中国吉丁虫新纪录种简记

近年来。笔在研究各地送鉴的大呈吉丁虫标本过程中。鉴定出一批中国新纪录种，今集中加以报道．并分别作简述如下。     

Mapping QTLs and meta-QTLs for two inflorescence architecture traits in multiple maize populations under different watering environments

Drought significantly affects the architectural development of maize inflorescence, which leads to massive losses in grain yield. However, the genetic mechanism for traits involved in inflorescence architecture in different watering environments, remains poorly understood in maize. In this study, 19 QTLs for tassel primary branch number (TBN) and ear number per plant (EN) were detected in 2 F_2:3 populations under both well-watered and water-stressed environments by single environment mapping with composite interval mapping (CIM); 11/19 QTLs were detected under water-stressed environments. Moreover, 21 QTLs were identified in the 2 F_2:3 populations by joint analysis of all environments with a mixed linear model based on composite interval mapping (MCIM), 11 QTLs were involved in QTL × environment interactions, seven epistatic interactions were identified with additive by additive/dominance effects. Remarkably, 12 stable QTLs (sQTLs) were simultaneously detected by single environment mapping with CIM and joint analysis through MCIM, which were concentrated in ten bins across the chromosomes: 1.05_1.07, 1.08_1.10, 2.01_2.04, 3.01, 4.06, 4.09, 5.06_5.07, 6.05, 7.00, and 7.04 regions. Twenty meta-QTLs (mQTLs) were detected across 19 populations under 51 watering environments using a meta-analysis, and 34 candidate genes were predicted in corresponding mQTLs regions to be involved in the regulation of inflorescence development and drought resistance. Therefore, these results provide valuable information for finding quantitative trait genes and to reveal the genetic mechanisms responsible for TBN and EN under different watering environments. Furthermore, alleles for TBN and EN provide useful targets for marker-assisted selection to generate high-yielding maize varieties.     

Use HypE to Hide Association Rules by Adding Items

During business collaboration, partners may benefit through sharing data. People may use data mining tools to discover useful relationships from shared data. However, some relationships are sensitive to the data owners and they hope to conceal them before sharing. In this paper, we address this problem in forms of association rule hiding. A hiding method based on evolutionary multi-objective optimization (EMO) is proposed, which performs the hiding task by selectively inserting items into the database to decrease the confidence of sensitive rules below specified thresholds. The side effects generated during the hiding process are taken as optimization goals to be minimized. HypE, a recently proposed EMO algorithm, is utilized to identify promising transactions for modification to minimize side effects. Results on real datasets demonstrate that the proposed method can effectively perform sanitization with fewer damages to the non-sensitive knowledge in most cases.     

Plasmonic Coupling Effects on the Refractive Index Sensitivities of Plane Au-Nanosphere-Cluster Sensors

Plasmonic coupling effects (between neighboring components) are able to red shift the peak wavelengths of dipolar-localized surface plasmon resonances (LSPRs) and increase the corresponding refractive index sensitivity of nanoparticle sensors. The coupling effects on plane Au-nanosphere-cluster (including nanosphere dimer, trimer, pentamer, and heptamer) sensors are numerically investigated by finite element method (FEM). We found that the coupling does not violate the quadratic response characteristics of LSPR peak wavelengths, hence the linear responses of the sensitivities to the bulk refractive index of Au cluster sensors. Yet, for nanosphere dimer sensors, they contribute to the exponential decrease of sensitivities with their gap distances, which follow the universal plasmon ruler behavior. The amplitude of their fractional sensitivity shift is revealed to be bulk refractive index independent, which is different from that of their fractional LSPR peak wavelength shift. These are analytically explained well in terms of an effective nanoparticle model. The present work also gives an upper sensitivity limit for Au nanosphere dimer systems and provides a method to estimate the interparticle separation between the two component nanospheres of the dimer.