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Application of Microbial BOD Sensors in Marine Monitoring

Marine science Bulletin 2001年第1期3卷 69-73页

作者：张悦王建龙李花子施汉昌竺建荣 tate Key Joint Laboratory of Environment Simulation and Pollution Control Department of Environmental Science and Engineering Tsinghua University Beijing 100084 tate Key Joint Laboratory of Environment Simulation and Pollution Control Department of Environmental Science and Engineering Tsinghua University Beijing 100084 strain of yeast which can endure high osmotic pressure is employed for the sensitive material of the microbial BOD sensor. Two immobilization methods are used i.e. calcium alginate gel beads and PVA gel beads. The results show that the PVA gel beads is better. The influences of osmosis and heavy metal ions on the yeast entrapped in the PVA gel beads are also studied in the experiment.

A strain of yeast, which can endure high osmotic pressure, is employed for the sensitive material of the microbial BOD sensor. Two immobilization methods are used, I.e. Calcium alginate gel be ads and PV A gel beads. The results show that the PVA gel beads is better. The influences of osmosis and heavy metal ions on the yeast entrapped in the PVA gel beads are also studied in the experiment.

关键词： Biochemical oxygen demand, microbial sensor, yeast, immobilized cells, marine pollution, monitoring

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Bioaugmentation: a new strategy for removal of recalcitrant compounds in wastewater—a case study of quinoline

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Journal of Environmental sciences 2000年第1期12卷 24-27页

作者： HAN Li-ping WANG Jian-long SHI Han-chang QIAN Yi State Key Joint Laboratory of Environmental Simulation and Pollution Control Department of Environmental Science and EngineeringTsinghua UniversityBeijing 100084China

To demonstrate the feasibility of using bioaugmentation to enhance biodegradation of quinoline, four strains capable of using quinoline as sole source of carbon, nitrogen and energy were isolated from different environmental samples by enrichment technique. Screening for quinoline degrader with the highest quinoline mineralizing rate was carried out in respirometer and one bacterium identified as \%Burkholderia pickettii W2\% was chosen as inoculum in bioaugmentation tests. Quinoline biodegradation experiment results showed that this bacterium degraded quinoline very quickly. 100, 200 and 500 mg/L quinoline can be transformed completely within 1, 2 and 7 hours respectively. A bioaugmentation procedure was proposed and laboratory experiments confirmed that bioaugmentation was an effective way to improve the performance of traditional wastewater treatment facilities for quinoline removal. The effect of inoculum size on bioaugmentation was also investigated in this paper.

关键词： bioaugmentation biodegradation quinoline inocula CLC number: X703 Document code: A

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Performance of Submerged Membrane Bioreactor for Domestic Wastewater Treatment

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Tsinghua science and Technology 2000年第3期5卷 237-240页

作者：黄霞桂萍钱易 State Key Joint Laboratory of Environment Simulation and Pollution Control Department of Environmental Science and Engineering Tsinghua University Beijing 100084 China

In the present research, a submerged membrane bioreactor was tested to treat domestic wastewater. Three experimental runs were conducted all with a hydraulic retention time of 5h and sludge retention times (SRTs) of 5, 10, and 20 d. The pollutant removal performance of the membrane bioreactor, the membrane effluent quality, and a kinetic model for sludge growth in the bioreactor were investigated. The combined process was capable of removing over 90% of both COD (chemical oxygen demand) and NH 3 N on the average. The total removal for COD was almost independent of SRT, but that for NH 3 N improved with increasing SRT. Membrane effluent quality meets the water quality standard for reuse issued by the Ministry of Construction of China. Increasing SRT causes the concentrations of suspended solids (SS) and volatile suspended solids (VSS) in the bioreactor to increase. However, the ratio of VSS/SS did not change much. Kinetic analysis showed that the sludge yield coefficient (kg VSS·kg COD -1 ) and the endogenous coefficient of microorganisms were 0.25 and 0.04d -1 , which are similar to those of the conventional activated sludge process. 

关键词： submerged membrane bioreactor domestic wastewater treatment pollutant removal performance effluent quality sludge retention time sludge growing kinetics

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Bioadsorption of 4-Chlorophenol to the Activated Sludge

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Tsinghua science and Technology 2000年第3期5卷 241-245页

作者：王建龙 Nigel Horan Ed.Stentiford 钱易 State Key Joint Laboratory of Environment Simulation and Pollution Control Department of Environmental Science and Engineering Tsinghua University Beijing 100084 China School of Civil Engineering Leeds University LS 9JT UK

The adsorption behaviour of 4 chlorophenol from aqueous solution to activated sludge was quantitatively characterized in this paper. The effects of the initial pH values, initial chlorophenol concentration and adsorbent dosage on bioadsorption were investigated. The maximum adsorption capacity was found to be 110.5 mg/g at 100 mg/L initial concentration. The Freundlich and Langmuir adsorption isotherms were applied to describe the biosorption processes and the isotherm constants were evaluated. 

关键词： 4-chlorophenol priority pollutant bioadsorption activated sludge

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TOMAHAWK NITROGEN PRESSURIZATION MAINTENANCE - WHY

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NAVAL ENGINEERS JOURNAL 1993年第2期105卷 66-68页

作者： CIARULA, TA NERADKA, VF Cdr. Thomas A. Ciarula: USN was born in Pottstown Pa. He attended Northrop University in Inglewood Calif. where he earned a bachelor of science degree in aircraft maintenance engineering in September 1971. He was selected for Officer Candidate School where he was commissioned an ensign (Aeronautical Maintenance Duty) in August 1972. Cdr. Ciarula has been assigned to VA-37 The AIMD at NAF Kadena Okinawa Japan VXE-6 and the USS Forrestal. He was the wing maintenance for training officer for Air Wing Three at NAS Chase Field in Beeville Tex. and the AIMD officer at NAS Key West Fla. In 1988 Cdr. Ciarula was assigned to the Cruise Missiles Project (PEO-CU) where he was the TASM class desk officer and the director of logistics. While at the Cruise Missiles Project he was awarded his master of science in general administration from Central Michigan University. He is currently assigned to PMA-205 in the Naval Air Systems Command. Vincent F. Neradka:received B.S. and M.S. degrees from the University of Maryland in aerospace engineering in 1964 and 1969 and an MS in technical management from the Johns Hopkins University in 1986. He joined the Johns Hopkins University Applied Physics Laboratory in 1979 working on the Vertical Launching System of the Aegis cruisers. Since that time he has participated in activities on the Phalanx program the SPS-48E radar and long term involvement with the Cruise Missile Program. On the Cruise Missile Program Mr. Neradka has focused on the specification of and testing related to environments. Simulation activities have included modeling of pneumatic systems and NASTRAN dynamic modeling. Mr. Neradka is a registered professional engineer.

This paper discusses the data that were recorded during a three-month accelerated humidity test of two Tomahawk all-up rounds (AURs), one pressurized with dry nitrogen in accordance with the current practice, and the other left unpressurized. Temperature and humidity were recorded inside the canisters and missiles. Data analysis consisted of psychrometric calculations to determine the moisture intrusion into these missiles during the test. The work was carried out in support of a technical effort directed at changing the storage and stowage environmental protection of the Tomahawk missile.

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Characterizing Smart Contract Evolution

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ACM Transactions on Software engineering and Methodology 1000年

作者： Xiangping Chen Ziang Qian Peiyong Liao Yuan Huang Changlin Yang Zibin Zheng Guangdong Key Laboratory for Big Data Analysis and Simulation of Public Opinion School of Journalism and Communication Sun Yat-sen University China School of Software Engineering Sun Yat-sen University China School of Computer Science and Engineering Sun Yat-sen University China

Smart contracts are programs that permanently store and automatically execute on the blockchain system such as Ethereum. Due to the non-tamperable nature of the underlying blockchain, smart contracts are difficult to update once deployed, which requires redeploying the contracts and migrating the data. It means that the observation of smart contract evolution in the real world makes more sense. Hence, in this paper, we conducted the first large-scale empirical study to characterize the evolution of smart contracts in Ethereum. For evolution identification, we presented a contract similarity-based search algorithm, digEvolution, and evaluated its effectiveness with five different search strategies. Then we applied this algorithm to 80,152 on-chain contracts we collected from Ethereum, to dig out the evolution among these contracts. We then explored three research questions. We first studied whether the evolution of smart contracts is common (RQ1), then we studied how do the Gas consumption (RQ2) and the vulnerability (RQ3) of smart contracts vary during the evolution. Our research results show that the evolution of smart contracts is not very common. There are some contract components that have vulnerability but still be called by users. The Gas consumption of most smart contracts doesn’t vary during the evolution, contract is Gas-efficient before and after the evolution. The vulnerability of most smart contracts doesn’t vary during the evolution, both are secure before and after the evolution.

关键词： Smart Contract Software Evolution Code Clone

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computational Intelligence and Intelligent Systems 1

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丛书名： Communications in Computer and Information science

1000年

作者： Zhihua Cai Zhenhua Li Zhuo Kang Yong Liu

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An indirect convergent Jacobi spectral collocation method for fractional optimal control problems

An indirect convergent Jacobi spectral collocation method fo...

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作者： Yang, Yin Zhang, Jiaqi Liu, Huan O. Vasilev, Aleksandr Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing & Information Processing of Ministry of Education School of Mathematics and Computational Science Xiangtan University Xiangtan Hunan China Ammosov North-Eastern Federal University Yakutsk Russia

In this paper, we present a novel indirect convergent Jacobi spectral collocation method for fractional optimal control problems governed by a dynamical system including both classical derivative and Caputo fractional derivative. First, we present some necessary optimality conditions. Then we suggest a new Jacobi spectral collocation method to discretize the obtained conditions. By the proposed method, we get a system of algebraic equations by solving of which we can approximate the optimal solution of the main problem. Finally, we present a convergence analysis for our method and solve three numerical examples to show the efficiency and capability of the method. © 2019 John Wiley & Sons, Ltd.

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An X Language-Driven Framework for Systematic Development of Digital Twin Healthcare Systems

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ACM Transactions on Multimedia Computing, Communications, and Applications 1000年

作者： Kunyu Xie Lin Zhang Yuan Yang Xiaohe Li Ridha Khedri Zhen Chen M. Jamal Deen Simulation Technology Innovation Center Hangzhou International Innovation Institute of Beihang University Hangzhou 311115 Zhejiang China School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China State Key Laboratory of Intelligent Manufacturing Systems Technology Beijing 100191 China School of Automation Science and Electrical Engineering Beihang University Beijing 100191 China Shenzhen Third People’s Hospital & Second Hospital Affiliated to Southern University of Science and Technology Shenzhen 518112 Guangdong China Dept. of Computing and Software McMaster University Hamilton Ontario Canada L8S 4K1 Department of Electrical and Computer Engineering McMaster University Hamilton ON L8S 4L8 Canada

The rapid advancements in big data and the Internet of Things (IoT) have significantly accelerated the digital transformation of medical institutions, leading to the widespread adoption of Digital Twin Healthcare (DTH). The Cloud DTH Platform (CDTH) serves as a cloud-based framework that integrates DTH models, healthcare resources, patient data, and medical services. By leveraging real-time data from medical devices, the CDTH platform enables intelligent healthcare services such as disease prediction and medical resource optimization. However, the platform functions as a system of systems (SoS), comprising interconnected yet independent healthcare services. This complexity is further compounded by the integration of both black-box AI models and domain-specific mechanistic models, which pose challenges in ensuring the interpretability and trustworthiness of DTH models. To address these challenges, we propose a Model-Based Systems engineering (MBSE)-driven DTH modeling methodology derived from systematic requirement and functional analyses. To implement this methodology effectively, we introduce a DTH model development approach using the X language, along with a comprehensive toolchain designed to streamline the development process. Together, this methodology and toolchain form a robust framework that enables engineers to efficiently develop interpretable and trustworthy DTH models for the CDTH platform. By integrating domain-specific mechanistic models with AI algorithms, the framework enhances model transparency and reliability. Finally, we validate our approach through a case study involving elderly patient care, demonstrating its effectiveness in supporting the development of DTH models that meet healthcare and interpretability requirements.

关键词： Digital Twin Model-based system engineering X Language Medical Cyber-Physical Systems Digital Twin Healthcare Design

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Feature Disentanglement Based Heterogeneous Defect Prediction

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ACM Transactions on Software engineering and Methodology 1000年

作者： Xu Yu Jiaqi Yan Qinqin Gao Qinglong Peng Bin Yu Junwei Du Ying Xing Dunwei Gong Qingdao Institute of Software China University of Petroleum East China) Qingdao China College of Computer Science and Technology China University of Petroleum East China) Qingdao China Shandong Key Laboratory of Intelligent Oil & Gas Industrial Software China University of Petroleum East China) Qingdao China School of Data Science Qingdao University of Science and Technology Qingdao China Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Changchun China School of Data Science Qingdao University of Science and Technology Qingdao China School of Computer and Information Technology Beijing Jiaotong University Beijing China School of Data Science Qingdao University of Science and TechnologyQingdao China School of Artificial Intelligence Beijing University of Posts and Telecommunications Beijing China Yunnan Key Laboratory of Software Engineering Kunming China College of Automation and Electronic Engineering Qingdao University of Science and Technology Qingdao China

Cross-project defect prediction (CPDP) utilizes the existing labeled data in the source project to assist with the prediction of unlabeled projects in the target dataset, which effectively improves the prediction performance and has become a research hotspot in software engineering. At present, CPDP can be categorized into homogeneous cross-project defect prediction and heterogeneous cross-project defect prediction (HDP), in which HDP doesn’t require that the source project and the target project have the same feature space, thus, it is more widely used in the actual CPDP. Most of current HDP methods map the original features to the latent feature space and reduce the inter-project variation by transferring domain-independent features, but the transferring process ignores the use of domain-related features, which affects the prediction performance of the model. Moreover, the mapped latent features are not conducive to the model’s interpretability. Based on these, this paper proposes a heterogeneous defect prediction method based on feature disentanglement (FD-HDP). We disentangle the features using domain-related and domain-independent feature extractors, respectively, to improve the interpretability of the model by maximizing the domain adversarial loss during training and guiding the feature extractors to produce accurate domain-related and domain-independent features. The weighted sum of the prediction results from domain-related and domain-independent predictors is used as the final prediction result of the project during the prediction process, which realizes the combination of domain-independent and domain-related features and effectively improves the prediction performance. In this paper, we conducted experiments using four publicly available defect datasets to construct heterogeneous scenarios. The results demonstrate that the FD-HDP model shows significant advantages over state-of-the-art methods in six metrics.

关键词： Heterogeneous Defect Prediction Feature Disentanglement Domain-related Features Domain-independent Features

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