Chronic sleep loss caused lots of health problems, also including cognition impairment. Tea is one of the most popular drinks when people stay up late. Nevertheless, the effects of tea on sleep deprivation-induced cognition impairment are still unclear. In the present study, we found 24-h sleep deprivation (S-DEP) increased membrane α-amino-3-hydroxy-5-methyl-4-isoxa-zolep-propionate (AMPA) receptor level through a tumor necrosis factor α (TNFα)-dependent pathway in hippocampi. Blocking elevated TNFα level can protect S-DEP mice from impaired learning ability according to behavioral test. Tea polyphenols, major active compounds in green tea, suppressed TNFα production through downregulating TNFα converting enzyme (TACE) level. Meanwhile, tea polyphenols treatment could ameliorate recognition impairment and anxiety-like behaviors in S-DEP mice. The aforementioned results demonstrate cognition protective effects of tea polyphenols in S-DEP mice model, which provide a theoretical basis for the treatments of S-DEP-induced cognition impairment by targeting the TACE/TNFα/AMPA pathway.
Smart grids, which possess flexibility, cleanliness, safety, economy, and friendliness, have drawn a lot of attention from all over the world in an era of rapid social and economic development, power technology change, and energy and environmental constraints. However, there are still issues with the design, installation, and operation of smart substations, such as insufficient LAN integration, difficulty quantifying network performance, and inability to keep track of communication. The basic meaning and key technologies of substation communication standards are used as the research object in this paper, and the basic attributes of substation data flow, such as source, type, and function, are qualitatively analyzed. The mathematical model that is most closely fitted is 2.8% more effective. The research object is the topology of the process bus. Through the comparison of various solutions, including star topology, ring topology, bus topology, and mesh topology, the advantages and disadvantages of each topology networking scheme are revealed along with the particular functional requirements of the substation process layer. Further discussion is given to the crucial topology-related technologies of network congestion and flow control.
Multiple inverters are connected to the distribution network with complex non-linear loads and may interact with the background harmonics in some cases. In addition to the parallel resonance caused by the harmonic current, the harmonic voltage also causes the series resonance. The matching of frequencies of the resonance voltage and current results in serious distortion of the grid-connected bus voltage waveform, or even threatens the stability of its operating point. A general method to analyze the network series and parallel resonance of multiple grid-connected inverters is yet to be proposed. In view of this, the authors provide an inverter model and an analytical method to traverse all the resonance points. Two typical control inverters were modelled under the transfer function model, and the defects of the traditional modal analysis method in traversing the series resonance were analyzed. Then, the authors propose to use an improved modal analysis method by adding virtual branches for resonance analysis. The obtained analytical results are consistent with the frequency sweeping results and simulation results, verifying the effectiveness of the proposed method. In order to prove the generality of the proposed method for traversing the series and parallel resonance of multiple grid-connected inverters, the inverter to suppress background harmonics of the grid voltage was incorporated into the multiple inverters network for case study. Using the improved modal analysis method to traverse the series and parallel resonance, the participation factor values of each node and loop under resonance mode were calculated. Finally, the proposed method was verified by hardware-in-the-loop simulation, and the result shows its universality.
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