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Background Prevention and control of cardiometabolic conditions and cardiovascular disease (CVD) in China may contribute to sustainable CVD reduction globally, given the fact that one-fifth of the worldwide population is in China. Knowing the distribution of behavioral risk factors (e.g., smoking and physical inactivity), especially at a national level in China, would be extremely relevant to the field of public health and CVD prevention. The objectives of this study were to investigate the nationwide prevalence of obesity, smoking, heavy drinking, and physical inactivity in Chinese adults, and further explore whether cardiometabolic conditions would modify the distribution of behavioral risk factors. Methods This population-based study is based on the China Health and Retirement Longitudinal Study (2011–2012), including 17,302 adults (≥45 years, mean age 59.67 years, female 51.66%) from 25 provinces in China. Data on demographics, lifestyle factors, health status and history of diseases were collected via structured interviews and laboratory tests. Smoking, heavy drinking, obesity, and physical inactivity were defined following standard guidelines. We performed descriptive analysis and logistic regressions in this study. Results The overall prevalence of heavy drinking, obesity, current smoking, and physical inactivity among middle-aged and older adults was 7.23% (95% confidence interval 6.53—7.29%), 11.53% (10.43—12.62%), 27.46% (26.30—28.62%), and 44.06% (41.19—46.92%), respectively. The prevalence varied between rural and urban areas as well as among geographic areas, with higher prevalence in the Northern and Northeastern regions. Heavy drinking and obesity were significantly associated with incident hypertension, diabetes, and high cholesterol; while current smoking was significantly associated with incident hypertension. Compared with healthy individuals, participants who self-reported a diagnosis of hypertension, high cholesterol, or diabetes were less likely to smoke currently and drink alcohol heavily, but more likely to be physically inactive and obese. Conclusions Among Chinese middle-aged and older adults, the prevalence of behavioral risk factors varies by geographic region. Further effort is required to improve physical activity and fitness for Chinese adults, especially those with cardiometabolic conditions.

Vulnerable transmission lines are key points of cascading failures and blackouts. While the vulnerable transmission line identification is challenging due to the complexity of power system. This study puts forward a vulnerable transmission line identification method using the improved structural hole theory (named ISH method) in correlation networks, in which the interactive strengths among transmission lines under N − 1 check are considered. This method converts the vulnerable transmission line identification in power grids into key node evaluation in correlation networks. Since weighted state and structure correlation networks reflect the changes of transmission lines in operation states and topology structures before and after N − 1 check, this method is more accurate than other methods based on static complex grid. Besides, this method is very efficient for only local information is used when calculating the constraint coefficient of each node by means of the ISH theory. Numerical simulations on the IEEE-39 bus system and a regional grid of China verify the validity and accuracy of the ISH method by comparing with other methods.

Excitation curves of ultra-high-voltage-transformers under conditions of deep saturation are difficult to obtain accurately. In addition, it is difficult to directly measure the remanence of the transformer cores after de-energizing. In this paper researches are made on the above problems. By theory analysis, changes of flux linkage are calculated during energizing and de-energizing processes of transformers. The flux linkage coupling, caused by electric connection of tertiary windings of single phase transformers, is proposed. Methods are proposed to obtain excitation curves and remanences by energizing and de-energizing tests. Results of simulations and experiments show that excitation curve of the transformers under conditions of deep saturation can be corrected by above method, and the remanence after de-energizing can be estimated accurately, thus a good practicability is found for the proposed methods.

Purpose To establish a single-nucleotide polymorphism-based analysis (SBA) method to identify triploidy in the miscarriage tissue by using low-coverage whole-genome sequencing (LC-WGS). Methods The method was established by fitting a quadratic curve model by counting the distribution of three heterozygous mutation content intervals. The triploid test result was mainly determined by the opening direction and the axis of symmetry of the quadratic curve, and Z test between the same batch samples was also used for auxiliary judgment. Results Two hundred thirteen diploid samples and 8 triploid samples were used for establishment of the analytical method and 203 unknown samples were used for blind testing. In the blind testing, we found 2 cases positive for triploidy. After chromosome microarray analysis (CMA) and mass spectrometry verification, we found that both samples were true positives. We randomly selected 5 samples from the negative samples for mass spectrometry verification, and the results showed that these samples were all true negatives. Conclusions Our method achieved accurate detection of triploidy in the miscarriage tissue and has the potential to detect more chromosomal abnormality types such as uniparental disomy (UPD) using a single LC-WGS approach.

Hydro-dominated power grids such as Sichuan and Yunnan in China face many new problems in power generation scheduling that have not been encountered in the small- and medium -sized hydropower systems. This brings great challenges to the safety and efficiency of power system operations and large-scale absorption of clean energy such as hydropower. Sichuan Power Grid whose hydropower capacity ranks first in the country is taken as the background. With its hydropower status and actual operation requirements, this study analyzes several main problems of hydro-dominated power system operations, including curse of dimensionality of large-scale hydropower plants, generation safety control of giant hydropower units, hydropower transmission and absorption in flood season, and coordinated operations of inter-provincial hydropower plants on main streams. With the theory of hydropower optimization and practical experiences, this study also puts forward appropriate suggestions and strategies.

One of the main problems in the future about the development of micro-grid is the stability of micro-grid with static synchronous compensators(STATCOM). In this paper, a two-degree-of-freedom internal model control (2DOF-IMC) controller, which can improve the tracking performance and robustness of STATCOM, is designed to replace traditional PI controller in STATCOM to steady voltage of microgrid. Compare and analyze the effects of STATCOM with two controllers on the voltage stability of islanded micro-grid by impedance method. The analysis and simulate results show that STATCOM with 2DOF-IMC controller can effectively improve the stability of the microgrid voltage.

In order to make the dynamic equivalent method for hydropower generator group based on phasor measurement information more suitable for the actual grid. A index use tie-line power oscillation to evaluate disturbance intensity is presented .Based on this index, consider disturbance location and it’s distance to the equivalent area, a disturbance selection method is proposed. Based on the equivalent method, dynamic equivalent online identification system is developed. The disturbance selection method proposed is verified using PMU measured disturbances data of Sichuan power grid China. Introduction Along with the increase of phasor measurement device(PMU) in the real power system, dynamic equivalent for hydropower generator group based on phasor measurement information has a broad application prospect. Dynamic equivalence is one of the most traditional research direction of power system, a large amount of research on the system dynamic equivalent model and parameter identification method are studied by many scholars and achieved abundant research results. But there is a little research on the application problem of equivalent in real power system . Reference 1-2 used 39 bus system with 10 generators to verify equivalent method the paper proposed; reference 3 did research on the equivalent method application in Tianjin power grid China, but disturbance selection is not involved . Existing literatures verify their equivalent method in simulation software generally. There is little Reference studies the application of equivalent method and disturbance selection in actual power grid, which affect the application of the equivalent method and the accuracy of equivalent. Therefore, this paper researches on dynamic equivalent for hydropower generator group based on phasor measurement information of tie-line. A index use tie-line power oscillation to evaluate disturbance intensity is presented, based on this index, consider disturbance location and it’s distance to the equivalent area, a disturbance selection method is proposed. And dynamic equivalent modeling software is developed. The equivalent method and disturbance selection method proposed is verified using PMU measured disturbances data of Sichuan power grid . Example analysis shows that disturbance data selection and dynamic equivalent method are effective and feasible. The method can make hydropower generator group dynamic characteristics simulation more accurate. Review of the dynamic equivalent method According to reference 4, the basic dynamic equivalent method for hydropower generator group based on phasor measurement information proposed in this paper can be concluded as follows: 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer (MMEBC 2016) © 2016. The authors Published by Atlantis Press 2192

A novel low voltage ride-through (LVRT) scheme for PMSG-based wind turbines based on the Resistor Superconducting Fault Current Limiter (R-SFCL) is proposed in this paper. The LVRT scheme is mainly formed by R-SFCL in series between the transformer and the Grid Side Converter (GSC), and basic modelling has been discussed in detail. The proposed LVRT scheme is implemented to interact with PMSG model in PSCAD/EMTDC under three phase short circuit fault condition, which proves that the proposed scheme based on R-SFCL can improve the transient performance and LVRT capability to consolidate grid connection with wind turbines.

Hashing methods have been widely applied for fast retrieval and efficient data storage. However, most existing hashing methods have not taken the discriminative features into account in nearest neighbors search which leads to unsatisfied retrieval accuracy, especially for high-dimensional dataset. In order to take best use of discriminative information, we introduce an effective feature extraction framework for hashing that can get high retrieval accuracy in this paper. Firstly, the divergence between two classes is represented by the ratio of signal to noise. Then the discriminative features of high-dimensional data are obtained through the generalized eigen-decomposition. Finally, we exploit the discriminative feature into hashing methods to generate compact binary code. Experimental results on data sets show that the proposed framework can reach better results in comparison with state-of-the-art methods.

Hashing methods play an important role in large-scale image retrieval, and have been widely applied due to fast approximate nearest neighbor search and efficient data storage. However, most existing hashing methods are not taken the low-dimensional manifold into account in nearest neighbors search. In this paper, we propose an effective hashing method to preserve the intrinsic structure of high-dimensional data points in the low-dimensional manifold space. In particular, we introduce a compressed algorithm to learn a smaller synthetic data set represent the database in the original space so that the approximated nearest neighbors can be quickly discovered. To this end, we exploit the manifold learning generate appropriate binary code. Experimental results on benchmark data sets show that the proposed approach is effective in comparison with state-of-the-art methods.

The dynamics of modern interconnected power system is characterized by low frequency oscillations (LFOs) which are produced as results of various disturbances such as changes in loads, tripping of lines, faults, and other discrete events. A data-driven empirical mode decomposition (EMD) method is applied to the detection of low frequency oscillation modes from disturbed trajectory with its strong non-stationary signal processing capability, but the mode mixing phenomenon serious impact on the analysis credibility and accuracy of EMD method. In this paper, an anti mode mixing EMD composite algorithm is proposed for detecting the characteristics of LFOs in power system. First, the improved frequency heterodyne method is proposed to increase the spectral distance between adjacent mode components in order to meet the octave resolution requirements. Second, the wavelet singularity detection technology is proposed to determine the adaptive sliding analysis window for each mode, in which there implements the intermittency mixed modes separation and their nonstationary parameters identification. Finally, the analysis result of interconnected grid test case verify that the proposed algorithm can effectively overcome the impact of the mode mixing existed in EMD and improve the characteristics detection accuracy of LFOs characteristics. DOI: http://dx.doi.org/10.11591/telkomnika.v11i8.3134

Both SVC (Static Var Compensator) and STATCOM (Static Synchronous Compensator) are important equipment of reactive compensation, which are compared in voltage supporting, improving the transient stability and transmission limit, and damping low frequency oscillation. Simulation results are presented as high capacity static var system for SVC or STATCOM is placed on transmission path of power system. Firstly, single SVC and STATCOM are limited in voltage supporting after fault occurrence, but STATCOM is little better than SVC. Secondly, STATCOM is much better than SVC in improving the transient stability and transmission limit. Thirdly, on the damping low frequency oscillation, STATCOM is much better than SVC as SVC and STATCOM have the same capacity, and performs similarly with SVC as the two have the same controllable capacity. Lastly, the results also indicate that dynamical response speed effects the control result little though STATCOM responses much faster than SVC.

This paper proposes a method of solving the task assignment of high-speed handling system to multiple robots. In order to reduce the state space and improve the efficiency of learning, an improved Q-learning algorithm based on peer to peer SAP is designed. In the proposed algorithm, all the Q value of the peer to peer SAP are updated after take an action, and these Q value are required only one memory unit. Compare to the standard Q-learning algorithm, the results demonstrate the efficiency of the proposed algorithm.