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Purposes: this paper is to analyze and quantify the eco-effect of building green facade, providing a reliable application methods and theory basis for solving current environmental issues. Methods: this paper using facade renovation project of Wismar University in Germany as the carrier, it uses Energy-Plus energy simulation software, CFD computational fluid dynamics software and U-wert.net calculation software for U value of material to get the simulation analysis of the energy, physical and regional eco-effect of building green facade. Results: building green facade can increase 23.7% heat resistance value, save 6.2% of the year-round air conditioning load, reduce indoor temperature by 3-5°C in summer, reduce the air velocity by 0.03m/s, maintain the stability of indoor temperature, the annual indoor temperature can maintain 20.84°C, improve the indoor comfort. The temperature around the building can reduce by 0.5-4°C after green facade renovation, reduce the wind speed in the region by 0.05m/s, and reduce the annual carbon emission by 7.1%. Conclusions: Through the simulation results, eco-effect of building green facade play a significant role in cooling and insulation, energy saving, heat island mitigation, improving comfort, maintaining the balance of carbon and oxygen. It has become one important way to suture rift between man and nature in cities, being an effective way to solve today's ecological issues.

The change of moisture-heat is the key factor that influences the seasonal freezing subgrade stability. In order to analyze the impact of the moisture on temperature field in the seasonal frozen subgrade, this paper established seasonal freezing subgrade model, calculated and analyzed the effects of subgrade temperature field in the middle of road, shoulder, slope and outside of slope with roadside accumulated water, based on the change of temperature field control equation. This research showed that roadside accumulated water has a significant influence on the subgrade temperature field. The results showed the range of 0°C isotherm under the accumulated water was bigger than normal subgrade, and the depth of 0°C isotherm was deeper under the accumulated water than normal.

Antimicrobial peptides (AMP) are potent, broad spectrum antibiotics which demonstrate potential as novel therapeutic agents. Because it is both time-consuming and laborious to identify new AMPs by experiment, this paper tries to resolve this problem by pattern recognition. Two major contents included: Firstly, up to six kinds of physicochemical properties value are selected to code the AMP sequence as physical-chemical property matrix (PCM), then auto and cross covariance transformation is performed to extract features from the PCM for AMP sequence expression; Secondly, these feature vectors are input to a powerful Support Vector Machine (SVM) classifier for training and new query AMP recognition. For a newly constructed AMP benchmark dataset, the overall classification accuracy about 96% has been achieved through the rigorous Leave-One-Out cross-validation. For convenience, a user-friendly web server, AMPpred, has been established at http://icpr.jci.jx.cn/bioinfo/AMPpred. It is anticipated that this on-line predictor may become a useful bioinformatics tool for molecular biology and drug development. Also, its novel approach will further stimulate the development of predicting peptide attributes.

It is an important topic to find and identify molecular drug targets for modern drug research. Naturally, to find new or potential drug-GPCRs couples is very useful for determining the new effective medicine target, because GPCRs are among the most frequent targets of therapeutic drugs and proven evolutionary pharmacology value. To realize this, this paper incorporates chemical functional groups of drugs and grey model GM(1,1) based on digital coding of amino acids to formulate the drug-GPCRs couples for statistical prediction. The overall success rate using the fuzzy K-Nearest Neighbor algorithm by the jackknife test is about 81%. This novel approach will further stimulate the development of scanning target via a computational approach.

In this research, in order to explore the main mechanism of direct and two-stage compression in as-cast light alloy, the mechanical property, microstructure evolution and the flowing of second phase particles were studied, before and after deformation. Then, the influence of the strain volume in first stage on flowing stress of the second stage deformation also was researched.

Photoelectrocatalytic (PEC) degradation efficiencies of a suspended TiO2 and Ti electrodes composite system in different ammonium salt solutions were investigated. Electrolyte type and concentration as well as the applied potential on the Ti electrodes had significant effects on photoelectrocatalytic degradation and electro-degradation efficiencies. PEC degradation and electro-degradation of methyl orange increased with increasing applied potential and electrolyte concentration. PEC degradation is much more powerful than electro-degradation. PEC degradation efficiency in (NH4)3PO4•3H2O solution is the highest 93.4%, whereas the efficiency in NH4Cl solution shows the worst 73.1%, which is even less than that of photocatalytic process alone. PEC degradation efficiencies in (NH4)2SO4 and NH4HCO3 solutions are 88.8% and 85.9% respectively, indicating no noticeable improvement compared with photocatalytic process.