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BackgroundViolence against doctors in China is a serious problem that has attracted attention from both domestic and international media. ObjectiveThis study investigates readers’ responses to media reports on violence against doctors to identify attitudes toward perpetrators and physicians and examine if such trends are influenced by national policies. MethodsWe searched 17 Chinese violence against doctors reports in international media sources from 2011 to 2020. We then tracked back the original reports and web crawled the 19,220 comments in China. To ascertain the possible turning point of public opinion, we searched violence against doctors–related policies from Tsinghua University ipolicy database from 2011 to 2020, and found 19 policies enacted by the Chinese central government aimed at alleviating the intense patient–physician relationship. We then conducted a series of interrupted time series analyses to examine the influence of these policies on public sentiment toward violence against doctors over time. ResultsThe interrupted time series analysis (ITSA) showed that the change in public sentiment toward violence against doctors reports was temporally associated with government interventions. The declarations of 10 of the public policies were followed by increases in the proportion of online public opinion in support of doctors (average slope changes of 0.010, P

S&T management data has a wide range of sources and types, and the innovation of S&T management data service model is an important way for the efficient utilization of S&T resources in the new era, so this paper creates an innovative model of S&T management data service based on Data-Information-Knowledge-Wisdom model and artificial intelligence technology. Heterogeneous data mining technology based on association rules is used to obtain the connection between S&T management data, Lagrange interpolation is used for heterogeneous data cleaning to predict the missing values of S&T management data, and data lineage resolution technology is used to solve the challenges brought by the complex and diverse S&T management data components. Experimental analyses are conducted from both S&T management data processing and data service cases to verify the effectiveness and scientificity of the S&T management data service innovation model proposed in this paper. The results show that in S&T management data processing, this paper’s method consumes less than 2.45s for associated data rule mining, which has high mining efficiency, and the duplication rate and missing rate of data are below 0.0260 and 0.0222. Through the analysis of the service quality data, it can be seen that the degree of explanation of the service process quality problems of the model proposed in this paper tends to be close to 1, which can reflect the differences in the service process quality problems, and provide accurate, intelligent and personalized services for the main body of science and technology innovation.

This paper first constructs an intelligent education management system for universities according to their needs and explains its logical and technical architecture. Secondly, a multi-task convolutional neural network with MTCNN is used to detect faces, and different loss functions are selected to ensure recognition accuracy. Finally, the effectiveness of the application of intelligent education management systems in universities is verified through performance tests. The results show that the time consumed for face recognition detection using MTCNN is 524ms, and the response time of each function of the system does not exceed 500ms when the number of concurrent users is less than 500, which indicates that the intelligent education management system based on MTCNN face recognition algorithm has a good response speed and meets the requirements of intelligent education management in colleges and universities.

Mg-based porous materials have broad application prospect in biomedical field.In order to improve the corrosion resistance of porous Mg-Al alloy in human body fluid，porous Mg-Al alloy was prepared by powder metallurgy，and Y2O3 with different contents (0，0.2%，0.4%，0.6%) was added to modify the Mg-Al alloy.The effects of Y2 O3 content on the porosity，pore morphology，microstructure，compressive strength and corrosion resistance of porous Mg-Al alloy in Hank's biomimetic solution were investigated by means of metallographic microscope，XRD，SEM，universal testing machine and electrochemical workstation.Results showed that the porosity of porous Mg-Al alloy prepared by powder metallurgy was about 39%，and the powder metallurgy method could accurately control the pore morphology and size of porous Mg-Al alloy.Moreover，porous Mg-Al alloy was mainly composed of Mg and the second phase Al12Mg17.The addition of Y2O3 could refine the grains of porous Mg-Al alloy，homogenize the grain size，distribute the second phase more evenly，and improve the compressive strength of porous Mg-Al alloy and its corrosion resistance in Hank's bionic solution.When the content of Y2O3 was 0.4%，the compressive strength of porous Mg-Al alloy was 46.4 MPa，and the corrosion rate in Hank's biomimetic solution was 0.887 44 mm/a.

The available evidence on the connection between excessive alcohol consumption and diabetes is controversial. Therefore, the primary objective of this investigation was to examine the connection between excessive alcohol consumption and incident diabetes in a Japanese population through the utilization of propensity score matching (PSM) analysis. Our retrospective cohort study encompassed a sample of 15,464 Japanese individuals who were initially free of diabetes between the years 2004 and 2015. The study utilized comprehensive medical records of individuals who underwent a physical examination. Employing a one:one PSM analysis, the current research included 2298 individuals with and without excessive alcohol consumption. Furthermore, a doubly robust estimation method was employed to ascertain the connection between excessive alcohol consumption and diabetes. The findings revealed that individuals with excessive alcohol consumption exhibited a 73% higher likelihood of developing diabetes (HR = 1.73, 95% CI 1.08–2.77). Furthermore, upon adjusting for variables, the PSM cohort demonstrated that individuals with excessive alcohol consumption had a 78% increased risk of developing diabetes in comparison to those with non-excessive alcohol consumption (HR = 1.78, 95% CI 1.08–2.93). Individuals with excessive alcohol consumption were found to have a 73% higher risk of developing diabetes compared to those with non-excessive alcohol consumption, even after controlling for propensity score (HR = 1.73, 95% CI 1.08–2.78). Participants in the PSM cohort with excessive alcohol consumption had a 73% higher risk of developing diabetes than those with non-excessive alcohol consumption after controlling for confounding factors. These findings underscore the importance of alcohol consumption guidelines aimed at reducing excessive drinking. Clinicians should be vigilant in screening for alcohol use in patients, particularly those at risk for diabetes, and provide appropriate counseling and resources to support alcohol reduction. [ABSTRACT FROM AUTHOR]

A copper/polydimethylsiloxane (Cu/PDMS) microfluidic chip was designed to synthesize SERS substrates through a displacement reaction between silver and copper in microfluidic channels to form a microfluidic SERS nanoparticles (AgNPs)/Cu chip. This SERS substrate fabrication method doesn't require complex manufacturing processes or expensive equipment, and it can be achieved at room temperature in just 4 min. Meanwhile, the AgNPs grown on copper foil could offer ample hot spots, effectively boosting Raman signals of target molecules, and the enhancement factor (EF) was 5.12 × 107 for methylene blue, 4.08 × 107 for crystal violet, and 4.81 × 105 for sulfadiazine. The chip could be reused at least 9 times with consistent signal performance. Combined with the concentration gradient microchannel network design, we could establish the standard curve for samples through one injection on a single chip. A rapid SERS method for detecting sulfadiazine in aquatic products was developed. The linear range for sulfadiazine analysis was 75.0–1000 μg L−1 with a limit of detection of 28.4 μg L−1. Sulfadiazine was found in aquatic products (43.8 μg kg−1), with recovery rates ranging from 82.7% to 110%. The result was validated using high-performance liquid chromatography, showing a relative error of 9.3%. The entire detection procedure could be completed in just 20 min to detect sulfadiazine. These results demonstrate that the developed SERS method is fast, accurate, and reliable for analysis of sulfadiazine in aquatic products. [ABSTRACT FROM AUTHOR]