Fabrication of Crack-free Photonic Crystal Films on Superhydrophobic Nanopin Surface

厦门大学生物仿生及软物质研究院林友辉副教授以及院长刘向阳教授在利用超疏水基底改善胶体小球自组装研究方向取得进展。 目前通过胶体小球自组装方法已构筑了许多复杂却高度有序的光子晶体。但是胶体小球在形成有序结构过程中会不可避免的产生收缩和应力，该方法通常会导致裂纹和缺陷的形成，降低了光子晶体的光学质量，也同时限制了其进一步的应用。 在该研究中，作者基于以上的研究现状，以纳米针状的超疏水表面为基底，来改善胶体小球的自组装，可以减少甚至消除大尺度的裂纹的效果。基于该原理，最后成功制备出厘米级别无裂纹的光子晶体薄膜。【Abstract】sed on their superior optical performance, photonic crystals (PCs) have been investigated as excellent candidates for widespread applications including sensors, displays, separation processes, and catalysis. However, fabrication of large-area PC assemblies with no defects and structurally controllable is still a tough task. Herein, we develop an effective strategy for preparing centimeter-scale crack-free photonic crystals films by the combined effects of soft assembly and superhydrophobic nanopin surfaces. Owing to its large contact angle and low adhesive force on the superhydrophobic substrate, the colloidal suspension exhibits a continuous retraction of the three-phase (gas−liquid−solid) contact line(TCL) in the process of solvent (water molecules) evaporation. The constantly receding TCL can bring the colloidal spheres closer to each other, which could timely close the gaps due to the loss of water molecules. As a result, close-packed and well-ordered assembly structures can be easily obtained. We expect that this work may pave the way to utilize novel superhy drophobic materials for designing and developing high-quality PCs and to apply PCs in different fields.This work is financially supported by National Nature Science Foundation (Nos. 21401154,U1405226), 111 project (B16029), Guangdong Natural Science Foundation (2014A030310005),the Fundamental Research Funds for the Central Universities of China (Nos. 20720170011,20720140528), Ph.D. Programs Foundation of Ministry of Education of China(20130121110018), Fujian Provincial Department of Science & Technology (2014H6022).X.Y.L.'s primary affiliation is the Department of Physics, National University of Singapore

上转换荧光点亮软物质体内成像新思路

传统的非侵入性活体生物成像技术主要是基于计算机断层扫描和核磁共振成像等技术，这些技术由于其相对较低的分辨率和对组织的损伤而受到限制。通过从介观尺度将稀土上转换纳米颗粒均匀地组装到丝素蛋白生物支架，使其具备在近红外激发下产生可见光波段发射光的上转换荧光性能。该团队使用低功率连续980 nm波长的近红外激光穿透大鼠皮肤和组织、激发植入的蚕丝丝素生物支架，产生可见光（绿光）图像。揭示了蚕丝生物支架的生物相容性、力学性能和生物降解性，以及组织细胞与生物支架的相互作用。丝素蛋白生物支架是一种软物质，上转换荧光技术为体内软物质成像提供了新思路。【中文摘要】首次采用上转换荧光技术实现了丝素蛋白生物支架体内生物成像，解决了传统体内软物质材料生物成像难以实现实时、高分辨、深穿透和低损伤的局限。【Abstract】In biomedical applications, it is very desirable to monitor the in vivo state of implanted devices, i.e., tracking the location, the state, and the interaction between the implanted devices and cell tissues. To achieve this goal, a generic strategy of soft materials meso-functionalization is presented. This is to acquire silk fibroin (SF) materials with added functions, i.e., in vivo bioimaging/sensing. The functionalization is by 3D materials assembly of functional components, lanthanide(Ln)-doped upconversion nanoparticles (UCNPs) on the mesoscopic scale to acquire upconversion fluorescent emission. To implement the meso-functionalization, the surfaces of UCNPs are modified by the hydroxyl groups (—OH) from SiO2 or polyethylene glycol coating layers, which can interact with the carbonyl groups (C==O) in SF scaffolds. The functionalized silk scaffolds are further implanted subcutaneously into mice, which allows the silk scaffolds to have fluorescent in vivo bioimaging and other biomedical functions. This material functionalization strategy may lead to the rational design of biomaterials in a more generic way.The work was supported by the 111 Project (Grant No. B16029), National Natural Science Foundation of China (Grant Nos. 21404087, 61674050, and U1405226), Fujian Provincial Department of Science and Technology (Grant Nos. 2017J06019, 2014H6022, and 2015J05109), Natural Science Foundation of Guangdong Province (Grant No. 2015A030310007), 1000 Talents Program, and President Foundation from Xiamen University (Grant No. 20720160088), NUS tear 1 funding (WBS: R-144-000-367-112)

Realising advanced risk-based port state control inspection using data-driven Bayesian networks

In the past decades, maritime transportation not only contributes to economic prosperity, but also renders many threats to the industry, causing huge casualties and losses. As a result, various maritime safety measures have been developed, including Port State Control (PSC) inspections. In this paper, we propose a data-driven Bayesian Network (BN) based approach to analyse risk factors influencing PSC inspections, and predict the probability of vessel detention. To do so, inspection data of bulk carriers in seven major European countries from 2005 to 2008 1 in Paris MoU is collected to identify the relevant risk factors. Meanwhile, the network structure is constructed via TAN learning and subsequently validated by sensitivity analysis. The results reveal two conclusions: first, the key risk factors influencing PSC inspections include number of deficiencies, type of inspection, Recognised Organisation (RO) and vessel age. Second, the model exploits a novel way to predict the detention probabilities under different situations, which effectively help port authorities to rationalise their inspection regulations as well as allocation of the resources. Further effort will be made to conduct contrastive analysis between ‘Pre-NIR’ period and ‘Post-NIR’ period to test the impact of NIR started in 2008. © 2018 Elsevier Lt

ACT001 improved cardiovascular function in septic mice by inhibiting the production of proinflammatory cytokines and the expression of JAK-STAT signaling pathway

Sepsis is a life-threatening multiple organ dysfunction syndrome (MODS) caused by a microbial infection that leads to high morbidity and mortality worldwide. Sepsis-induced cardiomyopathy (SIC) and coagulopathy promote the progression of adverse outcomes in sepsis. Here, we reported that ACT001, a modified compound of parthenolide, improved the survival of sepsis mice. In this work, we used cecal ligation and puncture (CLP) model to induce SIC. Transthoracic echocardiography and HE staining assays were adopted to evaluate the influence of ACT001 on sepsis-induced cardiac dysfunction. Our results showed that ACT001 significantly improved heart function and reduced SIC. Coagulation accelerates organ damage in sepsis. We found that ACT001 decreased blood clotting in the FeCl3-induced carotid artery thrombosis experiment. ACT001 also reduced the production of neutrophil extracellular traps (NETs). RNA-sequencing of heart tissues revealed that ACT001 significantly downregulated the expression of pro-inflammatory cytokines and the JAK-STAT signaling pathway. These results were confirmed with real-time PCR and ELISA. In summary, we found ACT001 rescued mice from septic shock by protecting the cardiovascular system. This was partially mediated by inhibiting pro-inflammatory cytokine production and down-regulating the JAK-STAT signaling

A risk-based game model for rational inspections in port state control

This paper analyses the game relationship between port authorities and ship owners under the new inspection regime (NIR). Based on 49328 inspection reports from Paris Memorandum of Understanding (MoU) (2015-2017), we present a Bayesian Network (BN) model to determine vessel detention rates after adding company performance as a new indicator in PSC inspection. A strategic game model is formulated by incorporating the BN model outcomes. The optimal inspection rate from the game model can help improve port authority performance in PSC. An empirical study is conducted to illustrate the insights of the results and provide suggestions for port authorities

Control Information Acquisition and Processing of the AMT System Based in LabVIEW and MATLAB

Part 6: Intelligent RobotInternational audienceIn this paper, the information acquisition and processing system is proposed for the automated mechanical transmission (AMT) control by LabVIEW and MATLAB. Firstly, an interface of the data acquisition was designed with the automated mechanical transmission system based in LabVIEW. Secondly, the data acquisition hardware was built by employing the single chip system incorporating with necessary sensors. Thirdly, the data acquired was transmitted into the data processing system built by MATLAB. By using the data processing system, the transmission status and driving parameters was presented in MATLAB which can be viewed easily and ready to be utilized further more

Pedestrian Navigation Method Based on Machine Learning and Gait Feature Assistance

In recent years, as the mechanical structure of humanoid robots increasingly resembles the human form, research on pedestrian navigation technology has become of great significance for the development of humanoid robot navigation systems. To solve the problem that the wearable inertial navigation system based on micro-inertial measurement units (MIMUs) installed on feet cannot effectively realize its positioning function when the body movement is too drastic to be measured correctly by commercial grade inertial sensors, a pedestrian navigation method based on construction of a virtual inertial measurement unit (VIMU) and gait feature assistance is proposed. The inertial data from different positions of pedestrians’ lower limbs are collected synchronously via actual IMUs as training samples. The nonlinear mapping relationship between inertial information from the human foot and leg is established by a visual geometry group-long short term memory (VGG-LSTM) neural network model, based on which the foot VIMU and virtual inertial navigation system (VINS) are constructed. The VINS experimental results show that, combined with zero-velocity update (ZUPT), the integrated method of error modification proposed in this paper can effectively reduce the accumulation of positioning errors in situations where the gait type exceeds the measurement range of the inertial sensors. The positioning performance of the proposed method is more accurate and stable in complex gait types than that merely using ZUPT