Isolation and identification of gut symbiotic bacteria of the termite Anacanthotermes vagans (Isoptera: Hodotermitidae)

Termites play a major role in reducing and decomposing woody materials within terrestrial ecosystems by degrading lingo-cellulosic materials with the help of the microbial community of their guts. We isolated the lignin-degrading bacteria from Anacanthotermes vagans (Hagen) using liquid and solid media containing wheat straw and lignin hydrochloric acid. Cellulose-degrading bacteria were also isolated using liquid medium containing filter paper, agar-cellulose and Congo red agar-cellulose. By conducting various experiments, 16 bacterial species were isolated and subjected to different biochemical tests for comparing their growth rates. The genera Enterobacter and Klebsiella showed the highest growth rate among the rest species of isolated lignin-degrading bacteria. The species Staphylococcus lentus and Bacillus subtilis were isolated from the media containing cellulose

esys-Escript User’s Guide: Solving Partial Differential Equations with Escript and Finley Release - 3.3.1 (r4302)

esys.escript is a python-based environment for implementing mathematical models, in particular those based on coupled, non-linear, time-dependent partial differential equations. It consists of five major components • esys.escript core library • finite element solver esys.finley (which uses fast vendor-supplied solvers or our paso linear solver library) • the meshing interface esys.pycad • a model library. • an inversion library. The current version supports parallelization through both MPI for distributed memory and OpenMP for distributed shared memory. In this release there are a number of small changes which are not backwards compatible. Please see Appendix B to see if your scripts will be affected. If you use this software in your research, then we would appreciate (but do not require) a citation. Some relevant references can be found in Appendix D. For Python3 support, see Appendix E

Study on breeding of imported brood stocks Litopenaeus vannamei in Iran environment

Regarding to breeding the Litopenaeus vannamei, a total of 126 pairs of broodstocks were imported from Hawaii to Iran in 2004 and 2005, and then transferred to the Bandargah Research Station in Bushehr. The female broodstocks were ablated, and were feeded 3 times per day with cuttlefish, small size shrimp and Nereis worm with a ratio of 30% body weight. The water exchange were done 3 times per day. During the years 2004 and 2005 a total 1700000 naupli were produced of which 772000 specimens of pl13 and pl7 were harvested and then transferred to Helleh Site for carrying out the next culture project. The average naupli and postlarvae were 170000 and 92000 in proportion to each broodstock. Also the mean survival rate was estimated 54%

Lattice Boltzmann Simulation of Solid Particles Motion in a Three Dimensional Flow using Smoothed Profile Method

Three-dimensional particulate flow has been simulated using Lattice Boltzmann Method (LBM). Solid-fluid interaction was modeled based on Smoothed Profile Method (SPM) (Jafari et. al, Lattice-Boltzmann method combined with smoothed-profile method for particulate suspensions, Phys. Rev. E, 2011). In this paper a GPU code based on three-dimensional lattice Boltzmann method and smoothed profile method has been prepared due to the ability of SPM-LBM to perform locally and in parallel mode. Results obtained for sedimentation of one and two spherical particles as well as their behavior in shear flow showed excellent correspondence with previous published works. Computations for a large number of particles sedimentation showed that combination of LBM and SPM on a GPU platform can be considered as an efficient and promising computational frame work in particulate flow simulations

esys-Escript User’s Guide: Solving Partial Differential Equations with Escript and Finley Release - 3.4 (r4488)

esys.escript is a python-based environment for implementing mathematical models, in particular those based on coupled, non-linear, time-dependent partial differential equations. It consists of five major components • esys.escript core library • finite element solver esys.finley (which uses fast vendor-supplied solvers or our paso linear solver library) • the meshing interface esys.pycad • a model library. • an inversion library. The current version supports parallelization through both MPI for distributed memory and OpenMP for distributed shared memory. In this release there are a number of small changes which are not backwards compatible. Please see Appendix B to see if your scripts will be affected. If you use this software in your research, then we would appreciate (but do not require) a citation. Some relevant references can be found in Appendix D. For Python3 support, see Appendix E

Site-specific differences in osteoblast phenotype, mechanical loading response and estrogen receptor-related gene expression

King’s Health Partner’s Research and Development Challenge Fun

esys-Escript User’s Guide: Solving Partial Differential Equations with Escript and Finley Release - 3.4.2 (r4925)

esys.escript is a python-based environment for implementing mathematical models, in particular those based on coupled, non-linear, time-dependent partial differential equations. It consists of five major components • esys.escript core library • finite element solver esys.finley (which uses fast vendor-supplied solvers or our paso linear solver library) • the meshing interface esys.pycad • a model library. • an inversion library. The current version supports parallelization through both MPI for distributed memory and OpenMP for shared memory. In this release there are a number of small changes which are not backwards compatible. Please see Appendix B to see if your scripts will be affected. If you use this software in your research, then we would appreciate (but do not require) a citation. Some relevant references can be found in Appendix D. For Python 3 support, see Appendix E

esys-Escript User’s Guide: Solving Partial Differential Equations with Escript and Finley Release - 4.0 (r5402)

esys.escript is a python-based environment for implementing mathematical models, in particular those based on coupled, non-linear, time-dependent partial differential equations. It consists of five major components: • esys.escript core library • finite element solvers esys.finley, esys.dudley, esys.ripley, and esys.speckley (which use fast vendor-supplied solvers or the included PASO linear solver library) • the meshing interface esys.pycad • a model library • an inversion module. All esys.escript modules should work under both python 2 and python 3, see Appendix E. The current version supports parallelization through MPI for distributed memory, OpenMP for shared memory on CPUs, as well as CUDA for some GPU-based solvers. This release comes with some significant changes and new features. Please see Appendix B for a detailed list. If you use this software in your research, then we would appreciate (but do not require) a citation. Some relevant references can be found in Appendix D

The production of plant protein diet, and determination of their effects on western white shrimp (Litopenaeus vannamei) growth indexes at earthen ponds

The effects of one diet contain of 42 percent soybean meal (experimental treatment with 38 percent crude protein) in comparison with commercial diet (control treatment with 39 percent crud protein) at 6 earthen ponds, each one with the area of 0.4 ha, ( 2 treatments and 3 replicates in each treatment) on growth indexes of western white shrimp (Litopenaeusvannamei) was determined. The initial weight of post larvae was 0.008±0.001g, with density of 25 ind/m^2 . The mean of culture periode in the experimental treatment and control treatment was 115 dayes, The mean of growth rate (GR) in the experimental treatment and control treatment was 15.70±0.88g and 15.60±0.52 g, respectively and significant statistically difference was between those (p0.05).The net protein utilization (NPU) in the experimental treatment and control treatment was 17.05 ±0.38 percent and 11.80±0.26 percent respectively, and significant statistically difference was between those (p0.05).The amount of diet consumption, in the experimental treatment and control treatment was 5144±112.23 kg and 5055±59.77 kg respectively, and significant statistically difference was between those (p<0.05). The price of 1 kg of plant diet and commercial diet computed 34.000 rials and 43.000 rials respectively. In the shrimp body analysis, crude protein percent, in the experimental treatment was more than control treatment and significant statistically difference was computed between those (p<0.05). Totally, the use of plant protein for the feeding of L.vannamei in the earthen pond, can decrease the cost of plant diet, 20 percent lower than commercial diet