SUPERLINEAR ELLIPTIC PROBLEMS WITH SIGN CHANGING COEFFICIENTS

Via variational methods, we study multiplicity of solutions for the problem {-Delta u = lambda b(x)vertical bar u vertical bar(q-2)u + au + g(x, u) in Omega, u - 0 on partial derivative Omega, where a simple example for g( x, u) is |u|(p-2)u; here a, lambda are real parameters, 1 < q < 2 < p <= 2* and b(x) is a function in a suitable space L-sigma. We obtain a class of sign changing coefficients b(x) for which two non-negative solutions exist for any lambda > 0, and a total of five nontrivial solutions are obtained when lambda is small and a >= lambda(1). Note that this type of results are valid even in the critical case.

Liquid-Liquid Equilibrium Data for the System Lard plus Oleic Acid plus Ethanol + Water at 318.2 K: Cholesterol Distribution Coefficients

This research reports liquid liquid equilibrium data for the system lard (swine fat), cis-9-octadecenoic acid (oleic acid), ethanol, and water at 318.2 K, as well as their correlation with the nonrandom two-liquid (NRTL) and universal quasichemical activity coefficient (UNIQUAC) thermodynamic equations, which have provided global deviations of 0.41 % and 0.53 %, respectively. Additional equilibrium experiments were also performed to obtain cholesterol partition (or distribution) coefficients to verify the availability of the use of ethanol plus water to reduce the cholesterol content in lard. The partition experiments were performed with concentrations of free fatty acids (commercial oleic acid) that varied from (0 to 20) mass % and of water in the solvent that varied from (0 to 18) mass %. The percentage of free fatty acids initially present in lard had a slight effect on the distribution of cholesterol between the phases. Furthermore, the distribution coefficients decreased by adding water in the ethanol; specifically, it resulted in a diminution of the capability of the solvent to remove the cholesterol.

Pattern formation for a reaction-diffusion system: Catalytic-dependent diffusion coefficients

[ES]Se considera un modelo de reacción-difusión para dos reactantes en presencia de un tercero, que actúa de catalizador. La escala temporal para el catalizador se compara con la de los reactantes y los coeficientes de difusión dependen solamente de la concentración en el estado de equilibrio del catalizador. Se realizan experimentos para diferentes cinéticas

On the identification of bridge decks aeroelastic coefficients: the covariance block hankel matrix method

Il seguente elaborato si concentra sull'identifi�cazione strutturale di sistemi soggetti a sollecitazioni aeroelastiche e nello speci�fico l'attenzione viene rivolta ad impalcati da ponte. Si analizzano i concetti principali caratterizzanti il campo dell'aeroelasticità indagando i fattori dominanti che entrano in gioco sul piano teorico. In seguito, si considera il metodo di identifi�cazione strutturale chiamato Covariance Block Hankel Matrix (CBHM) utilizzato come strumento di derivazione dei coeffi�cienti aeroelastici propri della struttura. Infi�ne, si indaga il comportamento di questo metodo di identi�ficazione al variare di una serie di parametri chiave e all'interno di diversi scenari, visionando risultati ottenuti tramite una serie di test eff�ettuati per provare l'a�dattabilità del metodo stesso al variare delle condizioni che caratterizzano il sistema.

Plotting regression coefficients and other estimates in Stata

Graphical presentation of regression results has become increasingly popular in the scientific literature, as graphs are much easier to read than tables in many cases. In Stata such plots can be produced by the -marginsplot- command. However, while -marginsplot- is very versatile and flexible, it has two major limitations: it can only process results left behind by -margins- and it can only handle one set of results at the time. In this article I introduce a new command called -coefplot- that overcomes these limitations. It plots results from any estimation command and combines results from several models into a single graph. The default behavior of -coefplot- is to plot markers for coefficients and horizontal spikes for confidence intervals. However, -coefplot- can also produce various other types of graphs. The capabilities of -coefplot- are illustrated in this article using a series of examples.

COEFPLOT: Stata module to plot regression coefficients and other results

coefplot plots results from estimation commands or Stata matrices. Results from multiple models or matrices can be combined in a single graph. The default behavior of coefplot is to draw markers for coefficients and horizontal spikes for confidence intervals. However, coefplot can also produce various other types of graphs.

Plotting regression coefficients and other estimates

Graphical display of regression results has become increasingly popular in presentations and in scientific literature because graphs are often much easier to read than tables. Such plots can be produced in Stata by the marginsplot command (see [R] marginsplot). However, while marginsplot is versatile and flexible, it has two major limitations: it can only process results left behind by margins (see [R] margins), and it can handle only one set of results at a time. In this article, I introduce a new command called coefplot that overcomes these limitations. It plots results from any estimation command and combines results from several models into one graph. The default behavior of coefplot is to plot markers for coefficients and horizontal spikes for confidence intervals. However, coefplot can also produce other types of graphs. I illustrate the capabilities of coefplot by using a series of examples.