Asthma prevalence based on the Baidu index and China's Health Statistical Yearbook from 2011 to 2020 in China

BackgroundDue to environmental pollution, changes in lifestyle, and advancements in diagnostic technology, the prevalence of asthma has been increasing over the years. Although China has made early efforts in asthma epidemiology and prevention, there is still a lack of unified and comprehensive epidemiological research within the country. The objective of the study is to determine the nationwide prevalence distribution of asthma using the Baidu Index and China's Health Statistical Yearbook.MethodsBased on China's Health Statistical Yearbook, we analyzed the gender and age distribution of asthma in China from 2011 to 2020, as well as the length of hospitalization and associated costs. By utilizing the Baidu Index and setting the covering all 31 provinces and autonomous regions in China, we obtained the Baidu Index for the keyword 'asthma'. Heatmaps and growth ratios described the prevalence and growth of asthma in mainland China.ResultsThe average expenditure for discharged asthma (standard deviation) patients was ¥5,870 (808). The average length of stay (standard deviation) was 7.9 (0.38) days. During the period of 2011 to 2020, hospitalization expenses for asthma increased while the length of hospital stay decreased. The proportion of discharged patients who were children under the age of 5 were 25.3% (2011), 19.4% (2012), 16% (2013), 17.9% (2014), 13.9% (2015), 11.3% (2016), 10.2% (2017), 9.4% (2018), 8.1% (2019), and 7.2% (2020), respectively. The prevalence of asthma among boys was higher than girls before the age of 14. In contrast, the proportion of women with asthma was larger than men after the age of 14. During the period from 2011 to 2020, the median [The first quartile (Q1)-the third quartile (Q3)] daily asthma Baidu index in Guangdong, Beijing, Jiangsu, Sichuan, and Zhejiang were 419 (279–476), 328 (258–376), 315 (227–365), 272 (166–313), and 312 (233–362) respectively. Coastal regions showed higher levels of attention toward asthma, indicating a higher incidence rate. Since 2014, there has been a rapid increase in the level of attention toward asthma, with the provinces of Qinghai, Sichuan, and Guangdong experiencing the fastest growth.ConclusionThere are regional variations in the prevalence of asthma among different provinces in China, and the overall prevalence of asthma is increasing

Dynamic Influence of Network Public Opinions on Price Fluctuation of Small Agricultural Products Based on NLP-TVP-VAR Model—Taking Garlic as an Example

In recent years, the price of small agricultural products has both plummeted and skyrocketed, which has a great impact on people’s lives. Studying the factors affecting the price fluctuation of small agricultural products is of great significance for stabilizing their price. With the development and application of social media, farmers and consumers are more greatly influenced by online public opinion, resulting in irrational planting behavior or purchasing behavior, which has a complex impact on the price of small agricultural products. Taking garlic as an example, we crawled through network public opinions about garlic price from January 2015 to December 2020 using web crawler technology. Then, the network public opinions were quantified using a natural language processing and time-varying parameter vector autoregression (NLP-TVP-VAR) model to empirically analyze their dynamic influence on garlic price fluctuation. It was found that both public attitude and public attention have a short-term influence on garlic price fluctuation, and the influences of each differ according to direction, intensity and timing. The influence of public attitude on garlic price fluctuation is positive, while the influence of public attention on garlic price fluctuation is largely negative. The influence intensity of public attitude is stronger than of public attention on garlic price fluctuation. The influence of public attitude on garlic price fluctuation shows a trend of intensifying, while that of public attention has been weaker than in previous years. In addition, based on the results of our study, we present some recommendations for improving the comprehensive information platform and price fluctuation early warning system for the whole industry chain of small agricultural products

Dynamic Influence of Network Public Opinions on Price Fluctuation of Small Agricultural Products Based on NLP-TVP-VAR Model—Taking Garlic as an Example

In recent years, the price of small agricultural products has both plummeted and skyrocketed, which has a great impact on people’s lives. Studying the factors affecting the price fluctuation of small agricultural products is of great significance for stabilizing their price. With the development and application of social media, farmers and consumers are more greatly influenced by online public opinion, resulting in irrational planting behavior or purchasing behavior, which has a complex impact on the price of small agricultural products. Taking garlic as an example, we crawled through network public opinions about garlic price from January 2015 to December 2020 using web crawler technology. Then, the network public opinions were quantified using a natural language processing and time-varying parameter vector autoregression (NLP-TVP-VAR) model to empirically analyze their dynamic influence on garlic price fluctuation. It was found that both public attitude and public attention have a short-term influence on garlic price fluctuation, and the influences of each differ according to direction, intensity and timing. The influence of public attitude on garlic price fluctuation is positive, while the influence of public attention on garlic price fluctuation is largely negative. The influence intensity of public attitude is stronger than of public attention on garlic price fluctuation. The influence of public attitude on garlic price fluctuation shows a trend of intensifying, while that of public attention has been weaker than in previous years. In addition, based on the results of our study, we present some recommendations for improving the comprehensive information platform and price fluctuation early warning system for the whole industry chain of small agricultural products

Spillover Effect of Network Public Opinion on Market Prices of Small-Scale Agricultural Products

Network public opinion plays a crucial role in the behavior and decision making of various stakeholders, including farmers, middlemen, and consumers. It also affects the price fluctuations of small-scale agricultural products. Understanding the transmission path and spillover effect of network public opinion on the price fluctuations of these products is essential for ensuring their sustainable development and price stability. This paper selects the monthly data of network public opinion and related market prices of small-scale agricultural products from January 2014 to December 2021, constructs a network public opinion value through the sentiment classification results of deep learning models, and uses the trivariate VAR-BEKK-GARCH(1,1) model and spillover index model to study the spillover effect and spillover index of network public opinion on the market prices of small-scale agricultural products (national average price and origin price). The results show that: (1) There is a bidirectional volatility spillover effect between public opinion sentiment and the market prices of small-scale agricultural products. Additionally, this two-way volatility spillover effect is also evident between the average market prices and the origin prices of these commodities. (2) The influence of network public opinion on the market prices of small-scale agricultural products is substantial, with the spillover index being more pronounced for origin prices than for national average prices and reaching its zenith earlier. Consequently, based on these results, recommendations are provided to adapt planting and inventory strategies, enhance vigilance towards price risk transmission amongst small-scale agricultural product markets, and improve the comprehensive information platform encompassing the entire industry chain

Pore Solution pH for the Corrosion Initiation of Rebars Embedded in Concrete under a Long-Term Natural Carbonation Reaction

This paper presents an in-situ inspection and experimental investigation on the pore solution pH of concrete cover for the corrosion initiation of rebars under a long-term natural carbonation reaction. A 77-year-old steel mill was inspected, and 35 concrete column cover samples were collected to test the pH of the pore solution and phase compositions layer by layer. The variation in pH and phase compositions of the concrete along the cover depth was studied. The in-situ inspection results indicate that the rebar embedded in concrete had begun to corrode when the carbonation depth was almost less than one-third of the cover depth. The corrosion initiation of rebars embedded in concrete can occur when the pH is between 11.3 and 12.1. The pore solution pH test results and X-ray diffraction (XRD) analysis indicated that there is a semi-carbonated zone between the fully carbonated zone and the rebar. The pH of a fully carbonated zone is in a range of 8.0–9.5, and the pH of a semi-carbonated zone is between 9.5 and 12.1

Characterization of Dehydrin protein, CdDHN4-L and CdDHN4-S, and their differential protective roles against abiotic stress in vitro

Abstract Background Dehydrins play positive roles in regulating plant abiotic stress responses. The objective of this study was to characterize two dehydrin genes, CdDHN4-L and CdDHN4-S, generated by alternative splicing of CdDHN4 in bermudagrass. Results Overexpression of CdDHN4-L with φ-segment and CdDHN4-S lacking of φ-segment in Arabidopsis significantly increased tolerance against abiotic stresses. The growth phenotype of Arabidopsis exposed to NaCl at 100 mM was better in plants overexpressing CdDHN4-L than those overexpressing CdDHN4-S, as well as better in E.coli cells overexpressing CdDHN4-L than those overexpressing CdDHN4-S in 300 and 400 mM NaCl, and under extreme temperature conditions at − 20 °C and 50 °C. The CdDHN4-L had higher disordered characterization on structures than CdDHN4-S at temperatures from 10 to 90 °C. The recovery activities of lactic dehydrogenase (LDH) and alcohol dehydrogenase (ADH) in presence of CdDHN4-L and CdDHN4-S were higher than that of LDH and ADH alone under freeze-thaw damage and heat. Protein-binding and bimolecular fluorescence complementation showed that both proteins could bind to proteins with positive isoelectric point via electrostatic forces. Conclusions These results indicate that CdDHN4-L has higher protective ability against abiotic stresses due to its higher flexible unfolded structure and thermostability in comparison with CdDHN4-S. These provided direct evidence of the function of the φ-segment in dehydrins for protecting plants against abiotic stress and to show the electrostatic interaction between dehydrins and client proteins

Ductilization of selective laser melted Ti6Al4V alloy by friction stir processing

The low ductility of Ti6Al4V alloy manufactured by Selective Laser Melting (SLM) adversely impacts the component performance in practical applications. A local post-treatment by Friction Stir Processing (FSP) significantly reduces the porosity and homogenizes the microstructure. This results in an increase in fracture strain from 0.21 after SLM to 0.65 following the FSP post-treatment. The porosity reduction was evidenced by 3D X-ray micro-computed tomography. A fully transformed β microstructure is formed after FSP. This microstructure involves α plates, α colonies, as well as equiaxed dynamically recrystallized α phases inside equiaxed prior-β grains. The deformed microstructure was observed during in-situ tensile test, using scanning electron microscopy, with the aim to unravel the damage mechanisms. In addition to the beneficial effect of initial porosity reduction, the transformed microstructure after FSP bears more damage before failure than the typical α’ martensite laths in the as-built SLM samples.status: Published onlin

Ductilization of selective laser melted Ti6Al4V alloy by friction stir processing

The low ductility of Ti6Al4V alloy manufactured by Selective Laser Melting (SLM) adversely impacts the component performance in practical applications. A local post-treatment by Friction Stir Processing (FSP) significantly reduces the porosity and homogenizes the microstructure. This results in an increase in fracture strain from 0.21 after SLM to 0.65 following the FSP post-treatment. The porosity reduction was evidenced by 3D X-ray micro-computed tomography. A fully transformed β microstructure is formed after FSP. This microstructure involves α plates, α colonies, as well as equiaxed dynamically recrystallized α phases inside equiaxed prior-β grains. The deformed microstructure was observed during in-situ tensile test, using scanning electron microscopy, with the aim to unravel the damage mechanisms. In addition to the beneficial effect of initial porosity reduction, the transformed microstructure after FSP bears more damage before failure than the typical α’ martensite laths in the as-built SLM samples

A global dataset on species occurrences and functional traits of Schizothoracinae fish

Abstract The Schizothoracinae fish are a natural group of cyprinids widely distributed in rivers and lakes in the Qinghai-Tibetan Plateau (QTP) and adjacent regions. These fish parallelly evolved with the QTP uplift and are thus important for uncovering geological history, the paleoclimatic environment, and the mechanisms of functional adaptation to environmental change. However, a dataset including species occurrences and functional traits, which are essential for resolving the above issues and guiding relevant conservation, remains unavailable. To fill this gap, we systematically compiled a comprehensive dataset on species occurrences and functional traits of Schizothoracinae fish from our long-term field samplings and various sources (e.g., publications and online databases). The dataset includes 7,333 occurrence records and 3,204 records of 32 functional traits covering all the genera and species of Schizothoracinae fish (i.e., 12 genera and 125 species or subspecies). Sampling records spanned over 180 years. This dataset will serve as a valuable resource for future research on the evolution, historical biogeography, responses to environmental change, and conservation of the Schizothoracinae fish

A Scale Conversion Model Based on Deep Learning of UAV Images

As a critical component of many remote sensing satellites and model validation, pixel-scale surface quantitative parameters are often affected by scale effects in the acquisition process, resulting in deviations in the accuracy of image scale parameters. Consequently, various successive scale conversion methods have been proposed to correct the errors caused by scale effects. In this study, we propose ResTransformer, a deep learning model for scale conversion of surface reflectance using UAV images, which fully extracts and fuses the features of UAV images in the sample area and sample points and establishes a high-dimensional nonlinear spatial correlation between sample points and sample area in the target sample area, so that the scale conversion of surface reflectance at the pixel-scale can be completed quickly and accurately. We collected and created a dataset of 500k samples to verify the accuracy and robustness of the model with other traditional scale conversion methods. The results show that the ResTransformer deep learning model works best, providing average MRE, average MRSE, and correlation coefficient R values of 0.6440%, 0.7460, and 0.99911, respectively, and the baseline improvements compared with the Simple Average method are 92.48%, 92.45%, and 16.59%, respectively. The ResTransformer model also shows the highest robustness and universality and can adapt to surface pixel-scale conversion scenarios with different sizes, heterogeneous sample areas, and arbitrary sampling methods. This method provides a promising, highly accurate, and robust method for converting pixel-scale surface reflectance scale