Validation of Live Animal Ultrasonic Measurements of Body Composition in Market Lambs

Market lambs from the state fair of Virginia (n = 172) were ultrasonically evaluated by 4 scan technicians and 3 image interpreters to determine accuracy of ultrasonic estimates of loin muscle area (ULMA), backfat thickness (UBF), and body wall thickness (UBW). Lambs were initially scanned at the preferred magnification setting of each technician; 2 chose 1.5× and 2 chose 2.0×. Lambs were then scanned a second time for ULMA and UBF with machine magnification settings changed from 1.5 to 2.0×, or vice versa, midway through the second scan. Lambs were then slaughtered, and analogous measurements [carcass loin muscle area, carcass backfat thickness, and carcass body wall thickness (CBW)] were recorded on chilled carcasses. Pooled, residual correlation coefficients within technicians and interpreters between ultrasonic measurements from the first scan and carcass measurements were 0.66 for loin muscle area, 0.78 for backfat thickness, and 0.73 for body wall thickness, but were reduced to 0.43, 0.69, and 0.50, respectively, by inclusion of linear effects of carcass weight in the model. Mean bias for technicians and interpreters ranged from −1.30 to −2.66 cm2 for loin muscle area, −0.12 to −0.17 cm for backfat thickness, and 0.14 to −0.03 cm for body wall thickness; prediction errors ranged from 1.86 to 2.22 cm2, 0.12 to 0.14 cm, and 0.35 to 0.38 cm, respectively. Pooled correlations between repeated measures were 0.67 for ULMA, 0.79 for UBF, and 0.68 for UBW at the same magnification and 0.73 for ULMA and 0.76 for UBF across different magnification settings. Mean differences between repeated measures were more variable among technicians and interpreters than statistics comparing ultrasound to carcass measures. Standard errors of repeatability ranged from 1.61 to 2.45 cm2 for ULMA, 0.07 to 0.11 cm for UBF, and 0.36 to 0.42 cm for UBW. The effect of changing magnification setting on technician and interpreter repeatability was small for UBF and ULMA. The accuracy of prediction of CBW from UBW was similar to that achieved for backfat thickness; further assessment of the value of ultrasonic measurements of body wall thickness in lambs is warranted. These results indicate that ultrasound scanning can reliably predict carcass loin muscle area and backfat thickness in live lambs and, accordingly, has value in selection programs to improve composition. Development of certification standards for US lamb ultrasound technicians based on results of this study and others is proposed

Evolution of opinions on social networks in the presence of competing committed groups

Public opinion is often affected by the presence of committed groups of individuals dedicated to competing points of view. Using a model of pairwise social influence, we study how the presence of such groups within social networks affects the outcome and the speed of evolution of the overall opinion on the network. Earlier work indicated that a single committed group within a dense social network can cause the entire network to quickly adopt the group's opinion (in times scaling logarithmically with the network size), so long as the committed group constitutes more than about 10% of the population (with the findings being qualitatively similar for sparse networks as well). Here we study the more general case of opinion evolution when two groups committed to distinct, competing opinions $A$ and $B$, and constituting fractions $p_A$ and $p_B$ of the total population respectively, are present in the network. We show for stylized social networks (including Erd\H{o}s-R\'enyi random graphs and Barab\'asi-Albert scale-free networks) that the phase diagram of this system in parameter space $(p_A,p_B)$ consists of two regions, one where two stable steady-states coexist, and the remaining where only a single stable steady-state exists. These two regions are separated by two fold-bifurcation (spinodal) lines which meet tangentially and terminate at a cusp (critical point). We provide further insights to the phase diagram and to the nature of the underlying phase transitions by investigating the model on infinite (mean-field limit), finite complete graphs and finite sparse networks. For the latter case, we also derive the scaling exponent associated with the exponential growth of switching times as a function of the distance from the critical point.Comment: 23 pages: 15 pages + 7 figures (main text), 8 pages + 1 figure + 1 table (supplementary info

Longitudinal changes in ultrasonic measurements of body composition during growth in Suffolk ram lambs and evaluation of alternative adjustment strategies for ultrasonic scan data

Four equations were used to compare alternative procedures to adjust ultrasonic estimates (y) of backfat thickness (BF) and LM area (LMA) for BW using data from a series of 7 scans on 24 Suffolk ram lambs born in 2007. Equations were linear, linear + quadratic, allometric (y = αBWβ), and allometric + BW (ABW; y = αBWβeγW). Goodness of fit was very similar between equations over the range of the data. Resulting adjustment equations were tested using 3 serial scans on winter-born Suffolk (n = 150), Hampshire (n = 36), and Dorset (n = 43) rams and 52 fall-born Dorset rams tested at the Virginia Ram Test in 1999 through 2002. Partial correlations (accounting for the effect of year) between predicted and actual measures ranged from 0.78 to 0.87 for BF and 0.66 to 0.93 for LMA in winter-born rams and from 0.70 to 0.71 for BF and 0.72 to 0.78 for LMA in fall-born rams. No significant differences in predictive ability existed between equations for BF or LMA (P \u3e 0.05), and there was no indication that the allometric equation was a better predictor than linear within the range of the data. Adjustment equations were also tested using serial scan data from 37 Suffolk ewe lambs born in the same contemporary group as the rams used to derive the prediction equations but fed for a substantially slower rate of BW gain. Correlations between predicted and actual values of BF and LMA indicated lambs were too young and small at the first scan (77 d, 32.4 kg) to reliably predict carcass measures at typical slaughter weights. For prediction using data from the 2 subsequent scans, at mean ages \u3e96 d and mean BW \u3e39 kg, correlations between predicted and actual values were 0.72 to 0.74 for BF and 0.54 to 0.76 for LMA. Little difference existed between equations for predicting BF. For LMA, the ABW form was a weaker predictor than the others, and the linear equation was slightly superior to allometric. Therefore, it appears the linear and allometric forms are both suitable for use in central ram test and performance-tested farm flocks

Use of ultrasound scanning and body condition score to evaluate composition traits in mature beef cows

The experiment was designed to validate the use of ultrasound to evaluate body composition in mature beef cows. Both precision and accuracy of measurement were assessed. Cull cows (n = 87) selected for highly variable fatness were used. Two experienced ultrasound technicians scanned and assigned BCS to each cow on 2 consecutive days. Ultrasound traits were backfat thickness (UBFT), LM area (ULMA), body wall thickness (UBWT), rump fat depth (URFD), rump muscle depth (URMD), and intramuscular fat (UIMF; %). Cows were then harvested. Carcass traits were HCW, backfat thickness (CBFT), LM area (CLMA), body wall thickness (CBWT), and marbling score (CMS). Correlations between consecutive live measurements were greatest for subcutaneous fat (r \u3e 0.94) and lower for BCS (r \u3e 0.74) and URMD (r \u3e 0.66). Repeatability bias differed from 0 for only 1 technician for URMD and UIMF (P \u3c 0.01). Technicians differed in repeatability SE for only ULMA (P \u3c 0.05). Correlations between live and carcass measurements were high for backfat and body wall thickness (r \u3e 0.90) and slightly less for intramuscular fat and LM area (r = 0.74 to 0.79). Both technicians underestimated all carcass traits with ultrasound, but only CBFT and CBWT prediction bias differed from 0 (P \u3c 0.05). Technicians had similar prediction SE for all traits (P \u3e 0.05). Technician effects generally explained P \u3c 0.0001) but were minimal for scan differences. When cows with mean BCS 7 were removed, the portion of remaining variation between repeated measurements defined by animal effects increased for most traits and was significant for UBFT and URFD (P = 0.03). Technician effects explained trivial variation in accuracy (P \u3e 0.24). Animal effects explained 87.2, 75.2, and 81.7% (P \u3c 0.0001) of variation remaining for CBFT, CLMA, and CBWT prediction error, respectively, and remained large and highly important (P \u3c 0.0001) when only considering cows with BCS from 4 to 7. We conclude that experienced ultrasound technicians can precisely and accurately measure traits indicative of composition in mature beef cows. However, animal differences define substantial variation in scan differences and, especially, prediction errors. Implications for technician certification, carcass pricing, and genetic evaluation are discussed

Patterns of patterns of synchronization: Noise induced attractor switching in rings of coupled nonlinear oscillators

Following the long-lived qualitative-dynamics tradition of explaining behavior in complex systems via the architecture of their attractors and basins, we investigate the patterns of switching between qualitatively distinct trajectories in a network of synchronized oscillators. Our system, consisting of nonlinear amplitude-phase oscillators arranged in a ring topology with reactive nearest neighbor coupling, is simple and connects directly to experimental realizations. We seek to understand how the multiple stable synchronized states connect to each other in state space by applying Gaussian white noise to each of the oscillators' phases. To do this, we first identify a set of locally stable limit cycles at any given coupling strength. For each of these attracting states, we analyze the effect of weak noise via the covariance matrix of deviations around those attractors. We then explore the noise-induced attractor switching behavior via numerical investigations. For a ring of three oscillators we find that an attractor-switching event is always accompanied by the crossing of two adjacent oscillators' phases. For larger numbers of oscillators we find that the distribution of times required to stochastically leave a given state falls off exponentially, and we build an attractor switching network out of the destination states as a coarse-grained description of the high-dimensional attractor-basin architecture