Human adipose-derived mesenchymal stem cells (hADMSCs) are a potential cell source for autologous cell therapy due to their regenerative ability. However, detailed cytological or phenotypic characteristics of these cells are still unclear. Therefore, we determined and compared cell size, morphology, ultrastructure, and immunohistochemical (IHC) expression profiles of isolated hADMSCs and cells located in human adipose tissues. We also characterized the localization of these cells in vivo. Light microscopy examination at low power revealed that hADMSCs acquired a spindle-shaped morphology after four passages. Additionally, high power views showed that these cells had various sizes, nuclear contours, and cytoplasmic textures. To further evaluate cell morphology, transmission electron microscopy was performed. hADMSCs typically had ultrastructural characteristics similar to those of primitive mesenchymal cells including a relatively high nuclear/cytosol ratio, prominent nucleoli, immature cytoplasmic organelles, and numerous filipodia. Some cells contained various numbers of lamellar bodies and lipid droplets. IHC staining demonstrated that PDGFR and CD10 were constitutively expressed in most hADMSCs regardless of passage number but expression levels of α-SMA, CD68, Oct4 and c-kit varied. IHC staining of adipose tissue showed that cells with immunophenotypic characteristics identical to those of hADMSCs were located mainly in the perivascular adventitia not in smooth muscle area. In summary, hADMSCs were found to represent a heterogeneous cell population with primitive mesenchymal cells that were mainly found in the perivascular adventitia. Furthermore, the cell surface markers would be CD10/PDGFR. To obtain defined cell populations for therapeutic purposes, further studies will be required to establish more specific isolation methods.

Objectives

A large scale energy storage system has become increasingly attractive and has been applied to various ancillary services. To serve energy for a longer time and to increase the profit of a multiple energy storages system, it should be operated considering each available energy source and the different efficiencies of the subordinate storages. This paper proposes a hierarchical control structure and three types of the power sharing methods for a multiple battery energy storages system. A maximum efficiency optimization method based on a piecewise linearized Lagrangian equation is suggested. In addition, a usable energy sharing algorithm is proposed to distribute the output power evenly according to the available energy of each battery. To improve the system availability, a combination algorithm that selects the appropriate control according to the situation is also proposed. The improvement in energy efficiency of the proposed methods is verified with a duty cycle test of Pacific Northwest National Laboratory by PSCAD/EMTDC.

Direct Current (DC) microgrids are expected to become larger due to the rapid growth of DC energy sources and power loads. As the scale of the system expends, the importance of voltage control will be increased to operate power systems stably. Many studies have been performed on voltage control methods in a DC microgrid, but most of them focused only on a small scale microgrid, such as a building microgrid. Therefore, a new control method is needed for a middle or large scale DC microgrid. This paper analyzes voltage drop problems in a large DC microgrid and proposes a cooperative voltage control scheme with a distributed generator (DG) and a grid connected converter (GCC). For the voltage control with DGs, their location and capacity should be considered for economic operation in the systems. Accordingly, an optimal DG allocation algorithm is proposed to minimize the capacity of a DG for voltage control in DC microgrids. The proposed methods are verified with typical load types by a simulation using MATLAB and PSCAD/EMTDC.

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In this study, domestic and foreign contributions to a severe PM2.5 episode in South Korea, in which “emergency reduction measures against particulate matter” were issued, were analyzed. During the period between 27 February and 7 March in 2019 when high PM2.5 concentrations occurred, the PM2.5 concentration in the Seoul metropolitan area (SMA) in South Korea was approximately 87.3 μg/m3 on average, and a severe PM2.5 concentration level of approximately 113.4 μg/m3 was observed between 3 March and 5 March. The results of the analysis conducted using the HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) model and meteorological observation data showed that northwesterly wind or westerly winds were formed during the P1 and P3 periods when the PM2.5 concentration markedly increased. When the PM2.5 concentrations in East Asia were simulated using the Community Multiscale Air Quality (CMAQ), it was found that the high PM2.5 concentrations that occurred in the SMA of South Korea were mostly affected by PM2.5 transported over long distances and following atmospheric stagnation. When the domestic and foreign contributions were evaluated using the brute-force method (BFM), the foreign and domestic contribution concentrations were found to be 62.8 and 16.8 μg/m3, respectively, during the target period of this study. It was also found that the foreign contribution was 78.8%, while the domestic contribution was 21.2%.

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