Soil microbial community analysis using terminal restriction fragment length polymorphisms

Terminal restriction fragment length polymorphism (T-RFLP) analysis is a polymerase chain reaction (PCR)-fingerprinting method that is commonly used for comparative microbial community analysis. The method can be used to analyze communities of bacteria, archaea, fungi, other phylogenetic groups or subgroups, as well as functional genes. The method is rapid, highly reproducible, and often yields a higher number of operational taxonomic units than other, commonly used PCR-fingerprinting methods. Sizing of terminal restriction fragments (T-RFs) can now be done using capillary sequencing technology allowing samples contained in 96- or 384-well plates to be sized in an overnight run. Many multivariate statistical approaches have been used to interpret and compare T-RFLP fingerprints derived from different communities. Detrended correspondence analysis and the additive main effects with multiplicative interaction model are particularly useful for revealing trends in T-RFLP data. Due to biases inherent in the method, linking the size of T-RFs derived from complex communities to existing sequence databases to infer their taxonomic position is not very robust. This approach has been used successfully, however, to identify and follow the dynamics of members within very simple or model communities. The T-RFLP approach has been used successfully to analyze the composition of microbial communities in soil, water, marine, and lacustrine sediments, biofilms, feces, in and on plant tissues, and in the digestive tracts of insects and mammals. The T-RFLP method is a user-friendly molecular approach to microbial community analysis that is adding significant information to studies of microbial populations in many environments.

On Combining Morphological Component Analysis and Concentric Morphology Model for Mammographic Mass Detection

Mammographic mass detection is an important task for the early diagnosis of breast cancer. However, it is difficult to distinguish masses from normal regions because of their abundant morphological characteristics and ambiguous margins. To improve the mass detection performance, it is essential to effectively preprocess mammogram to preserve both the intensity distribution and morphological characteristics of regions. In this paper, morphological component analysis is first introduced to decompose a mammogram into a piecewise-smooth component and a texture component. The former is utilized in our detection scheme as it effectively suppresses both structural noises and effects of blood vessels. Then, we propose two novel concentric layer criteria to detect different types of suspicious regions in a mammogram. The combination is evaluated based on the Digital Database for Screening Mammography, where 100 malignant cases and 50 benign cases are utilized. The sensitivity of the proposed scheme is 99% in malignant, 88% in benign, and 95.3% in all types of cases. The results show that the proposed detection scheme achieves satisfactory detection performance and preferable compromises between sensitivity and false positive rates.

Characteristics in frequency domain by inductively coupled plasma atomic emission spectrometry with charge injection detection

The charactesistics of two-dimension spectra obtained by inductively coupled plasma atomic emission spectrometry (ICP-AES) with charge injection detection (CID) in frequency domain were studied in the present paper. The measurement spectra were Fourier transformed and the frequency distribution of the spectra was obtained. Results showed that the spectra in frequency domain could he divided into two parts:high frequency and low frequency signals. The later stood for measurement spectra and the former for background and noises. However, the high frequecny signals could not be smoothed simply to reduce noises because the background was deteriorated even though the spectral signal did not change significantly.

综合权值递推最小二乘法估计从UUV航行参数

根据主UUV观测系统测量的从UUV方位信息精度高、距离信息精度低的特点,将遗忘因子和位置权值构成的综合权值融入递推最小二乘算法(RLS)用于从UUV航行参数分析,避免采用EKF算法对观测噪声要求高的缺陷,克服数据饱和现象。同时对从UUV方位信息进行预处理以提高航行参数估计的收敛速度。仿真实验证明了方法的有效性。

噪音环境下的FFFieldbus通讯性能研究

通过噪音对令牌运行过程的作用 ,本文分析了在噪音环境下 FF Fieldbus的性能变化 .本文首先建立了令牌运行过程的自动机模型 ,然后利用此模型分析了噪音对令牌运行方式的影响 .根据噪音的影响 ,本文推导出令牌运行时间和令牌平均运行时间 .最后利用解析表达式分析出噪音分布对 FF Fieldbus性能的影响 .

图象噪声的模糊聚类平滑方法

模糊C-means算法在聚类分析中已得到了成功的应用,本文提出一种利用模糊C-means算法消除噪声的新方法。一般来说,图象中的噪声点就是其灰度值与其周围象素的灰度值之差超过某个门限值的点。根据这个事实,首先利用模糊C-means算法分类,再利用标准核函数检测出噪声点,然后将噪声点去掉。由于只修改噪声点处的象素灰度值,而对于其它象素的灰度值不予改变,所以本算法能够很好地保护细节和边缘。本方法每次处理3×3个点,而以往的方法只能每次处理一个点,所以本方法能提高运算速度。文中给出了利用本方法对实际图象处理的结果,并与梯度倒数权值法进行了定量的比较。

小波域地震资料的处理方法（WSSP）研究

The modeling formula based on seismic wavelet can well simulate zero - phase wavelet and hybrid-phase wavelet, and approximate maximal - phase and minimal - phase wavelet in a certain sense. The modeling wavelet can be used as wavelet function after suitable modification item added to meet some conditions. On the basis of the modified Morlet wavelet, the derivative wavelet function has been derived. As a basic wavelet, it can be sued for high resolution frequency - division processing and instantaneous feature extraction, in acoordance with the signal expanding characters in time and scale domains by each wavelet structured. Finally, an application example proves the effectiveness and reasonability of the method. Based on the analysis of SVD (Singular Value Decomposition) filter, by taking wavelet as basic wavelet and combining SVD filter and wavelet transform, a new de - noising method, which is Based on multi - dimension and multi-space de - noising method, is proposed. The implementation of this method is discussed the detail. Theoretical analysis and modeling show that the method has strong capacity of de - noising and keeping attributes of effective wave. It is a good tool for de - noising when the S/N ratio is poor. To give prominence to high frequency information of reflection event of important layer and to take account of other frequency information under processing seismic data, it is difficult for deconvolution filter to realize this goal. A filter from Fourier Transform has some problems for realizing the goal. In this paper, a new method is put forward, that is a method of processing seismic data in frequency division from wavelet transform and reconstruction. In ordinary seismic processing methods for resolution improvement, deconvolution operator has poor part characteristics, thus influencing the operator frequency. In wavelet transform, wavelet function has very good part characteristics. Frequency - division data processing in wavelet transform also brings quite good high resolution data, but it needs more time than deconvolution method does. On the basis of frequency - division processing method in wavelet domain, a new technique is put forward, which involves 1) designing filter operators equivalent to deconvolution operator in time and frequency domains in wavelet transform, 2) obtaining derivative wavelet function that is suitable to high - resolution seismic data processing, and 3) processing high resolution seismic data by deconvolution method in time domain. In the method of producing some instantaneous characteristic signals by using Hilbert transform, Hilbert transform is very sensitive to high - frequency random noise. As a result, even though there exist weak high - frequency noises in seismic signals, the obtained instantaneous characteristics of seismic signals may be still submerged by the noises. One method for having instantaneous characteristics of seismic signals in wavelet domain is put forward, which obtains directly the instantaneous characteristics of seismic signals by taking the characteristics of both the real part (real signals, namely seismic signals) and the imaginary part (the Hilbert transfom of real signals) of wavelet transform. The method has the functions of frequency division and noise removal. What is more, the weak wave whose frequency is lower than that of high - frequency random noise is retained in the obtained instantaneous characteristics of seismic signals, and the weak wave may be seen in instantaneous characteristic sections (such as instantaneous frequency, instantaneous phase and instantaneous amplitude). Impedance inversion is one of tools in the description of oil reservoir. one of methods in impedance inversion is Generalized Linear Inversion. This method has higher precision of inversion. But, this method is sensitive to noise of seismic data, so that error results are got. The description of oil reservoir in researching important geological layer, in order to give prominence to geological characteristics of the important layer, not only high frequency impedance to research thin sand layer, but other frequency impedance are needed. It is difficult for some impedance inversion method to realize the goal. Wavelet transform is very good in denoising and processing in frequency division. Therefore, in the paper, a method of impedance inversion is put forward based on wavelet transform, that is impedance inversion in frequency division from wavelet transform and reconstruction. in this paper, based on wavelet transform, methods of time - frequency analysis is given. Fanally, methods above are in application on real oil field - Sansan oil field.

利用分频与反演提高地震资料信噪比与分辨率方法研究

This thesis mainly talks about the wavelet transfrom and the frequency division method. It describes the frequency division processing on prestack or post-stack seismic data and application of inversion noise attenuation, frequency division residual static correction and high resolution data in reservoir inversion. This thesis not only describes the frequency division and inversion in theory, but also proves it by model calculation. All the methods are integrated together. The actual data processing demonstrates the applying results. This thesis analyzes the differences and limitation between t-x prediction filter and f-x prediction filter noise attenuation from wavelet transform theory. It considers that we can do the frequency division attenuation process of noise and signal by wavelet frequency division theory according to the differences of noise and signal in phase, amplitude and frequency. By comparison with the f-x coherence noise, removal method, it approves the effects and practicability of frequency division in coherence and random noise isolation. In order to solve the side effects in non-noise area, we: take the area constraint method and only apply the frequency division processing in the noise area. So it can solve the problem of low frequency loss in non-noise area. The residual moveout differences in seismic data processing have a great effect on stack image and resolutions. Different frequency components have different residual moveout differences. The frequency division residual static correction realizes the frequency division and the calculation of residual correction magnitude. It also solves the problems of different residual correction magnitude in different frequency and protects the high frequency information in data. By actual data processing, we can get good results in phase residual moveout differences elimination of pre-stack data, stack image quality and improvement of data resolution. This thesis analyses the characters of the random noises and its descriptions in time domain and frequency domain. Furthermore it gives the inversion prediction solution methods and realizes the frequency division inversion attenuation of the random noise. By the analysis of results of the actual data processing, we show that the noise removed by inversion has its own advantages. By analyzing parameter's about resolution and technology of high resolution data processing, this thesis describes the relations between frequency domain and resolution, parameters about resolution and methods to increase resolution. It also gives the processing flows of the high resolution data; the effect and influence of reservoir inversion caused by high resolution data. Finally it proves the accuracy and precision of the reservoir inversion results. The research results of this thesis reveal that frequency division noise attenuation, frequency residual correction and inversion noise attenuation are effective methods to increase the SNR and resolution of seismic data.

乡镇级人口统计数据空间化研究

Population data which collected and saved according to administrative region is a kind of statistical data. As a traditional method of spatial data expression, average distribution in every administrative region brings population data on a low spatial and temporal precision. Now, an accurate population data with high spatial resolution is becoming more and more important in regional planning, environment protection, policy making and rural-urban development. Spatial distribution of population data is becoming more important in GIS study area. In this article, the author reviewed the progress of research on spatial distribution of population. Under the support of GIS, correlative geographical theories and Grid data model, Remote Sensing data, terrain data, traffic data, river data, resident data, and social economic statistic were applied to calculate the spatial distribution of population in Fujian province, which includes following parts: (1) Simulating of boundary at township level. Based on access cost index, land use data, traffic data, river data, DEM, and correlative social economic statistic data, the access cost surface in study area was constructed. Supported by the lowest cost path query and weighted Voronoi diagram, DVT model (Demarcation of Villages and Towns) was established to simulate the boundary at township level in Fujian province. (2) Modeling of population spatial distribution. Based on the knowledge in geography, seven impact factors, such as land use, altitude, slope, residential area, railway, road, and river were chosen as the parameters in this study. Under the support of GIS, the relations of population distribution to these impact factors were analyzed quantificationally, and the coefficients of population density on pixel scale were calculated. Last, the model of population spatial distribution at township level was established through multiplicative fusion of population density coefficients and simulated boundary of towns. (3) Error test and analysis of population spatial distribution base on modeling. The author not only analyzed the numerical character of modeling error, but also its spatial distribution. The reasons of error were discussed.

陆相砂泥岩层序的高精度检测方法研究及应用

Ordos Basin is a typical cratonic petroliferous basin with 40 oil-gas bearing bed sets. It is featured as stable multicycle sedimentation, gentle formation, and less structures. The reservoir beds in Upper Paleozoic and Mesozoicare are mainly low density, low permeability, strong lateral change, and strong vertical heterogeneous. The well-known Loess Plateau in the southern area and Maowusu Desert, Kubuqi Desert and Ordos Grasslands in the northern area cover the basin, so seismic data acquisition in this area is very difficult and the data often takes on inadequate precision, strong interference, low signal-noise ratio, and low resolution. Because of the complicated condition of the surface and the underground, it is very difficult to distinguish the thin beds and study the land facies high-resolution lithologic sequence stratigraphy according to routine seismic profile. Therefore, a method, which have clearly physical significance, based on advanced mathematical physics theory and algorithmic and can improve the precision of the detection on the thin sand-peat interbed configurations of land facies, is in demand to put forward.Generalized S Transform (GST) processing method provides a new method of phase space analysis for seismic data. Compared with wavelet transform, both of them have very good localization characteristics; however, directly related to the Fourier spectra, GST has clearer physical significance, moreover, GST adopts a technology to best approach seismic wavelets and transforms the seismic data into time-scale domain, and breaks through the limit of the fixed wavelet in S transform, so GST has extensive adaptability. Based on tracing the development of the ideas and theories from wavelet transform, S transform to GST, we studied how to improve the precision of the detection on the thin stratum by GST.Noise has strong influence on sequence detecting in GST, especially in the low signal-noise ratio data. We studied the distribution rule of colored noise in GST domain, and proposed a technology to distinguish the signal and noise in GST domain. We discussed two types of noises: white noise and red noise, in which noise satisfy statistical autoregression model. For these two model, the noise-signal detection technology based on GST all get good result. It proved that the GST domain noise-signal detection technology could be used to real seismic data, and could effectively avoid noise influence on seismic sequence detecting.On the seismic profile after GST processing, high amplitude energy intensive zone, schollen, strip and lentoid dead zone and disarray zone maybe represent specifically geologic meanings according to given geologic background. Using seismic sequence detection profile and combining other seismic interpretation technologies, we can elaborate depict the shape of palaeo-geomorphology, effectively estimate sand stretch, distinguish sedimentary facies, determine target area, and directly guide oil-gas exploration.In the lateral reservoir prediction in XF oilfield of Ordos Basin, it played very important role in the estimation of sand stretch that the study of palaeo-geomorphology of Triassic System and the partition of inner sequence of the stratum group. According to the high-resolution seismic profile after GST processing, we pointed out that the C8 Member of Yanchang Formation in DZ area and C8 Member in BM area are the same deposit. It provided the foundation for getting 430 million tons predicting reserves and unite building 3 million tons off-take potential.In tackling key problem study for SLG gas-field, according to the high-resolution seismic sequence profile, we determined that the deposit direction of H8 member is approximately N-S or NNE-SS W. Using the seismic sequence profile, combining with layer-level profile, we can interpret the shape of entrenched stream. The sunken lenticle indicates the high-energy stream channel, which has stronger hydropower. By this way we drew out three high-energy stream channels' outline, and determined the target areas for exploitation. Finding high-energy braided river by high-resolution sequence processing is the key technology in SLG area.In ZZ area, we studied the distribution of the main reservoir bed-S23, which is shallow delta thin sand bed, by GST processing. From the seismic sequence profile, we discovered that the schollen thick sand beds are only local distributed, and most of them are distributary channel sand and distributary bar deposit. Then we determined that the S23 sand deposit direction is NW-SE in west, N-S in central and NE-SW in east. The high detecting seismic sequence interpretation profiles have been tested by 14 wells, 2 wells mismatch and the coincidence rate is 85.7%. Based on the profiles we suggested 3 predicted wells, one well (Yu54) completed and the other two is still drilling. The completed on Is coincident with the forecastThe paper testified that GST is a effective technology to get high- resolution seismic sequence profile, compartmentalize deposit microfacies, confirm strike direction of sandstone and make sure of the distribution range of oil-gas bearing sandstone, and is the gordian technique for the exploration of lithologic gas-oil pool in complicated areas.

应急疏散语音告警信号设计参数的研究

Voice alarm plays an important role in emergency evacuation of public place, because it can provide information and instruct evacuation. This paper studied the optimization of acoustic and semantic parameters of voice alarms in emergency evacuation, so that alarm design can improve the evacuation performance. Both method of magnitude estimation and scale were implemented to investigate participants' perceived urgency of the alarms with different parameters. The results indicated that, participants evaluated the alarms with faster speech rate, with greater signal to noise ratio (SNR) and under louder noises more urgent. There was an interaction between noise level and content of voice alarm. Signals with speech rate below 4 characters / second were evaluated as non urgent at all. Intelligibility of the voice alarm was investigated by evaluating the key pointed recognition performance. The results showed that, speech rate’s effect was a marginal significance, and 7 characters / second has the highest intelligibility. It might because that the faster the signal spoken, the more attention was paid. Gender of speaker and SNR did not have a significant effect on the signals’ intelligibility. This paper also investigated impact of voice alarms' content on human behavior in emergency evacuation in a 3-D virtual reality environment. In condition of "telling the occupants what had happened and what to do", the number of participants who succeeded in evacuation was the largest. Further study, in which similar numbers of participants evacuate successfully in three conditions, indicated that the reaction time and evacuation time was the shortest in the aforesaid condition. Although one-way ANOVA shows that the difference was not significant, the results still provided some reference to the alarm design. In sum, parameters of voice alarm in emergency evacuation should be chosen to meet needs from both perceived urgency and intelligibility. Contents of the alarms should include "what had happened and what to do", and should vary according to noise levels in different public places.