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91.
Drug-likeness prediction is important for the virtual screening of drug candidates. It is challenging because the drug-likeness is presumably associated with the whole set of necessary properties to pass through clinical trials, and thus no definite data for regression is available. Recently, binary classification models based on graph neural networks have been proposed but with strong dependency of their performances on the choice of the negative set for training. Here we propose a novel unsupervised learning model that requires only known drugs for training. We adopted a language model based on a recurrent neural network for unsupervised learning. It showed relatively consistent performance across different datasets, unlike such classification models. In addition, the unsupervised learning model provides drug-likeness scores that well separate distributions with increasing mean values in the order of datasets composed of molecules at a later step in a drug development process, whereas the classification model predicted a polarized distribution with two extreme values for all datasets presumably due to the overconfident prediction for unseen data. Thus, this new concept offers a pragmatic tool for drug-likeness scoring and further can be applied to other biochemical applications.A new quantification method of drug-likeness based on unsupervised learning. The method only uses drug molecules as training set without any non-drug-like molecules. 相似文献
92.
Brain activation has been used to understand brain-level events associated with cognitive tasks or physical tasks. As a quantitative measure for brain activation, we propose entropy in place of signal amplitude and beta value, which are widely used, but sometimes criticized for their limitations and shortcomings as such measures. To investigate the relevance of our proposition, we provided 22 subjects with physical stimuli through elbow extension-flexion motions by using our exoskeleton robot, measured brain activation in terms of entropy, signal amplitude, and beta value; and compared entropy with the other two. The results show that entropy is superior, in that its change appeared in limited, well established, motor areas, while signal amplitude and beta value changes appeared in a widespread fashion, contradicting the modularity theory. Entropy can predict increase in brain activation with task duration, while the other two cannot. When stimuli shifted from the rest state to the task state, entropy exhibited a similar increase as the other two did. Although entropy showed only a part of the phenomenon induced by task strength, it showed superiority by showing a decrease in brain activation that the other two did not show. Moreover, entropy was capable of identifying the physiologically important location. 相似文献
93.
Park BK Jeong S Kim D Moon J Lim S Kim JS 《Journal of colloid and interface science》2007,311(2):417-424
We describe herein the synthesis of metallic copper nanoparticles in the presence of poly(vinylpyrrolidone), employed as a protecting agent, via a polyol method in ambient atmosphere. The obtained copper particles were confirmed by XRD to be crystalline copper with a face-centered cubic (fcc) structure. We observed monodisperse spherical copper nanoparticles with a diameter range 45+/-8 nm. The particle size and its distribution are controlled by varying the synthesis parameters such as the reducing agent concentration, reaction temperature, and precursor injection rate. The precursor injection rate plays an important role in controlling the size of the copper nanoparticles. On the basis of XPS and HRTEM results, we demonstrate that the surface of the copper is surrounded by amorphous CuO and that poly(vinylpyrrolidone) is chemisorbed on the copper surface. 相似文献
94.
Studies of the relationship between interfacial structure and mechanical properties in multicomponent materials are reviewed in this article. The following categories are considered for role of the interface in multicomponent systems: Interpenetrating polymer network(IPN), catalytic effect of silane coupling agent, morphological differences of filler surface, particle-particle interaction and particle size of the filler. The interfacial role in terms of the reinforcement mechanism of the composite and the behavior in the melt state is also discussed in the multicomponent system. 相似文献
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White organic light-emitting device was achieved through an incorporation of yellow YAG nanophosphors into blue polyfluorene emitting layer: electrode/YAG@polyfluorene/hole-transport/injection layers/ITO glass. The brightness of the proposed device (230 cd/m2 at 30 V) was enhanced by a factor of about two in comparison with that of phosphor-free reference device. It is attributed to the increased local electric field caused by bumps of nanophophors on the emitting layer. With increase of voltage, the blue-green emission decreased whereas the yellow emission increased. It is due to the effective energy transfer from the blue-green to the yellow bands. 相似文献
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Chul‐Soon Lee Zhengfei Dai Seong‐Yong Jeong Chang‐Hoon Kwak Bo‐Young Kim Do Hong Kim Prof. Ho Won Jang Joon‐Shik Park Prof. Jong‐Heun Lee 《Chemistry (Weinheim an der Bergstrasse, Germany)》2016,22(21):7102-7107
Monolayers of periodic porous Co3O4 inverse opal (IO) thin films for gas‐sensor applications were prepared by transferring cobalt‐solution‐dipped polystyrene (PS) monolayers onto sensor substrates and subsequent removal of the PS template by heat treatment. Monolayer Co3O4 IO thin films having periodic pores (d≈500 nm) showed a high response of 112.9 to 5 ppm C2H5OH at 200 °C with low cross‐responses to other interfering gases. Moreover, the selective detection of xylene and methyl benzenes (xylene+toluene) could be achieved simply by tuning the sensor temperature to 250 and 275 °C, respectively, so that multiple gases can be detected with a single chemiresistor. Unprecedentedly high ethanol response and temperature‐modulated control of selectivity with respect to ethanol, xylene, and methyl benzenes were attributed to the highly chemiresistive IO nanoarchitecture and to the tuned catalytic promotion of different gas‐sensing reactions, respectively. These well‐ordered porous nanostructures could have potential in the field of high‐performance gas sensors based on p‐type oxide semiconductors. 相似文献