校企合作是高等职业教育改革与发展的必由之路

校企合作是高等职业教育发展的重要趋势之一,是与现代化大生产、现代科学技术和现代高等教育发展相适应的一种客观要求.加强校企合作已成为高职院校制定面向21世纪发展战略的重要内容.高校和企业联合举办高职学院是新的发展时期对校企合作认识的深化,也是高校和企业之间开展全方位和深层次合作的最佳切入点.文章所阐述的校企合作主要指在人才培养、科学研究、技术开发、生产经营以及资源综合利用等多方面的协作.     

钢筋砼压弯剪构件抗震性能试验研究

本文根据146根钢筋砼压弯剪构件的试验结果,分析了压弯剪构件在低周往复荷载作用下的破坏形态,并提出了相应于各种破坏形态的强度计算方法。建立了低周往复荷载作用下压弯剪构件的延性系数及极限转角的计算公式和防止粘结破坏的构造措施。     

Anodic oxidation of mecoprop herbicide at lead dioxide

The electrochemical oxidation of an aqueous solution containing mecoprop (2-(2-methyl-4-chlorophenoxy)propionic acid) has been studied at PbO₂ anodes by cyclic voltammetry and bulk electrolysis. The influence of current density, hydrodynamic conditions, temperature and pH on the degradation rate and current efficiency is reported. The results obtained show that the use of PbO₂ leads to total mineralization of mecoprop due to the production of oxidant hydroxyl radical electrogenerated from water discharge. The current efficiency for the electro-oxidation of mecoprop is enhanced by low current density, high recycle flow-rates and high temperature. In contrast, the pH effect was not significant. It has also been observed that mecoprop decay kinetics follows a pseudo-first-order reaction and the rate constant increases with rising current density.     

Development of calibration models for quality control in the production of ethylene/propylene copolymers by FTIR spectroscopy,multivariate statistical tools,and artificial neural networks

Principal component regression (PCR), partial least squares (PLS), StepWise ordinary least squares regression (OLS), and back‐propagation artificial neural network (BP‐ANN) are applied here for the determination of the propylene concentration of a set of 83 production samples of ethylene–propylene copolymers from their infrared spectra. The set of available samples was split into (a) a training set, for models calculation; (b) a test set, for selecting the correct number of latent variables in PCR and PLS and the end point of the training phase of BP‐ANN; (c) a production set, for evaluating the predictive ability of the models. The predictive ability of the models is thus evaluated by genuine predictions. The model obtained by StepWise OLS turned out to be the best one, both in fitting and prediction. The study of the breakdown number of samples to be included in the training set showed that at least 52 experiments are necessary to build a reliable and predictive calibration model. It can be concluded that FTIR spectroscopy and OLS can be properly employed for monitoring the synthesis or the final product of ethylene–propylene copolymers, by predicting the concentration of propylene directly along the process line. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Assessment of the final metrological characteristics of a MOEMS-based NDIR spectrometer through system modeling and data processing

A model of a miniaturized non-dispersive infrared (NDIR) gas analysis system, aiming to predict the final system specifications, is presented. It comprises the different elements of the NDIR detector, including a surface micromachined Fabry-Perot tunable filter. These models have been used to estimate the response of the NDIR system to different gas mixtures. Multivariate regression methods like partial least squares allow recovering the true sample composition from the IR absorption spectra measured with the NDIR system, despite the limited selectivity of the filter. Combining model and data processing permits to predict the effect on the final system specification of design parameters. Here, we compare the effect of the technology used for the filter on the system errors.     

Aerobic degradation by white‐rot fungi of trichloroethylene (TCE) and mixtures of TCE and perchloroethylene (PCE)

BACKGROUND: Trichloroethylene (TCE) and perchloroethylene (PCE) are considered among the most important groundwater pollutants around the world. These compounds are usually found together in polluted environments but little is known about the ability of microorganisms to simultaneously degrade TCE and PCE. RESULTS: Data showed that several species of white‐rot fungi, including Trametes versicolor, Ganoderma lucidum, and Irpex lacteus, degrade substantial levels of TCE in pure culture. T. versicolor was chosen for further study since it degraded higher levels of TCE than the other organisms. Initial glucose concentration and reoxygenation of samples increased the amount of TCE dechlorination, but no significant difference in percentage TCE degradation was observed. T. versicolor was able to degrade 34.1 and 47.7% of PCE and TCE added as mixtures (containing 5 and 10 mg L⁻¹, respectively). CONCLUSIONS: The degradation ability of TCE was extended to other species of white‐rot fungi. Percentage degradation as well as chloride release from mixtures of TCE and PCE showed that T. versicolor degrades mixtures of TCE and PCE almost as well as its ability to degrade individually added TCE or PCE. The results suggest the potential promise of T. versicolor for bioremediation of TCE and PCE in the environment. Copyright © 2008 Society of Chemical Industry     

Kinetic modelling of textural changes in ready-to-eat breakfast cereals during soaking in semi-skimmed milk

Summary Ready‐to‐eat breakfast cereals immersed in milk undergo undesirable changes in texture because of sudden moisture uptake. The textural changes are ascribable to a plasticizing effect of water, which modifies the mechanical strength of products by softening the starch/protein matrix. In this work, some textural parameters of different cereal flakes were derived from the force–displacement curves monitored during 300 s of immersion in milk. Hardness loss, deformability increment and changes in the force–displacement curve profile were calculated and plotted against soaking time. The application of a sugar coating process to a model cereal flake increased the initial product hardness and improved the preservation of the textural parameters during immersion. The Peleg model closely fitted the experimental data, with regression coefficients from 0.967 to 0.999.