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4D BIM use 1

AEC project management 1

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BIM 1

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Boolean logic algebra system 1

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Study on Bio-Purifying Several Gaseous Pollutants

Sun Shi,Wang Jie,Wu Xianhua,Li Xiaomei,Xu XIaoyi,Deng Futang,Zhang Wei,Lei Yanmei,Zeng Erli

Strategic Study of CAE 2007, Volume 9, Issue 1,   Pages 73-77

Abstract:

  Bio-purification test of the seven kinds of gaseous pollutants, toluene, styrene, formaldehyde, CS2, SO2, H2S and NOx, which are commonly contained in industrial waste gases, by using the biofilm-packing tower system was performed. The test results showed that the biofilm-separately. And the purifying effects of biofilm-packing towers for three kinds of inorganic pollutants, SO2, H2S and NOx (bio-elimination capacity B = 90 — 150 mg/L·h) , were better obviously than that for three kinds of organic pollutants, styrene, formaldehyde and CS2, (bio-elimination capacity B < 30 mg/L·h) . The suitable operation conditions of the biofilm-packing tower system for purifying the 7 kinds of gaseous pollutants were confirmed and the seven kinds of special bacteria strains were identified in this study.

Keywords： seven kinds of gaseous pollutants     biofilm-packing tower     purification of waste gas     identifying ofbacteria    

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Identifying spreading influence nodes for social networks

Frontiers of Engineering Management   Pages 520-549 doi: 10.1007/s42524-022-0190-8

Abstract: The identification of spreading influence nodes in social networks, which studies how to detect important individuals in human society, has attracted increasing attention from physical and computer science, social science and economics communities. The identification algorithms of spreading influence nodes can be used to evaluate the spreading influence, describe the node’s position, and identify interaction centralities. This review summarizes the recent progress about the identification algorithms of spreading influence nodes from the viewpoint of social networks, emphasizing the contributions from physical perspectives and approaches, including the microstructure-based algorithms, community structure-based algorithms, macrostructure-based algorithms, and machine learning-based algorithms. We introduce diffusion models and performance evaluation metrics, and outline future challenges of the identification of spreading influence nodes.

Keywords： complex network     network science     spreading influence     machine learning    

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PathogenTrack and Yeskit: tools for identifying intracellular pathogens from single-cell RNA-sequencing

Frontiers of Medicine 2022, Volume 16, Issue 2,   Pages 251-262 doi: 10.1007/s11684-021-0915-9

Abstract: PathogenTrack is competitive to the state-of-the-art tools such as Viral-Track, and the first tools for identifying

Keywords： scRNA-seq     intracellular pathogen     microbe     COVID-19     SARS-CoV-2    

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Approaching the upper boundary of driver-response relationships: identifying factors using a novel framework

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 6, doi: 10.1007/s11783-023-1676-2

Abstract:

● A novel framework integrating quantile regression with machine learning is proposed.

Keywords： Driver-response     Upper boundary of relationship     Interpretable machine learning     Quantile regression     Total phosphorus     Chlorophyll a    

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Value of waist circumference, body mass index and hyperinsulinaemia in identifying metabolic syndrome

TIAN Hui, FANG Fusheng, SHAO Yinghong, LI Chunlin, LI Jian, YAN Shuangtong, ZHONG Wenwen, LI Yanyan, SUN Jingfang, CAO Xiutang, PAN Changyu, LU Juming, DOU Jingtao, MA Fangling, ZHOU Xiaoman

Frontiers of Medicine 2008, Volume 2, Issue 4,   Pages 400-405 doi: 10.1007/s11684-008-0077-z

Abstract: The combination of WC, BMI and HIns might be more helpful in identifying MS at early stage.

Keywords： mU/L     prevalence     Abnormal     dyslipidemia     computer    

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Identifying subassemblies and understanding their functions during a design review in immersive and non-immersive

Fanika LUKAČEVIĆ, Stanko ŠKEC, Peter TÖRLIND, Mario ŠTORGAL

Frontiers of Engineering Management 2021, Volume 8, Issue 3,   Pages 412-428 doi: 10.1007/s42524-020-0099-z

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Identifying stakeholders’ roles and relevant project documents for 4D-based collaborative decision making

Veronika BOLSHAKOVA, Annie GUERRIERO, Gilles HALIN

Frontiers of Engineering Management 2020, Volume 7, Issue 1,   Pages 104-118 doi: 10.1007/s42524-019-0041-4

Abstract: To fully understand and effectively implement 4D building information modelling (BIM) models and methods, we need to develop a precise knowledge of which project digital documents should be used and how they influence the decision-making (DM) process. This article studies the convergence between uses of 4D BIM and digital project documents. We hypothesize that a clear visualization of the construction simulation through a 4D model is a useful source of information and a support for DM at collaborative meetings. Through this research, we continue to progress toward a new 4D-based collective decision device, so these elements will contribute to propose 4D BIM as DM support on architecture engineering construction (AEC) projects. Further, the present research will be complemented by results from questionnaires given at a later research stage. The article presents a brief review of BIM context to consider ways of fostering the implementation of all 4D BIM uses (not only visualization). It then introduces a proposition for 4D BIM uses implementation by the project development phase. It concludes by summarizing stakeholders’ roles and documents relevant to 4D BIM uses.

Keywords： BIM     4D BIM     4D BIM use     AEC project management     collaboration     decision making    

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Identifying critical factors that affect the application of information technology in construction management

Meishan JIA, Youquan XU, Pengwang HE, Lingmin ZHAO

Frontiers of Engineering Management 2022, Volume 9, Issue 2,   Pages 281-296 doi: 10.1007/s42524-020-0122-4

Abstract: different IT and devices in the construction industry or site, few articles have specifically focused on identifying

Keywords： information technology     construction management     influential factors     empirical study     DEMATEL    

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Identifying human-induced influence on microbial community: A comparative study in the effluent-receiving

Yuhan Zheng, Zhiguo Su, Tianjiao Dai, Feifei Li, Bei Huang, Qinglin Mu, Chuanping Feng, Donghui Wen

Frontiers of Environmental Science & Engineering 2019, Volume 13, Issue 6, doi: 10.1007/s11783-019-1174-8

Abstract: Microbial compositions showed high differences in two study areas. COD was the key anthropogenic indicator in the coastal wastewater disposal area. Distinctive microbes capable of degrading toxic pollutants were screened. Microbial communities in effluent-receiving areas followed “niche theory”. Microbial community structure is affected by both natural processes and human activities. In coastal area, anthropegenetic activity can usually lead to the discharge of the effluent from wastewater treatment plant (WWTP) to sea, and thus the water quality chronically turns worse and marine ecosystem becomes unhealthy. Microorganisms play key roles in pollutants degradation and ecological restoration; however, there are few studies about how the WWTP effluent disposal influences coastal microbial communities. In this study, sediment samples were collected from two WWTP effluent-receiving areas (abbreviated as JX and SY) in Hangzhou Bay. First, based on the high-throughput sequencing of 16S rRNA gene, microbial community structure was analyzed. Secondly, several statistical analyses were conducted to reveal the microbial community characteristics in response to the effluent disposal. Using PCoA, the significant difference of in microbial community structure was determined between JX and SY; using RDA, water COD and temperature, and sediment available phosphate and ammonia nitrogen were identified as the key environmental factors for the community difference; using LDA effect size analysis, the most distinctive microbes were found and their correlations with environmental factors were investigated; and according to detrended beta-nearest-taxon-index, the sediment microbial communities were found to follow “niche theory”. An interesting and important finding was that in SY that received more and toxic COD, many distinctive microbes were related to the groups that were capable of degrading toxic organic pollutants. This study provides a clear illustration of eco-environmental deterioration under the long-term human pressure from the view of microbial ecology.

Keywords： Microbial community structure     Effluent-receiving area     High-throughput sequencing     Costal sediments     Wastewater treatment plant (WWTP)    

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Identifying combustion intermediates in premixed MTBE/gasoline/oxygen flame probed via synchrotron radiation

YAO Chunde, LI Jing, LI Qi, JI Qing, HUANG Chaoqun, WEI Lixia, WANG Jing, TIAN Zhenyu, LI Yuyang, QI Fei

Frontiers in Energy 2007, Volume 1, Issue 1,   Pages 79-84 doi: 10.1007/s11708-007-0007-9

Abstract: Molecular-beam sampling mass spectrometry (MBMS) combined with tunable synchrotron radiation photoionization technique offers obvious advantages for the study of flame chemistry over other techniques because of the precision measurement of the combustion intermediates and products in flame. In this paper, the results to identify combustion intermediates in low-pressure premixed gasoline/oxygen flame with the synchrotron radiation were reported. Based on the results obtained, the formation process of five products and the difference between gasoline/oxygen and MTBE/gasoline/oxygen flame were emphatically analyzed. The results achieved provide data basis for the analysis of intermediates and radicals in flame, and are helpful to establish the kinetic modeling of gasoline/oxygen and MTBE/gasoline/oxygen flames.

Keywords： synchrotron     photoionization technique     chemistry     analysis     difference    

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Identifying the driving factors of successful megaproject construction management: Findings from three

Qinghua HE, Junyan XU, Ting WANG, Albert P. C. CHAN

Frontiers of Engineering Management 2021, Volume 8, Issue 1,   Pages 5-16 doi: 10.1007/s42524-019-0058-8

Abstract: The construction of megaprojects has always resulted in extensive and long-term impacts on the society. However, the performance of megaproject management is poor, and improving it remains an urgent and necessary issue. Although many studies on megaproject success have been conducted, existing studies on the driving factors of successful megaproject construction are rather limited. Therefore, this study aims to systematically explore the key factors that can lead to successful megaproject construction management based on three cases: The Beijing–Shanghai High-Speed Railway, the Three Gorges Dam, and the Hong Kong–Zhuhai–Macao Bridge. Mixed research methods, such as literature review, case studies, and expert interviews, were used in this study. Consequently, 11 driving factors, namely, government support, public support, accumulation and application of technology and experience, development and innovation of technology, innovation and application of management system, organizational mode and structure, top management support, project culture, megaproject citizenship behavior, corporate reputation, and fulfillment of social responsibilities, were identified and grouped into five categories, namely, project environment, construction capabilities, organization, positive culture and behavior, and requirements for sustainable development. The contributions of this study lie in two aspects. First, the driving factors of successful megaproject construction are identified to deepen the understanding of industrial practitioners, assist them in focusing on key factors, and aid them in effectively managing megaprojects. Second, researchers could use the identified driving factors in conducting further empirical studies and apply them in future projects to enhance their chances of success.

Keywords： megaproject management     driving factors     project success     case study     China    

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An algorithm for identifying symmetric variables based on the order eigenvalue matrix Article

Xiao-hua LI, Ji-zhong SHEN

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 10,   Pages 1644-1653 doi: 10.1631/FITEE.1601052

Abstract: To simplify the process for identifying 12 types of symmetric variables in Boolean functions, we proposeconditions of the order eigenvalue matrix for 12 types of symmetric variables, an algorithm is proposed for identifying

Keywords： Boolean function     Symmetric variable     Boolean logic algebra system     Order eigenvalue matrix     Truth table    

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Identifying factors that influence soil heavy metals by using categorical regression analysis: A case

Jun Yang, Jingyun Wang, Pengwei Qiao, Yuanming Zheng, Junxing Yang, Tongbin Chen, Mei Lei, Xiaoming Wan, Xiaoyong Zhou

Frontiers of Environmental Science & Engineering 2020, Volume 14, Issue 3, doi: 10.1007/s11783-019-1216-2

Abstract: Identifying the factors that influence the heavy metal contents of soil could reveal the sources of soilA categorical regression represents a suitable method for identifying the factors that influence soil

Keywords： Soil     Heavy metal     Influencing factor     Categorical regression     Identification method    

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Profiling the Antimalarial Mechanism of Artemisinin by Identifying Crucial Target Proteins Article

Peng Gao, Jianyou Wang, Jiayun Chen, Liwei Gu, Chen Wang, Liting Xu, Yin Kwan Wong, Huimin Zhang, Chengchao Xu, Lingyun Dai, Jigang Wang

Engineering 2023, Volume 31, Issue 12,   Pages 86-97 doi: 10.1016/j.eng.2023.06.001

Abstract:

The widespread use of artemisinin (ART) and its derivatives has significantly reduced the global burden of malaria; however, malaria still poses a serious threat to global health. Although significant progress has been achieved in elucidating the antimalarial mechanisms of ART, the most crucial target proteins and pathways of ART remain unknown. Knowledge on the exact antimalarial mechanisms of ART is urgently needed, as signs of emerging ART resistance have been observed in some regions of the world. Here, we used a combined strategy involving mass spectrometry-coupled cellular thermal shift assay (MS-CETSA) and transcriptomics profiling to identify a group of putative antimalarial targets of ART. We then conducted a series of validation experiments on five prospective protein targets, demonstrating that ART may function against malaria parasites by interfering with redox homeostasis, lipid metabolism, and protein synthesis processes. Taken together, this study provides fresh perspectives on the antimalarial mechanisms of ART and identifies several crucial proteins involved in parasite survival that can be targeted to combat malaria.

Keywords： Artemisinin     Antimalaria     Target identification     MS-CETSA     Transcriptomics    

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Title Author Date Type Operation

Study on Bio-Purifying Several Gaseous Pollutants

Sun Shi,Wang Jie,Wu Xianhua,Li Xiaomei,Xu XIaoyi,Deng Futang,Zhang Wei,Lei Yanmei,Zeng Erli

Journal Article

Identifying spreading influence nodes for social networks

Journal Article

PathogenTrack and Yeskit: tools for identifying intracellular pathogens from single-cell RNA-sequencing

Journal Article

Approaching the upper boundary of driver-response relationships: identifying factors using a novel framework

Journal Article

Value of waist circumference, body mass index and hyperinsulinaemia in identifying metabolic syndrome

TIAN Hui, FANG Fusheng, SHAO Yinghong, LI Chunlin, LI Jian, YAN Shuangtong, ZHONG Wenwen, LI Yanyan, SUN Jingfang, CAO Xiutang, PAN Changyu, LU Juming, DOU Jingtao, MA Fangling, ZHOU Xiaoman

Journal Article

Identifying subassemblies and understanding their functions during a design review in immersive and non-immersive

Fanika LUKAČEVIĆ, Stanko ŠKEC, Peter TÖRLIND, Mario ŠTORGAL

Journal Article

Identifying stakeholders’ roles and relevant project documents for 4D-based collaborative decision making

Veronika BOLSHAKOVA, Annie GUERRIERO, Gilles HALIN

Journal Article

Identifying critical factors that affect the application of information technology in construction management

Meishan JIA, Youquan XU, Pengwang HE, Lingmin ZHAO

Journal Article

Identifying human-induced influence on microbial community: A comparative study in the effluent-receiving

Yuhan Zheng, Zhiguo Su, Tianjiao Dai, Feifei Li, Bei Huang, Qinglin Mu, Chuanping Feng, Donghui Wen

Journal Article

Identifying combustion intermediates in premixed MTBE/gasoline/oxygen flame probed via synchrotron radiation

YAO Chunde, LI Jing, LI Qi, JI Qing, HUANG Chaoqun, WEI Lixia, WANG Jing, TIAN Zhenyu, LI Yuyang, QI Fei

Journal Article

Identifying the driving factors of successful megaproject construction management: Findings from three

Qinghua HE, Junyan XU, Ting WANG, Albert P. C. CHAN

Journal Article

An algorithm for identifying symmetric variables based on the order eigenvalue matrix

Xiao-hua LI, Ji-zhong SHEN

Journal Article

Identifying factors that influence soil heavy metals by using categorical regression analysis: A case

Jun Yang, Jingyun Wang, Pengwei Qiao, Yuanming Zheng, Junxing Yang, Tongbin Chen, Mei Lei, Xiaoming Wan, Xiaoyong Zhou

Journal Article

Profiling the Antimalarial Mechanism of Artemisinin by Identifying Crucial Target Proteins

Peng Gao, Jianyou Wang, Jiayun Chen, Liwei Gu, Chen Wang, Liting Xu, Yin Kwan Wong, Huimin Zhang, Chengchao Xu, Lingyun Dai, Jigang Wang

Journal Article