scholarly journals The effect of group composition and mineral supplementation during rearing on the behavior and welfare of replacement gilts

2020 ◽  
Vol 4 (2) ◽  
pp. 1038-1050 ◽  
Author(s):  
Phoebe Hartnett ◽  
Laura A Boyle ◽  
Keelin O’Driscoll
Keyword(s):  
Mixed Models ◽  
Linear Mixed Models ◽  
Experimental Period ◽  
Good Health ◽  
The Body ◽  
Play Behavior ◽  
White Line ◽  
Sow Longevity ◽  
Line Separation ◽  
Copper Zinc

Abstract Sow longevity supported by good health and reproductive performance is necessary to optimize sow lifetime performance. In some countries, replacement gilts are reared with finisher pigs destined for slaughter, so they are exposed to sexual and aggressive behaviors performed by males. This is associated with stress and injury. Moreover, diets formulated for finishers are not designed to meet the needs of replacement gilts and may not supply the necessary minerals to promote limb health, optimal reproduction, and, thus, sow longevity. In this 2 × 2 factorial design experiment with 384 animals (32 pens [12 animals per pen]), we investigated the effect of female-only (FEM) or mixed-sex (MIX) rearing, with (SUPP) or without (CON) supplementary minerals (copper, zinc, and manganese) on locomotion, salivary cortisol levels, behavior, body lesions (BL), and hoof health of gilts. The experimental period began at transfer to the finisher stage (day 81.3 ± 0.5 of age; day 0) until breeding age (day 196 ± 0.5 of age; day 115). Locomotion was scored (0–5) biweekly from day 0 until slaughter day 67 or breeding age day 115 for the remaining gilts. Saliva samples were taken monthly from four focal gilts per pen. All counts of aggressive, harmful, sexual, and play behavior were recorded by direct observation 1 d biweekly (5- × 5-min observations/pen/d). BL scores were recorded on focal pigs biweekly from day 1 until day 99 on the back, neck, shoulder, flank, and hind quarter on each side of the body. Hind hooves were scored for eight disorders (heel erosion [HE], heel sole separation [HSS], and white line separation [WLS], dew claw length and dew claw cracks, toe length and both vertical and horizontal toe cracks) by severity, and a total hoof lesion score was calculated by summing individual scores. General linear mixed models were used to analyze cortisol, behavior, BL, and total hoof scores. Generalized linear mixed models were used for locomotion, bursitis and individual hoof disorders. There was less aggression (P < 0.05) and sexual behavior in the FEM compared to the MIX groups with more play behavior in MIX compared to FEM groups (P < 0.01). Gilts in the MIX groups had higher BL scores than gilts in the FEM groups (P < 0.001). Total hoof scores were higher in MIX (8.01 ± 0.15) than FEM (7.70 ± 0.12; P < 0.02) gilts. CON diet gilts had higher HE scores than SUPP gilts (P < 0.05). HSS (P < 0.05) and WLS (P < 0.05) scores were higher in MIX than FEM gilts. Rearing gilts in FEM groups had benefits for hoof health likely mediated through lower levels of activity due to male absence, and minerals helped reduce HE.

Glucose Calibration Modeling in Blood with Spline Regression Approaching to Non-Invasive Tools

2018 ◽  
pp. 144-149
Author(s):  
Ria Hayatun Nur ◽  
Indahwati A ◽  
Erfiani A
Keyword(s):  
Diabetes Mellitus ◽  
Linear Regression ◽  
Good Health ◽  
Cubic Spline ◽  
The Body ◽  
Spline Regression ◽  
Linear Quadratic ◽  
Important Thing ◽  
Non Invasive

In this globalization era, health is the most important thing to be able to run various activities. Without good health, this will hinder many activities. Diabetes mellitus is one of the diseases caused by unhealty lifestyle.There are many treatments that can be done to prevent the occurrence of diabetes. The treatments are giving the insulin and also checking the glucose rate to the patients.Checking the glucose rate needs the tools which is safety to the body. This research want to develop non invasive tool which is safety and do not injure the patient. The purpose of this research is also finding the best model which derived from Linear, Quadratic, and Cubic Spline Regression. Some respondents were taking to get the glucose measuring by invasive and non invasive tools. It could be seen clearly that Spline Linear Regression was the best model than Quadratic and Cubic Spline Regression. It had 70% and 33.939 for R2 and RMSEP respectively.

scholarly journals Heat, Hills and the High Season: A Model-Based Comparative Analysis of Spatio-Temporal Factors Affecting Shared Bicycle Use in Three Southern European Islands

2021 ◽  
Vol 13 (6) ◽  
pp. 3274
Author(s):  
Suzanne Maas ◽  
Paraskevas Nikolaou ◽  
Maria Attard ◽  
Loukas Dimitriou
Keyword(s):  
Correlation Analysis ◽  
Mixed Models ◽  
Linear Mixed Models ◽  
Positive Association ◽  
Sustainable Mobility ◽  
Weather Factors ◽  
Gran Canaria ◽  
Bivariate Correlation ◽  
Temporal Factors

Bicycle sharing systems (BSSs) have been implemented in cities worldwide in an attempt to promote cycling. Despite exhibiting characteristics considered to be barriers to cycling, such as hot summers, hilliness and car-oriented infrastructure, Southern European island cities and tourist destinations Limassol (Cyprus), Las Palmas de Gran Canaria (Canary Islands, Spain) and the Valletta conurbation (Malta) are all experiencing the implementation of BSSs and policies to promote cycling. In this study, a year of trip data and secondary datasets are used to analyze dock-based BSS usage in the three case-study cities. How land use, socio-economic, network and temporal factors influence BSS use at station locations, both as an origin and as a destination, was examined using bivariate correlation analysis and through the development of linear mixed models for each case study. Bivariate correlations showed significant positive associations with the number of cafes and restaurants, vicinity to the beach or promenade and the percentage of foreign population at the BSS station locations in all cities. A positive relation with cycling infrastructure was evident in Limassol and Las Palmas de Gran Canaria, but not in Malta, as no cycling infrastructure is present in the island’s conurbation, where the BSS is primarily operational. Elevation had a negative association with BSS use in all three cities. In Limassol and Malta, where seasonality in weather patterns is strongest, a negative effect of rainfall and a positive effect of higher temperature were observed. Although there was a positive association between BSS use and the number of visiting tourists in Limassol and Malta, this is predominantly explained through the multi-collinearity with weather factors rather than by intensive use of the BSS by tourists. The linear mixed models showed more fine-grained results and explained differences in BSS use at stations, including differences for station use as an origin and as a destination. The insights from the correlation analysis and linear mixed models can be used to inform policies promoting cycling and BSS use and support sustainable mobility policies in the case-study cities and cities with similar characteristics.

scholarly journals Confidence, prediction, and tolerance in linear mixed models

2019 ◽  
Vol 38 (30) ◽  
pp. 5603-5622 ◽  
Author(s):  
Bernard G. Francq ◽  
Dan Lin ◽  
Walter Hoyer
Keyword(s):  
Mixed Models ◽  
Linear Mixed Models

Power for balanced linear mixed models with complex missing data processes

2021 ◽  
pp. 1-19
Author(s):  
Kevin P. Josey ◽  
Brandy M. Ringham ◽  
Anna E. Barón ◽  
Margaret Schenkman ◽  
Katherine A. Sauder ◽  
...  
Keyword(s):  
Missing Data ◽  
Mixed Models ◽  
Linear Mixed Models

130 Utilization of Nutrack to Assess Variance Components and Heritability of Activity Traits

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 17-17
Author(s):  
Lexi M Ostrand ◽  
Melanie D Trenhaile-Grannemann ◽  
Garrett See ◽  
Ty B Schmidt ◽  
Eric Psota ◽  
...  
Keyword(s):  
Animal Model ◽  
Mixed Models ◽  
Variance Components ◽  
Average Speed ◽  
Genetic Variances ◽  
Sow Longevity ◽  
Selection Decisions ◽  
Recorded Data ◽  
Residual Variances ◽  
And Behavior

Abstract Overall activity and behavior are integral components of sows remaining productive in the herd. This investigation studied overall activity of group housed replacement gilts and the heritability of various activity traits. Beginning around 20 wk of age, video recorded data of approximately 75 gilts/group for a total of 2,378 gilts over 32 groups was collected for 7 consecutive d using the NUtrack System, which tracks distance travelled (m), avg speed (m/s), angle rotated (degrees), and time standing (s), sitting (s), eating (s), and laying (s). The recorded phenotypes were standardized to the distribution observed within a pen for each group. The final values used for analysis were the average daily standardized values. Data were analyzed using mixed models (RStudio V 1.2.5033) including effects of sire, dam, dam’s sire and dam, dam’s grandsire and granddam, farrowing group, barn, pen, and on-test date. Sire had an effect on every activity trait P < 0.001), and dam had an effect on average speed (P < 0.001). The dam’s sire had an effect on all activity traits (P < 0.001) and the dam’s grandsire had an effect on average speed (P < 0.001). Heritabilities and variance components of activity traits were estimated in ASReml 4 using an animal model with a two-generation pedigree. Genetic variances are 0.17 +/- 0.029, 0.19 +/- 0.034, and 0.11 +/- 0.024, residual variances are 0.37 +/- 0.023, 0.41 +/- 0.027, and 0.41 +/- 0.022, phenotypic variances are 0.54 +/- 0.018, 0.60 +/- 0.020, and 0.52 +/- 0.016, and heritabilities are 0.32 +/- 0.048, 0.32 +/- 0.049, and 0.21 +/- 0.044 for average speed, distance, and lie respectively. NUtrack offers potential to aid in selection decisions. Given the results presented herein, continued investigation into these activity traits and their association with sow longevity is warranted.

l2-Penalized temporal logit-mixed models for the estimation of regional obesity prevalence over time

2021 ◽  
pp. 096228022110175
Author(s):  
Jan P Burgard ◽  
Joscha Krause ◽  
Ralf Münnich ◽  
Domingo Morales
Keyword(s):  
Parameter Estimation ◽  
Medical Treatment ◽  
Mixed Models ◽  
Generalized Linear Mixed Models ◽  
Linear Mixed Models ◽  
Obesity Prevalence ◽  
Model Parameter ◽  
Model Parameter Estimation ◽  
Public Health Reporting ◽  
Over Time

Obesity is considered to be one of the primary health risks in modern industrialized societies. Estimating the evolution of its prevalence over time is an essential element of public health reporting. This requires the application of suitable statistical methods on epidemiologic data with substantial local detail. Generalized linear-mixed models with medical treatment records as covariates mark a powerful combination for this purpose. However, the task is methodologically challenging. Disease frequencies are subject to both regional and temporal heterogeneity. Medical treatment records often show strong internal correlation due to diagnosis-related grouping. This frequently causes excessive variance in model parameter estimation due to rank-deficiency problems. Further, generalized linear-mixed models are often estimated via approximate inference methods as their likelihood functions do not have closed forms. These problems combined lead to unacceptable uncertainty in prevalence estimates over time. We propose an l2-penalized temporal logit-mixed model to solve these issues. We derive empirical best predictors and present a parametric bootstrap to estimate their mean-squared errors. A novel penalized maximum approximate likelihood algorithm for model parameter estimation is stated. With this new methodology, the regional obesity prevalence in Germany from 2009 to 2012 is estimated. We find that the national prevalence ranges between 15 and 16%, with significant regional clustering in eastern Germany.

Estimation of variance components in normal linear mixed models with additivity

2015 ◽  
Author(s):  
Dário Ferreira ◽  
Sandra S. Ferreira ◽  
Célia Nunes ◽  
João T. Mexia
Keyword(s):  
Mixed Models ◽  
Variance Components ◽  
Linear Mixed Models ◽  
Estimation Of Variance
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