间歇式活性污泥法处理制革废水工程实例研究

介绍了由传统活性污泥法转换为间歇式活性污泥法处理制革废水的工程实践、运行工序及运行结果。转换后废水处理能力由700m^3/d提高到1200m^3/d，处理水达到国家排放标准。     

最小化总误时的随机型单机排序问题

本文研究最小化总误时的随机型(即工件的加工时间为随机变量)排序问题,推广了[1—2]的主要结果。     

Functionalized gold nanoparticles as additive to form polymer/metal composite matrix for improved DNA sequencing by capillary electrophoresis

A new matrix additive, poly (N,N-dimethylacrylamide)-functionalized gold nanoparticle (GNP-PDMA), was prepared by “grafting-to” approach, and then incorporated into quasi-interpenetrating network (quasi-IPN) composed of linear polyacrylamide (LPA, 3.3 MDa) and PDMA to form novel polymer/metal composite sieving matrix (quasi-IPN/GNP-PDMA) for DNA sequencing by capillary electrophoresis. Without complete optimization, quasi-IPN/GNP-PDMA yielded a readlength of 801 bases at 98% accuracy in about 64 min by using the ABI 310 Genetic Analyzer at 50 °C and 150 V/cm. Compared with previous quasi-IPN/GNPs, quasi-IPN/GNP-PDMA can further improve DNA sequencing performances. This is because the presence of GNP-PDMA can improve the compatibility of GNPs with the whole sequencing system, enhance the entanglement degree of networks, and increase the GNP concentration in system, which consequently lead to higher restriction and stability, higher apparent molecular weight (MW), and smaller pore size of the total sieving networks. Furthermore, the composite matrix was also compared with quasi-IPN containing higher-MW LPA and commercial POP-6. The results indicate that the composite matrix is a promising one for DNA sequencing to achieve full automation due to the separation provided with high resolution, speediness, excellent reproducibility, and easy loading in the presence of GNP-PDMA.     

Backtracking and exchange of information: Methods to enhance a beam search algorithm for assembly line scheduling

Beam search (BS) is used as a heuristic to solve various combinatorial optimization problems, ranging from scheduling to assembly line balancing. In this paper, we develop a backtracking and an exchange-of-information (EOI) procedure to enhance the traditional beam search method. The backtracking enables us to return to previous solution states in the search process with the expectation of obtaining better solutions. The EOI is used to transfer information accumulated in a beam to other beams to yield improved solutions.     

Two local search approaches for solving real-life car sequencing problems

The NP-hard problem of car sequencing appears as the heart of the logistic process of many car manufacturers. The subject of the ROADEF’2005 challenge addressed a car sequencing problem proposed by the car manufacturer RENAULT, more complex than the academic problem generally addressed in the literature. This paper describes two local search approaches for this problem. In the first part, a new approach by very large-scale neighborhood search is presented. This approach, designed during the qualification stage preceding the final, is based on an original integer linear programming formulation. The second part is dedicated to the approach which enabled us to win the ROADEF’2005 challenge. Inspired by the latest works on the subject, this one is based on very fast explorations of small neighborhoods. Our contribution here is mainly algorithmic, in particular by showing how much exploiting invariants speeds up the neighborhood evaluation and contributes to the diversification of the search. Finally, the two approaches are compared and discussed through an extensive computational study on RENAULT’s benchmarks. The main conclusion drawn at this point is that sophisticated metaheuristics are useless to solve car sequencing problems. More generally, our victory on ROADEF’2005 challenge demonstrates that algorithmic aspects, sometimes neglected, remain the key ingredients for designing and engineering high-performance local search heuristics.     

Learning activity sequencing in personalized education system

Personalized education provides an open learning environment which enriches the advanced technologies to establish a paradigm shift, active and dynamic teaching and learning patterns. E-learning has a various established approaches to the creation and sequencing of content-based, single learner, and self-paced learning objects. However, there is little understanding of how to create sequences of learning activities which involve groups of learners interacting within a structured set of collaborative environments. In this paper, we present an approach for learning activity sequencing based on ontology and activity graph in personalized education system. Modeling and management of learning activity and learner are depicted, and an algorithm is proposed to realize learning activity sequencing and learner ontology dynamically updating.     

Characterization and de novo sequencing of snow crab tropomyosin enzymatic peptides by both electrospary ionization and matrix‐assisted laser desorption ionization QqToF tandem mass spectrometry

The protein tropomyosin (TM) is a known major allergen present in shellfish causing frequent food allergies. TM is also an occupational allergen generated in the working environment of snow crab (Chionoecetes opilio) processing plants. The TM protein was purified from both claw and leg meats of snow crab and analyzed by electrospray ionization and matrix‐assisted laser desorption/ionization (MALDI) using hybrid quadruple time‐of‐flight tandem mass spectrometry (QqToF‐MS). The native polypeptide molecular weight of TM was determined to be 32 733 Da. The protein was further characterized using the ‘bottom‐up’ MS approach. A peptide mass fingerprinting was obtained by two different enzymatic digestions and de novo sequencing of the most abundant peptides performed. Any post‐translational modifications were identified by searching their calculated and predicted molecular weights in precursor ion spectra. The immunological reactivity of snow crab extract was evaluated using specific antibodies and allergenic reactivity assessed with serum of allergic patients. Subsequently, a signature peptide for TM was identified and evaluated in terms of identity and homology using the basic local alignment search tool (BLAST). The identification of a signature peptide for the allergen TM using MALDI‐QqToF‐MS will be critical for the sensitive and specific quantification of this highly allergenic protein in the work place. Copyright © 2010 John Wiley & Sons, Ltd.     

基于SLAF-seq的天竺桂群体遗传变异分析

【目的】探讨我国天竺桂资源的遗传多样性及群体的空间分布格局。【方法】分别对来自7个天然群体的30份天竺桂资源进行特异位点扩增片段测序(specific-locus amplified fragment sequencing, SLAF-seq)。基于检测到的SNP位点信息进行遗传变异分析。【结果】各样品的平均测序深度为15.11倍,开发获得 1 296 000个SLAF标签,其中377 250个SLAF标签在不同样品间具有多态性,共包含3 409 402个群体SNP,经过滤,最终获得268 821个高度一致性的群体SNP。基于这些SNP的系统进化分析发现,天竺桂是由中国东部向中国西部逐渐进化的。系统进化、主成分分析和群体结构分析均表明,来自5省(直辖市)7个天然群体的群体内变异小于群体间变异。30份天竺桂资源可分为2个大的亚群,其中,第1亚群位于中国第2阶梯上,第2亚群位于中国第3阶梯上,2个亚群间被大兴安岭—太行山脉—巫山—雪峰山山脉阻隔。第2亚群又可进一步分为3个小亚群,其中,来自浙江省和安徽桃岭的为第1个小亚群,来自安徽霍山的为第2个小亚群,而来自河南伏牛山的为第3个小亚群,第1个和第2个小亚群间被长江阻隔。【结论】山脉和湖泊的阻隔可能是造成天竺桂遗传分化的重要因素。本研究首次揭示天竺桂遗传结构及地理变化规律,为我国天竺桂资源的有效利用与科学保护提供理论依据。