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Aiming at the problem that the performance of traditional beamforming algorithm deteriorates sharply in the presence of main lobe interference, a beamforming algorithm based on radial basis function (RBF) neural network is proposed. Firstly, the minimum variance distortionless response (MVDR) is used to solve the optimal beam pattern in the presence of side lobe interference. Then, the training set of RBF neural network is constructed according to the optimal beam pattern and the direction information of main lobe interference to train the network, so that the trained RBF neural network can suppress the main lobe interference while maintaining the ability of optimal beamforming. The simulation results show that the method can overcome the limitations of traditional beamforming algorithm, suppress the main lobe interference and side lobe interference, and form the correct beam direction. At the same time, the algorithm also has good real-time performance.

A triazole-stabilized fluorescence sensor is developed for copper detection in the study. Tris-(benzyltriazolylmethyl)amine (TBTA) is used to improve the sensitivity and stability for the sensing system. A series of comparative experiments are performed with and without TBTA. In the presence of TBTA, the fluorescence decrease ratio is enhanced from 2.46 to 118.25; the detection limit is reduced from 67 nM to 3.6 nM; the higher selectivity toward copper compared to the other metal ions is verified, including K+, Ca2+, Cd2+, Zn2+, Mg2+, Mn2+, Pb2+, Hg2+, Fe3+ and Cr3+. Besides, the sensing system is successfully applied for copper determination in complex tea samples and chicken feed samples with the recovery range of 91.67–116.8%. A good consistency between the presented sensor and the flame atom absorbance spectrometry (FAAS) is confirmed by the low relative errors with the range from −2.39% to 7.02%.

Aiming at the problem that precision decrease of parameter measurements in the airborne radar and IRST cooperative location system lead to low location accuracy under the interference condition, an optimization algorithm of cooperative location based on ridge regression is discussed. According to the data optimization principle, two sets of measurements from the angle observation of ridge and infrared are selected by the principle of selecting the data. Using ridge regression for biased estimation, solves the ill-posed problem of positioning equation. And the target position estimation and position error covariance matrix is calculated, so GDOP model of fusion location algorithmic is constructed through using weighted least square algorithm and improving weighted coefficient matrix. Simulation analysis shows that this method significantly can improve the location accuracy of the whole detection area by using a combination of the radar's spare information and IRST's under the minimum variance of parameter estimation. The problem of low location accuracy by using single angle measuring subset is solved and a new working mode is discussed that sensors' cooperative detection in complex electromagnetic environment.

Objectives This study aims to investigate the characteristics of economic costs of occupational heat illnesses in South Australia, and to examine the association between high temperatures and occupational heat illness related economic costs. Methods Workers9 compensation claim data were obtained from SafeWork South Australia for the period of 2001–2015. Weather data were collected from the Bureau of Meteorology. The association between heat illness and economic loss was estimated by time-series analysis with generalized estimating equation models after controlling for day of week and long-term trends. Results There were 306 occupational heat illness claims during the study period, resulting in medical expenditure of $1,795,640 and 2,787 days of time loss. Male workers accounted for 87.8% and 82.5% of medical costs and time-lost days, respectively. The mining industry had the greatest proportion of medical expenditure (56.0%) and days off work due to heat illnesses (67.4%), followed by "community services" and "agriculture, forestry and fishing". There was a positive relationship between maximum temperature (Tmax), medical expenditure, and days of time lost. A 1°C increase of Tmax was associated with 18.5% (IRR 1.185, 95% CI 1.071–1.312) increase in medical expenditure and 34.6% (IRR 1.346, 95% CI 1.128–1.534) increase in time-lost days due to occupational heat illnesses, respectively. Conclusions Occupational heat related-illnesses represent a significant economic cost, and interventions in South Australia should be targeted at the mining industry.

Materials are often damaged during the process of detecting mass fractions by traditional methods. Acoustic emission (AE) technology combined with wavelet packet analysis is used to evaluate the mass fractions of microcrystalline graphite/polyvinyl alcohol (PVA) composites in this study. Attenuation characteristics of AE signals across the composites with different mass fractions are investigated. The AE signals are decomposed by wavelet packet technology to obtain the relationships between the energy and amplitude attenuation coefficients of feature wavelet packets and mass fractions as well. Furthermore, the relationship is validated by a sample. The larger proportion of microcrystalline graphite will correspond to the higher attenuation of energy and amplitude. The attenuation characteristics of feature wavelet packets with the frequency range from 125 kHz to 171.85 kHz are more suitable for the detection of mass fractions than those of the original AE signals. The error of the mass fraction of microcrystalline graphite calculated by the feature wavelet packet (1.8%) is lower than that of the original signal (3.9%). Therefore, AE detection base on wavelet packet analysis is an ideal NDT method for evaluate mass fractions of composite materials.

Background: Dengue is a significant climate-sensitive disease. Public health professionals play an important role in prevention and control of the disease. This study aimed to explore dengue control and prevention in the context of climate change in China. Methods: A cross-sectional survey was conducted among 630 public health professionals in 2015. Descriptive analysis and logistic regression were performed. Results: More than 80% of participants from southwest and central China believed climate change would affect dengue. However, participants from northeast China were less likely to believe so (65%). Sixty-nine percent of participants in Yunnan perceived that dengue had emerged/re-emerged in recent years, compared with 40.6% in Henan and 23.8% in Liaoning. Less than 60% of participants thought current prevention and control programs had been effective. Participants believed mosquitoes in high abundance, imported cases and climate change were main risk factors for dengue in China. Conclusion: There were varying views of dengue in China. Professionals in areas susceptible to dengue were more likely to be concerned about climate change and dengue. Current prevention and control strategies need to be improved. Providing more information for staff in lower levels of Centers for Disease Control and Prevention may help in containing a possible increase of dengue. Keywords: Climate change, Dengue control, Infectious disease, Public health professional, China

Background Hemorrhagic fever with renal syndrome (HFRS) is a serious public health problem in China. Although the incidence of HFRS sharply reduced towards the end of the twentieth century, there has been a re-emergence of the disease after 2008 in some parts of China. The aim of this study was to gauge the perceptions of health professionals in China concerning HFRS control and climate change. Methods A cross-sectional survey about HFRS and climate change was conducted among staff in the Centers for Disease Control and Prevention (CDC) in Liaoning and Anhui Provinces, where HFRS is still a public health concern. Descriptive analyses were performed to assess survey results. Results In total, 412 questionnaires were distributed, and 381 participants completed the survey. > 80% of participants thought climate change would have an influence on population health and infectious diseases. However, fewer participants (

This study aims to (1) investigate the associations between climatic factors and dengue; and (2) identify the susceptible subgroups. De-identified daily dengue cases in Guangzhou for 2005–2014 were obtained from the Chinese Center for Disease Control and Prevention. Weather data were downloaded from the China Meteorological Data Sharing Service System. Distributed lag non-linear models (DLNM) were used to graphically demonstrate the three-dimensional temperature-dengue association. Generalised estimating equation models (GEE) with piecewise linear spline functions were used to quantify the temperature-dengue associations. Threshold values were estimated using a broken-stick model. Middle-aged and older people, people undertaking household duties, retirees, and those unemployed were at high risk of dengue. Reversed U-shaped non-linear associations were found between ambient temperature, relative humidity, extreme wind velocity, and dengue. The optimal maximum temperature (Tmax) range for dengue transmission in Guangzhou was 21.6–32.9 °C, and 11.2–23.7 °C for minimum temperature (Tmin). A 1 °C increase of Tmax and Tmin within these ranges was associated with 11.9% and 9.9% increase in dengue at lag0, respectively. Although lag effects of temperature were observed for up to 141 days for Tmax and 150 days for Tmin, the maximum lag effects were observed at 32 days and 39 days respectively. Average relative humidity was negatively associated with dengue when it exceeded 78.9%. Maximum wind velocity ( >10.7 m/s) inhibited dengue transmission. Climatic factors had significant impacts on dengue in Guangzhou. Lag effects of temperature on dengue lasted the local whole epidemic season. To reduce the likely increasing dengue burden, more efforts are needed to strengthen the capacity building of public health systems. Refereed/Peer-reviewed

China is one of the largest countries in the world with nearly 20% of the world’s population. There have been significant improvements in economy, education and technology over the last three decades. Due to substantial investments from all levels of government, the public health system in China has been improved since the 2003 severe acute respiratory syndrome (SARS) outbreak. However, infectious diseases still remain a major population health issue and this may be exacerbated by rapid urbanization and unprecedented impacts of climate change. This commentary aims to explore China’s current capacity to manage infectious diseases which impair population health. It discusses the existing disease surveillance system and underscores the critical importance of strengthening the system. It also explores how the growing migrant population, dramatic changes in the natural landscape following rapid urbanization, and changing climatic conditions can contribute to the emergence and re-emergence of infectious disease. Continuing research on infectious diseases, urbanization and climate change may inform the country’s capacity to deal with emerging and re-emerging infectious diseases in the future. Refereed/Peer-reviewed

This study aims to investigate the associations between meteorological factors and hemorrhagic fever with renal syndrome (HFRS) in 19 cities selected from HFRS high risk areas across different climate zones in three Provinces of China. De-identified daily reports of HFRS in Anhui, Heilongjiang, and Liaoning Provinces for 2005-2014 were obtained from the Chinese Center for Disease Control and Prevention. Daily weather data from each study location were obtained from the China meteorological Data Sharing Service System. Generalised estimating equation models (GEE) were used to quantify the city-specific HFRS-weather associations. Multivariate random-effects meta-regression models were used to pool the city-specific HFRS-weather effect estimates. HFRS showed an overall downward trend during the study period with a slight rebound after 2010. Meteorological factors were significantly associated with HFRS incidence. HFRS was relatively more sensitive to weather variability in subtropical regions (Anhui Province) than in temperate regions (Heilongjiang and Liaoning Provinces). The size of effect estimates and the duration of lagged effects varied by locations. Pooled results of the 19 cities showed that a 1 °C increase in maximum temperature (Tmax) resulted in a 1.6% (95% CI: 1.0%-2.2%) increase in HFRS; a 1 mm increase in weekly precipitation was associated with 0.2% (95%CI: 0.1%-0.3%) increase in HFRS; a 1% increase in average relative humidity was associated with a 0.9% (95%CI: 0.5%-1.2%) increase in HFRS. The lags with the largest effects for Tmax, precipitation, and relative humidity occurred in weeks 29, 22, and 16, respectively. Lagged effects of meteorological factors did not end after an epidemic season but waned gradually in the following 3-4 epidemic seasons. Weather variability plays a significant role in HFRS transmission in China. The long duration of lagged effects indicates the necessity of continuous interventions following the epidemics. Refereed/Peer-reviewed

Background Though there was the significant decrease in the incidence of malaria in central and southwest China during the 1980s and 1990s, there has been a re-emergence of malaria since 2000. Methods A cross-sectional survey was conducted amongst the staff of eleven Centers for Disease Control and Prevention (CDC) in China to gauge their perceptions regarding the impacts of climate change on malaria transmission and its control and prevention. Descriptive analysis was performed to study CDC staff’s knowledge, attitudes, perceptions and suggestions for malaria control in the face of climate change. Results A majority (79.8%) of CDC staff were concerned about climate change and 79.7% believed the weather was becoming warmer. Most participants (90.3%) indicated climate change had a negative effect on population health, 92.6 and 86.8% considered that increasing temperatures and precipitation would influence the transmission of vector-borne diseases including malaria. About half (50.9%) of the surveyed staff indicated malaria had re-emerged in recent years, and some outbreaks were occurring in new geographic areas. The main reasons for such re-emergence were perceived to be: mosquitoes in high-density, numerous imported cases, climate change, poor environmental conditions, internal migrant populations, and lack of health awareness. Conclusions This study found most CDC staff endorsed the statement that climate change had a negative impact on infectious disease transmission. Malaria had re-emerged in some areas of China, and most of the staff believed that this can be managed. However, high densities of mosquitoes and the continuous increase in imported cases of malaria in local areas, together with environmental changes are bringing about critical challenges to malaria control in China. This study contributes to an understanding of climate change related perceptions of malaria control and prevention amongst CDC staff. It may help to formulate in-house training guidelines, community health promotion programmes and policies to improve the capacity of malaria control and prevention in the face of climate change in China. Electronic supplementary material The online version of this article (doi:10.1186/s12936-017-1790-3) contains supplementary material, which is available to authorized users.

Background: Dengue fever is an important climate-sensitive mosquito-borne viral disease that poses a risk to half the world's population. The disease is a major public health issue in China where in 2014 a major outbreak occurred in Guangdong Province. This study aims to gauge health professionals'; perceptions about the capacity of infectious disease control and prevention to meet the challenge of dengue fever in the face of climate change in Guangdong Province, China. Methods: A cross-sectional questionnaire survey was administered among staff in the Centers for Disease Control and Prevention (CDCs) in Guangdong Province. Data analysis was undertaken using descriptive methods and logistic regression. Results: In total, 260 questionnaires were completed. Most participants (80.7%) thought climate change would have a negative effect on population health, and 98.4% of participants reported dengue fever had emerged or re-emerged in China in recent years. Additionally, 74.9% of them indicated that the capability of the CDCs to detect infectious disease outbreak/epidemic at an early stage was excellent; 86.3% indicated laboratories could provide diagnostic support rapidly; and 83.1% believed levels of current staff would be adequate in the event of a major outbreak. Logistic regression analysis showed higher levels of CDCs were perceived to have better capacity for infectious disease control and prevention. Only 26.8% of participants thought they had a good understanding of climate change, and most (85.4%) thought they needed more information about the health impacts of climate change. Most surveyed staff suggested the following strategies to curb the public health impact of infectious diseases in relation to climate change: primary prevention measures, strengthening the monitoring of infectious diseases, the ability to actively forecast disease outbreaks by early warning systems, and more funding for public health education programs. Conclusion: Vigilant disease and vector surveillance, preventive practice and health promotion programs will likely be significant in addressing the threat of dengue fever in the future. Further efforts are needed to strengthen the awareness of climate change among health professionals, and to promote relevant actions to minimize the health burden of infectious diseases in a changing climate. Results will be critical for policy makers facing the current and future challenges associated with infectious disease prevention and control in China. Refereed/Peer-reviewed