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The goal of this letter is to report a novel class of dynamical behaviors observed from a generalized cellular automata CNN [Chua, 1998] with piecewise-linear (PWL) cells. Starting from an almost homogeneous initial condition, self-making (autopoietic in the sense of [Varela et al., 1974]) patterns, reminiscent of simple living systems, emerge as a result of the nonlinear coupling among cells. Similar to patterns of organization characterizing living systems, our patterns display features such as growth, maturity and death. The discovery of such patterns was made possible via mutations in several piecewise-linear CNN cell realizations of the "Game of Life" [Conway, 1982].
Abstract A new photocrosslinkable polymer designed for application in second harmonic generation has been prepared and tested for frequency doubling of IR lasers. The polymer is based on a colorless polyurethane with pendant tolane nonlinear optical chromophores that carry a polymerizable styrene moiety at their extremities. Photocrosslinking is achieved by irradiation of films containing a small amount of a bleachable radical photoinitiator. The effect of photoinduced radical crosslinking on the mobility of the chromophores has been studied by recording the intensity of the frequency doubled light, generated by a poled sample, with increasing temperature. As expected, photocrosslinking leads to NLO materials with highly stable chromophore orientation.
Abstract are studied under high‐pressure (20 atm) reaction conditions.
The syntheses of sila- and disilabenzene complexes of "Cp*Ru" (Cp* = C5Me5) are described. Li[C5H5SiH(tBu)] reacted with [Cp*RuCl]4 to give the neutral silacyclohexadienyl complex Cp*Ru[η5-C5H5SiH(tBu)] (2), characterized by NMR spectroscopy. Reaction of 2 with the Lewis acid B(C6F5)3 gave the product of Si−H abstraction, [Cp*Ru(η6-C5H5SitBu)][BH(C6F5)3] (3). Complex 3 represents the first example of an isolated silabenzene complex. The characterization of 3 follows from 1H, 13C, 29Si, 19F, and 11B NMR and IR spectroscopies. Finally, trans-1,4-dihydrohexamethyl-1,4-disilacyclohexa-2,5-diene reacted with Cp'(PMe3)2RuCH2SiMe3 (Cp' = C5Me4Et) to give Cp'(PMe3)RuH(η2-hexamethyl-1,4-disilabenzene) (4), whose structure (by X-ray crystallography) may be described as a metallodisilanorbornadiene.
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
We use the Cellular Neural Network (CNN) to study the pattern formation properties of large scale spatially distributed systems. We have found that the Cellular Neural Network can produce patterns similar to those found in Ising spin glass systems, discrete bistable systems, and the reaction-diffusion system. A thorough analysis of a 1-D CNN whose cells are coupled to immediate neighbors allows us to completely characterize the patterns that can exist as stable equilibria, and to measure their complexity thanks to an entropy function. In the 2-D case, we do not restrict the symmetric coupling between cells to be with immediate neighbors only or to have a special diffusive form. When larger neighborhoods and generalized diffusion coupling are allowed, it is found that some new and unique patterns can be formed that do not fit the standard ferro-antiferromagnetic paradigms. We have begun to develop a theoretical generalization of these paradigms which can be used to predict the pattern formation properties of given templates. We give many examples. It is our opinion that the Cellular Neural Network model provides a method to control the critical instabilities needed for pattern formation without obfuscating parameterizations, complex nonlinearities, or high-order cell states, and which will allow a general and convenient investigation of the essence of the pattern formation properties of these systems.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
We investigate the importance of parts for the tasks of action and attribute classification. We develop a part-based approach by leveraging convolutional network features inspired by recent advances in computer vision. Our part detectors are a deep version of poselets and capture parts of the human body under a distinct set of poses. For the tasks of action and attribute classification, we train holistic convolutional neural networks and show that adding parts leads to top-performing results for both tasks. We observe that for deeper networks parts are less significant. In addition, we demonstrate the effectiveness of our approach when we replace an oracle person detector, as is the default in the current evaluation protocol for both tasks, with a state-of-the-art person detection system.
Vibrations and Stability of Thin Structures: Eliza Haseganu's Analysis of Wrinkling in Pressurized Membranes (D J Steigmann) Buckling, Vibrations and Optimal Design of Ring-Stiffened Thin Cylindrical Shells (S B Filippov) Asymptotic Analysis of Thin Shell Buckling (A L Smirnov) Thin-Wall Structures Made of Materials with Variable Elastic Moduli (A L Smirnov & P E Tovstik) Asymptotic Integration of Free Vibration Equations of Cylindrical Shells by Symbolic Computation (E M Haseganu et al.) Vibrations and Stability in Continuum Mechanics: The Mechanics of Pre-Stressed and Pre-Polarized Piezoelectric Crystals (E Baesu) On the Stability of Transient Viscous Flow in an Annulus (A A Kolyshkin et al.) Biomechanics: Mechanical Models of the Development of Glaucoma (S M Bauer) A Micromechanical Model for Predicting Microcracking Induced Material Degradation in Human Cortical Bone Tissue (O Akkus et al.) Experimental and Computational Mechanics of Solids: An Evolution of Solid Elements for Thermal-Mechanical Finite Element Analysis (J Moyra & J McDill) Quantization Effects in Shallow Powder Bed Vibrations (J Pegna & J Zhu).
Abstract A brief historical perspective relating the discovery of dendrimers and other dendritic polymers is presented. Dendritic polymers are recognized as the fourth major class of macromolecular architecture consisting of four sub‐ classes, namely, (1) random hyperbranched, (2) dendrigrafts, (3) dendrons, and (4) dendrimers. The previous literature is reviewed with anecdotal events leading to implications for dendrimers in the emerging science of nanotechnology. © 2002 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 40: 2719–2728, 2002