Hypoglycaemic effect of comatin,an antidiabetic substance separated from Coprinus comatus broth,on alloxan-induced-diabetic rats

Comatin, an inhibitor of the non-enzymatic glycosylation (NEG) reaction, was isolated from Coprinus comatus fermentation broth by macroporous resin separation, followed by chromatographic purification using a C18 reversed-phase column. The compound was identified as 4,5-dihydroxy-2-methoxy-benzaldehyde by high-resolution MS, IR, NMR and UV analyses. The hypoglycaemic effect of comatin, on both normal and alloxan-induced-diabetic rats, was investigated in the paper. The blood glucose concentration of normal rats treated by the comatin at 80 mg/kg body weight was reduced from 5.14 mM to 4.28 mM in 3 h. Also, the concentrations of fructosamine, triglycerides and total cholesterol in induced-diabetic rats were significantly decreased. These results indicated that comatin could maintain a low level of blood glucose and improve glucose tolerance.     

Study on the spray-drying encapsulation of lutein in the porous starch and gelatin mixture

Spray-drying encapsulation of lutein was conducted to improve its stability and water-solubility. With the porous starch and gelatin as wall material, lutein microcapsules were effectively prepared by spray-drying process. Results showed the optimal technology of lutein encapsulation as follows: the ratio of core to wall material of 1/30, embedding temperature of 60 °C, embedding time 1.5 h, inlet gas temperature of 190 °C, feed flow rate 50 mL/min and drying air flow 60 m³/h, at which the microcapsules had good encapsulation efficiency (94.4 ± 0.4)% and high yield of product (92.6 ± 1.7)%. Its solubility was increased and it could be directly dissolved in water. The stability of lutein microcapsule in the new carrier mixture against heat, pH, light and oxygen was also greatly improved and their retention rates had been improved about 15–50% than that of free lutein. The results would be helpful to the application of lutein in food industry.     

Bilateral posteroventral pallidotomy in advanced Parkinson's disease in three patients

In this report, we describe the effect of staged bilateral posteroventral pallidotomy in three patients with advanced Parkinson's disease who were all of the young-onset type. Two patients had developed response fluctuations after the use of levodopa, with severe hypokinesia, painful dystonia, and rigidity in the "off" phase and violent dyskinesias in the "on" phase. One patient, in a continuous hypokinetic rigid state, was totally unresponsive to dopaminergic medication. All were at Hoehn and Yahr stage 5 in the "off" phase before surgery. After surgery, the hypokinetic state was reversed and dyskinesias were abolished in all patients. Hoehn and Yahr stages were 3 in the "off" phase postoperatively. Overall functional improvement was marked and lasting after follow-up for 7, 12, and 13 months, respectively. Complications were visual field deficit and transient central facial paresis, both in the same patient. Bilateral posteroventral pallidotomy can ameliorate response fluctuations, hypokinesia, rigidity, and painful dystonia in advanced Parkinson's disease.     

下行多用户NOMA系统中基于能效优化的资源分配

非正交多址接入技术（Non-orthogonal multiple access, NOMA）提高了通信系统的频谱效率且可支持大量用户接入,因此受到广泛关注。以能量效率（简称能效）最大化为目标的多用户NOMA系统下行链路的资源分配问题,是一个难以求解的非凸问题,为此,将问题分解成用户分组和功率分配2个子问题。首先采用一种基于贪婪算法的用户分组方式降低了穷举法的计算复杂度;其次根据确定的分组方式,得到各个子信道上复用用户的功率分配系数表达式。为了进一步提高系统的能效,研究了子信道间非等功率分配方案,将子信道功率分配问题规划成非线性非凸的比率和问题,并利用Dinkelbach类算法得到次优解。仿真结果显示,文中采用的方案可以达到更好的系统容量和能效。     

用乳酸溶液为电解质制备TiO2纳米管阵列

为了开发自组织阳极氧化制备TiO2纳米管阵列的新体系,以乳酸/NH4F混合溶液为电解质,研究了阳极氧化制备TiO2纳米管阵列的影响因素及形成机理.采用X射线衍射(XRD)和扫描电子显微镜(SEM)对样品进行检测,并通过观察阳极氧化过程中的电流-时间变化曲线,探讨TiO2纳米管阵列的形成机理.结果表明:阳极氧化电压、时间及电解质溶液的黏度是影响TiO2纳米管阵列结构和形貌的主要因素,在40 v阳极氧化电压下,制备出平均管径高达180 nm的纳米管,所获得的TiO2纳米管阵列为无定型结构,300℃热处理以后转变为锐钛矿型TiO2.     

SMT封装电路板三维在线检测技术

为了检测回流焊接之后SMT( Surface Mount Technology)封装电路板是否存在缺陷,设计并搭建了基于线结构光传感器的SMT封装电路板三维在线检测系统,通过线结构光扫描测量,获取SMT封装电路板表面三维数据。采用双传感器测量技术,有效减少数据丢失;研究了双传感器统一标定技术,可同时实现两个传感器的参数标定和坐标系统一。提出了自适应光条中心提取算法,对反射或散射影响而形成的光条图像噪声具有很好的抑制效果,能够提取准确的光条中心。实验表明系统测量精度可达到0.02 mm。系统测量得到的三维数据,可以为在线检测SMT封装电路板缺陷提供可靠的三维信息。     

Structural health monitoring by using a sparse coding-based deep learning algorithm with wireless sensor networks

Structural health monitoring has received remarkable attention due to the arising structural safety problems. Most of these structural health problems are accumulative damages such as slight changes in structural deformations which are very hard to be detected. In addition, the complexity of real structure and environmental noises make structural health monitoring more difficult. Existing methods largely use various types of sensors to collect useful parameters and then train a machine learning model to diagnose damage level and location, in which a large amount of training data are needed for the model training, while the labeled data are rare in the real world. To overcome this problem, sparse coding is employed in this paper to achieve structural health monitoring of a bridge equipped with a wireless sensor network, so that a large amount of unlabeled examples can be used to train a feature extractor based on the sparse coding algorithm. Features learned from sparse coding are then used to train a neural network classifier to distinguish different statuses of the bridge. Experimental results show the sparse coding-based deep learning algorithm achieves higher accuracy for structural health monitoring under the same level of environmental noises, compared with some existing methods.