A preliminary study of marine fungi from Abaco Island,the Bahamas

Marine soil, mangrove wood, and free floating algal collections were made in the shallow littoral zone of Abaco Island, The Bahamas. Material was subsequently examined in the laboratory for fungal populations inhabiting seawater shorelines of the island. The study follows previous mycological investigations of Abaco including the keratinophilic fungi (10) and the fresh water fungi (11).     

Real-time software methodologies: Are they suitable for developing Manufacturing control software?

Computer-Integrated Manufacturing (CIM) systems may be classified as real-time systems. Hence, the applicability of methodologies that are developed for specifying, designing, implementing, testing, and evolving real-time software is investigated in this article. The paper highlights the activities of the software development process. Among these activities, a great emphasis is placed on automating the software requirements specification activity, and a set of formal models and languages for specifying these requirements is presented. Moreover, a synopsis of the real-time software methodologies that have been implemented by the academic and industrial communities is presented together with a critique of the strengths and weaknesses of these methodologies. The possible use of the real-time methodologies in developing the control software of efficient and dependable manufacturing systems is explored. In these systems, efficiency is achieved by increasing the level of concurrency of the operations of a plan, and by scheduling the execution of these operations with the intent of maximizing the utilization of the devices of their systems. On the other hand, dependability requires monitoring the operations of these systems. This monitoring activity facilitates the detection of faults that may occur when executing the scheduled operations of a plan, recovering from these faults, and, whenever feasible, resuming the original schedule of the system. The paper concludes that the set of surveyed methodologies may be used to develop the real-time control software of efficient and dependable manufacturing systems. However, an integrated approach to planning, scheduling, and monitoring the operations of these systems will significantly enhance their utility, and no such approach is supported by any of these methodologies.     

Familial Clustering of Abdominal Visceral Fat and Total Fat Mass: The Québec Family Study

The evidence for common familial factors underlying total fat mass (estimated from underwater weighing) and abdominal visceral fat (assessed from CT scan) was examined in families participating in phase 2 of the Québec Family Study (QFS) using a bivariate familial correlation model. Previous QFS investigations suggest that both genetic (major and polygenic) and familial environmental factors influence each phenotype, accounting for between 55% to 71% of the phenotypic variance in fat mass, and between 55% to 72% for abdominal visceral fat The current study suggests that the bivariate familial effect ranges from 29% to 50%. This pattern suggests that there may be common familial determinants for abdominal visceral fat and total fat mass, as well as additional familial factors which are specific to each. The relatively high spouse cross-trait correlations usually suggest that a large percent of the bivariate familial effect may be environmental in origin. However, if mating is not random, then the spouse resemblance may reflect either genetic or environmental causes, depending on the source [i.e., through similar genes or cohabitation (environmental) effects]. Finally, there are significant sex differences in the magnitude of the familial cross-trait correlations involving parents, but not offspring, suggesting complex generation (i.e., age) and sex effects. For example, genes may turn on or off as a function of age and sex, and/or there may be an accumulation over time of effects due to the environment which may vary by sex. Whether the common familial factors are genetic (major and/or polygenic), environmental, or some combination of both, and whether the familial expression depends on sex and/or age warrants further investigation using more complex models.