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Understanding the differences in risk perception among various groups is crucial for policy development, and the cultural theory of risk provides significant insights into these group variations. Utilising data from Mainland China during the COVID-19 pandemic, we constructed a structural model that encompasses occupational background, risk culture, and risk perception, examining the interplay between these elements. Our findings reveal that risk culture, as initially conceptualised by Mary Douglas, acts as a mediating factor between occupational roles and the differences in risk perception, offering a deeper understanding of how diverse risk perceptions are shaped across distinct demographic groups. This study underscores the importance of considering cultural factors in risk perception and provides valuable guidance for the development of targeted risk communication and intervention policies. [ABSTRACT FROM AUTHOR]

• Novel GRU-LIME prediction method boosts accuracy. • GRU consistently beats traditional models for reliable predictions. • Renewable energy insights inform sustainable urban development. This study proposes a novel approach to sustainable energy transition in urban environments, focusing on the prediction and management of renewable energy outputs for low-carbon urban development. We introduce a new intelligent prediction model based on Gated Recurrent Unit (GRU) Networks to forecast the output power of both tidal and biomass units. The GRU model, known for its capability in capturing sequential dependencies, is employed to enhance the accuracy of renewable energy predictions in the context of urban sustainability. To address the interpretability challenges inherent in complex deep learning models, we leverage LIME (Local Interpretable Model-agnostic Explanations). By integrating LIME into our GRU-based prediction model, we enhance transparency and understandability. This approach facilitates the identification of key factors influencing predictions, providing stakeholders and decision-makers with valuable insights for effective sustainable energy management. The proposed hybrid model is applied to the digital model of real tidal and biomass sites in China, allowing for a statistical examination of renewable integration and energy management strategies. The results offer a comprehensive understanding of the dynamics between renewable energy sources and urban development, paving the way for informed decision-making in the pursuit of low-carbon and resilient cities. This research contributes to the broader discourse on sustainable urban development by offering a robust statistical framework for renewable energy integration and management in urban environments. [ABSTRACT FROM AUTHOR]

At present, China and some other countries and regions are adopting both electricity and carbon trading markets to optimize the resource allocation of the power industry. The aim of this research is to explain the production behaviors of fossil fuel power enterprises in these complex dual market conditions and then evaluate the market effects. On the basis of the real market rules of China and the production characteristics of these enterprises, we describe the production decision process of enterprises with different market positions (leader, follower, and taker), obtain their optimal yield, and then offer market equilibrium results (total electricity supply, clearing price, total CO 2 emissions, and carbon intensity level). Besides, we evaluate the impacts of government interventions (market condition changes) on regional market equilibrium situations by numerical simulation. Our results indicate that the direction (positive or negative) of the above impacts is determined by the level of the allocation coefficients of the carbon emission quota, and the degree of these impacts is determined by the level of fine for unit excess carbon emissions. Moreover, our research also proves that enterprise collusion behaviors aggravate market failure but lower the carbon intensity level. • Fossil fuel power enterprises in China are facing complex dual market conditions. • We describe the production decision process of enterprises with different market positions. • We offer the equilibrium results of electricity and carbon trading markets. • We evaluate the impacts of government interventions and enterprise collusion behaviors. [ABSTRACT FROM AUTHOR]

Cultivated land plays a pivotal role in ensuring national food security. The challenges of non-agriculture, non-grain production and the marginalization of cultivated land have become increasingly pronounced in the context of urbanization and industrialization in China, posing potential threats to long-term food security. This study employs a combination of remote sensing and statistical data to reveal the effects of non-agriculturalization, non-grainization, and the marginalization of cultivated land on grain production potential (GPP) at the grid scale. From 1992 to 2020, the total farmland area initially exhibited an ascending trend followed by a subsequent decline, resulting in a net decrease of approximately 0.84% in China. the northward shift in the center of gravity of cultivated land has accentuated the spatial disparity between grain production and consumption. Non-agriculturalization, non-grainization, and marginalization of cultivated land contributed 35.22%, 22.58%, and 42.20% to the GPP loss, respectively. GPP loss exhibited significant differences across the agroclimatic zones, with the combined loss in the Middle-lower Yangtze Plain and Huang-Huai-Hai Plain exceeding 60% of the national total. Cultivated land marginalization has emerged as the most impactful land-use change affecting GPP, leading to a substantial loss of approximately 11471.30 × 104 t. The affected area is predominantly concentrated in the southern region. The marginalization of cultivated land has not been effectively alleviated, and the expansion trend continues. Conservation endeavors targeting cultivated land should prioritize enhancing farmers' willingness to cultivate, curbing the extensive utilization of farmland, and mitigating the escalating trend of farmland marginalization. [ABSTRACT FROM AUTHOR]

Background: Prior to December 2022, there were no reports of reinfection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Shaanxi province, China. Since then, China has refined its strategy in response to coronaviruses. The purpose of this study was to determine the incidence of SARS-CoV-2 reinfections and its contributing factors, as well as to compare clinical characteristics between first and second episodes of infection in Shaanxi Province, China between December 2022 and February 2023., Methods: We conducted a cross-sectional study using an epidemiological survey system and electronic questionnaires to investigate the incidence of SARS-CoV-2 reinfection among previously infected individuals during the epidemic wave owing to the Omicron variant that began in December 2022. A logistic regression model was used to determine those factors influencing SARS-CoV-2 reinfections., Results: According to the virus variant that caused the first infection, the rate of reinfection for the Omicron variants was 1.28%, 1.96%, and 5.92% at 2-3 months, 4-5 months, and 7-9 months after the primary infection, respectively. The rate of reinfection for the Delta variants was 25.10% 11-12 months after the primary infection. Females, adults between 18 and 38 years and being a medical worker were associated with an increased risk of reinfection. Fever, cough, sore throat and fatigue were the four most common clinical symptoms during both first and second COVID-19 infections., Conclusions: In our study, the rate of SARS-CoV-2 reinfection increased over time during epidemic waves predominantly involving the Omicron variant in Shaanxi province, China. Large-scale infections are less likely in subsequent Omicron epidemic waves. Nevertheless, it is essential to continuously monitor cases of infection as well as continue surveillance for emerging SARS-CoV-2 variants., (© 2024. The Author(s).)

Purpose: To explore the accuracy of the improved SRK/T-Li formula in eyes following implantation of intraocular lens (IOL) of less than 10 D as calculated by using the SRK/T formula in Chinese., Methods: A total of 489 eyes from 489 patients with cataracts were included in this study. These patients were divided into a training set (271 patients) and a testing set (218 patients). The IOL power calculated by using SRK/T was less than 10 D. We evaluated the accuracy of the modified SRK/T-Li formula (P = P SRK/T  × 0.8 + 2 (P = implanted IOL power; P SRK/T  = IOL power calculated by SRK/T)). We evaluated the mean absolute error (MAE), percentage of prediction error (PE) within ± 0.25, ± 0.50, and ± 1.00 D, and the percentage of postoperative hyperopia., Results: The MAE values in order of lowest to highest were as follows: 0.412 D (SRK/T-Li), 0.414 D (Barrett Universal II, (BUII)), 0.814 D (SRK/T), and 1.039 D (Holladay 1). The percentage of PE within ± 0.25 D, ± 0.50 D, and ± 1.00 D was 38.99%, 69.27% and 92.66% (BUII), 40.83%, 69.27% and 94.04% (SRK/T-Li), 20.64%, 41.28% and 71.56% (SRK/T), and 7.34%, 16.51% and 53.21% (Holladay 1), respectively. SRK/T-Li had the smallest postoperative hyperopic shift., Conclusions: For Chinese patients with an IOL power of less than 10 D as calculated by using the SRK/T, the SRK/T-Li has good accuracy and is the best choice to reduce postoperative hyperopic shift., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Complemented croplands are a crucial component of cropland resources and play a significant role in ensuring national food security. In recent decades, to counter the loss of prime farmland caused by urban construction, the Chinese government introduced a requisition-compensation balance policy, leading to the substantial expansion of new croplands. Therefore, there is an urgent need to determine whether these complemented croplands can be effectively used. Taking Southwest China as a case study, we used high-precision long-term land-use data from 1990 to 2020 to reveal the dynamics of complemented cropland utilization, evaluate the efficiency of complemented cropland utilization from the perspective of abandoned farmland, and identify the factors driving complemented cropland use efficiency based on more than 13 million land parcels. The results showed that: (1) From 1990 to 2020, complemented cropland amounted to approximately 1170.07 × 10 4  hm 2 , accounting for 32.67% of the total arable land area in 1990. The potential grain production capacity of these complemented croplands was significantly lower than that of base croplands. (2) The abandonment of complemented croplands was more serious than that of base croplands, and 47.03% of the complemented croplands experienced abandonment at least once during the study period, and the average efficiency of the complemented croplands was 75.61%. (3) The labor population ratio, elevation, and land parcel size played pivotal roles in influencing the complemented cropland utilization efficiency; however, there was substantial variation among the different provinces. Labor replacement, overcoming farming difficulties brought by mountainous terrain, and improving farmers' income are the keys to alleviating cropland abandonment in mountainous areas and improving cropland utilization efficiency. This study provides novel insights into the efficiency assessment and exploration of the mechanisms driving complemented croplands and can provide references for cropland management., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)