Hierarchical community classification and assessment of aquatic ecosystems using artificial neural networks

Benthic macroinvertebrate communities in stream ecosystems were assessed hierarchically through two-level classification methods of unsupervised learning. Two artificial neural networks were implemented in combination. Firstly, the self-organizing map (SOM) was used to reduce the dimension of community data, and secondly, the adaptive resonance theory (ART) was subsequently applied to the SOM to further classify the groups in different scales. Hierarchical grouping in community data efficiently reflected the impact of the environmental factors such as topographic conditions, levels of pollution, and sampling location and time across different scales. New community data not included in the training process were used to test the trained network model. The input data were appropriately grouped at different hierarchical levels by the trained networks, and correspondingly revealed the impact of environmental disturbances and temporal dynamics of communities. The hierarchical clusters based on a two-level classification method could be useful for assessing ecosystem quality and community variations caused by environmental disturbances.     

Patterning and predicting aquatic macroinvertebrate diversities using artificial neural network

A counterpropagation neural network (CPN) was applied to predict species richness (SR) and Shannon diversity index (SH) of benthic macroinvertebrate communities using 34 environmental variables. The data were collected at 664 sites at 23 different water types such as springs, streams, rivers, canals, ditches, lakes, and pools in The Netherlands. By training the CPN, the sampling sites were classified into five groups and the classification was mainly related to pollution status and habitat type of the sampling sites. By visualizing environmental variables and diversity indices on the map of the trained model, the relationships between variables were evaluated. The trained CPN serves as a 'look-up table' for finding the corresponding values between environmental variables and community indices. The output of the model fitted SH and SR well showing a high accuracy of the prediction (r>0.90 and 0.67 for learning and testing process, respectively) for both SH and SR. Finally, the results of this study, which uses the capability of the CPN for patterning and predicting ecological data, suggest that the CPN can be effectively used as a tool for assessing ecological status and predicting water quality of target ecosystems.     

污染水域微栖境中的无脊椎动物群落结构特征

栖境结构的异质性影响群落的空间格局．对不同微栖境中的无脊椎动物群落研究发现,尽管群落组成差异不明显,但丰度和多样性有很大差异。协惯量分析结果表明,相对丰度与环境变量显著相关。本研究支持了模板理论。     

Exciton scattering mechanism in a single semiconducting MgZnO nanorod

Excitonic phenomena, such as excitonic absorption and emission, have been used in many photonic and optoelectronic semiconductor device applications. As the sizes of these nanoscale materials have approached to exciton diffusion lengths in semiconductors, a fundamental understanding of exciton transport in semiconductors has become imperative. We present exciton transport in a single MgZnO nanorod in the spatiotemporal regime with several nanometer-scale spatial resolution and several tens of picosecond temporal resolution. This study was performed using temperature-dependent cathodoluminescence and time-resolved photoluminescence spectroscopies. The exciton diffusion length in the MgZnO nanorod decreased from 100 to 70 nm with increasing temperature in the range of 5 and 80 K. The results obtained for the temperature dependence of exciton diffusion length and luminescence lifetime revealed that the dominant exciton scattering mechanism in MgZnO nanorod is exciton-phonon assisted piezoelectric field scattering.     

Physiological parameter monitoring from optical recordings with a mobile phone

We show that a mobile phone can serve as an accurate monitor for several physiological variables, based on its ability to record and analyze the varying color signals of a fingertip placed in contact with its optical sensor. We confirm the accuracy of measurements of breathing rate, cardiac R-R intervals, and blood oxygen saturation, by comparisons to standard methods for making such measurements (respiration belts, ECGs, and pulse-oximeters, respectively). Measurement of respiratory rate uses a previously reported algorithm developed for use with a pulse-oximeter, based on amplitude and frequency modulation sequences within the light signal. We note that this technology can also be used with recently developed algorithms for detection of atrial fibrillation or blood loss.     

Isolation and characterization of Cronobacter from desiccated foods in Korea

A total of 115 desiccated food samples, including agricultural and marine products, were investigated for the presence of Cronobacter. Cronobacter species were characterized with biochemical tests. Antibiotic resistance was assessed with the disk diffusion method, and the molecular subtypes of Cronobacter isolates were identified using an automated repetitive sequence-based PCR (rep-PCR) system. A total of 18 (15.7%) Cronobacter strains were isolated from 115 desiccated food products. Fifteen Cronobacter isolates were C. sakazakii (13%), followed by 2 C. dublinensis (1.7%), and 1 C. universalis (0.9%). The most common antibiotic resistance of Cronobacter observed was against cephalothin (77.8%) followed by ampicillin (5.6%). With exception of 2 strains, all Cronobacter strains isolated from different sources were successfully differentiated by using the automated rep-PCR system, indicating that it can be used for the purpose of contamination or outbreak source tracking of the bacteria.     

邢钢烧结矿MgO含量的选择

邢钢烧结矿ＭｇＯ含量的选择王叔（邢台钢铁公司烧结厂）关键词烧结矿；ＭｇＯ含量；影响１前言邢钢烧结厂２×２４ｍ２烧结机原设计生产能力为７６．８万ｔ／ａ。经过８０年代后半期的技术改造，实际生产能力不断提高，进入９０年代后，每年以１０～１５万ｔ台阶递增。１...     

国外准分子激光步进机的发展概况及前景

本文概述了准分子激光步进机的发展概况，预测了在今后几代集成电路生产中的广阔前景。主要介绍了准分子激光窄谱带宽控制，中心波长调准的稳定性要求，光学系统设计与材料要求，以及对步进扫描曝光技术研究的迫切性。