Taxol promising fungal endophyte, Pestalotiopsis species isolated from Taxus cuspidata

The endophytic fungi, Pestalotiopsis versicolor and Pestalotiopsis neglecta, were isolated from the healthy leaves and bark of the Japanese Yew tree, Taxus cuspidata. The fungal species were identified by their characteristic culture morphology and molecular analysis. For the first time, the test fungi were screened for the production of taxol in modified liquid medium. The presence of taxol was confirmed by HPLC, ¹H NMR, and LC–MS methods of analysis. The maximum amount of taxol production in P. versicolor was recorded as 478 μg/l. The production rate was increased to 9560-fold than that found in the culture broth of earlier reported fungus, Taxomyces andreanae. The extracted fungal taxol showed a strong cytotoxic activity in the in vitro culture of tested human cancer cells by apoptotic assay indicating that the increase in taxol concentration induces increased cell death. A PCR-based screening for ts, a unique gene in the formation of the taxane skeleton, confirmed the molecular blueprint for taxol biosynthesis. The results designate that the fungal endophyte, P. versicolor, is an excellent candidate for an alternate source of taxol supply and can also serve as a potential species for genetic engineering to enhance the production of taxol to a higher level.     

A β-galactosidase from chick pea (Cicer arietinum) seeds: Its purification,biochemical properties and industrial applications

A β-galactosidase from Cicer arietinum seeds has been purified to apparent electrophoretic homogeneity using a combination of various fractionation and chromatographic techniques, giving a final specific activity of 220 units mg⁻¹, with approximately 1840 fold purification. Analysis of the protein by SDS–PAGE revealed two subunits with molecular masses of 48 and 38 kDa, respectively. These bands were further confirmed with LC–MS/MS, indicating that Chick pea β-galactosidase (CpGAL) is a heterodimer. Molecular mass was determined to be 85 kDa by Superose-12 FPLC column, which is in agreement with the molecular mass suggested by mass spectroscopy to be 83 kDa. The optimum pH of the enzyme was 2.8 and it hydrolysed o-nitrophenyl β-d galactopyranoside (ONPG) with a K_m value of 1.73 mM at 37 °C. The energy of activation (E_a) calculated in the range of 35 to 60 °C, using Arrhenius equation, was determined to be 11.32 kcal mol⁻¹. The enzyme could also hydrolyse lactose, with an optimum pH of 4.0 at 40 °C. K_m and E_a for lactose hydrolysis was found to be 10 mM and 10.57 kcal mol⁻¹, respectively. The enzyme was found to be comparatively thermostable showing maximum activity at 60 °C for both ONPG and lactose. Galactose was found to be the competitive inhibitor. β-Galactosidase also exhibited glycoproteineous properties when applied on Con-A Sepharose column. The enzyme was localised in germinated seeds with X-gal activity staining and shown to be expressed prominently at grown radical tip and seed coat. Sequence alignment of CpGAL with other known plant β-galactosidase showed high amino acid sequence homology.     

Steel annealing furnace robust neural network model

Abstract

In this day and age, galvanised coated steel is an essential product in several key manufacturing sectors because of its anticorrosive properties. The increase in demand has led managers to improve the different phases in their production chains. Among the efforts needed to accomplish this task, process modelling can be identified as the one with the most powerful outputs in spite of its non-trivial development. In many fields, such as industrial modelling, multilayer feedforward neural networks are often proposed as universal function approximators. These supervised neural networks are commonly trained by the traditional, back-propagation learning format, which minimises the mean squared error (mse) of the training data. However, in the presence of corrupted or extremely deviated samples (outliers), this training scheme may produce incorrect models, and it is well known that industrial data sets frequently contain outliers. The process modelled is a steel coil annealing furnace in a galvanising line, which shares characteristics with most of the furnaces used in galvanised lines all over the world. This paper reports the effectiveness of robust learning algorithms compared to the classical mse-based learning algorithm for the modelling of a real industry process. From this model an adequate line velocity (the velocity set point) for a coil, depending on its characteristics and the furnace condition to receive this coil (temperature set points), can be obtained. With this set point generation model the operator could set strategies to manage the line, i.e. set the order of the coil to be treated or preview the line's speed conditions for the transitory situations.     

Cold model study of metal droplet descent through fluids including a treatment of the non-Newtonian behaviour as exhibited by molten slag system

Abstract

In the context of several high temperature metallurgical processes including blast furnaces, a cold model study simulating a metal droplet descent through the surrounding fluid system is presented. The study comprises an experimental programme employing wide range of fluids exhibiting both Newtonian and non-Newtonian behaviour. Such fluid systems are encountered in slag–metal droplet systems where viscosity of the slag system has a significant effect on the kinetics of refining reactions. Slag systems generally possess random network structures comprising internal regions of weak ordering and the presence of these regions may result in non-Newtonian behaviour of the slag. As the viscosity of the slag is very sensitive to structure, a treatment of non-Newtonian behaviour as exhibited by some molten slag systems is therefore required. Two parameters have been identified and estimated that help to determine the rheological characteristics of fluids in relation to their network structure. The underlying principle of the model development has been that the external pressure exerts a driving force that affects the motion of the fluid to a degree dependent on the rheological behaviour and the network structure of the fluid. The paper also describes some results of a cold model study of the momentum transfer to the fluid system by correlating the drag Reynolds number with the modified drag coefficient for non-Newtonian fluids

(N*_Rem)^½?n′ = (N _Rem)^½?n′ (1/2C _Dm )^½     

Numerical analysis of isothermal flow in lower part of blast furnace considering effect of cohesive zone

Abstract

The increasing interest in minimising fuel consumption and reducing environmental problems of the ironmaking industry has led to efforts to optimise the blast furnace process. One of the undeveloped fields generated from the adoption of new operating conditions is the internal phenomenon in the lower part of the furnace following the change of cohesive zone shape. The effective liquid flow in the dripping zone of a blast furnace is important for stable operation with high iron productivity. Study of the liquid flow behaviour in a packed bed needs to investigate the effect of various operational changes in the dripping zone. As a stepping stone toward the comprehensive modelling which includes chemical reaction and its associated heat transfer, isothermal flow for three phases is simulated with the variation of the shape of cohesive zone to see the effect of charging condition.     

Scrap melting in continuous process rotary melting furnace Part 1 – Bench scale furnace trials

Abstract

A heat transfer model was developed for scrap melting in an oxyfuel fired continuous process rotary melting furnace (CPRMF), which was envisioned as a replacement for the electric arc furnace in minimill steelmaking. The results are presented in a two part series. This first paper describes the bench scale CPRMF, the experimental procedure, and the operational results which will be used to validate the model. Two groups of copper melting trials were performed to explore aspects of furnace operation such as oxygen enrichment and slag thickness. The experimental results indicated that furnace thermal efficiency was significantly improved by moving from 37 to 80% oxygen in the combustion air and, extrapolating the results, would be ～30% for oxy fuel firing. With the constant oxygen level of 53%, the introduction of a slag layer significantly lowered the efficiency from 22 to 18% for 1·3 cm slag and 12% for 2·5 cm slag.     

Adaptive BLAST-type decision-feedback equalizers for DS-CDMA systems

In this paper, we propose two new adaptive equalization algorithms for direct sequence code division multiple access (DS-CDMA) systems operating over time-varying and frequency selective channels. The equalization schemes consist of a number of serially connected stages and detect users in an ordered manner, applying a decision feedback equalizer (DFE) at each stage. Both the equalizer filters and the order in which the users are extracted are updated in a recursive least squares (RLS) manner, efficiently realized through time- and order-update recursions. V-BLAST detection ordering is implemented, that is, the stronger signal is extracted first so that the weaker users can be more easily detected. The spreading codes are unavailable at the receiver of the first scheme, whereas the second algorithm employs the RAKE receiver concept, incorporating knowledge of the spreading sequences to offer performance improvement. The bit error rate (BER) performance of the equalizers is evaluated via simulations, in both mild and severe near-far environments. Their superiority over existing techniques is demonstrated.     

Effect of manganese ore blends on performance of submerged arc furnace for ferromanganese production

Abstract

Manganese ore blends are used in ferromanganese production. The blend composition controls the operational performance of submerged arc furnace. A case study has been carried out at FAP, Joda, Tata Steel to better understand the process. The results of experiments revealed that the phase decomposition and decrepitation of Mn ore at low temperatures (500–900°C) in the upper part of the furnace increased the furnace top temperature and thereby promoted agglomeration of the charge, which caused the violent eruptions in the furnace. The root cause of the problems in reaction zone (bottom part) of the furnace was changes in the composition of slag, i.e. low silica and high alumina, which was also due to selection of Mn ores in the blends. Various options for silica addition were examined and compared. The pretreatment of the Mn ores and use of synthetic slag for silica adjustment options were identified to overcome the operating problems and to utilise the captive Mn ores.     

Hatfield Memorial Lecture 2007 Railways and materials: synergetic progress

Abstract

Railways were originally uniquely identified with the material of their initial construction and now are technically identified by the characteristic contact of 'steel wheel on steel rail'. Over 160 years ago failures of iron railway axles led to research into what we now know as metal fatigue. Accidents throughout the ages have acted as catalysts for research and improvements: this lecture will identify some key incidents. The change from iron to steel, following Bessemer's discovery of a method of bulk production and its implementation in Sheffield, resulted in fewer materials failures and enabled greater loads to be carried at greater speeds. Today's railways rely on a wide variety of materials from all the major classes of materials. The requirements of cost, weight, reliability, crashworthiness, maintainability and inspection are often in conflict as the service loadings imposed by the modern railway on materials have become more severe. It is not therefore surprising that despite our advances in knowledge and capabilities, costly failures still occasionally occur. Nevertheless, railways have benefited from, and contributed to, advances in material engineering way beyond the initial emphasis on iron.     

Bottom design optimisation of electric arc furnace for ferromanganese production using nodal wear model

Abstract

This paper presents the optimisation on the design of the lining of an electric arc furnace that produces refined ferromanganese by applying the nodal wear model. This model is a new tool that systematises the wear/corrosion analysis applied to industrial furnaces linking the basic theoretical knowledge of the physical chemistry of wear/corrosion phenomena and the industrial conditions. The use of this tool to optimise the process helped increase the number of tappings between furnace bottom rebuilds from 19 in 1999 to 1200 in 2005 and the productivity to increase from 1·2 to 2·7 ton h^–1.