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In a route boiling water served as reaction medium, a stoichiometric amount of rare-earth compound and fluoride are put into this system to form α-NaYF4:Yb, Er nuclei. Then prepared sample is heated at elevated temperature to improve the fluorescence intensity, and next a NaGdF4shell grows on the surface of NaYF4nuclei. NaYF4:Yb,Er/NaGdF4core–shell structured upconversion nanoparticles (CSUCNPs) have been successfully synthesized by above route. The use of boiling water decreases the cubic-to-hexagonal phase transition temperature of NaYF4:Yb,Er to 350°C and increases its upconversion (UC) luminescence intensity. A heterogeneous NaGdF4epitaxially growing on the surface of Ln3+-doped NaYF4not only improves UC luminescence, but also creates a paramagnetic shell, which can be used as contrast agents in magnetic resonance imaging (MRI). The solution of CSUCNPs shows bright green UC fluorescence under the excitation at 980 nm in a power density only about 50 mW·cm–2. A broad spectrum with a dominant resonance at gof about 2 is observed by the electron paramagnetic resonance (EPR) spectrum of CSUCNPs. Above properties suggest that the obtained CSUCNPs could be potential candidates for dual-mode optical/magnetic bioapplications.

Eupatoriurn odoratum aerial parts were extracted with ligarine and the volatile constituents isolated were analyzed by gas chromatography (GC) and gas chromatography/mass spectrometry (GC/MS). Volatile constituents were isolated from the ground aerial parts of E. odoratum by ligarine extraction and analyzed by gas chromatography (GC) and gas chromatography/mass spectrometry (GC/MS). As a result, a total of fifteen compounds represented all of the extract were identified, amongst nine of fifteen compounds were sesquiterpenes. Esters and sesquiterpenes were found to compose three major chemotype accounted for 58.58% and 30.80% of the constituents, respectively. The main components was demonstrated to be dibutyl phthalate (39.73%), 11,14,17-eicosatrienoic acid, methyl ester (13.20%), (S)-spiro [4.nona-1,6-diene (6.80%), 1,2-benzenedicarboxylic acid, bis (2-methylpropyl) ester (5.65%) and cis-Z-α-bisabolene epoxide (5.56%). In addition, some pharmaceutical components such as α-cadinol and germacrene D were discovered. Antioxidant activity of the extract was assessed by the free radical scavenging (DPPH). The study offers theoretic basis for pharmaceutical utilization of the medicinal plant E. odoratum.

800x600 Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} The present rear-end collision accident proportion on the road increases day after day, car collision avoidance system is more and more paid attention. Analysising the existing car collision avoidance system, we propose a car anti-collision algorithm based on safe distance model in this paper. This method takes the influence factors of safety distance for main parameters which fully considers the speed change and the acceleration change of the car 1 and the car 2. It may realize real-time information acquisition and warning judgment according to the state of car 2, the car could automatic braking if necessary. VB simulation shows that the algorithm can effectively avoid collision, also automatically maintain the distance between vehicles, and lay a foundation for further research on the unmanned car.

The temperature control of the glass tempering and annealing process has characteristics of time-varying parameters，nonlinear and big lag. It is difficult to meet the expected control effect with the common control method. To solve this problem，this paper puts forward a kind of fuzzy neural network controller optimized by genetic algorithm. First，it uses neural network to construct fuzzy logic system according to the structure equivalence rule，thus the optimization of fuzzy control rules and membership functions can be realized by finding the weight value of the neural network. Then，it uses the improved genetic algorithm to find the global optimum weighted factors with a high speed so to improve the performance of the controller. The simulation results show that the optimized fuzzy neural network controller can obtain an excellent control performance for the nonlinearity system with time- varying parameters and lag.

This paper addresses the determination of aldehyde group (% of dialdehyde units) in dialdehyde cellulose (DACs) oxidized from bacterial cellulose (BC). With 4 determination methods, the oxidation degrees of DACs were studied: Automatic potential titration method through Schiff base reaction, Acid-base titration in Cannizzaro reaction, Metaperiodate consumption determination, and Measurement of amino nitrogen content in DAC derivatives. By comparing determination results of these methods, we found out the proper way suitable for this metaperiodate oxidation system of BC to measure the dialdehyde unit content of the DACs.

A series of dialdehyde cellulose samples with varied aldehyde content were prepared by oxidation of bacterial cellulose with sodium periodate. The X-ray diffractometry profile showed that the crystallinity degree of bacterial cellulose was 66%, but that of the dialdehyde cellulose (containing 12% aldehyde ) was 56%. Thermal decomposition of these dialdehyde cellulose samples and bacterial cellulose were studied by thermogravimetry. The decomposition of bacterial cellulose in nitrogen started at 230[removed info] and rapid weight loss occurred between 300-400[removed info]. The introduction of dialdehyde group to bacterial cellulose resulted in significant shifts of decomposition to lower temperature range. The decomposition of dialdehyde cellulose (12% aldehyde ) started at 180[removed info] and rapid weight loss between 200-350[removed info]. The temperature of rapidest weight loss shifted from 340[removed info] of bacterial cellulose to 290[removed info] of the dialdehyde cellulose(12% aldehyde).