Combined disturbance-observer-based control and iterative learning control design for pulsed superconducting radio frequency cavities

The development of iterative learning control combined with disturbance-observer-based(DOB)control for the digital low-level radio frequency(LLRF)system of the ...     

Primary structure of two-chain botrocetin, a von Willebrand factor modulator purified from the venom of Bothrops jararaca

The complete amino acid sequence and location of the disulfide bonds of two-chain botrocetin, which promotes platelet agglutination in the presence of von Willebrand factor, from venom of the snake Bothrops jararaca are presented. Sequences of the alpha and beta subunits were determined by analysis of peptides generated by digestion of the S-pyridylethylated protein with Achromobacter protease I or alpha-chymotrypsin and by chemical cleavage with cyanogen bromide or 2-(2'-nitrophenylsulfenyl)-3-methyl-3-bromoindolenine. Two-chain botrocetin is a heterodimer composed of the alpha subunit (consisting of 133 amino acid residues) and the beta subunit (consisting of 125 amino acid residues) held together by a disulfide bond. Seven disulfide bonds link half-cystine residues 2 to 13, 30 to 128, and 103 to 120 of the alpha subunit; 2 to 13, 30 to 121, and 98 to 113 of the beta subunit; and 80 of the alpha subunit to 75 of the beta subunit. In terms of amino acid sequence and disulfide bond location, two-chain botrocetin is homologous to echinoidin (a sea urchin lectin) and other C-type (Ca(2+)-dependent) lectins.     

Real-time supply-demand schedule update and operation for generators and battery energy storage system based on forecasted and actual photovoltaic power outputs

The photovoltaic (PV) power output might be frequently curtailed to maintain electricity supply-demand balance in future power systems. In our previous study, we proposed a new method for updating the battery energy storage system (BESS) charge/discharge and the generator unit commitment (UC) schedules based on the forecasted and actual PV power outputs. The forecast dataset was updated every 3 h (eight times a day). Although the simulation results showed that the proposed method could reduce the supply-demand imbalances, it was not clear whether the forecasted or actual values made contributions. Therefore, in this study, we propose and evaluate a real-time scheduling and operation method using the forecasted and actual PV power outputs assuming that the forecasted dataset is updated only once a day. Numerical simulations of supply-demand operations are conducted on the power system model of the Kanto area of Japan for one year. The results show that the previous study method has a slight advantage over proposed method in terms of curtailed PV energy and operational cost of thermal generators reduction, but the difference is very small, indicating that the contribution of the actual PV power outputs is greater than that of the forecasted PV power outputs.     

Estimator for generalization performance of machine learning model trained by biased data collected from multiple references

The data acquired in civil engineering tasks often involve high acquisition costs, and the available datasets tend to have a limited number of samples and are highly biased. To estimate the performance of machine learning models, k-fold cross-validation (k-CV) is widely used. However, if only limited data are available and the data distribution is biased, k-CV tends to overestimate the performance for practical applications. This study proposed a new estimator, leave one reference out and k-CV (LORO-k-CV), to determine the practical performance of machine learning models, that is, the generalization performance for population data in the target task, in case data are collected by multiple references resulting in biased data. LORO-k-CV is a combination of a new concept, LORO-CV, that estimates the performance in the extrapolation region of the training data without human intervention and k-CV, considering the ratio of the interpolation and extrapolation regions. The efficacy of LORO-k-CV was validated with its application to the regression task for the chloride-ion concentration of concrete structures. To more specifically demonstrate the advantages of LORO-k-CV in model construction, the feature selections were conducted using both k-CV and LORO-k-CV methods. These results revealed that LORO-k-CV can effectively construct a model with improved generalization performance even from the same data in cases where data are collected by multiple references, resulting in biased data.     

Determination of Carbonyl Groups in Starches by Polarographic Techniques Using o-Phenylenediamine. V. Reactions of Periodate Oxidized Starches with o-Phenylenediamine.

The reaction of oxyamylose with o-phenylenediamine (OPD) in alkaline media produces quinoxalines which can be followed by polarographic method and the dialdehyde content can easily be determined polarographically. The lower limit of the determination of dialdehyde content may be 0.01 in the ratio of NaIO₄/AGU. Quinoxalines produced from oxyamylose were studied chromatographically and spectrophotometrically and compared with those from D-glucose. Three quinoxalines were identified with quinoxaline, 2-methylquinoxaline and 2-hydroxyethylquinoxaline. Mechanism of the reaction of oxyamylose with OPD is discussed.