一类负模量Kirchhoff - Carrier方程的解

利用变分方法和反证法研究了一类含有非线性项的Kirchhoff - Carrier方程,证明了当0<λ1时,该方程至少存在一对非平凡解,且当λ≥a λ₁时该方程不存在同号解.     

浅谈索债型非法拘禁罪中的“索”＂债＂

索债型的非法拘禁罪,是随着我国社会发展所形成的一种特殊的非法拘禁罪,这种情形的出现引发了法学界不同学者的纷争。通过对索债型非法拘禁罪的概念、特征、存在依据和索债型非法拘禁罪的司法认定等一系列问题来分析索债型非法拘禁罪的法条内涵以及关于其的建议和完善措施。对于索债型的非法拘禁罪的研究有助于丰富我国非法拘禁罪的理论,能更加清楚明确地追究犯罪人的刑事责任,有助于我国的司法实践。刑法中还没有对于索债型非法拘禁罪进行具体规定,我国刑法应尽快对索债型非法拘禁罪的问题做出具体详细的规定,从而完善我国非法拘禁罪的理论。     

Boosting k-nearest neighbor classifier by means of input space projection

The k-nearest neighbors classifier is one of the most widely used methods of classification due to several interesting features, such as good generalization and easy implementation. Although simple, it is usually able to match, and even beat, more sophisticated and complex methods. However, no successful method has been reported so far to apply boosting to k-NN. As boosting methods have proved very effective in improving the generalization capabilities of many classification algorithms, proposing an appropriate application of boosting to k-nearest neighbors is of great interest.Ensemble methods rely on the instability of the classifiers to improve their performance, as k-NN is fairly stable with respect to resampling, these methods fail in their attempt to improve the performance of k-NN classifier. On the other hand, k-NN is very sensitive to input selection. In this way, ensembles based on subspace methods are able to improve the performance of single k-NN classifiers. In this paper we make use of the sensitivity of k-NN to input space for developing two methods for boosting k-NN. The two approaches modify the view of the data that each classifier receives so that the accurate classification of difficult instances is favored.The two approaches are compared with the classifier alone and bagging and random subspace methods with a marked and significant improvement of the generalization error. The comparison is performed using a large test set of 45 problems from the UCI Machine Learning Repository. A further study on noise tolerance shows that the proposed methods are less affected by class label noise than the standard methods.     

全变分极端通道先验的盲图像去噪去模糊

图像先验是图像复原中求解不适定问题的关键。针对在图像具有显著噪声时,极端通道先验去模糊算法容易产生振铃伪影和无法抑制噪声的缺点,利用全变分模型可以同时抑制噪声和保护边缘的优势,提出一种有效的全变分极端通道先验的盲图像去噪和去模糊模型。首先,将全变分模型分别引入暗通道和亮通道中,用于保护图像的边缘及消除噪声或振铃伪影;其次,利用半二次分裂技术解决模型的非凸问题和估计潜在的清晰图像;最后,用迭代多尺度盲反褶积估计图像的模糊核。实验结果表明,该算法能够在抑制噪声的同时很好地保护图像的边缘细节和消除振铃伪影。相比近几年具有代表性的其他方法,该模型的鲁棒性、主观视觉效果和客观评价指标均有明显提高。     

低临界胶束浓度PEGMA-b-PCL的制备及其 药物缓释性能

以ε-己内酯（ε-CL）为疏水链段,聚乙二醇甲醚甲基丙烯酸酯（PEGMA）为亲水链段,4-氰基-4-[(十二烷基硫基硫羰基)硫基]戊酸（CDPA）为可逆加成-断裂链转移（RAFT）试剂,在以甲苯为溶剂、N2氛围、80 ℃、反应24 h的条件下,通过RAFT聚合法制备了两嵌段聚合物PEGMA-b-PCL。将其自组装为胶束用作纳米药物载体,并以姜黄素（Cur）为胶束负载药物。考察了两嵌段聚合物结构、分子量及分布,表征了胶束载体粒径、形貌,测试了胶束载体的载药和释药性能。结果表明,不同嵌段聚合物相对分子质量范围为478~7318,此类聚合物具有较低的临界胶束浓度（CMC）,在常规条件下（pH=7.4）其范围为0.920~1.600 μg/mL。胶束载体粒径范围为:68.34~186.30 nm。当n(CDPA)∶n(ε-CL)=1∶200时,胶束载药量和包封率最高,可达12.05%和75.26%。在不同pH值环境下,药物缓释性能可达15 d,其中pH=5.0时释药量可达35.38%。     

Plastic deformation behind strong shock waves

The dislocation produced plastic deformation that must occur behind the front of strong shock waves is analysed in this paper. (A strong shock has a driving stress that is large compared with the bulk elastic modulus). Because the front of strong shock waves must be exceedingly narrow, there is a problem of how the effective shear stress, which is probably of the order of the theoretical shear strength at the immediate front itself, is relaxed in the region behind the shock front. Our analysis (Weertman and Follansbee, 1983)) of moderate strength shock waves is used for the relaxing region behind a strong shock wave front. It is concluded that a strong shock wave front has the following dislocation structure: The shock front, of atomic dimensions, consists of a Smith dislocation interface of dislocations that keep up with the front by moving at transonic or supersonic velocities. Immediately behind the Smith interface is a region of moving dislocations that do not keep up with the shock front. In this region normal dislocation motion and multiplication takes place. Within this region of normal plastic deformation the shock pressure rises by an amount that is quite small compared with the shock pressure itself.     

醛,2-异丁腈与硝基甲烷的多组分passerini反应

Passerini反应是一类重要的多组分反应,它可以快速的合成许多结构复杂的药物中间体,文章以苯甲醛,2-异丁腈和硝基甲烷为原料,氯化锌为催化剂,在微波作用下,发展新的多组分Passerini反应。     

（100）应变对正交相Ca2P0.25Si0.75能带结构及光学性质的影响

采用第一性原理赝势平面波方法对（100）应变下正交相Ca2P0.25Si0.75的能带结构及光学性质进行模拟计算.计算结果表明：（100）面在晶格发生100％～116％张应变时,带隙随着应变增加而减小;在晶格发生96％～100％压应变时,带隙随着张应变的增加而增加;88％～96％压应变时,带隙随着压应变的增加而减小;当压应变大于88％后转变为间接带半导体.当施加应变后光学性质发生显著的变化：随着压应变的增加静态介电常数、折射率逐渐减小,张应变则反之.施加压应变反射向低能方向偏移,施加张应变反射向高能方向偏移,但施加应变对反射区域的影响不显著.施压应变吸收谱、光电导率的变化与介电函数和折射率相反.综上所述,应变可以改变Ca2P0.25Si0.75的电子结构和光学常数,是调节Ca2P0.25Si0.75光电传输性能的有效手段.     

Bismuth oxide based ceramics with improved electrical and mechanical properties: Part I. Preparation and characterisation

A study of the preparative variables in the synthesis of ceramics based on Bi₂O₃-Er₂O₃ solid solutions has shown that the best results are obtained with a coprecipitation method. Critical parameters in the synthesis are found to be i) wet milling of the precalcined powder with an appropriate liquid and ii) calcining and sintering temperatures. With the proposed method it is possible to produce monophasic, contamination free, dense and machineable ceramics suitable for practical applications.     

基于小波包和PSO-Elman神经网络的滚动轴承故障诊断

针对滚动轴承的故障诊断,分析滚动轴承故障机理及特点,提出基于小波包分析的滚动轴承振动信号的特征向量提取算法,并建立PSO-Elman神经网络进行故障诊断和识别。将滚动轴承故障振动信号进行小波包分解,构造频带能量谱作为特征向量,输入PSO-Elman神经网络对故障进行识别。试验结果表明,基于小波包分析和PSO-Elman神经网络相结合的方法可准确地实现滚动轴承的故障诊断。