Anthropogenic disturbance as a driver of microspatial and microhabitat segregation of cytotypes of Centaurea stoebe and cytotype interactions in secondary contact zones

Background and Aims In a mixed-ploidy population, strong frequency-dependent mating will lead to the elimination of the less common cytotype, unless prezygotic barriers enhance assortative mating. However, such barriers favouring cytotype coexistence have only rarely been explored. Here, an assessment is made of the mechanisms involved in formation of mixed-ploidy populations and coexistence of diploid plants and their closely related allotetraploid derivates from the Centaurea stoebe complex (Asteraceae). Methods An investigation was made of microspatial and microhabitat distribution, life-history and fitness traits, flowering phenology, genetic relatedness of cytotypes and intercytotype gene flow (cpDNA and microsatellites) in six mixed-ploidy populations in Central Europe. Key Results Diploids and tetraploids were genetically differentiated, thus corroborating the secondary origin of contact zones. The cytotypes were spatially segregated at all sites studied, with tetraploids colonizing preferentially drier and open microhabitats created by human-induced disturbances. Conversely, they were rare in more natural microsites and microsites with denser vegetation despite their superior persistence ability (polycarpic life cycle). The seed set of tetraploid plants was strongly influenced by their frequency in mixed-ploidy populations. Triploid hybrids originated from bidirectional hybridizations were extremely rare and almost completely sterile, indicating a strong postzygotic barrier between cytotypes. Conclusions The findings suggest that tetraploids are later immigrants into already established diploid populations and that anthropogenic activities creating open niches favouring propagule introductions were the major factor shaping the non-random distribution and habitat segregation of cytotypes at fine spatial scale. Establishment and spread of tetraploids was further facilitated by their superior persistence through the perennial life cycle. The results highlight the importance of non-adaptive spatio-temporal processes in explaining microhabitat and microspatial segregation of cytotype

Maintaining scale as a realiable computational system for criticality safety analysis

Accurate and reliable computational methods are essential for nuclear criticality safety analyses. The SCALE (Standardized Computer Analyses for Licensing Evaluation) computer code system was originally developed at Oak Ridge National Laboratory (ORNL) to enable users to easily set up and perform criticality safety analyses, as well as shielding, depletion, and heat transfer analyses. Over the fifteen-year life of SCALE, the mainstay of the system has been the criticality safety analysis sequences that have featured the KENO-IV and KENO-V.A Monte Carlo codes and the XSDRNPM one-dimensional discrete-ordinates code. The criticality safety analysis sequences provide automated material and problem-dependent resonance processing for each criticality calculation. This report details configuration management which is essential because SCALE consists of more than 25 computer codes (referred to as modules) that share libraries of commonly used subroutines. Changes to a single subroutine in some cases affect almost every module in SCALE! Controlled access to program source and executables and accurate documentation of modifications are essential to maintaining SCALE as a reliable code system. The modules and subroutine libraries in SCALE are programmed by a staff of approximately ten Code Managers. The SCALE Software Coordinator maintains the SCALE system and is the only person who modifies the production source, executables, and data libraries. All modifications must be authorized by the SCALE Project Leader prior to implementation

Exposure Assessment Approaches for Engineered Nanomaterials

Products based on nanotechnology are rapidly emerging in the marketplace, sometimes with little notice to consumers of their nanotechnology pedigree. This wide variety of nanotechnology products will result (in some cases) in unintentional human exposure to purposely engineered nanoscale materials via the dermal, inhalation, ingestion, and ocular pathways. Occupational, consumer, and environmental exposure to the nanomaterials should be characterized during the entire product lifecycle—manufacture, use, and disposal. Monitoring the fate and transport of engineered nanomaterials is complicated by the lack of detection techniques and the lack of a defined set of standardized metrics to be consistently measured. New exposure metrics may be required for engineered nanomaterials, but progress is possible by building on existing tools. An exposure metric matrix could organize existing data by relating likely exposure pathways (dermal, inhalation, ocular, ingestion) with existing measurements of important characteristics of nanoscale materials (particle number, mass, size distribution, charge). Nanomaterial characteristics not commonly measured, but shown to initiate a biological response during toxicity testing, signal a need for further research, such as the pressing need to develop monitoring devices capable of measuring those aspects of engineered nanomaterials that result in biological responses in humans. Modeling the behavior of nanoparticles may require new types of exposure models that individually track particles through the environment while keeping track of the particle shape, surface area, and other surface characteristics as the nanoparticles are transformed or become reactive. Lifecycle analysis could also be used to develop conceptual models of exposure from engineered nanomaterials.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/79200/1/j.1539-6924.2010.01446.x.pd

Detecting Network Communities: An Application to Phylogenetic Analysis

This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be used for network construction so that the network structure can be analyzed to recover phylogenetically useful information from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks, explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix . The most relevant networks are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (>70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100 organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance, likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis

Magnetic moment of a two-quasiparticle state in <SUP>182</SUP>W

The magnetic moment of the I<SUP>&#928;</SUP> = 2<SUP>-</SUP> two-quasiparticle state at 1289keV in <SUP>182</SUP>W has been measured to be &#956; = 1.04 &#177; 0.24nm