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Big data is a valuable resource for the Internet education platform. Big data mining is an important technology for Internet education platforms to provide personalized services for learners [1-3]. Using big data related technology to explore the inherent rules among students, teachers, courses and grades can provide reference for decision-makers of education and teaching, and can also provide guidance for the school’s teaching tasks and teaching plans [4, 5]. This paper briefly introduces the concept of data mining and personalized teaching, and studies the application of data mining technology in the personalized teaching of Internet education platform, in order to improve the school’s teaching management level and students’ academic performance.

The aerosol–planetary boundary layer (PBL) interaction was proposed as an important mechanism to stabilize the atmosphere and exacerbate surface air pollution. Despite the tremendous progress made in understanding this process, its magnitude and significance still have large uncertainties and vary largely with aerosol distribution and meteorological conditions. In this study, we focus on the role of aerosol vertical distribution in thermodynamic stability and PBL development by jointly using micropulse lidar, sun photometer, and radiosonde measurements taken in Beijing. Despite the complexity of aerosol vertical distributions, cloud-free aerosol structures can be largely classified into three types: well-mixed, decreasing with height, and inverse structures. The aerosol–PBL relationship and diurnal cycles of the PBL height and PM2.5 associated with these different aerosol vertical structures show distinct characteristics. The vertical distribution of aerosol radiative forcing differs drastically among the three types, with strong heating in the lower, middle, and upper PBL, respectively. Such a discrepancy in the heating rate affects the atmospheric buoyancy and stability differently in the three distinct aerosol structures. Absorbing aerosols have a weaker effect of stabilizing the lower atmosphere under the decreasing structure than under the inverse structure. As a result, the aerosol–PBL interaction can be strengthened by the inverse aerosol structure and can be potentially neutralized by the decreasing structure. Moreover, aerosols can both enhance and suppress PBL stability, leading to both positive and negative feedback loops. This study attempts to improve our understanding of the aerosol–PBL interaction, showing the importance of the observational constraint of aerosol vertical distribution for simulating this interaction and consequent feedbacks.

Objective To explore the complex interactions between gut microbiota and immune cell phenotypes in rheumatoid arthritis development and identify potential therapeutic targets within the gut microbiota–immune cell axis. Methods We conducted a Mendelian randomization analysis to explore the causal relationship between gut microbiota and rheumatoid arthritis, including the role of immune cell mediators. Sensitivity analyses assessed pleiotropy and heterogeneity, while mediation analysis identified pathways through which immune cells mediate gut microbiota effects on rheumatoid arthritis development. Key microbial taxa and their effects on rheumatoid arthritis were quantified. Results Our analysis identified 27 gut microbiota taxa significantly associated with rheumatoid arthritis, with Provencibacterium massiliense showing the strongest protective effect (odds ratio = 0.807, 95% confidence interval: 0.700–0.911, P = 0.003). Additionally, 20 immune cell phenotypes with IgD+ CD38dim AC were significantly linked to rheumatoid arthritis (odds ratio = 1.064, 95% confidence interval: 1.027–1.102). Mediation analysis uncovered 13 significant gut microbiota–immune cell pathways, with the UBA8517–CCR2 monocyte pathway mediating 10.1% of the total effect (beta1 = −0.595, beta12 = 0.027, mediation proportion = 10.1%). Conclusion This study offers novel insights into the gut microbiota–immune cell axis in rheumatoid arthritis, identifying Provencibacterium massiliense, IgD+ CD38dim AC and the UBA8517—CCR2 monocyte pathway as potential therapeutic targets for rheumatoid arthritis treatment.

To reduce energy consumption or improve energy efficiency, the regenerative devices recently have drawn the public’s eyes. In this paper, a novel hydraulic energy-regenerative shock absorber (HERSA) is developed for vehicle suspension to regenerate the vibration energy which is dissipated by conventional viscous dampers into heat waste. At first, the schematic of HERSA is presented and a mathematic model is developed to describe the characteristic of HERSA. Then the parametric sensitivity analysis of the vibration energy is expounded, and the ranking of their influences is k1≫m2>m1>k2≈cs. Besides, a parametric study of HERSA is adopted to research the influences of the key parameters on the characteristic of HERSA. Moreover, an optimization of HERSA is carried out to regenerate more power as far as possible without devitalizing the damping characteristic. To make the optimization results more close to the actual condition, the displacement data of the shock absorber in the road test is selected as the excitation in the optimization. The results show that the RMS of regenerated energy is up to 107.94 W under the actual excitation. Moreover it indicates that the HERSA can improve its performance through the damping control.

Background As a country with one-fifth of the global population, China has experienced explosive growth in ischaemic stroke (IS) burden with significant ethnic and geographic disparities. The aim of this study was to examine the differences in potentially modifiable risk factors for ischaemic stroke among the Han population and two ethnic minorities (Tujia and Miao). Methods A case-control study was conducted with 324 cases of first-ever ischaemic stroke from the hospitals of the Xiangxi Tujia and Miao Autonomous Prefecture and 394 controls from communities covering the same area between May 1, 2018, and April 30, 2019. Structured questionnaires were administered, and physical examinations were performed in the same manner for cases and controls. Univariate and multivariate logistic regression analyses with adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were used to examine the association between risk factors and ischaemic stroke. An additive model was used to study the interaction between the modifiable risk factors and ethnicity with R software. Results Higher high-sensitivity C-reactive protein levels (OR 50.54, 95%CI 29.76–85.85), higher monthly family income (4.18, 2.40–7.28), increased frequency of hot pot consumption (2.90, 1.21–6.93), diabetes mellitus (2.62, 1.48–4.62), a higher apolipoprotein (Apo)B/ApoA1 ratio (2.60, 1.39–4.85), hypertension (2.52, 1.45–4.40) and moderate-intensity physical activity (0.50, 0.28–0.89) were associated with ischaemic stroke. There was an additive interaction between the ApoB/ApoA1 ratio and ethnicity in the Tujia and Miao populations with first-ever ischaemic stroke (the relative excess risk due to the interaction was 5.75, 95% CI 0.58 ~ 10.92; the attributable proportion due to the interaction was 0.65, 95% CI 0.38 ~ 0.91; the synergy index was 3.66, 95% CI 1.35 ~ 9.93). Conclusions This is the first case-control study examining modifiable risk factors for ischaemic stroke among the Han population and two ethnic minorities (Tujia and Miao) in China. Some differences were observed in the impact of risk factors among these ethnic groups. Our results may help interpret health-related data, including surveillance and research, when developing strategies for stroke prevention.

China has had explosive growth in ischemic stroke (IS) burden with significant ethnic and geographic disparities. The aim of this study was to explore the possible combination effect between gut microbiota and traditional potentially modifiable risk factors for IS among two ethnic minorities (Tujia and Miao) and the Han population. Herein, we first used the 16 S rRNA sequencing to compare the gut microbial compositions of 82 patients with first-ever IS vs. 82 normal controls (NCs) among Han, Tujia, and Miao people between 1 May 2018 and 30 April 2019, from Xiangxi Tujia and Miao Autonomous Prefecture in China. An additive model was used to study the interaction between traditional risk factors and gut microbiota with R software. Linear discriminant analysis (LDA) and LDA effect size (LEfSe) results showed that the identified key gut microbiota's taxonomic composition varied in different ethnicity between the IS patients and NCs. Furthermore, families Lactobacillaceae, Enterococcaceae, Streptococcaceae , and Enterobacteriaceae were found to be positively correlated with high-risk factors and negatively correlated with preventive factors in the IS patients, but families Ruminococcaceae and Lachnospiraceae were just the opposite in the NCs. There were additive interactions between traditional risk factors (systolic blood pressure, diastolic blood pressure, and high-sensitive C-reactive protein) and family Enterococcaceae for first-ever IS with the attributable proportion due to the interaction was 0.74, 0.71, and 0.85, respectively; and the synergy index was 4.45, 3.78, and 7.01, respectively. This preliminary but promising study showed that the gut microbiota disturbances may potentially interact to IS with different ethnic host's traditional risk factors.

Solid stress, originating from rigid and elastic components of extracellular matrix and cells, is a typical physical hallmark of tumors. Mounting evidence indicates that elevated solid stress drives metastasis and affects prognosis. However, the molecular mechanism of how cancer cells sense solid stress, thereby exacerbating malignancy, remains elusive. In this study, our clinical data suggest that elevated stress in metastatic solid tumors is highly associated with the expression of cytoskeleton-associated protein 4 (CKAP4). Intriguingly, CKAP4, as a sensitive intracellular mechanosensor, responds specifically to solid stress in a subset of studied tumor micro-environmental elements through liquid–liquid phase separation. These micron-scaled CKAP4 puncta adhere tightly onto microtubules and dramatically reorchestrate their curvature and branching to enhance cell spreading, which, as a result, boosts cancer cell motility and facilitates distant metastasis in vivo. Mechanistically, the intrinsically disordered region 1 (IDR1) of CKAP4 binds to microtubules, while IDR2 governs phase separation due to the Ca v 1.2-dependent calcium influx, which collectively remodels microtubules. These findings reveal an unprecedented mechanism of how cancer cells sense solid stress for cancer malignancy and bridge the gap between cancer physics and cancer cell biology.

Light detection and ranging (lidar) measurements have been widely used to profile the ambient aerosol extinction coefficient (σext). The particle extinction-to-backscatter ratio (lidar ratio, LR), which strongly depends on the aerosol dry particle number size distribution (PNSD) and aerosol hygroscopicity, is introduced to retrieve the σext profile from elastic-backscatter lidar signals. Conventionally, a constant column-integrated LR that is estimated from aerosol optical depth is used by the retrieving algorithms. In this paper, the influences of aerosol PNSD, aerosol hygroscopic growth and relative humidity (RH) profiles on the variation in LR are investigated based on the datasets from field measurements in the North China Plain (NCP). Results show that LR has an enhancement factor of 2.2 when RH reaches 92 %. Simulation results indicate that both the magnitude and vertical structures of the σext profiles by using the column-related LR method are significantly biased from the original σext profile. The relative bias, which is mainly influenced by RH and PNSD, can reach up to 40 % when RH at the top of the mixed layer is above 90 %. A new algorithm for retrieving σext profiles and a new scheme of LR enhancement factor by RH in the NCP are proposed in this study. The relative bias between the σext profile retrieved with this new algorithm and the ideal true value is reduced to below 13 %.

Determination of cloud condensation nuclei (CCN) number concentrations at cloud base is important to constrain aerosol–cloud interactions. A new method to retrieve CCN number concentrations using backscatter and extinction profiles from multiwavelength Raman lidars is proposed. The method implements hygroscopic enhancements of backscatter and extinction with relative humidity to derive dry backscatter and extinction and humidogram parameters. Humidogram parameters, Ångström exponents, and lidar extinction-to-backscatter ratios are then linked to the ratio of CCN number concentration to dry backscatter and extinction coefficient (ARξ). This linkage is established based on the datasets simulated by Mie theory and κ-Köhler theory with in-situ-measured particle size distributions and chemical compositions. CCN number concentration can thus be calculated with ARξ and dry backscatter and extinction. An independent theoretical simulated dataset is used to validate this new method and results show that the retrieved CCN number concentrations at supersaturations of 0.07 %, 0.10 %, and 0.20 % are in good agreement with theoretical calculated values. Sensitivity tests indicate that retrieval error in CCN arises mostly from uncertainties in extinction coefficients and RH profiles. The proposed method improves CCN retrieval from lidar measurements and has great potential in deriving scarce long-term CCN data at cloud base, which benefits aerosol–cloud interaction studies.

Hypersensitive cell death, a form of avirulent pathogen-induced programmed cell death (PCD), is one of the most efficient plant innate immunity. However, its regulatory mechanism is poorly understood. AtLSD1 is an important negative regulator of PCD and only two proteins, AtbZIP10 and AtMC1, have been reported to interact with AtLSD1. To identify a novel regulator of hypersensitive cell death, we investigate the possible role of plant LITAF domain protein GILP in hypersensitive cell death. Subcellular localization analysis showed that AtGILP is localized in the plasma membrane and its plasma membrane localization is dependent on its LITAF domain. Yeast two-hybrid and pull-down assays demonstrated that AtGILP interacts with AtLSD1. Pull-down assays showed that both the N-terminal and the C-terminal domains of AtGILP are sufficient for interactions with AtLSD1 and that the N-terminal domain of AtLSD1 is involved in the interaction with AtGILP. Real-time PCR analysis showed that AtGILP expression is up-regulated by the avirulent pathogen Pseudomonas syringae pv. tomato DC3000 avrRpt2 (Pst avrRpt2) and fumonisin B1 (FB1) that trigger PCD. Compared with wild-type plants, transgenic plants overexpressing AtGILP exhibited significantly less cell death when inoculated with Pst avrRpt2, indicating that AtGILP negatively regulates hypersensitive cell death. These results suggest that the LITAF domain protein AtGILP localizes in the plasma membrane, interacts with AtLSD1, and is involved in negatively regulating PCD. We propose that AtGILP functions as a membrane anchor, bringing other regulators of PCD, such as AtLSD1, to the plasma membrane. Human LITAF domain protein may be involved in the regulation of PCD, suggesting the evolutionarily conserved function of LITAF domain proteins in the regulation of PCD.