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This study was designed to establish a more effective and safe culture system for adoptive immunotherapy by investigating the use of homologous cord blood plasma (HCBP) instead of fetal bovine serum (FBS), which has various limitations including ethical problems for the ex vivo expansion of human umbilical T lymphocytes. Fresh human umbilical mononuclear cell fractions were isolated by Ficoll-Hypaque density centrifugation. Nonadherent mononuclear cell fractions were cultured with anti-CD3 antibody (5 μ g/ml), IL-2 (175 U/ml), and either 10% FBS or 10% HCBP. On day 8, the cellular proliferation rate and cell surface markers were assessed. There was no significant difference in proliferation when human umbilical cord blood T lymphocytes were grown in medium supplemented with FBS or HCBP (p > 0.05). In medium containing FBS, the proportion of CD3 human umbilical cord blood; T lymphocytes; ex vivo expansion; fetal bovine serum; homologous umbilical cord blood plasma

Hardware-based spiking neural networks (SNNs) inspired by a biological nervous system are regarded as an innovative computing system with very low power consumption and massively parallel operation. To train SNNs with supervision, we propose an efficient on-chip training scheme approximating backpropagation algorithm suitable for hardware implementation. We show that the accuracy of the proposed scheme for SNNs is close to that of conventional artificial neural networks (ANNs) by using the stochastic characteristics of neurons. In a hardware configuration, gated Schottky diodes (GSDs) are used as synaptic devices, which have a saturated current with respect to the input voltage. We design the SNN system by using the proposed on-chip training scheme with the GSDs, which can update their conductance in parallel to speed up the overall system. The performance of the on-chip training SNN system is validated through MNIST data set classification based on network size and total time step. The SNN systems achieve accuracy of 97.83% with 1 hidden layer and 98.44% with 4 hidden layers in fully connected neural networks. We then evaluate the effect of non-linearity and asymmetry of conductance response for long-term potentiation (LTP) and long-term depression (LTD) on the performance of the on-chip training SNN system. In addition, the impact of device variations on the performance of the on-chip training SNN system is evaluated.

We propose a designing of multi-layer neural networks using 2D NAND flash memory cell as a high-density and reliable synaptic device. Our operation scheme eliminates the waste of NAND flash cells and allows analogue input values. A 3-layer perceptron network with 40,545 synapses is trained on a MNIST database set using an adaptive weight update method for hardware-based multi-layer neural networks. The conductance response of NAND flash cells is measured and it is shown that the unidirectional conductance response is suitable for implementing multi-layer neural networks using NAND flash memory cells as synaptic devices. Using an online-learning, we obtained higher learning accuracy with NAND synaptic devices compared to that with a memristor-based synapse regardless of weight update methods. Using an adaptive weight update method based on a unidirectional conductance response, we obtained a 94.19% learning accuracy with NAND synaptic devices. This accuracy is comparable to 94.69% obtained by synapses based on the ideal perfect linear device. Therefore, NAND flash memory which is mature technology and has great advantage in cell density can be a promising synaptic device for implementing high-density multi-layer neural networks. INDEX TERMS Neuromorphic, NAND flash memory, deep neural networks (DNNs), synaptic device, deep learning, multi-layer neural networks, hardware-based neural network.

Along with the development in OLED TV panel manufacturing technology, the thickness of the panel is thinned, and the durability is also improved. It is also possible to generate sound by directly driving the panel. In this study, we have analyzed the acoustic characteristics of a directly driving the OLED panel speakers, using electroencephalography(EEG), in addition study the advantages of direct driving sound. OLED TV with direct drive speakers has a basic effect of matching the positions of the screen and sound. This is because the direction of the sound and the direction of the screen coincide with the viewers of the TV, so that the stress is less and the viewing is comfortable compared to the conventional TV. The acoustic characteristics of proposed OLED speakers are high in resolution. And the sound quality is better than ordinary TVs, because of direct transferred sound instead of listening to reflections or differenced sound sources compared with.