Development of a multicriteria assessment model for ranking biomass feedstock collection and transportation systems

This study details multicriteria assessment methodology that integrates economic, social, environmental, and technical factors in order to rank alternatives for biomass collection and transportation systems. Ranking of biomass collection systems is based on cost of delivered biomass, quality of biomass supplied, emissions during collection, energy input to the chain operations, and maturity of supply system technologies. The assessment methodology is used to evaluate alternatives for collecting 1.8×10⁶ dry t/yr based on assumptions made on performance of various assemblies of biomass collection systems is based on cost of delivered biomass, quality of biomass supplied, emissions during collection, energy input to the chain operations, and maturity of supply system technologies. The assessment methodology is used to evaluate alternatives for collecting 1.8×10⁶ dry t/yr based on assumptions made on performance of various assemblies of biomass collection systems. A proposed collection option using loafer/stacker was shown to be the best option followed by ensiling and baling. Ranking of biomass transport systems is based on cost of biomass transport, emissions during transport, traffic congestion, and maturity of different technologies. At a capacity of 4×10⁶ dry t/yr, rail transport was shown to be the best option, followed by truck transport and pipeline transport, respectively. These rankings depend highly on assumed maturity of technologies and scale of utilization. These may change if technologies such as loafing or ensiling (wet storage) methods are proved to be infeasible for large-scale collection systems.     

Band splitting in overloaded isocratic elution chromatography I. The experimental evidence

A series of samples of increasing volume (from 0.001 to 4.0 cm3), containing the same constant concentration (40 g/l) of two simple compounds, ethylbenzoate and 4-tert.-butylphenol were injected on a Kromasil-C18 column with methanol-water (62:38. v/v) as the mobile phase. Complex band profiles were observed when the volume of the sample became large enough and strong band interference took place. The analysis of the fractions collected during the elution of the mixed band demonstrates that, for samples larger than 2 cm3, the band of 4-tert.-butylphenol is split into two separate bands, one eluted before and the other eluted after the band of ethylbenzoate. Such a phenomenon has never been observed yet in RPLC, under isocratic elution conditions.     

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     

炉前煤低温干馏工艺中的挥发分除尘

为了寻求优化的炉前煤低温干馏工艺中的挥发分除尘方案，在使用400目金属滤网对间歇式粉煤固体热载体热解装置挥发分除尘研究的基础上，将颗粒床过滤器用于该过程的除尘研究。热态除尘实验表明，颗粒床的使用有效地降低了滤网的过滤负荷。选用2mm石英砂和φ5mm×2mm瓷环作为滤料，通过对比实验发现，两种滤料除尘效率均在90％以上；随着过滤操作的进行，由于颗粒床内粉尘的沉积使其过滤效率有所提高，而对气、液收率的影响很小。结果表明，颗粒床与滤网结合可作为粉煤炉前低温干馏工艺中可供选择的挥发分除尘方案。     

粗糙集理论及进展

粗糙集理论是一种新型的处理模糊和不确定知识的数学工具。本文给出了粗糙集理论的特点，主要阐述了几种粗糙集理论的扩展模型，然后讨论了近来粗糙集理论与其他方法的结合，并进一步讨论了粗糙集理论研究的前景。     

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.     

无人机机载测控设备统一帧结构研究

提出了飞控计算机与测控系统之间接口的统一帧结构设计新的方法和思路,初步建立了完备的格式化通信信息集。对帧结构进行动态配置,使帧结构具有通用化功能和可操作性。探讨了帧结构校验方法,使之具有检/纠错功能。理论分析表明,新的统一帧结构设计能够有效提高无人机测控系统机载设备的通用化。     

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.