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Digital technology is reshaping and enrich the types of social risks, making the lack of sense of security a widespread phenomenon. The predictors and enhancement strategies for the sense of security have drawn academic attention. However, there is still a debate on the relative effects of objective life experience and media construction on sense of security and how these influences evolve over time. Therefore, this study empirically examines the impact of digital media use and real-life experiences and their evolving mechanisms. This study based on data from CSS in 2013, 2017, and 2021, explored the impact and evolution of life experiences and digital inclusion on sense of security from the perspectives of experiential shaping and media construction. Results indicate that negative life experiences have a significant negative impact on sense of security, which first decreases but then increases over time. Digital inclusion also has a significant negative impact on sense of security, and this trend diminishes over time. Moreover, the results of relative importance show that despite digital inclusion's growing explanatory power, life experiences remain dominant, which means the current level of digital inclusion still cannot shake the decisive role of personal experiences. The educational differences in the impact of digital inclusion on sense of security suggest that education and digital literacy can mitigate the negative effects of digital inclusion, potentially turning them into positive influences. The findings indicate that in the process of digital society risk governance, it is also necessary to closely monitor the real-life domains of the public in order to achieve risk governance in both online and offline spaces.

Based on activity theory, this paper employed data from the 2013, 2015, and 2018 waves of the China Health and Retirement Longitudinal Survey, and adopted Hierarchical Linear Modeling and longitudinal mediation analysis to explore the temporal variation characteristics of loneliness and the influence of social participation on loneliness in Chinese Older Adults, as well as the mechanism of them. The study found that loneliness among older adults overall was at a moderate level from 2013 to 2018 and increased over time, which may be related to decreasing social participation from year to year. Decreased social participation was associated with increased loneliness over time (β = −0.060, p < 0.001) and lower social support (β = 0.109, p < 0.001), which was associated with more loneliness (β = −0.098, p < 0.001). In addition, social support played a significant mediating role in the realization of social participation in alleviating loneliness. Social participation can not only directly reduce loneliness, but also reduce loneliness by increasing social support.

Along with the development of information technology and innovation of teaching and learning methods, visual elements, such as images and graphics, being an indispensable method of representing and conveying knowledge, have become important components of digital teaching. However, without appropriate design of visual presentation, visual elements cannot authentically improve the efficiency and effectiveness of knowledge communication. The study emphasizes on the necessity of proper visual presentation design in digital foreign language teaching (DFLT) from the perspectives of second language acquisition and other theories, hoping to improve the efficiency of DFLT in modern teaching context.

Continuous evolution of Omicron has led to a rapid and simultaneous emergence of numerous variants that display growth advantages over BA.5 (ref. 1 ). Despite their divergent evolutionary courses, mutations on their receptor-binding domain (RBD) converge on several hotspots. The driving force and destination of such sudden convergent evolution and its effect on humoral immunity remain unclear. Here we demonstrate that these convergent mutations can cause evasion of neutralizing antibody drugs and convalescent plasma, including those from BA.5 breakthrough infection, while maintaining sufficient ACE2-binding capability. BQ.1.1.10 (BQ.1.1 + Y144del), BA.4.6.3, XBB and CH.1.1 are the most antibody-evasive strains tested. To delineate the origin of the convergent evolution, we determined the escape mutation profiles and neutralization activity of monoclonal antibodies isolated from individuals who had BA.2 and BA.5 breakthrough infections 2 , 3 . Owing to humoral immune imprinting, BA.2 and especially BA.5 breakthrough infection reduced the diversity of the neutralizing antibody binding sites and increased proportions of non-neutralizing antibody clones, which, in turn, focused humoral immune pressure and promoted convergent evolution in the RBD. Moreover, we show that the convergent RBD mutations could be accurately inferred by deep mutational scanning profiles 4 , 5 , and the evolution trends of BA.2.75 and BA.5 subvariants could be well foreseen through constructed convergent pseudovirus mutants. These results suggest that current herd immunity and BA.5 vaccine boosters may not efficiently prevent the infection of Omicron convergent variants. Convergent mutations in hotspots of the SARS-CoV-2 Omicron receptor-binding domain can cause immune evasion and maintain sufficient ACE2-binding capability.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron sublineages BA.2.12.1, BA.4 and BA.5 exhibit higher transmissibility than the BA.2 lineage 1 . The receptor binding and immune-evasion capability of these recently emerged variants require immediate investigation. Here, coupled with structural comparisons of the spike proteins, we show that BA.2.12.1, BA.4 and BA.5 (BA.4 and BA.5 are hereafter referred collectively to as BA.4/BA.5) exhibit similar binding affinities to BA.2 for the angiotensin-converting enzyme 2 (ACE2) receptor. Of note, BA.2.12.1 and BA.4/BA.5 display increased evasion of neutralizing antibodies compared with BA.2 against plasma from triple-vaccinated individuals or from individuals who developed a BA.1 infection after vaccination. To delineate the underlying antibody-evasion mechanism, we determined the escape mutation profiles 2 , epitope distribution 3 and Omicron-neutralization efficiency of 1,640 neutralizing antibodies directed against the receptor-binding domain of the viral spike protein, including 614 antibodies isolated from people who had recovered from BA.1 infection. BA.1 infection after vaccination predominantly recalls humoral immune memory directed against ancestral (hereafter referred to as wild-type (WT)) SARS-CoV-2 spike protein. The resulting elicited antibodies could neutralize both WT SARS-CoV-2 and BA.1 and are enriched on epitopes on spike that do not bind ACE2. However, most of these cross-reactive neutralizing antibodies are evaded by spike mutants L452Q, L452R and F486V. BA.1 infection can also induce new clones of BA.1-specific antibodies that potently neutralize BA.1. Nevertheless, these neutralizing antibodies are largely evaded by BA.2 and BA.4/BA.5 owing to D405N and F486V mutations, and react weakly to pre-Omicron variants, exhibiting narrow neutralization breadths. The therapeutic neutralizing antibodies bebtelovimab 4 and cilgavimab 5 can effectively neutralize BA.2.12.1 and BA.4/BA.5, whereas the S371F, D405N and R408S mutations undermine most broadly sarbecovirus-neutralizing antibodies. Together, our results indicate that Omicron may evolve mutations to evade the humoral immunity elicited by BA.1 infection, suggesting that BA.1-derived vaccine boosters may not achieve broad-spectrum protection against new Omicron variants. Biochemical and structural studies of the interactions between antibodies and spike proteins from SARS-CoV-2 Omicron subvariants indicate how these variants have evolved to escape antibody-mediated neutralization.

Background Regional citrate anticoagulation (RCA) is a widely used strategy for continuous renal replacement therapy (CRRT). Most of the current guidelines recommend liver failure as one of the contraindications for citrate anticoagulation. However, some studies suggested that the use of citrate for CRRT in liver failure patients did not increase the risk of citrate-related complications. The purpose of this systematic review is to summarize the current evidences on the safety and efficacy of RCA for CRRT in liver failure patients. Methods We performed a comprehensive search on PubMed, Embase, and the Cochrane Library databases from the inception to March 1, 2018. Studies enrolled adult (age > 18 years) patients with various levels of liver dysfunction underwent RCA-CRRT were included in this systematic review. Results After the study screening, 10 observational studies with 1241 liver dysfunction patients were included in this systematic review. The pooled rate of citrate accumulation and bleeding was 12% [3%, 22%] and 5% [2%, 8%], respectively. Compared with the baseline data, the serum pH, bicarbonate, and base excess (BE), the rate of metabolic alkalosis, the serum ionized calcium (ionCa) and total calcium (totCa) level, and the ratio of total calcium/ionized calcium (totCa/ionCa) significantly increased at the end of observation. However, no significant increase was observed in serum citrate (MD − 65.82 [− 194.19, 62.55]), lactate (MD 0.49 [− 0.27, 1.26]) and total bilirubin concentration (MD 0.79 [− 0.70, 2.29]) at the end of CRRT. Compared with non-liver failure patients, the live failure patients showed no significant difference in the pH (MD − 0.04 [− 0.13, 0.05]), serum lactate level (MD 0.69 [− 0.26, 1.64]), and totCa/ionCa ratio (MD 0.03 [− 0.12, 0.18]) during CRRT. The median of mean filter lifespan was 55.9 h, with a range from 22.7 to 72 h. Conclusions Regional citrate anticoagulation seems to be a safe anticoagulation method in liver failure patients underwent CRRT and could yield a favorable filter lifespan. Closely monitoring the acid base status and electrolyte balance may be more necessary during RCA-CRRT in patients with liver failure.

The recognition of cutting state of coal-rock is the key technology to realize “unmanned” mining in coal face. In order to realized real-time perception and accurate judgment of coal-rock cutting state information, this paper combined the field test sampling, construction technology of complex coal seam, virtual prototype technology, bidirectional coupling technology, data processing theory, image fusion method, and deep learning theory to carry out multi domain deep fusion experimental research on multi-source heterogeneous data of coal and rock cutting state. The typical complex coal seam containing gangue, inclusion, and minor fault in Yangcun mine of Yanzhou mining area was taken as the engineering object. The high-precision three-dimensional simulation model of the complex coal seam that can update and replace particles was constructed. Based on the simulation results of Discrete Element Method-Multi Flexible Body Dynamics (DEM-MFBD), the one-dimensional original vibration acceleration signals of the key components of the shearer cutting part were determined, including spiral drum, rocker arm shell, and square head. After transforming one-dimensional original signal data into two-dimensional time–frequency images by Short-time Fourier Transform, morphological wavelet image fusion technology was used to realize the effective fusion of characteristic information of spiral drum, rocker arm shell, and square head under different working conditions. Based on the deep learning theory, the DCGAN-RFCNN (Deep Convolutional Generative Adversarial Networks-Random Forest Convolutional Neural Networks) coal and rock cutting state recognition network model was constructed. Combining convolution neural network with random forest recognition classifier, RFCNN coal and rock cutting state recognition classification model was constructed, and the recognition network model was trained to obtain the model recognition results. Through the comparative experimental analysis of the RFCNN network model with different recognition network models and different synthetic sample numbers in the recognition network, the effectiveness of the recognition network model was verified. The results show that: When synthetic samples are not included in each working condition in the RFCNN model, the average recognition rate is 90.641%. With the increase of the number of synthetic samples, the recognition rate of coal and rock cutting state increases. When the number of synthetic samples added to each working condition reaches 5000, the recognition effect is the best, and the average recognition rate reaches 98.344%, which verifies the superiority of enriching the data set by using the improved DCGAN network. Also, the RFCNN outperformed the other variants: it obtained higher recognition accuracy by 25.085, 21.925 and 19.337%, respectively, over SVW, CNN, and AlexNet. Also, the experimental platform of shearer cutting coal and rock was built, where the coal and rock cutting state recognition network was trained and tested based on the migration learning theory. Through the statistical test results, the accuracy of coal and rock cutting state recognition is 98.64%, which realizes the accurate recognition of coal and rock cutting state.

Shearer cables, subjected to large deformations and exposed to harsh working conditions during frequent back-and-forth movements, pose difficulties in achieving comprehensive mechanical performance and extended fatigue life. This study addresses parametric modeling challenges related to determining tangency within and between layers, recursively generating spiral curves from the (n-1)-th level to the n-th level, and constructing irregular surfaces for insulation and sheath. Investigating tensile and bending properties, the research explores the impact of varying pitch diameter ratios at different stranding levels, stranding directions, and monofilaments on mechanical performance across scales. The results reveal a nonlinear increase in stress in power and control conductors with growing pitch diameter ratios. The optimal combination is determined as a pitch diameter ratio of 6 for cabling, 5 for the control conductor, and 14 for the power conductor. The predicted fatigue life of the improved cable by Ncode aligns with bending test results, demonstrating functionality up to 15.12e 4 cycles. Stress distribution in parallel stranding is lower and more even, tending to scatter. Conversely, counter stranding experiences relatively higher stress, ensuring a more stable structure. While maintaining a constant effective conductor cross-sectional area, finer monofilaments result in higher cross-sectional filling ratios, enhancing tensile and bending performance.

The continuing emergence of SARS-CoV-2 variants highlights the need to update COVID-19 vaccine compositions. However, immune imprinting induced by vaccination based on the ancestral (hereafter referred to as WT) strain would compromise the antibody response to Omicron-based boosters 1 – 5 . Vaccination strategies to counter immune imprinting are critically needed. Here we investigated the degree and dynamics of immune imprinting in mouse models and human cohorts, especially focusing on the role of repeated Omicron stimulation. In mice, the efficacy of single Omicron boosting is heavily limited when using variants that are antigenically distinct from WT—such as the XBB variant—and this concerning situation could be mitigated by a second Omicron booster. Similarly, in humans, repeated Omicron infections could alleviate WT vaccination-induced immune imprinting and generate broad neutralization responses in both plasma and nasal mucosa. Notably, deep mutational scanning-based epitope characterization of 781 receptor-binding domain (RBD)-targeting monoclonal antibodies isolated from repeated Omicron infection revealed that double Omicron exposure could induce a large proportion of matured Omicron-specific antibodies that have distinct RBD epitopes to WT-induced antibodies. Consequently, immune imprinting was largely mitigated, and the bias towards non-neutralizing epitopes observed in single Omicron exposures was restored. On the basis of the deep mutational scanning profiles, we identified evolution hotspots of XBB.1.5 RBD and demonstrated that these mutations could further boost the immune-evasion capability of XBB.1.5 while maintaining high ACE2-binding affinity. Our findings suggest that the WT component should be abandoned when updating COVID-19 vaccines, and individuals without prior Omicron exposure should receive two updated vaccine boosters. Exposure to early variants of SARS-CoV-2 results in immune imprinting in mouse models and in humans, reducing neutralizing antibody titres against Omicron variants, which could be mitigated with multiple updated boosters.

In this study an innovative parameterized water-bomb wheel modeling method based on recursive solving are introduced, significantly reducing the modeling workload compared to traditional methods. A multi-link supporting structure is designed upon the foundation of the water-bomb wheel model. The effectiveness of the supporting structure is verified through simulations and experiments. For robots equipped with this water-bomb wheel featuring the multi-link support, base on the kinematic model of multi-link structure, a mapping algorithm that incorporates parameterized kinematic solutions and IMU-fused parameterized odometry is proposed. Based on this algorithm, SLAM and autonomous navigation experiments are carried out in simulation environment and real environment respectively. Compared with the traditional algorithm, this algorithm the precision of SLAM is enhanced, achieving high-precision SLAM and autonomous navigation with a robot error rate below 5%.