Extraction of penicillin G from simulated media by an emulsion liquid membrane process

The extraction of penicillin G from simulated media was performed by water/oil/water (w/o/w) emulsion liquid membranes (ELMs) and studied under various operational conditions in a batch system. The degree of extraction achieved was between 80% and 95% under specific conditions. A concentration of greater than nine times the initial concentration of penicillin G in the external phase was obtained in the internal phase. The pH of the internal aqueous solution, containing a basic salt, was theoretically calculated on the basis of the amount of penicillin G transported into the internal phase. The calculated results agreed with the experimental data well and were used to select a suitable type and concentration of a basic salt in the internal phase to give a pH within the range 5 to 8 where penicillin G was stable after the termination of extraction. The extraction of penicillin G was successfully performed by the ELM process with sodium carbonate in the internal phase.     

α-Fe_2O_3(SO_4~(2-),Sn)气敏电阻的温度响应特性

在气敏温度区域内研究了α-Fe_2O_3(SO_4~(2-),Sn)材料的电阻-温度特性,认为表面结构的变化导致温度特性出现峰值并呈现气敏性。可利用空气中电阻温度特性提供的信息改性或发现新的气敏材料。     

Purification and renaturation of recombinant human lymphotoxin (tumour necrosis factor beta) expressed in Escherichia coli as inclusion bodies

High level expression of recombinant human tumour necrosis factor β (rh TNF-β) in Escherichia coli results in the formation of two portions of protein, namely soluble active protein and insoluble protein which is inactive and aggregates in the form of inclusion bodies (IBs). In this study, a procedure for purification and renaturation of rh TNF-β from inclusion bodies has been designed and verified experimentally with a product purity of more than 90% and a recovery of about 30%. The procedure includes washing of IBs with specific wash buffer (Triton X-100/EDTA/lysozyme/PMSF), their solubilization with 8 mol dm^?3 alkaline urea, purification with ion-exchange columns, refolding with renaturation buffer and finally concentration and desalination with an ultrafiltration membrane. The characteristics of the renatured protein were identical with those of purified protein from the soluble fraction as demonstrated by (1) SDS-PAGE, (2) cytotoxic activity on mouse L929 cells, (3) N-terminal amino acid sequence, and (4) gel filtration chromatography.     

Shortest path algorithms: A computational study with the C programming language

The main purpose of this study is to evaluate the computational efficiency of algorithms for calculating shortest paths when they are correctly coded by using the C programming language. The eight algorithms that we selected for this experiment are the most efficient, either measured in terms of worst-case bounds or marked as such from previous computational studies; they include the redistributive heap algorithm. We suggest computer implementations that use the full power of C. In particular, the network representation and the various data structures used to keep the scan eligible list may be managed by using only additions and no multiplications, while it is not possible with FORTRAN. These capabilities, unique to C, yield several interesting conclusions: one may expect to speed up a shortest path algorithm by a factor of 20%; in some cases, this factor may reach 30%. Interestingly, the level of programming difficulty required to achieve these benefits is not greater than that required by implementations using arrays.     

Efficient particle filter-based processing algorithm for clutter suppression and IR point targets enhancement

A novel soft decision-based median subtraction filter is presented for clutter suppression and infrared (IR) point targets enhancement. The decision is made based on a jump Markov model and its state and parameter estimation using a particle filter. The scheme is compared with other conventional clutter background removal techniques and good results are obtained.     

Application of artificial neural networks to the analysis of two‐dimensional fluorescence spectra in recombinant E coli fermentation processes

A two‐dimensional (2D) spectrofluorometer was used to monitor various fermentation processes with recombinant E coli for the production of 5‐aminolevulinic acid (ALA). The whole fluorescence spectral data obtained during a process were analyzed using artificial neural networks, ie self‐organizing map (SOM) and feedforward backpropagation neural network (BPNN). The SOM‐based classification of the whole spectral data has made it possible to qualitatively associate some process parameters with the normalized weights and variances, and to select some useful combinations of excitation and emission wavelengths. Based on the classified fluorescence spectra a supervised BPNN algorithm was used to predict some of the process parameters. It was also shown that the BPNN models could elucidate some sections of the process's performance, eg forecasting the process's performance. Copyright © 2005 Society of Chemical Industry