反应堆一回路中部分管道长期承受冷热流体的交替冲刷,局部可能出现的热分层现象使管道中的热应力进一步加大,由此产生的应力集中及疲劳问题可能危害反应堆的安全运行。基于热流固多物理场耦合方法结合ASME(American Society of Mechanic...反应堆一回路中部分管道长期承受冷热流体的交替冲刷,局部可能出现的热分层现象使管道中的热应力进一步加大,由此产生的应力集中及疲劳问题可能危害反应堆的安全运行。基于热流固多物理场耦合方法结合ASME(American Society of Mechanical Engineers)规范中适用于核一级承压设备的相关标准和分析流程,对某型号反应堆的管道系统开展了结构强度校核及疲劳分析,数值结果表明:当前工况参数及出现次数叠加作用下管道系统的应力分类结果满足规范要求,不会出现不可逆的结构损伤,且关键结构不连续位置的疲劳累积使用因子均小于1,未出现累积使用因子超限问题。展开更多
Spectrum map construction,which is crucial in cognitive radio(CR)system,visualizes the invisible space of the electromagnetic spectrum for spectrum-resource management and allocation.Traditional reconstruction methods...Spectrum map construction,which is crucial in cognitive radio(CR)system,visualizes the invisible space of the electromagnetic spectrum for spectrum-resource management and allocation.Traditional reconstruction methods are generally for twodimensional(2D)spectrum map and driven by abundant sampling data.In this paper,we propose a data-model-knowledge-driven reconstruction scheme to construct the three-dimensional(3D)spectrum map under multi-radiation source scenarios.We firstly design a maximum and minimum path loss difference(MMPLD)clustering algorithm to detect the number of radiation sources in a 3D space.Then,we develop a joint location-power estimation method based on the heuristic population evolutionary optimization algorithm.Considering the variation of electromagnetic environment,we self-learn the path loss(PL)model based on the sampling data.Finally,the 3D spectrum is reconstructed according to the self-learned PL model and the extracted knowledge of radiation sources.Simulations show that the proposed 3D spectrum map reconstruction scheme not only has splendid adaptability to the environment,but also achieves high spectrum construction accuracy even when the sampling rate is very low.展开更多
This paper presents an intelligent patrol and security robot integrating 2D LiDAR and RGB-D vision sensors to achieve semantic simultaneous localization and mapping(SLAM),real-time object recognition,and dynamic obsta...This paper presents an intelligent patrol and security robot integrating 2D LiDAR and RGB-D vision sensors to achieve semantic simultaneous localization and mapping(SLAM),real-time object recognition,and dynamic obstacle avoidance.The system employs the YOLOv7 deep-learning framework for semantic detection and SLAM for localization and mapping,fusing geometric and visual data to build a high-fidelity 2D semantic map.This map enables the robot to identify and project object information for improved situational awareness.Experimental results show that object recognition reached 95.4%mAP@0.5.Semantic completeness increased from 68.7%(single view)to 94.1%(multi-view)with an average position error of 3.1 cm.During navigation,the robot achieved 98.0%reliability,avoided moving obstacles in 90.0%of encounters,and replanned paths in 0.42 s on average.The integration of LiDAR-based SLAMwith deep-learning–driven semantic perception establishes a robust foundation for intelligent,adaptive,and safe robotic navigation in dynamic environments.展开更多
Most Convolutional Neural Network(CNN)interpretation techniques visualize only the dominant cues that the model relies on,but there is no guarantee that these represent all the evidence the model uses for classificati...Most Convolutional Neural Network(CNN)interpretation techniques visualize only the dominant cues that the model relies on,but there is no guarantee that these represent all the evidence the model uses for classification.This limitation becomes critical when hidden secondary cues—potentially more meaningful than the visualized ones—remain undiscovered.This study introduces CasCAM(Cascaded Class Activation Mapping)to address this fundamental limitation through counterfactual reasoning.By asking“if this dominant cue were absent,what other evidence would the model use?”,CasCAM progressively masks the most salient features and systematically uncovers the hierarchy of classification evidence hidden beneath them.Experimental results demonstrate that CasCAM effectively discovers the full spectrum of reasoning evidence and can be universally applied with nine existing interpretation methods.展开更多
Objective:To retrospectively evaluate the diagnostic efficacy of traditional MRI and T2 Mapping quantitative imaging technology for knee joint cartilage injury,clarify the differences in diagnostic value of the two im...Objective:To retrospectively evaluate the diagnostic efficacy of traditional MRI and T2 Mapping quantitative imaging technology for knee joint cartilage injury,clarify the differences in diagnostic value of the two imaging methods in different injury grades and different cartilage subregions,and provide evidence-based basis for the accurate diagnosis of clinical cartilage injury.Methods:Clinical and imaging data of 286 patients with knee joint lesions admitted to the Affiliated Hospital of Xiangtan Medicine and Health Vocational College from January 2020 to June 2023 were collected retrospectively.All patients underwent both traditional MRI sequences and T2 Mapping sequences.The knee joint cartilage was divided into 14 subregions.Two senior radiologists independently diagnosed the images of the two imaging technologies using a blind method and recorded the cartilage injury grades.The sensitivity,specificity,accuracy,positive predictive value,negative predictive value,and area under the receiver operating characteristic curve(AUC)of the two technologies for diagnosing cartilage injury were calculated and compared,and the differences in their diagnostic efficacy in different injury grades and different subregions were analyzed.Results:A total of 4004 cartilage subregions from 286 patients were included in the analysis,including 1836 injured subregions and 2168 normal subregions.The overall sensitivity(89.7%),accuracy(91.2%),and AUC(0.946)of T2 Mapping quantitative imaging for diagnosing cartilage injury were significantly higher than those of traditional MRI(76.3%,82.5%,and 0.852 respectively),with statistically significant differences(p<0.001);there was no significant difference in specificity between the two(93.5%vs 90.8%,p=0.062).Subgroup analysis showed that T2 Mapping had the most significant diagnostic advantage in early cartilage injury(Grade 1),with sensitivity(78.5%)33.2%higher than that of traditional MRI(45.3%)(p<0.001).Conclusion:The diagnostic efficacy of T2 Mapping quantitative imaging for knee joint cartilage injury is significantly superior to that of traditional MRI,especially in the detection of early cartilage injury and accurate evaluation of weight-bearing area injury.Data verify its clinical applicability and reliability.It can be used as an important supplementary method to traditional MRI,and is recommended for the early diagnosis,grading evaluation,and clinical follow-up of cartilage injury.展开更多
User identity linkage(UIL)across online social networks seeks to match accounts belonging to the same real-world individual.This cross-platformmapping enables accurate user modeling but also raises serious privacy ris...User identity linkage(UIL)across online social networks seeks to match accounts belonging to the same real-world individual.This cross-platformmapping enables accurate user modeling but also raises serious privacy risks.Over the past decade,the research community has developed a wide range of UIL methods,from structural embeddings tomultimodal fusion architectures.However,corresponding adversarial and defensive approaches remain fragmented and comparatively understudied.In this survey,we provide a unified overview of both mapping and antimappingmethods for UIL.We categorize representativemappingmodels by learning paradigmand datamodality,and systematically compare them with emerging countermeasures including adversarial injection,structural perturbation,and identity obfuscation.To bridge these two threads,we introduce amodality-oriented taxonomy and a formal gametheoretic framing that casts cross-network mapping as a contest between mappers and anti-mappers.This framing allows us to construct a cross-modality dependency matrix,which reveals structural information as themost contested signal,identifies node injection as the most robust defensive strategy,and points to multimodal integration as a promising direction.Our survey underscores the need for balanced,privacy-preserving identity inference and provides a foundation for future research on the adversarial dynamics of social identity mapping and defense.展开更多
Cotton is an important global cash crops that serve as the primary source of natural fiber for textiles.A thorough understand-ing of the long-term variations in cotton cultivation is vital for optimizing cotton cultiv...Cotton is an important global cash crops that serve as the primary source of natural fiber for textiles.A thorough understand-ing of the long-term variations in cotton cultivation is vital for optimizing cotton cultivation management and promoting the sustainable development of the cotton industry.Xinjiang is the primary cotton-producing region in China.However,long-term data of cotton cultiv-ation areas with high spatial resolution are unavailable for Xinjiang,China.Therefore,this study aimed to identify and map an accurate 30-m cotton cultivation area dataset in Xinjiang from 2000 to 2020 by applying a Random Forest(RF)-based method that integrates Landsat and Moderate Resolution Imaging Spectroradiometer(MODIS)images,and validated the applicability and accuracy of dataset at a large spatial scale.Then,this study analyzed the spatiotemporal variations and influencing factors of cotton cultivation in the study period.The results showed that a high classification accuracy was achieved(overall accuracy>85%,F1>0.80),strongly agreeing with county-level agricultural statistical yearbook data(R2>0.72).Significant spatiotemporal variation in the cotton cultivation areas was found in Xinjiang,with a total increase of 1131.26 kha from 2000 to 2020.Notably,cotton cultivation area in southern Xinjiang expan-ded substantially,with that in Aksu increasing from 20.10%in 2000 to 28.17%in 2020,representing an expansion of 374.29 kha.In northern Xinjiang,the cotton areas in the Tacheng region also exhibited significant increased by almost ten percentage points in the same period.In contrast,cotton cultivation in eastern Xinjiang declined,decreasing from 2.22%in 2000 to merely 0.24%in 2020.Standard deviation ellipse analysis revealed a‘northeast-southwest’spatial distribution,with the centroid consistently located in Aksu and shifting 102.96 km over the 20-yr period.Pearson correlation analysis indicated that socioeconomic factors had a stronger influence on cotton cultivation than climatic factors,with effective irrigation area(r=0.963,P<0.05)and total agricultural machinery power(r=0.823)showing significant positive correlations,whereas climatic variables exhibiting weak associations(r<0.200).These results provide valuable scientific data for informed agricultural management,sustainable development,and policymaking.展开更多
This study presents a reflective bibliometric review of 1457 peer-reviewed articles published in the Journal of Psychology in Africa(2008-2024,17 years),using a Meta-Editorial Mapping Framework(MEMF)analysis.The MEMF ...This study presents a reflective bibliometric review of 1457 peer-reviewed articles published in the Journal of Psychology in Africa(2008-2024,17 years),using a Meta-Editorial Mapping Framework(MEMF)analysis.The MEMF integrates citation metrics,keyword novelty ratios,TF-IDF weighting,and cluster-based topic modeling to trace long-term thematic trends and editorial evolution.Findings reveal sustained attention to foundational domains such as mental health,education,and identity,alongside a gradual integration of emergent themes including digital well-being,organizational behavior,and post-pandemic adaptation.Articles with moderate topical novelty(40%-60% new keywords)achieved the highest citation and usage metrics,suggesting that integrative innovation enhances scholarly impact.Clustering analyses indicate that the journal’s content forms overlapping conceptual domains rather than isolated silos.These insights contribute to editorial strategy,authorial positioning,and the future design of regional academic platforms.Moreover,the findings provide evidence supporting the use of the MEMF as a replicable tool for meta-editorial analysis across disciplinary and geographic boundaries.展开更多
English grain aphid （EGA） is a destructive insect pest of wheat. To identify the loci associated with EGA resistance and tolerance, 70 bread wheat accessions mainly from central Asia were evaluated for EGA resistanc...English grain aphid （EGA） is a destructive insect pest of wheat. To identify the loci associated with EGA resistance and tolerance, 70 bread wheat accessions mainly from central Asia were evaluated for EGA resistance and tolerance traits at two locations, and genotyped with 51 SSR markers. Totally, three accessions showed high or moderate levels resistance and 17 genotypes displayed highly or moderately tolerate to EGA. Genetic diversity of these lines was investigated also. After 97 SSR loci which evenly covered all wheat chromosomes were scanned for association, four SSR loci were significantly associated with EGA resistance and four with EGA tolerance. After association analysis was conducted with dynamic aphid densities, we found four loci Xgwm192b, Xgwm391, Xbarc98, and Xgwm613b were detected continuously at different growing stages of wheat. In addition, the loci of EGA resistance/tolerance and Russian wheat aphid resistance were compared. The results generated in this study would be helpful for utilization of the EGA resistance/tolerance germplasm, and for development of mapping populations in EGA resistance breeding programs.展开更多
An F2 population derived from the cross Zhong 9A/R68 was used to map the fertility-restoring （Rf） gene for ID-type cytoplasmic male sterility （CMS）. Two bulks （a fertile bulk and a sterile bulk） were constructed...An F2 population derived from the cross Zhong 9A/R68 was used to map the fertility-restoring （Rf） gene for ID-type cytoplasmic male sterility （CMS）. Two bulks （a fertile bulk and a sterile bulk） were constructed by pooling equal amount of ten highly fertile lines and ten highly sterile lines, respectively. Four hundred and thirteen pairs of simple sequence repeat （SSR） primers, which evenly distributed on 12 chromosomes of rice, were selected for analyzing polymorphisms between the parents and between the two bulks. The primer RM283 on chromosome 1 and the primers RM5756, RM258, RM6100 and RM171 on chromosome 10 were found to be polymorphic between the parents and between the two bulks. These five SSR markers were linked to fertility-restoring genes. A total of 82 excessive sterile lines were selected from Zhong 9A/R68 F2 population to estimate the genetic distance between five SSR markers and fertility-restoring genes respectively. The results indicated that one Rf gene was linked to RM283 located on chromosome 1 at a distance of 6.7 cM, and the other Rfgene was mapped to the long arm of chromosome 10 flanked by RM258 and RM6100 at the distances of 8.0 cM and 2.4 cM, respectively.展开更多
文摘反应堆一回路中部分管道长期承受冷热流体的交替冲刷,局部可能出现的热分层现象使管道中的热应力进一步加大,由此产生的应力集中及疲劳问题可能危害反应堆的安全运行。基于热流固多物理场耦合方法结合ASME(American Society of Mechanical Engineers)规范中适用于核一级承压设备的相关标准和分析流程,对某型号反应堆的管道系统开展了结构强度校核及疲劳分析,数值结果表明:当前工况参数及出现次数叠加作用下管道系统的应力分类结果满足规范要求,不会出现不可逆的结构损伤,且关键结构不连续位置的疲劳累积使用因子均小于1,未出现累积使用因子超限问题。
基金National Key Scientific Instrument and Equipment Development Project under Grant No.61827801the open research fund of State Key Laboratory of Integrated Services Networks,No.ISN22-11+1 种基金Natural Science Foundation of Jiangsu Province,No.BK20211182open research fund of National Mobile Communications Research Laboratory,Southeast University,No.2022D04。
文摘Spectrum map construction,which is crucial in cognitive radio(CR)system,visualizes the invisible space of the electromagnetic spectrum for spectrum-resource management and allocation.Traditional reconstruction methods are generally for twodimensional(2D)spectrum map and driven by abundant sampling data.In this paper,we propose a data-model-knowledge-driven reconstruction scheme to construct the three-dimensional(3D)spectrum map under multi-radiation source scenarios.We firstly design a maximum and minimum path loss difference(MMPLD)clustering algorithm to detect the number of radiation sources in a 3D space.Then,we develop a joint location-power estimation method based on the heuristic population evolutionary optimization algorithm.Considering the variation of electromagnetic environment,we self-learn the path loss(PL)model based on the sampling data.Finally,the 3D spectrum is reconstructed according to the self-learned PL model and the extracted knowledge of radiation sources.Simulations show that the proposed 3D spectrum map reconstruction scheme not only has splendid adaptability to the environment,but also achieves high spectrum construction accuracy even when the sampling rate is very low.
基金supported by the National Science and Technology Council of under Grant NSTC 114-2221-E-130-007.
文摘This paper presents an intelligent patrol and security robot integrating 2D LiDAR and RGB-D vision sensors to achieve semantic simultaneous localization and mapping(SLAM),real-time object recognition,and dynamic obstacle avoidance.The system employs the YOLOv7 deep-learning framework for semantic detection and SLAM for localization and mapping,fusing geometric and visual data to build a high-fidelity 2D semantic map.This map enables the robot to identify and project object information for improved situational awareness.Experimental results show that object recognition reached 95.4%mAP@0.5.Semantic completeness increased from 68.7%(single view)to 94.1%(multi-view)with an average position error of 3.1 cm.During navigation,the robot achieved 98.0%reliability,avoided moving obstacles in 90.0%of encounters,and replanned paths in 0.42 s on average.The integration of LiDAR-based SLAMwith deep-learning–driven semantic perception establishes a robust foundation for intelligent,adaptive,and safe robotic navigation in dynamic environments.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF),funded by the Ministry of Education(RS-2023-00249743).
文摘Most Convolutional Neural Network(CNN)interpretation techniques visualize only the dominant cues that the model relies on,but there is no guarantee that these represent all the evidence the model uses for classification.This limitation becomes critical when hidden secondary cues—potentially more meaningful than the visualized ones—remain undiscovered.This study introduces CasCAM(Cascaded Class Activation Mapping)to address this fundamental limitation through counterfactual reasoning.By asking“if this dominant cue were absent,what other evidence would the model use?”,CasCAM progressively masks the most salient features and systematically uncovers the hierarchy of classification evidence hidden beneath them.Experimental results demonstrate that CasCAM effectively discovers the full spectrum of reasoning evidence and can be universally applied with nine existing interpretation methods.
基金Application Research of MRI Physiological Quantitative Imaging Technology in the Diagnosis of Cartilage Injury(Project No.:RCYJ2021-04)。
文摘Objective:To retrospectively evaluate the diagnostic efficacy of traditional MRI and T2 Mapping quantitative imaging technology for knee joint cartilage injury,clarify the differences in diagnostic value of the two imaging methods in different injury grades and different cartilage subregions,and provide evidence-based basis for the accurate diagnosis of clinical cartilage injury.Methods:Clinical and imaging data of 286 patients with knee joint lesions admitted to the Affiliated Hospital of Xiangtan Medicine and Health Vocational College from January 2020 to June 2023 were collected retrospectively.All patients underwent both traditional MRI sequences and T2 Mapping sequences.The knee joint cartilage was divided into 14 subregions.Two senior radiologists independently diagnosed the images of the two imaging technologies using a blind method and recorded the cartilage injury grades.The sensitivity,specificity,accuracy,positive predictive value,negative predictive value,and area under the receiver operating characteristic curve(AUC)of the two technologies for diagnosing cartilage injury were calculated and compared,and the differences in their diagnostic efficacy in different injury grades and different subregions were analyzed.Results:A total of 4004 cartilage subregions from 286 patients were included in the analysis,including 1836 injured subregions and 2168 normal subregions.The overall sensitivity(89.7%),accuracy(91.2%),and AUC(0.946)of T2 Mapping quantitative imaging for diagnosing cartilage injury were significantly higher than those of traditional MRI(76.3%,82.5%,and 0.852 respectively),with statistically significant differences(p<0.001);there was no significant difference in specificity between the two(93.5%vs 90.8%,p=0.062).Subgroup analysis showed that T2 Mapping had the most significant diagnostic advantage in early cartilage injury(Grade 1),with sensitivity(78.5%)33.2%higher than that of traditional MRI(45.3%)(p<0.001).Conclusion:The diagnostic efficacy of T2 Mapping quantitative imaging for knee joint cartilage injury is significantly superior to that of traditional MRI,especially in the detection of early cartilage injury and accurate evaluation of weight-bearing area injury.Data verify its clinical applicability and reliability.It can be used as an important supplementary method to traditional MRI,and is recommended for the early diagnosis,grading evaluation,and clinical follow-up of cartilage injury.
基金funded by the National Key R&D Program of China under Grant(No.2022YFB3102901)National Natural Science Foundation of China(Nos.62072115,62102094)Shanghai Science and Technology Innovation Action Plan Project(No.22510713600).
文摘User identity linkage(UIL)across online social networks seeks to match accounts belonging to the same real-world individual.This cross-platformmapping enables accurate user modeling but also raises serious privacy risks.Over the past decade,the research community has developed a wide range of UIL methods,from structural embeddings tomultimodal fusion architectures.However,corresponding adversarial and defensive approaches remain fragmented and comparatively understudied.In this survey,we provide a unified overview of both mapping and antimappingmethods for UIL.We categorize representativemappingmodels by learning paradigmand datamodality,and systematically compare them with emerging countermeasures including adversarial injection,structural perturbation,and identity obfuscation.To bridge these two threads,we introduce amodality-oriented taxonomy and a formal gametheoretic framing that casts cross-network mapping as a contest between mappers and anti-mappers.This framing allows us to construct a cross-modality dependency matrix,which reveals structural information as themost contested signal,identifies node injection as the most robust defensive strategy,and points to multimodal integration as a promising direction.Our survey underscores the need for balanced,privacy-preserving identity inference and provides a foundation for future research on the adversarial dynamics of social identity mapping and defense.
基金Under the auspices of the National Natural Science Foundation of China(No.42101342,U2243205)the Third Comprehensive Scientific Expedition to Xinjiang(No.2021XJKK1403)。
文摘Cotton is an important global cash crops that serve as the primary source of natural fiber for textiles.A thorough understand-ing of the long-term variations in cotton cultivation is vital for optimizing cotton cultivation management and promoting the sustainable development of the cotton industry.Xinjiang is the primary cotton-producing region in China.However,long-term data of cotton cultiv-ation areas with high spatial resolution are unavailable for Xinjiang,China.Therefore,this study aimed to identify and map an accurate 30-m cotton cultivation area dataset in Xinjiang from 2000 to 2020 by applying a Random Forest(RF)-based method that integrates Landsat and Moderate Resolution Imaging Spectroradiometer(MODIS)images,and validated the applicability and accuracy of dataset at a large spatial scale.Then,this study analyzed the spatiotemporal variations and influencing factors of cotton cultivation in the study period.The results showed that a high classification accuracy was achieved(overall accuracy>85%,F1>0.80),strongly agreeing with county-level agricultural statistical yearbook data(R2>0.72).Significant spatiotemporal variation in the cotton cultivation areas was found in Xinjiang,with a total increase of 1131.26 kha from 2000 to 2020.Notably,cotton cultivation area in southern Xinjiang expan-ded substantially,with that in Aksu increasing from 20.10%in 2000 to 28.17%in 2020,representing an expansion of 374.29 kha.In northern Xinjiang,the cotton areas in the Tacheng region also exhibited significant increased by almost ten percentage points in the same period.In contrast,cotton cultivation in eastern Xinjiang declined,decreasing from 2.22%in 2000 to merely 0.24%in 2020.Standard deviation ellipse analysis revealed a‘northeast-southwest’spatial distribution,with the centroid consistently located in Aksu and shifting 102.96 km over the 20-yr period.Pearson correlation analysis indicated that socioeconomic factors had a stronger influence on cotton cultivation than climatic factors,with effective irrigation area(r=0.963,P<0.05)and total agricultural machinery power(r=0.823)showing significant positive correlations,whereas climatic variables exhibiting weak associations(r<0.200).These results provide valuable scientific data for informed agricultural management,sustainable development,and policymaking.
文摘This study presents a reflective bibliometric review of 1457 peer-reviewed articles published in the Journal of Psychology in Africa(2008-2024,17 years),using a Meta-Editorial Mapping Framework(MEMF)analysis.The MEMF integrates citation metrics,keyword novelty ratios,TF-IDF weighting,and cluster-based topic modeling to trace long-term thematic trends and editorial evolution.Findings reveal sustained attention to foundational domains such as mental health,education,and identity,alongside a gradual integration of emergent themes including digital well-being,organizational behavior,and post-pandemic adaptation.Articles with moderate topical novelty(40%-60% new keywords)achieved the highest citation and usage metrics,suggesting that integrative innovation enhances scholarly impact.Clustering analyses indicate that the journal’s content forms overlapping conceptual domains rather than isolated silos.These insights contribute to editorial strategy,authorial positioning,and the future design of regional academic platforms.Moreover,the findings provide evidence supporting the use of the MEMF as a replicable tool for meta-editorial analysis across disciplinary and geographic boundaries.
基金supported by the National Basic Research Program of China(2009CB118300)
文摘English grain aphid （EGA） is a destructive insect pest of wheat. To identify the loci associated with EGA resistance and tolerance, 70 bread wheat accessions mainly from central Asia were evaluated for EGA resistance and tolerance traits at two locations, and genotyped with 51 SSR markers. Totally, three accessions showed high or moderate levels resistance and 17 genotypes displayed highly or moderately tolerate to EGA. Genetic diversity of these lines was investigated also. After 97 SSR loci which evenly covered all wheat chromosomes were scanned for association, four SSR loci were significantly associated with EGA resistance and four with EGA tolerance. After association analysis was conducted with dynamic aphid densities, we found four loci Xgwm192b, Xgwm391, Xbarc98, and Xgwm613b were detected continuously at different growing stages of wheat. In addition, the loci of EGA resistance/tolerance and Russian wheat aphid resistance were compared. The results generated in this study would be helpful for utilization of the EGA resistance/tolerance germplasm, and for development of mapping populations in EGA resistance breeding programs.
基金the Zhejiang Province Key Program (Grant No. 2006C22G3010019)the High-tech Research and Development Program of China (Grant No. 2002AA2Z4321)the National Science and Technology Support Foundation and Basic Research Fund of CNRRI (Grant Nos. 1000005 and 1000006).The authors are grateful to Dr. Zhuang Jie-yun for his kindly help in molecular marker analysis and valuable comments on the manuscript.
文摘An F2 population derived from the cross Zhong 9A/R68 was used to map the fertility-restoring （Rf） gene for ID-type cytoplasmic male sterility （CMS）. Two bulks （a fertile bulk and a sterile bulk） were constructed by pooling equal amount of ten highly fertile lines and ten highly sterile lines, respectively. Four hundred and thirteen pairs of simple sequence repeat （SSR） primers, which evenly distributed on 12 chromosomes of rice, were selected for analyzing polymorphisms between the parents and between the two bulks. The primer RM283 on chromosome 1 and the primers RM5756, RM258, RM6100 and RM171 on chromosome 10 were found to be polymorphic between the parents and between the two bulks. These five SSR markers were linked to fertility-restoring genes. A total of 82 excessive sterile lines were selected from Zhong 9A/R68 F2 population to estimate the genetic distance between five SSR markers and fertility-restoring genes respectively. The results indicated that one Rf gene was linked to RM283 located on chromosome 1 at a distance of 6.7 cM, and the other Rfgene was mapped to the long arm of chromosome 10 flanked by RM258 and RM6100 at the distances of 8.0 cM and 2.4 cM, respectively.
