Ideological and political teaching practice of electrical specialty courses in colleges and universities

In the personnel training wo rk in colleges and universities, the basic task of establishing a person through each link, is always the goal that our country’s higher education pursues. In the background of the new period, how to penetrate the ideological and political content in the electrical course, construct the new model of the course ideological and political, become the key topic that the electrical teacher needs to explore. In order to cultivate the students of this major into high-quality talents with both morality and ability, the teachers of electrical major courses need to establish the ideological and political teaching model suitable for this major course as soon as possible. Based on this, this paper probes into the practical strategies of ideological and political teaching of electrical major courses in colleges and universities, in order to provide valuable reference for the majority of colleagues

New methods to measure residues coevolution in proteins

<p>Abstract</p> <p>Background</p> <p>The covariation of two sites in a protein is often used as the degree of their coevolution. To quantify the covariation many methods have been developed and most of them are based on residues position-specific frequencies by using the mutual information (MI) model.</p> <p>Results</p> <p>In the paper, we proposed several new measures to incorporate new biological constraints in quantifying the covariation. The first measure is the mutual information with the amino acid background distribution (MIB), which incorporates the amino acid background distribution into the marginal distribution of the MI model. The modification is made to remove the effect of amino acid evolutionary pressure in measuring covariation. The second measure is the mutual information of residues physicochemical properties (MIP), which is used to measure the covariation of physicochemical properties of two sites. The third measure called MIBP is proposed by applying residues physicochemical properties into the MIB model. Moreover, scores of our new measures are applied to a robust indicator <it>conn(k) </it>in finding the covariation signal of each site.</p> <p>Conclusions</p> <p>We find that incorporating amino acid background distribution is effective in removing the effect of evolutionary pressure of amino acids. Thus the MIB measure describes more biological background information for the coevolution of residues. Besides, our analysis also reveals that the covariation of physicochemical properties is a new aspect of coevolution information.</p

Soft Roof Failure Mechanism and Supporting Method for Gob-Side Entry Retaining

To study the soft roof failure mechanism and the supporting method for a gateway in a gently inclined coal seam with a dip angle of 16° kept for gob-side entry retaining, and through the methodology of field investigation and numerical and analytical modeling, this paper analyzed the stress evolution law of roof strata at the working face end and determined that the sharp horizontal stress unloading phenomenon along the coal wall side did not appear after the working face advanced. Conversely, the horizontal stress along the gob side instantly decreased and the tensile stress produced, and the vertical stress in the central part of the roof had a higher reduction magnitude as well. An in-depth study indicates that the soft roof of the working face end subsided and seriously separated due to the effect of the front abutment pressure and the roof hanging length above the gob line, as well as certain other factors, including the rapid unloading of the lateral stress, tension and shear on the lower roof rock layer and dynamic disturbance. Those influencing factors also led to rapid crack propagation on a large scale and serious fracturing in the soft roof of the working face end. However, in the gob stress stabilized zone, the soft roof in the gob-side entry retaining has a shearing failure along the filling wall inside affected by the overburden pressure, rock bulking pressure, and roof gravity. To maintain the roof integrity, decrease the roof deformation, and enable the control of the working face end soft roof and the stabilization of the gob-side entry retaining roof, this study suggests that the preferred bolt installation angle for the soft roof situation is 70° based on the rock bolt extrusion strengthening theory

Saturation Flow Rate and Start-up Lost Time of Dual-left Lanes at Signalized Intersection in Rainy Weather Condition

AbstractThis study aims at finding out the difference of saturation flow rate and start-up lost time at dual left lanes between normal and rainy weather. It is based on the investigation of a signalized intersection in Shanghai. The result shows that compared to clear weather, saturation flow in rainy weather decreases by 3-7 percent and each lane's start-up lost time rises by 21-31 percent. However, comparing light-medium rainy weather to clear weather, the statistical difference of each of these two parameters is not significant

T-URF13 Protein from Mitochondria of Texas Male-Sterile Maize (Zea mays L.)

The protein T-URF13 (URF13) is specific to mitochondria of maize (Zea mays L.) with Texas (T) male-sterile cytoplasm and has been implicated in causing male sterility and susceptibility to T-cytoplasm-specific fungal diseases. T-URF13 was purified from isolated mitochondria from maize (line B73) with T cytoplasm by gel filtration and a quasi two-dimensional polyacrylamide gel electrophoresis system. Antibodies to the purified and denatured protein were produced in rabbits. Anti-T-URF13 antiserum was used to show that T-URF13 is in the inner membrane of mitochondria and behaves as an integral membrane protein when mitochondria are fractionated with sodium carbonate or Triton X-114. The antiserum and protein A tagged with 20-nanometer-gold particles were used to localize T-URF13 in T mitochondria by electron microscopy of sections of isolated mitochondria from etiolated shoots and sections of roots and of tapetal cells at pre-and post-degeneration stages of microsporogenesis. The microscopic study confirms that T-URF13 is specifically localized in the mitochondrial membranes of all of the T mitochondria tested, notably those in the tapetum from the meiocyte stage to the late-microspore stage. No change in the amount of labeled T-URF13 protein in the mitochondria of aging tapetal cells was detected

Comparison of Different LGM-Based Methods with MAR and MNAR Dropout Data

The missing not at random (MNAR) mechanism may bias parameter estimates and even distort study results. This study compared the maximum likelihood (ML) selection model based on missing at random (MAR) mechanism and the Diggle–Kenward selection model based on MNAR mechanism for handling missing data through a Monte Carlo simulation study. Four factors were considered, including the missingness mechanism, the dropout rate, the distribution shape (i.e., skewness and kurtosis), and the sample size. The results indicated that: (1) Under the MAR mechanism, the Diggle–Kenward selection model yielded similar estimation results with the ML approach; Under the MNAR mechanism, the results of ML approach were underestimated, especially for the intercept mean and intercept slope (μi and μs). (2) Under the MAR mechanism, the 95% CP of the Diggle–Kenward selection model was lower than that of the ML method; Under the MNAR mechanism, the 95% CP for the two methods were both under the desired level of 95%, but the Diggle–Kenward selection model yielded much higher coverage probabilities than the ML method. (3) The Diggle–Kenward selection model was easier to be influenced by the non-normal degree of target variable's distribution than the ML approach. The level of dropout rate was the major factor affecting the parameter estimation precision, and the dropout rate-induced difference of two methods can be ignored only when the dropout rate falls below 10%

Personalized Estimate of Chemotherapy-Induced Nausea and Vomiting: Development and External Validation of a Nomogram in Cancer Patients Receiving Highly/Moderately Emetogenic Chemotherapy.

Chemotherapy-induced nausea and vomiting (CINV) is presented in over 30% of cancer patients receiving highly/moderately emetogenic chemotherapy (HEC/MEC). The currently recommended antiemetic therapy is merely based on the emetogenic level of chemotherapy, regardless of patient's individual risk factors. It is, therefore, critical to develop an approach for personalized management of CINV in the era of precision medicine.A number of variables were involved in the development of CINV. In the present study, we pooled the data from 2 multi-institutional investigations of CINV due to HEC/MEC treatment in Asian countries. Demographic and clinical variables of 881 patients were prospectively collected as defined previously, and 862 of them had full documentation of variables of interest. The data of 548 patients from Chinese institutions were used to identify variables associated with CINV using multivariate logistic regression model, and then construct a personalized prediction model of nomogram; while the remaining 314 patients out of China (Singapore, South Korea, and Taiwan) entered the external validation set. C-index was used to measure the discrimination ability of the model.The predictors in the final model included sex, age, alcohol consumption, history of vomiting pregnancy, history of motion sickness, body surface area, emetogenicity of chemotherapy, and antiemetic regimens. The C-index was 0.67 (95% CI, 0.62-0.72) for the training set and 0.65 (95% CI, 0.58-0.72) for the validation set. The C-index was higher than that of any single predictor, including the emetogenic level of chemotherapy according to current antiemetic guidelines. Calibration curves showed good agreement between prediction and actual occurrence of CINV.This easy-to-use prediction model was based on chemotherapeutic regimens as well as patient's individual risk factors. The prediction accuracy of CINV occurrence in this nomogram was well validated by an independent data set. It could facilitate the assessment of individual risk, and thus improve the personalized management of CINV