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Jack Pevenstein
Technology Partnership Office
301-975-5519
nisttech@nist.gov
100 Bureau Drive, M/S 2200
Gaithersburg, MD, 20899
The present invention is directed to an etchant/primer composition, an etchant/primer/adhesive monomer composition, kits using the same and methods using the same for improved bonding to dental structures. The etchant/primer composition comprises a compound having the formula: RN(CH2 YCO2 M)2 wherein R=R1 or R2 ; R1 =an aromatic group; R2 =a conjugated unsaturated aliphatic group; Y=a single bond, CH2, CHCH3 or C.dbd.CH2 ; and each M is independently H, an alkali metal, an alkaline earth metal, aluminum, a transition or redox metal or an alkyl group having 1 to 18 carbon atoms, with the proviso that when both M groups are alkyl groups, said compound is capable of being easily hydrolyzed, displaced, or exchanged with other reagents present in the etchant/primer composition, a polar solvent system, and nitric acid. The etchant/primer/adhesive monomer composition comprises a compound having the formula (I) as noted above, a polar solvent system, an acid selected from the group consisting of nitric acid, hydrochloric acid, citric acid, lactic acid, glycolic acid, formic acid, pyruvic acid and combinations thereof, and adhesive monomer resin, and an initiator. The above-noted compositions are applied to dental structures requiring dental restoration for improved bonding of adhesive resins and polymers to dental structures.
The present invention relates to a for a singular integral image deblurring comprising a direct procedure for classifying image smoothness and a class of fast, direct methods that recover fine-scale structure using Lipschitz (BESOV) space regularization, singular integrals, and the fast fourier transform.
The image restoration system and method of the present invention is applied to point spread functions p(x,y) which may be described in the Fourier domain as Ρ(.xi.,.eta.)=exp{-Σji=1 λi (Ξ2 +Η2)Βi }λi.gtoreq.0, 0<Βi<1, to improve noise performance and permit identification of fine detail. The novel method formulates the image restoration problem as a problem in the partial differential equations describing diffusion phenomena using a new type of a priori constraint. The restored image is obtained by minimizing a quadratic functional incorporating this new constraint. The solution of the minimization problem may be obtained directly by means of fast Fourier transform algorithms. The restoration method may be performed as a sequence of partial restorations as t↓0 wherein the partial restorations become sharper and noisier as t↓0, or as a single full restoration. The sequence of partial restorations may reveal features of the image before such features become obscured by noise and may permit adjustment of the parameters characterizing the blurring functions and constraints.