Photocatalytic reduction of 6-chloro-3-nitrotoluene-4-sulfonic acid (CNSA) was studied in UV-irradiated TiO₂ suspensions in the presence of methanol and surfactants. A mixture of CNSA, TiO₂, water, additives and surfactants was put into a quartz glass reactor with a jacket, which was irradiated with a high pressure Hg lamp in the purging of nitrogen gas. With methanol, the conversion of CNSA increased from 7.7% to 34.6%. Three surfactants significantly promoted the photocatalytic reduction conversion in reduced order of sodium dodecylbenzenesulfonate (DBS), cetyltrimethylammonium bromide (CTAB) and sodium dodecylsulfate (SDS). In suspensions involving DBS and CTAB respectively, CNSA conversion increased in consistence with the adsorption ratio with methanol, but varied inversely with the adsorption ratio without methanol. But no obvious influence on the adsorption ratio was observed with or without methanol added when the SDS concentration was critical micelle concentration (cmc). The photocatalytic reduction of CNSA was enhanced in UV-irradiated TiO₂ suspensions in the presence of methanol and surfactants. Methanol inhibited the recombination of photogenerated holes and electrons efficiently. Surfactants around 1 cmc led to the highest reduction conversion.

5-Fluorouracil (5-FU) has a broad spectrum of anti-tumor activity, widely applied to the treatment of cancers. However, it is necessary to determine the plasma concentration of 5-FU in clinical practice due to its narrow therapeutic index. Therefore, a simple, economic and sensitive high-performance liquid chromatography (HPLC) method was developed and validated for the determination of 5-FU in human plasma. Ethyl acetate was chosen as extraction reagent. Chromatographic separation was performed on a Diamonsil C18 column (250 mm × 4.6 mm i.d., 5 μm) with the mobile phase consisting of methanol and 20 mmol/L ammonium formate using a linear gradient elution at a flow rate of 0.8 mL/min. 5-FU and 5-bromouracil (5-BU) were detected by UV detector at 265 nm. The calibration curve was linear over the concentration range of 5–500 ng/mL and the correlation coefficient was not less than 0.992 6 for all calibration curves. The intra- and inter-day precisions were less than 10.5% and 4.3%, respectively, and the accuracy was within ±3.7%. The recovery at all concentration levels was 80.1±8.6%. 5-FU was stable under possible conditions of storing and handling. This method is proved applicable to therapeutic drug monitoring and pharmacokinetic studies of 5-FU in human.

Synthesis and kinetics of dichloro-methoxybenzenes were studied from 1,2,4-trichlorobenzene and sodium methoxide in a temperature range of 353–383 K. Effects of molar ratio of reactants, solvent and reaction temperature were investigated. Reaction products include three isomers. The order of selectivity for the three isomers was 1,4-dichloro-2-methoxybenzene>>2,4-dichloro-1-methoxybenzene>1,2-dichloro-4-methoxybenzene. Kinetic equations for the parallel liquid-solid interface reaction between 1,2,4-trichlorobenzene and sodium methoxide were established in the absence of catalyst. Kinetic parameters such as the pre-exponential factors and the activation energy were determined with the Arrhenius equation.

The influence of calcination temperature on TiO₂ nanotubes’ catalysis for TiO₂/UV/O₃ was investigated. TiO₂ nanotubes (TNTs) were prepared via the sol-gel method and calcined at 300–700 °C, which were labeled as TNTs-300, TNTs-400, TNTs-500, TNTs-600 and TNTs-700, respectively. TNTs were characterized by transmission electron microscopy(TEM) and X-ray diffraction (XRD). It is found that TNTs calcined at 400 °C showed the best thermal stability. When the calcination temperature increased from 400 °C to 700 °C, the special structure of tubes was destroyed and gradually converted into nanorods and/or particles. The transformation from anatase to rutile occurred at 600 °C, and the rutile phase was enhanced when the calcination temperature was increased to over 600 °C. The calcination temperature’s influence on TNTs’ adsorption activity for chemical oxygen demand (COD) and catalytic activity for TiO₂/UV/O₃ was investigated in landfill leachate solution. In landfill leachate solution, the adsorption activity of COD decreased in the reduced order of TNTs-300, TNTs-400, TNTs-500, TNTs-600 and TNTs-700. In photocatalytic ozonation, TNTs-400 showed the best catalytic activity while TNTs-700 exhibited the worst. In other three processes, the COD removal of TNTs-300/UV/O₃ was higher than those of TNTs-500/UV/O₃ and TNTs-600/UV/O₃ in the first 20 min, and then became close to those of the latter two in the following 40 min. Compared with TNTs-300 and TNTs- 400, TNTs-600 had the best anti-fouling activity, while TNTs-500 and TNTs-700 had lower anti-fouling activity than the former three. In photocatalytic ozonation, the calcination temperature of 400 °C was appropriate when TNTs were obtained at the synthesis temperature of 105 °C.

An exhaust heat recovery generator is proposed to be integrated with conventional gas-fired triple-effect LiBr/water absorption cooling cycles to improve system energy efficiency. As a case study, simulation of the novel cycle based on promising parallel flow with cooling capacity of 1 150 kW is carried out under various heat recovery generator vapor production ratios ranging from 0 to 3.5%. The life cycle saving economic analysis, for which the annual gas conservation is estimated with Bin method, is employed to prove the worthiness of extra expenditure. Results show that the optimum gas saving revenue is obtained at 2.8% heat recovery generator vapor production ratio with 42 kW exhaust heat recovered, and the system energy efficiency is improved from 1.78 to 1.83. The initial investment of exchanger can be paid back within 7 years and 9 000 CNY of gas saving revenue will be achieved over the 15-year life cycle of the machine. This technology can be easily implemented and present desirable economic effects, which is feasible to the development of triple-effect absorption cycles.

Long tunnel excavation with tunnel boring machine (TBM) is a complex and stochastic process. It is easily affected by uncertainties and needs to be adjusted according to specific geological conditions in different tunnel sections, which makes the construction scheduling and management difficult. Based on the rock mass classification, this paper estimates the penetration rate. Using the rate, a cyclic network simulation (CYCLONE) model of TBM boring system is established, and the advance rates under different geological conditions are determined. Then, the impact of different cutter head thrust, which is chosen in reasonable range according to previous experiences, on project schedule is analyzed. Moreover, the simulation model of mucking system is built to determine the number of muck trains and rail intersections reasonably, regarding the efficiency of muck loading and material transporting. Based on the interaction and interrelation between TBM boring system and mucking system, the combined CYCLONE model for the entire tunneling process is established. Then reasonable construction schedule, the utilization rate of working resources, and the probability of project completion are obtained through the model programming. At last, a project application shows the feasibility of the presented method.

Negative skin friction (NSF) is one of the important problems when designing a pile foundation. However, the influence of loading sequence on the dragload and downdrag for pile foundation is seldom studied. In this paper, a three-dimensional numerical model was established using FLAC3D. Compared with the results of model test, the established model could be used to study the NSF of pile foundation. The influencing factors were discussed including the length-diameter ratio of pile and the loading sequence of pile head load and surcharge. A case history was analyzed using FLAC3D. The calculated results are in good agreement with the measured results. It is concluded that the dragload and downdrag are remarkably influenced by the loading sequence of pile head load and surcharge. The dragload and downdrag reach the maximum values under the condition of surcharge after pile head load.

A grid and Green-Ampt based(Grid-GA)distributed hydrologic physical model was developed for flood simulation and forecasting in semi-humid and semi-arid basin. Based on topographical information of each grid cell extracted from the digital elevation model (DEM) and Green-Ampt infiltration method, the Grid-GA model takes into consideration the redistribution of water content, and consists of vegetation and root interception, evapotranspiration, runoff generation via the excess infiltration mechanism, runoff concentration, and flow routing. The downslope redistribution of soil moisture is explicitly calculated on a grid basis, and water exchange among grids within runoff routing along the river drainage networks is taken into consideration. The proposed model and Xin’anjiang model were applied to the upper Lushi basin in the Luohe River, a tributary of the Yellow River, with an area of 4 716 km² for flood simulation. Results show that both models perform well in flood simulation and can be used for flood forecasting in semi-humid and semi-arid region.

The reinforcement effect of a reconstruction scheme for a steel factory building was investigated using finite element method and dynamic performance test. The workshop concerned is a portal frame structure with four spans and two slope roofs, of which ten columns need cutting for expanding span. The design and reconstruction project of column-cut supported by joist were introduced, which includes column reinforcement, connection rebuilding between brackets and crane beams, and the changing of rigid joint into hinge joint. The construction scheme was put forward in the light of the characteristics of the reinforcement and reconstruction. Spot test of dynamic performance on the workshop and comparison with theoretical analysis results show that the column-cut supported by joist design is effective and the reconstruction project is successful.

In order to evaluate the seismic reliability of water distribution system and make rehabilitation decisions correspondingly, it is necessary to assess pipelines damage states and conduct functional analysis based on pipe leakage model. When an earthquake occurred, the water distribution system kept serving with leakage. By adding a virtual node at the centre of the pipeline with leakage, an efficient approach to pressure-driven analysis was developed for simulating a variety of low relative scenarios, and a hydraulic leakage model was also built to perform hydraulic analysis of the water supply network with seismic damage. Then the mean-first-order-second-moment method was used to analyse the seismic serviceability of the water distribution system. According to the assessment analysis, pipes that were destroyed or in heavy leakage were isolated and repaired emergently, which improved the water supply capability of the network and would constitute the basis for enhancing seismic reliability of the system. The proposed approach to seismic reliability and rehabilitation decision analysis on water distribution system is demonstrated effective through a case study.

In the economic order quantity (EOQ) model, the decision maker has vague information about holding cost, ordering cost and market demand. With these uncertainties characterized as fuzzy variables, a new formula is developed by analyzing the fuzzy total cost. By comparing with other four EOQ formulas, i.e., using the crisp numbers with the highest membership values in classic EOQ formula, using the expected values of fuzzy parameters in classic EOQ formula, using the fuzzy variables in classic EOQ formula and then calculating the expected value, and calculating EOQ by hybrid intelligent algorithm simulation, the effectiveness of this formula is illustrated.

In electroencephalogram (EEG) modeling techniques, data segment selection is the first and still an important step. The influence of a set of data-segment-related parameters on feature extraction and classification in an EEG-based brain-computer interface (BCI) was studied. An auto search algorithm was developed to study four data-segment-related parameters in each trial of 12 subjects’ EEG. The length of data segment (LDS), the start position of data (SPD) segment, AR order, and number of trials (NT) were used to build the model. The study showed that, compared with the classification ratio (CR) without parameter selection, the CR was increased by 20% to 30% with proper selection of these data-segment-related parameters, and the optimum parameter values were subject-dependent. This suggests that the data-segment-related parameters should be individualized when building models for BCI.