Modern Analysis

The important advances being made in modern analytical methods are indicative of the fundamental changes that are occuring in the theory and practice of “analytical chemistry”. “Information optimization” demands a new approach in teaching and research, and calls for the intergration of chemistry with other scientific and technical disciplines.     

Application of similarity aggregation techniques to a population of paraplegic patients

We studied a population of paraplegic patients in order to give prominence to a possible relationship between the topography of their spinal lesion and the occurrence of special articular diseases (P.O.A.). According to the motor and sensory state of their spinal cord, we first tried to obtain a classification of these lesions (the usual one schematically separates ‘flaccid’ and ‘rigid’ paraplegics). We mainly put the emphasis on this clustering step of the study:

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Fluorescence monitoring of ultrasound degradation processes

Ultrasound-based water treatment is often applied for degradation of stable organic pollutants, such as polycyclic aromatic hydrocarbons and halogenated compounds. Monitoring the degradation process, during the application of ultrasound radiation, is of considerable economical interest. In this work, the possibility of performing on-line spectral analysis during sonication was examined and it was found that direct absorption or fluorescence readings are misleading. Optical monitoring is strongly affected by the absorption and scattering of light by cavitation micro-bubbles and ultrasound induced particulates. A model was developed to account for these effects and to allow for on-line fluorescence analysis. The model takes into account the absorption and scattering coefficients of the micro-bubbles and particulates, as well as their time dependent concentration. The model parameters are found from independent measurements where the pollutants are added to already sonicated pure water. Then, the model is tested for predicting the actual fluorescence behavior during the sonication process. It has been shown that the model allows for recovery of the true degradation data, as obtained by off-line HPLC measurements.     

Optimization of a GFAAS method for determination of total inorganic arsenic in drinking water

The new 10 μg l⁻¹ arsenic standard in drinking water has been a spur to the search for reliable routine analytical methods with a limit of detection at the μg l⁻¹ level. These methods also need to be easy to handle due to the routine analyses that are required in drinking water monitoring. Graphite furnace atomic absorption spectrometry (GFAAS) meets these requirements, but the limit of detection is generally too high except for methods using a pre-concentration or separation step. The use of a high-intensity boosted discharge hollow-cathode lamp decreases the baseline noise level and therefore allows a lower limit of detection. The temperature program, chemical matrix modifier and thermal stabilizer additives were optimized for total inorganic arsenic determination with GFAAS, without preliminary treatment. The optimal furnace program was validated with a proprietary software. The limit of detection was 0.26 μg As l⁻¹ for a sample volume of 16 μl corresponding to 4.2 pg As. This attractive technique is rapid as 20 samples can be analysed per hour. This method was validated with arsenic reference solutions. Its applicability was verified with artificial and natural groundwaters. Recoveries from 91 to 105% with relative standard deviation <5% can be easily achieved. The effect of interfering anions and cations commonly found in groundwater was studied. Only phosphates and silicates (respectively at 4 and 20 mg l⁻¹) lead to significant interferences in the determination of total inorganic arsenic at 4 μg l⁻¹.     

Protein family classification and functional annotation

With the accelerated accumulation of genomic sequence data, there is a pressing need to develop computational methods and advanced bioinformatics infrastructure for reliable and large-scale protein annotation and biological knowledge discovery. The Protein Information Resource (PIR) provides an integrated public resource of protein informatics to support genomic and proteomic research. PIR produces the Protein Sequence Database of functionally annotated protein sequences. The annotation problems are addressed by a classification-driven and rule-based method with evidence attribution, coupled with an integrated knowledge base system being developed. The approach allows sensitive identification, consistent and rich annotation, and systematic detection of annotation errors, as well as distinction of experimentally verified and computationally predicted features. The knowledge base consists of two new databases, sequence analysis tools, and graphical interfaces. PIR-NREF, a non-redundant reference database, provides a timely and comprehensive collection of all protein sequences, totaling more than 1,000,000 entries. iProClass, an integrated database of protein family, function, and structure information, provides extensive value-added features for about 830,000 proteins with rich links to over 50 molecular databases. This paper describes our approach to protein functional annotation with case studies and examines common identification errors. It also illustrates that data integration in PIR supports exploration of protein relationships and may reveal protein functional associations beyond sequence homology.     

CAHN－2000磁天平的调试与数据处理系统的研制

叙述了ＣＡＨＮ－２０００磁天平（美国）调试过程中如何解决液氮温区的测试，自制了磁天平与计算机的接口，编写了数据采集、处理和控制等高原 软件，节省了几万美元，部分指标超过原配套水平，三年来仪器在对国同外开放过程中，液氮温区的工作一直正常，实测了上千个样品，提供的数据已撰写数十篇文章在国内外刊物上发表。由此说明，要充分发挥进口仪器的使用效率，必须对仪器的工作原理、结构特点有透乇的了解，同时要有相当的自     

Interior Layers for Second-Order Singular Equations

Our aim in this article is to study singularly perturbed problems which display boundary layers in the interior of the domain. These interior boundary layers which supplement the usual boundary layers at the boundary, are generated by discontinuities in the data. Second-order linear elliptic one-dimensional and multi-dimensional problems are considered in this article.     

基于智能数据采集器的研究与实现

针对目前各行业数字化、智能化产品应用日趋广泛，数据的获取、传输、分析、应用尤为重要，如何避免采集设备接口单一、功能固定、实用性差等缺点，提出采用ARM嵌入式工控模块M9080-N20为基础，采用VK3266串口芯片扩展UART串行接口，提出基于73K222AU调制解调器、HR219307变压器实现采集器二线模拟通信，并支持以太网、CAN总线和UART串行通信，可以有效解决数据远程采集、传输和控制，适用于特殊环境设备故障检测、诊断和抢修。实验结果证明，智能数据采集器不仅具有多种型号设备故障诊断功能；还能实现野外快速通信组网，不同类型设备数据远程采集、传输、分析和控制功能，在军民融合产品上具有广阔的应用前景和实用价值。     

Fuzzy structure-activity relationships

While quantitative structure-activity relationships attempt to predict the numerical value of the activities, it is found that statistically good predictors do not always do a good job of qualitatively determining the activity. This study shows how Fuzzy classifiers can be used to generate Fuzzy structure-activity relationships which can more accurately determine whether or not a compound will be highly inactive, moderately inactive or active, or highly active. Four examples of these classifiers are presented and applied to a well-studied activity dataset.     

Polymer chain conformation of copolymers with different monomer size: C NMR spectroscopy and MALS study

Copolymer composition, distribution and molecular size of the comonomer influence the final properties of polymer materials. Such influence can be followed from the effect on the chain conformation in solution determined from the scaling law between radius of gyration and molecular weight.