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Objective: To optimize the operating parameters of wheat milling in roller mill I skin mill to reduce the energy consumption of milling. Methods: Using EDEM discrete element simulation software, Box-Behnken test was designed for key milling factors such as roll pitch, feeding amount, rotational speed and rotational speed ratio to investigate the relationship between operating parameters and milling power. Results: The significance rankings of the effects on the toothed roll crushing power were, in order, speed ratio, roll pitch, feed volume, speed ratio quadratic term, roll pitch quadratic term, interaction of roll pitch and speed ratio, interaction of feed volume and speed ratio, and interaction of roll pitch and feed volume. According to the different requirements of the I-skin mill, the optimal parameter combinations were obtained: the finer powder output with a rolling pitch of 0.67 mm, a feeding amount of 803.60 kg/（cm·d）, a fast roller speed of 537.68 r/min, and a rotational speed ratio of 2.64, and the coarser powder output with the optimal low-power consumption of 0.79 mm, a feeding amount of 803.83 kg/（cm·d）, a fast roller speed of 576.08 r/min, and a rotational speed ratio of 2.23. Conclusion: The error between the simulation results and the measured results is within a reasonable range, and the established discrete element milling model can be used for power prediction in wheat milling.

Objective: To achieve surface wear life prediction of abrasive blast rollers of grinding machines. Methods: The wear images of the grinding roller surface were acquired by the built image acquisition system, and the texture parameters such as second order moments, entropy value, contrast and correlation in the wear cycle of the grinding roller were obtained based on the grey scale co-generation matrix algorithm, and the obtained texture feature parameters were input into the constructed PSO-based LS-SVM algorithm model to finally predict the wear life of the blast roller. Results: The particle swarm algorithm could optimize the penalty factor and kernel parameters of LS-SVM well, and the PSO-LS-SVM algorithm was far superior to the LS-SVM algorithm model. The wear state of the blast roller surface of the mill could be accurately identified using the PSO-LS-SVM algorithm. Conclusion: The system can accurately predict the service life of the blast rollers.

As cropland and water resources are most valuable, the rational development and utilization of agricultural water and land resources are crucial for national food, ecological, and resource security. Therefore, obtaining timely and accurate information about the quantity and utilization of these resources is vital for national stability and socio-economic development. Here, we summarize the status quo and problems of the monitoring and information services of agricultural water and land resources in China, and expound on the framework of a monitoring and information service system. Additionally, we propose the strategic goals, namely, realizing automatic, intelligent, and unmanned monitoring of agricultural resources and environment and marketing the monitoring information services. These goals can be achieved by increasing the efficiency and outcomes of water and land use and optimizing the spatial allocation of agricultural land and water resources. Moreover, we analyze the technological routes for agricultural water and land resource monitoring in the context of the deep integration of information technology and agriculture, and propose specific projects from the aspects of infrastructure construction, core technology development and integration, and information services. Furthermore, we propose the following policy suggestions: (1) strengthening the top-level design, (2) enhancing scientific and technological innovation, (2) building a sharing platform for agricultural resource monitoring, (4) deepening the interaction of government, industry, universities, research institutes, and users of agricultural resources, and (5) promoting high-level talent training. Our study is expected to provide theoretical references for the development of the agricultural water and land resource monitoring in China.

Abstract Background As a minimally invasive tool for caries prevention tool, the pulsed erbium:yttrium-aluminum-garnet (Er:YAG) laser is being used in a large number of studies. Microorganisms are extremely vital in the occurrence and development of dental caries. However, the impact of Er:YAG laser irradiation combined with fluoride on the dynamic microbial changes that occur in dental plaques is still uncertain. In this study, we examined the effect of an Er:YAG laser combined with fluorine on supragingival microbial composition and diversity in children with multiple caries. Methods In this study, dental plaque samples (n = 48) were collected from 12 children with over 8 filled teeth. Supragingival plaques from left mandibular molars before (CB) and after fluoride treatment (CA) and right mandibular molars before (EB) and after fluoride+Er:YAG laser treatment (EA) were collected from each patient. In CB and EB groups, the samples were collected just before the treatments. In CA and EA groups, the samples were collected 1 month after treatments. Then, all specimens were subjected to 16S rRNA high-throughput sequencing to investigate the changes in microbial composition and diversity in mandibular molar supragingival plaques before and after fluoride or fluoride+Er:YAG laser treatment. Results The dental plaque microbial diversity was higher in the EA group than in the EB group (baseline levels), and the microbial composition changed in EA group compared with EB group (P

Abstract Hydraulic fracturing experiments were conducted to study the change of initial fracture pressure and roof stress under repeated hydraulic fracturing in coal mines and to investigate the actual penetration enhancement effect on coal seams. The results show that as the fracturing is repeated, a lower initiation pressure is required. The roof stress changes consistently with water injection pressure. First, the stress in the area around the water injection hole gradually increases, and then stress transfers to the surroundings. With the re‐implementation of fracturing, the area of increased stress expands, and the scope of influence of hydraulic fracturing also becomes larger. When fracturing in a coal mine, for the same total fracturing time, the total water injection volume of repeated fracturing is 35% higher than that of single fracturing, and the affected area is increased by 31%. The concentration of repeated hydraulic fracturing is about 36% higher than that of a single hydraulic fracturing, and the pure flow of gas drainage is increased by about 1.3 times. The results of this study can guide the efficient implementation of hydraulic fracturing underground in coal mines, so as to achieve a larger impact range of coal seam hydraulic fracturing and better gas drainage effects.

Agricultural big data and information infrastructure are important foundations for modern agriculture, prerequisites for smart agriculture, and new elements of agricultural growth in the new era. In this article, we analyze the development status and existing problems of China’s agricultural big data and information infrastructure considering the strategic needs and challenges of smart agriculture development; summarize the relevant policies, action plans, and experiences in China and abroad; propose the strategic objectives of developing agricultural big data and information infrastructure in 2025, 2035, and 2050; and devise the future development technology roadmap. In the future, big data development should be promoted in the entire agricultural industry chain and the construction of the agricultural big data system needs to be standardized by building an integrated data sharing mechanism. Breakthroughs achieved in key common technologies can expand the application of agricultural big data. Agricultural big data industry bases are required for creating application clusters of agricultural big data. An urban–rural integrated information infrastructure needs to be built by coordinating urban and rural resources, and an agricultural cyberspace that features interconnection of everything, human–computer interaction, and sky–space–earth–sea integration is expected to be created. From the policy aspect, China should strengthen the overall planning to improve its rural network infrastructure and the digital transformation of traditional infrastructure, along with promoting the basic research and development of chips, model components, and basic information systems. Moreover, it should focus on core technologies such as agricultural big data acquisition, analysis, and service; strengthen the collaborative innovation of systems and mechanisms to achieve standardization and integrated sharing of agricultural data; and build a high-level talent team to provide basic support for developing smart agriculture in China.

Under the pressure of economy development and climate change, rice production and distribution in the Yangtze River basin have undergone great changes, which may pose a great threat to the ecological environment and food security. Based on land use remote sensing-monitoring data from1990 to 2015, the GIS spatial analysis method was used to explore the spatial pattern variation characteristics of paddy fields in the Yangtze River economic belt. Meanwhile, Ecosystem services value (ESV) was calculated by using the equivalent factor method corrected by region and time factor to measure the comprehensive impact of paddy field change. The results showed that, to begin with, paddy fields number of the Yangtze River economic belt continued to decrease, with a total decrease of 17 390km2, and the decrease rate presented a trend of growth with significant regional differences. The difference between the reduction rate of paddy fields in the middle upper and the lower reaches of the Yangtze River was about 9.56%. Among them, in the lower reaches of the Yangtze River, the proportion of paddy fields decreased, while in the middle and upper reaches which was just the opposite. Then, paddy fields mainly flowed to construction land and water, resulting from economic construction and aquaculture development. Paddy fields chiefly came from water, dry land and wetland, etc. Furthermore, paddy fields in the Yangtze River Delta, the middle reaches of the Yangtze River and the Chengdu-Chongqing urban agglomerations changed the most dramatically. The expansion of construction land to paddy fields was widespread, and paddy fields flooded by water primarily distributed in the two lake plains. In addition, the conversion of paddy fields and other ecosystems had a positive impact on ESV, in which the paddy-water diversion type contributed the most. Its scale determined the net increase of ESV in different periods. Value loss lead by conversion from water to paddy fields was the largest, and construction land invading paddy fields was the second. The conversions in different cities were different, so the difference in ESV increases and decreases. In addition, the tradeoffs within ecosystem services were mainly between hydrological regulation, water supply and food production, gas regulation, which were directly related to the increase of water resources and the loss of paddy fields. The research results are helpful to reveal the spatio-temporal changes process of paddy fields in the Yangtze River basin and its impact on ecological functions, and provide theoretical support for regional land use planning, agricultural policy and ecological sustainable development.

The human society is entering the era of big data and data is becoming one of the key production elements. It is thus critical to develop the China's data-driving digital agriculture system, which would greatly promote the construction of digital China, stimulate the agriculture high-quality development and improve the agricultural competitiveness at the global market. To achieve this goal, strong integration of information is needed from multi-sources, multi-sensors, and multi-scales. This research, from the perspective of agricultural information science, describes the new framework of satellite, aerial, and ground integrated (SAGI) digital agriculture system for comprehensive agricultural monitoring, modeling, and management. The SAGI system differs from traditional digital agriculture systems and includes 5 important functionalities which are resource survey, production controlling, disaster monitoring, market early-warning and decision supporting. To make the system running in operation, it is necessary to first build an observation system, which integrates the satellite, aerial, and ground in-situ observation systems to capture more sophisticated, accurate and reliable data at different scales. The system is extremely needed for China, a large country with a great geographic difference, diverse agricultural cultivation and multiple agricultural traditions. This observing system helps to form the agricultural big data for subsequent data analysis and data mining. Secondly, using the big data collected, 4 key digitalization and monitoring tasks targeting at resource property right, production process, natural disaster and market status should be implemented so as to transform the data to knowledge. In this process, some diagnosis algorithms and models are developed to understand the growth and health of crops and animals, as well as their interaction with the agro-environment. With the above support, a management system covering the full range of agricultural production, processing, selling, management and services should be established to provide the rapid and reliable information support to decision-making as well to the local farming management, thereby guaranteeing agricultural sustainability and national food security. Thirdly, some key fields for future science and technology innovation to support the applications of the SAGI system should to be enhanced such as the standardization designing, innovation in technologies and instruments, system integration and platform development. Finally, considering the complicated and integrative characteristics of this SAG system, this research also proposed some recommendations such as holistic planning, science-technology innovation, resource sharing, multi-stakeholders participation, and expansion of application fields, so as to drive this idea to the reality.

China's coal production has formed a large number of goaf, which contains a large amount of coal and coalbed methane resources. If these resources are stored in the goaf, it will not only cause a waste of resources, but also cause environmental pollution if the coalbed methane in the goaf leaks into the atmosphere. Therefore, the utilization of goaf resources is imminent. In order to achieve the purpose of efficient extraction, it is necessary to evaluate the amount of goaf resources. As an important part of goaf resources, the desorption law of abandoned coal is affected by many factors, among which water is an important factor affecting the desorption law of abandoned coal. At present, there are few studies on the desorption law of block coal under different watered-out volumes.

In the study of mineral resources evaluation model, the problem that the number of positive samples must be specified in the TSVM in the unlabeled samples.Then this article applied the improved algorithm to the evaluation of mineral resources, and the algorithm is TSVM based on BP neural network and BP-TSVM for short.The SVM is applied to studying the discernment and classification of labeling samples.We will annotate the plus or minus of unlabeled data within the boundary of already classified by utilizing BP neural network.The labeling samples as learned by SVM in the next iteration.The new algorithm will avoid decreased classified ability.TSVM can have more accurate estimates of number of plus of labeled data.Also, the number of training samples can reduce training times.The experimental result proves that compared with conventional SVM, TSVM and BP neural network the BP-TSVM is more accurate in evaluation of mineral resources.

Along with the development of the spectral imaging technology, the precision of the hyper-spectral imagery becomes very high, and the size of the hyper-spectral imagery becomes very large. In order to solve the problem of the transmission and the storage, it is necessary to research the compression algorithm. The traditional prediction algorithm is adopted in the serial processing mode, and the processing time is long. In this paper, we improve the efficiency of the parallel prediction compression algorithm, to meet the needs of the rapid compression. We select bands along the direction of spectral or the direction of space, so that the hyper-spectral imagery can be divided into sub images. We number the sub images, then send them to different processing units. Each unit does compression tasks at the same time. This paper also compares the relationship between the processing unit number and the compression time. The experiment shows that, the parallel predictive compression algorithm can improve the efficiency of compression effectively.