As power to gas (P2G) technology gradually matures, the coupling between electricity networks and natural gas networks should ideally evolve synergistically. With the intent of characterizing market behaviors of integrated electric power and natural gas networks (IPGNs) with P2G facilities, this paper establishes a steady-state model of P2G and constructs optimal dispatch models of an electricity network and a natural gas network separately. In addition, a concept of slack energy flow (SEF) is proposed as a tool for coordinated optimal dispatch between the two networks. To study how the market pricing mechanism affects coordinated optimal dispatch in an IPGN, a market equilibrium-solving model for an IPGN is constructed according to game theory, with a solution based on the Nikaido-Isoda function. Case studies are conducted on a joint model that combines the modified IEEE 118-node electricity network and the Belgian 20-node gas network. The results show that if the game between an electric power company and a natural gas company reaches market equilibrium, not only can both companies maximize their profits, but also the coordinated operation of the coupling units, i.e., gas turbines and P2G facilities, will contribute more to renewable energy utilization and carbon emission reduction.Keywords Integrated electric power and natural gas networks (IPGNs), Market equilibrium, Power to gas (P2G), Slack energy flow (SEF)

Background Coronavirus disease 2019 (COVID-19) causes a global pandemic and has devastating effects around the world, however, there are no specific antiviral drugs and vaccines for the constant mutation of SARS-CoV-2. Purpose In this study, we evaluted the antiviral and anti-inflammatory activities of Liushen Capsules (LS) on different novel coronavirus in vitro, studied its therapeutic effects on novel SARS-CoV-2 infected mice and observed the LS’s clinical efficacy and safety in COVID-19. Methods The antiviral and aiti-inflammatory effects of LS on the 501Y.V2/B.1.35 and G/478K.V1/ B.1.617.2 strains were determined in vitro. A hACE2 mouse model of novel SARS-CoV-2 pneumonia was established. Survival rates, histological changes, inflammatory markers, lung virus titers and the expression of the key proteins in the NF-κB/MAPK signaling pathway was detected by western blotting and immumohistochemical staining in the lungs were measured. Subsequently, the disease duration, prognosis of disease, time of negative nucleic acid and the cytokines levels in serum were used to assess the efficacy of treatment with LS in patients. Results The results showed that LS (2, 1, 0.5 μg/mL) could significantly inhibit the replication of the two SARS-CoV-2 variants and the expression of pro-inflammatory cytokines (IL-6, IL-8, IP-10, CCL-5, MIP-1α, IL-1α) induced by the virus in vitro. As for the survival experiment in mice, the survival rate of virus group was 20%, while LS-treatment groups (40, 80, 160 mg/kg) could increase the survival rate to 60, 100 and 100%, respectively. LS (40, 80, 160 mg/kg) could significantly decrease the lung titers in mice and it could improve the pathological changes, inhibit the excessive inflammatory mediators (IFN-α, IFN-γ, IP-10, MCP-1) and the protein expression of p-NF-κB p65 in mice. Moreover, LS could significantly decrease SARS-CoV-2-induced activation of p-NF-κB p65, p-IκBα, and p-p38 MAPK and increase the protein expression of the IκBα. In addition, the patient got complete relief of symptoms after being treated with LS for 6 days and was proven with negative PCR test after being treated for 23 days. Finally, treatment with LS could reduce the release of inflammatory cytokines (IL-6, PDGF-AA/BB, Eotaxin, MCP-1, MIP-1α, MIP-1β, GRO, CCL-5, MCP-3, IP-10, IL-1α). Conclusion LS effectively alleviated novel SARS-CoV-2 or variants induced pneumonia in vitro and in vivo, and improved the prognosis of COVID-19. In light of the efficacy and safety profiles, LS could be considered for the treatment of COVID-19 with a broad-spectrum antiviral and anti-inflammatory agent.

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Background : Although severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and human coronavirus 229E (HCoV-229E) pose a huge threat to human public health, no specific treatment is available. Jinzhen granule (JZ) is a traditional eight ingredients-Chinese medicine with prominent efficacy for treating viral-induced diseases. However, little is known about the antiviral effect and mechanism of JZ against SARS-CoV-2 and HCoV-229E. Purpose : This study aimed to reveal the antiviral effects of JZ against SARS-CoV-2 and HCoV-229E, and to further explore the underlying mechanisms regulating the host immune response. Methods : The chromatographic separation of JZ was performed using a Shimadzu analytical high-performance liquid chromatograph with UV detection and Alltech ELSD 2000ES. We conducted cytopathic effect (CPE) and plaque reduction assays to evaluate the antiviral effect of JZ. A lethal human angiotensin converting enzyme 2 (hACE2) transgenic mouse model of SARS-CoV-2 was established to determine the protective effect of JZ on mortality and lung virus titers. Real-time quantitative PCR assays were used to analyze the expression of proinflammatory cytokines in vitro and in vivo. Western blotting was further performed to determine the activities on regulating the nuclear factor kappa B (NF-κB)/MAPK pathway. Finally, mitochondrial membrane potential assays, flow cytometry analysis and western blotting were used to assess the anti-apoptotic potency toward HCoV-229E infection. Results : The results showed that 13 chemical components were identified and five peaks were determined and quantitated (gallic acid 1.97 mg/g, baicalin 20.69 mg/g, glycyrrhizic acid 4.92 mg/g, hyodeoxycholic acid 4.86 mg/g, cholic acid 4.07 mg/g). We found that JZ exerted inhibitory potency against SARS-CoV-2 and HCoV-229E in vitro by using CPE and plaque reduction assays, and it was further found that JZ protected mice infected by SARS-CoV-2 from death and inhibited lung virus titers. JZ also significantly decreased the induction of inflammatory cytokines (IL-1α, IL-6, CCL-5 and MIP-1β), similar to the observed in vitro effect. Moreover, JZ suppressed the release of inflammatory cytokines in vitro and it decreased the protein expression of p-p38 MAPK, p-JNK, p-NF-κB p65 and p-IκBα induced by HCoV-229E and increased the expression of IκBα. Notably, JZ significantly protected HCoV-229E-infected Huh-7 cells from mitochondrial damage and decreased apoptotic cells. The activation of the mitochondria-mediated apoptotic pathway was inhibited by JZ, as shown by the reduced expression of cleaved caspase-9, caspase-3 and p-PARP. Conclusions : In conclusion, JZ (gallic acid 1.97 mg/g, baicalin 20.69 mg/g, glycyrrhizic acid 4.92 mg/g, hyodeoxycholic acid 4.86 mg/g, cholic acid 4.07 mg/g) exhibited antiviral activities against SARS-CoV-2 and HCoV-229E by regulating the NF-κB/MAPK pathway and the mitochondria-mediate...

Accurate state estimation is essential for the safe and reliable operation of lithium-ion batteries. However, the accuracy of the battery state estimation depends on the accuracy of the battery parameters. Because the state of charge (SOC) cannot be directly measured, estimation methods based on the Kalman filter are widely used. However, it is difficult to estimate SOC online and get high accuracy results. This article proposes a method for parameter identification and SOC estimation for lithium-ion batteries. Because the lithium-ion battery has slow-varying parameters (such as internal resistance, and polarization resistance), and the SOC has fast-varying characteristics, so a multi-scale multi-innovation unscented Kalman filter and extended Kalman filter (MIUKF-EKF) are used to perform online measurement of battery parameters and SOC estimation in this method. The battery parameters are estimated with a macro-scale, and the SOC is estimated with a micro-scale. This method can improve the estimation accuracy of the SOC in real-time. Results of experiments indicate that the algorithm has higher accuracy in online parameter identification and SOC estimation than in the dual extended Kalman filter (DEKF) algorithm.

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