Does Exam-targeted Training Help Village Doctors Pass the Certified (Assistant) Physician Exam and Improve Their Practical Skills? A Cross-sectional Analysis of Village Doctors\u27 Perspectives in Changzhou in Eastern China

Background Quality of health care needs to be improved in rural China. The Chinese government, based on the 1999 Law on Physicians, started implementing the Rural Doctor Practice Regulation in 2004 to increase the percentage of certified physicians among village doctors. Special exam-targeted training for rural doctors therefore was launched as a national initiative. This study examined these rural doctors’ perceptions of whether that training helps them pass the exam and whether it improves their skills. Methods Three counties were selected from the 4 counties in Changzhou City in eastern China, and 844 village doctors were surveyed by a questionnaire in July 2012. Chi-square test and Fisher exact test were used to identify differences of attitudes about the exam and training between the rural doctors and certified (assistant) doctors. Longitudinal annual statistics (1980–2014) of village doctors were further analyzed. Results Eight hundred and forty-four village doctors were asked to participate, and 837 (99.17%) responded. Only 14.93% of the respondents had received physician (assistant) certification. Only 49.45% of the village doctors thought that the areas tested by the certification exam were closely related to the healthcare needs of rural populations. The majority (86.19%) felt that the training program was “very helpful” or “helpful” for preparing for the exam. More than half the village doctors (61.46%) attended the “weekly school”. The village doctors considered the most effective method of learning was “continuous training (40.36%)” . The majority of the rural doctors (89.91%) said they would be willing to participate in the training and 96.87% stated that they could afford to pay up to 2000 yuan for it. Conclusions The majority of village doctors in Changzhou City perceived that neither the certification exam nor the training for it are closely related to the actual healthcare needs of rural residents. Policies and programs should focus on providing exam-preparation training for selected rural doctors, reducing training expenditures, and utilizing web-based methods. The training focused on rural practice should be provided to all village doctors, even certified physicians. The government should also adjust the local licensing requirements to attract and recruit new village doctors

Enabling Quality Control for Entity Resolution: A Human and Machine Cooperation Framework

Even though many machine algorithms have been proposed for entity resolution, it remains very challenging to find a solution with quality guarantees. In this paper, we propose a novel HUman and Machine cOoperation (HUMO) framework for entity resolution (ER), which divides an ER workload between the machine and the human. HUMO enables a mechanism for quality control that can flexibly enforce both precision and recall levels. We introduce the optimization problem of HUMO, minimizing human cost given a quality requirement, and then present three optimization approaches: a conservative baseline one purely based on the monotonicity assumption of precision, a more aggressive one based on sampling and a hybrid one that can take advantage of the strengths of both previous approaches. Finally, we demonstrate by extensive experiments on real and synthetic datasets that HUMO can achieve high-quality results with reasonable return on investment (ROI) in terms of human cost, and it performs considerably better than the state-of-the-art alternatives in quality control.Comment: 12 pages, 11 figures. Camera-ready version of the paper submitted to ICDE 2018, In Proceedings of the 34th IEEE International Conference on Data Engineering (ICDE 2018

Age Is Important for the Early-Stage Detection of Breast Cancer on Both Transcriptomic and Methylomic Biomarkers

Patients at different ages have different rates of cell development and metabolisms. As a result, age should be an essential part of how a disease diagnosis model is trained and optimized. Unfortunately, most of the existing studies have not taken age into account. This study demonstrated that disease diagnosis models could be improved by merely applying individual models for patients of different age groups. Both transcriptomes and methylomes of the TCGA breast cancer dataset (TCGA-BRCA) were utilized for the analysis procedure of feature selection and classification. Our experimental data strongly suggested that disease diagnosis modeling should integrate patient age into the whole experimental design

Thermoplasmatales and Methanogens: Potential Association with the Crenarchaeol Production in Chinese Soils

Crenarchaeol is a unique isoprenoid glycerol dibiphytanyl glycerol tetraether (iGDGT) lipid, which is only identified in cultures of ammonia-oxidizing Thaumarchaeota. However, the taxonomic origins of crenarchaeol have been debated recently. The archaeal populations, other than Thaumarchaeota, may have associations with the production of crenarchaeol in ecosystems characterized by non-thaumarchaeotal microorganisms. To this end, we investigated 47 surface soils from upland and wetland soils and rice fields and another three surface sediments from river banks. The goal was to examine the archaeal community compositions in comparison with patterns of iGDGTs in four fractional forms (intact polar-, core-, monoglycosidic- and diglycosidic-lipid fractions) along gradients of environments. The DistLM analysis identified that Group I.1b Thaumarchaeota were mainly responsible for changes in crenarchaeol in the overall soil samples; however, Thermoplasmatales may also contribute to it. This is further supported by the comparison of crenarchaeol between samples characterized by methanogens, Thermoplasmatales or Group I.1b Thaumarchaeota, which suggests that the former two may contribute to the crenarchaeol pool. Last, when samples containing enhanced abundance of Thermoplasmatales and methanogens were considered, crenarchaeol was observed to correlate positively with Thermoplasmatales and archaeol, respectively. Collectively, our data suggest that the crenarchaeol production is mainly derived from Thaumarchaeota and partly associated with uncultured representatives of Thermoplasmatales and archaeol-producing methanogens in soil environments that may be in favor of their growth. Our finding supports the notion that Thaumarchaeota may not be the sole source of crenarchaeol in the natural environment, which may have implication for the evolution of lipid synthesis among different types of archaea

Reliability modelling for electricity transmission networks using maintenance records

Maintenance decisions for transmission network assets (TNAs) require accurate reliability prediction of complex repairable systems. There are a number of factors influencing the reliability prediction for TNAs, which includes structure characteristics (e.g. conductor type), voltage, load, and the operating environment (mechanical loading, wind, temperature, pollutants and humidity). The reliability analysis and prediction is complicated by the fact that TNAs are linear assets (as opposed to discrete assets) which require specific modelling approaches for reliability prediction. This paper details a new reliability prediction model for TNAs. Another challenge is that transmission network is hardly fail. Instead of using outage data, where most reliability model used, failure times were identified through extracting significant unplanned maintenance events for critical failure modes. A regression tree based grouping analysis was utilized to analyse the influences by variety of factors on future unplanned maintenance. These results were then used to build the reliability prediction model allowing a decision maker to have an estimate of future unplanned maintenance requirements. A case study using real industry data was conducted to test the proposed reliability prediction model. The results demonstrate the feasibility of using this approach for TNA maintenance decision support

Maximum likelihood estimation-assisted ASVSF through state covariance-based 2D SLAM algorithm

The smooth variable structure filter (ASVSF) has been relatively considered as a new robust predictor-corrector method for estimating the state. In order to effectively utilize it, an SVSF requires the accurate system model, and exact prior knowledge includes both the process and measurement noise statistic. Unfortunately, the system model is always inaccurate because of some considerations avoided at the beginning. Moreover, the small addictive noises are partially known or even unknown. Of course, this limitation can degrade the performance of SVSF or also lead to divergence condition. For this reason, it is proposed through this paper an adaptive smooth variable structure filter (ASVSF) by conditioning the probability density function of a measurementto the unknown parameters at one iteration. This proposed method is assumed to accomplish the localization and direct point-based observation task of a wheeled mobile robot, TurtleBot2. Finally, by realistically simulating it and comparing to a conventional method, the proposed method has been showing a better accuracy and stability in term of root mean square error (RMSE) of the estimated map coordinate (EMC) and estimated path coordinate (EPC)