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电池健康状态（state of health，SOH）是保证系统安全稳定运行的关键，健康状态估计不准将影响电池的使用性能，甚至引发电池滥用等问题。电池电化学阻抗谱通过宽频范围内电池的阻抗特征来反映其内部的电化学过程，蕴含了大量电池老化信息，已经逐渐成为分析锂离子电池性能的有力工具。然而，传统的电池阻抗谱测试方法耗时长、成本高昂。为此，以实现锂离子电池的精细化检测与健康状态快速评估为目标，围绕基于电化学阻抗谱重构技术的电池健康状态估计方法展开研究。通过逆重复最大长度序列设计多频电流激励信号，实现了电池阻抗谱的快速测试。采用连续小波变换开展阻抗谱重构，从而获取目标频率范围内的电池阻抗信息，整个过程耗时小于4.5 min。通过不同老化状态电池在特殊频率点下的重构阻抗幅值建立经验模型，实现了电池健康状态的快速准确评估。

Copyright of Journal of Geodesy & Geodynamics (1671-5942) is the property of Editorial Board Journal of Geodesy & Geodynamics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Electric Power Science & Technology is the property of Changsha University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Feed Industry is the property of Liaoning Provincial Institute of Agricultural Mechanization and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

[Objective]To establish the characteristic fingerprint of tobacco traceability by the determination of mineral elements in tobacco leaves combined with chemometrics method, and to verify the accuracy and reliability of the method. [Method]The contents of inorganic elements in 25 tobacco leaf samples planted in soils from five different areas were analyzed by ICP-OES combined with microwave digestion method. The data matrix was sequentially analyzed by one-way-ANOVA, principal component analysis and discriminant analysis. [Result]There were significant differences among tobacco leaves planted in different soils about the contents of mineral elements. The first two principal components obtained by principal component analysis could approximately reflect the information of original data, and realized the traceability of tobacco planted in soils from different regions by analyzing the mineral elements’ contents. Fisher discriminant analysis and leave-one-out cross-validation test were performed to validate these results, ideal verification results were obtained, and the correct discrimination rate were 100%, respectively. [Conclusion]Based on the specific differences of inorganic elements could discriminate the geographical origins of tobacco. [ABSTRACT FROM AUTHOR]

Copyright of Food Science & Technology & Economy is the property of Grain Science & Technology & Economy Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Two coordination polymers ([Co(tib) (mpda) (H2 O)2 ] ·H2 O, [Ni(tib) (mpda) (H2 O)2 ] ·H2 O) were synthesized based on flexible phenyldiacetic acid, and characterized by elemental analysis, infrared spectroscopy, thermogravimetric analysis and X-ray single crystal diffraction. In the structure of [Ni(tib)(mpda)(H2 O)2 ]·H2 O, the tib ligands coordinate as three nodes with Co(II) ions to form a 2D grid plane; cis-mpda ligands are attached to the 2D grid face as end-bases; through the O--H...O interaction between the mpda virgin carboxyl O and the coordinated water molecule (bond length of O1...O3 is 0. 262 4 nm, ∠O5--H5A...O2 = 155. 41°), a three-dimensional supramolecular network structure is formed. Two coordination polymers belong to the heterogeneous crystal structure. The specific surface areas of the two coordination polymers are 54 and 58 m² / g, respectively. [Ni(tib) (mpda) (H2 O)2 ] ·H2 O has a complete cyclic voltammetric curve (reduction and oxidation potentials are 0. 205 and 0. 563 V, respectively) and good scanning rate. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: To investigate the effects of long-chain non-coding RNA (LncRNA) MYU on the cycle distribution, cell proliferation, migration, invasion, and apoptosis of glioma cells, and to preliminarily explore its mechanism of action. Methods: The expression of LncRNA MYU in human brain normal glial cells HEB and glioma cells (U-251MG, A172, SHG139) was detected by real- time fluorescent quantitative PCR (RT-qPCR). SHG139 cells were selected and divided into normal control (NC) group, si-con group, and si-LncRNA MYU group for transfection experiments, and RT-qPCR was applied to detect the transfection effect. The effects of silencing LncRNA MYU on the cell cycle distribution and apoptosis, cell proliferation and, cell migration and invasion of SHG139 cells were detected respectively by flow cytometry, cell counting kit (CCK-8), and Transwell experiments. Western blot was used to detect the expression of matrix metalloproteinase (MMP-2), MMP-9, Cleaved caspase-3, Cleaved caspase-9, and Phosphatidylinositol-3-hydroxykinase/protein kinase B (PI3K/Akt) signaling pathway-related proteins. Results: The expression of LncRNA MYU in glioma cell lines was significantly higher than that in normal human brain glial cells(P<0.05), thereby SHG139 cells with the highest expression levels were selected for transfection experiments. Silencing LncRNA MYU can significantly induce G0-G1 phase arrest, inhibit the proliferation, migration and invasion, and induce apoptosis in SHG139 cells(P<0.05). Silencing LncRNA MYU can significantly inhibit the expression of MMP-2, MMP-9, p-PI3K and p-AKT, and promote the expression of Cleaved caspase-3 and Cleaved caspase-9(P<0.05). Conclusion: Silencing LncRNA MYU can induce G0-G1 phase arrest, inhibit cell proliferation, migration and invasion, and promote cell apoptosis in glioma cells, and its mechanism may be related to the inhibition of PI3K/AKT signaling pathway. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Tissue Engineering Research / Zhongguo Zuzhi Gongcheng Yanjiu is the property of Chinese Journal of Tissue Engineering Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Science & Technology & Economy is the property of Grain Science & Technology & Economy Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Science & Technology & Economy is the property of Grain Science & Technology & Economy Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Science & Technology & Economy is the property of Grain Science & Technology & Economy Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Copyright of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Food Safety & Quality is the property of Journal of Food Safety & Quality Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Food Science & Technology & Economy is the property of Grain Science & Technology & Economy Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transactions of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Geodesy & Geodynamics (1671-5942) is the property of Editorial Board Journal of Geodesy & Geodynamics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Materials Engineering / Cailiao Gongcheng is the property of Journal of Materials Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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Copyright of Chinese Journal of Tissue Engineering Research / Zhongguo Zuzhi Gongcheng Yanjiu is the property of Chinese Journal of Tissue Engineering Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Synthetic Crystals is the property of Journal of Synthetic Crystals Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shaanxi University of Science & Technology is the property of Journal of Shaanxi University of Science & Technology Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Water Conservancy & Electric Power Technology & Application is the property of Omniscient Pte. Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives: In the era of earthquake big data, it is of great significance to develop efficient automatic and accurate seismic recognition algorithms. Convolutional neural networks (CNN) has played an effective role in seismic automatic recognition in seismology. However, in the environment of noise interference, CNN identification accuracy is easily affected by noise and leads to decline. Generally, CNN methods eliminate the data with serious noise pollution through filtering and pre-processing or manual screening, so as to improve the accuracy of identification. Methods: In view of the problem of seismic event recognition, we propose a new method, normal time-frequency transform (NTFT) and CNN are combined for realizing automatic and accurate identification of seismic signals. The NTFT+CNN model has good robustness and does not require manual pre-processing and denoising of seismic data in advance. Taking 19 884 seismic events and 17 640 noise data randomly sampled from the Yingjiang County of Yunnan province, China, the comparison between CNN and NTFT+CNN was conducted from the respect of large samples and small samples. Results: In the experiments of the three stations, the recognition accuracy of CNN model is 93.10%, and the recognition accuracy of the NTFT+CNN model is 97.80%, which means that the introduction of NTFT reduces the recognition error rate by three times. It shows that NT⁃ FT+CNN model can recognize the seismic signal more effectively under the condition of noise interference. At the same time, the epoch in CNN model is 29 and that of in NTFT+CNN is 18, which shows that the convergence in NTFT+CNN model is quicker and more stable. In the experiment of a single station, the comparison of three typical noise conditions was investigated. The recognition accuracy of CNN model was 95.98%, 91.56% and 90.36% in weak background noise, strong background noise and similar waveform noise, respectively, while the recognition accuracy of NTFT+CNN model was 99.80%, 97.21% and 98.50%, respectively, which further verified the recognition effect of NTFT on noise and seismic signal, the correctness of model results. The NTFT+CNN model was applied to identify the seismic impulse noise data shared by the Southern California Earthquake Data Center. Comparing to CNN, NTFT+CNN model has more advantages on convergence speed, recognition accuracy and the number of training samples required. Conclusions: NTFT provides a new and efficient way for the recognition of seismic signal in neural network structure. [ABSTRACT FROM AUTHOR]

Copyright of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objectives: CAE (convolutional autoencoder) combines the autoencoder neural network structure and the convolutional network structure. This paper processes the gravity data based on the deep learning, and reconstructs the gravity contour image from the noisy gravity data with the CAE. The autoencoder structure contains the equal dimensional input and output data, which goes for the gravity data processing. The convolutional network structure is widely used in image recognition recent years, which can learn and recognize the specific objects in an image. Methods: To create the training set, we generate 1000 hexahedrons with the random triaxial length parameters and the random density to simulate the natural gravity source bodies. The 2D gravity data set for these bodies is fast computed with the gravity forward formula and the noisy gravity data set is generated by adding Gaussian noise to the computed data. Meanwhile the accuracy of the length parameters and density is limited in order to improve the representativeness of the training data set. Hence the 2D gravity data and the noisy data will be output and input data of the CAE. We design 5 layers CAE. The input and output layers both are 26×26. 32 and 64 feature maps are generated with 3×3 convolution kernels in the inner layers. The training is executed using RMSProp(root mean square propagation) optimizer. Results: To test the generalization of the trained CAE, the testing set with 500 samples is generated in the same way with the training set. The relative error histogram on the testing set shows that the reconstructing error is less than 5% and most of the error is around 0. To test the recognition of the gravity features in the 2D gravity, we test the CAE with simulated gravity data which contain 2 and more gravity anomalies. The results show that the CAE can recognize all gravity anomalies in an noisy gravity image and reconstruct them and the output image shows fairly fine reconstruction from the gravity with 10% noise. The measured gravity data of Kauring testing ground are used to test the generalization performance of the CAE. The reconstructed image is compared with the traditional FFT(fast Fourier transform) filtering and db wavelet filtering results. To increase the reconstruction difficulty, the Kauring data is added with 10% Gaussian noise. The results show that the trained CAE performs significantly less error than the FFT filter and the wavelet filter. Conclusions: In terms of reconstructing performance, the CAE can avoid over processing that may eliminate the real gravity anomaly, which is often seen in filtering especially for FFT filtering. The CAE reconstructs all of the 3 gravity anomalies of Kauring while the FFT filtering reconstructs 2. And the over-smoothing artifact is less than filtering methods. The CAE can process 2D gravity data and show lower error and generate less artifacts than filtering methods in our tests with testing set, simulated gravity data and measuring data. Beyond that, this article reveals that the deep learning can learn gravity image. With the convolution structure in a neural network, the network can learn single gravity anomaly samples and extensively recognize all gravity anomalies in a gravity image, which signifies that the gravity can integrate with the artificial intelligence technology. [ABSTRACT FROM AUTHOR]

Objectives: Based on the gravity focusing inversion, we propose the multi‑scale source grid focusing inversion. This method aims to reduce the computation time and improve the spatial resolution of the focusing inversion. Methods: Firstly, the source grid is divided into the coarse grid, which contains less cells than the regular grid. Then we perform the focusing inversion in the coarse grid using conjugate gradient method. In the coarse grid phase it consumes short computation time for each iteration. Secondly, as the relative residual decreases to a low threshold value, the iteration is suspended and the coarse grid density is mapped into the fine grid. We compared 3 density mapping methods. Those methods use the average value of coarse cells, the value of the maximum area coarse cell and the maximum value of coarse cells. Then we adopt the average value method for the optimum density mapping. Finally, the iteration is resumed in the fine grid and converges to the final solution. Results: The model testing result shows: (1) More than 50% computation time is cut down by using the multi‑scale source grid. (2)Compare to the single scale focusing inversion, the multi‑scale source grid focusing inversion of gravity and gravity gradient data considerably improve the revelation of the single hexahedron model, the double hexahedrons model placed horizontally and the double hexahedrons model with different sizes and depths. (3)In particular the revelation of the body bottom or the deeper bodies is improved from the regular gravity inversions. The measured data testing result shows: (1)The inversion result of gravity and gravity gradient data of Kauring testing ground is generally consistent with the known results. The revelation of the top and bottom of the center anomaly body is close to the previous results. (2)The result indicates the larger depth of the south side anomaly body than the previous results. That supports the wide and gentle slope form of the gravity gz data at the south side. Conclusions: The multi‑scale grid focusing inversion can process the gravity or/and gravity gradient simulated or measured data. This method significantly reduces the computation time and improves the resolution ability from the regular focusing inversion with the single scale source grid. [ABSTRACT FROM AUTHOR]

Copyright of China Pulp & Paper is the property of China Pulp & Paper Magazines Publisher and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Xinjiang Agricultural Sciences is the property of Xinjiang Agricultural Sciences Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Modern Laboratory Medicine is the property of Journal of Modern Laboratory Medicine Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Plastic film mulching plays an important role in Xinjiang cotton production. The main function of mulching is to maintain soil temperature and moisture. Plastic film mulching during the whole growth period may lead to soil temperature overheat and root respiration obstruction. In addition, the biodegradable film is expected to replace traditional plastic films. However, several studies have shown that the degradation period of biodegradable mulch film does not match the growth requirements of cotton. Therefore, balancing the relationship among mulching time, crop growth demand and the changes of farmland environmental factors is the key scientific issue to control the pollution of residual plastic film in Xinjiang. Field experiments were conducted in 2016 and 2017 to investigate the mechanisms behind the effects of mulching time on cotton (Gossypium hirsutum Linn.) growth. Six mulching time (40 d, 55 d, 70 d, 85 d, 100 d and whole growing season mulching) were designed. The cotton yield and Water Use Efficiency (WUE) were simulated by using Root Zone Water Quality Model-Version 2 (RZWQM2) model. The parameters of the RZWQM2 model were calibrated and verified by the measured data of 2016 and 2017. Then, the formation processes of biomass, yield and water use efficiency under the influence of different mulching times were simulated at intervals of 3 days, and the similar processes mentioned above were predicted in 2018 and 2019. The objective of this work was to provide a decision method for the model to simulate soil moisture changes and predict crop yields under the conditions of crop mulching, and it would be helpful to determine the reasonable mulching time and reduce the residual plastic film pollution in cotton field on the premise of ensuring high and stable yield. The model validation results showed that the Root Mean Square Error (RMSE) and Mean Square Error (MRE) between the simulated and measured soil water content in each layer of soil ranged from 0.02 to 0.04 cm3/cm3 and 5.90% to 28.66%. The simulation effect of the upper soil layer was not as good as that of the lower soil layer because of more complex temporal and spatial changes of soil surface organic matter content, macropores and other properties than deep soils. The aboveground biomass of two years increased with the extension of mulching time, and the seed cotton yield and WUE showed a trend of first increasing and then decreasing. The growth rate of seed cotton yield and water use efficiency was the highest when the mulching time was 73-81 d, and the yield was higher when the mulching time was mid-to-early August. At this time, the cotton canopy has been closed, and the surface receives less solar radiation, which maximally inhibits soil evaporation, thus reducing the non-productive water consumption and increasing the proportion of productive water consumption. At the same time, the soil ventilation and air permeability are improved after uncovering the film, and the soil microbial activity is enhanced. Therefore, it can be concluded that uncovering film in this period had little effect on cotton growth, and the tensile strength of mulching film at this time was still high, which was more conducive to mechanical recovery. The optimum mulching time of 91-99 d in southern Xinjiang was beneficial to reduce the risk of residual film contamination and maintain high seed cotton yield and water use efficiency. The mechanism of film mulching cycle on key physiological and ecological processes, such as water consumption structure transformation, salt distribution, nutrient migration and absorption in cotton field need further studies. Related work needs to be carried out in the future research, so as to improve the level of cognition and optimize relevant supporting measures. [ABSTRACT FROM AUTHOR]

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Copyright of Hydrographic Surveying & Charting / Haiyang Cehui is the property of Hydrographic Surveying & Charting Editorial Board and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)