, Ada; Jones, Helen; Velikova, Galina; Wright, Penny

2013-12-01

To provide new insights into the psychometrics of the revised Illness Perception Questionnaire (IPQ-R) in cancer patients. To undertake, for the first time using data from breast, colorectal and prostate cancer patients, a confirmatory factor analysis (CFA) to assess the validity of the IPQ-R's core seven-factor structure. Also, for the first time in any illness group, to undertake Rasch analysis to explore the extent to which the IPQ-R factors form unidimensional scales, with linear measurement properties and no Differential Item Functioning (DIF). Patients with potentially curable breast, colorectal or prostate cancer, within 6months post-diagnosis, completed the IPQ-R online (N=531). CFA was conducted, including multi-sample analysis, and for each IPQ-R factor fit to the Rasch model was assessed by examining, amongst other things, item fit, DIF and unidimensionality. The CFA showed a moderate fit of the data to the IPQ-R model, and stability across diagnosis, although fit was significantly improved following the removal of selected items. All seven factors achieved fit to the Rasch model, and exhibited unidimensionality and minimal DIF, although in most cases this was after some item rescoring and/or deletion. In both analyses, IPQ-R items 12, 18 and 24 were indicated as misfitting and removed. Given the rigorous standard of Rasch measurement, and the generic nature of the IPQ-R, it stood up well to the demands of the Rasch model in this study. Importantly, the results show that with some relatively minor, pragmatic modifications the IPQ-R could possess Rasch-standard measurement in cancer patients. © 2013.

The non-linear power spectrum of the Lyman alpha forest

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

Arinyo-i-Prats, Andreu; Miralda-Escudé, Jordi; Viel, Matteo

2015-12-01

The Lyman alpha forest power spectrum has been measured on large scales by the BOSS survey in SDSS-III at z∼ 2.3, has been shown to agree well with linear theory predictions, and has provided the first measurement of Baryon Acoustic Oscillations at this redshift. However, the power at small scales, affected by non-linearities, has not been well examined so far. We present results from a variety of hydrodynamic simulations to predict the redshift space non-linear power spectrum of the Lyα transmission for several models, testing the dependence on resolution and box size. A new fitting formula is introduced to facilitate themore » comparison of our simulation results with observations and other simulations. The non-linear power spectrum has a generic shape determined by a transition scale from linear to non-linear anisotropy, and a Jeans scale below which the power drops rapidly. In addition, we predict the two linear bias factors of the Lyα forest and provide a better physical interpretation of their values and redshift evolution. The dependence of these bias factors and the non-linear power on the amplitude and slope of the primordial fluctuations power spectrum, the temperature-density relation of the intergalactic medium, and the mean Lyα transmission, as well as the redshift evolution, is investigated and discussed in detail. A preliminary comparison to the observations shows that the predicted redshift distortion parameter is in good agreement with the recent determination of Blomqvist et al., but the density bias factor is lower than observed. We make all our results publicly available in the form of tables of the non-linear power spectrum that is directly obtained from all our simulations, and parameters of our fitting formula.« less

Bias-correction of PERSIANN-CDR Extreme Precipitation Estimates Over the United States

NASA Astrophysics Data System (ADS)

Faridzad, M.; Yang, T.; Hsu, K. L.; Sorooshian, S.

2017-12-01

Ground-based precipitation measurements can be sparse or even nonexistent over remote regions which make it difficult for extreme event analysis. PERSIANN-CDR (CDR), with 30+ years of daily rainfall information, provides an opportunity to study precipitation for regions where ground measurements are limited. In this study, the use of CDR annual extreme precipitation for frequency analysis of extreme events over limited/ungauged basins is explored. The adjustment of CDR is implemented in two steps: (1) Calculated CDR bias correction factor at limited gauge locations based on the linear regression analysis of gauge and CDR annual maxima precipitation; and (2) Extend the bias correction factor to the locations where gauges are not available. The correction factors are estimated at gauge sites over various catchments, elevation zones, and climate regions and the results were generalized to ungauged sites based on regional and climatic similarity. Case studies were conducted on 20 basins with diverse climate and altitudes in the Eastern and Western US. Cross-validation reveals that the bias correction factors estimated on limited calibration data can be extended to regions with similar characteristics. The adjusted CDR estimates also outperform gauge interpolation on validation sites consistently. It is suggested that the CDR with bias adjustment has a potential for study frequency analysis of extreme events, especially for regions with limited gauge observations.

Hölder Regularity of the 2D Dual Semigeostrophic Equations via Analysis of Linearized Monge-Ampère Equations

NASA Astrophysics Data System (ADS)

Le, Nam Q.

2018-05-01

We obtain the Hölder regularity of time derivative of solutions to the dual semigeostrophic equations in two dimensions when the initial potential density is bounded away from zero and infinity. Our main tool is an interior Hölder estimate in two dimensions for an inhomogeneous linearized Monge-Ampère equation with right hand side being the divergence of a bounded vector field. As a further application of our Hölder estimate, we prove the Hölder regularity of the polar factorization for time-dependent maps in two dimensions with densities bounded away from zero and infinity. Our applications improve previous work by G. Loeper who considered the cases of densities sufficiently close to a positive constant.

Dynamics of short-pulse generation via spectral filtering from intensely excited gain-switched 1.55-μm distributed-feedback laser diodes.

PubMed

Chen, Shaoqiang; Yoshita, Masahiro; Sato, Aya; Ito, Takashi; Akiyama, Hidefumi; Yokoyama, Hiroyuki

2013-05-06

Picosecond-pulse-generation dynamics and pulse-width limiting factors via spectral filtering from intensely pulse-excited gain-switched 1.55-μm distributed-feedback laser diodes were studied. The spectral and temporal characteristics of the spectrally filtered pulses indicated that the short-wavelength component stems from the initial part of the gain-switched main pulse and has a nearly linear down-chirp of 5.2 ps/nm, whereas long-wavelength components include chirped pulse-lasing components and steady-state-lasing components. Rate-equation calculations with a model of linear change in refractive index with carrier density explained the major features of the experimental results. The analysis of the expected pulse widths with optimum spectral widths was also consistent with the experimental data.

Cooperation without Culture? The Null Effect of Generalized Trust on Intentional Homicide: A Cross-National Panel Analysis, 1995–2009

PubMed Central

Robbins, Blaine

2013-01-01

Sociologists, political scientists, and economists all suggest that culture plays a pivotal role in the development of large-scale cooperation. In this study, I used generalized trust as a measure of culture to explore if and how culture impacts intentional homicide, my operationalization of cooperation. I compiled multiple cross-national data sets and used pooled time-series linear regression, single-equation instrumental-variables linear regression, and fixed- and random-effects estimation techniques on an unbalanced panel of 118 countries and 232 observations spread over a 15-year time period. Results suggest that culture and large-scale cooperation form a tenuous relationship, while economic factors such as development, inequality, and geopolitics appear to drive large-scale cooperation. PMID:23527211

A linear programming manual

NASA Technical Reports Server (NTRS)

Tuey, R. C.

1972-01-01

Computer solutions of linear programming problems are outlined. Information covers vector spaces, convex sets, and matrix algebra elements for solving simultaneous linear equations. Dual problems, reduced cost analysis, ranges, and error analysis are illustrated.

Association of Alimentary Factors and Nutritional Status with Caries in Children of Leon, Mexico.

PubMed

Guizar, Juan Manuel; Muñoz, Nathalie; Amador, Norma; Garcia, Gabriela

To determine the association between types of food consumed, nutritional status (BMI) and caries in schoolchildren. A cross-sectional study was performed with 224 schoolchildren 6 to 12 years of age. DMFT/ dmft indices, level of oral hygiene, nutritional status as quantified by BMI and types of food consumed were determined in all participants. Data were analysed using multiple linear regression with significance set at p < 0.05. Caries prevalence was 36%. In the multiple linear regression analysis adjusted for BMI, variables related to a higher number of caries were younger age and lower intake of vitamin D, calcium and fiber, with higher consumption of phosphorous and carbohydrates (R2 = 0.30; p < 0.0001 for the model). Sweetened softdrinks and chewy candy were risk factors for higher caries prevalence, while consuming milk and carrots were protectors. Caries in schoolchildren is highly prevalent in this community and is related to younger age and lower intake of vitamin D, calcium and fiber, but a higher consumption of phosphorous and carbohydrates. No relationship was found between caries and nutritional status.

Dynamics of f(R) gravity models and asymmetry of time

NASA Astrophysics Data System (ADS)

Verma, Murli Manohar; Yadav, Bal Krishna

We solve the field equations of modified gravity for f(R) model in metric formalism. Further, we obtain the fixed points of the dynamical system in phase-space analysis of f(R) models, both with and without the effects of radiation. The stability of these points is studied against the perturbations in a smooth spatial background by applying the conditions on the eigenvalues of the matrix obtained in the linearized first-order differential equations. Following this, these fixed points are used for analyzing the dynamics of the system during the radiation, matter and acceleration-dominated phases of the universe. Certain linear and quadratic forms of f(R) are determined from the geometrical and physical considerations and the behavior of the scale factor is found for those forms. Further, we also determine the Hubble parameter H(t), the Ricci scalar R and the scale factor a(t) for these cosmic phases. We show the emergence of an asymmetry of time from the dynamics of the scalar field exclusively owing to the f(R) gravity in the Einstein frame that may lead to an arrow of time at a classical level.

Relation between age and carotid artery intima-medial thickness: a systematic review.

PubMed

van den Munckhof, Inge C L; Jones, Helen; Hopman, Maria T E; de Graaf, Jacqueline; Nyakayiru, Jean; van Dijk, Bart; Eijsvogels, Thijs M H; Thijssen, Dick H J

2018-05-12

Carotid artery intima-medial thickness (cIMT) represents a popular measure of atherosclerosis and is predictive of future cardiovascular and cerebrovascular events. Although older age is associated with a higher cIMT, little is known about whether this increase in cIMT follows a linear relationship with age or it is affected under influence of cardiovascular diseases (CVD) or CVD risk factors. We hypothesize that the relationship between cIMT and age is nonlinear and is affected by CVD or risk factors. A systematic review of studies that examined cIMT in the general population and human populations free from CVD/risk factors was undertaken. The literature search was conducted in PubMed, Scopus, and Web of Science. Seventeen studies with 32 unique study populations, involving 10,124 healthy individuals free from CVD risk factors, were included. Furthermore, 58 studies with 115 unique study populations were included, involving 65,774 individuals from the general population (with and without CVD risk factors). A strong positive association was evident between age and cIMT in the healthy population, demonstrating a gradual, linear increase in cIMT that did not differ between age decades (r = 0.91, P < 0.001). Although populations with individuals with CVD demonstrated a higher cIMT compared to populations free of CVD, a linear relation between age and cIMT was also present in this population. Our data suggest that cIMT is strongly and linearly related to age. This linear relationship was not affected by CVD or risk factors. © 2018 Wiley Periodicals, Inc.

Iron status as a covariate in methylmercury-associated neurotoxicity risk.

PubMed

Fonseca, Márlon de Freitas; De Souza Hacon, Sandra; Grandjean, Philippe; Choi, Anna Lai; Bastos, Wanderley Rodrigues

2014-04-01

Intrauterine methylmercury exposure and prenatal iron deficiency negatively affect offspring's brain development. Since fish is a major source of both methylmercury and iron, occurrence of negative confounding may affect the interpretation of studies concerning cognition. We assessed relationships between methylmercury exposure and iron-status in childbearing females from a population naturally exposed to methylmercury through fish intake (Amazon). We concluded a census (refuse <20%) collecting samples from 274 healthy females (12-49 years) for hair-mercury determination and assessed iron-status through red cell tests and determination of serum ferritin and iron. Reactive C protein and thyroid hormones was used for excluding inflammation and severe thyroid dysfunctions that could affect results. We assessed the association between iron-status and hair-mercury by bivariate correlation analysis and also by different multivariate models: linear regression (to check trends); hierarchical agglomerative clustering method (groups of variables correlated with each other); and factor analysis (to examine redundancy or duplication from a set of correlated variables). Hair-mercury correlated weakly with mean corpuscular volume (r=.141; P=.020) and corpuscular hemoglobin (r=.132; .029), but not with the best biomarker of iron-status, ferritin (r=.037; P=.545). In the linear regression analysis, methylmercury exposure showed weak association with age-adjusted ferritin; age had a significant coefficient (Beta=.015; 95% CI: .003-.027; P=.016) but ferritin did not (Beta=.034; 95% CI: -.147 to .216; P=.711). In the hierarchical agglomerative clustering method, hair-mercury and iron-status showed the smallest similarities. Regarding factor analysis, iron-status and hair-mercury loaded different uncorrelated components. We concluded that iron-status and methylmercury exposure probably occur in an independent way. Copyright © 2013 Elsevier Ltd. All rights reserved.

Structural equation model of factors related to quality of life for community-dwelling schizophrenic patients in Japan

PubMed Central

2014-01-01

Background This study aimed to clarify how community mental healthcare systems can be improved. Methods We included 79 schizophrenic patients, aged 20 to 80 years, residing in the Tokyo metropolitan area who regularly visited rehabilitation facilities offering assistance to psychiatric patients and were receiving treatment on an outpatient basis. No subjects had severe cognitive disorders or were taking medication with side effects that could prevent the completion of questionnaires. Questionnaires included items related to quality of life, self-efficacy, self-esteem, psychosis based on the Behavior and Symptom Identification Scale, health locus of control, and socio-demographic factors. We performed multiple linear regression analysis with quality of life as the dependent variable and, based on covariance structural analysis, evaluated the goodness of fit of the resulting structural equations models. Results Self-efficacy, self-esteem, and degree of psychosis significantly impacted quality of life. Marital status, age, and types of medications also influenced quality of life. Multiple linear regression analysis revealed psychiatric symptoms (Behavior and Symptom Identification Scale-32 [daily living and role functioning] (Beta = −0.537, p < 0.001) and self-efficacy (Beta = 0.249, p < 0.05) to be predictors of total quality of life score. Based on covariance structural analysis, the resulting model was found to exhibit reasonable goodness of fit. Conclusions Self-efficacy had an especially strong and direct impact on QOL. Therefore, it is important to provide more positive feedback to patients, provide social skills training based on cognitive behavioral therapy, and engage patients in role playing to improve self-efficacy and self-concept. PMID:25101143

Combining fixed effects and instrumental variable approaches for estimating the effect of psychosocial job quality on mental health: evidence from 13 waves of a nationally representative cohort study.

PubMed

Milner, Allison; Aitken, Zoe; Kavanagh, Anne; LaMontagne, Anthony D; Pega, Frank; Petrie, Dennis

2017-06-23

Previous studies suggest that poor psychosocial job quality is a risk factor for mental health problems, but they use conventional regression analytic methods that cannot rule out reverse causation, unmeasured time-invariant confounding and reporting bias. This study combines two quasi-experimental approaches to improve causal inference by better accounting for these biases: (i) linear fixed effects regression analysis and (ii) linear instrumental variable analysis. We extract 13 annual waves of national cohort data including 13 260 working-age (18-64 years) employees. The exposure variable is self-reported level of psychosocial job quality. The instruments used are two common workplace entitlements. The outcome variable is the Mental Health Inventory (MHI-5). We adjust for measured time-varying confounders. In the fixed effects regression analysis adjusted for time-varying confounders, a 1-point increase in psychosocial job quality is associated with a 1.28-point improvement in mental health on the MHI-5 scale (95% CI: 1.17, 1.40; P < 0.001). When the fixed effects was combined with the instrumental variable analysis, a 1-point increase psychosocial job quality is related to 1.62-point improvement on the MHI-5 scale (95% CI: -0.24, 3.48; P = 0.088). Our quasi-experimental results provide evidence to confirm job stressors as risk factors for mental ill health using methods that improve causal inference. © The Author 2017. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Investigation on electromechanical properties of a muscle-like linear actuator fabricated by bi-film ionic polymer metal composites

NASA Astrophysics Data System (ADS)

Sun, Zhuangzhi; Zhao, Gang; Qiao, Dongpan; Song, Wenlong

2017-12-01

Artificial muscles have attracted great attention for their potentials in intelligent robots, biomimetic devices, and micro-electromechanical system. However, there are many performance bottlenecks restricting the development of artificial muscles in engineering applications, e.g., the little blocking force and short working life. Focused on the larger requirements of the output force and the lack characteristics of the linear motion, an innovative muscle-like linear actuator based on two segmented IPMC strips was developed to imitate linear motion of artificial muscles. The structures of the segmented IPMC strip of muscle-like linear actuator were developed and the established mathematical model was to determine the appropriate segmented proportion as 1:2:1. The muscle-like linear actuator with two segmented IPMC strips assemble by two supporting link blocks was manufactured for the study of electromechanical properties. Electromechanical properties of muscle-like linear actuator under the different technological factors were obtained to experiment, and the corresponding changing rules of muscle-like linear actuators were presented to research. Results showed that factors of redistributed resistance and surface strain on both end-sides were two main reasons affecting the emergence of different electromechanical properties of muscle-like linear actuators.

Factors affecting the HIV/AIDS epidemic: an ecological analysis of global data.

PubMed

Mondal, M N I; Shitan, M

2013-06-01

All over the world the prevalence of Human Immunodeficiency Virus (HIV)/Acquired Immune Deficiency Syndrome (AIDS) has became a stumbling stone in progress of human civilization and is a huge concern for people worldwide. To determine the social and health factors which contribute to increase the size of HIV epidemic globally. The country level indicators of HIV prevalence rates, are contraceptive prevalence rate, physicians density, proportion of Muslim populations, adolescent fertility rate, and mean year of schooling were compiled of 187 countries from the United Nations (UN) agencies. To extract the major factors from those indicators of the later five categories, backward multiple regression analysis was used as the statistical tool. The national HIV prevalence rate was significantly correlated with almost all the predictors. Backward multiple linear regression analysis identified the proportion of Muslims, physicians density, and adolescent fertility rate are as the three most prominent factors linked with the national HIV epidemic. The findings support the hypotheses that a higher adolescent fertility rate in the population is the adverse effect of premarital and extramarital sex that leads to longer period of sexual activity which increases the risk of HIV infection. On the hand, and cultural restrictions of Muslims and sufficient physicians will decelerate the spread of HIV infections in the society.

Correlation between HIV-1 genotype and clinical progression in HIV/AIDS patients in Surabaya, Indonesia

NASA Astrophysics Data System (ADS)

Rachman, B. E.; Khairunisa, S. Q.; Witaningrum, A. M.; Yunifiar, M. Q.; Nasronudin

2018-03-01

Several factors such as host and viral factors can affect the progression of HIV/AIDS. This study aims to identify the correlation viral factors, especially the HIV-1 subtype with HIV/AIDS progression. Inpatient HIV/AIDS during the period March to September 2017 and willing to participate are included in the study. Historical data of disease and treatment was taken by medical record. Blood samples were amplified, sequenced and undergone phylogenetic analysis. Linear regression analysis was used to estimate beta coefficient (β) and 95%CI of HIV/AIDS progression (measured by the CD4 change rate, ΔCD4 cell count/time span in months).This study has 17 samples. The HIV-1 subtype was dominated by CRF01_AE (81.8%) followed by subtype B (18.2%). There was significant correlation between subtype HIV-1 (p = 0.04) and body mass index (p = 0.038) with HIV/AIDS clinical stage. Many factors were assumed to be correlated with increased rate of CD4, but we only subtype HIV-1 had a significant correlation (p = 0.024) with it. From multivariate analysis, we also found that subtype HIV-1 had a significant correlation (β = 0.788, 95%CI: 17.5-38.6, p = 0.004).

Spatial pattern of spring phytoplankton community in the coastal waters of northern Zhejiang, East China Sea

NASA Astrophysics Data System (ADS)

Ye, Ran; Cai, Yanhong; Wei, Yongjie; Li, Xiaoming

2017-04-01

The spatial pattern of phytoplankton community can indicate potential environmental variation in different water bodies. In this context, spatial pattern of phytoplankton community and its response to environmental and spatial factors were studied in the coastal waters of northern Zhejiang, East China Sea using multivariate statistical techniques. Results showed that 94 species belonging to 40 genera, 5 phyla were recorded (the remaining 9 were identified to genus level) with diatoms being the most dominant followed by dinoflagellates. Hierarchical clustering analysis (HCA), nonmetric multidimentional scaling (NMDS), and analysis of similarity (ANOSIM) all demomstrated that the whole study area could be divided into 3 subareas with significant differences. Indicator species analysis (ISA) further confirmed that the indicator species of each subarea correlated significantly with specific environmental factors. Distance-based linear model (Distlm) and Mantel test revealed that silicate (SiO32-), phosphate (PO43-), pH, and dissolved oxygen (DO) were the most important environmental factors influencing phytoplankton community. Variation portioning (VP) finally concluded that the shared fractions of environmental and spatial factors were higher than either the pure environmental effects or the pure spatial effects, suggesting phytoplankton biogeography were mainly affected by both the environmental variability and dispersal limitation. Additionally, other factors (eg., trace metals, biological grazing, climate change, and time-scale variation) may also be the sources of the unexplained variation which need further study.

Influence of caregiver personality on the burden of family caregivers of terminally ill cancer patients.

PubMed

Kim, Ha-Hyun; Kim, Seon-Young; Kim, Jae-Min; Kim, Sung-Wan; Shin, Il-Seon; Shim, Hyun-Jeong; Hwang, Jun-Eul; Chung, Ik-Joo; Yoon, Jin-Sang

2016-02-01

To determine the influence of caregiver personality and other factors on the burden of family caregivers of terminally ill cancer patients. We investigated a wide range of factors related to the patient-family caregiver dyad in a palliative care setting using a cross-sectional design. Caregiver burden was assessed using the seven-item short version of the Zarit Burden Interview (ZBI-7). Caregiver personality was assessed using the 10-item short version of the Big Five Inventory (BFI-10), which measures the following five personality dimensions: extroversion, agreeableness, conscientiousness, neuroticism, and openness. Patient- and caregiver-related sociodemographic and psychological factors were included in the analysis because of their potential association with caregiver burden. Clinical patient data were obtained from medical charts or by using other measures. Multivariate linear regression analysis was performed to identify the independent factors associated with caregiver burden. We analyzed 227 patient-family caregiver dyads. The multivariate analysis revealed that caregiver extroversion was protective against caregiver burden, whereas depressive symptoms in caregivers were related to increased burden. Neuroticism was positively correlated with caregiver burden, but this relationship was nonsignificant following adjustment for depressive symptoms. Patient-related factors were not significantly associated with caregiver burden. Evaluating caregiver personality traits could facilitate identification of individuals at greater risk of high burden. Furthermore, depression screening and treatment programs for caregivers in palliative care settings are required to decrease caregiver burden.

Multifactor valuation models of energy futures and options on futures

NASA Astrophysics Data System (ADS)

Bertus, Mark J.

The intent of this dissertation is to investigate continuous time pricing models for commodity derivative contracts that consider mean reversion. The motivation for pricing commodity futures and option on futures contracts leads to improved practical risk management techniques in markets where uncertainty is increasing. In the dissertation closed-form solutions to mean reverting one-factor, two-factor, three-factor Brownian motions are developed for futures contracts. These solutions are obtained through risk neutral pricing methods that yield tractable expressions for futures prices, which are linear in the state variables, hence making them attractive for estimation. These functions, however, are expressed in terms of latent variables (i.e. spot prices, convenience yield) which complicate the estimation of the futures pricing equation. To address this complication a discussion on Dynamic factor analysis is given. This procedure documents latent variables using a Kalman filter and illustrations show how this technique may be used for the analysis. In addition, to the futures contracts closed form solutions for two option models are obtained. Solutions to the one- and two-factor models are tailored solutions of the Black-Scholes pricing model. Furthermore, since these contracts are written on the futures contracts, they too are influenced by the same underlying parameters of the state variables used to price the futures contracts. To conclude, the analysis finishes with an investigation of commodity futures options that incorporate random discrete jumps.

Multi-segment trunk models used to investigate the crunch factor in golf and their relationship with selected swing and launch parameters.

PubMed

Joyce, Christopher; Chivers, Paola; Sato, Kimitake; Burnett, Angus

2016-10-01

The use of multi-segment trunk models to investigate the crunch factor in golf may be warranted. The first aim of the study was to investigate the relationship between the trunk and lower trunk for crunch factor-related variables (trunk lateral bending and trunk axial rotation velocity). The second aim was to determine the level of association between crunch factor-related variables with swing (clubhead velocity) and launch (launch angle). Thirty-five high-level amateur male golfers (Mean ± SD: age = 23.8 ± 2.1 years, registered golfing handicap = 5 ± 1.9) without low back pain had kinematic data collected from their golf swing using a 10-camera motion analysis system operating at 500 Hz. Clubhead velocity and launch angle were collected using a validated real-time launch monitor. A positive relationship was found between the trunk and lower trunk for axial rotation velocity (r(35) = .47, P < .01). Cross-correlation analysis revealed a strong coupling relationship for the crunch factor (R(2) = 0.98) between the trunk and lower trunk. Using generalised linear model analysis, it was evident that faster clubhead velocities and lower launch angles of the golf ball were related to reduced lateral bending of the lower trunk.

A meta-analysis of cambium phenology and growth: linear and non-linear patterns in conifers of the northern hemisphere.

PubMed

Rossi, Sergio; Anfodillo, Tommaso; Cufar, Katarina; Cuny, Henri E; Deslauriers, Annie; Fonti, Patrick; Frank, David; Gricar, Jozica; Gruber, Andreas; King, Gregory M; Krause, Cornelia; Morin, Hubert; Oberhuber, Walter; Prislan, Peter; Rathgeber, Cyrille B K

2013-12-01

Ongoing global warming has been implicated in shifting phenological patterns such as the timing and duration of the growing season across a wide variety of ecosystems. Linear models are routinely used to extrapolate these observed shifts in phenology into the future and to estimate changes in associated ecosystem properties such as net primary productivity. Yet, in nature, linear relationships may be special cases. Biological processes frequently follow more complex, non-linear patterns according to limiting factors that generate shifts and discontinuities, or contain thresholds beyond which responses change abruptly. This study investigates to what extent cambium phenology is associated with xylem growth and differentiation across conifer species of the northern hemisphere. Xylem cell production is compared with the periods of cambial activity and cell differentiation assessed on a weekly time scale on histological sections of cambium and wood tissue collected from the stems of nine species in Canada and Europe over 1-9 years per site from 1998 to 2011. The dynamics of xylogenesis were surprisingly homogeneous among conifer species, although dispersions from the average were obviously observed. Within the range analysed, the relationships between the phenological timings were linear, with several slopes showing values close to or not statistically different from 1. The relationships between the phenological timings and cell production were distinctly non-linear, and involved an exponential pattern. The trees adjust their phenological timings according to linear patterns. Thus, shifts of one phenological phase are associated with synchronous and comparable shifts of the successive phases. However, small increases in the duration of xylogenesis could correspond to a substantial increase in cell production. The findings suggest that the length of the growing season and the resulting amount of growth could respond differently to changes in environmental conditions.

Measuring the global information society - explaining digital inequality by economic level and education standard

NASA Astrophysics Data System (ADS)

Ünver, H.

2017-02-01

A main focus of this research paper is to investigate on the explanation of the ‘digital inequality’ or ‘digital divide’ by economic level and education standard of about 150 countries worldwide. Inequality regarding GDP per capita, literacy and the so-called UN Education Index seem to be important factors affecting ICT usage, in particular Internet penetration, mobile phone usage and also mobile Internet services. Empirical methods and (multivariate) regression analysis with linear and non-linear functions are useful methods to measure some crucial factors of a country or culture towards becoming information and knowledge based society. Overall, the study concludes that the convergence regarding ICT usage proceeds worldwide faster than the convergence in terms of economic wealth and education in general. The results based on a large data analysis show that the digital divide is declining over more than a decade between 2000 and 2013, since more people worldwide use mobile phones and the Internet. But a high digital inequality explained to a significant extent by the functional relation between technology penetration rates, education level and average income still exists. Furthermore it supports the actions of countries at UN/G20/OECD level for providing ICT access to all people for a more balanced world in context of sustainable development by postulating that policymakers need to promote comprehensive education worldwide by means of using ICT.

Variables associated with health-related quality of life in a Brazilian sample of patients from a tertiary outpatient clinic for depression and anxiety disorders.

PubMed

Schwab, Bianca; Daniel, Heloisa Silveira; Lutkemeyer, Carine; Neves, João Arthur Lange Lins; Zilli, Louise Nassif; Guarnieri, Ricardo; Diaz, Alexandre Paim; Michels, Ana Maria Maykot Prates

2015-01-01

Health-related quality of life (HRQOL) assessment tools have been broadly used in the medical context. These tools are used to measure the subjective impact of the disease on patients. The objective of this study was to evaluate the variables associated with HRQOL in a Brazilian sample of patients followed up in a tertiary outpatient clinic for depression and anxiety disorders. Cross-sectional study. Independent variables were those included in a sociodemographic questionnaire and the Hospital Anxiety and Depression Scale (HADS) scores. Dependent variables were those included in the short version of the World Health Organization Quality of Life (WHOQOL-BREF) and the scores for its subdomains (overall quality of life and general health, physical health, psychological health, social relationships, and environment). A multiple linear regression analysis was used to find the variables independently associated with each outcome. Seventy-five adult patients were evaluated. After multiple linear regression analysis, the HADS scores were associated with all outcomes, except social relationships (p = 0.08). Female gender was associated with poor total scores, as well as psychological health and environment. Unemployment was associated with poor physical health. Identifying the factors associated with HRQOL and recognizing that depression and anxiety are major factors are essential to improve the care of patients.

Computational method for analysis of polyethylene biodegradation

NASA Astrophysics Data System (ADS)

Watanabe, Masaji; Kawai, Fusako; Shibata, Masaru; Yokoyama, Shigeo; Sudate, Yasuhiro

2003-12-01

In a previous study concerning the biodegradation of polyethylene, we proposed a mathematical model based on two primary factors: the direct consumption or absorption of small molecules and the successive weight loss of large molecules due to β-oxidation. Our model is an initial value problem consisting of a differential equation whose independent variable is time. Its unknown variable represents the total weight of all the polyethylene molecules that belong to a molecular-weight class specified by a parameter. In this paper, we describe a numerical technique to introduce experimental results into analysis of our model. We first establish its mathematical foundation in order to guarantee its validity, by showing that the initial value problem associated with the differential equation has a unique solution. Our computational technique is based on a linear system of differential equations derived from the original problem. We introduce some numerical results to illustrate our technique as a practical application of the linear approximation. In particular, we show how to solve the inverse problem to determine the consumption rate and the β-oxidation rate numerically, and illustrate our numerical technique by analyzing the GPC patterns of polyethylene wax obtained before and after 5 weeks cultivation of a fungus, Aspergillus sp. AK-3. A numerical simulation based on these degradation rates confirms that the primary factors of the polyethylene biodegradation posed in modeling are indeed appropriate.

Quantifying the predictive consequences of model error with linear subspace analysis

USGS Publications Warehouse

White, Jeremy T.; Doherty, John E.; Hughes, Joseph D.

2014-01-01

All computer models are simplified and imperfect simulators of complex natural systems. The discrepancy arising from simplification induces bias in model predictions, which may be amplified by the process of model calibration. This paper presents a new method to identify and quantify the predictive consequences of calibrating a simplified computer model. The method is based on linear theory, and it scales efficiently to the large numbers of parameters and observations characteristic of groundwater and petroleum reservoir models. The method is applied to a range of predictions made with a synthetic integrated surface-water/groundwater model with thousands of parameters. Several different observation processing strategies and parameterization/regularization approaches are examined in detail, including use of the Karhunen-Loève parameter transformation. Predictive bias arising from model error is shown to be prediction specific and often invisible to the modeler. The amount of calibration-induced bias is influenced by several factors, including how expert knowledge is applied in the design of parameterization schemes, the number of parameters adjusted during calibration, how observations and model-generated counterparts are processed, and the level of fit with observations achieved through calibration. Failure to properly implement any of these factors in a prediction-specific manner may increase the potential for predictive bias in ways that are not visible to the calibration and uncertainty analysis process.

Linear ordered collagen scaffolds loaded with collagen-binding basic fibroblast growth factor facilitate recovery of sciatic nerve injury in rats.

PubMed

Ma, Fukai; Xiao, Zhifeng; Chen, Bing; Hou, Xianglin; Dai, Jianwu; Xu, Ruxiang

2014-04-01

Natural biological functional scaffolds, consisting of biological materials filled with promoting elements, provide a promising strategy for the regeneration of peripheral nerve defects. Collagen conduits have been used widely due to their excellent biological properties. Linear ordered collagen scaffold (LOCS) fibers are good lumen fillers that can guide nerve regeneration in an ordered direction. In addition, basic fibroblast growth factor (bFGF) is important in the recovery of nerve injury. However, the traditional method for delivering bFGF to the lesion site has no long-term effect because of its short half-life and rapid diffusion. Therefore, we fused a specific collagen-binding domain (CBD) peptide to the N-terminal of native basic fibroblast growth factor (NAT-bFGF) to retain bFGF on the collagen scaffolds. In this study, a natural biological functional scaffold was constructed using collagen tubes filled with collagen-binding bFGF (CBD-bFGF)-loaded LOCS to promote regeneration in a 5-mm rat sciatic nerve transection model. Functional evaluation, histological investigation, and morphometric analysis indicated that the natural biological functional scaffold retained more bFGF at the injury site, guided axon growth, and promoted nerve regeneration as well as functional restoration.

Forecast and analysis of the ratio of electric energy to terminal energy consumption for global energy internet

NASA Astrophysics Data System (ADS)

Wang, Wei; Zhong, Ming; Cheng, Ling; Jin, Lu; Shen, Si

2018-02-01

In the background of building global energy internet, it has both theoretical and realistic significance for forecasting and analysing the ratio of electric energy to terminal energy consumption. This paper firstly analysed the influencing factors of the ratio of electric energy to terminal energy and then used combination method to forecast and analyse the global proportion of electric energy. And then, construct the cointegration model for the proportion of electric energy by using influence factor such as electricity price index, GDP, economic structure, energy use efficiency and total population level. At last, this paper got prediction map of the proportion of electric energy by using the combination-forecasting model based on multiple linear regression method, trend analysis method, and variance-covariance method. This map describes the development trend of the proportion of electric energy in 2017-2050 and the proportion of electric energy in 2050 was analysed in detail using scenario analysis.

Interpreting the sub-linear Kennicutt-Schmidt relationship: the case for diffuse molecular gas

NASA Astrophysics Data System (ADS)

Shetty, Rahul; Clark, Paul C.; Klessen, Ralf S.

2014-08-01

Recent statistical analysis of two extragalactic observational surveys strongly indicate a sub-linear Kennicutt-Schmidt (KS) relationship between the star formation rate (ΣSFR) and molecular gas surface density (Σmol). Here, we consider the consequences of these results in the context of common assumptions, as well as observational support for a linear relationship between ΣSFR and the surface density of dense gas. If the CO traced gas depletion time (τ_dep^CO) is constant, and if CO only traces star-forming giant molecular clouds (GMCs), then the physical properties of each GMC must vary, such as the volume densities or star formation rates. Another possibility is that the conversion between CO luminosity and Σmol, the XCO factor, differs from cloud-to-cloud. A more straightforward explanation is that CO permeates the hierarchical interstellar medium, including the filaments and lower density regions within which GMCs are embedded. A number of independent observational results support this description, with the diffuse gas comprising at least 30 per cent of the total molecular content. The CO bright diffuse gas can explain the sub-linear KS relationship, and consequently leads to an increasing τ_dep^CO with Σmol. If ΣSFR linearly correlates with the dense gas surface density, a sub-linear KS relationship indicates that the fraction of diffuse gas fdiff grows with Σmol. In galaxies where Σmol falls towards the outer disc, this description suggests that fdiff also decreases radially.

On the null distribution of Bayes factors in linear regression

USDA-ARS?s Scientific Manuscript database

We show that under the null, the 2 log (Bayes factor) is asymptotically distributed as a weighted sum of chi-squared random variables with a shifted mean. This claim holds for Bayesian multi-linear regression with a family of conjugate priors, namely, the normal-inverse-gamma prior, the g-prior, and...

On the Relation between the Linear Factor Model and the Latent Profile Model

ERIC Educational Resources Information Center

Halpin, Peter F.; Dolan, Conor V.; Grasman, Raoul P. P. P.; De Boeck, Paul

2011-01-01

The relationship between linear factor models and latent profile models is addressed within the context of maximum likelihood estimation based on the joint distribution of the manifest variables. Although the two models are well known to imply equivalent covariance decompositions, in general they do not yield equivalent estimates of the…

Advanced analysis technique for the evaluation of linear alternators and linear motors

NASA Technical Reports Server (NTRS)

Holliday, Jeffrey C.

1995-01-01

A method for the mathematical analysis of linear alternator and linear motor devices and designs is described, and an example of its use is included. The technique seeks to surpass other methods of analysis by including more rigorous treatment of phenomena normally omitted or coarsely approximated such as eddy braking, non-linear material properties, and power losses generated within structures surrounding the device. The technique is broadly applicable to linear alternators and linear motors involving iron yoke structures and moving permanent magnets. The technique involves the application of Amperian current equivalents to the modeling of the moving permanent magnet components within a finite element formulation. The resulting steady state and transient mode field solutions can simultaneously account for the moving and static field sources within and around the device.

Analysis of the effects of geological and geomorphological factors on earthquake triggered landslides using artificial neural networks (ANN)

NASA Astrophysics Data System (ADS)

Kawabata, D.; Bandibas, J.

2007-12-01

The occurrence of landslide is the result of the interaction of complex and diverse environmental factors. The geomorphic and geologic features, rock types and vegetative cover are important base factors of landslide occurrence. However, determining the relationship between these factors and landslide occurrence is very difficult using conventional mathematical analysis. The use of an advanced computing technique for this kind of analysis is very important. Artificial neural network (ANN) has recently been included in the list of analytical tools for a wide range of applications in the natural sciences research fields. One of the advantages of using ANN for pattern recognition is that it can handle data at any measurement scale ranging from nominal, ordinal to linear and ratio, and any form of data distribution (Wang et al., 1995). In addition, it can easily handle qualitative variables making it widely used in integrated analysis of spatial data from multiple sources for predicting and classification. This study focuses on the definition of the relationship between geological factors and landslide occurrence using artificial neural networks. The study also focuses on the effect of the DTMs (e.g. ASTER DTM, ALSM, digitized from paper map and digital photogrammetric measurement data). The main aim of the study is to generate landslide susceptibility index map using the defined relationship using ANN. Landslide data in the Chuetsu region were used in this research. The 2004 earthquake triggered many landslides in the region. The initial results of the study showed that ANN is more accurate in defining the relationship between geological and geomorphological factors and landslide occurrence. It also determined the best combination of geological and geomorphological factors that is directly related to landslide occurrence.

Combining global and local approximations

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.

1991-01-01

A method based on a linear approximation to a scaling factor, designated the 'global-local approximation' (GLA) method, is presented and shown capable of extending the range of usefulness of derivative-based approximations to a more refined model. The GLA approach refines the conventional scaling factor by means of a linearly varying, rather than constant, scaling factor. The capabilities of the method are demonstrated for a simple beam example with a crude and more refined FEM model.

Phytate (myo-inositol hexaphosphate) and risk factors for osteoporosis.

PubMed

López-González, A A; Grases, F; Roca, P; Mari, B; Vicente-Herrero, M T; Costa-Bauzá, A

2008-12-01

Several risk factors seem to play a role in the development of osteoporosis. Phytate is a naturally occurring compound that is ingested in significant amounts by those with diets rich in whole grains. The aim of this study was to evaluate phytate consumption as a risk factor in osteoporosis. In a first group of 1,473 volunteer subjects, bone mineral density was determined by means of dual radiological absorptiometry in the calcaneus. In a second group of 433 subjects (used for validation of results obtained for the first group), bone mineral density was determined in the lumbar column and the neck of the femur. Subjects were individually interviewed about selected osteoporosis risk factors. Dietary information related to phytate consumption was acquired by questionnaires conducted on two different occasions, the second between 2 and 3 months after performing the first one. One-way analysis of variance or Student's t test was used to determine statistical differences between groups. Bone mineral density increased with increasing phytate consumption. Multivariate linear regression analysis indicated that body weight and low phytate consumption were the risk factors with greatest influence on bone mineral density. Phytate consumption had a protective effect against osteoporosis, suggesting that low phytate consumption should be considered an osteoporosis risk factor.

Source apportionment of PAH in Hamilton Harbour suspended sediments: comparison of two factor analysis methods.

PubMed

Sofowote, Uwayemi M; McCarry, Brian E; Marvin, Christopher H

2008-08-15

A total of 26 suspended sediment samples collected over a 5-year period in Hamilton Harbour, Ontario, Canada and surrounding creeks were analyzed for a suite of polycyclic aromatic hydrocarbons and sulfur heterocycles. Hamilton Harbour sediments contain relatively high levels of polycyclic aromatic compounds and heavy metals due to emissions from industrial and mobile sources. Two receptor modeling methods using factor analyses were compared to determine the profiles and relative contributions of pollution sources to the harbor; these methods are principal component analyses (PCA) with multiple linear regression analysis (MLR) and positive matrix factorization (PMF). Both methods identified four factors and gave excellent correlation coefficients between predicted and measured levels of 25 aromatic compounds; both methods predicted similar contributions from coal tar/coal combustion sources to the harbor (19 and 26%, respectively). One PCA factor was identified as contributions from vehicular emissions (61%); PMF was able to differentiate vehicular emissions into two factors, one attributed to gasoline emissions sources (28%) and the other to diesel emissions sources (24%). Overall, PMF afforded better source identification than PCA with MLR. This work constitutes one of the few examples of the application of PMF to the source apportionment of sediments; the addition of sulfur heterocycles to the analyte list greatly aided in the source identification process.

Antipsychotic therapeutic drug monitoring: psychiatrists’ attitudes and factors predicting likely future use

PubMed Central

Law, Suzanne; Haddad, Peter M.; Chaudhry, Imran B.; Husain, Nusrat; Drake, Richard J.; Flanagan, Robert J.; David, Anthony S.

2015-01-01

Background: This study aimed to explore predictive factors for future use of therapeutic drug monitoring (TDM) and to further examine psychiatrists’ current prescribing practices and perspectives regarding antipsychotic TDM using plasma concentrations. Method: A cross-sectional study for consultant psychiatrists using a postal questionnaire was conducted in north-west England. Data were combined with those of a previous London-based study and principal axis factor analysis was conducted to identify predictors of future use of TDM. Results: Most of the 181 participants (82.9%, 95% confidence interval 76.7–87.7%) agreed that ‘if TDM for antipsychotics were readily available, I would use it’. Factor analysis identified five factors from the original 35 items regarding TDM. Four of the factors significantly predicted likely future use of antipsychotic TDM and together explained 40% of the variance in a multivariate linear regression model. Likely future use increased with positive attitudes and expectations, and decreased with potential barriers, negative attitudes and negative expectations. Scientific perspectives of TDM and psychiatrist characteristics were not significant predictors. Conclusion: Most senior psychiatrists indicated that they would use antipsychotic TDM if available. However, psychiatrists’ attitudes and expectations and the potential barriers need to be addressed, in addition to the scientific evidence, before widespread use of antipsychotic TDM is likely in clinical practice. PMID:26301077

[Resting metabolic rate estimated by bioelectrical impedance analysis and its determinants in maintenance hemodialysis patients].

PubMed

Da, J J; Peng, H Y; Lin, X; Shen, Y; Zhao, J Q; He, S; Zha, Y

2018-03-27

Objective: To explore the level of resting energy expenditure (REE) estimated by bioelectrical impedance analysis and the association of resting metabolic rate (RMR) with clinical related factors, and provide new ideas for improving protein energy wasting (PEW) in maintenance hemodialysis (MHD) patients. Methods: Seven hundred and sixty-five subjects receiving MHD between July 2015 and September 2016 in 11 hemodialysis centers in Guizhou province were enrolled in this cross-sectional study. Bioelectrical impedance analysis was used to measure RMR and body composition, such as lean body mass, fat mass and body cell mass (BCM). Baseline characteristics, routine blood test indexes and biochemical data of hemodialysis patients were collected. The level of RMR and body composition in hemodialysis patients was compared by gender grouping. Then the patients were divided into four groups according to the cutoff value of RMR quartile. Spearman correlation analysis and multiple linear regression analysis were used to analyze the relationships between RMR and clinical related factors. Results: The average age of MHD patients was (54.96±15.78) years and the duriation of dialysis was (42.3±9.0) months. The level of RMR in male patients (474 cases, 61.96%) was significantly higher than that in female patients [1 591(1 444, 1 764) kcal/d vs 1 226 (1 104, 1 354) kcal/d, P <0.001]. However, this significant difference of RMR between different genders disappeared after adjusting for lean body mass ( P =0.193). Multiple linear regression analysis showed that RMR was positively correlated with body surface area (β=0.817) and lactate dehydrogenase (LDH) (β=0.198), and negatively correlated with age (β=-0.141), all P <0.05. Conclusion: RMR levels in patients with maintenance hemodialysis are associated with lactate dehydrogenase level, which may become a new index to evaluate energy consumption.

Use of reflectance spectrophotometry and colorimetry in a general linear model for the determination of the age of bruises.

PubMed

Hughes, Vanessa K; Langlois, Neil E I

2010-12-01

Bruises can have medicolegal significance such that the age of a bruise may be an important issue. This study sought to determine if colorimetry or reflectance spectrophotometry could be employed to objectively estimate the age of bruises. Based on a previously described method, reflectance spectrophotometric scans were obtained from bruises using a Cary 100 Bio spectrophotometer fitted with a fibre-optic reflectance probe. Measurements were taken from the bruise and a control area. Software was used to calculate the first derivative at 490 and 480 nm; the proportion of oxygenated hemoglobin was calculated using an isobestic point method and a software application converted the scan data into colorimetry data. In addition, data on factors that might be associated with the determination of the age of a bruise: subject age, subject sex, degree of trauma, bruise size, skin color, body build, and depth of bruise were recorded. From 147 subjects, 233 reflectance spectrophotometry scans were obtained for analysis. The age of the bruises ranged from 0.5 to 231.5 h. A General Linear Model analysis method was used. This revealed that colorimetric measurement of the yellowness of a bruise accounted for 13% of the bruise age. By incorporation of the other recorded data (as above), yellowness could predict up to 32% of the age of a bruise-implying that 68% of the variation was dependent on other factors. However, critical appraisal of the model revealed that the colorimetry method of determining the age of a bruise was affected by skin tone and required a measure of the proportion of oxygenated hemoglobin, which is obtained by spectrophotometric methods. Using spectrophotometry, the first derivative at 490 nm alone accounted for 18% of the bruise age estimate. When additional factors (subject sex, bruise depth and oxygenation of hemoglobin) were included in the General Linear Model this increased to 31%-implying that 69% of the variation was dependent on other factors. This indicates that spectrophotometry would be of more use that colorimetry for assessing the age of bruises, but the spectrophotometric method used needs to be refined to provide useful data regarding the estimated age of a bruise. Such refinements might include the use of multiple readings or utilizing a comprehensive mathematical model of the optics of skin.

Item Response Theory Analyses of the Cambridge Face Memory Test (CFMT)

PubMed Central

Cho, Sun-Joo; Wilmer, Jeremy; Herzmann, Grit; McGugin, Rankin; Fiset, Daniel; Van Gulick, Ana E.; Ryan, Katie; Gauthier, Isabel

2014-01-01

We evaluated the psychometric properties of the Cambridge face memory test (CFMT; Duchaine & Nakayama, 2006). First, we assessed the dimensionality of the test with a bi-factor exploratory factor analysis (EFA). This EFA analysis revealed a general factor and three specific factors clustered by targets of CFMT. However, the three specific factors appeared to be minor factors that can be ignored. Second, we fit a unidimensional item response model. This item response model showed that the CFMT items could discriminate individuals at different ability levels and covered a wide range of the ability continuum. We found the CFMT to be particularly precise for a wide range of ability levels. Third, we implemented item response theory (IRT) differential item functioning (DIF) analyses for each gender group and two age groups (Age ≤ 20 versus Age > 21). This DIF analysis suggested little evidence of consequential differential functioning on the CFMT for these groups, supporting the use of the test to compare older to younger, or male to female, individuals. Fourth, we tested for a gender difference on the latent facial recognition ability with an explanatory item response model. We found a significant but small gender difference on the latent ability for face recognition, which was higher for women than men by 0.184, at age mean 23.2, controlling for linear and quadratic age effects. Finally, we discuss the practical considerations of the use of total scores versus IRT scale scores in applications of the CFMT. PMID:25642930

Methodology for sensitivity analysis, approximate analysis, and design optimization in CFD for multidisciplinary applications

NASA Technical Reports Server (NTRS)

Taylor, Arthur C., III; Hou, Gene W.

1993-01-01

In this study involving advanced fluid flow codes, an incremental iterative formulation (also known as the delta or correction form) together with the well-known spatially-split approximate factorization algorithm, is presented for solving the very large sparse systems of linear equations which are associated with aerodynamic sensitivity analysis. For smaller 2D problems, a direct method can be applied to solve these linear equations in either the standard or the incremental form, in which case the two are equivalent. Iterative methods are needed for larger 2D and future 3D applications, however, because direct methods require much more computer memory than is currently available. Iterative methods for solving these equations in the standard form are generally unsatisfactory due to an ill-conditioning of the coefficient matrix; this problem can be overcome when these equations are cast in the incremental form. These and other benefits are discussed. The methodology is successfully implemented and tested in 2D using an upwind, cell-centered, finite volume formulation applied to the thin-layer Navier-Stokes equations. Results are presented for two sample airfoil problems: (1) subsonic low Reynolds number laminar flow; and (2) transonic high Reynolds number turbulent flow.

Statistical methods and regression analysis of stratospheric ozone and meteorological variables in Isfahan

NASA Astrophysics Data System (ADS)

Hassanzadeh, S.; Hosseinibalam, F.; Omidvari, M.

2008-04-01

Data of seven meteorological variables (relative humidity, wet temperature, dry temperature, maximum temperature, minimum temperature, ground temperature and sun radiation time) and ozone values have been used for statistical analysis. Meteorological variables and ozone values were analyzed using both multiple linear regression and principal component methods. Data for the period 1999-2004 are analyzed jointly using both methods. For all periods, temperature dependent variables were highly correlated, but were all negatively correlated with relative humidity. Multiple regression analysis was used to fit the meteorological variables using the meteorological variables as predictors. A variable selection method based on high loading of varimax rotated principal components was used to obtain subsets of the predictor variables to be included in the linear regression model of the meteorological variables. In 1999, 2001 and 2002 one of the meteorological variables was weakly influenced predominantly by the ozone concentrations. However, the model did not predict that the meteorological variables for the year 2000 were not influenced predominantly by the ozone concentrations that point to variation in sun radiation. This could be due to other factors that were not explicitly considered in this study.

Finite Elements Analysis of a Composite Semi-Span Test Article With and Without Discrete Damage

NASA Technical Reports Server (NTRS)

Lovejoy, Andrew E.; Jegley, Dawn C. (Technical Monitor)

2000-01-01

AS&M Inc. performed finite element analysis, with and without discrete damage, of a composite semi-span test article that represents the Boeing 220-passenger transport aircraft composite semi-span test article. A NASTRAN bulk data file and drawings of the test mount fixtures and semi-span components were utilized to generate the baseline finite element model. In this model, the stringer blades are represented by shell elements, and the stringer flanges are combined with the skin. Numerous modeling modifications and discrete source damage scenarios were applied to the test article model throughout the course of the study. This report details the analysis method and results obtained from the composite semi-span study. Analyses were carried out for three load cases: Braked Roll, LOG Down-Bending and 2.5G Up-Bending. These analyses included linear and nonlinear static response, as well as linear and nonlinear buckling response. Results are presented in the form of stress and strain plots. factors of safety for failed elements, buckling loads and modes, deflection prediction tables and plots, and strainage prediction tables and plots. The collected results are presented within this report for comparison to test results.

Numerical Modeling of Sliding Stability of RCC dam

NASA Astrophysics Data System (ADS)

Mughieda, O.; Hazirbaba, K.; Bani-Hani, K.; Daoud, W.

2017-06-01

Stability and stress analyses are the most important elements that require rigorous consideration in design of a dam structure. Stability of dams against sliding is crucial due to the substantial horizontal load that requires sufficient and safe resistance to develop by mobilization of adequate shearing forces along the base of the dam foundation. In the current research, the static sliding stability of a roller-compacted-concrete (RCC) dam was modelled using finite element method to investigate the stability against sliding. A commercially available finite element software (SAP 2000) was used to analyze stresses in the body of the dam and foundation. A linear finite element static analysis was performed in which a linear plane strain isoperimetric four node elements was used for modelling the dam-foundation system. The analysis was carried out assuming that no slip will occur at the interface between the dam and the foundation. Usual static loading condition was applied for the static analysis. The greatest tension was found to develop in the rock adjacent to the toe of the upstream slope. The factor of safety against sliding along the entire base of the dam was found to be greater than 1 (FS>1), for static loading conditions.

Cattaneo-Christov based study of {TiO}_2 -CuO/EG Casson hybrid nanofluid flow over a stretching surface with entropy generation

NASA Astrophysics Data System (ADS)

Jamshed, Wasim; Aziz, Asim

2018-06-01

In the present research, a simplified mathematical model is presented to study the heat transfer and entropy generation analysis of thermal system containing hybrid nanofluid. Nanofluid occupies the space over an infinite horizontal surface and the flow is induced by the non-linear stretching of surface. A uniform transverse magnetic field, Cattaneo-Christov heat flux model and thermal radiation effects are also included in the present study. The similarity technique is employed to reduce the governing non-linear partial differential equations to a set of ordinary differential equation. Keller Box numerical scheme is then used to approximate the solutions for the thermal analysis. Results are presented for conventional copper oxide-ethylene glycol (CuO-EG) and hybrid titanium-copper oxide/ethylene glycol ({TiO}_2 -CuO/EG) nanofluids. The spherical, hexahedron, tetrahedron, cylindrical, and lamina-shaped nanoparticles are considered in the present analysis. The significant findings of the study is the enhanced heat transfer capability of hybrid nanofluids over the conventional nanofluids, greatest heat transfer rate for the smallest value of the shape factor parameter and the increase in Reynolds number and Brinkman number increases the overall entropy of the system.

The influence of a prediction display on the quasi-linear describing function and remnant measured with an adaptive analog-pilot in a closed loop

NASA Technical Reports Server (NTRS)

Dey, D.

1972-01-01

The effect of a prediction display on the human transfer characteristics is explained with the aid of a quasi-linear model. The prediction display causes an increase of the gain factor and the lead factor, a diminishing of the lag factor and a decrease of the remnant. Altogether, these factors yield a smaller mean square value of the control deviation and a simultaneous decrease of the mean square value of the stick signal.

Road Traffic and Railway Noise Exposures and Adiposity in Adults: A Cross-Sectional Analysis of the Danish Diet, Cancer, and Health Cohort

PubMed Central

Christensen, Jeppe Schultz; Raaschou-Nielsen, Ole; Tjønneland, Anne; Overvad, Kim; Nordsborg, Rikke B.; Ketzel, Matthias; Sørensen, Thorkild IA; Sørensen, Mette

2015-01-01

Background Traffic noise has been associated with cardiovascular and metabolic disorders. Potential modes of action are through stress and sleep disturbance, which may lead to endocrine dysregulation and overweight. Objectives We aimed to investigate the relationship between residential traffic and railway noise and adiposity. Methods In this cross-sectional study of 57,053 middle-aged people, height, weight, waist circumference, and bioelectrical impedance were measured at enrollment (1993–1997). Body mass index (BMI), body fat mass index (BFMI), and lean body mass index (LBMI) were calculated. Residential exposure to road and railway traffic noise exposure was calculated using the Nordic prediction method. Associations between traffic noise and anthropometric measures at enrollment were analyzed using general linear models and logistic regression adjusted for demographic and lifestyle factors. Results Linear regression models adjusted for age, sex, and socioeconomic factors showed that 5-year mean road traffic noise exposure preceding enrollment was associated with a 0.35-cm wider waist circumference (95% CI: 0.21, 0.50) and a 0.18-point higher BMI (95% CI: 0.12, 0.23) per 10 dB. Small, significant increases were also found for BFMI and LBMI. All associations followed linear exposure–response relationships. Exposure to railway noise was not linearly associated with adiposity measures. However, exposure > 60 dB was associated with a 0.71-cm wider waist circumference (95% CI: 0.23, 1.19) and a 0.19-point higher BMI (95% CI: 0.0072, 0.37) compared with unexposed participants (0–20 dB). Conclusions The present study finds positive associations between residential exposure to road traffic and railway noise and adiposity. Citation Christensen JS, Raaschou-Nielsen O, Tjønneland A, Overvad K, Nordsborg RB, Ketzel M, Sørensen TI, Sørensen M. 2016. Road traffic and railway noise exposures and adiposity in adults: a cross-sectional analysis of the Danish Diet, Cancer, and Health cohort. Environ Health Perspect 124:329–335; http://dx.doi.org/10.1289/ehp.1409052 PMID:26241990

Comparative transduction mechanisms of hair cells in the bullfrog utriculus. II. Sensitivity and response dynamics to hair bundle displacement

NASA Technical Reports Server (NTRS)

Baird, R. A.

1994-01-01

1. Hair cells in whole-mount in vitro preparations of the utricular macula of the bullfrog (Rana catesbeiana) were selected according to their macular location and hair bundle morphology. The sensitivity and response dynamics of selected hair cells to natural stimulation were examined by recording their voltage responses to step and sinusoidal hair bundle displacements applied to their longest stereocilia. 2. The voltage responses of 31 hair cells to sinusoidal hair bundle displacements were characterized by their gains and phases, taken with respect to peak hair bundle displacement. The gains of Type B and Type C cells at both 0.5 and 5.0 Hz were markedly lower than those of Type F and Type E cells. Phases, with the exception of Type C cells, lagged hair bundle displacement at 0.5 Hz. Type C cells had phase leads of 25-40 degrees. At 5.0 Hz, response phases in all cells were phase lagged with respect to those at 0.5 Hz. Type C cells had larger gains and smaller phase leads at 5.0 Hz than at 0.5 Hz, suggesting the presence of low-frequency adaptation. 3. Displacement-response curves, derived from the voltage responses to 5.0-Hz sinusoids, were sigmoidal in shape and asymmetrical, with the depolarizing response having a greater magnitude and saturating less abruptly than the hyperpolarizing response. When normalized to their largest displacement the linear ranges of these curves varied from < 0.5 to 1.25 microns and were largest in Type B and smallest in Type F and Type E cells. Sensitivity, defined as the slope of the normalized displacement-response curve, was inversely correlated with linear range. 4. The contribution of geometric factors associated with the hair bundle to linear range and sensitivity were predicted from realistic models of utricular hair bundles created using morphological data obtained from light and electron microscopy. Three factors, including 1) the inverse ratio of the lengths of the kinocilium and longest stereocilia, representing the lever arm between kinociliary and stereociliary displacement; 2) tip link extension/linear displacement, largely a function of stereociliary height and separation; and 3) stereociliary number, an estimate of the number of transduction channels, were considered in this analysis. The first of these factors was quantitatively more important than the latter two factors and their total contribution was largest in Type B and Type C cells. Theoretical models were also used to calculate the relation between rotary and linear displacement.(ABSTRACT TRUNCATED AT 400 WORDS).

Evaluation of electrical impedance ratio measurements in accuracy of electronic apex locators.

PubMed

Kim, Pil-Jong; Kim, Hong-Gee; Cho, Byeong-Hoon

2015-05-01

The aim of this paper was evaluating the ratios of electrical impedance measurements reported in previous studies through a correlation analysis in order to explicit it as the contributing factor to the accuracy of electronic apex locator (EAL). The literature regarding electrical property measurements of EALs was screened using Medline and Embase. All data acquired were plotted to identify correlations between impedance and log-scaled frequency. The accuracy of the impedance ratio method used to detect the apical constriction (APC) in most EALs was evaluated using linear ramp function fitting. Changes of impedance ratios for various frequencies were evaluated for a variety of file positions. Among the ten papers selected in the search process, the first-order equations between log-scaled frequency and impedance were in the negative direction. When the model for the ratios was assumed to be a linear ramp function, the ratio values decreased if the file went deeper and the average ratio values of the left and right horizontal zones were significantly different in 8 out of 9 studies. The APC was located within the interval of linear relation between the left and right horizontal zones of the linear ramp model. Using the ratio method, the APC was located within a linear interval. Therefore, using the impedance ratio between electrical impedance measurements at different frequencies was a robust method for detection of the APC.

[Influence of meteorological factors on the activity of the adult taiga tick (Ixodes persulcatus Sch., Ixodinae) in St. Petersburg and its environs].

PubMed

Osipova, T N; Grigoryeva, L A; Samoylova, E P; Shapar, A O; Bychkova, E M

2017-01-01

The article deals with influence of meteorolical factors on the activity of the taiga tick Ixodes persulvatus Sch. in St. Petersburg and its environs. The results of correlation analysis of meteorological data (21 index) and data ticks collected in 1980-2012 allowed determining linear dependence between 11 meteorological indices an average amount of ticks. Factor analysis reduced dimentionality down to 3 indices: sum of temperatures higher than +5.0 °C, sum of precipitation higher than 5 mm per year, and Selyaninov hydrothermal coefficient. It was demonstrated that, at the background of the general tendency for the decrease of the average number of active ticks in the studied territories, correlation between the amount of ticks and meteorological indices can significantly vary as in the correlation density, so in the character and in dependence of microclimatic features of the collecting site. When variability of the mean abundance of ticks during years of investigation is low, the methods of collecting can significantly affect the results of the statistical analysis. This fact must be taken in consideration during prognosis of both dates of the beginning of epidemiological season and its intensity.

Factors associated with the patient safety climate at a teaching hospital1

PubMed Central

Luiz, Raíssa Bianca; Simões, Ana Lúcia de Assis; Barichello, Elizabeth; Barbosa, Maria Helena

2015-01-01

Objectives: to investigate the association between the scores of the patient safety climate and socio-demographic and professional variables. Methods: an observational, sectional and quantitative study, conducted at a large public teaching hospital. The Safety Attitudes Questionnaire was used, translated and validated for Brazil. Data analysis used the software Statistical Package for Social Sciences. In the bivariate analysis, we used Student's t-test, analysis of variance and Spearman's correlation of (α=0.05). To identify predictors for the safety climate scores, multiple linear regression was used, having the safety climate domain as the main outcome (α=0.01). Results: most participants were women, nursing staff, who worked in direct care to adult patients in critical areas, without a graduate degree and without any other employment. The average and median total score of the instrument corresponded to 61.8 (SD=13.7) and 63.3, respectively. The variable professional performance was found as a factor associated with the safety environment for the domain perception of service management and hospital management (p=0.01). Conclusion: the identification of factors associated with the safety environment permits the construction of strategies for safe practices in the hospitals. PMID:26487138

Analysis of the factors creating consumer attributes of roasted beef steaks.

PubMed

Guzek, Dominika; Głąbska, Dominika; Gutkowska, Krystyna; Wierzbicki, Jerzy; Woźniak, Alicja; Wierzbicka, Agnieszka

2015-03-01

The aim of the study was to analyze the factors creating consumer attributes of roasted beef steaks of various animals. Eight cuts from 30 carcasses (characterized by various types of animal, conformation and fat class, rib fat thickness, ossification score) were selected. Samples were prepared using the roasting method and consumers rated the tenderness, juiciness, flavor, overall acceptability (rated in a 100-point scale), and satisfaction (rated from 2 to 5) for analyzed samples. No influence of type of animal, fat class, conformation class or ossification score on the results of consumer analysis was observed. For all analyzed factors, the influence of cut on consumer analysis was observed (the highest values of all consumer attributes were observed for tenderloin - for juiciness significantly higher than for other cuts, for tenderness, flavor and MQ4 comparable only with rump (RMP231), while for overall acceptability and satisfaction - with both rump cuts). For rib fat thickness consumer attributes of roasted beef meat were not linear, but the influence was observed - the highest values of consumer attributes were observed for 13 mm rib fat thickness. © 2014 Japanese Society of Animal Science.

Comparative factor analysis models for an empirical study of EEG data, II: A data-guided resolution of the rotation indeterminacy.

PubMed

Rogers, L J; Douglas, R R

1984-02-01

In this paper (the second in a series), we consider a (generic) pair of datasets, which have been analyzed by the techniques of the previous paper. Thus, their "stable subspaces" have been established by comparative factor analysis. The pair of datasets must satisfy two confirmable conditions. The first is the "Inclusion Condition," which requires that the stable subspace of one of the datasets is nearly identical to a subspace of the other dataset's stable subspace. On the basis of that, we have assumed the pair to have similar generating signals, with stochastically independent generators. The second verifiable condition is that the (presumed same) generating signals have distinct ratios of variances for the two datasets. Under these conditions a small elaboration of some elementary linear algebra reduces the rotation problem to several eigenvalue-eigenvector problems. Finally, we emphasize that an analysis of each dataset by the method of Douglas and Rogers (1983) is an essential prerequisite for the useful application of the techniques in this paper. Nonempirical methods of estimating the number of factors simply will not suffice, as confirmed by simulations reported in the previous paper.

[Comparison of application of Cochran-Armitage trend test and linear regression analysis for rate trend analysis in epidemiology study].

PubMed

Wang, D Z; Wang, C; Shen, C F; Zhang, Y; Zhang, H; Song, G D; Xue, X D; Xu, Z L; Zhang, S; Jiang, G H

2017-05-10

We described the time trend of acute myocardial infarction (AMI) from 1999 to 2013 in Tianjin incidence rate with Cochran-Armitage trend (CAT) test and linear regression analysis, and the results were compared. Based on actual population, CAT test had much stronger statistical power than linear regression analysis for both overall incidence trend and age specific incidence trend (Cochran-Armitage trend P value

Understanding the external pressure and behavior of commercial banks' environmental risk management: an empirical study undertaken in the Yangtze River delta of China.

PubMed

Liu, Yong; Lin, Zhongguo

2014-04-01

The present study employed a quantitative survey to ascertain whether the external pressure of environmental risk management (ERM) on commercial banks was a contributing factor to their ERM behavior. Data was obtained using questionnaires from 204 branches of commercial banks located in the Yangtze River Delta of China. The relationship between external pressure and behavior was tested using a linear structural relations model through path analysis. The results revealed that external pressure of ERM was significantly and positively related to the behavior and that pressure from governmental regulations was the most important contributing factor in the passive feedback behavior and preventive behavior of commercial banks. The pressure from markets was the most important contributing factor in banks' active participation behavior; the pressure from community and NGOs was the most important contributing factor in their enthusiastic behavior.

Analysis of high-frequency oscillations in mutually-coupled nano-lasers.

PubMed

Han, Hong; Shore, K Alan

2018-04-16

The dynamics of mutually coupled nano-lasers has been analyzed using rate equations which include the Purcell cavity-enhanced spontaneous emission factor F and the spontaneous emission coupling factor β. It is shown that in the mutually-coupled system, small-amplitude oscillations with frequencies of order 100 GHz are generated and are maintained with remarkable stability. The appearance of such high-frequency oscillations is associated with the effective reduction of the carrier lifetime for larger values of the Purcell factor, F, and spontaneous coupling factor, β. In mutually-coupled nano-lasers the oscillation frequency changes linearly with the frequency detuning between the lasers. For non-identical bias currents, the oscillation frequency of mutually-coupled nano-lasers also increases with bias current. The stability of the oscillations which appear in mutually coupled nano-lasers offers opportunities for their practical applications and notably in photonic integrated circuits.

ASTROP2-LE: A Mistuned Aeroelastic Analysis System Based on a Two Dimensional Linearized Euler Solver

NASA Technical Reports Server (NTRS)

Reddy, T. S. R.; Srivastava, R.; Mehmed, Oral

2002-01-01

An aeroelastic analysis system for flutter and forced response analysis of turbomachines based on a two-dimensional linearized unsteady Euler solver has been developed. The ASTROP2 code, an aeroelastic stability analysis program for turbomachinery, was used as a basis for this development. The ASTROP2 code uses strip theory to couple a two dimensional aerodynamic model with a three dimensional structural model. The code was modified to include forced response capability. The formulation was also modified to include aeroelastic analysis with mistuning. A linearized unsteady Euler solver, LINFLX2D is added to model the unsteady aerodynamics in ASTROP2. By calculating the unsteady aerodynamic loads using LINFLX2D, it is possible to include the effects of transonic flow on flutter and forced response in the analysis. The stability is inferred from an eigenvalue analysis. The revised code, ASTROP2-LE for ASTROP2 code using Linearized Euler aerodynamics, is validated by comparing the predictions with those obtained using linear unsteady aerodynamic solutions.

Morphological instability of a thermophoretically growing deposit

NASA Technical Reports Server (NTRS)

Castillo, Jose L.; Garcia-Ybarra, Pedro L.; Rosner, Daniel E.

1992-01-01

The stability of the planar interface of a structureless solid growing from a depositing component dilute in a carrier fluid is studied when the main solute transport mechanism is thermal (Soret) diffusion. A linear stability analysis, carried out in the limit of low growth Peclet number, leads to a dispersion relation which shows that the planar front is unstable either when the thermal diffusion factor of the condensing component is positive and the latent heat release is small or when the thermal diffusion factor is negative and the solid grows over a thermally-insulating substrate. Furthermore, the influence of interfacial energy effects and constitutional supersaturation in the vicinity of the moving interface is analyzed in the limit of very small Schmidt numbers (small solute Fickian diffusion). The analysis is relevant to physical vapor deposition of very massive species on cold surfaces, as in recent experiments of organic solid film growth under microgravity conditions.

Non-fluent speech following stroke is caused by impaired efference copy.

PubMed

Feenaughty, Lynda; Basilakos, Alexandra; Bonilha, Leonardo; den Ouden, Dirk-Bart; Rorden, Chris; Stark, Brielle; Fridriksson, Julius

2017-09-01

Efference copy is a cognitive mechanism argued to be critical for initiating and monitoring speech: however, the extent to which breakdown of efference copy mechanisms impact speech production is unclear. This study examined the best mechanistic predictors of non-fluent speech among 88 stroke survivors. Objective speech fluency measures were subjected to a principal component analysis (PCA). The primary PCA factor was then entered into a multiple stepwise linear regression analysis as the dependent variable, with a set of independent mechanistic variables. Participants' ability to mimic audio-visual speech ("speech entrainment response") was the best independent predictor of non-fluent speech. We suggest that this "speech entrainment" factor reflects integrity of internal monitoring (i.e., efference copy) of speech production, which affects speech initiation and maintenance. Results support models of normal speech production and suggest that therapy focused on speech initiation and maintenance may improve speech fluency for individuals with chronic non-fluent aphasia post stroke.

Road Traffic and Railway Noise Exposures and Adiposity in Adults: A Cross-Sectional Analysis of the Danish Diet, Cancer, and Health Cohort.

PubMed

Christensen, Jeppe Schultz; Raaschou-Nielsen, Ole; Tjønneland, Anne; Overvad, Kim; Nordsborg, Rikke B; Ketzel, Matthias; Sørensen, Thorkild Ia; Sørensen, Mette

2016-03-01

Traffic noise has been associated with cardiovascular and metabolic disorders. Potential modes of action are through stress and sleep disturbance, which may lead to endocrine dysregulation and overweight. We aimed to investigate the relationship between residential traffic and railway noise and adiposity. In this cross-sectional study of 57,053 middle-aged people, height, weight, waist circumference, and bioelectrical impedance were measured at enrollment (1993-1997). Body mass index (BMI), body fat mass index (BFMI), and lean body mass index (LBMI) were calculated. Residential exposure to road and railway traffic noise exposure was calculated using the Nordic prediction method. Associations between traffic noise and anthropometric measures at enrollment were analyzed using general linear models and logistic regression adjusted for demographic and lifestyle factors. Linear regression models adjusted for age, sex, and socioeconomic factors showed that 5-year mean road traffic noise exposure preceding enrollment was associated with a 0.35-cm wider waist circumference (95% CI: 0.21, 0.50) and a 0.18-point higher BMI (95% CI: 0.12, 0.23) per 10 dB. Small, significant increases were also found for BFMI and LBMI. All associations followed linear exposure-response relationships. Exposure to railway noise was not linearly associated with adiposity measures. However, exposure > 60 dB was associated with a 0.71-cm wider waist circumference (95% CI: 0.23, 1.19) and a 0.19-point higher BMI (95% CI: 0.0072, 0.37) compared with unexposed participants (0-20 dB). The present study finds positive associations between residential exposure to road traffic and railway noise and adiposity.

Analytic methods for questions pertaining to a randomized pretest, posttest, follow-up design.

PubMed

Rausch, Joseph R; Maxwell, Scott E; Kelley, Ken

2003-09-01

Delineates 5 questions regarding group differences that are likely to be of interest to researchers within the framework of a randomized pretest, posttest, follow-up (PPF) design. These 5 questions are examined from a methodological perspective by comparing and discussing analysis of variance (ANOVA) and analysis of covariance (ANCOVA) methods and briefly discussing hierarchical linear modeling (HLM) for these questions. This article demonstrates that the pretest should be utilized as a covariate in the model rather than as a level of the time factor or as part of the dependent variable within the analysis of group differences. It is also demonstrated that how the posttest and the follow-up are utilized in the analysis of group differences is determined by the specific question asked by the researcher.

Three-dimensional analysis of chevron-notched specimens by boundary integral method

NASA Technical Reports Server (NTRS)

Mendelson, A.; Ghosn, L.

1983-01-01

The chevron-notched short bar and short rod specimens was analyzed by the boundary integral equations method. This method makes use of boundary surface elements in obtaining the solution. The boundary integral models were composed of linear triangular and rectangular surface segments. Results were obtained for two specimens with width to thickness ratios of 1.45 and 2.00 and for different crack length to width ratios ranging from 0.4 to 0.7. Crack opening displacement and stress intensity factors determined from displacement calculations along the crack front and compliance calculations were compared with experimental values and with finite element analysis.

Analysis of shear test method for composite laminates

NASA Technical Reports Server (NTRS)

Bergner, H. W., Jr.; Davis, J. G., Jr.; Herakovich, C. T.

1977-01-01

An elastic plane stress finite element analysis of the stress distributions in four flat test specimens for in-plane shear response of composite materials subjected to mechanical or thermal loads is presented. The shear test specimens investigated include: slotted coupon, cross beam, losipescu, and rail shear. Results are presented in the form of normalized shear contour plots for all three in-plane stess components. It is shown that the cross beam, losipescu, and rail shear specimens have stress distributions which are more than adequate for determining linear shear behavior of composite materials. Laminate properties, core effects, and fixture configurations are among the factors which were found to influence the stress distributions.

Using Linear Algebra to Introduce Computer Algebra, Numerical Analysis, Data Structures and Algorithms (and To Teach Linear Algebra, Too).

ERIC Educational Resources Information Center

Gonzalez-Vega, Laureano

1999-01-01

Using a Computer Algebra System (CAS) to help with the teaching of an elementary course in linear algebra can be one way to introduce computer algebra, numerical analysis, data structures, and algorithms. Highlights the advantages and disadvantages of this approach to the teaching of linear algebra. (Author/MM)

Calculation and application of energy transaction allocation factors in electric power transmission systems

NASA Astrophysics Data System (ADS)

Fradi, Aniss

The ability to allocate the active power (MW) loading on transmission lines and transformers, is the basis of the "flow based" transmission allocation system developed by the North American Electric Reliability Council. In such a system, the active power flows must be allocated to each line or transformer in proportion to the active power being transmitted by each transaction imposed on the system. Currently, this is accomplished through the use of the linear Power Transfer Distribution Factors (PTDFs). Unfortunately, no linear allocation models exist for other energy transmission quantities, such as MW and MVAR losses, MVAR and MVA flows, etc. Early allocation schemes were developed to allocate MW losses due to transactions to branches in a transmission system, however they exhibited diminished accuracy, since most of them are based on linear power flow modeling of the transmission system. This thesis presents a new methodology to calculate Energy Transaction Allocation factors (ETA factors, or eta factors), using the well-known process of integration of a first derivative function, as well as consistent and well-established mathematical and AC power flow models. The factors give a highly accurate allocation of any non-linear system quantity to transactions placed on the transmission system. The thesis also extends the new ETA factors calculation procedure to restructure a new economic dispatch scheme where multiple sets of generators are economically dispatched to meet their corresponding load and their share of the losses.

[Association of occupational chronic psychological stress with heat shock protein 70 in serum and tumor necrosis factor-alpha expression levels].

PubMed

Qiu, F Y; Tian, R L; Qiang, Y; He, K P; Liu, H R; Zhang, W; Song, H

2016-05-01

To investigate the relationship between occupational chronic psychological stress with heat shock protein 70 (HSP70) and tumor necrosis factor-alpha (TNF-α). Using case-control study design, we selected 622 cases in 20 to 60 years old and unrelated patients with metabolic syndrome as the case group between October 2011 and October 2012 at two hospitals of Ningxia hui autonomous region. At the same time, we selected 600 healthy people from health check-up crowd in the above two hospitals as control group. The the research objects were sex, age, nation, height, weight, smoking, drinking, exercise, and so on. After informed consent, all the research objects were collected fasting venous blood samples 10 ml in order to proceed laboratory testing of biochemical indicators. The expression of HSP70 and TNF-α in serum was determined by ELISA. Using the revised occupational stress inventory (OSI) to survey the occupational chronic psychological stress factors and stress level of research object. The correlation of occupational chronic psychological stress scores with HSP70 and TNF-α was investigated by partial correlation analysis. We built a multivariate linear regression equation With HSP70 and TNF alpha as the independent variable and occupational chronic psychological stress scores as the dependent variable, using equation of the determination coefficient R(2) to judge the degree of fitting equation. The total points of chronic stress factors in all respondents was (136.65±16.19). Among them, the mild stress level group was 313, moderate was 588, severe was 321, chronic heart stress factors scores were (119.96±13.30), (135.33±3.23), (155.33±13.55) points, respectively. In the case group subjects, the expression of HSP70 in mild, moderate and severe occupational chronic psychological stress levels were (29.88±30.08), (36.38±30.08), (27.16±23.77) ng/ml (F=6.85, P=0.001). The control group were (27.64±9.89), (39.78±29.77), (3.94±3.09) ng/ml (F=125.71, P<0.001). Multiple linear regression analysis showed the expression of psychological stress and HSP70 was a negative linear relationship, while positive linear relationship with TNF-α, the fitting of the regression equation was y=-0.07x1+ 0.011x2+ 136.88. Partial correlation analysis results showed that the occupational chronic psychological stress scores and negatively correlated with HSP70 (r=-0.11, P<0.001) and was positively related with TNF-α (r=0.11, P<0.001). In all survey respondents, the expression of HSP70 in mild, moderate and severe occupational chronic psychological stress levels group were (28.49±20.10), (37.99±29.96), (17.98±21.77) ng/ml (F=64.08, P<0.001). The expression of TNF-α were (133.61±129.51), (171.23±133.69), (169.31±196.09) pg/ml (F=6.93, P=0.001). The expression levels of HSP70 and TNF-α in serum were affected by occupational chronic psychological stress. While the level of occupational chronic psychological stress increased, the expression level of HSP70 in serum reduced, the expression level of TNF-α raised.

Examining Factors Affecting Science Achievement of Hong Kong in PISA 2006 Using Hierarchical Linear Modeling

ERIC Educational Resources Information Center

Lam, Terence Yuk Ping; Lau, Kwok Chi

2014-01-01

This study uses hierarchical linear modeling to examine the influence of a range of factors on the science performances of Hong Kong students in PISA 2006. Hong Kong has been consistently ranked highly in international science assessments, such as Programme for International Student Assessment and Trends in International Mathematics and Science…

Amesos2 and Belos: Direct and Iterative Solvers for Large Sparse Linear Systems

DOE PAGES

Bavier, Eric; Hoemmen, Mark; Rajamanickam, Sivasankaran; ...

2012-01-01

Solvers for large sparse linear systems come in two categories: direct and iterative. Amesos2, a package in the Trilinos software project, provides direct methods, and Belos, another Trilinos package, provides iterative methods. Amesos2 offers a common interface to many different sparse matrix factorization codes, and can handle any implementation of sparse matrices and vectors, via an easy-to-extend C++ traits interface. It can also factor matrices whose entries have arbitrary “Scalar” type, enabling extended-precision and mixed-precision algorithms. Belos includes many different iterative methods for solving large sparse linear systems and least-squares problems. Unlike competing iterative solver libraries, Belos completely decouples themore » algorithms from the implementations of the underlying linear algebra objects. This lets Belos exploit the latest hardware without changes to the code. Belos favors algorithms that solve higher-level problems, such as multiple simultaneous linear systems and sequences of related linear systems, faster than standard algorithms. The package also supports extended-precision and mixed-precision algorithms. Together, Amesos2 and Belos form a complete suite of sparse linear solvers.« less

On the Use of Equivalent Linearization for High-Cycle Fatigue Analysis of Geometrically Nonlinear Structures

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.

2003-01-01

The use of stress predictions from equivalent linearization analyses in the computation of high-cycle fatigue life is examined. Stresses so obtained differ in behavior from the fully nonlinear analysis in both spectral shape and amplitude. Consequently, fatigue life predictions made using this data will be affected. Comparisons of fatigue life predictions based upon the stress response obtained from equivalent linear and numerical simulation analyses are made to determine the range over which the equivalent linear analysis is applicable.

Factors Associated With Work Ability in Patients Undergoing Surgery for Cervical Radiculopathy.

PubMed

Ng, Eunice; Johnston, Venerina; Wibault, Johanna; Löfgren, Håkan; Dedering, Åsa; Öberg, Birgitta; Zsigmond, Peter; Peolsson, Anneli

2015-08-15

Cross-sectional study. To investigate the factors associated with work ability in patients undergoing surgery for cervical radiculopathy. Surgery is a common treatment of cervical radiculopathy in people of working age. However, few studies have investigated the impact on the work ability of these patients. Patients undergoing surgery for cervical radiculopathy (n = 201) were recruited from spine centers in Sweden to complete a battery of questionnaires and physical measures the day before surgery. The associations between various individual, psychological, and work-related factors and self-reported work ability were investigated by Spearman rank correlation coefficient, multivariate linear regression, and forward stepwise regression analyses. Factors that were significant (P < 0.05) in each statistical analysis were entered into the successive analysis to reveal the factors most related to work ability. Work ability was assessed using the Work Ability Index. The mean Work Ability Index score was 28 (SD, 9.0). The forward stepwise regression analysis revealed 6 factors significantly associated with work ability, which explained 62% of the variance in the Work Ability Index. Factors highly correlated with greater work ability included greater self-efficacy in performing self-cares, lower physical load on the neck at work, greater self-reported chance of being able to work in 6 months' time, greater use of active coping strategies, lower frequency of hand weakness, and higher health-related quality of life. Psychological, work-related and individual factors were significantly associated with work ability in patients undergoing surgery for cervical radiculopathy. High self-efficacy was most associated with greater work ability. Consideration of these factors by surgeons preoperatively may provide optimal return to work outcomes after surgery. 3.

Genome-wide association study of clinical dimensions of schizophrenia: polygenic effect on disorganized symptoms.

PubMed

Fanous, Ayman H; Zhou, Baiyu; Aggen, Steven H; Bergen, Sarah E; Amdur, Richard L; Duan, Jubao; Sanders, Alan R; Shi, Jianxin; Mowry, Bryan J; Olincy, Ann; Amin, Farooq; Cloninger, C Robert; Silverman, Jeremy M; Buccola, Nancy G; Byerley, William F; Black, Donald W; Freedman, Robert; Dudbridge, Frank; Holmans, Peter A; Ripke, Stephan; Gejman, Pablo V; Kendler, Kenneth S; Levinson, Douglas F

2012-12-01

Multiple sources of evidence suggest that genetic factors influence variation in clinical features of schizophrenia. The authors present the first genome-wide association study (GWAS) of dimensional symptom scores among individuals with schizophrenia. Based on the Lifetime Dimensions of Psychosis Scale ratings of 2,454 case subjects of European ancestry from the Molecular Genetics of Schizophrenia (MGS) sample, three symptom factors (positive, negative/disorganized, and mood) were identified with exploratory factor analysis. Quantitative scores for each factor from a confirmatory factor analysis were analyzed for association with 696,491 single-nucleotide polymorphisms (SNPs) using linear regression, with correction for age, sex, clinical site, and ancestry. Polygenic score analysis was carried out to determine whether case and comparison subjects in 16 Psychiatric GWAS Consortium (PGC) schizophrenia samples (excluding MGS samples) differed in scores computed by weighting their genotypes by MGS association test results for each symptom factor. No genome-wide significant associations were observed between SNPs and factor scores. Most of the SNPs producing the strongest evidence for association were in or near genes involved in neurodevelopment, neuroprotection, or neurotransmission, including genes playing a role in Mendelian CNS diseases, but no statistically significant effect was observed for any defined gene pathway. Finally, polygenic scores based on MGS GWAS results for the negative/disorganized factor were significantly different between case and comparison subjects in the PGC data set; for MGS subjects, negative/disorganized factor scores were correlated with polygenic scores generated using case-control GWAS results from the other PGC samples. The polygenic signal that has been observed in cross-sample analyses of schizophrenia GWAS data sets could be in part related to genetic effects on negative and disorganized symptoms (i.e., core features of chronic schizophrenia).

Vestibular coriolis effect differences modeled with three-dimensional linear-angular interactions.

PubMed

Holly, Jan E

2004-01-01

The vestibular coriolis (or "cross-coupling") effect is traditionally explained by cross-coupled angular vectors, which, however, do not explain the differences in perceptual disturbance under different acceleration conditions. For example, during head roll tilt in a rotating chair, the magnitude of perceptual disturbance is affected by a number of factors, including acceleration or deceleration of the chair rotation or a zero-g environment. Therefore, it has been suggested that linear-angular interactions play a role. The present research investigated whether these perceptual differences and others involving linear coriolis accelerations could be explained under one common framework: the laws of motion in three dimensions, which include all linear-angular interactions among all six components of motion (three angular and three linear). The results show that the three-dimensional laws of motion predict the differences in perceptual disturbance. No special properties of the vestibular system or nervous system are required. In addition, simulations were performed with angular, linear, and tilt time constants inserted into the model, giving the same predictions. Three-dimensional graphics were used to highlight the manner in which linear-angular interaction causes perceptual disturbance, and a crucial component is the Stretch Factor, which measures the "unexpected" linear component.

A Risk Factor Analysis of West Nile Virus: Extraction of Relationships from a Neural-Network Model

NASA Astrophysics Data System (ADS)

Ghosh, Debarchana; Guha, Rajarshi

The West Nile Virus (WNV) is an infectious disease spreading rapidly throughout the United States, causing illness among thousands of birds, animals, and humans. The broad categories of risk factors underlying WNV incidences are: environmental, socioeconomic, built-environment, and existing mosquito abatement policies. Computational neural network (CNN) model was developed to understand the occurrence of WNV infected dead birds because of their ability to capture complex relationships with higher accuracy than linear models. In this paper, we describe a method to interpret a CNN model by considering the final optimized weights. The research was conducted in the Metropolitan area of Minnesota, which had experienced significant outbreaks from 2002 till present.

Integrated Composite Analyzer (ICAN): Users and programmers manual

NASA Technical Reports Server (NTRS)

Murthy, P. L. N.; Chamis, C. C.

1986-01-01

The use of and relevant equations programmed in a computer code designed to carry out a comprehensive linear analysis of multilayered fiber composites is described. The analysis contains the essential features required to effectively design structural components made from fiber composites. The inputs to the code are constituent material properties, factors reflecting the fabrication process, and composite geometry. The code performs micromechanics, macromechanics, and laminate analysis, including the hygrothermal response of fiber composites. The code outputs are the various ply and composite properties, composite structural response, and composite stress analysis results with details on failure. The code is in Fortran IV and can be used efficiently as a package in complex structural analysis programs. The input-output format is described extensively through the use of a sample problem. The program listing is also included. The code manual consists of two parts.

Factors Associated with Recurrent Suicidal Ideation among Racially and Ethnically Diverse College Students with a History of Suicide Attempt: The Role of Mindfulness.

PubMed

Chesin, Megan S; Jeglic, Elizabeth L

2016-01-01

Although one-third of enrolled U.S. undergraduate college students are non-White, little is known about risk factors for suicidal behavior among racial and ethnic minority students. Thus, we set out to determine psychosocial factors associated with recurrent suicidal ideation among racially and ethnically diverse college students with a history of suicide attempt. From 2012-2013, 1,734 racially and ethnically diverse college students completed an on-line survey of suicidal behavior and associated factors. Depression, hopelessness, rejection sensitivity, and mindfulness, as well as past-year discrimination, ethnic identification, and acculturative stress were measured using well-validated self-report instruments. The Beck Scale for Suicide Ideation was used to assess current suicidal ideation. A subsample of 118 college students who self-reported a past suicide attempt were selected for the current analysis. Logistic regression analysis was used to test associations between risk factors and the presence of suicidal ideation, and linear regression analysis was used to test factors associated with suicidal ideation severity among those who reported current suicidal ideation. Depression was significantly related to both the presence and severity of current suicidal ideation. Mindfulness, and in particular awareness of present moment experience, was also inversely associated with ideation severity. We found depression and mindlessness were associated with suicidal ideation severity among a sample of diverse college students at high risk for suicidal behavior due to a past suicide attempt. Factors unique to the minority experience, such as acculturative stress, were not associated with current suicidal ideation. Implications for suicide prevention are discussed.

Study of free-piston Stirling engine driven linear alternators

NASA Technical Reports Server (NTRS)

Nasar, S. A.; Chen, C.

1987-01-01

The analysis, design and operation of single phase, single slot tubular permanent magnet linear alternator is presented. Included is the no-load and on-load magnetic field investigation, permanent magnet's leakage field analysis, parameter identification, design guidelines and an optimal design of a permanent magnet linear alternator. For analysis of the magnetic field, a simplified magnetic circuit is utilized. The analysis accounts for saturation, leakage and armature reaction.

SPAR reference manual. [for stress analysis

NASA Technical Reports Server (NTRS)

Whetstone, W. D.

1974-01-01

SPAR is a system of related programs which may be operated either in batch or demand (teletype) mode. Information exchange between programs is automatically accomplished through one or more direct access libraries, known collectively as the data complex. Card input is command-oriented, in free-field form. Capabilities available in the first production release of the system are fully documented, and include linear stress analysis, linear bifurcation buckling analysis, and linear vibrational analysis.

Comparative Study on Code-based Linear Evaluation of an Existing RC Building Damaged during 1998 Adana-Ceyhan Earthquake

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

Toprak, A. Emre; Guelay, F. Guelten; Ruge, Peter

2008-07-08

Determination of seismic performance of existing buildings has become one of the key concepts in structural analysis topics after recent earthquakes (i.e. Izmit and Duzce Earthquakes in 1999, Kobe Earthquake in 1995 and Northridge Earthquake in 1994). Considering the need for precise assessment tools to determine seismic performance level, most of earthquake hazardous countries try to include performance based assessment in their seismic codes. Recently, Turkish Earthquake Code 2007 (TEC'07), which was put into effect in March 2007, also introduced linear and non-linear assessment procedures to be applied prior to building retrofitting. In this paper, a comparative study is performedmore » on the code-based seismic assessment of RC buildings with linear static methods of analysis, selecting an existing RC building. The basic principles dealing the procedure of seismic performance evaluations for existing RC buildings according to Eurocode 8 and TEC'07 will be outlined and compared. Then the procedure is applied to a real case study building is selected which is exposed to 1998 Adana-Ceyhan Earthquake in Turkey, the seismic action of Ms = 6.3 with a maximum ground acceleration of 0.28 g It is a six-storey RC residential building with a total of 14.65 m height, composed of orthogonal frames, symmetrical in y direction and it does not have any significant structural irregularities. The rectangular shaped planar dimensions are 16.40 mx7.80 m = 127.90 m{sup 2} with five spans in x and two spans in y directions. It was reported that the building had been moderately damaged during the 1998 earthquake and retrofitting process was suggested by the authorities with adding shear-walls to the system. The computations show that the performing methods of analysis with linear approaches using either Eurocode 8 or TEC'07 independently produce similar performance levels of collapse for the critical storey of the structure. The computed base shear value according to Eurocode is much higher than the requirements of the Turkish Earthquake Code while the selected ground conditions represent the same characteristics. The main reason is that the ordinate of the horizontal elastic response spectrum for Eurocode 8 is increased by the soil factor. In TEC'07 force-based linear assessment, the seismic demands at cross-sections are to be checked with residual moment capacities; however, the chord rotations of primary ductile elements must be checked for Eurocode safety verifications. On the other hand, the demand curvatures from linear methods of analysis of Eurocode 8 together with TEC'07 are almost similar.« less

Factorizing the factorization - a spectral-element solver for elliptic equations with linear operation count

NASA Astrophysics Data System (ADS)

Huismann, Immo; Stiller, Jörg; Fröhlich, Jochen

2017-10-01

The paper proposes a novel factorization technique for static condensation of a spectral-element discretization matrix that yields a linear operation count of just 13N multiplications for the residual evaluation, where N is the total number of unknowns. In comparison to previous work it saves a factor larger than 3 and outpaces unfactored variants for all polynomial degrees. Using the new technique as a building block for a preconditioned conjugate gradient method yields linear scaling of the runtime with N which is demonstrated for polynomial degrees from 2 to 32. This makes the spectral-element method cost effective even for low polynomial degrees. Moreover, the dependence of the iterative solution on the element aspect ratio is addressed, showing only a slight increase in the number of iterations for aspect ratios up to 128. Hence, the solver is very robust for practical applications.

Circulating interleukin-8 and tumor necrosis factor-α are associated with hot flashes in healthy postmenopausal women.

PubMed

Huang, Wan-Yu; Hsin, I-Lun; Chen, Dar-Ren; Chang, Chia-Chu; Kor, Chew-Teng; Chen, Ting-Yu; Wu, Hung-Ming

2017-01-01

Hot flashes have been postulated to be linked to systemic inflammation. This study aimed to investigate the relationship between hot flashes, pro-inflammatory factors, and leukocytes in healthy, non-obese postmenopausal women. In this cross-sectional study, a total of 202 women aged 45-60 years were stratified into one of four groups according to their hot-flash status: never experienced hot flashes (Group N), mild hot flashes (Group m), moderate hot flashes (Group M), and severe hot flashes (Group S). Variables measured in this study included clinical parameters, hot flash experience, leukocytes, and fasting plasma levels of nine circulating cytokines/chemokines measured by using multiplex assays. Multiple linear regression analysis was used to evaluate the associations of hot flashes with these pro-inflammatory factors. The study was performed in a hospital medical center. The mean values of leukocyte number were not different between these four groups. The hot flash status had a positive tendency toward increased levels of circulating IL-6 (P-trend = 0.049), IL-8 (P-trend < 0.001), TNF-α (P-trend = 0.008), and MIP1β (P-trend = 0.04). Multivariate linear regression analysis revealed that hot-flash severity was significantly associated with IL-8 (P-trend < 0.001) and TNFα (P-trend = 0.007) among these nine cytokines/chemokines after adjustment for age, menopausal duration, BMI and FSH. Multivariate analysis further revealed that severe hot flashes were strongly associated with a higher IL-8 (% difference, 37.19%; 95% confidence interval, 14.98,63.69; P < 0.001) and TNFα (51.27%; 6.64,114.57; P < 0.05). The present study provides evidence that hot flashes are associated with circulating IL-8 and TNF-α in healthy postmenopausal women. It suggests that hot flashes might be related to low-grade systemic inflammation.

Exploring the determinants that influence end-of-life hospital costs of the elderly in Shanghai, China.

PubMed

Li, Fen; Zhu, Bifan; He, Zhimin; Zhang, Xiaoxi; Wang, Changying; Wang, Linan; Song, Peipei; Ding, Lingling; Jin, Chunlin

2018-01-01

The aim of this study was to use data from the Information Center of the Shanghai Municipal Commission of Health and Family Planning (SMCHFP) to determine the factors affecting end-of-life hospital costs of patients. A total number of 43,806 decedents who died in medical facilities in 2015 were examined. These individuals, accounted for 34.85% of all deaths in 2015 in Shanghai. Descriptive analysis and multiple linear regression analysis were performed using STATA 13.0. Results indicated that 88.94% of the decedents who died in medical facilities were over age 60. Males accounted for 55.57% of decedents, and the insured were mostly covered by Urban Employee Basic Medical Insurance (UEBMI) (81.93%). Cancer and circulatory disease were the main causes of death, causing 34.53% and 26.19% of deaths. Hospital costs were higher for males (male vs. female: 9,013 USD vs. 7,844 USD), individuals insured by UEBMI (8,784 USD), and individuals with cancer (10,156USD). Twenty-nine-point-zero-three percent of admissions occurred in the month before death and accounted for 37.82% of costs. Multiple linear regression analysis indicated that hospital costs were correlated with gender, cause of death (cancer, circulatory disease, or respiratory disease), time-to-death, insurance schemes, level of medical facilities, and length of stay (LOS) (p < 0.05 for all). After controlling for other factors, age was not a significant factor (p > 0.05). A proximity-to-death (PTD) phenomenon was evident in Shanghai. This study suggested that the PTD should be considered when predicting medical cost. Primary medical care should be enhanced and gaps in insurance coverage should be reduced to improve the efficiency and equity of medical funding. More attention should be paid to the population with a heavier disease burden.

Circulating interleukin-8 and tumor necrosis factor-α are associated with hot flashes in healthy postmenopausal women

PubMed Central

Huang, Wan-Yu; Hsin, I-Lun; Chen, Dar-Ren; Chang, Chia-Chu; Kor, Chew-Teng; Chen, Ting-Yu

2017-01-01

Introduction Hot flashes have been postulated to be linked to systemic inflammation. This study aimed to investigate the relationship between hot flashes, pro-inflammatory factors, and leukocytes in healthy, non-obese postmenopausal women. Participants and design In this cross-sectional study, a total of 202 women aged 45–60 years were stratified into one of four groups according to their hot-flash status: never experienced hot flashes (Group N), mild hot flashes (Group m), moderate hot flashes (Group M), and severe hot flashes (Group S). Variables measured in this study included clinical parameters, hot flash experience, leukocytes, and fasting plasma levels of nine circulating cytokines/chemokines measured by using multiplex assays. Multiple linear regression analysis was used to evaluate the associations of hot flashes with these pro-inflammatory factors. Settings The study was performed in a hospital medical center. Results The mean values of leukocyte number were not different between these four groups. The hot flash status had a positive tendency toward increased levels of circulating IL-6 (P-trend = 0.049), IL-8 (P-trend < 0.001), TNF-α (P-trend = 0.008), and MIP1β (P-trend = 0.04). Multivariate linear regression analysis revealed that hot-flash severity was significantly associated with IL-8 (P-trend < 0.001) and TNFα (P-trend = 0.007) among these nine cytokines/chemokines after adjustment for age, menopausal duration, BMI and FSH. Multivariate analysis further revealed that severe hot flashes were strongly associated with a higher IL-8 (% difference, 37.19%; 95% confidence interval, 14.98,63.69; P < 0.001) and TNFα (51.27%; 6.64,114.57; P < 0.05). Conclusion The present study provides evidence that hot flashes are associated with circulating IL-8 and TNF-α in healthy postmenopausal women. It suggests that hot flashes might be related to low-grade systemic inflammation. PMID:28846735

Comparing the cognitive differences resulting from modeling instruction: Using computer microworld and physical object instruction to model real world problems

NASA Astrophysics Data System (ADS)

Oursland, Mark David

This study compared the modeling achievement of students receiving mathematical modeling instruction using the computer microworld, Interactive Physics, and students receiving instruction using physical objects. Modeling instruction included activities where students applied the (a) linear model to a variety of situations, (b) linear model to two-rate situations with a constant rate, (c) quadratic model to familiar geometric figures. Both quantitative and qualitative methods were used to analyze achievement differences between students (a) receiving different methods of modeling instruction, (b) with different levels of beginning modeling ability, or (c) with different levels of computer literacy. Student achievement was analyzed quantitatively through a three-factor analysis of variance where modeling instruction, beginning modeling ability, and computer literacy were used as the three independent factors. The SOLO (Structure of the Observed Learning Outcome) assessment framework was used to design written modeling assessment instruments to measure the students' modeling achievement. The same three independent factors were used to collect and analyze the interviews and observations of student behaviors. Both methods of modeling instruction used the data analysis approach to mathematical modeling. The instructional lessons presented problem situations where students were asked to collect data, analyze the data, write a symbolic mathematical equation, and use equation to solve the problem. The researcher recommends the following practice for modeling instruction based on the conclusions of this study. A variety of activities with a common structure are needed to make explicit the modeling process of applying a standard mathematical model. The modeling process is influenced strongly by prior knowledge of the problem context and previous modeling experiences. The conclusions of this study imply that knowledge of the properties about squares improved the students' ability to model a geometric problem more than instruction in data analysis modeling. The uses of computer microworlds such as Interactive Physics in conjunction with cooperative groups are a viable method of modeling instruction.

Association between metabolic syndrome and intravesical prostatic protrusion in patients with benign prostatic enlargement and lower urinary tract symptoms (MIPS Study).

PubMed

Russo, Giorgio I; Regis, Federica; Spatafora, Pietro; Frizzi, Jacopo; Urzì, Daniele; Cimino, Sebastiano; Serni, Sergio; Carini, Marco; Gacci, Mauro; Morgia, Giuseppe

2018-05-01

To investigate the association between metabolic syndrome (MetS) and morphological features of benign prostatic enlargement (BPE), including total prostate volume (TPV), transitional zone volume (TZV) and intravesical prostatic protrusion (IPP). Between January 2015 and January 2017, 224 consecutive men aged >50 years presenting with lower urinary tract symptoms (LUTS) suggestive of BPE were recruited to this multicentre cross-sectional study. MetS was defined according to International Diabetes Federation criteria. Multivariate linear and logistic regression models were performed to verify factors associated with IPP, TZV and TPV. Patients with MetS were observed to have a significant increase in IPP (P < 0.01), TPV (P < 0.01) and TZV (P = 0.02). On linear regression analysis, adjusted for age and metabolic factors of MetS, we found that high-density lipoprotein (HDL) cholesterol was negatively associated with IPP (r = -0.17), TPV (r = -0.19) and TZV (r = -0.17), while hypertension was positively associated with IPP (r = 0.16), TPV (r = 0.19) and TZV (r = 0.16). On multivariate logistic regression analysis adjusted for age and factors of MetS, hypertension (categorical; odds ratio [OR] 2.95), HDL cholesterol (OR 0.94) and triglycerides (OR 1.01) were independent predictors of TPV ≥ 40 mL. We also found that HDL cholesterol (OR 0.86), hypertension (OR 2.0) and waist circumference (OR 1.09) were significantly associated with TZV ≥ 20 mL. On age-adjusted logistic regression analysis, MetS was significantly associated with IPP ≥ 10 mm (OR 34.0; P < 0.01), TZV ≥ 20 mL (OR 4.40; P < 0.01) and TPV ≥ 40 mL (OR 5.89; P = 0.03). We found an association between MetS and BPE, demonstrating a relationship with IPP. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Archetypes for Organisational Safety

NASA Technical Reports Server (NTRS)

Marais, Karen; Leveson, Nancy G.

2003-01-01

We propose a framework using system dynamics to model the dynamic behavior of organizations in accident analysis. Most current accident analysis techniques are event-based and do not adequately capture the dynamic complexity and non-linear interactions that characterize accidents in complex systems. In this paper we propose a set of system safety archetypes that model common safety culture flaws in organizations, i.e., the dynamic behaviour of organizations that often leads to accidents. As accident analysis and investigation tools, the archetypes can be used to develop dynamic models that describe the systemic and organizational factors contributing to the accident. The archetypes help clarify why safety-related decisions do not always result in the desired behavior, and how independent decisions in different parts of the organization can combine to impact safety.

Characterization of HPGe gamma spectrometric detectors systems for Instrumental Neutron Activation Analysis (INAA) at the Colombian Geological Survey

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

Sierra, O., E-mail: osierra@sgc.gov.co; Parrado, G., E-mail: gparrado@sgc.gov.co; Cañón, Y.

This paper presents the progress made by the Neutron Activation Analysis (NAA) laboratory at the Colombian Geological Survey (SGC in its Spanish acronym), towards the characterization of its gamma spectrometric systems for Instrumental Neutron Activation Analysis (INAA), with the aim of introducing corrections to the measurements by variations in sample geometry. Characterization includes the empirical determination of the interaction point of gamma radiation inside the Germanium crystal, through the application of a linear model and the use of a fast Monte Carlo N-Particle (MCNP) software to estimate correction factors for differences in counting efficiency that arise from variations in samplemore » density between samples and standards.« less

The application of high-speed cinematography for the quantitative analysis of equine locomotion.

PubMed

Fredricson, I; Drevemo, S; Dalin, G; Hjertën, G; Björne, K

1980-04-01

Locomotive disorders constitute a serious problem in horse racing which will only be rectified by a better understanding of the causative factors associated with disturbances of gait. This study describes a system for the quantitative analysis of the locomotion of horses at speed. The method is based on high-speed cinematography with a semi-automatic system of analysis of the films. The recordings are made with a 16 mm high-speed camera run at 500 frames per second (fps) and the films are analysed by special film-reading equipment and a mini-computer. The time and linear gait variables are presented in tabular form and the angles and trajectories of the joints and body segments are presented graphically.

Validation of the conceptual research utilization scale: an application of the standards for educational and psychological testing in healthcare.

PubMed

Squires, Janet E; Estabrooks, Carole A; Newburn-Cook, Christine V; Gierl, Mark

2011-05-19

There is a lack of acceptable, reliable, and valid survey instruments to measure conceptual research utilization (CRU). In this study, we investigated the psychometric properties of a newly developed scale (the CRU Scale). We used the Standards for Educational and Psychological Testing as a validation framework to assess four sources of validity evidence: content, response processes, internal structure, and relations to other variables. A panel of nine international research utilization experts performed a formal content validity assessment. To determine response process validity, we conducted a series of one-on-one scale administration sessions with 10 healthcare aides. Internal structure and relations to other variables validity was examined using CRU Scale response data from a sample of 707 healthcare aides working in 30 urban Canadian nursing homes. Principal components analysis and confirmatory factor analyses were conducted to determine internal structure. Relations to other variables were examined using: (1) bivariate correlations; (2) change in mean values of CRU with increasing levels of other kinds of research utilization; and (3) multivariate linear regression. Content validity index scores for the five items ranged from 0.55 to 1.00. The principal components analysis predicted a 5-item 1-factor model. This was inconsistent with the findings from the confirmatory factor analysis, which showed best fit for a 4-item 1-factor model. Bivariate associations between CRU and other kinds of research utilization were statistically significant (p < 0.01) for the latent CRU scale score and all five CRU items. The CRU scale score was also shown to be significant predictor of overall research utilization in multivariate linear regression. The CRU scale showed acceptable initial psychometric properties with respect to responses from healthcare aides in nursing homes. Based on our validity, reliability, and acceptability analyses, we recommend using a reduced (four-item) version of the CRU scale to yield sound assessments of CRU by healthcare aides. Refinement to the wording of one item is also needed. Planned future research will include: latent scale scoring, identification of variables that predict and are outcomes to conceptual research use, and longitudinal work to determine CRU Scale sensitivity to change.

The predictors of chemistry achievement of 12th grade students in secondary schools in the United Arab Emirates

NASA Astrophysics Data System (ADS)

Khalaf, Ali Khalfan

2000-10-01

The purpose of this study is to explore variables related to chemistry achievement of 12th grade science students in the United Arab Emirates (UAE). The focus is to identify student, teacher, and school variables that predict chemistry achievement. The analysis sample included 204 males and 252 females in 66 classes in 60 schools from 10 districts or bureaus of education in the UAE. Thirty-two male and 33 female chemistry teachers and 60 school principals were included. The Khalaf Chemistry Achievement Test, GALT, the Student Questionnaire, Teacher Questionnaire, and School Information Questionnaire were administered. Descriptive statistics, correlations, analyses of variance, factor analysis, and stepwise multiple linear regression analyses were done. The results indicate that demographic, home environment, prior knowledge, scholastic ability, attitudes and perceptions related to chemistry and science, and student perception of instructional practices variables correlated with student chemistry achievement. The amount of help teachers received from the supervisor, class size, and courses in geology were teacher variables that correlated with class chemistry achievement. Nine school variables involving school, division, and class sizes correlated with school chemistry achievement. Analyses of variance revealed significant interaction effects: district by school size and district by student gender. In two districts, students in small schools achieved better than those in large schools. Generally female students achieved equal to or better than males. Three factors from the factor analysis: School Size, Prior Student Achievement, and Student Perception of Teacher Effectiveness, correlated with school chemistry achievement. The results of the multiple linear regression indicated that the factors of Prior Student Achievement, Student Perception of Teacher Effectiveness, and Teacher Experience and Expertise accounted for 45% of the variance in school chemistry achievement. Results indicate that the strongest predictors of chemistry achievement are prior achievement in science, Arabic language, and mathematics; student perception of teacher effectiveness; and teacher experience and expertise. Females tend to achieve better in chemistry than males. No nationality differences were found and the relationship of school size to chemistry achievement was inconclusive. Recommendations related to chemistry and science are presented. These include curriculum, school practice, teacher professional development, and future research.

Evaluation of mercury in rainbow trout collected from Duck Valley Indian Reservation reservoirs, southwestern Idaho and northern Nevada, 2007, 2009, and 2013

USGS Publications Warehouse

Williams, Marshall L.; MacCoy, Dorene E.; Maret, Terry R.

2015-07-17

Coupled with the dynamic put-and-take fishery, the outcomes reflect the system complexities among reservoirs despite their fairly close proximity to one another. The influence of these other factors is evident when the analysis of atmospheric Hg deposition at Mercury Deposition Network site NV02 in northern Nevada showed no significant linear trend in wet Hg deposition rates for 2003–2013 (average 3.02 micrograms per square meter).