中速柴油机机体铸造裂纹的原因分析及防止措施

根据柴油机机体裂纹产生的原因,对机体裂纹缺陷进行分析,找到了机体裂纹产生的主要原因。其主要原因可概括为铸件结构、化学成分、铸件补缩条件及开箱温度等,针对裂纹的主要原因采取相应的措施后,裂纹缺陷得到了根本的控制。     

锚栓用量对纯锚固岩棉保温系统抗风压性能的影响

采用ETAG 004:2013《外墙外保温薄抹灰系统欧洲技术认证指南》中规定的静态泡沫块法,测试在单位面积上使用不同数量锚栓的岩棉板外保温系统的抗风压性能。通过试验可以得出:在混凝土墙体上单纯采用敲击式锚栓锚固岩棉板外保温系统时,拉伸强度可达12.9 k Pa;单位面积增加锚栓的使用量可以提高系统的抗拉承载力,但在不同条件下增加相同数量锚栓对系统抗风载能力提高的程度不同;在普通混凝土墙中,单纯锚固岩棉板保温系统破坏时,单个锚栓承载力平均值的最大值约为其拉拔承载力的50.3%。     

125I粒子条联合胆道支架植入治疗恶性梗阻性黄疸22例疗效分析

【摘要】　 　目的 研究和探讨125I粒子条联合胆道支架植入治疗恶性梗阻性黄疸的临床疗效。方法 2011年6月—2013年9月收治恶性梗阻性黄疸患者40例。行胆道支架植入术治疗患者18例，为对照组；采用125I粒子条联合胆道支架植入患者22例，为观察组。两组均采用经皮肝穿刺胆道引流（PTCD）并胆道支架植入。结果 观察组与对照组的平均胆道开通时间分别为（8.7 ± 0.7）和（6.2 ± 0.4）个月，两组比较差异有统计学意义（P < 0.05）。观察组与对照组术后平均生存时间分别为（11.4 ± 0.8）和（8.7 ± 0.5）个月，生存时间的差异有统计学意义（P < 0.05）。术后近期疗效及并发症两组之间的比较无明显差异（P > 0.05），但是远期疗效有显著差异（P < 0.05）。结论 与对照组相比，观察组的术后生存时间及胆道开通时间明显延长，对于125I粒子条联合支架治疗恶性梗阻性黄疸值得进一步临床研究。
     

Enhance cycling performance of LiMn2O4 cathode by Sr2+ and Cr3+ doping

Spinel LiSr_0·1Cr_0·1Mn_1·8O₄ was synthesised by high temperature solid state method in order to enhance the electrochemical performance. The LiSr_0·1Cr_0·1Mn_1·8O₄ (LSCMO) materials were characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM) and electrochemical tests. The XRD and SEM studies confirm that LSCMO had spinel crystal structure with a space group of Fd3m, and the particle of LSCMO shows irregular shape. The cyclic voltammetry data illustrated that the heavy current charge–discharge performance of LMO was improved by Sr²⁺ and Cr³⁺ doping. The galvanostatic charge–discharge of LSCMO cathode materials was measured at 1, 5, 10 and 20 C. The results indicated that LSCMO improved the capacity retention.     

鸡西盆地太平普查区岩浆活动特征

通过对普查区喜山期玄武岩喷发分布范围、形态的分析,对燕山晚期闪长玢岩分布范围、与构造关系、对煤层的影响等方面的分析,阐述了太平普查区岩浆活动特征。     

A spatio-temporal fusion method for remote sensing data Using a linear injection model and local neighbourhood information

This paper presents a spatio-temporal fusion method for remote sensing images by using a linear injection model and local neighbourhood information. In this method, the linear injection model is first introduced to generate an initial fused image, the spatial details are extracted from the fine-resolution image at the base date, and are weighted by a proper injection gains. Then, the spatial details and the relative spectral information from the coarse-resolution images are blended to generate the fusion result. To further enhance its robustness to the noise, the local neighbourhood information, derived from the fine-resolution image and the fused result simultaneously, is introduced to refine the initial fused image to obtain a more accurate prediction result. The algorithm can effectively capture phenology change or land-cover-type change with minimum input data. Simulated data and two types of real satellite images with seasonal changes and land-cover-type changes are employed to test the performance of the proposed method. Compared with a spatial and temporal adaptive reflectance fusion model (STARFM) and a flexible spatio-temporal fusion algorithm (FSDAF), results show that the proposed approach improves the accuracy of fused images in phenology change area and effectively captures land-cover-type reflectance changes.     

Specific emitter identification for satellite communication using probabilistic neural networks

Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military.