Cellulase-producing bacteria were isolated from soil and identified as Pseudomonas fluorescens, Bacillus subtilIs, E. coli, and Serratia marcescens. Optimization of the fermentation medium for maximum cellulase production was carried out. The culture conditions like pH, temperature, carbon sources, and nitrogen sources were optimized. The optimum conditions found for cellulase production were 40°C at pH 10 with glucose as carbon source and ammonium sulphate as nitrogen source, and coconut cake stimulates the production of cellulase. Among bacteria, Pseudomonas fluorescens is the best cellulase producer among the four followed by Bacillus subtilis, E. coli, and Serratia marscens.

In this paper, we introduce the notion of snapstabilization. A snap-stabilizing algorithm protocol guarantees that, starting from an arbitrary system configuration, the protocol always behaves according to its specification. So, a snap-stabilizing protocol is a self-stabilizing protocol which stabilizes in 0 steps.We propose a snap-stabilizing Propagation of Information with Feedback (PIF) scheme on a rooted tree network. We call this scheme Propagation of information with Feedback and Cleaning (P F C ). We present two algorithms. The first one is a basic P F C scheme which is inherently snapstabilizing. However, it can be delayed Oh 2 steps (where h is the height of the tree) due to some undesirable local states. The second algorithm improves the worst delay of the basic P F C algorithm from Oh 2 to 1 step. The P F C scheme can be used to implement the distributed reset, the distributed infimum computation, and the global synchronizer in O1 waves (or PIF cycles). Moreover, assuming that a (local) checking mechanism exists to detect transient failures or topological changes, the P F C scheme allows processors to (locally) "detect" if the system is stabilized, in O1 waves without using any global metric (such as the diameter or size of the network).Finally, we show that the state requirement for both P F C algorithms matches the exact lower bound of the PIF algorithms on tree networks-3 states per processor, except for the root and leaf processors which use only 2 states. Thus, the proposed algorithms are optimal PIF schemes in terms of the number of states.

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Stability of anatase phase component present in commercial grade nanocrystalline powder of TiO2, synthesized from gas phase, is studied. Powders are heated at elevated temperatures under ambient conditions. X-ray and electron diffractometric studies are done to measure the microstructural parameters like crystallite size and rms strain. With annealing crystallite sizes of both anatase and rutile phases show a marginal increase up to 600 °C, beyond this temperature anatase phase transforms to rutile phase and the crystallite size of rutile phase increases rapidly. Annealing at 1000 °C resulted in the growth of hexagonal shaped crystallite of rutile phase oriented parallel to (110) plane. A detailed analysis of the dislocation arrangements in these nanosized crystallites is made from the x-ray diffraction data. The results of analysis show that at higher temperatures polygonization of the dislocations with lowering of dislocation density at the grain boundary possibly favors the growth of larger sized crystallites of rutile phase. High values of dislocation density obtained for anatase give evidence of piling up of dislocations and thereby increases the strain energy of the lattice. The increase in stored energy may be responsible for the observed changes in the lattice parameter for the anatase phase. Thus, it appears that the disordered lattice of anatase favors its transformfiation to rutile structure.

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The contribution of this paper is threefold. First, we present the paradigm of snap-stabilization. A snapstabilizing protocol guarantees that, starting from an arbitrary system configuration, the protocol always behaves according to its specification. So, a snap-stabilizing protocol is a time optimal self-stabilizing protocol (because it stabilizes in 0 rounds). Second, we propose a new Propagation of Information with Feedback (PIF) cycle, called Propagation of Information with Feedback and Cleaning (PFC). We show three different implementations of this new PIF. The first one is a basic PFC cycle which is inherently snap-stabilizing. However, the first PIF cycle can be delayed O(h 2 ) rounds (where h is the height of the tree) due to some undesirable local states. WARNING:The concept of snap-stabilization was first introduced in [12]. The concept evolved over the last eight years. We take this evolution in consideration in this paper, which includes the early results published in [10] and [12]. In particular, infinite repetition of computation cycles is a requirement of self -stabilizing systems. This is not required in snap-stabilization because snap-stabilization ensures that the first completed computation cycle is executed according to the specification of the problem. The correctness proofs conform to this basic property.The second algorithm improves the worst delay of the basic PFC algorithm from O(h 2 ) to 1 round. The state requirement for the above two algorithms is 3 states per processor, except for the root and leaf processors that use only 2 states. Also, they work on oriented trees. We then propose a third snap-stabilizing PIF algorithm on un-oriented tree networks. The state requirement of the third algorithm depends on the degree of the processors, and the delay is at most h rounds. Next, we analyze the maximum waiting time before a PIF cycle can be initiated whether the PIF cycle is infinitely and sequentially repeated or launch as an isolated PIF cycle. The analysis is made for both oriented and un-oriented trees. We show or conjecture that the two best of the above algorithms produce optimal waiting time. Finally, we compute the minimal number of states the processors require to implement a single PIF cycle, and show that both algorithms for oriented trees are also (in addition to being time optimal) optimal in terms of the number of states.

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