Multi-Objective Bayesian Optimization with Active Preference Learning

There are a lot of real-world black-box optimization problems that need to optimize multiple criteria simultaneously. However, in a multi-objective optimization (MOO) problem, identifying the whole Pareto front requires the prohibitive search cost, while in many practical scenarios, the decision maker (DM) only needs a specific solution among the set of the Pareto optimal solutions. We propose a Bayesian optimization (BO) approach to identifying the most preferred solution in the MOO with expensive objective functions, in which a Bayesian preference model of the DM is adaptively estimated by an interactive manner based on the two types of supervisions called the pairwise preference and improvement request. To explore the most preferred solution, we define an acquisition function in which the uncertainty both in the objective functions and the DM preference is incorporated. Further, to minimize the interaction cost with the DM, we also propose an active learning strategy for the preference estimation. We empirically demonstrate the effectiveness of our proposed method through the benchmark function optimization and the hyper-parameter optimization problems for machine learning models

Structure–function studies of ultrahigh molecular weight isoprenes provide key insights into their biosynthesis

Some plant trans-1,4-prenyltransferases (TPTs) produce ultrahigh molecular weight trans-1,4-polyisoprene (TPI) with a molecular weight of over 1.0 million. Although plant-derived TPI has been utilized in various industries, its biosynthesis and physiological function(s) are unclear. Here, we identified three novel Eucommia ulmoides TPT isoforms—EuTPT1, 3, and 5, which synthesized TPI in vitro without other components. Crystal structure analysis of EuTPT3 revealed a dimeric architecture with a central hydrophobic tunnel. Mutation of Cys94 and Ala95 on the central hydrophobic tunnel no longer synthesizd TPI, indicating that Cys94 and Ala95 were essential for forming the dimeric architecture of ultralong-chain TPTs and TPI biosynthesis. A spatiotemporal analysis of the physiological function of TPI in E. ulmoides suggested that it is involved in seed development and maturation. Thus, our analysis provides functional and mechanistic insights into TPI biosynthesis and uncovers biological roles of TPI in plants

Synthesis of hydroxylated polyisoprene-graft-polylactide copolymer

Polyisoprene (PI) has been widely used in many industries for decades. Many researches have reported that most significant weaknesses of polyisoprene are caused by unsaturated double bond C=C. The aim of this research was to synthesis and characterize a new copolymer utilizing the unsaturated double bond C=C of polyisoprene. PI is first modified to form hydroxylated polyisoprene (PIOH). The absence of alkene proton peak in NMR spectrum of PIOH is a strong evidence that the unsaturation of PI has been reduced. After that, PIOH is subjected as an initiator for the ringopening polymerization of D,L-lactide in bulk condition to form hydroxylated polyisoprene-graft-polylactide copolymer (PI-g-PLA). The NMR spectrum of the new copolymer structure showed an unique peak at 4.09 ppm corresponding to methine proton of polyisoprene backbone adjacent to the PLA chains, indicating the grafting of D,L-lactide is successful to form PIOH-g-PLA. The average molecular weight, Mw of PIOH-g-PLA was significantly increased compared to PIOH, from 38260 to 56870 according to GPC. The surface of PIOH-g-PLA displayed significantly higher wettability and hidrophilicity than polyisoprene with water contact angle of below 30°. This owes to the terminal hydroxyl groups of PLA chains that lead to the formation of hydrogen bonds. Thermal stability studies by TGA and DTG of PIOH-g-PLA indicated two thermal degradations at Tmax 260 and 392 ℃ corresponding to PLA side chains and PIOH backbone, respectively, with PIOH exhibiting highest thermal stability compared to PI and the graft copolymer

Synthesis and thermal properties of poly(ethylene glycol)-polydimetylsiloxane crosslinked copolymers

Poly(ethylene glycol)-polydimethylsiloxane (PEG-PDMS) crosslinked copolymers with mol ratios PEG:PDMS:Glycerol of 5:3:2, 6:2:2 and 7:1:2 have been prepared and characterized. The synthesis of the copolymers was carried out by the reaction between hydroxyl groups of PEG, PDMS and glycerol with isocyanate groups of 1,6-hexamethyelene diisocyanate (HMDI). In the reaction, glycerol was acted as the cross linker. The copolymers were then characterized by FTIR spectroscopy. The thermal behaviour was investigated by DSC and TGA. Based on FTIR results, the crosslinked structure of the copolymers was confirmed by the presence of absorption peak at 3350 and 1710 cm-1 which indicated the (-N-H) stretching and carbonyl (-C=O) correspond to urethane links. This showed that the hydroxyl groups of PEG, PDMS and glycerol have reacted to isocyanate groups of HMDI. The copolymers showed melting temperature (Tm) of PEG segments from 22°C to 27°C and glass transition temperature (Tg) from -11°C to -6°C. Meanwhile, the PDMS segment showed values from -53°C to -56°C for Tm, and Tg from -118°C to -122°C. Data obtained from the thermal analysis indicate that thermal stability increases with increasing PDMS mol ratio