1,043 research outputs found
Convergence to diffusion waves for solutions of Euler equations with time-depending damping on quadrant
This paper is concerned with the asymptotic behavior of the solution to the
Euler equations with time-depending damping on quadrant , \begin{equation}\notag \partial_t v
-
\partial_x u=0, \qquad \partial_t u
+
\partial_x p(v)
=\displaystyle
-\frac{\alpha}{(1+t)^\lambda} u, \end{equation} with null-Dirichlet boundary
condition or null-Neumann boundary condition on . We show that the
corresponding initial-boundary value problem admits a unique global smooth
solution which tends time-asymptotically to the nonlinear diffusion wave.
Compared with the previous work about Euler equations with constant coefficient
damping, studied by Nishihara and Yang (1999, J. Differential Equations, 156,
439-458), and Jiang and Zhu (2009, Discrete Contin. Dyn. Syst., 23, 887-918),
we obtain a general result when the initial perturbation belongs to the same
space. In addition, our main novelty lies in the facts that the cut-off points
of the convergence rates are different from our previous result about the
Cauchy problem. Our proof is based on the classical energy method and the
analyses of the nonlinear diffusion wave
Geo-Social Group Queries with Minimum Acquaintance Constraint
The prosperity of location-based social networking services enables
geo-social group queries for group-based activity planning and marketing. This
paper proposes a new family of geo-social group queries with minimum
acquaintance constraint (GSGQs), which are more appealing than existing
geo-social group queries in terms of producing a cohesive group that guarantees
the worst-case acquaintance level. GSGQs, also specified with various spatial
constraints, are more complex than conventional spatial queries; particularly,
those with a strict NN spatial constraint are proved to be NP-hard. For
efficient processing of general GSGQ queries on large location-based social
networks, we devise two social-aware index structures, namely SaR-tree and
SaR*-tree. The latter features a novel clustering technique that considers both
spatial and social factors. Based on SaR-tree and SaR*-tree, efficient
algorithms are developed to process various GSGQs. Extensive experiments on
real-world Gowalla and Dianping datasets show that our proposed methods
substantially outperform the baseline algorithms based on R-tree.Comment: This is the preprint version that is accepted by the Very Large Data
Bases Journa
The Relationship between Virtual Reality Technology and Anxiety State of Parturient Women with Labor Pain
As per the authors' request, the sequence of the affiliations have been adjusted accordingly
In silico enzyme modelling
The 2013 Nobel Prize in Chemistry went to Martin Karplus, Michael Levitt and Arieh Warshel for their pioneering work on computer modelling, specifically, the \u27development of multiscale models of complex chemical systems\u27 (1). This award not only recognises the critical contributions by the three laureates to the field of molecular simulations, but also underscores the broad impact that computer simulations have made in fields as diverse as chemistry, biophysics, enzymology and material sciences. This review will present an overview of computational enzymology, a rapidly maturing field where multiscale modelling plays a key role in deciphering enzymatic catalysis (2-4)
Exploration and Discussion on Rural Financial Innovation in the New Period
With the deepening of urban and rural planning, in the new period, if rural financial development wants to adapt to the development trend of society, it needs to carry out corresponding innovations to improve the rural economy and promote urban and rural construction. This paper mainly analyzes the necessity of rural financial innovation in the new period, the problems existing in rural financial development and the rural financial innovation strategy in the new period for reference
Minimizing stack and communication memory usage in real-time embedded applications
In the development of real-time embedded applications, especially those on systems-on-chip, an efficient use of RAM memory is as important as the effective scheduling of the computation resources. The protection of communication and state variables accessed by concurrent tasks must provide real-time schedulability guarantees while using the least amount of memory. Several schemes, including preemption thresholds, have been developed to improve schedulability and save stack space by selectively disabling preemption. However, the design synthesis problem is still open. In this article, we target the assignment of the scheduling parameters to minimize memory usage for systems of practical interest, including designs compliant with automotive standards. We propose algorithms either proven optimal or shown to improve on randomized optimization methods like simulated annealing.</jats:p
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