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您的检索式：作者名="Aqib Mahmood"
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| 1 | Quantifying the effects of short-term heat stress at booting stage on nonstructural carbohydrates remobilization in rice显示文摘Extreme heat stress events are becoming more frequent under anticipated climate change,which can have devastating impacts on rice growth and yield.To quantify the effects of short-term heat stress at booting stage on nonstructural carbohydrates(NSC)remobilization in rice,two varieties(Nanjing 41 and Wuyunjing 24)were subjected to 32/22/27°C(maximum/minimum/mean),36/26/31°C,40/30/35°C,and 44/34/39°C for 2,4 and 6 days in phytotrons at booting stage during 2014 and 2015.Yield and yield components,dry matter partitioning index(DMPI),NSC accumulation and translocation were measured and calculated.The results showed that the increase of high-temperature level and duration significantly reduced grain yield by suppressing spikelet number per panicle,seed-setting rate,and grain weight.Heat stress at booting decreased DMPI in panicles,increased DMPI in stems,but had no significant effect on photosynthetic rate.Stem NSC concentration increased whereas panicles NSC concentration,stem NSC translocation efficiency,and contribution of stem NSC to grain yield decreased.Severe heat stress even transformed the stem into a carbohydrate sink during grain filling.The heat-tolerant Wuyunjing 24 showed a higher NSC transport capacity under heat stress than the heat-sensitive Nanjing 41.Heat degree-days(HDD),which combines the effects of the intensity and duration of heat stress,used for quantifying the impacts of heat stress indicates the threshold HDD for the termination of NSC translocation is 9.82°C day.Grain yield was negatively correlated with stem NSC concentration and accumulation at maturity,and yield reduction was tightly related to NSC translocation reduction.The results suggest that heat stress at booting inhibits NSC translocation due to sink size reduction.Therefore,genotypes with higher NSC transport capacity under heat stress could be beneficial for rice yield formation. | Fengxian Zhen Junjie Zhou Aqib Mahmood Wei Wang Xini Chang Bing Liu Leilei Liu Weixing Cao Yan Zhu Liang Tang | 2020 | The Crop Journal2020，8，2： | 9 |
| 2 | Mining Software Repository for Cleaning Bugs Using Data Mining Technique显示文摘Despite advances in technological complexity and efforts,software repository maintenance requires reusing the data to reduce the effort and complexity.However,increasing ambiguity,irrelevance,and bugs while extracting similar data during software development generate a large amount of data from those data that reside in repositories.Thus,there is a need for a repository mining technique for relevant and bug-free data prediction.This paper proposes a fault prediction approach using a data-mining technique to find good predictors for high-quality software.To predict errors in mining data,the Apriori algorithm was used to discover association rules by fixing confidence at more than 40%and support at least 30%.The pruning strategy was adopted based on evaluation measures.Next,the rules were extracted from three projects of different domains;the extracted rules were then combined to obtain the most popular rules based on the evaluation measure values.To evaluate the proposed approach,we conducted an experimental study to compare the proposed rules with existing ones using four different industrial projects.The evaluation showed that the results of our proposal are promising.Practitioners and developers can utilize these rules for defect prediction during early software development. | Nasir Mahmood Yaser Hafeez Khalid Iqbal Shariq Hussain Muhammad Aqib Muhammad Jamal Oh-Young Song | 2021 | Computers, Materials & Continua2021，，10： | 0 |
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