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In recent years, the artificial potential field has garnered significant attention in ship route planning and traffic flow simulation. However, the traditional artificial potential field method faces challenges in accurately simulating a ship’s customary route and navigating experience, leading to significant deviations in prediction results. To address these issues, in this study, we propose an innovative method for simulating and predicting ship traffic flow, building upon the artificial potential field approach. We introduce an AIS track heat map based on the kernel density function and enhance the artificial potential field model by incorporating factors, such as ship navigation habits and ship size. Through a comparison of traffic flow changes before and after the construction of a wind farm, the optimized model demonstrates its effectiveness in improving the accuracy of prediction results.

Accurately predicting the breakdown pressure in horizontal sections is essential when designing and optimizing fracturing jobs for horizontal wells in tight gas reservoirs. Taking the Sulige block in the Ordos Basin as an example, for different completion methods combined with indoor rock experience data and well data, a new method for predicting breakdown pressure based on a linear regression model is proposed. Based on the Hossain horizontal well stress field model, this paper established a calculation model of breakdown pressure under different completion methods by using experimental and well data. The average error between the calculation results and the actual breakdown pressure at the initiation point is 3.67%. A Pearson correlation analysis was conducted for eight sensitive factors of horizontal well stress, which showed that the maximum horizontal principal stress, minimum horizontal principal stress, tensile strength, and elastic modulus had strong linear correlations with breakdown pressure. In this study, multiple linear regression was used to establish the prediction model of breakdown pressure under different completion conditions, and the calculation method of the prediction model was optimized. The model was verified using the relevant data for four horizontal wells. The average relative error between the prediction model and the actual breakdown pressure was 4.33–6.30%, indicating that the breakdown pressure obtained by the new prediction model was similar to the actual conditions. Thus, the prediction model is reasonable and reliable.

Phenazine compounds are widely used in agricultural control and the medicine industry due to their high inhibitory activity against pathogens and antitumor activity. The green and sustainable method of synthesizing phenazine compounds through microbial fermentation often requires a complex culture medium containing tryptone and yeast extract, and its cost is relatively high, which greatly limits the large-scale industrial production of phenazine compounds by fermentation. The aim of this study was to develop a cost-effective minimal medium for the efficient synthesis of phenazine compounds by Pseudomonas chlororaphis. Through testing the minimum medium commonly used by Pseudomonas, an ME medium for P. chlororaphis with a high production of phenazine compounds was obtained. Then, the components of the ME medium and the other medium were compared and replaced to verify the beneficial promoting effect of Fe2+ and NH4+ on phenazine compounds. A cost-effective general defined medium (GDM) using glycerol as the sole carbon source was obtained by optimizing the composition of the ME medium. Using the GDM, the production of phenazine compounds by P. chlororaphis reached 1073.5 mg/L, which was 1.3 times that achieved using a complex medium, while the cost of the GDM was only 10% that of a complex medium (e.g., the KB medium). Finally, by engineering the glycerol metabolic pathway, the titer of phenazine-1-carboxylic acid reached the highest level achieved using a minimum medium so far. This work demonstrates how we systematically analyzed and optimized the composition of the medium and integrated a metabolic engineering method to obtain the most cost-effective fermentation strategy.

With the emergence of more variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the immune evasion of these variants from existing vaccines, the development of broad-spectrum vaccines is urgently needed. In this study, we designed a novel SARS-CoV-2 receptor-binding domain (RBD) subunit (RBD5m) by integrating five important mutations from SARS-CoV-2 variants of concern (VOCs). The neutralization activities of antibodies induced by the RBD5m candidate vaccine are more balanced and effective for neutralizing different SARS-CoV-2 VOCs in comparison with those induced by the SARS-CoV-2 prototype strain RBD. Our results suggest that the RBD5m vaccine is a good broad-spectrum vaccine candidate able to prevent disease from several different SARS-CoV-2 VOCs.

VirG is outer membrane protein of Shigella and affects the spread of Shigella. Recently it has been reported that apyrase influences the location of VirG, although the underlying mechanism remains poorly understood. The site of interaction between apyrase and VirG is the focus of our research. First we constructed recombinant plasmid pHIS-phoN2 and pS-(v1–1102, v53–758, v759–1102, v53–319, v320–507, v507–758) by denaturation-renaturation, the phoN2:kan mutant of Shigella flexneri 5a M90T by a modified version of the lambda red recombination protocol originally described by Datsenko and Wanner and the complemented strain M90TΔphoN2/pET24a(PhisphoN2). Second, the recombinant plasmid pHIS-phoN2 and the pS-(v1–1102, v53–758, v759–1102, v53–319, v320–507, v507–758) were transformed into E. coli BL21 (DE3) and induced to express the fusion proteins. Third, the fusion proteins were purified and the interaction of VirG and apyrase was identified by pull-down. Fourth, VirG was divided and the interaction site of apyrase and VirG was determined. Finally, how apyrase affects the function of VirG was analyzed by immunofluorescence. Accordingly, the results provided the data supporting the fact that apyrase combines with the α-domain of VirG to influence the function of VirG.