Comparative studies of meat III. Rates of fattening in relation to the percentage of muscular and fatty tissue in a carcass

1949 ◽  
Vol 39 (4) ◽  
pp. 347-358 ◽  
Author(s):  
E. H. Callow
Keyword(s):  
Linear Regression ◽  
Comparative Studies ◽  
Close Correlation ◽  
Generalized Equation ◽  
Regression Equation ◽  
Muscular Tissue ◽  
Fatty Tissue ◽  
Linear Regression Equation ◽  
Biological Analysis

1. It has been shown in a previous paper (Callow, 1948) that, with ‘standard’ carcasses of cattle, sheep and pigs containing more than 18 % of fatty tissue, FT/C, there is a close correlation between FT/C and MT/C, the percentage of muscular tissue. This is shown by the linear regression equationMT/C = 76·1 — 0·684FT/C ± 1·0 (r= — 0·9782).The reasons for this close correlation and the effects of varying rates of fattening on the constants of the generalized equationMT/C = a — bFT/Chave been deduced by a mathematical and biological analysis of the data.

scholarly journals Relationship between Cognitive Style and Habits of Mind

2019 ◽  
Vol 2 (1) ◽  
pp. 23
Author(s):  
Hayatun Nufus ◽  
Rezi Ariawan
Keyword(s):  
Linear Regression ◽  
Cognitive Style ◽  
Significance Test ◽  
Regression Equation ◽  
Coefficient Of Determination ◽  
Habits Of Mind ◽  
Linear Regression Equation ◽  
Research Subjects ◽  
Analysis Technique ◽  
The Relationship

This research is a correlational study that examines the relationship between cognitive style and habits of mind. The research subjects involved 4th semester students in the Department of Mathematics Education at the Faculty of Tarbiyah and Teacher Training of UIN Suska Riau which consisted of students with heterogeneous academic abilities. Cognitive style data was collected using the GEFT question instrument with test techniques. Habits of mind data were collected using a questionnaire instrument with a questionnaire distribution technique. The data analysis technique begins with the Pearson Product Moment correlation test which is continued with the significance test and the calculation of the magnitude of the relationship that occurs using the coefficient of determination. Because the data is positively correlated, it continues with determining the linear regression equation. The results showed that there was a significant weak correlation between cognitive style and habits of mind with a relationship score of 6% and a linear regression equation y '= 36.35 + 0.31 x.

Coronal Suture Pathology and Synostotic Progression in Rabbits with Congenital Craniosynostosis

1996 ◽  
Vol 33 (5) ◽  
pp. 369-378 ◽  
Author(s):  
Mark P. Mooney ◽  
Timothy D. Smith ◽  
Annie M. Burrows ◽  
Herbert L. Langdon ◽  
Cynthia E. Stone ◽  
...  
Keyword(s):  
Linear Regression ◽  
Inbred Strain ◽  
Rabbit Model ◽  
Regression Equation ◽  
Histologic Examination ◽  
Coronal Suture ◽  
Linear Regression Equation ◽  
Cross Sectional ◽  
High Tension ◽  
Single Focus

The purpose of the present study was to describe coronal suture pathology and cross sectional synostotic progression in an inbred strain of rabbits with congenital craniosynostosis. Calvaria from 102 perinatal rabbits (39 unaffected; 63 bilateral or unilateral synostosis) were collected at fetal days 21 (n = 12), 25 (n = 20), 27 (n = 22), 30 (term) (n = 32), and 3 days post-term (n = 16) for gross morphologic and histologic examination. Synostotic foci, the extent of relative bony bridging, and suture morphology were evaluated qualitatively and quantitatively. Of the 204 coronal sutures examined, 91 sutures were synostosed, and 113 were patent. All synostosed sutures showed similar foci by day 25, which originated as bony bridges in the middle of each suture on the ectocortic surface. Bony bridging width increased significantly (p < .001) from day 25 through 3 days post-term, and was best described by a linear regression equation. Osteogenic front areas of synostosed sutures were up to 2.5 times greater than patent sutures in term fetuses. Findings demonstrate that coronal suture synostosis in the congenital rabbit model (1) begins early during suture morphogenesis (before 25 days of gestation); (2) consistently radiates from a single focus corresponding to a normal interdigitating region (i.e., a high-tension environment); (3) varies in onset and rate as evidenced by low R2 value between age and extent of bony bridging; and (4) is the result of early hyperostosis of the osteogenic fronts and sutural agenesis. A number of possible pathogenetic mechanisms are discussed.

Preliminary Study on Prediction Model of Forming Tubular Bulge Height for a Thick-Plate

2011 ◽  
Vol 314-316 ◽  
pp. 763-766
Author(s):  
Dan Liu ◽  
Xiao Ting Xiao ◽  
Yi Juan Liao ◽  
Zheng Rong Zhang
Keyword(s):  
Linear Regression ◽  
Prediction Model ◽  
Sheet Metal ◽  
Process Parameters ◽  
Thick Plate ◽  
Regression Equation ◽  
Linear Regression Equation ◽  
Forward Extrusion ◽  
Inner Diameter ◽  
Bulge Height

To form the thick-plate with the tubular bulge, the backward and forward extrusion and punch process is proposed. The thickness of sheet metal, the inner diameter of tubular bulge, the diameter of punch-die, the forward extrusion depth and other process parameters are set by orthogonal regression design method and these groups of values are used respectively to simulate the combined extruding and punching process by the plastic analysis software DEFORM3D. And then, the linear regression equation is obtained between the bulge height and process parameters. The results indicate that the main factors affecting the bulge height are the thickness of sheet metal and diameter of punch-die within a certain range. However, the inner diameter of tubular bulge and the forward extrusion depth have a little contribute to bulge height. Also, the reliability of linear regression equation is not fine and the prediction model of tubular bulge needs to a more in-depth study.

Incisor growth in twins during the seventh and eighth months of foetal life

1963 ◽  
Vol 12 (3) ◽  
pp. 238-246 ◽  
Author(s):  
Maurice V. Stack
Keyword(s):  
Linear Regression ◽  
Regression Equation ◽  
Linear Regression Equation ◽  
Central Incisor ◽  
Dental Tissue ◽  
Lower Upper ◽  
Incisor Growth ◽  
Foetal Life ◽  
Similar Development

SUMMARYWeights of mineralized dental tissue have been determined in incisors dissected from ten pairs of twins failing to survive beyond 7-8 months' gestation. Logarithms of weights were compared as ratios (lower/upper) with data from foetuses of similar development. Intra-twin differences were thus shown to be significantly less than inter-twin differences when comparing central incisors. Lateral incisors were too variable to allow this demonstration. The linear regression equation combining logarithms of lower and upper central incisor weights was suitable for estimating foetal age to within one week of the recorded age.

Comparative studies of meat V. Factors affecting the iodine number of the fat from the fatty and muscular tissues of cattle

1956 ◽  
Vol 48 (1) ◽  
pp. 61-73 ◽  
Author(s):  
E. H. Callow ◽  
S. R. Searle
Keyword(s):  
Iodine Number ◽  
Comparative Studies ◽  
Analysis Of Covariance ◽  
Muscular Tissue ◽  
Fatty Tissue ◽  
Factors Affecting ◽  
Rectangular Hyperbola ◽  
Straight Line ◽  
Line Relationship ◽  
Muscular Tissues

1. Carcasses of twenty-one fat cattle (from six cows, ten steers and five heifers, aged from 12 months to 12 years and representing seven breeds) have been dissected into nine joints, and the fatty and muscular tissue from each joint dissected and analysed for fat. The iodine number of each sample of fat has been determined.2. The fat in fatty tissues ranged from 28·3 to 96·7%, and in muscular tissues from 1·3 to 14·2%. Iodine numbers of fat from fatty tissues ranged from 34·0 to 69·0 and those of fat from muscular tissues from 45·9 to 73·2.3. By an analysis of covariance it has been possible to reduce these data to two families of regression lines—those for fatty tissue and those for muscular tissue.4. The equations for fatty tissue have the following generalized form:I.N. = AFT + CFT + JFT + b1F/FT,where AFT = 55·6 ± 1·7 and is a general constant,CFT is a series of constants for the various carcasses and ranges from +12·6 to −6·7,JFT is a series of constants for the various joints and ranges from +6·6 to −10·3,b1 is a general constant with the value −0·052(± 0·025),F/FT is the percentage of fat in any given sample of fatty tissue, and I.N. is its iodine number.5. A similar set of equations has been deduced for muscular tissue. Here, however, the relation between iodine number and percentage of fat is a rectangular hyperbola. Consequently, the inverse (Z) of the percentage of fat (in order to get a straight-line relationship) has been used.

Experiment of Artificial Floating Island Displacement Pile Fixation

2012 ◽  
Vol 220-223 ◽  
pp. 1670-1674
Author(s):  
Fang Li Su ◽  
Sheng Yu Shi ◽  
Hai Fu Li ◽  
Tie Liang Wang
Keyword(s):  
Experimental Data ◽  
Linear Regression ◽  
Flow Rate ◽  
Vertical Direction ◽  
Regression Equation ◽  
Maximum Force ◽  
Linear Regression Equation ◽  
Floating Island ◽  
The Impact

For providing refer to the experimental data of artificial floating island in river north, this study will get stability characteristics of artificial floating islands displacement pile fixation on simulating the impact of different flow rate of water. Analysising physical stress of artificial floating island displacement pile fixation and simulation, result shows that the sum of floating island of buoyancy and the maximum force of two fiber rope in the vertical direction should be greater than the maximum gravity of the floating island plants and ensure the maximum force of the two fiber rope in the horizontal direction must be greater than the flow momentum, the quality of floating island can be increased for improving stability. Depend on the different flow of water and linear regression equation, the distance between the floating island should be arranged reasonably.

scholarly journals PENGARUH KOMPENSASI DAN LINGKUNGAN KERJA TERHADAP SEMANGAT KERJA PADA KOPDIT CU MANDIRI TEBING TINGGI

2021 ◽  
pp. 213-223
Author(s):  
Elisabeth Simangunsong ◽  
Joana L. Saragih ◽  
Betniar Purba ◽  
Imelda R Purba
Keyword(s):  
Linear Regression ◽  
Work Environment ◽  
Positive Influence ◽  
Regression Equation ◽  
Coefficient Of Determination ◽  
Employee Morale ◽  
Linear Regression Equation ◽  
Significance Level ◽  
Environment Variables ◽  
Positive Meaning

The purpose of this study was to analyze the effect of compensation and work environment on employee morale at the CU Mandiri Tebing Tinggi Kopdit. Benefits of Research: Provide information material to the management of CU Mandiri Tebing Tinggi Kopdit about the effect of compensation and work environment on employee morale and For other researchers it can be used as a reference in conducting studies or research with the same subject matter as well as input for interested parties directly with this research. The number of samples was 96 respondents, the method of collecting data was through questionnaires and documentation, the variables studied were about the effect of compensation and work environment on employee morale at the Cooperative Unit of CU Mandiri Tebing Tinggi partially and simultaneously on work morale and data analysis methods with multiple regression. The results showed the linear regression equation: Linear regression equation: SK = 0.558 + 0.797Kom + 0.448LK., indicating the regression coefficient of the compensation variable (Kom) and work environment (LK), which was positive, meaning that all variables had a positive influence on work morale. The correlation coefficient (R) = 0.886, which means that the relationship between the compensation variable (Kom) and the work environment (LK) on work morale is very strong. The coefficient of determination (R2) = 0.785 means that the variable compensation (Kom) and work environment (LK) is able to explain 78.5% of work morale, while 21.5% is influenced by other factors. The calculated t value of the compensation variable = 6.871 and the work environment = 3.273 > t table which shows a significance number of 0.000 < 0.05, then the two variables have a partially significant effect on work morale. The calculated F value = 83.058 > F table with a significance level of 0.000 < 0.05, then Ho is rejected and H1 is accepted, meaning that the compensation variable (Kom) and work environment (LK) have a significant effect simultaneously on work morale. Based on the conclusion above, it is better if the Cooperative of CU Mandiri Tebing Tinggi needs to increase the compensation provided and the work environment to encourage employee morale so as to create job satisfaction. , Judging from the value of the coefficient of determination (R2) = 0.785, it means that compensation and work environment variables are able to explain 78.5% of work spirit while 21.5% is influenced by other factors. Other factors that affect morale should be investigated from the internal and external environment.

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