我国水-能源-粮食耦合关系及影响因素

为缓解我国水、能源和粮食资源紧张问题，促进资源可持续利用，构建水-能源-粮食系统，利用耦合协调度模型对我国的30个省（自治区、直辖市）进行测算,并利用空间杜宾模型分析主要影响因素。结果表明：2003—2017年，我国能源、粮食评价[JP]指数高于水资源评价指数，系统综合评价指数逐年递增；大部分省份耦合协调度处于初级协调水平且呈现逐年上升的态势，个别省份耦合协调度濒临失调；耦合协调度空间自相关性较强，虽有明显波动，但是呈现逐年加强的态势；影响耦合协调度的主要因素有从业人口数、固定资产投资额、人均生产总值、人口总数、[JP]文盲人口占比、工业污染排放、城镇化。     

基于VR技术的智能变电站运行仿真培训系统

为了更加真实、直观地呈现智能变电站的运行整体结构,构建基于VR技术的智能变电站运行仿真培训系统。该系统通过5个模块协同完成智能变电站运行仿真培训,结合实际变电站的设备情况,采用二维纹理映射方法完成变电站设备仿真建模;系统利用虚拟现实交互模块呈现培训场景,参与培训人员能够通过人机交互设备,实现场景漫游和相关培训内容操作。测试结果表明:该系统能够较好地模拟出智能变电站的实际运行情况,参与培训的人员可以身临其境地完成整个变电站的巡视,更真实、直观地呈现智能变电站的整体状态。     

C105管桩混凝土设计参数取值的探讨

通过试验得出了C105混凝土100 mm×100 mm×100 mm立方体非标准试件抗压强度换算系数以及C105混凝土的标准方差和强度变异系数。采用理论计算,得到了棱柱体抗压强度与立方体抗压强度的比值α_c1,并与试验实测平均值进行了比较,验证了理论计算方法的可行性。此外,通过对比分析,探讨了直接外延法和引用公式法两种C105混凝土设计参数计算方法的正确性,研究结果可为C105管桩混凝土的设计和应用提供参考。     

Influence of pressure and dwell time on pressure-assisted sintering of calcium cobaltite

Calcium cobaltite Ca₃Co₄O₉, abbreviated Co349, is a promising thermoelectric material for high-temperature applications in air. Its anisotropic properties can be assigned to polycrystalline parts by texturing. Tape casting and pressure-assisted sintering (PAS) are a possible future way for a cost-effective mass-production of thermoelectric generators. This study examines the influence of pressure and dwell time during PAS at 900°C of tape-cast Co349 on texture and thermoelectric properties. Tape casting aligns lentoid Co349. PAS results in a textured Co349 microstructure with the thermoelectrically favorable ab-direction perpendicular to the pressing direction. By pressure variation during sintering, the microstructure of Co349 can be tailored either toward a maximum figure of merit as required for energy harvesting or toward a maximum power factor as required for energy harvesting. Moderate pressure of 2.5 MPa results in 25% porosity and a textured microstructure with a figure of merit of 0.13 at 700°C, two times higher than the dry-pressed, pressureless-sintered reference. A pressure of 7.5 MPa leads to 94% density and a high power factor of 326 µW/mK² at 800°C, which is 11 times higher than the dry-pressed reference (30 MPa) from the same powder.     

A customized low-rank prior model for structured cartoon–texture image decomposition

The mathematical characterization of the texture component plays an instrumental role in image decomposition. In this paper, we are concerned with a low-rank texture prior based cartoon–texture image decomposition model, which utilizes a total variation norm and a global nuclear norm to characterize the cartoon and texture components, respectively. It is promising that our decomposition model is not only extremely simple, but also works perfectly for globally well-patterned images in the sense that the model can recover cleaner texture (or details) than the other novel models. Moreover, such a model can be easily reformulated as a separable convex optimization problem, thereby enjoying a splitting nature so that we can employ a partially parallel splitting method (PPSM) to solve it efficiently. A series of numerical experiments on image restoration demonstrate that PPSM can recover slightly higher quality images than some existing algorithms in terms of taking less iterations or computing time in many cases.     

Co-precipitation of nano Mg–Y/ZrO2 ternary oxide eutectic system: Effects of calcination temperature

In the family of inorganic nanomaterials, zirconia is a highly promising functional ceramic with a high refractive index, hardness, and dielectric constant, as well as excellent chemical inertness and thermal stability. These properties are enhanced in nano-zirconia ceramics, because nanopowders have a small particle size, good morphology, and uniform and dispersive distribution. In this study, a co-precipitation process was proposed to synthesise highly dispersed MgO–Y₂O₃ co-stabilized ZrO₂ nanopowders. The effects of different calcination temperatures on the crystallisation degree and particle dispersion of zirconia nanopowders were characterised by X-ray diffraction (XRD), thermogravimetry-differential scanning calorimetry (TG-DSC), Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR), nitrogen adsorption using the Brunauer–Emmett–Teller (BET) theory, transmission electron microscopy (TEM), and field emission scanning electron microscopy (FESEM). The optimum synthesis conditions were obtained as follows: 6 h of high-energy planetary grinding and calcination at 800 °C in an electric furnace. Under these optimum conditions, the average particle size of the prepared powder was 28.7 nm. This process enriches the literature on the controllable preparation of Mg–Y/ZrO₂ nanopowders obtained by the co-precipitation method.     

认同度修正下的近相邻改进推荐算法研究

如何融合多方因素准确地为用户提供个性化产品一直是关注的热点问题，由此，一个新的近相邻改进算法融入了大众化认同度和个性化认同度，利于更加高效地挖掘隐藏信息。实验结果表明，相对于传统近相邻算法，认同度修正算法虽然查全率小幅度上下波动，但其他多个评价指标都得到极大提升，假正率和深度有所减少，查准率、[F1]值和提升度得以增加，并且，受试者特征曲线和提升曲线也都说明此修正算法具有更为显著的推荐效果。     

Extrinsic parameter's adjustment and potential implications in Plasmodium falciparum malaria diagnosis

Malaria is a major public health concern, affecting over 3.2 billion people in 91 countries. The advent of digital microscopy and Machine learning with the aim of automating Plasmodium falciparum diagnosis extensively depends on the extracted image features. The color of the cells, plasma, and stained artifacts influence the topological, geometrical, and statistical parameters being used to extract image features. During microscopic image acquisition, custom adjustments to the condenser and color temperature controls often have an influence on the extracted statistical features. But, our human visual system sub-consciously adjusts the color and retains the originality in a different lighting environment. Despite the use of appropriate image preprocessing, findings from the literature indicate that statistical feature variations exist, allowing the risk of P. falciparum misinterpretation. In order to eliminate this pervasive variation, the current work focuses on preprocessing the extracted statistical features rather than the prepossessing of the source image. It begins with the augmentation of series images for a microscopic field by inducing illumination variations during the microscopic image acquisition stage. A set of such image series is analyzed using a Nonlinear Regression Model to generalize the relationship between microscopic images acquired with variable ambient brightness and a specific feature. The projection point of the centroid feature onto the brightness parameter is identified in the model and it is denoted as the optimum brightness factor (OBF). Using the model, the feature correction factor (CF) is calculated from the rate of change of feature values over the interval OBF, and the brightness of the test image is processed. The present work has investigated OBF for selected image textural features, namely Contrast, Homogeneity, Entropy, Energy, and Correlation individually from its co-occurrence matrices. For performance analysis, the best state-of-the-art method uses selected texture as a subset feature to evaluate the effectiveness of P. falciparum malaria classification. Then, the impact of proposed feature processing is evaluated on 274 blood smear images with and without Feature Correction (FC). As a result, the “p” value is less than .05, which leads to the result that it is highly significant and the classification accuracy and F-score of P. falciparum malaria are increased.