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The effects of key parameters on locked mode induced disruption (LMiD) are investigated in EAST experiments. The experimental data for locked mode are collected from 2015 to 2022 when the externally applied resonant magnetic perturbation is successfully employed in EAST. In this dataset, ∼42% of the total shots are LMiD, while the remaining 58% are LM without disruption. To better analyze the LMiD, an intuitive physical process is proposed. The LMiD process can be divided into two stages, the evolution of magnetic islands and the loss of plasma stored energy. The LMiD can also be related to the evolution of the other 8 physical quantities. On the basis of this physical process analysis, the time scale and the influencing factors for LMiD are investigated using statistical analysis. It is found that the density (ne), the distance from the magnetic island outer boundary to the plasma last closed surface (dedge), the loop-voltage (Vloop), and the plasma core electron temperature (Te), which are consistent with the intuitive physical model, are key parameters to LMiD. In addition, other potentially important parameters, the relevant reasons, and statistical analysis on the parameter intervals where rapid disruption with greater harmfulness occurred have also been investigated.

While (oxy)hydroxides are effective oxygen evolution electrocatalysts, the impacts of pre-catalyst properties on catalyst activities are challenging to assess. Here, authors find Mo dopants in Ni-Fe (oxyhydroxides) to promote lattice oxygen participation and to boost oxygen evolution activities.

Honeycomb sandwich composite structures are widely used in various aircraft structures due to their unique performance. However, honeycomb sandwich composite structures are prone to lightning damage that threatens the structure safety. Therefore, it is necessary to assess the residual mechanical properties of honeycomb sandwich composite structures after a lightning strike. In this study, simulated lightning strike tests were first conducted for honeycomb sandwich panels with and without carbon nanotube film (CNTF) to obtain different damage scenarios and study the protection effect of CNTF. Then, the residual compressive strength of the panels with lightning strike damage was predicted using a progressive damage analysis method and verified with the experimental results. It was found that the numerical prediction results agree with the experimental results. The size and extent of lightning damage have an important effect on the compression damage mode of honeycomb sandwich panel with closed edges.

In modern tokamak experiments, scenarios with weak central magnetic shear has been proposed. It is necessary to study the Alfvenic mode activities in such scenarios. Theoretical researches have predicted the multiplicity of core-localized toroidally induced Alfvenic eigenmodes for ε/s > 1, where ε is the inverse aspect ratio and s is magnetic shear. We numerically investigate the existence of multiplicity of core-localized TAEs and mode characteristics using NOVA code in the present work. We firstly verify the existence of the multiplicity for zero beta plasma and the even mode at the forbidden zone. For finite beta plasma, the mode parities become more distinguishable, and the frequencies of odd modes are close to the upper tip of the continuum, while the frequencies of even modes are close to the lower tip of the continuum. Their frequencies are well separated by the forbidden zone. With the increasing value of ε/s, more modes with multiple radial nodes will appear, which is in agreement with theoretical prediction. The discrepancy between theoretical prediction and our numerical simulation is also discussed in the main text.

The secure location of node is significant in the WSN (Wireless Sensor Networks) of the troop frontier defence system. The wormhole attack is a big threat in the secure location. The credibility of the beacon node was used to determine the malicious nodes produced by wormhole attack in the WSN. The estimated method of multibeacon nodes was adopted to improve DV-HOP algorithm after excluding the malicious nodes. In this paper, we compared the basic DV-HOP algorithm and the improved DV-HOP algorithm in the coverage percentage and the error of network localization by simulating. The simulation results indicate that the improved DV-HOP algorithm makes the localization coverage percentage can reach 90% on a certain scale of the network, and it makes the error percentage lower when the number of beacons is different.

Purpose: Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease influenced by environmental triggers, including the commensal microbiota. Recent research has highlighted distinctive features of the gut microbiota in RA patients. This study investigates the therapeutic potential of berberine (BBR), a gut microbiota modulator known for its significant anti-RA effects, and elucidates the underlying mechanisms. Methods: Utilizing the collagen-induced arthritis (CIA) rat model, we comprehensively evaluated the anti-rheumatoid arthritis effects of BBR in vivo through various indices, such as paw edema, arthritis index, ankle diameter, inflammatory cytokine levels, pathological conditions, and micro-CT analysis. Employing network pharmacology, we identified potential targets involved in RA alleviation by BBR. To analyze comprehensive metabolic profiles and identify underlying metabolic pathways, we conducted a serum-based widely targeted metabolomics analysis utilizing LC-MS technology. An integrated network encompassing metabolomics and network pharmacology data was constructed using Cytoscape. The potential therapeutic targets and signaling pathways of BBR in the management of RA were predicted using network pharmacology. Key targets and pathways were further validated by molecular docking and immunofluorescent staining, which integrated findings from serum metabolomics and network pharmacology analysis. Additionally, we analyzed the gut microbiota composition in rats employing 16S rDNA sequencing and investigated the effects of BBR on the microbiota of CIA rats through bioinformatics and statistical methods. Results: Our results showed that BBR demonstrated significant efficacy in alleviating RA symptoms in CIA rats, as evidenced by improvements in paw redness and swelling, attenuation of bone and cartilage damage, reduction in synovial hyperplasia, inflammatory cell infiltration, and suppression of proinflammatory cytokines IL-1β, IL-6, IL-17A, and TNF-α. KEGG analysis highlighted the PI3K/AKT signaling pathway as a key mediator of BBR's anti-RA effects. Metabolomics profiling via LC-MS revealed 22 potential biomarkers. Arginine and proline metabolism, cutin, suberine and wax biosynthesis, glycine, serine and threonine metabolism and taurine and hypotaurine metabolism are the most related pathways of BBR anti-RA. Molecular docking studies corroborated high affinities between BBR and key targets. Furthermore, 16S analysis demonstrated BBR's capacity to modulate gut bacteria composition, including an increase in the abundance of Lachnoclostridium, Akkermansia, Blautia, Romboutsia, and Faecalibacterium genera, alongside a decrease in Prevotella_9 abundance in genus level. Integrated analysis underscored a strong correlation between serum microbiota and fecal metabolites. Conclusion: Our findings elucidate the multifaceted mechanisms underlying BBR's therapeutic efficacy in RA, involving inhibition of the PI3K/AKT pathway, modulation of intestinal flora, and regulation of host metabolites. These insights provide novel perspectives on BBR's role in RA management. [ABSTRACT FROM AUTHOR]