209 research outputs found
Cooperative dual catalysis with thiourea organocatalysts
No full textThiourea organocatalysis represents a versatile activation strategy in synthetic organic chemistry. By hydrogen-bonding interactions with neutral or anionic substrates and/or intermediates, thiourea organocatalysts can often direct the reaction pathways with promising levels of stereochemical control. This dissertation demonstrates the cooperative use of thiourea organocatalysts in combination with other types of catalysts in addressing challenging synthetic problems that are not realized by either type alone. Specifically, cooperative catalysis of thiourea and iminium organocatalysts enabled the first highly enantioselective direct oxa-Pictet–Spengler reactions under weakly acidic conditions. In comTbination with a transition metal catalyst, an acid–thiourea catalyst afforded highly enantioselective A3 reactions with secondary amines. Strong Brønsted acid was also applied cooperatively with thiourea organocatalyst, furnishing the direct reductive etherification reactions with a wide variety of substrates.Ph.D.Includes bibliographical referencesby Chenfei Zha
Editorial: Advances in connectome-wide association studies (CWAS) along the neurodegeneration trajectory
No full textResearch on Data Mining of Sports Wearable Intelligent Devices Based on Big Data Analysis
No full textTraditional motion data mining models have some problems, such as poor dynamic data capture effect, low information classification effect rate, poor quantitative representation effect, and so on. Based on this, this paper studies the mining method of dynamic motion data based on neural network, constructs a data mining model based on discrete dynamic modeling technology, and realizes the collection of data information from the aspects of motion characteristics and types combined with multilayer sensors. Neural network algorithm is used for comprehensive analysis to realize multivariate analysis and objective evaluation of all data of dynamic motion process and accurate analysis and evaluation according to different data characteristics of different types of motion data. The results show that the data mining model based on discrete dynamic modeling technology and wearable sensor technology has the advantages of high feasibility, high intelligence, and wide application range
Spatial divergence of service industry agglomeration in the CCEC.
No full textSource: Created by the author based on the base map of the CCEC, which comes from the Service Center of Standard Map (http://bzdt.ch.mnr.gov.cn/), and the number of the permission is GS (2016) 2923.</p
Achieving Efficient and Privacy-Preserving Neural Network Training and Prediction in Cloud Environments
No full textThe inverse calculation of roughness coefficient in village and county circular pipe network based on Stochastic Particle Swarm Optimization
No full textDifferential Networks for Visual Question Answering
No full textThe task of Visual Question Answering (VQA) has emerged in recent years for its potential applications. To address the VQA task, the model should fuse feature elements from both images and questions efficiently. Existing models fuse image feature element vi and question feature element qi directly, such as an element product viqi. Those solutions largely ignore the following two key points: 1) Whether vi and qi are in the same space. 2) How to reduce the observation noises in vi and qi. We argue that two differences between those two feature elements themselves, like (vi − vj) and (qi −qj), are more probably in the same space. And the difference operation would be beneficial to reduce observation noise. To achieve this, we first propose Differential Networks (DN), a novel plug-and-play module which enables differences between pair-wise feature elements. With the tool of DN, we then propose DN based Fusion (DF), a novel model for VQA task. We achieve state-of-the-art results on four publicly available datasets. Ablation studies also show the effectiveness of difference operations in DF model
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