A comparison of silicon oxide and nitride as host matrices on the photoluminescence from Er+ ions

This paper compares the properties of silicon oxide and nitride as host matrices for Er ions.Erbium-doped silicon nitride films were deposited by a plasma-enhanced chemical-vapour deposition system.After deposition,the films were implanted with Er3+ at different doses.Er-doped thermal grown silicon oxide films were prepared at the same time as references.Photoluminescence features of Er3+ were inspected systematically.It is found that silicon nitride films are suitable for high concentration doping and the thermal quenching effect is not severe.However,a very high annealing temperature up to 1200° C is needed to optically activate Er3+,which may be the main obstacle to impede the application of Er-doped silicon nitride.     

High-lying excited states in <Superscript>10</Superscript>Be from the <Superscript>9</Superscript>Be(<Superscript>9</Superscript>Be,<Superscript>10</Superscript>Be)<Superscript>8</Superscript>Be reaction

A transfer-reaction experiment of ⁹Be(⁹Be, ¹⁰Be)⁸Be was performed at a beam energy of 45 MeV. Excited states in ¹⁰Be up to 18.80 MeV are produced using missing mass and invariant mass methods. Most of the observed high-lying resonant states, reconstructed from the α + ⁶He and t + ⁷Li decay channels, agree with the previously reported results. In addition, two new resonances at 15.6 and 18.8 MeV are identified from the present measurement. The 18.55 MeV state is found to decay into both the t + ⁷Li_g.s. and t + ⁷Li* (0.478 MeV) channels, with a relative branching ratio of 0.93 ± 0.33. Further theoretical investigations are encouraged to interpret this new information on cluster structure in neutron-rich light nuclei.     

Effect of defect configuration on the localization of phonons in two-dimensional phononic crystals

Effects of defect location on the defect frequency and the localization of phonons are investigated in two novel kinds of model, created by moving the location of the native cylinder and inserting an ad-cylinder in the central cellular respectively. The results show that the defect frequency in Model 1 is only related to the distance, while in Model 2, is related not only to the distance, but also to the moving direction. From the pressure distribution, obvious localization phenomenon is found. The position and shape of the localized energy are varied with the position of the defect.     

Evaluation of ADC measurements among solid pancreatic masses by respiratory-triggered diffusion-weighted MR imaging with inversion-recovery fat-suppression technique at 3.0 T

Purpose

The objective of this paper was to investigate the value of apparent diffusion coefficients (ADCs) for differential diagnosis among solid pancreatic masses using respiratory triggered diffusion-weighted MR imaging with inversion-recovery fat-suppression technique (RT-IR-DWI) at 3.0 T.

Materials and Methods

20 normal volunteers and 72 patients (Pancreatic ductal adenocarcinoma [PDCA, n = 30], mass-forming pancreatitis [MFP, n = 15], solid pseudopapillary neoplasm [SPN, n = 12], and pancreatic neuroendocrine tumor[PNET, n = 15]) underwent RT-IR-DWI (b values: 0 and 600 s/mm²) at 3.0 T. Results were correlated with histopathologic data and follow-up imaging. ADC values among different types of pancreatic tissue were statistically analyzed and compared.

Results

Statistical difference was noticed in ADC values among normal pancreas, MFP, PDCA, SPN and PNET by ANOVA (p < .001). Normal pancreas had the highest ADC value, then followed by PNET, PDCA, MFP and SPN. There was noticeable statistical difference in ADC values among PDCA, MFP and normal pancreas by Least Significant Difference (LSD) (p < .001). ADC of SPN was statistically lower than that of PNET (p = 0.1800 × 10^− 4), PDCA (p = 0.0300 × 10^− 4) and normal pancreas (p = 0.0007 × 10^− 4). ADC of PNET was statistically lower than that of normal pancreas (p = 0.0360) and higher than that of MFP (p = 9.3000 × 10^− 4).

Conclusions

ADC measurements using RT-IR-DWI at 3.0 T may aid to disclose the histopathological pattern of normal pancreas and solid pancreatic masses, which may be helpful in characterizing solid pancreatic lesions.     

Optimization of direct modulation rate for circular microlasers by adjusting mode Q factor

Semiconductor microcircular lasers have been investigated as potential light sources for photonic integrated circuits and optical interconnections for more than two decades. However, the direct modulation bandwidths of the circular microlasers remain a challenge, especially when being compared with other microlasers, such as photonic crystal lasers. In this paper, microcircular lasers connected to an output waveguide are investigated for high‐speed direct modulation with optimized mode Q factors. Small signal modulation with a resonance frequency of f_R = 12.5 GHz is realized for a AlGaInAs/InP circular microlaser with a radius of 10 µm at 290 K. Furthermore, clear eye diagrams are observed at 12.5 Gbit/s for a 15‐µm radius circular microlaser with f_R = 6.9 GHz.     

生地当归药队煎剂的表面增强拉曼散射光谱

为揭示单味煎剂与方剂间的关系,分别测试分析了生地当归药队、单味药生地和单味药当归煎剂的表面增强拉曼散射(surface-enhanced Raman scattering, SERS)光谱,并对其进行谱峰归属。本文主要针对存在于三种煎剂中的17个拉曼信号(538,622,732,761,835,876,959,1 145,1 245,1 276,1 326,1 402, 1 456,1 470,1 518,1 546和1 605 cm-1)进行讨论。生地当归药队煎剂SERS光谱在538,732,761,835,876,959,1 145,1 245,1 276,1 326,1 402,1 456,1 470,1 518和1 605 cm-1处,出现15个明显的拉曼信号;生地煎剂SERS光谱在538,761,835,876,959,1 145,1 245,1 276,1 326,1 402,1 470,1 518和1 546 cm-1处,出现13个明显的拉曼信号;当归煎剂SERS光谱在538,622,732,761,835,876,959,1 245,1 326和1 402 cm-1处,出现10个明显的拉曼信号。生地当归药队煎剂SERS光谱保留了和未观察到生地和当归单味煎剂的某些拉曼峰,且产生了生地和当归单味煎剂中所没有的拉曼信号(1 456和1 605 cm-1),即产生新药物成分。生地当归药队煎剂所包含的药物成分并非是生地和当归单味药物煎剂所含药物成分的简单相加。结果表明,SERS光谱可能为方剂研究提供一种高灵敏度、快速准确和操作简单的检测方法。     

Asymptotic Behavior of Least Energy Solutions for a Fractional Laplacian Eigenvalue Problem on ℝN

Acta Mathematica Sinica, English Series - We are interested in the existence and asymptotic behavior for the least energy solutions of the following fractional eigenvalue problem $$left({rm{P}}...     

Ni_n(n=2～20)团簇的结构

使用经验势和遗传算法 (GeneticAlgorithm) ,得到了Nin(n =2～ 2 0 )团簇的平衡结构和束缚能。对于小的团簇 (Ni2 ～Ni6) ,所得到的结果与基于第一性原理密度泛函的计算相一致。结果表明 ,团簇的结构不同于块体且随尺度发生引人注日的变化。每原子平均束缚能Eb 随尺度单调增长。根据过渡金属团簇表面原子配位数与电离势 (IP)的一个解析表达式计算所得的电离势与实验结果基本一致。由基态能量对分裂途径(FragmentationChannels)的分析表明 ,失去二聚体 (Dimer)在能量上是优先的。同时将计算所得的结构与Nin团簇吸收N2 的实验所推得的结构进行了比较     

Single-detector polarization-sensitive optical frequency domain imaging using high-speed intra A-line polarization modulation

We demonstrate a novel high-speed polarization-sensitive optical frequency domain imaging system employing high-speed polarization modulation. Rapid and continuous polarization modulation of light prior to illumination of the sample is accomplished by shifting the frequency of one polarization eigenstate by an amount equal to one quarter of the digitization sampling frequency. This approach enables polarization-sensitive imaging with a single detection channel and overcomes artifacts that may arise from temporal variations of the birefringence in fiber-optic imaging probes and spatial variation of birefringence in the sample.     

Relative density-based classification noise detection

Classification noise is a common byproduct of traditional data mining approaches, and no specialized approach for detecting classification noise is currently available. Methods for outlier detection are well-developed, but outliers and classification noise have characteristics different enough to make outlier detection algorithms unsuitable for classification noise detection. In this paper, a new, specialized approach to detect classification noise is proposed, named relative density based classification noise detection (RDBCND). Computational experiments in artificial data sets described herein show that RDBCND has time complexity of O(n log n), indicating greater efficiency than traditional approaches, which exhibit time complexity of at least O(n²). The use of classification noise detection to improve the generalization ability of common classifier algorithms is also described. In particular, a new unified approach based on RDBCND is compared to a cross validation approach applied to a BP neural network. Trials in both artificial and real-life datasets show that the RDBCND-based approach can greatly accelerate the process of identifying the best decision function. The novel method can also eliminate underfitting, as the algorithm simply searches for the highest training accuracy. The experiments also show that the RDBCND-based method has greater accuracy and lower cpu time in reaching global solutions than the cross-validation method. Since the relative density is a local concept, our new approach can be directly used in nonlinear datasets without data transformation. It is a great advantage compared to some linear classifier algorithms. As in current linear classifiers, the kernel functions or other transformations need to be used to make them suitable for non-linear datasets, and that will increase their complexity.