Self-consistent collective subspaces and diabatic/adiabatic motion in nuclei

We discuss the application of a theory of large-amplitude collective motion to a simple model mimicking the pairing-plus-quadrupole model of nuclear physics.Comment: 4 pages, RevTex using graphicx.sty, 1 postscript figures included. Talk presented at Conference on "Nuclear structure at the extremes" (June 17 - 19, 1998, Lewes, UK

Multi-Phonon γ\gamma-Vibrational Bands and the Triaxial Projected Shell Model

We present a fully quantum-mechanical, microscopic, unified treatment of ground-state band and multi-phonon $\gamma$-vibrational bands using shell model diagonalization with the triaxial projected shell model. The results agree very well with data on the g- and $\gamma$-band spectra in $^{156-170}$Er, as well as with recently measured $4^+$ 2-phonon $\gamma$-bandhead energies in $^{166}$Er and $^{168}$Er. Multi-phonon $\gamma$-excitation energies are predicted.Comment: 4 pages, 4 figures, submitted to Phys. Lett.

Parametrization of the octupole degrees of freedom

A simple parametrization for the octupole collective variables is proposed and the symmetries of the wave functions are discussed in terms of the solutions corresponding to the vibrational limit. [PACS: 21.60Ev, 21.60.Fw, 21.10.Re]Comment: 14 page

An overview of the higher level classification of Pucciniomycotina based on combined analyses of nuclear large and small subunit rDNA sequences

Mycologia, Vol. 98, nº6In this study we provide a phylogenetically based introduction to the classes and orders of Pucciniomycotina (5Urediniomycetes), one of three subphyla of Basidiomycota. More than 8000 species of Pucciniomycotina have been described including putative saprotrophs and parasites of plants, animals and fungi. The overwhelming majority of these(,90%) belong to a single order of obligate plant pathogens, the Pucciniales (5Uredinales), or rust fungi. We have assembled a dataset of previously published and newly generated sequence data from two nuclear rDNA genes (large subunit and small subunit) including exemplars from all known major groups in order to test hypotheses about evolutionary relationships among the Pucciniomycotina. The utility of combining nuc-lsu sequences spanning the entire D1-D3 region with complete nuc-ssu sequences for resolution and support of nodes is discussed. Our study confirms Pucciniomycotina as a monophyletic group of Basidiomycota. In total our results support eight major clades ranked as classes (Agaricostilbomycetes, Atractiellomycetes, Classiculomycetes,Cryptomycocolacomycetes,Cystobasidiomycetes, Microbotryomycetes,Mixiomycetes and Pucciniomycetes) and 18 orders

AxPcoords & parallel AxParafit: statistical co-phylogenetic analyses on thousands of taxa

Background Current tools for Co-phylogenetic analyses are not able to cope with the continuous accumulation of phylogenetic data. The sophisticated statistical test for host-parasite co-phylogenetic analyses implemented in Parafit does not allow it to handle large datasets in reasonable times. The Parafit and DistPCoA programs are the by far most compute-intensive components of the Parafit analysis pipeline. We present AxParafit and AxPcoords (Ax stands for Accelerated) which are highly optimized versions of Parafit and DistPCoA respectively. Results Both programs have been entirely re-written in C. Via optimization of the algorithm and the C code as well as integration of highly tuned BLAS and LAPACK methods AxParafit runs 5–61 times faster than Parafit with a lower memory footprint (up to 35% reduction) while the performance benefit increases with growing dataset size. The MPI-based parallel implementation of AxParafit shows good scalability on up to 128 processors, even on medium-sized datasets. The parallel analysis with AxParafit on 128 CPUs for a medium-sized dataset with an 512 by 512 association matrix is more than 1,200/128 times faster per processor than the sequential Parafit run. AxPcoords is 8–26 times faster than DistPCoA and numerically stable on large datasets. We outline the substantial benefits of using parallel AxParafit by example of a large-scale empirical study on smut fungi and their host plants. To the best of our knowledge, this study represents the largest co-phylogenetic analysis to date. Conclusion The highly efficient AxPcoords and AxParafit programs allow for large-scale co-phylogenetic analyses on several thousands of taxa for the first time. In addition, AxParafit and AxPcoords have been integrated into the easy-to-use CopyCat tool

Global patterns in endemicity and vulnerability of soil fungi

Fungi are highly diverse organisms, which provide multiple ecosystem services. However, compared with charismatic animals and plants, the distribution patterns and conservation needs of fungi have been little explored. Here, we examined endemicity patterns, global change vulnerability and conservation priority areas for functional groups of soil fungi based on six global surveys using a high-resolution, long-read metabarcoding approach. We found that the endemicity of all fungi and most functional groups peaks in tropical habitats, including Amazonia, Yucatan, West-Central Africa, Sri Lanka, and New Caledonia, with a negligible island effect compared with plants and animals. We also found that fungi are predominantly vulnerable to drought, heat and land-cover change, particularly in dry tropical regions with high human population density. Fungal conservation areas of highest priority include herbaceous wetlands, tropical forests, and woodlands. We stress that more attention should be focused on the conservation of fungi, especially root symbiotic arbuscular mycorrhizal and ectomycorrhizal fungi in tropical regions as well as unicellular early-diverging groups and macrofungi in general. Given the low overlap between the endemicity of fungi and macroorganisms, but high conservation needs in both groups, detailed analyses on distribution and conservation requirements are warranted for other microorganisms and soil organisms

Internet of Things for Sustainable Forestry

Forests and grasslands play an important role in water and air purification, prevention of the soil erosion, and in provision of habitat to wildlife. Internet of Things has a tremendous potential to play a vital role in the forest ecosystem management and stability. The conservation of species and habitats, timber production, prevention of forest soil degradation, forest fire prediction, mitigation, and control can be attained through forest management using Internet of Things. The use and adoption of IoT in forest ecosystem management is challenging due to many factors. Vast geographical areas and limited resources in terms of budget and equipment are some of the limiting factors. In digital forestry, IoT deployment offers effective operations, control, and forecasts for soil erosion, fires, and undesirable depositions. In this chapter, IoT sensing and communication applications are presented for digital forestry systems. Different IoT systems for digital forest monitoring applications are also discussed