Simulation of aerated lagoon using artificial neural networks and multivariate regression techniques

The aim of this study was to develop an empirical model that provides accurate predictions of the biochemical oxygen demand of the output stream from the aerated lagoon at International Paper of Brazil, one of the major pulp and paper plants in Brazil. Predictive models were calculated from functional link neural networks (FLNNs), multiple linear regression, principal components regression, and partial least-squares regression (PLSR). Improvement in FLNN modeling capability was observed when the data were preprocessed using the PLSR technique. PLSR also proved to be a powerful linear regression technique for this problem, which presents operational data limitations.     

Interpenetrating polymer networks of poly(dimethyl siloxane–urethane) and poly(methyl methacrylate)

Simultaneous IPNs of poly(dimethyl siloxane-urethane) (PDMSU)/poly(methyl methacrylate) (PMMA) and related isomers have been prepared by using new oligomers of bis(β-hydroxyethoxymethyl)poly(dimethyl siloxane)s (PDMS diols) and new crosslinkers biuret triisocyanate (BTI) and tris(β-hydroxylethoxymethyl dimethylsiloxy) phenylsilane (Si-triol). Their phase morphology have been characterized by DSC and SEM. The SEM phase domain size is decreased by increasing crosslink density of the PDMSU network. A single phase IPN of PDMSU/PMMA can be made at an M_c = 1000 and 80 wt % of PDMSU. All of the pseudo- or semi-IPNs and blends of PDMSU and PMMA were phase separated with phase domain sizes ranging from 0.2 to several micrometers. The full IPNs of PDMSU/PMMA have better thermal resistance compared to the blends of linear PDMSU and linear PMMA. © 1993 John Wiley & Sons, Inc.     

Retention modeling and simultaneous optimization of pH value and gradient steepness in RP‐HPLC using feed‐forward neural networks

A novel approach is proposed for the simultaneous optimization of mobile phase pH and gradient steepness in RP‐HPLC using artificial neural networks. By presetting the initial and final concentration of the organic solvent, a limited number of experiments with different gradient time and pH value of mobile phase are arranged in the two‐dimensional space of mobile phase parameters. The retention behavior of each solute is modeled using an individual artificial neural network. An “early stopping” strategy is adopted to ensure the predicting capability of neural networks. The trained neural networks can be used to predict the retention time of solutes under arbitrary mobile phase conditions in the optimization region. Finally, the optimal separation conditions can be found according to a global resolution function. The effectiveness of this method is validated by optimization of separation conditions for amino acids derivatised by a new fluorescent reagent.     

Graft copolymer of polymethyl methacrylate-g-polycarbonate urethane and the fully gelled grafted networks

We have synthesized and characterized the graft copolymer of polymethyl methacrylate (PMMA)-graft-polycarbonate urethane (PCU) (designated PMMA-g-PCU) and the fully gelled mutually crosslinked network composed of both PMMA and PCU (designated as PMMA-PCU-N). Unlike the previously synthesized one phase PCU/PMMA simultaneous interpenetrating polymer networks (IPN's), both of these new materials exhibited two distinct T_g's (from DSC and DMA studies) at all compositions which we have studied. The two-phase nature of the graft and network polymer was confirmed by TEM with domain sizes smaller than those found in the blends of the linear PCU and PMMA chains. In comparison with the corresponding IPN's, the PMMA-g-PCU and the PMMA-PCU-N were thermally less stable and had a lower ultimate strength. © 1992 John Wiley & Sons, Inc.     

Total spontaneous resolution of chiral covalent networks from stereochemically labile metal complexes

Stereochemically labile copper and zinc complexes with the N,N'-dimethylethylenediamine ligand (dmeda) have been shown to be promising precursors for the total spontaneous resolution of chiral covalent networks. (N,N')-[Cu(NO3)2(dmeda)]infinity crystallises as a conglomerate and yields either enantiopure (R,R)-1 or enantiopure (S,S)-1. A mixed-valence copper(I/II) complex, [{Cu(II)Br2(dmeda)}3(Cu(I)Br)2]infinity (2), which crystallises as a pair of interpenetrating chiral (10,3)-a nets, is formed from CuBr, CuBr2 and dmeda. One net contains ligands with solely (R,R) configuration and exhibits helices with (P) configuration while the other has solely (S,S)-dmeda ligands and gives rise to a net in which the helices have (M) configuration. The whole crystalline arrangement is racemic, because the interpenetrating chiral nets are of opposite handedness. With zinc chloride (R,S)-[ZnCl(dmeda)2]2[ZnCl4] (3) is obtained, which is a network structure, although not chiral. Total spontaneous resolution of stereochemically labile metal complexes formed from achiral or racemic building blocks is suggested as a viable route for the preparation of covalent chiral networks. Once the absolute structure of the compound has been determined by X-ray crystallography, a quantitative determination of the enantiomeric excess of the bulk product can be undertaken by means of solid-state CD spectroscopy.     

Artificial neural networks for quantification in unresolved capillary electrophoresis peaks

The application of the combination of experimental design (ED) and artificial neural networks (ANNs) for the quantification of overlapped peaks in capillary zone electrophoresis is described. When the total separation cannot be achieved by separation techniques, the use of ED-ANN can be a suitable approach. The unstability of EOF causes peak shift that has to be corrected in order to apply ED-ANN methods. In this work, normalization procedure of electropherograms with consequent application of ANNs for quantification purpose was developed. Both, spectra and electropherograms can be used as multivariate data. In general, both kinds of data were found to be suitable for unresolved peaks quantification by ED-ANN approach.     

电场对含高氯酸锂盐的互穿网络高分子快离子导体的电导的影响

研究了直流电场对含ＬｉＣｌＯ４的聚氧化乙烯（ＰＥＯ）４００与环氧树脂形成的液晶态互穿网络高分子忆禽子导体的电导率的影响。在室温至９０℃范围内，电导率随外加电压增加面降低。外加电压越高，对电导率变化的影响越大。     

反应注射成型聚氨酯互穿聚合物网络研究——刚性网络对于体系形态及性能的影响

用微型反应注射成型机制备了以聚氨酯(PU)为弹性相的两类同步互穿聚合物网络(SIN),其刚性相分别采用保留仲羟基的乙烯基酯树脂(VERH)以及封闭仲羟基的乙烯基酯树脂(VERA)。用傅里叶变换红外光谱在线跟踪了这类互穿网络的生成过程,发现刚性网络抑制了PU网络中硬段有序结构的形成,两个网络间有一定程度的互穿,而两个网络间的化学键作用进一步削弱氢键强度。自旋—自旋弛豫时间的测定进一步表明网络间存在一定的互穿以及刚性相对于PU硬段结晶的抑制作用。材料的力学性能与其SIN的形态有关。VERA网络对PU表现出明显的增强作用,而由VERH网络形成的SIN则由于体系相分离进程受到严重阻碍而使材料性能恶化。     

SYNTHESIS, STRUCTURE AND PROPERTIES OF INTERPENETRATING SULFONIC ACID RESINS WITH HIGH CAPACITY

Two series of interpenetrating sulfonic acid resins (ISAR), 10×n and n×10, were prepared by means of the wet method, and the physicochemical, thermodynamic and kinetic properties of the ISAR were measured. The results show: 10×n resins exhibit better properties than n×10 ones, mainly in higher apparent degree of crosslinking and larger conformational entropy effect, among which, 10×1 resin exhibits the best thermodynamic and kinetic properties. In the DTA graphs of n×10 resins, there are two T_g and two T_(ox), but in those of 10×n, only one T_g and one T_(ox). This result well supports the conclusion that 10×n resins have much better interpenetrating structural aspects.     

Analysis of RNA sequence structure maps by exhaustive enumeration I. Neutral networks

Summary Global relations between RNA sequences and secondary structures are understood as mappings from sequence space into shape space. These mappings are investigated by exhaustive folding of allGC andAU sequences with chain lengths up to 30. The computed structural data are evaluated through exhaustive enumeration and used as an exact reference for testing analytical results derived from mathematical models and sampling based on statistical methods. Several new concepts of RNA sequence to secondary structure mappings are investigated, among them that ofneutral networks (being sets of sequences folding into the same structure). Exhaustive enumeration allows to test several previously suggested relations: the number of (minimum free energy) secondary structures as a function of the chain length as well as the frequency distribution of structures at constant chain length (commonly resulting in generalized forms ofZipf's law).

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Analyse der Beziehungen zwischen RNA-Sequenzen und Sekundärstrukturen durch vollständige Faltung, 1. Mitt. Faltung, Neutrale Netzwerke

Zusammenfassung Die globalen Benziehungen zwischen RNA-Sequenzen und Sekundärstrukturen werden als Abbildungen aus einem Raum aller Sequenzen in einen Raum aller Strukturen aufgefaßt. Diese Abbildungen werden durch Falten aller binären Sequenzen desGC-undAU-Alphabets mit Kettenlängen bis zun=30 untersucht. Die berechneten Strukturdaten werden durch vollständiges Abzählen ausgewertet und als eine exakte Referenz zum Überprüfen analytischer Resultate aus mathematischen Modellen sowie zum Testen statistisch erhobener Proben verwendet. Einige neuartige Konzepte zur Beschreibung der Beziehungen zwischen Sequenzen und Strukturen werden eingehend untersucht, unter ihnen der Begriff derneutralen Netzwerke. Ein neutrales Netzwerk besteht aus allen Sequenzen, die eine bestimmte Struktur ausbilden. Vollständiges Abzählen ermöglicht beispielsweise die Bestimmung aller Strukturen minimaler freier Energie in Abhängigkeit von der Kettenlänge ebenso wie die Bestimmung der Häufigkeitsverteilungen der Strukturen bei konstanten Kettenlängen. Die letzteren folgen einer verallgemeinerten FormZipfschen Gesetzes.