Thermal and mechanical properties of epoxy composites reinforced by a natural hydrophobic sand

If a low weight percentage of crude fine fillers can improve properties of polymer materials directly without complicated chemical treatment process involved, it will be significant for many industrial applications. Our previous study indicated that a kind of Cancun natural sand could be an effective filler material for polymer composites. In this current work, the epoxy composites reinforced by this kind of natural sand particles were prepared and thermal and mechanical properties of the composites containing up to 5 wt % of the sand particles were characterized. Results showed that the highest flexural strength appears in the epoxy composite containing 1 wt % sand particles. A damage model was used to interpret the flexural properties, which showed an acceptable agreement with the experimental results. The glass transition temperature, high temperature storage modulus, and dimensional stability of the sand/epoxy composites monotonically increased with the addition of the sand particles. The sand particle/epoxy composites also displayed a noticeable enhancement in thermal conductivity. Theoretical analysis showed that in addition to conduction, other heat transport mechanisms played roles in the improved heat transmission through the composites. As a natural porous micron-scale material, Cancun sand has the potential for applications in cost-effective composites with enhanced mechanical and thermal properties. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

管线油电损耗的灰色模型及预测

对于管道运输来说，影响输油成本变化的因素有很多，但是对总成本影响最大的是油电损耗费用。由于来自现场的输量和相关参数样本数据不足，只知道连续几年的流量、油电损耗，要预测将来每年的油电损耗，经典经济数学不能满足这样的研究。然而灰色系统理论要求的研究样本较少，只要知道连续几年的流量、油电损耗，就能预测将来每年的油电损耗，估算其输油成本，且模型精度较高。利用灰色系统理论，以输油管线每年的输量、相应的电耗和油耗为时间序列，建立了三元素非等间距GM(1，1)模型，该模型为预测管线年输油成本提供了可靠的依据。     

气侵检测仪的研制与应用

基于气体侵入井眼后按气液两相流型分布的原理，利用声波可以早期检测到气侵。文章对气侵进行了深入研究，研制了声波气侵检测仪，做到了生产过程中早期气侵检测，以避免井喷的发生，并及时发现油气层。     

大比例尺地质剖面图第一条标高基线绘制方法的探讨

介绍了大比例尺地质剖面图第一条标高基线的几种绘制方法，总结了绘制经验。     

Neuronal units linked to microvascular modules in cerebral cortex: response elements for imaging the brain

How neuronal activity changes cerebral blood flow is of biological and practical importance. The rodent whisker-barrel system has special merits as a model for studies of changes in local cerebral blood flow (LCBF). Stimulus-evoked changes in neural firing and 'intrinsic signals' recorded through a cranial window were used to define regions of interest for repeated flow measurements. Whisker-activated changes in flow were measured with intravascular markers at the pia. LCBF changes were always prompt and localized over the appropriate barrel. Stimulus-related changes in parenchymal flow monitored continuously with H2 electrodes recorded short latency flow changes initiated in middle cortical layers. Activation that increased flow to particular barrels often led to reduced flow to adjacent cortex. Dye was injected into single penetrating arterioles from the pia of the fixed brain and injected into arterioles in slices of cortex where barrels were evident without stains. Arteriolar and venular domains at the surface were not directly related to underlying barrels. Capillary tufts in layer IV were mainly coincident with barrels. The matching between a capillary plexus (a vascular module) and a barrel (a functional neuronal unit) is a spatial organization of neurons and blood vessels that optimizes local interactions between the two. The paths of communication probably include: neurons to neurons, neurons to glia, neurons to vessels, glia to vessels, vessels to vessels and vessels to brain. Matching a functional grouping of neurons with a vascular module is an elegant means of reducing the risk of embarrassment for energy-expensive neuronal activity (ion pumping) while minimizing energy spent for delivery of the energy (cardiac output). For imaging studies this organization sets biological limits to spatial, temporal and magnitude resolution. Reduced flow to nearby inactive cortex enhances local differences.     

ASRNet: Adversarial Segmentation and Registration Networks for Multispectral Fundus Images

Multispectral imaging (MSI) technique is often used to capture images of the fundus by illuminating it with different wavelengths of light. However, these images are taken at different points in time such that eyeball movements can cause misalignment between consecutive images. The multispectral image sequence reveals important information in the form of retinal and choroidal blood vessel maps, which can help ophthalmologists to analyze the morphology of these blood vessels in detail. This in turn can lead to a high diagnostic accuracy of several diseases. In this paper, we propose a novel semi-supervised end-to-end deep learning framework called “Adversarial Segmentation and Registration Nets” (ASRNet) for the simultaneous estimation of the blood vessel segmentation and the registration of multispectral images via an adversarial learning process. ASRNet consists of two subnetworks: (i) A segmentation module S that fulfills the blood vessel segmentation task, and (ii) A registration module R that estimates the spatial correspondence of an image pair. Based on the segmention-driven registration network, we train the segmentation network using a semi-supervised adversarial learning strategy. Our experimental results show that the proposed ASRNet can achieve state-of-the-art accuracy in segmentation and registration tasks performed with real MSI datasets.     

即时定向新闻采集技术研究

互联网的迅速发展带动了信息量的爆炸性增加。如何更快地采集所需信息一直是国内外研究和开发的热点。近年来,不断增长的对特定信息(例如特定领域的新闻)的需求要求有针对性地从指定的网站即时采集相关信息。这些新闻一般具有不可预见性、更新频率较快、时效性强等特点。这要求我们必须能针对这些特点实现即时定向的采集。本文提出了一种有效抓取网页并进行分析的方法,实践表明取得了满意的效果。     

Bioderived Bilayer Shell Modification β-FeOOH Nanorods via Self-Assembly Technique as Sustainable Flame Retardants for Enhancing Flame Retardancy of Epoxy Resin

The design and application of bioderived flame retardants have been widely conducted to meet the concept of green and sustainable development. Here, self-assembly technique is used to prepare core–shell bioderived additives by using β-FeOOH as the core and polydopamine (PDA)/tannic acid (TA) bilayer as the shell, following adsorption of nickel ions to enhance the thermal stability, flame retardancy, and mechanical properties of epoxy resin (EP). The molecular structure of biobased resources is rich in hydroxyl groups and carbon content, which can be dehydrated and carbonized during combustion and promote the formation of robust protective char layer. With the addition of 5 wt% β-FeOOH@PTNi, the EP composites can pass V-0 rating in the UL-94 test. The peak heat release rate and total heat release decrease by 28.4% and 17.4% compared with pure EP. The bioderived nanorods can capture the oxygen free radicals, contributing to flame retarding in gaseous phase. Thus, the release of high-toxic CO and flammable gaseous is significantly suppressed. Besides, the storage modulus of EP composites increases by 16.0% with the addition of 5% β-FeOOH@PTNi compared with pure EP. This work provides a sustainable methodology for the design of bioderived flame retardants for EP.     

改性聚丙烯酰胺水溶液的疏水缔合性质

合成了一种疏水缔合水溶性聚丙烯酰胺共聚物，使用荧光光谱法并结合紫外及流变性实验，对制备的疏水缔合水溶性聚丙烯酰胺共聚物在水溶液中形成疏水微区、超分子聚集体及空间网络结构进行了研究，并用扫描电子显微镜证实了溶液中网络结构的存在．