Multi-site phase transfer catalyst assisted radical polymerisation of glycidyl methacrylate using potassium peroxydisulphate as initiator – a kinetic study

In this work, the kinetics and mechanism of free-radical polymerisation of glycidyl methacrylate (GMA) using potassium peroxydisulphate (PDS) as water soluble initiator in the presence of synthesized 1, 4-Bis (tributyl methyl ammonium) benzene dichloride (TBMABDC) as multi-site phase transfer catalyst (MPTC) was studied. The polymerisation reactions were carried out under inert and unstirred conditions at constant temperature of 60 ± 1°C in cyclohexane/water biphase media. The role of concentrations of monomer, initiator, catalyst and volume fraction of aqueous phase, solvent polarity and temperature on the rate of polymerisation (Rp) was ascertained. The order with respect to monomer and initiator was found to be unity. The order with respect to catalyst was found to be 0.51. The rate of polymerisation is independent of ionic strength and pH of the medium. However, an increase in the polarity of solvent has slightly increased the Rp value. Based on the results obtained, a suitable kinetic scheme has been proposed to account for the experimental observations and its significance discussed.     

Research on Marine Boiler＇s Pressurized Combustion and Heat Transfer

The effect of pressure on combustion and heat transfer is analyzed. The research is based on the basic combustion and heat transfer theorem. A correction for the heat calculation method for pressurized furnace is made on the basis of the normal pressure case. The correction takes the effect of pressurizing into account. The results show that the correction is reasonable and the method is applicable to combustion and heat transfer of the marine supercharged boiler.     

Softwarekartographie

Zusammenfassung  Anwendungslandschaften in Unternehmen sind langlebige hoch-komplexe Strukturen bestehend aus hunderten bis tausenden von miteinander vernetzten betrieblichen Informationssystemen, die von Personen mit sehr unterschiedlichen Interessen und Erfahrungshintergrund konzipiert, erstellt, modifiziert, betrieben, genutzt und finanziert werden. Die Softwarekartographie zielt darauf ab, die Kommunikation zwischen diesen Personen durch zielgruppenspezifische verst?ndliche graphische Visualisierungen zu unterstützen, die Gesch?fts- und Informatik-Aspekte gleicherma?en berücksichtigen, und die speziell für langfristige und strategische Management-Betrachtungen geeignet sind. In diesem Beitrag fassen wir zun?chst die in der betrieblichen Praxis wohlbekannten Probleme beim Management von Anwendungslandschaften zusammen und diagnostizieren erhebliche Kommunikationsdefizite. Da Anwendungslandschaften als Systeme von Systemen mit Menschen als integrale Systembestandteile zu verstehen sind, werden Karten als attraktiver L?sungsansatz identifiziert und die wesentlichen Konzepte der Softwarekartographie anhand von Beispielen vorgestellt. Dabei werden Querbezüge zu anderen Fachgebieten der Informatik und Wirtschaftsinformatik hergestellt, und die bisherige Nutzung der Forschungsergebnisse in der Praxis gezeigt.     

镁钴铝类水滑石催化合成安息香甲醚

采用共沉淀法制备了镁钴铝类水滑石化合物(MgCoAl-HTLcs),并用 X 射线衍射、扫描电子显微镜、NH_3程序升温脱附等方法对 MgCoAl-HTLcs 进行了表征,并以 MgCoAl-HTLcs 为催化剂催化苯甲醛与甲醇反应合成安息香甲醚,研究了n(Mg):n(Co):n(Al)、催化剂用量、原料配比、反应温度、反应时间对合成反应的影响。表征结果显示,MgCoAl-HTLcs 的晶相完整,表面主要为弱酸、弱碱性。催化合成安息香甲醚的适宜条件为:MgCoAl-HTLcs 催化剂用量0.10 g(约为原料总质量的0.23%),n(Mg):n(Co):n(Al)=0.4:1.6:1.0,V(苯甲醛):V(甲醇)=3:50,反应温度50℃,反应时间150 min。在此条件下,苯甲醛的平衡转化率达77.49%,安息香甲醚选择性接近100%。为洁净合成安息香甲醚开辟了一条新的途径。     

Recrystallization of phenylbutazone using supercritical fluid antisolvent process

Phenylbutazone was recrystallized from its solutions by using a supercritical fluid antisolvent process. It was dissolved in acetone and supercritical carbon dioxide was injected into the solution, thereby inducing supersaturation and particle formation. Variation in the physical properties of the recrystallized phenylbutazone was investigated as a function of the crystallizing temperature and the carbon dioxide injection rate. The recrystallized particles showed cleaner surfaces and more ordered morphology compared to the particles obtained by other methods such as solvent evaporation. X-ray diffraction patterns indicated that the crystallinity of the particles had been modified upon the recrystallization. Differential scanning calorimetry measurement revealed that the crystallizing temperature influenced the thermal stability of the resulting crystals. Larger crystals were produced when the carbon dioxide injection rate was reduced.     

B737机务CBT系统建设方案的探讨

通过对AICC制订的CBT课件开发规范的探讨，阐述了CBT的基本概念和波音737飞机机务CBT的开发制作过程，以及利用Authorware开发软件制作多媒体课件的技术难点。     

A Tutorial on GrÖbner Bases With Applications in Signals and Systems

This paper is a tutorial on GrÖbner bases and a survey on the applications of GrÖbner bases in the broad field of signals and systems. A reasonably detailed review is given of several fundamental theoretical issues that occur in the use of GrÖbner bases in multidimensional signals and systems applications. These topics include the primeness of multivariate polynomial matrices, multivariate unimodular polynomial matrix completion, and prime factorization of multivariate polynomial matrices. A brief review is also presented on the wide-ranging applications of GrÖbner bases in multidimensional as well as one-dimensional circuits, networks, control, coding, signals, and systems and other related areas like robotics and applied mechanics. The impact and scope of GrÖbner bases in signals and systems are highlighted with respect to what has already been accomplished as a stepping stone to expanding future research.      

Photochemical reduction of molecular weight and number of double bonds in natural rubber film

Natural rubber (NR) can be degraded depending on various factors such as heat, mechanical force, chemical reaction, and light. Light is a very interesting factor because it can cause the NR to degrade under low temperature and pressure. The photo-degradation of NR films was carried out to investigate the effects of the light and the temperature on the reduction of the weight-average molecular weight (Mw) and the double bonds in the NR films. The NR films, with and without catalysts, titanium dioxide (TiO₂), and potassium persulfate (K₂S₂O₈), were exposed to light from a mercury light bulb at 7,000 and 36,000 lux, and at the temperature of 25 °C and 80 °C for 192 hrs. After exposure, the Mw of the NR films was analyzed by gel permeation chromatography (GPC). Changes in the Mw were used to construct a kinetic model for the process, (1/Mw)=(1/Mw₀)+(kt/2M₀) where k is the rate constant, and M₀ is the Mw of the monomer unit. The linear relationship between 1/Mw and time suggested pseudo first-order processes with random scission. The Mw distribution information from the GPC was used to calculate the number of double bonds in the NR films. The trend of the double bonds reduction curves was quite similar to the result obtained from the calculation from the FTIR spectra. This indicated that this calculation method might possibly be another alternative way to obtain the number of double bonds in the NR.     

Power Distribution Fault Cause Identification With Imbalanced Data Using the Data Mining-Based Fuzzy Classification E-Algorithm

Power distribution systems have been significantly affected by many outage-causing events. Good fault cause identification can help expedite the restoration procedure and improve the system reliability. However, the data imbalance issue in many real-world data sets often degrades the fault cause identification performance. In this paper, the E-algorithm, which is extended from the fuzzy classification algorithm by Ishibuchi to alleviate the effect of imbalanced data constitution, is applied to Duke Energy outage data for distribution fault cause identification. Three major outage causes (tree, animal, and lightning) are used as prototypes. The performance of E-algorithm on real-world imbalanced data is compared with artificial neural network. The results show that the E-algorithm can greatly improve the performance when the data are imbalanced     

Self-adjusting the intensity of assortative mating in genetic algorithms

Mate selection plays a crucial role in both natural and artificial systems. While traditional Evolutionary Algorithms (EA) usually engage in random mating strategies, that is, mating chance is independent of genotypic or phenotypic distance between individuals, in natural systems non-random mating is common, which means that somehow this mechanism has been favored during the evolutionary process. In non-random mating, the individuals mate according to their parenthood or likeness. Previous studies indicate that negative assortative mating (AM)—also known as dissortative mating—, which is a specific type of non-random mating, may improve EAs performance by maintaining the genetic diversity of the population at a higher level during the search process. In this paper we present the Variable Dissortative Mating Genetic Algorithm (VDMGA). The algorithm holds a mechanism that varies the GA’s mating restrictions during the run by means of simple rule based on the number of chromosomes created in each generation and indirectly influenced by the genetic diversity of the population. We compare VDMGA not only with traditional Genetic Algorithms (GA) but also with two preceding non-random mating EAs: the CHC algorithm and the negative Assortative Mating Genetic Algorithm (nAMGA). We intend to study the effects of the different methods in the performance of GAs and verify the reliability of the proposed algorithm when facing an heterogeneous set of landscapes. In addition, we include the positive Assortative Mating Genetic Algorithm (pAMGA) in the experiments in order test both negative and positive AM mechanisms, and try to understand if and when negative AM (or DM) speeds up the search process or enables the GAs to escape local optima traps. For these purposes, an extensive set of optimization test problems was chosen to cover a variety of search landscapes with different characteristics. Our results confirm that negative AM is effective in leading EAs out of local optima traps, and show that the proposed VDMGA is at least as efficient as nAMGA when applied to the range of our problems, being more efficient in very hard functions were traditional GAs usually fail to escape local optima. Also, scalability tests have been made that show VDMGA ability to decrease optimal population size, thus reducing the amount of evaluations needed to attain global optima. We like to stress that only two parameters need to be hand-tuned in VDMGA, thus reducing the tuning effort present in traditional GAs and nAMGA.