Lithium might be associated with better decision-making performance in euthymic bipolar patients.

PubMed

Adida, Marc; Jollant, Fabrice; Clark, Luke; Guillaume, Sebastien; Goodwin, Guy M; Azorin, Jean-Michel; Courtet, Philippe

2015-06-01

Bipolar disorder is associated with impaired decision-making. Little is known about how treatment, especially lithium, influences decision-making abilities in bipolar patients when euthymic. We aimed at testing for an association between lithium medication and decision-making performance in remitted bipolar patients. Decision-making was measured using the Iowa Gambling Task in 3 groups of subjects: 34 and 56 euthymic outpatients with bipolar disorder, treated with lithium (monotherapy and lithium combined with anticonvulsant or antipsychotic) and without lithium (anticonvulsant, antipsychotic and combination treatment), respectively, and 152 matched healthy controls. Performance was compared between the 3 groups. In the 90 euthymic patients, the relationship between different sociodemographic and clinical variables and decision-making was assessed by stepwise multivariate regression analysis. Euthymic patients with lithium (p=0.007) and healthy controls (p=0.001) selected significantly more cards from the safe decks than euthymic patients without lithium, with no significant difference between euthymic patients with lithium and healthy controls (p=0.9). In the 90 euthymic patients, the stepwise linear multivariate regression revealed that decision-making was significantly predicted (p<0.001) by lithium dose, level of education and no family history of bipolar disorder (all p≤0.01). Because medication was not randomized, it was not possible to discriminate the effect of different medications. Lithium medication might be associated with better decision-making in remitted bipolar patients. A randomized trial is required to test for the hypothesis that lithium, but not other mood stabilizers, may specifically improve decision-making abilities in bipolar disorder. Copyright © 2015 Elsevier B.V. and ECNP. All rights reserved.

Dancing with the Muses: dissociation and flow.

PubMed

Thomson, Paula; Jaque, S Victoria

2012-01-01

This study investigated dissociative psychological processes and flow (dispositional and state) in a group of professional and pre-professional dancers (n=74). In this study, high scores for global (Mdn=4.14) and autotelic (Mdn=4.50) flow suggest that dancing was inherently integrating and rewarding, although 17.6% of the dancers were identified as possibly having clinical levels of dissociation (Dissociative Experiences Scale-Taxon cutoff score≥20). The results of the multivariate analysis of variance indicated that subjects with high levels of dissociation had significantly lower levels of global flow (p<.05). Stepwise linear regression analyses demonstrated that dispositional flow negatively predicted the dissociative constructs of depersonalization and taxon (p<.05) but did not significantly predict the variance in absorption/imagination (p>.05). As hypothesized, dissociation and flow seem to operate as different mental processes.

Episiotomy increases perineal laceration length in primiparous women.

PubMed

Nager, C W; Helliwell, J P

2001-08-01

The aim of this study was to determine the clinical factors that contribute to posterior perineal laceration length. A prospective observational study was performed in 80 consenting, mostly primiparous women with term pregnancies. Posterior perineal lacerations were measured immediately after delivery. Numerous maternal, fetal, and operator variables were evaluated against laceration length and degree of tear. Univariate and multivariate regression analyses were performed to evaluate laceration length and parametric clinical variables. Nonparametric clinical variables were evaluated against laceration length by the Mann-Whitney U test. A multivariate stepwise linear regression equation revealed that episiotomy adds nearly 3 cm to perineal lacerations. Tear length was highly associated with the degree of tear (R = 0.86, R(2) = 0.73) and the risk of recognized anal sphincter disruption. None of 35 patients without an episiotomy had a recognized anal sphincter disruption, but 6 of 27 patients with an episiotomy did (P <.001). Body mass index was the only maternal or fetal variable that showed even a slight correlation with laceration length (R = 0.30, P =.04). Episiotomy is the overriding determinant of perineal laceration length and recognized anal sphincter disruption.

Application of Multivariate Modeling for Radiation Injury Assessment: A Proof of Concept

PubMed Central

Bolduc, David L.; Villa, Vilmar; Sandgren, David J.; Ledney, G. David; Blakely, William F.; Bünger, Rolf

2014-01-01

Multivariate radiation injury estimation algorithms were formulated for estimating severe hematopoietic acute radiation syndrome (H-ARS) injury (i.e., response category three or RC3) in a rhesus monkey total-body irradiation (TBI) model. Classical CBC and serum chemistry blood parameters were examined prior to irradiation (d 0) and on d 7, 10, 14, 21, and 25 after irradiation involving 24 nonhuman primates (NHP) (Macaca mulatta) given 6.5-Gy 60Co Υ-rays (0.4 Gy min−1) TBI. A correlation matrix was formulated with the RC3 severity level designated as the “dependent variable” and independent variables down selected based on their radioresponsiveness and relatively low multicollinearity using stepwise-linear regression analyses. Final candidate independent variables included CBC counts (absolute number of neutrophils, lymphocytes, and platelets) in formulating the “CBC” RC3 estimation algorithm. Additionally, the formulation of a diagnostic CBC and serum chemistry “CBC-SCHEM” RC3 algorithm expanded upon the CBC algorithm model with the addition of hematocrit and the serum enzyme levels of aspartate aminotransferase, creatine kinase, and lactate dehydrogenase. Both algorithms estimated RC3 with over 90% predictive power. Only the CBC-SCHEM RC3 algorithm, however, met the critical three assumptions of linear least squares demonstrating slightly greater precision for radiation injury estimation, but with significantly decreased prediction error indicating increased statistical robustness. PMID:25165485

Multivariate class modeling techniques applied to multielement analysis for the verification of the geographical origin of chili pepper.

PubMed

Naccarato, Attilio; Furia, Emilia; Sindona, Giovanni; Tagarelli, Antonio

2016-09-01

Four class-modeling techniques (soft independent modeling of class analogy (SIMCA), unequal dispersed classes (UNEQ), potential functions (PF), and multivariate range modeling (MRM)) were applied to multielement distribution to build chemometric models able to authenticate chili pepper samples grown in Calabria respect to those grown outside of Calabria. The multivariate techniques were applied by considering both all the variables (32 elements, Al, As, Ba, Ca, Cd, Ce, Co, Cr, Cs, Cu, Dy, Fe, Ga, La, Li, Mg, Mn, Na, Nd, Ni, Pb, Pr, Rb, Sc, Se, Sr, Tl, Tm, V, Y, Yb, Zn) and variables selected by means of stepwise linear discriminant analysis (S-LDA). In the first case, satisfactory and comparable results in terms of CV efficiency are obtained with the use of SIMCA and MRM (82.3 and 83.2% respectively), whereas MRM performs better than SIMCA in terms of forced model efficiency (96.5%). The selection of variables by S-LDA permitted to build models characterized, in general, by a higher efficiency. MRM provided again the best results for CV efficiency (87.7% with an effective balance of sensitivity and specificity) as well as forced model efficiency (96.5%). Copyright © 2016 Elsevier Ltd. All rights reserved.

Stepwise photochromism of bisnaphthopyrans exhibiting an excitation intensity-dependent color change.

PubMed

Inagaki, Yuki; Mutoh, Katsuya; Abe, Jiro

2018-06-07

Non-linear photoresponses against excitation light intensity are important for the development of attractive photofunctional materials exhibiting high spatial selective photoswitching that is not affected by weak background light. Biphotochromic systems composed of two fast photochromic units have the potential to show a stepwise two-photon absorption process in which the optical properties can be non-linearly controlled by changing the excitation light conditions. Herein, we designed and synthesized novel bisnaphthopyran derivatives containing fast photoswitchable naphthopyran units. The bisnaphthopyran derivatives show a stepwise two-photon-induced photochromic reaction upon UV light irradiation accompanied by a drastic color change due to a large change in the molecular structure between the one-photon product and the two-photon product. Consequently, the color of the bisnaphthopyran derivatives can be non-linearly controlled by changing the excitation intensity. This characteristic photochromic property of the biphotochromic system provides important insight into advanced photoresponsive materials.

Association of serum orosomucoid with 30-min plasma glucose and glucose excursion during oral glucose tolerance tests in non-obese young Japanese women.

PubMed

Tsuboi, Ayaka; Minato, Satomi; Yano, Megumu; Takeuchi, Mika; Kitaoka, Kaori; Kurata, Miki; Yoshino, Gen; Wu, Bin; Kazumi, Tsutomu; Fukuo, Keisuke

2018-01-01

Inflammatory markers are elevated in insulin resistance (IR) and diabetes. We tested whether serum orosomucoid (ORM) is associated with postload glucose, β-cell dysfunction and IR inferred from plasma insulin kinetics during a 75 g oral glucose tolerance test (OGTT). 75 g OGTTs were performed with multiple postload glucose and insulin measurements over a 30-120 min period in 168 non-obese Japanese women (aged 18-24 years). OGTT responses, serum adiponectin and high-sensitivity C reactive protein (hsCRP) were cross-sectionally analyzed by analysis of variance and then Bonferroni's multiple comparison procedure. Stepwise multivariate linear regression analyses were used to identify most important determinants of ORM. Of 168 women, 161 had normal glucose tolerance. Postload glucose levels and the area under the glucose curve (AUCg) increased in a stepwise fashion from the first through the third ORM tertile. In contrast, there was no or modest, if any, association with fat mass index, trunk/leg fat ratio, adiponectin, hsCRP, postload insulinemia, the Matsuda index and homeostasis model assessment IR. In multivariable models, which incorporated the insulinogenic index, the Matsuda index and HOMA-IR, 30 min glucose (standardized β: 0.517) and AUCg (standardized β: 0.495) explained 92.8% of ORM variations. Elevated circulating orosomucoid was associated with elevated 30 min glucose and glucose excursion in non-obese young Japanese women independently of adiposity, IR, insulin secretion, adiponectin and other investigated markers of inflammation. Although further research is needed, these results may suggest a clue to identify novel pathways that may have utility in monitoring dysglycemia within normal glucose tolerance.

Stone volume is best predictor of operative time required in retrograde intrarenal surgery for renal calculi: implications for surgical planning and quality improvement.

PubMed

Sorokin, Igor; Cardona-Grau, Diana K; Rehfuss, Alexandra; Birney, Alan; Stavrakis, Costas; Leinwand, Gabriel; Herr, Allen; Feustel, Paul J; White, Mark D

2016-11-01

Retrograde intrarenal surgery (RIRS) is highly successful at eliminating renal stones of various sizes and compositions. As urologists are taking on more complex procedures using RIRS, this has led to an increase in operative (OR) times. Our objective was to determine the best predictor of OR time in patients undergoing RIRS. We retrospectively reviewed the records of patients undergoing unilateral RIRS for solitary stones over a 10 year time span. Stones were fragmented and actively extracted using a basket. Variables potentially affecting OR time such as patient age, sex, BMI, lower pole stone location, volume, Hounsfield units (HU), composition, ureteral access sheath (UAS) use, and pre-operative stenting were collected. Multivariable linear and stepwise regression was used to evaluate the predictors of OR time. There were 118 patients that met inclusion criteria. The median stone volume was 282.6 mm 3 (IQR 150.7-644.7) and the mean OR time was 50 min (±25.9 SD). On univariate linear regression, stone volume had a moderate correlation with OR time (y = 0.022x + 38.2, r 2  = 0.363, p < 0.01). On multivariable stepwise regression, stone volume had the strongest impact on OR time, increasing time by 2.0 min for each 100 mm 3 increase in stone volume (p < 0.001). UAS added 13.5 (SE 3.9, p = 0.001) minutes and renal lower pole location added 9 min (SE 4.3, p = 0.03) in each case they were used. Pre-operative stenting, HU, calcium oxalate stone composition, sex, and age had no significant effect on OR time. Amongst the main stone factors in RIRS, stone volume has the strongest impact on operative time. This can be used to predict the length of the procedure by roughly adding 2 min per 100 mm 3 increase in stone volume.

A Statistical Discrimination Experiment for Eurasian Events Using a Twenty-Seven-Station Network

DTIC Science & Technology

1980-07-08

to test the effectiveness of a multivariate method of analysis for distinguishing earthquakes from explosions. The data base for the experiment...to test the effectiveness of a multivariate method of analysis for distinguishing earthquakes from explosions. The data base for the experiment...the weight assigned to each variable whenever a new one is added. Jennrich, R. I. (1977). Stepwise discriminant analysis , in Statistical Methods for

Application of multivariate chemometric techniques for simultaneous determination of five parameters of cottonseed oil by single bounce attenuated total reflectance Fourier transform infrared spectroscopy.

PubMed

Talpur, M Younis; Kara, Huseyin; Sherazi, S T H; Ayyildiz, H Filiz; Topkafa, Mustafa; Arslan, Fatma Nur; Naz, Saba; Durmaz, Fatih; Sirajuddin

2014-11-01

Single bounce attenuated total reflectance (SB-ATR) Fourier transform infrared (FTIR) spectroscopy in conjunction with chemometrics was used for accurate determination of free fatty acid (FFA), peroxide value (PV), iodine value (IV), conjugated diene (CD) and conjugated triene (CT) of cottonseed oil (CSO) during potato chips frying. Partial least square (PLS), stepwise multiple linear regression (SMLR), principal component regression (PCR) and simple Beer׳s law (SBL) were applied to develop the calibrations for simultaneous evaluation of five stated parameters of cottonseed oil (CSO) during frying of French frozen potato chips at 170°C. Good regression coefficients (R(2)) were achieved for FFA, PV, IV, CD and CT with value of >0.992 by PLS, SMLR, PCR, and SBL. Root mean square error of prediction (RMSEP) was found to be less than 1.95% for all determinations. Result of the study indicated that SB-ATR FTIR in combination with multivariate chemometrics could be used for accurate and simultaneous determination of different parameters during the frying process without using any toxic organic solvent. Copyright © 2014 Elsevier B.V. All rights reserved.

Circulating miRNAs in Pediatric Pulmonary Hypertension Show Promise as Biomarkers of Vascular Function

PubMed Central

Sucharov, Carmen C.; Truong, Uyen; Dunning, Jamie; Ivy, Dunbar; Miyamoto, Shelley; Shandas, Robin

2017-01-01

Background/Objectives The objective of this study was to evaluate the utility of circulating miRNAs as biomarkers of vascular function in pediatric pulmonary hypertension. Method Fourteen pediatric pulmonary arterial hypertension patients underwent simultaneous right heart catheterization (RHC) and blood biochemical analysis. Univariate and stepwise multivariate linear regression was used to identify and correlate measures of reactive and resistive afterload with circulating miRNA levels. Furthermore, circulating miRNA candidates that classified patients according to a 20% decrease in resistive afterload in response to oxygen (O2) or inhaled nitric oxide (iNO) were identified using receiver-operating curves. Results Thirty-two circulating miRNAs correlated with the pulmonary vascular resistance index (PVRi), pulmonary arterial distensibility, and PVRi decrease in response to O2 and/or iNO. Multivariate models, combining the predictive capability of multiple promising miRNA candidates, revealed a good correlation with resistive (r = 0.97, P2−tailed < 0.0001) and reactive (r = 0.86, P2−tailed < 0.005) afterloads. Bland-Altman plots showed that 95% of the differences between multivariate models and RHC would fall within 0.13 (mmHg−min/L)m2 and 0.0085/mmHg for resistive and reactive afterloads, respectively. Circulating miR-663 proved to be a good classifier for vascular responsiveness to acute O2 and iNO challenges. Conclusion This study suggests that circulating miRNAs may be biomarkers to phenotype vascular function in pediatric PAH. PMID:28819545

A stepwise, multi-objective, multi-variable parameter optimization method for the APEX model

USDA-ARS?s Scientific Manuscript database

Proper parameterization enables hydrological models to make reliable estimates of non-point source pollution for effective control measures. The automatic calibration of hydrologic models requires significant computational power limiting its application. The study objective was to develop and eval...

Non-targeted 1H NMR fingerprinting and multivariate statistical analyses for the characterisation of the geographical origin of Italian sweet cherries.

PubMed

Longobardi, F; Ventrella, A; Bianco, A; Catucci, L; Cafagna, I; Gallo, V; Mastrorilli, P; Agostiano, A

2013-12-01

In this study, non-targeted (1)H NMR fingerprinting was used in combination with multivariate statistical techniques for the classification of Italian sweet cherries based on their different geographical origins (Emilia Romagna and Puglia). As classification techniques, Soft Independent Modelling of Class Analogy (SIMCA), Partial Least Squares Discriminant Analysis (PLS-DA), and Linear Discriminant Analysis (LDA) were carried out and the results were compared. For LDA, before performing a refined selection of the number/combination of variables, two different strategies for a preliminary reduction of the variable number were tested. The best average recognition and CV prediction abilities (both 100.0%) were obtained for all the LDA models, although PLS-DA also showed remarkable performances (94.6%). All the statistical models were validated by observing the prediction abilities with respect to an external set of cherry samples. The best result (94.9%) was obtained with LDA by performing a best subset selection procedure on a set of 30 principal components previously selected by a stepwise decorrelation. The metabolites that mostly contributed to the classification performances of such LDA model, were found to be malate, glucose, fructose, glutamine and succinate. Copyright © 2013 Elsevier Ltd. All rights reserved.

Evaluation of a stepwise, multi-objective, multi-variable parameter optimization method for the APEX model

USDA-ARS?s Scientific Manuscript database

Hydrologic models are essential tools for environmental assessment of agricultural non-point source pollution. The automatic calibration of hydrologic models, though efficient, demands significant computational power, which can limit its application. The study objective was to investigate a cost e...

[Contents of vitreous humor of dead body with different postmortem intervals].

PubMed

Tao, Tao; Xu, Jing; Luo, Tong-Xing; Liao, Zhi-Gang; Pan, Hong-Fu

2006-11-01

To establish regression correlations between postmortem interval (PMI) and contents of human vitreous humor of dead bodies for forensic purposes. The human vitreous humor were taken from 126 dead bodies between 0.5 to 216 hours after death, and 11 chemical elements were detected by the OLYMPUS AU400 auto-biochemistry instrument. (1) The glucose, natrium and chlorine in human vitreous humor decreased, while the urea, creatinine, uric acid, potassium, calcium, magnesium, phosphorus, and micro-protein increased after death. The change of glucose, potassium and phosphorus were well correlated with the PMI (r = 0.824, 0.967, 0.880). But the uric acid and micro-protein did not have a good correlation with the PMI(r = 0.350, 0.153). (2) The stepwise regression analysis established the following equations for the PMI (Y): Y = -35. 15+6.05X, R2 = 0.957 (X = potassium); Y = -27.83+ 5.49X(1) - 1.35X(2), R2 = 0.960 (X(1) = potassium, X(2) = glucose); Y = -6.37+3.93X(1) -2.29X(2) + 5.36X(3), R2 = 0.966 (X(1) = potassium, X(2) = glucose, X(3) = phosphorus). (1) Eleven chemical components in human vitreous humor change after death, among which postassium has the best linear correlation with the PMI within 72 hours after death. (2) The accuracy of the estimation of PMI could be improved by establishing a multi-variable equation through stepwise regression.

Behavioral activation: Is it the expectation or achievement, of mastery or pleasure that contributes to improvement in depression?

PubMed

Furukawa, Toshi A; Imai, Hissei; Horikoshi, Masaru; Shimodera, Shinji; Hiroe, Takahiro; Funayama, Tadashi; Akechi, Tatsuo

2018-06-06

Behavioral activation (BA) is receiving renewed interest as a stand-alone or as a component of cognitive-behavior therapy (CBT) for depression. However, few studies have examined which aspects of BA are most contributory to its efficacy. This is a secondary analysis of a 9-week randomized controlled trial of smartphone CBT for patients with major depression. Depression severity was measured at baseline and at end of treatment by the Patient Health Questionnaire-9. All aspects of behavioral activation tasks that the participants had engaged in, including their expected mastery and pleasure and obtained mastery and pleasure, were recorded in the web server. We examined their contribution to improvement in depression as simple correlations and in stepwise multivariable linear regression. Among the 78 patients who completed at least one behavioral experiment, all aspects of expected or achieved mastery or pleasure correlated with change in depression severity. Discrepancy between the expectation and achievement, representing unexpected gain in mastery or pleasure, was not correlated. In stepwise regression, expected mastery and pleasure, especially the maximum level of the latter, emerged as the strongest contributing factors. The study is observational and cannot deduce cause-effect relationships. It may be the expected and continued sense of pleasure in planning activities that are most meaningful and rewarding to individuals, and not the simple level or amount of obtained pleasure, that contributes to the efficacy of BA. Copyright © 2018. Published by Elsevier B.V.

Variation of facial features among three African populations: Body height match analyses.

PubMed

Taura, M G; Adamu, L H; Gudaji, A

2017-01-01

Body height is one of the variables that show a correlation with facial craniometry. Here we seek to discriminate the three populations (Nigerians, Ugandans and Kenyans) using facial craniometry based on different categories of body height of adult males. A total of 513 individuals comprising 234 Nigerians, 169 Ugandans and 110 Kenyans with mean age of 25.27, s=5.13 (18-40 years) participated. Paired and unpaired facial features were measured using direct craniometry. Multivariate and stepwise discriminate function analyses were used for differentiation of the three populations. The result showed significant overall facial differences among the three populations in all the body height categories. Skull height, total facial height, outer canthal distance, exophthalmometry, right ear width and nasal length were significantly different among the three different populations irrespective of body height categories. Other variables were sensitive to body height. Stepwise discriminant function analyses included maximum of six variables for better discrimination between the three populations. The single best discriminator of the groups was total facial height, however, for body height >1.70m the single best discriminator was nasal length. Most of the variables were better used with function 1, hence, better discrimination than function 2. In conclusion, adult body height in addition to other factors such as age, sex, and ethnicity should be considered in making decision on facial craniometry. However, not all the facial linear dimensions were sensitive to body height. Copyright © 2016 Elsevier GmbH. All rights reserved.

Is patriarchy the source of men's higher mortality?

PubMed Central

Stanistreet, D; Bambra, C; Scott-Samuel, A

2005-01-01

Objective: To examine the relation between levels of patriarchy and male health by comparing female homicide rates with male mortality within countries. Hypothesis: High levels of patriarchy in a society are associated with increased mortality among men. Design: Cross sectional ecological study design. Setting: 51 countries from four continents were represented in the data—America, Europe, Australasia, and Asia. No data were available for Africa. Results: A multivariate stepwise linear regression model was used. Main outcome measure was age standardised male mortality rates for 51 countries for the year 1995. Age standardised female homicide rates and GDP per capita ranking were the explanatory variables in the model. Results were also adjusted for the effects of general rates of homicide. Age standardised female homicide rates and ranking of GDP were strongly correlated with age standardised male mortality rates (Pearson's r = 0.699 and Spearman's 0.744 respectively) and both correlations achieved significance (p<0.005). Both factors were subsequently included in the stepwise regression model. Female homicide rates explained 48.8% of the variance in male mortality, and GDP a further 13.6% showing that the higher the rate of female homicide, and hence the greater the indicator of patriarchy, the higher is the rate of mortality among men. Conclusion: These data suggest that oppression and exploitation harm the oppressors as well as those they oppress, and that men's higher mortality is a preventable social condition, which could be tackled through global social policy measures. PMID:16166362

Linear discriminant analysis of dermoscopic parameters for the differentiation of early melanomas from Clark naevi.

PubMed

Oka, Hiroshi; Tanaka, Masaru; Kobayashi, Seiichiro; Argenziano, Giuseppe; Soyer, H Peter; Nishikawa, Takeji

2004-04-01

As a first step to develop a screening system for pigmented skin lesions, we performed digital discriminant analyses between early melanomas and Clark naevi. A total of 59 cases of melanoma, including 23 melanoma in situ and 36 thin invasive melanomas (Breslow thickness < or =0.75 mm), and 188 clinically equivocal, histopathologically diagnosed Clark naevi were used in our study. After calculating 62 mathematical variables related to the colour, texture, asymmetry and circularity based on the dermoscopic findings of the pigmented skin lesions, we performed multivariate stepwise discriminant analysis using these variables to differentiate melanomas from naevi. The sensitivities and specificities of our model were 94.4 and 98.4%, respectively, for discriminating between melanomas (Breslow thickness < or =0.75 mm) and Clark naevi, and 73.9 and 85.6%, respectively, for discriminating between melanoma in situ and Clark naevi. Our algorithm accurately discriminated invasive melanomas from Clark naevi, but not melanomas in situ from Clark naevi.

Mouth opening in patients irradiated for head and neck cancer: a prospective repeated measures study.

PubMed

Kamstra, J I; Dijkstra, P U; van Leeuwen, M; Roodenburg, J L N; Langendijk, J A

2015-05-01

Aims of this prospective cohort study were (1) to analyze the course of mouth opening up to 48months post-radiotherapy (RT), (2) to assess risk factors predicting decrease in mouth opening, and (3) to develop a multivariable prediction model for change in mouth opening in a large sample of patients irradiated for head and neck cancer. Mouth opening was measured prior to RT (baseline) and at 6, 12, 18, 24, 36, and 48months post-RT. The primary outcome variable was mouth opening. Potential risk factors were entered into a linear mixed model analysis (manual backward-stepwise elimination) to create a multivariable prediction model. The interaction terms between time and risk factors that were significantly related to mouth opening were explored. The study population consisted of 641 patients: 70.4% male, mean age at baseline 62.3years (sd 12.5). Primary tumors were predominantly located in the oro- and nasopharynx (25.3%) and oral cavity (20.6%). Mean mouth opening at baseline was 38.7mm (sd 10.8). Six months post-RT, mean mouth opening was smallest, 36.7mm (sd 10.0). In the linear mixed model analysis, mouth opening was statistically predicted by the location of the tumor, natural logarithm of time post-RT in months (Ln (months)), gender, baseline mouth opening, and baseline age. All main effects interacted with Ln (months). The mean mouth opening decreased slightly over time. Mouth opening was predicted by tumor location, time, gender, baseline mouth opening, and age. The model can be used to predict mouth opening. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multivariate analysis of early and late nest sites of Abert's Towhees

Treesearch

Deborah M. Finch

1985-01-01

Seasonal variation in nest site selection by the Abert's towhee (Pipilo aberti) was studied in honey mesquite (Prosopis glandulosa) habitat along the lower Colorado River from March to July, 1981. Stepwise discriminant function analysis identified nest vegetation type, nest direction, and nest height as the three most important variables that characterized the...

Identifying Pedophiles "Eligible" for Community Notification under Megan's Law: A Multivariate Model for Actuarially Anchored Decisions.

ERIC Educational Resources Information Center

Pallone, Nathaniel J.; Hennessy, James J.; Voelbel, Gerald T.

1998-01-01

A scientifically sound methodology for identifying offenders about whose presence the community should be notified is demonstrated. A stepwise multiple regression was calculated among incarcerated pedophiles (N=52) including both psychological and legal data; a precision-weighted equation produced 90.4% "true positives." This methodology can be…

Application of stepwise multiple regression techniques to inversion of Nimbus 'IRIS' observations.

NASA Technical Reports Server (NTRS)

Ohring, G.

1972-01-01

Exploratory studies with Nimbus-3 infrared interferometer-spectrometer (IRIS) data indicate that, in addition to temperature, such meteorological parameters as geopotential heights of pressure surfaces, tropopause pressure, and tropopause temperature can be inferred from the observed spectra with the use of simple regression equations. The technique of screening the IRIS spectral data by means of stepwise regression to obtain the best radiation predictors of meteorological parameters is validated. The simplicity of application of the technique and the simplicity of the derived linear regression equations - which contain only a few terms - suggest usefulness for this approach. Based upon the results obtained, suggestions are made for further development and exploitation of the stepwise regression analysis technique.

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.

Virtual Assessment of Sex: Linear and Angular Traits of the Mandibular Ramus Using Three-Dimensional Computed Tomography.

PubMed

Inci, Ercan; Ekizoglu, Oguzhan; Turkay, Rustu; Aksoy, Sema; Can, Ismail Ozgur; Solmaz, Dilek; Sayin, Ibrahim

2016-10-01

Morphometric analysis of the mandibular ramus (MR) provides highly accurate data to discriminate sex. The objective of this study was to demonstrate the utility and accuracy of MR morphometric analysis for sex identification in a Turkish population.Four hundred fifteen Turkish patients (18-60 y; 201 male and 214 female) who had previously had multidetector computed tomography scans of the cranium were included in the study. Multidetector computed tomography images were obtained using three-dimensional reconstructions and a volume-rendering technique, and 8 linear and 3 angular values were measured. Univariate, bivariate, and multivariate discriminant analyses were performed, and the accuracy rates for determining sex were calculated.Mandibular ramus values produced high accuracy rates of 51% to 95.6%. Upper ramus vertical height had the highest rate at 95.6%, and bivariate analysis showed 89.7% to 98.6% accuracy rates with the highest ratios of mandibular flexure upper border and maximum ramus breadth. Stepwise discrimination analysis gave a 99% accuracy rate for all MR variables.Our study showed that the MR, in particular morphometric measures of the upper part of the ramus, can provide valuable data to determine sex in a Turkish population. The method combines both anthropological and radiologic studies.

Reduction of time-resolved space-based CCD photometry developed for MOST Fabry Imaging data*

NASA Astrophysics Data System (ADS)

Reegen, P.; Kallinger, T.; Frast, D.; Gruberbauer, M.; Huber, D.; Matthews, J. M.; Punz, D.; Schraml, S.; Weiss, W. W.; Kuschnig, R.; Moffat, A. F. J.; Walker, G. A. H.; Guenther, D. B.; Rucinski, S. M.; Sasselov, D.

2006-04-01

The MOST (Microvariability and Oscillations of Stars) satellite obtains ultraprecise photometry from space with high sampling rates and duty cycles. Astronomical photometry or imaging missions in low Earth orbits, like MOST, are especially sensitive to scattered light from Earthshine, and all these missions have a common need to extract target information from voluminous data cubes. They consist of upwards of hundreds of thousands of two-dimensional CCD frames (or subrasters) containing from hundreds to millions of pixels each, where the target information, superposed on background and instrumental effects, is contained only in a subset of pixels (Fabry Images, defocused images, mini-spectra). We describe a novel reduction technique for such data cubes: resolving linear correlations of target and background pixel intensities. This step-wise multiple linear regression removes only those target variations which are also detected in the background. The advantage of regression analysis versus background subtraction is the appropriate scaling, taking into account that the amount of contamination may differ from pixel to pixel. The multivariate solution for all pairs of target/background pixels is minimally invasive of the raw photometry while being very effective in reducing contamination due to, e.g. stray light. The technique is tested and demonstrated with both simulated oscillation signals and real MOST photometry.

Optimization of elution salt concentration in stepwise elution of protein chromatography using linear gradient elution data. Reducing residual protein A by cation-exchange chromatography in monoclonal antibody purification.

PubMed

Ishihara, Takashi; Kadoya, Toshihiko; Endo, Naomi; Yamamoto, Shuichi

2006-05-05

Our simple method for optimization of the elution salt concentration in stepwise elution was applied to the actual protein separation system, which involves several difficulties such as detection of the target. As a model separation system, reducing residual protein A by cation-exchange chromatography in human monoclonal antibody (hMab) purification was chosen. We carried out linear gradient elution experiments and obtained the data for the peak salt concentration of hMab and residual protein A, respectively. An enzyme-linked immunosorbent assay was applied to the measurement of the residual protein A. From these data, we calculated the distribution coefficient of the hMab and the residual protein A as a function of salt concentration. The optimal salt concentration of stepwise elution to reduce the residual protein A from the hMab was determined based on the relationship between the distribution coefficient and the salt concentration. Using the optimized condition, we successfully performed the separation, resulting in high recovery of hMab and the elimination of residual protein A.

Timescale dependence of environmental controls on methane efflux from Poyang Hu, China

NASA Astrophysics Data System (ADS)

Liu, Lixiang; Xu, Ming; Li, Renqiang; Shao, Rui

2017-04-01

Lakes are an important natural source of CH4 to the atmosphere. However, the multi-seasonal CH4 efflux from lakes has been rarely studied. In this study, the CH4 efflux from Poyang Hu, the largest freshwater lake in China, was measured monthly over a 4-year period by using the floating-chamber technique. The mean annual CH4 efflux throughout the 4 years was 0.54 mmol m-2 day-1, ranging from 0.47 to 0.60 mmol m-2 day-1. The CH4 efflux had a high seasonal variation with an average summer (June to August) efflux of 1.34 mmol m-2 day-1 and winter (December to February) efflux of merely 0.18 mmol m-2 day-1. The efflux showed no apparent diel pattern, although most of the peak effluxes appeared in the late morning, from 10:00 to 12:00 CST (GMT + 8). Multivariate stepwise regression on a seasonal scale showed that environmental factors, such as sediment temperature, sediment total nitrogen content, dissolved oxygen, and total phosphorus content in the water, mainly regulated the CH4 efflux. However, the CH4 efflux only showed a strong positive linear correlation with wind speed within 1 day on a bihourly scale in the multivariate regression analyses but almost no correlation with wind speed on diurnal and seasonal scales.

Application of near-infrared spectroscopy for the rapid quality assessment of Radix Paeoniae Rubra

NASA Astrophysics Data System (ADS)

Zhan, Hao; Fang, Jing; Tang, Liying; Yang, Hongjun; Li, Hua; Wang, Zhuju; Yang, Bin; Wu, Hongwei; Fu, Meihong

2017-08-01

Near-infrared (NIR) spectroscopy with multivariate analysis was used to quantify gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra, and the feasibility to classify the samples originating from different areas was investigated. A new high-performance liquid chromatography method was developed and validated to analyze gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra as the reference. Partial least squares (PLS), principal component regression (PCR), and stepwise multivariate linear regression (SMLR) were performed to calibrate the regression model. Different data pretreatments such as derivatives (1st and 2nd), multiplicative scatter correction, standard normal variate, Savitzky-Golay filter, and Norris derivative filter were applied to remove the systematic errors. The performance of the model was evaluated according to the root mean square of calibration (RMSEC), root mean square error of prediction (RMSEP), root mean square error of cross-validation (RMSECV), and correlation coefficient (r). The results show that compared to PCR and SMLR, PLS had a lower RMSEC, RMSECV, and RMSEP and higher r for all the four analytes. PLS coupled with proper pretreatments showed good performance in both the fitting and predicting results. Furthermore, the original areas of Radix Paeoniae Rubra samples were partly distinguished by principal component analysis. This study shows that NIR with PLS is a reliable, inexpensive, and rapid tool for the quality assessment of Radix Paeoniae Rubra.

Controlled loading of cryoprotectants (CPAs) to oocyte with linear and complex CPA profiles on a microfluidic platform.

PubMed

Heo, Yun Seok; Lee, Ho-Joon; Hassell, Bryan A; Irimia, Daniel; Toth, Thomas L; Elmoazzen, Heidi; Toner, Mehmet

2011-10-21

Oocyte cryopreservation has become an essential tool in the treatment of infertility by preserving oocytes for women undergoing chemotherapy. However, despite recent advances, pregnancy rates from all cryopreserved oocytes remain low. The inevitable use of the cryoprotectants (CPAs) during preservation affects the viability of the preserved oocytes and pregnancy rates either through CPA toxicity or osmotic injury. Current protocols attempt to reduce CPA toxicity by minimizing CPA concentrations, or by minimizing the volume changes via the step-wise addition of CPAs to the cells. Although the step-wise addition decreases osmotic shock to oocytes, it unfortunately increases toxic injuries due to the long exposure times to CPAs. To address limitations of current protocols and to rationally design protocols that minimize the exposure to CPAs, we developed a microfluidic device for the quantitative measurements of oocyte volume during various CPA loading protocols. We spatially secured a single oocyte on the microfluidic device, created precisely controlled continuous CPA profiles (step-wise, linear and complex) for the addition of CPAs to the oocyte and measured the oocyte volumetric response to each profile. With both linear and complex profiles, we were able to load 1.5 M propanediol to oocytes in less than 15 min and with a volumetric change of less than 10%. Thus, we believe this single oocyte analysis technology will eventually help future advances in assisted reproductive technologies and fertility preservation.

Feature selection and recognition from nonspecific volatile profiles for discrimination of apple juices according to variety and geographical origin.

PubMed

Guo, Jing; Yue, Tianli; Yuan, Yahong

2012-10-01

Apple juice is a complex mixture of volatile and nonvolatile components. To develop discrimination models on the basis of the volatile composition for an efficient classification of apple juices according to apple variety and geographical origin, chromatography volatile profiles of 50 apple juice samples belonging to 6 varieties and from 5 counties of Shaanxi (China) were obtained by headspace solid-phase microextraction coupled with gas chromatography. The volatile profiles were processed as continuous and nonspecific signals through multivariate analysis techniques. Different preprocessing methods were applied to raw chromatographic data. The blind chemometric analysis of the preprocessed chromatographic profiles was carried out. Stepwise linear discriminant analysis (SLDA) revealed satisfactory discriminations of apple juices according to variety and geographical origin, provided respectively 100% and 89.8% success rate in terms of prediction ability. Finally, the discriminant volatile compounds selected by SLDA were identified by gas chromatography-mass spectrometry. The proposed strategy was able to verify the variety and geographical origin of apple juices involving only a reduced number of discriminate retention times selected by the stepwise procedure. This result encourages the similar procedures to be considered in quality control of apple juices. This work presented a method for an efficient discrimination of apple juices according to apple variety and geographical origin using HS-SPME-GC-MS together with chemometric tools. Discrimination models developed could help to achieve greater control over the quality of the juice and to detect possible adulteration of the product. © 2012 Institute of Food Technologists®

Multivariate Strategies in Functional Magnetic Resonance Imaging

ERIC Educational Resources Information Center

Hansen, Lars Kai

2007-01-01

We discuss aspects of multivariate fMRI modeling, including the statistical evaluation of multivariate models and means for dimensional reduction. In a case study we analyze linear and non-linear dimensional reduction tools in the context of a "mind reading" predictive multivariate fMRI model.

Advancing a Model-Validated Statistical Method for Decomposing the Key Oceanic Drivers of Regional Climate: Focus on Northern and Tropical African Climate Variability in the Community Earth System Model (CESM)

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

Wang, Fuyao; Yu, Yan; Notaro, Michael

This study advances the practicality and stability of the traditional multivariate statistical method, generalized equilibrium feedback assessment (GEFA), for decomposing the key oceanic drivers of regional atmospheric variability, especially when available data records are short. An advanced stepwise GEFA methodology is introduced, in which unimportant forcings within the forcing matrix are eliminated through stepwise selection. Method validation of stepwise GEFA is performed using the CESM, with a focused application to northern and tropical Africa (NTA). First, a statistical assessment of the atmospheric response to each primary oceanic forcing is carried out by applying stepwise GEFA to a fully coupled controlmore » run. Then, a dynamical assessment of the atmospheric response to individual oceanic forcings is performed through ensemble experiments by imposing sea surface temperature anomalies over focal ocean basins. Finally, to quantify the reliability of stepwise GEFA, the statistical assessment is evaluated against the dynamical assessment in terms of four metrics: the percentage of grid cells with consistent response sign, the spatial correlation of atmospheric response patterns, the area-averaged seasonal cycle of response magnitude, and consistency in associated mechanisms between assessments. In CESM, tropical modes, namely El Niño–Southern Oscillation and the tropical Indian Ocean Basin, tropical Indian Ocean dipole, and tropical Atlantic Niño modes, are the dominant oceanic controls of NTA climate. In complementary studies, stepwise GEFA is validated in terms of isolating terrestrial forcings on the atmosphere, and observed oceanic and terrestrial drivers of NTA climate are extracted to establish an observational benchmark for subsequent coupled model evaluation and development of process-based weights for regional climate projections.« less

Advancing a Model-Validated Statistical Method for Decomposing the Key Oceanic Drivers of Regional Climate: Focus on Northern and Tropical African Climate Variability in the Community Earth System Model (CESM)

DOE PAGES

Wang, Fuyao; Yu, Yan; Notaro, Michael; ...

2017-09-27

This study advances the practicality and stability of the traditional multivariate statistical method, generalized equilibrium feedback assessment (GEFA), for decomposing the key oceanic drivers of regional atmospheric variability, especially when available data records are short. An advanced stepwise GEFA methodology is introduced, in which unimportant forcings within the forcing matrix are eliminated through stepwise selection. Method validation of stepwise GEFA is performed using the CESM, with a focused application to northern and tropical Africa (NTA). First, a statistical assessment of the atmospheric response to each primary oceanic forcing is carried out by applying stepwise GEFA to a fully coupled controlmore » run. Then, a dynamical assessment of the atmospheric response to individual oceanic forcings is performed through ensemble experiments by imposing sea surface temperature anomalies over focal ocean basins. Finally, to quantify the reliability of stepwise GEFA, the statistical assessment is evaluated against the dynamical assessment in terms of four metrics: the percentage of grid cells with consistent response sign, the spatial correlation of atmospheric response patterns, the area-averaged seasonal cycle of response magnitude, and consistency in associated mechanisms between assessments. In CESM, tropical modes, namely El Niño–Southern Oscillation and the tropical Indian Ocean Basin, tropical Indian Ocean dipole, and tropical Atlantic Niño modes, are the dominant oceanic controls of NTA climate. In complementary studies, stepwise GEFA is validated in terms of isolating terrestrial forcings on the atmosphere, and observed oceanic and terrestrial drivers of NTA climate are extracted to establish an observational benchmark for subsequent coupled model evaluation and development of process-based weights for regional climate projections.« less

Retro-regression--another important multivariate regression improvement.

PubMed

Randić, M

2001-01-01

We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

Impact of “Sick” and “Recovery” Roles on Brain Injury Rehabilitation Outcomes

PubMed Central

Barclay, David A.

2012-01-01

This study utilizes a multivariate, correlational, expost facto research design to examine Parsons' “sick role” as a dynamic, time-sensitive process of “sick role” and “recovery role” and the impact of this process on goal attainment (H1) and psychosocial distress (H2) of adult survivors of acquired brain injury. Measures used include the Brief Symptom Inventory-18, a Goal Attainment Scale, and an original instrument to measure sick role process. 60 survivors of ABI enrolled in community reentry rehabilitation participated. Stepwise regression analyses did not fully support the multivariate hypotheses. Two models emerged from the stepwise analyses. Goal attainment, gender, and postrehab responsibilities accounted for 40% of the shared variance of psychosocial distress. Anxiety and depression accounted for 22% of the shared variance of goal attainment with anxiety contributing to the majority of the explained variance. Bivariate analysis found sick role variables, anxiety, somatization, depression, gender, and goal attainment as significant. The study has implications for ABI rehabilitation in placing greater emphasis on sick role processes, anxiety, gender, and goal attainment in guiding program planning and future research with survivors of ABI. PMID:23119164

A stepwise regression tree for nonlinear approximation: applications to estimating subpixel land cover

USGS Publications Warehouse

Huang, C.; Townshend, J.R.G.

2003-01-01

A stepwise regression tree (SRT) algorithm was developed for approximating complex nonlinear relationships. Based on the regression tree of Breiman et al . (BRT) and a stepwise linear regression (SLR) method, this algorithm represents an improvement over SLR in that it can approximate nonlinear relationships and over BRT in that it gives more realistic predictions. The applicability of this method to estimating subpixel forest was demonstrated using three test data sets, on all of which it gave more accurate predictions than SLR and BRT. SRT also generated more compact trees and performed better than or at least as well as BRT at all 10 equal forest proportion interval ranging from 0 to 100%. This method is appealing to estimating subpixel land cover over large areas.

A method for the selection of a functional form for a thermodynamic equation of state using weighted linear least squares stepwise regression

NASA Technical Reports Server (NTRS)

Jacobsen, R. T.; Stewart, R. B.; Crain, R. W., Jr.; Rose, G. L.; Myers, A. F.

1976-01-01

A method was developed for establishing a rational choice of the terms to be included in an equation of state with a large number of adjustable coefficients. The methods presented were developed for use in the determination of an equation of state for oxygen and nitrogen. However, a general application of the methods is possible in studies involving the determination of an optimum polynomial equation for fitting a large number of data points. The data considered in the least squares problem are experimental thermodynamic pressure-density-temperature data. Attention is given to a description of stepwise multiple regression and the use of stepwise regression in the determination of an equation of state for oxygen and nitrogen.

Differentiation of Chinese rice wines from different wineries based on mineral elemental fingerprinting.

PubMed

Shen, Fei; Wu, Jian; Ying, Yibin; Li, Bobin; Jiang, Tao

2013-12-15

Discrimination of Chinese rice wines from three well-known wineries ("Guyuelongshan", "Kuaijishan", and "Pagoda") in China has been carried out according to mineral element contents in this study. Nineteen macro and trace mineral elements (Na, Mg, Al, K, Ca, Mn, Fe, Cu, Zn, V, Cr, Co, Ni, As, Se, Mo, Cd, Ba and Pb) were determined by inductively coupled plasma mass spectrometry (ICP-MS) in 117 samples. Then the experimental data were subjected to analysis of variance (ANOVA) and principal component analysis (PCA) to reveal significant differences and potential patterns between samples. Stepwise linear discriminant analysis (LDA) and partial least square discriminant analysis (PLS-DA) were applied to develop classification models and achieved correct classified rates of 100% and 97.4% for the prediction sample set, respectively. The discrimination could be attributed to different raw materials (mainly water) and elaboration processes employed. The results indicate that the element compositions combined with multivariate analysis can be used as fingerprinting techniques to protect prestigious wineries and enable the authenticity of Chinese rice wine. Copyright © 2013 Elsevier Ltd. All rights reserved.

Using foreground/background analysis to determine leaf and canopy chemistry

NASA Technical Reports Server (NTRS)

Pinzon, J. E.; Ustin, S. L.; Hart, Q. J.; Jacquemoud, S.; Smith, M. O.

1995-01-01

Spectral Mixture Analysis (SMA) has become a well established procedure for analyzing imaging spectrometry data, however, the technique is relatively insensitive to minor sources of spectral variation (e.g., discriminating stressed from unstressed vegetation and variations in canopy chemistry). Other statistical approaches have been tried e.g., stepwise multiple linear regression analysis to predict canopy chemistry. Grossman et al. reported that SMLR is sensitive to measurement error and that the prediction of minor chemical components are not independent of patterns observed in more dominant spectral components like water. Further, they observed that the relationships were strongly dependent on the mode of expressing reflectance (R, -log R) and whether chemistry was expressed on a weight (g/g) or are basis (g/sq m). Thus, alternative multivariate techniques need to be examined. Smith et al. reported a revised SMA that they termed Foreground/Background Analysis (FBA) that permits directing the analysis along any axis of variance by identifying vectors through the n-dimensional spectral volume orthonormal to each other. Here, we report an application of the FBA technique for the detection of canopy chemistry using a modified form of the analysis.

A statistical model for Windstorm Variability over the British Isles based on Large-scale Atmospheric and Oceanic Mechanisms

NASA Astrophysics Data System (ADS)

Kirchner-Bossi, Nicolas; Befort, Daniel J.; Wild, Simon B.; Ulbrich, Uwe; Leckebusch, Gregor C.

2016-04-01

Time-clustered winter storms are responsible for a majority of the wind-induced losses in Europe. Over last years, different atmospheric and oceanic large-scale mechanisms as the North Atlantic Oscillation (NAO) or the Meridional Overturning Circulation (MOC) have been proven to drive some significant portion of the windstorm variability over Europe. In this work we systematically investigate the influence of different large-scale natural variability modes: more than 20 indices related to those mechanisms with proven or potential influence on the windstorm frequency variability over Europe - mostly SST- or pressure-based - are derived by means of ECMWF ERA-20C reanalysis during the last century (1902-2009), and compared to the windstorm variability for the European winter (DJF). Windstorms are defined and tracked as in Leckebusch et al. (2008). The derived indices are then employed to develop a statistical procedure including a stepwise Multiple Linear Regression (MLR) and an Artificial Neural Network (ANN), aiming to hindcast the inter-annual (DJF) regional windstorm frequency variability in a case study for the British Isles. This case study reveals 13 indices with a statistically significant coupling with seasonal windstorm counts. The Scandinavian Pattern (SCA) showed the strongest correlation (0.61), followed by the NAO (0.48) and the Polar/Eurasia Pattern (0.46). The obtained indices (standard-normalised) are selected as predictors for a windstorm variability hindcast model applied for the British Isles. First, a stepwise linear regression is performed, to identify which mechanisms can explain windstorm variability best. Finally, the indices retained by the stepwise regression are used to develop a multlayer perceptron-based ANN that hindcasted seasonal windstorm frequency and clustering. Eight indices (SCA, NAO, EA, PDO, W.NAtl.SST, AMO (unsmoothed), EA/WR and Trop.N.Atl SST) are retained by the stepwise regression. Among them, SCA showed the highest linear coefficient, followed by SST in western Atlantic, AMO and NAO. The explanatory regression model (considering all time steps) provided a Coefficient of Determination (R^2) of 0.75. A predictive version of the linear model applying a leave-one-out cross-validation (LOOCV) shows an R2 of 0.56 and a relative RMSE of 4.67 counts/season. An ANN-based nonlinear hindcast model for the seasonal windstorm frequency is developed with the aim to improve the stepwise hindcast ability and thus better predict a time-clustered season over the case study. A 7 node-hidden layer perceptron is set, and the LOOCV procedure reveals a R2 of 0.71. In comparison to the stepwise MLR the RMSE is reduced a 20%. This work shows that for the British Isles case study, most of the interannual variability can be explained by certain large-scale mechanisms, considering also nonlinear effects (ANN). This allows to discern a time-clustered season from a non-clustered one - a key issue for applications e.g., in the (re)insurance industry.

Factors contributing to tooth loss among the elderly: A cross sectional study.

PubMed

Natto, Zuhair S; Aladmawy, Majdi; Alasqah, Mohammed; Papas, Athena

2014-12-01

The present study evaluates the influence of several demographic, health, personal, and clinical factors on the number of missing teeth in old age sample. The number of patients included was 259; they received a full mouth examination and answered a questionnaire provided by one examiner. All the variables related to teeth loss based on the literature were included. These variables focused on age, gender, race, marital status, clinical attachment level, pocket depth, year of smoking, number of cigarettes smoked per day, number of medications, root decay, coronal decay, health status, and year of education. Statistical analysis involved stepwise multivariate linear regression. Teeth loss was statistically associated with clinical attachment level (CAL)(p value 0.0001), pocket depth (PD) (0.0007) and education level (0.0048). When smoking was included in the model, age was significantly associated with teeth loss (0.0037). At least one of these four factors was also related to teeth loss in several specific groups such as diabetes mellitus, male, and White. The multiple linear regressions for all the proposed variables showed that they contributed to teeth loss by about 23%. It can be concluded that less education or increased clinical attachment level loss may increase number of missing teeth. Additionally, age may cause teeth loss in the presence of smoking. Copyright © 2014. Published by Elsevier B.V.

Predictors of cervical lordosis loss after laminoplasty in patients with cervical spondylotic myelopathy.

PubMed

Zhang, Jing Tao; Li, Jia Qi; Niu, Rui Jie; Liu, Zhao; Tong, Tong; Shen, Yong

2017-04-01

To determine whether radiological, clinical, and demographic findings in patients with cervical spondylotic myelopathy (CSM) were independently associated with loss of cervical lordosis (LCL) after laminoplasty. The prospective study included 41 consecutive patients who underwent laminoplasty for CSM. The difference in C2-7 Cobb angle between the postoperative and preoperative films was used to evaluate change in cervical alignment. Age, sex, body mass index (BMI), smoking history, preoperative C2-7 Cobb angle, T1 slope, C2-7 range of motion (C2-7 ROM), C2-7 sagittal vertical axis (C2-7 SVA), and cephalad vertebral level undergoing laminoplasty (CVLL) were assessed. Data were analyzed using Pearson and Spearman correlation test, and univariate and stepwise multivariate linear regression. T1 slope, C2-7 SVA, and CVLL significantly correlated with LCL (P < 0.001), whereas age, BMI, and preoperative C2-7 Cobb angle did not. In multiple linear regression analysis, higher T1 slope (B = 0.351, P = 0.037), greater C2-7 SVA (B = 0.393, P < 0.001), and starting laminoplasty at C4 level (B = - 7.038, P < 0.001) were significantly associated with higher postoperative LCL. Cervical alignment was compromised after laminoplasty in patients with CSM, and the degree of LCL was associated with preoperative T1 slope, C2-7 SVA, and CVLL.

Delineating chalk sand distribution of Ekofisk formation using probabilistic neural network (PNN) and stepwise regression (SWR): Case study Danish North Sea field

NASA Astrophysics Data System (ADS)

Haris, A.; Nafian, M.; Riyanto, A.

2017-07-01

Danish North Sea Fields consist of several formations (Ekofisk, Tor, and Cromer Knoll) that was started from the age of Paleocene to Miocene. In this study, the integration of seismic and well log data set is carried out to determine the chalk sand distribution in the Danish North Sea field. The integration of seismic and well log data set is performed by using the seismic inversion analysis and seismic multi-attribute. The seismic inversion algorithm, which is used to derive acoustic impedance (AI), is model-based technique. The derived AI is then used as external attributes for the input of multi-attribute analysis. Moreover, the multi-attribute analysis is used to generate the linear and non-linear transformation of among well log properties. In the case of the linear model, selected transformation is conducted by weighting step-wise linear regression (SWR), while for the non-linear model is performed by using probabilistic neural networks (PNN). The estimated porosity, which is resulted by PNN shows better suited to the well log data compared with the results of SWR. This result can be understood since PNN perform non-linear regression so that the relationship between the attribute data and predicted log data can be optimized. The distribution of chalk sand has been successfully identified and characterized by porosity value ranging from 23% up to 30%.

Which Frail Older People Are Dehydrated? The UK DRIE Study

PubMed Central

Bunn, Diane K.; Downing, Alice; Jimoh, Florence O.; Groves, Joyce; Free, Carol; Cowap, Vicky; Potter, John F.; Hunter, Paul R.; Shepstone, Lee

2016-01-01

Background: Water-loss dehydration in older people is associated with increased mortality and disability. We aimed to assess the prevalence of dehydration in older people living in UK long-term care and associated cognitive, functional, and health characteristics. Methods: The Dehydration Recognition In our Elders (DRIE) cohort study included people aged 65 or older living in long-term care without heart or renal failure. In a cross-sectional baseline analysis, we assessed serum osmolality, previously suggested dehydration risk factors, general health, markers of continence, cognitive and functional health, nutrition status, and medications. Univariate linear regression was used to assess relationships between participant characteristics and serum osmolality, then associated characteristics entered into stepwise backwards multivariate linear regression. Results: DRIE included 188 residents (mean age 86 years, 66% women) of whom 20% were dehydrated (serum osmolality >300 mOsm/kg). Linear and logistic regression suggested that renal, cognitive, and diabetic status were consistently associated with serum osmolality and odds of dehydration, while potassium-sparing diuretics, sex, number of recent health contacts, and bladder incontinence were sometimes associated. Thirst was not associated with hydration status. Conclusions: DRIE found high prevalence of dehydration in older people living in UK long-term care, reinforcing the proposed association between cognitive and renal function and hydration. Dehydration is associated with increased mortality and disability in older people, but trials to assess effects of interventions to support healthy fluid intakes in older people living in residential care are needed to enable us to formally assess causal direction and any health benefits of increasing fluid intakes. PMID:26553658

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.

Correlation of P-wave dispersion with insulin sensitivity in obese adolescents.

PubMed

Sert, Ahmet; Aslan, Eyup; Buyukınan, Muammer; Pirgon, Ozgur

2017-03-01

P-wave dispersion is a new and simple electrocardiographic marker that has been reported to be associated with inhomogeneous and discontinuous propagation of sinus impulses. In the present study, we evaluated P-wave dispersion in obese adolescents and investigated the relationship between P-wave dispersion, cardiovascular risk factors, and echocardiographic parameters. We carried out a case-control study comparing 150 obese adolescents and 50 healthy controls. Maximum and minimum P-wave durations were measured using a 12-lead surface electrocardiogram, and P-wave dispersion was calculated as the difference between these two measures. Echocardiographic examination was also performed for each subject. Multivariate linear regression analysis with stepwise variable selection was used to evaluate parameters associated with increased P-wave dispersion in obese subjects. Maximum P-wave duration and P-wave dispersion were significantly higher in obese adolescents than control subjects (143±19 ms versus 117±20 ms and 49±15 ms versus 29±9 ms, p<0.0001 for both). P-wave dispersion was positively correlated with body mass index, waist and hip circumferences, systolic and diastolic blood pressures, total cholesterol, serum levels of low-density lipoprotein cholesterol, triglycerides, glucose, and insulin, homoeostasis model assessment for insulin resistance score, left ventricular mass, and left atrial dimension. P-wave dispersion was negatively correlated with high-density lipoprotein cholesterol levels. By multiple stepwise regression analysis, left atrial dimension (β: 0.252, p=0.008) and homoeostasis model assessment for insulin resistance (β: 0.205; p=0.009) were independently associated with increased P-wave dispersion in obese adolescents. Insulin resistance is a significant, independent predictor of P-wave dispersion in obese adolescents.

Atherosclerosis is associated with erectile function and lower urinary tract symptoms, especially nocturia, in middle-aged men.

PubMed

Tsujimura, Akira; Hiramatsu, Ippei; Aoki, Yusuke; Shimoyama, Hirofumi; Mizuno, Taiki; Nozaki, Taiji; Shirai, Masato; Kobayashi, Kazuhiro; Kumamoto, Yoshiaki; Horie, Shigeo

2017-06-01

Atherosclerosis is a systematic disease in which plaque builds up inside the arteries that can lead to serious problems related to quality of life (QOL). Lower urinary tract symptoms (LUTS), erectile dysfunction (ED), and late-onset hypogonadism (LOH) are highly prevalent in aging men and are significantly associated with a reduced QOL. However, few questionnaire-based studies have fully examined the relation between atherosclerosis and several urological symptoms. The study comprised 303 outpatients who visited our clinic with symptoms of LOH. Several factors influencing atherosclerosis, including serum concentrations of triglyceride, fasting blood sugar, and total testosterone measured by radioimmunoassay, were investigated. We also measured brachial-ankle pulse wave velocity (baPWV) and assessed symptoms by specific questionnaires, including the Sexual Health Inventory for Men (SHIM), Erection Hardness Score (EHS), International Prostate Symptom Score (IPSS), QOL index, and Aging Male Symptoms rating scale (AMS). Stepwise associations between the ratio of measured/age standard baPWV and clinical factors including laboratory data and the scores of the questionnaires were compared using the Jonckheere-Terpstra test for trend. The associations between the ratio of measured/age standard baPWV and each IPSS score were assessed in a multivariate linear regression model after adjustment for serum triglyceride, fasting blood sugar, and total testosterone. Regarding ED, a higher level of the ratio of measured/age standard baPWV was associated with a lower EHS, whereas no association was found with SHIM. Regarding LUTS, a higher ratio of measured/age standard baPWV was associated with a higher IPSS and QOL index. However, there was no statistically significant difference between the ratio of measured/age standard baPWV and AMS. A multivariate linear regression model showed only nocturia to be associated with the ratio of measured/age standard baPWV for each IPSS score. Atherosclerosis is associated with erectile function and LUTS, especially nocturia.

Word Problems: A "Meme" for Our Times.

ERIC Educational Resources Information Center

Leamnson, Robert N.

1996-01-01

Discusses a novel approach to word problems that involves linear relationships between variables. Argues that working stepwise through intermediates is the way our minds actually work and therefore this should be used in solving word problems. (JRH)

Estimating extent of mortality associated with the Douglas-fir beetle in the Central and Northern Rockies

Treesearch

Jose F. Negron; Willis C. Schaupp; Kenneth E. Gibson; John Anhold; Dawn Hansen; Ralph Thier; Phil Mocettini

1999-01-01

Data collected from Douglas-fir stands infected by the Douglas-fir beetle in Wyoming, Montana, Idaho, and Utah, were used to develop models to estimate amount of mortality in terms of basal area killed. Models were built using stepwise linear regression and regression tree approaches. Linear regression models using initial Douglas-fir basal area were built for all...

Identification of International Classification of Functioning, Disability and Health categories for patients with peripheral arterial disease.

PubMed

Vyskocil, Erich; Gruther, Wolfgang; Steiner, Irene; Schuhfried, Othmar

2014-07-01

Disease-specific categories of the International Classification of Functioning, Disability and Health have not yet been described for patients with chronic peripheral arterial obstructive disease (PAD). The authors examined the relationship between the categories of the Brief Core Sets for ischemic heart diseases with the Peripheral Artery Questionnaire and the ankle-brachial index to determine which International Classification of Functioning, Disability and Health categories are most relevant for patients with PAD. This is a retrospective cohort study including 77 patients with verified PAD. Statistical analyses of the relationship between International Classification of Functioning, Disability and Health categories as independent variables and the endpoints Peripheral Artery Questionnaire or ankle-brachial index were carried out by simple and stepwise linear regression models adjusting for age, sex, and leg (left vs. right). The stepwise linear regression model with the ankle-brachial index as dependent variable revealed a significant effect of the variables blood vessel functions and muscle endurance functions. Calculating a stepwise linear regression model with the Peripheral Artery Questionnaire as dependent variable, a significant effect of age, emotional functions, energy and drive functions, carrying out daily routine, as well as walking could be observed. This study identifies International Classification of Functioning, Disability and Health categories in the Brief Core Sets for ischemic heart diseases that show a significant effect on the ankle-brachial index and the Peripheral Artery Questionnaire score in patients with PAD. These categories provide fundamental information on functioning of patients with PAD and patient-centered outcomes for rehabilitation interventions.

Predictive factors for postoperative visual function of primary chronic rhegmatogenous retinal detachment after scleral buckling.

PubMed

Fang, Wei; Li, Jiu-Ke; Jin, Xiao-Hong; Dai, Yuan-Min; Li, Yu-Min

2016-01-01

To evaluate predictive factors for postoperative visual function of primary chronic rhegmatgenous retinal detachment (RRD) after sclera buckling (SB). Totally 48 patients (51 eyes) with primary chronic RRD were included in this prospective interventional clinical cases study, which underwent SB alone from June 2008 to December 2014. Age, sex, symptoms duration, detached extension, retinal hole position, size, type, fovea on/off, proliferative vitreoretinopathy (PVR), posterior vitreous detachment (PVD), baseline best corrected visual acuity (BCVA), operative duration, follow up duration, final BCVA were measured. Pearson correlation analysis, Spearman correlation analysis and multivariate linear stepwise regression were used to confirm predictive factors for better final visual acuity. Student's t-test, Wilcoxon two-sample test, Chi-square test and logistic stepwise regression were used to confirm predictive factors for better vision improvement. Baseline BCVA was 0.8313±0.6911 logMAR and final BCVA was 0.4761±0.4956 logMAR. Primary surgical success rate was 92.16% (47/51). Correlation analyses revealed shorter symptoms duration (r=0.3850, P=0.0053), less detached area (r=0.5489, P<0.0001), fovea (r=0.4605, P=0.0007), no PVR (r=0.3138, P=0.0250), better baseline BCVA (r=0.7291, P<0.0001), shorter operative duration (r=0.3233, P=0.0207) and longer follow up (r=-0.3358, P=0.0160) were related with better final BCVA, while independent predictive factors were better baseline BCVA [partial R-square (PR(2))=0.5316, P<0.0001], shorter symptoms duration (PR(2)=0.0609, P=0.0101), longer follow up duration (PR(2)=0.0278, P=0.0477) and shorter operative duration (PR(2)=0.0338, P=0.0350). Patients with vision improvement took up 49.02% (25/51). Univariate and multivariate analyses both revealed predictive factors for better vision improvement were better baseline vision [odds ratio (OR) =50.369, P=0.0041] and longer follow up duration (OR=1.144, P=0.0067). Independent predictive factors for better visual outcome of primary chronic RRD after SB are better baseline BCVA, shorter symptoms duration, shorter operative duration and longer follow up duration, while independent predictive factors for better vision improvement after operation are better baseline vision and longer follow up duration.

Linear models of coregionalization for multivariate lattice data: Order-dependent and order-free cMCARs.

PubMed

MacNab, Ying C

2016-08-01

This paper concerns with multivariate conditional autoregressive models defined by linear combination of independent or correlated underlying spatial processes. Known as linear models of coregionalization, the method offers a systematic and unified approach for formulating multivariate extensions to a broad range of univariate conditional autoregressive models. The resulting multivariate spatial models represent classes of coregionalized multivariate conditional autoregressive models that enable flexible modelling of multivariate spatial interactions, yielding coregionalization models with symmetric or asymmetric cross-covariances of different spatial variation and smoothness. In the context of multivariate disease mapping, for example, they facilitate borrowing strength both over space and cross variables, allowing for more flexible multivariate spatial smoothing. Specifically, we present a broadened coregionalization framework to include order-dependent, order-free, and order-robust multivariate models; a new class of order-free coregionalized multivariate conditional autoregressives is introduced. We tackle computational challenges and present solutions that are integral for Bayesian analysis of these models. We also discuss two ways of computing deviance information criterion for comparison among competing hierarchical models with or without unidentifiable prior parameters. The models and related methodology are developed in the broad context of modelling multivariate data on spatial lattice and illustrated in the context of multivariate disease mapping. The coregionalization framework and related methods also present a general approach for building spatially structured cross-covariance functions for multivariate geostatistics. © The Author(s) 2016.

Extendable nickel complex tapes that reach NIR absorptions.

PubMed

Audi, Hassib; Chen, Zhongrui; Charaf-Eddin, Azzam; D'Aléo, Anthony; Canard, Gabriel; Jacquemin, Denis; Siri, Olivier

2014-12-14

Stepwise synthesis of linear nickel complex oligomer tapes with no need for solid-phase support has been achieved. The control of the length in flat arrays allows a fine-tuning of the absorption properties from the UV to the NIR region.

Which Frail Older People Are Dehydrated? The UK DRIE Study.

PubMed

Hooper, Lee; Bunn, Diane K; Downing, Alice; Jimoh, Florence O; Groves, Joyce; Free, Carol; Cowap, Vicky; Potter, John F; Hunter, Paul R; Shepstone, Lee

2016-10-01

Water-loss dehydration in older people is associated with increased mortality and disability. We aimed to assess the prevalence of dehydration in older people living in UK long-term care and associated cognitive, functional, and health characteristics. The Dehydration Recognition In our Elders (DRIE) cohort study included people aged 65 or older living in long-term care without heart or renal failure. In a cross-sectional baseline analysis, we assessed serum osmolality, previously suggested dehydration risk factors, general health, markers of continence, cognitive and functional health, nutrition status, and medications. Univariate linear regression was used to assess relationships between participant characteristics and serum osmolality, then associated characteristics entered into stepwise backwards multivariate linear regression. DRIE included 188 residents (mean age 86 years, 66% women) of whom 20% were dehydrated (serum osmolality >300 mOsm/kg). Linear and logistic regression suggested that renal, cognitive, and diabetic status were consistently associated with serum osmolality and odds of dehydration, while potassium-sparing diuretics, sex, number of recent health contacts, and bladder incontinence were sometimes associated. Thirst was not associated with hydration status. DRIE found high prevalence of dehydration in older people living in UK long-term care, reinforcing the proposed association between cognitive and renal function and hydration. Dehydration is associated with increased mortality and disability in older people, but trials to assess effects of interventions to support healthy fluid intakes in older people living in residential care are needed to enable us to formally assess causal direction and any health benefits of increasing fluid intakes. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The association between temperature and mortality in tropical middle income Thailand from 1999 to 2008

NASA Astrophysics Data System (ADS)

Tawatsupa, Benjawan; Dear, Keith; Kjellstrom, Tord; Sleigh, Adrian

2014-03-01

We have investigated the association between tropical weather condition and age-sex adjusted death rates (ADR) in Thailand over a 10-year period from 1999 to 2008. Population, mortality, weather and air pollution data were obtained from four national databases. Alternating multivariable fractional polynomial (MFP) regression and stepwise multivariable linear regression analysis were used to sequentially build models of the associations between temperature variable and deaths, adjusted for the effects and interactions of age, sex, weather (6 variables), and air pollution (10 variables). The associations are explored and compared among three seasons (cold, hot and wet months) and four weather zones of Thailand (the North, Northeast, Central, and South regions). We found statistically significant associations between temperature and mortality in Thailand. The maximum temperature is the most important variable in predicting mortality. Overall, the association is nonlinear U-shape and 31 °C is the minimum-mortality temperature in Thailand. The death rates increase when maximum temperature increase with the highest rates in the North and Central during hot months. The final equation used in this study allowed estimation of the impact of a 4 °C increase in temperature as projected for Thailand by 2100; this analysis revealed that the heat-related deaths will increase more than the cold-related deaths avoided in the hot and wet months, and overall the net increase in expected mortality by region ranges from 5 to 13 % unless preventive measures were adopted. Overall, these results are useful for health impact assessment for the present situation and future public health implication of global climate change for tropical Thailand.

Remote sensing of soil organic matter of farmland with hyperspectral image

NASA Astrophysics Data System (ADS)

Gu, Xiaohe; Wang, Lei; Yang, Guijun; Zhang, Liyan

2017-10-01

Monitoring soil organic matter (SOM) of cultivated land quantitively and mastering its spatial change are helpful for fertility adjustment and sustainable development of agriculture. The study aimed to analyze the response between SOM and reflectivity of hyperspectral image with different pixel size and develop the optimal model of estimating SOM with imaging spectral technology. The wavelet transform method was used to analyze the correlation between the hyperspectral reflectivity and SOM. Then the optimal pixel size and sensitive wavelet feature scale were screened to develop the inversion model of SOM. Result showed that wavelet transform of soil hyperspectrum was help to improve the correlation between the wavelet features and SOM. In the visible wavelength range, the susceptible wavelet features of SOM mainly concentrated 460 603 nm. As the wavelength increased, the wavelet scale corresponding correlation coefficient increased maximum and then gradually decreased. In the near infrared wavelength range, the susceptible wavelet features of SOM mainly concentrated 762 882 nm. As the wavelength increased, the wavelet scale gradually decreased. The study developed multivariate model of continuous wavelet transforms by the method of stepwise linear regression (SLR). The CWT-SLR models reached higher accuracies than those of univariate models. With the resampling scale increasing, the accuracies of CWT-SLR models gradually increased, while the determination coefficients (R2) fluctuated from 0.52 to 0.59. The R2 of 5*5 scale reached highest (0.5954), while the RMSE reached lowest (2.41 g/kg). It indicated that multivariate model based on continuous wavelet transform had better ability for estimating SOM than univariate model.

Utility of an Abbreviated Dizziness Questionnaire to Differentiate between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study

PubMed Central

Roland, Lauren T.; Kallogjeri, Dorina; Sinks, Belinda C.; Rauch, Steven D.; Shepard, Neil T.; White, Judith A.; Goebel, Joel A.

2015-01-01

Objective Test performance of a focused dizziness questionnaire’s ability to discriminate between peripheral and non-peripheral causes of vertigo. Study Design Prospective multi-center Setting Four academic centers with experienced balance specialists Patients New dizzy patients Interventions A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Main outcomes Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and non-peripheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. Results 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and non-peripheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central and other causes were considered good as measured by c-indices of 0.75, 0.7 and 0.78, respectively. Conclusions This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from non-peripheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed. PMID:26485598

Utility of an Abbreviated Dizziness Questionnaire to Differentiate Between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study.

PubMed

Roland, Lauren T; Kallogjeri, Dorina; Sinks, Belinda C; Rauch, Steven D; Shepard, Neil T; White, Judith A; Goebel, Joel A

2015-12-01

Test performance of a focused dizziness questionnaire's ability to discriminate between peripheral and nonperipheral causes of vertigo. Prospective multicenter. Four academic centers with experienced balance specialists. New dizzy patients. A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and nonperipheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. In total, 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and nonperipheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central, and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central, and other causes was considered good as measured by c-indices of 0.75, 0.7, and 0.78, respectively. This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from nonperipheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed.

A model for predicting sulcus-to-sulcus diameter in posterior chamber phakic intraocular lens candidates: correlation between ocular biometric parameters.

PubMed

Ghoreishi, Mohammad; Abdi-Shahshahani, Mehdi; Peyman, Alireza; Pourazizi, Mohsen

2018-02-21

The aim of this study was to determine the correlation between ocular biometric parameters and sulcus-to-sulcus (STS) diameter. This was a cross-sectional study of preoperative ocular biometry data of patients who were candidates for phakic intraocular lens (IOL) surgery. Subjects underwent ocular biometry analysis, including refraction error evaluation using an autorefractor and Orbscan topography for white-to-white (WTW) corneal diameter and measurement. Pentacam was used to perform WTW corneal diameter and measurements of minimum and maximum keratometry (K). Measurements of STS and angle-to-angle (ATA) were obtained using a 50-MHz B-mode ultrasound device. Anterior optical coherence tomography was performed for anterior chamber depth measurement. Pearson's correlation test and stepwise linear regression analysis were used to find a model to predict STS. Fifty-eight eyes of 58 patients were enrolled. Mean age ± standard deviation of sample was 28.95 ± 6.04 years. The Pearson's correlation coefficient between STS with WTW, ATA, mean K was 0.383, 0.492, and - 0.353, respectively, which was statistically significant (all P < 0.001). Using stepwise linear regression analysis, there is a statistically significant association between STS with WTW (P = 0.011) and mean K (P = 0.025). The standardized coefficient was 0.323 and - 0.284 for WTW and mean K, respectively. The stepwise linear regression analysis equation was: (STS = 9.549 + 0.518 WTW - 0.083 mean K). Based on our result, given the correlation of STS with WTW and mean K and potential of direct and essay measurement of WTW and mean K, it seems that current IOL sizing protocols could be estimating with WTW and mean K.

Factors associated with self-rated health among North Korean defectors residing in South Korea.

PubMed

Wang, Bo-Ram; Yu, Shieun; Noh, Jin-Won; Kwon, Young Dae

2014-09-26

The number of North Korean refugees entering South Korea has increased recently. The health status of refugees is a significant factor in determining their success in resettlement; therefore, this study examined both the self-rated health status of North Korean defectors who have settled in South Korea and the factors associated with their self-rated health status. This study utilized data gained from face-to-face interviews with 500 North Korean defectors who arrived in South Korea in 2007. The interviews were structured and conducted by 'Yonsei University Research Team for North Korean defectors'. A stepwise multivariable linear regression was performed to determine the factors associated with their self-rated health status. North Korean defectors who were female, elderly, or had low annual household income, disability or chronic diseases reported lower health status. However, self-rated health status was higher among those who had settled in South Korea for 18 months or more, who were satisfied with government support or their current life, and who had experienced more traumatic events in North Korea. Government policies and refugee assistance programs should consider and reflect the factors relevant to the health status of North Korean defectors.

Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects.

PubMed

Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea

2016-01-01

Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms in the future.

Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects

PubMed Central

Kia, Seyed Mostafa; Vega Pons, Sandro; Weisz, Nathan; Passerini, Andrea

2017-01-01

Brain decoding is a popular multivariate approach for hypothesis testing in neuroimaging. Linear classifiers are widely employed in the brain decoding paradigm to discriminate among experimental conditions. Then, the derived linear weights are visualized in the form of multivariate brain maps to further study spatio-temporal patterns of underlying neural activities. It is well known that the brain maps derived from weights of linear classifiers are hard to interpret because of high correlations between predictors, low signal to noise ratios, and the high dimensionality of neuroimaging data. Therefore, improving the interpretability of brain decoding approaches is of primary interest in many neuroimaging studies. Despite extensive studies of this type, at present, there is no formal definition for interpretability of multivariate brain maps. As a consequence, there is no quantitative measure for evaluating the interpretability of different brain decoding methods. In this paper, first, we present a theoretical definition of interpretability in brain decoding; we show that the interpretability of multivariate brain maps can be decomposed into their reproducibility and representativeness. Second, as an application of the proposed definition, we exemplify a heuristic for approximating the interpretability in multivariate analysis of evoked magnetoencephalography (MEG) responses. Third, we propose to combine the approximated interpretability and the generalization performance of the brain decoding into a new multi-objective criterion for model selection. Our results, for the simulated and real MEG data, show that optimizing the hyper-parameters of the regularized linear classifier based on the proposed criterion results in more informative multivariate brain maps. More importantly, the presented definition provides the theoretical background for quantitative evaluation of interpretability, and hence, facilitates the development of more effective brain decoding algorithms in the future. PMID:28167896

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

PubMed

Dinç, Erdal; Ozdemir, Abdil

2005-01-01

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

A rapid learning and dynamic stepwise updating algorithm for flat neural networks and the application to time-series prediction.

PubMed

Chen, C P; Wan, J Z

1999-01-01

A fast learning algorithm is proposed to find an optimal weights of the flat neural networks (especially, the functional-link network). Although the flat networks are used for nonlinear function approximation, they can be formulated as linear systems. Thus, the weights of the networks can be solved easily using a linear least-square method. This formulation makes it easier to update the weights instantly for both a new added pattern and a new added enhancement node. A dynamic stepwise updating algorithm is proposed to update the weights of the system on-the-fly. The model is tested on several time-series data including an infrared laser data set, a chaotic time-series, a monthly flour price data set, and a nonlinear system identification problem. The simulation results are compared to existing models in which more complex architectures and more costly training are needed. The results indicate that the proposed model is very attractive to real-time processes.

Visual Analysis of North Atlantic Hurricane Trends Using Parallel Coordinates and Statistical Techniques

DTIC Science & Technology

2008-07-07

analyzing multivariate data sets. The system was developed using the Java Development Kit (JDK) version 1.5; and it yields interactive performance on a... script and captures output from the MATLAB’s “regress” and “stepwisefit” utilities that perform simple and stepwise regression, respectively. The MATLAB...Statistical Association, vol. 85, no. 411, pp. 664–675, 1990. [9] H. Hauser, F. Ledermann, and H. Doleisch, “ Angular brushing of extended parallel coordinates

Impact of stepwise ablation on the biatrial substrate in patients with persistent atrial fibrillation and heart failure.

PubMed

Jones, David G; Haldar, Shouvik K; Jarman, Julian W E; Johar, Sofian; Hussain, Wajid; Markides, Vias; Wong, Tom

2013-08-01

Ablation of persistent atrial fibrillation can be challenging, often involving not only pulmonary vein isolation (PVI) but also additional linear lesions and ablation of complex fractionated electrograms (CFE). We examined the impact of stepwise ablation on a human model of advanced atrial substrate of persistent atrial fibrillation in heart failure. In 30 patients with persistent atrial fibrillation and left ventricular ejection fraction ≤35%, high-density CFE maps were recorded biatrially at baseline, in the left atrium (LA) after PVI and linear lesions (roof and mitral isthmus), and biatrially after LA CFE ablation. Surface area of CFE (mean cycle length ≤120 ms) remote to PVI and linear lesions, defined as CFE area, was reduced after PVI (18.3±12.03 to 10.2±7.1 cm(2); P<0.001) and again after linear lesions (7.7±6.5 cm(2); P=0.006). Complete mitral isthmus block predicted greater CFE reduction (P=0.02). Right atrial CFE area was reduced by LA ablation, from 25.9±14.1 to 12.9±11.8 cm(2) (P<0.001). Estimated 1-year arrhythmia-free survival was 72% after a single procedure. Incomplete linear lesion block was an independent predictor of arrhythmia recurrence (hazard ratio, 4.69; 95% confidence interval, 1.05-21.06; P=0.04). Remote LA CFE area was progressively reduced following PVI and linear lesions, and LA ablation reduced right atrial CFE area. Reduction of CFE area at sites remote from ablation would suggest either regression of the advanced atrial substrate or that these CFE were functional phenomena. Nevertheless, in an advanced atrial fibrillation substrate, linear lesions after PVI diminished the target area for CFE ablation, and complete lesions resulted in a favorable clinical outcome.

Fixed order dynamic compensation for multivariable linear systems

NASA Technical Reports Server (NTRS)

Kramer, F. S.; Calise, A. J.

1986-01-01

This paper considers the design of fixed order dynamic compensators for multivariable time invariant linear systems, minimizing a linear quadratic performance cost functional. Attention is given to robustness issues in terms of multivariable frequency domain specifications. An output feedback formulation is adopted by suitably augmenting the system description to include the compensator states. Either a controller or observer canonical form is imposed on the compensator description to reduce the number of free parameters to its minimal number. The internal structure of the compensator is prespecified by assigning a set of ascending feedback invariant indices, thus forming a Brunovsky structure for the nominal compensator.

Porphinogen Formation from the Co-Oligomerization of Formaldehyde and Pyrrole: Free Energy Pathways.

PubMed

Kua, Jeremy; Loli, Helen

2017-10-26

We have investigated the nonoxidative stepwise co-oligomerization of formaldehyde and pyrrole to form porphinogen using density functional theory calculations that include free energy corrections. While the addition of formaldehyde to the pyrrole nitrogen is kinetically favored, thermodynamics suggest that this reaction is reversible in aqueous solution. The more thermodynamically favorable addition of formaldehyde to the ortho-carbon of pyrrole begins a stepwise process, forming dipyrromethane via an azafulvene intermediate. Subsequent additions of formaldehyde and pyrrole lead to bilanes (linear tetrapyrroles), which favorably cyclize to form porphinogen. Porphinogen is a precursor to porphin, the simplest unsubstituted porphyrin that could have played a role in primitive metabolism at the origin of life.

MULTIVARIATE LINEAR MIXED MODELS FOR MULTIPLE OUTCOMES. (R824757)

EPA Science Inventory

We propose a multivariate linear mixed (MLMM) for the analysis of multiple outcomes, which generalizes the latent variable model of Sammel and Ryan. The proposed model assumes a flexible correlation structure among the multiple outcomes, and allows a global test of the impact of ...

Electricity Consumption in the Industrial Sector of Jordan: Application of Multivariate Linear Regression and Adaptive Neuro-Fuzzy Techniques

NASA Astrophysics Data System (ADS)

Samhouri, M.; Al-Ghandoor, A.; Fouad, R. H.

2009-08-01

In this study two techniques, for modeling electricity consumption of the Jordanian industrial sector, are presented: (i) multivariate linear regression and (ii) neuro-fuzzy models. Electricity consumption is modeled as function of different variables such as number of establishments, number of employees, electricity tariff, prevailing fuel prices, production outputs, capacity utilizations, and structural effects. It was found that industrial production and capacity utilization are the most important variables that have significant effect on future electrical power demand. The results showed that both the multivariate linear regression and neuro-fuzzy models are generally comparable and can be used adequately to simulate industrial electricity consumption. However, comparison that is based on the square root average squared error of data suggests that the neuro-fuzzy model performs slightly better for future prediction of electricity consumption than the multivariate linear regression model. Such results are in full agreement with similar work, using different methods, for other countries.

A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

PubMed

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga

2006-08-01

A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

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

PubMed

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

2013-05-01

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

Soil sail content estimation in the yellow river delta with satellite hyperspectral data

USGS Publications Warehouse

Weng, Yongling; Gong, Peng; Zhu, Zhi-Liang

2008-01-01

Soil salinization is one of the most common land degradation processes and is a severe environmental hazard. The primary objective of this study is to investigate the potential of predicting salt content in soils with hyperspectral data acquired with EO-1 Hyperion. Both partial least-squares regression (PLSR) and conventional multiple linear regression (MLR), such as stepwise regression (SWR), were tested as the prediction model. PLSR is commonly used to overcome the problem caused by high-dimensional and correlated predictors. Chemical analysis of 95 samples collected from the top layer of soils in the Yellow River delta area shows that salt content was high on average, and the dominant chemicals in the saline soil were NaCl and MgCl2. Multivariate models were established between soil contents and hyperspectral data. Our results indicate that the PLSR technique with laboratory spectral data has a strong prediction capacity. Spectral bands at 1487-1527, 1971-1991, 2032-2092, and 2163-2355 nm possessed large absolute values of regression coefficients, with the largest coefficient at 2203 nm. We obtained a root mean squared error (RMSE) for calibration (with 61 samples) of RMSEC = 0.753 (R2 = 0.893) and a root mean squared error for validation (with 30 samples) of RMSEV = 0.574. The prediction model was applied on a pixel-by-pixel basis to a Hyperion reflectance image to yield a quantitative surface distribution map of soil salt content. The result was validated successfully from 38 sampling points. We obtained an RMSE estimate of 1.037 (R2 = 0.784) for the soil salt content map derived by the PLSR model. The salinity map derived from the SWR model shows that the predicted value is higher than the true value. These results demonstrate that the PLSR method is a more suitable technique than stepwise regression for quantitative estimation of soil salt content in a large area. ?? 2008 CASI.

Trends in anemia management among US hemodialysis patients.

PubMed

Coladonato, Joseph A; Frankenfield, Diane L; Reddan, Donal N; Klassen, Preston S; Szczech, Lynda A; Johnson, Curtis A; Owen, William F

2002-05-01

This study was undertaken to describe the relationship between hematocrit (Hct) and changes in the prescribed dose of erythropoietin (EPO) as well as selected patient and process care measures across annual national samples of hemodialysis patients from 1994 to 1998. This study uses the cohorts identified in the ESRD Core Indicators Project, random samples of 6181, 6241, 6364, 6634, and 7660 patients, stratified by ESRD Networks drawn for each year from 1994 to 1998. Patient demographic and clinical information was collected from October to December for each year. Surrogates of iron stores and patterns of iron and EPO administration were profiled from 1996 to 1998. Multivariable stepwise linear regression analyses were performed to adjust for potential confounding variables and to identify independent variables associated with Hct and EPO dose. Mean Hct and EPO dose increased each year from 31.1 +/- 5.2% to 34.1 +/- 3.7% and from 58.2 +/- 41.8 U/kg to 68.2 +/- 55.0 U/kg, respectively (P = 0.0001). Increasing Hct was positively associated with male gender, more years on dialysis, older age, higher urea reduction ratio and transferrin saturation, prescription of intravenous iron, and lower ferritin and EPO dose in multivariable models (all P = 0.0001). Male gender, older age, diabetes, higher Hct, and increasing weight, urea reduction ration, and transferrin saturation were associated with lower EPO doses (all P < 0.01). Conversely, intravenous EPO and iron were associated with higher prescribed EPO doses (all P = 0.0001). Although increasing Hct is associated with decreasing EPO dose at the patient level, the increase in Hct seen across years among the cohorts of hemodialysis patients in the United States has been associated with increasing doses of EPO at the population level.

Angiogenic and inflammatory biomarkers in mid-pregnancy and small-for-gestational age outcomes in Tanzania

PubMed Central

DARLING, Anne Marie; MCDONALD, Chloe R.; CONROY, Andrea L.; HAYFORD, Kyla T.; RAJWANS, Nimerta; WANG, Molin; ABOUD, Said; URASSA, Willy S.; KAIN, Kevin C.; FAWZI, Wafaie W.

2014-01-01

OBJECTIVE To investigate the relationship between a panel of angiogenic and inflammatory biomarkers measured in mid-pregnancy and small-for-gestational age (SGA) outcomes in sub-Saharan Africa. STUDY DESIGN Concentrations of 18 angiogenic and inflammatory biomarkers were determined in 432 pregnant women in Dar es Salaam, Tanzania who participated in a trial examining the effect of multivitamins on pregnancy outcomes. Infants falling below the 10th percentile of birth weight for gestational age relative to the applied growth standards were considered SGA. Multivariate binomial regression models with the log link function were used to determine the relative risk of SGA associated with increasing quartiles of each biomarker. Stepwise cubic restricted splines were used to test for non-linearity of these associations. Receiver operating curves obtained from multivariate logistic regression models were used to assess the discriminatory capability of selected biomarkers. RESULTS A total of 60 participants (13.9%) gave birth to SGA infants. Compared to those in the first quartile, the risk of SGA was reduced among those in the fourth quartiles of VEGF-A (adjusted risk ratio (RR) 0.38, 95% Confidence Interval (CI), 0.19-0.74), PGF (adjusted RR 0.28, 95% CI, 0.12-0.61), sFlt-1 (adjusted RR 0.48, 95% CI, 0.23-1.01), MCP-1 (adjusted RR 0.48, 95% CI, 0.25-0.92), and Leptin (adjusted RR 0.46, 95% CI, 0.22-0.96) CONCLUSION Our findings provide evidence of altered angiogenic and inflammatory mediators, at mid-pregnancy, in women who went on to deliver small for gestational age infants. PMID:24881826

The association between temperature and mortality in tropical middle income Thailand from 1999 to 2008.

PubMed

Tawatsupa, Benjawan; Dear, Keith; Kjellstrom, Tord; Sleigh, Adrian

2014-03-01

We have investigated the association between tropical weather condition and age-sex adjusted death rates (ADR) in Thailand over a 10-year period from 1999 to 2008. Population, mortality, weather and air pollution data were obtained from four national databases. Alternating multivariable fractional polynomial (MFP) regression and stepwise multivariable linear regression analysis were used to sequentially build models of the associations between temperature variable and deaths, adjusted for the effects and interactions of age, sex, weather (6 variables), and air pollution (10 variables). The associations are explored and compared among three seasons (cold, hot and wet months) and four weather zones of Thailand (the North, Northeast, Central, and South regions). We found statistically significant associations between temperature and mortality in Thailand. The maximum temperature is the most important variable in predicting mortality. Overall, the association is nonlinear U-shape and 31 °C is the minimum-mortality temperature in Thailand. The death rates increase when maximum temperature increase with the highest rates in the North and Central during hot months. The final equation used in this study allowed estimation of the impact of a 4 °C increase in temperature as projected for Thailand by 2100; this analysis revealed that the heat-related deaths will increase more than the cold-related deaths avoided in the hot and wet months, and overall the net increase in expected mortality by region ranges from 5 to 13 % unless preventive measures were adopted. Overall, these results are useful for health impact assessment for the present situation and future public health implication of global climate change for tropical Thailand.

Hyperferritinemia increases the risk of hyperuricemia in HFE-hereditary hemochromatosis.

PubMed

Flais, Jérémy; Bardou-Jacquet, Edouard; Deugnier, Yves; Coiffier, Guillaume; Perdriger, Aleth; Chalès, Gérard; Ropert, Martine; Loréal, Olivier; Guggenbuhl, Pascal

2017-05-01

Hyperuricemia is becoming increasingly frequent in the population, and is known to be sometimes the cause of gout. The impact of uric acid is still not clearly understood, however. The iron metabolism may interact with the uric acid metabolism. The aim of this study was to examine the relationship between the serum uric acid and serum ferritin levels in a cohort of hemochromatosis patients who were homozygous for the HFE p.Cys282Tyr mutation. 738 patients with the HFE gene mutation Cys282Tyr in the homozygous state were included in the study. The variables measured during the initial evaluation were compared in univariate analysis by Student's t test. In multivariate analysis, linear stepwise regression was used. In the group of hyperuricemic patients, ferritinemia was significantly higher than in the group of non-hyperuricemic patients (1576.7±1387.4μg/l vs. 1095.63±1319.24μg/l, P<0.005). With multivariate analysis, only ferritin and BMI independently explained the uricemia (R 2 =0.258) after adjustment for age, glycemia and CRP. The correlation between uricemia and log(ferritin) with partial regression correlation coefficients was 0.307 (P<0.01). The increase in uricemia is associated with the increase in ferritin in a population of patients who were homozygous for the HFE gene mutation p.Cys282Tyr and this independently of factors commonly associated with hyperuricemia. The increase in uric acid associated with hyperferritinemia, could be a response to the visceral toxicity of excess non-transferrin bound iron linked to oxidative stress via the antioxidant properties of uric acid. Copyright © 2016 Société française de rhumatologie. Published by Elsevier SAS. All rights reserved.

Correlation between increased urinary sodium excretion and decreased left ventricular diastolic function in patients with type 2 diabetes mellitus.

PubMed

Kagiyama, Shuntaro; Koga, Tokushi; Kaseda, Shigeru; Ishihara, Shiro; Kawazoe, Nobuyuki; Sadoshima, Seizo; Matsumura, Kiyoshi; Takata, Yutaka; Tsuchihashi, Takuya; Iida, Mitsuo

2009-10-01

Increased salt intake may induce hypertension, lead to cardiac hypertrophy, and exacerbate heart failure. When elderly patients develop heart failure, diastolic dysfunction is often observed, although the ejection fraction has decreased. Diabetes mellitus (DM) is an established risk factor for heart failure. However, little is known about the relationship between cardiac function and urinary sodium excretion (U-Na) in patients with DM. We measured 24-hour U-Na; cardiac function was evaluated directly during coronary catheterization in type 2 DM (n = 46) or non-DM (n = 55) patients with preserved cardiac systolic function (ejection fraction > or = 60%). Cardiac diastolic and systolic function was evaluated as - dp/dt and + dp/dt, respectively. The average of U-Na was 166.6 +/- 61.2 mEq/24 hour (mean +/- SD). In all patients, stepwise multivariate regression analysis revealed that - dp/dt had a negative correlation with serum B-type natriuretic peptide (BNP; beta = - 0.23, P = .021) and U-Na (beta = - 0.24, P = .013). On the other hand, + dp/dt negatively correlated with BNP (beta = - 0.30, P < .001), but did not relate to U-Na. In the DM-patients, stepwise multivariate regression analysis showed that - dp/dt still had a negative correlation with U-Na (beta = - 0.33, P = .025). The results indicated that increased urinary sodium excretion is associated with an impairment of cardiac diastolic function, especially in patients with DM, suggesting that a reduction of salt intake may improve cardiac diastolic function.

Variables Associated with Communicative Participation in People with Multiple Sclerosis: A Regression Analysis

ERIC Educational Resources Information Center

Baylor, Carolyn; Yorkston, Kathryn; Bamer, Alyssa; Britton, Deanna; Amtmann, Dagmar

2010-01-01

Purpose: To explore variables associated with self-reported communicative participation in a sample (n = 498) of community-dwelling adults with multiple sclerosis (MS). Method: A battery of questionnaires was administered online or on paper per participant preference. Data were analyzed using multiple linear backward stepwise regression. The…

Variation in Environmentalism among University Students: Majoring in Outdoor Recreation, Parks, and Tourism Predicts Environmental Concerns and Behaviors

ERIC Educational Resources Information Center

Arnocky, Steven; Stroink, Mirella L.

2011-01-01

In a survey of Canadian university students (N = 205), the relationship between majoring in an outdoor recreation university program and environmental concern, cooperation, and behavior were examined. Stepwise linear regression indicated that enrollment in outdoor recreation was predictive of environmental behavior and ecological cooperation; and…

Do 360-degree feedback survey results relate to patient satisfaction measures?

PubMed

Hageman, Michiel G J S; Ring, David C; Gregory, Paul J; Rubash, Harry E; Harmon, Larry

2015-05-01

There is evidence that feedback from 360-degree surveys-combined with coaching-can improve physician team performance and quality of patient care. The Physicians Universal Leadership-Teamwork Skills Education (PULSE) 360 is one such survey tool that is used to assess work colleagues' and coworkers' perceptions of a physician's leadership, teamwork, and clinical practice style. The Clinician & Group-Consumer Assessment of Healthcare Providers and System (CG-CAHPS), developed by the US Department of Health and Human Services to serve as the benchmark for quality health care, is a survey tool for patients to provide feedback that is based on their recent experiences with staff and clinicians and soon will be tied to Medicare-based compensation of participating physicians. Prior research has indicated that patients and coworkers often agree in their assessment of physicians' behavioral patterns. The goal of the current study was to determine whether 360-degree, also called multisource, feedback provided by coworkers could predict patient satisfaction/experience ratings. A significant relationship between these two forms of feedback could enable physicians to take a more proactive approach to reinforce their strengths and identify any improvement opportunities in their patient interactions by reviewing feedback from team members. An automated 360-degree software process may be a faster, simpler, and less resource-intensive approach than telephoning and interviewing patients for survey responses, and it potentially could facilitate a more rapid credentialing or quality improvement process leading to greater fiscal and professional development gains for physicians. Our primary research question was to determine if PULSE 360 coworkers' ratings correlate with CG-CAHPS patients' ratings of overall satisfaction, recommendation of the physician, surgeon respect, and clarity of the surgeon's explanation. Our secondary research questions were to determine whether CG-CAHPS scores correlate with additional composite scores from the Quality PULSE 360 (eg, insight impact score, focus concerns score, leadership-teamwork index score, etc). We retrospectively analyzed existing quality improvement data from CG-CAHPS patient surveys as well as from a department quality improvement initiative using 360-degree survey feedback questionnaires (Quality PULSE 360 with coworkers). Bivariate analyses were conducted to identify significant relationships for inclusion of research variables in multivariate linear analyses (eg, stepwise regression to determine the best fitting predictive model for CG-CAHPS ratings). In all higher order analyses, CG-CAHPS ratings were treated as the dependent variables, whereas PULSE 360 scores served as independent variables. This approach led to the identification of the most predictive linear model for each CG-CAHPS' performance rating (eg, [1] overall satisfaction; [2] recommendation of the physician; [3] surgeon respect; and [4] clarity of the surgeon's explanation) regressed on all PULSE scores with which there was a significant bivariate relationship. Backward stepwise regression was then used to remove unnecessary predictors from the linear model based on changes in the variance explained by the model with or without inclusion of the predictor. The Quality PULSE 360 insight impact score correlated with patient satisfaction (0.50, p = 0.01), patient recommendation (0.58, p = 0.002), patient rating of surgeon respect (0.74, p < 0.001), and patient impression of clarity of the physician explanation (0.69, p < 0.001). Additionally, leadership-teamwork index also correlated with patient rating of surgeon respect (0.46, p = 0.019) and patient impression of clarity of the surgeon's explanation (0.39, p = 0.05). Multivariate analyses supported retention of insight impact as a predictor of patient overall satisfaction, patient recommendation of the surgeon, and patient rating of surgeon respect. Both insight impact and leadership-teamwork index were retained as predictors of patient impression of explanation. Several other PULSE 360 variables were correlated with CG-CAHPS ratings, but none were retained in the linear models post stepwise regression. The relationship between Quality PULSE 360 feedback scores and measures of patient satisfaction reaffirm that feedback from work team members may provide helpful information into how patients may be perceiving their physicians' behavior and vice versa. Furthermore, the findings provide tentative support for the use of team-based feedback to improve the quality of relationships with both coworkers and patients. The 360-degree survey process may offer an effective tool for physicians to obtain feedback about behavior that could directly impact practice reimbursement and reputation or potentially be used for bonuses to incentivize better team professionalism and patient satisfaction, ie, "pay-for-professionalism." Further research is needed to expand on this line of inquiry, determine which interventions can improve 360-degree and patient satisfaction scores, and explain the shared variance in physician performance that is captured in the perceptions of patients and coworkers.

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

NASA Technical Reports Server (NTRS)

Belcastro, Christine M.

1998-01-01

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

Power of Models in Longitudinal Study: Findings from a Full-Crossed Simulation Design

ERIC Educational Resources Information Center

Fang, Hua; Brooks, Gordon P.; Rizzo, Maria L.; Espy, Kimberly Andrews; Barcikowski, Robert S.

2009-01-01

Because the power properties of traditional repeated measures and hierarchical multivariate linear models have not been clearly determined in the balanced design for longitudinal studies in the literature, the authors present a power comparison study of traditional repeated measures and hierarchical multivariate linear models under 3…

Predictors of poststroke health-related quality of life in Nigerian stroke survivors: a 1-year follow-up study.

PubMed

Hamza, Ashiru Mohammad; Al-Sadat, Nabilla; Loh, Siew Yim; Jahan, Nowrozy Kamar

2014-01-01

This study aims to identify the predictors in the different aspects of the health-related quality of life (HRQoL) and to measure the changes of functional status over time in a cohort of Nigerian stroke survivors. A prospective observational study was conducted in three hospitals of Kano state of Nigeria where stroke survivors receive rehabilitation. The linguistic-validated Hausa versions of the stroke impact scale 3.0, modified Rankin scale, Barthel index and Beck depression inventory scales were used. Paired samples t-test was used to calculate the amount of changes that occur over time and the forward stepwise linear regression model was used to identify the predictors. A total of 233 stroke survivors were surveyed at 6 months, and 93% (217/233) were followed at 1 year after stroke. Functional disabilities were significantly reduced during the recovery phase. Motor impairment, disability, and level of depression were independent predictors of HRQoL in the multivariate regression analysis. The involvement of family members as caregivers is the key factor for those survivors with improved functional status. Thus, to enhance the quality of poststroke life, it is proposed that a holistic stroke rehabilitation service and an active involvement of family members are established at every possible level.

Investigation of the key determinants of Asian nurses' quality of life.

PubMed

Makabe, Sachiko; Kowitlawakul, Yanika; Nurumal, Mohd Said; Takagai, Junko; Wichaikhum, Orn-Anong; Wangmo, Neyzang; Yap, Suk Foon; Kunaviktikul, Wipada; Komatsu, Junko; Shirakawa, Hideko; Kimura, Yutaka; Asanuma, Yoshihiro

2018-06-01

The study aimed to compare nurses' quality of life and investigate key determinants among Asian countries with different economic status. A cross-sectional survey was conducted across five Asian countries (Japan, Singapore, Malaysia, Thailand, and Bhutan). Quality of life (WHOQOL-BREF), job stress (National Institute of Occupational Safety and Health questionnaire), and demographic data were assessed. Stepwise multivariate linear regression analysis was performed to identify the key determinants of quality of life. Participants were 3,829 nurses (response rate: 82%) with a mean age of 33 ± 10 yr and majority were women (92%). Regarding quality of life, Bhutan yielded the highest scores, followed by Malaysia, Thailand, Singapore, and Japan, and these results were statistically significant. The key determinants that were significantly related to quality of life were "stress coping ability," "life satisfaction," "Japan," "social support," "job stress," and "Singapore" (adjusted R 2 =0.46). In conclusion, nurses' quality of life differs across Asian countries and is not linked to the country's economic development. To maintain a good quality of life for nurses, an international exchange program like international nursing conferences for work environment and staff coping strategies is recommended to broaden institution' minds and share experiences and exchange views to be able to realize their own problems and discover global solutions to them.

Computational technique for stepwise quantitative assessment of equation correctness

NASA Astrophysics Data System (ADS)

Othman, Nuru'l Izzah; Bakar, Zainab Abu

2017-04-01

Many of the computer-aided mathematics assessment systems that are available today possess the capability to implement stepwise correctness checking of a working scheme for solving equations. The computational technique for assessing the correctness of each response in the scheme mainly involves checking the mathematical equivalence and providing qualitative feedback. This paper presents a technique, known as the Stepwise Correctness Checking and Scoring (SCCS) technique that checks the correctness of each equation in terms of structural equivalence and provides quantitative feedback. The technique, which is based on the Multiset framework, adapts certain techniques from textual information retrieval involving tokenization, document modelling and similarity evaluation. The performance of the SCCS technique was tested using worked solutions on solving linear algebraic equations in one variable. 350 working schemes comprising of 1385 responses were collected using a marking engine prototype, which has been developed based on the technique. The results show that both the automated analytical scores and the automated overall scores generated by the marking engine exhibit high percent agreement, high correlation and high degree of agreement with manual scores with small average absolute and mixed errors.

Enhanced eumelanin emission by stepwise three-photon excitation

NASA Astrophysics Data System (ADS)

Kerimo, Josef; Rajadhyaksha, Milind; DiMarzio, Charles A.

2011-03-01

Eumelanin fluorescence from Sepia officinalis and black human hair was activated with near-infrared radiation and multiphoton excitation. A third order multiphoton absorption by a step-wise process appears to be the underlying mechanism. The activation was caused by a photochemical process since it could not be reproduced by simple heating. Both fluorescence and brightfield imaging indicate the near-infrared irradiation caused photodamage to the eumelanin and the activated emission originated from the photodamaged region. At least two different components with about thousand-fold enhanced fluorescence were activated and could be distinguished by their excitation properties. One component was excited with wavelengths in the visible region and exhibited linear absorption dependence. The second component could be excited with near-infrared wavelengths and had a third order dependence on the laser power. The third order dependence is explained by a step-wise excited state absorption (ESA) process since it could be observed equally with the CW and femtosecond lasers. The new method for photoactivating the eumelanin fluorescence was used to map the melanin content in human hair.

Joint effect of unlinked genotypes: application to type 2 diabetes in the EPIC-Potsdam case-cohort study.

PubMed

Knüppel, Sven; Meidtner, Karina; Arregui, Maria; Holzhütter, Hermann-Georg; Boeing, Heiner

2015-07-01

Analyzing multiple single nucleotide polymorphisms (SNPs) is a promising approach to finding genetic effects beyond single-locus associations. We proposed the use of multilocus stepwise regression (MSR) to screen for allele combinations as a method to model joint effects, and compared the results with the often used genetic risk score (GRS), conventional stepwise selection, and the shrinkage method LASSO. In contrast to MSR, the GRS, conventional stepwise selection, and LASSO model each genotype by the risk allele doses. We reanalyzed 20 unlinked SNPs related to type 2 diabetes (T2D) in the EPIC-Potsdam case-cohort study (760 cases, 2193 noncases). No SNP-SNP interactions and no nonlinear effects were found. Two SNP combinations selected by MSR (Nagelkerke's R² = 0.050 and 0.048) included eight SNPs with mean allele combination frequency of 2%. GRS and stepwise selection selected nearly the same SNP combinations consisting of 12 and 13 SNPs (Nagelkerke's R² ranged from 0.020 to 0.029). LASSO showed similar results. The MSR method showed the best model fit measured by Nagelkerke's R² suggesting that further improvement may render this method a useful tool in genetic research. However, our comparison suggests that the GRS is a simple way to model genetic effects since it does not consider linkage, SNP-SNP interactions, and no non-linear effects. © 2015 John Wiley & Sons Ltd/University College London.

Multivariate mixed linear model analysis of longitudinal data: an information-rich statistical technique for analyzing disease resistance data

USDA-ARS?s Scientific Manuscript database

The mixed linear model (MLM) is currently among the most advanced and flexible statistical modeling techniques and its use in tackling problems in plant pathology has begun surfacing in the literature. The longitudinal MLM is a multivariate extension that handles repeatedly measured data, such as r...

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…

Multiple linear regression analysis

NASA Technical Reports Server (NTRS)

Edwards, T. R.

1980-01-01

Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.

Of Heart & Kidneys: Hands-On Activities for Demonstrating Organ Function & Repair

ERIC Educational Resources Information Center

Kao, Robert M.

2014-01-01

A major challenge in teaching organ development and disease is deconstructing a complex choreography of molecular and cellular changes over time into a linear stepwise process for students. As an entry toward learning developmental concepts, I propose two inexpensive hands-on activities to help facilitate learning of (1) how to identify defects in…

Age, Sex, and Body Composition as Predictors of Children's Performance on Basic Motor Abilities and Health-Related Fitness Items.

ERIC Educational Resources Information Center

Pissanos, Becky W.; And Others

1983-01-01

Step-wise linear regressions were used to relate children's age, sex, and body composition to performance on basic motor abilities including balance, speed, agility, power, coordination, and reaction time, and to health-related fitness items including flexibility, muscle strength and endurance and cardiovascular functions. Eighty subjects were in…

An error bound for a discrete reduced order model of a linear multivariable system

NASA Technical Reports Server (NTRS)

Al-Saggaf, Ubaid M.; Franklin, Gene F.

1987-01-01

The design of feasible controllers for high dimension multivariable systems can be greatly aided by a method of model reduction. In order for the design based on the order reduction to include a guarantee of stability, it is sufficient to have a bound on the model error. Previous work has provided such a bound for continuous-time systems for algorithms based on balancing. In this note an L-infinity bound is derived for model error for a method of order reduction of discrete linear multivariable systems based on balancing.

Searching for New Biomarkers and the Use of Multivariate Analysis in Gastric Cancer Diagnostics.

PubMed

Kucera, Radek; Smid, David; Topolcan, Ondrej; Karlikova, Marie; Fiala, Ondrej; Slouka, David; Skalicky, Tomas; Treska, Vladislav; Kulda, Vlastimil; Simanek, Vaclav; Safanda, Martin; Pesta, Martin

2016-04-01

The first aim of this study was to search for new biomarkers to be used in gastric cancer diagnostics. The second aim was to verify the findings presented in literature on a sample of the local population and investigate the risk of gastric cancer in that population using a multivariant statistical analysis. We assessed a group of 36 patients with gastric cancer and 69 healthy individuals. We determined carcinoembryonic antigen, cancer antigen 19-9, cancer antigen 72-4, matrix metalloproteinases (-1, -2, -7, -8 and -9), osteoprotegerin, osteopontin, prothrombin induced by vitamin K absence-II, pepsinogen I, pepsinogen II, gastrin and Helicobacter pylori for each sample. The multivariate stepwise logistic regression identified the following biomarkers as the best gastric cancer predictors: CEA, CA72-4, pepsinogen I, Helicobacter pylori presence and MMP7. CEA and CA72-4 remain the best markers for gastric cancer diagnostics. We suggest a mathematical model for the assessment of risk of gastric cancer. Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Predictive value of grade point average (GPA), Medical College Admission Test (MCAT), internal examinations (Block) and National Board of Medical Examiners (NBME) scores on Medical Council of Canada qualifying examination part I (MCCQE-1) scores.

PubMed

Roy, Banibrata; Ripstein, Ira; Perry, Kyle; Cohen, Barry

2016-01-01

To determine whether the pre-medical Grade Point Average (GPA), Medical College Admission Test (MCAT), Internal examinations (Block) and National Board of Medical Examiners (NBME) scores are correlated with and predict the Medical Council of Canada Qualifying Examination Part I (MCCQE-1) scores. Data from 392 admitted students in the graduating classes of 2010-2013 at University of Manitoba (UofM), College of Medicine was considered. Pearson's correlation to assess the strength of the relationship, multiple linear regression to estimate MCCQE-1 score and stepwise linear regression to investigate the amount of variance were employed. Complete data from 367 (94%) students were studied. The MCCQE-1 had a moderate-to-large positive correlation with NBME scores and Block scores but a low correlation with GPA and MCAT scores. The multiple linear regression model gives a good estimate of the MCCQE-1 (R2 =0.604). Stepwise regression analysis demonstrated that 59.2% of the variation in the MCCQE-1 was accounted for by the NBME, but only 1.9% by the Block exams, and negligible variation came from the GPA and the MCAT. Amongst all the examinations used at UofM, the NBME is most closely correlated with MCCQE-1.

Gestational dating by metabolic profile at birth: a California cohort study.

PubMed

Jelliffe-Pawlowski, Laura L; Norton, Mary E; Baer, Rebecca J; Santos, Nicole; Rutherford, George W

2016-04-01

Accurate gestational dating is a critical component of obstetric and newborn care. In the absence of early ultrasound, many clinicians rely on less accurate measures, such as last menstrual period or symphysis-fundal height during pregnancy, or Dubowitz scoring or the Ballard (or New Ballard) method at birth. These measures often underestimate or overestimate gestational age and can lead to misclassification of babies as born preterm, which has both short- and long-term clinical care and public health implications. We sought to evaluate whether metabolic markers in newborns measured as part of routine screening for treatable inborn errors of metabolism can be used to develop a population-level metabolic gestational dating algorithm that is robust despite intrauterine growth restriction and can be used when fetal ultrasound dating is not available. We focused specifically on the ability of these markers to differentiate preterm births (PTBs) (<37 weeks) from term births and to assign a specific gestational age in the PTB group. We evaluated a cohort of 729,503 singleton newborns with a California birth in 2005 through 2011 who had routine newborn metabolic screening and fetal ultrasound dating at 11-20 weeks' gestation. Using training and testing subsets (divided in a ratio of 3:1) we evaluated the association among PTB, target newborn characteristics, acylcarnitines, amino acids, thyroid-stimulating hormone, 17-hydroxyprogesterone, and galactose-1-phosphate-uridyl-transferase. We used multivariate backward stepwise regression to test for associations and linear discriminate analyses to create a linear function for PTB and to assign a specific week of gestation. We used sensitivity, specificity, and positive predictive value to evaluate the performance of linear functions. Along with birthweight and infant age at test, we included 35 of the 51 metabolic markers measured in the final multivariate model comparing PTBs and term births. Using a linear discriminate analyses-derived linear function, we were able to sort PTBs and term births accurately with sensitivities and specificities of ≥95% in both the training and testing subsets. Assignment of a specific week of gestation in those identified as PTBs resulted in the correct assignment of week ±2 weeks in 89.8% of all newborns in the training and 91.7% of those in the testing subset. When PTB rates were modeled using the metabolic dating algorithm compared to fetal ultrasound, PTB rates were 7.15% vs 6.11% in the training subset and 7.31% vs 6.25% in the testing subset. When considered in combination with birthweight and hours of age at test, metabolic profile evaluated within 8 days of birth appears to be a useful measure of PTB and, among those born preterm, of specific week of gestation ±2 weeks. Dating by metabolic profile may be useful in instances where there is no fetal ultrasound due to lack of availability or late entry into care. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Gestational dating by metabolic profile at birth: a California cohort study

PubMed Central

Jelliffe-Pawlowski, Laura L.; Norton, Mary E.; Baer, Rebecca J.; Santos, Nicole; Rutherford, George W.

2016-01-01

Background Accurate gestational dating is a critical component of obstetric and newborn care. In the absence of early ultrasound, many clinicians rely on less accurate measures, such as last menstrual period or symphysis-fundal height during pregnancy, or Dubowitz scoring or the Ballard (or New Ballard) method at birth. These measures often underestimate or overestimate gestational age and can lead to misclassification of babies as born preterm, which has both short- and long-term clinical care and public health implications. Objective We sought to evaluate whether metabolic markers in newborns measured as part of routine screening for treatable inborn errors of metabolism can be used to develop a population-level metabolic gestational dating algorithm that is robust despite intrauterine growth restriction and can be used when fetal ultrasound dating is not available. We focused specifically on the ability of these markers to differentiate preterm births (PTBs) (<37 weeks) from term births and to assign a specific gestational age in the PTB group. Study Design We evaluated a cohort of 729,503 singleton newborns with a California birth in 2005 through 2011 who had routine newborn metabolic screening and fetal ultrasound dating at 11–20 weeks’ gestation. Using training and testing subsets (divided in a ratio of 3:1) we evaluated the association among PTB, target newborn characteristics, acylcarnitines, amino acids, thyroid-stimulating hormone, 17-hydroxyprogesterone, and galactose-1-phosphate-uridyl-transferase. We used multivariate backward stepwise regression to test for associations and linear discriminate analyses to create a linear function for PTB and to assign a specific week of gestation. We used sensitivity, specificity, and positive predictive value to evaluate the performance of linear functions. Results Along with birthweight and infant age at test, we included 35 of the 51 metabolic markers measured in the final multivariate model comparing PTBs and term births. Using a linear discriminate analyses-derived linear function, we were able to sort PTBs and term births accurately with sensitivities and specificities of ≥95% in both the training and testing subsets. Assignment of a specific week of gestation in those identified as PTBs resulted in the correct assignment of week ±2 weeks in 89.8% of all newborns in the training and 91.7% of those in the testing subset. When PTB rates were modeled using the metabolic dating algorithm compared to fetal ultrasound, PTB rates were 7.15% vs 6.11% in the training subset and 7.31% vs 6.25% in the testing subset. Conclusion When considered in combination with birthweight and hours of age at test, metabolic profile evaluated within 8 days of birth appears to be a useful measure of PTB and, among those born preterm, of specific week of gestation ±2 weeks. Dating by metabolic profile may be useful in instances where there is no fetal ultrasound due to lack of availability or late entry into care. PMID:26688490

Associations of adiponectin with individual European ancestry in African Americans: the Jackson Heart Study

PubMed Central

Bidulescu, Aurelian; Choudhry, Shweta; Musani, Solomon K.; Buxbaum, Sarah G.; Liu, Jiankang; Rotimi, Charles N.; Wilson, James G.; Taylor, Herman A.; Gibbons, Gary H.

2014-01-01

Background: Compared with European Americans, African Americans (AAs) exhibit lower levels of the cardio-metabolically protective adiponectin even after accounting for adiposity measures. Because few studies have examined in AA the association between adiponectin and genetic admixture, a dense panel of ancestry informative markers (AIMs) was used to estimate the individual proportions of European ancestry (PEA) for the AAs enrolled in a large community-based cohort, the Jackson Heart Study (JHS). We tested the hypothesis that plasma adiponectin and PEA are directly associated and assessed the interaction with a series of cardio-metabolic risk factors. Methods: Plasma specimens from 1439 JHS participants were analyzed by ELISA for adiponectin levels. Using pseudo-ancestral population genotype data from the HapMap Consortium, PEA was estimated with a panel of up to 1447 genome-wide preselected AIMs by a maximum likelihood approach. Interaction assessment, stepwise linear and cubic multivariable-adjusted regression models were used to analyze the cross-sectional association between adiponectin and PEA. Results: Among the study participants (62% women; mean age 48 ± 12 years), the median (interquartile range) of PEA was 15.8 (9.3)%. Body mass index (BMI) (p = 0.04) and insulin resistance (p = 0.0001) modified the association between adiponectin and PEA. Adiponectin was directly and linearly associated with PEA (β = 0.62 ± 0.28, p = 0.03) among non-obese (n = 673) and insulin sensitive participants (n = 1141; β = 0.74 ± 0.23, p = 0.001), but not among those obese or with insulin resistance. No threshold point effect was detected for non-obese participants. Conclusions: In a large AA population, the individual proportion of European ancestry was linearly and directly associated with plasma adiponectin among non-obese and non insulin-resistant participants, pointing to the interaction of genetic and metabolic factors influencing adiponectin levels. PMID:24575123

Predictive and mechanistic multivariate linear regression models for reaction development

PubMed Central

Santiago, Celine B.; Guo, Jing-Yao

2018-01-01

Multivariate Linear Regression (MLR) models utilizing computationally-derived and empirically-derived physical organic molecular descriptors are described in this review. Several reports demonstrating the effectiveness of this methodological approach towards reaction optimization and mechanistic interrogation are discussed. A detailed protocol to access quantitative and predictive MLR models is provided as a guide for model development and parameter analysis. PMID:29719711

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

PubMed Central

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

2012-01-01

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

A multivariate model and statistical method for validating tree grade lumber yield equations

Treesearch

Donald W. Seegrist

1975-01-01

Lumber yields within lumber grades can be described by a multivariate linear model. A method for validating lumber yield prediction equations when there are several tree grades is presented. The method is based on multivariate simultaneous test procedures.

A simple prognostic model for overall survival in metastatic renal cell carcinoma.

PubMed

Assi, Hazem I; Patenaude, Francois; Toumishey, Ethan; Ross, Laura; Abdelsalam, Mahmoud; Reiman, Tony

2016-01-01

The primary purpose of this study was to develop a simpler prognostic model to predict overall survival for patients treated for metastatic renal cell carcinoma (mRCC) by examining variables shown in the literature to be associated with survival. We conducted a retrospective analysis of patients treated for mRCC at two Canadian centres. All patients who started first-line treatment were included in the analysis. A multivariate Cox proportional hazards regression model was constructed using a stepwise procedure. Patients were assigned to risk groups depending on how many of the three risk factors from the final multivariate model they had. There were three risk factors in the final multivariate model: hemoglobin, prior nephrectomy, and time from diagnosis to treatment. Patients in the high-risk group (two or three risk factors) had a median survival of 5.9 months, while those in the intermediate-risk group (one risk factor) had a median survival of 16.2 months, and those in the low-risk group (no risk factors) had a median survival of 50.6 months. In multivariate analysis, shorter survival times were associated with hemoglobin below the lower limit of normal, absence of prior nephrectomy, and initiation of treatment within one year of diagnosis.

A simple prognostic model for overall survival in metastatic renal cell carcinoma

PubMed Central

Assi, Hazem I.; Patenaude, Francois; Toumishey, Ethan; Ross, Laura; Abdelsalam, Mahmoud; Reiman, Tony

2016-01-01

Introduction: The primary purpose of this study was to develop a simpler prognostic model to predict overall survival for patients treated for metastatic renal cell carcinoma (mRCC) by examining variables shown in the literature to be associated with survival. Methods: We conducted a retrospective analysis of patients treated for mRCC at two Canadian centres. All patients who started first-line treatment were included in the analysis. A multivariate Cox proportional hazards regression model was constructed using a stepwise procedure. Patients were assigned to risk groups depending on how many of the three risk factors from the final multivariate model they had. Results: There were three risk factors in the final multivariate model: hemoglobin, prior nephrectomy, and time from diagnosis to treatment. Patients in the high-risk group (two or three risk factors) had a median survival of 5.9 months, while those in the intermediate-risk group (one risk factor) had a median survival of 16.2 months, and those in the low-risk group (no risk factors) had a median survival of 50.6 months. Conclusions: In multivariate analysis, shorter survival times were associated with hemoglobin below the lower limit of normal, absence of prior nephrectomy, and initiation of treatment within one year of diagnosis. PMID:27217858

Assessment of craniometric traits in South Indian dry skulls for sex determination.

PubMed

Ramamoorthy, Balakrishnan; Pai, Mangala M; Prabhu, Latha V; Muralimanju, B V; Rai, Rajalakshmi

2016-01-01

The skeleton plays an important role in sex determination in forensic anthropology. The skull bone is considered as the second best after the pelvic bone in sex determination due to its better retention of morphological features. Different populations have varying skeletal characteristics, making population specific analysis for sex determination essential. Hence the objective of this investigation is to obtain the accuracy of sex determination using cranial parameters of adult skulls to the highest percentage in South Indian population and to provide a baseline data for sex determination in South India. Seventy adult preserved human skulls were taken and based on the morphological traits were classified into 43 male skulls and 27 female skulls. A total of 26 craniometric parameters were studied. The data were analyzed by using the SPSS discriminant function. The analysis of stepwise, multivariate, and univariate discriminant function gave an accuracy of 77.1%, 85.7%, and 72.9% respectively. Multivariate direct discriminant function analysis classified skull bones into male and female with highest levels of accuracy. Using stepwise discriminant function analysis, the most dimorphic variable to determine sex of the skull, was biauricular breadth followed by weight. Subjecting the best dimorphic variables to univariate discriminant analysis, high levels of accuracy of sexual dimorphism was obtained. Percentage classification of high accuracies were obtained in this study indicating high level of sexual dimorphism in the crania, setting specific discriminant equations for the gender determination in South Indian people. Copyright © 2015 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Time-frequency analysis of neuronal populations with instantaneous resolution based on noise-assisted multivariate empirical mode decomposition.

PubMed

Alegre-Cortés, J; Soto-Sánchez, C; Pizá, Á G; Albarracín, A L; Farfán, F D; Felice, C J; Fernández, E

2016-07-15

Linear analysis has classically provided powerful tools for understanding the behavior of neural populations, but the neuron responses to real-world stimulation are nonlinear under some conditions, and many neuronal components demonstrate strong nonlinear behavior. In spite of this, temporal and frequency dynamics of neural populations to sensory stimulation have been usually analyzed with linear approaches. In this paper, we propose the use of Noise-Assisted Multivariate Empirical Mode Decomposition (NA-MEMD), a data-driven template-free algorithm, plus the Hilbert transform as a suitable tool for analyzing population oscillatory dynamics in a multi-dimensional space with instantaneous frequency (IF) resolution. The proposed approach was able to extract oscillatory information of neurophysiological data of deep vibrissal nerve and visual cortex multiunit recordings that were not evidenced using linear approaches with fixed bases such as the Fourier analysis. Texture discrimination analysis performance was increased when Noise-Assisted Multivariate Empirical Mode plus Hilbert transform was implemented, compared to linear techniques. Cortical oscillatory population activity was analyzed with precise time-frequency resolution. Similarly, NA-MEMD provided increased time-frequency resolution of cortical oscillatory population activity. Noise-Assisted Multivariate Empirical Mode Decomposition plus Hilbert transform is an improved method to analyze neuronal population oscillatory dynamics overcoming linear and stationary assumptions of classical methods. Copyright © 2016 Elsevier B.V. All rights reserved.

Assessment of weather-associated causes of red spruce winter injury and consequences to aboveground carbon sequestration

Treesearch

Paul G. Schaberg; Brynne E. Lazarus; Gary J. Hawley; Joshua M. Halman; Catherine H. Borer; Christopher F. Hansen

2011-01-01

Despite considerable study, it remains uncertain what environmental factors contribute to red spruce (Picea rubens Sarg.) foliar winter injury and how much this injury influences tree C stores. We used a long-term record of winter injury in a plantation in New Hampshire and conducted stepwise linear regression analyses with local weather and regional...

Handwashing, sanitation and family planning practices are the strongest underlying determinants of child stunting in rural indigenous communities of Jharkhand and Odisha, Eastern India: a cross-sectional study.

PubMed

Saxton, Jennifer; Rath, Shibanand; Nair, Nirmala; Gope, Rajkumar; Mahapatra, Rajendra; Tripathy, Prasanta; Prost, Audrey

2016-10-01

The World Health Organisation has called for global action to reduce child stunting by 40% by 2025. One third of the world's stunted children live in India, and children belonging to rural indigenous communities are the worst affected. We sought to identify the strongest determinants of stunting among indigenous children in rural Jharkhand and Odisha, India, to highlight key areas for intervention. We analysed data from 1227 children aged 6-23.99 months and their mothers, collected in 2010 from 18 clusters of villages with a high proportion of people from indigenous groups in three districts. We measured height and weight of mothers and children, and captured data on various basic, underlying and immediate determinants of undernutrition. We used Generalised Estimating Equations to identify individual determinants associated with children's height-for-age z-score (HAZ; p < 0.10); we included these in a multivariable model to identify the strongest HAZ determinants using backwards stepwise methods. In the adjusted model, the strongest protective factors for linear growth included cooking outdoors rather than indoors (HAZ +0.66), birth spacing ≥24 months (HAZ +0.40), and handwashing with a cleansing agent (HAZ +0.32). The strongest risk factors were later birth order (HAZ -0.38) and repeated diarrhoeal infection (HAZ -0.23). Our results suggest multiple risk factors for linear growth faltering in indigenous communities in Jharkhand and Odisha. Interventions that could improve children's growth include reducing exposure to indoor air pollution, increasing access to family planning, reducing diarrhoeal infections, improving handwashing practices, increasing access to income and strengthening health and sanitation infrastructure. © 2016 The Authors. Maternal & Child Nutrition published by John Wiley & Sons Ltd.

Multiscale characterization and prediction of monsoon rainfall in India using Hilbert-Huang transform and time-dependent intrinsic correlation analysis

NASA Astrophysics Data System (ADS)

Adarsh, S.; Reddy, M. Janga

2017-07-01

In this paper, the Hilbert-Huang transform (HHT) approach is used for the multiscale characterization of All India Summer Monsoon Rainfall (AISMR) time series and monsoon rainfall time series from five homogeneous regions in India. The study employs the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) for multiscale decomposition of monsoon rainfall in India and uses the Normalized Hilbert Transform and Direct Quadrature (NHT-DQ) scheme for the time-frequency characterization. The cross-correlation analysis between orthogonal modes of All India monthly monsoon rainfall time series and that of five climate indices such as Quasi Biennial Oscillation (QBO), El Niño Southern Oscillation (ENSO), Sunspot Number (SN), Atlantic Multi Decadal Oscillation (AMO), and Equatorial Indian Ocean Oscillation (EQUINOO) in the time domain showed that the links of different climate indices with monsoon rainfall are expressed well only for few low-frequency modes and for the trend component. Furthermore, this paper investigated the hydro-climatic teleconnection of ISMR in multiple time scales using the HHT-based running correlation analysis technique called time-dependent intrinsic correlation (TDIC). The results showed that both the strength and nature of association between different climate indices and ISMR vary with time scale. Stemming from this finding, a methodology employing Multivariate extension of EMD and Stepwise Linear Regression (MEMD-SLR) is proposed for prediction of monsoon rainfall in India. The proposed MEMD-SLR method clearly exhibited superior performance over the IMD operational forecast, M5 Model Tree (MT), and multiple linear regression methods in ISMR predictions and displayed excellent predictive skill during 1989-2012 including the four extreme events that have occurred during this period.

Assessment of plant species diversity based on hyperspectral indices at a fine scale.

PubMed

Peng, Yu; Fan, Min; Song, Jingyi; Cui, Tiantian; Li, Rui

2018-03-19

Fast and nondestructive approaches of measuring plant species diversity have been a subject of excessive scientific curiosity and disquiet to environmentalists and field ecologists worldwide. In this study, we measured the hyperspectral reflectances and plant species diversity indices at a fine scale (0.8 meter) in central Hunshandak Sandland of Inner Mongolia, China. The first-order derivative value (FD) at each waveband and 37 hyperspectral indices were used to assess plant species diversity. Results demonstrated that the stepwise linear regression of FD can accurately estimate the Simpson (R 2  = 0.83), Pielou (R 2  = 0.87) and Shannon-Wiener index (R 2  = 0.88). Stepwise linear regression of FD (R 2  = 0.81, R 2  = 0.82) and spectral vegetation indices (R 2  = 0.51, R 2  = 0.58) significantly predicted the Margalef and Gleason index. It was proposed that the Simpson, Pielou and Shannon-Wiener indices, which are widely used as plant species diversity indicators, can be precisely estimated through hyperspectral indices at a fine scale. This research promotes the development of methods for assessment of plant diversity using hyperspectral data.

Handheld Tissue Hardness Meters for Assessing the Mechanical Properties of Skeletal Muscle: A Feasibility Study.

PubMed

Chino, Kentaro; Takahashi, Hideyuki

2016-09-01

The purpose of this study was to examine the feasibility of using handheld tissue hardness meters to assess the mechanical properties of skeletal muscle. This observational study included 33 healthy men (age, 22.4 ± 4.4 years) and 33 healthy women (age, 23.7 ± 4.2 years). Participants were placed in a supine position, and tissue hardness overlying the rectus femoris and the shear modulus of the muscle were measured on the right side of the body at 50% thigh length. In the same position, subcutaneous adipose tissue thickness and muscle thickness were measured using B-mode ultrasonography. To examine the associations of subcutaneous adipose tissue thickness, muscle thickness, and muscle shear modulus with tissue hardness, linear regression using a stepwise bidirectional elimination approach was performed. Stepwise linear regression revealed that subcutaneous adipose tissue thickness (r = -0.38, P = .002) and muscle shear modulus (r = 0.27, P = .03) were significantly associated with tissue hardness. Significant associations among adipose tissue thickness, muscle shear modulus, and tissue hardness show the limitations and feasibility of handheld tissue hardness meters for assessing the mechanical properties of skeletal muscles. Copyright © 2016. Published by Elsevier Inc.

Super-resolution fluorescence microscopy by stepwise optical saturation

PubMed Central

Zhang, Yide; Nallathamby, Prakash D.; Vigil, Genevieve D.; Khan, Aamir A.; Mason, Devon E.; Boerckel, Joel D.; Roeder, Ryan K.; Howard, Scott S.

2018-01-01

Super-resolution fluorescence microscopy is an important tool in biomedical research for its ability to discern features smaller than the diffraction limit. However, due to its difficult implementation and high cost, the super-resolution microscopy is not feasible in many applications. In this paper, we propose and demonstrate a saturation-based super-resolution fluorescence microscopy technique that can be easily implemented and requires neither additional hardware nor complex post-processing. The method is based on the principle of stepwise optical saturation (SOS), where M steps of raw fluorescence images are linearly combined to generate an image with a M-fold increase in resolution compared with conventional diffraction-limited images. For example, linearly combining (scaling and subtracting) two images obtained at regular powers extends the resolution by a factor of 1.4 beyond the diffraction limit. The resolution improvement in SOS microscopy is theoretically infinite but practically is limited by the signal-to-noise ratio. We perform simulations and experimentally demonstrate super-resolution microscopy with both one-photon (confocal) and multiphoton excitation fluorescence. We show that with the multiphoton modality, the SOS microscopy can provide super-resolution imaging deep in scattering samples. PMID:29675306

Profiling of barrier capacitance and spreading resistance using a transient linearly increasing voltage technique.

PubMed

Gaubas, E; Ceponis, T; Kusakovskij, J

2011-08-01

A technique for the combined measurement of barrier capacitance and spreading resistance profiles using a linearly increasing voltage pulse is presented. The technique is based on the measurement and analysis of current transients, due to the barrier and diffusion capacitance, and the spreading resistance, between a needle probe and sample. To control the impact of deep traps in the barrier capacitance, a steady state bias illumination with infrared light was employed. Measurements of the spreading resistance and barrier capacitance profiles using a stepwise positioned probe on cross sectioned silicon pin diodes and pnp structures are presented.

Improving Prediction Accuracy for WSN Data Reduction by Applying Multivariate Spatio-Temporal Correlation

PubMed Central

Carvalho, Carlos; Gomes, Danielo G.; Agoulmine, Nazim; de Souza, José Neuman

2011-01-01

This paper proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for Wireless Sensor Networks (WSN). Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, it may not be very accurate. Simulations were made involving simple linear regression and multiple linear regression functions to assess the performance of the proposed method. The results show a higher correlation between gathered inputs when compared to time, which is an independent variable widely used for prediction and forecasting. Prediction accuracy is lower when simple linear regression is used, whereas multiple linear regression is the most accurate one. In addition to that, our proposal outperforms some current solutions by about 50% in humidity prediction and 21% in light prediction. To the best of our knowledge, we believe that we are probably the first to address prediction based on multivariate correlation for WSN data reduction. PMID:22346626

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.

Quantitative laser-induced breakdown spectroscopy data using peak area step-wise regression analysis: an alternative method for interpretation of Mars science laboratory results

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

Clegg, Samuel M; Barefield, James E; Wiens, Roger C

2008-01-01

The ChemCam instrument on the Mars Science Laboratory (MSL) will include a laser-induced breakdown spectrometer (LIBS) to quantify major and minor elemental compositions. The traditional analytical chemistry approach to calibration curves for these data regresses a single diagnostic peak area against concentration for each element. This approach contrasts with a new multivariate method in which elemental concentrations are predicted by step-wise multiple regression analysis based on areas of a specific set of diagnostic peaks for each element. The method is tested on LIBS data from igneous and metamorphosed rocks. Between 4 and 13 partial regression coefficients are needed to describemore » each elemental abundance accurately (i.e., with a regression line of R{sup 2} > 0.9995 for the relationship between predicted and measured elemental concentration) for all major and minor elements studied. Validation plots suggest that the method is limited at present by the small data set, and will work best for prediction of concentration when a wide variety of compositions and rock types has been analyzed.« less

Improving prediction of metal uptake by Chinese cabbage (Brassica pekinensis L.) based on a soil-plant stepwise analysis.

PubMed

Zhang, Sha; Song, Jing; Gao, Hui; Zhang, Qiang; Lv, Ming-Chao; Wang, Shuang; Liu, Gan; Pan, Yun-Yu; Christie, Peter; Sun, Wenjie

2016-11-01

It is crucial to develop predictive soil-plant transfer (SPT) models to derive the threshold values of toxic metals in contaminated arable soils. The present study was designed to examine the heavy metal uptake pattern and to improve the prediction of metal uptake by Chinese cabbage grown in agricultural soils with multiple contamination by Cd, Cu, Ni, Pb, and Zn. Pot experiments were performed with 25 historically contaminated soils to determine metal accumulation in different parts of Chinese cabbage. Different soil bioavailable metal fractions were determined using different extractants (0.43M HNO3, 0.01M CaCl2, 0.005M DTPA, and 0.01M LWMOAs), soil moisture samplers, and diffusive gradients in thin films (DGT), and the fractions were compared with shoot metal uptake using both direct and stepwise multiple regression analysis. The stepwise approach significantly improved the prediction of metal uptake by cabbage over the direct approach. Strongly pH dependent or nonlinear relationships were found for the adsorption of root surfaces and in root-shoot uptake processes. Metals were linearly translocated from the root surface to the root. Therefore, the nonlinearity of uptake pattern is an important explanation for the inadequacy of the direct approach in some cases. The stepwise approach offers an alternative and robust method to study the pattern of metal uptake by Chinese cabbage (Brassica pekinensis L.). Copyright © 2016. Published by Elsevier B.V.

Vapor permeation-stepwise injection simultaneous determination of methanol and ethanol in biodiesel with voltammetric detection.

PubMed

Shishov, Andrey; Penkova, Anastasia; Zabrodin, Andrey; Nikolaev, Konstantin; Dmitrenko, Maria; Ermakov, Sergey; Bulatov, Andrey

2016-02-01

A novel vapor permeation-stepwise injection (VP-SWI) method for the determination of methanol and ethanol in biodiesel samples is discussed. In the current study, stepwise injection analysis was successfully combined with voltammetric detection and vapor permeation. This method is based on the separation of methanol and ethanol from a sample using a vapor permeation module (VPM) with a selective polymer membrane based on poly(phenylene isophtalamide) (PA) containing high amounts of a residual solvent. After the evaporation into the headspace of the VPM, methanol and ethanol were transported, by gas bubbling, through a PA membrane to a mixing chamber equipped with a voltammetric detector. Ethanol was selectively detected at +0.19 V, and both compounds were detected at +1.20 V. Current subtractions (using a correction factor) were used for the selective determination of methanol. A linear range between 0.05 and 0.5% (m/m) was established for each analyte. The limits of detection were estimated at 0.02% (m/m) for ethanol and methanol. The sample throughput was 5 samples h(-1). The method was successfully applied to the analysis of biodiesel samples. Copyright © 2015 Elsevier B.V. All rights reserved.

Cole-Cole, linear and multivariate modeling of capacitance data for on-line monitoring of biomass.

PubMed

Dabros, Michal; Dennewald, Danielle; Currie, David J; Lee, Mark H; Todd, Robert W; Marison, Ian W; von Stockar, Urs

2009-02-01

This work evaluates three techniques of calibrating capacitance (dielectric) spectrometers used for on-line monitoring of biomass: modeling of cell properties using the theoretical Cole-Cole equation, linear regression of dual-frequency capacitance measurements on biomass concentration, and multivariate (PLS) modeling of scanning dielectric spectra. The performance and robustness of each technique is assessed during a sequence of validation batches in two experimental settings of differing signal noise. In more noisy conditions, the Cole-Cole model had significantly higher biomass concentration prediction errors than the linear and multivariate models. The PLS model was the most robust in handling signal noise. In less noisy conditions, the three models performed similarly. Estimates of the mean cell size were done additionally using the Cole-Cole and PLS models, the latter technique giving more satisfactory results.

Stationary-phase optimized selectivity liquid chromatography: development of a linear gradient prediction algorithm.

PubMed

De Beer, Maarten; Lynen, Fréderic; Chen, Kai; Ferguson, Paul; Hanna-Brown, Melissa; Sandra, Pat

2010-03-01

Stationary-phase optimized selectivity liquid chromatography (SOS-LC) is a tool in reversed-phase LC (RP-LC) to optimize the selectivity for a given separation by combining stationary phases in a multisegment column. The presently (commercially) available SOS-LC optimization procedure and algorithm are only applicable to isocratic analyses. Step gradient SOS-LC has been developed, but this is still not very elegant for the analysis of complex mixtures composed of components covering a broad hydrophobicity range. A linear gradient prediction algorithm has been developed allowing one to apply SOS-LC as a generic RP-LC optimization method. The algorithm allows operation in isocratic, stepwise, and linear gradient run modes. The features of SOS-LC in the linear gradient mode are demonstrated by means of a mixture of 13 steroids, whereby baseline separation is predicted and experimentally demonstrated.

Basic principles of Hasse diagram technique in chemistry.

PubMed

Brüggemann, Rainer; Voigt, Kristina

2008-11-01

Principles of partial order applied to ranking are explained. The Hasse diagram technique (HDT) is the application of partial order theory based on a data matrix. In this paper, HDT is introduced in a stepwise procedure, and some elementary theorems are exemplified. The focus is to show how the multivariate character of a data matrix is realized by HDT and in which cases one should apply other mathematical or statistical methods. Many simple examples illustrate the basic theoretical ideas. Finally, it is shown that HDT is a useful alternative for the evaluation of antifouling agents, which was originally performed by amoeba diagrams.

Analysis techniques for multivariate root loci. [a tool in linear control systems

NASA Technical Reports Server (NTRS)

Thompson, P. M.; Stein, G.; Laub, A. J.

1980-01-01

Analysis and techniques are developed for the multivariable root locus and the multivariable optimal root locus. The generalized eigenvalue problem is used to compute angles and sensitivities for both types of loci, and an algorithm is presented that determines the asymptotic properties of the optimal root locus.

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

NASA Technical Reports Server (NTRS)

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

1980-01-01

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

Estimation of standard liver volume in Chinese adult living donors.

PubMed

Fu-Gui, L; Lu-Nan, Y; Bo, L; Yong, Z; Tian-Fu, W; Ming-Qing, X; Wen-Tao, W; Zhe-Yu, C

2009-12-01

To determine a formula predicting the standard liver volume based on body surface area (BSA) or body weight in Chinese adults. A total of 115 consecutive right-lobe living donors not including the middle hepatic vein underwent right hemi-hepatectomy. No organs were used from prisoners, and no subjects were prisoners. Donor anthropometric data including age, gender, body weight, and body height were recorded prospectively. The weights and volumes of the right lobe liver grafts were measured at the back table. Liver weights and volumes were calculated from the right lobe graft weight and volume obtained at the back table, divided by the proportion of the right lobe on computed tomography. By simple linear regression analysis and stepwise multiple linear regression analysis, we correlated calculated liver volume and body height, body weight, or body surface area. The subjects had a mean age of 35.97 +/- 9.6 years, and a female-to-male ratio of 60:55. The mean volume of the right lobe was 727.47 +/- 136.17 mL, occupying 55.59% +/- 6.70% of the whole liver by computed tomography. The volume of the right lobe was 581.73 +/- 96.137 mL, and the estimated liver volume was 1053.08 +/- 167.56 mL. Females of the same body weight showed a slightly lower liver weight. By simple linear regression analysis and stepwise multiple linear regression analysis, a formula was derived based on body weight. All formulae except the Hong Kong formula overestimated liver volume compared to this formula. The formula of standard liver volume, SLV (mL) = 11.508 x body weight (kg) + 334.024, may be applied to estimate liver volumes in Chinese adults.

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

NASA Technical Reports Server (NTRS)

Garg, Sanjay; Watts, Stephen R.

1995-01-01

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

Regression and multivariate models for predicting particulate matter concentration level.

PubMed

Nazif, Amina; Mohammed, Nurul Izma; Malakahmad, Amirhossein; Abualqumboz, Motasem S

2018-01-01

The devastating health effects of particulate matter (PM 10 ) exposure by susceptible populace has made it necessary to evaluate PM 10 pollution. Meteorological parameters and seasonal variation increases PM 10 concentration levels, especially in areas that have multiple anthropogenic activities. Hence, stepwise regression (SR), multiple linear regression (MLR) and principal component regression (PCR) analyses were used to analyse daily average PM 10 concentration levels. The analyses were carried out using daily average PM 10 concentration, temperature, humidity, wind speed and wind direction data from 2006 to 2010. The data was from an industrial air quality monitoring station in Malaysia. The SR analysis established that meteorological parameters had less influence on PM 10 concentration levels having coefficient of determination (R 2 ) result from 23 to 29% based on seasoned and unseasoned analysis. While, the result of the prediction analysis showed that PCR models had a better R 2 result than MLR methods. The results for the analyses based on both seasoned and unseasoned data established that MLR models had R 2 result from 0.50 to 0.60. While, PCR models had R 2 result from 0.66 to 0.89. In addition, the validation analysis using 2016 data also recognised that the PCR model outperformed the MLR model, with the PCR model for the seasoned analysis having the best result. These analyses will aid in achieving sustainable air quality management strategies.

Prediction of thyroidal 131I effective half-life in patients with Graves' disease.

PubMed

Zhang, Ruiguo; Zhang, Guizhi; Wang, Renfei; Tan, Jian; He, Yajing; Meng, Zhaowei

2017-10-06

Calculation of effective thyroidal half-life (Teff) of iodine-131( 131 I) is cumbersome and tedious. The aim of this study was to investigate factors that could be used to predict Teff and to develop a Teff prediction model in Graves' disease patients. A total of 256 patients with GD were involved in this study. We investigated the influences of age, gender, disease duration, thyroid weight, antithyroid drugs, antithyroid drugs discontinuation period (ADP), thyroid function indexes, thyroid autoantibodies, thyroid-stimulating hormone receptor antibody (TRAb) level and radioactive iodine uptake (RAIU) values before 131 I therapy on Teff, applying univariate and multivariate analyses. Teff correlated negatively with thyroid peroxidase antibody, TRAb and thyroid weight, as well as positively with 24-hour, 48-hour, and 72-hour RAIU. Additionally, a longer ADP (especially≥ 14d) or without antithyroid drugs before 131 I therapy led to a longer Teff. Stepwise multiple linear regression analysis showed that 24-hour and 72-hour RAIU were statistically significant predictors of Teff ( P <0.001). The relationship was: predictive Teff=5.277+0.295×72-hour RAIU-0.217×24-hour RAIU (r =0.865, P < 0.001). The present results indicate that prediction of Teff from 24-hour and 72-hour RAIU is feasible in patients with Graves' disease, with high prediction accuracy.

Plasma 8-iso-Prostaglandin F2α concentrations and outcomes after acute intracerebral hemorrhage.

PubMed

Du, Quan; Yu, Wen-Hua; Dong, Xiao-Qiao; Yang, Ding-Bo; Shen, Yong-Feng; Wang, Hao; Jiang, Li; Du, Yuan-Feng; Zhang, Zu-Yong; Zhu, Qiang; Che, Zhi-Hao; Liu, Qun-Jie

2014-11-01

Higher plasma 8-iso-Prostaglandin F2α concentrations have been associated with poor outcome of severe traumatic brain injury. We further investigated the relationships between plasma 8-iso-Prostaglandin F2α concentrations and clinical outcomes in patients with acute intracerebral hemorrhage. Plasma 8-iso-Prostaglandin F2α concentrations of 128 consecutive patients and 128 sex- and gender-matched healthy subjects were measured by enzyme-linked immunosorbent assay. We assessed their relationships with disease severity and clinical outcomes including 1-week mortality, 6-month mortality and unfavorable outcome (modified Rankin Scale score>2). Plasma 8-iso-Prostaglandin F2α concentrations were substantially higher in patients than in healthy controls. Plasma 8-iso-Prostaglandin F2α concentrations were positively associated with National Institutes of Health Stroke Scale (NIHSS) scores and hematoma volume using a multivariate linear regression. It emerged as an independent predictor for clinical outcomes of patients using a forward stepwise logistic regression. ROC curves identified the predictive values of plasma 8-iso-Prostaglandin F2α concentrations, and found its predictive value was similar to NIHSS scores and hematoma volumes. However, it just numerically added the predictive values of NIHSS score and hematoma volume. Increased plasma 8-iso-Prostaglandin F2α concentrations are associated with disease severity and clinical outcome after acute intracerebral hemorrhage. Copyright © 2014 Elsevier B.V. All rights reserved.

Physicians' reactions to uncertainty in the context of shared decision making.

PubMed

Politi, Mary C; Légaré, France

2010-08-01

Physicians' reactions towards uncertainty may influence their willingness to engage in shared decision making (SDM). This study aimed to identify variables associated with physician's anxiety from uncertainty and reluctance to disclose uncertainty to patients. We conducted a cross-sectional secondary analysis of longitudinal data of an implementation study of SDM among primary care professionals (n=122). Outcomes were anxiety from uncertainty and reluctance to disclose uncertainty to patients. Hypothesized factors that would be associated with outcomes included attitude, social norm, perceived behavioral control, intention to implement SDM in practice, and socio-demographics. Stepwise linear regression was used to identify predictors of anxiety from uncertainty and reluctance to disclose uncertainty to patients. In multivariate analyses, anxiety from uncertainty was influenced by female gender (beta=0.483; p=0.0039), residency status (1st year: beta=0.600; p=0.001; 2nd year: beta=0.972; p<0.001), and number of hours worked per week (beta=-0.012; p=0.048). Reluctance to disclose uncertainty to patients was influenced by having more years in formal education (beta=-1.996; p=0.012). Variables associated with anxiety from uncertainty differ from those associated with reluctance to disclose uncertainty to patients. Given the importance of communicating uncertainty during SDM, measuring physicians' reactions to uncertainty is essential in SDM implementation studies. Copyright 2009 Elsevier Ireland Ltd. All rights reserved.

Subjective cognitive complaints, psychosocial factors and nursing work function in nurses providing direct patient care.

PubMed

Barbe, Tammy; Kimble, Laura P; Rubenstein, Cynthia

2018-04-01

The aim of this study was to examine relationships among subjective cognitive complaints, psychosocial factors and nursing work function in nurses providing direct patient care. Cognitive functioning is a critical component for nurses in the assurance of error prevention, identification and correction when caring for patients. Negative changes in nurses' cognitive and psychosocial functioning can adversely affect nursing care and patient outcomes. A descriptive correlational design with stratified random sampling. The sample included 96 nurses from the major geographic regions of the United States. Over 9 months in 2016-2017, data were collected using a web-based survey. Stepwise multiple linear regression analyses were used to examine relationships among subjective cognitive complaints, psychosocial factors and nursing work function. Overall, participants reported minimal work function impairment and low levels of subjective cognitive complaints, depression and stress. In multivariate analyses, depression was not associated with nurses' work function. However, perceived stress and subjective concerns about cognitive function were associated with greater impairment of work function. Nurses experiencing subjective cognitive complaints should be encouraged to address personal and environmental factors that are associated with their cognitive status. Additionally, stress reduction in nurses should be a high priority as a potential intervention to promote optimal functioning of nurses providing direct patient care. Healthcare institutions should integrate individual and institutional strategies to reduce factors contributing to workplace stress. © 2017 John Wiley & Sons Ltd.

Investigation of the key determinants of Asian nurses’ quality of life

PubMed Central

MAKABE, Sachiko; KOWITLAWAKUL, Yanika; NURUMAL, Mohd Said; TAKAGAI, Junko; WICHAIKHUM, Orn-Anong; WANGMO, Neyzang; YAP, Suk Foon; KUNAVIKTIKUL, Wipada; KOMATSU, Junko; SHIRAKAWA, Hideko; KIMURA, Yutaka; ASANUMA, Yoshihiro

2018-01-01

The study aimed to compare nurses’ quality of life and investigate key determinants among Asian countries with different economic status. A cross-sectional survey was conducted across five Asian countries (Japan, Singapore, Malaysia, Thailand, and Bhutan). Quality of life (WHOQOL-BREF), job stress (National Institute of Occupational Safety and Health questionnaire), and demographic data were assessed. Stepwise multivariate linear regression analysis was performed to identify the key determinants of quality of life. Participants were 3,829 nurses (response rate: 82%) with a mean age of 33 ± 10 yr and majority were women (92%). Regarding quality of life, Bhutan yielded the highest scores, followed by Malaysia, Thailand, Singapore, and Japan, and these results were statistically significant. The key determinants that were significantly related to quality of life were “stress coping ability,” “life satisfaction,” “Japan,” “social support,” “job stress,” and “Singapore” (adjusted R2=0.46). In conclusion, nurses’ quality of life differs across Asian countries and is not linked to the country’s economic development. To maintain a good quality of life for nurses, an international exchange program like international nursing conferences for work environment and staff coping strategies is recommended to broaden institution’ minds and share experiences and exchange views to be able to realize their own problems and discover global solutions to them. PMID:29491251

Emergency department blood transfusion: the first two units are free.

PubMed

Ley, Eric J; Liou, Douglas Z; Singer, Matthew B; Mirocha, James; Melo, Nicolas; Chung, Rex; Bukur, Marko; Salim, Ali

2013-09-01

Studies on blood product transfusions after trauma recommend targeting specific ratios to reduce mortality. Although crystalloid volumes as little as 1.5 L predict increased mortality after trauma, little data is available regarding the threshold of red blood cell (RBC) transfusion volume that predicts increased mortality. Data from a level I trauma center between January 2000 and December 2008 were reviewed. Trauma patients who received at least 100 mL RBC in the emergency department (ED) were included. Each unit of RBC was defined as 300 mL. Demographics, RBC transfusion volume, and mortality were analyzed in the nonelderly (<70 y) and elderly (≥70 y). Multivariate logistic regression was performed at various volume cutoffs to determine whether there was a threshold transfusion volume that independently predicted mortality. A total of 560 patients received ≥100 mL RBC in the ED. Overall mortality was 24.3%, with 22.5% (104 deaths) in the nonelderly and 32.7% (32 deaths) in the elderly. Multivariate logistic regression demonstrated that RBC transfusion of ≥900 mL was associated with increased mortality in both the nonelderly (adjusted odds ratio 2.06, P = 0.008) and elderly (adjusted odds ratio 5.08, P = 0.006). Although transfusion of greater than 2 units in the ED was an independent predictor of mortality, transfusion of 2 units or less was not. Interestingly, unlike crystalloid volume, stepwise increases in blood volume were not associated with stepwise increases in mortality. The underlying etiology for mortality discrepancies, such as transfusion ratios, hypothermia, or immunosuppression, needs to be better delineated. Copyright © 2013 Elsevier Inc. All rights reserved.

Determinants of brain-derived neurotrophic factor (BDNF) in umbilical cord and maternal serum.

PubMed

Flöck, A; Weber, S K; Ferrari, N; Fietz, C; Graf, C; Fimmers, R; Gembruch, U; Merz, W M

2016-01-01

Brain-derived neurotrophic factor (BDNF) plays a fundamental role in brain development; additionally, it is involved in various aspects of cerebral function, including neurodegenerative and psychiatric diseases. Involvement of BDNF in parturition has not been investigated. The aim of our study was to analyze determinants of umbilical cord BDNF (UC-BDNF) concentrations of healthy, term newborns and their respective mothers. This cross-sectional prospective study was performed at a tertiary referral center. Maternal venous blood samples were taken on admission to labor ward; newborn venous blood samples were drawn from the umbilical cord (UC), before delivery of the placenta. Analysis was performed with a commercially available immunoassay. Univariate analyses and stepwise multivariate regression models were applied. 120 patients were recruited. UC-BDNF levels were lower than maternal serum concentrations (median 641 ng/mL, IQR 506 vs. median 780 ng/mL, IQR 602). Correlation between UC- and maternal BDNF was low (R=0.251, p=0.01). In univariate analysis, mode of delivery (MoD), gestational age (GA), body mass index at delivery, and gestational diabetes were determinants of UC-BDNF (MoD and smoking for maternal BDNF, respectively). Stepwise multivariate regression analysis revealed a model with MoD and GA as determinants for UC-BDNF (MoD for maternal BDNF). MoD and GA at delivery are determinants of circulating BDNF in the mother and newborn. We hypothesize that BDNF, like other neuroendocrine factors, is involved in the neuroendocrine cascade of delivery. Timing and mode of delivery may exert BDNF-induced effects on the cerebral function of newborns and their mothers. Copyright © 2015 Elsevier Ltd. All rights reserved.

Yield of Cytology Surveillance After High-Grade Vulvar Intraepithelial Neoplasia or Cancer.

PubMed

Kuroki, Lindsay M; Frolova, Antonina I; Wu, Ningying; Liu, Jingxia; Powell, Matthew; Thaker, Premal H; Massad, L Stewart

2017-07-01

The aim of the study was to estimate the risk of high-grade cervical and vaginal intraepithelial neoplasia (CIN/VAIN 2+) and cancer among women treated surgically for high-grade vulvar intraepithelial neoplasia (HGVIN) and vulvar cancer. We performed a retrospective cohort study of women who underwent surgery for HGVIN/vulvar cancer between 2006 and 2010. Univariate and multivariate analyses using stepwise selection were used to identify correlates of abnormal cytology after treatment for VIN and vulvar cancer. Among 191 women under surveillance for a median of 3.7 years who underwent treatment for HGVIN/vulvar cancer, primary vulvar lesions included VIN 2 (10, 5%), VIN 3 (102, 53%), and carcinoma (79, 41%). During follow-up, 71 (37%) had abnormal cytology, including 47 (25%) low grade, 23 (12%) high grade, and 1 (0.5%) carcinoma. Subsequent risk for VAIN 2+ was 11% (6/57) after previous hysterectomy and 8% for CIN 2+ (10/124) with intact cervix. Overall risk for CIN 3+ was 5%. Correlates of high-grade cytology after treatment for HGVIN/vulvar cancer included nonwhite race (odds ratio [OR] = 3.3, 95% CI = 1.50-7.36), immunodeficiency (OR = 4.2, 95% CI = 1.76-9.94), and previous abnormal cytology (OR = 2.7, 95% CI = 1.29-5.78). Stepwise multivariate analysis revealed immunosuppression as the only significant correlate of high-grade cytology after vulvar treatment (adjusted OR = 3.7, 95% CI = 1.26-10.83). Women with HGVIN/cancer should have cervical/vaginal cytology before vulvar surgery. Those with a negative cervical or vaginal cytology result should undergo cytology testing at 1- to 3-year intervals, based on the threshold for CIN 3+ set forth by the American Society for Colposcopy and Cervical Pathology.

Developing screening services for colorectal cancer on Android smartphones.

PubMed

Wu, Hui-Ching; Chang, Chiao-Jung; Lin, Chun-Che; Tsai, Ming-Chang; Chang, Che-Chia; Tseng, Ming-Hseng

2014-08-01

Colorectal cancer (CRC) is an important health problem in Western countries and also in Asia. It is the third leading cause of cancer deaths in both men and women in Taiwan. According to the well-known adenoma-to-carcinoma sequence, the majority of CRC develops from colorectal adenomatous polyps. This concept provides the rationale for screening and prevention of CRC. Removal of colorectal adenoma could reduce the mortality and incidence of CRC. Mobile phones are now playing an ever more crucial role in people's daily lives. The latest generation of smartphones is increasingly viewed as hand-held computers rather than as phones, because of their powerful on-board computing capability, capacious memories, large screens, and open operating systems that encourage development of applications (apps). If we can detect the potential CRC patients early and offer them appropriate treatments and services, this would not only promote the quality of life, but also reduce the possible serious complications and medical costs. In this study, an intelligent CRC screening app on Android™ (Google™, Mountain View, CA) smartphones has been developed based on a data mining approach using decision tree algorithms. For comparison, the stepwise backward multivariate logistic regression model and the fecal occult blood test were also used. Compared with the stepwise backward multivariate logistic regression model and the fecal occult blood test, the proposed app system not only provides an easy and efficient way to quickly detect high-risk groups of potential CRC patients, but also brings more information about CRC to customer-oriented services. We developed and implemented an app system on Android platforms for ubiquitous healthcare services for CRC screening. It can assist people in achieving early screening, diagnosis, and treatment purposes, prevent the occurrence of complications, and thus reach the goal of preventive medicine.

The relation of digital vascular function to cardiovascular risk factors in African-Americans using digital tonometry: the Jackson Heart Study.

PubMed

McClendon, Eric E; Musani, Solomon K; Samdarshi, Tandaw E; Khaire, Sushant; Stokes, Donny; Hamburg, Naomi M; Sheffy, Koby; Mitchell, Gary F; Taylor, Herman R; Benjamin, Emelia J; Fox, Ervin R

2017-06-01

Digital vascular tone and function, as measured by peripheral arterial tonometry (PAT), are associated with cardiovascular risk and events in non-Hispanic whites. There are limited data on relations between PAT and cardiovascular risk in African-Americans. PAT was performed on a subset of Jackson Heart Study participants using a fingertip tonometry device. Resting digital vascular tone was assessed as baseline pulse amplitude. Hyperemic vascular response to 5 minutes of ischemia was expressed as the PAT ratio (hyperemic/baseline amplitude ratio). Peripheral augmentation index (AI), a measure of relative wave reflection, also was estimated. The association of baseline pulse amplitude (PA), PAT ratio, and AI to risk factors was assessed using stepwise multivariable models. The study sample consisted of 837 participants from the Jackson Heart Study (mean age, 54 ± 11 years; 61% women). In stepwise multivariable regression models, baseline pulse amplitude was related to male sex, body mass index, and diastolic blood pressure (BP), accounting for 16% of the total variability of the baseline pulse amplitude. Age, male sex, systolic BP, diastolic BP, antihypertensive medication, and prevalent cardiovascular disease contributed to 11% of the total variability of the PAT ratio. Risk factors (primarily age, sex, and heart rate) explained 47% of the total variability of the AI. We confirmed in our cohort of African-Americans, a significant relation between digital vascular tone and function measured by PAT and multiple traditional cardiovascular risk factors. Further studies are warranted to investigate the utility of these measurements in predicting clinical outcomes in African-Americans. Copyright © 2017 American Society of Hypertension. Published by Elsevier Inc. All rights reserved.

Serum chemerin levels are independently associated with quality of life in colorectal cancer survivors: A pilot study

PubMed Central

Lee, Jee-Yon; Lee, Mi-Kyung; Kim, Nam-Kyu; Chu, Sang-Hui; Lee, Duk-Chul; Lee, Hye-Sun

2017-01-01

Background Colorectal cancer (CRC) survivors are known to experience various symptoms that significantly affect their quality of life (QOL); therefore, it is important to identify clinical markers related with CRC survivor QOL. Here we investigated the relationship between serum chemerin levels, a newly identified proinflammatory adipokine, and QOL in CRC survivors. Methods A data of total of 110 CRC survivors were analysed in the study. Serum chemerin levels were measured with an enzyme immunoassay analyser. Functional Assessment of Cancer Therapy (FACT) scores were used as an indicator of QOL in CRC survivors. Results Weak but not negligible relationships were observed between serum chemerin levels and FACT-General (G) (r = -0.22, p<0.02), FACT-Colorectal cancer (C) (r = -0.23, p<0.02) and FACT-Fatigue (F) scores (r = -0.27, p<0.01) after adjusting for confounding factors. Both stepwise and enter method multiple linear regression analyses confirmed that serum chemerin levels were independently associated with FACT-G (stepwise: β = -0.15, p<0.01; enter: β = -0.12, p = 0.02), FACT-C (stepwise: β = -0.19, p<0.01; enter; β = -0.14, p = 0.02) and FACT-F scores (stepwise: β = -0.23, p<0.01; enter: β = -0.20, p<0.01). Conclusions Our results demonstrate a weak inverse relationship between serum chemerin and CRC survivor QOL. Although it is impossible to determine causality, our findings suggest that serum chemerin levels may have a significant association with CRC survivor QOL. Further prospective studies are required to confirm the clinical significance of our pilot study. PMID:28475614

K/Ar dating of lunar soils. IV - Orange glass from 74220 and agglutinates from 14259 and 14163

NASA Technical Reports Server (NTRS)

Alexander, E. C., Jr.; Coscio, M. R., Jr.; Dragon, J. C.; Saito, K.

1980-01-01

Total fusion Ar-40 - A-39 analyses of orange glass from lunar soil 74220 combined with the sums of earlier stepwise heating data by other workers have yielded a precise K/Ar isochron with a slope corresponding to an age of 3.66 + or - 0.03 G.y. for the orange glass. The result is in marginal agreement with Huneke's (1978) age of 3.60 + or - 0.04 G.y. for 74220 glass. The Ar systematics in the agglutinates from 14259 and 14163 are dominated by volume correlated argon. Step-wise heating analyses yield data which define experimentally reproducible linear arrays in Ar-40/Ar-36 vs. K-40/Ar-36 diagrams. The slopes of these arrays correspond formally to very old ages, but it is not clear, however, that such ages have any physical significance.

Motor Nerve Conduction Velocity In Postmenopausal Women with Peripheral Neuropathy.

PubMed

Singh, Akanksha; Asif, Naiyer; Singh, Paras Nath; Hossain, Mohd Mobarak

2016-12-01

The post-menopausal phase is characterized by a decline in the serum oestrogen and progesterone levels. This phase is also associated with higher incidence of peripheral neuropathy. To explore the relationship between the peripheral motor nerve status and serum oestrogen and progesterone levels through assessment of Motor Nerve Conduction Velocity (MNCV) in post-menopausal women with peripheral neuropathy. This cross-sectional study was conducted at Jawaharlal Nehru Medical College during 2011-2013. The study included 30 post-menopausal women with peripheral neuropathy (age: 51.4±7.9) and 30 post-menopausal women without peripheral neuropathy (control) (age: 52.5±4.9). They were compared for MNCV in median, ulnar and common peroneal nerves and serum levels of oestrogen and progesterone estimated through enzyme immunoassays. To study the relationship between hormone levels and MNCV, a stepwise linear regression analysis was done. The post-menopausal women with peripheral neuropathy had significantly lower MNCV and serum oestrogen and progesterone levels as compared to control subjects. Stepwise linear regression analysis showed oestrogen with main effect on MNCV. The findings of the present study suggest that while the post-menopausal age group is at a greater risk of peripheral neuropathy, it is the decline in the serum estrogen levels which is critical in the development of peripheral neuropathy.

Predicting Retention Times of Naturally Occurring Phenolic Compounds in Reversed-Phase Liquid Chromatography: A Quantitative Structure-Retention Relationship (QSRR) Approach

PubMed Central

Akbar, Jamshed; Iqbal, Shahid; Batool, Fozia; Karim, Abdul; Chan, Kim Wei

2012-01-01

Quantitative structure-retention relationships (QSRRs) have successfully been developed for naturally occurring phenolic compounds in a reversed-phase liquid chromatographic (RPLC) system. A total of 1519 descriptors were calculated from the optimized structures of the molecules using MOPAC2009 and DRAGON softwares. The data set of 39 molecules was divided into training and external validation sets. For feature selection and mapping we used step-wise multiple linear regression (SMLR), unsupervised forward selection followed by step-wise multiple linear regression (UFS-SMLR) and artificial neural networks (ANN). Stable and robust models with significant predictive abilities in terms of validation statistics were obtained with negation of any chance correlation. ANN models were found better than remaining two approaches. HNar, IDM, Mp, GATS2v, DISP and 3D-MoRSE (signals 22, 28 and 32) descriptors based on van der Waals volume, electronegativity, mass and polarizability, at atomic level, were found to have significant effects on the retention times. The possible implications of these descriptors in RPLC have been discussed. All the models are proven to be quite able to predict the retention times of phenolic compounds and have shown remarkable validation, robustness, stability and predictive performance. PMID:23203132

The Val158Met COMT polymorphism is a modifier of the age at onset in Parkinson's disease with a sexual dimorphism

PubMed Central

Klebe, Stephan; Golmard, Jean-Louis; Nalls, Michael A; Saad, Mohamad; Singleton, Andrew B; Bras, Jose M; Hardy, John; Simon-Sanchez, Javier; Heutink, Peter; Kuhlenbäumer, Gregor; Charfi, Rim; Klein, Christine; Hagenah, Johann; Gasser, Thomas; Wurster, Isabel; Lesage, Suzanne; Lorenz, Delia; Deuschl, Günther; Durif, Franck; Pollak, Pierre; Damier, Philippe; Tison, François; Durr, Alexandra; Amouyel, Philippe; Lambert, Jean-Charles; Tzourio, Christophe; Maubaret, Cécilia; Charbonnier-Beaupel, Fanny; Tahiri, Khadija; Vidailhet, Marie; Martinez, Maria; Brice, Alexis; Corvol, Jean-Christophe

2013-01-01

The catechol-O-methyltranferase (COMT) is one of the main enzymes that metabolise dopamine in the brain. The Val158Met polymorphism in the COMT gene (rs4680) causes a trimodal distribution of high (Val/Val), intermediate (Val/Met) and low (Met/Met) enzyme activity. We tested whether the Val158Met polymorphism is a modifier of the age at onset (AAO) in Parkinson's disease (PD). The rs4680 was genotyped in a total of 16 609 subjects from five independent cohorts of European and North American origin (5886 patients with PD and 10 723 healthy controls). The multivariate analysis for comparing PD and control groups was based on a stepwise logistic regression, with gender, age and cohort origin included in the initial model. The multivariate analysis of the AAO was a mixed linear model, with COMT genotype and gender considered as fixed effects and cohort and cohort-gender interaction as random effects. COMT genotype was coded as a quantitative variable, assuming a codominant genetic effect. The distribution of the COMT polymorphism was not significantly different in patients and controls (p=0.22). The Val allele had a significant effect on the AAO with a younger AAO in patients with the Val/Val (57.1±13.9, p=0.03) than the Val/Met (57.4±13.9) and the Met/Met genotypes (58.3±13.5). The difference was greater in men (1.9 years between Val/Val and Met/Met, p=0.007) than in women (0.2 years, p=0.81). Thus, the Val158Met COMT polymorphism is not associated with PD in the Caucasian population but acts as a modifier of the AAO in PD with a sexual dimorphism: the Val allele is associated with a younger AAO in men with idiopathic PD. PMID:23408064

The Gutenberg health study: associations between occupational and private stress factors and work-privacy conflict.

PubMed

Garthus-Niegel, Susan; Hegewald, Janice; Seidler, Andreas; Nübling, Matthias; Espinola-Klein, Christine; Liebers, Falk; Wild, Philipp S; Latza, Ute; Letzel, Stephan

2016-02-29

Work-privacy conflict (WPC) is no longer a rarity but constitutes a societal problem. The objectives of the present study were (1) to investigate the distribution and prevalence of WPC among the employed participants in the Gutenberg Health Study at baseline and (2) to study the dependence of WPC on a broad range of private life and occupational characteristics as well as on psychosocial working conditions. This analysis is based on a representative, population-based sample of 3,709 employees participating in the Gutenberg Health Study. Descriptive and bivariable analyses were carried out separately for women and men. Distribution and prevalence of WPC were examined according to socio-demographic and occupational characteristics as well as psychosocial working conditions. Further, stepwise selection of Poisson log-linear regression models were performed to determine which socio-demographic and occupational characteristics were most associated with the outcome variable WPC and to obtain adjusted prevalence ratios from the final model. The multivariable analyses were conducted both separately for women and men and with all subjects together in one analysis. There was a high prevalence of WPC in the present study (27.4 % of the men and 23.0 % of the women reported a high or very high WPC). A variety of factors was associated with WPC, e.g. full-time employment, depression and many of the psychosocial risk factors at work. Also, the multivariable results showed that women were of higher risk for a WPC. By affecting the individual work life, home life, and the general well-being and health, WPC may lead to detrimental effects in employees, their families, employers, and society as a whole. Therefore, the high prevalence of WPC in our sample should be of concern. Among women, the risk for suffering from WPC was even higher, most likely due to multiple burdens.

Multi-disease analysis of maternal antibody decay using non-linear mixed models accounting for censoring.

PubMed

Goeyvaerts, Nele; Leuridan, Elke; Faes, Christel; Van Damme, Pierre; Hens, Niel

2015-09-10

Biomedical studies often generate repeated measures of multiple outcomes on a set of subjects. It may be of interest to develop a biologically intuitive model for the joint evolution of these outcomes while assessing inter-subject heterogeneity. Even though it is common for biological processes to entail non-linear relationships, examples of multivariate non-linear mixed models (MNMMs) are still fairly rare. We contribute to this area by jointly analyzing the maternal antibody decay for measles, mumps, rubella, and varicella, allowing for a different non-linear decay model for each infectious disease. We present a general modeling framework to analyze multivariate non-linear longitudinal profiles subject to censoring, by combining multivariate random effects, non-linear growth and Tobit regression. We explore the hypothesis of a common infant-specific mechanism underlying maternal immunity using a pairwise correlated random-effects approach and evaluating different correlation matrix structures. The implied marginal correlation between maternal antibody levels is estimated using simulations. The mean duration of passive immunity was less than 4 months for all diseases with substantial heterogeneity between infants. The maternal antibody levels against rubella and varicella were found to be positively correlated, while little to no correlation could be inferred for the other disease pairs. For some pairs, computational issues occurred with increasing correlation matrix complexity, which underlines the importance of further developing estimation methods for MNMMs. Copyright © 2015 John Wiley & Sons, Ltd.

Analytical framework for reconstructing heterogeneous environmental variables from mammal community structure.

PubMed

Louys, Julien; Meloro, Carlo; Elton, Sarah; Ditchfield, Peter; Bishop, Laura C

2015-01-01

We test the performance of two models that use mammalian communities to reconstruct multivariate palaeoenvironments. While both models exploit the correlation between mammal communities (defined in terms of functional groups) and arboreal heterogeneity, the first uses a multiple multivariate regression of community structure and arboreal heterogeneity, while the second uses a linear regression of the principal components of each ecospace. The success of these methods means the palaeoenvironment of a particular locality can be reconstructed in terms of the proportions of heavy, moderate, light, and absent tree canopy cover. The linear regression is less biased, and more precisely and accurately reconstructs heavy tree canopy cover than the multiple multivariate model. However, the multiple multivariate model performs better than the linear regression for all other canopy cover categories. Both models consistently perform better than randomly generated reconstructions. We apply both models to the palaeocommunity of the Upper Laetolil Beds, Tanzania. Our reconstructions indicate that there was very little heavy tree cover at this site (likely less than 10%), with the palaeo-landscape instead comprising a mixture of light and absent tree cover. These reconstructions help resolve the previous conflicting palaeoecological reconstructions made for this site. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed

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

2017-08-24

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

Statistical analysis of Thematic Mapper Simulator data for the geobotanical discrimination of rock types in southwest Oregon

NASA Technical Reports Server (NTRS)

Morrissey, L. A.; Weinstock, K. J.; Mouat, D. A.; Card, D. H.

1984-01-01

An evaluation of Thematic Mapper Simulator (TMS) data for the geobotanical discrimination of rock types based on vegetative cover characteristics is addressed in this research. A methodology for accomplishing this evaluation utilizing univariate and multivariate techniques is presented. TMS data acquired with a Daedalus DEI-1260 multispectral scanner were integrated with vegetation and geologic information for subsequent statistical analyses, which included a chi-square test, an analysis of variance, stepwise discriminant analysis, and Duncan's multiple range test. Results indicate that ultramafic rock types are spectrally separable from nonultramafics based on vegetative cover through the use of statistical analyses.

Associations with substance abuse treatment completion in drug court

PubMed Central

Brown, Randall T

2009-01-01

Subjects in the study included all participants (N = 573) in drug treatment court in a mid-sized U.S. city from 1996 through 2004. Administrative data from the drug court included measures of demographics and socioeconomics, substance use, and criminal justice history. Stepwise multivariate logistic regression yielded a final model of failure to complete drug treatment. Unemployment, lower educational attainment, and cocaine use disorders were associated with failure to complete treatment. The limitations of administrative data should be considered in the interpretation of results. Funding was provided by the National Institutes of Health, National Institute on Drug Abuse (1 K23 DA017283-01). PMID:20380560

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

On non-autonomous dynamical systems

NASA Astrophysics Data System (ADS)

Anzaldo-Meneses, A.

2015-04-01

In usual realistic classical dynamical systems, the Hamiltonian depends explicitly on time. In this work, a class of classical systems with time dependent nonlinear Hamiltonians is analyzed. This type of problems allows to find invariants by a family of Veronese maps. The motivation to develop this method results from the observation that the Poisson-Lie algebra of monomials in the coordinates and momenta is clearly defined in terms of its brackets and leads naturally to an infinite linear set of differential equations, under certain circumstances. To perform explicit analytic and numerical calculations, two examples are presented to estimate the trajectories, the first given by a nonlinear problem and the second by a quadratic Hamiltonian with three time dependent parameters. In the nonlinear problem, the Veronese approach using jets is shown to be equivalent to a direct procedure using elliptic functions identities, and linear invariants are constructed. For the second example, linear and quadratic invariants as well as stability conditions are given. Explicit solutions are also obtained for stepwise constant forces. For the quadratic Hamiltonian, an appropriated set of coordinates relates the geometric setting to that of the three dimensional manifold of central conic sections. It is shown further that the quantum mechanical problem of scattering in a superlattice leads to mathematically equivalent equations for the wave function, if the classical time is replaced by the space coordinate along a superlattice. The mathematical method used to compute the trajectories for stepwise constant parameters can be applied to both problems. It is the standard method in quantum scattering calculations, as known for locally periodic systems including a space dependent effective mass.

Local repair of stoma prolapse: Case report of an in vivo application of linear stapler devices.

PubMed

Monette, Margaret M; Harney, Rodney T; Morris, Melanie S; Chu, Daniel I

2016-11-01

One of the most common late complications following stoma construction is prolapse. Although the majority of prolapse can be managed conservatively, surgical revision is required with incarceration/strangulation and in certain cases laparotomy and/or stoma reversal are not appropriate. This report will inform surgeons on safe and effective approaches to revising prolapsed stomas using local techniques. A 58 year old female with an obstructing rectal cancer previously received a diverting transverse loop colostomy. On completion of neoadjuvant treatment, re-staging found new lung metastases. She was scheduled for further chemotherapy but incarcerated a prolapsed segment of her loop colostomy. As there was no plan to resect her primary rectal tumor at the time, a local revision was preferred. Linear staplers were applied to the prolapsed stoma in step-wise fashion to locally revise the incarcerated prolapse. Post-operative recovery was satisfactory with no complications or recurrence of prolapse. We detail in step-wise fashion a technique using linear stapler devices that can be used to locally revise prolapsed stoma segments and therefore avoid a laparotomy. The procedure is technically easy to perform with satisfactory post-operative outcomes. We additionally review all previous reports of local repairs and show the evolution of local prolapse repair to the currently reported technique. This report offers surgeons an alternative, efficient and effective option for addressing the complications of stoma prolapse. While future studies are needed to assess long-term outcomes, in the short-term, our report confirms the safety and effectiveness of this local technique.

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

PubMed

Liu, Shijian; Wilson, James G; Jiang, Fan; Griswold, Michael; Correa, Adolfo; Mei, Hao

2016-11-30

Genome-wide association study (GWAS) has been successful in identifying obesity risk genes by single-variant association analysis. For this study, we designed steps of analysis strategy and aimed to identify multi-variant effects on obesity risk among candidate genes. Our analyses were focused on 2137 African American participants with body mass index measured in the Jackson Heart Study and 657 common single nucleotide polymorphisms (SNPs) genotyped at 8 GWAS-identified obesity risk genes. Single-variant association test showed that no SNPs reached significance after multiple testing adjustment. The following gene-gene interaction analysis, which was focused on SNPs with unadjusted p-value<0.10, identified 6 significant multi-variant associations. Logistic regression showed that SNPs in these associations did not have significant linear interactions; examination of genetic risk score evidenced that 4 multi-variant associations had significant additive effects of risk SNPs; and haplotype association test presented that all multi-variant associations contained one or several combinations of particular alleles or haplotypes, associated with increased obesity risk. Our study evidenced that obesity risk genes generated multi-variant effects, which can be additive or non-linear interactions, and multi-variant study is an important supplement to existing GWAS for understanding genetic effects of obesity risk genes. Copyright © 2016 Elsevier B.V. All rights reserved.

High-throughput quantitative biochemical characterization of algal biomass by NIR spectroscopy; multiple linear regression and multivariate linear regression analysis.

PubMed

Laurens, L M L; Wolfrum, E J

2013-12-18

One of the challenges associated with microalgal biomass characterization and the comparison of microalgal strains and conversion processes is the rapid determination of the composition of algae. We have developed and applied a high-throughput screening technology based on near-infrared (NIR) spectroscopy for the rapid and accurate determination of algal biomass composition. We show that NIR spectroscopy can accurately predict the full composition using multivariate linear regression analysis of varying lipid, protein, and carbohydrate content of algal biomass samples from three strains. We also demonstrate a high quality of predictions of an independent validation set. A high-throughput 96-well configuration for spectroscopy gives equally good prediction relative to a ring-cup configuration, and thus, spectra can be obtained from as little as 10-20 mg of material. We found that lipids exhibit a dominant, distinct, and unique fingerprint in the NIR spectrum that allows for the use of single and multiple linear regression of respective wavelengths for the prediction of the biomass lipid content. This is not the case for carbohydrate and protein content, and thus, the use of multivariate statistical modeling approaches remains necessary.

Linear combination methods to improve diagnostic/prognostic accuracy on future observations

PubMed Central

Kang, Le; Liu, Aiyi; Tian, Lili

2014-01-01

Multiple diagnostic tests or biomarkers can be combined to improve diagnostic accuracy. The problem of finding the optimal linear combinations of biomarkers to maximise the area under the receiver operating characteristic curve has been extensively addressed in the literature. The purpose of this article is threefold: (1) to provide an extensive review of the existing methods for biomarker combination; (2) to propose a new combination method, namely, the nonparametric stepwise approach; (3) to use leave-one-pair-out cross-validation method, instead of re-substitution method, which is overoptimistic and hence might lead to wrong conclusion, to empirically evaluate and compare the performance of different linear combination methods in yielding the largest area under receiver operating characteristic curve. A data set of Duchenne muscular dystrophy was analysed to illustrate the applications of the discussed combination methods. PMID:23592714

A multiple linear regression analysis of hot corrosion attack on a series of nickel base turbine alloys

NASA Technical Reports Server (NTRS)

Barrett, C. A.

1985-01-01

Multiple linear regression analysis was used to determine an equation for estimating hot corrosion attack for a series of Ni base cast turbine alloys. The U transform (i.e., 1/sin (% A/100) to the 1/2) was shown to give the best estimate of the dependent variable, y. A complete second degree equation is described for the centered" weight chemistries for the elements Cr, Al, Ti, Mo, W, Cb, Ta, and Co. In addition linear terms for the minor elements C, B, and Zr were added for a basic 47 term equation. The best reduced equation was determined by the stepwise selection method with essentially 13 terms. The Cr term was found to be the most important accounting for 60 percent of the explained variability hot corrosion attack.

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

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

Echocardiographic Linear Fractional Shortening for Quantification of Right Ventricular Systolic Function - a Cardiac Magnetic Resonance Validation Study

PubMed Central

Srinivasan, Aparna; Kim, Jiwon; Khalique, Omar; Geevarghese, Alexi; Rusli, Melissa; Shah, Tara; Di Franco, Antonino; Alakbarli, Javid; Goldburg, Samantha; Rozenstrauch, Meenakshi; Devereux, Richard B.; Weinsaft, Jonathan W.

2017-01-01

Background Echocardiography (Echo)-based linear fractional shortening (FS) is widely used to assess left ventricular dysfunction (LVdys), but has not been systematically tested for right ventricular dysfunction (RVdys). Methods The population comprised LVdys patients with and without RVdys (EF<50%) on cardiac MRI (CMR): Echo included standard RV indices (fractional area change [FAC], TAPSE, S’ and FS in parasternal long axis (RV outflow tract [RVOT]) and apical 4-chamber views (width [RVWD], length [RVLG]). Results 168 patients underwent echo and CMR (3±3 days); FAC (46±9 vs. 28±11), TAPSE (1.9±0.4 vs. 1.5±0.3) and S’ (11.4±2.3 vs. 10.0±2.6, all p≤ 0.001) were lower among RVdys patients, as were FS indices (RVOT 32±8 vs 17±10 | RVWD 40±11 vs 22±12 | RVLG 16±5 vs 9±4%; all p<0.001). FS indices yielded similar magnitude of correlation with CMR RVEF (r=0.73–0.56) as did FAC (r=0.70), which was slightly higher than TAPSE (r=0.47) and S’ (r=0.31; all p<0.001). FS indices decreased stepwise vs. CMR RVEF tertiles, as did FAC (all p<0.001). In multivariate analysis, FS in RVOT (regression coefficient 0.51 [CI 0.37–0.65]), RVWD (0.30 [0.19–0.41]), and RVLG (0.45 [0.20–0.71]; all p≤ 0.001) were independently associated with CMR RVEF. FS indices yielded good overall diagnostic performance (AUC: RVOT 0.89 [CI 0.82–0.97] | RVWD 0.87 [0.78–0.96] | RVLG 0.80 [0.70–0.90]; all p<0.001) for CMR-defined RVdy (RVEF<50%). Conclusions RV linear FS provides RV functional indices that parallel CMR RVEF. Parasternal long-axis RVOT width, 4-chamber RV width and length are independently associated with RVEF, supporting use of multiple FS indices for RV functional assessment. PMID:28247463

Quantitative structure-activity relationship of the curcumin-related compounds using various regression methods

NASA Astrophysics Data System (ADS)

Khazaei, Ardeshir; Sarmasti, Negin; Seyf, Jaber Yousefi

2016-03-01

Quantitative structure activity relationship were used to study a series of curcumin-related compounds with inhibitory effect on prostate cancer PC-3 cells, pancreas cancer Panc-1 cells, and colon cancer HT-29 cells. Sphere exclusion method was used to split data set in two categories of train and test set. Multiple linear regression, principal component regression and partial least squares were used as the regression methods. In other hand, to investigate the effect of feature selection methods, stepwise, Genetic algorithm, and simulated annealing were used. In two cases (PC-3 cells and Panc-1 cells), the best models were generated by a combination of multiple linear regression and stepwise (PC-3 cells: r2 = 0.86, q2 = 0.82, pred_r2 = 0.93, and r2m (test) = 0.43, Panc-1 cells: r2 = 0.85, q2 = 0.80, pred_r2 = 0.71, and r2m (test) = 0.68). For the HT-29 cells, principal component regression with stepwise (r2 = 0.69, q2 = 0.62, pred_r2 = 0.54, and r2m (test) = 0.41) is the best method. The QSAR study reveals descriptors which have crucial role in the inhibitory property of curcumin-like compounds. 6ChainCount, T_C_C_1, and T_O_O_7 are the most important descriptors that have the greatest effect. With a specific end goal to design and optimization of novel efficient curcumin-related compounds it is useful to introduce heteroatoms such as nitrogen, oxygen, and sulfur atoms in the chemical structure (reduce the contribution of T_C_C_1 descriptor) and increase the contribution of 6ChainCount and T_O_O_7 descriptors. Models can be useful in the better design of some novel curcumin-related compounds that can be used in the treatment of prostate, pancreas, and colon cancers.

Evidence for the Stepwise Stress Model: Gambusia holbrooki and Daphnia magna under acid mine drainage and acidified reference water stress.

PubMed

Gerhardt, Almut; Janssens de Bisthoven, Luc; Soares, Amadeu M V

2005-06-01

The Stepwise Stress Model (SSM) states that a cascade of regulative behavioral responses with different intrinsic sensitivities and threshold values offers increased behavioral plasticity and thus a wider range of tolerance for environmental changes or pollutant exposures. We tested the SSM with a widely introduced fish Gambusia holbrooki (Girard) (Pisces, Poeciliidae) and the standard laboratory test species Daphnia magna Straus (Crustacea, Daphniidae). The stress was simulated by short-term exposure to acid mine drainage (AMD) and to acidified reference water (ACID). Recording of behavioral responses with the multispecies freshwater biomonitor (MFB) generated continuous time-dependent dose-response data that were modeled in three-dimensional (3D) surface plots. Both the pH-dependent mortalities and the strong linear correlations between pH and aqueous metals confirmed the toxicity of the AMD and ACID gradients, respectively, for fish and Daphnia, the latter being more sensitive. AMD stress at pH < or = 5.5 amplified circadian rhythmicity in both species, while ACID stress did so only in G. holbrooki. A behavioral stepwise stress response was found in both species: D. magna decreased locomotion and ventilation (first step) (AMD, ACID), followed by increased ventilation (second step) (AMD). G. holbrooki decreased locomotion (first step) (AMD, ACID) and increased ventilation at intermediate pH levels (second step) (AMD). Both species, although from different taxonomic groups and feeding habits, followed the SSM, which might be expanded to a general concept for describing the behavioral responses of aquatic organims to pollution. Stepwise stress responses might be applied in online biomonitors to provide more sensitive and graduated alarm settings, hence optimizing the "early warning" detection of pollution waves.

Multivariate Profiles of Selected versus Non-Selected Elite Youth Brazilian Soccer Players

PubMed Central

Alves, Isabella S.; Padilha, Maickel B.; Casanova, Filipe; Puggina, Enrico F.; Maia, José

2017-01-01

Abstract This study determined whether a multivariate profile more effectively discriminated selected than non-selected elite youth Brazilian soccer players. This examination was carried out on 66 youth soccer players (selected, n = 28, mean age 16.3 ± 0.1; non-selected, n = 38, mean age 16.7 ± 0.4) using objective instruments. Multivariate profiles were assessed through anthropometric characteristics, biological maturation, tactical-technical skills, and motor performance. The Student’s t-test identified that selected players exhibited significantly higher values for height (t = 2.331, p = 0.02), lean body mass (t = 2.441, p = 0.01), and maturity offset (t = 4.559, p < 0.001), as well as performed better in declarative tactical knowledge (t = 10.484, p < 0.001), shooting (t = 2.188, p = 0.03), dribbling (t = 5.914, p < 0.001), speed – 30 m (t = 8.304, p < 0.001), countermovement jump (t = 2.718, p = 0.008), and peak power tests (t = 2.454, p = 0.01). Forward stepwise discriminant function analysis showed that declarative tactical knowledge, running speed –30 m, maturity offset, dribbling, height, and peak power correctly classified 97% of the selected players. These findings may have implications for a highly efficient selection process with objective measures of youth players in soccer clubs. PMID:29339991

Nonlinear multivariate and time series analysis by neural network methods

NASA Astrophysics Data System (ADS)

Hsieh, William W.

2004-03-01

Methods in multivariate statistical analysis are essential for working with large amounts of geophysical data, data from observational arrays, from satellites, or from numerical model output. In classical multivariate statistical analysis, there is a hierarchy of methods, starting with linear regression at the base, followed by principal component analysis (PCA) and finally canonical correlation analysis (CCA). A multivariate time series method, the singular spectrum analysis (SSA), has been a fruitful extension of the PCA technique. The common drawback of these classical methods is that only linear structures can be correctly extracted from the data. Since the late 1980s, neural network methods have become popular for performing nonlinear regression and classification. More recently, neural network methods have been extended to perform nonlinear PCA (NLPCA), nonlinear CCA (NLCCA), and nonlinear SSA (NLSSA). This paper presents a unified view of the NLPCA, NLCCA, and NLSSA techniques and their applications to various data sets of the atmosphere and the ocean (especially for the El Niño-Southern Oscillation and the stratospheric quasi-biennial oscillation). These data sets reveal that the linear methods are often too simplistic to describe real-world systems, with a tendency to scatter a single oscillatory phenomenon into numerous unphysical modes or higher harmonics, which can be largely alleviated in the new nonlinear paradigm.

Transition from a multiport technique to a single-port technique for lung cancer surgery: is lymph node dissection inferior using the single-port technique?†.

PubMed

Liu, Chia-Chuan; Shih, Chih-Shiun; Pennarun, Nicolas; Cheng, Chih-Tao

2016-01-01

The feasibility and radicalism of lymph node dissection for lung cancer surgery by a single-port technique has frequently been challenged. We performed a retrospective cohort study to investigate this issue. Two chest surgeons initiated multiple-port thoracoscopic surgery in a 180-bed cancer centre in 2005 and shifted to a single-port technique gradually after 2010. Data, including demographic and clinical information, from 389 patients receiving multiport thoracoscopic lobectomy or segmentectomy and 149 consecutive patients undergoing either single-port lobectomy or segmentectomy for primary non-small-cell lung cancer were retrieved and entered for statistical analysis by multivariable linear regression models and Box-Cox transformed multivariable analysis. The mean number of total dissected lymph nodes in the lobectomy group was 28.5 ± 11.7 for the single-port group versus 25.2 ± 11.3 for the multiport group; the mean number of total dissected lymph nodes in the segmentectomy group was 19.5 ± 10.8 for the single-port group versus 17.9 ± 10.3 for the multiport group. In linear multivariable and after Box-Cox transformed multivariable analyses, the single-port approach was still associated with a higher total number of dissected lymph nodes. The total number of dissected lymph nodes for primary lung cancer surgery by single-port video-assisted thoracoscopic surgery (VATS) was higher than by multiport VATS in univariable, multivariable linear regression and Box-Cox transformed multivariable analyses. This study confirmed that highly effective lymph node dissection could be achieved through single-port VATS in our setting. © The Author 2015. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Comprehensive drought characteristics analysis based on a nonlinear multivariate drought index

NASA Astrophysics Data System (ADS)

Yang, Jie; Chang, Jianxia; Wang, Yimin; Li, Yunyun; Hu, Hui; Chen, Yutong; Huang, Qiang; Yao, Jun

2018-02-01

It is vital to identify drought events and to evaluate multivariate drought characteristics based on a composite drought index for better drought risk assessment and sustainable development of water resources. However, most composite drought indices are constructed by the linear combination, principal component analysis and entropy weight method assuming a linear relationship among different drought indices. In this study, the multidimensional copulas function was applied to construct a nonlinear multivariate drought index (NMDI) to solve the complicated and nonlinear relationship due to its dependence structure and flexibility. The NMDI was constructed by combining meteorological, hydrological, and agricultural variables (precipitation, runoff, and soil moisture) to better reflect the multivariate variables simultaneously. Based on the constructed NMDI and runs theory, drought events for a particular area regarding three drought characteristics: duration, peak, and severity were identified. Finally, multivariate drought risk was analyzed as a tool for providing reliable support in drought decision-making. The results indicate that: (1) multidimensional copulas can effectively solve the complicated and nonlinear relationship among multivariate variables; (2) compared with single and other composite drought indices, the NMDI is slightly more sensitive in capturing recorded drought events; and (3) drought risk shows a spatial variation; out of the five partitions studied, the Jing River Basin as well as the upstream and midstream of the Wei River Basin are characterized by a higher multivariate drought risk. In general, multidimensional copulas provides a reliable way to solve the nonlinear relationship when constructing a comprehensive drought index and evaluating multivariate drought characteristics.

Comparison of connectivity analyses for resting state EEG data

NASA Astrophysics Data System (ADS)

Olejarczyk, Elzbieta; Marzetti, Laura; Pizzella, Vittorio; Zappasodi, Filippo

2017-06-01

Objective. In the present work, a nonlinear measure (transfer entropy, TE) was used in a multivariate approach for the analysis of effective connectivity in high density resting state EEG data in eyes open and eyes closed. Advantages of the multivariate approach in comparison to the bivariate one were tested. Moreover, the multivariate TE was compared to an effective linear measure, i.e. directed transfer function (DTF). Finally, the existence of a relationship between the information transfer and the level of brain synchronization as measured by phase synchronization value (PLV) was investigated. Approach. The comparison between the connectivity measures, i.e. bivariate versus multivariate TE, TE versus DTF, TE versus PLV, was performed by means of statistical analysis of indexes based on graph theory. Main results. The multivariate approach is less sensitive to false indirect connections with respect to the bivariate estimates. The multivariate TE differentiated better between eyes closed and eyes open conditions compared to DTF. Moreover, the multivariate TE evidenced non-linear phenomena in information transfer, which are not evidenced by the use of DTF. We also showed that the target of information flow, in particular the frontal region, is an area of greater brain synchronization. Significance. Comparison of different connectivity analysis methods pointed to the advantages of nonlinear methods, and indicated a relationship existing between the flow of information and the level of synchronization of the brain.

Destination bedside: using research findings to visualize optimal unit layouts and health information technology in support of bedside care.

PubMed

Watkins, Nicholas; Kennedy, Mary; Lee, Nelson; O'Neill, Michael; Peavey, Erin; Ducharme, Maria; Padula, Cynthia

2012-05-01

This study explored the impact of unit design and healthcare information technology (HIT) on nursing workflow and patient-centered care (PCC). Healthcare information technology and unit layout-related predictors of nursing workflow and PCC were measured during a 3-phase study involving questionnaires and work sampling methods. Stepwise multiple linear regressions demonstrated several HIT and unit layout-related factors that impact nursing workflow and PCC.

Resilient Brain Aging: Characterization of Discordance between Alzheimer’s Disease Pathology and Cognition

PubMed Central

Negash, Selam; Wilson, Robert S.; Leurgans, Sue E.; Wolk, David A.; Schneider, Julie A.; Buchman, Aron S.; Bennett, David A.; Arnold, Steven. E.

2014-01-01

Background Although it is now evident that normal cognition can occur despite significant AD pathology, few studies have attempted to characterize this discordance, or examine factors that may contribute to resilient brain aging in the setting of AD pathology. Methods More than 2,000 older persons underwent annual evaluation as part of participation in the Religious Orders Study or Rush Memory Aging Project. A total of 966 subjects who had brain autopsy and comprehensive cognitive testing proximate to death were analyzed. Resilience was quantified as a continuous measure using linear regression modeling, where global cognition was entered as a dependent variable and global pathology was an independent variable. Studentized residuals generated from the model represented the discordance between cognition and pathology, and served as measure of resilience. The relation of resilience index to known risk factors for AD and related variables was examined. Results Multivariate regression models that adjusted for demographic variables revealed significant associations for early life socioeconomic status, reading ability, APOE-ε4 status, and past cognitive activity. A stepwise regression model retained reading level (estimate = 0.10, SE = 0.02; p < 0.0001) and past cognitive activity (estimate = 0.27, SE = 0.09; p = 0.002), suggesting the potential mediating role of these variables for resilience. Conclusions The construct of resilient brain aging can provide a framework for quantifying the discordance between cognition and pathology, and help identify factors that may mediate this relationship. PMID:23919768

Longitudinal changes in late systolic cardiac load and serum NT-proBNP levels in healthy middle-aged Japanese men.

PubMed

Tomiyama, Hirofumi; Nishikimi, Toshio; Matsumoto, Chisa; Kimura, Kazutaka; Odaira, Mari; Shiina, Kazuki; Yamashina, Akira

2015-04-01

We determined whether any significant association exists between change in late systolic cardiac load with time, estimated by radial pressure waveform analysis, and development of cardiac hemodynamic stress in individuals with preserved cardiac function. Brachial-ankle pulse wave velocity, radial augmentation index (rAI), first peak of the radial pressure waveform (SP1), systolic and pulse pressure at the second peak of the radial pressure waveform (SP2 and PP2), and serum levels of N-terminal fragment B-type natriuretic peptide (NT-proBNP) were measured at the start (first examination) and at the end (second examination) of this 3-year study in healthy Japanese men (n = 1,851). A stepwise multivariate linear regression analysis demonstrated that among the parameters of radial pressure waveform analysis and markers of arterial stiffness analyzed, only PP2 was significantly associated with serum NT-proBNP levels in study participants at both the first and second examinations. Furthermore, among the parameters analyzed, only change in PP2 was significantly correlated with the change in serum NT-proBNP levels during the study period (beta = 0.131, P < 0.001). Sustained late systolic cardiac load might be a more significant determinant of the development of cardiac hemodynamic stress than sustained early systolic cardiac load or arterial stiffening in individuals with preserved cardiac function. © American Journal of Hypertension, Ltd 2014. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Assessing soil quality indicator under different land use and soil erosion using multivariate statistical techniques.

PubMed

Nosrati, Kazem

2013-04-01

Soil degradation associated with soil erosion and land use is a critical problem in Iran and there is little or insufficient scientific information in assessing soil quality indicator. In this study, factor analysis (FA) and discriminant analysis (DA) were used to identify the most sensitive indicators of soil quality for evaluating land use and soil erosion within the Hiv catchment in Iran and subsequently compare soil quality assessment using expert opinion based on soil surface factors (SSF) form of Bureau of Land Management (BLM) method. Therefore, 19 soil physical, chemical, and biochemical properties were measured from 56 different sampling sites covering three land use/soil erosion categories (rangeland/surface erosion, orchard/surface erosion, and rangeland/stream bank erosion). FA identified four factors that explained for 82 % of the variation in soil properties. Three factors showed significant differences among the three land use/soil erosion categories. The results indicated that based upon backward-mode DA, dehydrogenase, silt, and manganese allowed more than 80 % of the samples to be correctly assigned to their land use and erosional status. Canonical scores of discriminant functions were significantly correlated to the six soil surface indices derived of BLM method. Stepwise linear regression revealed that soil surface indices: soil movement, surface litter, pedestalling, and sum of SSF were also positively related to the dehydrogenase and silt. This suggests that dehydrogenase and silt are most sensitive to land use and soil erosion.

Main biomarkers associated with age-related plasma zinc decrease and copper/zinc ratio in healthy elderly from ZincAge study.

PubMed

Giacconi, R; Costarelli, L; Piacenza, F; Basso, A; Rink, L; Mariani, E; Fulop, T; Dedoussis, G; Herbein, G; Provinciali, M; Jajte, J; Lengyel, I; Mocchegiani, E; Malavolta, M

2017-12-01

Zinc (Zn) plays an essential role in many biological processes including immune response. Impaired Zn status promotes immune dysfunction, and it has been associated with enhanced chronic inflammation during aging. It has been suggested that the measurement of circulating Zn by itself could not reflect the real Zn status of an individual. It is therefore necessary to identify other determinants associated with plasma Zn to better understanding how physiopathological conditions during aging may affect the concentration of this metal. We have investigated the association between Zn levels and some biomarkers in 1090 healthy elderly from five European countries to increase the accuracy in the assessment of the Zn status. Stepwise multivariate linear regression models were used to analyze the influence of factors such as age, dietary intake, inflammatory mediators, laboratory parameters and polymorphisms previously associated with Zn homeostasis. Plasma Zn decrement was most strongly predicted by age, while positive correlations were found with albumin, RANTES and Zn intake after adjustment for multiple confounders. HSP70 +1267 AA genotype was an independent factor associated with Zn plasma concentrations. Cu/Zn ratio was positively associated with markers of systemic inflammation and age and negatively associated with albumin serum levels. Our findings show the most important independent determinants of plasma Zn concentration and Cu/Zn ratio variability in elderly population and suggest that the decline with age of Zn circulating levels is more dependent on physiopathological changes occurring with aging rather than to its nutritional intake.

Serum Predictors of Percent Lean Mass in Young Adults.

PubMed

Lustgarten, Michael S; Price, Lori L; Phillips, Edward M; Kirn, Dylan R; Mills, John; Fielding, Roger A

2016-08-01

Lustgarten, MS, Price, LL, Phillips, EM, Kirn, DR, Mills, J, and Fielding, RA. Serum predictors of percent lean mass in young adults. J Strength Cond Res 30(8): 2194-2201, 2016-Elevated lean (skeletal muscle) mass is associated with increased muscle strength and anaerobic exercise performance, whereas low levels of lean mass are associated with insulin resistance and sarcopenia. Therefore, studies aimed at obtaining an improved understanding of mechanisms related to the quantity of lean mass are of interest. Percent lean mass (total lean mass/body weight × 100) in 77 young subjects (18-35 years) was measured with dual-energy x-ray absorptiometry. Twenty analytes and 296 metabolites were evaluated with the use of the standard chemistry screen and mass spectrometry-based metabolomic profiling, respectively. Sex-adjusted multivariable linear regression was used to determine serum analytes and metabolites significantly (p ≤ 0.05 and q ≤ 0.30) associated with the percent lean mass. Two enzymes (alkaline phosphatase and serum glutamate oxaloacetate aminotransferase) and 29 metabolites were found to be significantly associated with the percent lean mass, including metabolites related to microbial metabolism, uremia, inflammation, oxidative stress, branched-chain amino acid metabolism, insulin sensitivity, glycerolipid metabolism, and xenobiotics. Use of sex-adjusted stepwise regression to obtain a final covariate predictor model identified the combination of 5 analytes and metabolites as overall predictors of the percent lean mass (model R = 82.5%). Collectively, these data suggest that a complex interplay of various metabolic processes underlies the maintenance of lean mass in young healthy adults.

Epidemiological characteristics and deaths of premature infants in a referral hospital for high-risk pregnancies

PubMed Central

de Freitas, Brunnella Alcantara Chagas; Sant'Ana, Luciana Ferreira da Rocha; Longo, Giana Zarbato; Siqueira-Batista, Rodrigo; Priore, Silvia Eloiza; Franceschin, Sylvia do Carmo Castro

2012-01-01

Objective To analyze the process of care provided to premature infants in a neonatal intensive care unit and the factors associated with their mortality. Methods Cross-sectional retrospective study of premature infants in an intensive care unit between 2008 and 2010. The characteristics of the mothers and premature infants were described, and a bivariate analysis was performed on the following characteristics: the study period and the "death" outcome (hospital, neonatal and early) using Pearson's chi-square test, Fisher's exact test or a chi-square test for linear trends. Bivariate and multivariable logistic regression analyses were performed using a stepwise backward logistic regression method between the variables with p<0.20 and the "death" outcome. A p value <0.05 was considered to be significant. Results In total, 293 preterm infants were studied. Increased access to complementary tests (transfontanellar ultrasound and Doppler echocardiogram) and breastfeeding rates were indicators of improving care. Mortality was concentrated in the neonatal period, especially in the early neonatal period, and was associated with extreme prematurity, small size for gestational age and an Apgar score <7 at 5 minutes after birth. The late-onset sepsis was also associated with a greater chance of neonatal death, and antenatal corticosteroids were protective against neonatal and early deaths. Conclusions Although these results are comparable to previous findings regarding mortality among premature infants in Brazil, the study emphasizes the need to implement strategies that promote breastfeeding and reduce neonatal mortality and its early component. PMID:23917938

Uptake of PAHs by cabbage root and leaf in vegetable plots near a large coking manufacturer and associations with PAHs in cabbage core.

PubMed

Xiong, GuanNan; Zhang, YunHui; Duan, YongHong; Cai, ChuanYang; Wang, Xin; Li, JingYa; Tao, Shu; Liu, WenXin

2017-08-01

Samples of ambient air (including gaseous and particulate phases), dust fall, surface soil, rhizosphere soil, core (edible part), outer leaf, and root of cabbage from eight vegetable plots near a large coking manufacturer were collected during the harvest period. Concentrations, compositions, and distributions of parent PAHs in different samples were determined. Our results indicated that most of the parent PAHs in air occurred in the gaseous phase, dominated by low molecular weight (LMW) species with two to three rings. Specific isomeric ratios and principal component analysis were employed to preliminarily identify the local sources of parent PAHs emitted. The main emission sources of parent PAHs could be apportioned as a mixture of coal combustion, coking production, and traffic tailing gas. PAH components with two to four rings were prevailing in dust fall, surface soil, and rhizosphere soil. Concentrations of PAHs in surface soil exhibited a significant positive correlation with topsoil TOC fractions. Compositional profiles in outer leaf and core of cabbage, dominated by LMW species, were similar to those in the local air. Overall, the order of parent PAH concentration in cabbage was outer leaf > root > core. Partial correlation analysis and multivariate linear stepwise regression revealed that PAH concentrations in cabbage core were closely associated with PAHs present both in root and in outer leaf, namely, affected by adsorption, then absorption, and translocation of PAHs from rhizosphere soil and ambient air, respectively.

Lung function and left ventricular hypertrophy in morbidly obese candidates for bariatric surgery

PubMed Central

Müller, Paulo de Tarso; Domingos, Hamilton; Patusco, Luiz Armando Pereira; Rapello, Gabriel Victor Guimarães

2015-01-01

Objective: To look for correlations between lung function and cardiac dimension variables in morbidly obese patients, in order to test the hypothesis that the relative size of the small airways is independently correlated with left ventricular hypertrophy. Methods: This was a retrospective study involving 192 medical records containing a clinical protocol employed in candidates for bariatric surgery between January of 2006 and December of 2010. Results: Of the 192 patients evaluated, 39 (10 males and 29 females) met the inclusion criteria. The mean BMI of the patients was 49.2 ± 7.6 kg/m2, and the mean age was 35.5 ± 7.7 years. The FEF25-75/FVC, % correlated significantly with left ventricular posterior wall thickness and relative left ventricular posterior wall thickness, those correlations remaining statistically significant (r = −0.355 and r = −0.349, respectively) after adjustment for weight, gender, and history of systemic arterial hypertension. Stepwise multivariate linear regression analysis showed that FVC and FEV1 were the major determinants of left ventricular mass (in grams or indexed to body surface area). Conclusions: A reduction in the relative size of the small airways appears to be independently correlated with obesity-related cardiac hypertrophy, regardless of factors affecting respiratory mechanics (BMI and weight), gender, or history of systemic arterial hypertension. However, FEV1 and FVC might be important predictors of left ventricular mass in morbidly obese individuals. PMID:26578134

LIVER ULTRASONOGRAPHY IN DOLPHINS: USE OF ULTRASONOGRAPHY TO ESTABLISH A TECHNIQUE FOR HEPATOBILIARY IMAGING AND TO EVALUATE METABOLIC DISEASE-ASSOCIATED LIVER CHANGES IN BOTTLENOSE DOLPHINS (TURSIOPS TRUNCATUS).

PubMed

Seitz, Kelsey E; Smith, Cynthia R; Marks, Stanley L; Venn-Watson, Stephanie K; Ivančić, Marina

2016-12-01

The objective of this study was to establish a comprehensive technique for ultrasound examination of the dolphin hepatobiliary system and apply this technique to 30 dolphins to determine what, if any, sonographic changes are associated with blood-based indicators of metabolic syndrome (insulin greater than 14 μIU/ml or glucose greater than 112 mg/dl) and iron overload (transferrin saturation greater than 65%). A prospective study of individuals in a cross-sectional population with and without elevated postprandial insulin levels was performed. Twenty-nine bottlenose dolphins ( Tursiops truncatus ) in a managed collection were included in the final data analysis. An in-water ultrasound technique was developed that included detailed analysis of the liver and pancreas. Dolphins with hyperinsulinemia concentrations had larger livers compared with dolphins with nonelevated concentrations. Using stepwise, multivariate regression including blood-based indicators of metabolic syndrome in dolphins, glucose was the best predictor of and had a positive linear association with liver size (P = 0.007, R 2 = 0.24). Bottlenose dolphins are susceptible to metabolic syndrome and associated complications that affect the liver, including fatty liver disease and iron overload. This study facilitated the establishment of a technique for a rapid, diagnostic, and noninvasive ultrasonographic evaluation of the dolphin liver. In addition, the study identified ultrasound-detectable hepatic changes associated primarily with elevated glucose concentration in dolphins. Future investigations will strive to detail the pathophysiological mechanisms for these changes.

Comparison of three portable instruments to measure compression pressure.

PubMed

Partsch, H; Mosti, G

2010-10-01

Measurement of interface pressure between the skin and a compression device has gained practical importance not only for characterizing the efficacy of different compression products in physiological and clinical studies but also for the training of medical staff. A newly developed portable pneumatic pressure transducer (Picopress®) was compared with two established systems (Kikuhime® and SIGaT tester®) measuring linearity, variability and accuracy on a cylindrical model using a stepwise inflated sphygmomanometer as the reference. In addition the variation coefficients were measured by applying the transducers repeatedly under a blood pressure cuff on the distal lower leg of a healthy human subject with stepwise inflation. In the pressure range between 10 and 80 mmHg all three devices showed a linear association compared with the sphygmomanometer values (Pearson r>0.99). The best reproducibility (variation coefficients between 1.05-7.4%) and the highest degree of accuracy demonstrated by Bland-Altman plots was achieved with the Picopress® transducer. Repeated measurements of pressure in a human leg revealed average variation coefficients for the three devices of 4.17% (Kikuhime®), 8.52% (SIGaT®) and 2.79% (Picopress®). The results suggest that the Picopress® transducer, which also allows dynamic pressure tracing in connection with a software program and which may be left under a bandage for several days, is a reliable instrument for measuring the pressure under a compression device.

The influence of attention deficits on functional recovery post stroke during the first 12 months after discharge from hospital.

PubMed

Hyndman, D; Pickering, R M; Ashburn, A

2008-06-01

Attention deficits have been linked to poor recovery after stroke and may predict outcome. We explored the influence of attention on functional recovery post stroke in the first 12 months after discharge from hospital. People with stroke completed measures of attention, balance, mobility and activities of daily living (ADL) ability at the point of discharge from hospital, and 6 and 12 months later. We used correlational analysis and stepwise linear regression to explore potential predictors of outcome. We recruited 122 men and women, mean age 70 years. At discharge, 56 (51%) had deficits of divided attention, 45 (37%) of sustained attention, 43 (36%) of auditory selective attention and 41 (37%) had visual selective attention deficits. Attention at discharge correlated with mobility, balance and ADL outcomes 12 months later. After controlling for the level of the outcome at discharge, correlations remained significant in only five of the 12 relationships. Stepwise linear regression revealed that the outcome measured at discharge, days until discharge and number of medications were better predictors of outcome: in no case was an attention variable at discharge selected as a predictor of outcome at 12 months. Although attention and function correlated significantly, this correlation was reduced after controlling for functional ability at discharge. Furthermore, side of lesion and the attention variables were not demonstrated as important predictors of outcome 12 months later.

Periodontitis in coronary heart disease patients: strong association between bleeding on probing and systemic biomarkers.

PubMed

Bokhari, Syed Akhtar H; Khan, Ayyaz A; Butt, Arshad K; Hanif, Mohammad; Izhar, Mateen; Tatakis, Dimitris N; Ashfaq, Mohammad

2014-11-01

Few studies have examined the relationship of individual periodontal parameters with individual systemic biomarkers. This study assessed the possible association between specific clinical parameters of periodontitis and systemic biomarkers of coronary heart disease risk in coronary heart disease patients with periodontitis. Angiographically proven coronary heart disease patients with periodontitis (n = 317), aged >30 years and without other systemic illness were examined. Periodontal clinical parameters of bleeding on probing (BOP), probing depth (PD), and clinical attachment level (CAL) and systemic levels of high-sensitivity C-reactive protein (CRP), fibrinogen (FIB) and white blood cells (WBC) were noted and analyzed to identify associations through linear and stepwise multiple regression analyses. Unadjusted linear regression showed significant associations between periodontal and systemic parameters; the strongest association (r = 0.629; p < 0.001) was found between BOP and CRP levels, the periodontal and systemic inflammation marker, respectively. Stepwise regression analysis models revealed that BOP was a predictor of systemic CRP levels (p < 0.0001). BOP was the only periodontal parameter significantly associated with each systemic parameter (CRP, FIB, and WBC). In coronary heart disease patients with periodontitis, BOP is strongly associated with systemic CRP levels; this association possibly reflects the potential significance of the local periodontal inflammatory burden for systemic inflammation. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Variable Importance in Multivariate Group Comparisons.

ERIC Educational Resources Information Center

Huberty, Carl J.; Wisenbaker, Joseph M.

1992-01-01

Interpretations of relative variable importance in multivariate analysis of variance are discussed, with attention to (1) latent construct definition; (2) linear discriminant function scores; and (3) grouping variable effects. Two numerical ranking methods are proposed and compared by the bootstrap approach using two real data sets. (SLD)

Explanation of the variance in quality of life and activity capacity of patients with heart failure by laboratory data.

PubMed

Athanasopoulos, Leonidas V; Dritsas, Athanasios; Doll, Helen A; Cokkinos, Dennis V

2010-08-01

This study was conducted to explain the variance in quality of life (QoL) and activity capacity of patients with congestive heart failure from pathophysiological changes as estimated by laboratory data. Peak oxygen consumption (peak VO2) and ventilation (VE)/carbon dioxide output (VCO2) slope derived from cardiopulmonary exercise testing, plasma N-terminal prohormone of B-type natriuretic peptide (NT-proBNP), and echocardiographic markers [left atrium (LA), left ventricular ejection fraction (LVEF)] were measured in 62 patients with congestive heart failure, who also completed the Minnesota Living with Heart Failure Questionnaire and the Specific Activity Questionnaire. All regression models were adjusted for age and sex. On linear regression analysis, peak VO2 with P value less than 0.001, VE/VCO2 slope with P value less than 0.01, LVEF with P value less than 0.001, LA with P=0.001, and logNT-proBNP with P value less than 0.01 were found to be associated with QoL. On stepwise multiple linear regression, peak VO2 and LVEF continued to be predictive, accounting for 40% of the variability in Minnesota Living with Heart Failure Questionnaire score. On linear regression analysis, peak VO2 with P value less than 0.001, VE/VCO2 slope with P value less than 0.001, LVEF with P value less than 0.05, LA with P value less than 0.001, and logNT-proBNP with P value less than 0.001 were found to be associated with activity capacity. On stepwise multiple linear regression, peak VO2 and LA continued to be predictive, accounting for 53% of the variability in Specific Activity Questionnaire score. Peak VO2 is independently associated both with QoL and activity capacity. In addition to peak VO2, LVEF is independently associated with QoL, and LA with activity capacity.

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

NASA Technical Reports Server (NTRS)

Lehtomaki, N. A.

1981-01-01

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

POWERLIB: SAS/IML Software for Computing Power in Multivariate Linear Models

PubMed Central

Johnson, Jacqueline L.; Muller, Keith E.; Slaughter, James C.; Gurka, Matthew J.; Gribbin, Matthew J.; Simpson, Sean L.

2014-01-01

The POWERLIB SAS/IML software provides convenient power calculations for a wide range of multivariate linear models with Gaussian errors. The software includes the Box, Geisser-Greenhouse, Huynh-Feldt, and uncorrected tests in the “univariate” approach to repeated measures (UNIREP), the Hotelling Lawley Trace, Pillai-Bartlett Trace, and Wilks Lambda tests in “multivariate” approach (MULTIREP), as well as a limited but useful range of mixed models. The familiar univariate linear model with Gaussian errors is an important special case. For estimated covariance, the software provides confidence limits for the resulting estimated power. All power and confidence limits values can be output to a SAS dataset, which can be used to easily produce plots and tables for manuscripts. PMID:25400516

Socio-economic factors associated with infant mortality in Italy: an ecological study.

PubMed

Dallolio, Laura; Di Gregori, Valentina; Lenzi, Jacopo; Franchino, Giuseppe; Calugi, Simona; Domenighetti, Gianfranco; Fantini, Maria Pia

2012-08-16

One issue that continues to attract the attention of public health researchers is the possible relationship in high-income countries between income, income inequality and infant mortality (IM). The aim of this study was to assess the associations between IM and major socio-economic determinants in Italy. Associations between infant mortality rates in the 20 Italian regions (2006-2008) and the Gini index of income inequality, mean household income, percentage of women with at least 8 years of education, and percentage of unemployed aged 15-64 years were assessed using Pearson correlation coefficients. Univariate linear regression and multiple stepwise linear regression analyses were performed to determine the magnitude and direction of the effect of the four socio-economic variables on IM. The Gini index and the total unemployment rate showed a positive strong correlation with IM (r = 0.70; p < 0.001 and r = 0.84; p < 0.001 respectively), mean household income showed a strong negative correlation (r = -0.78; p < 0.001), while female educational attainment presented a weak negative correlation (r = -0.45; p < 0.05). Using a multiple stepwise linear regression model, only unemployment rate was independently associated with IM (b = 0.15, p < 0.001). In Italy, a high-income country where health care is universally available, variations in IM were strongly associated with relative and absolute income and unemployment rate. These results suggest that in Italy IM is not only related to income distribution, as demonstrated for other developed countries, but also to economic factors such as absolute income and unemployment. In order to reduce IM and the existing inequalities, the challenge for Italian decision makers is to promote economic growth and enhance employment levels.

Evaluation of job satisfaction and working atmosphere of dental nurses in Germany.

PubMed

Goetz, Katja; Hasse, Philipp; Campbell, Stephen M; Berger, Sarah; Dörfer, Christof E; Hahn, Karolin; Szecsenyi, Joachim

2016-02-01

The purpose of the study was to assess the level of job satisfaction of dental nurses in ambulatory care and to explore the impact of aspects of working atmosphere on and their association with job satisfaction. This cross-sectional study was based on a job satisfaction survey. Data were collected from 612 dental nurses working in 106 dental care practices. Job satisfaction was measured with the 10-item Warr-Cook-Wall job satisfaction scale. Working atmosphere was measured with five items. Linear regression analyses were performed in which each item of the job satisfaction scale was handled as dependent variables. A stepwise linear regression analysis was performed with overall job satisfaction and the five items of working atmosphere, job satisfaction, and individual characteristics. The response rate was 88.3%. Dental nurses were satisfied with 'colleagues' and least satisfied with 'income.' Different aspects of job satisfaction were mostly associated with the following working atmosphere issues: 'responsibilities within the practice team are clear,' 'suggestions for improvement are taken seriously,' 'working atmosphere in the practice team is good,' and 'made easier to admit own mistakes.' Within the stepwise linear regression analysis, the aspect 'physical working condition' (β = 0.304) showed the highest association with overall job satisfaction. The total explained variance of the 14 associated variables was 0.722 with overall job satisfaction. Working atmosphere within this discrete sample of dental care practice seemed to be an important influence on reported working condition and job satisfaction for dental nurses. Because of the high association of job satisfaction with physical working condition, the importance of paying more attention to an ergonomic working position for dental nurses to ensure optimal quality of care is highlighted. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Improving the Accuracy of Mapping Urban Vegetation Carbon Density by Combining Shadow Remove, Spectral Unmixing Analysis and Spatial Modeling

NASA Astrophysics Data System (ADS)

Qie, G.; Wang, G.; Wang, M.

2016-12-01

Mixed pixels and shadows due to buildings in urban areas impede accurate estimation and mapping of city vegetation carbon density. In most of previous studies, these factors are often ignored, which thus result in underestimation of city vegetation carbon density. In this study we presented an integrated methodology to improve the accuracy of mapping city vegetation carbon density. Firstly, we applied a linear shadow remove analysis (LSRA) on remotely sensed Landsat 8 images to reduce the shadow effects on carbon estimation. Secondly, we integrated a linear spectral unmixing analysis (LSUA) with a linear stepwise regression (LSR), a logistic model-based stepwise regression (LMSR) and k-Nearest Neighbors (kNN), and utilized and compared the integrated models on shadow-removed images to map vegetation carbon density. This methodology was examined in Shenzhen City of Southeast China. A data set from a total of 175 sample plots measured in 2013 and 2014 was used to train the models. The independent variables statistically significantly contributing to improving the fit of the models to the data and reducing the sum of squared errors were selected from a total of 608 variables derived from different image band combinations and transformations. The vegetation fraction from LSUA was then added into the models as an important independent variable. The estimates obtained were evaluated using a cross-validation method. Our results showed that higher accuracies were obtained from the integrated models compared with the ones using traditional methods which ignore the effects of mixed pixels and shadows. This study indicates that the integrated method has great potential on improving the accuracy of urban vegetation carbon density estimation. Key words: Urban vegetation carbon, shadow, spectral unmixing, spatial modeling, Landsat 8 images

Perception of self and significant others by alcoholics and nonalcoholics.

PubMed

Quereshi, M Y; Soat, D M

1976-01-01

Ratings of self and 15 significant others on four personality factors by 47 alcoholic and 90 nonalcoholic males were analyzed by means of step-wise regression analysis and multivariate analysis of covariance. Alcoholics rated themselves less positively on extraversion and self-assertiveness (lower mean on extraversion and higher on self-assertiveness) and also judged intimate others (father, mother, and spouse) less positively on unhappiness, extraversion, and productive persistence (higher mean on unhappiness and lower means on extraversion and productive persistence). There were no significant differences between the two groups in judging persons as a whole or in the degree of differentiation that was exhibited in rating all 16 persons including self.

Patient-Reported Outcomes of Periacetabular Osteotomy from the Prospective ANCHOR Cohort Study

PubMed Central

Clohisy, John C.; Ackerman, Jeffrey; Baca, Geneva; Baty, Jack; Beaulé, Paul E.; Kim, Young-Jo; Millis, Michael B.; Podeszwa, David A.; Schoenecker, Perry L.; Sierra, Rafael J.; Sink, Ernest L.; Sucato, Daniel J.; Trousdale, Robert T.; Zaltz, Ira

2017-01-01

Background: Current literature describing the periacetabular osteotomy (PAO) is mostly limited to retrospective case series. Larger, prospective cohort studies are needed to provide better clinical evidence regarding this procedure. The goals of the current study were to (1) report minimum 2-year patient-reported outcomes (pain, hip function, activity, overall health, and quality of life), (2) investigate preoperative clinical and disease characteristics as predictors of clinical outcomes, and (3) report the rate of early failures and reoperations in patients undergoing contemporary PAO surgery. Methods: A large, prospective, multicenter cohort of PAO procedures was established, and outcomes at a minimum of 2 years were analyzed. A total of 391 hips were included for analysis (79% of the patients were female, and the average patient age was 25.4 years). Patient-reported outcomes, conversion to total hip replacement, reoperations, and major complications were documented. Variables with a p value of ≤0.10 in the univariate linear regressions were included in the multivariate linear regression. The backward stepwise selection method was used to determine the final risk factors of clinical outcomes. Results: Clinical outcome analysis demonstrated major clinically important improvements in pain, function, quality of life, overall health, and activity level. Increasing age and a body mass index status of overweight or obese were predictive of improved results for certain outcome metrics. Male sex and mild acetabular dysplasia were predictive of lesser improvements in certain outcome measures. Three (0.8%) of the hips underwent early conversion to total hip arthroplasty, 12 (3%) required reoperation, and 26 (7%) experienced a major complication. Conclusions: This large, prospective cohort study demonstrated the clinical success of contemporary PAO surgery for the treatment of symptomatic acetabular dysplasia. Patient and disease characteristics demonstrated predictive value that should be considered in surgical decision-making. Level of Evidence: Therapeutic Level IV. See Instructions for Authors for a complete description of levels of evidence. PMID:28060231

A comparison of the effects of C2-cyclosporine and C0-tacrolimus on renal function and cardiovascular risk factors in kidney transplant recipients.

PubMed

Kim, S Joseph; Prasad, G V Ramesh; Huang, Michael; Nash, Michelle M; Famure, Olusegun; Park, Joseph; Thenganatt, Mary Ann; Chowdhury, Nizamuddin; Cole, Edward H; Fenton, Stanley S A; Cattran, Daniel C; Zaltzman, Jeffrey S; Cardella, Carl J

2006-10-15

There are few data directly comparing the effects of two-hour postingestion monitored cyclosporine (C2-CsA) vs. trough-monitored tacrolimus (C0-Tac) on renal function and cardiovascular risk factors. We studied 378 (202 C2-CsA vs. 176 C0-Tac) incident kidney transplant recipients in Toronto, Canada, from August 1, 2000 and December 31, 2003. Outcomes included changes in estimated glomerular filtration rate (eGFR at 1 and 6 months by modification of diet in renal disease four-variable equation), mean arterial pressure (MAP), total cholesterol (TC), and new-onset diabetes mellitus (NODM) at six months posttransplant. The independent effect of treatment/monitoring strategies on continuous outcomes and time-to-NODM was modeled using linear and Cox regression, respectively. Mean eGFR was 59.5 vs. 62.9 ml/min at one month and 50.6 vs. 61.2 ml/min at six months for C2-CsA vs. C0-Tac, respectively. Multiple linear regression revealed the slope of eGFR to be 0.93 ml/min/month lower in C2-CsA patients. This was equivalent to an adjusted average eGFR difference of 4.64 ml/min between months one and six posttransplant. There was no significant difference in average MAP and TC. In a stepwise multivariable Cox model and a propensity score analysis, there was no significant association between the type of treatment/monitoring strategy and time-to-NODM. There was a greater decline in eGFR for patients on C2-CsA (vs. C0-Tac) between one and six months posttransplant. However, MAP, TC, and the risk of NODM were comparable in both treatment/monitoring groups. The long-term impact of short-term reductions in eGFR as a function of the type of treatment/monitoring strategy requires further study.

Work stress and hair cortisol levels among workers in a Bangladeshi ready-made garment factory - Results from a cross-sectional study.

PubMed

Steinisch, Maria; Yusuf, Rita; Li, Jian; Stalder, Tobias; Bosch, Jos A; Rahman, Omar; Strümpell, Christian; Ashraf, Hasan; Fischer, Joachim E; Loerbroks, Adrian

2014-12-01

Evidence on the association of work stress with cortisol levels is inconsistent and mostly stems from Western countries, with limited generalizability to other regions of the world. These inconsistencies may partly be due to methodological limitations associated with the measurement of cortisol secretion in saliva, serum or urine. The present study set out to explore associations of work stress with long-term integrated cortisol levels in hair among 175 workers of an export oriented ready-made garment (RMG) factory in Dhaka, Bangladesh. Work-related demands (WD), interpersonal resources (IR) and work-related values (WV) were assessed using a psychometrically evaluated interview. WD consisted of four items on physical demands, time pressure, worries about mistakes and exposure to abusive language. IR comprised five items addressing support, recognition, adequate payment, workers' trust in the management, and the management's trust in workers, as perceived by the workers. WV captured job security, promotion prospects and job latitude by three items. Hair cortisol concentrations (HCC) were analyzed by liquid chromatography-mass spectrometry. Stepwise multivariable linear regression models (backward elimination of predictors) were used to estimate associations of HCC with the three work stress components. For significant work stress component(s), further multivariable linear regression analyses were conducted to explore whether, and if so, which individual item(s) contributed most. The mean HCC equaled 3.27 (SD 2.58) pg/mg. HCC were found to be significantly associated with WV (beta=0.209, p=0.021). Additional analyses of the three WV items revealed that this association was largely driven the item on "promotion prospects" (beta=0.230, p=0.007) implying that the perception of good promotion prospects was associated with higher HCC. The finding of elevated HCC with good promotion prospects may initially seem counter-intuitive, but is supported by research documenting that job promotion may result in poorer mental well-being. Moreover, being promoted in the Bangladeshi RMG industry may represent a stressful experience: job promotions are rare in this setting and are associated with the need to meet exceptional job-related demands. Further research from ethnic and culturally diverse occupational settings is needed to test this hypothesis, to shed light on the reproducibility of our findings and to improve our understanding of the psychobiological implications of psychosocial working conditions across cultures and contexts. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Direction-dependent secondary bonds and their stepwise melting in a uracil-based molecular crystal studied by infrared spectroscopy and theoretical modeling

NASA Astrophysics Data System (ADS)

Szekrényes, Zsolt; Nagy, Péter R.; Tarczay, György; Maggini, Laura; Bonifazi, Davide; Kamarás, Katalin

2018-01-01

Three types of supramolecular interactions are identified in the three crystallographic directions in crystals of 1,4-bis[(1-hexylurac-6-yl) ethynyl]benzene, a uracil-based molecule with a linear backbone. These three interactions, characterized by their strongest component, are: intermolecular double H-bonds along the molecular axis, London dispersion interaction of hexyl chains connecting these linear assemblies, and π - π stacking of the aromatic rings perpendicular to the molecular planes. On heating, two transitions happen, disordering of hexyl chains at 473 K, followed by H-bond melting at 534 K. The nature of the bonds and transitions was established by matrix-isolation and temperature-dependent infrared spectroscopy and supported by theoretical computations.

Financial Distress Prediction using Linear Discriminant Analysis and Support Vector Machine

NASA Astrophysics Data System (ADS)

Santoso, Noviyanti; Wibowo, Wahyu

2018-03-01

A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.

Load compensation in a lean burn natural gas vehicle

NASA Astrophysics Data System (ADS)

Gangopadhyay, Anupam

A new multivariable PI tuning technique is developed in this research that is primarily developed for regulation purposes. Design guidelines are developed based on closed-loop stability. The new multivariable design is applied in a natural gas vehicle to combine idle and A/F ratio control loops. This results in better recovery during low idle operation of a vehicle under external step torques. A powertrain model of a natural gas engine is developed and validated for steady-state and transient operation. The nonlinear model has three states: engine speed, intake manifold pressure and fuel fraction in the intake manifold. The model includes the effect of fuel partial pressure in the intake manifold filling and emptying dynamics. Due to the inclusion of fuel fraction as a state, fuel flow rate into the cylinders is also accurately modeled. A linear system identification is performed on the nonlinear model. The linear model structure is predicted analytically from the nonlinear model and the coefficients of the predicted transfer function are shown to be functions of key physical parameters in the plant. Simulations of linear system and model parameter identification is shown to converge to the predicted values of the model coefficients. The multivariable controller developed in this research could be designed in an algebraic fashion once the plant model is known. It is thus possible to implement the multivariable PI design in an adaptive fashion combining the controller with identified plant model on-line. This will result in a self-tuning regulator (STR) type controller where the underlying design criteria is the multivariable tuning technique designed in this research.

Local polynomial estimation of heteroscedasticity in a multivariate linear regression model and its applications in economics.

PubMed

Su, Liyun; Zhao, Yanyong; Yan, Tianshun; Li, Fenglan

2012-01-01

Multivariate local polynomial fitting is applied to the multivariate linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improving the traditional two-stage method. Due to non-parametric technique of local polynomial estimation, it is unnecessary to know the form of heteroscedastic function. Therefore, we can improve the estimation precision, when the heteroscedastic function is unknown. Furthermore, we verify that the regression coefficients is asymptotic normal based on numerical simulations and normal Q-Q plots of residuals. Finally, the simulation results and the local polynomial estimation of real data indicate that our approach is surely effective in finite-sample situations.

Computer Mapping of Water Quality in Saginaw Bay with LANDSAT Digital Data

NASA Technical Reports Server (NTRS)

Rogers, R. H. (Principal Investigator); Shah, N. J.; Smith, V. E.; Mckeon, J. B.

1976-01-01

The author has identified the following significant results. LANDSAT digital data and ground truth measurements for Saginaw Bay (Lake Huron), Michigan, for 31 July 1975 were correlated by stepwise linear regression and the resulting equations used to estimate invisible water quality parameters in nonsampled areas. Chloride, conductivity, total Kjeldahl nitrogen, total phosphorus, and chlorophyll a were best correlated with the ratio of LANDSAT Band 4 to Band 5. Temperature and Secchi depth correlate best with Band 5.

Transverse Motion of a Particle with an Oscillating Charge and Variable Mass in a Magnetic Field

NASA Astrophysics Data System (ADS)

Alisultanov, Z. Z.; Ragimkhanov, G. B.

2018-03-01

The problem of motion of a particle with an oscillating electric charge and variable mass in an uniform magnetic field has been solved. Three laws of mass variation have been considered: linear growth, oscillations, and stepwise growth. Analytical expressions for the particle velocity at different time dependences of the particle mass are obtained. It is established that simultaneous consideration of changes in the mass and charge leads to a significant change in the particle trajectory.

Time dependent shear stress and temperature distribution over an insulated flat plate moving at hypersonic speed.

NASA Technical Reports Server (NTRS)

Rodkiewicz, C. M.; Gupta, R. N.

1971-01-01

The laminar two-dimensional flow over a stepwise accelerated flat plate moving with hypersonic speed at zero angle of attack is analysed. The governing equations in the self-similar form are linearized and solved numerically for small times. The solutions obtained are the deviations of the velocity and the temperature profiles from those of steady state. The presented results may be used to find the first order boundary layer induced pressure on the plate.

Multivariate assessment of subjective and objective measures of social and family satisfaction in Veterans with history of traumatic brain injury.

PubMed

Orff, Henry J; Hays, Chelsea C; Twamley, Elizabeth W

2016-01-01

Approximately 20% of current-era Veterans have sustained a traumatic brain injury (TBI), which can result in persistent postconcussive symptoms. These symptoms may disrupt family and social functioning. We explored psychiatric, postconcussive, and cognitive factors as correlates of objective functioning and subjective satisfaction in family and social relationships. At entry into a supported employment study, 50 unemployed Veterans with a history of mild to moderate TBI and current cognitive impairment were administered baseline assessments. Multivariate stepwise regressions determined that higher levels of depressive symptomatology were strongly associated with less frequent social contact, as well as lower subjective satisfaction with family and social relationships. Worse verbal fluency predicted less frequent social contact, whereas worse processing speed and switching predicted higher levels of subjective satisfaction with family relationships. The pattern of results remained similar when examining those Veterans with only mild TBI. Depressive symptoms and cognitive functioning may impact Veterans' social contact and satisfaction with family and social relationships. Evidence-based interventions addressing depression and cognition may therefore aid in improving community reintegration and satisfaction with social and family relationships.

Estimating a graphical intra-class correlation coefficient (GICC) using multivariate probit-linear mixed models.

PubMed

Yue, Chen; Chen, Shaojie; Sair, Haris I; Airan, Raag; Caffo, Brian S

2015-09-01

Data reproducibility is a critical issue in all scientific experiments. In this manuscript, the problem of quantifying the reproducibility of graphical measurements is considered. The image intra-class correlation coefficient (I2C2) is generalized and the graphical intra-class correlation coefficient (GICC) is proposed for such purpose. The concept for GICC is based on multivariate probit-linear mixed effect models. A Markov Chain Monte Carlo EM (mcm-cEM) algorithm is used for estimating the GICC. Simulation results with varied settings are demonstrated and our method is applied to the KIRBY21 test-retest dataset.

Developing Screening Services for Colorectal Cancer on Android Smartphones

PubMed Central

Wu, Hui-Ching; Chang, Chiao-Jung; Lin, Chun-Che; Tsai, Ming-Chang; Chang, Che-Chia

2014-01-01

Abstract Introduction: Colorectal cancer (CRC) is an important health problem in Western countries and also in Asia. It is the third leading cause of cancer deaths in both men and women in Taiwan. According to the well-known adenoma-to-carcinoma sequence, the majority of CRC develops from colorectal adenomatous polyps. This concept provides the rationale for screening and prevention of CRC. Removal of colorectal adenoma could reduce the mortality and incidence of CRC. Mobile phones are now playing an ever more crucial role in people's daily lives. The latest generation of smartphones is increasingly viewed as hand-held computers rather than as phones, because of their powerful on-board computing capability, capacious memories, large screens, and open operating systems that encourage development of applications (apps). Subjects and Methods: If we can detect the potential CRC patients early and offer them appropriate treatments and services, this would not only promote the quality of life, but also reduce the possible serious complications and medical costs. In this study, an intelligent CRC screening app on Android™ (Google™, Mountain View, CA) smartphones has been developed based on a data mining approach using decision tree algorithms. For comparison, the stepwise backward multivariate logistic regression model and the fecal occult blood test were also used. Results: Compared with the stepwise backward multivariate logistic regression model and the fecal occult blood test, the proposed app system not only provides an easy and efficient way to quickly detect high-risk groups of potential CRC patients, but also brings more information about CRC to customer-oriented services. Conclusions: We developed and implemented an app system on Android platforms for ubiquitous healthcare services for CRC screening. It can assist people in achieving early screening, diagnosis, and treatment purposes, prevent the occurrence of complications, and thus reach the goal of preventive medicine. PMID:24848873

The relationship between hemoglobin level and the type 1 diabetic nephropathy in Anhui Han's patients.

PubMed

Jiang, Jun; Lei, Lan; Zhou, Xiaowan; Li, Peng; Wei, Ren

2018-02-20

Recent studies have shown that low hemoglobin (Hb) level promote the progression of chronic kidney disease. This study assessed the relationship between Hb level and type 1 diabetic nephropathy (DN) in Anhui Han's patients. There were a total of 236 patients diagnosed with type 1 diabetes mellitus and (T1DM) seen between January 2014 and December 2016 in our centre. Hemoglobin levels in patients with DN were compared with those without DN. The relationship between Hb level and the urinary albumin-creatinine ratio (ACR) was examined by Spearman's correlational analysis and multiple stepwise regression analysis. The binary logistic multivariate regression analysis was performed to analyze the correlated factors for type 1 DN, calculate the Odds Ratio (OR) and 95%confidence interval (CI). The predicting value of Hb level for DN was evaluated by area under receiver operation characteristic curve (AUROC) for discrimination and Hosmer-Lemeshow goodness-of-fit test for calibration. The average Hb levels in the DN group (116.1 ± 20.8 g/L) were significantly lower than the non-DN group (131.9 ± 14.4 g/L) , P < 0.001. Hb levels were independently correlated with the urinary ACR in multiple stepwise regression analysis. The logistic multivariate regression analysis showed that the Hb level (OR: 0.936, 95% CI: 0.910 to 0.963, P < 0.001) was inversely correlated with DN in patients with T1DM. In sub-analysis, low Hb level (Hb < 120g/L in female, Hb < 130g/L in male) was still negatively associated with DN in patients with T1DM. The AUROC was 0.721 (95% CI: 0.655 to 0.787) in assessing the discrimination of the Hb level for DN. The value of P was 0.593 in Hosmer-Lemeshow goodness-of-fit test. In Anhui Han's patients with T1DM, the Hb level is inversely correlated with urinary ACR and DN. This article is protected by copyright. All rights reserved.

Psychoactive substances use and associated factors among middle and high school students in the North Center of Morocco: a cross-sectional questionnaire survey.

PubMed

Zarrouq, B; Bendaou, B; El Asri, A; Achour, S; Rammouz, I; Aalouane, R; Lyoussi, B; Khelafa, S; Bout, A; Berhili, N; Hlal, H; Najdi, A; Nejjari, C; El Rhazi, K

2016-06-04

Data on psychoactive substance (PAS) consumption among adolescents in the North Center of Morocco are not at all available. Therefore, the current study aimed at investigating the prevalence and the determinants of psychoactive substances use among middle and high school students in this region. A cross-sectional study was conducted from April 2012 to November 2013 in public middle and high schools in the North Central Region of Morocco. An anonymous self-administered questionnaire was used to assess psychoactive substances use among a representative sample of school students from the 7th to the 12th grade, aged 11-23 years, selected by stratified cluster random sampling. Factors associated with psychoactive substance use were identified using multivariate stepwise logistic regression analyses. A total of 3020 school students completed the questionnaires, 53.0 % of which were males. The overall lifetime smoking prevalence was 16.1 %. The lifetime, annual and past month rates of any psychoactive substance use among the study subjects were 9.3, 7.5, and 6.3 % respectively. Cannabis recorded the highest lifetime prevalence of 8.1 %, followed by alcohol 4.3 %, inhalants 1.7 %, psychotropic substances without medical prescription 1.0, cocaine 0.7, heroine 0.3, and amphetamine with only 0.2 %. Psychoactive substance use was associated with males more than females. The risk factors identified by multivariate stepwise logistic regression analyses were being male, studying in secondary school level, smoking tobacco, living with a family member who uses tobacco, and feeling insecure within the family. The prevalence among all school students reported by the current study was comparable to the national prevalence. Efforts to initiate psychoactive substance prevention programs among school students should be made by designing such programs based on the significant factors associated with psychoactive substance use identified in this study.

Work disability in Argentinian patients with systemic lupus erythematosus is prevalent and it is due to ethnic, socioeconomic and disease-related factors.

PubMed

Pisoni, Cecilia N; Muñoz, Sebastián A; Tamborenea, María N; García, Mercedes; Curti, Ana; Cappuccio, Ana; Rillo, Oscar; Imamura, Patricia M; Schneeberger, Emilce; Ballent, Marcela; Cousseau, Mario L; Velasco Zamora, Jorge; Saurit, Verónica; Toloza, Sergio; Danielsen, María C; Bellomio, Verónica I; Graf, Cesar; Paira, Sergio; Cavallasca, Javier; Pons Estel, Bernardo; Moreno, José L C; Díaz, Mónica; Alba, Paula; Verando, Marcela; Tate, Guillermo; Mysler, Eduardo; Sarano, Judith; Civit, Emma E; Risueño, Fabián; Álvarez Sepúlveda, Pablo; Larroude, María S; Méndez, Marcos F; Conforti, Andrea; Sohn, Débora

2018-04-02

To study the prevalence and the associated factors of work disability (WD) in systemic lupus erythematosus (SLE) patients. A sample of 419 SLE patients from an observational cross-sectional multicenter study was included. Sociodemographic features, disease characteristics, comorbidities, quality of life, unhealthy behaviors, and work-related factors were measured in a standardized interview. Work disability was defined by patient self-report of not being able to work because of SLE. To identify variables associated with work disability, two different multivariate regression models using a stepwise backward method were performed. Prevalence of WD due to SLE was 24.3%. Eighty-nine percent were female and 51% were Caucasians. Mean disease duration was 8.9 ± 7.2 years, and median System Lupus International Collaborating Clinics/American College of Rheumatology damage index SLICC-SDI was 1.5 (range 0-17). In stepwise multivariate logistic regression, living below the poverty line (odds ratio [OR] = 4.65), less than 12 years of education (OR = 2.84), Mestizo ethnicity (OR = 1.94) and SLICC-SDI (OR = 1.25) were predictors of WD. A second model was performed including patient-derived measures; in this model sedentary lifestyle (OR = 2.69) and lower emotional health domain score of the Lupus Quality of Life (LupusQoL) questionnaire (OR = 1.03) were found to be associated to WD and a higher score in LupusQoL physical health domain (OR = 0.93) was protective. The prevalence of WD in Argentinian SLE patients was 24.3%. WD was associated with ethnic (Mestizo), socioeconomic (poverty) and disease-related factors. Patient-related outcomes such us sedentary lifestyle and poor emotional quality of life were also associated with WD. © 2018 Asia Pacific League of Associations for Rheumatology and John Wiley & Sons Australia, Ltd.

Multivariable control of a twin lift helicopter system using the LQG/LTR design methodology

NASA Technical Reports Server (NTRS)

Rodriguez, A. A.; Athans, M.

1986-01-01

Guidelines for developing a multivariable centralized automatic flight control system (AFCS) for a twin lift helicopter system (TLHS) are presented. Singular value ideas are used to formulate performance and stability robustness specifications. A linear Quadratic Gaussian with Loop Transfer Recovery (LQG/LTR) design is obtained and evaluated.

Relationship between Spiritual Health and Quality of Life in Patients with Cancer.

PubMed

Mohebbifar, Rafat; Pakpour, Amir H; Nahvijou, Azin; Sadeghi, Atefeh

2015-01-01

As the essence of health in humans, spiritual health is a fundamental concept for discussing chronic diseases such as cancer and a major approach for improving quality of life in patients is through creating meaningfulness and purpose. The present descriptive analytical study was conducted to assess the relationship between spiritual health and quality of life in 210 patients with cancer admitted to the Cancer Institute of Iran, selected through convenience sampling in 2014. Data were collected using Spiritual Health Questionnaire and the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC-QLQ). Patients' performance was assessed through the Karnofsky Performance Status Indicator and their cognitive status through the Mini-Mental State Examination (MMSE). Data were analyzed in SPSS-16 using descriptive statistics and stepwise linear regression. The results obtained reported the mean and standard deviation of the patients' spiritual health scoreas 78.4±16.1and the mean and standard deviation of their quality of life score as 58.1±18.7. The stepwise linear regression analysis confirmed a positive and significant relationship between spiritual health and quality of life in patients with cancer (β=0.688 and r=0.00). The results of the study show that spiritual health should be more emphasized and reinforced as a factor involved in improving quality of life in patients with cancer. Designing care therapies and spiritual interventions is a priority in the treatment of these patients.

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 tutorial on the LQG/LTR method. [Linear Quadratic Gaussian/Loop Transfer Recovery

NASA Technical Reports Server (NTRS)

Athans, M.

1986-01-01

In this paper the so-called Linear-Quadratic-Gaussian method with Loop-Transfer-Recovery is surveyed. The objective is to provide a pragmatic exposition, with special emphasis on the step-by-step characteristics for designing multivariable feedback control systems.

An iterative technique to stabilize a linear time invariant multivariable system with output feedback

NASA Technical Reports Server (NTRS)

Sankaran, V.

1974-01-01

An iterative procedure for determining the constant gain matrix that will stabilize a linear constant multivariable system using output feedback is described. The use of this procedure avoids the transformation of variables which is required in other procedures. For the case in which the product of the output and input vector dimensions is greater than the number of states of the plant, general solution is given. In the case in which the states exceed the product of input and output vector dimensions, a least square solution which may not be stable in all cases is presented. The results are illustrated with examples.

An approach to multivariable control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, H.

1987-01-01

The paper presents simple schemes for multivariable control of multiple-joint robot manipulators in joint and Cartesian coordinates. The joint control scheme consists of two independent multivariable feedforward and feedback controllers. The feedforward controller is the minimal inverse of the linearized model of robot dynamics and contains only proportional-double-derivative (PD2) terms - implying feedforward from the desired position, velocity and acceleration. This controller ensures that the manipulator joint angles track any reference trajectories. The feedback controller is of proportional-integral-derivative (PID) type and is designed to achieve pole placement. This controller reduces any initial tracking error to zero as desired and also ensures that robust steady-state tracking of step-plus-exponential trajectories is achieved by the joint angles. Simple and explicit expressions of computation of the feedforward and feedback gains are obtained based on the linearized model of robot dynamics. This leads to computationally efficient schemes for either on-line gain computation or off-line gain scheduling to account for variations in the linearized robot model due to changes in the operating point. The joint control scheme is extended to direct control of the end-effector motion in Cartesian space. Simulation results are given for illustration.

Improvements in Health-related Quality of Life among Methadone Maintenance Clients in Dar es Salaam, Tanzania

PubMed Central

Ubuguyu, Omary; Tran, Olivia C.; Bruce, R. Douglas; Masao, Frank; Nyandindi, Cassian; Sabuni, Norman; McCurdy, Sheryl; Mbwambo, Jessie

2016-01-01

Background Injection of heroin has become widespread in Dar es Salaam, Tanzania and is spreading throughout the country. To prevent potential bridging of HIV epidemics, the Tanzanian government established a methadone maintenance treatment (MMT) clinic in February 2011. We assess the effect of MMT on health-related quality of life (HRQOL) and examine factors, particularly HIV infection and methadone dose, associated with changes in HRQOL. Methods This study utilized routine data on clients enrolling in methadone from February 2011 to April 2012 at Muhimbili National Hospital. Change in physical (PCS) and mental health (MCS) composite scores, as measured by the SF-12 tool, were the primary outcomes. Backward stepwise linear regression, with a criterion of p<0.2 was used to identify baseline exposure variables for inclusion in multivariable models, while adjusting for baseline scores. Results A total of 288 MMT clients received baseline and follow-up assessments. Mean methadone dose administered was 45 mg (SD±25) and 76(27%) were confirmed HIV-positive. Significant improvements were observed in PCS and MCS, with mean increases of 15.7 and 3.3, respectively. In multivariable models, clients who had previous poly-substance use with cocaine [p=0.040] had a significantly higher mean change in PCS. Clients who were living with HIV [p=0.002]; satisfied with current marital situation [p=0.045]; had a history of suicidal thoughts [p=0.021]; and previously experienced cognitive difficulties [p=0.012] had significantly lower mean change in PCS. Clients with shorter history of heroin use [p=0.012] and who received higher methadone doses [p=0.028] had significantly higher mean change in MCS, compared to their counterparts. Discussion Aspects of mental and physical health, risk behaviors and quality of life among drug users are intertwined and complex. Our research revealed positive short-term effects of MMT on HRQOL and highlights the importance of sustained retention for optimal benefits. Comprehensive supportive services in addition to provision of methadone are needed to address the complex health needs of people who inject drugs. PMID:27017376

Gender difference in the impact of gynoid and android fat masses on the progression of hepatic steatosis in Japanese patients with type 2 diabetes.

PubMed

Bouchi, Ryotaro; Fukuda, Tatsuya; Takeuchi, Takato; Nakano, Yujiro; Murakami, Masanori; Minami, Isao; Izumiyama, Hajime; Hashimoto, Koshi; Yoshimoto, Takanobu; Ogawa, Yoshihiro

2017-01-01

Increased visceral adiposity is strongly associated with non-alcoholic fatty liver disease (NAFLD). However, little attention has been paid to the association between the change in subcutaneous adipose mass and the progression of non-alcoholic fatty liver disease (NAFLD). We aimed to investigate whether increased subcutaneous adipose tissue (gynoid fat mass) could be protective against the progression of NAFLD in Japanese patients with type 2 diabetes. This is a retrospective observational study of 294 Japanese patients with type 2 diabetes (65 ± 10 years old, 40% female). Liver attenuation index (LAI) measured by abdominal computed tomography was used for the assessment of hepatic steatosis. Both gynoid (kg) and android (kg) fat masses were measured by the whole body dual-energy X-ray absorptiometry. One-year changes in LAI, gynoid, and android fat masses were evaluated in both male and female patients. Linear regression analysis with a stepwise procedure was used for the statistical analyses to investigate the association of the changes in gynoid and android fat masses with the change in LAI. LAI levels at baseline were 1.15 ± 0.31 and 1.10 ± 0.34 in female and male patients ( p  = 0.455). The change in gynoid fat mass was significantly and positively associated with the change in LAI in both univariate (standardized β 0.331, p  = 0.049) and multivariate (standardized β 0.360, p  = 0.016) models in the female patients. However, no significant association was observed in males. In contrast, the increase in android fat mass was significantly associated with the reduced LAI in both genders in the multivariate models (standardized β -0.651, p  < 0.001 in females and standardized β -0.519, p  = 0.042 in males). This study provides evidence that increased gynoid fat mass may be protective against the progression of NAFLD in female Japanese patients with type 2 diabetes.

An interative solution of an integral equation for radiative transfer by using variational technique

NASA Technical Reports Server (NTRS)

Yoshikawa, K. K.

1973-01-01

An effective iterative technique is introduced to solve a nonlinear integral equation frequently associated with radiative transfer problems. The problem is formulated in such a way that each step of an iterative sequence requires the solution of a linear integral equation. The advantage of a previously introduced variational technique which utilizes a stepwise constant trial function is exploited to cope with the nonlinear problem. The method is simple and straightforward. Rapid convergence is obtained by employing a linear interpolation of the iterative solutions. Using absorption coefficients of the Milne-Eddington type, which are applicable to some planetary atmospheric radiation problems. Solutions are found in terms of temperature and radiative flux. These solutions are presented numerically and show excellent agreement with other numerical solutions.

A high surface area Zr(IV)-based metal–organic framework showing stepwise gas adsorption and selective dye uptake

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

Lv, Xiu-Liang; Tong, Minman; Huang, Hongliang

2015-03-15

Exploitation of new metal–organic framework (MOF) materials with high surface areas has been attracting great attention in related research communities due to their broad potential applications. In this work, a new Zr(IV)-based MOF, [Zr{sub 6}O{sub 4}(OH){sub 4}(eddb){sub 6}] (BUT-30, H{sub 2}eddb=4,4′-(ethyne-1,2-diyl)dibenzoic acid) has been solvothermally synthesized, characterized, and explored for gases and dyes adsorptions. Single-crystal X-ray diffraction analysis demonstrates a three-dimensional cubic framework structure of this MOF, in which each Zr{sub 6}O{sub 4}(OH){sub 4} building unit is linked by 12 linear eddb ligands. BUT-30 has been found stable up to 400 °C and has a Brunauer–Emmett–Teller (BET) surface area asmore » high as 3940.6 m{sup 2} g{sup −1} (based on the N{sub 2} adsorption at 77 K) and total pore volume of 1.55 cm{sup 3} g{sup −1}. It is more interesting that this MOF exhibits stepwise adsorption behaviors for Ar, N{sub 2}, and CO{sub 2} at low temperatures, and selective uptakes towards different ionic dyes. - Graphical abstract: A new Zr(IV)-based MOF with high surface area has been synthesized and structurally characterized, which shows stepwise gas adsorption at low temperature and selective dye uptake from solution. - Highlights: • A new Zr-based MOF was synthesized and structurally characterized. • This MOF shows a higher surface area compared with its analogous UiO-67 and 68. • This MOF shows a rare stepwise adsorption towards light gases at low temperature. • This MOF performs selective uptakes towards cationic dyes over anionic ones. • Using triple-bond spacer is confirmed feasible in enhancing MOF surface areas.« less

Linear quadratic regulators with eigenvalue placement in a horizontal strip

NASA Technical Reports Server (NTRS)

Shieh, Leang S.; Dib, Hani M.; Ganesan, Sekar

1987-01-01

A method for optimally shifting the imaginary parts of the open-loop poles of a multivariable control system to the desirable closed-loop locations is presented. The optimal solution with respect to a quadratic performance index is obtained by solving a linear matrix Liapunov equation.

NONPARAMETRIC MANOVA APPROACHES FOR NON-NORMAL MULTIVARIATE OUTCOMES WITH MISSING VALUES

PubMed Central

He, Fanyin; Mazumdar, Sati; Tang, Gong; Bhatia, Triptish; Anderson, Stewart J.; Dew, Mary Amanda; Krafty, Robert; Nimgaonkar, Vishwajit; Deshpande, Smita; Hall, Martica; Reynolds, Charles F.

2017-01-01

Between-group comparisons often entail many correlated response variables. The multivariate linear model, with its assumption of multivariate normality, is the accepted standard tool for these tests. When this assumption is violated, the nonparametric multivariate Kruskal-Wallis (MKW) test is frequently used. However, this test requires complete cases with no missing values in response variables. Deletion of cases with missing values likely leads to inefficient statistical inference. Here we extend the MKW test to retain information from partially-observed cases. Results of simulated studies and analysis of real data show that the proposed method provides adequate coverage and superior power to complete-case analyses. PMID:29416225

Association of NT-proBNP and Multiple Biomarkers with Severity of Angiographic Coronary Artery Disease in Diabetic and Pre-Diabetic Chinese Patients

PubMed Central

Fang, Zhou; Bao, Yuanyuan; Ding, Wei; Luo, Xinping; Hu, Renming

2011-01-01

Background Little is known about the plasma levels of N-terminal pro-brain natriuretic peptide (NT-proBNP), and the relationship between the severity of coronary heart disease (CHD) with NT-proBNP and multiple biomarkers in diabetic and pre-diabetic patients, compared to individuals with normal glucose levels. Methods Four hundred and fifteen consecutive Chinese patients of both sexes were assigned to three groups on the basis of the new hemoglobin (Hb) A1c (HbA1c) cut-off points for diagnosis of diabetes and pre-diabetes. The three groups were divided into tertiles according to NT-proBNP, hs-CRP, cystatin C, and troponin T levels. Gensini scores were compared among the three groups and biomarker tertiles. Receiver operating characteristic (ROC) curves were used to obtain the angiographic CHD cut-off points for each biomarker. Stepwise multivariate linear correlation analysis was applied to examine the association between the severity of CHD and biomarker levels. Results Gensini scores increased with increasing biomarker tertile levels and HbA1c. Gensini scores were significantly different in the middle and upper NT-proBNP tertiles of the diabetic, pre-diabetic and control groups. NT-proBNP had the highest positive and negative predictive values and area under the curve for CHD. Only NT-proBNP was identified as an independent variable for Gensini score. Conclusions Plasma NT-proBNP may be an important biomarker to evaluate the severity of CHD and screen for CHD in diabetic or pre-diabetic patients. PMID:21857933

Predictive factors of functional capacity and real-world functioning in patients with schizophrenia.

PubMed

Menendez-Miranda, I; Garcia-Portilla, M P; Garcia-Alvarez, L; Arrojo, M; Sanchez, P; Sarramea, F; Gomar, J; Bobes-Bascaran, M T; Sierra, P; Saiz, P A; Bobes, J

2015-07-01

This study was performed to identify the predictive factors of functional capacity assessed by the Spanish University of California Performance Skills Assessment (Sp-UPSA) and real-world functioning assessed by the Spanish Personal and Social Performance scale (PSP) in outpatients with schizophrenia. Naturalistic, 6-month follow-up, multicentre, validation study. Here, we report data on 139 patients with schizophrenia at their baseline visit. Positive and Negative Syndrome Scale (PANSS), Clinical Global Impression-Severity (CGI-S), Sp-UPSA and PSP. Pearson's correlation coefficient (r) was used to determine the relationships between variables, and multivariable stepwise linear regression analyses to identify predictive variables of Sp-UPSA and PSP total scores. Functional capacity: scores on the PSP and PANSS-GP entered first and second at P<0.0001 and accounted for 21% of variance (R(2)=0.208, model df=2, F=15.724, P<0.0001). Real-world functioning: scores on the CGI-S (B=-5.406), PANSS-N (B=-0.657) and Sp-UPSA (B=0.230) entered first, second and third, and accounted for 51% of variance (model df=3, F=37.741, P<0.0001). In patients with schizophrenia, functional capacity and real-world functioning are two related but different constructs. Each one predicts the other along with other factors; general psychopathology for functional capacity, and severity of the illness and negative symptoms for real-world functioning. These findings have important clinical implications: (1) both types of functioning should be assessed in patients with schizophrenia and (2) strategies for improving them should be different. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

The impact of levothyroxine sodium treatment on oxidative stress in Hashimoto's thyroiditis.

PubMed

Ates, Ihsan; Altay, Mustafa; Yilmaz, Fatma Meric; Topcuoglu, Canan; Yilmaz, Nisbet; Berker, Dilek; Guler, Serdar

2016-06-01

Although several studies reported increased oxidative stress in Hashimoto's thyroiditis (HT), the effect of levothyroxine treatment on oxidative status is not studied extensively. Therefore, we conducted this study to investigate the effects of levothyroxine replacement on oxidative stress in HT. Thirty-six patients recently diagnosed with HT-related hypothyroidism and 36 healthy controls were included in the study. Levothyroxine replacement was started to patients with hypothyroidism, and had been followed-up for 6 months. Mean basal serum total antioxidant status (TAS), total thiol, arylesterase, and paraoxonase 1 (PON1) levels were significantly lower, and serum total oxidant status (TOS) and oxidative stress index (OSI) were significantly higher in the patients with hypothyroid than the controls. In the hypothyroid group serum TAS, total thiol, arylesterase, and PON1 levels increased and serum TOS and OSI levels decreased significantly after levothyroxine treatment. Pretreatment serum TAS, total thiol, PON1, and arylesterase levels were positively correlated with free levothyroxine (fT4) and negatively correlated with thyroid-stimulating hormone (TSH), antithyroid peroxidase (anti-TPO), and antithyroglobulin (anti-TG) levels. Also, pretreatment serum TOS and OSI levels were negatively correlated with fT4 levels and positively correlated with TSH, anti-TPO, and anti-TG. We have also found that the fT4 and anti-TPO levels are independent predictors of the oxidative stress parameters in stepwise multivariable linear regression analysis. This study suggests that levothyroxine replacement decreases oxidant status and increases antioxidant status following the 6 months of levothyroxine replacement in hypothyroidism that develops in accordance with the HT. © 2016 European Society of Endocrinology.

Preterm birth, social disadvantage, and cognitive competence in Swedish 18- to 19-year-old men.

PubMed

Ekeus, Cecilia; Lindström, Karolina; Lindblad, Frank; Rasmussen, Finn; Hjern, Anders

2010-01-01

The aim was to study the impact of a range of gestational ages (GAs) on cognitive competence in late adolescence and how this effect is modified by contextual social adversity in childhood. This was a register study based on a national cohort of 119664 men born in Sweden from 1973 to 1976. Data on GA and other perinatal factors were obtained from the Medical Birth Register, and information on cognitive test scores was extracted from military conscription at the ages of 18 to 19 years. Test scores were analyzed as z scores on a 9-point stanine scale, whereby each unit is equivalent to 0.5 SD. Socioeconomic indicators of the childhood household were obtained from the Population and Housing Census of 1990. The data were analyzed by multivariate linear regression. The mean cognitive test scores decreased in a stepwise manner with GA. In unadjusted analysis, the test scores were 0.63 stanine unit lower in men who were born after 24 to 32 gestational weeks than in those who were born at term. The difference in global scores between the lowest and highest category of socioeconomic status was 1.57. Adjusting the analysis for the childhood socioeconomic indicators decreased the effect of GA on cognitive test scores by 26% to 33%. There was also a multiplicative interaction effect of social adversity and moderately preterm birth on cognitive test scores. This study confirms previous claims of an incremental association of cognitive competence with GA. Socioeconomic indicators in childhood modified this effect at all levels of preterm birth.

Foot Type Biomechanics Part 2: are structure and anthropometrics related to function?

PubMed

Mootanah, Rajshree; Song, Jinsup; Lenhoff, Mark W; Hafer, Jocelyn F; Backus, Sherry I; Gagnon, David; Deland, Jonathan T; Hillstrom, Howard J

2013-03-01

Many foot pathologies are associated with specific foot types. If foot structure and function are related, measurement of either could assist with differential diagnosis of pedal pathologies. Biomechanical measures of foot structure and function are related in asymptomatic healthy individuals. Sixty-one healthy subjects' left feet were stratified into cavus (n=12), rectus (n=27) and planus (n=22) foot types. Foot structure was assessed by malleolar valgus index, arch height index, and arch height flexibility. Anthropometrics (height and weight), age, and walking speed were measured. Foot function was assessed by center of pressure excursion index, peak plantar pressure, maximum force, and gait pattern parameters. Foot structure and anthropometric variables were entered into stepwise linear regression models to identify predictors of function. Measures of foot structure and anthropometrics explained 10-37% of the model variance (adjusted R(2)) for gait pattern parameters. When walking speed was included, the adjusted R(2) increased to 45-77% but foot structure was no longer a factor. Foot structure and anthropometrics predicted 7-47% of the model variance for plantar pressure and 16-64% for maximum force parameters. All multivariate models were significant (p<0.05), supporting acceptance of the hypothesis. Foot structure and function are related in asymptomatic healthy individuals. The structural parameters employed are basic measurements that do not require ionizing radiation and could be used in a clinical setting. Further research is needed to identify additional predictive parameters (plantar soft tissue characteristics, skeletal alignment, and neuromuscular control) and to include individuals with pathology. Copyright © 2012. Published by Elsevier B.V.

Foot Type Biomechanics Part 2: Are structure and anthropometrics related to function?

PubMed Central

Mootanah, Rajshree; Song, Jinsup; Lenhoff, Mark W.; Hafer, Jocelyn F.; Backus, Sherry I.; Gagnon, David; Deland, Jonathan T.; Hillstrom, Howard J.

2013-01-01

Background Many foot pathologies are associated with specific foot types. If foot structure and function are related, measurement of either could assist with differential diagnosis of pedal pathologies. Hypothesis Biomechanical measures of foot structure and function are related in asymptomatic healthy individuals. Methods Sixty-one healthy subjects' left feet were stratified into cavus (n = 12), rectus (n = 27) and planus (n = 22) foot types. Foot structure was assessed by malleolar valgus index, arch height index, and arch height flexibility. Anthropometrics (height and weight), age, and walking speed were measured. Foot function was assessed by center of pressure excursion index, peak plantar pressure, maximum force, and gait pattern parameters. Foot structure and anthropometric variables were entered into stepwise linear regression models to identify predictors of function. Results Measures of foot structure and anthropometrics explained 10–37% of the model variance (adjusted R2) for gait pattern parameters. When walking speed was included, the adjusted R2 increased to 45–77% but foot structure was no longer a factor. Foot structure and anthropometrics predicted 7–47% of the model variance for plantar pressure and 16–64% for maximum force parameters. All multivariate models were significant (p < 0.05), supporting acceptance of the hypothesis. Discussion and conclusion Foot structure and function are related in asymptomatic healthy individuals. The structural parameters employed are basic measurements that do not require ionizing radiation and could be used in a clinical setting. Further research is needed to identify additional predictive parameters (plantar soft tissue characteristics, skeletal alignment, and neuromuscular control) and to include individuals with pathology. PMID:23107624

ACE ID genotype affects blood creatine kinase response to eccentric exercise.

PubMed

Yamin, Chen; Amir, Offer; Sagiv, Moran; Attias, Eric; Meckel, Yoav; Eynon, Nir; Sagiv, Michael; Amir, Ruthie E

2007-12-01

Unaccustomed exercise may cause muscle breakdown with marked increase in serum creatine kinase (CK) activity. The skeletal muscle renin-angiotensin system (RAS) plays an important role in exercise metabolism and tissue injury. A functional insertion (I)/deletion (D) polymorphism in the angiotensin I-converting enzyme (ACE) gene (rs4646994) has been associated with ACE activity. We hypothesized that ACE ID genotype may contribute to the wide variability in individuals' CK response to a given exercise. Young individuals performed maximal eccentric contractions of the elbow flexor muscles. Pre- and postexercise CK activity was determined. ACE genotype was significantly associated with postexercise CK increase and peak CK activity. Individuals harboring one or more of the I allele had a greater increase and higher peak CK values than individuals with the DD genotype. This response was dose-dependent (mean +/- SE U/L: II, 8,882 +/- 2,362; ID, 4,454 +/- 1,105; DD, 2,937 +/- 753, ANOVA, P = 0.02; P = 0.009 for linear trend). Multivariate stepwise regression analysis, which included age, sex, body mass index, and genotype subtypes, revealed that ACE genotype was the most powerful independent determinant of peak CK activity (adjusted odds ratio 1.3, 95% confidence interval 1.03-1.64, P = 0.02). In conclusion, we indicate a positive association of the ACE ID genotype with CK response to strenuous exercise. We suggest that the II genotype imposes increased risk for developing muscle damage, whereas the DD genotype may have protective effects. These findings support the role of local RAS in the regulation of exertional muscle injury.

The demographic and medical correlates of plasma aβ40 and aβ42.

PubMed

Metti, Andrea L; Cauley, Jane A; Ayonayon, Hilsa N; Harris, Tamara B; Rosano, Caterina; Williamson, Jeff D; Yaffe, Kristine

2013-01-01

Plasma amyloid β-42 (Aβ42) and Aβ42/Aβ40 are increasingly recognized as biomarkers for dementia, with low levels indicating increased risk. Little is known about the demographic and medical correlates of plasma Aβ40 or Aβ42. In 997 community-dwelling, nondemented older adults from the Health, Aging, and Body Composition Study, we determined the cross-sectional association between a wide range of demographic and medical variables with Aβ40 and Aβ42. In multivariate stepwise linear regression models, Aβ40 was significantly associated with race (β=-14.70, F=22.01, P<0.0001), age (β=1.34, F=6.39, P=0.01), creatinine (β=52.91, F=151.77, P<0.0001), and the serum brain-derived neurotrophic factor (β=-0.0004, F=7.34, P=0.007); Aβ42 was significantly associated with race (β=-3.72, F=30.83, P<0.0001), sex (β=1.39, F=4.32, P=0.04), education (β=1.50, F=4.78, P=0.03), apolipoprotein E e4 genotype (β=-2.82, F=16.57, P<0.0001), and creatinine (β=9.32, F=120.09, P<0.0001). These correlates should be considered as potential confounders in future studies investigating plasma Aβ as a biomarker of dementia. Understanding fully how these correlates mediate or modify the association between plasma Aβ and dementia will be a fundamental step in determining the biological pathways through which plasma Aβ40 and Aβ42 are associated with dementia, and in determining their full potential as biomarkers.

Effect of Shift Work on Sleep, Health, and Quality of Life of Health-care Workers.

PubMed

Nena, Evangelia; Katsaouni, Maria; Steiropoulos, Paschalis; Theodorou, Evangelos; Constantinidis, Theodoros C; Tripsianis, Grigorios

2018-01-01

Shift work is associated with sleep disruption, impaired quality of life, and is a risk factor for several health conditions. Aim of this study was to investigate the impact of shift work on sleep and quality of life of health-care workers (HCW). Tertiary University hospital in Greece. Cross-sectional study. Included were HCW, working either in an irregular shift system or exclusively in morning shifts. All participants answered the WHO-5 Well-Being Index (WHO-5) and a questionnaire on demographics and medical history. Shift workers filled the Shift Work Disorders Screening Questionnaire (SWDSQ). Descriptive statistics, Student's t -test, one-way analysis of variance (ANOVA), Pearson's r correlation coefficient, and multivariate stepwise linear regression analysis were applied. Included were 312 employees (87.9% females), 194 working in irregular shift system and 118 in morning shifts. Most shift-workers (58.2%) were somehow or totally dissatisfied with their sleep quality. Regression analysis revealed the following independent determinants for sleep impairment: parenthood ( P < 0.001), age 36-45 years ( P < 0.001), >3 night shifts/week ( P < 0.001), work >5 years in an irregular shift system ( P < 0.001). Diabetes mellitus was the most common medical condition reported by shift workers ( P = 0.008). Comparison between the two groups revealed a significantly impairment in WHO-5 total score, as well as in 4 of 5 of its items ( P < 0.001). Shift-work impairs quality of life, whereas its duration and frequency, along with age and family status of employees can have adverse effects on sleep.

Severity of coronary artery disease in obese patients undergoing coronary angiography: "obesity paradox" revisited.

PubMed

Niraj, Ashutosh; Pradhan, Jyotiranjan; Pradahan, Jyotiranjan; Fakhry, Hesham; Veeranna, Vikas; Afonso, Luis

2007-08-01

Recent studies have highlighted the existence of an 'obesity paradox' in patients undergoing coronary angiography, i.e., a high body mass Index (BMI) is associated with less severe coronary lesions. We sought to confirm the existence of this phenomenon in the US patient population. Study subjects included 770 consecutive patients (470 men, 428 African-Americans, 212 Caucasians) referred for coronary angiography to a tertiary care center. Duke myocardial jeopardy score, a prognostication tool predictive of 1-year mortality in coronary artery disease (CAD) patients, was assigned to angiographic data. Patients were classified according to their BMI (kg/m2) as normal (21-24), overweight (25-29), obesity class I (30-34), class II (35-39) and class III (40 or above). Patients in the increasing obesity class had a higher prevalence of diabetes, hypertension and dyslipidemia and were more likely to be women. A negative correlation was observed between BMI and age (R = - 0.15 p < 0.001) as well as between BMI and Duke Jeopardy score (r = - 0.07, p < 0.05) indicating that patients with higher BMI were referred for coronary angiography at a younger age, and had a lower coronary artery disease (CAD) burden. BMI was not an independent predictor of coronary lesion severity on multivariate stepwise linear regression analysis. Obese patients are referred for coronary angiography at an earlier age and have a lower CAD burden lending further credence to the existence of an apparent "obesity paradox". However, obesity per se, after adjustment for comorbidities, is not an independent predictor of severity of coronary artery disease. (c) 2007 Wiley Periodicals, Inc.

A population-based study of the association of medical manpower with county trauma death rates in the United States.

PubMed Central

Rutledge, R; Fakhry, S M; Baker, C C; Weaver, N; Ramenofsky, M; Sheldon, G F; Meyer, A A

1994-01-01

OBJECTIVE: To determine the association between measures of medical manpower available to treat trauma patients and county trauma death rates in the United States. The primary hypothesis was that greater availability of medical manpower to treat trauma injury would be associated with lower trauma death rates. SUMMARY BACKGROUND DATA: When viewed from the standpoint of the number of productive years of life lost, trauma has a greater effect on health care and lost productivity in the United States than any disease. Allocation of health care manpower to treat injuries seems logical, but studies have not been done to determine its efficacy. The effect of medical manpower and hospital resource allocation on the outcome of injury in the United States has not been fully explored or adequately evaluated. METHODS: Data on trauma deaths in the United States were obtained from the National Center for Health Statistics. Data on the number of surgeons and emergency medicine physicians were obtained from the American Hospital Association and the American Medical Association. Data on physicians who have participated in the American College of Surgeons (ACS) Advanced Trauma Life Support Course (ATLS) were obtained from the ACS. Membership information for the American Association for Surgery of Trauma (AAST) was obtained from that organization. Demographic data were obtained from the United States Census Bureau. Multivariate stepwise linear regression and cluster analysis were used to model the county trauma death rates in the United States. The Statistical Analysis System (Cary, NC) for statistical analysis was used. RESULTS: Bivariate and multivariate analyses showed that a variety of medical manpower measures and demographic factors were associated with county trauma death rates in the United States. As in other studies, measures of low population density and high levels of poverty were found to be strongly associated with increased trauma death rates. After accounting for these variables, using multivariate analysis and cluster analysis, an increase in the following medical manpower measures were associated with decreased county trauma death rates: number of board-certified general surgeons, number of board-certified emergency medicine physicians, number of AAST members, and number of ATLS-trained physicians. CONCLUSIONS: This study confirms previous work that showed a strong relation among measures of poverty, rural setting, and increased county trauma death rates. It also found that counties with more board-certified surgeons per capita and with more surgeons with an increased interest (AAST membership) or increased training (ATLS) in trauma care have lower per-capita trauma death rates.(ABSTRACT TRUNCATED AT 400 WORDS) Images Figure 1. PMID:8185404

A continuous damage model based on stepwise-stress creep rupture tests

NASA Technical Reports Server (NTRS)

Robinson, D. N.

1985-01-01

A creep damage accumulation model is presented that makes use of the Kachanov damage rate concept with a provision accounting for damage that results from a variable stress history. This is accomplished through the introduction of an additional term in the Kachanov rate equation that is linear in the stress rate. Specification of the material functions and parameters in the model requires two types of constituting a data base: (1) standard constant-stress creep rupture tests, and (2) a sequence of two-step creep rupture tests.

Application of ERTS-1 imagery to the study of caribou movements and winter dispersal in relation to prevailing snowcover

NASA Technical Reports Server (NTRS)

Lent, P. C. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Step-wise discriminate analysis has demonstrated the feasibility of feature identification using linear discriminate functions of ERTS-1 MSS band densities and their ratios. The analysis indicated that features such as small streams can be detected even when they are in dark mountain shadow. The potential utility of this and similar analytic techniques appears considerable, and the limits it can be applied to analysis of ERTS-1 imagery are not yet fully known.

Cloud field classification based upon high spatial resolution textural features. I - Gray level co-occurrence matrix approach

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Chen, D. W.

1988-01-01

Stratocumulus, cumulus, and cirrus clouds were identified on the basis of cloud textural features which were derived from a single high-resolution Landsat MSS NIR channel using a stepwise linear discriminant analysis. It is shown that, using this method, it is possible to distinguish high cirrus clouds from low clouds with high accuracy on the basis of spatial brightness patterns. The largest probability of misclassification is associated with confusion between the stratocumulus breakup regions and the fair-weather cumulus.

Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines.

PubMed

Grajeda, Laura M; Ivanescu, Andrada; Saito, Mayuko; Crainiceanu, Ciprian; Jaganath, Devan; Gilman, Robert H; Crabtree, Jean E; Kelleher, Dermott; Cabrera, Lilia; Cama, Vitaliano; Checkley, William

2016-01-01

Childhood growth is a cornerstone of pediatric research. Statistical models need to consider individual trajectories to adequately describe growth outcomes. Specifically, well-defined longitudinal models are essential to characterize both population and subject-specific growth. Linear mixed-effect models with cubic regression splines can account for the nonlinearity of growth curves and provide reasonable estimators of population and subject-specific growth, velocity and acceleration. We provide a stepwise approach that builds from simple to complex models, and account for the intrinsic complexity of the data. We start with standard cubic splines regression models and build up to a model that includes subject-specific random intercepts and slopes and residual autocorrelation. We then compared cubic regression splines vis-à-vis linear piecewise splines, and with varying number of knots and positions. Statistical code is provided to ensure reproducibility and improve dissemination of methods. Models are applied to longitudinal height measurements in a cohort of 215 Peruvian children followed from birth until their fourth year of life. Unexplained variability, as measured by the variance of the regression model, was reduced from 7.34 when using ordinary least squares to 0.81 (p < 0.001) when using a linear mixed-effect models with random slopes and a first order continuous autoregressive error term. There was substantial heterogeneity in both the intercept (p < 0.001) and slopes (p < 0.001) of the individual growth trajectories. We also identified important serial correlation within the structure of the data (ρ = 0.66; 95 % CI 0.64 to 0.68; p < 0.001), which we modeled with a first order continuous autoregressive error term as evidenced by the variogram of the residuals and by a lack of association among residuals. The final model provides a parametric linear regression equation for both estimation and prediction of population- and individual-level growth in height. We show that cubic regression splines are superior to linear regression splines for the case of a small number of knots in both estimation and prediction with the full linear mixed effect model (AIC 19,352 vs. 19,598, respectively). While the regression parameters are more complex to interpret in the former, we argue that inference for any problem depends more on the estimated curve or differences in curves rather than the coefficients. Moreover, use of cubic regression splines provides biological meaningful growth velocity and acceleration curves despite increased complexity in coefficient interpretation. Through this stepwise approach, we provide a set of tools to model longitudinal childhood data for non-statisticians using linear mixed-effect models.

A generalized fuzzy linear programming approach for environmental management problem under uncertainty.

PubMed

Fan, Yurui; Huang, Guohe; Veawab, Amornvadee

2012-01-01

In this study, a generalized fuzzy linear programming (GFLP) method was developed to deal with uncertainties expressed as fuzzy sets that exist in the constraints and objective function. A stepwise interactive algorithm (SIA) was advanced to solve GFLP model and generate solutions expressed as fuzzy sets. To demonstrate its application, the developed GFLP method was applied to a regional sulfur dioxide (SO2) control planning model to identify effective SO2 mitigation polices with a minimized system performance cost under uncertainty. The results were obtained to represent the amount of SO2 allocated to different control measures from different sources. Compared with the conventional interval-parameter linear programming (ILP) approach, the solutions obtained through GFLP were expressed as fuzzy sets, which can provide intervals for the decision variables and objective function, as well as related possibilities. Therefore, the decision makers can make a tradeoff between model stability and the plausibility based on solutions obtained through GFLP and then identify desired policies for SO2-emission control under uncertainty.

Polynomial compensation, inversion, and approximation of discrete time linear systems

NASA Technical Reports Server (NTRS)

Baram, Yoram

1987-01-01

The least-squares transformation of a discrete-time multivariable linear system into a desired one by convolving the first with a polynomial system yields optimal polynomial solutions to the problems of system compensation, inversion, and approximation. The polynomial coefficients are obtained from the solution to a so-called normal linear matrix equation, whose coefficients are shown to be the weighting patterns of certain linear systems. These, in turn, can be used in the recursive solution of the normal equation.

Stimulation of a turbofan engine for evaluation of multivariable optimal control concepts. [(computerized simulation)

NASA Technical Reports Server (NTRS)

Seldner, K.

1976-01-01

The development of control systems for jet engines requires a real-time computer simulation. The simulation provides an effective tool for evaluating control concepts and problem areas prior to actual engine testing. The development and use of a real-time simulation of the Pratt and Whitney F100-PW100 turbofan engine is described. The simulation was used in a multi-variable optimal controls research program using linear quadratic regulator theory. The simulation is used to generate linear engine models at selected operating points and evaluate the control algorithm. To reduce the complexity of the design, it is desirable to reduce the order of the linear model. A technique to reduce the order of the model; is discussed. Selected results between high and low order models are compared. The LQR control algorithms can be programmed on digital computer. This computer will control the engine simulation over the desired flight envelope.

Utility of Intermediate-Delay Washout CT Images for Differentiation of Malignant and Benign Adrenal Lesions: A Multivariate Analysis.

PubMed

Ng, Chaan S; Altinmakas, Emre; Wei, Wei; Ghosh, Payel; Li, Xiao; Grubbs, Elizabeth G; Perrier, Nancy D; Lee, Jeffrey E; Prieto, Victor G; Hobbs, Brian P

2018-06-27

The objective of this study was to identify features that impact the diagnostic performance of intermediate-delay washout CT for distinguishing malignant from benign adrenal lesions. This retrospective study evaluated 127 pathologically proven adrenal lesions (82 malignant, 45 benign) in 126 patients who had undergone portal venous phase and intermediate-delay washout CT (1-3 minutes after portal venous phase) with or without unenhanced images. Unenhanced images were available for 103 lesions. Quantitatively, lesion CT attenuation on unenhanced (UA) and delayed (DL) images, absolute and relative percentage of enhancement washout (APEW and RPEW, respectively), descriptive CT features (lesion size, margin characteristics, heterogeneity or homogeneity, fat, calcification), patient demographics, and medical history were evaluated for association with lesion status using multiple logistic regression with stepwise model selection. Area under the ROC curve (A z ) was calculated from both univariate and multivariate analyses. The predictive diagnostic performance of multivariate evaluations was ascertained through cross-validation. A z for DL, APEW, RPEW, and UA was 0.751, 0.795, 0.829, and 0.839, respectively. Multivariate analyses yielded the following significant CT quantitative features and associated A z when combined: RPEW and DL (A z = 0.861) when unenhanced images were not available and APEW and UA (A z = 0.889) when unenhanced images were available. Patient demographics and presence of a prior malignancy were additional significant factors, increasing A z to 0.903 and 0.927, respectively. The combined predictive classifier, without and with UA available, yielded 85.7% and 87.3% accuracies with cross-validation, respectively. When appropriately combined with other CT features, washout derived from intermediate-delay CT with or without additional clinical data has potential utility in differentiating malignant from benign adrenal lesions.

Multivariate generalized multifactor dimensionality reduction to detect gene-gene interactions

PubMed Central

2013-01-01

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

A High-Dimensional, Multivariate Copula Approach to Modeling Multivariate Agricultural Price Relationships and Tail Dependencies

Treesearch

Xuan Chi; Barry Goodwin

2012-01-01

Spatial and temporal relationships among agricultural prices have been an important topic of applied research for many years. Such research is used to investigate the performance of markets and to examine linkages up and down the marketing chain. This research has empirically evaluated price linkages by using correlation and regression models and, later, linear and...

Impact of Explicit Presentation of Slopes in Three Dimensions on Students' Understanding of Derivatives in Multivariable Calculus

ERIC Educational Resources Information Center

McGee, Daniel Lee; Moore-Russo, Deborah

2015-01-01

In two dimensions (2D), representations associated with slopes are seen in numerous forms before representations associated with derivatives are presented. These include the slope between two points and the constant slope of a linear function of a single variable. In almost all multivariable calculus textbooks, however, the first discussion of…

Piecewise multivariate modelling of sequential metabolic profiling data.

PubMed

Rantalainen, Mattias; Cloarec, Olivier; Ebbels, Timothy M D; Lundstedt, Torbjörn; Nicholson, Jeremy K; Holmes, Elaine; Trygg, Johan

2008-02-19

Modelling the time-related behaviour of biological systems is essential for understanding their dynamic responses to perturbations. In metabolic profiling studies, the sampling rate and number of sampling points are often restricted due to experimental and biological constraints. A supervised multivariate modelling approach with the objective to model the time-related variation in the data for short and sparsely sampled time-series is described. A set of piecewise Orthogonal Projections to Latent Structures (OPLS) models are estimated, describing changes between successive time points. The individual OPLS models are linear, but the piecewise combination of several models accommodates modelling and prediction of changes which are non-linear with respect to the time course. We demonstrate the method on both simulated and metabolic profiling data, illustrating how time related changes are successfully modelled and predicted. The proposed method is effective for modelling and prediction of short and multivariate time series data. A key advantage of the method is model transparency, allowing easy interpretation of time-related variation in the data. The method provides a competitive complement to commonly applied multivariate methods such as OPLS and Principal Component Analysis (PCA) for modelling and analysis of short time-series data.

Higher-order Multivariable Polynomial Regression to Estimate Human Affective States

NASA Astrophysics Data System (ADS)

Wei, Jie; Chen, Tong; Liu, Guangyuan; Yang, Jiemin

2016-03-01

From direct observations, facial, vocal, gestural, physiological, and central nervous signals, estimating human affective states through computational models such as multivariate linear-regression analysis, support vector regression, and artificial neural network, have been proposed in the past decade. In these models, linear models are generally lack of precision because of ignoring intrinsic nonlinearities of complex psychophysiological processes; and nonlinear models commonly adopt complicated algorithms. To improve accuracy and simplify model, we introduce a new computational modeling method named as higher-order multivariable polynomial regression to estimate human affective states. The study employs standardized pictures in the International Affective Picture System to induce thirty subjects’ affective states, and obtains pure affective patterns of skin conductance as input variables to the higher-order multivariable polynomial model for predicting affective valence and arousal. Experimental results show that our method is able to obtain efficient correlation coefficients of 0.98 and 0.96 for estimation of affective valence and arousal, respectively. Moreover, the method may provide certain indirect evidences that valence and arousal have their brain’s motivational circuit origins. Thus, the proposed method can serve as a novel one for efficiently estimating human affective states.

Higher-order Multivariable Polynomial Regression to Estimate Human Affective States

PubMed Central

Wei, Jie; Chen, Tong; Liu, Guangyuan; Yang, Jiemin

2016-01-01

From direct observations, facial, vocal, gestural, physiological, and central nervous signals, estimating human affective states through computational models such as multivariate linear-regression analysis, support vector regression, and artificial neural network, have been proposed in the past decade. In these models, linear models are generally lack of precision because of ignoring intrinsic nonlinearities of complex psychophysiological processes; and nonlinear models commonly adopt complicated algorithms. To improve accuracy and simplify model, we introduce a new computational modeling method named as higher-order multivariable polynomial regression to estimate human affective states. The study employs standardized pictures in the International Affective Picture System to induce thirty subjects’ affective states, and obtains pure affective patterns of skin conductance as input variables to the higher-order multivariable polynomial model for predicting affective valence and arousal. Experimental results show that our method is able to obtain efficient correlation coefficients of 0.98 and 0.96 for estimation of affective valence and arousal, respectively. Moreover, the method may provide certain indirect evidences that valence and arousal have their brain’s motivational circuit origins. Thus, the proposed method can serve as a novel one for efficiently estimating human affective states. PMID:26996254

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

NASA Technical Reports Server (NTRS)

Giesy, Daniel P.; Armstrong, Ernest S.

1989-01-01

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

General Multivariate Linear Modeling of Surface Shapes Using SurfStat

PubMed Central

Chung, Moo K.; Worsley, Keith J.; Nacewicz, Brendon, M.; Dalton, Kim M.; Davidson, Richard J.

2010-01-01

Although there are many imaging studies on traditional ROI-based amygdala volumetry, there are very few studies on modeling amygdala shape variations. This paper present a unified computational and statistical framework for modeling amygdala shape variations in a clinical population. The weighted spherical harmonic representation is used as to parameterize, to smooth out, and to normalize amygdala surfaces. The representation is subsequently used as an input for multivariate linear models accounting for nuisance covariates such as age and brain size difference using SurfStat package that completely avoids the complexity of specifying design matrices. The methodology has been applied for quantifying abnormal local amygdala shape variations in 22 high functioning autistic subjects. PMID:20620211

A methodology for designing robust multivariable nonlinear control systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Grunberg, D. B.

1986-01-01

A new methodology is described for the design of nonlinear dynamic controllers for nonlinear multivariable systems providing guarantees of closed-loop stability, performance, and robustness. The methodology is an extension of the Linear-Quadratic-Gaussian with Loop-Transfer-Recovery (LQG/LTR) methodology for linear systems, thus hinging upon the idea of constructing an approximate inverse operator for the plant. A major feature of the methodology is a unification of both the state-space and input-output formulations. In addition, new results on stability theory, nonlinear state estimation, and optimal nonlinear regulator theory are presented, including the guaranteed global properties of the extended Kalman filter and optimal nonlinear regulators.

[Correlation between gaseous exchange rate, body temperature, and mitochondrial protein content in the liver of mice].

PubMed

Muradian, Kh K; Utko, N O; Mozzhukhina, T H; Pishel', I M; Litoshenko, O Ia; Bezrukov, V V; Fraĭfel'd, V E

2002-01-01

Correlative and regressive relations between the gaseous exchange, thermoregulation and mitochondrial protein content were analyzed by two- and three-dimensional statistics in mice. It has been shown that the pair wise linear methods of analysis did not reveal any significant correlation between the parameters under exploration. However, it became evident at three-dimensional and non-linear plotting for which the coefficients of multivariable correlation reached and even exceeded 0.7-0.8. The calculations based on partial differentiation of the multivariable regression equations allow to conclude that at certain values of VO2, VCO2 and body temperature negative relations between the systems of gaseous exchange and thermoregulation become dominating.

A matrix-based method of moments for fitting the multivariate random effects model for meta-analysis and meta-regression

PubMed Central

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

2013-01-01

Multivariate meta-analysis is becoming more commonly used. Methods for fitting the multivariate random effects model include maximum likelihood, restricted maximum likelihood, Bayesian estimation and multivariate generalisations of the standard univariate method of moments. Here, we provide a new multivariate method of moments for estimating the between-study covariance matrix with the properties that (1) it allows for either complete or incomplete outcomes and (2) it allows for covariates through meta-regression. Further, for complete data, it is invariant to linear transformations. Our method reduces to the usual univariate method of moments, proposed by DerSimonian and Laird, in a single dimension. We illustrate our method and compare it with some of the alternatives using a simulation study and a real example. PMID:23401213

Evaluation and simplification of the occupational slip, trip and fall risk-assessment test

PubMed Central

NAKAMURA, Takehiro; OYAMA, Ichiro; FUJINO, Yoshihisa; KUBO, Tatsuhiko; KADOWAKI, Koji; KUNIMOTO, Masamizu; ODOI, Haruka; TABATA, Hidetoshi; MATSUDA, Shinya

2016-01-01

Objective: The purpose of this investigation is to evaluate the efficacy of the occupational slip, trip and fall (STF) risk assessment test developed by the Japan Industrial Safety and Health Association (JISHA). We further intended to simplify the test to improve efficiency. Methods: A previous cohort study was performed using 540 employees aged ≥50 years who took the JISHA’s STF risk assessment test. We conducted multivariate analysis using these previous results as baseline values and answers to questionnaire items or score on physical fitness tests as variables. The screening efficiency of each model was evaluated based on the obtained receiver operating characteristic (ROC) curve. Results: The area under the ROC obtained in multivariate analysis was 0.79 when using all items. Six of the 25 questionnaire items were selected for stepwise analysis, giving an area under the ROC curve of 0.77. Conclusion: Based on the results of follow-up performed one year after the initial examination, we successfully determined the usefulness of the STF risk assessment test. Administering a questionnaire alone is sufficient for screening subjects at risk of STF during the subsequent one-year period. PMID:27021057

Differences in temperament, character and psychopathology among subjects with different patterns of cannabis use.

PubMed

Spalletta, Gianfranco; Bria, Pietro; Caltagirone, Carlo

2007-01-01

Patients who use illicit drugs and suffer from comorbid psychiatric illnesses have worse outcomes than drug users without a dual diagnosis. For this reason we aimed at identifying predictors of cannabis use severity using a multivariate model in which different clinical and socio-demographic variables were included. We administered the Temperament and Character Inventory, SCID-P, SCID-II, the Beck Depression Inventory and the State-Trait Anxiety Inventory. Of the 84 subjects included, 25 were occasional users, 37 were abusers, and 22 were dependent on cannabis. A stepwise multiple regression analysis identified increased self-transcendence scores and state anxiety severity as the only predictors of a increased cannabis use severity (F = 6.635; d.f. = 2, 81; p = 0.0021). In particular, in a further multivariate analysis of variance, the transpersonal identification issue of self-transcendence was associated significantly (F = 4.267; d.f. = 2, 81; p = 0.017) with greater severity of cannabis use. Character dimension of self-transcendence and symptoms of state anxiety should be taken into consideration during the assessment procedure of patients with cannabis use as they may be helpful in the discrimination of cannabis use severity.

Pharmacy Student Attitudes and Willingness to Engage in Care with People Living with HIV/AIDS

PubMed Central

Furtek, Kari J.; Malladi, Ruthvik; Ng, Eric; Zhou, Maria

2016-01-01

Objective. To describe the extent to which pharmacy students hold negative attitudes toward people living with HIV/AIDS (PLWHA) and to determine whether background variables, student knowledge, and professional attitudes may affect willingness to care for PLWHA. Methods. An online survey tool was developed and administered to 150 pharmacy students in their third professional year. Descriptive and stepwise multivariate regressions were performed. Results. While descriptive results showed a majority of respondents had favorable professional attitudes towards caring for PLWHA, most pharmacy students expressed discomfort with specific attitudes about being in close physical contact and receiving selected services from PLWHA. Multivariate results revealed that: (1) being a minority predicted greater knowledge; (2) having received prior HIV instruction and greater HIV knowledge predicted more positive professional attitudes caring for PLWHA; (3) being more socially liberal, having more positive professional attitudes caring for PLWHA, and having greater empathy towards PLWHA predicted student willingness to provide services. Conclusion. Future educational interventions specifically targeted toward socially conservative whites may impact greater student willingness to care for PLWHA. Additional research should also explore the generalizability of the present findings and modeling to pharmacy students in other regions of the country. PMID:27170816

Exploring the facilitators and barriers to engagement in physical activity for people with multiple sclerosis.

PubMed

Kayes, Nicola M; McPherson, Kathryn M; Schluter, Philip; Taylor, Denise; Leete, Marta; Kolt, Gregory S

2011-01-01

To explore the relationship that cognitive behavioural and other previously identified variables have with physical activity engagement in people with multiple sclerosis (MS). This study adopted a cross-sectional questionnaire design. Participants were 282 individuals with MS. Outcome measures included the Physical Activity Disability Survey--Revised, Cognitive and Behavioural Responses to Symptoms Questionnaire, Barriers to Health Promoting Activities for Disabled Persons Scale, Multiple Sclerosis Self-efficacy Scale, Self-Efficacy for Chronic Diseases Scales and Chalder Fatigue Questionnaire. Multivariable stepwise regression analyses found that greater self-efficacy, greater reported mental fatigue and lower number of perceived barriers to physical activity accounted for a significant proportion of variance in physical activity behaviour, over that accounted for by illness-related variables. Although fear-avoidance beliefs accounted for a significant proportion of variance in the initial analyses, its effect was explained by other factors in the final multivariable analyses. Self-efficacy, mental fatigue and perceived barriers to physical activity are potentially modifiable variables which could be incorporated into interventions designed to improve physical activity engagement. Future research should explore whether a measurement tool tailored to capture beliefs about physical activity identified by people with MS would better predict participation in physical activity.

An open-source software package for multivariate modeling and clustering: applications to air quality management.

PubMed

Wang, Xiuquan; Huang, Guohe; Zhao, Shan; Guo, Junhong

2015-09-01

This paper presents an open-source software package, rSCA, which is developed based upon a stepwise cluster analysis method and serves as a statistical tool for modeling the relationships between multiple dependent and independent variables. The rSCA package is efficient in dealing with both continuous and discrete variables, as well as nonlinear relationships between the variables. It divides the sample sets of dependent variables into different subsets (or subclusters) through a series of cutting and merging operations based upon the theory of multivariate analysis of variance (MANOVA). The modeling results are given by a cluster tree, which includes both intermediate and leaf subclusters as well as the flow paths from the root of the tree to each leaf subcluster specified by a series of cutting and merging actions. The rSCA package is a handy and easy-to-use tool and is freely available at http://cran.r-project.org/package=rSCA . By applying the developed package to air quality management in an urban environment, we demonstrate its effectiveness in dealing with the complicated relationships among multiple variables in real-world problems.

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.

A land use regression model for ambient ultrafine particles in Montreal, Canada: A comparison of linear regression and a machine learning approach.

PubMed

Weichenthal, Scott; Ryswyk, Keith Van; Goldstein, Alon; Bagg, Scott; Shekkarizfard, Maryam; Hatzopoulou, Marianne

2016-04-01

Existing evidence suggests that ambient ultrafine particles (UFPs) (<0.1µm) may contribute to acute cardiorespiratory morbidity. However, few studies have examined the long-term health effects of these pollutants owing in part to a need for exposure surfaces that can be applied in large population-based studies. To address this need, we developed a land use regression model for UFPs in Montreal, Canada using mobile monitoring data collected from 414 road segments during the summer and winter months between 2011 and 2012. Two different approaches were examined for model development including standard multivariable linear regression and a machine learning approach (kernel-based regularized least squares (KRLS)) that learns the functional form of covariate impacts on ambient UFP concentrations from the data. The final models included parameters for population density, ambient temperature and wind speed, land use parameters (park space and open space), length of local roads and rail, and estimated annual average NOx emissions from traffic. The final multivariable linear regression model explained 62% of the spatial variation in ambient UFP concentrations whereas the KRLS model explained 79% of the variance. The KRLS model performed slightly better than the linear regression model when evaluated using an external dataset (R(2)=0.58 vs. 0.55) or a cross-validation procedure (R(2)=0.67 vs. 0.60). In general, our findings suggest that the KRLS approach may offer modest improvements in predictive performance compared to standard multivariable linear regression models used to estimate spatial variations in ambient UFPs. However, differences in predictive performance were not statistically significant when evaluated using the cross-validation procedure. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

Optimizing working space in laparoscopy: CT measurement of the effect of pre-stretching of the abdominal wall in a porcine model.

PubMed

Vlot, John; Wijnen, René; Stolker, Robert Jan; Bax, Klaas N

2014-03-01

Determinants of working space in minimal access surgery have not been well studied. Using computed tomography (CT) to measure volumes and linear dimensions, we are studying the effect of a number of determinants of CO2 working space in a porcine laparoscopy model. Here we report the effects of pre-stretching of the abdominal wall. Earlier we had noted an increase in CO2 pneumoperitoneum volume at repeat insufflation with an intra-abdominal pressure (IAP) of 5 mmHg after previous stepwise insufflation up to an IAP of 15 mmHg. We reviewed the data of this serendipity group; data of 16 pigs were available. In a new group of eight pigs, we also explored this effect at repeat IAPs of 10 and 15 mmHg. Volumes and linear dimensions of the CO2 pneumoperitoneum were measured on reconstructed CT images and compared between the initial and repeat insufflation runs. Previous stepwise insufflation of the abdomen with CO2 up to 15 mmHg significantly (p < 0.01) increased subsequent working-space volume at a repeat IAP of 5 mmHg by 21 %, 7 % at a repeat IAP of 10 mmHg and 3 % at a repeat IAP of 15 mmHg. The external anteroposterior diameter significantly (p < 0.01) increased by 0.5 cm (14 %) at repeat 5 mmHg. Other linear dimensions showed a much smaller change. There was no statistically significant correlation between the duration of the insufflation run and the volume increase after pre-stretching at all IAP levels. Pre-stretching of the abdominal wall allows for the same surgical-field exposure at lower IAPs, reducing the negative effects of prolonged high-pressure CO2 pneumoperitoneum on the cardiorespiratory system and microcirculation. Pre-stretching has important scientific consequences in studies addressing ways of increasing working space in that its effect may confound the possible effects of other interventions aimed at increasing working space.

Recent trends of groundwater temperatures in Austria

NASA Astrophysics Data System (ADS)

Benz, Susanne A.; Bayer, Peter; Winkler, Gerfried; Blum, Philipp

2018-06-01

Climate change is one of if not the most pressing challenge modern society faces. Increasing temperatures are observed all over the planet and the impact of climate change on the hydrogeological cycle has long been shown. However, so far we have insufficient knowledge on the influence of atmospheric warming on shallow groundwater temperatures. While some studies analyse the implication climate change has for selected wells, large-scale studies are so far lacking. Here we focus on the combined impact of climate change in the atmosphere and local hydrogeological conditions on groundwater temperatures in 227 wells in Austria, which have in part been observed since 1964. A linear analysis finds a temperature change of +0.7 ± 0.8 K in the years from 1994 to 2013. In the same timeframe surface air temperatures in Austria increased by 0.5 ± 0.3 K, displaying a much smaller variety. However, most of the extreme changes in groundwater temperatures can be linked to local hydrogeological conditions. Correlation between groundwater temperatures and nearby surface air temperatures was additionally analysed. They vary greatly, with correlation coefficients of -0.3 in central Linz to 0.8 outside of Graz. In contrast, the correlation of nationwide groundwater temperatures and surface air temperatures is high, with a correlation coefficient of 0.83. All of these findings indicate that while atmospheric climate change can be observed in nationwide groundwater temperatures, individual wells are often primarily dominated by local hydrogeological conditions. In addition to the linear temperature trend, a step-wise model was also applied that identifies climate regime shifts, which were observed globally in the late 70s, 80s, and 90s. Hinting again at the influence of local conditions, at most 22 % of all wells show these climate regime shifts. However, we were able to identify an additional shift in 2007, which was observed by 37 % of all wells. Overall, the step-wise representation provides a slightly more accurate picture of observed temperatures than the linear trend.

Socio-economic factors associated with infant mortality in Italy: an ecological study

PubMed Central

2012-01-01

Introduction One issue that continues to attract the attention of public health researchers is the possible relationship in high-income countries between income, income inequality and infant mortality (IM). The aim of this study was to assess the associations between IM and major socio-economic determinants in Italy. Methods Associations between infant mortality rates in the 20 Italian regions (2006–2008) and the Gini index of income inequality, mean household income, percentage of women with at least 8 years of education, and percentage of unemployed aged 15–64 years were assessed using Pearson correlation coefficients. Univariate linear regression and multiple stepwise linear regression analyses were performed to determine the magnitude and direction of the effect of the four socio-economic variables on IM. Results The Gini index and the total unemployment rate showed a positive strong correlation with IM (r = 0.70; p < 0.001 and r = 0.84; p < 0.001 respectively), mean household income showed a strong negative correlation (r = −0.78; p < 0.001), while female educational attainment presented a weak negative correlation (r = −0.45; p < 0.05). Using a multiple stepwise linear regression model, only unemployment rate was independently associated with IM (b = 0.15, p < 0.001). Conclusions In Italy, a high-income country where health care is universally available, variations in IM were strongly associated with relative and absolute income and unemployment rate. These results suggest that in Italy IM is not only related to income distribution, as demonstrated for other developed countries, but also to economic factors such as absolute income and unemployment. In order to reduce IM and the existing inequalities, the challenge for Italian decision makers is to promote economic growth and enhance employment levels. PMID:22898293

Emission and distribution of phosphine in paddy fields and its relationship with greenhouse gases.

PubMed

Chen, Weiyi; Niu, Xiaojun; An, Shaorong; Sheng, Hong; Tang, Zhenghua; Yang, Zhiquan; Gu, Xiaohong

2017-12-01

Phosphine (PH 3 ), as a gaseous phosphide, plays an important role in the phosphorus cycle in ecosystems. In this study, the emission and distribution of phosphine, carbon dioxide (CO 2 ) and methane (CH 4 ) in paddy fields were investigated to speculate the future potential impacts of enhanced greenhouse effect on phosphorus cycle involved in phosphine by the method of Pearson correlation analysis and multiple linear regression analysis. During the whole period of rice growth, there was a significant positive correlation between CO 2 emission flux and PH 3 emission flux (r=0.592, p=0.026, n=14). Similarly, a significant positive correlation of emission flux was also observed between CH 4 and PH 3 (r=0.563, p=0.036, n=14). The linear regression relationship was determined as [PH 3 ] flux =0.007[CO 2 ] flux +0.063[CH 4 ] flux -4.638. No significant differences were observed for all values of matrix-bound phosphine (MBP), soil carbon dioxide (SCO 2 ), and soil methane (SCH 4 ) in paddy soils. However, there was a significant positive correlation between MBP and SCO 2 at heading, flowering and ripening stage. The correlation coefficients were 0.909, 0.890 and 0.827, respectively. In vertical distribution, MBP had the analogical variation trend with SCO 2 and SCH 4 . Through Pearson correlation analysis and multiple stepwise linear regression analysis, pH, redox potential (Eh), total phosphorus (TP) and acid phosphatase (ACP) were identified as the principal factors affecting MBP levels, with correlative rankings of Eh>pH>TP>ACP. The multiple stepwise regression model ([MBP]=0.456∗[ACP]+0.235∗[TP]-1.458∗[Eh]-36.547∗[pH]+352.298) was obtained. The findings in this study hold great reference values to the global biogeochemical cycling of phosphorus in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

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

NASA Technical Reports Server (NTRS)

Soeder, J. F.

1983-01-01

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

Sources of variability in satellite-derived estimates of phytoplankton production in the eastern tropical Pacific

NASA Technical Reports Server (NTRS)

Banse, Karl; Yong, Marina

1990-01-01

As a proxy for satellite CZCS observations and concurrent measurements of primary production rates, data from 138 stations occupied seasonally during 1967-1968 in the offshore eastern tropical Pacific were analyzed in terms of six temporal groups and our current regimes. Multiple linear regressions on column production Pt show that simulated satellite pigment is generally weakly correlated, but sometimes not correlated with Pt, and that incident irradiance, sea surface temperature, nitrate, transparency, and depths of mixed layer or nitracline assume little or no importance. After a proxy for the light-saturated chlorophyll-specific photosynthetic rate P(max) is added, the coefficient of determination ranges from 0.55 to 0.91 (median of 0.85) for the 10 cases. In stepwise multiple linear regressions the P(max) proxy is the best predictor for Pt.

Commentary on A General Curriculum in Mathematics for Colleges.

ERIC Educational Resources Information Center

Committee on the Undergraduate Program in Mathematics, Berkeley, CA.

This document constitutes a complete revision of the report of the same name first published in 1965. A new list of basic courses is described, consisting of Calculus I, Calculus II, Elementary Linear Algebra, Multivariable Calculus I, Linear Algebra, and Introductory Modern Algebra. Commentaries outline the content and spirit of these courses in…

Computation of nonlinear least squares estimator and maximum likelihood using principles in matrix calculus

NASA Astrophysics Data System (ADS)

Mahaboob, B.; Venkateswarlu, B.; Sankar, J. Ravi; Balasiddamuni, P.

2017-11-01

This paper uses matrix calculus techniques to obtain Nonlinear Least Squares Estimator (NLSE), Maximum Likelihood Estimator (MLE) and Linear Pseudo model for nonlinear regression model. David Pollard and Peter Radchenko [1] explained analytic techniques to compute the NLSE. However the present research paper introduces an innovative method to compute the NLSE using principles in multivariate calculus. This study is concerned with very new optimization techniques used to compute MLE and NLSE. Anh [2] derived NLSE and MLE of a heteroscedatistic regression model. Lemcoff [3] discussed a procedure to get linear pseudo model for nonlinear regression model. In this research article a new technique is developed to get the linear pseudo model for nonlinear regression model using multivariate calculus. The linear pseudo model of Edmond Malinvaud [4] has been explained in a very different way in this paper. David Pollard et.al used empirical process techniques to study the asymptotic of the LSE (Least-squares estimation) for the fitting of nonlinear regression function in 2006. In Jae Myung [13] provided a go conceptual for Maximum likelihood estimation in his work “Tutorial on maximum likelihood estimation

A way around the Nyquist lag

NASA Astrophysics Data System (ADS)

Penland, C.

2017-12-01

One way to test for the linearity of a multivariate system is to perform Linear Inverse Modeling (LIM) to a multivariate time series. LIM yields an estimated operator by combining a lagged covariance matrix with the contemporaneous covariance matrix. If the underlying dynamics is linear, the resulting dynamical description should not depend on the particular lag at which the lagged covariance matrix is estimated. This test is known as the "tau test." The tau test will be severely compromised if the lag at which the analysis is performed is approximately half the period of an internal oscillation frequency. In this case, the tau test will fail even though the dynamics are actually linear. Thus, until now, the tau test has only been possible for lags smaller than this "Nyquist lag." In this poster, we investigate the use of Hilbert transforms as a way to avoid the problems associated with Nyquist lags. By augmenting the data with dimensions orthogonal to those spanning the original system, information that would be inaccessible to LIM in its original form may be sampled.

Exploring the association between parental rearing styles and medical students' critical thinking disposition in China.

PubMed

Huang, Lei; Wang, Zhaoxin; Yao, Yuhong; Shan, Chang; Wang, Haojie; Zhu, Mengyi; Lu, Yuan; Sun, Pengfei; Zhao, Xudong

2015-05-14

Critical thinking is an essential ability for medical students. However, the relationship between parental rearing styles and medical students' critical thinking disposition has rarely been considered. The aim of this study was to investigate whether parental rearing styles were significant predictors of critical thinking disposition among Chinese medical students. 1,075 medical students from the first year to the fifth year attending one of three medical schools in China were recruited via multistage stratified cluster sampling. The Chinese Critical Thinking Disposition Inventory(CTDI-CV) and The Egna Minnen av Barndoms Uppfostran (EMBU) questionnaire were applied to collect data and to conduct descriptive analysis. Stepwise multiple linear regression was used to analyze the data. The critical thinking disposition average mean score was 287.44 with 632 participants (58.79%) demonstrating positive critical thinking disposition. Stepwise multiple linear regression analysis revealed that the rearing styles of fathers, including "overprotection", "emotional warmth and understanding", "rejection" and "over-interference" were significant predictors of medical students' critical thinking disposition that explained 79.0% of the variance in critical thinking ability. Rearing styles of mothers including "emotional warmth and understanding", "punishing" and "rejection" were also found to be significant predictors, and explained 77.0% of the variance. Meaningful association has been evidenced between parental rearing styles and Chinese medical students' critical thinking disposition. Parental rearing styles should be considered as one of the many potential determinant factors that contribute to the cultivation of medical students' critical thinking capability. Positive parental rearing styles should be encouraged in the cultivation of children's critical thinking skills.

Relationship between masticatory performance using a gummy jelly and masticatory movement.

PubMed

Uesugi, Hanako; Shiga, Hiroshi

2017-10-01

The purpose of this study was to clarify the relationship between masticatory performance using a gummy jelly and masticatory movement. Thirty healthy males were asked to chew a gummy jelly on their habitual chewing side for 20s, and the parameters of masticatory performance and masticatory movement were calculated as follows. For evaluating the masticatory performance, the amount of glucose extraction during chewing of a gummy jelly was measured. For evaluating the masticatory movement, the movement of the mandibular incisal point was recorded using the MKG K6-I, and ten parameters of the movement path (opening distance and masticatory width), movement rhythm (opening time, closing time, occluding time, and cycle time), stability of movement (stability of path and stability of rhythm), and movement velocity (opening maximum velocity and closing maximum velocity) were calculated from 10 cycles of chewing beginning with the fifth cycle. The relationship between the amount of glucose extraction and parameters representing masticatory movement was investigated and then stepwise multiple linear regression analysis was performed. The amount of glucose extraction was associated with 7 parameters representing the masticatory movement. Stepwise multiple linear regression analysis showed that the opening distance, closing time, stability of rhythm, and closing maximum velocity were the most important factors affecting the glucose extraction. From these results it was suggested that there was a close relation between masticatory performance and masticatory movement, and that the masticatory performance could be increased by rhythmic, rapid and stable mastication with a large opening distance. Copyright © 2017 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

The use of machine learning for the identification of peripheral artery disease and future mortality risk.

PubMed

Ross, Elsie Gyang; Shah, Nigam H; Dalman, Ronald L; Nead, Kevin T; Cooke, John P; Leeper, Nicholas J

2016-11-01

A key aspect of the precision medicine effort is the development of informatics tools that can analyze and interpret "big data" sets in an automated and adaptive fashion while providing accurate and actionable clinical information. The aims of this study were to develop machine learning algorithms for the identification of disease and the prognostication of mortality risk and to determine whether such models perform better than classical statistical analyses. Focusing on peripheral artery disease (PAD), patient data were derived from a prospective, observational study of 1755 patients who presented for elective coronary angiography. We employed multiple supervised machine learning algorithms and used diverse clinical, demographic, imaging, and genomic information in a hypothesis-free manner to build models that could identify patients with PAD and predict future mortality. Comparison was made to standard stepwise linear regression models. Our machine-learned models outperformed stepwise logistic regression models both for the identification of patients with PAD (area under the curve, 0.87 vs 0.76, respectively; P = .03) and for the prediction of future mortality (area under the curve, 0.76 vs 0.65, respectively; P = .10). Both machine-learned models were markedly better calibrated than the stepwise logistic regression models, thus providing more accurate disease and mortality risk estimates. Machine learning approaches can produce more accurate disease classification and prediction models. These tools may prove clinically useful for the automated identification of patients with highly morbid diseases for which aggressive risk factor management can improve outcomes. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Evaluation of interpolation techniques for the creation of gridded daily precipitation (1 × 1 km2); Cyprus, 1980-2010

NASA Astrophysics Data System (ADS)

Camera, Corrado; Bruggeman, Adriana; Hadjinicolaou, Panos; Pashiardis, Stelios; Lange, Manfred A.

2014-01-01

High-resolution gridded daily data sets are essential for natural resource management and the analyses of climate changes and their effects. This study aims to evaluate the performance of 15 simple or complex interpolation techniques in reproducing daily precipitation at a resolution of 1 km2 over topographically complex areas. Methods are tested considering two different sets of observation densities and different rainfall amounts. We used rainfall data that were recorded at 74 and 145 observational stations, respectively, spread over the 5760 km2 of the Republic of Cyprus, in the Eastern Mediterranean. Regression analyses utilizing geographical copredictors and neighboring interpolation techniques were evaluated both in isolation and combined. Linear multiple regression (LMR) and geographically weighted regression methods (GWR) were tested. These included a step-wise selection of covariables, as well as inverse distance weighting (IDW), kriging, and 3D-thin plate splines (TPS). The relative rank of the different techniques changes with different station density and rainfall amounts. Our results indicate that TPS performs well for low station density and large-scale events and also when coupled with regression models. It performs poorly for high station density. The opposite is observed when using IDW. Simple IDW performs best for local events, while a combination of step-wise GWR and IDW proves to be the best method for large-scale events and high station density. This study indicates that the use of step-wise regression with a variable set of geographic parameters can improve the interpolation of large-scale events because it facilitates the representation of local climate dynamics.

Clinical utility of the AlphaFIM® instrument in stroke rehabilitation.

PubMed

Lo, Alexander; Tahair, Nicola; Sharp, Shelley; Bayley, Mark T

2012-02-01

The AlphaFIM instrument is an assessment tool designed to facilitate discharge planning of stroke patients from acute care, by extrapolating overall functional status from performance in six key Functional Independence Measure (FIM) instrument items. To determine whether acute care AlphaFIM rating is correlated to stroke rehabilitation outcomes. In this prospective observational study, data were analyzed from 891 patients referred for inpatient stroke rehabilitation through an Internet-based referral system. Simple linear and stepwise regression models determined correlations between rehabilitation-ready AlphaFIM rating and rehabilitation outcomes (admission and discharge FIM ratings, FIM gain, FIM efficiency, and length of stay). Covariates including demographic data, stroke characteristics, medical history, cognitive deficits, and activity tolerance were included in the stepwise regressions. The AlphaFIM instrument was significant in predicting admission and discharge FIM ratings at rehabilitation (adjusted R² 0.40 and 0.28, respectively; P < 0.0001) and was weakly correlated with FIM gain and length of stay (adjusted R² 0.04 and 0.09, respectively; P < 0.0001), but not FIM efficiency. AlphaFIM rating was inversely related to FIM gain. Age, bowel incontinence, left hemiparesis, and previous infarcts were negative predictors of discharge FIM rating on stepwise regression. Intact executive function and physical activity tolerance of 30 to 60 mins were predictors of FIM gain. The AlphaFIM instrument is a valuable tool for triaging stroke patients from acute care to rehabilitation and predicts functional status at discharge from rehabilitation. Patients with low AlphaFIM ratings have the potential to make significant functional gains and should not be denied admission to inpatient rehabilitation programs.

Analysis of blood flow in the long posterior ciliary artery of the cat.

PubMed

Koss, M C

1999-03-01

Experiments were undertaken to use a new technique for direct on-line measurement of blood flow in the long posterior ciliary artery (LPCA) in cats and to evaluate possible physiological mechanisms controlling blood flow in the vascular beds perfused by this artery. Blood flow in the temporal LPCA was measured on a continuous basis using ultrasonic flowmetry in anesthetized cats. Effects of acute sectioning of the sympathetic nerve and changes in LPCA and cerebral blood flows in response to altered levels of inspired CO2 and O2 were tested in some animals. In others, the presence of vascular autoregulatory mechanisms in response to stepwise elevations of intraocular pressure was studied. Blood flow in the temporal LPCA averaged 0.58+/-0.03 ml/min in 45 cats anesthetized with pentobarbital. Basal LPCA blood flow was not altered by acute sectioning of the sympathetic nerve or by changes in low levels of inspired CO2 and O2, although 10% CO2 caused a modest increase. Stepwise elevations of intraocular pressure resulted in comparable stepwise decreases of LPCA blood flow, with perfusion pressure declining in a linear manner throughout the perfusion-pressure range. Ultrasonic flowmetry seems to be a useful tool for continuous on-line measurement of LPCA blood flow in the cat eye. Blood flow to vascular beds perfused by this artery does not seem to be under sympathetic neural control and is refractory to modest alterations of blood gas levels of CO2 and O2. Blood vessels perfused by the LPCA show no clear autoregulatory mechanisms.

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

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

2016-01-01

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

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

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

2016-01-01

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

Kernel canonical-correlation Granger causality for multiple time series

NASA Astrophysics Data System (ADS)

Wu, Guorong; Duan, Xujun; Liao, Wei; Gao, Qing; Chen, Huafu

2011-04-01

Canonical-correlation analysis as a multivariate statistical technique has been applied to multivariate Granger causality analysis to infer information flow in complex systems. It shows unique appeal and great superiority over the traditional vector autoregressive method, due to the simplified procedure that detects causal interaction between multiple time series, and the avoidance of potential model estimation problems. However, it is limited to the linear case. Here, we extend the framework of canonical correlation to include the estimation of multivariate nonlinear Granger causality for drawing inference about directed interaction. Its feasibility and effectiveness are verified on simulated data.

Decoupling in linear time-varying multivariable systems

NASA Technical Reports Server (NTRS)

Sankaran, V.

1973-01-01

The necessary and sufficient conditions for the decoupling of an m-input, m-output, linear time varying dynamical system by state variable feedback is described. The class of feedback matrices which decouple the system are illustrated. Systems which do not satisfy these results are described and systems with disturbances are considered. Some examples are illustrated to clarify the results.

Standard Error of Linear Observed-Score Equating for the NEAT Design with Nonnormally Distributed Data

ERIC Educational Resources Information Center

Zu, Jiyun; Yuan, Ke-Hai

2012-01-01

In the nonequivalent groups with anchor test (NEAT) design, the standard error of linear observed-score equating is commonly estimated by an estimator derived assuming multivariate normality. However, real data are seldom normally distributed, causing this normal estimator to be inconsistent. A general estimator, which does not rely on the…

Flipping an Algebra Classroom: Analyzing, Modeling, and Solving Systems of Linear Equations

ERIC Educational Resources Information Center

Kirvan, Rebecca; Rakes, Christopher R.; Zamora, Regie

2015-01-01

The present study investigated whether flipping an algebra classroom led to a stronger focus on conceptual understanding and improved learning of systems of linear equations for 54 seventh- and eighth-grade students using teacher journal data and district-mandated unit exam items. Multivariate analysis of covariance was used to compare scores on…

Differentiation of infiltrative cholangiocarcinoma from benign common bile duct stricture using three-dimensional dynamic contrast-enhanced MRI with MRCP.

PubMed

Yu, X-R; Huang, W-Y; Zhang, B-Y; Li, H-Q; Geng, D-Y

2014-06-01

To retrospectively evaluate the criteria for discriminating infiltrative cholangiocarcinoma from benign common bile duct (CBD) stricture using three-dimensional dynamic contrast-enhanced (3D-DCE) magnetic resonance imaging (MRI) combined with magnetic resonance cholangiopancreatography (MRCP) imaging and to determine the predictors for cholangiocarcinoma versus benign CBD stricture. 3D-DCE MRI and MRCP images in 28 patients with infiltrative cholangiocarcinoma and 23 patients with benign causes of CBD stricture were reviewed retrospectively. The final diagnosis was based on surgical or biopsy records. Two radiologists analysed the MRI images for asymmetry, including the wall thickness, length, and enhancement pattern of the narrowed CBD segment, and upstream CBD dilatation. MRI findings that could be used as predictors were identified by univariate analysis and multivariable stepwise logistic regression analysis. Malignant strictures were significantly thicker (4.4 ± 1.2 mm) and longer (16.7 ± 7.7 mm) than the benign strictures (p < 0.05), and upstream CBD dilatation was larger in the infiltrative cholangiocarcinoma cases (20.7 ± 5.7 mm) than in the benign cases (16.5 ± 5.2 mm; p = 0.018). During both the portal venous and equilibrium phases, hyperenhancement was more frequently observed in malignant cases than in benign cases (p < 0.001). The results of the multivariable stepwise logistic regression analysis showed that both hyperenhancement of the involved CBD during the equilibrium phase and the ductal thickness were significant predictors for malignant strictures. When two diagnostic predictive values were used in combination, almost all patients with malignant strictures (n = 26, 92.9%) and benign strictures (n = 21, 91.3%) were correctly identified; the overall accuracy was 92.2% with correct classifications in 47 of the 51 patients. Infiltrative cholangiocarcinoma and benign CBD strictures could be effectively differentiated using DCE-MRI and MRCP based on hyperenhancement during the equilibrium phase and bile wall thickness of the involved segment. Copyright © 2014 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

A Test Strategy for High Resolution Image Scanners.

DTIC Science & Technology

1983-10-01

for multivariate analysis. Holt, Richart and Winston, Inc., New York. Graybill , F.A., 1961: An introduction to linear statistical models . SVolume I...i , j i -(7) 02 1 )2 y 4n .i ij 13 The linear estimation model for the polynomial coefficients can be set up as - =; =(8) with T = ( x’ . . X-nn "X...Resolution Image Scanner MTF Geometrical and radiometric performance Dynamic range, linearity , noise - Dynamic scanning errors Response uniformity Skewness of

On Generalizations of Cochran’s Theorem and Projection Matrices.

DTIC Science & Technology

1980-08-01

Definiteness of the Estimated Dispersion Matrix in a Multivariate Linear Model ," F. Pukelsheim and George P.H. Styan, May 1978. TECHNICAL REPORTS...with applications to the analysis of covariance," Proc. Cambridge Philos. Soc., 30, pp. 178-191. Graybill , F. A. and Marsaglia, G. (1957...34Idempotent matrices and quad- ratic forms in the general linear hypothesis," Ann. Math. Statist., 28, pp. 678-686. Greub, W. (1975). Linear Algebra (4th ed

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.

[Use of multiple regression models in observational studies (1970-2013) and requirements of the STROBE guidelines in Spanish scientific journals].

PubMed

Real, J; Cleries, R; Forné, C; Roso-Llorach, A; Martínez-Sánchez, J M

In medicine and biomedical research, statistical techniques like logistic, linear, Cox and Poisson regression are widely known. The main objective is to describe the evolution of multivariate techniques used in observational studies indexed in PubMed (1970-2013), and to check the requirements of the STROBE guidelines in the author guidelines in Spanish journals indexed in PubMed. A targeted PubMed search was performed to identify papers that used logistic linear Cox and Poisson models. Furthermore, a review was also made of the author guidelines of journals published in Spain and indexed in PubMed and Web of Science. Only 6.1% of the indexed manuscripts included a term related to multivariate analysis, increasing from 0.14% in 1980 to 12.3% in 2013. In 2013, 6.7, 2.5, 3.5, and 0.31% of the manuscripts contained terms related to logistic, linear, Cox and Poisson regression, respectively. On the other hand, 12.8% of journals author guidelines explicitly recommend to follow the STROBE guidelines, and 35.9% recommend the CONSORT guideline. A low percentage of Spanish scientific journals indexed in PubMed include the STROBE statement requirement in the author guidelines. Multivariate regression models in published observational studies such as logistic regression, linear, Cox and Poisson are increasingly used both at international level, as well as in journals published in Spanish. Copyright © 2015 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.

Stepwise pumping approach to improve free phase light hydrocarbon recovery from unconfined aquifers

NASA Astrophysics Data System (ADS)

Cooper, Grant S.; Peralta, Richard C.; Kaluarachchi, Jagath J.

1995-04-01

A stepwise, time-varying pumping approach is developed to improve free phase oil recovery of light non-aqueous phase liquids (LNAPL) from a homogeneous, unconfined aquifer. Stepwise pumping is used to contain the floating oil plume and obtain efficient free oil recovery. The graphical plots. The approach uses ARMOS ©, an areal two-dimensional multiphase flow, finite-element simulation model. Systematic simulations of free oil area changes to pumping rates are analyzed. Pumping rates are determined that achieve LNAPL plume containment at different times (i.e. 90, 180 and 360 days) for a planning period of 360 days. These pumping rates are used in reverse order as a stepwise (monotonically increasing) pumping strategy. This stepwise pumping strategy is analyzed further by performing additional simulations at different pumping rates for the last pumping period. The final stepwise pumping strategy is varied by factors of -25% and +30% to evaluate sensitivity in the free oil recovery process. Stepwise pumping is compared to steady pumping rates to determine the best free oil recovery strategy. Stepwise pumping is shown to improve oil recovery by increasing recoveredoil volume (11%) and decreasing residual oil (15%) when compared with traditional steady pumping strategies. The best stepwise pumping strategy recovers more free oil by reducing the amount of residual oil left in the system due to pumping drawdown. This stepwise pumping pproach can be used to enhance free oil recovery and provide for cost-effective design and management of LNAPL cleanup.

Adaptive velocity-based six degree of freedom load control for real-time unconstrained biomechanical testing.

PubMed

Lawless, I M; Ding, B; Cazzolato, B S; Costi, J J

2014-09-22

Robotic biomechanics is a powerful tool for further developing our understanding of biological joints, tissues and their repair. Both velocity-based and hybrid force control methods have been applied to biomechanics but the complex and non-linear properties of joints have limited these to slow or stepwise loading, which may not capture the real-time behaviour of joints. This paper presents a novel force control scheme combining stiffness and velocity based methods aimed at achieving six degree of freedom unconstrained force control at physiological loading rates. Copyright © 2014 Elsevier Ltd. All rights reserved.

Prediction of health levels by remote sensing

NASA Technical Reports Server (NTRS)

Rush, M.; Vernon, S.

1975-01-01

Measures of the environment derived from remote sensing were compared to census population/housing measures in their ability to discriminate among health status areas in two urban communities. Three hypotheses were developed to explore the relationships between environmental and health data. Univariate and multiple step-wise linear regression analyses were performed on data from two sample areas in Houston and Galveston, Texas. Environmental data gathered by remote sensing were found to equal or surpass census data in predicting rates of health outcomes. Remote sensing offers the advantages of data collection for any chosen area or time interval, flexibilities not allowed by the decennial census.

Laboratory- and field-based testing as predictors of skating performance in competitive-level female ice hockey.

PubMed

Henriksson, Tommy; Vescovi, Jason D; Fjellman-Wiklund, Anncristine; Gilenstam, Kajsa

2016-01-01

The purpose of this study was to examine whether field-based and/or laboratory-based assessments are valid tools for predicting key performance characteristics of skating in competitive-level female hockey players. Cross-sectional study. Twenty-three female ice hockey players aged 15-25 years (body mass: 66.1±6.3 kg; height: 169.5±5.5 cm), with 10.6±3.2 years playing experience volunteered to participate in the study. The field-based assessments included 20 m sprint, squat jump, countermovement jump, 30-second repeated jump test, standing long jump, single-leg standing long jump, 20 m shuttle run test, isometric leg pull, one-repetition maximum bench press, and one-repetition maximum squats. The laboratory-based assessments included body composition (dual energy X-ray absorptiometry), maximal aerobic power, and isokinetic strength (Biodex). The on-ice tests included agility cornering s-turn, cone agility skate, transition agility skate, and modified repeat skate sprint. Data were analyzed using stepwise multivariate linear regression analysis. Linear regression analysis was used to establish the relationship between key performance characteristics of skating and the predictor variables. Regression models (adj R (2)) for the on-ice variables ranged from 0.244 to 0.663 for the field-based assessments and from 0.136 to 0.420 for the laboratory-based assessments. Single-leg tests were the strongest predictors for key performance characteristics of skating. Single leg standing long jump alone explained 57.1%, 38.1%, and 29.1% of the variance in skating time during transition agility skate, agility cornering s-turn, and modified repeat skate sprint, respectively. Isokinetic peak torque in the quadriceps at 90° explained 42.0% and 32.2% of the variance in skating time during agility cornering s-turn and modified repeat skate sprint, respectively. Field-based assessments, particularly single-leg tests, are an adequate substitute to more expensive and time-consuming laboratory assessments if the purpose is to gain knowledge about key performance characteristics of skating.

Laboratory- and field-based testing as predictors of skating performance in competitive-level female ice hockey

PubMed Central

Henriksson, Tommy; Vescovi, Jason D; Fjellman-Wiklund, Anncristine; Gilenstam, Kajsa

2016-01-01

Objectives The purpose of this study was to examine whether field-based and/or laboratory-based assessments are valid tools for predicting key performance characteristics of skating in competitive-level female hockey players. Design Cross-sectional study. Methods Twenty-three female ice hockey players aged 15–25 years (body mass: 66.1±6.3 kg; height: 169.5±5.5 cm), with 10.6±3.2 years playing experience volunteered to participate in the study. The field-based assessments included 20 m sprint, squat jump, countermovement jump, 30-second repeated jump test, standing long jump, single-leg standing long jump, 20 m shuttle run test, isometric leg pull, one-repetition maximum bench press, and one-repetition maximum squats. The laboratory-based assessments included body composition (dual energy X-ray absorptiometry), maximal aerobic power, and isokinetic strength (Biodex). The on-ice tests included agility cornering s-turn, cone agility skate, transition agility skate, and modified repeat skate sprint. Data were analyzed using stepwise multivariate linear regression analysis. Linear regression analysis was used to establish the relationship between key performance characteristics of skating and the predictor variables. Results Regression models (adj R2) for the on-ice variables ranged from 0.244 to 0.663 for the field-based assessments and from 0.136 to 0.420 for the laboratory-based assessments. Single-leg tests were the strongest predictors for key performance characteristics of skating. Single leg standing long jump alone explained 57.1%, 38.1%, and 29.1% of the variance in skating time during transition agility skate, agility cornering s-turn, and modified repeat skate sprint, respectively. Isokinetic peak torque in the quadriceps at 90° explained 42.0% and 32.2% of the variance in skating time during agility cornering s-turn and modified repeat skate sprint, respectively. Conclusion Field-based assessments, particularly single-leg tests, are an adequate substitute to more expensive and time-consuming laboratory assessments if the purpose is to gain knowledge about key performance characteristics of skating. PMID:27574474

Correlates of cognitive function scores in elderly outpatients.

PubMed

Mangione, C M; Seddon, J M; Cook, E F; Krug, J H; Sahagian, C R; Campion, E W; Glynn, R J

1993-05-01

To determine medical, ophthalmologic, and demographic predictors of cognitive function scores as measured by the Telephone Interview for Cognitive Status (TICS), an adaptation of the Folstein Mini-Mental Status Exam. A secondary objective was to perform an item-by-item analysis of the TICS scores to determine which items correlated most highly with the overall scores. Cross-sectional cohort study. The Glaucoma Consultation Service of the Massachusetts Eye and Ear Infirmary. 472 of 565 consecutive patients age 65 and older who were seen at the Glaucoma Consultation Service between November 1, 1987 and October 31, 1988. Each subject had a standard visual examination and review of medical history at entry, followed by a telephone interview that collected information on demographic characteristics, cognitive status, health status, accidents, falls, symptoms of depression, and alcohol intake. A multivariate linear regression model of correlates of TICS score found the strongest correlates to be education, age, occupation, and the presence of depressive symptoms. The only significant ocular condition that correlated with lower TICS score was the presence of surgical aphakia (model R2 = .46). Forty-six percent (216/472) of patients fell below the established definition of normal on the mental status scale. In a logistic regression analysis, the strongest correlates of an abnormal cognitive function score were age, diabetes, educational status, and occupational status. An item analysis using step-wise linear regression showed that 85 percent of the variance in the TICS score was explained by the ability to perform serial sevens and to repeat 10 items immediately after hearing them. Educational status correlated most highly with both of these items (Kendall Tau R = .43 and Kendall Tau R = .30, respectively). Education, occupation, depression, and age were the strongest correlates of the score on this new screening test for assessing cognitive status. These factors were stronger correlates of the TICS score than chronic medical conditions, visual loss, or medications. The Telephone Interview for Cognitive Status is a useful instrument, but it may overestimate the prevalence of dementia in studies with a high prevalence of persons with less than a high school education.

Development and validation of empirical indices to assess the insulinemic potential of diet and lifestyle

PubMed Central

Tabung, Fred K.; Wang, Weike; Fung, Teresa T.; Hu, Frank B.; Smith-Warner, Stephanie A.; Chavarro, Jorge E.; Fuchs, Charles S.; Willett, Walter C.; Giovannucci, Edward L.

2017-01-01

The glycemic and insulin indices assess postprandial glycemic and insulin response to foods respectively, which may not reflect the long-term effects of diet on insulin response. We developed and evaluated the validity of four empirical indices to assess the insulinemic potential of usual diets and lifestyles, using dietary, lifestyle and biomarker data from the Nurses’ Health Study (NHS, n=5,812 for hyperinsulinemia, n=3,929 for insulin resistance). The four indices were: the empirical dietary index for hyperinsulinemia (EDIH) and empirical lifestyle index for hyperinsulinemia (ELIH); empirical dietary index for insulin resistance (EDIR) and empirical lifestyle index for insulin resistance (ELIR). We entered 39 food frequency questionnaire-derived food groups in stepwise linear regression models and defined indices as the patterns most predictive of fasting plasma C-peptide, for the hyperinsulinemia pathway (EDIH and ELIH); and of the triglyceride/high density lipoprotein-cholesterol (TG/HDL) ratio, for the insulin resistance pathway (EDIR and ELIR). We evaluated the validity of indices in two independent samples from NHS-II and Health Professionals Follow-up Study (HPFS) using multivariable-adjusted linear regression analyses to calculate relative concentrations of biomarkers. EDIH is comprised of 18 food groups; 13 were positively associated with C-peptide, five inversely. EDIR is comprised of 18 food groups; ten were positively associated with TG/HDL and eight inversely. Lifestyle indices had fewer dietary components, and included BMI and physical activity as components. In the validation samples, all indices significantly predicted biomarker concentrations, e.g., the relative concentrations (95%CI) of the corresponding biomarkers comparing extreme index quintiles in HPFS were: EDIH, 1.29(1.22, 1.37); ELIH, 1.78(1.68, 1.88); EDIR, 1.44(1.34, 1.55); ELIR, 2.03(1.89, 2.19); all P-trend<0.0001. The robust associations of these novel hypothesis-driven indices with insulin response biomarker concentrations suggests their usefulness in assessing the ability of whole diets and lifestyles to stimulate and/or sustain insulin secretion. PMID:27821188

Optimal Stochastic Modeling and Control of Flexible Structures

DTIC Science & Technology

1988-09-01

1.37] and McLane [1.18] considered multivariable systems and derived their optimal control characteristics. Kleinman, Gorman and Zaborsky considered...Leondes [1.72,1.73] studied various aspects of multivariable linear stochastic, discrete-time systems that are partly deterministic, and partly stochastic...June 1966. 1.8. A.V. Balaknishnan, Applied Functional Analaysis , 2nd ed., New York, N.Y.: Springer-Verlag, 1981 1.9. Peter S. Maybeck, Stochastic

A Civilian/Military Trauma Institute: National Trauma Coordinating Center

DTIC Science & Technology

2015-12-01

zip codes was used in “proximity to violence” analysis. Data were analyzed using SPSS (version 20.0, SPSS Inc., Chicago, IL). Multivariable linear...number of adverse events and serious events was not statistically higher in one group, the incidence of deep venous thrombosis (DVT) was statistically ...subjects the lack of statistical difference on multivariate analysis may be related to an underpowered sample size. It was recommended that the

Multivariate moment closure techniques for stochastic kinetic models

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

Lakatos, Eszter, E-mail: e.lakatos13@imperial.ac.uk; Ale, Angelique; Kirk, Paul D. W.

2015-09-07

Stochastic effects dominate many chemical and biochemical processes. Their analysis, however, can be computationally prohibitively expensive and a range of approximation schemes have been proposed to lighten the computational burden. These, notably the increasingly popular linear noise approximation and the more general moment expansion methods, perform well for many dynamical regimes, especially linear systems. At higher levels of nonlinearity, it comes to an interplay between the nonlinearities and the stochastic dynamics, which is much harder to capture correctly by such approximations to the true stochastic processes. Moment-closure approaches promise to address this problem by capturing higher-order terms of the temporallymore » evolving probability distribution. Here, we develop a set of multivariate moment-closures that allows us to describe the stochastic dynamics of nonlinear systems. Multivariate closure captures the way that correlations between different molecular species, induced by the reaction dynamics, interact with stochastic effects. We use multivariate Gaussian, gamma, and lognormal closure and illustrate their use in the context of two models that have proved challenging to the previous attempts at approximating stochastic dynamics: oscillations in p53 and Hes1. In addition, we consider a larger system, Erk-mediated mitogen-activated protein kinases signalling, where conventional stochastic simulation approaches incur unacceptably high computational costs.« less

Robust Nonlinear Feedback Control of Aircraft Propulsion Systems

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

TG study of the Li0.4Fe2.4Zn0.2O4 ferrite synthesis

NASA Astrophysics Data System (ADS)

Lysenko, E. N.; Nikolaev, E. V.; Surzhikov, A. P.

2016-02-01

In this paper, the kinetic analysis of Li-Zn ferrite synthesis was studied using thermogravimetry (TG) method through the simultaneous application of non-linear regression to several measurements run at different heating rates (multivariate non-linear regression). Using TG-curves obtained for the four heating rates and Netzsch Thermokinetics software package, the kinetic models with minimal adjustable parameters were selected to quantitatively describe the reaction of Li-Zn ferrite synthesis. It was shown that the experimental TG-curves clearly suggest a two-step process for the ferrite synthesis and therefore a model-fitting kinetic analysis based on multivariate non-linear regressions was conducted. The complex reaction was described by a two-step reaction scheme consisting of sequential reaction steps. It is established that the best results were obtained using the Yander three-dimensional diffusion model at the first stage and Ginstling-Bronstein model at the second step. The kinetic parameters for lithium-zinc ferrite synthesis reaction were found and discussed.

The hydrodeoxygenation of bioderived furans into alkanes.

PubMed

Sutton, Andrew D; Waldie, Fraser D; Wu, Ruilian; Schlaf, Marcel; Silks, Louis A Pete; Gordon, John C

2013-05-01

The conversion of biomass into fuels and chemical feedstocks is one part of a drive to reduce the world's dependence on crude oil. For transportation fuels in particular, wholesale replacement of a fuel is logistically problematic, not least because of the infrastructure that is already in place. Here, we describe the catalytic defunctionalization of a series of biomass-derived molecules to provide linear alkanes suitable for use as transportation fuels. These biomass-derived molecules contain a variety of functional groups, including olefins, furan rings and carbonyl groups. We describe the removal of these in either a stepwise process or a one-pot process using common reagents and catalysts under mild reaction conditions to provide n-alkanes in good yields and with high selectivities. Our general synthetic approach is applicable to a range of precursors with different carbon content (chain length). This allows the selective generation of linear alkanes with carbon chain lengths between eight and sixteen carbons.

The hydrodeoxygenation of bioderived furans into alkanes

NASA Astrophysics Data System (ADS)

Sutton, Andrew D.; Waldie, Fraser D.; Wu, Ruilian; Schlaf, Marcel; ‘Pete' Silks, Louis A.; Gordon, John C.

2013-05-01

The conversion of biomass into fuels and chemical feedstocks is one part of a drive to reduce the world's dependence on crude oil. For transportation fuels in particular, wholesale replacement of a fuel is logistically problematic, not least because of the infrastructure that is already in place. Here, we describe the catalytic defunctionalization of a series of biomass-derived molecules to provide linear alkanes suitable for use as transportation fuels. These biomass-derived molecules contain a variety of functional groups, including olefins, furan rings and carbonyl groups. We describe the removal of these in either a stepwise process or a one-pot process using common reagents and catalysts under mild reaction conditions to provide n-alkanes in good yields and with high selectivities. Our general synthetic approach is applicable to a range of precursors with different carbon content (chain length). This allows the selective generation of linear alkanes with carbon chain lengths between eight and sixteen carbons.

Attitude control/momentum management of the Space Station Freedom for large angle torque-equilibrium-attitude configurations

NASA Technical Reports Server (NTRS)

Parlos, Alexander G.; Sunkel, John W.

1990-01-01

An attitude-control and momentum-management (ACMM) system for the Space Station in a large-angle torque-equilibrium-attitude (TEA) configuration is developed analytically and demonstrated by means of numerical simulations. The equations of motion for a rigid-body Space Station model are outlined; linearized equations for an arbitrary TEA (resulting from misalignment of control and body axes) are derived; the general requirements for an ACMM are summarized; and a pole-placement linear-quadratic regulator solution based on scheduled gains is proposed. Results are presented in graphs for (1) simulations based on configuration MB3 (showing the importance of accounting for the cross-inertia terms in the TEA estimate) and (2) simulations of a stepwise change from configuration MB3 to the 'assembly complete' stage over 130 orbits (indicating that the present ACCM scheme maintains sufficient control over slowly varying Space Station dynamics).

Characterizing multivariate decoding models based on correlated EEG spectral features

PubMed Central

McFarland, Dennis J.

2013-01-01

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

Drunk driving detection based on classification of multivariate time series.

PubMed

Li, Zhenlong; Jin, Xue; Zhao, Xiaohua

2015-09-01

This paper addresses the problem of detecting drunk driving based on classification of multivariate time series. First, driving performance measures were collected from a test in a driving simulator located in the Traffic Research Center, Beijing University of Technology. Lateral position and steering angle were used to detect drunk driving. Second, multivariate time series analysis was performed to extract the features. A piecewise linear representation was used to represent multivariate time series. A bottom-up algorithm was then employed to separate multivariate time series. The slope and time interval of each segment were extracted as the features for classification. Third, a support vector machine classifier was used to classify driver's state into two classes (normal or drunk) according to the extracted features. The proposed approach achieved an accuracy of 80.0%. Drunk driving detection based on the analysis of multivariate time series is feasible and effective. The approach has implications for drunk driving detection. Copyright © 2015 Elsevier Ltd and National Safety Council. All rights reserved.

Effect of agomelatine treatment on C-reactive protein levels in patients with major depressive disorder: an exploratory study in "real-world," everyday clinical practice.

PubMed

De Berardis, Domenico; Fornaro, Michele; Orsolini, Laura; Iasevoli, Felice; Tomasetti, Carmine; de Bartolomeis, Andrea; Serroni, Nicola; De Lauretis, Ida; Girinelli, Gabriella; Mazza, Monica; Valchera, Alessandro; Carano, Alessandro; Vellante, Federica; Matarazzo, Ilaria; Perna, Giampaolo; Martinotti, Giovanni; Di Giannantonio, Massimo

2017-08-01

Agomelatine is a newer antidepressant but, to date, no studies have been carried out investigating its effects on C-reactive protein (CRP) levels in major depressive disorder (MDD) before and after treatment. The present study aimed (i) to investigate the effects of agomelatine treatment on CRP levels in a sample of patients with MDD and (ii) to investigate if CRP variations were correlated with clinical improvement in such patients. 30 adult outpatients (12 males, 18 females) with a Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-TR) diagnosis of MDD were recruited in "real-world," everyday clinical practice and treated with a flexible dose of agomelatine for 12 weeks. The Hamilton Rating Scale for Depression (HAM-D) and the Snaith-Hamilton Pleasure Scale (SHAPS) were used to evaluate depressive symptoms and anhedonia, respectively. Moreover, serum CRP was measured at baseline and after 12 weeks of treatment. Agomelatine was effective in the treatment of MDD, with a significant reduction in HAM-D and SHAPS scores from baseline to endpoint. CRP levels were reduced in the whole sample, with remitters showing a significant difference in CRP levels after 12 weeks of agomelatine. A multivariate stepwise linear regression analysis showed that higher CRP level variation was associated with higher baseline HAM-D scores, controlling for age, gender, smoking, BMI, and agomelatine dose. Agomelatine's antidepressant properties were associated with a reduction in circulating CRP levels in MDD patients who achieved remission after 12 weeks of treatment. Moreover, more prominent CRP level variation was associated with more severe depressive symptoms at baseline.

S175. AMOTIVATION IS ASSOCIATED WITH SMALLER VENTRAL STRIATUM VOLUMES IN OLDER PATIENTS WITH SCHIZOPHRENIA

PubMed Central

Caravaggio, Fernando; Fervaha, Gagan; Iwata, Yusuke; Plitman, Eric; Chung, Jun Ku; Nakajima, Shinichiro; Mar, Wanna; Gerretsen, Philip; Kim, Julia; Chakravarty, Mallar; Mulsant, Benoit; Pollock, Bruce; Mamo, David; Remington, Gary; Graff-Guerrero, Ariel

2018-01-01

Abstract Background Motivational deficits are prevalent in patients with schizophrenia, persist despite antipsychotic treatment, and predict long‐term outcomes. Evidence suggests that patients with greater amotivation have smaller ventral striatum (VS) volumes. We wished to replicate this finding in a sample of older, chronically medicated patients with schizophrenia. Using structural imaging and positron emission tomography, we examined whether amotivation uniquely predicted VS volumes beyond the effects of striatal dopamine D2/3 receptor (D2/3R) blockade by antipsychotics. Methods Data from 41 older schizophrenia patients (mean age: 60.2 ± 6.7; 11 female) were reanalysed from previously published imaging data. We constructed multivariate linear stepwise regression models with VS volumes as the dependent variable and various sociodemographic and clinical variables as the initial predictors: age, gender, total brain volume, and antipsychotic striatal D2/3R occupancy. Amotivation was included as a subsequent step to determine any unique relationships with VS volumes beyond the contribution of the covariates. In a reduced sample (n = 36), general cognition was also included as a covariate. Results Amotivation uniquely explained 8% and 6% of the variance in right and left VS volumes, respectively (right: β = -.38, t = -2.48, P = .01; left: β = -.31, t = -2.17, P = .03). Considering cognition, amotivation levels uniquely explained 9% of the variance in right VS volumes (β = -.43, t = -0.26, P = .03). Discussion We replicate and extend the finding of reduced VS volumes with greater amotivation. We demonstrate this relationship uniquely beyond the potential contributions of striatal D2/3R blockade by antipsychotics. Elucidating the structural correlates of amotivation in schizophrenia may help develop treatments for this presently irremediable deficit.

Preoperative Thromboelastometry as a Predictor of Transfusion Requirements during Adult Living Donor Liver Transplantation.

PubMed

Fayed, Nirmeen; Mourad, Wessam; Yassen, Khaled; Görlinger, Klaus

2015-03-01

The ability to predict transfusion requirements may improve perioperative bleeding management as an integral part of a patient blood management program. Therefore, the aim of our study was to evaluate preoperative thromboelastometry as a predictor of transfusion requirements for adult living donor liver transplant recipients. The correlation between preoperative thromboelastometry variables in 100 adult living donor liver transplant recipients and intraoperative blood transfusion requirements was examined by univariate and multivariate linear regression analysis. Thresholds of thromboelastometric parameters for prediction of packed red blood cells (PRBCs), fresh frozen plasma (FFP), platelets, and cryoprecipitate transfusion requirements were determined with receiver operating characteristics analysis. The attending anesthetists were blinded to the preoperative thromboelastometric analysis. However, a thromboelastometry-guided transfusion algorithm with predefined trigger values was used intraoperatively. The transfusion triggers in this algorithm did not change during the study period. Univariate analysis confirmed significant correlations between PRBCs, FFP, platelets or cryoprecipitate transfusion requirements and most thromboelastometric variables. Backward stepwise logistic regression indicated that EXTEM coagulation time (CT), maximum clot firmness (MCF) and INTEM CT, clot formation time (CFT) and MCF are independent predictors for PRBC transfusion. EXTEM CT, CFT and FIBTEM MCF are independent predictors for FFP transfusion. Only EXTEM and INTEM MCF were independent predictors of platelet transfusion. EXTEM CFT and MCF, INTEM CT, CFT and MCF as well as FIBTEM MCF are independent predictors for cryoprecipitate transfusion. Thromboelastometry-based regression equation accounted for 63% of PRBC, 83% of FFP, 61% of cryoprecipitate, and 44% of platelet transfusion requirements. Preoperative thromboelastometric analysis is helpful to predict transfusion requirements in adult living donor liver transplant recipients. This may allow for better preparation and less cross-matching prior to surgery. The findings of our study need to be re-validated in a second prospective patient population.

The relationship between environmental exposure to cadmium and lead and blood selenium concentration in randomly selected population of children inhabiting industrial regions of Silesian Voivodship (Poland).

PubMed

Gać, P; Pawlas, N; Poręba, R; Poręba, M; Pawlas, K

2014-06-01

This study aimed at determining the relationship between environmental exposure to lead (Pb) and cadmium (Cd) and blood selenium (Se) concentration in randomly selected population of children inhabiting the industrial regions of Silesian Voivodship, Poland. The study was conducted on a group of consecutive randomly selected 349 children aged below 15 years and inhabiting the industrial regions in Upper Silesia. The examined variables included whole blood Cd concentration (Cd-B), whole blood Pb concentration (Pb-B) and whole blood Se concentration (Se-B). The concentration of Cd-B, Pb-B and Se-B in the studied group of children amounted to 0.26 ± 0.14, 37.62 ± 25.30 and 78.31 ± 12.82 μg/L, respectively. In the entire examined group a statistically significant negative linear relationship was noted between Pb-B and Se-B (r = -0.12, p < 0.05). Also, a statistically insignificant negative correlation was detected between Cd-B and Se-B (r = -0.02, p > 0.05) and a statistically insignificant positive correlation between Pb-B and Cd-B (r = 0.08, p > 0.05). A multivariate backward stepwise regression analysis demonstrated that in the studied group of children higher Pb-B and a more advanced age-represented independent risk factors for a decreased Se-B. Environmental exposure to Pb may represent an independent risk factor for Se deficit in blood of the studied population of children. In children, the lowered Se-B may create one of the mechanisms in which Pb unfavourably affects human body. © The Author(s) 2014.

Activity Profile and Energy Expenditure Among Active Older Adults, British Columbia, 2011-2012.

PubMed

Madden, Kenneth M; Ashe, Maureen C; Chase, Jocelyn M

2015-07-16

Time spent by young adults in moderate to vigorous activity predicts daily caloric expenditure. In contrast, caloric expenditure among older adults is best predicted by time spent in light activity. We examined highly active older adults to examine the biggest contributors to energy expenditure in this population. Fifty-four community-dwelling men and women aged 65 years or older (mean, 71.4 y) were enrolled in this cross-sectional observational study. All were members of the Whistler Senior Ski Team, and all met current American guidelines for physical activity. Activity levels (sedentary, light, and moderate to vigorous) were recorded by accelerometers worn continuously for 7 days. Caloric expenditure was measured using accelerometry, galvanic skin response, skin temperature, and heat flux. Significant variables were entered into a stepwise multivariate linear model consisting of activity level, age, and sex. The average (standard deviation [SD]) daily nonlying sedentary time was 564 (92) minutes (9.4 [1.5] h) per day. The main predictors of higher caloric expenditure were time spent in moderate to vigorous activity (standardized β = 0.42 [SE, 0.08]; P < .001) and male sex (standardized β = 1.34 [SE, 0.16]; P < .001). A model consisting of only moderate to vigorous physical activity and sex explained 68% of the variation in caloric expenditure. An increase in moderate to vigorous physical activity by 1 minute per day was associated with an additional 16 kcal expended in physical activity. The relationship between activity intensity and caloric expenditure in athletic seniors is similar to that observed in young adults. Active older adults still spend a substantial proportion of the day engaged in sedentary behaviors.

Maternal and Cord Blood Adiponectin Multimeric Forms in Gestational Diabetes Mellitus

PubMed Central

Ballesteros, Mónica; Simón, Inmaculada; Vendrell, Joan; Ceperuelo-Mallafré, Victoria; Miralles, Ramon M.; Albaiges, Gerard; Tinahones, Francisco; Megia, Ana

2011-01-01

OBJECTIVE To analyze the relationship between maternal adiponectin (mAdiponectin) and cord blood adiponectin (cbAdiponectin) multimeric forms (high molecular weight [HMW], medium molecular weight [MMW], and low molecular weight [LMW]) in a cohort of gestational diabetes mellitus (GDM) and normal glucose–tolerant (NGT) pregnant women. RESEARCH DESIGN AND METHODS A total of 212 women with a singleton pregnancy, 132 with NGT and 80 with GDM, and their offspring were studied. Maternal blood was obtained in the early third trimester and cord blood was obtained at delivery. Total adiponectin and the multimeric forms of adiponectin were determined in cord blood and maternal serum. Spearman rank correlation and stepwise linear correlation analysis were used to assess the relationship between cbAdiponectin levels and clinical and analytical parameters. RESULTS No differences in cbAdiponectin concentration or its multimeric forms were observed in the offspring of diabetic mothers compared with NGT mothers. The HMW-to-total adiponectin ratio was higher in cord blood than in maternal serum, whereas the MMW- and LMW-to-total adiponectin ratio was lower. Cord blood total and HMW adiponectin levels were positively correlated with birth weight and the ponderal index (PI), whereas cord blood MMW adiponectin was negatively correlated with the PI. In addition, cbAdiponectin and its multimeric forms were correlated with mAdiponectin concentrations. In the multivariate analysis, maternal multimeric forms of adiponectin emerged as independent predictors of cbAdiponectin, its multimers, and their distribution. CONCLUSIONS cbAdiponectin concentrations are independently related to mAdiponectin levels and unrelated to the diagnosis of GDM. Maternal multimeric forms of adiponectin are independent predictors of the concentrations of cbAdiponectin and its multimeric forms at delivery. PMID:21911780

Effects of gaps in priorities between ideal and real lives on psychological burnout among academic faculty members at a medical university in Japan: a cross-sectional study.

PubMed

Chatani, Yuki; Nomura, Kyoko; Horie, Saki; Takemoto, Keisuke; Takeuchi, Masumi; Sasamori, Yukifumi; Takenoshita, Shinichi; Murakami, Aya; Hiraike, Haruko; Okinaga, Hiroko; Smith, Derek

2017-04-04

Accumulating evidence from medical workforce research indicates that poor work/life balance and increased work/home conflict induce psychological distress. In this study we aim to examine the existence of a priority gap between ideal and real lives, and its association with psychological burnout among academic professionals. This cross-sectional survey, conducted in 2014, included faculty members (228 men, 102 women) at a single medical university in Tokyo, Japan. The outcome of interest was psychological burnout, measured with a validated inventory. Discordance between ideal- and real-life priorities, based on participants' responses (work, family, individual life, combinations thereof), was defined as a priority gap. The majority (64%) of participants chose "work" as the greatest priority in real life, but only 28% chose "work" as the greatest priority in their conception of an ideal life. Priority gaps were identified in 59.5% of respondents. A stepwise multivariable general linear model demonstrated that burnout scores were associated positively with respondents' current position (P < 0.0018) and the presence of a priority gap (P < 0.0001), and negatively with the presence of social support (P < 0.0001). Among participants reporting priority gaps, burnout scores were significantly lower in those with children than in those with no children (P interaction  = 0.011); no such trend was observed in participants with no priority gap. A gap in priorities between an ideal and real life was associated with an increased risk of burnout, and the presence of children, which is a type of "family" social support, had a mitigating effect on burnout among those reporting priority gaps.

Faculty motivations to use active learning among pharmacy educators.

PubMed

Rockich-Winston, Nicole; Train, Brian C; Rudolph, Michael J; Gillette, Chris

2018-03-01

Faculty motivations to use active learning have been limited to surveys evaluating faculty perceptions within active learning studies. Our objective in this study was to evaluate the relationship between faculty intrinsic motivation, extrinsic motivation, and demographic variables and the extent of active learning use in the classroom. An online survey was administered to individual faculty members at 137 colleges and schools of pharmacy across the United States. The survey assessed intrinsic and extrinsic motivations, active learning strategies, classroom time dedicated to active learning, and faculty development resources. Bivariate associations and multivariable stepwise linear regression were used to analyze the results. In total, 979 faculty members completed the questionnaire (23.6% response rate). All motivation variables were significantly correlated with percent active learning use (p < 0.001). Intrinsic motivation demonstrated the highest correlation (r = 0.447) followed by current extrinsic motivations (r = 0.245) and ideal extrinsic motivations (r = 0.291). Variables associated with higher intrinsic motivation included the number of resources used (r = 0.233, p < 0.001) and the number of active learning methods used in the last year (r = 0.259, p < 0.001). Years of teaching experience was negatively associated with intrinsic motivation (r = -0.177, p < 0.001). Regression analyses confirmed the importance of intrinsic and extrinsic motivations in predicting active learning use. Our results suggest that faculty members who are intrinsically motivated to use active learning are more likely to dedicate additional class time to active learning. Furthermore, intrinsic motivation may be positively associated with encouraging faculty members to attend active learning workshops and supporting faculty to use various active learning strategies in the classroom. Copyright © 2017 Elsevier Inc. All rights reserved.

Population pharmacokinetic study of isepamicin with intensive care unit patients.

PubMed Central

Tod, M; Padoin, C; Minozzi, C; Cougnard, J; Petitjean, O

1996-01-01

The pharmacokinetics (PK) of isepamicin, a new aminoglycoside, were studied in 85 intensive care unit (ICU) patients and were compared with those observed in 10 healthy volunteers. A parametric method based on a nonlinear mixed-effect model was used to assess population PK. Isepamicin was given intravenously over 0.5 h at dosages of 15 mg/kg once daily or 7.5 mg/kg twice daily. The data were fitted to a bicompartmental open model. Compared with healthy volunteers, the mean values of the PK parameters were profoundly modified in ICU patients: elimination clearance was reduced by 48%, the volume of distribution in the central compartment (Vc) was increased by 50%, the peripheral volume of distribution was 70% higher, the distribution clearance was 146% lower, and the elimination half-life was ca. 3.4 times higher. The interindividual variability in PK parameters was about 50% in ICU patients. Five covariates (body weight [BW], simplified acute physiology score [SAPS], temperature, serum creatinine level, and creatinine clearance [CLCR]) were tentatively correlated with PK parameters by multivariate linear regression analysis with stepwise addition and deletion. The variability of isepamicin clearance was explained by three covariates (BW, SAPS, and CLCR), that of Vc was explained by BW and SAPS, and that of the elimination half-life was explained by CLCR and SAPS. Simulation of the concentration-versus-time profile for 500 individuals showed that the mean peak (0.75 h) concentration was 18% lower in ICU patients than in healthy volunteers and that the range in ICU patients was very broad (28.4 to 95.4 mg/liter). Therefore, monitoring of the isepamicin concentration is in ICU patients is mandatory. PMID:8849264

Baseline triglyceride levels and insulin sensitivity are major determinants of the increase of LDL particle size and buoyancy induced by rosuvastatin treatment in patients with primary hyperlipidemia.

PubMed

Kostapanos, Michael S; Milionis, Haralampos J; Lagos, Konstantinos G; Rizos, Christos B; Tselepis, Alexandros D; Elisaf, Moses S

2008-08-20

The influence of various statins on low-density-lipoprotein (LDL)-particle phenotype has been reportedly trivial or moderate. We assessed the effect of rosuvastatin (the newest statin available) on the LDL subfraction profile in patients with primary hyperlipidemia. One hundred and twenty patients with primary hyperlipidemia without evidence of cardiovascular disease were randomized to therapeutic lifestyle modification ('control' group, N=60) or therapeutic lifestyle modification plus rosuvastatin 20 mg/day (N=60). Laboratory evaluation was performed at baseline and 12 weeks post-treatment. LDL subfraction analysis was carried out electrophoretically using of high-resolution 3% polyacrylamide gel tubes and the Lipoprint LDL System. Rosuvastatin induced a redistribution of LDL-cholesterol from small-dense LDL particles to large-buoyant ones and increased the mean LDL particle size. This beneficial effect was observed only in patients with baseline triglyceride levels >or=150 mg/dl (mean LDL particle size 255+/-7 A vs 260+/-5 A, P<0.01), whereas the LDL subfraction profile was not altered in those with triglyceride levels <150 mg/dl. Stepwise multivariate linear regression analysis revealed that baseline triglyceride levels (R(2)=0.29, P=0.001) followed by baseline insulin resistance as assessed by the HOmeostasis Model Assessment (HOMA) (R(2)=0.25, P=0.001) were independently associated with the rosuvastatin-induced increase in the mean LDL particle size. In conclusion, rosuvastatin at 20 mg/day favorably modified the relative distribution of LDL-cholesterol distribution on LDL subfractions as well as on the mean LDL particle size in patients treated for primary dyslipidemia. Baseline triglyceride levels as well as baseline HOMA-index were found to be the major predictors of this beneficial action of rosuvastatin.

Subclinical changes in MRI-determined right ventricular volumes and function in subjects with prediabetes and diabetes.

PubMed

Patscheider, Hannah; Lorbeer, Roberto; Auweter, Sigrid; Schafnitzel, Anina; Bayerl, Christian; Curta, Adrian; Rathmann, Wolfgang; Heier, Margit; Meisinger, Christa; Peters, Annette; Bamberg, Fabian; Hetterich, Holger

2018-07-01

The aim of this study was to assess subclinical changes in right ventricular volumes and function in subjects with prediabetes and diabetes and controls without a history of cardiovascular disease. Data from 400 participants in the KORA FF4 study without self-reported cardiovascular disease who underwent 3-T whole-body MRI were obtained. The right ventricle was evaluated using the short axis and a four-chamber view. Diabetes was defined according to WHO criteria. Associations between glucose tolerance and right ventricular parameters were assessed using multivariable adjusted linear regression models. Data from 337 participants were available for analysis. Of these, 43 (13%) had diabetes, 87 (26%) had prediabetes, and 207 (61%) were normoglycaemic controls. There was a stepwise decrease in right ventricular volumes in men with prediabetes and diabetes in comparison with controls, including right ventricular end-diastolic volume (β = -20.4 and β = -25.6, respectively; p ≤ 0.005), right ventricular end-systolic volume (β = -12.3 and β = -12.7, respectively; p ≤ 0.037) and right ventricular stroke volume (β = -8.1 and β = -13.1, respectively, p ≤ 0.016). We did not observe any association between prediabetes or diabetes and right ventricular volumes in women or between prediabetes or diabetes and right ventricular ejection fraction in men and women. This study points towards early subclinical changes in right ventricular volumes in men with diabetes and prediabetes. • MRI was used to detect subclinical changes in right ventricular parameters. • Diabetes mellitus is associated with right ventricular dysfunction. • Impairment of right ventricular volumes seems to occur predominantly in men.

Development of a prediction model for child maltreatment recurrence in Japan: A historical cohort study using data from a Child Guidance Center.

PubMed

Horikawa, Hiroyuki; Suguimoto, S Pilar; Musumari, Patou Masika; Techasrivichien, Teeranee; Ono-Kihara, Masako; Kihara, Masahiro

2016-09-01

To develop a prediction model for the first recurrence of child maltreatment within the first year after the initial report, we carried out a historical cohort study using administrative data from 716 incident cases of child maltreatment (physical abuse, psychological abuse, or neglect) not receiving support services, reported between April 1, 1996 through March 31, 2011 to Shiga Central Child Guidance Center, Japan. In total, 23 items related to characteristics of the child, the maltreatment, the offender, household, and other related factors were selected as predictive variables and analyzed by multivariate logistic regression model for association with first recurrence of maltreatment. According to the stepwise selection procedure six factors were identified that include 9-13year age of child (AOR=3.43/95%CI=1.52-7.72), <40year age of the offender (AOR=1.65/95%CI=1.09-2.51), offender's history of maltreatment during childhood (AOR=2.56/95%CI=1.31-4.99), household financial instability or poverty (AOR=1.64/95%CI=1.10-2.45), absence of someone in the community who could watch over the child (AOR=1.68/95%CI=1.16-2.44), and the organization as the referral source (AOR=2.21/95%CI=1.24-3.93). Using these six predictors, we generated a linear prediction model with a sensitivity and specificity of 45.2% and 82.4%, respectively. The model may be useful to assess the risk of further maltreatment and help the child and family welfare administrations to develop preventive strategies for recurrence. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Puberty timing and fluid intelligence: a study of correlations between testosterone and intelligence in 8- to 12-year-old Chinese boys.

PubMed

Shangguan, Fangfang; Shi, Jiannong

2009-08-01

Sex hormone such as testosterone was recently recognized as an important contributor of spatial cognition and intelligence during development, but the relationship between puberty timing and intelligence especially in children is largely unknown. Here in this study, we investigated the potential relationship between the level of sex hormones in saliva and fluid intelligence in 8- to 12-year-old Chinese boys. Fluid intelligence was measured by the Cattell's Culture Fair Intelligence Test. 1600 children aged 8-12 years were included in the Cattell's Culture Fair Intelligence Test and saliva samples were collected thereafter from 166 boys with normal intelligence distribution, composed of 49, 54 and 63 boys in 8-, 10- and 12-year-old group respectively. The level of salivary testosterone and estradiol was measured with enzyme-immunoassay technique. Data of BMI and age were collected. The relationship between the level of salivary sex hormones and fluid intelligence was analysed by correlation test. There was no significant correlation between salivary testosterone level and fluid intelligence in 8-year-old boys, whereas there was a significant positive correlation in 10-year-old boys and a significant negative correlation in 12-year-old boys between those two variable. To verify the correlation, we performed stepwise multivariate linear regression and discriminant analysis, with both the age and BMI of the boys and their parents, and salivary estradiol level considered. The results showed that the level of testosterone and intelligence was correlated, and the correlation was much stronger when the level of salivary testosterone was higher than 14 pg/ml. In summary, the study suggests that the relationship of testosterone and intelligence varies from late childhood to early adolescence, and the puberty timing is closely related with fluid intelligence.

Risk of Hospitalization Due to Unintentional Fall Injury in British Columbia, Canada, 1999-2008: Ecological Associations with Socioeconomic Status, Geographic Place, and Aboriginal Ethnicity.

PubMed

Jin, Andrew; Brussoni, Mariana; George, M Anne; Lalonde, Christopher E; McCormick, Rod

2017-08-01

Aboriginal people in British Columbia (BC), especially those residing on Indian reserves, have higher risk of unintentional fall injury than the general population. We test the hypothesis that the disparities are attributable to a combination of socioeconomic status, geographic place, and Aboriginal ethnicity. Within each of 16 Health Service Delivery Areas in BC, we identified three population groups: total population, Aboriginal off-reserve, and Aboriginal on-reserve. We calculated age and gender-standardized relative risks (SRR) of hospitalization due to unintentional fall injury (relative to the total population of BC), during time periods 1999-2003 and 2004-2008, and we obtained custom data from the 2001 and 2006 censuses (long form), describing income, education, employment, housing, proportions of urban and rural dwellers, and prevalence of Aboriginal ethnicity. We studied association of census characteristics with SRR of fall injury, by multivariable linear regression. The best-fitting model was an excellent fit (R 2  = 0.854, p < 0.001) and predicted SRRs very close to observed values for the total, Aboriginal off-reserve, and Aboriginal on-reserve populations of BC. After stepwise regression, the following terms remained: population per room, urban residence, labor force participation, income per capita, and multiplicative interactions of Aboriginal ethnicity with population per room and labor force participation. The disparities are predictable by the hypothesized risk markers. Aboriginal ethnicity is not an independent risk marker: it modifies the effects of socioeconomic factors. Closing the gap in fall injury risk between the general and Aboriginal populations is likely achievable by closing the gaps in socioeconomic conditions.

Mapping CHU9D Utility Scores from the PedsQLTM 4.0 SF-15.

PubMed

Mpundu-Kaambwa, Christine; Chen, Gang; Russo, Remo; Stevens, Katherine; Petersen, Karin Dam; Ratcliffe, Julie

2017-04-01

The Pediatric Quality of Life Inventory™ 4.0 Short Form 15 Generic Core Scales (hereafter the PedsQL) and the Child Health Utility-9 Dimensions (CHU9D) are two generic instruments designed to measure health-related quality of life in children and adolescents in the general population and paediatric patient groups living with specific health conditions. Although the PedsQL is widely used among paediatric patient populations, presently it is not possible to directly use the scores from the instrument to calculate quality-adjusted life-years (QALYs) for application in economic evaluation because it produces summary scores which are not preference-based. This paper examines different econometric mapping techniques for estimating CHU9D utility scores from the PedsQL for the purpose of calculating QALYs for cost-utility analysis. The PedsQL and the CHU9D were completed by a community sample of 755 Australian adolescents aged 15-17 years. Seven regression models were estimated: ordinary least squares estimator, generalised linear model, robust MM estimator, multivariate factorial polynomial estimator, beta-binomial estimator, finite mixture model and multinomial logistic model. The mean absolute error (MAE) and the mean squared error (MSE) were used to assess predictive ability of the models. The MM estimator with stepwise-selected PedsQL dimension scores as explanatory variables had the best predictive accuracy using MAE and the equivalent beta-binomial model had the best predictive accuracy using MSE. Our mapping algorithm facilitates the estimation of health-state utilities for use within economic evaluations where only PedsQL data is available and is suitable for use in community-based adolescents aged 15-17 years. Applicability of the algorithm in younger populations should be assessed in further research.

The development and validation of new equations for estimating body fat percentage among Chinese men and women.

PubMed

Liu, Xin; Sun, Qi; Sun, Liang; Zong, Geng; Lu, Ling; Liu, Gang; Rosner, Bernard; Ye, Xingwang; Li, Huaixing; Lin, Xu

2015-05-14

Equations based on simple anthropometric measurements to predict body fat percentage (BF%) are lacking in Chinese population with increasing prevalence of obesity and related abnormalities. We aimed to develop and validate BF% equations in two independent population-based samples of Chinese men and women. The equations were developed among 960 Chinese Hans living in Shanghai (age 46.2 (SD 5.3) years; 36.7% male) using a stepwise linear regression and were subsequently validated in 1150 Shanghai residents (58.7 (SD 6.0) years; 41.7% male; 99% Chinese Hans, 1% Chinese minorities). The associations of equation-derived BF% with changes of 6-year cardiometabolic outcomes and incident type 2 diabetes (T2D) were evaluated in a sub-cohort of 780 Chinese, compared with BF% measured by dual-energy X-ray absorptiometry (DXA; BF%-DXA). Sex-specific equations were established with age, BMI and waist circumference as independent variables. The BF% calculated using new sex-specific equations (BF%-CSS) were in reasonable agreement with BF%-DXA (mean difference: 0.08 (2 SD 6.64) %, P= 0.606 in men; 0.45 (2 SD 6.88) %, P< 0.001 in women). In multivariate-adjusted models, the BF%-CSS and BF%-DXA showed comparable associations with 6-year changes in TAG, HDL-cholesterol, diastolic blood pressure, C-reactive protein and uric acid (P for comparisons ≥ 0.05). Meanwhile, the BF%-CSS and BF%-DXA had comparable areas under the receiver operating characteristic curves for associations with incident T2D (men P= 0.327; women P= 0.159). The BF% equations might be used as surrogates for DXA to estimate BF% among adult Chinese. More studies are needed to evaluate the application of our equations in different populations.

[Development of the Spanish brief-version of the University of California Performance Skills Assessment (Sp-UPSA-Brief) in patients with schizophrenia and bipolar disorder].

PubMed

Garcia-Portilla, María Paz; Gomar, Jesús; Bobes-Bascaran, María Teresa; Menendez-Miranda, Isabel; Saiz, Pilar Alejandra; Muñiz, José; Arango, Celso; Patterson, Thomas; Harvey, Philip; Bobes, Julio; Goldberg, Terry

2014-01-01

In patients with severe mental disorders outcome measurement should include symptoms, cognition, functioning and quality of life at least. Shorter and efficient instruments have greater potential for pragmatic and valid clinical utility. Our aim was to develop the Spanish UPSA Brief scale (Sp-UPSA-Brief). Naturalistic, 6-month follow-up, multicentre study. 139 patients with schizophrenia, 57 with bipolar disorder and 31 controls were evaluated using the Sp-UPSA, CGI-S, GAF, and PSP. We conducted a multivariate linear regression model to identify candidate subscales for the Sp-UPSA-Brief. The stepwise regression model for patients with schizophrenia showed that communication and transportation Sp-UPSA subscales entered first and second at p<0.0001 (R(2)=0.88, model df=2, F=395.05). In patients with bipolar disorder transportation and communication Sp-UPSA subscales entered first and second at p<0.0001 (R(2)=0.87, model df=2, F=132.32). Cronbach's alpha was 0.78 in schizophrenia and 0.64 in bipolar patients. Test-retest was 0.66 and 0.64 (p<0.0001) respectively. Pearson correlation coefficients between Sp-UPSA and Sp-UPSA-Brief were 0.93 for schizophrenia and 0.92 for bipolar patients (p<0.0001).The Sp-UPSA-Brief discriminated between patients and controls. In schizophrenia patients it also discriminated among different levels of illness severity according to CGI-S scores. The Sp-UPSA-Brief is an alternate instrument to evaluate functional capacity that is valid and reliable. Having a shorter instrument makes it more feasible to assess functional capacity in patients with severe mental disorders, especially in everyday clinical practice. Copyright © 2013 SEP y SEPB. Published by Elsevier España. All rights reserved.

Factors Affecting Sexual Function in Midlife Women: Results from the Midlife Women's Health Study.

PubMed

Smith, Rebecca L; Gallicchio, Lisa; Flaws, Jodi A

2017-09-01

The objective of this study was to estimate the importance of risk factors affecting sexual function in sexually active midlife women. A cohort of 780 women undergoing the menopausal transition was surveyed each year for up to 7 years. Data were collected from sexually active women on sexual function, including frequencies of enjoyment, arousal, orgasm, passion for partner, satisfaction with partner, pain, lack of lubrication, fantasizing, and sexual activity. Data were also collected on a large number of potential risk factors for sexual dysfunction, including behaviors (smoking and alcohol use), health status (overall and frequency of different disorders), and demographic information (race, education, income, etc.). Height and weight were measured at an annual clinic visit; serum hormone concentrations were assayed using blood samples donated annually. Data on individual outcomes were examined with ordinal logistic regression models using individual as a random effect. An overall sexual function score was constructed from individual outcome responses, and this score was examined with linear regression. All factors with univariate associations of p < 0.1 were considered in multivariate model building with stepwise addition. A total of 1,927 women-years were included in the analysis. Women with much more physical work than average had higher sexual function scores and higher rates of enjoyment, passion, and satisfaction. Higher family income was associated with lower sexual function score and more frequent dry sex. Married women had significantly lower sexual function scores, as did those with frequent irritability or vaginal dryness. A higher step on the Ladder of Life was associated with a higher sexual function score and higher frequency of sexual activity. The factors associated with sexual outcome in menopausal women are complex and vary depending on the sexual outcome.

Ethnic differences in cognitive development in the first 7 years: does maternal generational status matter?

PubMed

Smith, Neil R; Kelly, Yvonne J; Nazroo, James Y

2016-05-01

Differences in cognitive development have been observed across a variety of ethnic minority groups but relatively little is known about the persistence of these developmental inequalities over time or generations. A repeat cross-sectional analysis assessed cognitive ability scores of children aged 3, 5 and 7 years from the longitudinal UK Millennium Cohort Study (white UK born n=7630; Indian n=248; Pakistani n=328; Bangladeshi n=87; black Caribbean n=172; and black African n=136). Linear regression estimated ethnic differences in age normed scores at each time point. Multivariable logistic regression estimated within-group generational differences in test scores at each age adjusting stepwise for sociodemographic factors, maternal health behaviours, indicators of the home learning environment and parenting styles. The majority of ethnic minority groups scored lower than the white UK born reference group at 3 years with these differences narrowing incrementally at ages 5 and 7 years. However, the black Caribbean group scored significantly lower than the white UK born reference group throughout early childhood. At 3 years, Pakistani, black Caribbean and black African children with UK born mothers had significantly higher test scores than those with foreign born mothers after baseline adjustment for maternal age and child gender. Controlling for social, behavioural and parenting factors attenuated this generational advantage. By 7 years there were no significant generational differences in baseline models. Ethnic differences in cognitive development diminish throughout childhood for the majority of groups. Cumulative exposure to the UK environment may be associated with higher cognitive development scores. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Predictors for total medical costs for acute hemorrhagic stroke patients transferred to the rehabilitation ward at a regional hospital in Taiwan.

PubMed

Chen, Chien-Min; Ke, Yen-Liang

2016-02-01

One-third of the acute stroke patients in Taiwan receive rehabilitation. It is imperative for clinicians who care for acute stroke patients undergoing inpatient rehabilitation to identify which medical factors could be the predictors of the total medical costs. The aim of this study was to identify the most important predictors of the total medical costs for first-time hemorrhagic stroke patients transferred to inpatient rehabilitation using a retrospective design. All data were retrospectively collected from July 2002 to June 2012 from a regional hospital in Taiwan. A stepwise multivariate linear regression analysis was used to identify the most important predictors for the total medical costs. The medical records of 237 patients (137 males and 100 females) were reviewed. The mean total medical cost per patient was United States dollar (USD) 5939.5 ± 3578.5.The following were the significant predictors for the total medical costs: impaired consciousness [coefficient (B), 1075.7; 95% confidence interval (CI) = 138.5-2012.9], dysphagia [coefficient (B), 1025.8; 95% CI = 193.9-1857.8], number of surgeries [coefficient (B), 796.4; 95% CI = 316.0-1276.7], pneumonia in the neurosurgery ward [coefficient (B), 2330.1; 95% CI = 1339.5-3320.7], symptomatic urinary tract infection (UTI) in the rehabilitation ward [coefficient (B), 1138.7; 95% CI = 221.6-2055.7], and rehabilitation ward stay [coefficient (B), 64.9; 95% CI = 31.2-98.7] (R(2) = 0.387). Our findings could help clinicians to understand that cost reduction may be achieved by minimizing complications (pneumonia and UTI) in these patients.

Assessing the socio-economic and demographic impact on health-related quality of life: evidence from Greece.

PubMed

Pappa, Evelina; Kontodimopoulos, Nick; Papadopoulos, Angelos A; Niakas, Dimitris

2009-01-01

The impact of socioeconomic status on health has been extensively studied and studies have shown that low socio-economic status is related to lower values of various health and quality-of-health measures. The aim of this study was to assess the influence of demographic and socio-economic factors on health- related quality of life (HRQoL). A cross-sectional study was carried out in 2003 using a representative sample of a Greek general population (n = 1007, 18+ years old), living in Athens area. Multivariate stepwise linear regression analyses were performed to investigate the influence of socio-demographic and economic variables on HRQoL, measured by eight scales of the SF-36. Interaction effects between socioeconomic status (SES) and demographic variables were also performed. Females and elderly people were associated with impaired HRQoL in all SF-36 scales. Disadvantaged SES i. e. primary education and low total household income was related to important decline in HRQoL and a similar relation was identified among men and women. Only the interaction effects between age and SES was statistically significant for some SF-36 scales. Multiple regression analyses produced models explaining significant portions of the variance in SF-36 scales, especially physical functioning. The analysis presented here gives evidence of a relationship existing between SES and HRQoL similar to what has been found elsewhere. In order to protect people from the damaging effects of poverty in health it is important to formulate health promotion educational programs or to direct policies to empower the disposable income etc. Helping people in disadvantaged SES to achieve the good health that people in more advantaged SES attained would help to prevent the widening of health inequalities.

Activity Profile and Energy Expenditure Among Active Older Adults, British Columbia, 2011–2012

PubMed Central

Ashe, Maureen C.; Chase, Jocelyn M.

2015-01-01

Introduction Time spent by young adults in moderate to vigorous activity predicts daily caloric expenditure. In contrast, caloric expenditure among older adults is best predicted by time spent in light activity. We examined highly active older adults to examine the biggest contributors to energy expenditure in this population. Methods Fifty-four community-dwelling men and women aged 65 years or older (mean, 71.4 y) were enrolled in this cross-sectional observational study. All were members of the Whistler Senior Ski Team, and all met current American guidelines for physical activity. Activity levels (sedentary, light, and moderate to vigorous) were recorded by accelerometers worn continuously for 7 days. Caloric expenditure was measured using accelerometry, galvanic skin response, skin temperature, and heat flux. Significant variables were entered into a stepwise multivariate linear model consisting of activity level, age, and sex. Results The average (standard deviation [SD]) daily nonlying sedentary time was 564 (92) minutes (9.4 [1.5] h) per day. The main predictors of higher caloric expenditure were time spent in moderate to vigorous activity (standardized β = 0.42 [SE, 0.08]; P < .001) and male sex (standardized β = 1.34 [SE, 0.16]; P < .001). A model consisting of only moderate to vigorous physical activity and sex explained 68% of the variation in caloric expenditure. An increase in moderate to vigorous physical activity by 1 minute per day was associated with an additional 16 kcal expended in physical activity. Conclusion The relationship between activity intensity and caloric expenditure in athletic seniors is similar to that observed in young adults. Active older adults still spend a substantial proportion of the day engaged in sedentary behaviors. PMID:26182147

Deficits in vision and visual attention associated with motor performance of very preterm/very low birth weight children.

PubMed

Geldof, Christiaan J A; van Hus, Janeline W P; Jeukens-Visser, Martine; Nollet, Frans; Kok, Joke H; Oosterlaan, Jaap; van Wassenaer-Leemhuis, Aleid G

2016-01-01

To extend understanding of impaired motor functioning of very preterm (VP)/very low birth weight (VLBW) children by investigating its relationship with visual attention, visual and visual-motor functioning. Motor functioning (Movement Assessment Battery for Children, MABC-2; Manual Dexterity, Aiming & Catching, and Balance component), as well as visual attention (attention network and visual search tests), vision (oculomotor, visual sensory and perceptive functioning), visual-motor integration (Beery Visual Motor Integration), and neurological status (Touwen examination) were comprehensively assessed in a sample of 106 5.5-year-old VP/VLBW children. Stepwise linear regression analyses were conducted to investigate multivariate associations between deficits in visual attention, oculomotor, visual sensory, perceptive and visual-motor integration functioning, abnormal neurological status, neonatal risk factors, and MABC-2 scores. Abnormal MABC-2 Total or component scores occurred in 23-36% of VP/VLBW children. Visual and visual-motor functioning accounted for 9-11% of variance in MABC-2 Total, Manual Dexterity and Balance scores. Visual perceptive deficits only were associated with Aiming & Catching. Abnormal neurological status accounted for an additional 19-30% of variance in MABC-2 Total, Manual Dexterity and Balance scores, and 5% of variance in Aiming & Catching, and neonatal risk factors for 3-6% of variance in MABC-2 Total, Manual Dexterity and Balance scores. Motor functioning is weakly associated with visual and visual-motor integration deficits and moderately associated with abnormal neurological status, indicating that motor performance reflects long term vulnerability following very preterm birth, and that visual deficits are of minor importance in understanding motor functioning of VP/VLBW children. Copyright © 2016 Elsevier Ltd. All rights reserved.

A cross-sectional analysis of daytime versus nocturnal polysomnographic respiratory parameters in cystic fibrosis during early adolescence.

PubMed

Waters, K A; Lowe, A; Cooper, P; Vella, S; Selvadurai, Hiran

2017-03-01

In Cystic Fibrosis (CF), early detection and treatment of respiratory disease is considered the standard for respiratory care. Overnight polysomnography (PSG) may help identify respiratory deterioration in young patients with CF. A prospective cohort study of 46 patients with CF, aged 8-12years, from a specialist clinic in a tertiary paediatric hospital. Daytime pulmonary function, shuttle test exercise testing and overnight PSG were studied. Of 81 children aged 8-12years, 46 (57%) agreed to participate. FEV 1 (% predicted, mean 74.6%) was normal in 23 (50%), mildly abnormal in 12 (26.1%), moderately abnormal in 10 (21.7%) and severely abnormal in 1 (2.2%). Amongst sleep study parameters, FEV 1 (% predicted) showed significant correlation with the respiratory rate (RR) in slow wave sleep (SWS), CO 2 change in REM, baseline SaO 2 , and the arousal index (h -1 ). Backward, stepwise linear regression modelling for FEV 1 (% predicted) included the entire group with a wide spectrum of clinical severity. From sleep, variables remaining in the multivariate model for FEV 1 (F=16.81, p<0.001) were the RR in SWS (min -1 ) and the CO 2 change in REM (p=0.003, and 0.014, respectively). When daytime tests were included, the variables remaining were RR in SWS and SD score for BMI (BMIsds) (F=18.70, p<0.001). Respiratory abnormalities on overnight sleep studies included elevated respiratory rates during SWS and mild CO 2 retention in REM sleep, and these incorporated into a model correlating with FEV 1 (% predicted). Thus, mild mechanical impairment of ventilation is evident on overnight sleep studies in children with cystic fibrosis although the significance of this finding will require further investigation. Copyright © 2016 European Cystic Fibrosis Society. All rights reserved.

Overlapped Partitioning for Ensemble Classifiers of P300-Based Brain-Computer Interfaces

PubMed Central

Onishi, Akinari; Natsume, Kiyohisa

2014-01-01

A P300-based brain-computer interface (BCI) enables a wide range of people to control devices that improve their quality of life. Ensemble classifiers with naive partitioning were recently applied to the P300-based BCI and these classification performances were assessed. However, they were usually trained on a large amount of training data (e.g., 15300). In this study, we evaluated ensemble linear discriminant analysis (LDA) classifiers with a newly proposed overlapped partitioning method using 900 training data. In addition, the classification performances of the ensemble classifier with naive partitioning and a single LDA classifier were compared. One of three conditions for dimension reduction was applied: the stepwise method, principal component analysis (PCA), or none. The results show that an ensemble stepwise LDA (SWLDA) classifier with overlapped partitioning achieved a better performance than the commonly used single SWLDA classifier and an ensemble SWLDA classifier with naive partitioning. This result implies that the performance of the SWLDA is improved by overlapped partitioning and the ensemble classifier with overlapped partitioning requires less training data than that with naive partitioning. This study contributes towards reducing the required amount of training data and achieving better classification performance. PMID:24695550

Overlapped partitioning for ensemble classifiers of P300-based brain-computer interfaces.

PubMed

Onishi, Akinari; Natsume, Kiyohisa

2014-01-01

A P300-based brain-computer interface (BCI) enables a wide range of people to control devices that improve their quality of life. Ensemble classifiers with naive partitioning were recently applied to the P300-based BCI and these classification performances were assessed. However, they were usually trained on a large amount of training data (e.g., 15300). In this study, we evaluated ensemble linear discriminant analysis (LDA) classifiers with a newly proposed overlapped partitioning method using 900 training data. In addition, the classification performances of the ensemble classifier with naive partitioning and a single LDA classifier were compared. One of three conditions for dimension reduction was applied: the stepwise method, principal component analysis (PCA), or none. The results show that an ensemble stepwise LDA (SWLDA) classifier with overlapped partitioning achieved a better performance than the commonly used single SWLDA classifier and an ensemble SWLDA classifier with naive partitioning. This result implies that the performance of the SWLDA is improved by overlapped partitioning and the ensemble classifier with overlapped partitioning requires less training data than that with naive partitioning. This study contributes towards reducing the required amount of training data and achieving better classification performance.

Multivariate detrending of fMRI signal drifts for real-time multiclass pattern classification.

PubMed

Lee, Dongha; Jang, Changwon; Park, Hae-Jeong

2015-03-01

Signal drift in functional magnetic resonance imaging (fMRI) is an unavoidable artifact that limits classification performance in multi-voxel pattern analysis of fMRI. As conventional methods to reduce signal drift, global demeaning or proportional scaling disregards regional variations of drift, whereas voxel-wise univariate detrending is too sensitive to noisy fluctuations. To overcome these drawbacks, we propose a multivariate real-time detrending method for multiclass classification that involves spatial demeaning at each scan and the recursive detrending of drifts in the classifier outputs driven by a multiclass linear support vector machine. Experiments using binary and multiclass data showed that the linear trend estimation of the classifier output drift for each class (a weighted sum of drifts in the class-specific voxels) was more robust against voxel-wise artifacts that lead to inconsistent spatial patterns and the effect of online processing than voxel-wise detrending. The classification performance of the proposed method was significantly better, especially for multiclass data, than that of voxel-wise linear detrending, global demeaning, and classifier output detrending without demeaning. We concluded that the multivariate approach using classifier output detrending of fMRI signals with spatial demeaning preserves spatial patterns, is less sensitive than conventional methods to sample size, and increases classification performance, which is a useful feature for real-time fMRI classification. Copyright © 2014 Elsevier Inc. All rights reserved.

The role of chemometrics in single and sequential extraction assays: a review. Part II. Cluster analysis, multiple linear regression, mixture resolution, experimental design and other techniques.

PubMed

Giacomino, Agnese; Abollino, Ornella; Malandrino, Mery; Mentasti, Edoardo

2011-03-04

Single and sequential extraction procedures are used for studying element mobility and availability in solid matrices, like soils, sediments, sludge, and airborne particulate matter. In the first part of this review we reported an overview on these procedures and described the applications of chemometric uni- and bivariate techniques and of multivariate pattern recognition techniques based on variable reduction to the experimental results obtained. The second part of the review deals with the use of chemometrics not only for the visualization and interpretation of data, but also for the investigation of the effects of experimental conditions on the response, the optimization of their values and the calculation of element fractionation. We will describe the principles of the multivariate chemometric techniques considered, the aims for which they were applied and the key findings obtained. The following topics will be critically addressed: pattern recognition by cluster analysis (CA), linear discriminant analysis (LDA) and other less common techniques; modelling by multiple linear regression (MLR); investigation of spatial distribution of variables by geostatistics; calculation of fractionation patterns by a mixture resolution method (Chemometric Identification of Substrates and Element Distributions, CISED); optimization and characterization of extraction procedures by experimental design; other multivariate techniques less commonly applied. Copyright © 2010 Elsevier B.V. All rights reserved.

Characterizations of linear sufficient statistics

NASA Technical Reports Server (NTRS)

Peters, B. C., Jr.; Reoner, R.; Decell, H. P., Jr.

1977-01-01

A surjective bounded linear operator T from a Banach space X to a Banach space Y must be a sufficient statistic for a dominated family of probability measures defined on the Borel sets of X. These results were applied, so that they characterize linear sufficient statistics for families of the exponential type, including as special cases the Wishart and multivariate normal distributions. The latter result was used to establish precisely which procedures for sampling from a normal population had the property that the sample mean was a sufficient statistic.

A neural network approach to cloud classification

NASA Technical Reports Server (NTRS)

Lee, Jonathan; Weger, Ronald C.; Sengupta, Sailes K.; Welch, Ronald M.

1990-01-01

It is shown that, using high-spatial-resolution data, very high cloud classification accuracies can be obtained with a neural network approach. A texture-based neural network classifier using only single-channel visible Landsat MSS imagery achieves an overall cloud identification accuracy of 93 percent. Cirrus can be distinguished from boundary layer cloudiness with an accuracy of 96 percent, without the use of an infrared channel. Stratocumulus is retrieved with an accuracy of 92 percent, cumulus at 90 percent. The use of the neural network does not improve cirrus classification accuracy. Rather, its main effect is in the improved separation between stratocumulus and cumulus cloudiness. While most cloud classification algorithms rely on linear parametric schemes, the present study is based on a nonlinear, nonparametric four-layer neural network approach. A three-layer neural network architecture, the nonparametric K-nearest neighbor approach, and the linear stepwise discriminant analysis procedure are compared. A significant finding is that significantly higher accuracies are attained with the nonparametric approaches using only 20 percent of the database as training data, compared to 67 percent of the database in the linear approach.

QSRR modeling for diverse drugs using different feature selection methods coupled with linear and nonlinear regressions.

PubMed

Goodarzi, Mohammad; Jensen, Richard; Vander Heyden, Yvan

2012-12-01

A Quantitative Structure-Retention Relationship (QSRR) is proposed to estimate the chromatographic retention of 83 diverse drugs on a Unisphere poly butadiene (PBD) column, using isocratic elutions at pH 11.7. Previous work has generated QSRR models for them using Classification And Regression Trees (CART). In this work, Ant Colony Optimization is used as a feature selection method to find the best molecular descriptors from a large pool. In addition, several other selection methods have been applied, such as Genetic Algorithms, Stepwise Regression and the Relief method, not only to evaluate Ant Colony Optimization as a feature selection method but also to investigate its ability to find the important descriptors in QSRR. Multiple Linear Regression (MLR) and Support Vector Machines (SVMs) were applied as linear and nonlinear regression methods, respectively, giving excellent correlation between the experimental, i.e. extrapolated to a mobile phase consisting of pure water, and predicted logarithms of the retention factors of the drugs (logk(w)). The overall best model was the SVM one built using descriptors selected by ACO. Copyright © 2012 Elsevier B.V. All rights reserved.

Extending local canonical correlation analysis to handle general linear contrasts for FMRI data.

PubMed

Jin, Mingwu; Nandy, Rajesh; Curran, Tim; Cordes, Dietmar

2012-01-01

Local canonical correlation analysis (CCA) is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM), a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR) and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic.

Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data

PubMed Central

Jin, Mingwu; Nandy, Rajesh; Curran, Tim; Cordes, Dietmar

2012-01-01

Local canonical correlation analysis (CCA) is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM), a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR) and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic. PMID:22461786

The rate of adherence to urate-lowering therapy and associated factors in Chinese gout patients: a cross-sectional study.

PubMed

Yin, Rulan; Cao, Haixia; Fu, Ting; Zhang, Qiuxiang; Zhang, Lijuan; Li, Liren; Gu, Zhifeng

2017-07-01

The aim of this study was to assess adherence rate and predictors of non-adherence with urate-lowering therapy (ULT) in Chinese gout patients. A cross-sectional study was administered to 125 gout patients using the Compliance Questionnaire on Rheumatology (CQR) for adherence to ULT. Patients were asked to complete the Treatment Satisfaction Questionnaire for Medication version II, Health Assessment Questionnaire, Confidence in Gout Treatment Questionnaire, Gout Knowledge Questionnaire, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and 36-Item Short Form Health Survey. Data were analyzed by independent sample t test, rank sum test, Chi-square analysis as well as binary stepwise logistic regression modeling. The data showed that the rate of adherence (CQR ≥80%) to ULT was 9.6% in our investigated gout patients. Adherence was associated with functional capacity, gout-related knowledge, satisfaction with medication, confidence in gout treatment and mental components summary. Multivariable analysis of binary stepwise logistic regression identified gout-related knowledge and satisfaction of effectiveness with medication was the independent risk factors of medication non-adherence. Patients unaware of gout-related knowledge, or with low satisfaction of effectiveness with medication, were more likely not to adhere to ULT. Non-adherence to ULT among gout patients is exceedingly common, particularly in patients unaware of gout-related knowledge, or with low satisfaction of effectiveness with medication. These findings could help medical personnel develop useful interventions to improve gout patients' medication adherence.

Relationships between temperaments, occupational stress, and insomnia among Japanese workers.

PubMed

Deguchi, Yasuhiko; Iwasaki, Shinichi; Ishimoto, Hideyuki; Ogawa, Koichiro; Fukuda, Yuichi; Nitta, Tomoko; Mitake, Tomoe; Nogi, Yukako; Inoue, Koki

2017-01-01

Insomnia among workers reduces the quality of life, contributes toward the economic burden of healthcare costs and losses in work performance. The relationship between occupational stress and insomnia has been reported in previous studies, but there has been little attention to temperament in occupational safety and health research. The aim of this study was to clarify the relationships between temperament, occupational stress, and insomnia. The subjects were 133 Japanese daytime local government employees. Temperament was assessed using the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego-Auto questionnaire (TEMPS-A). Occupational stress was assessed using the Generic Job Stress Questionnaire (GJSQ). Insomnia was assessed using the Athens Insomnia Scale (AIS). Stepwise multiple logistic regression analyses were conducted. In a stepwise multivariate logistic regression analysis, it was found that the higher subdivided stress group by "role conflict" (OR = 5.29, 95% CI, 1.61-17.32) and anxious temperament score (OR = 1.33; 95% CI, 1.19-1.49) was associated with the presence of insomnia using an adjusted model, whereas other factors were excluded from the model. The study limitations were the sample size and the fact that only Japanese local government employees were surveyed. This study demonstrated the relationships between workers' anxious temperament, role conflict, and insomnia. Recognizing one's own anxious temperament would lead to self-insight, and the recognition of anxious temperament and reduction of role conflict by their supervisors or coworkers would reduce the prevalence of insomnia among workers in the workplace.

Ectopic fat depots and left ventricular function in nondiabetic men with nonalcoholic fatty liver disease.

PubMed

Granér, Marit; Nyman, Kristofer; Siren, Reijo; Pentikäinen, Markku O; Lundbom, Jesper; Hakkarainen, Antti; Lauerma, Kirsi; Lundbom, Nina; Nieminen, Markku S; Taskinen, Marja-Riitta

2015-01-01

Nonalcoholic fatty liver disease has emerged as a novel cardiovascular risk factor. The aim of the study was to assess the effect of different ectopic fat depots on left ventricular (LV) function in subjects with nonalcoholic fatty liver disease. Myocardial and hepatic triglyceride contents were measured with 1.5 T magnetic resonance spectroscopy and LV function, visceral adipose tissue (VAT) and subcutaneous adipose tissue, epicardial and pericardial fat by MRI in 75 nondiabetic men. Subjects were stratified by hepatic triglyceride content into low, moderate, and high liver fat groups. Myocardial triglyceride, epicardial and pericardial fat, VAT, and subcutaneous adipose tissue increased stepwise from low to high liver fat group. Parameters of LV diastolic function showed a stepwise decrease over tertiles of liver fat and VAT, and they were inversely correlated with hepatic triglyceride, VAT, and VAT/subcutaneous adipose tissue ratio. In multivariable analyses, hepatic triglyceride and VAT were independent predictors of LV diastolic function, whereas myocardial triglyceride was not associated with measures of diastolic function. Myocardial triglyceride, epicardial and pericardial fat increased with increasing amount of liver fat and VAT. Hepatic steatosis and VAT associated with significant changes in LV structure and function. The association of LV diastolic function with hepatic triglyceride and VAT may be because of toxic systemic effects. The effects of myocardial triglyceride on LV structure and function seem to be more complex than previously thought and merit further study. © 2014 American Heart Association, Inc.

Relationships between temperaments, occupational stress, and insomnia among Japanese workers

PubMed Central

Ishimoto, Hideyuki; Ogawa, Koichiro; Fukuda, Yuichi; Nitta, Tomoko; Mitake, Tomoe; Nogi, Yukako; Inoue, Koki

2017-01-01

Insomnia among workers reduces the quality of life, contributes toward the economic burden of healthcare costs and losses in work performance. The relationship between occupational stress and insomnia has been reported in previous studies, but there has been little attention to temperament in occupational safety and health research. The aim of this study was to clarify the relationships between temperament, occupational stress, and insomnia. The subjects were 133 Japanese daytime local government employees. Temperament was assessed using the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego-Auto questionnaire (TEMPS-A). Occupational stress was assessed using the Generic Job Stress Questionnaire (GJSQ). Insomnia was assessed using the Athens Insomnia Scale (AIS). Stepwise multiple logistic regression analyses were conducted. In a stepwise multivariate logistic regression analysis, it was found that the higher subdivided stress group by “role conflict” (OR = 5.29, 95% CI, 1.61–17.32) and anxious temperament score (OR = 1.33; 95% CI, 1.19–1.49) was associated with the presence of insomnia using an adjusted model, whereas other factors were excluded from the model. The study limitations were the sample size and the fact that only Japanese local government employees were surveyed. This study demonstrated the relationships between workers’ anxious temperament, role conflict, and insomnia. Recognizing one’s own anxious temperament would lead to self-insight, and the recognition of anxious temperament and reduction of role conflict by their supervisors or coworkers would reduce the prevalence of insomnia among workers in the workplace. PMID:28407025

Apolipoprotein E4 serum concentration for increased sensitivity and specificity of diagnosis of drug treated Alzheimer's disease patients vs. drug treated parkinson's disease patients vs. age-matched normal controls.

PubMed

Goldknopf, Ira L; Park, Helen R; Sabbagh, Marwan

2012-12-01

Inasmuch as Alzheimer's disease (AD) is difficult to diagnose, patients with suspected dementias are often given FDA approved medications, including donepezil, rivastigmine, memantine HCl, or a combination, prior to diagnosis, and some respond with improved cognition. The present study demonstrates how concentrations of a select group of serum protein biomarkers can provide the basis for sensitive and specific differential diagnosis of AD in drug treated patients. Optimization is addressed by taking into account whether the patients and controls have or do not have increased risk of AD die to the presence or absence of Apolipoprotein E4. For differential diagnosis of AD, prospectively collected newly drawn blood serum samples were obtained from drug treated Alzheimer's disease and Parkinson's disease patients from a first (39 drug treated DTAD, and 31 age matched normal controls) and second medical center (56 drug treated DTPD, 47 age-matched normal controls). Analytically validated quantitative 2D gel electrophoresis (%CV ≤ 20%; LOD ≥ 0.5 ng/spot, 300 μg/ml of blood serum) was employed with patient and control sera for differential diagnosis of AD. Protein quantitation was subjected to statistical analysis by single variable Dot, Box and Whiskers and Receiver Operator Characteristics (ROC) plots for individual biomarker performance, and multivariate linear discriminant analysis for joint performance of groups of biomarkers. Protein spots were identified and characterized by LC MS/MS of in-gel trypsin digests, amino acid sequence spans of the identified peptides, and the protein spot molecular weights and isoelectric points. The single variable statistical profiles of 58 individual protein biomarker concentrations of the DTAD patient group differed from those of the normal and/or the disease control groups. Multivariate linear discriminant analysis of blood serum concentrations of the 58 proteins distinguished drug treated Alzheimer's disease (DTAD) patients from drug treated Parkinson's disease (DTPD) patients and age matched normal controls (collectively not-DTAD, DTAD Sensitivity 87.2%, Not-DTAD Specificity 87.2). Moreover, when the patients and controls were stratified into carriers or non-carriers of Alzheimer's high risk Apolipoprotein E 4 allele and/or the Apolipoprotein E4 protein, the DTAD, DTPD and control Apo E4 (+) profiles were more divergent from one another than the corresponding Apo E4 (-) profiles. Multivariate stepwise linear discriminant analysis selected 17 of the 58 biomarkers as optimal and complimentary for distinguishing Apo E4 (+) DTAD patients from Apo E4 (+) DTPD and Apo E4 (+) controls (collectively Apo E4 (+) not-DTAD, DTAD Sensitivity 100%, not-DTAD Specificity 100%) and 22 of the 58 biomarkers for distinguishing Apo E4 (-) DTAD patients from Apo E4 (-) DTPD and Apo E4 (-) controls (collectively Apo E4 (-) not-DTAD, DTAD Sensitivity 94.4%, not- DTAD Specificity 94.4%). Only 6 of the selected proteins were common to both the Apo E4 (+) and the Apo E4 (-) discriminant functions. Recombining of the results of Apo E4 (+) and Apo E4 (-) discriminations provided overall sensitivity for total DTAD of 97.4% and specificity for total not-DTAD of 95.7%. These results can form the basis of a blood test for differential diagnosis of Alzheimer's disease patients already under treatment (DTAD) by anti dementia drugs, including donepezil, rivastigmine, memantine HCl, or a combination thereof. Also, the profile differences and the rise in specificity and sensitivity obtained by handling the Apo E4 (+) and Apo E4 (-) groups separately supports the concept that they are different patient and control populations in terms of the "normal" physiology, the pathophysiology of disease, and the response to drug treatment. Taking that into account enables increased sensitivity and specificity of differential diagnosis of Alzheimer's disease.

Study relationship between inorganic and organic coal analysis with gross calorific value by multiple regression and ANFIS

USGS Publications Warehouse

Chelgani, S.C.; Hart, B.; Grady, W.C.; Hower, J.C.

2011-01-01

The relationship between maceral content plus mineral matter and gross calorific value (GCV) for a wide range of West Virginia coal samples (from 6518 to 15330 BTU/lb; 15.16 to 35.66MJ/kg) has been investigated by multivariable regression and adaptive neuro-fuzzy inference system (ANFIS). The stepwise least square mathematical method comparison between liptinite, vitrinite, plus mineral matter as input data sets with measured GCV reported a nonlinear correlation coefficient (R2) of 0.83. Using the same data set the correlation between the predicted GCV from the ANFIS model and the actual GCV reported a R2 value of 0.96. It was determined that the GCV-based prediction methods, as used in this article, can provide a reasonable estimation of GCV. Copyright ?? Taylor & Francis Group, LLC.

Identification of multivariable nonlinear systems in the presence of colored noises using iterative hierarchical least squares algorithm.

PubMed

Jafari, Masoumeh; Salimifard, Maryam; Dehghani, Maryam

2014-07-01

This paper presents an efficient method for identification of nonlinear Multi-Input Multi-Output (MIMO) systems in the presence of colored noises. The method studies the multivariable nonlinear Hammerstein and Wiener models, in which, the nonlinear memory-less block is approximated based on arbitrary vector-based basis functions. The linear time-invariant (LTI) block is modeled by an autoregressive moving average with exogenous (ARMAX) model which can effectively describe the moving average noises as well as the autoregressive and the exogenous dynamics. According to the multivariable nature of the system, a pseudo-linear-in-the-parameter model is obtained which includes two different kinds of unknown parameters, a vector and a matrix. Therefore, the standard least squares algorithm cannot be applied directly. To overcome this problem, a Hierarchical Least Squares Iterative (HLSI) algorithm is used to simultaneously estimate the vector and the matrix of unknown parameters as well as the noises. The efficiency of the proposed identification approaches are investigated through three nonlinear MIMO case studies. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Multiscale analysis of information dynamics for linear multivariate processes.

PubMed

Faes, Luca; Montalto, Alessandro; Stramaglia, Sebastiano; Nollo, Giandomenico; Marinazzo, Daniele

2016-08-01

In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving average (MA) component, we describe how to represent the resulting VARMA process using statespace (SS) models and how to exploit the SS model parameters to compute analytical measures of information storage and information transfer for the original and rescaled processes. The framework is then used to quantify multiscale information dynamics for simulated unidirectionally and bidirectionally coupled VAR processes, showing that rescaling may lead to insightful patterns of information storage and transfer but also to potentially misleading behaviors.

Aerobic Fitness Does Not Contribute to Prediction of Orthostatic Intolerance

NASA Technical Reports Server (NTRS)

Convertino, Victor A.; Sather, Tom M.; Goldwater, Danielle J.; Alford, William R.

1986-01-01

Several investigations have suggested that orthostatic tolerance may be inversely related to aerobic fitness (VO (sub 2max)). To test this hypothesis, 18 males (age 29 to 51 yr) underwent both treadmill VO(sub 2max) determination and graded lower body negative pressures (LBNP) exposure to tolerance. VO(2max) was measured during the last minute of a Bruce treadmill protocol. LBNP was terminated based on pre-syncopal symptoms and LBNP tolerance (peak LBNP) was expressed as the cumulative product of LBNP and time (torr-min). Changes in heart rate, stroke volume cardiac output, blood pressure and impedance rheographic indices of mid-thigh-leg initial accumulation were measured at rest and during the final minute of LBNP. For all 18 subjects, mean (plus or minus SE) fluid accumulation index and leg venous compliance index at peak LBNP were 139 plus or minus 3.9 plus or minus 0.4 ml-torr-min(exp -2) x 10(exp 3), respectively. Pearson product-moment correlations and step-wise linear regression were used to investigate relationships with peak LBNP. Variables associated with endurance training, such as VO(sub 2max) and percent body fat were not found to correlate significantly (P is less than 0.05) with peak LBNP and did not add sufficiently to the prediction of peak LBNP to be included in the step-wise regression model. The step-wise regression model included only fluid accumulation index leg venous compliance index, and blood volume and resulted in a squared multiple correlation coefficient of 0.978. These data do not support the hypothesis that orthostatic tolerance as measured by LBNP is lower in individuals with high aerobic fitness.

Some Integrated Squared Error Procedures for Multivariate Normal Data,

DTIC Science & Technology

1986-01-01

a lnear regresmion or experimental design model). Our procedures have &lSO been usned wcelyOn non -linear models but we do not addres nan-lnear...of fit, outliers, influence functions, experimental design , cluster analysis, robustness 24L A =TO ACT (VCefme - pvre alli of magsy MW identif by...structured data such as multivariate experimental designs . Several illustrations are provided. * 0 %41 %-. 4.’. * " , -.--, ,. -,, ., -, ’v ’ , " ,,- ,, . -,-. . ., * . - tAma- t

Effect of Contact Damage on the Strength of Ceramic Materials.

DTIC Science & Technology

1982-10-01

variables that are important to erosion, and a multivariate , linear regression analysis is used to fit the data to the dimensional analysis. The...of Equations 7 and 8 by a multivariable regression analysis (room tem- perature data) Exponent Regression Standard error Computed coefficient of...1980) 593. WEAVER, Proc. Brit. Ceram. Soc. 22 (1973) 125. 39. P. W. BRIDGMAN, "Dimensional Analaysis ", (Yale 18. R. W. RICE, S. W. FREIMAN and P. F

Analysis of Forest Foliage Using a Multivariate Mixture Model

NASA Technical Reports Server (NTRS)

Hlavka, C. A.; Peterson, David L.; Johnson, L. F.; Ganapol, B.

1997-01-01

Data with wet chemical measurements and near infrared spectra of ground leaf samples were analyzed to test a multivariate regression technique for estimating component spectra which is based on a linear mixture model for absorbance. The resulting unmixed spectra for carbohydrates, lignin, and protein resemble the spectra of extracted plant starches, cellulose, lignin, and protein. The unmixed protein spectrum has prominent absorption spectra at wavelengths which have been associated with nitrogen bonds.

A mathematical theory of learning control for linear discrete multivariable systems

NASA Technical Reports Server (NTRS)

Phan, Minh; Longman, Richard W.

1988-01-01

When tracking control systems are used in repetitive operations such as robots in various manufacturing processes, the controller will make the same errors repeatedly. Here consideration is given to learning controllers that look at the tracking errors in each repetition of the process and adjust the control to decrease these errors in the next repetition. A general formalism is developed for learning control of discrete-time (time-varying or time-invariant) linear multivariable systems. Methods of specifying a desired trajectory (such that the trajectory can actually be performed by the discrete system) are discussed, and learning controllers are developed. Stability criteria are obtained which are relatively easy to use to insure convergence of the learning process, and proper gain settings are discussed in light of measurement noise and system uncertainties.

A FORTRAN program for multivariate survival analysis on the personal computer.

PubMed

Mulder, P G

1988-01-01

In this paper a FORTRAN program is presented for multivariate survival or life table regression analysis in a competing risks' situation. The relevant failure rate (for example, a particular disease or mortality rate) is modelled as a log-linear function of a vector of (possibly time-dependent) explanatory variables. The explanatory variables may also include the variable time itself, which is useful for parameterizing piecewise exponential time-to-failure distributions in a Gompertz-like or Weibull-like way as a more efficient alternative to Cox's proportional hazards model. Maximum likelihood estimates of the coefficients of the log-linear relationship are obtained from the iterative Newton-Raphson method. The program runs on a personal computer under DOS; running time is quite acceptable, even for large samples.

Eigenvalue assignment by minimal state-feedback gain in LTI multivariable systems

NASA Astrophysics Data System (ADS)

Ataei, Mohammad; Enshaee, Ali

2011-12-01

In this article, an improved method for eigenvalue assignment via state feedback in the linear time-invariant multivariable systems is proposed. This method is based on elementary similarity operations, and involves mainly utilisation of vector companion forms, and thus is very simple and easy to implement on a digital computer. In addition to the controllable systems, the proposed method can be applied for the stabilisable ones and also systems with linearly dependent inputs. Moreover, two types of state-feedback gain matrices can be achieved by this method: (1) the numerical one, which is unique, and (2) the parametric one, in which its parameters are determined in order to achieve a gain matrix with minimum Frobenius norm. The numerical examples are presented to demonstrate the advantages of the proposed method.

Depression is a predictor for balance in people with multiple sclerosis.

PubMed

Alghwiri, Alia A; Khalil, Hanan; Al-Sharman, Alham; El-Salem, Khalid

2018-05-26

Balance impairments are common and multifactorial among people with multiple sclerosis (MS). Depression is the most common psychological disorder in MS population and is strongly correlated with MS disease. Depression might be one of the factors that contribute to balance deficits in this population. However, the relationship between depression and balance impairments has not been explored in people with MS. To investigate the association between depression and balance impairments in people with MS. Cross sectional design was used in patients with MS. The Activities-specific Balance Confidence scale (ABC) and Berg Balance Scale (BBS) was used to assess balance. Beck Depression Inventory (BDI-II) was used to quantify depression and Kurtizki Expanded Disability Status Scale (EDSS) was utilized for the evaluation of MS disability severity. Pearson correlation coefficient was used to examine the association between depression and balance measurements. Multiple linear stepwise regressions were also conducted to find out if depression is a potential predictor for balance deficits. Seventy-five individuals with MS (Female = 69%) with a mean age (SD) of 38.8 (10) and a mean (SD) EDSS score of 3.0 (1.4) were recruited in this study. Depression was present in 53% of the patients. Depression was significantly correlated with balance measurements and EDSS. However, multiple linear stepwise regressions found that only depression and age significantly predict balance. Depression and balance were found frequent and associated in people with MS. Importantly depression was a significant predictor for balance impairments in individuals with MS. Balance rehabilitation may be hindered by depression. Therefore, depression should be evaluated and treated properly in individuals with MS. Copyright © 2018 Elsevier B.V. All rights reserved.

Nutritional and biochemical parameters associated with 6-year change in bone mineral density in community-dwelling Japanese women aged 69 years and older: The Muramatsu Study.

PubMed

Nakamura, Kazutoshi; Oyama, Mari; Saito, Toshiko; Oshiki, Rieko; Kobayashi, Ryosaku; Nishiwaki, Tomoko; Nashimoto, Mitsue; Tsuchiya, Yasuo

2012-04-01

Predictors of bone loss in elderly Asian women have been unclear. This cohort study aimed to assess lifestyle, nutritional, and biochemical predictors of bone loss in elderly Japanese women. Subjects included 389 community-dwelling women aged 69 y and older from the Muramatsu cohort initiated in 2003; follow-up ended in 2009. We obtained data on physical characteristics, osteoporosis treatment (with bisphosphonates or selective estrogen receptor modulators), physical activity, calcium intake, serum 25-hydroxyvitamin D, undercarboxylated osteocalcin, serum albumin, and bone turnover markers as predictors. The outcome was a 6-y change in forearm BMD (ΔBMD). Osteoporosis treatment was coded as 0 for none, 1 for sometimes, and 2 for always during the follow-up period. Stepwise multiple linear regression analysis was used to identify independent predictors of ΔBMD. Mean age of the subjects was 73.3 y. Mean values of ΔBMD and Δweight were -0.019 g/cm(2) (-5.8%) and -2.2 kg, respectively. Stepwise multiple linear regression analysis revealed baseline BMD (β = -0.137, P < 0.0001), osteoporosis treatment (β = 0.0068, P = 0.0105), serum albumin levels (β = 0.0122, P = 0.0319), and Δweight (β = 0.0015, P = 0.0009) as significant independent predictors of ΔBMD. However, none of the other nutritional or biochemical indices were found to be significant predictors of ΔBMD. Our findings indicate that adequate general nutrition and appropriate osteoporosis medication, rather than specific nutritional regimens, may be effective in preventing bone loss in elderly women. Copyright © 2012 Elsevier Inc. All rights reserved.

Masticatory performance and oral health-related quality of life before and after complete denture treatment.

PubMed

Yamamoto, Saori; Shiga, Hiroshi

2018-03-13

To clarify the relationship between masticatory performance and oral health-related quality of life (OHRQoL) before and after complete denture treatment. Thirty patients wearing complete dentures were asked to chew a gummy jelly on their habitual chewing side, and the amount of glucose extraction during chewing was measured as the parameter of masticatory performance. Subjects were asked to answer the Oral Health Impact Profile (OHIP-J49) questionnaire, which consists of 49 questions related to oral problems. The total score of 49 question items along with individual domain scores within the seven domains (functional limitation, pain, psychological discomfort, physical disability, psychological disability, social disability and handicap) were calculated and used as the parameters of OHRQoL. These records were obtained before treatment and 3 months after treatment. Each parameter of masticatory performance and OHRQoL was compared before treatment and after treatment. The relationship between masticatory performance and OHRQoL was investigated, and a stepwise multiple linear regression analysis was performed. Both masticatory performance and OHRQoL were significantly improved after treatment. Furthermore, masticatory performance was significantly correlated with some parameters of OHRQoL. The stepwise multiple linear regression analysis showed functional limitation and pain as important factors affecting masticatory performance before treatment and functional limitation as important factors affecting masticatory performance after treatment. These results suggested that masticatory performance and OHRQoL are significantly improved after treatment and that there is a close relationship between the two. Moreover, functional limitation was found to be the most important factor affecting masticatory performance. Copyright © 2018 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

What makes patients with fibromyalgia feel better? Correlations between Patient Global Impression of Improvement and changes in clinical symptoms and function: a pooled analysis of 4 randomized placebo-controlled trials of duloxetine.

PubMed

Hudson, James I; Arnold, Lesley M; Bradley, Laurence A; Choy, Ernest H S; Mease, Philip J; Wang, Fujun; Ahl, Jonna; Wohlreich, Madelaine M

2009-11-01

To investigate the relationship between changes in clinical rating scale items and endpoint Patient Global Impression of Improvement (PGI-I). Data were pooled from 4 randomized, double-blind, placebo-controlled studies of duloxetine in patients with fibromyalgia (FM). Variables included in the analyses were those that assessed symptoms in FM domains of pain, fatigue, sleep, cognitive difficulties, emotional well-being, physical function, and impact on daily living. The association of endpoint PGI-I with changes from baseline in individual variables was assessed using Pearson product-moment correlations (r). Stepwise linear regression was used to identify those variables for which changes from baseline were statistically significant independent predictors of the endpoint PGI-I ratings. Changes in pain variables and interference of symptoms with the ability to work were highly correlated (r >or= 0.5 or r

Heart rate dynamics during cardio-pulmonary exercise testing are associated with glycemic control in individuals with type 1 diabetes.

PubMed

Moser, Othmar; Eckstein, Max L; McCarthy, Olivia; Deere, Rachel; Bain, Stephen C; Haahr, Hanne L; Zijlstra, Eric; Heise, Tim; Bracken, Richard M

2018-01-01

This study investigated the degree and direction (kHR) of the heart rate to performance curve (HRPC) during cardio-pulmonary exercise (CPX) testing and explored the relationship with diabetes markers, anthropometry and exercise physiological markers in type 1 diabetes (T1DM). Sixty-four people with T1DM (13 females; age: 34 ± 8 years; HbA1c: 7.8 ± 1% (62 ± 13 mmol.mol-1) performed a CPX test until maximum exhaustion. kHR was calculated by a second-degree polynomial representation between post-warm up and maximum power output. Adjusted stepwise linear regression analysis was performed to investigate kHR and its associations. Receiver operating characteristic (ROC) curve was performed based on kHR for groups kHR < 0.20 vs. > 0.20 in relation to HbA1c. We found significant relationships between kHR and HbA1c (β = -0.70, P < 0.0001), age (β = -0.23, P = 0.03) and duration of diabetes (β = 0.20, P = 0.04). Stepwise linear regression resulted in an overall adjusted R2 of 0.57 (R = 0.79, P < 0.0001). Our data revealed also significant associations between kHR and percentage of heart rate at heart rate turn point from maximum heart rate (β = 0.43, P < 0.0001) and maximum power output relativized to bodyweight (β = 0.44, P = 0.001) (overall adjusted R2 of 0.44 (R = 0.53, P < 0.0001)). ROC curve analysis based on kHR resulted in a HbA1c threshold of 7.9% (62 mmol.mol-1). Our data demonstrate atypical HRPC during CPX testing that were mainly related to glycemic control in people with T1DM.

Effects of inhibition of nitric oxide synthase on basal anterior segment ocular blood flows and on potential autoregulatory mechanisms.

PubMed

Koss, M C

2001-08-01

Experiments were undertaken to determine the role played by nitric oxide (NO) in basal ocular blood flow in the anterior aspect of the eye. Subsequent studies focused on existence of autoregulatory mechanisms and on the potential involvement of NO. Cats were anesthetized with pentobarbital (36 mg/kg, i.p.). A femoral artery and vein were cannulated for measuring blood pressure and for drug administration, respectively. Anterior segment blood flow was measured in a continuous fashion from the long posterior ciliary artery (LPCA) using ultrasonic flowmetry and from the anterior choroid using laser-Doppler flowmetry. A needle was placed into the anterior chamber, and autoregulatory mechanisms were studied by decreasing ocular perfusion pressure via stepwise elevations of IOP. Non-selective inhibition of NO synthase with L-NAME (20 mg/kg, i.v.) significantly decreased basal blood flow from both sites. L-NAME (5 mg/kg, i.v.) was without effect as was D-NAME (25 mg/kg, i.v.). Increasing IOP produced a linear decrease on LPCA blood flow indicating absence of autoregulation. In contrast, stepwise elevation of IOP produced a delayed, non-linear response in the anterior choroid suggestive of a strong autoregulatory response. Neither response to elevated ocular perfusion pressure was further altered by inhibition of NO synthase with L-NAME (20 mg/kg, i.v.). The results confirm previous reports that nitric oxide plays a pivotal role in maintenance of basal ocular blood flow. Autoregulation was not seen in the LPCA. In contrast, there was a clear autoregulatory response in the anterior choroid, although neither response was altered by inhibition of NO synthase.

Preoperative determinant of early postoperative renal function following radical cystectomy and intestinal urinary diversion.

PubMed

Gondo, Tatsuo; Ohno, Yoshio; Nakashima, Jun; Hashimoto, Takeshi; Nakagami, Yoshihiro; Tachibana, Masaaki

2017-02-01

To identify preoperative factors correlated with postoperative early renal function in patients who had undergone radical cystectomy (RC) and intestinal urinary diversion. We retrospectively identified 201 consecutive bladder cancer patients without distant metastasis who had undergone RC at our institution between 2003 and 2012. The estimated glomerular filtration rate (eGFR) was calculated using the modified Chronic Kidney Disease Epidemiology equation before RC and 3 months following RC. Univariate and stepwise multiple linear regression analyses were applied to estimate postoperative renal function and to identify significant preoperative predictors of postoperative renal function. Patients who had undergone intestinal urinary diversion and were available for the collection of follow-up data (n = 164) were eligible for the present study. Median preoperative and postoperative eGFRs were 69.7 (interquartile range [IQR] 56.3-78.0) and 70.7 (IQR 57.3-78.1), respectively. In univariate analyses, age, preoperative proteinuria, thickness of abdominal subcutaneous fat tissue (TSF), preoperative serum creatinine level, preoperative eGFR, and urinary diversion type were significantly associated with postoperative eGFR. In a stepwise multiple linear regression analysis, preoperative eGFR, age, and TSF were significant factors for predicting postoperative eGFR (p < 0.001, p = 0.02, and p = 0.046, respectively). The estimated postoperative eGFRs correlated well with the actual postoperative eGFRs (r = 0.65, p < 0.001). Preoperative eGFR, age, and TSF were independent preoperative factors for determining postoperative renal function in patients who had undergone RC and intestinal urinary diversion. These results may be used for patient counseling before surgery, including the planning of perioperative chemotherapy administration.

Non-fragile multivariable PID controller design via system augmentation

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

The microbiological profile and presence of bloodstream infection influence mortality rates in necrotizing fasciitis

PubMed Central

2011-01-01

Introduction Necrotizing fasciitis (NF) is a life threatening infectious disease with a high mortality rate. We carried out a microbiological characterization of the causative pathogens. We investigated the correlation of mortality in NF with bloodstream infection and with the presence of co-morbidities. Methods In this retrospective study, we analyzed 323 patients who presented with necrotizing fasciitis at two different institutions. Bloodstream infection (BSI) was defined as a positive blood culture result. The patients were categorized as survivors and non-survivors. Eleven clinically important variables which were statistically significant by univariate analysis were selected for multivariate regression analysis and a stepwise logistic regression model was developed to determine the association between BSI and mortality. Results Univariate logistic regression analysis showed that patients with hypotension, heart disease, liver disease, presence of Vibrio spp. in wound cultures, presence of fungus in wound cultures, and presence of Streptococcus group A, Aeromonas spp. or Vibrio spp. in blood cultures, had a significantly higher risk of in-hospital mortality. Our multivariate logistic regression analysis showed a higher risk of mortality in patients with pre-existing conditions like hypotension, heart disease, and liver disease. Multivariate logistic regression analysis also showed that presence of Vibrio spp in wound cultures, and presence of Streptococcus Group A in blood cultures were associated with a high risk of mortality while debridement > = 3 was associated with improved survival. Conclusions Mortality in patients with necrotizing fasciitis was significantly associated with the presence of Vibrio in wound cultures and Streptococcus group A in blood cultures. PMID:21693053

Cognitive models of medical decision-making capacity in patients with mild cognitive impairment.

PubMed

Okonkwo, O C; Griffith, H R; Belue, K; Lanza, S; Zamrini, E Y; Harrell, L E; Brockington, J C; Clark, D; Raman, R; Marson, D C

2008-03-01

This study investigated cognitive predictors of medical decision-making capacity (MDC) in patients with amnestic mild cognitive impairment (MCI). A total of 56 healthy controls, 60 patients with MCI, and 31 patients with mild Alzheimer's disease (AD) were administered the Capacity to Consent to Treatment Instrument (CCTI) and a neuropsychological test battery. The CCTI assesses MDC across four established treatment consent standards--S1 (expressing choice), S3 (appreciation), S4 (reasoning), and S5 (understanding)--and one experimental standard [S2] (reasonable choice). Scores on neuropsychological measures were correlated with scores on each CCTI standard. Significant bivariate correlates were subsequently entered into stepwise regression analyses to identity group-specific multivariable predictors of MDC across CCTI standards. Different multivariable cognitive models emerged across groups and consent standards. For the MCI group, measures of short-term verbal memory were key predictors of MDC for each of the three clinically relevant standards (S3, S4, and S5). Secondary predictors were measures of executive function. In contrast, in the mild AD group, measures tapping executive function and processing speed were primary predictors of S3, S4, and S5. MDC in patients with MCI is supported primarily by short-term verbal memory. The findings demonstrate the impact of amnestic deficits on MDC in patients with MCI.

Predictors of Parent-Adolescent Communication in Post-apartheid South Africa: A Protective Factor in Adolescent Sexual and Reproductive Health

PubMed Central

Coetzee, Jenny; Dietrich, Janan; Otwombe, Kennedy; Nkala, Busi; Khunwane, Mamakiri; van der Watt, Martin; Sikkema, Kathleen J; Gray, Glenda E

2014-01-01

In the HIV context, risky sexual behaviours can be reduced through effective parent-adolescent communication. This study used the Parent Adolescent Communication Scale to determine parent-adolescent communication by ethnicity and identify predictors of high parent-adolescent communication amongst South African adolescents post-apartheid. A cross-sectional interviewer-administered survey was administered to 822 adolescents from Johannesburg, South Africa. Backward stepwise multivariate regressions were performed. The sample was predominantly Black African (62%, n=506) and female (57%, n=469). Of the participants, 57% (n=471) reported high parent-adolescent communication. Multivariate regression showed that gender was a significant predictor of high parent-adolescent communication (Black African OR:1.47,CI:1.0-2.17, Indian OR:2.67,CI:1.05-6.77, White OR:2.96,CI:1.21-7.18). Female-headed households were predictors of high parent-adolescent communication amongst Black Africans (OR:1.49,CI:1.01-2.20), but of low parent-adolescent communication amongst Whites (OR:0.36,CI: 0.15-0.89). Overall levels of parent-adolescent communication in South Africa are low. HIV prevention programmes for South African adolescents should include information and skills regarding effective parent-adolescent communication. PMID:24636691

Association of pretreatment neutrophil-lymphocyte ratio and outcome in emergency colorectal cancer care.

PubMed

Palin, R P; Devine, A T; Hicks, G; Burke, D

2018-04-01

Introduction The association between the neutrophil-lymphocyte ratio (NLR) and outcome in elective colorectal cancer surgery is well established; the relationship between NLR and the emergency colorectal cancer patient is, as yet, unexplored. This paper evaluates the predictive quality of the NLR for outcome in the emergency colorectal cancer patient. Materials and Methods A total of 187 consecutive patients who underwent emergency surgery for colorectal cancer were included in the study. NLR was calculated from the haematological tests done on admission. Receiver operating characteristic analyses were used to determine the most suitable cut-off for NLR. Outcomes were assessed by mortality at 30 and 90 days using stepwise Cox proportional hazards regression. Results An NLR cut-off of 5 was found to have the highest sensitivity and specificity. At 30 days, age and time from admission to surgery were associated with increased mortality; a high NLR was associated with an increased risk of mortality in univariate but not multivariate analysis. At 90 days, age, NLR, time from admission to surgery and nodal status were all significantly associated with increased mortality on multivariate analysis. Conclusions Pre-operative NLR is a cheap, easily performed and useful clinical tool to aid prediction of outcome in the emergency colorectal cancer patient.

Prediction of the birch pollen season characteristics in Cracow, Poland using an 18-year data series.

PubMed

Dorota, Myszkowska

2013-03-01

The aim of the study was to construct the model forecasting the birch pollen season characteristics in Cracow on the basis of an 18-year data series. The study was performed using the volumetric method (Lanzoni/Burkard trap). The 98/95 % method was used to calculate the pollen season. The Spearman's correlation test was applied to find the relationship between the meteorological parameters and pollen season characteristics. To construct the predictive model, the backward stepwise multiple regression analysis was used including the multi-collinearity of variables. The predictive models best fitted the pollen season start and end, especially models containing two independent variables. The peak concentration value was predicted with the higher prediction error. Also the accuracy of the models predicting the pollen season characteristics in 2009 was higher in comparison with 2010. Both, the multi-variable model and one-variable model for the beginning of the pollen season included air temperature during the last 10 days of February, while the multi-variable model also included humidity at the beginning of April. The models forecasting the end of the pollen season were based on temperature in March-April, while the peak day was predicted using the temperature during the last 10 days of March.

Predictors of the Perception of Smoking Health Risks in Smokers With or Without Schizophrenia.

PubMed

Kowalczyk, William J; Wehring, Heidi J; Burton, George; Raley, Heather; Feldman, Stephanie; Heishman, Stephen J; Kelly, Deanna L

2017-01-01

This study sought to examine the predictors of health risk perception in smokers with or without schizophrenia. The health risk subscale from the Smoking Consequences Questionnaire was dichotomized and used to measure health risk perception in smokers with (n = 67) and without schizophrenia (n = 100). A backward stepwise logistic regression was conducted using variables associated at the bivariate level to determine multivariate predictors. Overall, 62.5% of smokers without schizophrenia and 40.3% of smokers with schizophrenia completely recognize the health risks of smoking (p ≤ .01). Multivariate predictors for smokers without schizophrenia included: sex (Exp (B) = .3; p < .05), Smoking Consequences Questionnaire state enhancement (Exp (B) = .69; p < .01), and craving relief (Exp (B) = 1.8; p < .01). Among smokers with schizophrenia, predictors were education (Exp (B) = .7; p < .05), nicotine dependence (Exp (B) = .5; p < .01), motivation to quit (Exp (B) = 1.8; p < .01), and Smoking Consequences Questionnaire craving relief (Exp (B) = 1.8; p < .01). There was overlap and differences between predictors in smokers with and without schizophrenia. Commonly used techniques for education on the health consequences of cigarettes may work in smokers with schizophrenia, but intervention efforts specifically tailored to smokers with schizophrenia might be more efficacious.

Predictors of the Perception of Smoking Health Risks in Smokers With or Without Schizophrenia

PubMed Central

Kowalczyk, William J.; Wehring, Heidi J.; Burton, George; Raley, Heather; Feldman, Stephanie; Heishman, Stephen J.; Kelly, Deanna L.

2017-01-01

Objective This study sought to examine the predictors of health risk perception in smokers with or without schizophrenia. Methods The health risk subscale from the Smoking Consequences Questionnaire was dichotomized and used to measure health risk perception in smokers with (n = 67) and without schizophrenia (n = 100). A backward stepwise logistic regression was conducted using variables associated at the bivariate level to determine multivariate predictors. Results Overall, 62.5% of smokers without schizophrenia and 40.3% of smokers with schizophrenia completely recognize the health risks of smoking (p ≤ .01). Multivariate predictors for smokers without schizophrenia included: sex (Exp (B) = .3; p < .05), Smoking Consequences Questionnaire state enhancement (Exp (B) = .69; p < .01), and craving relief (Exp (B) = 1.8; p < .01). Among smokers with schizophrenia, predictors were education (Exp (B) = .7; p < .05), nicotine dependence (Exp (B) = .5; p < .01), motivation to quit (Exp (B) = 1.8; p < .01), and Smoking Consequences Questionnaire craving relief (Exp (B) = 1.8; p < .01). Conclusions There was overlap and differences between predictors in smokers with and without schizophrenia. Commonly used techniques for education on the health consequences of cigarettes may work in smokers with schizophrenia, but intervention efforts specifically tailored to smokers with schizophrenia might be more efficacious. PMID:27858591

[Risk factors for anorexia in children].

PubMed

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

2016-11-01

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

H. Pylori as a predictor of marginal ulceration: A nationwide analysis.

PubMed

Schulman, Allison R; Abougergi, Marwan S; Thompson, Christopher C

2017-03-01

Helicobacter pylori has been implicated as a risk factor for development of marginal ulceration following gastric bypass, although studies have been small and yielded conflicting results. This study sought to determine the relationship between H. pylori infection and development of marginal ulceration following bariatric surgery in a nationwide analysis. This was a retrospective cohort study using the 2012 Nationwide Inpatient Sample (NIS) database. Discharges with ICD-9-CM code indicating marginal ulceration and a secondary ICD-9-CM code for bariatric surgery were included. Primary outcome was incidence of marginal ulceration. A stepwise forward selection model was used to build the multivariate logistic regression model based on known risk factors. A P value of 0.05 was considered significant. There were 253,765 patients who met inclusion criteria. Prevalence of marginal ulceration was 3.90%. Of those patients found to have marginal ulceration, 31.20% of patients were H. pylori-positive. Final multivariate regression analysis revealed that H. pylori was the strongest independent predictor of marginal ulceration. H. pylori is an independent predictor of marginal ulceration using a large national database. Preoperative testing for and eradication of H. pylori prior to bariatric surgery may be an important preventive measure to reduce the incidence of ulcer development. © 2017 The Obesity Society.

Impact of total body weight on acute kidney injury in patients with gram-negative bacteremia.

PubMed

Hall, Ronald G; Yoo, Eunice; Faust, Andrew; Smith, Terri; Goodman, Edward; Mortensen, Eric M; Felder, Victoria; Alvarez, Carlos A

2018-05-10

The impact of total body weight (TBW) on the development of acute kidney injury (AKI) associated with gram-negative bacteremia has not been previously evaluated. The cohort included 323 patients >/ = 18 years old with gram-negative bacteremia (1/1/2008-8/31/2011) who received >/ = 48 hours of antibiotics. We compared the incidence of AKI in patients with a TBW 80kg with a multivariable stepwise logistic regression adjusting for age >/ = 70 years, baseline serum creatinine of > 2.0 mg/dl, and receipt of a vasopressor. AKI was defined as an increase of 0.5 mg/dL or a > 50% increase from baseline for at least two consecutive days. The cohort was 62% TBW 80kg. TBW >80kg patients had higher risk of AKI (24% vs. 9%, p < 0.001), which was significant in the multivariable analysis (OR 3.41, 95% CI 1.73-6.73). A baseline serum creatinine of > 2.0 mg/dl and vasopressor use were also independently associated with AKI. TBW >80kg was associated with the development of AKI. However, the mechanism for this association is not clear.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-05-01

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

Spatially resolved regression analysis of pre-treatment FDG, FLT and Cu-ATSM PET from post-treatment FDG PET: an exploratory study

PubMed Central

Bowen, Stephen R; Chappell, Richard J; Bentzen, Søren M; Deveau, Michael A; Forrest, Lisa J; Jeraj, Robert

2012-01-01

Purpose To quantify associations between pre-radiotherapy and post-radiotherapy PET parameters via spatially resolved regression. Materials and methods Ten canine sinonasal cancer patients underwent PET/CT scans of [18F]FDG (FDGpre), [18F]FLT (FLTpre), and [61Cu]Cu-ATSM (Cu-ATSMpre). Following radiotherapy regimens of 50 Gy in 10 fractions, veterinary patients underwent FDG PET/CT scans at three months (FDGpost). Regression of standardized uptake values in baseline FDGpre, FLTpre and Cu-ATSMpre tumour voxels to those in FDGpost images was performed for linear, log-linear, generalized-linear and mixed-fit linear models. Goodness-of-fit in regression coefficients was assessed by R2. Hypothesis testing of coefficients over the patient population was performed. Results Multivariate linear model fits of FDGpre to FDGpost were significantly positive over the population (FDGpost~0.17 FDGpre, p=0.03), and classified slopes of RECIST non-responders and responders to be different (0.37 vs. 0.07, p=0.01). Generalized-linear model fits related FDGpre to FDGpost by a linear power law (FDGpost~FDGpre0.93, p<0.001). Univariate mixture model fits of FDGpre improved R2 from 0.17 to 0.52. Neither baseline FLT PET nor Cu-ATSM PET uptake contributed statistically significant multivariate regression coefficients. Conclusions Spatially resolved regression analysis indicates that pre-treatment FDG PET uptake is most strongly associated with three-month post-treatment FDG PET uptake in this patient population, though associations are histopathology-dependent. PMID:22682748

Key-Generation Algorithms for Linear Piece In Hand Matrix Method

NASA Astrophysics Data System (ADS)

Tadaki, Kohtaro; Tsujii, Shigeo

The linear Piece In Hand (PH, for short) matrix method with random variables was proposed in our former work. It is a general prescription which can be applicable to any type of multivariate public-key cryptosystems for the purpose of enhancing their security. Actually, we showed, in an experimental manner, that the linear PH matrix method with random variables can certainly enhance the security of HFE against the Gröbner basis attack, where HFE is one of the major variants of multivariate public-key cryptosystems. In 1998 Patarin, Goubin, and Courtois introduced the plus method as a general prescription which aims to enhance the security of any given MPKC, just like the linear PH matrix method with random variables. In this paper we prove the equivalence between the plus method and the primitive linear PH matrix method, which is introduced by our previous work to explain the notion of the PH matrix method in general in an illustrative manner and not for a practical use to enhance the security of any given MPKC. Based on this equivalence, we show that the linear PH matrix method with random variables has the substantial advantage over the plus method with respect to the security enhancement. In the linear PH matrix method with random variables, the three matrices, including the PH matrix, play a central role in the secret-key and public-key. In this paper, we clarify how to generate these matrices and thus present two probabilistic polynomial-time algorithms to generate these matrices. In particular, the second one has a concise form, and is obtained as a byproduct of the proof of the equivalence between the plus method and the primitive linear PH matrix method.

On the interpretation of weight vectors of linear models in multivariate neuroimaging.

PubMed

Haufe, Stefan; Meinecke, Frank; Görgen, Kai; Dähne, Sven; Haynes, John-Dylan; Blankertz, Benjamin; Bießmann, Felix

2014-02-15

The increase in spatiotemporal resolution of neuroimaging devices is accompanied by a trend towards more powerful multivariate analysis methods. Often it is desired to interpret the outcome of these methods with respect to the cognitive processes under study. Here we discuss which methods allow for such interpretations, and provide guidelines for choosing an appropriate analysis for a given experimental goal: For a surgeon who needs to decide where to remove brain tissue it is most important to determine the origin of cognitive functions and associated neural processes. In contrast, when communicating with paralyzed or comatose patients via brain-computer interfaces, it is most important to accurately extract the neural processes specific to a certain mental state. These equally important but complementary objectives require different analysis methods. Determining the origin of neural processes in time or space from the parameters of a data-driven model requires what we call a forward model of the data; such a model explains how the measured data was generated from the neural sources. Examples are general linear models (GLMs). Methods for the extraction of neural information from data can be considered as backward models, as they attempt to reverse the data generating process. Examples are multivariate classifiers. Here we demonstrate that the parameters of forward models are neurophysiologically interpretable in the sense that significant nonzero weights are only observed at channels the activity of which is related to the brain process under study. In contrast, the interpretation of backward model parameters can lead to wrong conclusions regarding the spatial or temporal origin of the neural signals of interest, since significant nonzero weights may also be observed at channels the activity of which is statistically independent of the brain process under study. As a remedy for the linear case, we propose a procedure for transforming backward models into forward models. This procedure enables the neurophysiological interpretation of the parameters of linear backward models. We hope that this work raises awareness for an often encountered problem and provides a theoretical basis for conducting better interpretable multivariate neuroimaging analyses. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

Using joint ICA to link function and structure using MEG and DTI in schizophrenia

PubMed Central

Stephen, JM; Coffman, BA; Jung, RE; Bustillo, JR; Aine, CJ; Calhoun, VD

2013-01-01

In this study we employed joint independent component analysis (jICA) to perform a novel multivariate integration of magnetoencephalography (MEG) and diffusion tensor imaging (DTI) data to investigate the link between function and structure. This model-free approach allows one to identify covariation across modalities with different temporal and spatial scales [temporal variation in MEG and spatial variation in fractional anisotropy (FA) maps]. Healthy controls (HC) and patients with schizophrenia (SP) participated in an auditory/visual multisensory integration paradigm to probe cortical connectivity in schizophrenia. To allow direct comparisons across participants and groups, the MEG data were registered to an average head position and regional waveforms were obtained by calculating the local field power of the planar gradiometers. Diffusion tensor images obtained in the same individuals were preprocessed to provide FA maps for each participant. The MEG/FA data were then integrated using the jICA software (http://mialab.mrn.org/software/fit). We identified MEG/FA components that demonstrated significantly different (p < 0.05) covariation in MEG/FA data between diagnostic groups (SP vs. HC) and three components that captured the predominant sensory responses in the MEG data. Lower FA values in bilateral posterior parietal regions, which include anterior/posterior association tracts, were associated with reduced MEG amplitude (120-170 ms) of the visual response in occipital sensors in SP relative to HC. Additionally, increased FA in a right medial frontal region was linked with larger amplitude late MEG activity (300-400 ms) in bilateral central channels for SP relative to HC. Step-wise linear regression provided evidence that right temporal, occipital and late central components were significant predictors of reaction time and cognitive performance based on the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) cognitive assessment battery. These results point to dysfunction in a posterior visual processing network in schizophrenia, with reduced MEG amplitude, reduced FA and poorer overall performance on the MATRICS. Interestingly, the spatial location of the MEG activity and the associated FA regions are spatially consistent with white matter regions that subserve these brain areas. This novel approach provides evidence for significant pairing between function (electrophysiology) and structure (white matter integrity) and demonstrates the sensitivity of this multivariate, multimodal integration technique to group differences in function and structure. PMID:23777757

qFeature

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

2015-09-14

This package contains statistical routines for extracting features from multivariate time-series data which can then be used for subsequent multivariate statistical analysis to identify patterns and anomalous behavior. It calculates local linear or quadratic regression model fits to moving windows for each series and then summarizes the model coefficients across user-defined time intervals for each series. These methods are domain agnostic-but they have been successfully applied to a variety of domains, including commercial aviation and electric power grid data.

Chemical synthesis of the tetrasaccharide repeating unit of the O-polysaccharide isolated from Azospirillum brasilense SR80.

PubMed

Sarkar, Vikramjit; Mukhopadhyay, Balaram

2015-04-10

A linear strategy has been developed for the synthesis of the tetrasaccharide repeating unit of the O-polysaccharide from Azospirillum brasilense SR80. Stepwise glycosylation of the rationally protected thioglycoside donors activated by NIS in the presence of La(OTf)3 furnished the target tetrasaccharide. The glycosylation reactions resulted in the formation of the desired linkage with absolute stereoselectivity and afforded the required derivatives in good to excellent yields. The phthalimido group has been used as the precursor of the desired acetamido group to meet the requirement of 1,2-trans glycosidic linkage. Copyright © 2015 Elsevier Ltd. All rights reserved.

Snow mapping and land use studies in Switzerland

NASA Technical Reports Server (NTRS)

Haefner, H. (Principal Investigator)

1977-01-01

The author has identified the following significant results. A system was developed for operational snow and land use mapping, based on a supervised classification method using various classification algorithms and representation of the results in maplike form on color film with a photomation system. Land use mapping, under European conditions, was achieved with a stepwise linear discriminant analysis by using additional ratio variables. On fall images, signatures of built-up areas were often not separable from wetlands. Two different methods were tested to correlate the size of settlements and the population with an accuracy for the densely populated Swiss Plateau between +2 or -12%.

A modified dodge algorithm for the parabolized Navier-Stokes equations and compressible duct flows

NASA Technical Reports Server (NTRS)

Cooke, C. H.

1981-01-01

A revised version of a split-velocity method for numerical calculation of compressible duct flow was developed. The revision incorporates balancing of mass flow rates on each marching step in order to maintain front-to-back continuity during the calculation. The (checkerboard) zebra algorithm is applied to solution of the three-dimensional continuity equation in conservative form. A second-order A-stable linear multistep method is employed in effecting a marching solution of the parabolized momentum equations. A checkerboard successive overrelaxation iteration is used to solve the resulting implicit nonlinear systems of finite-difference equations which govern stepwise transition.

The economics of transboundary air pollution in Europe.

PubMed

Van Ierland, E C

1991-01-01

Acid rain is causing substantial damage in all Eastern and Western European countries. This article presents a stepwise linear optimisation model, that places transboundary air pollution by SO2 and NOx in a game theoretical framework. The national authorities of 28 countries are perceived as players in a game in which they can choose optimal strategies. It is illustrated that optimal national abatement programmes may be far from optimal if considered from an international point of view. Several scenarios are discussed, including a reference case, full cooperation, Pareto optimality and a critical loads approach. The need for international cooperation and regional differentiation of abatement programmes is emphasised.

Unified nonlinear approach to both weak and strong-interaction problems. [heat transfer in hypersonic flow

NASA Technical Reports Server (NTRS)

Gupta, R. N.; Rodkiewicz, C. M.

1975-01-01

The numerical results are obtained for heat transfer, skin-friction, and viscous interaction induced pressure for a step-wise accelerated flat plate in hypersonic flow. In the unified approach here the results are presented for both weak and strong-interaction problems without employing any linearization scheme. With the help of the numerical method used in this work an accurate prediction of wall shear can be made for the problems with plate velocity changes of 1% or larger. The obtained results indicate that the transient contribution to the induced pressure for helium is greater than that for air.

Predictive factors for rebleeding and death in alcoholic cirrhotic patients with acute variceal bleeding: a multivariate analysis.

PubMed

Krige, Jake E J; Kotze, Urda K; Distiller, Greg; Shaw, John M; Bornman, Philippus C

2009-10-01

Bleeding from esophageal varices is a leading cause of death in alcoholic cirrhotic patients. The aim of the present single-center study was to identify risk factors predictive of variceal rebleeding and death within 6 weeks of initial treatment. Univariate and multivariate analyses were performed on 310 prospectively documented alcoholic cirrhotic patients with acute variceal hemorrhage (AVH) who underwent 786 endoscopic variceal injection treatments between January 1984 and December 2006. All injections were administered during the first 6 weeks after the patients were treated for their first variceal bleed. Seventy-five (24.2%) patients experienced a rebleed, 38 within 5 days of the initial treatment and 37 within 6 weeks of their initial treatment. Of the 15 variables studied and included in a multivariate analysis using a logistic regression model, a bilirubin level >51 mmol/l and transfusion of >6 units of blood during the initial hospital admission were predictors of variceal rebleeding within the first 6 weeks. Seventy-seven (24.8%) patients died, 29 (9.3%) within 5 days and 48 (15.4%) between 6 and 42 days after the initial treatment. Stepwise multivariate logistic regression analysis showed that six variables were predictors of death within the first 6 weeks: encephalopathy, ascites, bilirubin level >51 mmol/l, international normalized ratio (INR) >2.3, albumin <25 g/l, and the need for balloon tube tamponade. Survival was influenced by the severity of liver failure, with most deaths occurring in Child-Pugh grade C patients. Patients with AVH and encephalopathy, ascites, bilirubin levels >51 mmol/l, INR >2.3, albumin <25 g/l and who require balloon tube tamponade are at increased risk of dying within the first 6 weeks. Bilirubin levels >51 mmol/l and transfusion of >6 units of blood were predictors of variceal rebleeding.

[Discriminant analysis to predict the clinical diagnosis of primary immunodeficiencies: a preliminary report].

PubMed

Murata, Chiharu; Ramírez, Ana Belén; Ramírez, Guadalupe; Cruz, Alonso; Morales, José Luis; Lugo-Reyes, Saul Oswaldo

2015-01-01

The features in a clinical history from a patient with suspected primary immunodeficiency (PID) direct the differential diagnosis through pattern recognition. PIDs are a heterogeneous group of more than 250 congenital diseases with increased susceptibility to infection, inflammation, autoimmunity, allergy and malignancy. Linear discriminant analysis (LDA) is a multivariate supervised classification method to sort objects of study into groups by finding linear combinations of a number of variables. To identify the features that best explain membership of pediatric PID patients to a group of defect or disease. An analytic cross-sectional study was done with a pre-existing database with clinical and laboratory records from 168 patients with PID, followed at the National Institute of Pediatrics during 1991-2012, it was used to build linear discriminant models that would explain membership of each patient to the different group defects and to the most prevalent PIDs in our registry. After a preliminary run only 30 features were included (4 demographic, 10 clinical, 10 laboratory, 6 germs), with which the training models were developed through a stepwise regression algorithm. We compared the automatic feature selection with a selection made by a human expert, and then assessed the diagnostic usefulness of the resulting models (sensitivity, specificity, prediction accuracy and kappa coefficient), with 95% confidence intervals. The models incorporated 6 to 14 features to explain membership of PID patients to the five most abundant defect groups (combined, antibody, well-defined, dysregulation and phagocytosis), and to the four most prevalent PID diseases (X-linked agammaglobulinemia, chronic granulomatous disease, common variable immunodeficiency and ataxiatelangiectasia). In practically all cases of feature selection the machine outperformed the human expert. Diagnosis prediction using the equations created had a global accuracy of 83 to 94%, with sensitivity of 60 to 100%, specificity of 83 to 95% and kappa coefficient of 0.37 to 0.76. In general, the selection of features has clinical plausibility, and the practical advantage of utilizing only clinical attributes, infecting germs and routine lab results (blood cell counts and serum immunoglobulins). The performance of the model as a diagnostic tool was acceptable. The study's main limitations are a limited sample size and a lack of cross validation. This is only the first step in the construction of a machine learning system, with a wider approach that includes a larger database and different methodologies, to assist the clinical diagnosis of primary immunodeficiencies.

LFSPMC: Linear feature selection program using the probability of misclassification

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr.; Marion, B. P.

1975-01-01

The computational procedure and associated computer program for a linear feature selection technique are presented. The technique assumes that: a finite number, m, of classes exists; each class is described by an n-dimensional multivariate normal density function of its measurement vectors; the mean vector and covariance matrix for each density function are known (or can be estimated); and the a priori probability for each class is known. The technique produces a single linear combination of the original measurements which minimizes the one-dimensional probability of misclassification defined by the transformed densities.

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.

[Factors influencing glucose metabolism in young obese subjects with obstructive sleep apnea hypopnea syndrome].

PubMed

Gu, C J; Li, Q Y; Li, M; Zhou, J; Du, J; Yi, H H; Feng, J; Zhou, L N; Wang, Q

2016-05-17

To explore the factors influencing glucose metabolism in young obese subjects with obstructive sleep apnea hypopnea syndrome (OSAHS). A total of 106 young obese subjects[18-44 years old, body mass index (BMI) ≥30 kg/m(2)]were enrolled and divided into two groups based on full-night polysomnography (PSG), OSAHS group[apnea hypopnea index (AHI) ≥5 events/h]and non-OSAHS group (AHI<5 events/h). Oral glucose tolerance-insulin releasing test (OGTT-IRT) was performed and serum glycosylated hemoglobin A1 (HbA1c) levels were measured after an overnight fast. Homeostasis model assessment-IR (HOMA-IR), Matsuda insulin sensitivity index (MI), homeostasis model assessment-β (HOMA-β), the early phase insulinogenic index (ΔI(30)/ΔG(30)), total area under the curve of insulin in 180 minutes (AUC-I180) and oral disposition index (DIo) were calculated to evaluate insulin resistance and pancreatic β cell function. Stepwise multiple linear regressions were conducted to determine the independent linear correlation of glucose measurements with PSG parameters. Prevalence of diabetes was higher in OSAHS than in non-OSAHS group (22.0% vs 4.3%, P=0.009). OGTT 0, 30, 60 min glucose and HbA1c levels were higher in OSAHS group than those in non-OASHS group (all P<0.05). DIo were lower in OSAHS group than those in non-OASHS group (P=0.024), HOMA-IR, MI, HOMA-β, ΔI(30)/ΔG(30), and AUC-I(180) were similar between two groups (all P>0.05). In stepwise multiple linear regressions, OGTT 0, 30 and 60 min glucose were positively correlated with oxygen desaturation index (ODI) (β=0.243, 0.273 and 0.371 respectively, all P<0.05). HOMA-β was negatively correlated with AHI (β=-0.243, P=0.011). DIo was negatively correlated with ODI (β=-0.234, P=0.031). OSAHS worsens glucose metabolism and compensatory pancreatic β-cell function in young obese subjects, which could probably be attributed to sleep apnea related oxygen desaturation during sleep.

Rapid differentiation of Ghana cocoa beans by FT-NIR spectroscopy coupled with multivariate classification

NASA Astrophysics Data System (ADS)

Teye, Ernest; Huang, Xingyi; Dai, Huang; Chen, Quansheng

2013-10-01

Quick, accurate and reliable technique for discrimination of cocoa beans according to geographical origin is essential for quality control and traceability management. This current study presents the application of Near Infrared Spectroscopy technique and multivariate classification for the differentiation of Ghana cocoa beans. A total of 194 cocoa bean samples from seven cocoa growing regions were used. Principal component analysis (PCA) was used to extract relevant information from the spectral data and this gave visible cluster trends. The performance of four multivariate classification methods: Linear discriminant analysis (LDA), K-nearest neighbors (KNN), Back propagation artificial neural network (BPANN) and Support vector machine (SVM) were compared. The performances of the models were optimized by cross validation. The results revealed that; SVM model was superior to all the mathematical methods with a discrimination rate of 100% in both the training and prediction set after preprocessing with Mean centering (MC). BPANN had a discrimination rate of 99.23% for the training set and 96.88% for prediction set. While LDA model had 96.15% and 90.63% for the training and prediction sets respectively. KNN model had 75.01% for the training set and 72.31% for prediction set. The non-linear classification methods used were superior to the linear ones. Generally, the results revealed that NIR Spectroscopy coupled with SVM model could be used successfully to discriminate cocoa beans according to their geographical origins for effective quality assurance.

Characterizing multivariate decoding models based on correlated EEG spectral features.

PubMed

McFarland, Dennis J

2013-07-01

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

Multivariable control of the Space Shuttle Remote Manipulator System using linearization by state feedback. M.S. Thesis

NASA Technical Reports Server (NTRS)

Gettman, Chang-Ching LO

1993-01-01

This thesis develops and demonstrates an approach to nonlinear control system design using linearization by state feedback. The design provides improved transient response behavior allowing faster maneuvering of payloads by the SRMS. Modeling uncertainty is accounted for by using a second feedback loop designed around the feedback linearized dynamics. A classical feedback loop is developed to provide the easy implementation required for the relatively small on board computers. Feedback linearization also allows the use of higher bandwidth model based compensation in the outer loop, since it helps maintain stability in the presence of the nonlinearities typically neglected in model based designs.

Multivariate Time Series Decomposition into Oscillation Components.

PubMed

Matsuda, Takeru; Komaki, Fumiyasu

2017-08-01

Many time series are considered to be a superposition of several oscillation components. We have proposed a method for decomposing univariate time series into oscillation components and estimating their phases (Matsuda & Komaki, 2017 ). In this study, we extend that method to multivariate time series. We assume that several oscillators underlie the given multivariate time series and that each variable corresponds to a superposition of the projections of the oscillators. Thus, the oscillators superpose on each variable with amplitude and phase modulation. Based on this idea, we develop gaussian linear state-space models and use them to decompose the given multivariate time series. The model parameters are estimated from data using the empirical Bayes method, and the number of oscillators is determined using the Akaike information criterion. Therefore, the proposed method extracts underlying oscillators in a data-driven manner and enables investigation of phase dynamics in a given multivariate time series. Numerical results show the effectiveness of the proposed method. From monthly mean north-south sunspot number data, the proposed method reveals an interesting phase relationship.

Multivariate analysis of progressive thermal desorption coupled gas chromatography-mass spectrometry.

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

Van Benthem, Mark Hilary; Mowry, Curtis Dale; Kotula, Paul Gabriel

Thermal decomposition of poly dimethyl siloxane compounds, Sylgard{reg_sign} 184 and 186, were examined using thermal desorption coupled gas chromatography-mass spectrometry (TD/GC-MS) and multivariate analysis. This work describes a method of producing multiway data using a stepped thermal desorption. The technique involves sequentially heating a sample of the material of interest with subsequent analysis in a commercial GC/MS system. The decomposition chromatograms were analyzed using multivariate analysis tools including principal component analysis (PCA), factor rotation employing the varimax criterion, and multivariate curve resolution. The results of the analysis show seven components related to offgassing of various fractions of siloxanes that varymore » as a function of temperature. Thermal desorption coupled with gas chromatography-mass spectrometry (TD/GC-MS) is a powerful analytical technique for analyzing chemical mixtures. It has great potential in numerous analytic areas including materials analysis, sports medicine, in the detection of designer drugs; and biological research for metabolomics. Data analysis is complicated, far from automated and can result in high false positive or false negative rates. We have demonstrated a step-wise TD/GC-MS technique that removes more volatile compounds from a sample before extracting the less volatile compounds. This creates an additional dimension of separation before the GC column, while simultaneously generating three-way data. Sandia's proven multivariate analysis methods, when applied to these data, have several advantages over current commercial options. It also has demonstrated potential for success in finding and enabling identification of trace compounds. Several challenges remain, however, including understanding the sources of noise in the data, outlier detection, improving the data pretreatment and analysis methods, developing a software tool for ease of use by the chemist, and demonstrating our belief that this multivariate analysis will enable superior differentiation capabilities. In addition, noise and system artifacts challenge the analysis of GC-MS data collected on lower cost equipment, ubiquitous in commercial laboratories. This research has the potential to affect many areas of analytical chemistry including materials analysis, medical testing, and environmental surveillance. It could also provide a method to measure adsorption parameters for chemical interactions on various surfaces by measuring desorption as a function of temperature for mixtures. We have presented results of a novel method for examining offgas products of a common PDMS material. Our method involves utilizing a stepped TD/GC-MS data acquisition scheme that may be almost totally automated, coupled with multivariate analysis schemes. This method of data generation and analysis can be applied to a number of materials aging and thermal degradation studies.« less

Practical Methods for the Compensation and Control of Multivariable Systems.

DTIC Science & Technology

1982-04-01

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

Sequential design of discrete linear quadratic regulators via optimal root-locus techniques

NASA Technical Reports Server (NTRS)

Shieh, Leang S.; Yates, Robert E.; Ganesan, Sekar

1989-01-01

A sequential method employing classical root-locus techniques has been developed in order to determine the quadratic weighting matrices and discrete linear quadratic regulators of multivariable control systems. At each recursive step, an intermediate unity rank state-weighting matrix that contains some invariant eigenvectors of that open-loop matrix is assigned, and an intermediate characteristic equation of the closed-loop system containing the invariant eigenvalues is created.

A comparison of two multi-variable integrator windup protection schemes

NASA Technical Reports Server (NTRS)

Mattern, Duane

1993-01-01

Two methods are examined for limit and integrator wind-up protection for multi-input, multi-output linear controllers subject to actuator constraints. The methods begin with an existing linear controller that satisfies the specifications for the nominal, small perturbation, linear model of the plant. The controllers are formulated to include an additional contribution to the state derivative calculations. The first method to be examined is the multi-variable version of the single-input, single-output, high gain, Conventional Anti-Windup (CAW) scheme. Except for the actuator limits, the CAW scheme is linear. The second scheme to be examined, denoted the Modified Anti-Windup (MAW) scheme, uses a scalar to modify the magnitude of the controller output vector while maintaining the vector direction. The calculation of the scalar modifier is a nonlinear function of the controller outputs and the actuator limits. In both cases the constrained actuator is tracked. These two integrator windup protection methods are demonstrated on a turbofan engine control system with five measurements, four control variables, and four actuators. The closed-loop responses of the two schemes are compared and contrasted during limit operation. The issue of maintaining the direction of the controller output vector using the Modified Anti-Windup scheme is discussed and the advantages and disadvantages of both of the IWP methods are presented.

Clinical and laboratory factors associated with mortality in dengue.

PubMed

Saroch, Atul; Arya, Vivek; Sinha, Nitin; Taneja, R S; Sahai, Pooja; Mahajan, R K

2017-04-01

Dengue is endemic in more than 100 countries, giving rise to an increased number of deaths in the last five years in the South-East Asian region. We report our findings from a retrospective study of adults admitted with confirmed dengue at our institution. We studied the clinical and laboratory parameters associated with mortality in these patients. Of the 172 hospitalised patients studied, 156 (90.69 %) recovered while 16 (9.3%) died. Univariate analysis showed altered sensorium on presentation, lower haemoglobin and haematocrit levels, higher serum creatinine, higher serum transaminase and lower serum albumin levels to be significantly associated with mortality in dengue. Further, using stepwise multivariate logistic regression, altered sensorium ( P = 0.006) and hypoalbuminemia ( P = 0.013) were identified as independent predictors of mortality in dengue. Identification of these parameters early in the course of disease should prompt intensification of treatment in dengue cases.

Alternatives for Jet Engine Control

NASA Technical Reports Server (NTRS)

Leake, R. J.; Sain, M. K.

1976-01-01

Approaches are developed as alternatives to current design methods which rely heavily on linear quadratic and Riccati equation methods. The main alternatives are discussed in two broad categories, local multivariable frequency domain methods and global nonlinear optimal methods.

Analytical methods in multivariate highway safety exposure data estimation

DOT National Transportation Integrated Search

1984-01-01

Three general analytical techniques which may be of use in : extending, enhancing, and combining highway accident exposure data are : discussed. The techniques are log-linear modelling, iterative propor : tional fitting and the expectation maximizati...

Why are we regressing?

PubMed

Jupiter, Daniel C

2012-01-01

In this first of a series of statistical methodology commentaries for the clinician, we discuss the use of multivariate linear regression. Copyright © 2012 American College of Foot and Ankle Surgeons. Published by Elsevier Inc. All rights reserved.

[Analysis of variance of repeated data measured by water maze with SPSS].

PubMed

Qiu, Hong; Jin, Guo-qin; Jin, Ru-feng; Zhao, Wei-kang

2007-01-01

To introduce the method of analyzing repeated data measured by water maze with SPSS 11.0, and offer a reference statistical method to clinical and basic medicine researchers who take the design of repeated measures. Using repeated measures and multivariate analysis of variance (ANOVA) process of the general linear model in SPSS and giving comparison among different groups and different measure time pairwise. Firstly, Mauchly's test of sphericity should be used to judge whether there were relations among the repeatedly measured data. If any (P

On the Bayesian Treed Multivariate Gaussian Process with Linear Model of Coregionalization

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

Konomi, Bledar A.; Karagiannis, Georgios; Lin, Guang

2015-02-01

The Bayesian treed Gaussian process (BTGP) has gained popularity in recent years because it provides a straightforward mechanism for modeling non-stationary data and can alleviate computational demands by fitting models to less data. The extension of BTGP to the multivariate setting requires us to model the cross-covariance and to propose efficient algorithms that can deal with trans-dimensional MCMC moves. In this paper we extend the cross-covariance of the Bayesian treed multivariate Gaussian process (BTMGP) to that of linear model of Coregionalization (LMC) cross-covariances. Different strategies have been developed to improve the MCMC mixing and invert smaller matrices in the Bayesianmore » inference. Moreover, we compare the proposed BTMGP with existing multiple BTGP and BTMGP in test cases and multiphase flow computer experiment in a full scale regenerator of a carbon capture unit. The use of the BTMGP with LMC cross-covariance helped to predict the computer experiments relatively better than existing competitors. The proposed model has a wide variety of applications, such as computer experiments and environmental data. In the case of computer experiments we also develop an adaptive sampling strategy for the BTMGP with LMC cross-covariance function.« less

Patient satisfaction in Dental Healthcare Centers.

PubMed

Ali, Dena A

2016-01-01

This study aimed to (1) measure the degree of patient satisfaction among the clinical and nonclinical dental services offered at specialty dental centers and (2) investigate the factors associated with the degree of overall satisfaction. Four hundred and ninety-seven participants from five dental centers were recruited for this study. Each participant completed a self-administered questionnaire to measure patient satisfaction with clinical and nonclinical dental services. Analysis of variance, t-tests, a general linear model, and stepwise regression analysis was applied. The respondents were generally satisfied, but internal differences were observed. The exhibited highest satisfaction with the dentists' performance, followed by the dental assistants' services, and the lowest satisfaction with the center's physical appearance and accessibility. Females, participants with less than a bachelor's degree, and younger individuals were more satisfied with the clinical and nonclinical dental services. The stepwise regression analysis revealed that the coefficient of determination (R (2)) was 40.4%. The patient satisfaction with the performance of the dentists explained 42.6% of the overall satisfaction, whereas their satisfaction with the clinical setting explained 31.5% of the overall satisfaction. Additional improvements with regard to the accessibility and physical appearance of the dental centers are needed. In addition, interventions regarding accessibility, particularly when booking an appointment, are required.

Stochastic optimal operation of reservoirs based on copula functions

NASA Astrophysics Data System (ADS)

Lei, Xiao-hui; Tan, Qiao-feng; Wang, Xu; Wang, Hao; Wen, Xin; Wang, Chao; Zhang, Jing-wen

2018-02-01

Stochastic dynamic programming (SDP) has been widely used to derive operating policies for reservoirs considering streamflow uncertainties. In SDP, there is a need to calculate the transition probability matrix more accurately and efficiently in order to improve the economic benefit of reservoir operation. In this study, we proposed a stochastic optimization model for hydropower generation reservoirs, in which 1) the transition probability matrix was calculated based on copula functions; and 2) the value function of the last period was calculated by stepwise iteration. Firstly, the marginal distribution of stochastic inflow in each period was built and the joint distributions of adjacent periods were obtained using the three members of the Archimedean copulas, based on which the conditional probability formula was derived. Then, the value in the last period was calculated by a simple recursive equation with the proposed stepwise iteration method and the value function was fitted with a linear regression model. These improvements were incorporated into the classic SDP and applied to the case study in Ertan reservoir, China. The results show that the transition probability matrix can be more easily and accurately obtained by the proposed copula function based method than conventional methods based on the observed or synthetic streamflow series, and the reservoir operation benefit can also be increased.

Quantifying Parkinson's disease finger-tapping severity by extracting and synthesizing finger motion properties.

PubMed

Sano, Yuko; Kandori, Akihiko; Shima, Keisuke; Yamaguchi, Yuki; Tsuji, Toshio; Noda, Masafumi; Higashikawa, Fumiko; Yokoe, Masaru; Sakoda, Saburo

2016-06-01

We propose a novel index of Parkinson's disease (PD) finger-tapping severity, called "PDFTsi," for quantifying the severity of symptoms related to the finger tapping of PD patients with high accuracy. To validate the efficacy of PDFTsi, the finger-tapping movements of normal controls and PD patients were measured by using magnetic sensors, and 21 characteristics were extracted from the finger-tapping waveforms. To distinguish motor deterioration due to PD from that due to aging, the aging effect on finger tapping was removed from these characteristics. Principal component analysis (PCA) was applied to the age-normalized characteristics, and principal components that represented the motion properties of finger tapping were calculated. Multiple linear regression (MLR) with stepwise variable selection was applied to the principal components, and PDFTsi was calculated. The calculated PDFTsi indicates that PDFTsi has a high estimation ability, namely a mean square error of 0.45. The estimation ability of PDFTsi is higher than that of the alternative method, MLR with stepwise regression selection without PCA, namely a mean square error of 1.30. This result suggests that PDFTsi can quantify PD finger-tapping severity accurately. Furthermore, the result of interpreting a model for calculating PDFTsi indicated that motion wideness and rhythm disorder are important for estimating PD finger-tapping severity.

Patient satisfaction in Dental Healthcare Centers

PubMed Central

Ali, Dena A.

2016-01-01

Objectives: This study aimed to (1) measure the degree of patient satisfaction among the clinical and nonclinical dental services offered at specialty dental centers and (2) investigate the factors associated with the degree of overall satisfaction. Materials and Methods: Four hundred and ninety-seven participants from five dental centers were recruited for this study. Each participant completed a self-administered questionnaire to measure patient satisfaction with clinical and nonclinical dental services. Analysis of variance, t-tests, a general linear model, and stepwise regression analysis was applied. Results: The respondents were generally satisfied, but internal differences were observed. The exhibited highest satisfaction with the dentists’ performance, followed by the dental assistants’ services, and the lowest satisfaction with the center's physical appearance and accessibility. Females, participants with less than a bachelor's degree, and younger individuals were more satisfied with the clinical and nonclinical dental services. The stepwise regression analysis revealed that the coefficient of determination (R2) was 40.4%. The patient satisfaction with the performance of the dentists explained 42.6% of the overall satisfaction, whereas their satisfaction with the clinical setting explained 31.5% of the overall satisfaction. Conclusion: Additional improvements with regard to the accessibility and physical appearance of the dental centers are needed. In addition, interventions regarding accessibility, particularly when booking an appointment, are required. PMID:27403045

The Alkaline Hydrolysis of Sulfonate Esters: Challenges in Interpreting Experimental and Theoretical Data

PubMed Central

2013-01-01

Sulfonate ester hydrolysis has been the subject of recent debate, with experimental evidence interpreted in terms of both stepwise and concerted mechanisms. In particular, a recent study of the alkaline hydrolysis of a series of benzene arylsulfonates (Babtie et al., Org. Biomol. Chem.10, 2012, 8095) presented a nonlinear Brønsted plot, which was explained in terms of a change from a stepwise mechanism involving a pentavalent intermediate for poorer leaving groups to a fully concerted mechanism for good leaving groups and supported by a theoretical study. In the present work, we have performed a detailed computational study of the hydrolysis of these compounds and find no computational evidence for a thermodynamically stable intermediate for any of these compounds. Additionally, we have extended the experimental data to include pyridine-3-yl benzene sulfonate and its N-oxide and N-methylpyridinium derivatives. Inclusion of these compounds converts the Brønsted plot to a moderately scattered but linear correlation and gives a very good Hammett correlation. These data suggest a concerted pathway for this reaction that proceeds via an early transition state with little bond cleavage to the leaving group, highlighting the care that needs to be taken with the interpretation of experimental and especially theoretical data. PMID:24279349

Multielement fingerprinting as a tool in origin authentication of PGI food products: Tropea red onion.

PubMed

Furia, Emilia; Naccarato, Attilio; Sindona, Giovanni; Stabile, Gaetano; Tagarelli, Antonio

2011-08-10

Tropea red onion ( Allium cepa L. var. Tropea) is among the most highly appreciated Italian products. It is cultivated in specific areas of Calabria and, due to its characteristics, was recently awarded with the protected geographical indications (PGI) certification from the European Union. A reliable classification of onion samples in groups corresponding to "Tropea" and "non-Tropea" categories is now available to the producers. This important goal has been achieved through the evaluation of three supervised chemometric approaches. Onion samples with PGI brand (120) and onion samples not cultivated following the production regulations (80) were digested by a closed-vessel microwave oven system. ICP-MS equipped with a dynamic reaction cell was used to determine the concentrations of 25 elements (Al, Ba, Ca, Cd, Ce, Cr, Dy, Eu, Fe, Ga, Gd, Ho, La, Mg, Mn, Na, Nd, Ni, Pr, Rb, Sm, Sr, Tl, Y, and Zn). The multielement fingerprint was processed using linear discriminant analysis (LDA) (standard and stepwise), soft independent modeling of class analogy (SIMCA), and back-propagation artificial neural network (BP-ANN). The cross-validation procedure has shown good results in terms of the prediction ability for all of the chemometric models: standard LDA, 94.0%; stepwise LDA, 94.5%; SIMCA, 95.5%; and BP-ANN, 91.5%.

Validation of a Statistical Methodology for Extracting Vegetation Feedbacks: Focus on North African Ecosystems in the Community Earth System Model

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

Yu, Yan; Notaro, Michael; Wang, Fuyao

Generalized equilibrium feedback assessment (GEFA) is a potentially valuable multivariate statistical tool for extracting vegetation feedbacks to the atmosphere in either observations or coupled Earth system models. The reliability of GEFA at capturing the terrestrial impacts on regional climate is demonstrated in this paper using the National Center for Atmospheric Research Community Earth System Model (CESM), with focus on North Africa. The feedback is assessed statistically by applying GEFA to output from a fully coupled control run. To reduce the sampling error caused by short data records, the traditional or full GEFA is refined through stepwise GEFA by dropping unimportantmore » forcings. Two ensembles of dynamical experiments are developed for the Sahel or West African monsoon region against which GEFA-based vegetation feedbacks are evaluated. In these dynamical experiments, regional leaf area index (LAI) is modified either alone or in conjunction with soil moisture, with the latter runs motivated by strong regional soil moisture–LAI coupling. Stepwise GEFA boasts higher consistency between statistically and dynamically assessed atmospheric responses to land surface anomalies than full GEFA, especially with short data records. GEFA-based atmospheric responses are more consistent with the coupled soil moisture–LAI experiments, indicating that GEFA is assessing the combined impacts of coupled vegetation and soil moisture. Finally, both the statistical and dynamical assessments reveal a negative vegetation–rainfall feedback in the Sahel associated with an atmospheric stability mechanism in CESM versus a weaker positive feedback in the West African monsoon region associated with a moisture recycling mechanism in CESM.« less

Validation of a Statistical Methodology for Extracting Vegetation Feedbacks: Focus on North African Ecosystems in the Community Earth System Model

DOE PAGES

Yu, Yan; Notaro, Michael; Wang, Fuyao; ...

2018-02-05

Generalized equilibrium feedback assessment (GEFA) is a potentially valuable multivariate statistical tool for extracting vegetation feedbacks to the atmosphere in either observations or coupled Earth system models. The reliability of GEFA at capturing the terrestrial impacts on regional climate is demonstrated in this paper using the National Center for Atmospheric Research Community Earth System Model (CESM), with focus on North Africa. The feedback is assessed statistically by applying GEFA to output from a fully coupled control run. To reduce the sampling error caused by short data records, the traditional or full GEFA is refined through stepwise GEFA by dropping unimportantmore » forcings. Two ensembles of dynamical experiments are developed for the Sahel or West African monsoon region against which GEFA-based vegetation feedbacks are evaluated. In these dynamical experiments, regional leaf area index (LAI) is modified either alone or in conjunction with soil moisture, with the latter runs motivated by strong regional soil moisture–LAI coupling. Stepwise GEFA boasts higher consistency between statistically and dynamically assessed atmospheric responses to land surface anomalies than full GEFA, especially with short data records. GEFA-based atmospheric responses are more consistent with the coupled soil moisture–LAI experiments, indicating that GEFA is assessing the combined impacts of coupled vegetation and soil moisture. Finally, both the statistical and dynamical assessments reveal a negative vegetation–rainfall feedback in the Sahel associated with an atmospheric stability mechanism in CESM versus a weaker positive feedback in the West African monsoon region associated with a moisture recycling mechanism in CESM.« less

MIDAS: Regionally linear multivariate discriminative statistical mapping.

PubMed

Varol, Erdem; Sotiras, Aristeidis; Davatzikos, Christos

2018-07-01

Statistical parametric maps formed via voxel-wise mass-univariate tests, such as the general linear model, are commonly used to test hypotheses about regionally specific effects in neuroimaging cross-sectional studies where each subject is represented by a single image. Despite being informative, these techniques remain limited as they ignore multivariate relationships in the data. Most importantly, the commonly employed local Gaussian smoothing, which is important for accounting for registration errors and making the data follow Gaussian distributions, is usually chosen in an ad hoc fashion. Thus, it is often suboptimal for the task of detecting group differences and correlations with non-imaging variables. Information mapping techniques, such as searchlight, which use pattern classifiers to exploit multivariate information and obtain more powerful statistical maps, have become increasingly popular in recent years. However, existing methods may lead to important interpretation errors in practice (i.e., misidentifying a cluster as informative, or failing to detect truly informative voxels), while often being computationally expensive. To address these issues, we introduce a novel efficient multivariate statistical framework for cross-sectional studies, termed MIDAS, seeking highly sensitive and specific voxel-wise brain maps, while leveraging the power of regional discriminant analysis. In MIDAS, locally linear discriminative learning is applied to estimate the pattern that best discriminates between two groups, or predicts a variable of interest. This pattern is equivalent to local filtering by an optimal kernel whose coefficients are the weights of the linear discriminant. By composing information from all neighborhoods that contain a given voxel, MIDAS produces a statistic that collectively reflects the contribution of the voxel to the regional classifiers as well as the discriminative power of the classifiers. Critically, MIDAS efficiently assesses the statistical significance of the derived statistic by analytically approximating its null distribution without the need for computationally expensive permutation tests. The proposed framework was extensively validated using simulated atrophy in structural magnetic resonance imaging (MRI) and further tested using data from a task-based functional MRI study as well as a structural MRI study of cognitive performance. The performance of the proposed framework was evaluated against standard voxel-wise general linear models and other information mapping methods. The experimental results showed that MIDAS achieves relatively higher sensitivity and specificity in detecting group differences. Together, our results demonstrate the potential of the proposed approach to efficiently map effects of interest in both structural and functional data. Copyright © 2018. Published by Elsevier Inc.

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

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

Prognostic Impact of the 6th and 7th American Joint Committee on Cancer TNM Staging Systems on Esophageal Cancer Patients Treated With Chemoradiotherapy

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

Nomura, Motoo, E-mail: excell@hkg.odn.ne.jp; Department of Radiation Oncology, Aichi Cancer Center Hospital; Shitara, Kohei

2012-02-01

Purpose: The new 7th edition of the American Joint Committee on Cancer TNM staging system is based on pathologic data from esophageal cancers treated by surgery alone. There is no information available on evaluation of the new staging system with regard to prognosis of patients treated with chemoradiotherapy (CRT). The objective of this study was to evaluate the prognostic impact of the new staging system on esophageal cancer patients treated with CRT. Methods and Materials: A retrospective review was performed on 301 consecutive esophageal squamous cell carcinoma patients treated with CRT. Comparisons were made of the prognostic impacts of themore » 6th and 7th staging systems and the prognostic impacts of stage and prognostic groups, which were newly defined in the 7th edition. Results: There were significant differences between Stages I and III (p < 0.01) according to both editions. However, the 7th edition poorly distinguishes the prognoses of Stages III and IV (p = 0.36 by multivariate analysis) in comparison to the 6th edition (p = 0.08 by multivariate analysis), although these differences were not significant. For all patients, T, M, and gender were independent prognostic factors by multivariate analysis (p < 0.05). For the Stage I and II prognostic groups, survival curves showed a stepwise decrease with increase in stage, except for Stage IIA. However, there were no significant differences seen between each prognostic stage. Conclusions: Our study indicates there are several problems with the 7th TNM staging system regarding prognostic factors in patients undergoing CRT.« less

Type 2 diabetes is an independent negative prognostic factor in patients undergoing surgical resection of a WHO grade I meningioma.

PubMed

Nayeri, Arash; Chotai, Silky; Prablek, Marc A; Brinson, Philip R; Douleh, Diana G; Weaver, Kyle D; Thompson, Reid C; Chambless, Lola

2016-10-01

In recent years, there has been increased recognition of the relationship between type 2 diabetes mellitus (DM) and poor outcomes following a variety of surgical procedures. We sought to study the role of type 2 DM as a prognostic factor affecting the long-term survival of patients undergoing surgical resection of a WHO Grade I meningioma. We conducted a retrospective cohort study on 196 patients who had a WHO Grade I meningioma resected at our institution between 2001 and 2013. The medical record was reviewed to identify a pre-existing diagnosis of type 2 DM. Patient mortality was reviewed by medical record and Social Security Death Index (SSDI). Variables associated with survival in a univariate analysis were included in the multivariate Cox model if P<0.10. Variables with probability values >0.05 were then removed from the multivariate model in a step-wise fashion. 33 (17%) patients had pre-existing diagnoses of type 2 DM prior to clinical presentation. Mean survival time in diabetic patients was 52.1 months compared to 160.9 months in non-diabetics. The decreased survival rate and time in patients with type 2 DM were found to be statistically significant (p=0.008 and p<0.0001, respectively). In a multivariate Cox analysis, a pre-existing history of type 2 DM was independently associated with decreased survival following the resection of a WHO Grade I meningioma (HR=2.6, p=0.045). A pre-existing diagnosis of type 2 DM is an independent negative prognostic indicator following the resection of a WHO Grade I meningioma. Copyright © 2016 Elsevier B.V. All rights reserved.

Anal sphincter lacerations and upright delivery postures--a risk analysis from a randomized controlled trial.

PubMed

Altman, Daniel; Ragnar, Inga; Ekström, Asa; Tydén, Tanja; Olsson, Sven-Eric

2007-02-01

To evaluate obstetric sphincter lacerations after a kneeling or sitting position at second stage of labor in a multivariate risk analysis model. Two hundred and seventy-one primiparous women with normal pregnancies and spontaneous labor were randomized, 138 to a kneeling position and 133 to a sitting position. Medical data were retrieved from delivery charts and partograms. Risk factors were tested in a multivariate logistic regression model in a stepwise manner. The trial was completed by 106 subjects in the kneeling group and 112 subjects in the sitting group. There were no significant differences with regard to duration of second stage of labor or pre-trial maternal characteristics between the two groups. Obstetrical sphincter tears did not differ significantly between the two groups but an intact perineum was more common in the kneeling group (p<0.03) and episiotomy (mediolateral) was more common in the sitting group (p<0.05). Three grade IV sphincter lacerations occurred in the sitting group compared to none in the kneeling group (NS). Multivariate risk analysis indicated that prolonged duration of second stage of labor and episiotomy were associated with an increased risk of third- or fourth-degree sphincter tears (p<0.01 and p<0.05, respectively). Delivery posture, maternal age, fetal weight, use of oxytocin, and use of epidural analgesia did not increase the risk of obstetrical anal sphincter lacerations in the two upright postures. Obstetrical anal sphincter lacerations did not differ significantly between a kneeling or sitting upright delivery posture. Episiotomy was more common after a sitting delivery posture, which may be associated with an increased risk of anal sphincter lacerations. Upright delivery postures may be encouraged in healthy women with normal, full-term pregnancy.

Relations of insulin resistance and glycemic abnormalities to cardiovascular magnetic resonance measures of cardiac structure and function: the Framingham Heart Study.

PubMed

Velagaleti, Raghava S; Gona, Philimon; Chuang, Michael L; Salton, Carol J; Fox, Caroline S; Blease, Susan J; Yeon, Susan B; Manning, Warren J; O'Donnell, Christopher J

2010-05-01

Data regarding the relationships of diabetes, insulin resistance, and subclinical hyperinsulinemia/hyperglycemia with cardiac structure and function are conflicting. We sought to apply volumetric cardiovascular magnetic resonance (CMR) in a free-living cohort to potentially clarify these associations. A total of 1603 Framingham Heart Study Offspring participants (age, 64+/-9 years; 55% women) underwent CMR to determine left ventricular mass (LVM), LVM to end-diastolic volume ratio (LVM/LVEDV), relative wall thickness (RWT), ejection fraction, cardiac output, and left atrial size. Data regarding insulin resistance (homeostasis model, HOMA-IR) and glycemia categories (normal, impaired insulinemia or glycemia, prediabetes, and diabetes) were determined. In a subgroup (253 men, 290 women) that underwent oral glucose tolerance testing, we related 2-hour insulin and glucose with CMR measures. In both men and women, all age-adjusted CMR measures increased across HOMA-IR quartiles, but multivariable-adjusted trends were significant only for LVM/ht(2.7) and LVM/LVEDV. LVM/LVEDV and RWT were higher in participants with prediabetes and diabetes (in both sexes) in age-adjusted models, but these associations remained significant after multivariable adjustment only in men. LVM/LVEDV was significantly associated with 2-hour insulin in men only, and RWT was significantly associated with 2-hour glucose in women only. In multivariable stepwise selection analyses, the inclusion of body mass index led to a loss in statistical significance. Although insulin and glucose indices are associated with abnormalities in cardiac structure, insulin resistance and worsening glycemia are consistently and independently associated with LVM/LVEDV. These data implicate hyperglycemia and insulin resistance in concentric LV remodeling.

Relations of Insulin Resistance and Glycemic Abnormalities to Cardiovascular Magnetic Resonance Measures of Cardiac Structure and Function: the Framingham Heart Study

PubMed Central

Velagaleti, Raghava S.; Gona, Philimon; Chuang, Michael L.; Salton, Carol J.; Fox, Caroline S.; Blease, Susan J.; Yeon, Susan B.; Manning, Warren J.; O’Donnell, Christopher J.

2011-01-01

Background Data regarding the relationships of diabetes, insulin resistance and sub-clinical hyperinsulinemia/hyperglycemia with cardiac structure and function are conflicting. We sought to apply volumetric cardiovascular magnetic resonance (CMR) in a free-living cohort to potentially clarify these associations. Methods and Results A total of 1603 Framingham Heart Study Offspring participants (age 64±9 years; 55% women) underwent CMR to determine left ventricular mass (LVM), LVM to end-diastolic volume ratio (LVM/LVEDV), relative wall thickness (RWT), ejection fraction (EF), cardiac output (CO) and left atrial size (LAD). Data regarding insulin resistance (homeostasis model, HOMA-IR) and glycemia categories (normal, impaired insulinemia or glycemia, pre-diabetes and diabetes) were determined. In a subgroup (253 men, 290 women) that underwent oral glucose tolerance testing, we related 2-hr insulin and glucose with CMR measures. In both men and women, all age-adjusted CMR measures increased across HOMA-IR quartiles, but multivariable-adjusted trends were significant only for LVM/ht2.7 and LVM/LVEDV. LVM/LVEDV and RWT were higher in participants with pre-diabetes and diabetes (in both sexes) in age-adjusted models, but these associations remained significant after multivariable-adjustment only in men. LVM/LVEDV was significantly associated with 2-hr insulin in men only, and RWT was significantly associated with 2-hr glucose in women only. In multivariable stepwise selection analyses, the inclusion of BMI led to a loss in statistical significance. Conclusions While insulin and glucose indices are associated with abnormalities in cardiac structure, insulin resistance and worsening glycemia are consistently and independently associated with LVM/LVEDV. These data implicate hyperglycemia and insulin resistance in concentric LV remodeling. PMID:20208015

MAOA, MTHFR, and TNF-β genes polymorphisms and personality traits in the pathogenesis of migraine.

PubMed

Ishii, Masakazu; Shimizu, Shunichi; Sakairi, Yuki; Nagamine, Ayumu; Naito, Yuika; Hosaka, Yukiko; Naito, Yuko; Kurihara, Tatsuya; Onaya, Tomomi; Oyamada, Hideto; Imagawa, Atsuko; Shida, Kenji; Takahashi, Johji; Oguchi, Katsuji; Masuda, Yutaka; Hara, Hajime; Usami, Shino; Kiuchi, Yuji

2012-04-01

Migraine is a multifactorial disease with various factors, such as genetic polymorphisms and personality traits, but the contribution of those factors is not clear. To clarify the pathogenesis of migraine, the contributions of genetic polymorphisms and personality traits were simultaneously investigated using multivariate analysis. Ninety-one migraine patients and 119 non-headache healthy volunteers were enrolled. The 12 gene polymorphisms analysis and NEO-FFI personality test were performed. At first, the univariate analysis was performed to extract the contributing factors to pathogenesis of migraine. We then extracted the factors that independently contributed to the pathogenesis of migraine using multivariate stepwise logistic regression analysis. Using the multivariate analysis, three gene polymorphisms including monoamine oxidase A (MAOA) T941G, methylenetetrahydrofolate reductase (MTHFR) C677T, and tumor necrosis factor beta (TNF-β) G252Α, and the neuroticism and conscientiousness scores in NEO-FFI were selected as significant factors that independently contributed to the pathogenesis of migraine. Their odds ratios were 1.099 (per point of neuroticism score), 1.080 (per point of conscientiousness score), 2.272 (T and T/T or T/G vs G and G/G genotype of MAOA), 1.939 (C/T or T/T vs C/C genotype of MTHFR), and 2.748 (G/A or A/A vs G/G genotype of TNF-β), respectively. We suggested that multiple factors, such as gene polymorphisms and personality traits, contribute to the pathogenesis of migraine. The contribution of polymorphisms, such as MAOA T941G, MTHFR C677T, and TNF-β G252A, were more important than personality traits in the pathogenesis of migraine, a multifactorial disorder.

Molecular Classification Substitutes for the Prognostic Variables Stage, Age, and MYCN Status in Neuroblastoma Risk Assessment.

PubMed

Rosswog, Carolina; Schmidt, Rene; Oberthuer, André; Juraeva, Dilafruz; Brors, Benedikt; Engesser, Anne; Kahlert, Yvonne; Volland, Ruth; Bartenhagen, Christoph; Simon, Thorsten; Berthold, Frank; Hero, Barbara; Faldum, Andreas; Fischer, Matthias

2017-12-01

Current risk stratification systems for neuroblastoma patients consider clinical, histopathological, and genetic variables, and additional prognostic markers have been proposed in recent years. We here sought to select highly informative covariates in a multistep strategy based on consecutive Cox regression models, resulting in a risk score that integrates hazard ratios of prognostic variables. A cohort of 695 neuroblastoma patients was divided into a discovery set (n=75) for multigene predictor generation, a training set (n=411) for risk score development, and a validation set (n=209). Relevant prognostic variables were identified by stepwise multivariable L1-penalized least absolute shrinkage and selection operator (LASSO) Cox regression, followed by backward selection in multivariable Cox regression, and then integrated into a novel risk score. The variables stage, age, MYCN status, and two multigene predictors, NB-th24 and NB-th44, were selected as independent prognostic markers by LASSO Cox regression analysis. Following backward selection, only the multigene predictors were retained in the final model. Integration of these classifiers in a risk scoring system distinguished three patient subgroups that differed substantially in their outcome. The scoring system discriminated patients with diverging outcome in the validation cohort (5-year event-free survival, 84.9±3.4 vs 63.6±14.5 vs 31.0±5.4; P<.001), and its prognostic value was validated by multivariable analysis. We here propose a translational strategy for developing risk assessment systems based on hazard ratios of relevant prognostic variables. Our final neuroblastoma risk score comprised two multigene predictors only, supporting the notion that molecular properties of the tumor cells strongly impact clinical courses of neuroblastoma patients. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

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

PubMed Central

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

2015-01-01

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

Linear solvation energy relationship for the adsorption of synthetic organic compounds on single-walled carbon nanotubes in water.

PubMed

Ding, H; Chen, C; Zhang, X

2016-01-01

The linear solvation energy relationship (LSER) was applied to predict the adsorption coefficient (K) of synthetic organic compounds (SOCs) on single-walled carbon nanotubes (SWCNTs). A total of 40 log K values were used to develop and validate the LSER model. The adsorption data for 34 SOCs were collected from 13 published articles and the other six were obtained in our experiment. The optimal model composed of four descriptors was developed by a stepwise multiple linear regression (MLR) method. The adjusted r(2) (r(2)adj) and root mean square error (RMSE) were 0.84 and 0.49, respectively, indicating good fitness. The leave-one-out cross-validation Q(2) ([Formula: see text]) was 0.79, suggesting the robustness of the model was satisfactory. The external Q(2) ([Formula: see text]) and RMSE (RMSEext) were 0.72 and 0.50, respectively, showing the model's strong predictive ability. Hydrogen bond donating interaction (bB) and cavity formation and dispersion interactions (vV) stood out as the two most influential factors controlling the adsorption of SOCs onto SWCNTs. The equilibrium concentration would affect the fitness and predictive ability of the model, while the coefficients varied slightly.

Comparing Different Approaches for Mapping Urban Vegetation Cover from Landsat ETM+ Data: A Case Study on Brussels

PubMed Central

Van de Voorde, Tim; Vlaeminck, Jeroen; Canters, Frank

2008-01-01

Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city's inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP) at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing. PMID:27879914

Developing a multipoint titration method with a variable dose implementation for anaerobic digestion monitoring.

PubMed

Salonen, K; Leisola, M; Eerikäinen, T

2009-01-01

Determination of metabolites from an anaerobic digester with an acid base titration is considered as superior method for many reasons. This paper describes a practical at line compatible multipoint titration method. The titration procedure was improved by speed and data quality. A simple and novel control algorithm for estimating a variable titrant dose was derived for this purpose. This non-linear PI-controller like algorithm does not require any preliminary information from sample. Performance of this controller is superior compared to traditional linear PI-controllers. In addition, simplification for presenting polyprotic acids as a sum of multiple monoprotic acids is introduced along with a mathematical error examination. A method for inclusion of the ionic strength effect with stepwise iteration is shown. The titration model is presented with matrix notations enabling simple computation of all concentration estimates. All methods and algorithms are illustrated in the experimental part. A linear correlation better than 0.999 was obtained for both acetate and phosphate used as model compounds with slopes of 0.98 and 1.00 and average standard deviations of 0.6% and 0.8%, respectively. Furthermore, insensitivity of the presented method for overlapping buffer capacity curves was shown.

Biomarker selection for medical diagnosis using the partial area under the ROC curve

PubMed Central

2014-01-01

Background A biomarker is usually used as a diagnostic or assessment tool in medical research. Finding an ideal biomarker is not easy and combining multiple biomarkers provides a promising alternative. Moreover, some biomarkers based on the optimal linear combination do not have enough discriminatory power. As a result, the aim of this study was to find the significant biomarkers based on the optimal linear combination maximizing the pAUC for assessment of the biomarkers. Methods Under the binormality assumption we obtain the optimal linear combination of biomarkers maximizing the partial area under the receiver operating characteristic curve (pAUC). Related statistical tests are developed for assessment of a biomarker set and of an individual biomarker. Stepwise biomarker selections are introduced to identify those biomarkers of statistical significance. Results The results of simulation study and three real examples, Duchenne Muscular Dystrophy disease, heart disease, and breast tissue example are used to show that our methods are most suitable biomarker selection for the data sets of a moderate number of biomarkers. Conclusions Our proposed biomarker selection approaches can be used to find the significant biomarkers based on hypothesis testing. PMID:24410929

Step-wise refolding of recombinant proteins.

PubMed

Tsumoto, Kouhei; Arakawa, Tsutomu; Chen, Linda

2010-04-01

Protein refolding is still on trial-and-error basis. Here we describe step-wise dialysis refolding, in which denaturant concentration is altered in step-wise fashion. This technology controls the folding pathway by adjusting the concentrations of the denaturant and other solvent additives to induce sequential folding or disulfide formation.

Adam Smith in the Mathematics Classroom

ERIC Educational Resources Information Center

Lipsey, Sally I.

1975-01-01

The author describes a series of current economic ideas and situations which can be used in the mathematics classroom to illustrate the use of signed numbers, the coordinate system, univariate and multivariate functions, linear programing, and variation. (SD)

Linear Multivariable Regression Models for Prediction of Eddy Dissipation Rate from Available Meteorological Data

NASA Technical Reports Server (NTRS)

MCKissick, Burnell T. (Technical Monitor); Plassman, Gerald E.; Mall, Gerald H.; Quagliano, John R.

2005-01-01

Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.

Compulsive buying: Earlier illicit drug use, impulse buying, depression, and adult ADHD symptoms.

PubMed

Brook, Judith S; Zhang, Chenshu; Brook, David W; Leukefeld, Carl G

2015-08-30

This longitudinal study examined the association between psychosocial antecedents, including illicit drug use, and adult compulsive buying (CB) across a 29-year time period from mean age 14 to mean age 43. Participants originally came from a community-based random sample of residents in two upstate New York counties. Multivariate linear regression analysis was used to study the relationship between the participant's earlier psychosocial antecedents and adult CB in the fifth decade of life. The results of the multivariate linear regression analyses showed that gender (female), earlier adult impulse buying (IB), depressive mood, illicit drug use, and concurrent ADHD symptoms were all significantly associated with adult CB at mean age 43. It is important that clinicians treating CB in adults should consider the role of drug use, symptoms of ADHD, IB, depression, and family factors in CB. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Compulsive Buying: Earlier Illicit Drug Use, Impulse Buying, Depression, and Adult ADHD Symptoms

PubMed Central

Brook, Judith S.; Zhang, Chenshu; Brook, David W.; Leukefeld, Carl G.

2015-01-01

This longitudinal study examined the association between psychosocial antecedents, including illicit drug use, and adult compulsive buying (CB) across a 29-year time period from mean age 14 to mean age 43. Participants originally came from a community-based random sample of residents in two upstate New York counties. Multivariate linear regression analysis was used to study the relationship between the participant’s earlier psychosocial antecedents and adult CB in the fifth decade of life. The results of the multivariate linear regression analyses showed that gender (female), earlier adult impulse buying (IB), depressive mood, illicit drug use, and concurrent ADHD symptoms were all significantly associated with adult CB at mean age 43. It is important that clinicians treating CB in adults should consider the role of drug use, symptoms of ADHD, IB, depression, and family factors in CB. PMID:26165963

Regularization with numerical extrapolation for finite and UV-divergent multi-loop integrals

NASA Astrophysics Data System (ADS)

de Doncker, E.; Yuasa, F.; Kato, K.; Ishikawa, T.; Kapenga, J.; Olagbemi, O.

2018-03-01

We give numerical integration results for Feynman loop diagrams such as those covered by Laporta (2000) and by Baikov and Chetyrkin (2010), and which may give rise to loop integrals with UV singularities. We explore automatic adaptive integration using multivariate techniques from the PARINT package for multivariate integration, as well as iterated integration with programs from the QUADPACK package, and a trapezoidal method based on a double exponential transformation. PARINT is layered over MPI (Message Passing Interface), and incorporates advanced parallel/distributed techniques including load balancing among processes that may be distributed over a cluster or a network/grid of nodes. Results are included for 2-loop vertex and box diagrams and for sets of 2-, 3- and 4-loop self-energy diagrams with or without UV terms. Numerical regularization of integrals with singular terms is achieved by linear and non-linear extrapolation methods.

Visual analysis of mass cytometry data by hierarchical stochastic neighbour embedding reveals rare cell types.

PubMed

van Unen, Vincent; Höllt, Thomas; Pezzotti, Nicola; Li, Na; Reinders, Marcel J T; Eisemann, Elmar; Koning, Frits; Vilanova, Anna; Lelieveldt, Boudewijn P F

2017-11-23

Mass cytometry allows high-resolution dissection of the cellular composition of the immune system. However, the high-dimensionality, large size, and non-linear structure of the data poses considerable challenges for the data analysis. In particular, dimensionality reduction-based techniques like t-SNE offer single-cell resolution but are limited in the number of cells that can be analyzed. Here we introduce Hierarchical Stochastic Neighbor Embedding (HSNE) for the analysis of mass cytometry data sets. HSNE constructs a hierarchy of non-linear similarities that can be interactively explored with a stepwise increase in detail up to the single-cell level. We apply HSNE to a study on gastrointestinal disorders and three other available mass cytometry data sets. We find that HSNE efficiently replicates previous observations and identifies rare cell populations that were previously missed due to downsampling. Thus, HSNE removes the scalability limit of conventional t-SNE analysis, a feature that makes it highly suitable for the analysis of massive high-dimensional data sets.

[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector].

PubMed

Li, Zhenghua; Cheng, Fansheng; Xia, Zhining

2011-01-01

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.

Pre-Stroke Weight Loss is Associated with Post-Stroke Mortality among Men in the Honolulu-Asia Aging Study

PubMed Central

Bell, Christina L.; Rantanen, Taina; Chen, Randi; Davis, James; Petrovitch, Helen; Ross, G. Webster; Masaki, Kamal

2013-01-01

Objective To examine baseline pre-stroke weight loss and post-stroke mortality among men. Design Longitudinal study of late-life pre-stroke body mass index (BMI), weight loss and BMI change (midlife to late-life), with up to 8-year incident stroke and mortality follow-up. Setting Honolulu Heart Program/Honolulu-Asia Aging Study. Participants 3,581 Japanese-American men aged 71–93 years and stroke-free at baseline. Main Outcome Measure Post-stroke Mortality: 30-day post-stroke, analyzed with stepwise multivariable logistic regression and long-term post-stroke (up to 8-year), analyzed with stepwise multivariable Cox regression. Results Weight loss (10-pound decrements) was associated with increased 30-day post-stroke mortality (aOR=1.48, 95%CI 1.14–1.92), long-term mortality after incident stroke (all types n=225, aHR=1.25, 95%CI=1.09–1.44) and long-term mortality after incident thromboembolic stroke (n=153, aHR 1.19, 95%CI-1.01–1.40). Men with overweight/obese late-life BMI (≥25kg/m2, compared to normal/underweight BMI) had increased long-term mortality after incident hemorrhagic stroke (n=54, aHR=2.27, 95%CI=1.07–4.82). Neither desirable nor excessive BMI reductions (vs. no change/increased BMI) were associated with post-stroke mortality. In the overall sample (n=3,581), nutrition factors associated with increased long-term mortality included 1) weight loss (10-pound decrements, aHR=1.15, 1.09–1.21); 2) underweight BMI (vs. normal BMI, aHR=1.76, 1.40–2.20); and 3) both desirable and excessive BMI reductions (vs. no change or gain, separate model from weight loss and BMI, aHRs=1.36–1.97, p<0.001). Conclusions Although obesity is a risk factor for stroke incidence, pre-stroke weight loss was associated with increased post-stroke (all types and thromboembolic) mortality. Overweight/obese late-life BMI was associated with increased post-hemorrhagic stroke mortality. Desirable and excessive BMI reductions were not associated with post-stroke mortality. Weight loss, underweight late-life BMI and any BMI reduction were all associated with increased long-term mortality in the overall sample. PMID:24113337

A joint modeling and estimation method for multivariate longitudinal data with mixed types of responses to analyze physical activity data generated by accelerometers.

PubMed

Li, Haocheng; Zhang, Yukun; Carroll, Raymond J; Keadle, Sarah Kozey; Sampson, Joshua N; Matthews, Charles E

2017-11-10

A mixed effect model is proposed to jointly analyze multivariate longitudinal data with continuous, proportion, count, and binary responses. The association of the variables is modeled through the correlation of random effects. We use a quasi-likelihood type approximation for nonlinear variables and transform the proposed model into a multivariate linear mixed model framework for estimation and inference. Via an extension to the EM approach, an efficient algorithm is developed to fit the model. The method is applied to physical activity data, which uses a wearable accelerometer device to measure daily movement and energy expenditure information. Our approach is also evaluated by a simulation study. Copyright © 2017 John Wiley & Sons, Ltd.

Toward the prevention of childhood undernutrition: diet diversity strategies using locally produced food can overcome gaps in nutrient supply.

PubMed

Parlesak, Alexandr; Geelhoed, Diederike; Robertson, Aileen

2014-06-01

Chronic undernutrition is prevalent in Mozambique, where children suffer from stunting, vitamin A deficiency, anemia, and other nutrition-related disorders. Complete diet formulation products (CDFPs) are increasingly promoted to prevent chronic undernutrition. Using linear programming, to investigate whether diet diversification using local foods should be prioritized in order to reduce the prevalence of chronic undernutrition. Market prices of local foods were collected in Tete City, Mozambique. Linear programming was applied to calculate the cheapest possible fully nutritious food baskets (FNFB) by stepwise addition of micronutrient-dense localfoods. Only the top quintile of Mozambican households, using average expenditure data, could afford the FNFB that was designed using linear programming from a spectrum of local standard foods. The addition of beef heart or liver, dried fish and fresh moringa leaves, before applying linear programming decreased the price by a factor of up to 2.6. As a result, the top three quintiles could afford the FNFB optimized using both diversification strategy and linear programming. CDFPs, when added to the baskets, were unable to overcome the micronutrient gaps without greatly exceeding recommended energy intakes, due to their high ratio of energy to micronutrient density. Dietary diversification strategies using local, low-cost, nutrient-dense foods can meet all micronutrient recommendations and overcome all micronutrient gaps. The success of linear programming to identify a low-cost FNFB depends entirely on the investigators' ability to select appropriate micronutrient-dense foods. CDFPs added to food baskets are unable to overcome micronutrient gaps without greatly exceeding recommended energy intake.

A constitutive model for the warp-weft coupled non-linear behavior of knitted biomedical textiles.

PubMed

Yeoman, Mark S; Reddy, Daya; Bowles, Hellmut C; Bezuidenhout, Deon; Zilla, Peter; Franz, Thomas

2010-11-01

Knitted textiles have been used in medical applications due to their high flexibility and low tendency to fray. Their mechanics have, however, received limited attention. A constitutive model for soft tissue using a strain energy function was extended, by including shear and increasing the number and order of coefficients, to represent the non-linear warp-weft coupled mechanics of coarse textile knits under uniaxial tension. The constitutive relationship was implemented in a commercial finite element package. The model and its implementation were verified and validated for uniaxial tension and simple shear using patch tests and physical test data of uniaxial tensile tests of four very different knitted fabric structures. A genetic algorithm with step-wise increase in resolution and linear reduction in range of the search space was developed for the optimization of the fabric model coefficients. The numerically predicted stress-strain curves exhibited non-linear stiffening characteristic for fabrics. For three fabrics, the predicted mechanics correlated well with physical data, at least in one principal direction (warp or weft), and moderately in the other direction. The model exhibited limitations in approximating the linear elastic behavior of the fourth fabric. With proposals to address this limitation and to incorporate time-dependent changes in the fabric mechanics associated with tissue ingrowth, the constitutive model offers a tool for the design of tissue regenerative knit textile implants. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Landscape controls on total and methyl Hg in the Upper Hudson River basin, New York, USA

USGS Publications Warehouse

Burns, Douglas A.; Riva-Murray, K.; Bradley, P.M.; Aiken, G.R.; Brigham, M.E.

2012-01-01

Approaches are needed to better predict spatial variation in riverine Hg concentrations across heterogeneous landscapes that include mountains, wetlands, and open waters. We applied multivariate linear regression to determine the landscape factors and chemical variables that best account for the spatial variation of total Hg (THg) and methyl Hg (MeHg) concentrations in 27 sub-basins across the 493 km2 upper Hudson River basin in the Adirondack Mountains of New York. THg concentrations varied by sixfold, and those of MeHg by 40-fold in synoptic samples collected at low-to-moderate flow, during spring and summer of 2006 and 2008. Bivariate linear regression relations of THg and MeHg concentrations with either percent wetland area or DOC concentrations were significant but could account for only about 1/3 of the variation in these Hg forms in summer. In contrast, multivariate linear regression relations that included metrics of (1) hydrogeomorphology, (2) riparian/wetland area, and (3) open water, explained about 66% to >90% of spatial variation in each Hg form in spring and summer samples. These metrics reflect the influence of basin morphometry and riparian soils on Hg source and transport, and the role of open water as a Hg sink. Multivariate models based solely on these landscape metrics generally accounted for as much or more of the variation in Hg concentrations than models based on chemical and physical metrics, and show great promise for identifying waters with expected high Hg concentrations in the Adirondack region and similar glaciated riverine ecosystems.

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

Penna, M.L.; Duchiade, M.P.

The authors report the results of an investigation into the possible association between air pollution and infant mortality from pneumonia in the Rio de Janeiro Metropolitan Area. This investigation employed multiple linear regression analysis (stepwise method) for infant mortality from pneumonia in 1980, including the study population's areas of residence, incomes, and pollution exposure as independent variables. With the income variable included in the regression, a statistically significant association was observed between the average annual level of particulates and infant mortality from pneumonia. While this finding should be accepted with caution, it does suggest a biological association between these variables.more » The authors' conclusion is that air quality indicators should be included in studies of acute respiratory infections in developing countries.« less

In-line metrology for roll-to-roll UV assisted nanoimprint lithography using diffractometry

NASA Astrophysics Data System (ADS)

Kreuzer, Martin; Whitworth, Guy L.; Francone, Achille; Gomis-Bresco, Jordi; Kehagias, Nikolaos; Sotomayor-Torres, Clivia M.

2018-05-01

We describe and discuss the optical design of a diffractometer to carry out in-line quality control during roll-to-roll nanoimprinting. The tool measures diffractograms in reflection geometry, through an aspheric lens to gain fast, non-invasive information of any changes to the critical dimensions of target grating structures. A stepwise tapered linear grating with constant period was fabricated in order to detect the variation in grating linewidth through diffractometry. The minimum feature change detected was ˜40 nm to a precision of 10 nm. The diffractometer was then integrated with a roll-to-roll UV assisted nanoimprint lithography machine to gain dynamic measurements in situ.

Conductance of carbon based macro-molecular structures

NASA Astrophysics Data System (ADS)

Stafström, S.; Hansson, A.; Paulsson, M.

2000-11-01

Electron transport through metallic nanotubes and stacks of wide bandgap polyaromatic hydrocarbons (PAH) are studied theoretically using the Landauer formalism. These two systems constitute examples of different types of carbon based nanostructured materials of potential use in molecular electronics. The studies are carried out for structures with finite length that bridge two contact pads. In the case of perfect metallic nanotubes, the current is observed to increase stepwise with the applied voltage and the resistance is independent on the length of the tube. In the PAH stacks, the off resonance tunneling conductance decreases exponentially with the number of molecules in the stack and shows a near linear increase with the number of carbon atoms in each molecule.

Models of subjective response to in-flight motion data

NASA Technical Reports Server (NTRS)

Rudrapatna, A. N.; Jacobson, I. D.

1973-01-01

Mathematical relationships between subjective comfort and environmental variables in an air transportation system are investigated. As a first step in model building, only the motion variables are incorporated and sensitivities are obtained using stepwise multiple regression analysis. The data for these models have been collected from commercial passenger flights. Two models are considered. In the first, subjective comfort is assumed to depend on rms values of the six-degrees-of-freedom accelerations. The second assumes a Rustenburg type human response function in obtaining frequency weighted rms accelerations, which are used in a linear model. The form of the human response function is examined and the results yield a human response weighting function for different degrees of freedom.

Prognostic Significance of Tumor Necrosis in Hilar Cholangiocarcinoma.

PubMed

Atanasov, Georgi; Schierle, Katrin; Hau, Hans-Michael; Dietel, Corinna; Krenzien, Felix; Brandl, Andreas; Wiltberger, Georg; Englisch, Julianna Paulina; Robson, Simon C; Reutzel-Selke, Anja; Pascher, Andreas; Jonas, Sven; Pratschke, Johann; Benzing, Christian; Schmelzle, Moritz

2017-02-01

Tumor necrosis and peritumoral fibrosis have both been suggested to have a prognostic value in selected solid tumors. However, little is known regarding their influence on tumor progression and prognosis in hilar cholangiocarcinoma (HC). Surgically resected tumor specimens of HC (n = 47) were analyzed for formation of necrosis and extent of peritumoral fibrosis. Tumor necrosis and grade of fibrosis were assessed histologically and correlated with clinicopathological characteristics, tumor recurrence, and patients' survival. Univariate Kaplan-Meier analysis and a stepwise multivariable Cox regression model were applied. Mild peritumoral fibrosis was evident in 12 tumor samples, moderate peritumoral fibrosis in 20, and high-grade fibrosis in 15. Necrosis was evident in 19 of 47 tumor samples. Patients with tumors characterized by necrosis showed a significantly decreased 5-year recurrence-free survival (37.9 vs. 25.7 %; p < .05) and a significantly decreased 5-year overall survival (42.6 vs. 12.4 %; p < .05), when compared with patients with tumors showing no necrosis. R status, tumor recurrence, and tumor necrosis were of prognostic value in the univariate analysis (all p < .05). Multivariate survival analysis confirmed tumor necrosis (p = .038) as the only independent prognostic variable. The assessment of tumor necrosis appears as a valuable additional prognostic tool in routine histopathological evaluation of HC. These observations might have implications for monitoring and more individualized multimodal therapeutic strategies.

Diagnostic value of history and physical examination in patients suspected of lumbosacral nerve root compression

PubMed Central

Vroomen, P; de Krom, M C T F M; Wilmink, J; Kester, A; Knottnerus, J

2002-01-01

Objective: To evaluate patient characteristics, symptoms, and examination findings in the clinical diagnosis of lumbosacral nerve root compression causing sciatica. Methods: The study involved 274 patients with pain radiating into the leg. All had a standardised clinical assessment and magnetic resonance (MR) imaging. The associations between patient characteristics, clinical findings, and lumbosacral nerve root compression on MR imaging were analysed. Results: Nerve root compression was associated with three patient characteristics, three symptoms, and four physical examination findings (paresis, absence of tendon reflexes, a positive straight leg raising test, and increased finger-floor distance). Multivariate analysis, analysing the independent diagnostic value of the tests, showed that nerve root compression was predicted by two patient characteristics, four symptoms, and two signs (increased finger-floor distance and paresis). The straight leg raise test was not predictive. The area under the curve of the receiver-operating characteristic was 0.80 for the history items. It increased to 0.83 when the physical examination items were added. Conclusions: Various clinical findings were found to be associated with nerve root compression on MR imaging. While this set of findings agrees well with those commonly used in daily practice, the tests tended to have lower sensitivity and specificity than previously reported. Stepwise multivariate analysis showed that most of the diagnostic information revealed by physical examination findings had already been revealed by the history items. PMID:11971050

Predictors of parent-adolescent communication in post-apartheid South Africa: a protective factor in adolescent sexual and reproductive health.

PubMed

Coetzee, Jenny; Dietrich, Janan; Otwombe, Kennedy; Nkala, Busi; Khunwane, Mamakiri; van der Watt, Martin; Sikkema, Kathleen J; Gray, Glenda E

2014-04-01

In the HIV context, risky sexual behaviours can be reduced through effective parent-adolescent communication. This study used the Parent Adolescent Communication Scale to determine parent-adolescent communication by ethnicity and identify predictors of high parent-adolescent communication amongst South African adolescents post-apartheid. A cross-sectional interviewer-administered survey was administered to 822 adolescents from Johannesburg, South Africa. Backward stepwise multivariate regressions were performed. The sample was predominantly Black African (62%, n = 506) and female (57%, n = 469). Of the participants, 57% (n = 471) reported high parent-adolescent communication. Multivariate regression showed that gender was a significant predictor of high parent-adolescent communication (Black African OR:1.47, CI: 1.0-2.17, Indian OR: 2.67, CI: 1.05-6.77, White OR: 2.96, CI: 1.21-7.18). Female-headed households were predictors of high parent-adolescent communication amongst Black Africans (OR:1.49, CI: 1.01-2.20), but of low parent-adolescent communication amongst Whites (OR:0.36, CI: 0.15-0.89). Overall levels of parent-adolescent communication in South Africa are low. HIV prevention programmes for South African adolescents should include information and skills regarding effective parent-adolescent communication. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Scintigraphic calf perfusion symmetry after exercise and prediction of cardiovascular events: One stone to kill two birds?

NASA Astrophysics Data System (ADS)

Tellier, Philippe; Lecouffe, Pascal; Zureik, Mahmoud

2007-02-01

BackgroundPeripheral arterial disease (PAD) is commonly associated with a high cardiovascular mortality and morbidity as a marker of plurifocal atherosclerosis. Whether exercise thallium perfusion muscular asymmetry in the legs associated with PAD has prognostic value is unknown. Such a hypothesis was evaluated in a prospective study which remains the gold standard in clinical research. Methods and resultsScintigraphic calf perfusion symmetry after exercise (SCPSE) was measured at the end of a maximal or symptom-limited treadmill exercise test in 358 patients with known or suspected coronary artery disease (CAD). During the follow-up period (mean 85.3±32.8 months), 93 cardiovascular events and deaths (incident cases) occurred. Among those incident cases, the percentage of subjects with higher SCPSE values (third tertile) was 45.2%, versus 29.1% in controls (lower tertiles) ( p=0.005). In stepwise multivariate analysis performed with the Cox proportional hazards model, previous CAD and SCPSE were the only significant independent predictors of prognosis. The multivariate relative risk of cardiovascular death or event in subjects with higher values of SCPSE was 1.94 (95% CI: 1.15-3.21; p<0.01). ConclusionsScintigraphic calf perfusion asymmetry after exercise was independently associated with incident cardiovascular events in high-risk subjects. This index, which is easily and quickly calculated, could be used for evaluation of cardiovascular risk.

Effective network inference through multivariate information transfer estimation

NASA Astrophysics Data System (ADS)

Dahlqvist, Carl-Henrik; Gnabo, Jean-Yves

2018-06-01

Network representation has steadily gained in popularity over the past decades. In many disciplines such as finance, genetics, neuroscience or human travel to cite a few, the network may not directly be observable and needs to be inferred from time-series data, leading to the issue of separating direct interactions between two entities forming the network from indirect interactions coming through its remaining part. Drawing on recent contributions proposing strategies to deal with this problem such as the so-called "global silencing" approach of Barzel and Barabasi or "network deconvolution" of Feizi et al. (2013), we propose a novel methodology to infer an effective network structure from multivariate conditional information transfers. Its core principal is to test the information transfer between two nodes through a step-wise approach by conditioning the transfer for each pair on a specific set of relevant nodes as identified by our algorithm from the rest of the network. The methodology is model free and can be applied to high-dimensional networks with both inter-lag and intra-lag relationships. It outperforms state-of-the-art approaches for eliminating the redundancies and more generally retrieving simulated artificial networks in our Monte-Carlo experiments. We apply the method to stock market data at different frequencies (15 min, 1 h, 1 day) to retrieve the network of US largest financial institutions and then document how bank's centrality measurements relate to bank's systemic vulnerability.

The association of corporate work environment factors, health risks, and medical conditions with presenteeism among Australian employees.

PubMed

Musich, Shirley; Hook, Dan; Baaner, Stephanie; Spooner, Michelle; Edington, Dee W

2006-01-01

To investigate the impact of selected corporate environment factors, health risks, and medical conditions on job performance using a self-reported measure of presenteeism. A cross-sectional survey utilizing health risk appraisal (HRA) data merging presenteeism with corporate environment factors, health risks, and medical conditions. Approximately 8000 employees across ten diverse Australian corporations. Employees (N = 1523; participation rate, 19%) who completed an HRA questionnaire. Self-reported HRA data were used to test associations of defined adverse corporate environment factors with presenteeism. Stepwise multivariate logistic regression modeling assessed the relative associations of corporate environment factors, health risks, and medical conditions with increased odds of any presenteeism. Increased presenteeism was significantly associated with poor working conditions, ineffective management/leadership, and work/life imbalance (adjusting for age, gender, health risks, and medical conditions). In multivariate logistic regression models, work/life imbalance, poor working conditions, life dissatisfaction, high stress, back pain, allergies, and younger age were significantly associated with presenteeism. Although the study has some limitations, including a possible response bias caused by the relatively low participation rate across the corporations, the study does demonstrate significant associations between corporate environment factors, health risks, and medical conditions and self-reported presenteeism. The study provides initial evidence that health management programming may benefit on-the-job productivity outcomes if expanded to include interventions targeting work environments.

Diels–Alder Reactions of Allene with Benzene and Butadiene: Concerted, Stepwise, and Ambimodal Transition States

PubMed Central

2015-01-01

Multiconfigurational complete active space methods (CASSCF and CASPT2) have been used to investigate the (4 + 2) cycloadditions of allene with butadiene and with benzene. Both concerted and stepwise radical pathways were examined to determine the mechanism of the Diels–Alder reactions with an allene dienophile. Reaction with butadiene occurs via a single ambimodal transition state that can lead to either the concerted or stepwise trajectories along the potential energy surface, while reaction with benzene involves two separate transition states and favors the concerted mechanism relative to the stepwise mechanism via a diradical intermediate. PMID:25216056

Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise multiple linear regression

USGS Publications Warehouse

Kokaly, R.F.; Clark, R.N.

1999-01-01

We develop a new method for estimating the biochemistry of plant material using spectroscopy. Normalized band depths calculated from the continuum-removed reflectance spectra of dried and ground leaves were used to estimate their concentrations of nitrogen, lignin, and cellulose. Stepwise multiple linear regression was used to select wavelengths in the broad absorption features centered at 1.73 ??m, 2.10 ??m, and 2.30 ??m that were highly correlated with the chemistry of samples from eastern U.S. forests. Band depths of absorption features at these wavelengths were found to also be highly correlated with the chemistry of four other sites. A subset of data from the eastern U.S. forest sites was used to derive linear equations that were applied to the remaining data to successfully estimate their nitrogen, lignin, and cellulose concentrations. Correlations were highest for nitrogen (R2 from 0.75 to 0.94). The consistent results indicate the possibility of establishing a single equation capable of estimating the chemical concentrations in a wide variety of species from the reflectance spectra of dried leaves. The extension of this method to remote sensing was investigated. The effects of leaf water content, sensor signal-to-noise and bandpass, atmospheric effects, and background soil exposure were examined. Leaf water was found to be the greatest challenge to extending this empirical method to the analysis of fresh whole leaves and complete vegetation canopies. The influence of leaf water on reflectance spectra must be removed to within 10%. Other effects were reduced by continuum removal and normalization of band depths. If the effects of leaf water can be compensated for, it might be possible to extend this method to remote sensing data acquired by imaging spectrometers to give estimates of nitrogen, lignin, and cellulose concentrations over large areas for use in ecosystem studies.We develop a new method for estimating the biochemistry of plant material using spectroscopy. Normalized band depths calculated from the continuum-removed reflectance spectra of dried and ground leaves were used to estimate their concentrations of nitrogen, lignin, and cellulose. Stepwise multiple linear regression was used to select wavelengths in the broad absorption features centered at 1.73 ??m, 2.10 ??m, and 2.301 ??m that were highly correlated with the chemistry of samples from eastern U.S. forests. Band depths of absorption features at these wavelengths were found to also be highly correlated with the chemistry of four other sites. A subset of data from the eastern U.S. forest sites was used to derive linear equations that were applied to the remaining data to successfully estimate their nitrogen, lignin, and cellulose concentrations. Correlations were highest for nitrogen (R2 from 0.75 to 0.94). The consistent results indicate the possibility of establishing a single equation capable of estimating the chemical concentrations in a wide variety of species from the reflectance spectra of dried leaves. The extension of this method to remote sensing was investigated. The effects of leaf water content, sensor signal-to-noise and bandpass, atmospheric effects, and background soil exposure were examined. Leaf water was found to be the greatest challenge to extending this empirical method to the analysis of fresh whole leaves and complete vegetation canopies. The influence of leaf water on reflectance spectra must be removed to within 10%. Other effects were reduced by continuum removal and normalization of band depths. If the effects of leaf water can be compensated for, it might be possible to extend this method to remote sensing data acquired by imaging spectrometers to give estimates of nitrogen, lignin, and cellulose concentrations over large areas for use in ecosystem studies.

Multivariate Linear Regression and CART Regression Analysis of TBM Performance at Abu Hamour Phase-I Tunnel

NASA Astrophysics Data System (ADS)

Jakubowski, J.; Stypulkowski, J. B.; Bernardeau, F. G.

2017-12-01

The first phase of the Abu Hamour drainage and storm tunnel was completed in early 2017. The 9.5 km long, 3.7 m diameter tunnel was excavated with two Earth Pressure Balance (EPB) Tunnel Boring Machines from Herrenknecht. TBM operation processes were monitored and recorded by Data Acquisition and Evaluation System. The authors coupled collected TBM drive data with available information on rock mass properties, cleansed, completed with secondary variables and aggregated by weeks and shifts. Correlations and descriptive statistics charts were examined. Multivariate Linear Regression and CART regression tree models linking TBM penetration rate (PR), penetration per revolution (PPR) and field penetration index (FPI) with TBM operational and geotechnical characteristics were performed for the conditions of the weak/soft rock of Doha. Both regression methods are interpretable and the data were screened with different computational approaches allowing enriched insight. The primary goal of the analysis was to investigate empirical relations between multiple explanatory and responding variables, to search for best subsets of explanatory variables and to evaluate the strength of linear and non-linear relations. For each of the penetration indices, a predictive model coupling both regression methods was built and validated. The resultant models appeared to be stronger than constituent ones and indicated an opportunity for more accurate and robust TBM performance predictions.

Stepwise Analysis of Differential Item Functioning Based on Multiple-Group Partial Credit Model.

ERIC Educational Resources Information Center

Muraki, Eiji

1999-01-01

Extended an Item Response Theory (IRT) method for detection of differential item functioning to the partial credit model and applied the method to simulated data using a stepwise procedure. Then applied the stepwise DIF analysis based on the multiple-group partial credit model to writing trend data from the National Assessment of Educational…

HIV lipodystrophy in participants randomised to lopinavir/ritonavir (LPV/r) +2-3 nucleoside/nucleotide reverse transcriptase inhibitors (N(t)RTI) or LPV/r + raltegravir as second-line antiretroviral therapy.

PubMed

Martin, Allison; Moore, Cecilia L; Mallon, Patrick W G; Hoy, Jennifer F; Emery, Sean; Belloso, Waldo H; Phanuphak, Praphan; Ferret, Samuel; Cooper, David A; Boyd, Mark A

2013-01-01

To compare changes over 48 weeks in body fat, lipids, Metabolic Syndrome and cardiovascular disease risk between patients randomised 1:1 to lopinavir/ritonavir (r/LPV) plus raltegravir (RAL) compared to r/LPV plus 2-3 nucleoside/nucleotide reverse transcriptase inhibitors (N(t)RTIs) as second-line therapy. Participants were HIV-1 positive (>16 years) failing first-line treatment (2 consecutive HIV RNA >500 copies/mL) of NNRTI +2N(t)RTI. Whole body dual energy x-ray absorptiometry was performed at baseline and week 48. Data were obtained to calculate the Metabolic Syndrome and Framingham cardiovascular disease (CVD) risk score. Linear regression was used to compare mean differences between arms. Logistic regression compared incidence of metabolic syndrome. Associations between percent limb fat changes at 48 weeks with baseline variables were assessed by backward stepwise multivariate linear regression. Analyses were adjusted for gender, body mass index and smoking status. 210 participants were randomised. The mean (95% CI) increase in limb fat over 48 weeks was 15.7% (5.3, 25.9) or 0.9 kg (0.2, 1.5) in the r/LPV+N(t)RTI arm and 21.1% (11.1, 31,1) or 1.3 kg (0.7, 1.9) in the r/LPV+RAL arm, with no significant difference between treatment arms (-5.4% [-0.4 kg], p>0.1). Increases in total body fat mass (kg) and trunk fat mass (kg) were also similar between groups. Total:HDL cholesterol ratio was significantly higher in the RAL arm (mean difference -0.4 (1.4); p = 0.03), there were no other differences in lipid parameters between treatment arms. There were no statistically significant differences in CVD risk or incidence of Metabolic Syndrome between the two treatment arms. The baseline predictors of increased limb fat were high viral load, high insulin and participant's not taking lipid lowering treatment. In patients switching to second line therapy, r/LPV combined with RAL demonstrated similar improvements in limb fat as an N(t)RTI + r/LPV regimen, but a worse total:HDL cholesterol ratio over 48 weeks. This clinical trial is registered on Clinicaltrials.gov, registry number NCT00931463 http://clinicaltrials.gov/ ct2/show/NCT00931463?term = NCT00931463&rank = 1.

A general framework for multivariate multi-index drought prediction based on Multivariate Ensemble Streamflow Prediction (MESP)

NASA Astrophysics Data System (ADS)

Hao, Zengchao; Hao, Fanghua; Singh, Vijay P.

2016-08-01

Drought is among the costliest natural hazards worldwide and extreme drought events in recent years have caused huge losses to various sectors. Drought prediction is therefore critically important for providing early warning information to aid decision making to cope with drought. Due to the complicated nature of drought, it has been recognized that the univariate drought indicator may not be sufficient for drought characterization and hence multivariate drought indices have been developed for drought monitoring. Alongside the substantial effort in drought monitoring with multivariate drought indices, it is of equal importance to develop a drought prediction method with multivariate drought indices to integrate drought information from various sources. This study proposes a general framework for multivariate multi-index drought prediction that is capable of integrating complementary prediction skills from multiple drought indices. The Multivariate Ensemble Streamflow Prediction (MESP) is employed to sample from historical records for obtaining statistical prediction of multiple variables, which is then used as inputs to achieve multivariate prediction. The framework is illustrated with a linearly combined drought index (LDI), which is a commonly used multivariate drought index, based on climate division data in California and New York in the United States with different seasonality of precipitation. The predictive skill of LDI (represented with persistence) is assessed by comparison with the univariate drought index and results show that the LDI prediction skill is less affected by seasonality than the meteorological drought prediction based on SPI. Prediction results from the case study show that the proposed multivariate drought prediction outperforms the persistence prediction, implying a satisfactory performance of multivariate drought prediction. The proposed method would be useful for drought prediction to integrate drought information from various sources for early drought warning.

Minimization of transmission cost in decentralized control systems

NASA Technical Reports Server (NTRS)

Wang, S.-H.; Davison, E. J.

1978-01-01

This paper considers the problem of stabilizing a linear time-invariant multivariable system by using local feedback controllers and some limited information exchange among local stations. The problem of achieving a given degree of stability with minimum transmission cost is solved.

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

Influence assessment in censored mixed-effects models using the multivariate Student’s-t distribution

PubMed Central

Matos, Larissa A.; Bandyopadhyay, Dipankar; Castro, Luis M.; Lachos, Victor H.

2015-01-01

In biomedical studies on HIV RNA dynamics, viral loads generate repeated measures that are often subjected to upper and lower detection limits, and hence these responses are either left- or right-censored. Linear and non-linear mixed-effects censored (LMEC/NLMEC) models are routinely used to analyse these longitudinal data, with normality assumptions for the random effects and residual errors. However, the derived inference may not be robust when these underlying normality assumptions are questionable, especially the presence of outliers and thick-tails. Motivated by this, Matos et al. (2013b) recently proposed an exact EM-type algorithm for LMEC/NLMEC models using a multivariate Student’s-t distribution, with closed-form expressions at the E-step. In this paper, we develop influence diagnostics for LMEC/NLMEC models using the multivariate Student’s-t density, based on the conditional expectation of the complete data log-likelihood. This partially eliminates the complexity associated with the approach of Cook (1977, 1986) for censored mixed-effects models. The new methodology is illustrated via an application to a longitudinal HIV dataset. In addition, a simulation study explores the accuracy of the proposed measures in detecting possible influential observations for heavy-tailed censored data under different perturbation and censoring schemes. PMID:26190871

Multivariate and repeated measures (MRM): A new toolbox for dependent and multimodal group-level neuroimaging data

PubMed Central

McFarquhar, Martyn; McKie, Shane; Emsley, Richard; Suckling, John; Elliott, Rebecca; Williams, Stephen

2016-01-01

Repeated measurements and multimodal data are common in neuroimaging research. Despite this, conventional approaches to group level analysis ignore these repeated measurements in favour of multiple between-subject models using contrasts of interest. This approach has a number of drawbacks as certain designs and comparisons of interest are either not possible or complex to implement. Unfortunately, even when attempting to analyse group level data within a repeated-measures framework, the methods implemented in popular software packages make potentially unrealistic assumptions about the covariance structure across the brain. In this paper, we describe how this issue can be addressed in a simple and efficient manner using the multivariate form of the familiar general linear model (GLM), as implemented in a new MATLAB toolbox. This multivariate framework is discussed, paying particular attention to methods of inference by permutation. Comparisons with existing approaches and software packages for dependent group-level neuroimaging data are made. We also demonstrate how this method is easily adapted for dependency at the group level when multiple modalities of imaging are collected from the same individuals. Follow-up of these multimodal models using linear discriminant functions (LDA) is also discussed, with applications to future studies wishing to integrate multiple scanning techniques into investigating populations of interest. PMID:26921716

Prediction of the Main Engine Power of a New Container Ship at the Preliminary Design Stage

NASA Astrophysics Data System (ADS)

Cepowski, Tomasz

2017-06-01

The paper presents mathematical relationships that allow us to forecast the estimated main engine power of new container ships, based on data concerning vessels built in 2005-2015. The presented approximations allow us to estimate the engine power based on the length between perpendiculars and the number of containers the ship will carry. The approximations were developed using simple linear regression and multivariate linear regression analysis. The presented relations have practical application for estimation of container ship engine power needed in preliminary parametric design of the ship. It follows from the above that the use of multiple linear regression to predict the main engine power of a container ship brings more accurate solutions than simple linear regression.

Is there a step-wise migration in Nigeria? A case study of the migrational histories of migrants in Lagos.

PubMed

Afolayan, A A

1985-09-01

"The paper sets out to test whether or not the movement pattern of people in Nigeria is step-wise. It examines the spatial order in the country and the movement pattern of people. It then analyzes the survey data and tests for the validity of step-wise migration in the country. The findings show that step-wise migration cannot adequately describe all the patterns observed." The presence of large-scale circulatory migration between rural and urban areas is noted. Ways to decrease the pressure on Lagos by developing intermediate urban areas are considered. excerpt

Characteristics of H+ current transients induced by adverse H+ gradient pulses in toad bladder.

PubMed

Nero, A C; Schwartz, J H; Furtado, M R

1987-10-01

Acidification in the toad bladder occurs as a result of electrogenic H+ secretion (JH). When a pH gradient is applied in a stepwise fashion in the absence of exogenous CO2, JH decreases linearly with the mucosal (M) solution pH and is null when pHm is approximately 4.5. When pHm is returned to initial values (7.4) in a stepwise fashion, JH increases linearly with pHm. However, on this return, higher values of JH are initially obtained. To investigate this hysteresis, hemibladders mounted in chambers were used to measure the change in the H+ current before and after acid pulses were applied to the mucosal solution. In the absence of exogenous CO2, the application of graded acid pulses to mucosa for 1, 2, 4, and 8 min resulted in a graded decrease in JH. The restoration of pHm to 7.4 was followed by an immediate transient overshoot of reversed short-circuit current (Irsc), which was related to the time of exposure and the magnitude of the acid pulse. The longer the acid pulse or the larger the pulse, the greater the Irsc overshoot. The addition of protonophores, dinitrophenol, or salicylate, into the mucosal solution enhanced this overshoot. Similar Irsc overshoots could be obtained with the application of pulses of adverse electrical gradients. Introduction of exogenous CO2 into the system (3%) completely inhibited the overshoot in JH after an acid pulse. In conclusion, when pHm is decreased JH is reduced and the cell pH presumably decreases because of continued exit of alkali at the serosal side of the cell and entry of H+ from the mucosal solution. The decrease in cell pH then triggers the pump to produce a sharp overshoot in JH when pHm returns to 7.4.

Regression Models For Multivariate Count Data

PubMed Central

Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei

2016-01-01

Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data. PMID:28348500

Regression Models For Multivariate Count Data.

PubMed

Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei

2017-01-01

Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data.

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

PubMed

Bolea, Yolanda; Puig, Vicenç

2016-07-01

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

Causality networks from multivariate time series and application to epilepsy.

PubMed

Siggiridou, Elsa; Koutlis, Christos; Tsimpiris, Alkiviadis; Kimiskidis, Vasilios K; Kugiumtzis, Dimitris

2015-08-01

Granger causality and variants of this concept allow the study of complex dynamical systems as networks constructed from multivariate time series. In this work, a large number of Granger causality measures used to form causality networks from multivariate time series are assessed. For this, realizations on high dimensional coupled dynamical systems are considered and the performance of the Granger causality measures is evaluated, seeking for the measures that form networks closest to the true network of the dynamical system. In particular, the comparison focuses on Granger causality measures that reduce the state space dimension when many variables are observed. Further, the linear and nonlinear Granger causality measures of dimension reduction are compared to a standard Granger causality measure on electroencephalographic (EEG) recordings containing episodes of epileptiform discharges.

Physical Function in Older Men With Hyperkyphosis

PubMed Central

Harrison, Stephanie L.; Fink, Howard A.; Marshall, Lynn M.; Orwoll, Eric; Barrett-Connor, Elizabeth; Cawthon, Peggy M.; Kado, Deborah M.

2015-01-01

Background. Age-related hyperkyphosis has been associated with poor physical function and is a well-established predictor of adverse health outcomes in older women, but its impact on health in older men is less well understood. Methods. We conducted a cross-sectional study to evaluate the association of hyperkyphosis and physical function in 2,363 men, aged 71–98 (M = 79) from the Osteoporotic Fractures in Men Study. Kyphosis was measured using the Rancho Bernardo Study block method. Measurements of grip strength and lower extremity function, including gait speed over 6 m, narrow walk (measure of dynamic balance), repeated chair stands ability and time, and lower extremity power (Nottingham Power Rig) were included separately as primary outcomes. We investigated associations of kyphosis and each outcome in age-adjusted and multivariable linear or logistic regression models, controlling for age, clinic, education, race, bone mineral density, height, weight, diabetes, and physical activity. Results. In multivariate linear regression, we observed a dose-related response of worse scores on each lower extremity physical function test as number of blocks increased, p for trend ≤.001. Using a cutoff of ≥4 blocks, 20% (N = 469) of men were characterized with hyperkyphosis. In multivariate logistic regression, men with hyperkyphosis had increased odds (range 1.5–1.8) of being in the worst quartile of performing lower extremity physical function tasks (p < .001 for each outcome). Kyphosis was not associated with grip strength in any multivariate analysis. Conclusions. Hyperkyphosis is associated with impaired lower extremity physical function in older men. Further studies are needed to determine the direction of causality. PMID:25431353

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

PubMed

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

2016-05-01

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

Design of linear quadratic regulators with eigenvalue placement in a specified region

NASA Technical Reports Server (NTRS)

Shieh, Leang-San; Zhen, Liu; Coleman, Norman P.

1990-01-01

Two linear quadratic regulators are developed for placing the closed-loop poles of linear multivariable continuous-time systems within the common region of an open sector, bounded by lines inclined at +/- pi/2k (for a specified integer k not less than 1) from the negative real axis, and the left-hand side of a line parallel to the imaginary axis in the complex s-plane, and simultaneously minimizing a quadratic performance index. The design procedure mainly involves the solution of either Liapunov equations or Riccati equations. The general expression for finding the lower bound of a constant gain gamma is also developed.

Linear quadratic regulators with eigenvalue placement in a specified region

NASA Technical Reports Server (NTRS)

Shieh, Leang S.; Dib, Hani M.; Ganesan, Sekar

1988-01-01

A linear optimal quadratic regulator is developed for optimally placing the closed-loop poles of multivariable continuous-time systems within the common region of an open sector, bounded by lines inclined at + or - pi/2k (k = 2 or 3) from the negative real axis with a sector angle of pi/2 or less, and the left-hand side of a line parallel to the imaginary axis in the complex s-plane. The design method is mainly based on the solution of a linear matrix Liapunov equation, and the resultant closed-loop system with its eigenvalues in the desired region is optimal with respect to a quadratic performance index.

The Multidimensional Structure of Verbal Comprehension Test Items.

ERIC Educational Resources Information Center

Peled, Zimra

1984-01-01

The multidimensional structure of verbal comprehension test items was investigated. Empirical evidence was provided to support the theory that item tasks are multivariate-multiordered composites of faceted components: language, contextual knowledge, and cognitive operation. Linear and circular properties of cylindrical manifestation were…

Multivariate longitudinal data analysis with censored and intermittent missing responses.

PubMed

Lin, Tsung-I; Lachos, Victor H; Wang, Wan-Lun

2018-05-08

The multivariate linear mixed model (MLMM) has emerged as an important analytical tool for longitudinal data with multiple outcomes. However, the analysis of multivariate longitudinal data could be complicated by the presence of censored measurements because of a detection limit of the assay in combination with unavoidable missing values arising when subjects miss some of their scheduled visits intermittently. This paper presents a generalization of the MLMM approach, called the MLMM-CM, for a joint analysis of the multivariate longitudinal data with censored and intermittent missing responses. A computationally feasible expectation maximization-based procedure is developed to carry out maximum likelihood estimation within the MLMM-CM framework. Moreover, the asymptotic standard errors of fixed effects are explicitly obtained via the information-based method. We illustrate our methodology by using simulated data and a case study from an AIDS clinical trial. Experimental results reveal that the proposed method is able to provide more satisfactory performance as compared with the traditional MLMM approach. Copyright © 2018 John Wiley & Sons, Ltd.

Multivariate meta-analysis using individual participant data

PubMed Central

Riley, R. D.; Price, M. J.; Jackson, D.; Wardle, M.; Gueyffier, F.; Wang, J.; Staessen, J. A.; White, I. R.

2016-01-01

When combining results across related studies, a multivariate meta-analysis allows the joint synthesis of correlated effect estimates from multiple outcomes. Joint synthesis can improve efficiency over separate univariate syntheses, may reduce selective outcome reporting biases, and enables joint inferences across the outcomes. A common issue is that within-study correlations needed to fit the multivariate model are unknown from published reports. However, provision of individual participant data (IPD) allows them to be calculated directly. Here, we illustrate how to use IPD to estimate within-study correlations, using a joint linear regression for multiple continuous outcomes and bootstrapping methods for binary, survival and mixed outcomes. In a meta-analysis of 10 hypertension trials, we then show how these methods enable multivariate meta-analysis to address novel clinical questions about continuous, survival and binary outcomes; treatment–covariate interactions; adjusted risk/prognostic factor effects; longitudinal data; prognostic and multiparameter models; and multiple treatment comparisons. Both frequentist and Bayesian approaches are applied, with example software code provided to derive within-study correlations and to fit the models. PMID:26099484

Sick of our loans: Student borrowing and the mental health of young adults in the United States.

PubMed

Walsemann, Katrina M; Gee, Gilbert C; Gentile, Danielle

2015-01-01

Student loans are increasingly important and commonplace, especially among recent cohorts of young adults in the United States. These loans facilitate the acquisition of human capital in the form of education, but may also lead to stress and worries related to repayment. This study investigated two questions: 1) what is the association between the cumulative amount of student loans borrowed over the course of schooling and psychological functioning when individuals are 25-31 years old; and 2) what is the association between annual student loan borrowing and psychological functioning among currently enrolled college students? We also examined whether these relationships varied by parental wealth, college enrollment history (e.g. 2-year versus 4-year college), and educational attainment (for cumulative student loans only). We analyzed data from the National Longitudinal Survey of Youth 1997 (NLSY97), a nationally representative sample of young adults in the United States. Analyses employed multivariate linear regression and within-person fixed-effects models. Student loans were associated with poorer psychological functioning, adjusting for covariates, in both the multivariate linear regression and the within-person fixed effects models. This association varied by level of parental wealth in the multivariate linear regression models only, and did not vary by college enrollment history or educational attainment. The present findings raise novel questions for further research regarding student loan debt and the possible spillover effects on other life circumstances, such as occupational trajectories and health inequities. The study of student loans is even more timely and significant given the ongoing rise in the costs of higher education. Copyright © 2014 Elsevier Ltd. All rights reserved.

Decreasing triage time: effects of implementing a step-wise ESI algorithm in an EHR.

PubMed

Villa, Stephen; Weber, Ellen J; Polevoi, Steven; Fee, Christopher; Maruoka, Andrew; Quon, Tina

2018-06-01

To determine if adapting a widely-used triage scale into a computerized algorithm in an electronic health record (EHR) shortens emergency department (ED) triage time. Before-and-after quasi-experimental study. Urban, tertiary care hospital ED. Consecutive adult patient visits between July 2011 and June 2013. A step-wise algorithm, based on the Emergency Severity Index (ESI-5) was programmed into the triage module of a commercial EHR. Duration of triage (triage interval) for all patients and change in percentage of high acuity patients (ESI 1 and 2) completing triage within 15 min, 12 months before-and-after implementation of the algorithm. Multivariable analysis adjusted for confounders; interrupted time series demonstrated effects over time. Secondary outcomes examined quality metrics and patient flow. About 32 546 patient visits before and 33 032 after the intervention were included. Post-intervention patients were slightly older, census was higher and admission rate slightly increased. Median triage interval was 5.92 min (interquartile ranges, IQR 4.2-8.73) before and 2.8 min (IQR 1.88-4.23) after the intervention (P < 0.001). Adjusted mean triage interval decreased 3.4 min (95% CI: -3.6, -3.2). The proportion of high acuity patients completing triage within 15 min increased from 63.9% (95% CI 62.5, 65.2%) to 75.0% (95% CI 73.8, 76.1). Monthly time series demonstrated immediate and sustained improvement following the intervention. Return visits within 72 h and door-to-balloon time were unchanged. Total length of stay was similar. The computerized triage scale improved speed of triage, allowing more high acuity patients to be seen within recommended timeframes, without notable impact on quality.

A nomogram to predict the survival of stage IIIA-N2 non-small cell lung cancer after surgery.

PubMed

Mao, Qixing; Xia, Wenjie; Dong, Gaochao; Chen, Shuqi; Wang, Anpeng; Jin, Guangfu; Jiang, Feng; Xu, Lin

2018-04-01

Postoperative survival of patients with stage IIIA-N2 non-small cell lung cancer (NSCLC) is highly heterogeneous. Here, we aimed to identify variables associated with postoperative survival and develop a tool for survival prediction. A retrospective review was performed in the Surveillance, Epidemiology, and End Results database from January 2004 to December 2009. Significant variables were selected by use of the backward stepwise method. The nomogram was constructed with multivariable Cox regression. The model's performance was evaluated by concordance index and calibration curve. The model was validated via an independent cohort from the Jiangsu Cancer Hospital Lung Cancer Center. A total of 1809 patients with stage IIIA-N2 NSCLC who underwent surgery were included in the training cohort. Age, sex, grade, histology, tumor size, visceral pleural invasion, positive lymph nodes, lymph nodes examined, and surgery type (lobectomy vs pneumonectomy) were identified as significant prognostic variables using backward stepwise method. A nomogram was developed from the training cohort and validated using an independent Chinese cohort. The concordance index of the model was 0.673 (95% confidence interval, 0.654-0.692) in training cohort and 0.664 in validation cohort (95% confidence interval, 0.614-0.714). The calibration plot showed optimal consistency between nomogram predicted survival and observed survival. Survival analyses demonstrated significant differences between different subgroups stratified by prognostic scores. This nomogram provided the individual survival prediction for patients with stage IIIA-N2 NSCLC after surgery, which might benefit survival counseling for patients and clinicians, clinical trial design and follow-up, as well as postoperative strategy-making. Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Sex determination from the mandibular ramus flexure of Koreans by discrimination function analysis using three-dimensional mandible models.

PubMed

Lin, Chenghe; Jiao, Benzheng; Liu, Shanshan; Guan, Feng; Chung, Nak-Eun; Han, Seung-Ho; Lee, U-Young

2014-03-01

It has been known that mandible ramus flexure is an important morphologic trait for sex determination. However, it will be unavailable when mandible is incomplete or fragmented. Therefore, the anthropometric analysis on incomplete or fragmented mandible becomes more important. The aim of this study is to investigate the sex-discriminant potential of mandible ramus flexure on the Korean three-dimensional (3D) mandible models with anthropometric analysis. The sample consists of 240 three dimensional mandibular models obtained from Korean population (M:F; 120:120, mean age 46.2 y), collected by The Catholic Institute for Applied Anatomy, The Catholic University of Korea. Anthropometric information about 11 metric was taken with Mimics, anthropometry libraries toolkit. These parameters were subjected to different discriminant function analyses using SPSS 17.0. Univariate analyses showed that the resubstitution accuracies for sex determination range from 50.4 to 77.1%. Mandibular flexure upper border (MFUB), maximum ramus vertical height (MRVH), and upper ramus vertical height (URVH) expressed the greatest dimorphism, 72.1 to 77.1%. Bivariate analyses indicated that the combination of MFUB and MRVH hold even higher resubstitution accuracy of 81.7%. Furthermore, the direct and stepwise discriminant analyses with the variables on the upper ramus above flexure could predict sex in 83.3 and 85.0%, respectively. When all variables of mandibular ramus flexure were input in stepwise discriminant analysis, the resubstitution accuracy arrived as high as 88.8%. Therefore, we concluded that the upper ramus above flexure hold the larger potentials than the mandibular ramus flexure itself to predict sexes, and that the equations in bivariate and multivariate analysis from our study will be helpful for sex determination on Korean population in forensic science and law. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

PREOPERATIVE MRI IMPROVES PREDICTION OF EXTENSIVE OCCULT AXILLARY LYMPH NODE METASTASES IN BREAST CANCER PATIENTS WITH A POSITIVE SENTINEL LYMPH NODE BIOPSY

PubMed Central

Loiselle, Christopher; Eby, Peter R.; Kim, Janice N.; Calhoun, Kristine E.; Allison, Kimberly H.; Gadi, Vijayakrishna K.; Peacock, Sue; Storer, Barry; Mankoff, David A.; Partridge, Savannah C.; Lehman, Constance D.

2014-01-01

Rationale and Objectives To test the ability of quantitative measures from preoperative Dynamic Contrast Enhanced MRI (DCE-MRI) to predict, independently and/or with the Katz pathologic nomogram, which breast cancer patients with a positive sentinel lymph node biopsy will have ≥ 4 positive axillary lymph nodes upon completion axillary dissection. Methods and Materials A retrospective review was conducted to identify clinically node-negative invasive breast cancer patients who underwent preoperative DCE-MRI, followed by sentinel node biopsy with positive findings and complete axillary dissection (6/2005 – 1/2010). Clinical/pathologic factors, primary lesion size and quantitative DCE-MRI kinetics were collected from clinical records and prospective databases. DCE-MRI parameters with univariate significance (p < 0.05) to predict ≥ 4 positive axillary nodes were modeled with stepwise regression and compared to the Katz nomogram alone and to a combined MRI-Katz nomogram model. Results Ninety-eight patients with 99 positive sentinel biopsies met study criteria. Stepwise regression identified DCE-MRI total persistent enhancement and volume adjusted peak enhancement as significant predictors of ≥4 metastatic nodes. Receiver operating characteristic (ROC) curves demonstrated an area under the curve (AUC) of 0.78 for the Katz nomogram, 0.79 for the DCE-MRI multivariate model, and 0.87 for the combined MRI-Katz model. The combined model was significantly more predictive than the Katz nomogram alone (p = 0.003). Conclusion Integration of DCE-MRI primary lesion kinetics significantly improved the Katz pathologic nomogram accuracy to predict presence of metastases in ≥ 4 nodes. DCE-MRI may help identify sentinel node positive patients requiring further localregional therapy. PMID:24331270

Assessment and prediction of short term hospital admissions: the case of Athens, Greece

NASA Astrophysics Data System (ADS)

Kassomenos, P.; Papaloukas, C.; Petrakis, M.; Karakitsios, S.

The contribution of air pollution on hospital admissions due to respiratory and heart diseases is a major issue in the health-environmental perspective. In the present study, an attempt was made to run down the relationships between air pollution levels and meteorological indexes, and corresponding hospital admissions in Athens, Greece. The available data referred to a period of eight years (1992-2000) including the daily number of hospital admissions due to respiratory and heart diseases, hourly mean concentrations of CO, NO 2, SO 2, O 3 and particulates in several monitoring stations, as well as, meteorological data (temperature, relative humidity, wind speed/direction). The relations among the above data were studied through widely used statistical techniques (multivariate stepwise analyses) and Artificial Neural Networks (ANNs). Both techniques revealed that elevated particulate concentrations are the dominant parameter related to hospital admissions (an increase of 10 μg m -3 leads to an increase of 10.2% in the number of admissions), followed by O 3 and the rest of the pollutants (CO, NO 2 and SO 2). Meteorological parameters also play a decisive role in the formation of air pollutant levels affecting public health. Consequently, increased/decreased daily hospital admissions are related to specific types of meteorological conditions that favor/do not favor the accumulation of pollutants in an urban complex. In general, the role of meteorological factors seems to be underestimated by stepwise analyses, while ANNs attribute to them a more important role. Comparison of the two models revealed that ANN adaptation in complicate environmental issues presents improved modeling results compared to a regression technique. Furthermore, the ANN technique provides a reliable model for the prediction of the daily hospital admissions based on air quality data and meteorological indices, undoubtedly useful for regulatory purposes.

Complex interaction between symptoms, social factors, and gender in social functioning in a community-dwelling sample of schizophrenia.

PubMed

Vila-Rodriguez, F; Ochoa, S; Autonell, J; Usall, J; Haro, J M

2011-12-01

Social functioning (SF) is the ultimate target aimed in treatment plans in schizophrenia, thus it is critical to know what are the factors that determine SF. Gender is a well-established variable influencing SF, yet it is not known how social variables and symptoms interact in schizophrenia patients. Furthermore, it remains unclear whether the interaction between social variables and symptoms is different in men compared to women. Our aim is to test whether social variables are better predictors of SF in community-dwelled individuals with schizophrenia, and whether men and women differ in how symptoms and social variables interact to impact SF. Community-dwelling individuals with schizophrenia (N = 231) were randomly selected from a register. Participants were assessed with symptom measures (PANSS), performance-based social scale (LSP), objective social and demographic variables. Stratification by gender and stepwise multivariate regression analyses by gender were used to find the best-fitting models that predict SF in both gender. Men had poorer SF than women in spite of showing similar symptom scores. On stepwise regression analyses, gender was the main variable explaining SF, with a significant contribution by disorganized and excitatory symptoms. Age of onset made a less marked, yet significant, contribution to explain SF. When the sample was stratified by gender, disorganized symptoms and 'Income' variable entered the model and accounted for a 30.8% of the SF variance in women. On the other hand, positive and disorganized symptoms entered the model and accounted for a 36.1% of the SF variance in men. Community-dwelling men and women with schizophrenia differ in the constellation of variables associated with SF. Symptom scores still account for most of the variance in SF in both genders.

Improved separation and size characterization of gold nanoparticles through a novel capillary zone electrophoresis method using poly(sodium4-styrenesulfonate) as stabiliser and a stepwise field strength gradient.

PubMed

Ciriello, Rosanna; Iallorenzi, Pina Teresa; Laurita, Alessandro; Guerrieri, Antonio

2017-03-01

A novel capillary zone electrophoresis (CZE) method was developed for an improved separation and size characterization of pristine gold nanoparticles (AuNP) using uncoated fused-silica capillaries with UV-Vis detection at 520 nm. To avoid colloid aggregation and/or adsorption during runs, poly(sodium 4-styrenesulfonate) (PSS) was added (1%, w/v) in the running buffer (CAPS 10 mM, pH 11). This polyelectrolyte conferred an enhanced stabilization to AuNP, both steric and electrostatic, exalting at the same time their differences in electrophoretic mobility. Resolution was further and successfully improved through a stepwise field strength gradient by the application of 25 kV for the first 5 min and then 10 kV. Migration times varied linearly with particles diameters showing relative standard deviations better than 1% for daily experiments and 3% for interday experiments. A comparison with the size distribution obtained by transmission electron microscopy (TEM) allowed assessing that the electrophoretic profile can reasonably be considered as representative of the effective size heterogeneity of each colloid. Finally, the practical utility of the proposed method was demonstrated by measuring the core diameter of a gold colloid sample produced by chemical synthesis which was in good agreement with the value obtained by TEM measurements. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predicting psychopharmacological drug effects on actual driving performance (SDLP) from psychometric tests measuring driving-related skills.

PubMed

Verster, Joris C; Roth, Thomas

2012-03-01

There are various methods to examine driving ability. Comparisons between these methods and their relationship with actual on-road driving is often not determined. The objective of this study was to determine whether laboratory tests measuring driving-related skills could adequately predict on-the-road driving performance during normal traffic. Ninety-six healthy volunteers performed a standardized on-the-road driving test. Subjects were instructed to drive with a constant speed and steady lateral position within the right traffic lane. Standard deviation of lateral position (SDLP), i.e., the weaving of the car, was determined. The subjects also performed a psychometric test battery including the DSST, Sternberg memory scanning test, a tracking test, and a divided attention test. Difference scores from placebo for parameters of the psychometric tests and SDLP were computed and correlated with each other. A stepwise linear regression analysis determined the predictive validity of the laboratory test battery to SDLP. Stepwise regression analyses revealed that the combination of five parameters, hard tracking, tracking and reaction time of the divided attention test, and reaction time and percentage of errors of the Sternberg memory scanning test, together had a predictive validity of 33.4%. The psychometric tests in this test battery showed insufficient predictive validity to replace the on-the-road driving test during normal traffic.

Disorganized Symptoms Predicted Worse Functioning Outcome in Schizophrenia Patients with Established Illness.

PubMed

Ortiz, Bruno Bertolucci; Gadelha, Ary; Higuchi, Cinthia Hiroko; Noto, Cristiano; Medeiros, Daiane; Pitta, José Cássio do Nascimento; de Araújo Filho, Gerardo Maria; Hallak, Jaime Eduardo Cecílio; Bressan, Rodrigo Affonseca

Most patients with schizophrenia will have subsequent relapses of the disorder, with continuous impairments in functioning. However, evidence is lacking on how symptoms influence functioning at different phases of the disease. This study aims to investigate the relationship between symptom dimensions and functioning at different phases: acute exacerbation, nonremission and remission. Patients with schizophrenia were grouped into acutely ill (n=89), not remitted (n=89), and remitted (n=69). Three exploratory stepwise linear regression analyses were performed for each phase of schizophrenia, in which the five PANSS factors and demographic variables were entered as the independent variables and the total Global Assessment of Functioning Scale (GAF) score was entered as the dependent variable. An additional exploratory stepwise logistic regression analysis was performed to predict subsequent remission at discharge in the inpatient population. The Disorganized factor was the most significant predictor for acutely ill patients (p<0.001), while the Hostility factor was the most significant for not-remitted patients and the Negative factor was the most significant for remitted patients (p=0.001 and p<0.001, respectively). In the logistic regression, the Disorganized factor score presented a significant negative association with remission (p=0.007). Higher disorganization symptoms showed the greatest impact in functioning at acute phase, and prevented patients from achieving remission, suggesting it may be a marker of symptom severity and worse outcome in schizophrenia.

Novel methods of time-resolved fluorescence data analysis for in-vivo tissue characterization: application to atherosclerosis.

PubMed

Jo, J A; Fang, Q; Papaioannou, T; Qiao, J H; Fishbein, M C; Dorafshar, A; Reil, T; Baker, D; Freischlag, J; Marcu, L

2004-01-01

This study investigates the ability of new analytical methods of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data to characterize tissue in-vivo, such as the composition of atherosclerotic vulnerable plaques. A total of 73 TR-LIFS measurements were taken in-vivo from the aorta of 8 rabbits, and subsequently analyzed using the Laguerre deconvolution technique. The investigated spots were classified as normal aorta, thin or thick lesions, and lesions rich in either collagen or macrophages/foam-cells. Different linear and nonlinear classification algorithms (linear discriminant analysis, stepwise linear discriminant analysis, principal component analysis, and feedforward neural networks) were developed using spectral and TR features (ratios of intensity values and Laguerre expansion coefficients, respectively). Normal intima and thin lesions were discriminated from thick lesions (sensitivity >90%, specificity 100%) using only spectral features. However, both spectral and time-resolved features were necessary to discriminate thick lesions rich in collagen from thick lesions rich in foam cells (sensitivity >85%, specificity >93%), and thin lesions rich in foam cells from normal aorta and thin lesions rich in collagen (sensitivity >85%, specificity >94%). Based on these findings, we believe that TR-LIFS information derived from the Laguerre expansion coefficients can provide a valuable additional dimension for in-vivo tissue characterization.

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 linear spectral matching technique for retrieving equivalent water thickness and biochemical constituents of green vegetation

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Goetz, Alexander F. H.

1992-01-01

Over the last decade, technological advances in airborne imaging spectrometers, having spectral resolution comparable with laboratory spectrometers, have made it possible to estimate biochemical constituents of vegetation canopies. Wessman estimated lignin concentration from data acquired with NASA's Airborne Imaging Spectrometer (AIS) over Blackhawk Island in Wisconsin. A stepwise linear regression technique was used to determine the single spectral channel or channels in the AIS data that best correlated with measured lignin contents using chemical methods. The regression technique does not take advantage of the spectral shape of the lignin reflectance feature as a diagnostic tool nor the increased discrimination among other leaf components with overlapping spectral features. A nonlinear least squares spectral matching technique was recently reported for deriving both the equivalent water thicknesses of surface vegetation and the amounts of water vapor in the atmosphere from contiguous spectra measured with the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The same technique was applied to a laboratory reflectance spectrum of fresh, green leaves. The result demonstrates that the fresh leaf spectrum in the 1.0-2.5 microns region consists of spectral components of dry leaves and the spectral component of liquid water. A linear least squares spectral matching technique for retrieving equivalent water thickness and biochemical components of green vegetation is described.

Esophageal cancer detection based on tissue surface-enhanced Raman spectroscopy and multivariate analysis

NASA Astrophysics Data System (ADS)

Feng, Shangyuan; Lin, Juqiang; Huang, Zufang; Chen, Guannan; Chen, Weisheng; Wang, Yue; Chen, Rong; Zeng, Haishan

2013-01-01

The capability of using silver nanoparticle based near-infrared surface enhanced Raman scattering (SERS) spectroscopy combined with principal component analysis (PCA) and linear discriminate analysis (LDA) to differentiate esophageal cancer tissue from normal tissue was presented. Significant differences in Raman intensities of prominent SERS bands were observed between normal and cancer tissues. PCA-LDA multivariate analysis of the measured tissue SERS spectra achieved diagnostic sensitivity of 90.9% and specificity of 97.8%. This exploratory study demonstrated great potential for developing label-free tissue SERS analysis into a clinical tool for esophageal cancer detection.

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

NASA Technical Reports Server (NTRS)

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

1977-01-01

The control evaluated has been designed for the F100-PW-100 turbofan engine. The F100 engine represents the current state-of-the-art in aircraft gas turbine technology. The control makes use of a multivariable, linear quadratic regulator. The evaluation procedure employed utilized a real-time hybrid computer simulation of the F100 engine and an implementation of the control logic on the NASA LeRC digital computer/controller. The results of the evaluation indicated that the control logic and its implementation will be capable of controlling the engine throughout its operating range.

The effect of thermal history on crystalline structure and mechanical properties of β-nucleated isotactic polypropylene

NASA Astrophysics Data System (ADS)

Tian, Yefei; Zhou, Jian; Feng, Jiachun

2018-04-01

The effect of thermal history on β-nucleated iPP was systematically investigated by comparing the variance of crystalline microstructures and mechanical property of stepwise crystallized sample and annealed sample, which experienced different thermal history. The mechanical property tests exhibit that that the toughness of stepwise crystallized sample and annealed sample were both decreased compared to control sample, while the tensile strength of the stepwise crystallized sample increased slightly. Structure investigation showed that the α-relaxation peak, which is related to the assignment of chains in rigid amorphous phase, moved to the high temperature region for stepwise crystallized sample, while it moved to the low temperature region for annealed sample. The results indicated the weakening in rigid amorphous fraction (RAF) and the increase in lamellar thickness of β-iPP after stepwise crystallization treatment. For annealed sample, the RAF strengthened and lamellar thickness decreased slightly after thermal treatment. A mechanism of crystalline microstructures evolution of restricted area between the main lamellar under different treatments was proposed.

Improving meat quality of organic pork through post mortem handling of carcasses: an innovative approach.

PubMed

Therkildsen, Margrethe; Kristensen, Lars; Kyed, Sybille; Oksbjerg, Niels

2012-06-01

This study was conducted to examine the best combination of post mortem chilling, suspension and ageing in order to optimize tenderness of organic pork at slaughter, which may be tougher than conventionally produced pork, because of lower daily gain. Combinations of stepwise chilling with a holding period of 6h at 10°C or traditional blast tunnel chilling, suspension in the pelvic bone or Achilles Tendon and ageing 2 or 4 days post mortem were tested. Stepwise chilling and ageing improved tenderness of the loin, and the effects were additive, whereas pelvic suspension was less effective in texture improvements, and non-additive to stepwise chilling. Stepwise chilling improved tenderness to a similar degree as can be obtained within 2-4 days of extended ageing, however, the minimum temperature during the holding period seems to be crucial in order to obtain a positive effect of stepwise chilling, and it should be above 7.5°C. Copyright © 2011 Elsevier Ltd. All rights reserved.

Estimation of parameters in Shot-Noise-Driven Doubly Stochastic Poisson processes using the EM algorithm--modeling of pre- and postsynaptic spike trains.

PubMed

Mino, H

2007-01-01

To estimate the parameters, the impulse response (IR) functions of some linear time-invariant systems generating intensity processes, in Shot-Noise-Driven Doubly Stochastic Poisson Process (SND-DSPP) in which multivariate presynaptic spike trains and postsynaptic spike trains can be assumed to be modeled by the SND-DSPPs. An explicit formula for estimating the IR functions from observations of multivariate input processes of the linear systems and the corresponding counting process (output process) is derived utilizing the expectation maximization (EM) algorithm. The validity of the estimation formula was verified through Monte Carlo simulations in which two presynaptic spike trains and one postsynaptic spike train were assumed to be observable. The IR functions estimated on the basis of the proposed identification method were close to the true IR functions. The proposed method will play an important role in identifying the input-output relationship of pre- and postsynaptic neural spike trains in practical situations.

Multivariate quadrature for representing cloud condensation nuclei activity of aerosol populations

DOE PAGES

Fierce, Laura; McGraw, Robert L.

2017-07-26

Here, sparse representations of atmospheric aerosols are needed for efficient regional- and global-scale chemical transport models. Here we introduce a new framework for representing aerosol distributions, based on the quadrature method of moments. Given a set of moment constraints, we show how linear programming, combined with an entropy-inspired cost function, can be used to construct optimized quadrature representations of aerosol distributions. The sparse representations derived from this approach accurately reproduce cloud condensation nuclei (CCN) activity for realistically complex distributions simulated by a particleresolved model. Additionally, the linear programming techniques described in this study can be used to bound key aerosolmore » properties, such as the number concentration of CCN. Unlike the commonly used sparse representations, such as modal and sectional schemes, the maximum-entropy approach described here is not constrained to pre-determined size bins or assumed distribution shapes. This study is a first step toward a particle-based aerosol scheme that will track multivariate aerosol distributions with sufficient computational efficiency for large-scale simulations.« less

Multivariate quadrature for representing cloud condensation nuclei activity of aerosol populations

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

Fierce, Laura; McGraw, Robert L.

Here, sparse representations of atmospheric aerosols are needed for efficient regional- and global-scale chemical transport models. Here we introduce a new framework for representing aerosol distributions, based on the quadrature method of moments. Given a set of moment constraints, we show how linear programming, combined with an entropy-inspired cost function, can be used to construct optimized quadrature representations of aerosol distributions. The sparse representations derived from this approach accurately reproduce cloud condensation nuclei (CCN) activity for realistically complex distributions simulated by a particleresolved model. Additionally, the linear programming techniques described in this study can be used to bound key aerosolmore » properties, such as the number concentration of CCN. Unlike the commonly used sparse representations, such as modal and sectional schemes, the maximum-entropy approach described here is not constrained to pre-determined size bins or assumed distribution shapes. This study is a first step toward a particle-based aerosol scheme that will track multivariate aerosol distributions with sufficient computational efficiency for large-scale simulations.« less