Migrating Knowledge between Physical Scenarios based on Artificial Neural Networks

Deep learning is known to be data-hungry, which hinders its application in many areas of science when datasets are small. Here, we propose to use transfer learning methods to migrate knowledge between different physical scenarios and significantly improve the prediction accuracy of artificial neural networks trained on a small dataset. This method can help reduce the demand for expensive data by making use of additional inexpensive data. First, we demonstrate that in predicting the transmission from multilayer photonic film, the relative error rate is reduced by 46.8% (26.5%) when the source data comes from 10-layer (8-layer) films and the target data comes from 8-layer (10-layer) films. Second, we show that the relative error rate is decreased by 22% when knowledge is transferred between two very different physical scenarios: transmission from multilayer films and scattering from multilayer nanoparticles. Finally, we propose a multi-task learning method to improve the performance of different physical scenarios simultaneously in which each task only has a small dataset

Electrospun polyvinyl alcohol/carbon dioxide modified polyethyleneimine composite nanofiber scaffolds

A novel biocompatible polyvinyl alcohol/carbon dioxide modified polyethyleneimine (PVA/PEI-CO2) composite nanofiber was fabricated by a green and facile protocol, which reduces the cytotoxicity of PEI through the surface modification of the PEI with CO2. The 13C NMR spectrum, elemental analysis, and TGA show that CO2 has been incorporated in the PEI surface resulting in a relatively stable structure. The resulting PVA/PEI-CO2 composite nanofibers have been characterized by attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR), contact angle, and scanning electron microscopy (SEM). The results show that the average diameters of the nanofibers range from 265 ± 53 nm to 423 ± 80 nm. The cytotoxicity of PVA/PEI-CO2 composite nanofibers was assessed by cytotoxicity evaluation using the growth and cell proliferation of normal mice Schwann cells. SEM and the MTT assay demonstrated the promotion of cell growth and proliferation on the PVA/PEI-CO2 composite scaffold. It suggests that PEI-CO2 can have tremendous potential applications in biological material research

Design of a compact microfludic device for controllable cell distribution

A compact microfluidic device with 96 microchambers allocated within four circular units was designed and examined for cell distribution. In each unit, cells were distributed to the surrounding chambers radially from the center. The circular arrangement of the chambers makes the design simple and compact. A controllable and quantitative cell distribution is achievable in this device. This design is significant to the microfluidic applications where controllable distribution of cells in multipule microchambers is demanded.<br /

In-situ EXAFS study on the thermal decomposition of TiH2

Thermal decomposition behaviors of TiH2 powder under a flowing helium atmosphere and in a low vacuum condition have been studied by using in-situ EXAFS technique. By an EXAFS analysis containing the multiple scattering paths including H atoms, the changes of hydrogen stoichiometric ratio and the phase transformation sequence are obtained. The results demonstrate that the initial decomposition temperature is dependent on experimental conditions, which occurs, respectively, at about 300 and 400 degree in a low vacuum condition and under a flowing helium atmosphere. During the decomposition process of TiH2 in a low vacuum condition, the sample experiences a phase change process: {\delta}(TiH2) - {\delta}(TiHx) - {\delta}(TiHx)+{\beta}(TiHx) - {\delta}(TiHx)+{\beta}(TiHx)+{\alpha}(Ti) - {\beta}(TiHx)+{\alpha}(Ti) - {\alpha}(Ti)+{\beta}(Ti). This study offers a way to detect the structural information of hydrogen. A detailed discussion about the decomposition process of TiH2 is given in this paper.Comment: 9 pages, 7 figure

Long-time self-similar asymptotic of the macroscopic quantum models

The unipolar and bipolar macroscopic quantum models derived recently for instance in the area of charge transport are considered in spatial one-dimensional whole space in the present paper. These models consist of nonlinear fourth-order parabolic equation for unipolar case or coupled nonlinear fourth-order parabolic system for bipolar case. We show for the first time the self-similarity property of the macroscopic quantum models in large time. Namely, we show that there exists a unique global strong solution with strictly positive density to the initial value problem of the macroscopic quantum models which tends to a self-similar wave (which is not the exact solution of the models) in large time at an algebraic time-decay rate.Comment: 18 page

A Descriptive Model of Robot Team and the Dynamic Evolution of Robot Team Cooperation

At present, the research on robot team cooperation is still in qualitative analysis phase and lacks the description model that can quantitatively describe the dynamical evolution of team cooperative relationships with constantly changeable task demand in Multi-robot field. First this paper whole and static describes organization model HWROM of robot team, then uses Markov course and Bayesian theorem for reference, dynamical describes the team cooperative relationships building. Finally from cooperative entity layer, ability layer and relative layer we research team formation and cooperative mechanism, and discuss how to optimize relative action sets during the evolution. The dynamic evolution model of robot team and cooperative relationships between robot teams proposed and described in this paper can not only generalize the robot team as a whole, but also depict the dynamic evolving process quantitatively. Users can also make the prediction of the cooperative relationship and the action of the robot team encountering new demands based on this model. Journal web page & a lot of robotic related papers www.ars-journal.co

SIRT3 Protects Rotenone-induced Injury in SH-SY5Y Cells by Promoting Autophagy through the LKB1-AMPK-mTOR Pathway.

SIRT3 is a class III histone deacetylase that modulates energy metabolism, genomic stability and stress resistance. It has been implicated as a potential therapeutic target in a variety of neurodegenerative diseases, including Parkinson's disease (PD). Our previous study demonstrates that SIRT3 had a neuroprotective effect on a rotenone-induced PD cell model, however, the exact mechanism is unknown. In this study, we investigated the underlying mechanism. We established a SIRT3 stable overexpression cell line using lentivirus infection in SH-SY5Y cells. Then, a PD cell model was established using rotenone. Our data demonstrate that overexpression of SIRT3 increased the level of the autophagy markers LC3 II and Beclin 1. After addition of the autophagy inhibitor 3-MA, the protective effect of SIRT3 diminished: the cell viability decreased, while the apoptosis rate increased; α-synuclein accumulation enhanced; ROS production increased; antioxidants levels, including SOD and GSH, decreased; and MMP collapsed. These results reveal that SIRT3 has neuroprotective effects on a PD cell model by up-regulating autophagy. Furthermore, SIRT3 overexpression also promoted LKB1 phosphorylation, followed by activation of AMPK and decreased phosphorylation of mTOR. These results suggest that the LKB1-AMPK-mTOR pathway has a role in induction of autophagy. Together, our findings indicate a novel mechanism by which SIRT3 protects a rotenone-induced PD cell model through the regulation of autophagy, which, in part, is mediated by activation of the LKB1-AMPK-mTOR pathway