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Simple Linear Regression (simple + linear_regression)
Terms modified by Simple Linear Regression Selected AbstractsCaloric Restriction Inhibits Seizure Susceptibility in Epileptic EL Mice by Reducing Blood GlucoseEPILEPSIA, Issue 11 2001Amanda E. Greene Summary: ,Purpose: Caloric restriction (CR) involves underfeeding and has long been recognized as a dietary therapy that improves health and increases longevity. In contrast to severe fasting or starvation, CR reduces total food intake without causing nutritional deficiencies. Although fasting has been recognized as an effective antiseizure therapy since the time of the ancient Greeks, the mechanism by which fasting inhibits seizures remains obscure. The influence of CR on seizure susceptibility was investigated at both juvenile (30 days) and adult (70 days) ages in the EL mouse, a genetic model of multifactorial idiopathic epilepsy. Methods: The juvenile EL mice were separated into two groups and fed standard lab chow either ad libitum (control, n = 18) or with a 15% CR diet (treated, n = 17). The adult EL mice were separated into three groups; control (n = 15), 15% CR (n = 6), and 30% CR (n = 3). Body weights, seizure susceptibility, and the levels of blood glucose and ketones (,-hydroxybutyrate) were measured over a 10-week treatment period. Simple linear regression and multiple logistic regression were used to analyze the relations among seizures, glucose, and ketones. Results: CR delayed the onset and reduced the incidence of seizures at both juvenile and adult ages and was devoid of adverse side effects. Furthermore, mild CR (15%) had a greater antiepileptogenic effect than the well-established high-fat ketogenic diet in the juvenile mice. The CR-induced changes in blood glucose levels were predictive of both blood ketone levels and seizure susceptibility. Conclusions: We propose that CR may reduce seizure susceptibility in EL mice by reducing brain glycolytic energy. Our preclinical findings suggest that CR may be an effective antiseizure dietary therapy for human seizure disorders. [source] Effects of feeding ratio of beet pulp to alfalfa hay or grass hay on ruminal mat characteristics and chewing activity in Holstein dry cowsANIMAL SCIENCE JOURNAL, Issue 2 2010Kenichi IZUMI ABSTRACT The influence of the feeding ratio of a non-forage fiber source and hay on ruminal mat characteristics and chewing activity was evaluated in dairy dry cows. Cows were fed four different diets: the ratios of alfalfa hay (AH) to beet pulp (BP) were 8:2 (dry matter basis, A8B2) and 2:8 (A2B8), and those of grass hay (GH) to BP were 8:2 (G8B2) and 2:8 (G2B8). Total eating time was decreased with increasing BP content (P < 0.01). Total rumination time for AH was shorter than that for GH (P < 0.01), and it decreased with increasing BP content (P < 0.01). The ruminal mat was detected by using a penetration resistance test of the rumen digesta. Penetration resistance value (PRV) of ruminal mat was highest with the G8B2 diet and PRV decreased with increasing BP content (P < 0.05) and feeding AH (P < 0.05). Thickness of the ruminal mat was greater for increasing BP content (P < 0.05). Simple linear regression of ruminal mat PRV on total rumination time resulted in a high positive correlation (r = 0.744; P < 0.001; n = 16). The results demonstrated that increasing the PRV of the ruminal mat stimulated rumination activity and a ruminal mat could be formed, although it was soft even when cows were offered a large quantity of BP. [source] Neurophysiological and biomechanical characterization of goat cervical facet joint capsulesJOURNAL OF ORTHOPAEDIC RESEARCH, Issue 4 2005Ying Lu Abstract Cervical facet joints have been implicated as a major source of pain after whiplash injury. We sought to identify facet joint capsule receptors in the cervical spine and quantify their responses to capsular deformation. The response of mechanosensitive afferents in C5,C6 facet joint capsules to craniocaudal stretch (0.5 mm/s) was examined in anaesthetized adult goats. Capsular afferents were characterized into Group III and IV based on their conduction velocity. Two-dimensional strains across the capsules during stretch were obtained by a stereoimaging technique and finite element modeling. 17 (53%) Group III and 14 (56%) Group IV afferents were identified with low strain thresholds of 0.107 ± 0.033 and 0.100 ± 0.046. A subpopulation of low-strain-threshold afferents had discharge rate saturation at the strains of 0.388 ± 0.121 (n = 9, Group III) and 0.341 ± 0.159 (n = 9, Group IV). Two (8%) Group IV units responded only to high strains (0.460 ± 0.170). 15 (47%) Group III and 9 (36%) Group IV units could not be excited even by noxious capsular stretch. Simple linear regressions were conducted with capsular load and principal strain as independent variables and neural response of low-strain-threshold afferents as the dependent variable. Correlation coefficients (R2) were 0.73 ± 0.11 with load, and 0.82 ± 0.12 with principal strain. The stiffness of the C5,C6 capsules was 16.8 ± 11.4 N/mm. Our results indicate that sensory receptors in cervical facet joint capsules are not only capable of signaling a graded physiological mechanical stimulus, but may also elieit pain sensation under excessive deformation. © 2005 Orthopaedic Research Society. Published by Elsevier Ltd. All rights reserved. [source] The greening and browning of Alaska based on 1982,2003 satellite dataGLOBAL ECOLOGY, Issue 4 2008David Verbyla Abstract Aim To examine the trends of 1982,2003 satellite-derived normalized difference vegetation index (NDVI) values at several spatial scales within tundra and boreal forest areas of Alaska. Location Arctic and subarctic Alaska. Methods Annual maximum NDVI data from the twice monthly Global Inventory Modelling and Mapping Studies (GIMMS) NDVI 1982,2003 data set with 64-km2 pixels were extracted from a spatial hierarchy including three large regions: ecoregion polygons within regions, ecozone polygons within boreal ecoregions and 100-km climate station buffers. The 1982,2003 trends of mean annual maximum NDVI values within each area, and within individual pixels, were computed using simple linear regression. The relationship between NDVI and temperature and precipitation was investigated within climate station buffers. Results, At the largest spatial scale of polar, boreal and maritime regions, the strongest trend was a negative trend in NDVI within the boreal region. At a finer scale of ecoregion polygons, there was a strong positive NDVI trend in cold arctic tundra areas, and a strong negative trend in interior boreal forest areas. Within boreal ecozone polygons, the weakest negative trends were from areas with a maritime climate or colder mountainous ecozones, while the strongest negative trends were from warmer basin ecozones. The trends from climate station buffers were similar to ecoregion trends, with no significant trends from Bering tundra buffers, significant increasing trends among arctic tundra buffers and significant decreasing trends among interior boreal forest buffers. The interannual variability of NDVI among the arctic tundra buffers was related to the previous summer warmth index. The spatial pattern of increasing tundra NDVI at the pixel level was related to the west-to-east spatial pattern in changing climate across arctic Alaska. There was no significant relationship between interannual NDVI and precipitation or temperature among the boreal forest buffers. The decreasing NDVI trend in interior boreal forests may be due to several factors including increased insect/disease infestations, reduced photosynthesis and a change in root/leaf carbon allocation in response to warmer and drier growing season climate. Main conclusions There was a contrast in trends of 1982,2003 annual maximum NDVI, with cold arctic tundra significantly increasing in NDVI and relatively warm and dry interior boreal forest areas consistently decreasing in NDVI. The annual maximum NDVI from arctic tundra areas was strongly related to a summer warmth index, while there were no significant relationships in boreal areas between annual maximum NDVI and precipitation or temperature. Annual maximum NDVI was not related to spring NDVI in either arctic tundra or boreal buffers. [source] Estimation of nitrogen concentration and in vitro dry matter digestibility of herbage of warm-season grass pastures from canopy hyperspectral reflectance measurementsGRASS & FORAGE SCIENCE, Issue 2 2008P. J. Starks Abstract Remote sensing of nitrogen (N) concentration and in vitro dry matter digestibility (IVDMD) in herbage can help livestock managers make timely decisions for adjusting stocking rate and managing pastures during the grazing season. Traditional laboratory analyses of N and IVDMD are time-consuming and costly. Non-destructive measurements of canopy hyperspectral reflectance of pasture may provide a rapid and inexpensive means of estimating these measures of nutritive value. Using a portable spectroradiometer, canopy reflectance was measured in eight warm-season grass pastures in the USA in June and July in 2002 and 2003 to develop and validate algorithms for estimating N concentration and IVDMD of herbage. Nitrogen concentration of herbage was linearly correlated (r = 0·82; P < 0·001) with a ratio of reflectance in the 705- and 1685-nm wavebands (R705/R1685) and IVDMD was correlated with R705/R535 (r = 0·74; P < 0·001). Compared with simple linear regressions of N concentration and IVDMD in herbage with two-waveband reflectance ratios, multiple regression, using maximum r2 improvement, band-depth analysis with step-wise regression, and partial least-squares regression enhanced the correlation between N concentration and IVDMD of herbage and canopy reflectance values (0·81 , |r| , 0·90; P < 0·001). Validation of the prediction equations indicated that multiple regression only slightly improved accuracy of a model for predicting N concentration and IVDMD of herbage compared with simple linear regression of reflectance ratios. Results suggest that the N concentration and IVDMD of herbage of warm-season grass pastures can be rapidly and non-destructively estimated during the grazing season using canopy reflectance in a few narrow wavebands. [source] A Statistical Estimator of the Spatial Distribution of the Water-Table AltitudeGROUND WATER, Issue 1 2003Nicasio Sepúlveda An algorithm was designed to statistically estimate the areal distribution of water-table altitude. The altitude of the water table was bounded below by the minimum water-table surface and above by the land surface. Using lake elevations and stream stages, and interpolating between lakes and streams, the minimum water-table surface was generated. A multiple linear regression among the minimum water-table altitude, the difference between land-surface and minimum water-table altitudes, and the water-level measurements from surficial aquifer system wells resulted in a consistently high correlation for all groups of physiographic regions in Florida. A simple linear regression between land-surface and water-level measurements resulted in a root-mean-square residual of 4.23 m, with residuals ranging from , 8.78 to 41.54 m. A simple linear regression between the minimum water table and the water-level measurements resulted in a root-mean-square residual of 1.45 m, with residuals ranging from ,7.39 to 4.10 m. The application of the multiple linear regression presented herein resulted in a root-mean-square residual of 1.05 m, with residuals ranging from , 5.24 to 5.63 m. Results from complete and partial F tests rejected the hypothesis of eliminating any of the regressors in the multiple linear regression presented in this study. [source] Pattern hunting in climate: a new method for finding trends in gridded climate dataINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 1 2007A. Hannachi Abstract Trends are very important in climate research and are ubiquitous in the climate system. Trends are usually estimated using simple linear regression. Given the complexity of the system, trends are expected to have various features such as global and local characters. It is therefore important to develop methods that permit a systematic decomposition of climate data into different trend patterns and remaining no-trend patterns. Empirical orthogonal functions and closely related methods, widely used in atmospheric science, are unable in general to capture trends because they are not devised for that purpose. The present paper presents a novel method capable of systematically capturing trend patterns from gridded data. The method is based on an eigenanalysis of the covariance/correlation matrix obtained using correlations between time positions of the sorted data, and trends are associated with the leading nondegenerate eigenvalues. Application to simple low-dimensional time series models and reanalyses data are presented and discussed. Copyright © 2006 Royal Meteorological Society. [source] Penalized Regression with Ordinal PredictorsINTERNATIONAL STATISTICAL REVIEW, Issue 3 2009Jan Gertheiss Summary Ordered categorial predictors are a common case in regression modelling. In contrast to the case of ordinal response variables, ordinal predictors have been largely neglected in the literature. In this paper, existing methods are reviewed and the use of penalized regression techniques is proposed. Based on dummy coding two types of penalization are explicitly developed; the first imposes a difference penalty, the second is a ridge type refitting procedure. Also a Bayesian motivation is provided. The concept is generalized to the case of non-normal outcomes within the framework of generalized linear models by applying penalized likelihood estimation. Simulation studies and real world data serve for illustration and to compare the approaches to methods often seen in practice, namely simple linear regression on the group labels and pure dummy coding. Especially the proposed difference penalty turns out to be highly competitive. Résumé Les variables indépendantes catégoriques ordinales sont un cas courant dans les modèles de régression. Contrairement au cas des variables dépendantes ordinales, les variables indépendantes ordinales ont été largement négligées par la recherche. Le présent article présente les méthodes existantes et propose l'utilisation de techniques de régression pénalisée. Deux types de pénalisation basés sur des variables dummy sont exposés; le premier impose une pénalité de différence, le second est une procédure basée sur une forme de régression ridge. D'autre part, une motivation baysienne est présentée. La méthode est également appliquée au cas de variables dépendantes non gaussiennes. Des études de simulation et des données réelles servent à illustrer et à comparer les nouvelles méthodes aux méthodes que l'on rencontre souvent dans la pratique - à savoir les régressions linéaires sur les nombres entiers et sur des variables dummy sans penalité. Une pénalité de différence notamment a montré de bons résultats. [source] Three-dimensional balanced steady state free precession imaging of the prostate: Flip angle dependency of the signal based on a two component T2-decay modelJOURNAL OF MAGNETIC RESONANCE IMAGING, Issue 5 2010Tryggve H. Storås MS Abstract Purpose: To investigate the contrast of three-dimensional balanced steady state free precession (3D bSSFP) in the two component T2 model and to apply the results to optimize 3D bSSFP for prostate imaging at 1.5 Tesla. Materials and Methods: In each of seven healthy volunteers, six 3D bSSFP acquisitions were performed with flip angles (,) equally spaced between 10° and 110°. Predictions of signal and contrast were obtained from synthetic bSSFP images calculated from relaxation parameters obtained from a multi-spin-echo acquisition. One biexponential and two monoexponential models were applied. Measured and predicted signals were compared by simple linear regression. Results: The measured contrast to signal ratio increased continuously with ,. Mean R2 for the biexponential model was almost constant for , in the range 50,110°. The biexponential model was a better predictor of the measured signal than the monoexponential model. A monoexponential model restricted to the echoes TE = 50,125 ms performed similar to the biexponential model. The predicted contrast peaked at , between 50° and 90°. Conclusion: Prostate imaging with bSSFP benefited from high flip angles. The biexponential model provided good signal prediction while predictions from the monoexponential models are dependent on the range of TE used for T2 determination. J. Magn. Reson. Imaging 2010;31:1124,1131. © 2010 Wiley-Liss, Inc. [source] Excessive longitudinal FEV1 decline and risks to future health: A case,control study,AMERICAN JOURNAL OF INDUSTRIAL MEDICINE, Issue 12 2009Mei Lin Wang MD Abstract Background Accelerated loss of forced expiratory volume in 1,s (FEV1) in an individual is considered an indicator of developing lung disease. Methods We investigated longitudinal FEV1 slopes, calculated by simple linear regression, and adverse health outcomes after 10,30 years, among 1,428 chemical plant workers. Cases were defined by FEV1 slopes below 5th percentile values for the cohort. Cases were matched with controls (107 pairs) for race, gender, smoking status, year of birth, age, height, and calendar year at first test. Matched pair statistics were used for comparisons. Results Cases had a higher proportion, compared to controls, of diagnosis of COPD or emphysema (17.8% vs. 1.9%, P,=,0.0002), medication use for respiratory diseases (24.3% vs. 4.7%, P,<,0.0001), dyspnea (15% vs. 3.7%, P,=,0.0042), and wheezing or rhonchi on examination (10.3% vs. 1.9%, P,=,0.0225). Conclusions Chemical plant workers who experienced accelerated FEV1 declines experienced four to nine times as many adverse health conditions over 10,30 years. Am. J. Ind. Med. 52:909,915, 2009. © 2009 Wiley-Liss, Inc. [source] Comparison of three diagrammatic keys for the quantification of late blight in tomato leavesPLANT PATHOLOGY, Issue 6 2009F. M. Corrêa Three diagrammatic grading keys were designed for the assessment of the severity of late blight (caused by Phytophthora infestans) in tomato leaves. Simplified and broad keys considered, respectively, six (3, 12, 22, 40, 60 and 77%) and eight (3, 6, 12, 22, 40, 60, 77 and 90%) levels of disease severity, whilst a modified key based on a previous proposal for potato late blight considered six levels (1, 5, 10, 16, 32 and 50%). The keys were validated by 24 evaluators who assessed digital images of tomato leaves exhibiting different areas with lesions. Evaluator errors were compared using a mixed model in which evaluators were considered as random effects and the keys and evaluations as fixed effects. The accuracy and precision of the evaluators were compared by simple linear regression between the estimated and actual values of disease severity. The repeatability of evaluators was assessed using Pearson's correlation coefficient. There was significant (P , 0·001) variability amongst the errors made by evaluators, although the precision of each of the three keys was high with a coefficient of determination (R2) of 0·96, 0·93 and 0·83 for the simplified, broad and modified key, respectively. Repeatability of estimations amongst the evaluators was adequate (correlation coefficients of 0·91, 0·91 and 0·90 for the three keys, respectively). The simplified and broad keys resulted in higher precision and accuracy for the estimation of severity than did the modified key. Since the simplified key considers a smaller number of disease severity levels, its use is recommended in the assessment of late blight in tomato leaves. [source] Estimation of nitrogen concentration and in vitro dry matter digestibility of herbage of warm-season grass pastures from canopy hyperspectral reflectance measurementsGRASS & FORAGE SCIENCE, Issue 2 2008P. J. Starks Abstract Remote sensing of nitrogen (N) concentration and in vitro dry matter digestibility (IVDMD) in herbage can help livestock managers make timely decisions for adjusting stocking rate and managing pastures during the grazing season. Traditional laboratory analyses of N and IVDMD are time-consuming and costly. Non-destructive measurements of canopy hyperspectral reflectance of pasture may provide a rapid and inexpensive means of estimating these measures of nutritive value. Using a portable spectroradiometer, canopy reflectance was measured in eight warm-season grass pastures in the USA in June and July in 2002 and 2003 to develop and validate algorithms for estimating N concentration and IVDMD of herbage. Nitrogen concentration of herbage was linearly correlated (r = 0·82; P < 0·001) with a ratio of reflectance in the 705- and 1685-nm wavebands (R705/R1685) and IVDMD was correlated with R705/R535 (r = 0·74; P < 0·001). Compared with simple linear regressions of N concentration and IVDMD in herbage with two-waveband reflectance ratios, multiple regression, using maximum r2 improvement, band-depth analysis with step-wise regression, and partial least-squares regression enhanced the correlation between N concentration and IVDMD of herbage and canopy reflectance values (0·81 , |r| , 0·90; P < 0·001). Validation of the prediction equations indicated that multiple regression only slightly improved accuracy of a model for predicting N concentration and IVDMD of herbage compared with simple linear regression of reflectance ratios. Results suggest that the N concentration and IVDMD of herbage of warm-season grass pastures can be rapidly and non-destructively estimated during the grazing season using canopy reflectance in a few narrow wavebands. [source] | ||||||||||||||||