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In order to effectively prevent and combat online public opinion crises triggered by major emergencies, this paper explores the dissemination mechanism of uncertain information on online social platforms. According to the decision-making behavior of netizens after receiving uncertain information, they are divided into eight categories. Considering that there will be a portion of netizens who clarify uncertain information after receiving it, this paper proposes a SEFTFbTbMR model of uncertain information clarification behavior. The propagation dynamics equations of the model are given based on the theory of differential equations, the basic regeneration number R0 of the model is calculated, and the existence and stability of the equilibrium point of the model are analyzed. The theoretical analysis of the model is validated using numerical simulation software, and sensitivity analysis is performed on the parameters related to R0. In order to reduce the influence caused by uncertain information, the optimal control strategy of the model is proposed using the Hamiltonian function. It is found that the dissemination of uncertain information among netizens can be suppressed by strengthening the regulation of social platforms, improving netizens’ awareness of identifying the authenticity of information, and encouraging netizens to participate in the clarification of uncertain information. The results of this work can provide a theoretical basis for future research on the uncertain information dissemination mechanism triggered by major emergencies. In addition, the results can also provide methodological support for the relevant government departments to reduce the adverse effects caused by uncertain information in the future.

To study the propagation pattern of congestion risk in the traffic network and enhance risk control capabilities, a model has been developed. This model takes into account the probabilities of five threats (the risk occurrence probability; the risk of loss; the unpredictability of risk; the uncontrollability of risk; the transferability of risk) in the traffic network to define the risk entropy and determine the risk capacity, analyze the mechanism of congestion risk propagation, and explore the impact of risk resistance, the average degree of risk capacity at intersections, and the degree of correlation on congestion risk propagation. Further, a control method model for risk propagation is proposed. Numerical simulation results demonstrate that the risk resistance parameter θ can inhibit the propagation of congestion risk during traffic congestion. The highest efficiency in controlling risk propagation is achieved when θ reaches a threshold value θ*. Furthermore, the average degree of intersection risk capacity α shows a positive correlation with θ* and a negative correlation with control efficiency. However, the degree of association ω has a negative effect on risk propagation control, decreasing the degree of association between nodes aids in risk propagation control.

Server consolidation is a useful solution aiming at cost-efficiency and high resource utilization of data centers and clusters. Nowadays, as the data-intensive and I/O intensive applications are widely used, more attention is paid to the local storage-based clouds which can offer much better I/O performance at relatively low price compared with the shared storage. However, it will obviously increase the migration cost (e.g., energy and time). Meanwhile, there is few suitable resource demand estimation method for local storage-based clouds at present, which plays an important role in system's migration efficiency. And we find out that in this specific storage architecture, almost all the existing server consolidation algorithms do not have a suitable resource demand estimation method and a live migration scheme. To solve this problems, this paper designs and implements Combining Three (C3), a cloud architecture for local storage, C3 significant modules: prediction, consolidation, and migration. It was proved in statistical analysis that ARIMA may be the most suitable prediction model for the server workload, which motivates us to propose the resource estimation predictor. Also, we improve the existing consolidation method by adjusting the sorting index and fit degree during migration. Then, we propose a live migration scheme for local storage environment as the third module of C3. We conduct extensive experiments using real-world traces from Google to validate the effectiveness and superiority of our proposed algorithm.

With the development of wireless sensor network (WSN) technologies, WSNs have been applied in many areas. In all WSN technologies, localization is a crucial problem. Traditional localization approaches in WSNs mainly focus on calculating the current location of sensor nodes or mobile objects. In this paper, we study the problem of future location prediction in WSNs. We assume the location histories of mobile objects as a rating matrix and then use a random walk based social recommender algorithm to predict the future locations of mobile objects. Experiments show that the proposed algorithm has better prediction accuracy and can solve the rating matrix sparsity problem more effectively than related works.

In order to solve the problems of carbon nanotubes, steel fibers, and carbon nanotubes + steel fibers on the compressive strength and impact resistance of concrete, the author proposes a test method for the frost resistance and corrosion resistance of carbon nanofiber bridge concrete. Using carbon nanotubes and steel fibers as reinforcing materials, the effects of carbon nanotubes and steel fibers on the compressive strength and impact resistance of concrete were studied. Experimental results show that incorporating carbon nanotubes and steel fibers can improve the compressive strength of concrete. Compared with the single-doped carbon nanotubes, the single-doped steel fiber has a greater effect on the improvement of the impact resistance of the concrete. The toughness and ductility of carbon nanotubes and steel fiber reinforced concrete are improved again compared with that of single steel fiber reinforced concrete. The effect of adding 1% steel fiber +0.30% carbon nanotubes is the most significant in enhancing the performance of concrete. Conclusion. The synergistic effect of carbon nanotubes and steel fibers is more conducive in complementing each other's advantages and improving the performance of concrete.

The asparaginase and isoaspartyl peptidase 1 (ASRGL1) is an L-asparaginase and beta-aspartyl peptidase enzyme that may be involved in the formation of L-aspartate, a neurotransmitter that can operate as an excitatory neurotransmitter in some brain regions. Although variants in ASRGL1 have been reported in retinitis pigmentosa (RP) patients, the in vivo functions and mechanisms of ASRGL in RP remains unknown due to the lack of suitable disease models. To explore the role of ASRGL in RP, we generated an Asrgl1 knockout mouse model (Asrgl1 KO) using the CRISPR/Cas9 technique. Asrgl1 ablation in mice led to an attenuated electroretinogram (ERG) response around 8 months. The thickness of the outer nuclei layer (ONL) started to decrease around 9 months in Asrgl1 KO mice and gradually intensified at 12 and 15 months. Immunostaining revealed thinner inner segment (IS) and thinner outer segment (OS) as well as the progressive degeneration of rod and cone cells in Asrgl1 KO mice. One hundred forty-nine transcriptional differentially expressed genes (DEGs) were found by RNA-seq in Asrgl1 KO retina. These DEGs were linked to a number of biological processes that were considerably enriched, including gastrointestinal disease and organismal injury and abnormalities. By analysis of canonical pathways, glucocorticoid receptor signaling was the most significant canonical pathway altered in Asrgl1 KO retina. Several molecules, including NFE2L2, IL-4, Foxp3, and Fos, were in the central nodes of the interaction network in Asrgl1 KO retina. In summary, our study provided a knockout mouse model for a better understanding of the molecular mechanism for ASRGL1-related RP.

Abstract Background Colorectal surgery is associated with high rates of surgical site infection (SSI). We investigated SSI in radical resection of colon or rectal carcinoma and its epidemiological distribution in 26 hospitals in China. Methods We conducted prospective surveillance of patients who underwent radical resection of colon or rectal carcinoma in 26 selected hospitals from January 2015 to June 2016.An information system monitored all of the surgical inpatients. Infection control professionals observed the inpatients with suspected SSI who had been screened by the system at the bedside. The infection status of the incisions was followed up by telephone 1 month after the operation. Results In total, 5729 patients were enrolled for the two operations; SSIs occurred in 206 patients, and the infection rate was 3.60%. The incidence of SSI after radical resection of rectal carcinoma (5.12%; 119/2323) was 2.1 times higher than that after radical resection of colon carcinoma (2.55%; 87/3406) (P

Objective: In order to investigate the prevalence of intestinal parasites in captive wild animals in four zoological gardens in Heilongjiang Province of Northeast China. Method: From September 2016 to September 2020, fecal samples were collected from Harbin North Forest Zoo, Jiamusi Water Source Mountain Park, Qiqihar Longsha Zoological and Botanical Gardens, and Jixi City Zoo. The morphological identification of eggs or oocysts was carried out using the water washing precipitation method, saturated saline floatation method, and saturated sucrose floatation method. Results: The overall parasite positive detection rate in the four zoos were 18.33% (33/180), 21.69%(18/83), 22.22%(8/36), and 26.32%(10/38), respectively. The most prevalent parasitic species of Carnivora, Artiodactyla, Perissodactyla, Primates, and Aves were Ascaridoidea, Trichuris spp., and Contracaecum sp. Zoonotic parasites were also observed (Toxocara cati, Spirometra mansoni, Trichostrongylus sp.). Conclusions: The results are beneficial in assisting zoo management to formulate and implement preventive and control measures against the spread of infectious parasitic diseases among the animals or to humans.