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We study decentralized plug-in electric vehicle (PEV) charging control, wherein the system operator (SO) sends pricebased signals to a load aggregator (LA) that optimizes charging of a PEV fleet. We study a pricing scheme that conveys price and quantity information to the LA and compare it to a simpler priceonly scheme. We prove that the price/quantity-based mechanism can yield a socially optimal solution. We also examine several numerical case studies to demonstrate the superior performance of the price/quantity-based scheme. The price/quantity scheme yields nearly identical PEV charging costs compared to the social optima, whereas the price-only scheme is highly sensitive to the choice of a regularization penalty term that is needed to ensure convergence. We also show that the time to compute an equilibrium with the price-only mechanism can be up to two orders of magnitude greater than with the price/quantity scheme and can involve 24 times more information exchange between the SO and LA.

In this study, a novel metabolomics technique based on ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry in the MS mode was used to investigate the milk metabolomics of healthy, subclinical, and clinical mastitis cows, which were classified based on somatic cell count and presentation of clinical symptoms. Meanwhile, univariate and multivariate statistical analyses were performed to identify the significant differences across the 3 groups. Compared with healthy milk samples, less glucose, d-glycerol-1-phosphate, 4-hydroxyphenyllactate, l-carnitine, sn-glycero-3-phosphocholine, citrate, and hippurate were detected in the clinical mastitic milk samples, whereas less d-glycerol-1-phosphate, benzoic acid, l-carnitine, and cis-aconitate were found in the subclinical mastitic milk samples. Meanwhile, the milk concentration of arginine and Leu-Leu increased in both the clinical and subclinical mastitis groups. Besides, less 4-hydroxyphenyllactate, cis-aconitate, lactose, and oxoglutarate were detected in the clinical than the subclinical mastitic milk samples, whereas the abundance of some oligopeptides (Leu-Ala, Phe-Pro-Ile, Asn-Arg-Ala-Ile, and Val-Phe-Val-Tyr) increased by over 7.95-fold. Our results suggest that significant variations exist across healthy and mastitis cows. The current metabolomics approach will help in better understanding the pathobiology of mastitis, although clinical validation will be required before field application.

A mixture of organic solvent and ionic liquid (IL) was proposed as entrainer for the ethanol/water separation by extractive distillation. The vapor−liquid equilibrium (VLE) experimental results showed that the relative volatility of ethanol to water is significantly enhanced using the ethylene glycol (EG) and [EMIM] + [Ac] − mixed entrainers when compared to that of the benchmark solvent EG. The nonrandom-two-liquid model parameters were correlated using the measured ternary and quaternary experimental VLE data. On this basis, process simulation was carried out to evaluate the improvement of the proposed mixed entrainers. It was found that for the ethanol/water separation using the mixed entrainers, the overall heat duties on reboilers in the processes without and with heat integration (HI) decrease 11.53% and 10.34%, respectively, when compared to the conventional benchmark solvent EG. Moreover, the presented process intensification method is easily achieved in practice by substituting the proposed mixed entrainers for the conventional solvent without changing the whole flowsheet.