Stability of Mixtoxantrone Hydrochloride in Solution

A stability-indicating reversed-phase high performance liquid chromatographic method was developed for the detection of mitoxantrone HC1 and its degradation products under accelerated degradation conditions. The degradation kinetics of mitoxantrone HC1 in aqueous solution over a pH range of 1.18 to 7.20 and its stability in propylene glycol-or polyethylene glycol 400-based solutions were investigated. The observed rate constants were shown to follow apparent first-order kinetics in all cases. The pH-rate profile shows that maximum stability of mitoxantrone HC1 was obtained at pH 4.01. No general acid or base catalysis from acetate or phosphate buffer species was observed. The catalysis rate constants on the protonated mitoxantrone imposed by hydrogen ion water and hydroxy ion were determined to be 3.72 × 10 min^-1 5.64 × 10-min^-1 and 1.108 × 10^-2min^-1, respectively. The degradation rate constants of mitoxantrone affected by different ionic strength systems. Irradiation with 254 nm UV light at 25±0.5°C was found when canpared with the light-protected controls. Incorporation of nonaqueous propylene glycol or polyethylene glycol in the pH 4.01 mitoxantrone solution shows an increase in its stability at 502±0.5°C.     

四坐标数控加工原理及算法研究

本文对四坐标数控加工原理和算法作了详细介绍，尤其对四坐标加工的刀轴矢量算法进行了研究，提出了用垂直于回转轴的平面与刀具运动方向和前导角形成的圆锥面求交，生成刀轴矢量的方法，该方法具有立意新颖、思路清晰，性能可靠，易于在微机上实现等特点，对复杂曲面零件的加工编程，具有重要的实用价值。     

环形孔径对部分相干光光谱的影响

本文推导了部分相干光在经过环形孔径之后,远场轴上点的光谱S(ω)与环形孔径处光的光谱S~(0)(ω)之间的关系。数值计算结果表明,S(ω)不仅依赖于S~(0)(ω),而且还与环形孔径处光的相干性以及环形孔径的参数有关。     

信息系统安全等级化防护研究探讨

文章针对广州强力安全部门网络安全系统防护提出的一种网络安全系统设计构架;对其中的网络安全体系结构设计与实现进行了详细的分析;提出了安全体系结构模型和管理执行策略模型,并详述了其设计过程。把安全体系结构、安全策略管理的实现和网络安全的实现机制有机地结合在一起。     

基于重叠分段和FrFT的VCO非线性度检测方法*

VCO非线性度检测是实现其非线性度精确校正的前提,研究VCO非线性度检测方法具有重要理论意义和实用价值。针对目前基于微元法和分数阶傅里叶变换的VCO非线性度检测方法在抗噪性、实时性等方面存在的不足,提出了一种基于重叠分段和分数阶傅里叶变换的VCO非线性度检测方法。所提方法采取重叠分段的策略以抑制噪声干扰,在分数阶傅里叶变换域进行幅度峰值搜索时改用收敛速度快的黄金分割法以增强实时性。仿真实验表明所提方法具有良好的抗噪性,分段重叠率为0.25时其检测的均方根误差约为现有方法的1/2;当重叠率小于2/3时,其实时性也优于现有方法。     

Energy efficiency in cloud computing based on mixture power spectral density prediction

Due to the budget and environmental issues, adaptive energy efficiency receives a lot of attention these days, especially for cloud computing. In the previous research, we developed a combined methodology based on nonparametric prediction and convex optimization to produce proactive energy efficiency-oriented solution. In this work, the predictive analysis was further enhanced by deriving the mixture power spectral density to model the complex cloud monitoring statistics. By engaging the improved technique to the predictive analysis, the prediction process was more adaptive to handle the fluctuation in system utilization. As a consequence, the optimization process could subsequently produce more appropriate setting for energy savings. After the infrastructure setting has been made available, the instruction of virtual machine migration was created and implemented by the cloud orchestrator. This instruction condensed the services into the pool of active facilities, satisfying the objective of power efficiency. Eventually, any physical machine out of the power configuration would be gradually terminated. Compared to our former method, the effectiveness of the proposed technique has been proven by cutting down 4.92% of energy consumption, while still maintaining a similar quality of services.

     

小波神经网络在雷达故障诊断中的应用研究

根据某型雷达接收机的信号特点,提出了基于小波神经网络和专家知识相结合的雷达智能故障诊断方法,探讨了该方法在某型雷达接收机故障诊断中的应用,采样信号经过小波去噪和小波特征向量提取后再进行归一化处理,作为小波神经网络的输入向量,小波神经网络隐含层的激活函数选用小波函数,完成雷达接收机典型故障的诊断;MATLAB实例仿真结果表明,该方法诊断准确,智能化水平高,有很好的自学习能力,提高了故障诊断的正确性和效率。     

Performance implications of internet channels in financial services: A comprehensive perspective

Advances in information technology (IT) have forced financial services firms to explore new organizational forms and deliver service innovation. Given the obvious differences in the business model in which the financial services sector provides online services, it is natural to ask whether the emergence of Internet channels leads to superior achievement. Using a sample of twenty-four Taiwanese publicly traded financial services firms from 1997 to 2003, this empirical study attempts to assess the Internet channel??s effect on firm performance by means of applying event study methodology and data envelopment analysis. Results show that the magnitudes of average abnormal returns are uniformly positive and increase the operating efficiency of firms following announcements via Internet channels. This work therefore concludes that Internet channels have positive influences on firm performance.     

Utilizing an Animal Model to Identify Brain Neurodegeneration-Related Biomarkers in Aging

Glycine N-methyltransferase (GNMT) regulates S-adenosylmethionine (SAMe), a methyl donor in methylation. Over-expressed SAMe may cause neurogenic capacity reduction and memory impairment. GNMT knockout mice (GNMT-KO) was applied as an experimental model to evaluate its effect on neurons. In this study, proteins from brain tissues were studied using proteomic approaches, Haemotoxylin and Eosin staining, immunohistochemistry, Western blotting, and ingenuity pathway analysis. The expression of Receptor-interacting protein 1(RIPK1) and Caspase 3 were up-regulated and activity-dependent neuroprotective protein (ADNP) was down-regulated in GNMT-KO mice regardless of the age. Besides, proteins related to neuropathology, such as excitatory amino acid transporter 2, calcium/calmodulin-dependent protein kinase type II subunit alpha, and Cu-Zn superoxide dismutase were found only in the group of aged wild-type mice; 4-aminobutyrate amino transferase, limbic system-associated membrane protein, sodium- and chloride-dependent GABA transporter 3 and ProSAAS were found only in the group of young GNMT-KO mice and are related to function of neurons; serum albumin and Rho GDP dissociation inhibitor 1 were found only in the group of aged GNMT-KO mice and are connected to neurodegenerative disorders. With proteomic analyses, a pathway involving Gonadotropin-releasing hormone (GnRH) signal was found to be associated with aging. The GnRH pathway could provide additional information on the mechanism of aging and non-aging related neurodegeneration, and these protein markers may be served in developing future therapeutic treatments to ameliorate aging and prevent diseases.