As an innovative software application mode,Software as a service(SaaS) shows many attractive advantages.Migrating legacy system to SaaS can make outdated systems revived.In the process of migration,the existing valuab...As an innovative software application mode,Software as a service(SaaS) shows many attractive advantages.Migrating legacy system to SaaS can make outdated systems revived.In the process of migration,the existing valuable components need to be discovered and reused in order that the target system could be developed/integrated more efficiently.An innovative approach is proposed in this paper to extract the reusable components from legacy systems.Firstly,implementation models of legacy system are recovered through reverse engineering.Secondly,function models are derived by vertical clustering,and then logical components are discovered by horizontal clustering based on the function models.Finally,the reusable components with specific feature descriptions are extracted.Through experimental verification,the approach is considered to be efficient in reusable component discovery and to be helpful to migrating legacy system to SaaS.展开更多
The Hangzhou Bay（HZB） and Xiangshan Bay（XSB）, in northern Zhejiang Province and connect to the East China Sea（ECS） were considerably affected by the consequence of water quality degradation. In this study, we an...The Hangzhou Bay（HZB） and Xiangshan Bay（XSB）, in northern Zhejiang Province and connect to the East China Sea（ECS） were considerably affected by the consequence of water quality degradation. In this study, we analyzed physical and biogeochemical properties of water quality via multivariate statistical techniques. Hierarchical cluster analysis（HCA） grouped HZB and XSB into two subareas of different pollution sources based on similar physical and biogeochemical properties. Principal component analysis（PCA） identified three latent pollution sources in HZB and XSB respectively and emphasized the importance of terrestrial inputs, coastal industries as well as natural processes in determining the water quality of the two bays. Therefore, proper measurement for the protection of aquatic ecoenvironment in HZB and XSB were of great urgency.展开更多
Sorghum is an important food crop in Eritrea where it is widely grown in the mid and low lands,of semi-arid regions.Eritrea being the center of origin of sorghum,a large variability exist in its landraces being ...Sorghum is an important food crop in Eritrea where it is widely grown in the mid and low lands,of semi-arid regions.Eritrea being the center of origin of sorghum,a large variability exist in its landraces being grown by the farmers since generations.In order to improve the productivity of sorghum under moisture stress conditions,it is imperative to evaluate these landraces for drought tolerant characteristics and their use for further crop improvement programmes.Therefore,a field study was conducted in a randomized complete block design with three replications to estimate the extent of genetic variability of 20 sorghum genotypes for moisture stress tolerance using various morphological,phenological,yield and yield related parameters under rainfed conditions at Hagaz Research Station.Significant difference was observed for almost all the characters in the individual analysis of variance suggesting that these sorghum accessions were highly variable.Accessions EG 537,EG 1257,EG 849,EG 791,EG 783 and EG 813 showed promising results for post flowering drought tolerance,grain yield and stay green traits.Higher PCV and GCV were also obtained in parameters like plant height,leaf area,biomass,peduncle exertion,panicle length,and grain yield and panicle weight.The genotypes also exhibited varying degrees of heritability estimates.Characters such as plant height,panicle length,days to flowering and maturity showed higher heritability.Cluster analysis revealed that sorghum landraces were grouped on the basis of their morphological traits and geographical sites.77.3%of the total variation of sorghum landraces was contributed by the first four principal components analysis having Eigen value>1.Overall,the current study confirmed that EG 537,EG 849,EG 1257,EG 791,and EG 813 are drought tolerant sorghum landraces during post flowering stage.展开更多
Background Despite significant global effort to control and eradicate malaria,many cases and deaths are still reported yearly.These efforts are hindered by several factors,including the severe underestimation of cases...Background Despite significant global effort to control and eradicate malaria,many cases and deaths are still reported yearly.These efforts are hindered by several factors,including the severe underestimation of cases and deaths,especially in Africa.Methods We used a mathematical model,incorporating the underestimation of cases and seasonality in mosquito biting rate,to study the malaria dynamics in Cameroon.Using a Bayesian inference framework,we calibrated our model to the monthly reported malaria cases in ten regions of Cameroon from 2019 to 2021 to quantify the underestimation of cases and estimate other important epidemiological parameters.We performed Hierarchical Clustering on Principal Components analysis to understand regional disparities,looking at underestimation rates,population sizes,healthcare personnel,and healthcare facilities per 1000 people.Results We found varying levels of case underestimation across regions,with the East region having the lowest(14%)and the Northwest having the highest(70%).The mosquito biting rate peaks once every year in most regions,except in the Northwest where it peaks every 6.02 months and in Littoral every 15 months.We estimated a median mosquito biting rate of over 5 bites/day for most regions with Littoral having the highest(9.86 bites/day).Two regions have rates below five:Adamawa(4.78 bites/day)and East(4.64 bites/day).Conclusions The low case estimation underscores the pressing requirement to bolster reporting and surveillance systems.Regions in Cameroon display a range of unique features contributing to the differing levels of underestimation.These distinctions should be considered when evaluating the efficacy of community-based interventions.展开更多
基金supported by National Natural Science Foundation of China(No.61262082,No.61462066)Key Project of Chinese Ministry of Education(No.212025)+1 种基金Inner Mongolia Science Foundation for Distinguished Young Scholars(No.2012JQ03)Inner Mongolia Natural Science Foundation of Inner Mongolia(No.2012MS0922)
文摘As an innovative software application mode,Software as a service(SaaS) shows many attractive advantages.Migrating legacy system to SaaS can make outdated systems revived.In the process of migration,the existing valuable components need to be discovered and reused in order that the target system could be developed/integrated more efficiently.An innovative approach is proposed in this paper to extract the reusable components from legacy systems.Firstly,implementation models of legacy system are recovered through reverse engineering.Secondly,function models are derived by vertical clustering,and then logical components are discovered by horizontal clustering based on the function models.Finally,the reusable components with specific feature descriptions are extracted.Through experimental verification,the approach is considered to be efficient in reusable component discovery and to be helpful to migrating legacy system to SaaS.
基金The National Marine Ecoenvironment Assessment Program of State Oceanic Administration
文摘The Hangzhou Bay（HZB） and Xiangshan Bay（XSB）, in northern Zhejiang Province and connect to the East China Sea（ECS） were considerably affected by the consequence of water quality degradation. In this study, we analyzed physical and biogeochemical properties of water quality via multivariate statistical techniques. Hierarchical cluster analysis（HCA） grouped HZB and XSB into two subareas of different pollution sources based on similar physical and biogeochemical properties. Principal component analysis（PCA） identified three latent pollution sources in HZB and XSB respectively and emphasized the importance of terrestrial inputs, coastal industries as well as natural processes in determining the water quality of the two bays. Therefore, proper measurement for the protection of aquatic ecoenvironment in HZB and XSB were of great urgency.
文摘Sorghum is an important food crop in Eritrea where it is widely grown in the mid and low lands,of semi-arid regions.Eritrea being the center of origin of sorghum,a large variability exist in its landraces being grown by the farmers since generations.In order to improve the productivity of sorghum under moisture stress conditions,it is imperative to evaluate these landraces for drought tolerant characteristics and their use for further crop improvement programmes.Therefore,a field study was conducted in a randomized complete block design with three replications to estimate the extent of genetic variability of 20 sorghum genotypes for moisture stress tolerance using various morphological,phenological,yield and yield related parameters under rainfed conditions at Hagaz Research Station.Significant difference was observed for almost all the characters in the individual analysis of variance suggesting that these sorghum accessions were highly variable.Accessions EG 537,EG 1257,EG 849,EG 791,EG 783 and EG 813 showed promising results for post flowering drought tolerance,grain yield and stay green traits.Higher PCV and GCV were also obtained in parameters like plant height,leaf area,biomass,peduncle exertion,panicle length,and grain yield and panicle weight.The genotypes also exhibited varying degrees of heritability estimates.Characters such as plant height,panicle length,days to flowering and maturity showed higher heritability.Cluster analysis revealed that sorghum landraces were grouped on the basis of their morphological traits and geographical sites.77.3%of the total variation of sorghum landraces was contributed by the first four principal components analysis having Eigen value>1.Overall,the current study confirmed that EG 537,EG 849,EG 1257,EG 791,and EG 813 are drought tolerant sorghum landraces during post flowering stage.
基金support from New Frontier in Research Fund-Exploratory(Grant No.NFRFE-2021-00879)NSERC Discovery Grant(Grant No.RGPIN-2022-04559)+1 种基金Portions of this work were performed at the Los Alamos National Laboratory under the auspices of the US Department of Energy contract 89233218CNA000001supported by NIH grant R01-OD011095.
文摘Background Despite significant global effort to control and eradicate malaria,many cases and deaths are still reported yearly.These efforts are hindered by several factors,including the severe underestimation of cases and deaths,especially in Africa.Methods We used a mathematical model,incorporating the underestimation of cases and seasonality in mosquito biting rate,to study the malaria dynamics in Cameroon.Using a Bayesian inference framework,we calibrated our model to the monthly reported malaria cases in ten regions of Cameroon from 2019 to 2021 to quantify the underestimation of cases and estimate other important epidemiological parameters.We performed Hierarchical Clustering on Principal Components analysis to understand regional disparities,looking at underestimation rates,population sizes,healthcare personnel,and healthcare facilities per 1000 people.Results We found varying levels of case underestimation across regions,with the East region having the lowest(14%)and the Northwest having the highest(70%).The mosquito biting rate peaks once every year in most regions,except in the Northwest where it peaks every 6.02 months and in Littoral every 15 months.We estimated a median mosquito biting rate of over 5 bites/day for most regions with Littoral having the highest(9.86 bites/day).Two regions have rates below five:Adamawa(4.78 bites/day)and East(4.64 bites/day).Conclusions The low case estimation underscores the pressing requirement to bolster reporting and surveillance systems.Regions in Cameroon display a range of unique features contributing to the differing levels of underestimation.These distinctions should be considered when evaluating the efficacy of community-based interventions.
