Subjects: Agriculture, Forestry,Livestock & Aquatic Products Science >> Other Disciplines of Agriculture, Forestry,Livestock & Aquatic Products Science submitted time 2023-05-15 Cooperative journals: 《智慧农业（中英文）》
Abstract： Accurate and efficient monitoring of animal information, timely analysis of animal physiological and physical health conditions, and automatic feeding and farming management combined with intelligent technologies are of great significance for large-scale livestock farming. Deep learning techniques, with automatic feature extraction and powerful image representation capabilities, solve many visual challenges, and are more suitable for application in monitoring animal information in complex livestock farming environments. In order to further analyze the research and application of artificial intelligence technology in intelligent animal farming, this paper presents the current state of research on deep learning techniques for tag detection recognition, body condition evaluation and weight estimation, and behavior recognition and quantitative analysis for cattle, sheep and pigs. Among them, target detection and recognition is conducive to the construction of electronic archives of individual animals, on which basis the body condition and weight information, behavior information and health status of animals can be related, which is also the trend of intelligent animal farming. At present, intelligent animal farming still faces many problems and challenges, such as the existence of multiple perspectives, multiscale, multiple scenarios and even small sample size of a certain behavior in data samples, which greatly increases the detection difficulty and the generalization of intelligent technology application. In addition, animal breeding and animal habits are a long-term process. How to accurately monitor the animal health information in real time and effectively feed it back to the producer is also a technical difficulty. According to the actual feeding and management needs of animal farming, the development of intelligent animal farming is prospected and put forward. First, enrich the samples and build a multi perspective dataset, and combine semi supervised or small sample learning methods to improve the generalization ability of in-depth learning models, so as to realize the perception and analysis of the animal's physical environment. Secondly, the unified cooperation and harmonious development of human, intelligent equipment and breeding animals will improve the breeding efficiency and management level as a whole. Third, the deep integration of big data, deep learning technology and animal farming will greatly promote the development of intelligent animal farming. Last, research on the interpretability and security of artificial intelligence technology represented by deep learning model in the breeding field. And other development suggestions to further promote intelligent animal farming. Aiming at the progress of research application of deep learning in livestock smart farming, it provides reference for the modernization and intelligent development of livestock farming.
Subjects: Other Disciplines >> Synthetic discipline submitted time 2023-03-28 Cooperative journals: 《中国科学院院刊》
Abstract： In 2015, the United Nations adopted 17 sustainable development goals (SDGs) to guide the economic, social, and environmental aspects of development. However, several factors have constrained the implementation of the SDGs, including uneven development, lack of data, and the interconnection and mutual restriction between the goals. In particular, the outbreak of COVID-19 pandemic in 2020 exacerbated the challenges faced by countries in implementing SDGs. This study focuses on the need to improve data services for SDGs in order to strengthen scientific research on monitoring and evaluating SDG indicators. We advocate for a scientific think tank that guides technological innovation for sustainable development and provides suggestions on education and training for developing countries that warrant serious consideration for rapid and meaningful sustained progress in the future. This paper highlights research on improving SDG monitoring and evaluation of SDGs carried out under the Big Earth Data Science Engineering Program of Chinese Academy of Sciences, the progress made in the development of the big data information platform for SDGs, and the monitoring and evaluation of SDG indicators. Further, the paper introduces the sustainable development scientific satellite due to launch in October 2021, a first of its kind in a series of satellites and the International Research Center of Big Data for Sustainable Development Goals (CBAS), which is being established to strengthen national and international efforts through improved scientific support driven by innovative big data solutions for SDGs.
Subjects: Mechanics >> Applied Mechanics submitted time 2023-03-20 Cooperative journals: 《应用力学学报》
Abstract： In micro-milling , due to the limitation of machining allowance , the feed per tooth of the millingcutter is very small or even smaller than the internal grain size of the material. When the cutting is carriedout between the grains , it will cause discontinuity in cutting , which will sharply increase the chatter duringthe milling process , cause the quality of the processed surface to decrease , and seriously affect the fatiguelife and performance of the micro-parts. Based on the Voronoi diagram , the paper establishes a polycrystal-line geometric model.'Through the method of simulation and experimental verification , the influence law ofthe cutting edge arc radius , cutting depth and grain size on the residual stress of the machined surface isstudied in detail, and a multiple linear regression model is established.Perform a significance test. The micro-milling experiment was carried out on the superalloy GH4169 with different grain sizes after heattreatment. The residual stress value of the machined surface in the feed direction of the workpiece was meas-ured by X-ray diffraction method , and the experimental value was compared with the predicted value to veri-fy the residual stress prediction model Accuracy. 'The results show that the error distribution is 2.18%o-7.35% ,not more than 10% , which can indicate that the prediction model of residual stress is more accurate.
Subjects: Medicine, Pharmacy >> Preventive Medicine and Hygienics submitted time 2023-12-05 Cooperative journals: 《中国全科医学》
Abstract： Background Against the backdrop of global aging，the number of patients with chronic diseases is increasing，and the multimorbidity is becoming more severe. Traditionally，cardiovascular diseases and type 2 diabetes are mostly considered diseases of the elderly. However，with changes in lifestyle patterns such as the pace of life and diet，many diseases are showing a trend of rejuvenation. Recent studies have also shown that individuals who develop diabetes at a young age have an increased relative risk of developing cardiovascular diseases and higher mortality rates compared to the general population. Objective To investigate the burden of cardiovascular diseases attributed to diabetes among Chinese adults from 1990 to 2019， so as to provide evidence for comorbidity prevention. Methods Based on the 2019 Global Burden of Disease（GBD） study data，indicators such as mortality rates，disability-adjusted life years（DALY） rates，and estimated annual percentage change （EAPC） were used to assess the burden of cardiovascular diseases in China（including ischemic heart disease，stroke，and peripheral arterial disease） attributed to diabetes. The analysis was stratified by age group（25-49 years，50-69 years，≥ 70 years） and gender，and the temporal trends in disease burden were finally analyzed. Results The number of cardiovascular disease deaths attributable to diabetes increased from 298 050 in 1990 to 700 340 in 2019 among people aged 25 years and older in China. The age-standardized mortality rate for CVD attributed to diabetes increased for males compared to 1990，while it decreased for females，with males consistently having higher rates than females. In 2019，the DALY for CVD attributed to diabetes was 13 585 850 person-years. The age-specific mortality rate and DALY rate increased with age. The downward trend in standardized DALY rate was more pronounced in females（EAPC=-0.32%，95%CI=-0.49% to -0.11%） than in males （EAPC=-0.01%，95%CI=-0.26% to 0.29%）. The mortality and DALY rates for ischemic heart disease and peripheral arterial disease attributed to diabetes increased in the three age groups from 1990 to 2019，while the mortality rates for stroke attributed to diabetes declined in all three age groups in 2019 compared to 1990. The percentage of standardized DALY rates attributable to diabetes for the 3 cardiovascular diseases in cardiovascular disease fluctuated from 1990 to 2019. However，the percentage of standardized DALY rates for all 3 cardiovascular diseases attributable to diabetes was higher in 2019 than in 1990. Conclusion From 1990 to 2019，there has been an overall increasing trend in the mortality and DALY rates of cardiovascular diseases attributed to diabetes among adults in China. Population is at greater risk for comorbidities of diabetes and CVD，emphasizing the need to focus on screening for CVD among individuals with diabetes or those at high risk of developing CVD. Emphasis should be placed on males，the elderly，and younger individuals with unhealthy lifestyle habits for early health interventions to reduce the burden of comorbidities.
Subjects: Library Science，Information Science >> Library Science submitted time 2023-07-09 Cooperative journals: 《中国科学院院刊》
Abstract： To promote economic development, social progress, and scientific and technological innovation, it is necessary to strengthen scientific cooperation and information sharing. Open data has emerged in response and become a seemingly inevitable development in the evolution of digital technology. Open data, however, must be supported by infrastructure composed of physical entities and virtual systems that meet the needs of data applications in many fields. Constructing and strengthening open data infrastructure should therefore be considered important objectives of information technology development. This study analyzes the elements of open data infrastructure and expounds its significant positive role in implementing open science. Based on an analysis of the current state and substantial development of China’s open data infrastructure, this study puts forward relevant measures and suggestions in view of the shortcomings and challenges China has faced with its open data infrastructure.
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