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您的检索式：作者名="Tianshi Luo"
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| 1 | Estimation of genetic parameters and breeding values in shrimp F enneropenaeus chinensis using the REML/BLUP procedure显示文摘An analysis of a selection experiment was used to assess the impact of various animal model structures on REML estimates of variance components.The analyses were carried out based on 162 d body mass (BM) of 1 287 animals from 21 paternal half-sib groups of Fenneropenaeus chinensis.Estimated breeding values (EBV) of BM of all individuals were estimated using eight statistical models (A,AB,ABC,ABDC,ABMFC,ABMDC,ABFDC and ABMFDC) and BLUP (best linear unbiased prediction).These models were designed involving factors such as sex,spawn date as fixed effects,maternal genetic effects,full-sib family effects as random effects,mean BM of families at tagging and age at recording (covariate).The results demonstrate the importance of correct interpretation of effects in the data set,particularly those that can influence resemblance between relatives.The data structure and the particular model that was applied markedly influenced the magnitude of variance component estimates.Models based on few effects obtained upward biased estimates of additive genetic variance.The accuracy of genetic parameters and breeding value estimated by ABFDC model was higher than other models.The results imply that additive genetic direct value,full-sib family effects,and covariance effects besides sex and spawn date as fixed effects were very important for estimating genetic parameters and breeding value of body mass.This model had a heritability estimate of 162 d BM of 0.44.The comparison of the efficiency of selection based on breeding values or phenotypic value revealed great difference:average breeding value of the best 24 families selected by the 162 d BM breeding value and phenotype were 0.577 g and 0.366 g,respectively,representing a 36.57% higher efficiency in the former.In conclusion,selection based on breeding value was more effective than selection based on phenotypic value.Our results indicate that effects influencing the magnitude of estimates should be taken into account when estimating heritability and breeding values for BM. | ZHANG Tianshi KONG Jie LUAN Sheng WANG Qingyin LUO Kun TIAN Yia | 2011 | Acta Oceanologica Sinica2011，30，1： | 12 |
| 2 | Frontiers of collaborative intelligence systems显示文摘The development of information technology has propelled technological reform in artificial intelligence(AI).To address the needs of diversified and complex applications,AI has been increasingly trending towards intelligent,collaborative,and systematized development across different levels and tasks.Research on intelligent,collaborative and systematized AI can be divided into three levels:micro,meso,and macro.Firstly,the micro-level collaboration is illustrated through the introduction of swarm intelligence collaborative methods related to individuals collaboration and decision variables collaboration.Secondly,the meso-level collaboration is discussed in terms of multi-task collaboration and multi-party collaboration.Thirdly,the macro-level collaboration is primarily in the context of intelligent collaborative systems,such as terrestrial-satellite collaboration,space-air-ground collaboration,space-air-ground-air collaboration,vehicle-road-cloud collaboration and end-edge-cloud collaboration.Finally,this paper provides prospects on the future development of relevant fields from the perspectives of the micro,meso,and macro levels. | Maoguo Gong Yajing He Hao Li Yue Wu Mingyang Zhang Shanfeng Wang Tianshi Luo | 2024 | Journal of Information and Intelligence2024，2，1： | 0 |
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