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Based on the concept of sustainability and the aim of addressing China?s great need for talent with green skills, a green skills scale was designed with the help of Chinese university students. Students from four institutions of higher education who had agreed to the Principles for Responsible Management Education (PRME) participated as research subjects. With reference to the reviewed literature, a green skills scale was developed for Chinese university students. The scale was reviewed by experts and scholars and subjected to a reliability and validity analysis, and 900 students were selected to be included in the sample. The green skills of university students are divided into four dimensions: cognition of green knowledge, mastery of green skills, application of green skills, and green skills development, resulting in a total of 16 questions. The overall reliability of the scale is 0.845, the reliability of the dimensions lies between 0.813 and 0.880, the correlation coefficients between the dimensions lie between 0.185 and 0.497, and the root-mean-square values of the AVE of the corresponding coefficients are all larger than the correlation coefficients of the corresponding row and column variables, demonstrating that the green skills scale for university students has good reliability and validity.

The professional development of teachers is fundamental to educational reform and promotion, and such a development includes teachers' aesthetic experiences. This study aims to explore the impact of Chinese teachers' aesthetic experiences on their professional development and the differences between male and female teachers in terms of the impact of aesthetic experiences on professional development. In total, 500 teachers from 20 universities in Hainan and Guangzhou, China, were surveyed, and 488 valid questionnaires were collected. A multivariate regression analysis was conducted to examine the impact of each variable. The results of the study indicate that "aesthetic attitude," "understanding of beauty," and "full experience" all have a significantly positive impact on the professional development of both male and female teachers, whereas "pleasure of beauty" has no significant impact on teachers' professional development. The findings also demonstrate that no difference exists between male and female teachers in terms of the impact of aesthetic experiences on professional development, and the more practical conceptions of aesthetic experience have a direct impact on teachers' development.

The atomic relaxation time of a hydrogen atomic clock is the time required for atomic system after the selected state removing the atoms of the ground state hyperfine energy level (F = 0, mF = 0) and (F = 1, mF = −1) state to change from the (F = 1, mF = 0) state to the (F = 0, mF = 0) state until the atomic system reaches equilibrium. This parameter reflects the lifetime of atoms and directly affects performance of hydrogen clock. In order to measure the relaxation time of active hydrogen atomic clock and thus evaluate its performance, hydrogen atomic relaxation test system was established, which was composed of a Raspberry Pi (RPI), signal generator, digital attenuation, microwave detection, and data acquisition circuits. RPI generates timing signal to control the relay of digital attenuator and ionization source power supply circuit, so as to control the opening of microwave detection signal and the on-off of atomic beam current. The relaxation time of the hydrogen atomic clock is measured by data fitting of the acquired free induction decay signals. This method is important for optimizing the atomic linewidth and improving the performance of the active hydrogen clock.

Objective: Exploring the microwave drying characteristics of pork and optimizing the microwave drying process of meat. Methods: microwave drying equipment with microwave frequency of 2 450 MHz and microwave output power of 70, 140, 210, 280, 350, 420 W were used for microwave drying of pork with dry mass of 20, 25, 30 g in this paper; Five classical thin-layer drying models were selected for non-linear fitting of drying data, R2 （coefficient of determination） and RMSE （root mean square error） were used as evaluation indexes to screen the best drying model. Results: The Logarithmic model was the best model for microwave drying of pork. The average energy consumption per unit of pork microwave drying was 10.89 MJ/kg, and the microwave drying efficiency was 20.72%. Conclusion: The best model for microwave drying of pork is the Logarithmic model, pork mass of 25 g, microwave power of 210 W, can significantly reduce the average unit microwave energy consumption, and improve the efficiency of microwave drying.

Objective： A method for simple and rapid determination of potassium content in cigarette paper will be built for workshops of cigarette factory. Methods: An ion-selective electrode method was used by comparing with the pretreatment methods for cigarette paper samples and potential response behaviors of potassium ion-selective electrodes in different buffer solutions. Results: The potassium ion selective electrode possessed excellent response performance for K+ in lithium acetate buffer solution （0.1 mol/L, pH 7.0） with a linear response range of 1.0×10-5 ~1.0×10-2 mol/L, a slope of 55.79 mV/dec （25 ℃）, and a lower limit of detection of 2.14×10-6 mol/L. The average relative standard deviations of the K+ selective electrode on cigarette paper samples were 0.55% for intra-day test and 2.8% for inter-day test, both less than 5%. The test results of the electrode method were in well agreement with that of ion chromatography, with an average relative deviation of 4.1% （n=10） and recoveries between 95.0% and 101.9%. It was demonstrated effectively through a consecutive test over one week. Conclusion: Among the pretreatment methods for cigarette paper samples, the ultrasonic extraction of potassium ions with 1% diluted acetic acid for 30 min has been found to be fast, simple and environmentally friendly. The ion-selective electrode method is accurate and reliable, which is suitable for the rapid detection of potassium in cigarette paper.

Aim: Diabetic cognitive impairment (DCI), considered one of the most severe and commonly overlooked complications of diabetes, has shown inconsistent findings regarding the metabolic profiles in DCI patients. This systematic review and meta‐analysis aimed to identify dysregulated metabolites as potential biomarkers for early DCI, providing valuable insights into the underlying pathophysiological mechanisms. Materials and Methods: A systematic search of four databases, namely PubMed, Embase, Web of Science and Cochrane, was conducted up to March 2024. Subsequently, a qualitative review of clinical studies was performed followed by a meta‐analysis of metabolite markers. Finally, the sources of heterogeneity were explored through subgroup and sensitivity analyses. Results: A total of 774 unique publications involving 4357 participants and the identification of multiple metabolites were retrieved. Of these, 13 clinical studies reported metabolite differences between the DCI and control groups. Meta‐analysis was conducted for six brain metabolites and two metabolite ratios. The results revealed a significant increase in myo‐inositol (MI) concentration and decreases in glutamate (Glu), Glx (glutamate and glutamine) and N‐acetylaspartate/creatine (NAA/Cr) ratios in DCI, which have been identified as the most sensitive metabolic biomarkers for evaluating DCI progression. Notably, brain metabolic changes associated with cognitive impairment are more pronounced in type 2 diabetes mellitus than in type 1 diabetes mellitus, and the hippocampus emerged as the most sensitive brain region regarding metabolic changes associated with DCI. Conclusions: Our results suggest that MI, Glu, and Glx concentrations and NAA/Cr ratios within the hippocampus may serve as metabolic biomarkers for patients with early‐stage DCI. [ABSTRACT FROM AUTHOR]

To make an accurate estimation of leaf are index (LAI) based on machine learning methods and images from UAV, we compared the several mainstream machine learning methods for maize LAI prediction, such as Artificial Neural Network method (ANN), Gaussian Process Regression method (GPR), Support Vector Regression method (SVR), and Gradient Boosting Decision Tree (GBDT). For this purpose, field experiments that considering apply of different amount of organic fertilizer, different amount of inorganic fertilizer, different amount of crop residue, and different planting density were carried out. Based on these experiments, field campaign were conducted to obtain UAV multispectral images and LAI data at different growth stages in maize. Based on above data, firstly, correlation analysis was used to select LAI-sensitive spectral indices, and then the Partial Least Squares Regression method (PLSR) and ANN, GPR, SVR, GBDT were coupled to design the LAI prediction models, respectively, and their performance for LAI prediction were compared. The results showed that the LAI prediction model constructed by PLSR+GBDT method had the highest accuracy and the best stability. The models of R² and RMSE values were 0.90 and 0.25, and the verified R² and RMSE values were 0.90 and 0.29 during validation, respectively. The model based on PLSR+GPR model was followed, with R² and RMSE values of 0.86 and 0.30 during calibration, and R² and RMSE values of 0.89 and 0.29 during validation, respectively. Besides, it had faster training speed and could give the uncertainty of the prediction. The model designed by PLSR+ANN method had R² and RMSE values of 0.85 and 0.31 during calibration, and R² and RMSE values of 0.89 and 0.30 during validation, respectively. The model designed by PLSR+SVR method had R² and RMSE values of 0.86 and 0.32, and R² and RMSE values of 0.90 and 0.33, respectively. Therefore, PLSR+GBDT method and PLSR+GPR method are recommended as the optimal methods for designing maize LAI prediction models. [ABSTRACT FROM AUTHOR]

With the application of supercritical fluid heat transfer equipment in industrial fields such as solar thermal power generation, chemical industry, aerospace, etc., studying the heat transfer characteristics of supercritical fluid in micro-fin tubes has become a key theoretical basis for the development of micro-fin low-resistance heat transfer enhancement technology. In view of micro-fin tubes with different fin shapes, this paper took into account thermophysical properties of nitrogen under supercritical conditions and completed a numerical simulation study on the heat transfer process of nitrogen in 2 mm micro-fin tubes under supercritical pressure. The temperature field distribution of supercritical nitrogen in the micro-fin tube was analyzed, and the turbulent flow mechanism of the micro-fin was studied. It was found that micro-fin could increase the heat exchange area, destroy the boundary layer, and improve the heat transfer coefficient. This paper took comprehensive heat transfer performance evaluation factor PEC to compare the influence of different fin shapes on heat transfer enhancement performance of the heat exchange unit. It was found that the comprehensive heat transfer factor of the square straight micro-fin tube was about 1.22 times that of the smooth round tube, and PEC of the triangular straight micro tube was about 1.08 times that of the smooth tube. The results suggest that square straight micro-fin tube has significantly superior heat transfer performance than smooth round tube and triangular straight micro-fin tube.

The flow characteristics of the supercritical fluid in the micro-fin tube is the theoretical basis for the development of heat transfer enhancement and flow resistance reduction in the micro-fin tube. For micro-fin tubes with different fin shapes, this paper considered the physical properties of nitrogen in the supercritical state and adopted the enhanced wall function, reasonable turbulence equations, and control equations, etc., to numerically simulate the flow of nitrogen in a 2 mm micro-fin tube under supercritical pressure. The distribution of velocity field, turbulence and pressure field of supercritical nitrogen in the micro-fin tube was analyzed. The turbulent flow mechanism of the micro-fins was obtained, and it is found that the existence of the viscous bottom layer slows down the inter-costal fluid velocity and increases the frictional resistance during the flow process.

In the design of the excavation protection scheme in the soft soil area, it is often necessary to set up cement-soil mixing piles in the passive area. In this way, the stability requirements of the excavation can be met, and the lateral displacement of the retaining pile can be greatly restricted. This paper uses PLAXIS 3D to establish a excavation model in a soft area, and discusses the influence of various parameters of the passive zone mixing pile on the deformation and force of the excavation. Within a certain range, as the cohesive force or secant modulus or reinforcement width or depth of the reinforcement area increases, the lateral displacement and settlement outside the pit will decrease. But when it exceeds a certain range, the decreasing trend becomes very slow. With the increase of the four parameters of the reinforcement zone, bending moments in opposite directions appear below the bottom of the excavation. Moreover, the value of the bending moment is getting larger and larger. Therefore, considering the force, it is not that the wider and deeper the reinforced zone is, the more advantageous is.

A model of a certain excavation was established using PLAXIS 3D, and the measured value was compared with the calculated value. The thickness, elastic modulus, and embedded depth of the diaphragm wall are analysed by the controlled variable method. The graphs of the influence of the above three factors on the deformation of the retaining wall of the excavation, the settlement of the soil outside the pit, and the bending moment of the retaining wall are obtained. The data is relativized to make the comparison result more intuitive and vivid. With the increase of wall thickness or elastic modulus or embedded depth, the deformation of the retaining wall and the settlement of the soil outside the pit will decrease. As the wall thickness or elastic modulus increases, the bending moment of the retaining wall will increase. The embedded depth has almost no effect on the bending moment. The magnitude of the influence on the deformation and force of the excavation is sorted from the largest to the smallest as the wall thickness, the elastic modulus, and the embedded depth.

Based on the data of the soil and enclosure structure of a certain excavation, a PLAXIS model was established. The actual monitoring results are compared with the PLAXIS calculation results to verify the reliability of the model. On this basis, the six main parameters in the soil hardening model were changed by a single variable method to obtain the influence of each parameter on the deformation of the excavation. As the soil weight or Poisson’s ratio increases, the lateral displacement of the retaining wall increases. With the increase of the secant modulus or cohesive force or internal friction angle of the soil, the lateral displacement of the retaining wall decreases. The power index m has basically no effect on the lateral displacement of the retaining wall. With the increase of m, the settlement of the soil gradually increases uniformly.