A maximum selectivity of 65% was obtained for the mixed amino acids via one-step separation. These PAAILMs have the advantages of low operating pressure, high water flux, good antibacterial and antifouling properties, and excellent reusability, thereby indicating their potential for industrial application in the separation of l-phenylalanine and l-aspartic acid.Understanding the stability evolution of the silver nanoparticles (Ag NPs) in colloid has great benefits for its controllable preparation, storage and application. Herein, uncapped Ag NPs with diameter of 1.66 ± 0.37 nm are obtained by laser ablation of Ag target in deionized water, corresponding surface plasma resonance (SPR) bands, ζ potential and particle size distribution are monitored to investigate uncapped Ag NPs' stability evolution. Due to negatively charged surface, uncapped Ag NPs show an excellent dispersion stability in 70 days without any external disturbance. But its dispersion stability and structure stability are destroyed easily by an oscillation treatment, resulting in a tardy growth and the formation of one-dimensional Ag nanochain. In addition, the chemical stability of uncapped Ag NPs is dramatically varied by a displacement reaction with an inserted copper wire. As comparison, two typical cationic and anionic surfactant molecules, N-hexadecyl trimethyl ammonium chloride (CTAC) and sodium dodecyl benzene sulfonate (SDBS) are severally used to prepare surface capped Ag NPs. https://www.selleckchem.com/peptide/bulevirtide-myrcludex-b.html With same treatment of Ag colloid, both two kinds of capped Ag NPs display better dispersion stability and structure stability than uncapped Ag NPs. Moreover, CTAC capped Ag NPs keep a better chemical stability than SDBS capped Ag NPs.Though Center of Gravity (CoG) defuzzification is a well-known and long-standing method in the history of fuzzy systems, because of its computational complexity, its use in the field of modeling of fuzzy controllers is almost nil. From literature, it appears that modeling of fuzzy Proportional Integral Derivative (FPID) controllers is rarely attempted using CoG defuzzification. In fact, none of the FPID controller models are obtained using both two-dimensional input space and CoG defuzzification. The available mathematical models of fuzzy Proportional Integral (FPI) and fuzzy Proportional Derivative (FPD) controllers using two-dimensional input space and CoG defuzzification were due to Arun and Mohan (2017). In this paper, the authors make an attempt to model and design an FPID controller using two-dimensional input space and CoG defuzzification. The incremental control effort produced by the newly developed FPID controller is found by combining the individual control efforts produced by incremental FPI and incremental FPD controllers. The incremental FPI and incremental FPD controller structures are unveiled using two-dimensional input space, CoG defuzzification, Min t-norm, Max t-conorm, and Larsen Product (LP) inference. The applicability and usefulness of the newly obtained FPID controller are depicted with simulation and real-time experimentation.Initial positioning errors and the low adaptability of a priori digital elevation maps result in large positioning uncertainty intervals in the initial stage of terrain-aided navigation (TAN). This produces pseudo-peaks and mismatches in the initial position likelihood function and renders the convergence of the particle filter (PF) slow and unstable, while even causing divergence. Thus, the occurrence of the "kidnapped robot problem" is highly probable during the initial stage of TAN and is a scenario frequently faced by deep-sea and ultra-long-range underwater vehicles. In this study, a PF initialization method based on non-linear multi-terrain aided fusion position (NLMTP) is proposed to improve the stability and accuracy of TAN. NLMTP uses the terrain-aided position (TAP) information during the initial stage of TAN to estimate the high-precision probability distribution of the starting position via backward smoothing. Accordingly, a PF initialization method for non-Gaussian prior distribution probability is proposed to improve the convergence speed of the PF during the initial stage of underwater TAN. Finally, a performance comparison of PF initialized via the NLMTP, TAP confidence interval, and TERCOM methods was performed using the survey data obtained via onboard sensors. The experimental results show that NLMTP initialization improves the convergence speed and positioning accuracy of PF in the initial TAN phase; this improvement is clear in the low terrain-adaptability area.Quantitative and qualitative analysis of acoustic backscattered signals from the seabed bottom to the sea surface is used worldwide for fish stocks assessment and marine ecosystem monitoring. Huge amounts of raw data are collected yet require tedious expert labeling. This paper focuses on a case study where the ground truth labels are non-obvious echograms labeling, which is time-consuming and critical for the quality of fisheries and ecological analysis. We investigate how these tasks can benefit from supervised learning algorithms and demonstrate that convolutional neural networks trained with non-stationary datasets can be used to stress parts of a new dataset needing human expert correction. Further development of this approach paves the way toward a standardization of the labeling process in fisheries acoustics and is a good case study for non-obvious data labeling processes.This paper describes a model predictive control method for Nine-Switch Inverter (NSI)-based AC drive systems. Two separate three-phase AC loads (dual-output mode operation) or a single six-phase load (six-phase mode operation) can be connected to output terminals of an NSI. Three different Finite Control Set Model Predictive Control (FCS-MPC) strategies are presented and described. Firstly, dual-output mode FCS-MPC provides flexible control of detached load stages without any undesirable interaction. When disseminated loads are needed to be controlled, the output terminals of NSI are individually connected to separate load stages. Secondly, six-phase mode FCS-MPC provides robust control of six-phase load current. Thirdly, the predictive control scheme for controlling multiple induction machines is presented. Experimental and simulation tests have demonstrated that the proposed method exhibits a secured converter operation. The proposed predictive control strategies of Nine-Switch Inverter are accomplished using a Field Programmable Gate Arrays (FPGA).


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Last-modified: 2025-01-23 (木) 06:28:09 (20d)