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Background: Major decision-making self-efficacy (MDMSE) is an important indicator of students' ability to make effective decisions in specialty selection. It has implications for students' personal growth and career counselling interventions. While the previous MDMSES has been widely used in the context of China's New College Entrance Examination reform, the increased choice of majors and advancement of career planning necessitate a new scale to assess high school students' MDMSE levels. Methods: Scale items were generated based on a literature review, student interviews, and expert reviews. Exploratory Factor Analysis and Confirmatory Factor Analysis were used to assess the appropriateness of the scale's structure, and network analysis was used to calculate concurrent validity. Retest reliability was calculated to evaluate stability. Results: The MDMSES contains 24 items with five factors (Information Acquisition, Decision Persistence, Self-Determination, Self-Evaluation, and Social Support). The results show that the scale has a good five-factor structure (χ2/df = 1.91, CFI = 0.92, TLI = 0.91, RMSEA = 0.05, and SRMR = 0.06), and the internal consistency reliability of the total scale is 0.91. Conclusion: The scale development results satisfied the psychometric and statistical criteria, allowing the scale to be used as a means of detection to support intervention efforts for individuals with low MDMSE levels. [ABSTRACT FROM AUTHOR]

Drought stress is one of the major adversity stresses affecting soybean (Glycine max [L.] Merr.) yield. Late embryogenesis abundant protein (LEA protein) is a large family of proteins widely distributed in various types of organisms, and this class of proteins plays an important role in protecting proteins, membrane lipids, and lipids inside the cell. The soybean GmPM35 gene is a member of the LEA_6 subfamily. The expression of the GmPM35 gene was significantly increased after drought stress in soybeans. A subcellular localization assay confirmed that the gene acts on the cell membrane. Against wild-type Arabidopsis thaliana, we found that Arabidopsis lines overexpressing the GmPM35 gene were significantly more drought-tolerant at germination and seedling stages under drought stress. To further investigate the drought tolerance function of this gene in soybeans, nine overexpression lines of the T3 generation soybean GmPM35 gene and two editing lines of the T3 generation soybean GmPM35 gene were obtained by Agrobacterium-mediated method using a wild-type soybean strain (JN28) as a receptor. Germination rate, root length, chlorophyll (CHL) content, Proline (Pro) content, malondialdehyde (MDA) content, superoxide anion (O2•−) content, hydrogen peroxide (H2O2) content, (NBT, DAB) staining, and activities of antioxidant enzymes (CAT, SOD, POD), and photosynthetic physiological indexes of the three different types of strains were measured and analyzed before and after drought stress. Combined with the results of rehydration experiments and physiological and biochemical indices, we found that overexpression of the GmPM35 gene protected the activities of antioxidant enzymes under drought stress. The activities of superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) were increased by an average of 34.28%, 26.12%, and 30.01%, respectively, in soybean plants overexpressing the GmPM35 gene compared with wild-type soybeans. Under drought stress conditions, soybean plants overexpressing the GmPM35 gene showed an average increase of 76.81% in photosynthesis rate (Pn), 39.8% in transpiration rate (Tr), 126% in stomatal conductance (Gs), 47.71% in intercellular CO2 concentration (Ci), and 26.44% in instantaneous water use efficiency (WUEi). The improvement of these indexes helped to reduce the accumulation of reactive oxygen species (ROS) in the plants. In addition, we found that under drought stress, the MDA content was reduced by an average of 18.8%, and the Pro content was increased by an average of 60.14% in soybean plants overexpressing the GmPM35 gene, and the changes in these indexes indicated that the plants had stronger antioxidant and osmoregulatory capacities in response to drought stress. In summary, this experiment demonstrated that the GmPM35 gene plays an important role in soybean tolerance to drought stress, and by overexpressing the GmPM35 gene, soybean plants can better tolerate drought stress and maintain normal physiological functions. [ABSTRACT FROM AUTHOR]

Summary: The article examines the positional relationships and transmission/reception signal direction information within unmanned aerial vehicle (UAV) cluster formations. Considering the distinctive characteristics of various formation shapes (such as circle and cone), a study is conducted on the polar and Cartesian coordinate systems in neural network models to address position deviation issues arising in UAV formation flights. The passive receiving signal UAV positioning model is established by applying the triangular cosine theorem. Additionally, the position relationship model of the UAV is formulated using optimization theory. The article introduces a deep learning‐based deviated UAV adjustment algorithm designed to automatically adjust UAV positions. This is achieved by establishing a triangular relationship between the passive signal receiving UAV and other UAVs. The implementation involves C# programming and MATLAB visualization. The proposed method not only resolves UAV positioning and position adjustment challenges but also optimizes the adjustment strategy. This optimization leads to maximum savings in time and distance costs associated with sending and receiving signals among UAVs, thereby enhancing the overall performance of UAVs during flights. [ABSTRACT FROM AUTHOR]

Urban expressways take on rapid and external transport in the city due to their fast, safe, and large capacity. Implementing intelligent and active traffic control can effectively improve the performance of urban traffic and mitigate the urban traffic congestion problem. Real-time traffic guidance is one critical way of intelligent active traffic control, and travel time is the most important input for real-time traffic guidance. We employed and improved a machine learning method called the evolving fuzzy participatory learning (ePL) model to predict the freeway travel time online in this paper. The ePL model has a promising nonlinear mapping potential, which is well suitable for the traffic prediction. We used generalized recursive least square (GRLS) to improve the estimation accuracy of the model's parameters. This model is a fuzzy control model. Its output is the forecasting result which is also the fuzzy reasoning result. We tested this model by comparing it to other travel time prediction approaches, with the freeway data from the Caltrans Performance Measurement System. The results from the improved ePL model showed mean absolute error of 5.941 seconds, mean absolute percentage error of 1.316%, and root mean square error of 10.923s. The performances are better than those of the baseline models including ARIMA and BPN. This model can be used to predict the travel time in the field to be used for active traffic control and traffic guidance., Author(s): Yongyi Li (corresponding author) [1]; Ming Zhang [1]; Yixing Ding [2]; Zhenghua Zhou [3]; Lingyu Xu [1] 1. Introduction The ways to predict travel time have undergone a significant [...]

Comprehensive Summary: A monolithic column‐based mass spectrometry (MS) analysis kit was prepared for whole blood analysis with MS. The kit is disposable and can be used for purification, storage, transportation and direct analysis of whole blood. The kit mainly consists of a capillary for quantitative microsampling, a cation exchange monolithic column for purification and storage, and a syringe for loading sample. This kit is very friendly to various users that one can easily siphon the blood in the kit followed by rapid clean‐up. We established a quantitative method using the kit with a limit detection as low as 0.33 nmol/L, and achieved more than five orders of magnitude enhancement in sensitivity compared to direct nanoelectrospray ionization MS analysis. The column can avoid analyte exposure to environment, which helps the storage of the sample for laboratory analysis. The relative standard deviation of immediate blood analysis and storage blood analysis within 10 d was less than 10%. This method has been successfully applied to the quantitative analysis of procainamide hydrochloride in 2 μL rat blood. These results indicate that this disposable kit does have the potential to achieve highly sensitive quantitative MS analysis in biological samples, which is expected to become a cost‐effective and powerful tool for in vitro diagnostics. [ABSTRACT FROM AUTHOR]