沉降比在活性污泥法处理污水中的作用

通过分析沉降变化规律与其他有关参数之间的对应关系，旨在掌握和控制活性污泥法工艺处理污水的工艺运行情况，使处理后水质稳定达标。     

中性磷萃淋树脂吸附铼的性能和机理研究ⅢCL－P＿（350）－KReO＿4－HNO＿3体系

本文报道四甲基膦酸二甲庚酸萃淋树脂（ＣＬ－Ｐ＿（３５０）从硝酸溶液中吸附鳞的性能和机理研究。实验结果表明，吸附平衡服从Ｌａｎｇｍｕｉｒ经验等温式。测得吸附物分子中Ｐ（３５０）与Ｒｅ（Ⅶ）的摩尔比为２：１。Ｒｅ（Ⅶ）是以形式被树脂吸附，其吸附机理属于综合反应：并测定了吸附过程的热力学函数。     

BP网络及其应用

基函数选取和系数求解是函数逼近中的两个关键问题,目前广泛应用的回归分析或其它映射方法均有局限性。采用人工神经网络中的BP网较好地解决了这两个问题,对理论和实际的数据进行了比较与验证,结果表明.BP网络有助于提高数据处理的可靠性与预测的精度.     

沼气在果菜粮贮藏业上的应用

文中介绍沼气这种新型绿色能源在果菜粮贮藏中的应用情况,详尽描述了其在贮藏果品、蔬菜中的应用过程,文中对其作用的原理和益处也给予了适当介绍。     

Expression and Characterization of HGV E2 cDNA in Pichia pastoris

A 559 base pair fragment of cDNA locating at the putative E2 region of GBV-C/HGV was in-serted into Pichia pastoris expression vector pPICgK in the reading frame of α-factor secreting signal pep-tide. The recombinant expression plasmid pPIC9K-E2 was introduced into P. pastoris GSll5 with electro-poration and recombined with the host genome by homological recombination. The His+Mut+ recombinantyeasts were selected and cultivated in the BMMY medium. After 3 days induction with 0. 5% methanol,the target protein(E2) accumulated up to 30% of total proteins in the supernatant. The expressed E2 pro-tein was proved possessing antigenicity and high specificity with Western blot and ELISA probed with serafrom the immunized rabbits and the patients infected by GBV-C/HGV.     

AC发泡剂新工艺研究—Ⅲ电解氧化法

用钌钛金属阳极在含有Ｃｌ—和Ｂｒ－离子的酸性溶液中进行电解氧化联二脲制备偶氮二甲酰胺，获得产品得率为９３—９８％、纯度为９９．６％、电流效率为８８－９２％。母液可循环使用，基本不产生废液．     

森林面积分布系统的最优控制存在性问题

本文研究森林面积分布系统的最优控制问题。本文将林木总和长消率作为控制变量，以“范数最小”来衡量其最优性，利用空间Ｌ＾２（０，Ｔ）Ｔ〉０的自反、光滑和严格凸性，给出了森林面积分布系统最优控制的一个存在性定理。     

可压缩流体网络的建模方法

本文运用网络分析手段,首次提出了任意拓扑结构可压缩流体网络动态特性的建模方法.该方法突破了目前在流体网络分析中普遍采用的“小扰动”线性化处理方法的局限。     

Learning attention-based strategies to cooperate for multi-agent path finding

Multi-agent path finding (MAPF) is a challenging multi-agent systems problem where all agents are required to effectively reach their goals concurrently with not colliding with each other and avoiding obstacles. In MAPF, it is a challenge to effectively express the observation of agents, utilize historical information, and effectively communicate with neighbor agents. To tackle these issues, in this work, we proposed a well-designed model that utilizes the local states of nearby agents and outputs an optimal action for each agent to execute. We build the local observation encoder by using residual attention CNN to extract local observations and use the Transformer architecture to build an interaction layer to combine local observations of agents. With the purpose of overcoming the deficiency of success rate, we also designed a new evaluation index, namely extra time rate (ETR). The experimental results show that our model is superior to most previous models in terms of success rate and ETR. In addition, we also completed the ablation study on the model, and the effectiveness of each component of the model was proved.