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.     

Unreliable numbers: error and harm induced by bad design can be reduced by better design

Number entry is a ubiquitous activity and is often performed in safety- and mission-critical procedures, such as healthcare, science, finance, aviation and in many other areas. We show that Monte Carlo methods can quickly and easily compare the reliability of different number entry systems. A surprising finding is that many common, widely used systems are defective, and induce unnecessary human error. We show that Monte Carlo methods enable designers to explore the implications of normal and unexpected operator behaviour, and to design systems to be more resilient to use error. We demonstrate novel designs with improved resilience, implying that the common problems identified and the errors they induce are avoidable.     

Glycosylation in Indolent,Significant and Aggressive Prostate Cancer by Automated High-Throughput N-Glycan Profiling

The diagnosis and treatment of prostate cancer (PCa) is a major health-care concern worldwide. This cancer can manifest itself in many distinct forms and the transition from clinically indolent PCa to the more invasive aggressive form remains poorly understood. It is now universally accepted that glycan expression patterns change with the cellular modifications that accompany the onset of tumorigenesis. The aim of this study was to investigate if differential glycosylation patterns could distinguish between indolent, significant, and aggressive PCa. Whole serum N-glycan profiling was carried out on 117 prostate cancer patients’ serum using our automated, high-throughput analysis platform for glycan-profiling which utilizes ultra-performance liquid chromatography (UPLC) to obtain high resolution separation of N-linked glycans released from the serum glycoproteins. We observed increases in hybrid, oligomannose, and biantennary digalactosylated monosialylated glycans (M5A1G1S1, M8, and A2G2S1), bisecting glycans (A2B, A2(6)BG1) and monoantennary glycans (A1), and decreases in triantennary trigalactosylated trisialylated glycans with and without core fucose (A3G3S3 and FA3G3S3) with PCa progression from indolent through significant and aggressive disease. These changes give us an insight into the disease pathogenesis and identify potential biomarkers for monitoring the PCa progression, however these need further confirmation studies.     

Pressure drop and optimization meta-models for arbitrary low-height pleated filter shapes and flowrates

Journal of Mechanical Science and Technology - This study delivers equations useful for low-height pleated fibrous filter design: two pressure drop equations and one set of optimum design equations...     

Deliberately Losing Control of C−H Activation Processes in the Design of Small-Molecule-Fragment Arrays Targeting Peroxisomal Metabolism

Combined photochemical arylation, “nuisance effect” (S_NAr) reaction sequences have been employed in the design of small arrays for immediate deployment in medium-throughput X-ray protein–ligand structure determination. Reactions were deliberately allowed to run “out of control” in terms of selectivity; for example the ortho-arylation of 2-phenylpyridine gave five products resulting from mono- and bisarylations combined with S_NAr processes. As a result, a number of crystallographic hits against NUDT7, a key peroxisomal CoA ester hydrolase, have been identified.     

Engineering egress data considering pedestrians with reduced mobility

To quantify the evacuation process, evacuation practitioners use engineering egress data describing the occupant movement characteristics. These data are typically based to young and fit populations. However, the movement abilities of occupants who might be involved in evacuations are becoming more variable—with the building populations of today typically including increasing numbers of individuals: with impairments or who are otherwise elderly or generally less mobile. Thus, there will be an increasing proportion of building occupants with reduced ability to egress. For safe evacuation, there is therefore a need to provide valid engineering egress data considering pedestrians with disabilities. Gwynne and Boyce recently compiled a series of data sets related to the evacuation process to support practitioner activities in the chapter Engineering Data in the SFPE Handbook of Fire Protection Engineering. This paper supplements these data sets by providing information on and presenting data obtained from additional research related to the premovement and horizontal movement of participants with physical‐, cognitive‐, or age‐related disabilities. The aim is to provide an overview of currently available data sets related to, and key factors affecting the egress performance of, mixed ability populations which could be used to guide fire safety engineering decisions in the context of building design.