应变纤锌矿ZnO/MgxZn1-xO量子点中离子施主束缚激子的光学性质

Within the framework of the effective-mass approximation and the dipole approximation, considering the three-dimensional confinement of the electron and hole and the strong built-in electric field(BEF) in strained wurtzite Zn O/Mg0:25Zn0:75O quantum dots(QDs), the optical properties of ionized donor-bound excitons(D+, X)are investigated theoretically using a variational method. The computations are performed in the case of finite band offset. Numerical results indicate that the optical properties of(D+, X) complexes sensitively depend on the donor position, the QD size and the BEF. The binding energy of(D+, X) complexes is larger when the donor is located in the vicinity of the left interface of the QDs, and it decreases with increasing QD size. The oscillator strength reduces with an increase in the dot height and increases with an increase in the dot radius. Furthermore, when the QD size decreases, the absorption peak intensity shows a marked increment, and the absorption coefficient peak has a blueshift. The strong BEF causes a redshift of the absorption coefficient peak and causes the absorption peak intensity to decrease remarkably. The physical reasons for these relationships have been analyzed in depth.     

Effects of different carbon sources and C/N values on nonvolatile taste components of Pleurotus eryngii

Pleurotus eryngii, the second largest industrial cultivation mushroom in China, is usually cultivated on substrates mainly consisting of sawdust and corncob. In this study, experiments were performed to determine the effects of different carbon sources and C/N values on nonvolatile taste components of P. eryngii. The effects of different carbon sources on nonvolatile taste components levels revealed that sawdust was beneficial to high levels of crude protein, amino acids, 5′‐nucleotides and equivalent umami concentration, while corncob was beneficial to high contents of carbohydrate, polysaccharides and trehalose. At the similar C/N values, relatively higher sawdust content was beneficial to umami amino acid production, while relatively higher corncob content was beneficial to high contents of carbohydrate, polysaccharides and mannitol. Higher C/N value was beneficial to high levels of crude protein, amino acids, 5′‐nucleotides and equivalent umami concentration, while lower C/N value was beneficial to high contents of carbohydrate, polysaccharides and trehalose. These results provided information for P. eryngii fruit body industrial cultivation to obtain specific nonvolatile taste components with high levels.     

GOS+MU:一种查询对象选择新方法

在分析单一MU(Most Uncertainty)采样缺陷的基础上,提出一种"全局最优搜寻"方法 GOS(Global Optimal Search),并结合MU共同完成查询选择。GOS+MU方法中,GOS着眼全局寻找目标,在应用环境能提供的训练样本数量有限、分类器受训不充分时,该方法选择的对象学习价值高,能快速推进分类器学习进程;MU则能够在GOS采样失效情形下,利用分类器当前训练成果,选择查询不确定性最强的样本补充训练集。通过对网络商品的用户评论进行分类仿真,并比较其他采样学习方法的效果,证明了GOS+MU方法在压缩学习成本、提高训练效率方面的有效性。     

Distributed De La Garza algorithm for load-balancing routing in wireless sensor networks

Large scale wireless sensor networks raise many challenges in the design of efficient and effective routing algorithm due to their complexity and hardware constraints. However, the scalability challenge may be mitigated from a macroscopic perspective. One example is the distributed De la Garza iteration (DDLGI) algorithm for global routing load-balancing, based on a set of partial differential equations iteratively solved by the De la Garza method. We theoretically analyze the parallelism of DDLGI and illustrate that the region of interest may impact the degree of parallelism and error. Furthermore, though DDLGI always converges, the slow convergence and long-range information exchange problems may lead to excess energy consumption in communication. Thus, we propose various enhanced De la Garza routing (E-DLGR) algorithms to alleviate the energy consumption problem by which nodes may exchange less information and only need to exchange information with closer nodes to complete each iteration. Our theoretical analysis and simulation results show that the proposed E-DLGR algorithms may have less transmission overhead, thus further reducing energy consumption, and converge faster while still maintaining adequate accuracy.