婴儿湿巾缓冲能力的测试——一个贴近生活的实验

为了有效提升学生在缓冲溶液学习过程中的学习兴趣及积极性,在此推荐一个将现实中的生活用品作为实验对象引入实验课教学过程中的案例。该实验设计将性质实验扩充到婴儿湿巾,将实验内容变为对婴儿湿巾工作原理的验证,而不再是过去简单的酸碱体系的配制及相关验证实验。通过该实验的实施,学生普遍反映能够有效激发其在学习缓冲溶液相关课程中的学习积极性与兴趣,并最终促使学生认知缓冲体系内pH变化的特点及缓冲机理。     

问题引导法提高学生学习主动性的探索与实践*——以大学化学混合式教学为例

建设具有创新性、高阶性和挑战度的“金课”,是当代创新型人才培养的必然要求。大学化学是本校非化学类理工科专业基础课,相比于数学和物理,学生重视不足,导致教学效果不理想。为了解决这一问题,采取以学生为主的混合式教学模式,通过设置基础性、应用性及创新性问题,引导学生分层次解决,提高学生参与主动性。所设置的应用性问题包括科技前沿、专业相关、社会热点等,以增加内容的深度和广度,激发学生探索的兴趣。通过实验方案设计及实验检验培养学生的创新思维。采取累加式进行教学效果评价,实践表明该混合式教学模式能显著提高学生自主学习能力和兴趣,提高教学效果。     

有机化学教学中的“三融合、二反思、四进阶”创新教学模式*

为培养出新时代创新人才,构建的“三融合、二反思、四进阶”教学模式有效提升了学生们科技创新能力。依据有机化学特点,创设科学发现情境,通过核心知识点网融合(挑战度)、理论实践交叉融合(高阶性)和化学思政融合(课程思政)“三融合”策略,不断激发学生们学习兴趣;通过教师反思、学生反思的“二反思”过程不断优化教学过程,改善教学效果;最终使具有不同知识层次的学生通过“四进阶”教学策略逐步提升科创能力(创新性)。     

长三角地区房地产市场是如何实现"去库存"的?

长三角地区在全国房地产"库存"的背景下,实现了房地产市场的不断向好.对长三角地区有关面板数据进行实证研究,实证结果表明房地产开发投资、医院床位数、工业生产总值与人均房地产成交面积呈正相关.城镇人口数,中、长期贷款利率与人均房地产成交面积呈负相关,高收入城市比低收入城市人均房地产成交面积低14.%,教育支出和城镇居民总的可支配收入对人均房地产成交面积影响不显著.     

Optimal Randomness for Stochastic Configuration Network (SCN) with Heavy-Tailed Distributions

Stochastic Configuration Network (SCN) has a powerful capability for regression and classification analysis. Traditionally, it is quite challenging to correctly determine an appropriate architecture for a neural network so that the trained model can achieve excellent performance for both learning and generalization. Compared with the known randomized learning algorithms for single hidden layer feed-forward neural networks, such as Randomized Radial Basis Function (RBF) Networks and Random Vector Functional-link (RVFL), the SCN randomly assigns the input weights and biases of the hidden nodes in a supervisory mechanism. Since the parameters in the hidden layers are randomly generated in uniform distribution, hypothetically, there is optimal randomness. Heavy-tailed distribution has shown optimal randomness in an unknown environment for finding some targets. Therefore, in this research, the authors used heavy-tailed distributions to randomly initialize weights and biases to see if the new SCN models can achieve better performance than the original SCN. Heavy-tailed distributions, such as Lévy distribution, Cauchy distribution, and Weibull distribution, have been used. Since some mixed distributions show heavy-tailed properties, the mixed Gaussian and Laplace distributions were also studied in this research work. Experimental results showed improved performance for SCN with heavy-tailed distributions. For the regression model, SCN-Lévy, SCN-Mixture, SCN-Cauchy, and SCN-Weibull used less hidden nodes to achieve similar performance with SCN. For the classification model, SCN-Mixture, SCN-Lévy, and SCN-Cauchy have higher test accuracy of 91.5%, 91.7% and 92.4%, respectively. Both are higher than the test accuracy of the original SCN.     

Selecting an Effective Entropy Estimator for Short Sequences of Bits and Bytes with Maximum Entropy

Entropy makes it possible to measure the uncertainty about an information source from the distribution of its output symbols. It is known that the maximum Shannon’s entropy of a discrete source of information is reached when its symbols follow a Uniform distribution. In cryptography, these sources have great applications since they allow for the highest security standards to be reached. In this work, the most effective estimator is selected to estimate entropy in short samples of bytes and bits with maximum entropy. For this, 18 estimators were compared. Results concerning the comparisons published in the literature between these estimators are discussed. The most suitable estimator is determined experimentally, based on its bias, the mean square error short samples of bytes and bits.     

Informationen

Studies on the workability of precise seeders by means of labelling methods has been possible due to the solution of the following problems: labelling of seeds, radiation collimation of labelled seeds being sown, elaboration of measuring and registering systems as well as processing systems of a measuring signal. The developed method allows for precise, quick and fully objective evaluation of the studied seeders to be done under natural conditions.     

Real-World Forward Rate Dynamics With Affine Realizations

We investigate the existence of affine realizations for Lévy driven interest rate term structure models under the real-world probability measure, which so far has only been studied under an assumed risk-neutral probability measure. For models driven by Wiener processes, all results obtained under the risk-neutral approach concerning the existence of affine realizations are transferred to the general case. A similar result holds true for models driven by compound Poisson processes with finite jump size distributions. However, in the presence of jumps with infinite activity we obtain severe restrictions on the structure of the market price of risk; typically, it must even be constant.     

带连续变利率风险模型最终破产概率上界

考虑了带二元连续变利息力的Sparre Andersen风险模型.研究了积累值盈余过程的表达式与性质;在利率递增环境下,利用推广后的调节系数方程组与递归技术推导了最终破产概率的上界,结论表明得到的破产概率上界是更为一般的Lundberg指数上界.     

随机利率下服从指数O-U过程的可转换债券的鞅定价

从定量的角度分析了随机利率下有股利分配的可转换债券的价值构成,并在股价服从广义O-U过程的条件下,利用鞅定价方法推导出可转换债券的定价公式.