Organic mesh template-based laminated object manufacturing to fabricate ceramics with regular micron scaled pore structures

A new aqueous slurry-based laminated object manufacturing process for porous ceramics is proposed: firstly, an organic mesh sheet is pre-paved as a pore-forming template before slurry layer scraping; secondly, the 2D pattern is built with laser outline cutting of the dried mesh–ceramic composite layer; finally, the pore structure is formed after degreasing and sintering. Alumina parts with porosities of 51.5 %, round hole diameters of 80 ± 5 μm were fabricated using 70 wt. % solid content slurry and 100 mesh nylon net. Using an organic mesh as the framework and template not only reduces the risk of damage of the green body but also ensures the regularity, uniformity and connectivity of the micron scaled pore network. The layer-by-layer drying method avoids the delamination phenomenon and improves the paving density. The new method can realize the flexible design of the pore structure by using various organic mesh templates.     

射线照相检测及质量评定虚拟仿真实验系统开发

在射线检测原理与方法的基础上,开发了一套基于计算机和信息技术的射线照相检测及质量评定虚拟仿真实验系统,可还原射线照相检测及质量评定的真实情境,直观反映射线照检测设备、工艺、人员和各环节的状态和参与过程,可以激发学生的学习兴趣与爱好,提高学生发现问题、分析问题和解决问题的能力.     

Spatiotemporal Magnetocaloric Microenvironment for Guiding the Fate of Biodegradable Polymer Implants

The degradation behavior of implants is significantly important for bone repair. However, it is still unprocurable to spatiotemporally regulate the degradation of the implants to match bone ingrowth. In this paper, a magneto-controlled biodegradation model is established to explore the degradation behavior of magnetic scaffolds in a magnetothermal microenvironment generated by an alternating magnetic field (AMF). The results demonstrate that the scaffolds can be heated by magnetic nanoparticles (NPs) under AMF, which dramatically accelerated scaffold degradation. Especially, magnetic NPs modified by oleic acid with a better interface compatibility exhibit a greater heating efficiency to further facilitate the degradation. Furthermore, the molecular dynamics simulations reveal that the enhanced motion correlation between magnetic NPs and polymer matrix can accelerate the energy transfer. As a proof-of-concept, the feasibility of magneto-controlled degradation for implants is demonstrated, and an optimizing strategy for better heating efficiency of nanomaterials is provided, which may have great instructive significance for clinical medicine.     

A Highly Sensitive,Reversible, and Bidirectional Humidity Actuator by Calcium Carbonate Ionic Oligomers Incorporated Poly(Vinylidene Fluoride)

Sensitivity and multi-directional motivation are major two factors for developing optimized humidity-response materials, which are promising for sensing, energy production, etc. Organic functional groups are commonly used as the water sensitive units through hydrogen bond interactions with water molecules in actuators. The multi-coordination ability of inorganic ions implies that the inorganic ionic compounds are potentially superior water sensitive units. However, the particle forms of inorganic ionic compounds produced by classical nucleation limit the number of exposed ions to interact with water. Recent progress on the inorganic ionic oligomers has broken through the limitation of classical nucleation, and realized the molecular-scaled incorporation of inorganic ionic compounds into an organic matrix. Here, the incorporation of hydrophilic calcium carbonate ionic oligomers into hydrophobic poly(vinylidene fluoride) (PVDF) is demonstrated. The ultra-small calcium carbonate oligomers within a PVDF film endow it with an ultra-sensitive, reversible, and bidirectional response. The motivation ability is superior to other bidirectional humidity-actuators at present, which realizes self-motivation on an ice surface, converting the chemical potential energy of the humidity gradient from ice to kinetic energy.     

Reducing web latency with coding-based fast multi-path loss recovery

Wireless Networks - TCP latency is critical to the performance of Web services. However, packet loss greatly impairs the TCP performance due to its poor loss recovery mechanisms. Recent work FUSO...     

基于度量学习的意图识别和槽填充方法

人机对话中小样本学习场景下的意图识别和槽填充,是自然语言处理的一个重要课题.本文采用基于度量学习的方法,通过计算query set中的样本与support set中样本的距离,寻找距离最近的类别样本作为分类标签,同时将两个任务联合进行训练,用以提升模型的效果.从实验结果中可以得出,本文提出的Fine-tune方法,对意图识别和槽填充任务都有一定的帮助和提升.胶囊网络在意图识别中也起到了一定的效果,可以帮助去除一部分无关信息,但对槽填充任务的帮助不明显;而任务自适应的投影网络,可以更好地将不同类的向量分开,提升了两个任务的性能.