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Background Lean body mass has been identified as a key determinant of left ventricular mass and wall thickness. However, the importance of lean body mass or other body‐size measures as normative determinants of carotid intima‐media thickness ( cIMT ), a widely used early indicator of atherosclerosis, has not been well established. Methods and Results Carotid artery ultrasound measurements of cIMT and carotid artery plaque burden (derived from plaque number and maximum size) and measurements of body size, including height, body mass index, weight, body fat proportion, and lean body mass ([1−body fat proportion]×weight), were recorded in 25 020 participants from 10 regions of China. Analyses were restricted to a healthy younger subset (n=6617) defined as never or long‐term ex‐regular smokers aged cIMT , but was not associated with plaque burden: overall, each 10 kg higher lean body mass was associated with a 0.03 (95% CI , 0.03–0.04) mm higher cIMT ( P =5×10 −33 ). Fat mass, height, and other body‐size measures were more weakly associated with cIMT . Conclusions The strong association of lean body mass with cIMT, but not with plaque burden, in healthy adults suggests a normative relationship rather than reflecting atherosclerotic pathology. Common mechanisms may underlie the associations of lean body mass with cIMT and with nonatherosclerotic vascular traits.

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Based on multi-scenario technique, a reliability analysis method considering the operating strategy of grid-connected microgrid in the market environment is proposed in this paper. First, an optimal operation model for the microgrid managed by microgrid operator is presented. Then, impacts of power and load level on failure rate in different time periods were considered in utilizing the time-dependent component reliability model. According to multi-scenario technique, the randomness and time sequential correlation of the power, load and price are taken into account. A practical case study was employed to verify the effectiveness of the method and model proposed on the modified BUS6 system on the IEEE-RBTS test system. The Simulation results show that the optimal operation of grid-connected microgrid can improve microgrid reliability generally.

The economic and reliable operation of distribution network relies on state variables information from state estimator. However, since the amount of distributed generation (DG) and electric vehicles connected to distribution network is steadily growing, the distribution network is full of randomness and volatility, which increases the difficulty of accurate state estimation. In this paper, a dynamic state estimation (DSE) algorithm based on unscented particle filter (UPF) is proposed. This algorithm uses the unscented Kalman filter (UKF) estimated results as the proposal distribution of particle filter (PF), and updates the latest measurements information in the process of generating predictive particles, which makes the distribution of particles much closer to the posterior probability distribution of true states. At the same time, a pseudo measurement model based on spiking neural network (SNN) is established, which outputs the pseudo measurement load at each sampling moment to enhance the accuracy of state estimation. The simulation results show that the proposed algorithm can effectively track the true value of distribution network states and is superior to the traditional DSE algorithm in estimation accuracy and noise robustness.

Power grid dispatching is a high-risk process, and its execution depends on an available cyber system. However, the effects of cyber systems have not caught enough attention in current research on risk assessments in dispatching processes, which may cause optimistic risk results. In order to solve this problem, this paper proposes a risk assessment model that considers the impact of a cyber system on power grid dispatching processes. Firstly, a cyber-physical switchgear state model that integrates the reliability states of both cyber system functions and switchgears is proposed, based on the transition of switchgear states in the dispatching process. Then, the potential effects of each operating step on power grid states are analyzed considering the failure model of cyber-physical system (CPS) components. The risk probabilities and consequences of the power grid states are calculated to quantify the risk index. Finally, the workings and effectiveness of this model are illustrated using the IEEE Reliability Test System-1979.

We report two rare cases of multiple myeloma (MM) with dural intracranial disease and TP53 deletion. The two patients presented with skull lytic lesion and dural involvement of myeloma. The association between intracranial involvement in MM and TP53 deletion has not been determined. The two patients received bortezomib-based intensive induction and got good response, just as that reported in literature. MM presenting with dural intracranial disease and TP53 deletion at diagnosis is associated with poor outcome. Multi-drug regime containing bortezomib followed by autologous or allogeneic stem cell transportation would improve the prognosis.两例初治多发性骨髓瘤伴颅内侵犯的患者起病均以中枢神经系统功能受损为临床表现，颅骨受到破坏的同时存在多发硬膜侵犯。伴TP53缺失的遗传学异常与颅内侵犯的相关性，尚无定论。患者均接受含硼替佐米、阿霉素的多药联合方案，取得良好的短期疗效，与文献报道符合。TP53缺失的初治多发性骨髓瘤伴颅内侵犯预后不良。以硼替佐米为基础的强化学药物治疗方案联合自体或异基因造血干细胞移植有望提高临床疗效。.

In view of the adverse impacts on the power grid dispatching, energy management and other aspects caused by the volatility, intermittence and uncertainty of photovoltaic (PV) power generation, this paper proposes a novel short-term PV power forecasting method based on K-means algorithm and spiking neural networks (SNN). Considering meteorological factors and seasonal characteristics, this approach utilizes the K-means algorithm to cluster different short-term PV power generation characteristics and implements SNN training with different kinds of PV power generation data obtained from clustering results. In addition, an improved particle swarm optimization (PSO) algorithm is employed to globally optimize the synaptic weights of SNN, which enhances the pattern recognition ability and numerical stability of the forecasting model. We assess the performance of the proposed method by using actual PV power generation data in a certain area for simulation analysis. The simulation results illustrate that the proposed method can achieve a better prediction accuracy than the conventional BP neural network and support vector machine (SVM), and performs excellent engineering application potential.

The article analysed and studied the structure performance and mathematical model of the permanent magnet synchronous motor, and it further researched the principle of vector control technology and the SVPWM algorithm on this basis. A closed-loop simulation model of permanent magnet synchronous motor speed/current was built. The waveform of the simulation result is consistent with the theoretical analysis, which verifies the effectiveness of the simulation experiment platform and mathematical model. It also verifies the superiority of the id=0 control algorithm and vector control. A theory for the research and design of the permanent magnet synchronous motor vector control system basis is provided.

To overcome the low precision and poor flexibility of the wind power scenario model, this paper proposes a nonlinear two-cluster Gaussian mixture scenario model for wind power based on the expectation maximization (EM) algorithm according to Wasserstein optimal scenario theory. First, the EM algorithm is used to classify the wind speed data and establish the Gaussian mixture model (GMM). Second, the Wasserstein distance scenarios of two Gaussian distributions with different parameters are calculated based on wind speed data and nonlinear wind turbine power curve, respectively. Finally, a cross combination of the two scenarios is used to obtain the nonlinear two-cluster mixture scenario model with a mixture Gaussian probability parameters. The obtained results show that the nonlinear two-cluster Gaussian mixture scenario model is applicable not only to the regular wind speed probability distribution but also to that with irregular and two-peak characteristics. Moreover, the generated energy deviation can be controlled within 2.5%. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Aims/hypothesis In women, higher parity has been associated with increased risk of diabetes later in life. It is unclear, however, whether this association is mainly due to biological effects of childbearing, or to socioeconomic and lifestyle factors associated with childrearing. We assessed the association between number of children and diabetes risk separately in women and men. Methods Between 2004 and 2008, the nationwide China Kadoorie Biobank recruited 0.5 million individuals aged 30–79 (mean 51 years) from ten diverse regions across China. During 7 years of follow-up, 8,840 incident cases of diabetes were recorded among 463,347 participants without prior cardiovascular diseases or diabetes. Multivariable Cox regression yielded sex-specific HRs and 95% CIs for incident diabetes by number of children. Results Overall, ∼98% of all participants had children. In women, there was a J-shaped association between number of children and risk of diabetes. Compared with women with one child, the adjusted HRs for diabetes were 1.39 (95% CI 1.11, 1.73) for childless women, 1.12 (95% CI 1.07, 1.18) for those with two children, 1.23 (95% CI 1.16, 1.31) for those with three children, and 1.32 (95% CI 1.21, 1.44) for those with four or more children. In men, there was a similar association with risk of diabetes; the corresponding HRs were 1.28 (95% CI 1.02, 1.60), 1.19 (95% CI 1.12, 1.26), 1.32 (95% CI 1.21, 1.44) and 1.41 (95% CI 1.24, 1.60), respectively. In both sexes, the findings were broadly similar in different population subgroups. Conclusions/interpretation The similarity between women and men in the association between number of children and risk of diabetes suggests that parenthood is most likely to affect diabetes risk through factors associated with childrearing rather than via biological effects of childbearing. Electronic supplementary material The online version of this article (doi:10.1007/s00125-016-3980-x) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

Crop plant architecture plays a highly important role in its agronomic performance. Plant height (PH) and primary branch number (PB) are two major factors that affect the plant architecture of rapeseed (Brassica napus). Previous studies have shown that these two traits are controlled by multiple quantitative trait loci (QTL); however, QTLs have not been delimited to regions less than 10cM. Genome-wide association study (GWAS) is a highly efficient approach for identifying genetic loci controlling traits at relatively high resolution. In this study, variations in PH and PB of a panel of 472 rapeseed accessions that had previously been analyzed by a 60k SNP array were investigated for three consecutive years and studied by GWAS. Eight QTLs on chromosome A03, A05, A07 and C07 were identified for PH, and five QTLs on A01, A03, A07 and C07 were identified for PB. Although most QTLs have been detected in previous studies based on linkage analyses, the two QTLs of PH on A05 and the QTL of PB on C07 were novel. In the genomic regions close to the GWAS peaks, orthologs of the genes involved in flower development, phytohormone biosynthesis, metabolism and signaling in Arabidopsis were identified.

With the rapid development of the smart grid, a large number of intelligent sensors and meters have been introduced in distribution network, which will inevitably increase the integration of physical networks and cyber networks, and bring potential security threats to the operating system. In this paper, the functions of the information system on distribution network are described when cyber attacks appear at the intelligent electronic devices (lED) or at the distribution main station. The effect analysis of the distribution network under normal operating condition or in the fault recovery process is carried out, and the reliability assessment model of the distribution network considering cyber attacks is constructed. Finally, the IEEE-33-bus distribution system is taken as a test system to presented the evaluation process based on the proposed model.

Cyber system is indispensable in guaranteeing the security operation of power system, which reminds the need to analyze the impact of cyber system failure on power grid cascading blackout. According to different functions, the cyber system is divided into three parts, which are monitoring, controlling and protecting respectively. Then, the states of the cyber system and the physical system are sampled to simulate cascading outage based on failure probabilities of the power components and the failure model of the cyber system. Finally, the proposed method is verified on the IEEE RTS-79 system. The numerical results show that cyber system failure usually accelerates cascading blackouts, and the loss of blackouts increase with the increase of failure probability of cyber system.

Owning to the intelligence and complexity of modern distribution network, determining and applying the key factors to improve the reliability of distribution network effectively and correctly is a difficult task. Based on acquired data of distribution network, a data mining method for key factors extraction of distribution network reliability is proposed in this paper. The factor analysis is used to reduce the dimension of raw data matrix, and effective factors of distribution network are found. The association rules mining is used to analyze the relevance between effective factors and reliability indices and the key factors are determined. Case study shows that the proposed method is effective and feasible.

Rationale Little evidence from large-scale cohort studies exists about the relationship of solid fuel use with hospitalization and mortality from major respiratory diseases. Objectives To examine the associations of solid fuel use and risks of acute and chronic respiratory diseases. Methods A cohort study of 277,838 Chinese never-smokers with no prior major chronic diseases at baseline. During 9 years of follow-up, 19,823 first hospitalization episodes or deaths from major respiratory diseases, including 10,553 chronic lower respiratory disease (CLRD), 4,398 chronic obstructive pulmonary disease (COPD), and 7,324 acute lower respiratory infection (ALRI), were recorded. Cox regression yielded adjusted hazard ratios (HRs) for disease risks associated with self-reported primary cooking fuel use. Measurements and Main Results Overall, 91% of participants reported regular cooking, with 52% using solid fuels. Compared with clean fuel users, solid fuel users had an adjusted HR of 1.36 (95% confidence interval, 1.32–1.40) for major respiratory diseases, whereas those who switched from solid to clean fuels had a weaker HR (1.14, 1.10–1.17). The HRs were higher in wood (1.37, 1.33–1.41) than coal users (1.22, 1.15–1.29) and in those with prolonged use (≥40 yr, 1.54, 1.48–1.60; Conclusions Among Chinese adults, solid fuel use for cooking was associated with higher risks of major respiratory disease admissions and death, and switching to clean fuels or use of ventilated cookstoves had lower risk than not switching.

Rapeseed (Brassica napus L.) is an important oil-producing crop for the world. Its adaptation, yield and quality have been considerably improved in recent decades, but the genomic basis underlying successful breeding selection remains unclear. Hence, we conducted a comprehensive genomic assessment of rapeseed in the breeding process based on the whole-genome resequencing of 418 diverse rapeseed accessions. We unraveled the genomic basis for the selection of adaptation and agronomic traits. Genome-wide association studies identified 628 associated loci-related causative candidate genes for 56 agronomically important traits, including plant architecture and yield traits. Furthermore, we uncovered nonsynonymous mutations in plausible candidate genes for agronomic traits with significant differences in allele frequency distributions across the improvement process, including the ribosome recycling factor (BnRRF) gene for seed weight. This study provides insights into the genomic basis for improving rapeseed varieties and a valuable genomic resource for genome-assisted rapeseed breeding.

Although the power system is becoming more intelligent, accidents caused by human factors occur frequently in electrical operation. Therefore, it is necessary to evaluate the working status of the dispatcher. According to the actual situation of power grid dispatching, a status index system of dispatcher is established. Then a working status evaluation model of dispatcher based on the fuzzy comprehensive evaluation method is proposed, which can be used as an auxiliary analysis tool for dispatching operation risk and management process. In the proposed model, the impact of factors such as mental state, working ability and working environment on the dispatcher are synthetically considered. According to assessment results, some improvements can be taken to address these significant affecting indicators, which will substantially improve the working status of dispatcher and help to reduce the risk level of the dispatching operation.

Aiming at the complexity and ambiguity of the risk of substation operation, a risk assessment method of substation operation based on the triangular fuzzy number AHP method and cloud model is presented. The risk assessment of substation operation is a complex multi-factor comprehensive evaluation process. Based on the principle of system engineering, the risk assessment index system for substation operation is established in four aspects: “man, machine, environment and management”. Triangular fuzzy number AHP (Analytic Hierarchy Process) is applied to calculate the weight for each index and backward cloud generator is used to transform the marking results of experts into the numerical characteristics of the cloud model for each index. The comprehensive cloud picture and the whole evaluation cloud picture are produced by the positive cloud generator. The results show that the proposed indexes and evaluation method can reflect the risk level of substation operation intuitively, flexibly and accurately.

The glyoxalase pathway is composed of glyoxalase I (GLYI) and glyoxalase II (GLYII) and is responsible for the detoxification of a cytotoxic metabolite methylglyoxal (MG) into the nontoxic S-D-lactoylglutathione. The two glyoxalase enzymes play a crucial role in stress tolerance in various plant species. Recently, the GLY gene families have well been analyzed in Arabidopsis, rice and soybean, however, little is known about them in Chinese cabbage (Brassica rapa). Here, 16 BrGLYI and 15 BrGLYII genes were identified in the B. rapa genome, and the BrGLYI and BrGLYII proteins were both clustered into five subfamilies. The classifications, chromosomal distributions, gene duplications, exon-intron structures, localizations, conserved motifs and promoter cis-elements were also predicted and analyzed. In addition, the expression pattern of these genes in different tissues and their response to biotic and abiotic stresses were analyzed using publicly available data and a quantitative real-time PCR analysis (RT-qPCR). The results indicated that the expression profiles of BrGLY genes varied among different tissues. Notably, a number of BrGLY genes showed responses to biotic and abiotic stress treatments, including Plasmodiophora brassicae infection and various heavy metal stresses. Taken together, this study identifies BrGLYI and BrGLYII gene families in B. rapa and offers insight into their roles in plant development and stress resistance, especially in heavy metal stress tolerance and pathogen resistance.

ObjectivesThis study aims to develop assessment indicators of health education and promotion for non-communicable disease (NCD) demonstration districts in China and to identify significant factors associated with NCD health education and promotion work.MethodsThree complementary techniques were used to conduct this study in Hunan Province, China, between late 2013 and 2015. The Delphi technique was used to develop weighted assessment indicators, followed by the rank sum ratio (RSR) to normalise the weights through rank conversion. Lastly, the technique for order of preference by similarity to ideal solution was conducted to assess five randomly selected NCD demonstration districts representing five different orientations in the province.ResultsA total of 24 assessment indicators were constructed covering the following sections: organisational management, fund support, personnel supplies, health education and promotion, people’s awareness of NCDs, management and control of patients with NCD, satisfaction with health education and promotion and health literacy of residents. Five districts were selected as samples for evaluation (Furong District, Ziyang District, Shaodong County, Shuangfeng County and Luxi County). Performance varied among the sites, with Furong District greatly surpassing the other sites, especially in fund support, media promotion, technical support for publicity materials, community promotion and supportive environment supplies. The latter four factors were also much greater in the second-ranked Luxi County site than those in the other sites (except Furong District).ConclusionsThere were gaps in health education and promotion work in NCD demonstration districts in Hunan Province. The districts that performed better had obvious advantages in fund support, media promotion, technical support, community promotion and supportive environment supplies. Our study provided both a methodological reference and an assessment indicator framework for similar future studies.

With the development of power and information technology, the impact of network attacks on the power infrastructure has gradually become a hot issue at home and abroad. In order to measure the risk caused by network attack to power facilities, this paper proposes a risk assessment model for distribution network considering network attack. In this paper, firstly, the definition of attack object, network attack pattern and attack consequence are defined. Secondly, the risk assessment index of distribution network is put forward. And then, Monte Carlo method is used to simulate the network attack scene, that is, attack the elements in the target component set with a certain probability. Finally, the risk index of distribution network is calculated by the proposed evaluation model, and the risk assessment of distribution network is completed. The proposed model can deeply reveal the security level of power grid under network attack. The validity and feasibility of the proposed method are verified by an example of IEEE-33 node distribution system.

In the opening electricity market, distributed generation can be used as reserve capacity, which can help to improve the reliability of distributed network. A reliability price and compensation model for distribution network with distributed generation is proposed in this paper, where the interests of both the power supplier and the customer is fully considered, and the investment cost is apportioned according to the customer's reliability requirements to obtain the reliability price. In addition, this method considers the outage cost of unit electricity as a variable that varies with the duration of power outages, which breaks the traditional idea that the outage cost of unit electricity regarded as a fixed value. Furthermore, the value engineering theory is used to derive the formula of reliability compensation, and the reliability compensation mechanism for distribution network with distributed generation is constructed. Finally, an example on RBTS-BUS6 system is presented to show the validity and practicability of the proposed method.

An alternating-direction implicit finite-difference (ADI-FDTD) based time-domain inverse algorithm is proposed in this paper. The imaging algorithm based on forward-backward time-stepping (FBTS) method. By comparing the processing results, it was found that the proposed ADI-FDTD method can substitute for the conventional finite-difference time-domain (FDTD) method, strongly validating the former's usefulness and accuracy. Moreover, processing time can be reduced significantly for microwave tomography.

Background Self‐rated health ( SRH ) is a strong predictor of mortality in different populations. However, the associations between SRH measures and risk of ischemic heart disease ( IHD ) have not been extensively explored, especially in a Chinese population. Methods and Results More than 500 000 adults from 10 cities in China were followed from baseline (2004–2008) through December 31, 2013. Global and age‐comparative SRH were reported from baseline questionnaires. Incident IHD cases were identified through links to well‐established disease registry systems and the national health insurance system. During 3 423 542 person‐years of follow‐up, we identified 24 705 incident cases of IHD . In multivariable‐adjusted models, both global and age‐comparative SRH was significantly associated with incident IHD . Compared with excellent SRH , the hazard ratios for good, fair, and poor SRH were 1.02 (95% confidence interval [CI], 0.98–1.07), 1.32 (95% CI, 1.27–1.37), and 1.76 (95% CI, 1.68–1.85), respectively. Compared with better age‐comparative SRH , the hazard ratios for same and worse age‐comparative SRH were 1.23 (95% CI, 1.19–1.27) and 1.78 (95% CI, 1.70–1.86), respectively. The associations persisted in all subgroup analyses, although they were slightly modified by study location, education, and income levels. Conclusions A simple questionnaire for self‐assessment of health status was significantly associated with incident IHD in Chinese adults. Individuals and healthcare providers can use SRH measures as a convenient tool for assessing future IHD risk.

BACKGROUND: Adherence to a combination of healthy lifestyle factors has been related to a considerable reduction of cardiovascular risk in white populations; however, little is known whether such associations persist in nonwhite populations like the Asian population. OBJECTIVES: This study aimed to examine the associations of a combination of modifiable, healthy lifestyle factors with the risks of ischemic cardiovascular diseases and estimate the proportion of diseases that could potentially be prevented by adherence to these healthy lifestyle patterns. METHODS: This study examined the associations of 6 lifestyle factors with ischemic heart disease and ischemic stroke (IS) in the China Kadoorie Biobank of 461,211 participants 30 to 79 years of age who did not have cardiovascular diseases, cancer, or diabetes at baseline. Low-risk lifestyle factors were defined as nonsmoking status or having stopped smoking for reasons other than illness, alcohol consumption of

Plant architecture is vital not only for crop yield, but also for field management, such as mechanical harvesting. The branch angle is one of the key factors determining plant architecture. With the aim of revealing the genetic control underlying branch angle in rapeseed (Brassica napus L.), the positional variation of branch angles on individual plants was evaluated, and the branch angle increased with the elevation of branch position. Furthermore, three middle branches of individual plants were selected to measure the branch angle because they exhibited the most representative phenotypic values. An association panel with 472 diverse accessions was estimated for branch angle trait in six environments and genotyped with a 60K Brassica Infinium® SNP array. As a result of association mapping, 46 and 38 significantly-associated loci were detected using a mixed linear model (MLM) and a multi-locus random-SNP-effect mixed linear model (MRMLM), which explained up to 62.2 and 66.2% of the cumulative phenotypic variation, respectively. Numerous highly-promising candidate genes were identified by annotating against Arabidopsis thaliana homologous, including some first found in rapeseed, such as TAC1, SGR1, SGR3, and SGR5. These findings reveal the genetic control underlying branch angle and provide insight into genetic improvements that are possible in the plant architecture of rapeseed.

Considerable genome variation had been incorporated within rapeseed breeding programs over past decades. In past decades, there have been substantial changes in phenotypic properties of rapeseed as a result of extensive breeding effort. Uncovering the underlying patterns of allelic variation in the context of genome organisation would provide knowledge to guide future genetic improvement. We assessed genome-wide genetic changes, including population structure, genetic relatedness, the extent of linkage disequilibrium, nucleotide diversity and genetic differentiation based on F ST outlier detection, for a panel of 472 Brassica napus inbred accessions using a 60 k Brassica Infinium® SNP array. We found genetic diversity varied in different sub-groups. Moreover, the genetic diversity increased from 1950 to 1980 and then remained at a similar level in China and Europe. We also found ~6–10 % genomic regions revealed high F ST values. Some QTLs previously associated with important agronomic traits overlapped with these regions. Overall, the B. napus C genome was found to have more high F ST signals than the A genome, and we concluded that the C genome may contribute more valuable alleles to generate elite traits. The results of this study indicate that considerable genome variation had been incorporated within rapeseed breeding programs over past decades. These results also contribute to understanding the impact of rapeseed improvement on available genome variation and the potential for dissecting complex agronomic traits.

It is important to evaluate yield and agronomic traits when selecting for elite lines in Brassica napus L. In this study, 488 global collections of B. napus L. were evaluated for yield and agronomic traits during two consecutive years under growing conditions in central China. A series of phenotypic data for yield and agronomic traits were obtained. Large variations in yield and agronomic traits were found among these accessions, making selection possible for these characters. Chinese accessions, in general, tended to have higher plot yield (POY), higher seed yield per plant (PY), higher thousand-seed weight (TSW), more seeds per silique (SS), and fewer siliques per plant (PS) than foreign accessions. Comparing winter, semi-winter, and spring accessions, semi-winter accessions tended to have the highest POY, highest PY, highest TSW, most SS and fewest PS. Genotypic variation for TSW accounted for 71.23 % of the total variation, and it was the highest for all 12 of the phenotypic traits. Significant correlations were observed between different traits. Principal component analysis (PCA) revealed that significant variation among the traits with the first four principal components could explain 49.8 % of the total variation. Three major groups (winter, spring and semi-winter oilseed rape accessions) could be distinguished when projecting the accessions onto the first two PCAs. The information on variations in yield and agronomic traits detected in this study provided useful parents for rapeseed breeding. Moreover, the phenotypic data on yield and agronomic traits obtained may be used in our subsequent genome-wide association studies for B. napus.

Association mapping can quickly and efficiently dissect complex agronomic traits. Rapeseed is one of the most economically important polyploid oil crops, although its genome sequence is not yet published. In this study, a recently developed 60K Brassica Infinium(®) SNP array was used to analyse an association panel with 472 accessions. The single-nucleotide polymorphisms (SNPs) of the array were in silico mapped using 'pseudomolecules' representative of the genome of rapeseed to establish their hypothetical order and to perform association mapping of seed weight and seed quality. As a result, two significant associations on A8 and C3 of Brassica napus were detected for erucic acid content, and the peak SNPs were found to be only 233 and 128 kb away from the key genes BnaA.FAE1 and BnaC.FAE1. BnaA.FAE1 was also identified to be significantly associated with the oil content. Orthologues of Arabidopsis thaliana HAG1 were identified close to four clusters of SNPs associated with glucosinolate content on A9, C2, C7 and C9. For seed weight, we detected two association signals on A7 and A9, which were consistent with previous studies of quantitative trait loci mapping. The results indicate that our association mapping approach is suitable for fine mapping of the complex traits in rapeseed.

Changsha was one of the most affected areas during the 2009 A (H1N1) influenza pandemic in China. Here, we analyze the spatial–temporal dynamics of the 2009 pandemic across Changsha municipal districts, evaluate the relationship between case incidence and the local urban spatial structure and predict high-risk areas of influenza A (H1N1). We obtained epidemiological data on all cases of influenza A (H1N1) reported across municipal districts in Changsha during period May 2009–December 2010 and data on population density and basic geographic characteristics for 239 primary schools, 97 middle schools, 347 universities, 96 malls and markets, 674 business districts and 121 hospitals. Spatial–temporal K functions, proximity models and logistic regression were used to analyze the spatial distribution pattern of influenza A (H1N1) incidence and the association between influenza A (H1N1) cases and spatial risk factors and predict the infection risks. We found that the 2009 influenza A (H1N1) was driven by a transmission wave from the center of the study area to surrounding areas and reported cases increased significantly after September 2009. We also found that the distribution of influenza A (H1N1) cases was associated with population density and the presence of nearest public places, especially universities (OR = 10.166). The final predictive risk map based on the multivariate logistic analysis showed high-risk areas concentrated in the center areas of the study area associated with high population density. Our findings support the identification of spatial risk factors and high-risk areas to guide the prioritization of preventive and mitigation efforts against future influenza pandemics.

DNA methylation is responsive to various biotic and abiotic stresses. Heat stress is a serious threat to crop growth and development worldwide. Heat stress results in an array of morphological, physiological and biochemical changes in plants. The relationship between DNA methylation and heat stress in crops is relatively unknown. We investigated the differences in methylation levels and changes in the cytosine methylation patterns in seedlings of two rapeseed genotypes (heat-sensitive and heat-tolerant) under heat stress. Our results revealed that the methylation levels were different between a heat-tolerant genotype and a heat-sensitive one under control conditions. Under heat treatment, methylation increased more in the heat-sensitive genotype than in the heat-tolerant genotype. More DNA demethylation events occurred in the heat-tolerant genotype, while more DNA methylation occurred in the heat-sensitive genotype. A large and diverse set of genes were affected by heat stress via cytosine methylation changes, suggesting that these genes likely play important roles in the response and adaption to heat stress in Brassica napus L. This study indicated that the changes in DNA methylation differed between heat-tolerant and heat-sensitive genotypes of B. napus in response to heat stress, which further illuminates the molecular mechanisms of the adaption to heat stress in B. napus.

Background Cost-effective strategies of chronic disease control, integrated health education and health promotion play important roles in the programs of chronic disease demonstration districts in China. The performance of these districts can be directly assessed by their health education and promotion work. However, there have been only a few performance assessments done on these programs, most of which made without the inclusion of proper quality indicators. This study was designed to establish a framework of indicators for outcome evaluation of health education and promotion efforts in Chinese districts, and explore the factors involved in promoting these efforts. Methods A modified two-round Delphi survey was first used to construct quality indicators on a nine-point Likert scale. With those indicators, the rank sum ratio (RSR) method was then conducted through rank conversion and parametric statistics, to assess and classify the performance of ten districts or counties randomly chosen both from demonstration and non-demonstration districts in the Hunan province. Results The Delphi process produced seven themes and 25 sub-themes as quality indicators. The seven themes included organizational management, financial support, professional personnel, health education and promotion, residents’ health awareness and behaviors, residents’ satisfaction, and residents’ health literacy. The districts were classified into four levels by RSR as follows: One demonstration district at the first-ranked level, five other demonstration districts at the second-ranked level, all non-demonstration districts at the third-ranked level. None were at the fourth-qualified level. Discussion Chronic disease demonstration districts performed better on the work of health education and health promotion than the non-demonstration districts. The work should be focused on the following measures of chronic diseases: organizational management, financial support, media-related broadcasting, technical support, community-based promotion and supportive environment, and people’s enhanced awareness and health literacy.

Notifiable infectious diseases reporting system is vital for infectious diseases surveillance and basis for infectious disease prevention and control strategy. Well formulated notifiable disease reporting system is a vital tool for public health surveillance. A qualitative survey was conducted among senior professional staffs who work on notifiable infectious diseases surveillance at provincial city, and county level Center for Disease Control and Prevention (CDC) in China via e-mail questionnaire. Informed consent was guaranteed. There were a total of 39 participants who returned questionnaires of the 42 submitted. Most participants (79.5%) agreed that case definition of hand, foot and mouth disease (HFMD) is not so clear, and 82.1% participants thought adjustment of HFMD case definition is needed. There was no statistical significance for X2 test. Most participants (76.9%) agreed that case definition of infectious diarrhea is not so clear, X2 test showed statistical significant (odds ratio (OR) = 6.88, p < 0.05) 89.7%; participants thought adjustment of infectious diarrhea case definition is needed. There were 48.7% participants who thought there was an underreporting of infectious diarrhea, X2 test showed statistical significant (OR = 9.96, p < 0.01). Most participants demonstrated that confirmed clinical laboratory reporting is more valuable than symptom case report for infectious disease surveillance. Adjustment of HFMD and infectious diarrhoea of notifiable infectious diseases should clarify the case definition and strengthen sentinel surveillance. A quality-assureed infectious disease surveillance system should integrate results from clinical laboratories and epidemiological data. Key words: Notifiable infectious disease, surveillance, hand foot and mouth disease (HFMD), infectious diarrhea.

The conventional FDTD method is extensively applied in dealing with microwave imaging, however, because of the constraint of Courant-Friedrich-Levy (CFL) stability condition, the time-step size required should be smaller enough as well as the fine cells selected is smaller, which brings an increase computational effort. The ADI-FDTD method, on the other hand, utilizing alternating-direction implicit method is available to overcome the constraint of Courant-Friedrich-Levy (CFL) stability condition. It is obvious that the processing result of ADI-FDTD method and conventional FDTD method can coincide with each other perfectly by the MATLAB simulation experiment.

Rapeseed (Brassica napus L.) is one of the most important oil crops in the world. However, the yield and quality of rapeseed were largely decreased by clubroot (Plasmodiophora brassicae Woronin). Therefore, it is of great importance for screening more resistant germplasms or genes and improving the resistance to P. brassicae in rapeseed breeding. In this study, a massive resistant identification for a natural global population was conducted in two environments with race/pathotype 4 of P. brassicae which was the most predominant in China, and a wide range of phenotypic variation was found in the population. In addition, a genome-wide association study of 472 accessions for clubroot resistance (CR) was performed with 60K Brassica Infinium SNP arrays for the first time. In total, nine QTLs were detected, seven of which were novel through integrative analysis. Furthermore, additive effects in genetic control of CR in rapeseed among the above loci were found. By bioinformatic analyses, the candidate genes of these loci were predicted, which indicated that TIR-NBS gene family might play an important role in CR. It is believable that the results presented in our study could provide valuable information for understanding the genetic mechanism and molecular regulation of CR.

Plants have developed sophisticated systems to adapt to local conditions during evolution, domestication and natural or artificial selection. The selective pressures of these different growing conditions have caused significant genomic divergence within species. The flowering time trait is the most crucial factor because it helps plants to maintain sustainable development. Controlling flowering at appropriate times can also prevent plants from suffering from adverse growth conditions, such as drought, winter hardness, and disease. Hence, discovering the genome-wide genetic mechanisms that influence flowering time variations and understanding their contributions to adaptation should be a central goal of plant genetics and genomics. A global core collection panel with 448 inbred rapeseed lines was first planted in four independent environments, and their flowering time traits were evaluated. We then performed a genome-wide association mapping of flowering times with a 60 K SNP array for this core collection. With quality control and filtration, 20,342 SNP markers were ultimately used for further analyses. In total, 312 SNPs showed marker-trait associations in all four environments, and they were based on a threshold p-value of 4.06 × 10(-4); the 40 QTLs showed significant association with flowering time variations. To explore flowering time QTLs and genes related to growth habits in rapeseed, selection signals related to divergent habits were screened at the genome-wide level and 117 genomic regions were found. Comparing locations of flowering time QTLs and genes with these selection regions revealed that 20 flowering time QTLs and 224 flowering time genes overlapped with 24 and 81 selected regions, respectively. Based on this study, a number of marker-trait associations and candidate genes for flowering time variations in rapeseed were revealed. Moreover, we also showed that both flowering time QTLs and genes play important roles in rapeseed growth habits. These results will be applied to rapeseed breeding programs, and they will aid in our understanding of the relation between flowering time variations and growth habits in plants.

To discover chloroplast genome (cpDNA) variations, we performed an assessment of high-resolution melt curve (HRM) analysis for DNA variation within the cp gene accD (acetyl-COA carboxylase gene beta-subunit) at different taxa level of Crucifer. Five short regions of the target gene with sufficient diversity were selected. The results showed that the detection efficiency varied at highly and low polymorphic loci. Amplicons with only one or multiple SNPs were distinguished perfectly. At the intraspecific level, at least 80% variations can be detected, although a few false positives (FPs) existed; however, complex amplicons with multiple SNPs and INDELs coexistence at intertribal level were analysed with more false negatives (FNs). In brief, HRM is an ideal tool when used on rare variance identification within large populations. Further advances in HRM analysis should make it a useful tool for basic and applied studies of plant genetics.

Crude water-soluble polysaccharides were isolated from gel juice, skin juice and flowers of Aloe vera . Results indicate that skin juice contained similar amount of polysaccharides to gel juice, suggesting the potential industrial application of A. vera skin rather than discarded. After anion-exchange chromatography, neutral polysaccharides account for more than 95% of the crude polysaccharides from skin juice and gel juice, whereas, the crude flower polysaccharides are largely composed of weakly acidic polysaccharides (88.7%). Sugar analysis of the polysaccharides after gel-permeation chromatography shows that the neutral polysaccharides from skin juice and gel juice consist of mannose and glucose in a similar ratio of (4.7–5.0):1; whereas the acidic polysaccharides from skin juice are composed mainly of glucose (42.5–45.3%), appeared to be different to those of gel juice, which are constituted predominantly mannose, glucose and galactose. Except a high content of glucuronic acid (20.8%) in flower acidic polysaccharide, the flower neutral and acidic polysaccharides had similar sugar compositions, with galactose, glucose and mannose being the main sugar components, quite different from those of skin juice and gel juice polysaccharides. Glucuronic acid was as the major uronic acid in all acidic polysaccharides from different tissues.

The selection of cultivars with high carotenoid content represents a novel goal in the genetic improvement of oilseed rape. The successful development of an efficient method for the quantification of carotenoids in oilseed rape is a prerequisite for this breeding initiative. In the present study, ultrasound-assisted extraction was combined with a spectrophotometric method to quantify seed carotenoid levels in oilseed rape. The key variables were optimised as follows: the solvent used was a 1 : 1 (v : v) mixture of petroleum ether and acetone, the solid to solvent concentration was 0.08 g/mL, the ultrasound frequency and power were set at 45/100 (kHZ/w), and three extractions of 15 min each were performed. Compared with the conventional solvent extraction method, the time required for extraction using the ultrasound-assisted extraction method was significantly shortened (by 24 times), and the reproducibility was also remarkably improved. These results indicate that ultrasound-assisted spectrophotometric quantification is a rapid, accurate, simple and low cost tool for the screening and selection of rapeseed cultivars with high carotenoid content.

Mustard (Brassicajuncea) is an important crop in both ancient and modern world. It has a broad resource of genetic diversity that is used primarily as oilseed but as vegetables, condiment and medicines also. Its superior tolerance to adverse environments, e.g., drought, high temperature and low fertility suggests its better adaptability in future possible harsh environments. Chinese vegetable mustard displays a wide spectrum of morphotypes. A collection of 95 accessions of B. juncea representing oil and vegetable mustards from China, France, India, Pakistan, and Japan were assessed to determine diversity at the molecular level using sequence-related amplified polymorphism (SRAP). Eight SRAP primer combinations identified a total of 326 scorable fragments of which 161 were polymorphic (49.39%). The percentage of polymorphism for each primer combination varied from 21.88 to 66.67%. Both Shannon-Weaver and Simpson genetic diversity index indicated that the level of genetic diversity within vegetable mustard is much higher than within oil mustard, and also winter oil mustards are genetically more diverse than spring oil mustards. Based on the Cluster and Principal Coordinates analysis, which were conducted on the similarity matrix of SRAP marker data, vegetable, spring oil and winter oil mustard were clearly divided into three distinct groups and among these three groups, spring and winter oil mustard are geneticlly closer than vegetable mustard. This suggests that bilateral gene exchange between oil and vegetable gene pools in the breeding program will effectively elevate the genetic potential in developing higher yields, more disease resistance, better quality and better adapted lines.

Aiming at the problem that using current reliability evaluation indices, which can reflect only one segment of power system, for power system planning leads to partial planning results and is hard to achieve the goal of global programming, this paper proposes an approach to evaluate the reliability of the entire power system, considering the effect of generation, transmission, transformation and distribution system. The power supply reliability not only depends on the structure of the distribution system, but also on the main grid. In the proposed evaluation procedure electrical connection of substation is firstly equated to some equivalent branches based on minimal cut-set method. Then Monte Carlo Simulation (MCS) is used to assess the reliability of generation and transmission composite system and substation system simultaneously by sampling and to obtain hierarchical available capacities and probabilities. Finally, the hierarchical reliability indices of the main grid are used as multi-state equivalent sources to assess the distribution system reliability. The proposed method is tested using a system constituted by the IEEE RTS 79 and feeder of IEEE RBTS-bus6. The results show that the main grid has obvious influence on the reliability of distribution system, and the proposed method can provide more details for system planning and operation.

This paper presents a research on the integration and coordination control of distributed generation (DG) in a hybrid microgrid (MG). This approach integrates DGs by the direct current (DC) power lines added to the local power distri bution system, while the alternating current (AC) power lines take charge of providing the conversional power energy for the local loads, and an energy conversion station is designed to mix energy from the DC generation line with energy from the utility grid. The voltage stability logic controller makes it easier and more convenient for the coordinated control between the DGs and the utility grid, as well as avoids coping with AC integration problems, AC stability and line synchronization for instance. Matlab/Simulink simulation tool was used to show the robust operation performance and to validate the effectiveness of the proposed method above.

Aiming at the difficulty of determining the exact topology of distribution network during long-term reliability evaluation, a weighted cloud prediction model is proposed to predict the reliability of distribution network in long-term planning. Firstly, the digital features of cloud model of the influencing factors are obtained from the statistical historical data by an improved backward cloud generator. Secondly, based on the above digital features, the average weighted cloud prediction model are set up where the weight of each influencing factor is calculated by analytic hierarchy process according to the sensitivity of the influencing factors on reliability. Finally, the effectiveness and feasibility of the proposed method is demonstrated by comparison with the traditional cloud prediction method and the least square support vector machine method from the indices of maximum, minimum and average error.

The construction projects for distribution networks require good economy besides energy saving and voltage quality improvement. Thus the line loss rate and voltage qualification rate are the main assessment indices of construction projects for distribution networks. This paper proposes a comprehensive energy saving potential (ESP) evaluation system for distribution networks. The above basic indices and comprehensive ESP indices for each selected feeder are calculated under different improvement measures. Firstly, typical feeders are modeled using Power Factory software. Then power flow for distribution networks is calculated and weak networks can be found. Secondly, improvement measures for typical feeders can be chosen based on weak networks analysis to achieve the purpose of reducing the power loss rate. Thirdly, the paper gives the definition of loss reduction rate, voltage improvement rate and economic benefits. Furthermore, the implementation order of the measures is optimized according to the value of comprehensive ESP indices and the difficulty extent of implementation. The investment cost and the transformation effect are considered simultaneously for planning. Four measures which include replacing high-loss transformers and worn conductors, adding reactive power compensation devices and adjusting bus voltage are carried out on the IEEE 33-bus test system. The results of simulation calculation demonstrate the validity and superiority of the proposed system.

Currently, the photovoltaic generation has been paid highly attention to and has obtained policy encouragement. With the increasing popularity of single-phase photovoltaic in low-voltage distribution networks, it may deteriorate the overall grid performance including power flows, losses and voltage pro files. On the other side, single-phase photovoltaic connected to the distribution networks will have some influence on the balance of three-phase that may bring additional losses under a three-phase unbalanced situation. In this paper, the concept of three-phase load current unbalance factor is introduced and additional losses in circuits and transformers induced by the three-phase unbalance are firstly analyzed. Secondly, the variation characteristics of the power loss and the three-phase unbalance are studied when single-phase photovoltaic is connected to different phases and different capacities. Furthermore, the paper also investigates the influence on the power loss considering different positions the photovoltaic connected along the low-voltage feeder. From the perspective of decreasing the three-phase unbalance factor, some advice for the photovoltaic connected to the distribution networks is proposed at last. The simulation results show that the proposed advice can effectively reduce the losses caused by the three-phase unbalance. It also provides effective guidance and recommendations for the electricity company to carry out loss reduction work and to deal with large-scale single-phase photovoltaic connection in the future.

Purpose In adult Chinese men, smoking prevalence is high, but little is known about its association with chronic respiratory disease, which is still poorly diagnosed and managed. Methods A nationwide study recruited 0.5 million men and women aged 30–79 years during 2004–2008 from ten geographically diverse areas across the Mainland China. Information was collected from each participant regarding smoking and self-reported physician diagnosis of chronic bronchitis/emphysema (CB/E), along with measurement of lung function indices. Logistic regression was used to yield sex-specific odds ratios (ORs) relating smoking to airflow obstruction (AFO), defined as forced expiratory volume in 1 second (FEV1)/forced vital capacity (FVC)

DNA methylation is known to play a crucial role in regulating plant development and organ or tissue differentiation. In this study, we assessed the extent and pattern of cytosine methylation during rapeseed (Brassica napus L.) seed germination, and compared the methylation level of various tissues in seedling, using the techniques of methylation-sensitive amplified polymorphism (MSAP) and HPLC separation and quantification of nucleosides. In all, 484 bands, each representing a recognition site cleaved by either or both of the isoschizomers, were amplified by 12 pairs of selective primers in DNA obtained from dry seeds. A total of 76 sites were found to be differentially digested by the isoschizomers, indicating that approximately 15.7% of 5′-CCGG-3′ sites in the genome were cytosine methylated. Four classes of patterns were observed in a comparative assay of cytosine methylation in the dry and germinating seeds; a small number of hypermethylation events occurred at 5′-CCGG-3′ sites in germinating seeds compared with dry seeds, while many more hypomethylation events were detected after seed germination. Differences in DNA methylation level in various tissues were also detected; radicel was less methylated than hypocotyl and cotyledon. These observations were further confirmed by HPLC analysis. In addition, sequencing of eleven differentially methylated fragments and the subsequent blast search revealed that cytosine methylated 5′-CCGG-3′ sequences were equally distributed between coding and non-coding regions. These results clearly demonstrate the power of MSAP technique for large-scale DNA methylation detection in rapeseed genome, and the complexity of DNA methylation change during seed germination. DNA Hypomethylation going with seed germination appears to be a necessary step toward transcriptional activation in gene expression, and may well contribute to the developmental gene regulation.