Discussion of Calculation of Power Function with Special Reference to Respiratory Metabolism in Fish

1969 ◽  
Vol 26 (10) ◽  
pp. 2643-2650 ◽  
Author(s):  
Norman R. Glass
Keyword(s):  
Body Weight ◽  
Oxygen Consumption ◽  
Power Function ◽  
Body Weight Data ◽  
Fitting Method ◽  
Wide Range ◽  
Curve Fitting Method ◽  
Parameter Values ◽  
Weight Data ◽  
Range Of Values

The rationale for employing a nonlinear iterative least-squares technique for fitting the well-known power function to oxygen consumption–body weight data is set forth. Twenty-six sets of routine or standard metabolism data from six authors were used to demonstrate the relative merits of two methods of calculating parameter values for the power function. The conclusion was reached that if accuracy in predicting oxygen consumption over a wide range of values of body weight is desired, an iterative curve fitting method may be superior to the much used technique of performing a linear regression on logarithmically transformed data.

scholarly journals Estimating my equilibrium energy intake during lockdown: very introspective study

BMJ ◽  
2020 ◽  
pp. m4561
Author(s):  
R A Lewis
Keyword(s):  
Body Weight ◽  
Energy Intake ◽  
Outcome Measures ◽  
Dietary Energy ◽  
Saturday Morning ◽  
Dietary Energy Intake ◽  
Body Weight Data ◽  
Tuesday Afternoon ◽  
Weight Data ◽  
At Home

AbstractObjectiveTo estimate the daily dietary energy intake for me to maintain a constant body weight. How hard can it be?DesignVery introspective study.SettingAt home. In lockdown. (Except every Tuesday afternoon and Saturday morning, when I went for a run.)ParticipantsMe. n=1.Main outcome measuresMy weight, measured each day.ResultsSleeping, I shed about a kilogram each night (1.07 (SD 0.25) kg). Running 5 km, I shed about half a kilogram (0.57 (SD 0.15) kg). My daily equilibrium energy intake is about 10 000 kJ (10 286 (SD 201) kJ). Every kJ above (or below) 10 000 kJ adds (or subtracts) about 40 mg (35.4 (SD 3.2) mg).ConclusionsBody weight data show persistent variability, even when the screws of control are tightened and tightened.

scholarly journals A Fast Haar Classifier based Gesture Recognition using camShift algorithm and Curve Fitting Method

2012 ◽  
pp. 295-299
Author(s):  
Bhavish Sushiel Agarwal ◽  
Jyoti R Desai ◽  
Snehanshu Saha
Keyword(s):  
Human Computer Interaction ◽  
Gesture Recognition ◽  
Curve Fitting ◽  
Lead Point ◽  
Hand Gestures ◽  
Curve Fit ◽  
Camshift Algorithm ◽  
Fitting Method ◽  
Wide Range ◽  
Curve Fitting Method

The use of hand gestures opens a wide range of application for human computer interaction. The paper makes use of haar classifiers and camShift algorithm to track the movement of hand. Parallelism is introduced at every step by segmenting the data from camshaft into an NxN grid. Every block of the grid now represents a lead point which is calculated from mean of all the points belonging to the particular grid. Now we have only N2 points to recognize the curve that was performed by the user in his action. Finally the fit that was found is compared to pre-defined curve fit data to find out the curve using Mahalanobis equation. Parallelism used in reducing the number of points to be fitted allows the recognition to be faster.

scholarly journals Comparison of a soluble co-formulation of insulin degludec/insulin aspart vs biphasic insulin aspart 30 in type 2 diabetes: a randomised trial

2012 ◽  
Vol 167 (3) ◽  
pp. 453 ◽  
Author(s):  
Leo Niskanen ◽  
Lawrence A Leiter ◽  
Edward Franek ◽  
Jianping Weng ◽  
Taner Damci ◽  
...  
Keyword(s):  
Body Weight ◽  
Insulin Aspart ◽  
Randomised Trial ◽  
Baseline Hba1c ◽  
Body Weight Data ◽  
Biphasic Insulin Aspart 30 ◽  
Article Type ◽  
Full Analysis ◽  
Weight Data

The journal and the authors apologise for errors in Table 2 of this article that was published in the August issue (vol 167, pp 287–294). The n values were incorrectly published. The correct values are presented below and the table is published in full below.Table 2Observed mean changes from baseline HbA1c, FPG and body weight. Data are observed as mean (s.d.) for all randomised subjects (full analysis set).nBaselineaWeek 16bChange from baselineHbA1c (%) IDegAsp618.5 (1.2)6.7 (1.0)−1.8 (1.1)c AF598.5 (0.9)6.6 (0.6)−1.9 (1.1)c BIAsp 30628.6 (1.0)6.7 (0.7)−1.8 (0.9)cFPG (mmol/l) IDegAsp6111.5 (2.6)6.4 (2.2)−5.1 (2.9) AF5911.8 (2.9)6.5 (1.9)−5.3 (3.0) BIAsp 306211.7 (3.1)7.5 (2.1)−4.3 (3.0)Body Weight (kg) IDegAsp6187.5 (16.3)88.6 (16.9)1.1 (2.8) AF5984.9 (14.3)85.6 (14.9)0.7 (2.5) BIAsp 306291.8 (13.5)93.2 (13.1)1.4 (3.2)aValues at randomisation.bLast observation carried forward.c% points.

One Parameter Chi-squared Analysis

2019 ◽  
pp. 18-31
Author(s):  
Carey Witkov ◽  
Keith Zengel
Keyword(s):  
Curve Fitting ◽  
Physical Experiments ◽  
Fitting Method ◽  
Wide Range ◽  
Chi Squared ◽  
Measurement Uncertainties ◽  
Distributed Measurement ◽  
Curve Fitting Method ◽  
The One ◽  
Parameter Case

The chi-squared method for parameter estimation and model testing is developed for the one-parameter case of a line with a slope but no intercept. Curve fitting is motivated, and several methods for curve fitting are introduced. The chi-squared method is shown to be the optimal curve fitting method whenever Gaussian distributed measurement uncertainties and a model are present. The central limit theorem, which assures Gaussian distributed measurement uncertainties for a wide range of physical experiments, is introduced. End-of-chapter problems are included (with solutions in an appendix).

Evaluation of Alternative Methods to Analyze Pig Body Weight Data from Animal Sorting Technologies

2009 ◽  
Vol 25 (6) ◽  
pp. 654-662 ◽  
Author(s):  
A.P. Schinckel ◽  
M. Wastell ◽  
M.E. Einstein ◽  
J.T. Hubbs ◽  
P.V. Preckel
Keyword(s):  
Body Weight ◽  
Alternative Methods ◽  
Body Weight Data ◽  
Weight Data

scholarly journals Brain weight predicts yawn duration across domesticated dog breeds

2019 ◽  
Vol 66 (4) ◽  
pp. 401-405
Author(s):  
Andrew C Gallup ◽  
Lea Moscatello ◽  
Jorg J M Massen
Keyword(s):  
Body Weight ◽  
Large Scale ◽  
Brain Temperature ◽  
Single Species ◽  
Brain Weight ◽  
Canis Lupus Familiaris ◽  
Taxonomic Rank ◽  
Body Weight Data ◽  
Final Sample ◽  
Weight Data

Abstract Previous research shows that yawning enhances intracranial circulation and regulates brain temperature. Consistent with these functional outcomes, yawn duration correlates positively with interspecies variation in brain weight across mammals, with robust relationships documented at both the taxonomic rank of class and the more restricted scale of family (e.g., Felidae). This study provides the first investigation into whether differences in brain weight within a single species, domesticated dogs Canis lupus familiaris, can predict intraspecific variation in yawn duration. Measures of yawn duration were obtained from public videos available online and then paired with previously published brain and body weight data of different dog breeds. The final sample consisted of 272 yawns from 198 dogs across 23 breeds. Consistent with recent studies, we find robust correlations between yawn duration and brain weight across breeds. Moreover, these correlations remain significant after controlling for differences in body weight across breeds. These findings replicate and extend upon past work in this area and provide further support that yawns evolved to serve an important and large-scale neurophysiologic function.

scholarly journals Successful Treatment of a Pacemaker Infection with Intraperitoneal Daptomycin

2016 ◽  
Vol 36 (1) ◽  
pp. 114-117 ◽  
Author(s):  
Anne B. Taegtmeyer ◽  
Nina Kononowa ◽  
Dominique Fasel ◽  
Manuel Haschke ◽  
Felix Burkhalter
Keyword(s):  
Body Weight ◽  
Peak Concentration ◽  
Single Case ◽  
Intraperitoneal Administration ◽  
Therapeutic Drug ◽  
Serum Drug Concentration ◽  
Dose Administration ◽  
Pacemaker Infection ◽  
Body Weight Data ◽  
Weight Data

We investigated the pharmacokinetics of intraperitoneal administration of daptomcyin in a peritoneal dialysis (PD) patient treated for a pacemaker infection with Staphylococcus epidermidis. After initial start of intravenous daptomycin at 9 mg/kg body weight every 48 hours, the therapy was switched to intraperitoneal administration of 5.3 mg/kg body weight in 1 L icodextrin 7.5% with a dwell time of 12 hours overnight every 48 hours. Therapeutic drug monitoring (TDM) was performed at 4 hours and 24 hours after dose administration. Due to high peak concentration above target peak concentration, the dose was reduced to a final maintenance dose of 3.2 mg/kg body weight. Data from this single case suggest that serum drug concentration above the minimal inhibitory concentration (MIC) can be easily achieved with intraperitoneal administration of daptomycin every 48 hours even with a lower dose, as recommended for the intravenous administration, but measurement of serum concentration and dose adjustments are mandatory in such cases.

scholarly journals PSV-20 The effect of differing implant strategies on the galanin receptor 2 genotype on feed intake, efficiency, and feeding behavior of crossbred Angus finishing steers

2020 ◽  
Vol 98 (Supplement_3) ◽  
pp. 159-159
Author(s):  
Jerica R Hall ◽  
Mara Hirchert ◽  
Kasey R Maddock Carlin ◽  
Carl R Dahlen ◽  
Alison K Ward
Keyword(s):  
Body Weight ◽  
Feeding Behavior ◽  
Rfid Tags ◽  
Galanin Receptor ◽  
Future Studies ◽  
Body Weight Data ◽  
Finishing Steers ◽  
Main Effect ◽  
N 93 ◽  
Weight Data

Abstract Abstract: The objective of this study was to determine how the interaction different implant strategies with the galanin receptor 2 (GALR2) would influence intake, efficiency, and feeding behavior of finishing steers along with carcass characteristics. Angus crossbred steers (n = 93) were selected for this study based on their GALR2 genotype (GG, TT, and TG) and weaning weight with 19 GG, 36 TT, and 38 TG. Calves were blocked by initial body weight and fed a standard feedlot ration for 166 d or 202 d. Body weight data and blood samples were collected every 28 d. Steers were randomly assigned to one of two implant strategies; 1) a single Revalor-S (Merk, New Jersey) on d 77, or 2) a Revalor-S with on d 0 and another on d 77. Intake and feeding behavior data were recorded using RFID tags and Insentec feeders (Hokofarm Group, B.V., Marknesse, the Netherlands). Total DMI and feeding behavior were summarized following procedures described by (Swanson et al. 2014). Data were analyzed using the mixed procedure in SAS with a 2 x 3 factorial arrangement of treatments. The interaction of genotype x implant had a significant effect on minutes spent eating/visit (P = 0.02). The main effect of genotype had a significant effect on DMI (P = 0.05), number of meals/day (P 0.0001), and intake/minute (P = 0.002). While there was a greater DMI with the GG genotype we do not see the benefit of improved feed efficiency. The main effect of implant had a significant effect on ADG (P = 0.0008) and intake/visit (P 0.0012). Based on this data we conclude that there is no interaction between GALR2 genotype and implant strategy on efficiency or intake in finishing steers, however there may be benefit to future studies focusing on the GALR2 genotype and intake.

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