This study highlights the positive impact of a stock market listing on workplace safety. We find that workplace injuries in publicly listed firms are lower than those in comparable private firms, and this effect relates to heightened monitoring by the media and regulators. The media pays more attention to public firms’ safety issues than to those of private firms, and the reduced media scrutiny due to local newspaper closures leads to greater increases in injuries in public firms. Regulators also monitor public firms more strictly, evidenced by a higher likelihood of nonroutine inspections and larger penalties for detected violations.

The great demographic pressure brings tremendous volume of beef demand. The key to solve this problem is the growth and development of Chinese cattle. In order to find molecular markers conducive to the growth and development of Chinese cattle, sequencing was used to determine the position of copy number variations (CNVs), bioinformatics analysis was used to predict the function of ZNF146 gene, real-time fluorescent quantitative polymerase chain reaction (qPCR) was used for CNV genotyping and one-way analysis of variance was used for association analysis. The results showed that there exists CNV in Chr 18: 47225201-47229600 (5.0.1 version) of ZNF146 gene through the early sequencing results in the laboratory and predicted ZNF146 gene was expressed in liver, skeletal muscle and breast cells, and was amplified or overexpressed in pancreatic cancer, which promoted the development of tumour through bioinformatics. Therefore, it is predicted that ZNF146 gene affects the proliferation of muscle cells, and then affects the growth and development of cattle. Furthermore, CNV genotyping of ZNF146 gene was three types (deletion type, normal type and duplication type) by Real-time fluorescent quantitative PCR (qPCR). The association analysis results showed that ZNF146-CNV was significantly correlated with rump length of Qinchuan cattle, hucklebone width of Jiaxian red cattle and heart girth of Yunling cattle. From the above results, ZNF146-CNV had a significant effect on growth traits, which provided an important candidate molecular marker for growth and development of Chinese cattle.

The incidence of scarlet fever has increased dramatically in recent years in Chongqing, China, but there has no effective method to forecast it. This study aimed to develop a forecasting model of the incidence of scarlet fever using a seasonal autoregressive integrated moving average (SARIMA) model. Monthly scarlet fever data between 2011 and 2019 in Chongqing, China were retrieved from the Notifiable Infectious Disease Surveillance System. From 2011 to 2019, a total of 5073 scarlet fever cases were reported in Chongqing, the male-to-female ratio was 1.44:1, children aged 3–9 years old accounted for 81.86% of the cases, while 42.70 and 42.58% of the reported cases were students and kindergarten children, respectively. The data from 2011 to 2018 were used to fit a SARIMA model and data in 2019 were used to validate the model. The normalised Bayesian information criterion (BIC), the coefficient of determination (R2) and the root mean squared error (RMSE) were used to evaluate the goodness-of-fit of the fitted model. The optimal SARIMA model was identified as (3, 1, 3) (3, 1, 0)12. The RMSE and mean absolute per cent error (MAPE) were used to assess the accuracy of the model. The RMSE and MAPE of the predicted values were 19.40 and 0.25 respectively, indicating that the predicted values matched the observed values reasonably well. Taken together, the SARIMA model could be employed to forecast scarlet fever incidence trend, providing support for scarlet fever control and prevention.

The early identification and prediction of hand-foot-and-mouth disease (HFMD) play an important role in the disease prevention and control. However, suitable models are different in regions due to the differences in geography, social economy factors. We collected data associated with daily reported HFMD cases and weather factors of Zibo city in 2010~2019 and used the generalised additive model (GAM) to evaluate the effects of weather factors on HFMD cases. Then, GAM, support vectors regression (SVR) and random forest regression (RFR) models are used to compare predictive results. The annual average incidence was 129.72/100 000 from 2010 to 2019. Its distribution showed a unimodal trend, with incidence increasing from March, peaking from May to September. Our study revealed the nonlinear relationship between temperature, rainfall and relative humidity and HFMD cases and based on the predictive result, the performances of three models constructed ranked in descending order are: SVR > GAM> RFR, and SVR has the smallest prediction errors. These findings provide quantitative evidence for the prediction of HFMD for special high-risk regions and can help public health agencies implement prevention and control measures in advance.

While there has been much research on welfare exit and entry into employment, less research has looked at return to government assistance. Applying survival analysis on data from a national government assistance programme in Singapore, we found two important factors of welfare return to which activation programmes need to pay greater attention. First, return was more likely if former beneficiaries accumulated a higher number of types of arrears rather than higher dollar values of arrears. This new finding contributes to the emerging literature on bandwidth tax, and suggests the importance of designing programmes that relieve mental accounting due to debt and poverty. Second, return was more likely if respondents had an infant or toddler child. This points to the importance of a range of support policies including affordable and accessible childcare, exemption from work requirement in receipt of welfare, and family leave for low-wage workers.

This paper presents Parallel World Framework as a solution for simulations of complex systems within a time-varying knowledge graph and its application to the electric grid of Jurong Island in Singapore. The underlying modeling system is based on the Semantic Web Stack. Its linked data layer is described by means of ontologies, which span multiple domains. The framework is designed to allow what-if scenarios to be simulated generically, even for complex, inter-linked, cross-domain applications, as well as conducting multi-scale optimizations of complex superstructures within the system. Parallel world containers, introduced by the framework, ensure data separation and versioning of structures crossing various domain boundaries. Separation of operations, belonging to a particular version of the world, is taken care of by a scenario agent. It encapsulates functionality of operations on data and acts as a parallel world proxy to all of the other agents operating on the knowledge graph. Electric network optimization for carbon tax is demonstrated as a use case. The framework allows to model and evaluate electrical networks corresponding to set carbon tax values by retrofitting different types of power generators and optimizing the grid accordingly. The use case shows the possibility of using this solution as a tool for CO2 reduction modeling and planning at scale due to its distributed architecture.

The pandemic of coronavirus disease 2019 (COVID-19) has posed serious challenges. It is vitally important to further clarify the epidemiological characteristics of the COVID-19 outbreak for future study and prevention and control measures. Epidemiological characteristics and spatial−temporal analysis were performed based on COVID-19 cases from 21 January 2020 to 1 March 2020 in Shandong Province, and close contacts were traced to construct transmission chains. A total of 758 laboratory-confirmed cases were reported in Shandong. The sex ratio was 1.27: 1 (M: F) and the median age was 42 (interquartile range: 32–55). The high-risk clusters were identified in the central, eastern and southern regions of Shandong from 25 January 2020 to 10 February 2020. We rebuilt 54 transmission chains involving 209 cases, of which 52.2% were family clusters, and three widespread infection chains were elaborated, occurring in Jining, Zaozhuang and Liaocheng, respectively. The geographical and temporal disparity may alert public health agencies to implement specific measures in regions with different risk, and should attach importance on how to avoid household and community transmission.

Porphyromonas gingivalis has been linked to the development and progression of oesophageal squamous cell carcinoma (ESCC), and is considered to be a high-risk factor for ESCC. Currently, the commonly used methods for P. gingivalis detection are culture or DNA extraction-based, which are either time and labour intensive especially for high-throughput applications. We aimed to establish and evaluate a rapid and sensitive direct quantitative polymerase chain reaction (qPCR) protocol for the detection of P. gingivalis without DNA extraction which is suitable for large-scale epidemiological studies. Paired gingival swab samples from 192 subjects undergoing general medical examinations were analysed using two direct and one extraction-based qPCR assays for P. gingivalis. Tris-EDTA buffer-based direct qPCR (TE-direct qPCR), lysis-based direct qPCR (lysis-direct qPCR) and DNA extraction-based qPCR (kit-qPCR) were used, respectively, in 192, 132 and 60 of these samples for quantification of P. gingivalis. The sensitivity and specificity of TE-direct qPCR was 95.24% and 100% compared with lysis-direct qPCR, which was 100% and 97.30% when compared with kit-qPCR; TE-direct qPCR had an almost perfect agreement with lysis-direct qPCR (κ = 0.954) and kit-qPCR (κ = 0.965). Moreover, the assay time used for TE-direct qPCR was 1.5 h. In conclusion, the TE-direct qPCR assay is a simple and efficient method for the quantification of oral P. gingivalis and showed high sensitivity and specificity compared with routine qPCR.

This report is on the synthesis by electrospinning of multiferroic core-shell nanofibers of strontium hexaferrite and lead zirconate titanate or barium titanate and studies on magneto-electric (ME) coupling. Fibers with well-defined core–shell structures showed the order parameters in agreement with values for nanostructures. The strength of ME coupling measured by the magnetic field-induced polarization showed the fractional change in the remnant polarization as high as 21%. The ME voltage coefficient in H-assembled films showed the strong ME response for the zero magnetic bias field. Follow-up studies and potential avenues for enhancing the strength of ME coupling in the core–shell nanofibers are discussed.

The localization and number of the different types of water in two Na-smectites (Laponite and hectorite) were studied as a function of the hydromechanical stresses applied. Water volume variation was obtained by macroscopic oedometric tests. Thermogravimetric analysis (TGA), X-ray diffraction (XRD) and nuclear magnetic resonance (NMR) were used to study water-smectite interactions. The TGA results show that the bulk water content decreases while the adsorbed water content remains practically constant with increasing mechanical stress; hectorite adsorbs less water than Laponite at low hydraulic stress. The proportion of adsorbed water obtained by NMR confirms the TGA data. The interlamellar space and the equivalent water layers decrease with increasing mechanical stress and is always lower in hectorite than in Laponite. Hydromechanical effects on the water-Na-smectite system are in agreement with microtexture changes measured by porosimetry. Differences in the properties of the two clays can be attributed to the higher extension of the layers in hectorite compared with Laponite.

Changes in particle organization and pore-spaces with applied mechanical and hydraulic stresses were followed using TEM, SAXS mercury porosimetry and gas adsorption for two Na-smectites, Laponite and hectorite, with similar structural formulae but different particle sizes. The TEM images show that hectorite has particles larger and more anisotropic than those of Laponite. The particles order perpendicularly to the direction of axial mechanical stress and become disoriented under hydraulic stress. According to the SAXS results, Laponite is composed of 1 – 3 small layers and hectorite of more compact (10 – 80 layers) particles. In Laponite, mechanical stress strongly reduces the amount of macropores but does not affect micropores and mesopores; hydraulic stress increases the macropores. In hectorite, the pore-volume is lower than in Laponite. The different techniques used yield complementary results and show the considerable effect of layer dimension on the behaviour and microtexture parameters of smectite submitted to hydromechanical stresses.

A free standing 2D PS colloidal crystal with Au nanoshells/hydrogel composite film (CAuHCF) was fabricated by embedding a 2D PS colloidal crystal with Au nanoshells into a polyacrylic acid (PAA) hydrogel film. This CAuHCF can act as a visualized sensor with high diffraction intensity. The 2D PS colloidal crystal with Au nanoshells was prepared by depositing an Au layer on PS colloidal crystal obtained by interfacial self-assembly. The diffraction intensity of the CAuHCF was increased by about 30-fold than that of traditional 2D PS colloidal crystal/hydrogel composite film on transparent substrate due to large scattering cross section of Au shell. Such sensors based Au nanoshells array with the simple preparation process and the strong diffraction signal are promising ones for practical applications in visual detection. Additionally, with the simple preparation process and high diffraction intensity, other visualized sensors based different hydrogel matrix and the 2D PS colloidal crystal with Au nanoshells could be synthesized for monitoring various analysts.

Understanding film initiation and growth mechanisms at the atomic level is crucial to obtain high-quality nonpolar ZnO films. Using the advanced reactive force field-based molecular dynamics method, we theoretically studied the effect of substrate temperature (350–950 K) on the quality, layer develop mechanism and defect formation of ZnO films. Investigation of the energy, radial distribution function, layer coverage, sputtering and injecting phenomena indicated that the present films grown at 500–600 K possessed the optimal quality. Further investigation of the growth condition, instant film profiles, interfacial microstructure evolutions and layered snapshots revealed that, addition of atoms on newly formed localized films can induce some partially bonded or extruded atoms out of the film plane. Further adherence of depositing atoms to these unstable or extruded atoms induces the initiation and growth of a new layer.

Grape proanthocyanidins (GPCs) are a family of naturally derived polyphenols that have aroused interest in the poultry industry due to their versatile role in animal health. This study was conducted to investigate the potential benefits and appropriate dosages of GPCs on growth performance, jejunum morphology, plasma antioxidant capacity and the biochemical indices of broiler chicks. A total of 280 newly hatched male Cobb 500 broiler chicks were randomly allocated into four treatments of seven replicates each, and were fed a wheat–soybean meal-type diet with or without (control group), 7.5, 15 or 30 mg/kg of GPCs. Results show that dietary GPCs decrease the feed conversion ratio and average daily gain from day 21 to day 42, increase breast muscle yield by day 42 and improve jejunum morphology between day 21 and day 42. Chicks fed 7.5 and 15 mg/kg of GPCs show increased breast muscle yield and exhibit improved jejunum morphologies than birds in the control group. Dietary GPCs fed at a level of 15 mg/kg markedly increased total superoxide dismutase (T-SOD) activity between day 21 and day 42, whereas a supplement of GPCs at 7.5 mg/kg significantly increased T-SOD activity and decreased lipid peroxidation malondialdehyde content by day 42. A supplement of 30 mg/kg of GPCs has no effect on antioxidant status but adversely affects the blood biochemical indices, as evidenced by increased creatinine content, increased alkaline phosphatase by day 21 and increased alanine aminotransferase by day 42 in plasma. GPC levels caused quadratic effect on growth, jejunum morphology and plasma antioxidant capacity. The predicted optimal GPC levels for best plasma antioxidant capacity at 42 days was 13 to 15 mg/kg, for best feed efficiency during grower phase was 16 mg/kg, for best jejunum morphology at 42 days was 17 mg/kg. In conclusion, GPCs (fed at a level of 13 to 17 mg/kg) have the potential to be a promising feed additive for broiler chicks.

With the aid of the Green's function method and complex function method, the scattering problem of SH-wave by a cylindrical inclusion and a semi-cylindrical hollow in the bi-material half space is considered to obtain the steady state response. Firstly, by the means of the image method, the essential solution of displacement field as well as Green's function is constructed which satisfies the stress free on the horizontal boundary in a right-angle space including a cylindrical inclusion and a semi-cylindrical hollow and bearing a harmonic out-plane line source force at any point on the vertical boundary. Secondly, the bi-material half space is divided into two parts along the vertical interface, and the first kind of Fredholm integral equations containing undetermined anti-plane forces at the linking section is established by “the conjunction method” and “the crack-division method”, the integral equations are reduced to the algebraic equations consisting of finite items by effective truncation. Finally, dynamic stress concentration factor around the edge of cylindrical inclusion and dynamic stress intensity factor at crack tip are calculated, and the influences of effect of interface and different combination of material parameters, etc. on dynamic stress concentration factor and dynamic stress intensity factor are discussed.

Imaging atmospheric Cherenkov telescopes (IACTs) are sensitive to rare gamma-ray photons, buried in the background of charged cosmic-ray (CR) particles, the flux of which is several orders of magnitude greater. The ability to separate gamma rays from CR particles is important, as it is directly related to the sensitivity of the instrument. This gamma-ray/CR-particle classification problem in IACT data analysis can be treated with the rapidly-advancing machine learning algorithms, which have the potential to outperform the traditional box-cut methods on image parameters. We present preliminary results of a precise classification of a small set of muon events using a convolutional neural networks model with the raw images as input features. We also show the possibility of using the convolutional neural networks model for regression problems, such as the radius and brightness measurement of muon events, which can be used to calibrate the throughput efficiency of IACTs.