Pore-scale remaining oil distribution under different pore volume water injection based on CT technology

A water-injection experiment was performed on a water-wet reservoir core plug that was filled with brine first and then displaced by synthetic oil. A X-ray Computed Tomography was used to take snapshots of the process of oil-water displacement at predefined time intervals to characterize the distribution of remaining oil. The quasi-real time images were used to understand the pore-scale phase displacement mechanisms and the distributional pattern of the remaining oil. Four forms of the distributional patterns, i.e. network, porous, isolated and film shape, were observed and analyzed with respect to the injected pore volumes (PV). The results show that with the increased level of water injection, the volume of the oil phase continuously decreases, and the morphology of the oil phase changes from initial continuous network-like to film shape forms. At 15 PV, the network- like remaining oil disappears and transforms into isolated and film-like forms. The statistics of the volume for each form of the remaining oil show that the isolated blobs increase with increasing water injection, by contrast, the average volume of the remaining oil decreases with increasing water injection. The rate of volumetric changes is fast before 5 PV but slow in the later period.Cited as: Liu, Z., Yang, Y., Yao, J., et al. Pore-scale remaining oil distribution under different pore volume water injection based on CT technology. Advances in Geo-Energy Research, 2017, 1(3): 171-181, doi: 10.26804/ager.2017.03.0

Characterization of a Novel, Cold-Adapted, and Thermostable Laccase-Like Enzyme With High Tolerance for Organic Solvents and Salt and Potent Dye Decolorization Ability, Derived From a Marine Metagenomic Library

Synthetic dyes are widely used in many industries, but they cause serious environmental problems due to their carcinogenic and mutagenic properties. In contrast to traditional physical and chemical treatments, biodegradation is generally considered an environmental-friendly, efficient, and inexpensive way to eliminate dye contaminants. Here, a novel laccase-like enzyme Lac1326 was cloned from a marine metagenomic library. It showed a maximum activity at 60°C, and it retained more than 40% of its maximal activity at 10°C and more than 50% at 20–70°C. Interestingly, the laccase behaved stably below 50°C, even in commonly used water-miscible organic solvents. The enzyme decolorized all tested dyes with high decolorization efficiency. This thermostable enzyme with high decolorization activity and excellent tolerance of organic solvents and salt has remarkable potential for bioremediation of dye wastewater. It is thus proposed as an industrial enzyme

Electrical Conductivity and Photodetection in 3D‐Printed Nanoporous Structures via Solution‐Processed Functional Materials

3D-printed conductive structures are highly attractive due to their great potential for customizable electronic devices. While the traditional 3D printing of metal requires high temperatures to sinter metal powders or polymer/metal composites, low or room temperature processes will be advantageous to enable multi-material deposition and integration of optoelectronic applications. Herein, digital light processing technology and inkjet printing are combined as an effective strategy to fabricate customized 3D conductive structures. In this approach, a 3D-printed nanoporous (NPo) polymeric material is used as a substrate onto which a nanoparticle-based Ag ink is printed. SEM and X-ray nano computed tomography (nanoCT) measurements show that the porous morphology of the pristine NPo is retained after deposition and annealing of the Ag ink. By optimizing the deposition conditions, conductive structures with sheet resistance <2 Ω sq−1 are achieved when annealing at temperatures as low as 100 °C. Finally, the integration of an inkjet-printed photodetector is investigated based on an organic semiconductor active layer onto the NPo substrate. Thus, the potential of this approach is demonstrated for the additive manufacturing of functional 3D-printed optoelectronic devices

A unified neurocognitive model of semantics language social behaviour and face recognition in semantic dementia

Funder: Chinese Scholarship CouncilFunder: National Key R&D Program of China (2016YFC1306305)Funder: ERC grant (GAP: 670428 - BRAIN2MIND_NEUROCOMP)Abstract: The anterior temporal lobes (ATL) have become a key brain region of interest in cognitive neuroscience founded upon neuropsychological investigations of semantic dementia (SD). The purposes of this investigation are to generate a single unified model that captures the known cognitive-behavioural variations in SD and map these to the patients’ distribution of frontotemporal atrophy. Here we show that the degree of generalised semantic impairment is related to the patients’ total, bilateral ATL atrophy. Verbal production ability is related to total ATL atrophy as well as to the balance of left > right ATL atrophy. Apathy is found to relate positively to the degree of orbitofrontal atrophy. Disinhibition is related to right ATL and orbitofrontal atrophy, and face recognition to right ATL volumes. Rather than positing mutually-exclusive sub-categories, the data-driven model repositions semantics, language, social behaviour and face recognition into a continuous frontotemporal neurocognitive space

Superpixel-Based Classification Using K Distribution and Spatial Context for Polarimetric SAR Images

Classification techniques play an important role in the analysis of polarimetric synthetic aperture radar (PolSAR) images. PolSAR image classification is widely used in the fields of information extraction and scene interpretation or is performed as a preprocessing step for further applications. However, inherent speckle noise of PolSAR images hinders its application on further classification. A novel supervised superpixel-based classification method is proposed in this study to suppress the influence of speckle noise on PolSAR images for the purpose of obtaining accurate and consistent classification results. This method combines statistical information with spatial context information based on the stochastic expectation maximization (SEM) algorithm. First, a modified simple linear iterative clustering (SLIC) algorithm is utilized to generate superpixels as classification elements. Second, class posterior probabilities of superpixels are calculated by a K distribution in iterations of SEM. Then, a neighborhood function is defined to express the spatial relationship among adjacent superpixels quantitatively, and the class posterior probabilities are updated by this predefined neighborhood function in a probabilistic label relaxation (PLR) procedure. The final classification result is obtained by the maximum a posteriori decision rule. A simulated image, a spaceborne RADARSAT-2 image, and an airborne AIRSAR image are used to evaluate the proposed method, and the classification accuracy of our proposed method is 99.28%, 93.16% and 89.70%, respectively. The experimental results indicate that the proposed method obtains more accurate and consistent results than other methods

颐和“智”苑

Yizhiyuan can control lighting, fans, air conditioning, ambient lights, TV, curtains and other furniture, and can also adjust the brightness, speed, volume, lighting mode and so on.And equipped with intelligent voice recognition for control, more convenient.Through the PC, the intelligent living system can locate the living location, detect smoke, gas concentration, light intensity, temperature and humidity, control the switch of the master bedroom light, living room light, hall light and curtain by voice, as well as weather monitoring function.Users can view the data detected by the sensor nodes and the status of home appliances through the "YiheZhiyuan" APP installed on the mobile platform, and adjust the status of home appliances at the same time

基于物联网技术的智疗手环系统设计

This paper introduces the design of intelligent Therapy Bracelet system based on Internet of things technology. The smart Therapy Bracelet system mainly realizes the functions of blood pressure detection, blood pressure value viewing, historical blood pressure value viewing, peripheral services, personal information, account setting, etc. Firstly, the research background and demand analysis of the intelligent Therapy Bracelet system are analyzed, and then the function modules of the system are designed. Finally, the hardware is selected and designed according to the required functions and performance requirements, and the system functions are realized. Through the test, the system runs well, can achieve the expected goal, and has good application value