Detecting uber-operons in prokaryotic genomes

We present a study on computational identification of uber-operons in a prokaryotic genome, each of which represents a group of operons that are evolutionarily or functionally associated through operons in other (reference) genomes. Uber-operons represent a rich set of footprints of operon evolution, whose full utilization could lead to new and more powerful tools for elucidation of biological pathways and networks than what operons have provided, and a better understanding of prokaryotic genome structures and evolution. Our prediction algorithm predicts uber-operons through identifying groups of functionally or transcriptionally related operons, whose gene sets are conserved across the target and multiple reference genomes. Using this algorithm, we have predicted uber-operons for each of a group of 91 genomes, using the other 90 genomes as references. In particular, we predicted 158 uber-operons in Escherichia coli K12 covering 1830 genes, and found that many of the uber-operons correspond to parts of known regulons or biological pathways or are involved in highly related biological processes based on their Gene Ontology (GO) assignments. For some of the predicted uber-operons that are not parts of known regulons or pathways, our analyses indicate that their genes are highly likely to work together in the same biological processes, suggesting the possibility of new regulons and pathways. We believe that our uber-operon prediction provides a highly useful capability and a rich information source for elucidation of complex biological processes, such as pathways in microbes. All the prediction results are available at our Uber-Operon Database: , the first of its kind

The case for addressing the limiting impact of interference on wireless scheduling

Abstract—Co-channel interference is a limiting factor to the predictability and performance of wireless networks, thus interference-oriented scheduling of channel access has become a basic building block of wireless networking. Despite much work in this area, the existing algorithms did not address the limiting impact of interference when optimizing transmission scheduling. Towards understanding the importance of considering the limiting impact of interference, we formulate the concept of interference budget, and we propose the scheduling algorithm iOrder that maximizes the schedulability of future channel access when scheduling concurrent transmissions. When selecting concurrent transmitters for a time slot, more specifically, iOrder tries to maximize the additional interference that can be tolerated by all the receivers while satisfying the application requirement on link reliability. We analyze the approximation ratio of iOrder, and, through extensive simulation and testbedbased measurement, we observe that addressing the limiting impact of interference can improve the performance of existing algorithms by a significant margin, for instance, improving the throughput of the well-known algorithm LQF by a factor up to 2. Thus our study demonstrates the importance of explicitly addressing the limiting impact of interference, which opens up new avenues for future research and for optimizing wireless network performance. I

Characteristics of rice husk gasification in cyclone pyrolysis-suspended combustion system

The cyclonic gasification technology could realize self-separation of syngas and residual carbon, simplifying the purification system. In cyclone pyrolysis-suspension combustion system, bottom air was fed into carbon-rich area of gasifier. Due to the high height/diameter ratio and uneven temperature distribution in cyclone gasifier, the primary/secondary/bottom air rates were 30%, 20%, and 50%, respectively. Effects of gasification intensity and air equivalent ratio on rice husk gasification performance were explored. The results show that for cyclone pyrolysis-suspension combustion, the optimum gasification intensity is 885.24 kg/m2h. Strengthening the subregion of air supplement could cause a gradual increasing of temperature along the axis of gasifier. The syngas yield was independent of gasification intensity, but increased from 0.98 Nm3/kg at ER = 0.23 to 1.38 Nm3/kg at ER = 0.32. At ER = 0.26~0.29, the gasification performance is best, with gas heat value of 4.99~5.37 MJ/Nm3, cold gasification efficiency of 48.25~49.67% and tar content of 5.38~5.75 g/Nm3

Facile synthesis of high surface area hedgehog-like CuO microspheres with improved lithium storage properties

We report the preparation of high surface area hedgehog-like CuO microspheres by a wet-chemical method and their application in Li-ion batteries used as anode materials. The samples were characterized by Nitrogen adsorption, X-ray diffraction, scanning electron microscopy, transmission electron microscopy, temperature-programmed reduction and thermogravimetric analysis. The synthesized hedgehog-like CuO microspheres with a size of 1-3 um possessed a high surface area of 103.5 -157.4 m(2) g(-1) and an average crystal size of 7-9 nm. When used as anode materials, they showed an initial discharge and charge capacity of 1294.6 and 647.6 mAh g(-1), respectively, much higher than the corresponding values of the low surface area CuO microspheres, which are 967.1 and 382.6 mAh g(-1) respectively. After calcination at 300 and 600 degrees C, the morphology of hedgehog-like CuO microspheres was still maintained, and a high capacity of 570-590 mAh g(-1) at 0.1 C was observed after 50 cycles. Meanwhile, the average capacity fading rates for calcined hedgehog-like CuO microspheres were much lower than that of non-calcined and low surface area CuO microspheres, demonstrating that the calcination of CuO microspheres with the high surface area leads to a better cycling performance. This work provides a new method to prepare high surface area CuO materials, which are promising anode materials with high capacity and long cycling life in Li-ion batteries. (C) 2012 Elsevier B.V. All rights reserved