The current status of European wetland inventories and classifications

The status of wetland inventory and classification is considered for 44 European countries, as well as for the continent as a whole. Data and information were obtained from questionnaires compiled by the International Waterfowl and Wetland Research Bureau, the MedWet sub-project on inventory and monitoring, and the Ramsar Bureau. Nine European countries have national wetland inventories, and 32 have inventories of sites of international importance listed under the Ramsar Convention. There has been a trend in producing regional or continental inventories for wetlands that are important as waterfowl habitat. There is an urgent need to produce wetland inventories for all European countries. The Ramsar database takes into consideration hydrological and economic wetland values, as well as ecological ones. The Ramsar classification lists a total of 35 wetland types, and is sufficiently flexible that it could be used for classifying European wetlands at the national scale.     

根瘤菌资源数据库（RRDB）的建立

在总结我室多年对根瘤菌资源调查与分类研究的基础上,建立了根瘤菌资源数据库（ＲＲＤＢ）。此库依据根瘤菌研究特点而设计,包括：基本信息、采集信息、保藏信息、回接信息、参考文献、性状信息、菌株说明等七个子库。目前收录了来自国内２１个省或地区及国外部分研究单位提供的;并经全面性状分析与分类研究的２８６个菌株的信息,每个菌株设有寄主来源、固氮酶活性、碳源、氮源的利用等３２１个数据项。该库具有数据维护、查询检索、数据统计、输出打印等功能,引入并连接了聚类分析软件包－ＭＩＮＴＳ系统,可以满足当前研究的需要。     

A real-time database/models base/expert system in predictive microbiology

Summary This paper describes the development and operation of a database/models base/expert system funded by the Ministry of Agriculture, Fisheries and Food in the UK. As part of an on-going coordinated program on predictive microbiology, the system being established involves storage of data and models relevant to changes in populations of food-borne pathogens under given conditions. The system is due to be completed by March 1994.     

Statistical analysis of vertebrate sequences reveals that long genes are scarce in GC-rich isochores

We compared the exon/intron organization of vertebrate genes belonging to different isochore classes, as predicted by their GC content at third codon position. Two main features have emerged from the analysis of sequences published in GenBank: (1) genes coding for long proteins (i.e., 500 aa) are almost two times more frequent in GC-poor than in GC-rich isochores; (2) intervening sequences (=sum of introns) are on average three times longer in GC-poor than in GC-rich isochores. These patterns are observed among human, mouse, rat, cow, and even chicken genes and are therefore likely to be common to all warm-blooded vertebrates. Analysis of Xenopus sequences suggests that the same patterns exist in cold-blooded vertebrates. It could be argued that such results do not reflect the reality because sequence databases are not representative of entire genomes. However, analysis of biases in GenBank revealed that the observed discrepancies between GC-rich and GC-poor isochores are not artifactual, and are probably largely underestimated. We investigated the distribution of microsatellites and interspersed repeats in introns of human and mouse genes from different isochores. This analysis confirmed previous studies showing that Ll repeats are almost absent from GC-rich isochores. Microsatellites and SINES (Alu, B1, B2) are found at roughly equal frequencies in introns from all isochore classes. Globally, the presence of repeated sequences does not account for the increased intron length in GC-poor isochores. The relationships between gene structure and global genome organization and evolution are discussed.     

Prototypic sequences for human repetitive DNA

Summary We report a collection of 53 prototypic sequences representing known families of repetitive elements from the human genome. The prototypic sequences are either consensus sequences or selected examples of repetitive sequences. The collection includes: prototypes for high and medium reiteration frequency interspersed repeats, long terminal repeats of endogenous retroviruses, alphoid repeats, telomere-associated repeats, and some miscellaneous repeats. The collection is annotated and available electronically.[/ap ]Offprint requests to: J. Jurka     

Voice Pathologies Classification and Detection Using EMD-DWT Analysis Based on Higher Order Statistic Features

BackgroundThe voice is a prominent tool allowing people to communicate and to change information in their daily activities. However, any slight alteration in the voice production system may affect the voice quality. Over the last years, researchers in biomedical engineering field worked to develop a robust automatic system that may help clinicians to perform a preventive diagnosis in order to detect the voice pathologies in an early stage.MethodIn this context, pathological voice detection and classification method based on EMD-DWT analysis and Higher Order Statistics (HOS) features, is proposed. Also DWT coefficients features are extracted and tested. To carry out our experiments a wide subset of voice signal from normal subjects and subjects which suffer from the five most frequent pathologies in the Saarbrücken Voice Database (SVD), is selected. In The first step, we applied the Empirical Mode Decomposition (EMD) to the voice signal. Afterwards, among the obtained candidates of Intrinsic Mode Functions (IMFs), we choose the robust one based on temporal energy criterion. In the second step, the selected IMF was decomposed via the Discrete Wavelet Transform (DWT). As a result, two features vector includes six HOSs parameters, and a features vector includes six DWT features were formed from both approximation and detail coefficients. In order to classify the obtained data a support vector machine (SVM) is employed. After having trained the proposed system using the SVD database, the system was evaluated using voice signals of volunteer's subjects from the Neurological department of RABTA Hospital of Tunis.ResultsThe proposed method gives promising results in pathological voices detection. The accuracies reached 99.26% using HOS features and 93.1% using DWT features for SVD database. In the classification, an accuracy of 100% was reached for “Funktionelle Dysphonia vs. Rekrrensparese” based on HOS features. Nevertheless, using DWT features the accuracy achieved was 90.32% for “Hyperfunktionelle Dysphonia vs. Rekurrensparse”. Furthermore, in the validation the accuracies reached were 94.82%, 91.37% for HOS and DWT features, respectively. In the classification the highest accuracies reached were for classifying “Parkinson versus Paralysis” 94.44% and 88.87% based on HOS and DWT features, respectively.ConclusionHOS features show promising results in the automatic voice pathology detection and classification compared to DWT features. Thus, it can reliably be used as noninvasive tool to assist clinical evaluation for pathological voices identification.     

Open access to tree genomes: the path to a better forest

An open-access culture and a well-developed comparative-genomics infrastructure must be developed in forest trees to derive the full potential of genome sequencing in this diverse group of plants that are the dominant species in much of the earth''s terrestrial ecosystems.