Close Neighbors Plus Relatives──An unforgettable Trip to the Philippines

At the invitation of the.Asian Center of the Philip-pine University,a five-mem-berCAFIU delegation visited the Philippines.The host high-ly regarded our visit,gave us a W arm and courteous recep-tion.Mr.Estrada.

Critical Behavior of the Energy Gap and Its Relation with the Berry Phase Close to the Excited State Quantum Phase Transition in the Lipkin Model

In our previous work [Phys. Rev. A 85 （2012） 044102], we studied the Berry phase of the ground state and exited states in the Lipkin model. In this work, using the Hellmann-Feynman theorem, we derive the relation between the energy gap and the Berry phase closed to the excited state quantum phase transition （ESQPT） in the Lipkin model. It is found that the energy gap is approximately linearly dependent on the Berry phase being closed to the ESQPT for large N. As a result, the critical behavior of the energy gap is similar to that of the Berry phase. In addition, we also perform a semiclassical qualitative analysis about the critical behavior of the energy gap.

C:N:P stoichiometry of Ericaceae species in shrubland biomes across Southern China:influences of climate,soil and species identity

Aims Carbon(C),nitrogen(N)and phosphorus(P)stoichiometry strongly affect functions and nutrient cycling within ecosystems.However,the related researches in shrubs were very limited.In this study,we aimed to inves-tigate leaf stoichiometry and its driving factors in shrubs,and whether stoichiometry significantly differs among closely related species.Methods We analyzed leaf C,N and P concentrations and their ratios in 32 species of Ericaceae from 161 sites across southern China.We examined the relationships of leaf stoichiometry with environmen-tal variables using linear regressions,and quantified the interactive and independent effects of climate,soil and species on foliar stoi-chiometry using general linear models(GLM).Important Findings The foliar C,N and P contents of Ericaceae were 484.66,14.44 and 1.06 mg g−1,respectively.Leaf C,N and P concentrations and their ratios in Ericaceae were significantly related with latitude and altitude,except the N:P insignificantly correlated with latitude.Climate(mean annual temperature and precipitation)and soil properties(soil C,N and P and bulk density)were significantly influenced element stoichiom-etry.The GLM analysis showed that soil exerted a greater direct effect on leaf stoichiometry than climate did,and climate affected leaf traits mainly via indirect ways.Further,soil properties had stronger influ-ences on leaf P than on leaf C and N.Among all independent factors examined,we found species accounted for the largest proportion of the variation in foliar stoichiometry.These results suggest that species can largely influence foliar stoichiometry,even at a lower taxonomic level.

Analyzing close relations between target artifacts for improving IR-based requirement traceability recovery

Requirement traceability is an important and costly task that creates trace links from requirements to different software artifacts.These trace links can help engineers reduce the time and complexity of software maintenance.The information retrieval(IR)technique has been widely used in requirement traceability.It uses the textual similarity between software artifacts to create links.However,if two artifacts do not share or share only a small number of words,the performance of the IR can be very poor.Some methods have been developed to enhance the IR by considering relations between target artifacts,but they have been limited to code rather than to other types of target artifacts.To overcome this limitation,we propose an automatic method that combines the IR method with the close relations between target artifacts.Specifically,we leverage close relations between target artifacts rather than just text matching from requirements to target artifacts.Moreover,the method is not limited to the type of target artifacts when considering the relations between target artifacts.We conduct experiments on five public datasets and take account of trace links between requirements and different types of software artifacts.Results show that under the same recall,the precisions on the five datasets improve by 40%,8%,20%,4%,and6%,respectively,compared with the baseline method.The precision on the five datasets improves by an average of15.6%,showing that our method outperforms the baseline method when working under the same conditions.