BackgroundAlthough the incidence of tuberculosis (TB) in most parts of China are well under control now, in less developed areas such as Qinghai, TB still remains a major public health problem. This study aims to reveal the spatio-temporal patterns of TB in the Qinghai province, which could be helpful in the planning and implementing key preventative measures.MethodsWe extracted data of reported TB cases in the Qinghai province from the China Information System for Disease Control and Prevention (CISDCP) during January 2009 to December 2016. The Kulldorff’s retrospective space-time scan statistics, calculated by using the discrete Poisson probability model, was used to identify the temporal, spatial, and spatio-temporal clusters of TB at the county level in Qinghai.ResultsA total of 48,274 TB cases were reported from 2009 to 2016 in Qinghai. Results of the Kulldorff’s scan revealed that the TB cases in Qinghai were significantly clustered in spatial, temporal, and spatio-temporal distribution. The most likely spatio-temporal cluster (LLR = 2547.64, RR = 4.21, P < 0.001) was mainly concentrated in the southwest of Qinghai, covering seven counties and clustered in the time frame from September 2014 to December 2016.ConclusionThis study identified eight significant space-time clusters of TB in Qinghai from 2009 to 2016, which could be helpful in prioritizing resource assignment in high-risk areas for TB control and elimination in the future.Electronic supplementary materialThe online version of this article (doi:10.1186/s12879-017-2643-y) contains supplementary material, which is available to authorized users.

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Tourists’ perceptions of various risks at their travel destinations have crucial implications for destination management organizations and other tourism industry practitioners, which is growing into an unprecedented concern in the post-pandemic era. The Internet has boosted the global homestay industry. The perceived risk of homestay tourists requires further attention from researchers to promote the sustainable development of the homestay industry, especially in the post-pandemic era. To supplement and enrich the literature, this study aims to explore the relationships between tourists’ perceived risk, three dimensions of tourists’ emotional solidarity with hosts (feeling welcome, sympathetic understanding, and emotional closeness), and their customer loyalty towards the homestay industry in the post-pandemic era by taking the homestay industry of Guangzhou, China as the context, and employing SmartPLS for the empirical analysis. The results indicate that perceived risk has a significantly negative impact on emotional solidarity and customer loyalty, while emotional solidarity has a significantly positive impact on customer loyalty and plays a partial mediating role in the relationship between perceived risk and customer loyalty. The theoretical contributions of the article and the practical implications of the findings for the sustainable development of the homestay industry are discussed.

Two unusual flavonones coupled with styryl units, communins A (1) and B (2), and a new benzonaphthoxanthenone, ohioensin H (3), together with 11 known compounds, were isolated from the moss Polytrichum commune. The structures of 1-3 were assigned by spectroscopic data interpretation. The new compounds were evaluated for cytotoxicity against a small panel of cancer cell lines.

A sol-gel coating technique was applied for the preparation of a solid-phase microextraction fiber by coating the metal-organic framework UiO-67 onto a stainless-steel wire. The prepared fiber was explored for the headspace solid-phase microextraction of five nitrobenzene compounds from water samples before gas chromatography with mass spectrometric detection. The effects of the extraction temperature, extraction time, sample solution volume, salt addition, and desorption conditions on the extraction efficiency were optimized. Under the optimal conditions, the linearity was observed in the range of 0.015-12.0 μg/L for the compounds in water samples, with the correlation coefficients (r) of 0.9945-0.9987. The limits of detection of the method were 5.0-10.0 ng/L, and the recoveries of the analytes from spiked water samples for the method were in the range of 74.0-102.0%. The precision for the measurements, expressed as the relative standard deviation, was less than 11.9%.

A nanoporous carbon derived from an aluminumbased metal-organic framework was deposited on stainless steel wires in a sol-gel matrix. The resulting fibers were applied to the solid-phase microextraction of the polycyclic aromatic hydrocarbons (PAHs) naphthalene, acenaphthene, fluorene, phenanthrene and anthracene from water and soil samples. The fiber was then directly inserted into the GC injector and the PAHs were quantified by GC-MS. The effects of salt addition, extraction temperature, extraction time, sample volume and desorption conditions on the extraction efficiency were optimized. A linear response to the analytes was observed in the 0.1 to 12 μg L −1 range for water samples, and in the 0.6 to 30 μg kg −1 for soil samples, with the correlation coefficients ranging from 0.9934 to 0.9985. The limits of detection ranged from 5.0 to 20 ng L −1 for water samples, and from 30 to 90 ng kg −1 for soil samples. The recoveries of spiked samples were between 72.4 and 108.0 %, and the precision, expressed as the relative standard deviations, is <12.8 %.

We define cumulative intraday returns and consider their prediction from such returns on a market index. We model these returns as curves in a function space. We propose several functional regression models which can be viewed as extensions of the capital asset pricing model to intraday returns defined as curves. After deriving parameter estimates and prediction functions for these models, we compare their prediction errors by application to cumulative intraday returns of large U.S. corporations. We find that complex functional regression models do not perform better than a simple model. In particular, we find that modelling error dependence does not improve forecasts.

A sol-gel coating technique was applied for the preparation of metal organic frameworks (MOFs)-based solid phase microextraction (SPME) fibers by coating MIL-101 onto stainless steel wires. The prepared fiber was explored for the headspace SPME (HS-SPME) of seven volatile aromatic compounds (VACs) from water samples followed by gas chromatography-mass spectrometric analysis. Several important experimental parameters, such as extraction temperature, extraction time, sample volume, salt addition and desorption conditions, were investigated. Under the optimized experimental conditions, the developed HS-SPME method with MIL-101 coated fiber had a good linearity in the range of 0.05-50.0 mg L À1 for the analytes with the correlation coefficients (r) ranging from 0.9974 to 0.9988. Based on a signal-to-noise ratio (S/N) of 3, the limits of detection (LODs) for the seven analytes ranged from 1.0 to 5.0 ng L À1 . Compared with two commercial SPME fibers, the laboratory-made MIL-101 coated fiber showed a higher extraction efficiency for the seven VACs. The established method was successfully applied for the determination of the VACs in real local tap and lake water samples. The recoveries for the method of the seven VACs at spiking levels of 0.1 and 5.0 mg L À1 were in the range from 76.4% to 116.1%.