2,992 research outputs found
Vat photopolymerisation 3D printing of controlled drug delivery devices
Pharmaceutical three-dimensional (3D) printing has led to a paradigm shift in the way medicines are designed and manufactured, moving away from the traditional ‘one-size-fits-all’ approaches and advancing towards personalised medicines. Among different 3D printing techniques, vat photopolymerisation 3D printing affords superior printing resolution, which in turn enables fabrication of micro-structures and smooth finishes.
This thesis aims to investigate different vat photopolymerisation 3D printing techniques for the fabrication of personalised drug delivery devices for different routes of administration. Stereolithography (SLA) and digital light processing (DLP) 3D printing was used to manufacture devices with flexible materials for localised delivery of a single drug in the bladder and at the anterior segment of the eye. In vitro release studies demonstrated drug releases from these devices were sustained over weeks. Subsequently, to investigate the feasibility of loading more than one drug in a single dosage form, clinically relevant multi-layer antihypertensive polypills were fabricated using SLA 3D printing. A drug-photopolymer interaction was observed from these polypills, and Michael’s addition reaction was confirmed to have occurred. Despite these studies demonstrating the viable use of vat photopolymerization 3D printing for fabricating drug delivery devices, the bulky nature of current printers could be a barrier to clinical integration. As such, a smartphone-enabled DLP 3D printing system was developed to fabricate personalised oral dosage forms and patient-specific drug delivery devices. The portability of this printer could secure exciting opportunities for manufacturing personalised medicines at point-of-care settings. Overall, this thesis showed the potential of vat photopolymerisation 3D printing in preparing different patient-centric drug delivery devices with tuneable and sustained release profiles as well as advancing traditional treatments towards digital healthcare
側鎖変換性ジビニルモノマーからの配列制御共重合体の合成:環化重合の精密制御と配列特異的物性の創出
京都大学新制・課程博士博士(工学)甲第24905号工博第5185号京都大学大学院工学研究科高分子化学専攻(主査)教授 大内 誠, 教授 田中 一生, 教授 大北 英生学位規則第4条第1項該当Doctor of Philosophy (Engineering)Kyoto UniversityDGA
Quality-Gated Convolutional LSTM for Enhancing Compressed Video
The past decade has witnessed great success in applying deep learning to
enhance the quality of compressed video. However, the existing approaches aim
at quality enhancement on a single frame, or only using fixed neighboring
frames. Thus they fail to take full advantage of the inter-frame correlation in
the video. This paper proposes the Quality-Gated Convolutional Long Short-Term
Memory (QG-ConvLSTM) network with bi-directional recurrent structure to fully
exploit the advantageous information in a large range of frames. More
importantly, due to the obvious quality fluctuation among compressed frames,
higher quality frames can provide more useful information for other frames to
enhance quality. Therefore, we propose learning the "forget" and "input" gates
in the ConvLSTM cell from quality-related features. As such, the frames with
various quality contribute to the memory in ConvLSTM with different importance,
making the information of each frame reasonably and adequately used. Finally,
the experiments validate the effectiveness of our QG-ConvLSTM approach in
advancing the state-of-the-art quality enhancement of compressed video, and the
ablation study shows that our QG-ConvLSTM approach is learnt to make a
trade-off between quality and correlation when leveraging multi-frame
information. The project page: https://github.com/ryangchn/QG-ConvLSTM.git.Comment: Accepted to IEEE International Conference on Multimedia and Expo
(ICME) 201
Assigning personality/identity to a chatting machine for coherent conversation generation
Endowing a chatbot with personality or an identity is quite challenging but
critical to deliver more realistic and natural conversations. In this paper, we
address the issue of generating responses that are coherent to a pre-specified
agent profile. We design a model consisting of three modules: a profile
detector to decide whether a post should be responded using the profile and
which key should be addressed, a bidirectional decoder to generate responses
forward and backward starting from a selected profile value, and a position
detector that predicts a word position from which decoding should start given a
selected profile value. We show that general conversation data from social
media can be used to generate profile-coherent responses. Manual and automatic
evaluation shows that our model can deliver more coherent, natural, and
diversified responses.Comment: an error on author informatio
{1,3-Bis[(diphenylphosphanyl-κP)oxy]propane}dicarbonyliron(0)
The structure of the title compound, [Fe(C27H26O2P2)(CO)2], exhibits a distorted tetrahedral coordination [bond angle range = 96.31 (12)–119.37 (4)°], comprising two P-atom donors from the chelating 1,3-bis[(diphenylphosphanyl)oxy]propane ligand [Fe—P = 2.1414 (10) and 2.1462 (10) Å] and two carbonyl ligands [Fe—C = 1.763 (4) and 1.765 (3) Å]
Construction and exploration of intelligent control technology innovation teaching team
Intelligent control technology innovation teaching team is to implement the “Made in China 2025” national major strategic
deployment, relying on intelligent robot training room, industrial robot training room, AI science and technology innovation studio, PLC
association, electronic information Association and other platforms, to the construction of high-level teachers as the starting point, integrate
and optimize regional resources, strengthen school-enterprise cooperation, To form an innovative, collaborative, efficient and industry_x005funiversity-research innovative teaching team. This paper expounds and summarizes the team building process from the aspects of base
construction objectives, construction contents, construction paths, construction achievements and construction characteristics, aiming at
providing reference for the construction of professional teaching teams in the fi eld of artifi cial intelligence in higher vocational colleges
A Structural Model of Demand, Cost, and Export Market Selection for Chinese Footwear Producers
In this paper we use micro data on both trade and production for a sample of large Chinese manufacturing firms in the footwear industry from 2002-2006 to estimate an empirical model of export demand, pricing, and market participation by destination market. We use the model to construct indexes of firm-level demand, cost, and export market profitability. The empirical results indicate substantial firm heterogeneity in both the demand and cost dimensions with demand being more dispersed. The firm-specific demand and cost components are very useful in explaining differences in the extensive margin of trade, the length of time a firm exports to a destination, and the number and mix of destinations, as well as the export prices, while cost is more important in explaining the quantity of firm exports on the intensive margin. We use the estimates to analyze the reallocation resulting from removal of the quota on Chinese footwear exports to the EU and find that it led to a rapid restructuring of export supply sources in favor of firms with high demand and low cost indexes.
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