A systematic study of chloride vs. nitrate selectivity across six anion transporters has revealed a good correlation between the selectivities of their anion binding and membrane transport properties. This work reveals the limitations of the chloride-nitrate exchange assay and shows how new approaches can be used to measure anion uniport. assays that could measure the rate of anion uniport mediated by anion transporters without the need for an anion exchange process to occur. 10 We here make use of two complementary vesicle-based assays to determine anion transport selectivity, in particular Cl À /NO 3 À selectivity, of a library of hydrogen bond-based anion transporters 1-6 that contain increasing numbers of hydrogen bond donors (Fig. 1). By comparing these results with association constants for anion complexation determined in acetonitrile, we demonstrate for the first time a strong correlation between binding selectivity and transport selectivity across a series of structurally diverse anion transporters. Compounds 1, 2, 3, 5, and 6 are examples of anion transporters previously studied by our group. 9,10b,11 These compounds represent two distinct design approaches to highly effective anion transporters. Compounds 1-3 contain highly acidic NH groups, leading to high anion binding affinity and the ability to disperse the negative charge of the bound anion. in acetonitrile were determined by UV-vis absorption titrations using tetrabutylammonium (TBA + ) salts of the anions Fig. 1 Structures of anion transporters 1-6.

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A novel doubly N-confused isophlorin (2) was prepared by the nucleophilic ring-opening reaction of N-confused, N-fused porphyrin (1) with benzenethiol. The structure, redox property and copper coordination ability of isophlorin 2 were investigated by various spectroscopic methods and theoretical calculations.

Hybrid metal−organic frameworks (MOFs) with core/shell-like hierarchical structure comprised of zirconium metal and porphyrin (e.g., TPP) and its isomer, N-confused porphyrin (NCP), were synthesized through a seed-mediated reaction. The hierarchical structures of hybrid MOFs were characterized by the microscopic image analyses (e.g., scanning electron microscope (SEM), energy dispersive X-ray (EDX) spectrometry, and confocal laser scanning microscope (CLSM)). Taking advantage of the intrinsic light-harvesting properties of the porphyrin dye and the Nconfused isomer, changing the core/shell layer structures of hybrid MOFs allows for tuning of the visible-to-near-infrared (NIR) absorption/emission characters, excited-state energy migrations, and photosensitization capabilities. The Forster energy transfer event occurring in the bulk MOF samples by photoexcitation enabled us to control the photoinduced singlet oxygen generation through the comprehensive light-harvesting ability of these hybrid porphyrinic MOFs. Therefore, implementation of a precisely designed porphyrin "substitute" into the MOF-based materials indeed provides a new mimic of the photosynthetic pigment system and should be potentially applicable for solar-light-driven devices.

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The cruise control of high-speed trains is challenging due to the presence of time-varying air resistance coefficients and control constrains. Because the resistance coefficients for high-speed trains are not accurately known and will change with the actual operating environment, the precision of high speed train model is lower. In order to ensure the safe and effective operation of the train, the operating conditions of the train must meet the safety constraints. The most traditional cruise control methods are PID control, model predictive control, and so on, in which the high-speed train model is identified offline. However, the traditional methods typically suffer from performance degradations in the presence of time-varying resistance coefficients. In this paper, an adaptive model predictive control (MPC) method is proposed for cruise control of high-speed trains with time-varying resistance coefficients. The adaptive MPC is designed by combining an adaptive updating law for estimated parameters and a multiply constrained MPC for the estimated system. It is proved theoretically that, with the proposed adaptive MPC, the high-speed trains track the desired speed with ultimately bounded tracking errors, while the estimated parameters are bounded and the relative spring displacement between the two neighboring cars is stable at the equilibrium state. Simulations results validate that proposed method is better than the traditional model predictive control.

The remaining useful life estimation has been widely studied for engineering systems. A system commonly works under varying operating conditions, which may affect the system degradation trajectory differently and consequently reduce the accuracy of remaining useful life estimation. In this paper, we propose CNN-XGB with extended time window to tackle this issue. Firstly, the extended time window is created by feature extension and time window processing in data preprocessing. In feature extension, multiple degradation features are extracted by an improved differential method, and these features are appended to the raw data as additional features. To make the time window cover more information for better prognostic accuracy, a time window padding method is used considering the problem of missing data in some samples. Secondly, a convolutional neural network architecture with multichannel 1 * 1 filter kernel is proposed considering the effect of varying operating conditions. Furthermore, to improve the prognostic robustness and avoid the sensitivity to the abnormal data, convolutional neural network and extreme gradient boosting are fused by model averaging (CNN-XGB). The validity of the proposed method is verified using aero-engine datasets from NASA.INDEX TERMS Neural networks, lifetime estimation, time series analysis, prognostics and health management.