Magnetically Guidable Proteinaceous Adhesive Microbots for Targeted Locoregional Therapeutics Delivery in the Highly Dynamic Environment of the Esophagus

The esophagus is a tubular-shaped muscular organ where swallowed fluids and muscular contractions constitute a highly dynamic environment. The turbulent, coordinated processes that occur through the oropharyngeal conduit can often compromise targeted administration of therapeutic drugs to a lesion, significantly reducing therapeutic efficacy. Here, magnetically guidable drug vehicles capable of strongly adhering to target sites using a bioengineered mussel adhesive protein (MAP) to achieve localized delivery of therapeutic drugs against the hydrodynamic physiological conditions are proposed. A suite of highly uniform microparticles embedded with iron oxide (IO) nanoparticles (MAP@IO MPs) is microfluidically fabricated using the genipin-mediated covalent cross-linking of bioengineered MAP. The MAP@IO MPs are successfully targeted to a specific region and prolongedly retained in the tubular-structured passageway. In particular, orally administered MAP@IO MPs are effectively captured in the esophagus in vivo in a magnetically guidable manner. Moreover, doxorubicin (DOX)-loaded MAP@IO MPs exhibit a sustainable DOX release profile, effective anticancer therapeutic activity, and excellent biocompatibility. Thus, the magnetically guidable locomotion and robust underwater adhesive properties of the proteinaceous soft microbots can provide an intelligent modular approach for targeted locoregional therapeutics delivery to a specific lesion site in dynamic fluid-associated tubular organs such as the esophagus.     

Generating Questions Based on Semi-Automated and End-to-End Neural Network

With the emergence of large-scale knowledge base, how to use triple information to generate natural questions is a key technology in question answering systems. The traditional way of generating questions require a lot of manual intervention and produce lots of noise. To solve these problems, we propose a joint model based on semi-automated model and End-to-End neural network to automatically generate questions. The semi-automated model can generate question templates and real questions combining the knowledge base and center graph. The End-to-End neural network directly sends the knowledge base and real questions to BiLSTM network. Meanwhile, the attention mechanism is utilized in the decoding layer, which makes the triples and generated questions more relevant. Finally, the experimental results on SimpleQuestions demonstrate the effectiveness of the proposed approach.     

客车涂装底层材料配套性分析

针对南方客户在使用我司客车一段时间后，车身涂层不同程度出现了起泡的质量问题，进行了现场查看，发现起泡位置在车身左右侧蒙皮，且发生在涂层最底层。初步分析原因是热镀锌板+阴极电泳漆 +原子灰三者之间配套存在问题，通过热镀锌板 +阴极电泳漆 +原子灰三者之间的耐高温 80 ℃配套试验，以及室外曝晒试验，得出镀锌板表面是否钝化、电泳漆膜致密程度和原子灰苯乙烯含量是造成涂层底层起泡的主要原因。为了控制涂层起泡问题，重新修订了我司原子灰、镀锌板、电泳漆的技术标准以及部分工艺文件。     

Fractional order battery modelling methodologies for electric vehicle applications: Recent advances and perspectives

Science China Technological Sciences - Accurate modelling of lithium ion batteries is crucial for battery management in electric vehicles. Recent studies have revealed the fractional order nature...     

A Preamble Re-utilizing Access Scheme for Machine-Type Communications with Optimal Access Class Barring

Wireless Personal Communications - The existing long term evolution networks originally designed for human-to-human communications are hard to tackle numerous and bursty random access requests from...