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The reform of the optional subjects of the college entrance examination under the new situation puts forward higher challenges to the talent cultivation of higher vocational colleges. In this paper, for students entering higher vocational colleges and universities after the new college entrance examination, the random forest framework is improved by mining students’ homework and quiz data with PCA dimensionality reduction. Behavioral feature extraction using Random Forest and coding definitions are proposed after feature screening. Based on general feature coding, the behavioral group differentiation extraction of higher education students was constructed, which finally provided label classification of students’ cognitive-behavioral features. After analyzing the impact of the optional subjects on the quality of higher vocational students, the learning behaviors of higher vocational students were dissected. The probability density distribution plots of students’ entry rates show that the overall probability density distribution curves of entry for different students are significantly different. The wave heights of the first, second, third and fourth academic years were 10.25, 16.48, 13.24 and 12.61, respectively, and the study behavior of senior students after the selection of subjects in the college entrance examination showed a unique pattern. In response to the behavioral performance of higher vocational students, institutions need to scientifically use assessment reports to launch talent development work.

Epithelial-mesenchymal transition (EMT) is critical in the development of coronary artery disease (CAD). However, landscapes of EMT-related genes have not been fully established in CAD. We identified the differentially expressed mRNAs and lncRNAs (DElncRNAs) from the Gene Expression Omnibus database. Pearson’s correlation analysis, the least absolute shrinkage and selection operator regression, and support vector machine reverse feature elimination algorithms were used to screen EMT-related lncRNAs. The cis–trans regulatory networks were constructed based on EMT-related lncRNAs. Quantitative real-time polymerase chain reaction was performed to validate the expression of EMT-related genes in a cohort of six patients with CAD and six healthy controls. We further estimated the infiltration of the immune cells in CAD patients with five algorithms, and the correlation between EMT-related genes and infiltrating immune cells was analyzed. We identified eight EMT-related lncRNAs in CAD. The area under curve value was greater than 0.95. The immune analysis revealed significant CD8 T cells, monocytes, and NK cells in CAD and found that EMT-related lncRNAs were correlated with these immune cell subsets. Moreover, SNAI2, an EMT-TF gene, was found in the trans-regulatory network of EMT-related lncRNAs. Further, we found SNAI2 as a biomarker for the diagnosis of CAD but it also had a close correlation with immune cell subsets in CAD. Eight EMT-related lncRNAs and SNAI2 have important significance in the diagnosis of CAD patients.

The membrane fouling issue has aroused great concern. To improve their antifouling properties, surface grafting with oxidative deposition were employed to amend a polyvinylidene fluoride (PVDF) membrane. The modifiers were amino-modified graphene oxide (AMGO), dopamine (DPA) and 1,3-diaminoguanidine hydrochloride (DAGH). To take bovine serum albumin (BSA, 1 g/l) as an example of organic materials, BSA interception rate and pure water flux recovery rate increased to 93.65% and 66.74%, respectively, while the corresponding values for the original membrane were much lower (72.82% and 31.72%). The optimum synthesis conditions were found to be 1.5 mg/ml of DPA, 1 wt% of DAGH, 2 mg/ml of AMGO, 4 h of DPA oxidation deposition time and 1 h of AMGO grafting time. Many functional groups like C = N, -NH2, C = O and -OH improved the membrane surface hydrophilicity leading to a higher resistance to organic pollution. Dopamine and guanidyl facilitated the antimicrobial performance of the modified membrane, whose antimicrobial rate was up to 96%, while the raw membrane had no antimicrobial activity. The amended membrane possessed 40% higher mechanical strength than the initial one. It could withstand a high pumping suction force. The noteworthy property was that the irreversible fouling rate decreased by 55%. Therefore, the amended membrane could restore its flux much more easily. HIGHLIGHTS The graphene oxide, dopamine and guanidine-based composite modification offered high hydrophilic and antibacterial radicals.; The irreversible pollution rate of the modified membrane decreased by 55%, its pure water flux recovery rate increased by twice and BSA interception rate was around 94%.; The antimicrobial rate of the modified membrane reached 96%, while the original one did not display any antimicrobial behaviors.;

Taking into consideration the disadvantages of the serial structure controller-slow operation speed, poor grid current quality for the present grid-connected invert, the authors proposed a new grid-connected invert architecture, which is based on SOPC control technology on FPGA platform. It adopts the direct current PI control strategy with grid voltage feed-forward and uses hardware to realize algorithm, which improved the running speed and the overall performance of system. Meanwhile, designed regulator parameters for the control strategy and constructed grid-connected control system IP hard core for the invert in this paper. Experimental results of 1 kW prototype show that this method has good grid current quality and strong synchronous tracking capability.

Three-dimension solid model of helical gear limited slip differential is built by using CATIA,and then the virtual prototype model is established through importing the 3D solid model into ADAMS/View. In the virtual environment,based on the kinematics dynamics simulation and analysis with two different typical work conditions,including straight-line driving on good pavement and double tire-road friction coefficients,the torque curve,the force and angular velocity curves of helical gear of limited slip differential are acquired.By comparing with theoretical calculations values,the correctness of model and the effectiveness of simulation method are verified. The study results provide the basis for the dynamic optimization and fatigue life prediction of the helical gear limited slip differential.

Currently, pattern recognition technique is widely applied in human identity recognition while there are shortages remaining in most kinds of such techniques. In order to overcome these problems, a novel algorithm is proposed to apply in identity recognition course in new field-static gait recognition field. Two combined features are going for static gait recognition: the distance between each part of center pressure and overall foot and the side length of outline triangle of human foot. Then through the comparison of different classifier, the best course for recognition can be obtained.