Characteristic equation solution strategy for deriving fundamental analytical solutions of 3D isotropic elasticity

A simple characteristic equation solution strategy for deriving the fun- damental analytical solutions of 3D isotropic elasticity is proposed. By calculating the determinant of the differential operator matrix obtained from the governing equations of 3D elasticity, the characteristic equation which the characteristic general solution vectors must satisfy is established. Then, by substitution of the characteristic general solution vectors, which satisfy various reduced characteristic equations, into various reduced ad- joint matrices of the differential operator matrix, the corresponding fundamental analyt- ical solutions for isotropic 3D elasticity, including Boussinesq-Galerkin （B-G） solutions, modified Papkovich-Neuber solutions proposed by Min-zhong WANG （P-N-W）, and quasi HU Hai-chang solutions, can be obtained. Furthermore, the independence characters of various fundamental solutions in polynomial form are also discussed in detail. These works provide a basis for constructing complete and independent analytical trial func- tions used in numerical methods.

Molecular uniting set identified characteristic(MUSIC): a promising strategy for purely organic RTP luminogens

The room temperature phosphorescences（RTP）are of growing interest owing to their promising applications in material science and bioimaging.To date,the lumiogens showing persistent RTP effect mainly contain the noble metals which have the shortcomings such as high cost,potential toxicity.The exploration of metal free luminogens,i.e.,purely organic RTP luminogens,is thus of great importance for the community.

A User-Transformer Relation Identification Method Based on QPSO and Kernel Fuzzy Clustering

User-transformer relations are significant to electric power marketing,power supply safety,and line loss calculations.To get accurate user-transformer relations,this paper proposes an identification method for user-transformer relations based on improved quantum particle swarm optimization(QPSO)and Fuzzy C-Means Clustering.The main idea is:as energymeters at different transformer areas exhibit different zero-crossing shift features,we classify the zero-crossing shift data from energy meters through Fuzzy C-Means Clustering and compare it with that at the transformer end to identify user-transformer relations.The proposed method contributes in three main ways.First,based on the fuzzy C-means clustering algorithm(FCM),the quantum particle swarm optimization(PSO)is introduced to optimize the FCM clustering center and kernel parameters.The optimized FCM algorithm can improve clustering accuracy and efficiency.Since easily falls into a local optimum,an improved PSO optimization algorithm(IQPSO)is proposed.Secondly,considering that traditional FCM cannot solve the linear inseparability problem,this article uses a FCM(KFCM)that introduces kernel functions.Combinedwith the IQPSOoptimization algorithm used in the previous step,the IQPSO-KFCM algorithm is proposed.Simulation experiments verify the superiority of the proposed method.Finally,the proposed method is applied to transformer detection.The proposed method determines the class members of transformers and meters in the actual transformer area,and obtains results consistent with actual user-transformer relations.This fully shows that the proposed method has practical application value.