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Accurate prediction of PM2.5 concentration is important for pollution control, public health, and ecological protection. However, due to the nonlinear nature of PM2.5 data, the accuracy of existing methods suffers and performs poorly in both short-term and long-term predictions. In this study, a deep learning hybrid prediction model based on clustering and quadratic decomposition is proposed. The model utilizes the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) to decompose the PM2.5 sequences into multiple intrinsic modal function components (IMFs), and clusters and re-fuses the subsequences with similar complexity by permutation entropy (PE) and K-means clustering. For the fused high-frequency sequences, a secondary decomposition is performed using the whale optimization algorithm (WOA) optimized variational modal decomposition (VMD). Finally, the nonlinear and temporal features are captured for prediction using the long- and short-term memory neural network (LSTM). Experiments show that this proposed model exhibits good stability and generalization ability. It does not only make accurate predictions in the short term, but also captures the trends in the long-term prediction. There is a significant performance improvement over the baseline models. Further comparisons with existing models outperform the current state-of-the-art models. [ABSTRACT FROM AUTHOR]

PM2.5 pollution poses an important threat to the atmospheric environment and human health. To precisely forecast PM2.5 concentration, this study presents an innovative combined model: EMD-SE-GWO-VMD-ZCR-CNN-LSTM. First, empirical mode decomposition (EMD) is used to decompose PM2.5, and sample entropy (SE) is used to assess the subsequence complexity. Secondly, the hyperparameters of variational mode decomposition (VMD) are optimized by Gray Wolf Optimization (GWO) algorithm, and the complex subsequences are decomposed twice. Next, the sequences are divided into high-frequency and low-frequency parts by using the zero crossing rate (ZCR); the high-frequency sequences are predicted by a convolutional neural network (CNN), and the low-frequency sequences are predicted by a long short-term memory network (LSTM). Finally, the predicted values of the high-frequency and low-frequency sequences are reconstructed to obtain the final results. The experiment was conducted based on the data of 1009A, 1010A, and 1011A from three air quality monitoring stations in the Beijing area. The results indicate that the R2 value of the designed model increased by 2.63%, 0.59%, and 1.88% on average in the three air quality monitoring stations, respectively, compared with the other single model and the mixed model, which verified the significant advantages of the proposed model. [ABSTRACT FROM AUTHOR]

The aim was to estimate the association of egg consumption with dyslipidemia and its subtypes in Chinese adults. The cross-sectional health survey was conducted in Hanzhong city of Shaanxi province in 2010. Consumption of eggs (alone and mixed in foods) and nutrients were assessed using a semi-quantitative 81-item food frequency questionnaire (FFQ). Serum lipids and other physical measurements were measured by trained medical staff. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated from multivariable logistic regressions. Restricted cubic spline was used to visualize the possible non-linear association. A total of 2241 participants (mean age, 48.0 years; 34.5% men) were included. The age- and gender- standardization dyslipidemia prevalence was 21.1% in men and 18.4% in women, respectively. Approximately 42.1% of individuals never or rarely consumed egg, while 9.4% consumed ≥2 times/week. The mean egg intake was 21.5 g/d in men and 17.4 in women. In women, after adjustment for demographics and lifestyle factors, the ORs (95%CI) for dyslipidemia and hypertriglyceridemia were 0.57(0.32–1.05) and 0.38 (0.17–0.85) for individuals consuming egg ≥2 times/week, compared with never or rarely consumers. When further adjustment of BMI and dietary factors, the inverse relation persisted for hypertriglyceridemia but attenuated to margin of significance for dyslipidemia (P-trend = 0.050). Increment of 25 g/d was associated with 15% (OR: 0.85, (0.71–1.00)) lower risk of dyslipidemia. Results from restricted cubic splines showed a substantial reduction of the risk within lower range of consumption, which reached the minimum risk around 20–50 g/d (P-nonlinearity = 0.069). No associations were observed in men. Egg consumption was associated with decreased risk of dyslipidemia among Chinese women but not men. Additionally, the beneficial effect tended to be stronger at 20–50 g egg per day. Further study is warranted to validate these findings and clarify the causality. [ABSTRACT FROM AUTHOR]

Purpose: To characterize the quality of life and mental health status of patients with uveitis and investigate predictors of psychological problems.Methods: A total of 245 patients and 105 controls were enrolled in this cross-sectional study. Quality of life, psychological status, socio-demographic and clinical data were obtained from questionnaires and medical records. Multivariate regression analyses and Receiver Operating Characteristic (ROC) were applied to obtain the model predicting psychological problems of patients.Results: Of 245 patients, 16.7% and 26.5% (P< .0001) screened positive for anxiety and depression, respectively. The model predicting anxiety was comprised of low annual household income and poor self-reported visual function (P= .029,P< .0001, respectively), with an AUC of ROC of 0.744. The model predicting depression was comprised of poor self-reported visual function and ocular complications (P< .0001, P= .012, respectively), with an AUC of 0.78.Conclusions: Economic hardship, ocular complications, and poor self-reported visual function are predictors of mental problems in patients with uveitis. [ABSTRACT FROM AUTHOR]

The current expansion of national colleges and universities or the increase in the number of enrolments requires teaching management to ensure the quality of teaching. The problem of scheduling is a very complicated problem in teaching management, and there are many restrictions. If the number of courses scheduled is large, it will be necessary to repeat the experiment and make adjustments. This kind of work is difficult to accomplish accurately by manpower. Moreover, for a comprehensive university, there are many subjects, many professional settings, limited classroom resources, limited multimedia classroom resources, and other factors that limit and constrain the results of class scheduling. Such a large data volume and complicated workforce are difficult to complete accurately. Therefore, manpower scheduling cannot meet the needs of the educational administration of colleges and universities. Today, computer technology is highly developed. It is very economical to use software technology to design a course scheduling system and let the computer complete this demanding and rigorous work. Common course scheduling systems mainly include hill climbing algorithms, tabu search algorithms, ant colony algorithms, and simulated annealing algorithms. These algorithms have certain shortcomings. In this research, we investigated the mutation genetic algorithm and applied the algorithm to the student's scheduling system. Finally, we tested the running speed and accuracy of the system. We found that the algorithm worked well in the course scheduling system and provided strong support for solving the tedious scheduling work of the educational administration staff. [ABSTRACT FROM AUTHOR]

Purpose: To compare the utility of the Chinese diagnostic criteria for Vogt-Koyanagi-Harada (VKH) disease (CDCV), the revised diagnostic criteria (RDC) and the classification criteria by SUN (SUN-C)., Methods: Two groups of patients (VKH group and non-VKH group) were assessed in this retrospective case-control study. Sensitivity, specificity and area under receiver operating characteristic curve (AUC) were evaluated among these criteria., Results: 258 patients were included after propensity score matching. The sensitivities were 92.2% in CDCV, 66.7% in RDC, and 54.3% in SUN-C. In different disease stages (early and late), similar sensitivity results were observed. The specificities were 96.1% in CDCV, 97.7% in RDC, and 99.2% in SUN-C. The AUCs were 0.942 in CDCV, 0.822 in RDC and 0.767 in SUN-C., Conclusion: A higher sensitivity value and larger AUC in CDCV were found. CDCV are highly useful in the diagnosis and classification of VKH disease in Chinese patients.

Objective: To evaluate the quality of diet among rural residents in Hanzhong, Shaanxi province and to investigate the relative factors., Methods: A cross-sectional survey on dietary status together with a semi-quantitative food frequency questionnaire were conducted among rural residents aged between 18 and 80 in Hanzhong of Shaanxi, in 2010. Quality of diet was evaluated by using DBI-07 scoring and evaluating system. Linear regression models were developed to identify factors related to under or over intakes., Results: 2 241 rural residents were under study. 65% of the residents' daily intake of grains, oil and salt exceeded the RNI while animal food, diary food, eggs, vegetables and fruits were under, to some extent. The average values of DBI&#95;LBS and DBI&#95;HBS were 24.83 and 5.70. The proportions of moderate under-intake (25≤DBI&#95;LBS≤36) and moderate over-intake (14≤DBI&#95;HBS≤19)were 33.4% and 51.0%. Factors as family number, education level, fortune index, physical activity, higher labor intensity seemed to be protective for dietary under intake (P < 0.05). Moderate fortune index, drinking alcohol (more than once a week), being male, age and smoking status(>15 cigarettes per day)were risk factors for over-intake of diet (P < 0.05). Factors as larger family size and having had education above the levels senior school were significantly and negatively associated with the over-intake of diet (P < 0.05)., Conclusion: The main diet problem among the rural residents was related to under-intaken but over-intake did exist to some extents. Our study results called for specific intervention in improving the quality of diet among the residents in Hanzhong.

Objective: To study the current status and risk factors of spontaneous abortion of women with Tibetan ethnicity at reproductive age in rural areas., Methods: Pregnant women who lived in Tibet were interviewed on their former reproductive history and being followed on the outcomes of pregnant from 2006 to 2012. Generalized Poisson regression model was used to explore the influencing factors of spontaneous abortion. OR value of the research factors was estimated and its 95% confidence interval counted., Results: There were 1 557 pregnant women under this study, with a total number of 2 687 pregnancies and 2 382 productions. 171 women underwent spontaneous abortion, with a total number of 204 times, 93 women had histories of abortion, with a total number of 101 times. Among all the Tibetan pregnant women, the ratio between spontaneous abortion and pregnant women was 7.6% while the rate of spontaneous abortion was 7.9% . Ratio between the number of women who had experienced spontaneous abortion and the total number of women under survey was 11.0% . Pregnancy appeared the important reason on spontaneous abortion. The risk of having spontaneous abortion would increase among women who had more than 3 pregnancies. Results from Poisson regression analysis revealed that the odds ratio (OR) value before the adjustment was 3.921 (95% CI:2.553-6.021) but after the adjustment, it increased to 4.722 (95% CI:2.834-7.866). The increase of production time could reduce the risk of spontaneous abortion in women of childbearing age. Risks related to spontaneous abortion were associated with the number of pregnancies. Women seemed to have lower risk for spontaneous abortion after 2009, with OR value as 0.419 (95%CI:0.285-0.616) before, compared to aOR value as 0.580 (95%CI:0.380-0.885) after the adjustment Social-demographic characteristics was not found to be particularly associated with the occurrence of spontaneous abortion., Conclusion: Rate of spontaneous abortion among Tibetan women at childbearing age was not particularly high when comparing to those women living in the plain area such as Shanxi. However, in order to further reduce the incidence of spontaneous abortion among Tibetan women, approaches should include the following items:strengthening maternal health care, extending the spacing of pregnancy and reducing the frequency of pregnancy.

Objective: To investigate the growth pattern of rural Tibetan children in the first year after birth., Methods: In rural area of Lhasa, Tibet, 252 subjects were recruited and their weight, length were measured longitudinally from birth to 12th months of age. Frequency of monitoring reached 5 times in total and Ponderal index (PI)was calculated for each visit. Mixed model was used to analyze the changes of length and weight by gender after controlling for birth weight., Results: Birth weight and length showed great influence on children's growth (weight: β = -0.681 9, P < 0.000 1, length: β = -0.957 1, P < 0.000 1). Weight and length of Tibetan male infants at each age point were lower than WHO new standard on growth and the Reference from 2005 National Survey on growth of children in China. The gap seemed widened by time but the gap between Tibetan female infants and Chinese standard narrowed 6 months after birth. Data showed that the higher PI of Tibetan infants than that of other Chinese infants which might infer that Tibetan infants had a more solid body mass under their own height., Conclusion: The growth pattern of Tibetan infants might have its own feature. Tibetan infants appeared to have had higher PI, which was contradictory to the general conclusion that poor growth and development status had been seen in Tibetan children.

Objective: To explore the dietary pattern and intake of nutrients of rural residents in Hanzhong of Shaanxi Province., Methods: A cross-sectional on dietary pattern together with a semi-quantitative food frequency questionnaire was conducted among rural residents aged from 18 to 80 in Hanzhong of Shaanxi in 2010. Factor analysis was used to identify food patterns based on food frequency., Results: 2958 rural residents were investigated with the average age as 50.0 years old and the average schooling--years were 6.8. Four main factors were derived through factors analysis, which were named as diversity pattern, vegetarian diet, alcohol pattern and economical pattern. Among all kinds of food under analysis, the daily intakes of grains, beans, oil, and salt of the residents were higher than average level of China's rural residents (P < 0.05) and higher than the daily reference intake except beans; meanwhile, animal food, dairy products, egg and fruits were lower (P < 0.01). Among all kinds of nutrients, the daily intakes of energy, protein, carbohydrate, K, Na, Mg, Fe and Zn were lower than average level of China's rural residents (P < 0.01), Ca, fat and some Vitamins were higher. And only some nutrients such as fat, Vitamin E, Vitamin C, Na, Fe and Mn reached or exceeded the RNI/AI (88.8% - 315.3%). Grains provided 50% of energy. 7.1% of energy and 11.4% of protein were from animal foods, which were lower the average level of China's rural residents. 58.9% of Fe was provided by grains., Conclusion: Diet of rural residents in Hanzhong included the main food recommended by Chinese Dietary Guidelines, but the quantity of food was not balanced. Two aspects including under-nutrition and over-nutrition, should be considered to improve the nutrition condition, furthermore the elder women should ask for more attention.