With the ongoing challenge of air pollution posing serious health and environmental threats, particularly in rapidly industrializing regions, accurate forecasting and effective pollutant identification are crucial for enhancing public health and ecological stability. This study aimed to optimize air quality management through the prediction of the Air Quality Index (AQI) and identification of air pollutants. Our study spans nine representative cities (Hohhot, Yinchuan, Lanzhou, Beijing, Taiyuan, Xi’an, Shanghai, Nanjing, Wuhan) in China, with data collected from January 1, 2015, to November 30, 2021. We proposed a new model for daily AQI prediction, termed VMD-CSA-CNN-LSTM, which employed advanced machine learning techniques, including convolutional neural networks (CNN) and long short-term memory (LSTM) networks, and leveraged the chameleon swarm algorithm (CSA) for hyperparameter optimization, integrated through a variational mode decomposition approach. The model was developed using data from Lanzhou, with a split ratio of 8:1:1 into training, validation, and test sets, achieving an RMSE of 2.25, MAPE of 0.02, adjusted R-squared of 98.91%, and training efficiency of 5.31%. The model was further externally validated in the other eight cities, yielding comparable results, with an adjusted R-squared above 96%, MAPE below 0.1, and RMSE below 7.5. Additionally, we employed a random forest algorithm to identify the primary pollutants contributing to AQI levels. Our results indicated that PM_2.5 was the most significant pollutant in Beijing, Taiyuan, and Xi’an, while PM₁₀ was dominant in Hohhot, Yinchuan, and Lanzhou. In Shanghai, Nanjing, and Wuhan, both PM_2.5 and PM₁₀ were critical, with ozone also identified as a major air pollutant. This study not only advances the predictive accuracy of AQI models but also aids policymakers by providing a reliable tool for air quality management and strategic planning aimed at pollution reduction. The integration of these advanced computational techniques into environmental monitoring practices offers a promising avenue for enhancing air quality and mitigating pollution-related risks.

Background: Hand, foot, and mouth disease (HFMD) is a highly contagious viral illness. Understanding the long-term trends of HFMD incidence and its epidemic characteristics under the circumstances of the enterovirus 71 (EV71) vaccination program and the outbreak of COVID-19 is crucial for effective disease surveillance and control. Objective: We aim to give an overview of the trends of HFMD over the past decades and evaluate the impact of the EV71 vaccination program and the COVID-19 pandemic on the epidemic trends of HFMD. Methods: Using official surveillance data from the Yunnan Province, China, we described long-term incidence trends and severity rates of HFMD as well as the variation of enterovirus proportions among cases. We conducted the autoregressive integrated moving average (ARIMA) of time series analyses to predict monthly incidences based on given subsets. The difference between the actual incidences and their counterfactual predictions was compared using absolute percentage errors (APEs) for periods after the EV71 vaccination program and the COVID-19 pandemic, respectively. Results: The annual incidence of HFMD fluctuated between 25.62 cases per 100,000 people in 2008 and 221.52 cases per 100,000 people in 2018. The incidence for men ranged from 30 to 250 cases per 100,000 people from 2008 to 2021, which was constantly higher than that for women. The annual incidence for children aged 1 to 2 years old ranged from 54.54 to 630.06 cases per 100,000 people, which was persistently higher than that for other age groups. For monthly incidences, semiannual peaks were observed for each year. All actual monthly incidences of 2014 to 2015 fell within the predicted 95% CI by the ARIMA(1,0,1)(1,1,0)[12] model. The average APE was 19% for a 2-year prediction. After the EV71 vaccination program, the actual monthly incidence of HFMD was consistently lower than the counterfactual predictions by ARIMA(1,0,1)(1,1,0)[12], with negative APEs ranging from −11% to −229% from January 2017 to April 2018. In the meantime, the proportion of EV71 among the enteroviruses causing HFMD decreased significantly, and the proportion was highly correlated (r=0.73, P=.004) with the severity rate. After the onset of the COVID-19 pandemic in 2020, the actual monthly incidence of HFMD consistently maintained a lower magnitude compared to the counterfactual predictions—ARIMA(1,0,1)(0,1,0)[12]—from February to September 2020, with considerable negative APEs (ranging from −31% to −2248%). Conclusions: EV71 vaccination alleviated severe HFMD cases and altered epidemiological trends. The HFMD may also benefit from nonpharmaceutical interventions during outbreaks such as the COVID-19 pandemic. Further development of a multivalent virus vaccine is crucial for effectively controlling HFMD outbreaks. Policymakers should implement nonpharmaceutical interventions and emphasize personal hygiene for routine prevention when appropriate.

Portfolio optimization is one of the most complex problems in the financial field, and technical analysis is a popular tool to find an optimal solution that maximizes the yields. This paper establishes a portfolio optimization model consisting of a weighted unidirectional dual-layer LSTM model and an SMA-slope strategy. The weighted unidirectional dual-layer LSTM model is developed to predict the daily prices of gold/Bitcoin, which addresses the traditional problem of prediction lag. Based on the predicted prices and comparison of two representative investment strategies, simple moving average (SMA) and Bollinger bands (BB), this paper adopts a new investment strategy, SMA-slope strategy, which introduces the concept of k-slope to measure the daily ups and downs of gold/Bitcoin. As two typical financial products, gold and Bitcoin are opposite in terms of their characteristics, which may represent many existing financial products in investors portfolios. With a principle of $1000, this paper conducts a five-year simulation of gold and Bitcoin trading from 11 September 2016 to 10 September 2021. To compensate for the SMA and BB that may miss buying and selling points, 4 different parameters values in the k-slope are obtained through particle swarm optimization simulation. Also, the simulation results imply that the proposed portfolio optimization model contributes to helping investors make investment decisions with high profitability.

Objectives: Diabetes is associated with decline of cognitive function. Exploring different trajectories of cognitive function occurring in people with diabetes is important to improved prognosis. This study aimed to investigate differential patterns of trajectories of cognitive function and baseline determinants of trajectory group membership utilizing data from middle-aged and older Chinese adults with diabetes. Methods: Participants of the Chinese Health And Retirement Longitudinal Study (CHARLS) aged 45 years and above received biennial assessments between 2011 and 2018. The primary outcome was overall cognitive function score operationalized as sum of mental intactness and episodic memory scores derived from the Telephone Interview of Cognitive Status (TICS). A weighted growth mixture model was used to estimate cognitive function trajectories of CHARLS participants with diabetes, and baseline factors associated with trajectory group membership were investigated with weighted multinomial logistic regression. Results: Data from 1,463 participants with diabetes aged 45 years and above were analyzed, a three-group trajectory model showed the best fit for overall cognitive scores: low baseline, linear declining (22.1%); moderate baseline, linear declining (37.5%) and high-stable (40.3%). Older participants, females, participants with low education, with nighttime sleep <6 h, without daytime napping habits, and with depressive symptoms were at a higher risk of unfavorable cognitive function trajectories. Conclusions: We identified heterogeneous trajectories of cognitive function among middle-aged and older people living with diabetes in China. Socially vulnerable groups including females, rural residents, and those with low education were at a higher risk for unfavorable trajectories. In health programs aimed at preventing and mitigating cognitive decline in individuals with diabetes more attention should be given to vulnerable groups. Reduced nighttime sleep, lack of daytime napping, and depressive symptoms appear to be modifiable risk factors.

Diquat poisoning is common in Asia and the optimal enhanced elimination strategy is unknown. This study aimed to evaluate the clinical value of plasma diquat concentrations in guiding personalized extracorporeal treatment regimens for patients with acute diquat poisoning. This multi-center retrospective cohort study included 163 patients with acute diquat poisoning admitted between February 2022 and July 2023. Patients were divided into three groups based on plasma diquat concentrations measured upon presentation to the emergency department: low (<100 μg/L), medium (100-1,000 μg/L), and high (≥1,000 μg/L). The evaluated extracorporeal treatment regimens included hemoperfusion alone and a combination of hemoperfusion with continuous veno-venous hemodiafiltration. Kaplan-Meier survival curves were used to estimate cumulative survival probabilities, with survival probabilities compared using log-rank tests. All 66 patients survived in the low concentration group, regardless of the extracorporeal treatment used. In the medium and high concentration groups, five patients who refused extracorporeal treatment died, whereas 92 patients who received extracorporeal treatment had a case fatality rate of 48.9%. In the high concentration group, patients receiving hemoperfusion combined with continuous veno-venous hemodiafiltration had a case fatality rate of 76.7% and better survival probabilities, compared to hemoperfusion-only patients, which had no survivors. Additionally, among those treated with a combination of hemoperfusion and continuous veno-venous hemodiafiltration, the time interval from the end of hemoperfusion session to the initiation of continuous veno-venous hemodiafiltration was, on average, shorter for survivors than deaths (3.7 h versus 4.7 h). This retrospective observational study of diquat poisoned patients highlights the potential for personalized extracorporeal treatment regimens using an initial plasma diquat concentration. Future randomized trials are warranted to evaluate the optimal use of extracorporeal treatments. Obtaining plasma diquat concentrations may be of great value for guiding extracorporeal treatment regimens to improve prognosis in patients with acute diquat poisoning.