Effect of temperature on raw whole milk density and its potential impact on milk payment in the dairy industry

The objective of this study was to determine the effect of temperature on whole milk density measured at four different temperatures: 5, 10, 15, and 20 °C. A total of ninety-three individual milk samples were collected from morning milking of thirty-two Holstein Friesian dairy cows, of national average genetic merit, once every two weeks over a period of 4 weeks and were assessed by Fourier transform infrared spectroscopy for milk composition analysis. Density of the milk was evaluated using two different analytical methods: a portable density meter DMA35 and a standard desktop model DMA4500M (Anton Paar GmbH, UK). Milk density was analysed with a linear mixed model with the fixed effects of sampling period, temperature and analysis method; triple interaction of sampling period x analysis method x temperature; and the random effect of cow to account for repeated measures. The effect of temperature on milk density (ρ) was also evaluated including temperature (t) as covariate with linear and quadratic effects within each analytic method. The regression equation describing the curvature and density–temperature relationship for the DMA35 instrument was ρ = 1.0338−0.00017T−0.0000122T² (R² = 0.64), while it was ρ = 1.0334 + 0.000057T−0.00001T² (R² = 0.61) for DMA4500 instrument. The mean density determined with DMA4500 at 5 °C was 1.0334 g cm⁻³, with corresponding figures of 1.0330, 1.0320 and 1.0305 g cm⁻³ at 10, 15 and 20 °C, respectively. The milk density values obtained in this study at specific temperatures will help to address any bias in weight–volume calculations and thus may also improve the financial and operational control for the dairy processors in Ireland and internationally.     

Knowledge-based diagnosis of drill conditions

One major bottleneck in the automation of the drilling process by robots in the aerospace industry is drill condition monitoring. This paper describes a system approach to solve this problem through the advancement of new machine design, sensor instrumentation, metal-cutting research, and intelligent software development. All drill failures can be detected and distinguished: chisel edge wear, flank wear, crater wear, margin wear, corner wear, breakage, asymmetry, lip height difference, and chipping at lips. However, in the real manufacturing environment, different workpiece materials, drill size, drill geometry, drill material, cutting speed, feed rate, etc. will change the criteria for judging the drill condition. The knowledge base used for diagnosing the drill failures requires a huge data bank and prior exhaustive testing. A self-learning scheme is therefore introduced to the machine in order to acquire the threshold history needed for automatic diagnosis by using the same new tool under the same drilling conditions.     

Optimal nonnegative color scanning filters

In this correspondence, the problem of designing color scanning filters for multi-illuminant color recording is considered. The filter transmittances are determined from a minimum-mean-squared orthogonal tristimulus error criterion that minimizes the color error in estimates obtained from noisy recorded data. Nonnegativity constraints essential for physical realizability are imposed on the filter transmittances. In order to demonstrate the significant improvements obtained, the resulting filters are compared with suboptimal filters reported in earlier literature.     

Corrections for nonuniform sampling distortions in magnetic resonance imagery

A technique for estimating and correcting nonuniform sampling distortions in magnetic resonance imagery is presented. The technique consists of first estimating the sampling grid distortion using a parametric model, and then estimating the uniformly sampled data by interpolation on the nonuniform grid. Parameterized models for two particular sampling grid distortion are presented. Maximum likelihood and maximum a posteriori estimators are developed for these distortions. Using computer simulated data, these estimators are shown to perform well.     

Reactive blending of thermoplastic polyurethane in situ with poly(vinyl chloride)

In this study, a novel reactive blending process was developed for producing poly(vinyl chloride)/thermoplastic polyurethane (PVC/TPU) blends. An alternative to melt or solution blending, the advantages to such a blending technique are fewer processing steps and less cost, no solvent removal, reduced PVC degradation, and the potential for producing otherwise unobtainable blend morphologies and properties. Using an internal mixer, PVC was compounded and plasticized with the polyol and chain extender of a polyester‐based TPU. Then, upon addition of the stoichiometric amount of TPU diisocyanate, a high molecular weight TPU was polymerized in situ with PVC. Because of reaction‐induced phase separation, the resulting partially miscible PVC/TPU blends were characterized by heterogeneous, multiphase morphologies. In addition, they exhibited excellent tensile properties intermediate between that of neat PVC and TPU. POLYM. ENG. SCI., 45:876–887, 2005. © 2005 Society of Plastics Engineers     

Fear Appeals,Message Processing Cues,and Credibility in the Websites of Violent,Ideological, and Nonideological Groups

Ideological groups use the Internet to deliver their messages unhindered by the constraints of traditional media. We examined how ideological groups promote their worldview through their websites. Using the elaboration likelihood model (ELM), this research used trained coders to examine the websites of nonideological groups (n = 37), nonviolent ideological groups (n = 36), and violent ideological groups (n = 32) for credibility, persuasion processing cues, and interactivity factors. Results of this study found that the websites of violent ideological groups use more fear appeals, were less interactive, and were the least credible of the 3 groups. All 3 groups used more central cues than peripheral suggesting they focused on evidence for their arguments rather than emotion.     

Termination rate coefficients for acrylamide in the aqueous phase at low conversion

The kinetics of acrylamide (AAm) free radical polymerization at low conversion of monomer to polymer in the aqueous phase was investigated at 50 °C using γ-radiolysis relaxation, which is sensitive to radical-loss processes. The values of the termination rate coefficients for AAm ranged from 8×10⁶ to 3×10⁷ M⁻¹ s⁻¹ as the weight fraction of polymer ranged from 0.002 to 0.0035, which is significantly lower than the low-conversion values for monomers such as styrene (2×10⁸ M⁻¹ s⁻¹) and methyl methacrylate (4×10⁷ M⁻¹ s⁻¹) in organic media. These can be quantitatively explained by applying a chain-length-dependent model of free-radical polymerization kinetics [Russell GT, Gilbert RG, Napper DH. Macromolecules 1992;25:2459. [19]] in which termination kinetics are expressed in terms of a diffusion-controlled encounter of radicals which ultimately yields an expression for the chain-length-averaged termination rate coefficient, 〈k_t〉. The lower 〈k_t〉 for AAm arises due to a combination of the high k_p value, promoting rapid formation of slower terminating long chains, and the slow diffusion of short propagating chains, relative to other common monomers. The chain transfer to monomer constant for AAm in water at 50 °C, C_M, was estimated using the chain-length-distribution method with correction for band-broadening [Castro JV, van Berkel KY, Russell GT, Gilbert RG. Aust J Chem 2005;58:178. [21]] and found to be 1.2×10⁻⁴ (±10%). The diffusion characteristics for AAm were adapted from those obtained for a similar aqueous system (hydroxyethyl methacrylate) together with a 0.5 exponent for the power law dependence on penetrant degree of polymerization at zero weight fraction polymer. This provides an adequate fit to the 〈k_t〉 data. This is the first application of the chain-length-dependent model to describe experimental termination rate coefficients for an aqueous system at low conversion to polymer. The result that the experimental termination rate coefficients can be reproduced with an a priori model with physically reasonable parameters supports the physical assumptions underlying that model.     

Aberrant protein expression in plasma and kidney tissue during experimental obstructive nephropathy

Kidney failure is a major health problem worldwide. Patients with end-stage renal disease require intensive medical support by dialysis or kidney transplantation. Current methods for diagnosis of kidney disease are either invasive or insensitive, and renal function may decline by as much as 50% before it can be detected using current techniques. The goal of this study was, therefore, to identify biomarkers of kidney disease (associated with renal fibrosis) that can be used for the development of a non-invasive clinical test for early disease detection. We utilized two protein-profiling technologies (SELDI-TOF MS and 2-D) to screen the plasma and kidney proteome for aberrantly expressed proteins in an experimental mouse model of unilateral uretric obstruction, which mimics the pathology of human renal disease. Several differentially regulated proteins were detected at the plasma level of day-3-obstructed animals, which included serum amyloid A1, fibrinogen α, haptoglobin precursor protein, haptoglobin and major urinary proteins 11 and 8. Differentially expressed proteins detected at the tissue level included ras-like activator protein 2, haptoglobin precursor protein, malate dehydrogenase, α enolase and murine urinary protein (all p<0.05 versus controls). Immunohistochemistry was used to confirm the up-regulation of fibrinogen. Interestingly, these proteins are largely separated into four major classes: (i) acute-phase reactants (ii) cell-signaling molecules (iii) molecules involved in cell growth and metabolism and (iv) urinary proteins. These results provide new insights into the pathology of obstructive nephropathy and may facilitate the development of specific assay(s) to detect and monitor renal fibrosis.