A novel temperature-tolerant foamed resin for enhanced oil recovery

The synthesis and performance of a novel temperature-tolerant foamed resin for enhanced oil recovery were investigated using various methods, including infrared, NMR, scanning electron microscopy (SEM), and displacement experiments. Polycondensation of furfuryl alcohol prepolymers was confirmed by the infrared and NMR results. The poor temperature tolerance of furfuryl alcohol prepolymers after gelation at high temperatures is mainly due to the fracture of furan rings. The addition of ester additives is an effective method of increasing the temperature tolerance of the prepared foamed resins and can effectively reduce the weight-loss rate of the polycondensation products. The SEM results show that the skeleton structure of the foamed resin remains intact after high-temperature treatment. Thus, the novel plugging agent system has excellent thermal stability and still has a high strength (>0.8 MPa) after high-temperature aging treatment for 40 days, giving the prepared foamed resin a good plugging performance (plugging rate > 91%) at 250 °C. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47161.     

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。
     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.     

Enhanced photoreactivity of MOFs by intercalating interlayer bands via simultaneous ?NCO and ?SCu modification

Herein, we propose a novel method to enhance the photoreactivity of an MOF catalyst by grafting isocyanate bonds ( NCO) and sulfhydryl-complexed copper ( SCu) onto ZIF-8 (NIF-SCu). The grafting process intercalated interlayer bands between the conduction and valence bands of ZIF-8, thereby providing a “ladder” for facile electron transition. The extreme improvement in the photoreactivity of NIF-SCu could be attributed to the enhancement in light responses in the range of 350–450 nm by  NCO groups and the widening of the visible light range of the MOF by  SCu groups. The formation of staggered energy levels in NIF-SCu could also narrow the band gap, lower the resistance, and facilitate the transfer of photogenerated carriers, thereby generating electrons with strong reduction potential in the  SCu conduction band. This study provides a new strategy for improving or even endowing the photoactivity of environmental functional materials with wide bandgaps.     

Super-Resolution Reconstruction of Images Based on Microarray Camera

In the field of images and imaging, super-resolution (SR) reconstruction of images is a technique that converts one or more low-resolution (LR) images into a highresolution (HR) image. The classical two types of SR methods are mainly based on applying a single image or multiple images captured by a single camera. Microarray camera has the characteristics of small size, multi views, and the possibility of applying to portable devices. It has become a research hotspot in image processing. In this paper, we propose a SR reconstruction of images based on a microarray camera for sharpening and registration processing of array images. The array images are interpolated to obtain a HR image initially followed by a convolution neural network (CNN) procedure for enhancement. The convolution layers of our convolution neural network are 3×3 or 1×1 layers, of which the 1×1 layers are used to improve the network performance particularly. A bottleneck structure is applied to reduce the parameter numbers of the nonlinear mapping and to improve the nonlinear capability of the whole network. Finally, we use a 3×3 deconvolution layer to significantly reduce the number of parameters compared to the deconvolution layer of FSRCNN-s. The experiments show that the proposed method can not only ameliorate effectively the texture quality of the target image based on the array images information, but also further enhance the quality of the initial high resolution image by the improved CNN.