Search Results (33)

Geopolitical conflicts continue to disrupt global energy supply chains, causing sharp changes in energy prices. These changes reshape the cost structure and efficiency levels of grain circulation. Based on panel data from 30 Chinese provinces covering 2011–2022, this study constructs a proxy for grain circulation efficiency using a resource misallocation framework and counterfactual decomposition. We employ panel threshold regression and double machine learning methods to systematically examine the nonlinear impact of energy price levels on grain circulation efficiency and to reveal regional differences. The findings are as follows: (1) Energy price levels exhibit a significant single-threshold effect. When energy prices remain within a low range, rising prices exert a positive technology push effect; beyond the threshold, a cost-squeeze suppression dominates. (2) The eastern region shows the highest tolerance for price increases, whereas the western region has the lowest tolerance, with the central region falling in between. (3) Double machine learning feature importance analysis reveals that research and experimental development investment and economic development are the dominant factors affecting agricultural product circulation efficiency in the eastern region; water consumption and capital stock are the key factors in the central region; and energy prices, foreign trade dependence, and infrastructure are the most sensitive factors in the western region. This study provides empirical evidence for designing differentiated regional circulation policies and enhancing the resilience of the grain circulation system. Full article

Cross-domain data collaboration is a core requirement for the intelligent development of critical areas such as the Internet of Vehicles and intelligent transportation systems. In this scenario, vehicles and various sensors deployed roadside continuously generate massive amounts of time-series data, yet this data often forms “data silos” due to privacy regulations and a lack of trust between collaborating entities. Existing integrated schemes combining “Federated Learning + Blockchain” have achieved a certain degree of process traceability and automated payments, but risks of gradient-level privacy leakage persist, and inflexible and delayed incentive mechanisms result in low participation quality. To systematically address these bottlenecks, this paper proposes the Federated Learning with Assured Privacy and Reputation-Driven Incentives (FLARE) architecture, whose core innovation lies in the native integration of cryptographic security and mechanism design theory. It includes the Secure and Faithfully Executed Gradient aggregation (SafeGrad) protocol, which integrates partial homomorphic encryption and zero-knowledge proofs to provide verifiable privacy guarantees for gradient contributions while enabling efficient secure aggregation, defending against inversion attacks at the source; alongside this, it includes the Economy-on-Chain incentive (EconChain) mechanism, which designs an on-chain economic system based on blockchain, achieving precise measurement and sustainable incentivization of training process contributions through fine-grained instant micro-rewards and a dynamic reputation model. Experiments show that, compared to baseline schemes, FLARE can effectively enhance node participation enthusiasm and contribution quality without compromising model accuracy, providing a new paradigm with both strong security and high vitality for the trusted and efficient circulation of data. Full article

Regional production-consumption imbalances and deficient multimodal connectivity in grain circulation systems have rendered traditional segmented transport inefficient, loss-intensive, and costly, constraining overall supply chain performance. In China, the persistent north-to-south and west-to-east grain transfer patterns, driven by regional production–consumption imbalances, have imposed significant challenges on the grain circulation system, making multimodal transport optimization a critical priority for national food security. Multimodal transport, a critical logistics optimization strategy, integrates diverse transport modes and hub nodes to enable end-to-end coordination, thereby enhancing circulation efficiency and food security. This study systematically reviews the transport configurations and modal characteristics of grain multimodal transport, and employs bibliometric analysis with the VOSviewer tool to map publication trends and keyword co-occurrence networks. Subsequently, recent advances in transshipment hub location selection and route optimization in multimodal transport systems are examined. Finally, existing technical bottlenecks are summarized, and future research directions are outlined from the perspectives of intelligent logistics, green and low-carbon development, coordinated operations, and supply chain resilience. Full article

With the explosive growth of Internet of Things (IoT) devices, massive amounts of heterogeneous data are continuously generated. However, IoT data transactions and sharing face multiple challenges such as limited device resources, untrustworthy network environment, highly sensitive user privacy, and serious data silos. How to achieve fine-grained access control and privacy protection for massive devices while ensuring secure and reliable data circulation has become a key issue that needs to be urgently addressed in the current IoT field. To address the above challenges, this paper proposes a blockchain-based data transaction and privacy protection framework. First, the framework builds a multi-layer security architecture that integrates blockchain and IPFS and adapts to the “end–edge–cloud” collaborative characteristics of IoT. Secondly, a data sharing mechanism that takes into account both access control and interest balance is designed. On the one hand, the mechanism uses attribute-based encryption (ABE) technology to achieve dynamic and fine-grained access control for massive heterogeneous IoT devices; on the other hand, it introduces a game theory-driven dynamic pricing model to effectively balance the interests of both data supply and demand. Finally, in response to the needs of confidential analysis of IoT data, a secure computing scheme based on CKKS fully homomorphic encryption is proposed, which supports efficient statistical analysis of encrypted sensor data without leaking privacy. Security analysis and experimental results show that this scheme is secure under standard cryptographic assumptions and can effectively resist common attacks in the IoT environment. Prototype system testing verifies the functional completeness and performance feasibility of the scheme, providing a complete and effective technical solution to address the challenges of data integrity, verifiable transactions, and fine-grained access control, while mitigating the reliance on a trusted central authority in IoT data sharing. Full article

The rising number of disturbances caused by natural hazards, epidemics, and international conflicts seriously threatens global agriculture and food systems. In order to combat the increasing uncertainty, the Chinese government proposed a “dual circulation” strategy, which puts forward a new requirement of promoting self-sufficiency. Among various food categories, grain serves as a cornerstone for sustaining human life during public crises. Guangdong Province is one of the most economically developed and highly densely populated regions in China; therefore, it faces significant pressure to enhance food security. This study investigates the spatial and temporal patterns of the rate of grain self-sufficiency (RSSG) at the county levels in Guangdong Province from 2014 to 2023. The findings reveal the following: (1) rice remains the predominant grain crop, with its sown area and production consistently accounting for over 75%; (2) the RSSG is 28.14% on average, which is lower than the governmental goal of 30%; (3) the RSSG has significant regional disparities and distinct agglomeration patterns; and (4) scenario simulations indicate that grain yield improvement and grain loss reduction have the potential to promote the RSSG to 34.14%. Based on the research findings, this paper proposes the following policy recommendations: (1) prioritize farmland preservation and implement the “storing grain in the land” strategy to ensure food supply; (2) adopt advanced agricultural technologies under the “storing grain in the technology” strategy to improve grain yield; (3) reduce grain loss by strengthening disaster prevention, improving storage management, and enhancing storage efficiency; and (4) strengthen interdepartmental coordination. The integrated application of these strategies will help Guangdong Province enhance its grain self-sufficiency, ensure food security, and contribute to the achievement of national food security goals. Full article

When flowing through the blood stream, drug carriers such as nanoparticles encounter hundreds of plasma proteins, forming a protein layer on the nanoparticle surface, known as the “protein corona”. Since the protein corona influences the size, shape, and surface properties of nanoparticles, it can modulate their circulating lifetime, cytotoxicity, and targeting efficiency. Therefore, understanding the mechanism of protein corona formation at the atomic scale is crucial, which has become possible due to advances in computer power and simulation methodologies. This review covers the following topics: (1) the structure, dynamics, and composition of protein corona on nanoparticles; (2) the effects of protein concentration and ionic strength on protein corona formation; (3) the effects of particle size, morphology, and surface properties on corona formation; (4) the interactions among lipids, membranes, and nanoparticles with the protein corona. For each topic, mesoscale, coarse-grained, and all-atom molecular dynamics simulations since 2020 are discussed. These simulations not only successfully reproduce experimental observations but also provide physical insights into the protein corona formation. In particular, these simulation findings can be applied to manipulate the formation of a protein corona that can target specific cells, aiding in the rational design of nanomedicines for drug delivery applications. Full article

The construction of high-standard basic farmland is the cornerstone of high-quality agricultural development. In theory, the construction of high-standard farmland will affect changes in land management patterns but there is a limited amount of literature on the relationship between high-standard basic farmland construction and land transfer. Based on the panel data of 31 provinces in China, this study uses the continuous double difference method to analyze the impact of high-standard farmland construction policies on land transfer. The results show the following: the high-standard farmland construction policy implemented by the Chinese government can promote land transfer, which will significantly increase the proportion of land transfer area by 0.196 units. After robustness testing, it was found that this result is still reliable. Heterogeneity analysis shows that the construction of high-standard farmland has a stronger promoting effect on land transfer in major grain-producing areas, eastern and central regions, mountainous, and more economically structured planting areas. The mechanism test shows that the construction of high-standard farmland promotes land circulation through three paths: improving agricultural production conditions, improving factor utilization efficiency, and resisting disasters and increasing income. This study provides a valuable reference for improving the construction of high-standard farmland and promoting land circulation. Full article

Based on the factor endowment theory and the agriculture-induced technological innovation theory, this study examines the impact of high-standard farmland construction (HFC) on agricultural ecological efficiency (AEE) and sustainable agricultural development. Using empirical data from 30 provinces in China between 2005 and 2022, it explores how high-standard farmland construction techniques can enhance AEE, considering factor endowment preferences and geographical characteristics. Empirical research indicates that high-standard farmland significantly enhances AEE, particularly in the eastern region, the main grain-producing areas, and the regions with less geographical fluctuation. Additionally, agricultural innovations, capital accumulation, and land circulation reinforce the benefits of such construction, whereas labor mobility has a moderating effect. Quantile regression analyses show that the impact of HFC on AEE initially increases and then diminishes, potentially due to inadequate post-management and maintenance. Consequently, the study recommends that the government enhance policy support and supervision for high-standard farmland projects, integrate agricultural technology with capital accumulation, optimize human resource allocation, guide labor mobility, and reform land transfer systems to boost AEE and sustainability. Full article

As the primary grain crop in China, wheat holds a significant position in the country’s agricultural production, circulation, consumption, and various other aspects. However, the presence of imperfect grains has greatly impacted wheat quality and, subsequently, food security. In order to detect perfect wheat grains and six types of imperfect grains, a method for the fast and non-destructive identification of imperfect wheat grains using hyperspectral images was proposed. The main contents and results are as follows: (1) We collected wheat grain hyperspectral data. Seven types of wheat grain samples, each containing 300 grains, were prepared to construct a hyperspectral imaging system for imperfect wheat grains, and visible near-infrared hyperspectral data from 2100 wheat grains were collected. The Savitzky–Golay algorithm was used to analyze the hyperspectral images of wheat grains, selecting 261 dimensional effective hyperspectral datapoints within the range of 420.61–980.43 nm. (2) The Successive Projections Algorithm was used to reduce the dimensions of the 261 dimensional hyperspectral datapoints, selecting 33 dimensional hyperspectral datapoints. Principal Component Analysis was used to extract the optimal spectral wavelengths, specifically selecting hyperspectral images at 647.57 nm, 591.78 nm, and 568.36 nm to establish the dataset. (3) Particle Swarm Optimization was used to optimize the Support Vector Machines model, Convolutional Neural Network model, and MobileNet V2 model, which were established to recognize seven types of wheat grains. The comprehensive recognition rates were 93.71%, 95.14%, and 97.71%, respectively. The results indicate that a larger model with more parameters may not necessarily yield better performance. The research shows that the MobileNet V2 network model exhibits superior recognition efficiency, and the integration of hyperspectral image technology with the classification model can accurately identify imperfect wheat grains. Full article

This study aimed to determine the values of net energy (NE), digestible energy (DE) and metabolizable energy (ME) and digestibility coefficients of corn ethanol coproducts produced in Brazil and their effects on the nitrogen balance and blood parameters of pigs. Ten barrows were housed in metabolic study cages for total collection and fed a reference diet (RD) or 800 g/kg RD + 200 g/kg of a coproduct of corn ethanol. Distiller’s dried grains with solubles (DDGS), corn bran with solubles (CBS), distiller’s dried grains (DDG) and high-protein distiller’s dried grain (HPDDG) were evaluated. The experimental design was randomized blocks with three repetitions per period, totaling six repetitions per diet. Diets containing the HPDDG had greater DE and ME than those containing CBS and DDGS and greater DE than those containing the DDG (p < 0.05). HPDDG, DDG, CBS and DDGS showed 4498, 3419, 3029 and 3335 kcal/kg DE; 4366, 3305, 2934 and 3214 kcal/kg ME; and 2515, 1938, 1649 and 1725 kcal/kg NE, respectively. Pigs fed diets containing HPDDG and CBS showed greater nitrogen retention efficiency than pigs fed DDGS (p < 0.05). Pigs fed diets containing HPDDG had higher blood urea levels than pigs fed CBS and RD, while triglyceride levels in animals that received the CBS diet were greater than those in animals that received all other diets. The HPDDG had the highest energy levels and the best digestibility coefficients. The chemical composition of coproducts influences the nitrogen balance and circulating levels of urea and triglycerides in pigs. Full article

Against the backdrop of global warming, intensifying regional conflicts, deglobalization, and the spread of diseases, global food security is facing severe challenges. Studying the food security situation in China and the United States in depth can provide practical experience for formulating food security policies for countries around the world and promoting global food security governance. On the basis of a meticulous review of the evolving connotations of food security, this study adopts six dimensions—quantity security, quality security, circulation security, economic security, ecological resource security, and policy security—as breakthrough points to construct a framework consisting of food security evaluation indicator system comprising 29 specific indicators. The CRITIC–MEREC–MARCOS model is applied to evaluate the status of food security in China and the United States from 2000 to 2022, while the obstacle degree model (ODM) model is utilized to identify factors impeding food security between the two countries. The results indicate that the level of food security in China has shown slight fluctuations initially, followed by a steady upward trend. The gap with the United States is continuously narrowing. However, significant differences between China and the United States still exist in terms of economic security, ecological resource security, and policy security. Furthermore, due to the limited productivity of agricultural labor, scarcity of water and soil resources, and low efficiency in the use of fertilizers and pesticides, China’s food security is subject to economic and environmental constraints. The restrictions imposed by economic security and ecological resource security on China’s food security are showing an increasing trend year by year. For the United States, with the obstruction of grain exports and the increasing frequency of drought disasters, the impact of circulation security and ecological resource security on food security is becoming increasingly prominent. In the future, China and the United States should join hands to address challenges, actively promote international cooperation in food security, and drive sustainable development for humanity. Full article

Ecosystem carbon use efficiency (CUE), water use efficiency (WUE), and light use efficiency (LUE) are critical parameters for estimating CO₂ uptake, water circulation, and ecosystem balance. Research on the change trends of individual use efficiency has matured; however, studies on the spatiotemporal heterogeneity and driving mechanisms of divergence patterns for multi-use efficiencies capability are limited. Therefore, taking southwest China as an example, this study constructed a compound use efficiency (COM) through CUE, WUE, and LUE. Based on the spatiotemporal patterns and divergence characteristics analysis of water–carbon–light use efficiencies, the scale effects and driving mechanism of its divergence characteristics for COM at the optimal scale were clarified. The results revealed that the average value of CUE, LUE, WUE, and COM were 0.49, 0.7 gC m⁻² MJ⁻¹, 2.31 gC kg⁻¹ H₂O, and 0.87, respectively. Apart from CUE, the LUE, WUE, and COM parameters exhibited a fluctuating upward trend. Statistically, there was a high COM in karst and ecological restoration regions, reflecting the strong adaptability of karst vegetation and the effectiveness of ecological restoration; as the elevation rose, COM increased and then decreased, with the highest value at the elevation of 3000 m; the lowest COM was found in grassland, refuting the inference that it can be used as an optimal vegetation type for China’s Grain to Green program from the perspective of use efficiency. Sub-basin was the most optimal divergence scale, and although temperature and elevation were the dominant single force causing COM divergence, the couplings of precipitation and population density and elevation and population density had more controlling impacts than a single force. These findings enrich the understanding of ecosystem use efficiency and are beneficial for the improvement in ecological restoration strategies in karst landscapes. Full article

Timely and effective drying of agricultural products is crucial for ensuring the quality and yield of grains. Biomass drying enhances energy utilization and reduces energy pressure. To this end, a novel multi-channel circulating biomass hot air furnace was designed to provide precise control of the heat source for grain drying, thereby improving the efficiency and quality of the drying process. The combustion process utilizes a multi-channel combined air supply to ensure complete combustion of biomass pellet fuel. During the heat exchange process, heat exchange plates isolate hot and cold areas, discharging combustion exhaust, while ensuring a pure air output. Using rapeseed as the drying subject, a temperature controller based on adaptive fuzzy PID was designed, targeting the biomass hot air furnace’s heat exchange system for modeling and verifying the model with the step response method. Model simulations were conducted in Matlab’s Simulink module using both adaptive fuzzy PID and traditional PID controllers, for a given signal. The settling times for the conventional PID and fuzzy PID were 445 s and 364 s, respectively, with overshoots of 20.1% and 6.3%, showing that the fuzzy PID controller performed better in terms of control performance. The validation tests showed that both control methods could maintain the temperature within ±5 °C. Compared to traditional PID control, the adaptive fuzzy PID control achieved a precision of ±3 °C. At the target temperature of 90 °C, the error was reduced to 3.7%, with a stabilization time of 1014 s. The use of fuzzy PID control exhibited better dynamic response characteristics, meeting the drying needs of rapeseed. This study provides a theoretical basis for the structural design and control system design of biomass hot air furnaces. Full article

Scaling service operations is an effective way to promote modernization among small farmers. Exploring the factors influencing grain farmers’ choices in selecting services is essential to promote the strong development of the agricultural production service market and improve the efficiency of agricultural operations in China. Based on the 2019 data on corn farmers in the China Rural Revitalization Survey (CRRS) database, and using the Double-Hurdle Model, the factors influencing the service selection behavior of corn farmers are explored, and the research conclusions are as follows: (1) agricultural service prices have a negative impact on the demand for agricultural services, which varies from service to service; (2) labor prices do not influence the demand for any kind of service; (3) land circulation rents have a negative impact on the demand for agricultural services, which varies from service to service; (4) a high family net income can significantly prompt the adoption of agricultural services, which varies from service to service; (5) small-scale farmers are more sensitive to changes in service prices than large-scale farmers; (6) the four economic factors have no effect on the sowing service market. Based on the above conclusions, this paper puts forward suggestions such as improving the market price mechanism for agricultural production services, and increasing subsidies related to agricultural production services. Full article

The reliable circulation of automotive supply chain data is crucial for automotive manufacturers and related enterprises as it promotes efficient supply chain operations and enhances their competitiveness and sustainability. However, with the increasing prominence of privacy protection and information security issues, traditional data sharing solutions are no longer able to meet the requirements for highly reliable secure storage and flexible access control. In response to this demand, we propose a secure data storage and access control scheme for the supply chain ecosystem based on the enterprise-level blockchain platform Hyperledger Fabric. The design incorporates a dual-layer attribute-based auditable access control model for access control, with four smart contracts aimed at coordinating and implementing access policies. The experimental results demonstrate that the proposed approach exhibits significant advantages under large-scale data and multi-attribute conditions. It enables fine-grained, dynamic access control under ciphertext and maintains high throughput and security in simulated real-world operational scenarios. Full article