How to Retain Rural Preschool Teachers?

As a result of the accelerated urbanization and the improved remunerations of urban teachers, a large number of rural teachers have been pursuing employment in urban areas, resulting in a severe shortage of rural teaching staff. This phenomenon is particularly pronounced in developing countries. Disadvantages in rural school working and living situations such as low pay, poor living conditions, heavy workloads, limited professional development has made teacher recruitment and retention extremely challenging tasks. The unbalanced urban-rural distribution of teachers, especially high-quality teachers, have become barriers to rural education development and further exacerbated the disadvantaged situations of rural students

Brain MRI Super Resolution Using 3D Deep Densely Connected Neural Networks

Magnetic resonance image (MRI) in high spatial resolution provides detailed anatomical information and is often necessary for accurate quantitative analysis. However, high spatial resolution typically comes at the expense of longer scan time, less spatial coverage, and lower signal to noise ratio (SNR). Single Image Super-Resolution (SISR), a technique aimed to restore high-resolution (HR) details from one single low-resolution (LR) input image, has been improved dramatically by recent breakthroughs in deep learning. In this paper, we introduce a new neural network architecture, 3D Densely Connected Super-Resolution Networks (DCSRN) to restore HR features of structural brain MR images. Through experiments on a dataset with 1,113 subjects, we demonstrate that our network outperforms bicubic interpolation as well as other deep learning methods in restoring 4x resolution-reduced images.Comment: Accepted by ISBI'1

Working Mechanism and Structure of Customer Services Support System

On the basis of analyzing customer services of manufacturing enterprises and these supporting requires, using the method of discrete system simulating, the paper provides the classifications of customer services suitable information technology supporting, brings forward the working mechanisms suitable to the supporting system of different kinds of customer services and the relevant system structure

Enhanced laser emission in opposite handedness using a cholesteric polymer film stack

We demonstrate an enhanced circularly polarized laser emission whose handedness is opposite to the cholesteric helix by the stacked cholesteric polymeric films. The dye-doped right-handed cholesteric polymer film is sandwiched between a mirror and a cholesteric polymer reflector. Due to the stimulated amplification and light recycling effects, the original laser emission from the middle active layer is not only dramatically enhanced but also converted to a left-handed circularly polarized emission with high purity. Moreover, a single 15 mu m dye-doped cholesteric film is found to lase more efficiently when the top side faces the pump source than when the bottom side does. This phenomenon is attributed to the band gap broadening of the bottom side

Energy Wall for Exascale Supercomputing

"Sustainable development" is one of the major issues in the 21st century. Thus the notions of green computing, green development and so on show up one after another. As the large-scale parallel computing systems develop rapidly, energy consumption of such systems is becoming very huge, especially system performance reaches Petascale (10^15 Flops) or even Exascale (10^18 Flops). The huge energy consumption increases the system temperature, which seriously undermines the stability and reliability, and limits the growth of system size. The effects of energy consumption on scalability become a growing concern. Against the background, this paper proposes the concept of "Energy Wall" to highlight the significance of achieving scalable performance in peta/exascale supercomputing by taking energy consumption into account. We quantify the effect of energy consumption on scalability by building the energy-efficiency speedup model, which integrates computing performance and system energy. We define the energy wall quantitatively, and provide the theorem on the existence of the energy wall, and categorize the large-scale parallel computers according to the energy consumption. In the context of several representative types of HPC applications, we analyze and extrapolate the existence of the energy wall considering three kinds of topologies, 3D-Torus, binary n-cube and Fat tree which provides insights on how to mitigate the energy wall effect in system design and through hardware/software optimization in peta/exascale supercomputing

Efficient and Accurate MRI Super-Resolution using a Generative Adversarial Network and 3D Multi-Level Densely Connected Network

High-resolution (HR) magnetic resonance images (MRI) provide detailed anatomical information important for clinical application and quantitative image analysis. However, HR MRI conventionally comes at the cost of longer scan time, smaller spatial coverage, and lower signal-to-noise ratio (SNR). Recent studies have shown that single image super-resolution (SISR), a technique to recover HR details from one single low-resolution (LR) input image, could provide high-quality image details with the help of advanced deep convolutional neural networks (CNN). However, deep neural networks consume memory heavily and run slowly, especially in 3D settings. In this paper, we propose a novel 3D neural network design, namely a multi-level densely connected super-resolution network (mDCSRN) with generative adversarial network (GAN)-guided training. The mDCSRN quickly trains and inferences and the GAN promotes realistic output hardly distinguishable from original HR images. Our results from experiments on a dataset with 1,113 subjects show that our new architecture beats other popular deep learning methods in recovering 4x resolution-downgraded im-ages and runs 6x faster.Comment: 10 pages, 2 figures, 2 tables. MICCAI 201

Direction controllable linearly polarized laser from a dye-doped cholesteric liquid crystal

We demonstrate a direction controllable linearly polarized laser from a dye-doped cholesteric liquid crystal (CLC) in a homogeneous cell coated with a metallic mirror on the inner side of a glass substrate. Due to coherent superposition of two orthogonal polarization states, the output laser light becomes linearly polarized and its output energy is greatly enhanced. Moreover, the linear polarization direction angle is proportional to the product of the CLC effective birefringence and cell gap. Hence direction tunable laser devices can be demonstrated by controlling the cell gap and the operating temperature

Cholesteric liquid crystal laser in a dielectric mirror cavity upon band-edge excitation

Low threshold laser action of dye-doped cholesteric liquid crystals ( CLCs) is demonstrated using an input circularly polarized light whose handedness is the same as the cholesteric helix of the sample at the high-energy band edge of the reflection band. The mechanism originates from the dramatic increase of the photon density of state at the band edges. We also demonstrate an enhanced laser action of a CLC in a dielectric multilayer cavity. In such a device configuration, the band-edge excitation at high-energy band edge improves the lasing performance not only for the same handedness circularly polarized pump beam as the cholesteric helix but also for the opposite one. It stems from the polarization independence of the dielectric multilayers