A novel photoresponsive functional monomer bearing diaminopyridine and azobenzene moieties was synthesized and applied to the preparation of photo-regulated molecularly imprinted polymers, which can recognize porphyrin derivatives through hydrogen bonding. The binding affinity of the imprinted cavities was regulated by UV irradiation, suggesting that azobenzene groups located inside the binding sites worked as photosensitizers and the trans-cis isomerization could regulate the affinity for the target compounds. Repetitive binding of the target compound to trans-IP and cis-IP was directly monitored by slab optical waveguide spectroscopy and the photo-mediated regulation of binding affinity was successfully confirmed.

Synthetic polymers which can adsorb bisphenol A (BPA) and related compounds were prepared by a covalent molecular imprinting technique. BPA dimethacrylate, used as template molecule, was polymerized with a crosslinker, triethylene glycol dimethacrylate (TEGDMA) or trimethylol propane trimethacrylate (TRIM). After the polymerization treatment with dilute NaOH was used to cleave BPA from the polymers. For high recovery of BPA with low polymer matrix degradation, the hydrolysis conditions were determined to be treatment with 1.0 mol L(-1) NaOH for 48 h. The binding sites generated by the hydrolysis were evaluated by determination of the retentivity of BPA, BPA analogues, and other endocrine disruptors. The polymers strongly adsorbed compounds with two hydroxyl groups at the 4,4'-positions. Generally the TEGDMA-based polymers had stronger affinity than the TRIM-based polymers, although the TRIM-based polymer adsorbed steroidal hormones with two hydroxyl groups, for example 17 alpha-estradiol and 17 beta-estradiol, more strongly than the TEGDMA-based polymer, meaning that the crosslinkers affected the properties of the binding sites and, depending upon the target molecules, suitable crosslinkers should be chosen in this system.

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This study was intended to efficiently perform the probabilistic safety and optimal design assessment of steel cable-stayed bridges (SCS bridges) using stochastic finite element analysis (SFEA) and expected life-cycle cost (LCC) concept. To that end, advanced probabilistic finite element algorithm (APFEA) which enables to execute the static and dynamic SFEA considering aleatory uncertainties contained in random variable was developed. APFEA is the useful analytical means enabling to conduct the reliability assessment (RA) in a systematic way by considering the result of SFEA based on linearity and nonlinearity of before or after introducing initial tensile force. Appropriateness of APFEA was verified in such a way of comparing the result of SFEA of a simple structure and the result of numerical analysis using Monte Carlo Simulation (MCS) program. The probabilistic method of SCS bridges was set, taking into account of analytical parameters. The dynamic response characteristic by probabilistic method was evaluated using ASFEA, and RA was carried out based on analysis result, thereby quantitatively calculating the probabilistic safety. The optimal design of SCS bridges was determined based on the expected LCC according to the results of SFEA and RA of alternative designs. Moreover, given the potential epistemic uncertainty contained in safety index, failure probability and minimum LCC, the sensitivity analysis was conducted and as a result, a critical distribution phase was illustrated using a cumulative-percentile.