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Tick-borne Encephalitis (TBE) is a zoonotic disease caused by the Tick-borne Encephalitis virus (TBEV), which affects the central nervous system of both humans and animals. Currently, there is no specific therapy for patients with TBE, with symptomatic treatment being the primary approach. In this study, the effects of minocycline (MIN), which is a kind of tetracycline antibiotic, on TBEV propagation and cellular protection in TBEV-infected cell lines were evaluated. Indirect immunofluorescence, virus titers, and RT-qPCR results showed that 48 h post-treatment with MIN, TBEV replication was significantly inhibited in a dose-dependent manner. In addition, the inhibitory effect of MIN on different TBEV multiplicities of infection (MOIs) in Vero cells was studied. Furthermore, the transcriptomic analysis and RT-qPCR results indicate that after incubation with MIN, the levels of TBEV and CALML4 were decreased, whereas the levels of calcium channel receptors, such as RYR2 and SNAP25, were significantly increased. MIN also regulated MAPK-ERK-related factors, including FGF2, PDGFRA, PLCB2, and p-ERK, and inhibited inflammatory responses. These data indicate that administering MIN to TBEV-infected cells can reduce the TBEV level, regulate calcium signaling pathway-associated proteins, and inhibit the MAPK-ERK signaling pathway and inflammatory responses. This research offers innovative strategies for the advancement of anti-TBEV therapy.

Gas hydrate has gradually become a new potential energy resource. However, some engineering and environmental problems related to the mechanical properties of gas hydrate-bearing sediments (GHBS) during gas recovery may occur. Many studies have been carried out on the basic mechanical properties of GHBS samples based on laboratory tests, but their evolution characteristics and suitable models require further research. Based on a series of data analyses of published laboratory experimental results on GHBS samples with different hydrate saturations under various confining pressures, the evolution characteristics of strength and dilation parameters were investigated. It was found that cohesion (c) increases quickly to a peak value and then decreases gradually to a residual value with an increasing plastic shear strain, and the samples with higher hydrate saturations have higher initial values, peak values, and residual values of cohesion (c). The internal friction angle (φ) increases quickly with increasing plastic shear strain and then becomes stable at a residual value for all the samples with different hydrate saturations. The dilation angle (ψ) increases from negative to positive values with increasing plastic shear strain and then becomes stable at a residual value. These characteristics are likely to be related to the compaction occurring at the early stage of compression before expansion due to dilation. In this paper, a non-linearly fitted model is proposed considering the evolution of the mechanical parameters, and the verification tests show that the proposed model can simulate the stress–strain behaviors of the GHBS samples well. This model is also adopted in the stability analysis of submarine slopes containing hydrate reservoirs. The analytical approach is developed, accompanied by the strength reduction method.

Smart hydrogels possess both intelligent and responsive properties, which are designed to exhibit specific responses to external stimuli such as changes in temperature, pH, or the presence of specific ions/counterions, making them “smart” or “responsive” materials [...]

For the problem that rolling bearing fault characteristics are difficult to extract accurately and the fault diagnosis accuracy is not high, an unsupervised characteristic selection method of refined composite multiscale fluctuation-based dispersion entropy (RCMFDE) combined with self-paced learning and low-redundant regularization (SPLR) is proposed, for which the fault diagnosis is carried out by support vector machine (SVM) optimized by the marine predator algorithm (MPA). First, we extract the entropy characteristics of the bearings under different fault states by RCMFDE and the introduction of the fine composite multiscale coarse-grained method and fluctuation strategy improves the stability and estimation accuracy of the bearing characteristics; then, a novel dimensionality-reduction method, SPLR, is used to select better entropy characteristics, and the local flow structure of the fault characteristics is preserved and the redundancy is constrained by two regularization terms; finally, using the MPA-optimized SVM classifier by combining Levy motion and Eddy motion strategies, the preferred RCMFDE is fed into the MPA–SVM model for fault diagnosis, for which the obtained bearing fault diagnosis accuracy is 97.67%. The results show that the RCMFDE can effectively improve the stability and accuracy of the bearing characteristics, the SPLR-based low-dimensional characteristics can suppress the redundancy characteristics and improve the effectiveness of the characteristics, and the MPA-based adaptive SVM model solves the parameter randomness problem and, therefore, the proposed method has outstanding superiority.

Global warming and land-use change affects runoff in the regional basin. Affected by different factors, such as abundant rainfall and increased impervious surface, the Taihu basin becomes more vulnerable to floods. As a result, a future flood risk analysis is of great significance. This paper simulated the land-use expansion and analyzed the surface change from 2020 to 2050 using the neural network Cellular Automata Markov (CA-Markov) model. Moreover, the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) dataset was corrected for deviation and used to analyze the climate trend. Second, the verified SWAT model was applied to simulate future runoff and to analyze the future flood risk. The results show that (1) land use is dominated by cultivated land and forests. In the future, the area of cultivated land will decrease and construction land will expand to 1.5 times its present size. (2) The average annual precipitation and temperature will increase by 1.2% and 1.5 degrees from 2020 to 2050, respectively. During the verified period, the NSE and r-square values of the SWAT model are greater than 0.7. (3) Compared with the historical extreme runoff, the extreme runoff in the return period will increase 10%~25% under the eight climate models in 2050. In general, the flood risk will increase further under the climate scenarios.

Polymer foams are promising for sound absorption applications. In order to process an industrial product, a series of polystyrene (PS) composite foams were prepared by continuous extrusion foaming assisted by supercritical CO2. Because the cell size and cell density were the key to determine the sound absorption coefficient at normal incidence, the bio-resource lignin was employed for the first time to control the cellular structure on basis of hetero-nucleation effect. The sound absorption range of the PS/lignin composite foams was corresponding to the cellular structure and lignin content. As a result, the maximum sound absorption coefficient at normal incidence was higher than 0.90. For a comparison, multiwall carbon nanotube (MWCNT) and micro graphite (mGr) particles were also used as the nucleation agent during the foaming process, respectively, which were more effective on the hetero-nucleation effect. The mechanical property and thermal stability of various foams were measured as well. Lignin showed a fire retardant effect in PS composite foam.

Measuring the absolute calibration constant is crucial for the radiometric calibration of synthetic aperture radar (SAR) systems. However, it is expensive to monitor the calibration constant continuously using manmade calibrators, and it is regionally restricted using the rainforest as the calibration field. In this study, the stability of SAR backscattering for common objects on the earth surface was analyzed, expecting to find the stable backscattering feature that could be used for maintaining absolute radiometric calibration. A database was established using Sentinel-1 dataset, and a classification model based on neural networks was proposed to extract the image slices of proper objects. Based on these, a temporal stable backscattering feature with a standard deviation of 0.19 dB was obtained from urban areas, and it was proved to be even more stable than the rainforest. Finally, the calibration scheme was given using this stable feature as a reference, which provided a new means of monitoring the SAR radiometric calibration constant.