the energy 
We use the analytic tools such as the energy, and the Laplacians defined by Kigami


We consider the CamassaHolm equation with data in the energy norm H1(R1).


When the singularities are not integrable on the energy surface the results are significative since the order w.r.t.


The energy method is the main method used for errors estimation in this paper.


The methods rely on the energy analysis and a scale argument.


Several theorems on the finiteness of energy for quasiharmonic spheres are proved, some counterexamples which state that the energy of quasiharmonic sphere may be infinite are given.


The implementation of this method depends on the Lp  Lq estimate and the energy estimate.


By use of the special properties of this element, and by introducing the complementary space and a series of novel techniques, the optimal error estimates of the energy norm and the L2norm are obtained.


And then by exact analysis of the energy equation, it is shown that the global weak attractor is actually the global strong attractor in Hperk.


Furthermore, the dissipative particle dynamics (DPD) was adopted to simulate the aggregation of CTAB in water and ethanol/water mixtures, and the energy difference was calculated for the surfactant tail groups after mixing with the solvent.


The spectra indicate that the energy transfer takes place from the triplet excited state of MLCT (metaltoligand charge transfer) state for Sr2CeO4 (sensitizer) to the rare earth ions (activator).


The performance of the algorithm is evaluated by the covered percentage of region/events, the detecting ability and the energy equalization of the networks.


The order and number of nodes on the route traversed by a mobile agent determine the energy consumption, and hence, they have a significant impact on the overall performance of the whole system.


To overcome this one of the main drawbacks in image sparse decomposition, the property of the energy distribution of atoms is studied in this paper.


Therefore, it can jointly optimize the aggregation and transmission costs and reduce the energy consumption for data gathering.


Simulation results show that the energy consumption difference between this distributed online algorithm and the previous offline one is within 17% under any network conditions.


In the light of the energy economy principle, the cutting theory on the micron and longslice wood fiber was put forward.


The result showed that the energy waste by machining at micron is much lower than by heat grind and the high quality and longslice wood fiber was gained.


It was found that aluminum foam filling can increase the energy absorption capacities of the hat sections.


When the energy in silicon lattice reaches its maximum value, the bonds of silicon atoms are broken and the material is removed.

