Colonization-extinction dynamics of opossums on small islands in Panama

2000 ◽  
Vol 78 (11) ◽  
pp. 1972-1979 ◽  
Author(s):  
William D Boyett ◽  
Mark J Endries ◽  
Gregory H Adler
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Small Islands ◽  
Metapopulation Model ◽  
Island Size ◽  
Dependent Variables ◽  
Isolation Distance ◽  
The Mean ◽  
Central Panama ◽  
Metachirus Nudicaudatus

We studied the distributions and colonization-extinction dynamics of five species of opossums (Didelphis marsupialis, Marmosa robinsoni, Philander opossum, Caluromys derbianus, and Metachirus nudicaudatus) on 12 small islands in Gatun Lake in central Panama. Opossums were censused by monthly livetrapping from 1991 (eight islands) or 1993 (four islands) through 1995. We recorded 75 colonizations over the course of the study. Didelphis marsupialis was the most frequent colonizer and accounted for 56% of all colonizations recorded. However, only four D. marsupialis populations that reproduced successfully resulted from these colonizations, and most populations went extinct. Marmosa robinsoni and P. opossum also frequently colonized these islands but rarely established successful populations. Multiple linear regression was used to relate the mean numbers of colonizations and population establishments per year and mean and standardized persistence times of all five species of opossums to island size and isolation. These four dependent variables were not related to island area or isolation distance. This system, characterized by frequent colonizations and extinctions, fit the mainland-island metapopulation model, and nearby mainland areas that maintained persistent populations of all five species provided colonists to the small islands.

Breastfeeding Self-Efficacy and Its Relationship with the Perceived Stress and the Breastfeeding Performance in Iranian Mothers with Late Preterm Infants, 2019

2020 ◽  
Author(s):  
Akram Kahforoushan ◽  
Shirin Hasanpour ◽  
Mojgan Mirghafourvand
Keyword(s):  
Standard Deviation ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Preterm Infants ◽  
Perceived Stress ◽  
Self Efficacy ◽  
Short Form ◽  
Late Preterm ◽  
Late Preterm Infants ◽  
The Mean

Abstract BackgroundLate preterm infants suffer from many short-term and long-term problems after birth. The key factor in fighting these problems is effective breastfeeding. The present study aimedto determine the breastfeeding self-efficacy and its relationship with the perceived stress and breastfeeding performance in mothers with late preterm infants. MethodsIn this prospective study, 171 nursing mothers with late preterm infants born in Alzahra Medical Center of Tabriz, Iran, who met the conditions of this study were selected through convenience sampling. The Breastfeeding Self-Efficacy Scale-Short Form (BSES- SF) was employed to measure breastfeeding self-efficacy and 14-item Perceived Stress Scale (PSS14) was used to measure the perceived stress during 24 hours after giving birth and when the child was 4 months old the breastfeeding performance was measured by the standard breastfeeding performance questionnaire. The data were analyzed by Pearson and Spearman’s correlation tests, independent t-test, one-way ANOVA, and Multiple Linear Regression.ResultsThe mean (standard deviation) of breastfeeding self-efficacy equaled 50.0 (7.8) from the scores ranging between13-65 and the mean (standard deviation) of the perceived stress equaled to 26.5 (8.8) from the scores ranging between 0-56. The median (25-75 percentiles) of breastfeeding performance score in the mothers equaled 2.0 (1.0 to 3.0) from the scores ranging between 0-6. On the basis of multiple linear regression and through adjusting the personal-social characteristic, by increasing the score of the breastfeeding self-efficacy, the perceived stress was decreased to a statistically significant amount (B=-0.1, 95%CI=-0.3 to 0.0), however, there was no statistically significant relationship between breastfeeding self-efficacy and breastfeeding performance (p=0.418). ConclusionDue to the modifiable variability of breastfeeding self-efficacy and its role in perceived maternal stress, the development of appropriate strategies to further increase breastfeeding self-efficacy and provide more support to these mothers and infants is of particular importance.

scholarly journals Comparison of Methods for Harvest Prediction in ‘Gigante’ Cactus Pear

2019 ◽  
Vol 11 (14) ◽  
pp. 216 ◽  
Author(s):  
Bruno V. C. Guimarães ◽  
Sérgio L. R. Donato ◽  
Ignacio Aspiazú ◽  
Alcinei M. Azevedo ◽  
Abner J. de Carvalho
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Regression Models ◽  
Coefficient Of Determination ◽  
Cactus Pear ◽  
Federal Institute ◽  
The Mean ◽  
Artificial Neural

Behavior analysis and plant expression are the answers the researcher needs to construct predictive models that minimize the effects of the uncertainties of field production. The objective of this study was to compare the simple and multiple linear regression methods and the artificial neural networks to allow the maximum security in the prediction of harvest in ‘Gigante’ cactus pear. The uniformity test was conducted at the Federal Institute of Bahia, Campus Guanambi, Bahia, Brazil, coordinates 14°13′30″ S, 42°46′53″ W and altitude of 525 m. At 930 days after planting, we evaluated 384 basic units, in which were measured the following variables: plant height (PH); cladode length (CL), width (CW) and thickness (CT); cladode number (CN); total cladode area (TCA); cladode area (CA) and cladode yield (Y). For the comparison between the artificial neural networks (ANN) and regression models (single and multiple-SLR and MLR), we considered the mean prediction error (MPE), the mean quadratic error (MQE), the mean square of deviation (MSD) and the coefficient of determination (R2).The values estimated by the ANN 7-5-1 showed the best proximity to the data obtained in field conditions, followed by ANN 6-2-1, MLR (TCA and CT), SLR (TCA) and SLR (CN). In this way, the ANN models with the topologies 7-2-1 and 6-2-1, MLR with the variables total cladode area and cladode thickness and SLR with the isolated descriptors total cladode area and cladode number, explain 85.1; 81.5; 76.3; 74.09 and 65.87%, respectively, of the yield variation. The ANNs were more efficient at predicting the yield of the ‘Gigante’ cactus pear when compared to the simple and multiple linear regression models.

scholarly journals Choroidal Remodeling Distribution Pattern in the Macular Region in Chinese Young Patients with Myopia

2021 ◽  
Author(s):  
Jun Wang ◽  
Xin Ye ◽  
Xiangjun She ◽  
Jiahao Xu ◽  
Yiqi Chen ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Distribution Pattern ◽  
Young Patients ◽  
Enhanced Depth Imaging ◽  
Potential Marker ◽  
Luminal Area ◽  
The Mean ◽  
Foveal Center ◽  
The Relationship

Abstract Background: The pathogenesis of myopia has been found to be associated with the blood supply of the choroid. This study aimed to determine the relationship between distribution pattern of the choroidal remodeling and the degree of myopia in young patients.Methods: Young patients (age < 18 years) with spherical equivalent of less than -12 diopters (D) were included. Spectral-domain optical coherence tomography (SD-OCT) with enhanced depth imaging (EDI) modality was used to measure the choroidal thickness (CT) and choroidal vascularity index (CVI) in the macular regions. CVI was calculated as the proportion of luminal area to choroidal area and was measured within 1 mm and 3 mm nasal (N1 and N3), temporal (T1 and T3), superior (S1 and S3), and inferior (I1 and I3) to the foveal center. CT and CVI were compared across different ages (i.e., 5~9 years, 10~13 years, and 14~18 years), axial lengths (ALs) (i.e., 21.00~25.00mm and 25.01~29.00mm), and spherical equivalents (SEs) (i.e., SE>-0.5D, -0.5~-3.0D, -3.01~-6.0D, and <-6.0D). Multiple linear regression was applied to examine the associations amongst age, AL, SE, and CVI of different locations.Results: 164 of 172 eyes from 85 volunteers were included. The mean CT in the central foveal was 269.87 ± 63.32µm (ranging from 93.00µm to 443.00µm). The mean sub foveal-CVI was 67.66 ± 2.40% (ranging from 57.84% to 79.60%). Multiple linear regression results revealed significant correlations between SE and T1-CVI (p < 0.05, r2= 0.082, β= 0.194), N1-CVI (p < 0.05, r2= 0.039, β= 0.212). Simple linear regression results revealed that T1-CVI (p < 0.05, r2 = 0.09) and T3-CVI (p < 0.05, r2 = 0.05) were negatively correlated with SE; N1-CVI (p < 0.05, r2 = 0.05) and N3-CVI (p < 0.05, r2 = 0.04) were negatively correlated with SE. Conclusions and Relevance: CVI in the horizontal meridian underwent the largest change as myopia worsened. Temporal and nasal CVIs within the r =1mm and r=3mm sub foveal range were positively associated with degree of myopia in young patients. The CVI value may be used to assess the vascular status of the choroid and be a potential marker of myopic progression.

scholarly journals Ridge Estimation's Effectiveness for Multiple Linear Regression with Multicollinearity: An Investigation Using Monte-Carlo Simulations

2021 ◽  
pp. 278-281
Author(s):  
O. G. Obadina ◽  
Adedayo Funmi Adedotuun ◽  
O. A. Odusanya
Keyword(s):  
Monte Carlo ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Random Error ◽  
Ordinary Least Squares ◽  
Linear Regression Coefficient ◽  
Monte Carlo Simulation Technique ◽  
Independent Variables ◽  
Average Mean Square Error ◽  
The Mean

The goal of this research is to compare multiple linear regression coefficient estimations with multicollinearity. In order to quantify the effectiveness of estimations by the mean of average mean square error, the ordinary least squares technique (OLS), modified ridge regression method (MRR), and generalized Liu-Kejian method (LKM) are compared (AMSE). For this study, the simulation scenarios are 3 and 5 independent variables with zero mean normally distributed random error of variance 1, 5, and 10, three correlation coefficient levels; i.e., low (0.2), medium (0.5), and high (0.8) are determined for independent variables, and all combinations are performed with sample sizes 15, 55, and 95 by Monte Carlo simulation technique for 1,000 times in total. As the sample size rose, the AMSE decreased. The MRR and LKM both outperformed the LSM. At random error of variance 10, the MRR is the most suitable for all circumstances.

Association of increased time from chemoradiation (CRT) to esophagectomy (E) with increased surgical complications (Cx) in esophageal cancer (EC).

2013 ◽  
Vol 31 (4_suppl) ◽  
pp. 77-77
Author(s):  
Joshua E. Meyer ◽  
Alan Thomay ◽  
Karen J. Ruth ◽  
Talha Shaikh ◽  
Andre A. Konski ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Clinical Stage ◽  
Pathologic Complete Response ◽  
Multivariable Analysis ◽  
Optimal Timing ◽  
Time Interval ◽  
Data Set ◽  
Estimated Blood Loss ◽  
The Mean

77 Background: EC is often treated with CRT followed by E. E is typically performed 6 weeks after completion of CRT, but the optimal timing is unknown. Previous work has shown that a longer time interval (TI) between CRT and E resulted in a higher percentage of patients (pts) with pathologic complete response. This study was undertaken to determine whether this improved response comes at the expense of increased surgical Cx. Methods: Complete records were available for 85 pts who underwent CRT and subsequent E at a single academic center from 2001-2011. Surgical Cx were collected. Univariable and multivariable analyses were performed to investigate the association between length of TI from CRT to E and Cx, adjusting for age, gender, and surgery type. Multiple linear regression was performed to examine the association of length of stay (LOS) and estimated blood loss (EBL) with TI, adjusting for covariates. Results: Of 85 patients, 72 were male and the histology was adenocarcinoma in 72. The median age was 61 (range: 36-80), the most common clinical stage was T3N1 and 60% of pts had ECOG performance status of 1 (range 0-2). The median length of CRT (most commonly Cisplatin, 5FU and 50.4 Gy) was 37 days and median TI from initiation of CRT to E was 89 days (range: 64-242). 59 pts (69%) experienced at least 1 complication. The mean TIs for pts with and without Cx were 97 and 87 days (P=0.019). When specific Cx were examined, the mean TI for pulmonary Cx was greater (107 v. 89 days; P=0.018). Patients experiencing anastamotic leaks had shorter mean TIs (83 v. 96 days; P=0.022). Multiple linear regression showed a positive association between LOS and TI (p=0.0027) but none with EBL. On multivariable analysis, increased TI predicted for pulmonary complications (OR 1.05, P=0.0061) and LOS (OR 1.03, P=0.033). Increased TI predicted for decreased risk of anastamotic leak (OR 0.94, P=0.063). Conclusions: In this retrospective data set, we demonstrated an association between longer TI from CRT to E and pulmonary toxicity in EC pts. Longer TI was also associated with increased LOS. In contrast, anastamotic leaks were associated with shorter TIs. These data suggest TI from CRT to E may impact the risk of Cx.

FAKTOR-FAKTOR YANG MEMPENGARUHI KEPUTUSAN PEMBELIAN PADA PT SHAFCO MULTI TRADING MEDAN

2020 ◽  
Vol 5 (1) ◽  
pp. 315
Author(s):  
Yurmaini Yurmaini ◽  
Karmila Karmila
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Product Quality ◽  
Quantitative Research ◽  
Research Data ◽  
T Test ◽  
Linear Regression Equation ◽  
Purchasing Decisions ◽  
Independent Variables ◽  
Dependent Variables

This study is shown to determine the factors that influence purchasing decisions at PT. Safco Multi Trading Medan. Price and product quality as independent variables and purchasing decisions as dependent variables. The method used in this research is to use quantitative research. Data obtained and analyzed using multiple linear regression equation with the equation Y = 4.020 + 0.378X1 + 0.500X2. This analysis includes the t test in the effect of price on purchasing decisions is 3.619 with Sig 0.001 and the t test in the effect of product quality on purchasing decisions is 5.639 with Sig 0.000, R-Square of 0.391, f test of 26.355 with Sig 0.000. The results showed that the price had a positive and significant effect on purchasing decisions at customers of PT. Shafco Multi Trading. Product quality has a positive and significant effect of 39.1% on purchasing decisions at customers of PT. Shafco Multi Trading, purchasing decision is a moderating variable in influencing product quality on purchasing decisions at PT. Shafco Multi Trading so that 60.9% is influenced by other factors not examined by researchers.

ANALYSIS OF THE COMPOSITION OF WATER-ALCOHOL MIXTURES USING THE INFRARED ABSORPTION SPECTRA OF THEIR VAPORS

2021 ◽  
Vol 88 (6) ◽  
pp. 933-941
Author(s):  
V. L. Vesnin
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Absorption Spectra ◽  
Infrared Absorption ◽  
Liquid Mixture ◽  
The Mean ◽  
Alcohol Mixtures ◽  
Infrared Absorption Spectra ◽  
Water Alcohol

The article presents the results of studies of infrared absorption spectra of saturated vapors of alcohols and alcohol-containing mixtures in the range of 1.3—1.5 μm. A method was developed for the quantitative determination of the composition of water-alcohol mixtures based on the use of multiple linear regression, and a range of methanol concentrations was determined, in which the nonlinearity of the dependence of the concentration of alcohols in saturated vapors over a liquid mixture on the concentration of alcohols in this liquid mixture does not significantly affect the results of analysis of the mixture composition. A method for optimizing a set of wavelengths for multiple linear regression, based on minimizing the mean-square error in determining the concentration is proposed and implemented. The developed methods make it possible to determine the presence of small (<1%) amounts of methanol against the background of large amounts of ethanol and water using relatively inexpensive and accessible spectroscopic equipment.

scholarly journals Multiple linear regression for the analysis of the parameters used in dyes decolourisation by ozonation techniques

2018 ◽  
Vol 154 ◽  
pp. 01003 ◽  
Author(s):  
Siti Fatimah ◽  
Wiharto Wiharto
Keyword(s):  
Linear Regression ◽  
Prediction Model ◽  
Multiple Linear Regression ◽  
Predictive Modeling ◽  
Dye Decolorization ◽  
Acid Orange 7 ◽  
Independent Variables ◽  
Dependent Variables ◽  
The Cost ◽  
Ozonation Process

The ozonation process of dye Acid Orange 7 (AO7), Acid Yellow 19 (AY19), and Acid Black 1 (AB1) have been performed. The experimental results predicted the magnitude of the influence of each variable by using Multiple Linear Regression (MLR). This process produces predictive modeling of the variables studied. The variables studied in this ozonation process are independent variables consisting of ozone concentration (mg/L), concentration of dye (mg/L), pH and temperature (°C). The dependent variables studied were the percentage of dye decolorization. The feasibility of the prediction model used has also been tested using the t-test. Based on the prediction model, R2 values for AO7, AY19, and AB1 dyes are 0.84. 0.87, and 0.93 respectively. The analysis of the influence of the independent variables on the percentage of dye decolorization predicted that the concentration of ozone, dyestuff concentration and pH, significantly influenced the ozonation process of AO7, AY19, and AB1. In the ozonation process the temperature variables have a significant effect on AY19 and AB1, but stronger influence on AO7 ozonation process. Based on the predictions of the influence of each variable, the process in the laboratory can be optimized more effectively and efficiently, so that the cost and time factor can be reduced.

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