Enhanced Quick-Cooking Red Beans: An Energy-Efficient Drying Method with Hot Air and Stepwise Microwave Techniques.

This research introduced an energy-efficient drying method combining hot-air drying with stepwise microwave heating for producing quick-cooking red beans. Crucial parameters such as the effective diffusivity coefficient (De), and specific energy consumption (SEC) were examined across varying conditions with the aim of optimizing the drying condition. The results showed that De and SEC varied in a range of 0.53 × 10-9-3.18 × 10-9 m2·s-1 and 16.58-68.06 MJ·(kg·h-1)-1, respectively. The findings from the response surface methodology indicated that optimal drying conditions for cooked red beans are achieved at a hot air temperature of 90 °C, a microwave power of 450 W (corresponding to an initial intensity of 2.25 W·g-1), and a rotational speed of 0.2 Hz. These conditions lead to the maximum effective diffusivity coefficient and the lowest specific energy consumption. Further investigations into step-up (150-300 W to 300-450 W) and step-down (300-450 W to 150-300 W) microwave heating modes were conducted to refine the drying process for enhanced energy efficiency. The synthetic evaluation index revealed that step-down microwave heating strategies of 450 W-to-150 W and 300 W-to-150 W, applied at a temperature of 90 °C and a rotational speed of 0.2 Hz, were notably effective. These methods successfully minimized energy use while preserving the quality attributes of the final product, which were comparable to those of traditionally cooked and freeze-dried red beans. The combined approach of hot-air drying with step-down microwave heating presents a promising, energy-saving technique for producing quick-cooking beans that retain their rehydration qualities and texture.

Toward an application of automatic evaluation system for central facial palsy using two simple evaluation indices in emergency medicine.

A stroke is a medical emergency and thus requires immediate treatment. Paramedics should accurately assess suspected stroke patients and promptly transport them to a hospital with stroke care facilities; however, current assessment procedures rely on subjective visual assessment. We aim to develop an automatic evaluation system for central facial palsy (CFP) that uses RGB cameras installed in an ambulance. This paper presents two evaluation indices, namely the symmetry of mouth movement and the difference in mouth shape, respectively, extracted from video frames. These evaluation indices allow us to quantitatively evaluate the degree of facial palsy. A classification model based on these indices can discriminate patients with CFP. The results of experiments using our dataset show that the values of the two evaluation indices are significantly different between healthy subjects and CFP patients. Furthermore, our classification model achieved an area under the curve of 0.847. This study demonstrates that the proposed automatic evaluation system has great potential for quantitatively assessing CFP patients based on two evaluation indices.

Clarifying the correlations between hydraulic indicators evaluating the hydraulic performance of free water surface constructed wetlands.

Previous studies have shown a strong linear correlation between the common hydraulic indicators of free water surface constructed wetlands (FWS CWs), which results in the waste of computing resources and confusion in evaluating the hydraulic performance of FWS CWs. There is an urgent need to define a relatively independent and authoritative hydraulic indicator. In this study, based on three years' data, the correlations among five representative hydraulic indicators, that is, short-circuit index (φ10), Morrill dispersion index (MDI), effective volume ratio (e), moment index (MI), and hydraulic efficiency (λe), were analyzed by combining a variety of methods. The results of the correlation analysis and principal component analysis clearly showed the positive correlations among φ10, e, MI, and λe (p < 0.01), and the strong negative correlations between MDI and the remaining four indexes, which were further confirmed by redundancy analysis (RDA). Most importantly, the significant correlations between MI vs e and φ10 vs e were proved through rigorous mathematical reasoning for the first time. Besides, the results of RDA indicated that the studied design parameters, namely, water depth, hydraulic loading rate, plant spacing, aspect ratio, layout of inlet and outlet, and plant species, could generally explain the variation in hydraulic indicators. The layout of inlet and outlet displayed positive effects on hydraulic performance, and the water depth exhibited negative effects. Combining the clarity of physical meaning, convenience of calculation, and universality of reflecting both hydraulic and treatment performances, e was recommended as the most authoritative hydraulic indicator to evaluate hydraulic performance. The clustering results based on e were highly consistent with those based on the comprehensive principal component score. Wetlands with a combination of lower water depth and better layout of inlet and outlet usually have better hydraulic performance. This study successfully revealed the significant correlations among hydraulic indicators and their sources, and recommended a unique hydraulic indicator to authoritatively evaluate the hydraulic performance of FWS CWs.

Utilizing machine learning for reactive material selection and width design in permeable reactive barrier (PRB).

Permeable reactive barrier (PRB) is an important groundwater treatment technology. However, selecting the optimal reactive material and estimating the width remain critical and challenging problems in PRB design. Machine learning (ML) has advantages in predicting evolution and tracing contaminants in temporal and spatial distribution. In this study, ML was developed to design PRB, and its feasibility was validated through experiments and a case study. ML algorithm showed a good prediction about the Freundlich equilibrium parameter (R2 0.94 for KF, R2 0.96 for n). After SHapley Additive exPlanation (SHAP) analysis, redefining the range of the significant impact factors (initial concentration and pH) can further improve the prediction accuracy (R2 0.99 for KF, R2 0.99 for n). To mitigate model bias and ensure comprehensiveness, evaluation index with expert opinions was used to determine the optimal material from candidate materials. Meanwhile, the ML algorithm was also applied to predict the width of the mass transport zone in the adsorption column. This procedure showed excellent accuracy with R2 and root-mean-square-error (RMSE) of 0.98 and 1.2, respectively. Compared with the traditional width design methodology, ML can enhance design efficiency and save experiment time. The novel approach is based on traditional design principles, and the limitations and challenges are highlighted. After further expanding the data set and optimizing the algorithm, the accuracy of ML can make up for the existing limitations and obtain wider applications.

Establishment of an Evaluation Index System of Competencies for College Senior Students in General Practice Medicine in Anhui Province, China.

Background: The competencies of college senior students in general practice medicine have attracted attention. This study aimed to construct an evaluation index system of competencies for college senior students in general practice medicine and to promote the reform and optimization of training programs for general medicine talent in colleges. Methods: The two-round Delphi method was used to determine the evaluation index system of competencies for college senior students in general practice medicine, and the analytic hierarchy process (AHP) was used to calculate the weights of all levels of elements. Results: The evaluation index system of competencies for college senior students in general practice medicine was established with 3 primary factors, 9 secondary factors and 32 tertiary factors. The Delphi results revealed that the active coefficient of experts was 1 and the authority coefficient was 0.858. The 3 primary factors were knowledge level, job skills and professionalism with weights of 0.1532, 0.4207 and 0.4261, respectively. Among the secondary factors, the top three weight coefficients were professional ethics (0.2614), community practice (0.1526) and communication skills (0.1308). Among tertiary factors, "scientific research" exhibited the lowest value with a weight coefficient of 0.0049. Conclusion: In this study, we constructed an evaluation index system of competencies for college senior students in general practice medicine. The consensus on the content of the competencies of college senior students in general practice medicine suggests that these elements are necessary for those who will become general practitioners. This system can be used as the basis to evaluate the ability of college senior students in general practice medicine and provide guidance for the cultivation and evaluation of general medicine talent.

Research on Coal and Gangue Recognition Based on the Improved YOLOv7-Tiny Target Detection Algorithm.

The recognition technology of coal and gangue is one of the key technologies of intelligent mine construction. Aiming at the problems of the low accuracy of coal and gangue recognition models and the difficult recognition of small-target coal and gangue caused by low-illumination and high-dust environments in the coal mine working face, a coal and gangue recognition model based on the improved YOLOv7-tiny target detection algorithm is proposed. This paper proposes three model improvement methods. The coordinate attention mechanism is introduced to improve the feature expression ability of the model. The contextual transformer module is added after the spatial pyramid pooling structure to improve the feature extraction ability of the model. Based on the idea of the weighted bidirectional feature pyramid, the four branch modules in the high-efficiency layer aggregation network are weighted and cascaded to improve the recognition ability of the model for useful features. The experimental results show that the average precision mean of the improved YOLOv7-tiny model is 97.54%, and the FPS is 24.73 f·s-1. Compared with the Faster-RCNN, YOLOv3, YOLOv4, YOLOv4-VGG, YOLOv5s, YOLOv7, and YOLOv7-tiny models, the improved YOLOv7-tiny model has the highest recognition rate and the fastest recognition speed. Finally, the improved YOLOv7-tiny model is verified by field tests in coal mines, which provides an effective technical means for the accurate identification of coal and gangue.

Research on the evaluation system of "vegetation-atmosphere-water" environmental coordination development under ecological management.

As environmental issues on a global scale continue to worsen, all regions are pursuing ecological management and sustainable development strategies. The coordinated development of the "vegetation-air-water" environment is one of the most essential research topics in ecological governance. The purpose of this paper is to develop an evaluation system for the development of environmental governance in Shaanxi Province, as well as to evaluate the benefits of environmental governance in Shaanxi Province from 2012 to 2021 and its influencing factors. An index system for the coordinated development of "vegetation-atmosphere-water" is constructed, and the benefits and influencing factors of environmental governance are comprehensively analysed by using comprehensive analysis methods such as the coupled coordination model of the system and entropy weight TOPSIS. The results indicate that the development trend of the coupling coordination degree has evolved through the stages of "uncoordinated development at the early stage of governance, transformed development at the middle stage of governance, and coordinated development at the first success stage of governance." In addition, we identify the obstacles to the coordinated development of the environment and suggest appropriate countermeasures. The efficacy of environmental policy governance provides recommendations for future enhancements. It is important to note that ecological governance is influenced by both policy and nature; political influences, such as the switch from "returning farmland to forests" to "returning forests to farmland," will result in the destruction of the original good vegetation growth, which will significantly reduce the coordinated benefits of ecological governance. The original coordinated system will also be fractured, which is a problem worth contemplating. And policymakers, researchers, and practitioners can use the evaluation system and analysis method proposed in this paper as an effective tool to promote sustainable development and ecological governance.

[Health Assessment of the Stream Ecosystem in Beijing, China].

With economic development, the health of river ecosystems is becoming severely threatened because of the increasing effects of human activities on river ecosystems. Here, 101 sites along regional river systems in Beijing rivers were investigated from autumn 2020 to summer 2021. A total of 34 metrics, including aquatic organisms, hydrology, water quality, and habitat, were calculated to be the candidate indicators. Principal component and correlation analyses were used to select the core metrics from the candidate indicators, and the weight of each core metric was estimated using the entropy method. The integrated index of stream ecological health was constructed to assess the health condition of the Beijing rivers. The results of the PCA and correlation analyses revealed that eleven metrics were selected as the core metrics to construct the integrated index of stream ecological health, including water temperature, flow velocity, BOD5, NH4+-N, Cu, the density of phytoplankton and zooplankton, the Shannon-Wiener diversity index of macroinvertebrates and fish, the BMWP index, and the qualitative habitat evaluation index. According to the health assessment results, 4.95% of the sampling sites were healthy, 23.76% were subhealthy, and 71.29% were in a fair or below healthy state. The river health status showed strong spatial heterogeneity, and the river health statuses in the northern and western regions were relatively good, whereas the river health status in the central and southeastern regions were relatively poor. The results of four aspects stream ecosystem assessment showed that the overall water quality of the rivers was "subhealthy" and the aquatic organisms and habitat were "general poor," but the hydrology was "poor." The evaluation results of five water systems demonstrated that the Chaobai River had the best health status, followed by that of the Yongding River, Daqing River, and Jiyun River, and the Beiyun River had the worst health status. Maintaining river ecological baseflow, ensuring river system connectivity, and improving and restoring the river habitat environment are the key aspects of river ecological restoration and protection in Beijing in the future.

Developing an evaluation indicators of health literacy for cervical cancer among Chinese women: a modified Delphi method study.

BACKGROUND: Increasing women's health literacy is the key to preventing cervical cancer, and various tools have been developed to assess women's cancer health literacy. However, many of these tools come from other countries and have not been adapted to Chinese requirements. Furthermore, a system for evaluating cervical cancer health literacy among Chinese women has not been developed. Therefore, we sought to establish an evaluation index system for cervical cancer health literacy among Chinese women and to provide an effective evaluation tool for tertiary prevention of cervical cancer in China. METHODS: We invited 20 recognized experts to participate in two rounds of Delphi expert consultation, and the modified Delphi process with percentage weighting and multiplication was used. A literature review identified 67 potential indicators. Subsequent discussions within our research team led to the retention of 48 indicators following a rigorous screening process. On this basis, two rounds of Delphi expert consultation were conducted to rate and screen the indexes. Percentage weighting and multiplication were used to determine index weights. RESULTS: Twenty experts participated in the first-round Delphi consultations (95.23% recovery rate). In the second-round Delphi consultations, 20 questionnaires were returned (100%), and the expert authority coefficient was 0.93 ± 0.02. After both rounds of Delphi consultation, 4 first-level indicators, 9 second-level indicators, and 32 third-level indicators were identified for cervical cancer literacy among Chinese women. On a five-point scale, importance ratings ranged from 3.76 to 4.95 points, with variation coefficients ranging from 0.06 to 0.25, while sensitivity ratings ranged from 3.71 to 4.83 points, with variation coefficients ranging from 0.08 to 0.24. Across both rounds, Kendall's W coefficients ranged from 0.168 to 0.248. The weights of first-level indicators of basic knowledge and attitudes about cervical cancer, primary prevention of cervical cancer literacy, secondary prevention of cervical cancer literacy, and tertiary prevention of cervical cancer literacy were 0.257, 0.249, 0.251, and 0.243, respectively. CONCLUSIONS: We have developed the first tertiary prevention-based, comprehensive evaluation index system for cervical cancer literacy among Chinese women, which will provide theoretical support for cervical cancer prevention and health education programs.

Ecological impact assessment of green virtual water flow in inter-provincial crop commutation within China.

Green water is crucial for to regional ecological sustainability. Currently, there is a lack of research on the impact of crop green water communication on the regional ecology in China. The ecological impact index (EII) and integrated ecological water supply (IES) were proposed to comprehensively evaluate the regional ecological impact of the green virtual water flow (GVWF) of crops. Based on the principle of trade cost minimization, this study simulated the inter-provincial crop commutation within China during 2010-2019 by assigning weights to production, demand, and transportation costs, and analyzed the impact of crop communication on regional ecology. The results showed that multi-year average GVWF among provinces was 216.45 Gm3, accounting for 33.7 % of the total green water footprint of crops. The ecological impact of GVWF varies among provinces and years. The EII values in Beijing, Shanghai, and Jiangsu were all >100, whereas it was <1 in Yunnan and Xizang. Regional management policies for water resources, ecology, and economic development should be formulated taking into account the IES and EII jointly. It is recommended to increase the export of green virtual water of crops and expand the ecological area while ensuring the utilization rate of green water in regions with higher EII values, such as Guangxi and Yunnan. In the future, it is important for district managers to prioritize the quality of ecological development and protect ecological areas from erosion while pursuing urban development. This study innovatively evaluated the ecological impact of crop communication in different regions, which has guiding significance for the trade management in the ecologically water-deficient areas.

CNSeg: A dataset for cervical nuclear segmentation.

BACKGROUND AND OBJECTIVE: Nuclear segmentation in cervical cell images is a crucial technique for automatic cytopathology diagnosis. Experimental evaluation of nuclear segmentation methods with datasets is helpful in promoting the advancement of nuclear segmentation techniques. However, public datasets are not enough for a reasonable and comprehensive evaluation because of insufficient quantity, single data source, and low segmentation difficulty. METHODS: Therefore, we provide the largest dataset for cervical nuclear segmentation (CNSeg). It contains 124,000 annotated nuclei collected from 1,530 patients under different conditions. The image styles in this dataset cover most practical application scenarios, including microbial infection, cytopathic heterogeneity, overlapping nuclei, etc. To evaluate the performance of segmentation methods from different aspects, we divided the CNSeg dataset into three subsets, namely the patch segmentation dataset (PatchSeg) with nuclei images collected under complex conditions, the cluster segmentation dataset (ClusterSeg) with cluster nuclei, and the domain segmentation dataset (DomainSeg) with data from different domains. Furthermore, we propose a post-processing method that processes overlapping nuclei single ones. RESULTS AND CONCLUSION: Experiments show that our dataset can comprehensively evaluate cervical nuclear segmentation methods from different aspects. We provide guidelines for other researchers to use the dataset. https://github.com/jingzhaohlj/AL-Net.

A quality-comprehensive-evaluation-index-based model for evaluating traditional Chinese medicine quality.

BACKGROUND: Evaluating traditional Chinese medicine (TCM) quality is a powerful method to ensure TCM safety. TCM quality evaluation methods primarily include characterization evaluations and separate physical, chemical, and biological evaluations; however, these approaches have limitations. Nevertheless, researchers have recently integrated evaluation methods, advancing the emergence of frontier research tools, such as TCM quality markers (Q-markers). These studies are largely based on biological activity, with weak correlations between the quality indices and quality. However, these TCM quality indices focus on the individual efficacies of single bioactive components and, therefore, do not accurately represent the TCM quality. Conventionally, provenance, place of origin, preparation, and processing are the key attributes influencing TCM quality. In this study, we identified TCM-attribute-based quality indices and developed a comprehensive multiweighted multi-index-based TCM quality composite evaluation index (QCEI) for grading TCM quality. METHODS: The area of origin, number of growth years, and harvest season are considered key TCM quality attributes. In this study, licorice was the model TCM to investigate the quality indicators associated with key factors that are considered to influence TCM quality using multivariate statistical analysis, identify biological-evaluation-based pharmacological activity indicators by network pharmacology, establish real quality indicators, and develop a QCEI-based model for grading TCM quality using a machine learning model. Finally, to determine whether different licorice quality grades differently reduced the inflammatory response, TNF-α and IL-1ß levels were measured in RAW 264.7 cells using ELISA analysis. RESULTS: The 21 quality indices are suitable candidates for establishing a method for grading licorice quality. A computer model was established using SVM analysis to predict the TCM quality composite evaluation index (TCM QCEI). The tenfold cross validation accuracy was 90.26%. Licorice diameter; total flavonoid content; similarities of HPLC chromatogram fingerprints recorded at 250 and 330 nm; contents of liquiritin apioside, liquiritin, glycyrrhizic acid, and liquiritigenin; and pharmacological activity quality index were identified as the key indices for constructing the model for evaluating licorice quality and determining which model contribution rates were proportionally weighted in the model. The ELISA analysis results preliminarily suggest that the inflammatory responses were likely better reduced by premium-grade than by first-class licorice. CONCLUSIONS: In the present study, traditional sensory characterization and modern standardized processes based on production process and pharmacological efficacy evaluation were integrated for use in the assessment of TCM quality. Multidimensional quality evaluation indices were integrated with a machine learning model to identify key quality indices and their corresponding weight coefficients, to establish a multiweighted multi-index and comprehensive quality index, and to construct a QCEI-based model for grading TCM quality. Our results could facilitate and guide the development of TCM quality control research.

Study on skin infection model of Staphylococcus aureus based on analytic hierarchy process and Delphi method.

Purpose: Infectious skin diseases are a type of inflammatory skin lesions caused by pathogenic microorganisms. Because of the uncertainty of methodology, the skin infection model usually have low replication rate and lack of good evaluation system. We aimed to establish multi-index and comprehensive evaluation method for Staphylococcus aureus (S.aureus) skin-infection models through Analytic hierarchy process (AHP) and Delphi method, and screen high quality animal models through it. Materials and methods: Firstly, the evaluation indicators of skin infection were collected basing on literature research. The weight of the evaluation indicators were decided according to AHP and Delphi method. Then different ulcer models (mouse or rat) infected by S. aureus were selected as the research objects. Results: The evaluation indicators were classified into four groups of criteria (including ten sub-indicators) and given different weights, physical sign changes (0.0518), skin lesion appearance (0.2934), morphological observation (0.3184), etiological examination (0.3364). Through the evaluation system, we screened and found that the mouse ulcer model which caused by a round wound and 1.0 × 1010 CFU/mL (0.1 mL) bacterial concentration got the highest comprehensive score, and also found that the model which caused by a 1.5 cm-round wound and 1.0 × 1010 CFU/mL (0.2 mL) maybe the best rat ulcer model. Conclusions: This study has established an evaluation system based on AHP and Delphi method, also provided the best skin ulcer models selected by this system, the models are suitable for disease research and drug development research of skin ulcer.

Research on the construction of the evaluation index system of game-based teaching.

This research aims to combine the pursuit of literacy cultivation with a focused investigation into the evidence of game-based teaching (GBT). To achieve this, the study employs a mixed-methods approach including the interview method, Delphi method, and network hierarchical analysis (ANP) to analysis Expert opinions and construct a comprehensive GBT evaluation index system. The results indicated that a comprehensive GBT evaluation index system is comprised of five primary indicators: teaching objectives, game-based teaching methods, teaching content, game-based teaching processes, and game-based teaching characteristics. Additionally, there are 19 secondary indicators, such as objective content, game presentation, context construction, and flow experience. This study expects to effectively capture the unique attributes of game-based classes and to assist teachers in improving the design of GBT activities in practical applications.

Quantitative cost­effectiveness index of cancer treatments.

In spite of advancements being made in technology and treatment strategies, which have markedly improved the survival rate of patients, the cost of cancer care worldwide has increased over the past decades. The presence of several cost-effectiveness ratios has provided significant indexes to assess the balance between cost and effectiveness. However, the currently available indexes still fail to provide a comprehensive and objective evaluation of cancer treatment. Therefore, the present study developed a novel approach, namely a quantitative cost-effectiveness index of cancer treatment, based on the calculation of the hospitalization expense index and efficacy evaluation index. The present study used the data of 16 patients with childhood acute myeloid leukemia who received the high-dose chemotherapy as an example, and the quantitative cost-effectiveness index was used to evaluate the value of this approach. As the increasing prevalence of cancer and the rising cost of pharmaceuticals have contributed to the expenditure, the development of this index may help to solve the current dilemma of cancer treatment and may prove to be essential for the development of an effective approach which may be accessible to and affordable by common persons; thus would then lead to a higher cure rate.

Zero-valent iron based materials selection for permeable reactive barrier using machine learning.

The zero-valent iron (ZVI) based reactive materials are potential remediation reagents in permeable reactive barriers (PRB). Considering that reactive materials is the essential to determining the long-term stability of PRB and the emergence of a large number of new iron-based materials. Here, we present a new approach using machine learning to screen PRB reactive materials, which proposes to improve the efficiency and practicality of selection of ZVI-based materials. To compensate for the insufficient amount of existing machine learning source data and the real-world implementation, machine learning combines evaluation index (EI) and reactive material experimental evaluations. XGboost model is applied to estimate the kinetic data and SHAP is used to improve the accuracy of model. Batch and column tests were conducted to investigate the geochemical characteristics of groundwater. The study find that specific surface area is a fundamental factor correlated with the kinetic constants of ZVI-based materials, according to SHAP analysis. Reclassifying the data with specific surface area significantly improved prediction accuracy (reducing RMSE from 1.84 to 0.6). Experimental evaluation results showed that ZVI had 3.2 times higher anaerobic corrosion reaction kinetic constants and 3.8 times lower selectivity than AC-ZVI. Mechanistic studies revealed the transformation pathways and endpoint products of iron compounds. Overall, this study is a successful initial attempt to use machine learning for selecting reactive materials.

Evaluation of ecological green high-quality development based on network hierarchy model for the demonstration area in Yangtze River Delta in China.

Introduction: The construction of the Yangtze River Delta ecological green development demonstration area aims to take the lead in exploring an eco-friendly development model, demonstrating and leading the higher quality integrated development of the Yangtze River Delta in China. Methods: Through literature research, expert inquiries, and policy documents as the guidance, this study builds an ecological green high-quality development evaluation system for the demonstration area, including building an index system composed of 4 first-class indicators, 16 second-class indicators and 42 third-class indicators derived from economy, society and environment system, determining the index weight through the network analytic hierarchy process, and establishing the comprehensive evaluation index (CEI) and differential diagnosis index (DDI) of high-quality development, which is based on the relevant theory of statistical comprehensive index. Results: The establishment of this system provides a complete theoretical support and scientific guidance for the comprehensive evaluation of high-quality ecological green development and more balanced development of the demonstration area; and it can point out the development direction for the subsequent development of the Yangtze River Delta. Discussion: However, due to the availability of data, there is still room for further improvement in this paper. In the future research, the model can be used to evaluate the high-quality development level of the demonstration area through the relevant data of the demonstration area.

Evaluation of Citizen Epidemic Prevention Information Literacy in the Post-Epidemic Era in Mainland China.

Improving citizen epidemic prevention information literacy is one of the most cost-efficient and important measures to improve people's epidemic prevention abilities to effectively deal with future public health crises. Epidemic prevention information literacy is beneficial to improve individuals' ability to deal with public health crises in the future. By summarizing related domestic and international research, and utilizing an empirical methodology, we constructed an epidemic prevention information literacy assessment model with good reliability, validity, and model fit. The model is composed of four indicators: (1) "epidemic prevention information awareness"; (2) "epidemic prevention information knowledge"; (3) "epidemic prevention information ability"; (4) "epidemic prevention information morality". We used the model to assess the epidemic prevention information literacy of Chinese citizens. The results showed the following: (1) the overall level of the epidemic prevention information literacy of Chinese citizens was comparatively high, however, its development was unbalanced, and the capability and moral levels of the epidemic prevention information were comparatively low; (2) the four dimensions of the epidemic prevention information literacy were different in terms of the citizens' education levels and locations. We analyzed the probable causes of these problems, and we propose specific corresponding countermeasures. The research provides a set of methods and norms for the evaluation of citizen epidemic prevention information literacy in the post-epidemic era.

A study on the quality evaluation index system of smart home care for older adults in the community --based on Delphi and AHP.

BACKGROUND: In the context of the "silver wave" and "technology wave", smart home care for older adults in the community provide new ways for China and other countries to support ageing in place. Yet, only very few studies have focused on developing a quality index system of smart care. This study attempted to draw on the SERVQUAL model to establish a quality evaluation index system for smart senior care for older adults in the community. METHODS: On the basis of the service quality model, this paper has integrated qualitative and quantitative analyses using the Delphi and Analytic Hierarchy Process (AHP) methods to construct the index system of smart home care in the community and obtain the weights. These were based on literature research and field interviews in Guangzhou and Shenzhen pilot districts. RESULTS: A quality evaluation indexes system of smart home care for older adults in the community was developed, with 5 primary indices and 33 secondary indices. The weights of the 5 stair indices from high to low were smart emergency assistance 0.332, smart meal assistance 0.272, smart medical assistance 0.229, smart cleaning assistance 0.110 and smart amusement assistance 0.057. CONCLUSION: The results from the weight allocation revealed smart emergency assistance, smart meal assistance, and smart medical care assistance were the most important and crucial aspects of community-based smart home care. The study also suggested that "timeliness", "reliability", and "ease of use" should be given more attention. It is recommended to use this index system as a regulatory benchmark to guide the government bodies, senior care enterprises and communities to take measures to enhance the quality.

Improved method for benthic ecosystem health assessment by integrating chemical indexes into multiple biological indicator species-A case study of the Baiyangdian Lake, China.

A comprehensive and scientific assessment of benthic ecosystem health is key to the rational selection of endogenous pollution reduction technologies for lakes. However, current assessments are mainly limited to biological indicators and ignore the actual benthic ecosystem situations, such as the impact of eutrophication and heavy metal pollution, which may lead to the one-sidedness of the evaluation results. In this study, taking Baiyangdian Lake, the largest shallow mesotrophic-eutrophic lake in the North China Plain, as an example, the chemical assessment index and biological integrity index were first combined to estimate the biological conditions, nutritional status and heavy metal pollution of lakes. The indicator system incorporated three biological assessments (benthic index of biotic integrity (B-IBI), submerged aquatic vegetation index of biological integrity (SAV-IBI) and microbial index of biological integrity (M-IBI)) and three chemical assessments (dissolved oxygen (DO), comprehensive trophic level index (TLI) and index of geoaccumulation (Igeo)). Twenty-three attributes of B-IBI, fourteen attributes of SAV-IBI and twelve attributes of M-IBI were screened by range, responsiveness, and redundancy tests to keep the core metrics that were significantly correlated with disturbance gradients or showed strong discriminatory power between reference and impaired sites. The assessment results of B-IBI, SAV-IBI, and M-IBI showed significant differences in the response to anthropogenic activities and seasonal change, among which the submerged plants showed more significant seasonal differences. It is difficult to reach a comprehensive conclusion regarding the benthic ecosystem health status based on a single biological community. In comparison with biological indicators, the score of chemical indicators is relatively low. DO, TLI and Igeo provide an essential supplement for the benthic ecosystem health assessment of lakes with eutrophication and heavy metal pollution problems. Using the new integrated assessment method, the benthic ecosystem health of Baiyangdian Lake was rated as fair, especially the northern parts of the lake adjacent to the inflow mouth of the Fu River, which were in poor condition, indicating that the lake has experienced anthropogenic disturbance, resulting in eutrophication, heavy metal pollution and biological community degradation. Whether it's spring or summer, the integrated assessment method provides a more plausible and comprehensive view of benthic ecosystem health under the pressure of increasing human activities and changing habitat and hydrological conditions, overcoming the narrow perspective and uncertainties of the single-index method. Thus, it can assist lake managers in providing technical support for ecological indication and restoration.