Prediction Of Carcass Lean Content In Live Pigs Using Scanoprobe Ultrasonic Machine

A total of 40 entire males within 60kg weight range from Large White control and selected crossbred improved indigenous pigs were used to study relationships between live and carcass measurements using the Scanoprobe ultrasonic machine. Within this live weight range the fat depths (P1, P2 and P3)and muscle measurements (MP2 and MLA) were more variable in the crossbreds than the purebred exotics although the carcass lean content, 365g/kg and 395g/kg for the purebred and crossbreds respectively were not significantly different. The fat depths, using the ultrasonic machine was a little lower than the actual values: 15.1 as against 16.6mm for P1 and 15.05 against 16.3mm for P2 with a residual standard deviation of 2.56 and 3.25mm respectively. Whilst the MLA gave values of 2886mm2 for ultrasonics as against 3025mm2 for carcass measurement with S.D. of 357 and 328mm2 respectively. Relative to the different fat depths measurements, the regression of carcass lean on P1 was -3.90±1.716 whilst at P2 and P3 it was -2.94±0.949 and -3.41±0.810gms respectively, resulting in a prediction equation for lean content of 57.85 - 0.751 P2 gm.

Timeliness of U.S. mortality data releases during the COVID-19 pandemic: delays are associated with electronic death registration system and elevated weekly mortality

All-cause mortality counts allow public health authorities to identify populations experiencing excess deaths from pandemics, natural disasters, and other emergencies. Further, delays in mortality reporting may contribute to misinformation because death counts take weeks to become accurate. We estimate the timeliness of all-cause mortality releases during the Covid-19 pandemic, and identify potential reasons for reporting delays, using 35 weeks of provisional mortality counts between April 3 and December 4, 2020 for 52 states/jurisdictions. On average, states' mortality counts are delayed by 5.6 weeks (standard deviation 1.74), with a range of 8.8 weeks between the fastest state and the slowest state. States that hadn't adopted the electronic death registration system were about 4 weeks slower, and 100 additional weekly deaths per million were associated with 0.4 weeks delays, but the residual standard deviation was 0.9 weeks, suggesting other sources of delay. Disaster planning should include improving the timeliness of mortality data.

Chanter model: nonlinear modeling of the fruit growth of cocoa

ABSTRACT: The growth of plants and animals can be described through a growth curve. This curve is given by the equation of a nonlinear model, such as the Logistic model and the Gompertz model. The objective of this study was to adjust the Chanter model, as well as Logistic and Gompertz, using a set of cocoa (clone Sial-105) fruit whose length and diameter measurements were evaluated from 30 to 180 days after pollination, every 15 days. The Chanter model is a hybrid between the Logistic model and Gompertz model whose parameters can be interpreted similarly. A comparison of the quality of fit between the models was made using the following statistical measures: the Akaike’s information criterion (AIC), the Akaike’s weights criterion, Bayesian information criterion (BIC), residual standard deviation (RSD),the adjusted coefficient of determination (R²aj) and the measures of non-linearity Box’s bias and curvature of Bates and Watts. It was verified that the Chanter model is the most suitable one among the studied models for modeling the cocoa data.

Forces modeling in a surface peripheral grinding process with the use of various design of experiment (DoE)

The paper presents forces modeling with the use of DoE models, such as (Box-Wilson) central composite design in face centered variant (CCF) and Box-Behnken design in a surface peripheral grinding process of 100Cr6 steel with M3X60K5VE01-35 grinding wheel. Experiment design and result analysis were done with the use of Design-Expert software. Force models, obtained with application of selected designs of experiment, were compared on the basis of the coefficient of determination, and values of residual standard deviation.

Mid-upper tropospheric methane retrieval from IASI and its validation

Mid-upper tropospheric methane (CH4), as an operational product at NOAA's (National Oceanic and Atmospheric Administration) Comprehensive Large Array-data Stewardship System (CLASS), has been retrieved from the Infrared Atmospheric Sounding Interferometer (IASI) since 2008. This paper provides a description of the retrieval method and the validation using 596 CH4 vertical profiles from aircraft measurements by the HIAPER Pole-to-Pole Observations (HIPPO) program over the Pacific Ocean. The number of degrees of freedom for the CH4 retrieval is mostly less than 1.5, and it decreases under cloudy conditions. The retrievals show greatest sensitivity between 100–600 hPa in the tropics and 200–750 hPa in the mid- to high latitude. Validation is accomplished using aircraft measurements (convolved by applying the monthly mean averaging kernels) collocated with all the retrieved profiles within 200 km and on the same day, and the results show that, on average, a larger error of CH4 occurs at 300–500 hPa. The bias in the trapezoid of 374–477 hPa is −1.74% with a residual standard deviation of 1.20%, and at layer 596–753 hPa the bias is −0.69% with a residual standard deviation of 1.07%. The retrieval error is relatively larger in the high northern latitude regions and/or under cloudy conditions. The main reasons for this negative bias include the uncertainty in the spectroscopy near the methane Q branch and/or the empirical bias correction, plus residual cloud contamination in the cloud-cleared radiances. It is expected for NOAA to generate the CH4 product for 20 + years using a similar algorithm from three similar thermal infrared sensors: Atmospheric Infrared Sounder (AIRS), IASI and the Cross-track Infrared Sounder (CrIS). Such a unique product will provide a supplementary to the current ground-based observation network, particularly in the Arctic, for monitoring the CH4 cycle, its transport and trend associated with climate change.

Study on the Formulas of the Dog-Bone Shape of Edger Rolling in Hot Strip Mill

3D elastic-plastic FEM model was established with ANSYS/LS-DYNA for edger rolling in hot strip mill. The effect of width reduction of edger roll, the slab original width and thickness, and edger diameter on the main parameters of dog-bone shape has been studied. According to many simulated conditions, the formulas of the main parameters of the dog-bone shape have been developed. In order to test the accuracy of the models, multiple correlation coefficient and residual standard deviation were calculated.The results show that multiple correlation coefficients are all above 98% and residual standard deviations are all below 5%, which indicate that these formulas acquire a high precise.

Relationship of weaning weight to the mature liveweight of cashmere does on Australian farms

Median weaning weight and its relationship with the median mature liveweight of does was quantified for four commercial Australian cashmere farms in various parts of Australia. Individual liveweights, of does of all ages at the time of weaning in December, ranged from 9 to 61 kg. Individual farm means of adult does (>1 year old) ranged from 24.6 to 38.8 kg. The model for the logarithm of liveweight was: log10(liveweight) = a + br(Age + 0.6); where a, b and r are parameters that are different for each farm. The result that the r parameter differs with farm was statistically significant (P = 9.4 × 10−6). The percentage variance accounted for was 84.4% and the residual standard deviation was 0.042. Farms differed greatly in the median mature liveweight with some farms reaching ~44 kg and others only 31 kg. Median weaning weight was 14.1 kg (range 11.4–16.8 kg). Median weaning weight as a percentage of median mature doe liveweight on a particular farm varied from 32 to 42%. These weaning weights appear low in absolute and relative terms and thus are likely to incur production penalties.

A comparison of phase inversion and traveltime tomography for processing near-surface refraction traveltimes

With phase inversion, one can estimate subsurface velocities using the phases of first-arriving waves, which are the frequency-domain equivalents of the traveltimes. Phase inversion is modified to make it suitable for processing traveltimes from near-surface refraction surveys. The modifications include parameterizing the model, correcting the observed phases, and selecting the complex frequency. This modified phase inversion is compared to traveltime tomography. For two comparisons using computer-simulated traveltimes, the difference between the estimated and correct models, the residual mean, and the residual standard deviation are smaller for the phase inversion than they are for the traveltime tomography. For a comparison using field data from an S-wave refraction survey, both methods estimate models that are consistent with the known geology. Nonetheless, the phase-inversion model includes small-scale features in the bedrock that are geologically plausible; the residual mean and the residual standard deviation are smaller for the phase inversion than they are for the traveltime tomography.