Assessment of GFR: chemical techniques and prediction equations

2006 ◽  
pp. 21-28
Keyword(s):  
Prediction Equations ◽  
Chemical Techniques

Accuracy of 1-RM prediction equations from 7-10RM in college wrestlers

2007 ◽  
Vol 16 (1) ◽  
pp. 39-46 ◽  
Author(s):  
윤재량 ◽  
임승길
Keyword(s):  
Prediction Equations

Prediction Equations for Estimating the Quantity of Muscle in 25- to 45-Kg Pigs

1981 ◽  
Vol 53 (3) ◽  
pp. 663-665 ◽  
Author(s):  
Terry J. Prince ◽  
Daryl L. Kuhlers ◽  
Steve B. Jungst ◽  
Dennis N. Marple ◽  
Joseph C. Cordray ◽  
...  
Keyword(s):  
Prediction Equations

scholarly journals Ground Motion Prediction Equations for Malaysia Due to Subduction Zone Earthquakes in Sumatran Region

IEEE Access ◽  
2017 ◽  
Vol 5 ◽  
pp. 23920-23937
Author(s):  
M. S. Liew ◽  
Kamaluddeen Usman Danyaro ◽  
Mazlina Mohamad ◽  
Lim Eu Shawn ◽  
Aziz Aulov
Keyword(s):  
Subduction Zone ◽  
Ground Motion ◽  
Motion Prediction ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
Subduction Zone Earthquakes

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

scholarly journals Evaluating the Chemical Components and Flavor Characteristics Responsible for Triggering the Perception of “Beer Flavor” in Non-Alcoholic Beer

Foods ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 1914
Author(s):  
Scott Lafontaine ◽  
Kay Senn ◽  
Laura Knoke ◽  
Christian Schubert ◽  
Johanna Dennenlöhr ◽  
...  
Keyword(s):  
North American ◽  
Alternative Food ◽  
Chemical Components ◽  
Sensory Panel ◽  
Food And Beverage ◽  
Beer Flavor ◽  
Chemical Techniques ◽  
Selection Of

Forty-two commercial non-alcoholic beer (NAB) brands were analyzed using sensory and chemical techniques to understand which analytes and/or flavors were most responsible for invoking the perception of “beer flavor” (for Northern Californian consumers). The aroma and taste profiles of the commercial NABs, a commercial soda, and a carbonated seltzer water (n = 44) were characterized using replicated descriptive and CATA analyses performed by a trained sensory panel (i.e., 11 panelists). A number of non-volatile and volatile techniques were then used to chemically deconstruct the products. Consumer analysis (i.e., 129 Northern Californian consumers) was also used to evaluate a selection of these NABs (i.e., 12) and how similar they thought the aroma, taste and mouthfeels of these products were to beer, soda, and water. The results show that certain constituents drive the aroma and taste profiles which are responsible for invoking beer perception for these North American consumers. Further, beer likeness might not be a driver of preference in this diverse beverage class for Northern Californian consumers. These are important insights for brewers planning to create products for similar markets and/or more broadly for companies interested in designing other functional/alternative food and beverage products.

scholarly journals Ground motions in urban Los Angeles from the 2019 Ridgecrest earthquake sequence

2021 ◽  
pp. 875529302110039
Author(s):  
Filippos Filippitzis ◽  
Monica D Kohler ◽  
Thomas H Heaton ◽  
Robert W Graves ◽  
Robert W Clayton ◽  
...  
Keyword(s):  
Los Angeles ◽  
Ground Motion ◽  
Ground Motions ◽  
Earthquake Sequence ◽  
Motion Prediction ◽  
Ground Motion Prediction Equations ◽  
Prediction Equations ◽  
Ground Motion Prediction ◽  
Velocity Models ◽  
Spectral Accelerations

We study ground-motion response in urban Los Angeles during the two largest events (M7.1 and M6.4) of the 2019 Ridgecrest earthquake sequence using recordings from multiple regional seismic networks as well as a subset of 350 stations from the much denser Community Seismic Network. In the first part of our study, we examine the observed response spectral (pseudo) accelerations for a selection of periods of engineering significance (1, 3, 6, and 8 s). Significant ground-motion amplification is present and reproducible between the two events. For the longer periods, coherent spectral acceleration patterns are visible throughout the Los Angeles Basin, while for the shorter periods, the motions are less spatially coherent. However, coherence is still observable at smaller length scales due to the high spatial density of the measurements. Examining possible correlations of the computed response spectral accelerations with basement depth and Vs30, we find the correlations to be stronger for the longer periods. In the second part of the study, we test the performance of two state-of-the-art methods for estimating ground motions for the largest event of the Ridgecrest earthquake sequence, namely three-dimensional (3D) finite-difference simulations and ground motion prediction equations. For the simulations, we are interested in the performance of the two Southern California Earthquake Center 3D community velocity models (CVM-S and CVM-H). For the ground motion prediction equations, we consider four of the 2014 Next Generation Attenuation-West2 Project equations. For some cases, the methods match the observations reasonably well; however, neither approach is able to reproduce the specific locations of the maximum response spectral accelerations or match the details of the observed amplification patterns.

scholarly journals Ethnic Specific body fat percent prediction equation as surrogate marker of obesity in Ethiopian adults

2021 ◽  
Vol 40 (1) ◽  
Author(s):  
Makeda Sinaga ◽  
Melese Sinaga Teshome ◽  
Tilhun Yemane ◽  
Elsah Tegene ◽  
David Lindtsrom ◽  
...  
Keyword(s):  
Body Fat ◽  
Age Groups ◽  
Surrogate Marker ◽  
Cost Effective ◽  
Prediction Equation ◽  
Prediction Equations ◽  
Altman Plot ◽  
Cross Sectional ◽  
Bland Altman Plot ◽  
Body Fat Percent

Abstract Background Application of advanced body composition measurement methods is not practical in developing countries context due to cost and unavailability of facilities. This study generated ethnic specific body fat percent prediction equation for Ethiopian adults using appropriate data. Methods A cross-sectional study was carried ifrom February to April 2015 among 704 randomly selected adult employees of Jimma University. Ethnic specific Ethiopian body fat percent (BF%) prediction equation was developed using a multivariable linear regression model with measured BF% as dependent variable and age, sex, and body mass index as predictor variables. Agreement between fat percent measured using air displacement plethysmography and body fat percent estimated using Caucasian prediction equations was determined using Bland Altman plot. Results Comparison of ADP measured and predicted BF% showed that Caucasian prediction equation underestimated body fat percent among Ethiopian adults by 6.78% (P < 0.0001). This finding is consistent across all age groups and ethnicities in both sexes. Bland Altman plot did not show agreement between ADP and Caucasian prediction equation (mean difference = 6.7825) and some of the points are outside 95% confidence interval. The caucasian prediction equation significantly underestimates body fat percent in Ethiopian adults, which is consistent across all ethnic groups in the sample. The study developed Ethnic specific BF% prediction equations for Ethiopian adults. Conclusion The Caucasian prediction equation significantly underestimates body fat percent among Ethiopian adults regardless of ethnicity. Ethiopian ethnic-specific prediction equation can be used as a very simple, cheap, and cost-effective alternative for estimating body fat percent among Ethiopian adults for health care provision in the prevention of obesity and related morbidities and for research purposes.

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