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It has been controversial whether the matching of learning styles with teaching environment has improved the teaching effects. This paper constructs matching modes by choosing Sternberg's three learning styles (liberal leaning, internal scope and global level) and adopts curriculum comprehensiveness and instructing modes. The research, based on data of off-line teaching collected from 456 college students in China, finds that: (1) direct effect: three learning styles have significant effects on eight dimensions of learners' cognitive information processing (CIP); (2) matching effect: the alignment of learners' liberal leaning and instructing modes has a direct impact on the eight dimensions of learners' CIP; the alignment of learners' global level and curriculum characteristics has a direct impact on the 7 dimensions; the alignment of learners' internal scope and instructing modes have no significant direct impact on the 7 dimensions; and (3) moderating effect of the mandatory use of IT (MUIT): MUIT may restrain or strengthen effects of some matching modes on some dimensions of CIP. The key conclusion is that whether personalized instructing based on learners' characteristics can improve teaching results requires the selection of appropriate matching modes. Not all matching modes have matching effects, and matching effect is influenced by MUIT.

We collected 599 policies related to medical treatment combination issued by local governments from October 2010 to December 2022 to study the differences and characteristics of medical treatment combination policies in different regions of China. Descriptive statistics and the structural topic model were used to compare medical treatment combination policies in four major economic regions (West, Central, East, Northeast) of China from three dimensions: the number of policies issued, policy types and policy topics. The study shows that: the structure of Chinese local medical treatment combination policy system was not balanced and was characterized by an emphasis on implementation rules rather than standard specifications; the construction of hierarchical diagnosis and treatment service system and the management model of medical treatment combination are hot topics, while the topics such as supporting measures and disease prevention and treatment have not received widespread attention. The construction of medical treatment combination in each region shows diversified exploration. The local government needs to issue relevant policies according to the regional differences, so as to supplement the shortcomings of the policy and promote the improvement of the policy system of the regional medical treatment combination. [ABSTRACT FROM AUTHOR]

In recent years, the sustainable development of agricultural water resources has received much attention. The mismatch between agricultural water distribution patterns, land resources, and socioeconomics threatens food production, especially in vast water-scarce plains. Therefore, monitoring agricultural water spatial equilibrium (AWRSE) is necessary. Based on equilibrium theory and information entropy, in this study, the AWRSE evaluation model is constructed from three aspects: agricultural water resources, land resources, and socioeconomics. In addition, the relationship between social factors with cropping pattern as the primary explanatory variable and AWRSE was examined in conjunction with the extended STIRPAT model and applied to the water-receiving area of the Middle Route of South-to-North Water Diversion Project (MR-SNWDP). The results show that compared with the pre-diversion period, the AWRSE of 75% of the water-receiving cities has been significantly improved by the MR-SNWTP water supply. The MK test z value of the overall regional AWRSE has changed from − 0.328 to − 2.65, and the AWRSE development has shifted from not significantly better to significantly better. The cropping pattern shows a positive response to this development, and this effect can be mitigated in the late stage of water transfer; when the proportion of food crop cultivation increases by 1%, the sub-regional AWRSE value will increase by 0.347%. The evaluation model demonstrates a broad range of inclusiveness and application potential; it provides novel insights for examining agroecological, social, and economic stability. [ABSTRACT FROM AUTHOR]

There is an urgent need to ensure regional food security and increase irrigation water productivity in response to water shortages in arid and semi-arid regions. Previous studies of the optimal allocation of irrigation water did not consider simultaneously optimizing across multiple crops or at different growth stages. This paper describes the development of an irrigation water optimization model that uses a crop water allocation priority (CWAP) model. The CWAP value was determined by quantifying the changes in three indicators: yield, economic benefits, and irrigation water productivity. Maximum yield, maximum economic benefits, and minimum irrigation shortage (at the critical crop and growth stage) were used as the objective functions of a non-linear multi-objective optimization model. The largest irrigation district in the northern arid area of China, Hetao Irrigation District (HID), was chosen to prototype this model. The optimization results, using CWAP, showed that yield, economic benefits, irrigation water productivity, and water productivity could be increased, respectively, by up to 13.38%, 13.40%, 2.30%, and 6.29%, for most crops when compared with optimization results without CWAP. Comparison of the optimized net irrigation quantities with the actual net irrigation quantities showed that optimization reduced water usage by up to 60.77% for wheat, 51.24% for corn, and 63.59% for sunflower. Blue water utilization under optimal irrigation conditions decreased by 1.12% for wheat, 2.91% for corn, and 9.91% for sunflower, compared with those in actual irrigation scenario. This method of optimizing irrigation water allocation in arid areas using CWAP provides decision-makers with accurate water-saving irrigation protocols that will reduce demand for water resources and promote sustainable agriculture. [ABSTRACT FROM AUTHOR]

A time series of satellite data on Chlorophyll-a concentration (Chl-a) that used ocean color was studied to determine mechanisms of phytoplankton variation in recent decade in the Yellow Sea, China during 2003–2015. The variability patterns on seasonal and inter-annual oscillation periods were confirmed using the Empirical Orthogonal Function (EOF), and Morlet wavelet transform analyses, respectively. The first EOF mode for Chl-a was dominated by obvious spring and fall blooms in a spatial pattern that was related to the strong mixing of the water masses from the Yellow Sea Cold Warm Mass (YSCWM) and the Yellow Sea Warm Current (YSWC) in winter. The second EOF mode for Chl-a showed an opposite spatial pattern between the northern and southern regions. The temporal coefficient showed differences in the timing of blooms. On an inter-annual scale, Chl-a indicated variation at periods of 2–4 years during 2003–2015. Chl-a showed a significantly negative correlation with the sea surface temperature (r = -0.21, p<0.01), with time lags of 4 months (Chl-a ahead). Chl-a was coupled with El Niño Southern Oscillation (ENSO) events, with a positive correlation (r = 0.46, p<0.01) at a lag of 3–5 months (ENSO ahead). The present study demonstrated that the variation in phytoplankton biomass was controlled primarily by water mass seasonally, and it was influenced by ENSO events on an inter-annual scale. [ABSTRACT FROM AUTHOR]

Agricultural water management is the core part of agricultural efficient water use in irrigation districts, which provides basic guarantee and decision-support for improving the efficiency of water production. This study was conducted in three typical irrigation districts in Huang-huai-hai river basin of north China. The evaluation index system of agricultural water management in irrigation districts was established which included technology index, engineering index, management index, environment index and economic index, classified 5 sorts of second-grade indices, 14 third-grade indices and 35 fourth-grade indices. The weight of each index was confirmed through improved AHP method. The grades of agricultural water management of Fenhe, Shijin and Renmin Shengliqu irrigation districts in Huang-huai-hai riverbasin were obtained using Grey Correlation method and Fuzzy Comprehensive Evaluation method. Results showed that the evaluation indices ranked according to the descending order of their weights as engineering index, 0.2147; management index, 0.2138; technology index, 0.2128; economics index, 0.1797; environment index, 0.1791 in the criterion level. The engineering and management index were the most two important factors which influenced the agricultural water management in irrigation districts. The grades of Fenhe, Shijin and Renmin Shengliqu irrigation districts were good, good and average, respectively. The study provides a theoretical basis in improving the level of agricultural water management and water use efficiency in irrigation districts of north China. [ABSTRACT FROM AUTHOR]

Modelling crop evapotranspiration (ET) response to different planting scenarios in an irrigation district plays a significant role in optimizing crop planting patterns, resolving agricultural water scarcity and facilitating the sustainable use of water resources. In this study, the SWAT model was improved by transforming the evapotranspiration module. Then, the improved model was applied in Qingyuan Irrigation District of northwest China as a case study. Land use, soil, meteorology, irrigation scheduling and crop coefficient were considered as input data, and the irrigation district was divided into subdivisions based on the DEM and local canal systems. On the basis of model calibration and verification, the improved model showed better simulation efficiency than did the original model. Therefore, the improved model was used to simulate the crop evapotranspiration response under different planting scenarios in the irrigation district. Results indicated that crop evapotranspiration decreased by 2.94% and 6.01% under the scenarios of reducing the planting proportion of spring wheat (scenario 1) and summer maize (scenario 2) by keeping the total cultivated area unchanged. However, the total net output values presented an opposite trend under different scenarios. The values decreased by 3.28% under scenario 1, while it increased by 7.79% under scenario 2, compared with the current situation. This study presents a novel method to estimate crop evapotranspiration response under different planting scenarios using the SWAT model, and makes recommendations for strategic agricultural water management planning for the rational utilization of water resources and development of local economy by studying the impact of planting scenario changes on crop evapotranspiration and output values in the irrigation district of northwest China. [ABSTRACT FROM AUTHOR]

Optimizing layout of pumping well plays a vital role in curbing the groundwater level decline. A novel optimization model is presented in this study. First, the optimal well number is obtained by taking into account factors of local economy and environment based on nonlinear programming model. Then, the well spatial layout assessment model is attained based on information entropy weight and technique for order preference by similarity to ideal solution (TOPSIS). After that, the relative closeness to positive ideal solution of alternative ( ci) on the rationality of well spatial layout in cultivated land is calculated, and a set of alternatives are ranked according to the descending order of ci. Finally, the well optimization layout is obtained by combining the optimal well number with well spatial layout assessment result based on the GIS data of pumping wells. As a case study, this method was applied in Yongchang Irrigation District of Shiyang River Basin, the arid region of northwest China. Results show that under the conditions of sustainable use of water resources, the irrigation district needed 724 wells for irrigation, with a decrease of 31.0% when compared with the existing number of wells. The wells with low flow rate and operating efficiency distributed in high density where groundwater is over-exploitation were recommended to be closed. This well optimization layout method is expected to play a significant role in helping make plans for exploiting groundwater at more sustainable level, curbing the groundwater level decline trend, and improving the local ecological environment. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

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The China-France Oceanography SATellite (CFOSAT), launched on 29 October 2018, is a joint mission developed by China and France. To evaluate the CFOSAT wind product, L2B swath data with a spatial resolution of 25 × 25 km were compared with in situ measurements between December 2018 and December 2020. The in situ measurements were collected from 217 buoys. All buoy winds were adjusted to 10 m height using a simple logarithmic correction method. The temporal and spatial separations between the CFOSAT and in situ measurements were restricted to less than 30 min and 0.25°. The results indicate that the CFOSAT wind retrievals agree well with the buoy measurements. The root mean square errors (RMSEs) of wind vectors were 1.39 m s−1 and 34.32° and negligible biases were found. In the near shore under rain-free conditions, the RMSEs were enhanced to 1.42 m s−1 and 33.43°. Similarly, the RMSEs were reduced to 1.16 m s−1 and 30.41° offshore after the rain effect was removed. After winds less than 4 m s−1 were removed, the RMSE of wind directions was reduced to 19.69°. The effects of significant wave height, air-sea temperature difference, sea surface temperature, atmospheric pressure and ocean surface current on the wind residuals were assessed. The performance of wind retrievals under the passage of tropical cyclones was evaluated. The evaluation results show that the CFOSAT wind retrievals satisfy the accuracy requirements of scientific research, although some improvements are needed to enhance the performance. [ABSTRACT FROM AUTHOR]

[Display omitted] • Classical optimal planting pattern (COPP) can improve regional water productivity. • The first assessment regarding the impact of COPP on food-energy-water-carbon nexus. • COPP can decrease carbon neutrality capacity by 13.09% in China's major arid area. • Need to redefine "optimum" planting pattern under the context of global warming. Global warming, water scarcity and limited land resources are the most challenging problems facing agriculture to ensure food security for the expected 9 billion people in 2050. To solve these problems, the classical optimal planting pattern, based on crop suitability evaluation method, is often adopted to reallocate water and land resources. However, whether or not the classical optimal planting pattern, which only considers environmental conditions in crop suitability evaluation, is beneficial to the regional carbon neutrality goal and saves water and energy resources has rarely been explored. Here, China's major arid food production area, the middle reaches of Heihe River Basin, is chosen as the demonstration to explore this issue. The classical optimal planting pattern obtained by crop suitability evaluation is compared with current planting in terms of planting distribution, carbon sequestration, energy consumption and water productivity from 2002 to 2016. Interestingly, the results indicate that optimal planting would reduce the regional net carbon sequestration capacity by up to 13.09% and increase regional carbon emissions by up to 22%, which is harmful to reach the commitment of carbon neutrality goal in China. Contrary, optimal crop planting pattern can increase regional water productivity by 1.74–32.59% and economic benefits by 1.52–30.55% while having little impact on energy consumption and water consumption. Considering the contradictions effects of classical optimal planting pattern on the food-energy-water-carbon nexus, we strongly recommend redefining the "optimal" in crop planting management by taking impacts on carbon into consideration to alleviate the crisis of global warming. [ABSTRACT FROM AUTHOR]

When planning agricultural production, planting area and water allocation are two major subjects faced by decision makers. In this study, a framework integrated Nerlove supply response model (Nerlove model) and interval fuzzy credibility-constraint bi-level programming (IFCBP) model is developed for planning the agricultural production in arid and semi-arid regions. Through Nerlove model, the planning process of crop planting area was described as an economic problem for forecasting farmers' behavior rather than an optimization problem for allocating farmland resources, and the relationship between crop planting area and market price can be obtained and further provide credible future crop planting area information. The IFCBP model can not only deal with uncertainties presented as interval and fuzzy numbers but also examine the credibility of the constraints and handle tradeoffs between two-level decision makers. To solve the IFCBP model, a solution method based on the interval interactive algorithm and credibility-cut method is proposed. Then, to verify the validity of the developed framework and solving method for agricultural production planning, they were applied to a real-case in the middle reaches of the Heihe River basin, northwest China. The forecasting results obtained from Nerlove model have better performance in predicting the future planting area of corn and vegetable than wheat, indicating that wheat plays a more vulnerable role in the decision-making process of planting area owing to its higher substitutability. The results show that the proposed framework can tackle two-level decision makers' concerns under uncertainties featured as inexact and fuzzy numbers, which can help regional managers plan future resources effectively. Furthermore, a comparison was made between IFCBP and two corresponding single-level models in this study. The comparison indicates that the developed model provides an effective tradeoff between two decision makers from different decision-making levels in IFCBP. The developed framework provides managers an effective way to plan agricultural production in arid and semi-arid regions, and the developed model and related thinking may help solve similar problems. • An agricultural production planning approach based on interval fuzzy credibility-constrained bi-level programming (IFCBP) and Nerlove supply response theory. • Both objective and subject factors are considered through the entropy method and analytic hierarchy process method separately. • This approach is applied to a case study for planning crop planting area and irrigation-water allocation. • The results can support water managers formulate more efficient agricultural production planning strategy. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel regional grid-scale crop dynamic layout optimization model was constructed. • Multiyear crop layout plan was obtained by considering inter-annual impacts. • Spatial variance of parameters and neighbourhood effects of crop units were noted. • Overall government planning and farmers' crop rotation behaviour were regarded. • Stakeholders and their multi-objective planting preferences were balanced. Rapid population growth has led to an increasing demand for food, accompanied by an increase in the resources invested in producing food, and the extensive food production practices have placed a huge burden on the environment. There is an urgent desire of need to find a sustainable model of food production. Therefore, this study attempted to develop a dynamic regional grid-scale crop layout model (ABCAMODP-Crop) combining agent-based model, multi-objective programming, dynamic programming and cellular automata model to promote more sustainable food production from a supply-side perspective. The model can: (1) take into account the planting preferences and practical behaviours of government and farmer as stakeholders in crop layout; (2) further weigh the conflicts among the various objectives that stakeholders are concerned with from resource, environmental, nutritional and economic dimensions; (3) consider the impact of the previous year's crop layout on the next year's crop placement; and (4) obtain grid-scale accurate crop layout solutions by considering the spatial variability of optimization parameters and the neighborhood effects of crop layout cells. The model was applied to the Shiyang River Basin in China to verify its usefulness. Over the entire planning period, crop layout schemes optimized with the objective of integrating irrigation water productivity, environmental impact, nutrient availability and economic benefits have higher comprehensive benefits than the original scheme, with an increase in average irrigation water productivity per unit area of 14.55%, an increase in total yield of 14.45%, an increase in total carbohydrate availability of 7.39%, an increase in total calcium availability of 18.74%, an increase in total net carbon sequestration of 8.05%, an increase in total net benefit of 20.08%. The model developed allows for a holistic view of crop layout and guides decision-makers in a rational distribution of regional crops, thus promoting more sustainable food production. It can equally be extended to other regions as a generic modelling framework. [ABSTRACT FROM AUTHOR]

Rapidly growing population has led to increasing food demands and greater food system pressure. It is urged to find a way to improve the sustainability of food system. Therefore, this study attempted to develop a regional crop layout model (CAMOO-Crop) combining cellular automata model with multi-objective optimization model to improve food system sustainability. The model can (1) consider the carbon sequestration of farmland vegetation, carbon emissions from production inputs, and human demand for crop nutrient supply, (2) balance the trade-offs among multiple dimensions of resource, environment, economy and nutrition in the crop food system, (3) obtain grid-scale crop space layout schemes considering special distribution. The model was applied to the Shiyang River Basin in China to verify its effectiveness. After optimization, crop water productivity per unit area increased by 2.12%, carbon sequestration increased by 0.32%, carbon emission decreased by 1.87%, the net benefit increased by 2.66%, carbohydrate supply decreased by 0.19%, calcium supply increased by 5.74%. In addition, a cropland-scale food system sustainability evaluation index system was constructed, and the Food System Sustainability Index (FSSI) and Coupling Coordination Degree (CCD) were introduced to evaluate the sustainability of food systems under different crop layout scenarios. The results showed that compared with single-objective model scenario and the status quo, CAMOO-Crop model performed best, with FSSI from 0.70 to 0.91; CCD from 0.83 to 0.95. The developed model can promote sustainable development of the regional food system and guide decision-makers to rationally distribute regional crops. [Display omitted] • A novel crop layout framework was developed to improve food system sustainability. • A model for coupling cellular automata and multi-objective programming was provided. • Trade-offs between resource, environment, economy and nutrition were realized. • A farmland scale food system sustainability evaluation system was constructed. • Layout options were developed for decision-makers considering special distribution. [ABSTRACT FROM AUTHOR]

It is urgent to determine the crop critical irrigation period and the priority of crop water irrigation in arid and semi-arid regions to cope with agricultural water shortage. In this study, a method combining Agricultural Production Systems Simulator (APSIM) crop model with grey relational analysis was proposed to determine the irrigation priority of wheat, maize, and sunflower in the irrigation water distribution to ensure food security, and applied to the Hetao Irrigation District (HID) in China. Crop irrigation priority was determined by crop yield, water supply demand ratio (SDR), and water productivity (WP). The maximum yield, maximum water productivity and minimum water stress (crop growth stage) were evaluated. The obtained results indicate that: (1) When the irrigation scenario was 100%, the critical irrigation period for wheat was the first 10 days after sowing and 40–61 days after sowing; The critical irrigation priority for maize was 20–30 days after sowing and 61–81 days after sowing; And the critical irrigation priority for sunflower was 30–61 days after sowing. (2) In early May, irrigation priority was wheat priority to maize, while maize was a priority to wheat in mid to late May. In June, sunflower priority to wheat and maize irrigation. From early to middle July, irrigation priority to maize, and from late July to late August, sunflower water irrigation priority to maize. The method of to identify irrigation priority and crop priority to provide irrigation decision for allocating agriculture water resources. [Display omitted] • A novel method based on crop model and grey relational analysis is proposed. • The best irrigation time after sowing wheat, maize, and sunflower is identified. • Priority for intercrop water irrigation at the same time is proposed. • The effects of water stress, water productivity, and yield is considered. [ABSTRACT FROM AUTHOR]

Background: The integrated health management system (IHMS), which unites all health care-related institutions under a health-centered organizational framework, is of great significance to China in promoting the hierarchical treatment system and improving the new health care reform. China's IHMS policy consists of multiple policies at different levels and at different times; however, there is a lack of comprehensive interpretation and analysis of these policies, which is not conducive to the further development of the IHMS in China., Objective: This study aims to comprehensively analyze and understand the characteristics, development, and evolution of China's IHMS policy to inform the design and improvement of the system., Methods: We followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to collect 152 policy documents. With the perspective of policy tools and policy orientation as the core, a comprehensive 6D framework including policy level, policy nature, release time, policy tools, stakeholders, and policy orientation was established by combining the content of policy texts. These dimensions were then analyzed using content analysis., Results: First, we found that, regarding the coordination of policy tools and stakeholders, China's IHMS policy was more inclined to use environment-based policy tools (1089/1929, 56.45%), which suggests a need for further balance in the internal structure of policy tools. Attention to different actors varied, and the participation of physicians and residents needs further improvement (65/2019, 3.22% and 11/2019, 0.54%, respectively). Second, in terms of level differences, Shanghai's IHMS policy used fewer demand-based policy tools (43/483, 8.9%), whereas the national IHMS policy and those of other provinces and cities used fewer supply-based tools (61/357, 17.1% and 248/357, 69.5%, respectively). The national IHMS strategy placed more emphasis on the construction of smart health care (including digital health; 10/275, 3.6%), whereas Shanghai was a leader in the development of healthy community and healthy China (9/158, 5.7% and 4/158, 2.5%, respectively). Third, in terms of time evolution, the various policy tools showed an increasing and then decreasing trend from 2014 to 2021, with relatively more use of environment-based policy tools and less use of demand-based policy tools in the last 3 years. The growth of China's IHMS policy can be divided into 3 stages: the disease-centered period (2014-2017), the e-health technology development period (2017-2019), and the health-centered period (2018-2021)., Conclusions: Policy makers should make several adjustments, such as coordinating policy tools and the uneven relationships among stakeholders; grasping key policy priorities in the context of local characteristics; and focusing on horizontal, multidimensional integration of health resources starting from the community. This study expands the objects of policy research and improves the framework for policy analysis. The findings provide some possible lessons for future policy formulation and optimization., (©Yang Yu, Sufen Wang, Lijue You. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 24.01.2024.)

Background: The application of big data resources and the development of medical collaborative networks (MCNs) boost each other. However, MCNs are often assumed to be exogenous. How big data resources affect the emergence, development, and evolution of endogenous MCNs has not been well explained., Objective: This study aimed to explore and understand the influence of the mechanism of a wide range of shared and private big data resources on the transaction efficiency of medical services to reveal the impact of big data resources on the emergence and development of endogenous MCNs., Methods: This study was conducted by administering a survey questionnaire to information technology staff and medical staff from 132 medical institutions in China. Data from information technology staff and medical staff were integrated. Structural equation modeling was used to test the direct impact of big data resources on transaction efficiency of medical services. For those big data resources that had no direct impact, we analyzed their indirect impact., Results: Sharing of diagnosis and treatment data (β=.222; P=.03) and sharing of medical research data (β=.289; P=.04) at the network level (as big data itself) positively directly affected the transaction efficiency of medical services. Network protection of the external link systems (β=.271; P=.008) at the level of medical institutions (as big data technology) positively directly affected the transaction efficiency of medical services. Encryption security of web-based data (as big data technology) at the level of medical institutions, medical service capacity available for external use, real-time data of diagnosis and treatment services (as big data itself) at the level of medical institutions, and policies and regulations at the network level indirectly affected the transaction efficiency through network protection of the external link systems at the level of medical institutions., Conclusions: This study found that big data technology, big data itself, and policy at the network and organizational levels interact with, and influence, each other to form the transaction efficiency of medical services. On the basis of the theory of neoclassical economics, the study highlighted the implications of big data resources for the emergence and development of endogenous MCNs., (©Junyi Yuan, Sufen Wang, Changqing Pan. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 21.04.2022.)