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Accurate Origin-Destination (OD) prediction is significant for effective traffic monitor, which can support operation decision in traffic planning and management field. The enclosed expressway network system like toll gates system in China can collect mounts of trip records which can be gathered for OD prediction. The paper develops a novel neural network, which is named Expressway OD Prediction Neural Network (EODPNN) for toll data-based prediction. The network consists of the following three modules: The Feature Extension Module, the Memory Module, and the Prediction Module. In the process, the attributes data which can reflect the city attribute such as GDP, population, and the number of vehicles are considered to embeded into the notwork to increase the accuracy of the model. For the applicability improvment of the model, we categorize the cities in multiple classes based on their economy and population scales in this paper, which can provide a higher accurate prediction of OD by EODPNN. The results shows that, comparing to the traditional model like ARIMA and SVM, or typical neural networks like Bidirectional Long Short-term Memory, the EODPNN delivers a better prediction performance. The method proposed in this paper has been fully verified and has a potential to transplant to the other OD data-based management systems for a more accurate and flexible prediction. [ABSTRACT FROM AUTHOR]

This paper presents the development and evaluation of the train-the-trainer (TTT) workshop for lay resident leaders to be lay health promoters. The TTT workshop aimed to prepare the trainees to implement and/or assist in conducting a series of community-based family well-being activities for the residents in a public low rent housing estate, entitled “Learning Families Project”, under the FAMILY project. The four-hour TTT workshop was conducted for 32 trainees (72% women, 43% aged ≥ 60, 41% ≤ elementary school education). The workshop aimed to promote trainees’ knowledge, self-efficacy, attitude and practice of incorporating the positive psychology themes into their community activities and engaging the residents to join these activities and learn with their family members. Post-training support was provided. The effectiveness of the TTT was examined by self-administered questionnaires about trainees’ reactions to training content, changes in learning and practice at three time points (baseline, and immediately and one year after training), and the difference in residents’ survey results before and after participating in the community activities delivered by the trainees. The trainees’ learning about the general concepts of family well-being, learning family, leadership skills and planning skills increased significantly with medium to large effect sizes (Cohen’s d: 0.5–1.4) immediately after the training. The effects of perceived knowledge and attitude towards practice were sustained to one year (Cohen’s d: 0.4–0.6). The application of planning skills to implement community activities was higher at one year (Cohen’s d: 0.4), compared with baseline. At one year, the residents’ survey results showed significant increases in the practice of positive communication behaviours and better neighbour cohesions after joining the family well-being activities of LFP. Qualitative feedback supported the quantitative results. Our TTT workshop could serve as a practical example of development and evaluation of training programs for lay personnel to be lay health promoters. Trial registration: ClinicalTrials.gov [ABSTRACT FROM AUTHOR]

Based on carbon spot prices selected from seven carbon pilots, we assess the financial performances related to carbon volatility in China on the overall perspective. According to the results, the Chinese carbon market fluctuated severely at the beginning of carbon trading, but has stabilised in general, despite several dramatic changes related to ‘yearly compliance events’. Long-term memory exists in the volatility series. Moreover, asymmetry exists in the Chinese carbon market, and volatility reacts more severely to good news than to bad news. Finally, we discuss our empirical results, and make certain suggestions regarding firms’ awareness, international cooperation and individual investors not only for policy makers in China but also for other developing countries who are contemplating either commencing carbon trading or improving the current market. [ABSTRACT FROM AUTHOR]

Research has found that preschoolers’ imitation demonstrates in-group bias and is guided by behavior efficacy. However, little is known about whether children’s sensitivity to behavior efficacy affects their in-group imitation. This study aimed to investigate preschoolers’ imitation tendency when group preference and behavior efficacy are in conflict. Participants were 4-year-old (N = 72) and 6-year-old (N = 72) preschoolers in China. They observed two demonstrators (one in-group and one out-group) pressing two different buttons, respectively, to turn on a music box, and were then asked to try it themselves. In the experimental condition, the out-group demonstrator always succeeded, whereas the in-group demonstrator failed half the time. The results showed that more 6-year-old children imitated the less-effective behaviors of the in-group demonstrator, whereas 4-year-old children showed no such inclination. Two control conditions confirmed that children chose to imitate in-group rather than out-group members (Control 1: both in-group and out-group demonstrators succeeded all four times), and could imitate according to efficacy (Control 2: two in-group demonstrators succeeded two and four times, respectively). These results indicated that 6-year-olds faithfully followed the in-group modeled behavior, regardless of behavior efficacy. Results are discussed through the social function of in-group imitative learning. [ABSTRACT FROM AUTHOR]

Accurately predicting reference evapotranspiration (ET0) with limited climatic data is crucial for irrigation scheduling design and agricultural water management. This study evaluated eight machine learning models in four categories, i.e. neuron-based (MLP, GRNN and ANFIS), kernel-based (SVM, KNEA), tree-based (M5Tree, XGBoost) and curve-based (MARS) models, for predicting daily ET0 with maximum/maximum temperature and precipitation data during 2001–2015 from 14 stations in various climatic regions of China, i.e., arid desert of northwest China (NWC), semi-arid steppe of Inner Mongolia (IM), Qinghai-Tibetan Plateau (QTP), (semi-)humid cold-temperate northeast China (NEC), semi-humid warm-temperate north China (NC), humid subtropical central China (CC) and humid tropical south China (SC). The results showed machine learning models using only temperature data obtained satisfactory daily ET0 estimates (on average R2 = 0.829, RMSE = 0.718 mm day−1, NRMSE = 0.250 and MAE = 0.508 mm day−1). The prediction accuracy was improved by 7.6% across China when information of precipitation was further considered, particularly in (sub)tropical humid regions (by 9.7% in CC and 12.4% in SC). The kernel-based SVM, KNEA and curve-based MARS models generally outperformed the others in terms of prediction accuracy, with the best performance by KNEA in NWC and IM, by SVM in QTP, CC and SC, and very similar performance by them in NEC and NC. SVM (1.9%), MLP (2.0%), MARS (2.6%) and KNEA (6.4%) showed relatively small average increases in RMSE during testing compared with training RMSE. SVM is highly recommended for predicting daily ET0 across China in light of best accuracy and stability, while KNEA and MARS are also promising powerful models. [ABSTRACT FROM AUTHOR]

School socioeconomic status (SES) is studied primarily as a variable to explain academic achievement; however, few previous studies have investigated how SES can influence individual student's academic achievement. The present study used a national representative sample of 10,784 grade 7 to 9 students (53.2% boys and 46.8% girls) in mainland China to examine the links between school SES and students' math and Chinese achievements, including the math and Chinese teacher-student relationships as mediating factors. The parents provided family socioeconomic information and the students reported on their teacher-student relationships. Achievements in math and Chinese were assessed using standardized tests. Multilevel mediation analyses revealed that school SES was positively related to students' math and Chinese achievements. Moreover, the link between school SES and students' math achievement was partially mediated by students' perception of the math teacher-student relationship. The Chinese teacher-student relationship had no mediating effect. This study indicated that school SES can influence individual student's academic achievement via their perception of teacher-student relationship. The poverty and lack of resources is obvious, yet low SES schools could make efforts in improving teacher-student relationship's quality to promote students' academic performance. Meanwhile, low SES schools should receive more attention from policymakers to improve teaching quality and school climate. Furthermore, the study findings could be used for future research on the gap between low and high SES schools. [ABSTRACT FROM AUTHOR]

Objective: Team-based learning (TBL) is an increasingly popular teaching method in medical education. However, TBL hasn’t been well-studied in the ophthalmology clerkship context. This study was to examine the impact of modified TBL in such context and to assess the student evaluations of TBL. Methods: Ninety-nine students of an 8-year clinical medicine program from Zhongshan Ophthalmic Centre, Sun Yat-sen University, were randomly divided into four sequential units and assigned to six teams with the same faculty. The one-week ophthalmology clerkship module included traditional lectures, gross anatomy and a TBL module. The effects of the TBL module on student performance were measured by the Individual Readiness Assurance Test (IRAT), the Group Readiness Assurance Test (GRAT), the Group Application Problem (GAP) and final examination scores (FESs). Students’ evaluations of TBL were measured by a 16-item questionnaire. IRAT and GRAT scores were compared using a paired t-test. One-way analysis of variance (ANOVA) and subgroup analysis compared the effects among quartiles that were stratified by the Basic Ophthalmology Levels (BOLs). The BOLs were evaluated before the ophthalmology clerkship. Results: In TBL classes, the GRAT scores were significantly higher than the IRAT scores in both the full example and the BOL-stratified groups. It highlighted the advantages of TBL compared to the individual learning. Quartile-stratified ANOVA comparisons showed significant differences at FES scores (P < 0.01). In terms to IRAT, GRAT and GAP scores, there was no significant result. Moreover, IRAT scores only significantly differed between the first and fourth groups. The FES scores of the first three groups are significantly higher than the fourth group. Gender-specific differences were significant in FES but not the IRAT. Overall, 57.65% of student respondents agreed that TBL was helpful. Male students tended to rate TBL higher than female students. Conclusion: The application of modified TBL to the ophthalmology clerkship curriculum improved students’ performance and increased students’ engagement and satisfaction. TBL should be further optimized and developed to enhance the educational outcomes among multi-BOLs medical students. [ABSTRACT FROM AUTHOR]

The article presents a study that evaluates the effect of remote ischemic preconditioning (RIPC) on the memory ability and spatial learning after focal cerebral ischemia-reperfusion (I/R). The study is conducted in thirty-six male Sprague-Dawley rats that were subjected to sham operations without middle cerebral artery occlussion (MCAO). The results of the study show that RIPC could improve the spatial learning ability and memory function of the study subjects.

Background: There are many discussions about dyslexia based on studies conducted in western countries, and some risk factors to dyslexia, such as gender and home literacy environment, have been widely accepted based on these studies. However, to our knowledge, there are few studies focusing on the risk factors of dyslexia in China. Therefore, the aim of our study was to investigate the prevalence of dyslexia and its potential risk factors. Methods: A cross-sectional study was conducted in Qianjiang, a city in Hubei province, China. Two stages sampling strategy was applied to randomly selected 5 districts and 9 primary schools in Qianjiang. In total, 6,350 students participated in this study and there were 5,063 valid student questionnaires obtained for the final analyses. Additional questionnaires (such as Dyslexia Checklist for Chinese Children and Pupil Rating Scale) were used to identify dyslexic children. The chi-square test and multivariate logistic regression were employed to reveal the potential risk factors to dyslexia. Results: Our study revealed that the prevalence of dyslexia was 3.9% in Qianjiang city, which is a middle-sized city in China. Among dyslexic children, the gender ratio (boys to girls) was nearly 3∶1. According to the P-value in the multivariate logistic regression, the gender (P<0.01), mother's education level (P<0.01), and learning habits (P<0.01) (active learning, scheduled reading time) were associated with dyslexia. Conclusion: The prevalence rate of dyslexic children in middle-sized cities is 3.9%. The potential risk factors of dyslexic children revealed in this study will have a great impact on detecting and treating dyslexic children in China as early as possible, although more studies are still needed to further investigate the risk factors of dyslexic children in China. [ABSTRACT FROM AUTHOR]