A Mathematical Basis for an Interval Arithmetic Standard

Basic concepts for an interval arithmetic standard are discussed in the paper. Interval arithmetic deals with closed and connected sets of real numbers. Unlike floating-point arithmetic it is free of exceptions. A complete set of formulas to approximate real interval arithmetic on the computer is displayed in section 3 of the paper. The essential comparison relations and lattice operations are discussed in section 6. Evaluation of functions for interval arguments is studied in section 7. The desirability of variable length interval arithmetic is also discussed in the paper. The requirement to adapt the digital computer to the needs of interval arithmetic is as old as interval arithmetic. An obvious, simple possible solution is shown in section 8.

A Basis for Z-Graded Identities of Matrices over Infinite Fields

2000 Mathematics Subject Classification: 16R10, 16R20, 16R50

Exploring the biological basis for Salmonella persistence in food manufacturing environments

The persistence of Salmonella spp. in low moisture foods is a challenge for the food industry as despite control strategies already in place, notable outbreaks still occur. The aim of this study was to characterise isolates of Salmonella, known to be persistent in the food manufacturing environment, by comparing their microbiological characteristics with a panel of matched clinical and veterinary isolates. The gross morphology of the challenge panel was phenotypically characterised in terms of cellular size, shape and motility. In all the parameters measured, the factory isolates were indistinguishable from the human, clinical and veterinary strains. Further detailed metabolic profiling was undertaken using the biolog Microbial ID system. Multivariate analysis of the metabolic microarray revealed differences in metabolism of the factory isolate of S.Montevideo, based on its upregulated ability to utilise glucose and the sugar alcohol groups. The remainder of the serotype-matched isolates were metabolically indistinguishable. Temperature and humidity are known to influence bacterial survival and through environmental monitoring experimental parameters were defined. The results revealed Salmonella survival on stainless steel was affected by environmental temperatures that may be experienced in a food processing environment; with higher survival rates (D25=35.4) at temperatures at 25°C and lower humidity levels of 15% RH, however a rapid decline in cell count (D10=3.4) with lower temperatures of 10°C and higher humidity of 70% RH. Several resident factories strains survived in higher numbers on stainless steel (D25=29.69) compared to serotype matched clinical and veterinary isolates (D25=22.98). Factory isolates of Salmonella did not show an enhanced growth rate in comparison to serotype matched solates grown in Luria broth, Nutrient broth and M9 minimal media indicating that as an independent factor, growth was unlikely to be a major factor driving Salmonella persistence. Using a live / dead stain coupled with fluorescence microscopy revealed that when no longer culturable, isolates of S.Schwarzengrund entered into a viable nonculturable state. The biofilm forming capacity of the panel was characterised and revealed that all were able to form biofilms. None of the factory isolates showed an enhanced capability to form biofilms in comparison to serotype-matched isolates. In disinfection studies, planktonic cells were more susceptible to disinfectants than cells in biofilm and all the disinfectants tested were successful in reducing bacterial load. Contact time was one of the most important factors for reducing bacterial populations in a biofilm. The genomes of eight strains were sequenced. At the nucleotide and amino acid level the food factory isolates were similar to those of isolates from other environments; no major genomic rearrangements were observed, supporting the conclusions of the phenotypic and metabolic analysis. In conclusion, having investigated a variety of morphological, biochemical and genomic factors, it is unlikely that the persistence of Salmonella in the food manufacturing environment is attributable to a single phenotypic, metabolic or genomic factor. Whilst a combination of microbiological factors may be involved it is also possible that strain persistence in the factory environment is a consequence of failure to apply established hygiene management principles.

Neural Networks in Bankruptcy Prediction - A Comparative Study on the Basis of the First Hungarian Bankruptcy Model

The article attempts to answer the question whether or not the latest bankruptcy prediction techniques are more reliable than traditional mathematical–statistical ones in Hungary. Simulation experiments carried out on the database of the first Hungarian bankruptcy prediction model clearly prove that bankruptcy models built using artificial neural networks have higher classification accuracy than models created in the 1990s based on discriminant analysis and logistic regression analysis. The article presents the main results, analyses the reasons for the differences and presents constructive proposals concerning the further development of Hungarian bankruptcy prediction.

The calculation of dynamic ecological footprint on the basis of the dynamic input-output model

The Leontief input-output model is widely used to determine the ecological footprint of consumption in a region or a country. It is able to capture spillover environmental effects along the supply change, thus its popularity is increasing in ecology related economic research. These studies are static and the dynamic investigations are neglected. The dynamic Leontief model makes it possible to involve the capital and inventory investment in the footprint calculation that projects future growth of GDP and environmental impacts. We show a new calculation method to determine the effect of capital accumulation on ecological footprint. Keywords: Dynamic Leontief model, Dynamic ecological footprint, Environmental management, Allocation method