Contrast summation across eyes and space is revealed along the entire dipper function by a "Swiss cheese" stimulus.

Previous contrast discrimination experiments have shown that luminance contrast is summed across ocular (T. S. Meese, M. A. Georgeson, & D. H. Baker, 2006) and spatial (T. S. Meese & R. J. Summers, 2007) dimensions at threshold and above. However, is this process sufficiently general to operate across the conjunction of eyes and space? Here we used a "Swiss cheese" stimulus where the blurred "holes" in sine-wave carriers were of equal area to the blurred target ("cheese") regions. The locations of the target regions in the monocular image pairs were interdigitated across eyes such that their binocular sum was a uniform grating. When pedestal contrasts were above threshold, the monocular neural images contained strong evidence that the high-contrast regions in the two eyes did not overlap. Nevertheless, sensitivity to dual contrast increments (i.e., to contrast increments in different locations in the two eyes) was a factor of ∼1.7 greater than to single increments (i.e., increments in a single eye), comparable with conventional binocular summation. This provides evidence for a contiguous area summation process that operates at all contrasts and is influenced little, if at all, by eye of origin. A three-stage model of contrast gain control fitted the results and possessed the properties of ocularity invariance and area invariance owing to its cascade of normalization stages. The implications for a population code for pattern size are discussed.

Improving the design process for factories:modelling human performance variation

Theprocess of manufacturing system design frequently includes modeling, and usually, this means applying a technique such as discrete event simulation (DES). However, the computer tools currently available to apply this technique enable only a superficial representation of the people that operate within the systems. This is a serious limitation because the performance of people remains central to the competitiveness of many manufacturing enterprises. Therefore, this paper explores the use of probability density functions to represent the variation of worker activity times within DES models.

Review of industrial temperature measurement technologies and research priorities for the thermal characterisation of the factories of the future

As the largest source of dimensional measurement uncertainty, addressing the challenges of thermal variation is vital to ensure product and equipment integrity in the factories of the future. While it is possible to closely control room temperature, this is often not practical or economical to realise in all cases where inspection is required. This article reviews recent progress and trends in seven key commercially available industrial temperature measurement sensor technologies primarily in the range of 0 °C–50 °C for invasive, semi-invasive and non-invasive measurement. These sensors will ultimately be used to measure and model thermal variation in the assembly, test and integration environment. The intended applications for these technologies are presented alongside some consideration of measurement uncertainty requirements with regard to the thermal expansion of common materials. Research priorities are identified and discussed for each of the technologies as well as temperature measurement at large. Future developments are briefly discussed to provide some insight into which direction the development and application of temperature measurement technologies are likely to head.

Surface microbial consortia from Livarot, a French smear-ripened cheese

The surface microflora (902 isolates) of Livarot cheeses from three dairies was investigated during ripening. Yeasts were mainly identified by Fourier transform infrared spectroscopy. Geotrichum candidum was the dominating yeast among 10 species. Bacteria were identified using Biotype 100 strips, dereplicated by repetitive extragenic palindromic PCR (rep-PCR); 156 representative strains were identified by either BOX-PCR or (GTG) 55-PCR, and when appropriate by 16S rDNA sequencing and SDS-PAGE analysis. Gram-positive bacteria accounted for 65% of the isolates and were mainly assigned to the genera Arthrobacter, Brevibacterium, Corynebacterium, and Staphylococcus. New taxa related to the genera Agrococcus and Leucobacter were found. Yeast and Gram-positive bacteria strains deliberately added as smearing agents were sometimes undetected during ripening. Thirty-two percent of the isolates were Gram-negative bacteria, which showed a high level of diversity and mainly included members of the genera Alcaligenes, Hafnia, Proteus, Pseudomonas, and Psychrobacter. Whatever the milk used (pasteurized or unpasteurized), similar levels of biodiversity were observed in the three dairies, all of which had efficient cleaning procedures and good manufacturing practices. It appears that some of the Gramnegative bacteria identified should now be regarded as potentially useful in some cheese technologies. The assessment of their positive versus negative role should be objectively examined.