Metagenomic and functional analysis of hindgut microbiota of a wood-feeding higher termite

From the standpoints of both basic research and biotechnology, there is considerable interest in reaching a clearer understanding of the diversity of biological mechanisms employed during lignocellulose degradation. Globally, termites are an extremely successful group of wood-degrading organisms and are therefore important both for their roles in carbon turnover in the environment and as potential sources of biochemical catalysts for efforts aimed at converting wood into biofuels. Only recently have data supported any direct role for the symbiotic bacteria in the gut of the termite in cellulose and xylan hydrolysis. Here we use a metagenomic analysis of the bacterial community resident in the hindgut paunch of a wood-feeding 'higher' Nasutitermes species (which do not contain cellulose-fermenting protozoa) to show the presence of a large, diverse set of bacterial genes for cellulose and xylan hydrolysis. Many of these genes were expressed in vivo or had cellulase activity in vitro, and further analyses implicate spirochete and fibrobacter species in gut lignocellulose degradation. New insights into other important symbiotic functions including H2 metabolism, CO2-reductive acetogenesis and N2 fixation are also provided by this first system-wide gene analysis of a microbial community specialized towards plant lignocellulose degradation. Our results underscore how complex even a 1-microl environment can be.     

Sequential interactions with Sec23 control the direction of vesicle traffic

How the directionality of vesicle traffic is achieved remains an important unanswered question in cell biology. The Sec23p/Sec24p coat complex sorts the fusion machinery (SNAREs) into vesicles as they bud from the endoplasmic reticulum (ER). Vesicle tethering to the Golgi begins when the tethering factor TRAPPI binds to Sec23p. Where the coat is released and how this event relates to membrane fusion is unknown. Here we use a yeast transport assay to demonstrate that an ER-derived vesicle retains its coat until it reaches the Golgi. A Golgi-associated kinase, Hrr25p (CK1δ orthologue), then phosphorylates the Sec23p/Sec24p complex. Coat phosphorylation and dephosphorylation are needed for vesicle fusion and budding, respectively. Additionally, we show that Sec23p interacts in a sequential manner with different binding partners, including TRAPPI and Hrr25p, to ensure the directionality of ER-Golgi traffic and prevent the back-fusion of a COPII vesicle with the ER. These events are conserved in mammalian cells.     

Modeling the effects of ore properties on water recovery in the thickening process

A better understanding of solid-liquid separation would assist in improving the thickening performance and perhaps water recovery as well. The present work aimed to develop an empirical model to study the effects of ore properties on the thickening process based on pilot tests using a column. A hydro-cyclone was used to prepare the required samples for the experiments. The model significantly predicted the experimental underflow solid content using a regression equation at a given solid flux and bed level for different samples, indicating that ore properties are the effective parameters in the thickening process. This work confirmed that the water recovery would be increased about 5% by separating the feed into two parts, overflow and underflow, and introducing two different thickeners into them separately. This is duo to the fact that thickeners are limited by permeability and compressibility in operating conditions.     

Structural and dielectric properties of doped ferrite nanomaterials suitable for microwave and biomedical applications

The sol–gel auto-combustion method was adopted to synthesize nanomaterials of single-phase X-type hexagonal ferrites with the composition of Sr2?xGdxNi2Fe28?yCdyO46 (x=0.00, 0.02, 0.04, 0.06, 0.08, 0.10 and y=0, 0.1, 0.2, 0.3, 0.4, 0.5). The structural properties were carried out by XRD analysis and the lattice parameters show variation with the doping of Gd–Cd. The average particle size measured by TEM was in the range of 8–10 nm which is beneficial in obtaining suitable signal-to-noise ratio in recording media and biomedical applications. The room temperature resistivity enhanced with the increase of the dopant concentration. The increase in resistivity indicates that the synthesized materials can be considered good for the formation of the multilayer chip inductors (MLCIs) as well as for the reduction of eddy current losses. The dielectric constant decreased with the increase in the frequency which is the general reported trend of the hexagonal ferrites and can be explained on the basis of Koop?s theory and Maxwell–Wagner polarization-model. The abnormal dielectric behavior indicates the formation of small polarons in the material. The maximum value of tangent loss at low frequencies reflects the application of these materials in medium frequency devices (MF).     

Evaluation and modification of inclusion characteristics in HK40 heatresistant cast steel

Specifications of inclusions such as the type, morphology, number, composition, size, and place of inclusions in HK40 heat-resistant casting steel were studied by optical microscopy and scanning electron microscopy equipped with an energy-dispersive spectroscopy system. The effects of calcium silicide (CaSi) addition on these characteristics were evaluated at two pouring temperatures of 1420℃ and 1470℃. It was found that most of the appeared inclusions were in the type of chromium oxide. CaSi addition had a significant effect on the morphological modification, size and distribution of inclusions as well as changing the composition to oxide-sulfide compounds.     

Climatic regionalization mapping of the Murrumbidgee Irrigation Area,Australia

In this study,spatial analysis techniques were used to generate climatic zoning maps of the East Murrumbidgee Irrigation Area (MIA),Australia.Long term climate data were used to analyze and assess regional climatic variation by cluster analysis in a GIS environment.Based on thermal and moisture factors,four variables were chosen to develop climate zones.These variables include annual average rainfalls,annual average ETc,annual average Growing Day Degree (GDD) and daily average temperature generated from daily climate data of 36 years (1971-2006) on 12 local weather stations as the fundamental elements of regional climate characteristics.GIS-based spatial analysis models are used to map climate sub-regions from sets of climatic parameters derived from regional climate data sources.Two climate zoning schemes are presented by integration of spatial interpolation,spatial cluster analysis and climate indices methods.One scheme comes with the two climate zones of the West and the East based on spatial cluster analysis according to selected climatic variables,and the other comes with the three comprehensive hydro-thermal zones and the six hydro-thermal balance zones.     

A self-similar local neuro-fuzzy model for short-term demand forecasting

This paper proposes a selfsimilar local neurofuzzy （SSLNF） model with mutual informati onbased input selection algorithm for the shortterm electricity demand forecasting. The proposed self similar model is composed of a number of local models, each being a local linear neurofuzzy （LLNF） model, and their associated validity functions and can be interpreted itself as an LLNF model. The proposed model is trained by a nested local liner model tree （NLOLIMOT） learning algorithm which partitions the input space into axisorthogonal subdomains and then fits an LLNF model and its associated validity function on each subdomain. Furthermore, the proposed approach allows different input spaces for rule premises （validity functions） and consequents （local models）. This appealing property is employed to assign the candidate input variables （i.e., previous load and temperature） which influence shortterm electricity demand in linear and nonlinear ways to local models and validity functions, respectively. Numerical results from shortterm load forecasting in the New England in 2002 demonstrated the accuracy of the SSLNF model for the STLF applications.