Effects of Undercooling and Transformation Time on Microstructure and Strength of Fe–C–Mn–Si Superbainitic Steel

Strength of Materials - A metallographic method, dilatometry, and X-ray diffraction were applied to investigate the effects of undercooling and holding time on bainitic transformation,...     

A lightweight autonomous MAV for indoor search and rescue

Micro Aerial Vehicles (MAVs) have great potentials to be applied for indoor search and rescue missions. In this paper, we propose a modular lightweight design of an autonomous MAV with integrated hardware and software. The MAV is equipped with the 2D laser scanner, camera, mission computer and flight controller, running all the computation onboard in real time. The onboard perception system includes a laser‐based SLAM module and a custom‐designed visual detection module. A dual Kalman filter design provides robust state estimation by multiple sensor fusion. Specifically, the fusion module provides robust altitude measurement in the circumstance of surface changing. In addition, indoor‐outdoor transition is explicitly handled by the fusion module. In order to efficiently navigate through obstacles and adapt to multiple tasks, a task tree‐based mission planning method is seamlessly integrated with path planning and control modules. The MAV is capable of searching and rescuing victims from unknown indoor environments effectively. It was validated by our award‐winning performance at the 2017 International Micro Air Vehicle Competition (IMAV 2017), held in Toulouse, France. The performance video is available on https://youtu.be/8H19ppS_VXM .     

基于桥连接的词典学习方法的语义解析

现阶段的语义解析方法大部分都基于组合语义,这类方法的核心就是词典。词典是词汇的集合,词汇定义了自然语言句子中词语到知识库本体中谓词的映射。语义解析一直面临着词典中词汇覆盖度不够的问题。针对此问题,该文在现有工作的基础上,提出了基于桥连接的词典学习方法,该方法能够在训练中自动引入新的词汇并加以学习,为了进一步提高新学习到的词汇的准确度,该文设计了新的词语—二元谓词的特征模板,并使用基于投票机制的核心词典获取方法。该文在两个公开数据集(WebQuestions和Free917)上进行了对比实验,实验结果表明,该文方法能够学习到新的词汇,提高词汇的覆盖度,进而提升语义解析系统的性能,特别是召回率。     

Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.

     

Sintering behaviour of fluorapatite–silicate composites produced from natural fluorapatite and quartz

In this work, the sintering behaviour of fluorapatite (FAp)–silicate composites prepared by mixing variable amounts of natural quartz (2.5 wt% to 20 wt%) and FAp was studied. The composites were pressureless sintered in air at temperatures from 1000 °C to 1350 °C. The effects of temperatures on the densification, phase formation, chemical bonding and Vickers hardness of the composites were evaluated. All the samples exhibited mixed phase, comprising FAp and francolite as the major constituents along with some minor phases of cristobalite, wollastonite, dicalcium silicate and/or whitlockite dependent on the quartz content and sintering temperature. The composite containing 2.5 wt% quartz exhibited the best sintering properties. The highest bulk density of 3 g/cm³ and a Vickers hardness of >4.2 GPa were obtained for the 2.5 wt% quartz–FAp composite when sintered at 1100 °C. The addition of quartz was found to alter the microstructure of the composites, where it exhibited a rod-like morphology when sintered at 1000 °C and a regular rounded grain structure when sintered at 1350 °C. A wetted grain surface was observed for composites containing high quartz content and was believed to be associated with a transient liquid phase sintering.     

Biodegradation of poly(lactic acid)—cassava bagasse composites produced by injection molding

Neat poly (lactic acid) (PLA) and PLA/cassava bagasse (CB) composites were used to produce seedling tubes by extrusion and injection molding. The tubes were buried in simulated soil, and their biodegradation was investigated by weight loss, scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR). After 180 days, the composites' biodegradation was higher than neat PLA material, and the higher the CB content, the higher the biodegradation, which caused fissures and voids in the material. The biodegradation of PLA/CB composites increased the phosphorus content in the soil after 180 days. Composites of PLA with CB, an abundant agro-industrial residue in Brazil, are promising because they can reduce the environmental impact due to CB's proper destination, and the composites' costs and biodegradation are faster than pure PLA material. Both the faster biodegradation of the tube and the higher P content are advantageous for seedling tubes.     

Pull-Down of Metalloproteins in Their Native States by Using Desthiobiotin-Based Probes

One-third of all proteins are estimated to require metals for structural stability and/or catalytic activity. Desthiobiotin probes containing metal binding groups can be used to capture metalloproteins with exposed active-site metals under mild conditions so as to prevent changes in metallation state. The proof-of-concept was demonstrated with carbonic anhydrase (CA), an open active site, Zn²⁺-containing protein. CA was targeted by using sulfonamide derivatives. Linkers of various lengths and structures were screened to determine the optimal structure for capture of the native protein. The optimized probes could selectively pull down CA from red blood cell lysate and other protein mixtures. Pull-down of differently metallated CAs was also investigated.