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China's Clinical Medicine Level Test (CMLT) was designed to evaluate the key factors that affect the learning outcome of medical students prior to entering clinical practice. In this study, we systemically analyzed the performance of a cohort of medical students at Jinan University School of Medicine participating in the recent CMLT. The analytical results of the medical students' written and objective structured clinical examination (OSCE) scores showed that their academic performance was predominantly associated with students' internship allocations, although other demographic characteristics such as sex, age, geographical origin of students, and grade point average (GPA) might be sporadically related to the students' OSCE performance at different OSCE stations. To explore the inherent reasons behind this, a survey was implemented among the medical students who participated in the examination to further interpret the factors influencing the students' learning outcome. The findings of this questionnaire manifested that intrinsic motivation and identified regulation acted as the major motivational profiles for the medical students from three different internship sites, whereas external regulation emerged as the crucial factor to make the students perform well academically in the CMLT. The result of this study suggested that strengthening the quality control of the clinical learning environment and improving medical administration may still be the most effective approaches to ensure the quality of clinical medical education.

This experimental study probes into the evolution patterns of fine damage and mechanical and seepage characteristics of coal rocks using the coal rock triaxial servo experiment system by employing three types of pretreatment methods, namely heating, freeze-thawing with liquid nitrogen and freeze-thawing with water, with an aim to investigate the effect of temperature on freeze-thaw damage and seepage characteristics of coal rocks.Results show that higher preheating temperature leads to more severe structural damage, damage to water-filled liquid nitrogen freeze-thawed coal samples at the same temperature is greater than that of liquid nitrogen freeze-thawed coal samples and heated coal samples only, the degree of damage is negatively correlated with the wave speed and positively correlated with the number of joint dimensions of the end face damage; coal samples with high triaxial compressive strength feature low pre-deformation under different pretreatment methods; all three pre-treatment methods lead to an increase in the number of internal pores and fractures in the coal sample, resulting in the formation of a network of fractures.Freezing and thawing the coal sample with warmed water and liquid nitrogen demonstrate more stronger effect than that of freezing and thawing with warmed liquid nitrogen only.Therefore, in engineering practice, preheating-water injection-liquid nitrogen injection freeze-thaw could be employed to achieve efficient coal seam penetration and improve the effect of gas extraction.

Students' preferences and engagement with online educational resources and activities are crucial for academic success in the context of online medical education. This study investigated the preferences of Chinese medical students regarding the teaching strategies used by instructors and their relationship with course difficulty level, student's academic performance, and perceived effectiveness. Survey data (n = 375) were collected from the medical students from one of the largest medical schools in Southern China during the spring semester of 2020. First, exploratory factor analysis demonstrated that there were three latent factors behind online teaching strategies, including teacher-led instructional strategies, supervised and monitored learning strategies, and self-directed learning strategies. Instructional activities under teacher supervision and monitoring received the highest rating while teacher-led strategies received the lowest ratings. Second, the popularity of the three online instructional strategies we have identified was positively associated with students' perceived effectiveness of online teaching and their self-reported academic performance. Third, analysis of the quantified answers to the open-ended question reported a positive association between the perceived difficulty level of the courses and students' preference of teacher-led strategies. It also manifested a positive correlation between perceived effectiveness level of the online teaching and the use of self-directed learning strategies before their online lectures. Further implications of the findings are fully discussed.

This study explored the feasibility of applying visible and near-infrared (400?1 000 nm), and mid- and short-wave near infrared (900?1 700 nm) spectroscopy for detecting Camellia oleifera fruit with different degrees of natural mildew. The near infrared spectra of the equatorial shady and sunny sides, and the junction surfaces of samples with different degrees of mildew were collected in two wavelength bands. The average spectra were analyzed by principal component analysis (PCA), revealing that samples with different mildew degrees could be clustered into different groups, and the first and second principal components (PC1 and PC2) were effective in distinguishing the samples in each category. The full-spectrum partial least squares-discriminant analysis (PLS-DA) model based on the original spectra performed better than of its counterpart based on the preprocessed spectra. In the selection of characteristic wavelengths, successive projections algorithm (SPA) was found to be superior to PC loadings in establishing the simplified models for both spectral ranges. The correct classification rate and kappa coefficient were 84.4% and 0.766 7 for the prediction set, respectively. Based on the observation of confusion matrices for the prediction set, the specificities of the two optimal simplified models for the prediction of each degree of mildew were equivalent to each other and above 0.84. However, mid- and short-wave near infrared spectra in the wavelength range of 900–1 700 nm provided slightly higher sensitivity (0.72) in classifying samples with moderate degree of mildew. Our study showed that near-infrared spectroscopy could be used to detect the degree of natural mildew of C. oleifera fruit, and visible and near-infrared spectroscopy showed comparable results to mid- and short-wave near infrared spectroscopy. Considering its lower cost, visible and near-infrared spectroscopy has a better application prospect for real-time detection.

Mineralized indicator minerals are an important geological and mineral exploration indicator. Rapid extraction of mineralized indicator minerals from hyperspectral remote sensing images using ensemble learning model has important geological significance for mineral resources exploration. In this study, two mineralized indicator minerals, limonite and chlorite, exposed at the surface of Qinghai Gouli area were used as the research objects. Sparrow search algorithm (SSA) was combined with random forest (RF) and gradient boosting decision tree (GBDT) ensemble learning models, respectively, to construct hyperspectral mineralized indicative mineral information extraction models in the study area. Youden index (YD) and ore deposit coincidence (ODC) were applied to evaluate the performance of different models in the mineral information extraction. The results indicate that the optimization of SSA parameter algorithm is obvious, and the accuracy of both the integrated learning models after parameter search has been improved substantially, among which the SSA-GBDT model has the best performance, and the YD and the ODC can reach 0.661 and 0.727, respectively. Compared with traditional machine learning model, integrated learning model has higher reliability and stronger generalization performance in hyperspectral mineral information extraction and application, with YD greater than 0.6. In addition, the distribution of mineralized indicative minerals extracted by the ensemble learning model after parameter optimization is basically consistent with the distribution pattern of the fracture tectonic spreading characteristics and known deposits (points) in the area, which is in line with the geological characteristics of mineralization in the study area. Therefore, the classification and extraction model of minerals based on hyperspectral remote sensing technology, combined with the SSA optimization algorithm and ensemble learning model, is an efficient mineral exploration method.

Jinan University in Guangdong province has several years experience of sending medical students abroad for short-term training, based on the schools' agreement with international universities. Currently, we analyze the problems and experience including the medical students' favorite countries, timing, purposes, academic marks, and expenses etc., which came forth from medical students of Jinan University who had participated in the short-term training in the past several years. Our survey suggests that the choices of Chinese medical students about the host universities vary, although the universities in Western countries are still the most popular. The optimal timing the students prefer for short-term training abroad is during vacation especially after grade 2. Broadening the horizons, learning the different knowledge and increasing their academic experience are the major objectives for most exchange students. Furthermore, the survey shows that students hope to improve exchange students' status management and credit acknowledgement system among interschool administrations. This study could supply useful information for the upcoming exchange students for Chinese medical universities/schools and meanwhile, for the host universities receiving Chinese medical students in the world. Hence, both universities and medical students will benefit for more efficiently implementing the exchange programs in the future.