How Far Has China's Urbanization Come? (Japanese)

Currently, China is urbanizing its population at an unprecedented pace in human history. China's urbanization rate is expected to reach to 50% in 2010, reflecting that China has entered into a society of urban majority. In consideration of the massive surplus in the labor force in rural areas, the process of urbanization in China is far from complete and will continue over the next two decades. Under the effects of a unique "household registration system" and the rapidly evolving labor market, China's urbanization is facing more challenges than its predecessors of developed countries and its peers of developing countries. With the signs of frequent manpower shortages and rising labor costs in coastal regions in recent years, China's labor market has been deemed to pass the Lewisian turning point. Although the rapid economic growth and population aging are shaping the labor market in China, the household registration system still constitutes a barrier for the more efficient allocation of its labor force. This paper will examine the urbanization process in China and propose relevant new policies and systems to reconcile with the country's demographic trends and economic growth.

Exploring Training Effect in 42 Human Subjects Using a Non-invasive Sensorimotor Rhythm Based Online BCI

Electroencephalography based brain-computer interfaces (BCIs) show promise of providing an alternative communication channel between the brain and an external device. It is well acknowledged that BCI control is a skill and could be improved through practice and training. In this study, we explore the change of BCI behavioral performance as well as the electrophysiological properties across three training sessions in a pool of 42 human subjects. Our results show that the group average of BCI accuracy and the information transfer rate improved significantly in the third session compared to the first session; especially the significance reached in a smaller subset of a low BCI performance group (average accuracy <70%) as well. There was a significant difference of event-related desynchronization (ERD) lateralization for BCI control between the left- and right-hand imagination task in the last two sessions, but this significant difference was not revealed in the first training sessions. No significant change of R2 value or event-related desynchronization and synchronization (ERD/ERS) for either channel C3 or channel C4, which were used for online control, was found across the training sessions. The change of ERD lateralization was also not significant across the training sessions. The present results indicate that BCI training could induce a change of behavioral performance and electrophysiological properties quickly, within just a few hours of training, distributed into three sessions. Multiple training sessions might especially be beneficial for the low BCI performers

Cooperative Jamming with AF Relay in Power Monitoring and Communication Systems for Mining

In underground mines, physical layer security (PLS) technology is a promising method for the effective and secure communication to monitor the mining process. Therefore, in this paper, we investigate the PLS of an amplify-and-forward relay-aided system in power monitoring and communication systems for mining, with the consideration of multiple eavesdroppers. Explicitly, we propose a PLS scheme of cooperative jamming and precoding for a full-duplex system considering imperfect channel state information. To maximize the secrecy rate of the communications, an effective block coordinate descent algorithm is used to design the precoding and jamming matrix at both the source and the relay. Furthermore, the effectiveness and convergence of the proposed scheme with high channel state information uncertainty have been proven

PAEDID: Patch Autoencoder Based Deep Image Decomposition For Pixel-level Defective Region Segmentation

Unsupervised pixel-level defective region segmentation is an important task in image-based anomaly detection for various industrial applications. The state-of-the-art methods have their own advantages and limitations: matrix-decomposition-based methods are robust to noise but lack complex background image modeling capability; representation-based methods are good at defective region localization but lack accuracy in defective region shape contour extraction; reconstruction-based methods detected defective region match well with the ground truth defective region shape contour but are noisy. To combine the best of both worlds, we present an unsupervised patch autoencoder based deep image decomposition (PAEDID) method for defective region segmentation. In the training stage, we learn the common background as a deep image prior by a patch autoencoder (PAE) network. In the inference stage, we formulate anomaly detection as an image decomposition problem with the deep image prior and domain-specific regularizations. By adopting the proposed approach, the defective regions in the image can be accurately extracted in an unsupervised fashion. We demonstrate the effectiveness of the PAEDID method in simulation studies and an industrial dataset in the case study

Topiramate inhibits the proliferation of bladder cancer cells via PI3K/AKTR signaling pathway

Purpose: To explore new treatment options for bladder cancer (BC) based on topiramate (TPM).Methods: The MTT assay and flow cytometry were used to determine the effect of topiramate on partial growth-related malignant phenotype of BC cells. Expression levels of apoptosis-related biomarkers and signaling pathway-related factors were analyzed using quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting. In vivo experiments were conducted to investigate the role of TPM on tumor growth in mice with bladder cancer.Results: The MTT results showed that topiramate blocked the growth of BC cells (p < 0.05). Growth inhibition was positively correlated with TPM concentration. Flow cytometry results revealed that bladder cancer cell apoptosis rose with increase in TPM concentration, while the mRNAs of apoptosisassociated factors Bcl-2 and Mcl-1 were down-regulated in a concentration-based manner by TPM (p < 0.05). Western blot assay indicated that Bax and Caspase-3 proteins were up-regulated, and the higher the concentration of TPM, the more significant the protein expression levels (p < 0.05).Conclusion: Topiramate (TPM) slows down the rate of growth of BC cells and accelerates their rate of apoptosis through the regulation of P13K/AKT/mTOR signaling pathway. Thus, the compound has potentials for development as an anti-bladder cancer agent

Low expression of Notch1 may be associated with acute myocardial infarction

BackgroundThe transmembrane protein Notch1 is associated with cell growth, development, differentiation, proliferation, apoptosis, adhesion, and the epithelial mesenchymal transition. Proteomics, as a research method, uses a series of sequencing techniques to study the composition, expression levels, and modifications of proteins. Here, the association between Notch1 and acute myocardial infarction (AMI) was investigated using proteomics, to assess the possibility of using Notch1 as a biomarker for the disease.MethodsFifty-five eligible patients with AMI and 74 with chronic coronary syndrome (CCS) were enrolled, representing the experimental and control groups, respectively. The mRNA levels were assessed using RT-qPCR and proteins were measured using ELISA, and the results were compared and analyzed.ResultsNotch1 mRNA levels were 0.52 times higher in the peripheral blood mononuclear cells of the AMI group relative to the CCS group (p < 0.05) while Notch1 protein levels were 0.63 times higher in peripheral blood plasma in AMI patients (p < 0.05). Notch1 levels were not associated with older age, hypertension, smoking, high abdominal-blood glucose, high total cholesterol, and high LDL in AMI. Logistic regression indicated associations between AMI and reduced Notch1 expression, hypertension, smoking, and high fasting glucose.ConclusionsNotch1 expression was reduced in the peripheral blood of patients with AMI relative to those with CCS. The low expression of Notch1 was found to be an independent risk factor for AMI and may thus be an indicator of the disease