Large-scale parallel lattice Boltzmann–cellular automaton model of two-dimensional dendritic growth

An extremely scalable lattice Boltzmann (LB)–cellular automaton (CA) model for simulations of two-dimensional (2D) dendritic solidification under forced convection is presented. The model incorporates effects of phase change, solute diffusion, melt convection, and heat transport. The LB model represents the diffusion, convection, and heat transfer phenomena. The dendrite growth is driven by a difference between actual and equilibrium liquid composition at the solid–liquid interface. The CA technique is deployed to track the new interface cells. The computer program was parallelized using the Message Passing Interface (MPI) technique. Parallel scaling of the algorithm was studied and major scalability bottlenecks were identified. Efficiency loss attributable to the high memory bandwidth requirement of the algorithm was observed when using multiple cores per processor. Parallel writing of the output variables of interest was implemented in the binary Hierarchical Data Format 5 (HDF5) to improve the output performance, and to simplify visualization. Calculations were carried out in single precision arithmetic without significant loss in accuracy, resulting in 50% reduction of memory and computational time requirements. The presented solidification model shows a very good scalability up to centimeter size domains, including more than ten million of dendrites.     

Electrostatic dust collectors compared to inhalable samplers for measuring endotoxin concentrations in farm homes

Paired electrostatic dust collectors (EDCs) and daily, inhalable button samplers (BS) were used concurrently to sample endotoxin in 10 farm homes during 7‐day periods in summer and winter. Winter sampling included an optical particle counter (OPC) to measure PM_2.5 and PM_2.5–10. Electrostatic dust collectors and BS filters were analyzed for endotoxin using the kinetic chromogenic Limulus amebocyte lysate assay. Optical particle counter particulate matter (PM) data were divided into two PM categories. In summer, geometric mean (geometric standard deviation) endotoxin concentrations were 0.82 EU/m³ (2.7) measured with the BS and 737 EU/m² (1.9) measured with the EDC. Winter values were 0.52 EU/m³ (3.1) for BS and 538 EU/m² (3.0) for EDCs. Seven‐day endotoxin values of EDCs were highly correlated with the 7‐day BS sampling averages (r = 0.70; P < 0.001). Analysis of variance indicated a 2.4‐fold increase in EDC endotoxin concentrations for each unit increase of the ratio of PM_2.5 to PM_2.5–10. There was also a significant correlation between BS and EDCs endotoxin concentrations for winter (r = 0.67; P < 0.05) and summer (r = 0.75; P < 0.05). Thus, EDCs sample comparable endotoxin concentrations to BS, making EDCs a feasible, easy to use alternative to BS for endotoxin sampling.     

Dynamic rough clustering and its applications

Dynamic data mining has gained increasing attention in the last decade. It addresses changing data structures which can be observed in many real-life applications, e.g. buying behavior of customers. As opposed to classical, i.e. static data mining where the challenge is to discover pattern inherent in given data sets, in dynamic data mining the challenge is to understand – and in some cases even predict – how such pattern will change over time. Since changes in general lead to uncertainty, the appropriate approaches for uncertainty modeling are needed in order to capture, model, and predict the respective phenomena considered in dynamic environments. As a consequence, the combination of dynamic data mining and soft computing is a very promising research area. The proposed algorithm consists of a dynamic clustering cycle when the data set will be refreshed from time to time. Within this cycle criteria check if the newly arrived data have structurally changed in comparison to the data already analyzed. If yes, appropriate actions are triggered, in particular an update of the initial settings of the cluster algorithm. As we will show, rough clustering offers strong tools to detect such changing data structures. To evaluate the proposed dynamic rough clustering algorithm it has been applied to synthetic as well as to real-world data sets where it provides new insights regarding the underlying dynamic phenomena.     

A crossover‐UNIQUAC model for critical and noncritical LLE calculations

A new model, named the crossover‐UNIQUAC model, has been proposed based on the crossover procedure for predicting constant‐pressure liquid–liquid equilibria (LLE). In this manner, critical fluctuations were incorporated into the classical UNIQUAC equation. Coexistence curves were estimated for systems having a diverse range of asymmetries. These systems included the LLE of five different mixtures, composed of nitrobenzene with one of the members of the alkane homologous family (either pentane, octane, decane, dodecane, or tetradecane), as well as an extra system having a different chemical nature, namely the mixture of n‐perfluorohexane and hexane, to further check the validity of the proposed approach. Using these nonideal mixtures, the validity of the new model was investigated within wide ranges, covering near‐critical to regions falling far away from the critical point. The graphical trends, as well as the quantitative comparison with experimental data indicated the good agreement of the proposed model results with the experimental data. A maximum AARD% value of 3.97% was obtained in calculating molar compositions by the proposed model for such challenging systems covering noncritical, as well as critical regions. In addition, to show the strength of the proposed crossover approach to describe properties other than LLE, molar heat capacities were investigated for the system of nitrobenzene + dodecane. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3094–3103, 2015     

Food hygiene and hazard analysis critical control point in the United Kingdom food industry: practices, perceptions, and attitudes.

A mail survey was designed and distributed to 1,650 managers of food businesses across the manufacturing, retail, and catering sectors of the United Kingdom food industry. Respondents were asked about the food hygiene practices of their business, their use of systems such as hazard analysis critical control point (HACCP), and their attitudes toward a range of food hygiene-related issues. Complete responses were received from 254 businesses, a response rate of 15.3%. The results showed that 69% of manufacturers were using HACCP systems, significantly more than the 13% and 15% in the retail and catering sectors, respectively (P < 0.05); 53% of manufacturing, 59% of retail, and 48% of catering managers thought that their business represented a low risk to food safety. Among businesses using HACCP, specific training in the system was significantly related to the likelihood that businesses had adopted all seven of the HACCP principles (P < 0.05). Business size was a significant factor in the use of HACCP in both the manufacturing and retail sectors. Higher levels of food hygiene qualifications among business managers, business status, and higher perceptions among managers of the risk to food safety of the business were also significantly related to HACCP use in all sectors (P < 0.05). The results from this survey have implications for the future development of HACCP, particularly within the UK retail and catering sectors. Risk communication and training are highlighted as areas of concern for marketing HACCP within these industry sectors.     

Systematic survey on the prevalence of genes coding for staphylococcal enterotoxins SElM, SElO, and SElN

Staphylococcus aureus remains a leading cause of food-poisoning with substantial impact on public health. Using a multiplex polymerase chain reaction-DNA enzyme immunoassay (PCR-DEIA), we studied the presence of genes encoding staphylococcal enterotoxin-like (SEl) superantigens sem, sen, and seo, associated with the enterotoxin gene cluster (egc), in 429 clinical Staphylococcus aureus isolates. 294 (68.5%) isolates tested positive for at least one of the three SEl genes. In contrast to the fixed gene combination seg/sei also located on egc, a substantial number of isolates (n = 108) were found to bear only one or two of the genes encoding SElM, SElN, and SElO. Regarding the origin of the S. aureus isolates, a significant difference (P = 0.022) was found for the possession of seo (61.2% of blood isolates versus 42.9% of nasal strains). Also sem (not significantly) was found more common in blood isolates (52.1% versus 40.5%). The survey of the newly described SEl genes sem-seo supports the concept that most clinical S. aureus isolates harbor subsets of pyrogenic toxin superantigens. The potential contribution of seo and sem to the pathogenic potential of S. aureus has to be further evaluated.     

The problem of selective determination of PSP toxins in mussels

Levels of paralytic shellfish poisoning (PSP) toxins in shellfish are routinely determined by mouse bioassay. In order to improve the qualitative and quantitative determination of PSP toxins, chromatographic techniques with fluorescence detection have been developed. These HPLC methods and the HPLC/MS coupling were used to determine a second PSP toxin which was found, in addition to saxitoxin, in canned Spanish mussels. These canned mussels were rejected in 1986 by the German food control because PSP concentrations were too high. It has been shown that these samples contained mainly dc-saxitoxin.