Regulation of Secondary Metabolism in the Penicillium Genus

Penicillium, one of the most common fungi occurring in a diverse range of habitats, has a worldwide distribution and a large economic impact on human health. Hundreds of the species belonging to this genus cause disastrous decay in food crops and are able to produce a varied range of secondary metabolites, from which we can distinguish harmful mycotoxins. Some Penicillium species are considered to be important producers of patulin and ochratoxin A, two well-known mycotoxins. The production of these mycotoxins and other secondary metabolites is controlled and regulated by different mechanisms. The aim of this review is to highlight the different levels of regulation of secondary metabolites in the Penicillium genus.     

Photorefractive Deconvolution Techniques for Optical Differentiation of Images

Abstract

A photorefractive deconvolution process for optical differentiation of images is suggested. The problems associated with the intrinsic resolution capabilities of this technique, resulting from the reading process, application of external fields and the spontaneous excitation rate of the carriers are discussed. The potential of this scheme is illustrated by using two well known test functions.     

An intelligent air quality monitoring model in manufacturing

While low air quality may have negative effect on product quality in manufacturing, it has become a social concern as there are many reports on the result of worker exposure to low air quality. Manufacturing experienced a boom increase after World War I and II due to higher demands for products that gave birth to an unhealthy environment for workers. For example, Epidemiological investigations have linked unhealthy environment (air pollution) to adverse health effects such as respiratory diseases, and increased mortality and morbidity. These manufacturing systems represented less than 14% of the private employment and accounted for 42% of the nonfatal workplace illnesses. It is evident that manufacturing systems still have significant impact on the health of workers. Therefore, this study proposes a fuzzy Bayesian air quality monitoring model that is able to mimic human-like intelligent behavior in the environmental analysis. An illustrative example is demonstrated to present the application of the model.     

An approach for modelling concrete spalling in finite strains

A new approach for modelling concrete spalling process is here proposed, taking into account a fully nonlinear-displacement/strain theory able to catch complex interactions between pressure, thermal and mechanical fields. The micro-structural modelling of concrete under fire conditions is derived from a mechanical and thermodynamic consistent theory and it is strictly related to a self-consistent, carefully extracted set of experimental data, in order to make a correct validation and calibration of the numerical F.E. procedures and codes. Even if appearing as a first but successful example, it is shown that a procedure accounting for coupled material and geometric nonlinearities is able to attain valuable and realistic numerical results concerning spalling process in concrete.     

Real Time Dynamic Programming Control of Rapid Thermal Processing Furnaces

In the rapid thermal processing of a semi-conductor wafer, the temperature of the latter has to follow a preset time evolution profile while keeping spatial uniformity. A model-based open loop control strategy is presented in all its steps. A global and sufficiently accurate thermal model, based on the component interaction network, is used for the prediction of the required instantaneous heat flux distribution gained by the wafer. The same model is used to calculate the distribution of the net heat flux gainedby the wafer for each radiant emitter. The optimal combination of input powers to the radiant emitters is then determined using real time dynamic programming. It consists in minimizing the maximum difference between the required heat flux distribution and the one corresponding to the tested combination of input powers at each time step. The objective function is corrected according to the preceding time step errors, in a way to avoid cumulative temperature deviation. The solution algorithm is described, step by step, and a test case is treated. The results show good temperature tracking and uniformity.     

Quantification of Fusarium graminearum and Fusarium culmorum by real-time PCR system and zearalenone assessment in maize

Zearalenone (ZEA) is a mycotoxin produced by some species of Fusarium, especially by Fusarium graminearum and F. culmorum. ZEA induces hyperoestrogenic responses in mammals and can result in reproductive disorders in farm animals. In the present study, a real-time PCR (qPCR) assay has been successfully developed for the detection and quantification of Fusarium graminearum based on primers targeting the gene PKS13 involved in ZEA biosynthesis. A standard curve was developed by plotting the logarithm of known concentrations of F. graminearum DNA against the cycle threshold (Ct) value. The developed real time PCR system was also used to analyze the occurrence of zearalenone producing F. graminearum strains on maize. In this context, DNA extractions were performed from thirty-two maize samples, and subjected to real time PCR. Maize samples also were analyzed for zearalenone content by HPLC. F. graminearum DNA content (pg DNA/ mg of maize) was then plotted against ZEA content (ppb) in maize samples. The regression curve showed a positive and good correlation (R2=0.760) allowing for the estimation of the potential risk from ZEA contamination. Consequently, this work offers a quick alternative to conventional methods of ZEA quantification and mycological detection and quantification of F. graminearum in maize.     

Petrographic, mechanical and chemical properties of major coarse aggregate resources in Lebanon, eastern Mediterranean

 In a previous study to locate the major coarse aggregate resources currently being exploited in the Lebanon, 20 major operating quarrying sites were located, described and sampled. This paper reports the evaluation of these samples, based on petrographic analysis and mechanical and chemical acceptance tests as well as the results of tests conducted on fresh and hardened concrete samples made with various types of coarse aggregate. In general, the samples were of good quality and suitable for use in concrete although the grading of the aggregates varied widely between quarries and some samples were found to be gap graded. Only the material from Berquayel failed the soundness test. Cherts were identified in some of the samples, leading to the conclusion that alkali-aggregate reactions might occur in these rocks. The results of the concrete tests showed that the measured concrete stiffness was in many cases slightly lower than the anticipated theoretical value. It is hoped that the results of the study will provide valuable assistance to all those involved in the construction industry, including engineers, contractors, ready-mix plant operators and government officials. Received: 21 September 1999 · Accepted: 10 December 1999     

The impact of Hurricane Andrew on deviant behavior among a multi-racial/ethnic sample of adolescents in Dade County, Florida: a longitudinal analysis

Findings from a longitudinal study are presented on the relationships between the problems and stresses resulting from Hurricane Andrew and posthurricane minor deviant behavior. The sample (N = 4,978) included Hispanic, African-American, and White non-Hispanic middle school students enrolled in Dade County, Florida public schools. Two waves of data were collected prior to the hurricane; a third was obtained approximately 6 months following the storm. Results indicated that females were likely to report higher levels of hurricane-related stress symptoms than males. After controlling for prehurricane levels of minor deviance, family support, and race/ethnicity, hurricane stress symptom level remained a significant predictor of posthurricane minor deviant behavior. The findings lend support to stress theories of social deviance.     

Family history score as a predictor of breast cancer mortality: prospective data from the Cancer Prevention Study II, United States, 1982-1991

A consistent predictor of a woman's risk for breast cancer is a family history of the disease. Most studies of family history and breast cancer have used the number of affected relatives in the family to calculate relative risk, but they have not considered the heterogeneity of the familial risk for breast cancer in a systematic way. With the use of data from a large prospective mortality study of US adults, the authors compared simple classification of family history of breast cancer (yes/no) to the method of using a quantitative family history score method, which takes into account the effects of family structure, age, and birth cohort as predictors of breast cancer mortality. After 9 years of follow-up, 1,428 cases of fatal breast cancer were observed among 453,073 women with complete information on number and age of siblings and family history. With the use of the family history score, about one-third of women with a positive family history of breast cancer were at no higher risk for breast cancer mortality than those without a family history of the disease. As a quantitative measure of relative risk for each family, family history score gave a better fit to the data, and it provided an incremental improvement of predictive accuracy of developing fatal breast cancer. Family history score can also be used as a categorical variable to stratify families. This allows researchers to focus on which risk groups would benefit from conducting further genetic analysis and to test the effects of genetic factors, environmental exposure, and gene-environment interactions on the etiology of the development of breast cancer.