Continuously Tunable Wettability by Using Surface Patterned Shape Memory Polymers with Giant Deformability

Designing smart surfaces with tunable wettability has drawn much attention in recent years for academic research and practical applications. Most of the previous methods to achieve such surfaces demand some particular materials that inherently have special features or complicated structures which are usually not easy to obtain. A novel strategy to achieve such smart surfaces is proposed by using the surface patterned shape memory polymers of chemically crosslinked polycyclooctene which shows a giant deformability of up to ≈730% strain. The smart surfaces possess the ability to continuously tune the wettability by controlling the recovery temperature and/or time. Coating the modified titanium dioxide nanoparticles onto such surfaces renders the surface superhydrophobicity and expands the tunable range of contact angles (CAs). Theoretical calculations of the CAs at different strains via modified Cassie model well explain the tunable wettability behaviors of such smart surfaces.     

A Dynamically Tunable,Bioinspired Micropatterned Surface Regulates Vascular Endothelial and Smooth Muscle Cells Growth at Vascularization

Regulation of the growth of vascular endothelial cells (ECs) and smooth muscle cells (SMCs) with artificial vascular grafts at vascularization is well‐known to regenerate functional blood vessels for treating cardiovascular disease; however, little research has been published on this subject. Here, a novel polymer vascular graft is presented, whose inner surface contains an assembled circular microgroove pattern decorated with a combination of concentric circular microgrooves and radial, straight microgrooves inspired by the orientation of SMCs and ECs in natural tissues. The surface micropatterns can produce dynamically tunable variations via the thermally switched shape memory. The results from the in vitro EC/SMC co‐cultures reveal that the surface micropatterns have a great capacity to regulate the specific distribution of ECs/SMCs because the ECs grow along the radial, straight microgrooves and the SMCs grow along concentric circular microgrooves. The in vivo vascularization is further analyzed by implanting the vascular graft in the rabbit carotid artery. Both histological analysis and immunofluorescence staining demonstrate that it is capable of highly effectively capturing ECs and SMCs in the blood and subsequent regeneration of new blood vessels. Therefore, this study opens a new possibility for regenerating neovessels to replace and repair damaged vessels for cardiovascular diseases treatment.     

Teams in cooperating grammar systems

Abstract

We consider grammar systems in which several components are active at the same moment (a team of components is working). The power of such mechanisms is investigated and it is found that in many cases the team feature increases the generative capacity of grammar systems. In the so-called t-mode of derivation (a team works as much as it can) it is found that the team size does not induce an infinite hierarchy of languages. However, the family obtained in this case is a full abstract family of languages properly including ETOL.     

液固交互过程中固体破碎现象的实时模拟

提出一种适用于液固交互过程中的固体破碎模拟方法.针对传统液固交互边界处理算法复杂,难以实时模拟固体破碎的缺陷,本文基于SPH算法,提出对液体与固体使用统一的粒子表示,将预测校正方案应用于处理液固交互过程中固体之间的碰撞问题,从而将固体破碎过程简化为固体碎片边界粒子生成的过程,并使用形状匹配算法对固体碎片进行形状约束.实验结果证明,采用文中方法能够实时模拟出液固交互过程中,细节丰富的固体破碎现象,效果真实.     

基于无参数形状检测子和DT-CWT的交通标志识别

针对车辆行驶环境中难以检测的交通标志,提出了一种检测和识别方法.首先分割交通标志的特征颜色区域,并扩展感兴趣区域,提取区域边缘.然后用直线分割和杂点去除粗略划分边缘,根据直线间顶点处的曲率关系,计算转向角并分类顶点的类型,用无参数形状检测子来检测图像中的圆形、三角形和矩形等.将检测到的候选区域送入形状分类器中,分类形状并排除杂质的干扰,最后通过二元树复小波变换和二维独立分量分析相结合来识别交通标志类型.实验结果表明提出的方法对交通标志被遮挡、光照不均匀、颜色部分失真的情况下,检测率和识别率均较高,并且可以达到实时处理的效果.     

粒子群优化算法在船型优化设计中的应用仿真

研究船舶外形结构优化设计,由于船舶在航行过程中,不同型号的船舶机动性能力和稳定性存在着较大差异,造成船舶外形的梯度信息突变明显.传统的优化设计方法多是基于梯度信息的优化设计方法,在船舶外形结构梯度发生突变的情况下,很容易陷入梯度差过大,结果不收敛,造成外形设计的缺陷较为明显.为解决上述问题,提出一种基于粒子群优化算法的船舶外形优化设计,利用粒子群的搜索能力,对设计结构中的参数进行最优搜索.针对船舶外形梯度信息差异大,很难小范围收敛的问题,通过遗传算法对其进行优化,使得参数在小范围内也能实现最优化.保证设计结果的稳定,仿真结果表明,改进算法设计的船舶外形参数在升力、阻力和升阻比等参数上有了较为明显的优化,在全航行周期中具有更优的性能.     

形状和颜色混合不变量在图像检索中的应用

多视觉特征的图像检索是当前基于内容的图像检索领域的重要方向.已有的多特征的检索主要通过线性加权的方法对特征进行组合,但这种组合方式仅实现了代数意义上的合并,未能真正利用和发掘特征间存在的相互关系,并且权重值不容易确定,检索结果易受权重值的影响.针对这一问题,提出一种形状-颜色混合不变特征的构造方法,特征提取的过程包含同时对形状、颜色信息的抽取,直接构造出能够同时对形状仿射变换和颜色对角-偏移变换具有不变性的特征,也称作形状-颜色矩不变量.首先分别在图像的2维几何空间、3维颜色空间定义形状核、颜色核,然后对形状核、颜色核的乘积进行多重积分,最后做规范化,就得到一个不变量.理论上,通过选择不同的形状核、颜色核可以推导出无穷多的不变量.实验结果表明,该方法优于加权组合特征的方法;与加权特征、局部特征相比,形状-颜色矩不变量对于同一物体不同成像条件下的近复制图像、整体属性相似的图像、大体类似的物体图像等表现出较高的检索性能及效率.     

视频检测烟雾的研究现状

检测烟雾可以预警火灾,通过视觉监控烟雾比其它方式监控范围更广、反应更灵敏、对环境要求更低。但是目前的烟雾检测算法,无论是利用单一的色彩、纹理、形状、飘动性、闪烁以及频率等特征,或者要求满足多样特征或者采用支持向量机、神经网络、Bayesian等分类器的方法,都无法保证判断的准确性、适应性和快速性。本文综述了各种烟雾检测的方法后,认为要得到更加可靠的检测效果,一方面需要更加本质的烟雾特征,另一方面要对已有的特征进行更深入的实验验证,同时也要有更全面的样本视频数据库和算法评价标准。