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| 1 | Flesh quality of hybrid grouper(Epinephelus fuscoguttatus♀×Epinephelus lanceolatus♂)fed with hydrolyzed porcine mucosasupplemented low fishmeal diet显示文摘Iso-nitrogenous and iso-lipidic diets containing 0%,3%,6%,9%,and 12%hydrolyzed porcine mucosa(namely,HPM0,HPM3,HPM6,HPM9,and HPM12)were prepared to evaluate their effects on the growth performance,muscle nutrition composition,texture property,and gene expression related to muscle growth of hybrid groupers(Epinephelus fuscoguttatus\Epinephelus lanceolatus_).Groupers were fed to apparent satiation at 08:00 and 16:00 every day for a total of 56 days.It was found that the weight gain percentage in the HPM0,HPM3,and HPM6 groups did not differ(P>0.05).The cooking loss and drip loss of the dorsal muscle in the HPM3 group were lower than those in the HPM6 and HPM9 groups(P<0.05).The hardness and chewiness of the dorsal muscle in the HPM3 group were higher than those in the HPM0,HPM9,and HPM12 groups(P<0.05).The gumminess in the HPM3 group was higher than that in the HPM9 and HPM12 groups(P<0.05).The total essential amino acid content of the dorsal muscle in the HPM12 group was higher than that in the HPM0 group(P<0.05).The contents of total n-3 polyunsaturated fatty acid and total n-3 highly unsaturated fatty acid,as well as the ratio of n-3/n-6 polyunsaturated fatty acid in the dorsal muscle was higher in the HPM0 group than in all other groups(P<0.05).The relative expressions of gene myogenic factor 5,myocyte enhancer factor 2c,myocyte enhancer factor 2a,myosin heavy chain,transforming growth factor-beta 1(TGF-b1),and follistatin(FST)were the highest in the dorsal muscle of the HPM3 group.The results indicated that the growth performance of hybrid grouper fed a diet with 6%HPM and 27%fish meal was as good as that of the HPM0 group.When fish ingested a diet containing 3%HPM,the expression of genes TGF-β1 and FST involved in muscle growth were upregulated,and then the muscle quality related to hardness and chewiness were improved.An appropriate amount of HPM could be better used in grouper feed. | Xuanyi Yang Xinyan Zhi Ziling Song Guanghui Wang Xumin Zhao Shuyan Chi Beiping Tan | 2022 | Animal Nutrition2022，，1： | 2 |
| 2 | Evolution process of rock mass engineering system using systems science显示文摘1.Introduction The rock mass engineering system(RMES)basically consists of rock mass engineering(RME),water system and surrounding ecological environments.etc.The RMES is characterized by nonlinearity,occurrence of chaos and self-organization(Tazaka,1998;Tsuda,1998;Kishida,2000).From construction to abandonment of RME,the RMES will experience four stages,i.e.initial phase,development phase,declining phase and failure phase.In | Laigui Wang Yanhui Xi Xiangfeng Liu Na Zhao Ziling Song | 2015 | Journal of Rock Mechanics and Geotechnical Engineering2015，7，6： | 1 |
| 3 | Technology trends in large-scale high-efficiency network computing显示文摘Network technology is the basis for large-scale high-efficiency network computing, such as supercomputing, cloud computing, big data processing, and artificial intelligence computing. The network technologies of network computing systems in different fields not only learn from each other but also have targeted design and optimization. Considering it comprehensively,three development trends, i.e., integration, differentiation, and optimization, are summarized in this paper for network technologies in different fields. Integration reflects that there are no clear boundaries for network technologies in different fields, differentiation reflects that there are some unique solutions in different application fields or innovative solutions under new application requirements,and optimization reflects that there are some optimizations for specific scenarios. This paper can help academic researchers consider what should be done in the future and industry personnel consider how to build efficient practical network systems. | Jinshu SU Baokang ZHAO Yi DAI Jijun CAO Ziling WEI Na ZHAO Congxi SONG Yujing LIU Yusheng XIA | 2022 | Frontiers of Information Technology & Electronic Engineering2022，23，12： | 0 |
| 4 | Study on the thermal decomposition characteristics of C_(4)F_(7)N-CO_(2)mixture as ecofriendly gas-insulating medium显示文摘The authors explored the thermal decomposition characteristics of perfluoroisobutyronitrile–carbon dioxide(C_(4)F_(7)N–CO_(2))gas mixture as eco-friendly dielectric medium.The main by-products and decomposition mechanism of C_(4)F_(7)N–CO_(2)gas mixture under different temperature and gas pressure conditions were revealed and analysed.It was found that the thermal decomposition of 6%C_(4)F_(7)N–94%CO_(2)gas mixture starts at about 350°C(0.15 MPa),producing C_(3)F_(6) and CO first.Some other characteristic by-products such as CF_(4),C_(2)F_(6),CF_(3)CN,COF_(2) and(CN)_(2) could also be detected at higher temperature.The yield of C_(3)F_(6),(CN)_(2) increased with the temperature(lower than 450℃)first and then decreased when it reached to 500℃.While the yield of CO,C3F8,COF_(2) and CF_(3)CN increased with temperature(350–550℃).The generation of CF_(4) and C_(2)F_(6) begins at temperatures higher than 500℃,which can be used as the feature component of severe overheating fault.The thermal decomposition amount and by-products yield of C_(4)F_(7)N–CO_(2)gas mixture slowed down with the increase of gas pressure,indicating that C_(4)F_(7)N–CO_(2)gas mixture is quite suitable used at high-pressure equipment,especially high-voltage devices such as gas insulated switchgear. | Yi Li Xiaoxing Zhang Ji Zhang Cheng Xie Xianjun Shao Ziling Wang Dachang Chen Song Xiao | 2020 | High Voltage2020，5，1： | 0 |
| 5 | Machine learning-based spectral and spatial analysis of hyper-and multi-spectral leaf images for Dutch elm disease detection and resistance screening显示文摘Diseases caused by invasive pathogens are an increasing threat to forest health,and early and accurate disease detection is essential for timely and precision forest management.The recent technological advancements in spectral imaging and artificial intelligence have opened up new possibilities for plant disease detection in both crops and trees.In this study,Dutch elm disease(DED;caused by Ophiostoma novo-ulmi,)and American elm(Ulmus americana)was used as example pathosystem to evaluate the accuracy of two in-house developed high-precision portable hyper-and multi-spectral leaf imagers combined with machine learning as new tools for forest disease detection.Hyper-and multi-spectral images were collected from leaves of American elm geno-types with varied disease susceptibilities after mock-inoculation and inoculation with O.novo-ulmi under green-house conditions.Both traditional machine learning and state-of-art deep learning models were built upon derived spectra and directly upon spectral image cubes.Deep learning models that incorporate both spectral and spatial features of high-resolution spectral leaf images have better performance than traditional machine learning models built upon spectral features alone in detecting DED.Edges and symptomatic spots on the leaves were highlighted in the deep learning model as important spatial features to distinguish leaves from inoculated and mock-inoculated trees.In addition,spectral and spatial feature patterns identified in the machine learning-based models were found relative to the DED susceptibility of elm genotypes.Though further studies are needed to assess applications in other pathosystems,hyper-and multi-spectral leaf imagers combined with machine learning show potential as new tools for disease phenotyping in trees. | Xing Wei Jinnuo Zhang Anna O.Conrad Charles E.Flower Cornelia C.Pinchot Nancy Hayes-Plazolles Ziling Chen Zhihang Song Songlin Fei Jian Jin | 2023 | Artificial Intelligence in Agriculture2023，，4： | 0 |
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