登封市王村乡大型唐宋古瓷窑群“神前窑”址的发现与研究

发源于河南省登封市中岳嵩山下的颍河， 是中国古陶瓷的孕育之地。建国后我国考古工作者在颍河两岸已经发现了著名的曲河窑和钧台窑。我经过 １０ 年考察发现了中原地区在民间口头上流传了 １０００ 余年的赫赫有名的 “神前窑”， 它位于登封市西南部的王村乡颍河北岸， 由前庄、朱垌、磨脐、玉翠 ４ 座大型古瓷窑址组成， 其中前庄窑和玉翠窑兼烧唐花釉瓷。该古瓷窑群规模宏大， 名声很高，

Noisy Chaotic Neural Network for Resource Allocation in High-Speed Train OFDMA System

High-speed train communication system is a typical high-mobility wireless communication network. Resource allocation problem has a great impact on the system performance. However, conventional resource allocation approaches in cellular network cannot be directly applied to this kind of special communication environment. A multidomain resource allocation strategy was proposed in the orthogonal frequency-division multiple access(OFDMA) of high-speed. By analyzing the effect of Doppler shift, sub-channels, antennas, time slots and power were jointly considered to maximize the energy efficiency under the constraint of total transmission power. For the purpose of reducing the computational complexity, noisy chaotic neural network algorithm was used to solve the above optimization problem. Simulation results showed that the proposed resource allocation method had a better performance than the traditional strategy.

Application of FAHP and Artificial Neural Network on Clothing Plant Location

Clothing manufacturers＇ direct investment and joint ventures in developing regions have seen to grow rapidly in the past few decades. Non-optimized selection can contribute to adverse effects affecting the performance of the plants on aspects of productivity, manufacturing and logistics cost. Selection of proper plant location is thus crucial. The conventional approaches to sites location are based on the factors and their weights. However, determining the weight of each factor is very difficult and time consuming. While the situation is changed, all the work must be redone again. This study aims to develop a decision-making system on clothing plant location for Hoog Kong clothing manufacturer. The proposed system utilizes artificial neural network to study the relationship between the factors and the suitability index of candidate sites. Firstly, the factors are stratified using the fuzzy analytical hierarchy process （FAHP） by review the related references and interviewing the experts. Secondly, the corresponding data are collected from the experts by questionnaire and the related government publication. Finally, the feedforward neural network with error backpropagation（EBP） learning algorithm is trained and applied to make decision. The results show that the proposed system performs well and has the characteristic of adaptability and plasticity.

Mysteries and Mysticism in the Arabian Desert

Saudi Arabia is rich not only in its oil, but also in its cultural heritages. With 1,500 rock arts and 4,000 archaeological sites it is the fourth largest rock art region in the world. The entire Saudi Arabia has been comprehensively surveyed, investigated, and documented under the auspices of the Saudi Arabian Department of Antiquities （now Saudi Commission for Tourism and Antiquities）. The archaeological and rock art investigations revealed tantalizing results providing the evidence of human presence in the Arabian Peninsula from the early Acheulean period until the present day. In addition to the ancient towns and cities like Madain Saleh （contemporary to Petra in Jordan）, Tayma, Domat al-Jandal, Thaj, and al-Fao and Ukhdoud hundreds of strange, mysterious, and mystic structures and petrolyghs are located in the deserts of Arabia. A few of such sites are discussed in this paper, highlighting the strong but still unknown to the world the cultural heritage of Saudi Arabia.

Three Years＇ Experience of the Web Site NEMIS

Results of the 2007/08 survey ＂Energy--the present and the future＂ conducted on a population of 1439 students from Zagreb University have shown that after school and television, internet is the third major source of knowledge for the participants. Therefore, ＂NEMIS＂ web site （www.nemis.zpf.fer.hr） was launched at the end of the 2008. NEMIS is a Croatian acronym for ＂Nuclear Energy--Mysticism and Reality＂. The site was envisioned as a place where interested visitors could get information, prepared by experts, on all the issues relating to nuclear energy. The main objectives of the work reported in this paper are to present the structure of the NEMIS web site and to analyze the activity on the site during the last three years. Based on the performed analysis, future activities on the site are set and discussed.

Response enhancement of olfactory sensory neurons-based biosensors for odorant detection

This paper presents a novel strategy for the response enhancement of olfactory sensory neurons (OSNs)-based biosensors by monitoring the enhancive responses of OSNs to odorants. An OSNs-based biosensor was developed on the basis of the light addressable potentiometric sensor (LAPS), in which rat OSNs were cultured on the surface of LAPS chip and served as sensing elements. LY294002, the specific inhibitor of phosphatidylinositol 3-kinase (PI3K), was used to enhance the responses of OSNs to odorants. The responses of OSNs to odorants with and without the treatment of LY294002 were recorded by LAPS. The results show that the enhancive effect of LY294002 was recorded efficiently by LAPS and the responses of this OSNs-LAPS hybrid biosensor were enhanced by LY294002 by about 1.5-fold. We conclude that this method can enhance the responses of OSNs-LAPS hybrid biosensors, which may provide a novel strategy for the bioelectrical signal monitor of OSNs in biosensors. It is also suggested that this strategy may be applicable to other kinds of OSNs-based biosensors for cellular activity detection, such as microelectrode array (MEA) and field effect transistor (FET).