Cross-document relation extraction(RE),as an extension of information extraction,requires integrating information from multiple documents retrieved from open domains with a large number of irrelevant or confusing nois...Cross-document relation extraction(RE),as an extension of information extraction,requires integrating information from multiple documents retrieved from open domains with a large number of irrelevant or confusing noisy texts.Previous studies focus on the attention mechanism to construct the connection between different text features through semantic similarity.However,similarity-based methods cannot distinguish valid information from highly similar retrieved documents well.How to design an effective algorithm to implement aggregated reasoning in confusing information with similar features still remains an open issue.To address this problem,we design a novel local-toglobal causal reasoning(LGCR)network for cross-document RE,which enables efficient distinguishing,filtering and global reasoning on complex information from a causal perspective.Specifically,we propose a local causal estimation algorithm to estimate the causal effect,which is the first trial to use the causal reasoning independent of feature similarity to distinguish between confusing and valid information in cross-document RE.Furthermore,based on the causal effect,we propose a causality guided global reasoning algorithm to filter the confusing information and achieve global reasoning.Experimental results under the closed and the open settings of the large-scale dataset Cod RED demonstrate our LGCR network significantly outperforms the state-ofthe-art methods and validate the effectiveness of causal reasoning in confusing information processing.展开更多
Background: Motor competence and health-related fitness are important components for the development and maintenance of a healthy lifestyle in children. This study examined cross-cultural performances on motor compete...Background: Motor competence and health-related fitness are important components for the development and maintenance of a healthy lifestyle in children. This study examined cross-cultural performances on motor competence and health-related fitness between Portuguese and U.S.children.Methods: Portuguese(n = 508; 10.14 § 2.13 years, mean § SD) and U.S.(n = 710; 9.48 § 1.62 years) children performed tests of cardiorespiratory fitness(Progressive Aerobic Cardiovascular Endurance Run), upper body strength(handgrip), locomotor skill performance(standing long jump), and object projection skill performance(throwing and kicking). Portuguese and U.S. children were divided into 2 age groups(6à9 and 10à13 years) for data analysis purposes. A twoàfactor oneàway analysis of covariance(ANOVA) was conducted with the Progressive Aerobic Cardiovascular Endurance Run, handgrip, standing long jump scores, kicking, and throwing speed(km/h) as dependent variables.Results: Results indicated that Portuguese children, irrespective of sex, presented better performances in locomotor and cardiorespiratory performance(standing long jump and Progressive Aerobic Cardiovascular Endurance Run) than U.S. children in both age bands. U.S. children outperformed Portuguese children during throwing and handgrip tests. Kicking tests presented gender differences: Portuguese boys and U.S. girls outperformed their internationally matched counterparts.Conclusion: Cultural differences in physical education curricula and sports participation may impact differences in motor competence and fitness development in these countries.展开更多
An algorithm for GPS receiver performing to mitigate cross correlations between weak satellite signal and strong satellite signals is presented.By using the tracking result of strong signal,the cross-correlation and c...An algorithm for GPS receiver performing to mitigate cross correlations between weak satellite signal and strong satellite signals is presented.By using the tracking result of strong signal,the cross-correlation and cross correlation sequence between weak signals and strong signal can be computed,further modifying the local generate C/A code to drive the cross correlation to zero. The advantage of this method is that it does not require estimation of the strong signal amplitude and it partially independent of the data bit value.Simulation result shows it can eliminate the interference of 75%,and this method is at the cost of sensitivity loss of 0.28dB.展开更多
基金supported in part by the National Key Research and Development Program of China(2022ZD0116405)the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA27030300)the Key Research Program of the Chinese Academy of Sciences(ZDBS-SSW-JSC006)。
文摘Cross-document relation extraction(RE),as an extension of information extraction,requires integrating information from multiple documents retrieved from open domains with a large number of irrelevant or confusing noisy texts.Previous studies focus on the attention mechanism to construct the connection between different text features through semantic similarity.However,similarity-based methods cannot distinguish valid information from highly similar retrieved documents well.How to design an effective algorithm to implement aggregated reasoning in confusing information with similar features still remains an open issue.To address this problem,we design a novel local-toglobal causal reasoning(LGCR)network for cross-document RE,which enables efficient distinguishing,filtering and global reasoning on complex information from a causal perspective.Specifically,we propose a local causal estimation algorithm to estimate the causal effect,which is the first trial to use the causal reasoning independent of feature similarity to distinguish between confusing and valid information in cross-document RE.Furthermore,based on the causal effect,we propose a causality guided global reasoning algorithm to filter the confusing information and achieve global reasoning.Experimental results under the closed and the open settings of the large-scale dataset Cod RED demonstrate our LGCR network significantly outperforms the state-ofthe-art methods and validate the effectiveness of causal reasoning in confusing information processing.
基金supported by grants from the National Institutes of Health (1R15HD071514-01A1 and R21HD05562101A2)the National Association for Sport and Physical Education Research Grant Program
文摘Background: Motor competence and health-related fitness are important components for the development and maintenance of a healthy lifestyle in children. This study examined cross-cultural performances on motor competence and health-related fitness between Portuguese and U.S.children.Methods: Portuguese(n = 508; 10.14 § 2.13 years, mean § SD) and U.S.(n = 710; 9.48 § 1.62 years) children performed tests of cardiorespiratory fitness(Progressive Aerobic Cardiovascular Endurance Run), upper body strength(handgrip), locomotor skill performance(standing long jump), and object projection skill performance(throwing and kicking). Portuguese and U.S. children were divided into 2 age groups(6à9 and 10à13 years) for data analysis purposes. A twoàfactor oneàway analysis of covariance(ANOVA) was conducted with the Progressive Aerobic Cardiovascular Endurance Run, handgrip, standing long jump scores, kicking, and throwing speed(km/h) as dependent variables.Results: Results indicated that Portuguese children, irrespective of sex, presented better performances in locomotor and cardiorespiratory performance(standing long jump and Progressive Aerobic Cardiovascular Endurance Run) than U.S. children in both age bands. U.S. children outperformed Portuguese children during throwing and handgrip tests. Kicking tests presented gender differences: Portuguese boys and U.S. girls outperformed their internationally matched counterparts.Conclusion: Cultural differences in physical education curricula and sports participation may impact differences in motor competence and fitness development in these countries.
文摘An algorithm for GPS receiver performing to mitigate cross correlations between weak satellite signal and strong satellite signals is presented.By using the tracking result of strong signal,the cross-correlation and cross correlation sequence between weak signals and strong signal can be computed,further modifying the local generate C/A code to drive the cross correlation to zero. The advantage of this method is that it does not require estimation of the strong signal amplitude and it partially independent of the data bit value.Simulation result shows it can eliminate the interference of 75%,and this method is at the cost of sensitivity loss of 0.28dB.
基金The author would like to appreciate the support of General Financial Grant from the China Postdoctoral Science Foundation funded project （Grant No. 2016M600057） and Chinese Hanban, and also give sincere thanks to Pu CAO in Renmin University of China for the help of coding and analyzing.
