“四合”成就清史专家阎崇年

他因中央电视台《百家讲坛》之“清十二帝疑案”节目的热播，红遍大江南北，他在研究历史五十多年间、熟读儒家经典，悟出建树业绩的密笈。

Is platinum-loaded titania the best material for dye-sensitized hydrogen evolution under visible light?

A dye-sensitized photocatalyst combining Pt-loaded TiO_(2) and Ru(Ⅱ)tris-diimine sensitizer(RuP)was constructed and its activity for photochemical hydrogen evolution was compared with that of Pt-intercalated HCa_(2)Nb_(3)O_(10) nanosheets.When the sacrificial donor ethylenediaminetetraacetic acid(EDTA)disodium salt dihydrate was used,RuP/Pt/TiO_(2) showed higher activity than RuP/Pt/HCa_(2)Nb_(3)O_(10).In contrast,when NaI(a reversible electron donor)was used,RuP/Pt/TiO_(2) showed little activity due to back electron transfer to the electron acceptor(I_(3)-),which was gener-ated as the oxidation product of I-.By modification with anionic polymers(sodium poly(styrenesulfonate)or sodium polymethacrylate)that could inhibit the scavenging of conduction band electrons by I_(3)-,the H_(2) production activity from aqueous NaI was improved,but it did not exceed that of RuP/Pt/HCa_(2)Nb_(3)O_(10).Transient absorption measurements showed that the rate of semiconductor-to-dye back electron transfer was slower in the case of TiO_(2) than HCa_(2)Nb_(3)O_(10),but the electron transfer reaction to I3-was much faster.These results indicate that Pt/TiO_(2) is useful for reactions with sacrificial reductants(e.g.,EDTA),where the back electron transfer reaction to the more reducible product can be neglected.However,more careful design of the catalyst will be nec-essary when a reversible electron donor is employed.

Simultaneous Identification of Thermophysical Properties of Semitransparent Media Using a Hybrid Model Based on Artificial Neural Network and Evolutionary Algorithm

A hybrid identification model based on multilayer artificial neural networks(ANNs) and particle swarm optimization(PSO) algorithm is developed to improve the simultaneous identification efficiency of thermal conductivity and effective absorption coefficient of semitransparent materials.For the direct model,the spherical harmonic method and the finite volume method are used to solve the coupled conduction-radiation heat transfer problem in an absorbing,emitting,and non-scattering 2D axisymmetric gray medium in the background of laser flash method.For the identification part,firstly,the temperature field and the incident radiation field in different positions are chosen as observables.Then,a traditional identification model based on PSO algorithm is established.Finally,multilayer ANNs are built to fit and replace the direct model in the traditional identification model to speed up the identification process.The results show that compared with the traditional identification model,the time cost of the hybrid identification model is reduced by about 1 000 times.Besides,the hybrid identification model remains a high level of accuracy even with measurement errors.

Comparison of Newly Synthetic Hexaploid Wheat with Its Donors on SSR Products

Microsatellites or SSRs as powerful genetic markers have widely been used in genetics and evolutionary biology in common wheat. Because of the high polymorphism, newly synthesized hexaploid wheat has been used in the construction of genetic segregation population for SSR markers, However, data on the evolution of microsatellites during the polyploidization event of hexaploid wheat are limited. In this study, 66 pairs of specific to A/B genome SSR patterns among newly synthesized hexaploid wheat, the donor tetraploid wheat and Aegilops tauschii were compared. The results indicated that most SSR markers were conserved during the polyploidization events of newly synthetic hexaploid wheat, from Triticum turgidum and Ae. tauschii. Over 70% A/B genome specific SSR markers could amplify the SSR sequences from the D genome ofAe. tauschii. Most amplified fragments from Ae, tauschii were detected in synthetic hexaploid at corresponding positions with the same sizes and patterns as in its parental Ae. tauschii. This suggested that these SSR markers, specific for A/B genome in common wheat, could amplify SSR products of D genome besides A/B genome in the newly synthesized hexaploid wheat, that is, these SSR primers specific for A/B genome in common wheat were nonspecific for the A/B genome in the synthetic hexaploid wheat. In addition, one amplified Ae. tauschii product was not detected in the newly synthetic hexaploid wheat. An extra-amplified product was found in the newly synthetic hexaploid wheat. These results suggested that caution should be taken when using SSR marker to genotype newly synthetic hexaploid wheat.

Improvement and application of neural network models in development of wrought magnesium alloys

Neural network models of mechanical properties prediction for wrought magnesium alloys were improved by using more reasonable parameters, and were used to develop new types of magnesium alloys. The parameters were confirmed by comparing prediction errors and correlation coefficients of models, which have been built with all the parameters used commonly with training of all permutations and combinations. The application was focused on Mg-Zn-Mn and Mg-Zn-Y-Zr alloys. The prediction of mechanical properties of Mg-Zn-Mn alloys and the effects of mole ratios of Y to Zn on the strengths in Mg-Zn-Y-Zr alloys were investigated by using the improved models. The predicted results are good agreement with the experimental values. A high strength extruded Mg-Zn-Zr-Y alloy was also developed by the models. The applications of the models indicate that the improved models can be used to develop new types of wrought magnesium alloys.

Compositional optimization of glass forming alloys based on critical dimension by using artificial neural network

An artificial neural network （ANN） model was developed for simulating and predicting critical dimension dc of glass forming alloys. A group of Zr-Al-Ni-Cu and Cu-Zr-Ti-Ni bulk metallic glasses were designed based on the dc and their de values were predicted by the ANN model. Zr-Al-Ni-Cu and Cu-Zr-Ti-Ni bulk metallic glasses were prepared by injecting into copper mold. The amorphous structures and the determination of the dc of as-cast alloys were ascertained using X-ray diffraction. The results show that the predicted de values of glass forming alloys are in agreement with the corresponding experimental values. Thus the developed ANN model is reliable and adequate for designing the composition and predicting the de of glass forming alloy.

Constructing processing map of Ti40 alloy using artificial neural network

Based on the experimental data of Ti40 alloy obtained from Gleeble-1500 thermal simulator,an artificial neural network model of high temperature flow stress as a function of strain,strain rate and temperature was established.In the network model,the input parameters of the model are strain,logarithm strain rate and temperature while flow stress is the output parameter.Multilayer perceptron（MLP） architecture with back-propagation algorithm is utilized.The present study achieves a good performance of the artificial neural network（ANN） model,and the predicted results are in agreement with experimental values.A processing map of Ti40 alloy is obtained with the flow stress predicted by the trained neural network model.The processing map developed by ANN model can efficiently track dynamic recrystallization and flow localization regions of Ti40 alloy during deforming.Subsequently,the safe and instable domains of hot working of Ti40 alloy are identified and validated through microstructural investigations.

Intelligent method to develop constitutive relationship of Ti-6Al-2Zr-1Mo-1V alloy

The isothermal compression tests were carried out in the Thermecmastor-Z thermo-simulator at temperatures of 800, 850, 900, 950, 1000 and 1050 ℃ and the strain rates of 0.01, 0.1, 1 and 10 s-1. The influence of deformation temperature and strain rate on the flow stress of Ti-6Al-2Zr-IMo-IV alloy was studied. Based on the experimental data sets, the high temperature deformation behavior of Ti-6A1-2Zr-IMo-IV alloy was presented using the intelligent method of artificial neural network （ANN）. The results indicate that the predicted flow stress values by ANN model is quite consistent with the experimental results, which implies that the artificial neural network is an effective tool for studying the hot deformation behavior of the present alloy. In addition, the development of graphical user interface is implemented using Visual Basic programming language.

Prediction of mechanical properties of A357 alloy using artificial neural network

The workpieces of A357 alloy were routinely heat treated to the T6 state in order to gain an adequate mechanical property.The mechanical properties of these workpieces depend mainly on solid-solution temperature,solid-solution time,artificial aging temperature and artificial aging time.An artificial neural network（ANN） model with a back-propagation（BP） algorithm was used to predict mechanical properties of A357 alloy,and the effects of heat treatment processes on mechanical behavior of this alloy were studied.The results show that this BP model is able to predict the mechanical properties with a high accuracy.This model was used to reflect the influence of heat treatments on the mechanical properties of A357 alloy.Isograms of ultimate tensile strength and elongation were drawn in the same picture,which are very helpful to understand the relationship among aging parameters,ultimate tensile strength and elongation.

DEPTH PREDICTION OF RAIN WATER ON ROAD SURFACE BASED ON ARTIFICIAL NEURAL NETWORK

A model based on the non-linear artificial neural network （ANN） is established to predict the thickness of the water film on road surfaces. The weight and the threshold can be determined by training test data, and the water film thickness on the road surface can be accurately predicted by the empirical verification based on sample data. Results show that the proposed ANN model is feasible to predict the water film thickness of the road surface.

Effect of pre-deformation on microstructures and mechanical properties of high purity Al-Cu-Mg alloy

The effects of pre-deformation following solution treatment on the microstructure and mechanical properties of aged high purity Al-Cu-Mg alloy were studied by tensile test, micro-hardness measurements, transmission electron microscopy and scanning electron microscopy. The micro-hardness measurements indicate that compared with un-deformed samples, the peak hardness is increased and the time to reach peak hardness is reduced with increasing pre-strain. Additionally, a double-peak hardness evolution behavior of cold-rolled （CR） samples was observed during aging. The results of TEM observation show that the number density of S′（Al2CuMg） phase is increased and the size is decreased in CR alloy with increase of pre-strain. The peak hardness and peak strength of the CR alloy are increased because of quantity increasing and refinement of S′ phase and high density dislocation.

Feature fusing in face recognition

With the aim of extracting the features of face images in face recognition, a new method of face recognition by fusing global features and local features is presented. The global features are extracted using principal component analysis （PCA）. Active appearance model （AAM） locates 58 facial fiducial points, from which 17 points are characterized as local features using the Gabor wavelet transform （GWT）. Normalized global match degree （local match degree） can be obtained by global features （local features） of the probe image and each gallery image. After the fusion of normalized global match degree and normalized local match degree, the recognition result is the class that included the gallery image corresponding to the largest fused match degree. The method is evaluated by the recognition rates over two face image databases （AR and SJTU-IPPR）. The experimental results show that the method outperforms PCA and elastic bunch graph matching （EBGM）. Moreover, it is effective and robust to expression, illumination and pose variation in some degree.

Activities of Urease and Phosphatase in Integrated Vertical Flow Constructed Wetland and Purification Effect of Black and Malodorous River

[Objective]The activities of urease and phosphatase in integrated vertical flow constructed wetland and purification effect of black and malodorous river were studied.[Method]Honeycomb stone and soft filler were used as matrix,the biological grid integrated vertical flow constructed wetland system was built to strengthen treatment for black and malodorous river,and the activities of urease and phosphatase of two fillers in different functional areas of constructed wetland were tested to study the film formation property of two fillers in different functional areas.[Result]Both urease and phosphatase activities on biofilm of soft filler were significantly higher than on biofilm of honeycomb stone filler;indicating that choosing soft filler was more advantageous to the growth of biofilm;and urease activity had significant correlation with total nitrogen removal rate,while phosphatase activity had no significant correlation with total phosphorus removal rate.[Conclusion]This study provided evidences for utilizing the activities of urease and phosphatase to evaluate the purification effect of black and malodorous river and choose appropriate filler.

Human Settlements in Rural-urban Fringe

On basis of human settlements theory, the research explored status quo of human settlements theory in rural-urban fringe, and analyzed and concluded predicaments confronted by rural-urban fringe, laying foundation for human settle- ments theory of rural-urban fringe.

Challenges and Demands for College English Teachers Raised by Training All-round Qualified Persons

The latest issue of College English Curriculum Requirements has posed challenges and demands for teachers in terms of linguistic competence, academic knowledge, language skills, professional morality, emotional and attitudinal qualifications, etc., which requires teachers to embrace and handle with active and open-minded responses. Hence, teachers ought to strive to develop and improve their own overall qualifications in collaboration with the long-term development of the subject and of the national higher education, with the need of qualified persons demanded by social development and the students＇ learning. Teachers also ought to form a notion of scientific development by keeping pace with the time, so as to discern the trend of subject development, to form appropriate judgments concerning the social development and to properly regulate their own development.

On the Training Modes of Interdisciplinary and Application-oriented Talents of Business English

This paper focuses on the training modes of interdisciplinary and application-oriented talents of business English and the constructions of curriculum. In the light of our socialist market-oriented economy characteristics, the discussion proceeds, in theory and practice, by putting forward a relatively profound approach according to the trend in the demands for business English talents and to the operational patterns of business English discipline, with some suggestions about the training modes of interdisciplinary and application-oriented talents and the construction of curriculum.

Affinity Chromatography Purification of Recombinant Human Interleukin-6 from Its Fusion Protein with GST

Recombinant E.coli JM109, containing pHZ1818 plasmid which included the fused gene encoding human interleukin 6(IL 6), expressed a fusion protein with glutathion S transferase(GST). The fusion protein existed both in the supernatant and inside the bacterial cell,but the insoluble protein had no biological activity and could not be refolded. The rotative speed of the shaker and the temperature of induction were optimized to maximize the expression of the soluble fusion protein. From the supernatant of the cell sonicates Glutathion Sephrose 4B affinity column chromatography was employed to isolate the fusion protein which could be purified to >80 0 0 in a single step. The yield of soluble GST IL 6 was about 10 mg per liter culture. The GST was site specifically cloven by 6 hours of treatment with thrombin and from the thrombin digest mixture IL 6 was purified by Q high performance ion exchange chromatography. From 1 liter of E.coli culture 2 mg refined IL 6 was obtained. The purified IL 6 had a purity of more than 95 0 0 and a biological activity of 1.02×10 8 IU/mg.

On educational system of legal translation course in colleges of China

With the broadening of economic and commercial communication between China and the outside world, the market of legal and contract document translation job is blooming harshly in both China and abroad. Accompanying this tendency, the professionalizing forensic development of translation is booming up as well. The request for higher education institutions to establish the education system of forensic translation is shining in human＇s eyes, and the cultivating system for the future, the world and profession is highly regarded. So comprehensive profession-cultivating, socialization and economy-serving should be the direction of the education of foreign languages department, related foreign forensic document translation and professional direction of public foreign language teaching as well are the aims of this reform of education. So the aim of this new education system should be the establishing the system of professional translation, forensic translation, cross-subject education and the cultivation of multi-professionals.

科学发展观对传统哲学的继承与超越

从传统哲学的视角探讨科学发展观的精神资源，是一次传统与现代超越时空的对话。传统哲学是科学发展观的源头活水，是其内在的历史根据，科学发展观则是对传统哲学的有机整合和与时俱进的发展。在继承传统哲学的优秀成果的基础上，科学发展观也完成了其时代性超越。其中，统筹兼顾的根本方法是对传统哲学中阴阳辩证思维方式的继承和发展，“以人为本”思想源于中华文明的“以民为本”思想，可持续发展观是对“天人合一”思想的历史继承与理性超越。

Application of novel physical picture based on artificial neural networks to predict microstructure evolution of Al-Zn-Mg-Cu alloy during solid solution process

The effects of the solid solution conditions on the microstructure and tensile properties of Al?Zn?Mg?Cu aluminum alloy were investigated by in-situ resistivity measurement, optical microscopy (OM), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and tensile test. A radial basis function artificial neural network (RBF-ANN) model was developed for the analysis and prediction of the electrical resistivity of the tested alloy during the solid solution process. The results show that the model is capable of predicting the electrical resistivity with remarkable success. The correlation coefficient between the predicted results and experimental data is 0.9958 and the relative error is 0.33%. The predicted data were adopted to construct a novel physical picture which was defined as “solution resistivity map”. As revealed by the map, the optimum domain for the solid solution of the tested alloy is in the temperature range of 465?475 °C and solution time range of 50?60 min. In this domain, the solution of second particles and the recrystallization phenomenon will reach equilibrium.