Photocatalytic oxidation of low concentration 2,4-D solution with new TiO2 fiber catalyst in a continuous flow reactor.

Environmental pollution by low concentrations of 2,4-Dichlorophenoxyacetic acid (2,4-D) is a concern these days due to ever increasingly stringent regulations. Photocatalysis with immobilized TiO2 fiber is a promising oxidation method. Laboratory experiments on photocatalytic degradation of 0.045 mmol l(-1) 2,4-D with the world's first high-strength TiO2 fiber catalyst were carried out in a continuous flow reactor in which the degradations were, in general, similar to those with high 2,4-D concentrations investigated elsewhere. Degradation and mineralization of 2,4-D were significantly enhanced with no initial pH adjustments. The rate constants for total organic carbon (TOC) without pH adjustment were about two-fold bigger than the pH adjustment cases. CO2 gas measurement and carbon mass-balance were carried out for the first time, where about 34% organic carbon converted into CO2 gas during four-hour oxidation. 2,4-Dichlorophenol (2,4-DCP), phenol, benzyl alcohol and two unknowns (RT = 2.65 and 3.78 min.) were detected as aromatic intermediates while Phenol was the new aromatic in HPLC analysis. Dechlorination efficiencies were high (> 70%) in all the cases, and more than 90% efficiencies were observed in chloride mass balance. Bigger flow rates and solution temperature fixed at 20 degrees C without pH adjustment greatly enhanced 2,4-D mineralization. These results can be an important basis in applying the treatment method for dioxin-contaminated water and wastewater.     

Catalytic aminolysis of epoxide by alumina prepared from amine-protected Al precursor

The catalytic activities of alumina prepared from an Al alkoxide-amine adduct monomer for the reaction of cyclopentene oxide with piperidine was determined after various pretreatments, including calcination and exposure to moisture. They were compared with the activity of alumina prepared by the conventional hydrolysis method. It was found that the as-prepared sample from the alkoxide-amine monomer preparation was five times more active than a conventional preparation, suggesting that it has a higher density of surface Lewis acid sites. However, its activity was much more severely suppressed by exposure to moisture.     

Kinetic Characteristics of Amino Acid Salt Crystallization in Methanol‐Water System

Nucleation and growth mechanisms and kinetics of crystals of an amino acid salt were investigated in a methanol‐water system by measuring and evaluating the induction time as a function of the supersaturation ratio and temperature in batch salting out crystallization experiments. Discrimination between the possible crystallization mechanisms, and estimation of the kinetic parameters were carried out using nonlinear parameter identification. The results concerning the growth mechanism obtained were checked additionally by measuring the induction time as a function of number density of seed crystals.     

Stability analysis of a feedback-controlled resonant DC-DC converter

This paper reports on the stability analysis of one member of a dual-channel resonant DC-DC converter family. The study is confined to the buck configuration in symmetrical operation. The output voltage of the converter is controlled by a closed loop applying constant-frequency pulsewidth modulation. The dynamic analysis reveals that a bifurcation cascade develops as a result of increasing the loop gain. The trajectory of the variable-structure piecewise-linear nonlinear system pierces through the Poincare plane at the fixed point in state space when the loop gain is small. For stability criterion the positions of the characteristic multipliers of the Jacobian matrix belonging to the Poincare map function defined around the fixed point located in the Poincare plane is applied. In addition to the stability analysis, a bifurcation diagram is developed showing the four possible states of the feedback loop: the periodic, the quasi-periodic, the subharmonic, and the chaotic states. Simulation and test results verify the theory.     

Small–Capacity Modular Units. Experience in Startup and Management

A series of small–capacity units has recently been constructed in regions of oil field development and crude oil and gas condensate production to satisfy the requirements for such petroleum products as naphtha, diesel fuel, kerosene, and boiler fuel and to reduce costs for delivery of these products. There are almost no data in the technical literature, particularly in periodicals, on the construction and operation of small–capacity units. We attempt to generalize the experience of Orgeneftekhimzavody Trust in this area. We hope that this experience will be useful to specialists in the development and management of small–capacity plants.     

Comparison of total and faecal coliforms as faecal indicator in eutrophicated surface water.

The aim of this study was to evaluate the use of total coliforms (TC) and faecal coliforms (FC) using a membrane filtration method for precise monitoring of faecal pollution in Korean surface water. The samples were collected in Korea from both main rivers and their tributaries. Presumptive TC * FC were enumerated. The ratios of presumptive FC to TC were not constant, but varied widely, and TC were difficult to enumerate because of overgrowth by background colonies. For FC this was not the case. Seven hundred and three purified strains of presumptive TC * FC and their background colonies were biotyped using API 20E. Among 272 presumptive TC, non-faecal related species, Aeromonas hydrophila dominated (34.6%) and E. coli accounted for only 5.1%. In contrast, E. coli made up 89% of the 209 presumptive FC. Furthermore, of 164 background colonies on Endo Agar LES, 54.9% was A. hydrophila, while background colonies on m-FC Agar were few (58 strains), and despite their atypical colony appearance, most of them were biotyped as enteric bacteria. These results reveal that the detection of FC rather than TC using m-FC Agar is more appropriate for faecal pollution monitoring in eutrophicated surface water located in a temperate region.     

Self-reflective segmentation of human bodily motions using recurrent neural networks

For realizing a naturalistic collaboration between the human and the robot, we have to establish the intention sharing from the series of motion data that are observed and exchanged between the human and the machine. In a word, this is a problem to detect "meanings" out of the digitized data stream. In this paper, we propose a novel approach based on semiosis, and present a method of interpreting bodily motions using recurrent neural networks called Elman networks. We made some experiments using the raw data acquired while a human performs a simple task of fetching objects by stretching and folding his/her arm, and demonstrate that the network can learn invariant features of the generalized motion concepts, classify the motion by referring to self-organized memory structure, and understand a task structure of the observed human bodily motion. These capabilities are essential for machine intelligence to establishing the human-robot shared autonomy, a new style of human-machine collaboration proposed in the area of robotics.     

Training and optimization of an artificial neural network controlling a hybrid power filter

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimizing its total cost. An artificial neural network (ANN) is used to control the HPC amidst a very dynamic power system environment. The performance of a reference ANN is evaluated while controlling an HPC connected to a typical nonlinear industrial load. The training and performance of the ANN is then optimized in terms of training set size, training set packing and ANN topology and the performance compared to the reference ANN. This paper highlights the importance of optimising the mentioned ANN parameters to achieve optimum ANN training and modeling accuracy. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately.