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  1. Book ; Online: Carbon Dioxide Capture, Utilization and Storage (CCUS)

    Feng, Dongdong / Sun, Jian / Zhou, Zijian

    2023  

    Keywords Technology: general issues ; Chemical engineering ; CO2 capture ; polyethylenimine ; regeneration temperature ; oxy-fuel combustion ; evaporation system ; distributed parameter modeling ; pulverized coal boiler ; partial-cooling cycle ; supercritical CO2 Brayton cycle ; advanced fast reactors ; exergoeconomic analyses ; CO2 utilization ; carbon dioxide (CO2) ; carbon capture and storage (CCS) ; offshore Atlantic ; efficiency factors ; southeastern United States ; crystallization induction period ; ammonium bicarbonate ; binary blend solvent ; crystal surface growth mechanism ; fine particles ; CFB boiler ; PSDs ; dust removal ; physicochemical properties ; MgAl-LDH ; carbon oxide ; photoreduction ; modification strategy ; charged droplets ; sphericity ; numerical simulation ; trapping efficiency ; particulate matter (PM) ; Zhundong coal ; PM10 ; PM1 ; PM0.2 ; external mineral addition ; PM ; coal ; combustion ; Mg ; Ca ; Fe ; power-to-gas ; methanation ; oxyfuel ; glass industry ; CO2-separation ; economic evaluation
    Language English
    Size 1 electronic resource (204 pages)
    Publisher MDPI - Multidisciplinary Digital Publishing Institute
    Publishing place Basel
    Document type Book ; Online
    Note English
    HBZ-ID HT030377882
    ISBN 9783036574202 ; 3036574204
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Book ; Online ; Conference proceedings: Proceedings of the 2022 International Conference on Sport Science, Education and Social Development (SSESD 2022)

    Sun, Jian / Chew, Fong Peng / Khan, Intakhab Alam / Jenks, Christopher

    (Advances in Social Science, Education and Humanities Research ; 684)

    2023  

    Author's details edited by Jian Sun, Fong Peng Chew, Intakhab Alam Khan, Christopher Jenks
    Series title Advances in Social Science, Education and Humanities Research ; 684
    Keywords Sports sciences ; Education ; Social sciences
    Subject code 796.015
    Language English
    Size 1 Online-Ressource (XV, 586 p. 86 illus., 76 illus. in color)
    Edition 1st ed. 2023
    Publisher Atlantis Press SARL ; Imprint: Atlantis Press
    Publishing place Paris
    Document type Book ; Online ; Conference proceedings
    HBZ-ID HT021682076
    ISBN 978-2-494069-13-8 ; 9782494069121 ; 2-494069-13-0 ; 2494069122
    DOI 10.2991/978-2-494069-13-8
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  3. Book: Polyphenols

    Sun, Jian

    chemistry, dietary sources & health benefits

    (Nutrition and diet research progress)

    2013  

    Author's details Jian Sun ... ed
    Series title Nutrition and diet research progress
    Keywords Polyphenols--Physiological effect ; Phenols--Therapeutic use.
    Language English
    Size VII, 571 S. : Ill., graph. Darst., 26 cm
    Publisher Nova Biomedical
    Publishing place New York
    Publishing country United States
    Document type Book
    HBZ-ID HT017358364
    ISBN 978-1-62081-809-1 ; 1-62081-809-4
    Database Catalogue ZB MED Nutrition, Environment, Agriculture

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    In stock of ZB MED Bonn / Germany

    Shelf markLoan statusLocation
    134/84 available for loan (reading room) Freihandmagazin (U1)

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  4. Article: Exploring the Impact of Music Education on the Psychological and Academic Outcomes of Students: Mediating Role of Self-Efficacy and Self-Esteem.

    Sun, Jian

    Frontiers in psychology

    2022  Volume 13, Page(s) 841204

    Abstract: In recent years, there has been a growing interest in scholars and practitioners to explore the factors that lead to an improvement in Students' psychological wellbeing. Due to the tough challenges faced by students during their academic life, severe ... ...

    Abstract In recent years, there has been a growing interest in scholars and practitioners to explore the factors that lead to an improvement in Students' psychological wellbeing. Due to the tough challenges faced by students during their academic life, severe issues of stress, anxiety, and other mental health issues emerge, which affect their academic performance and have a long-lasting impact on their future careers. The pandemic accelerates the stress levels, anxiety, and mental issues of students. The main purpose of this study was to explore how music education impacts on Students' psychological wellbeing and academic performance. This study also investigates the mediating effect of self-esteem and self-efficacy. To the best of our knowledge, there has been little to no study exploring the relationship of music education on the psychological wellbeing and performance of students, especially from the perspective of Asian countries. This study was conducted in undergraduate and graduate institutions of China. This study was quantitative in nature and data were collected from 319 respondents. The structural equation modeling (SEM) technique was employed for data analysis. Results reveal that music education has a significant positive impact on psychological wellbeing, which improves Students' academic performance. Moreover, psychological wellbeing also has a significant and positive impact on Students' academic performance. Self-efficacy and self-esteem significantly mediate the relationship between music education and psychological wellbeing. The findings of this study open new avenues for future research in music education and psychological wellbeing. This study suggests that the policymakers and practitioners should make such policies that encourage educational institutes to adopt music education to improve the psychological wellbeing of students.
    Language English
    Publishing date 2022-02-08
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2563826-9
    ISSN 1664-1078
    ISSN 1664-1078
    DOI 10.3389/fpsyg.2022.841204
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Contemporary Value Assessment of Marxist Ideology under the Context of Deep Learning.

    Sun, Jian

    publication RETRACTED

    Computational and mathematical methods in medicine

    2022  Volume 2022, Page(s) 4654153

    Abstract: As a conceptual superstructure, ideology plays a very important role in national security, social stability, and healthy economic development. As a result, ideological work is critical to the Party's success, and the current focus of ideological work is ... ...

    Abstract As a conceptual superstructure, ideology plays a very important role in national security, social stability, and healthy economic development. As a result, ideological work is critical to the Party's success, and the current focus of ideological work is to increase ideological risk prevention. The focus of ideological risk avoidance is gradually shifting to cyberspace as the Internet becomes the primary arena and forum for information interchange, value dissemination, and ideological exchanges. Deep learning, as a data processing technology, is characterized by deep data analysis and full generalization and can have an impact on ideological security work: on the one hand, it helps work subjects evaluate and count the process and effect of work in order to grasp the trend of public opinion; on the other hand, it helps work subjects understand and reflect on the inner logic and contemporary value of Marxist theory through diversified work platforms and diverse work methods and promotes work subjects' understanding of Marxist theory. On the other hand, through diversified working platforms and various working methods, we help the working targets to understand and reflect on the inner logic and contemporary values of Marxist theory and promote their true identification with socialist core values. Based on the impact of deep learning on work subjects and work objects, this paper proposes that Marxian ideological security workers can use it to effectively achieve good communication and contemporary value assessment among different work subjects, set specific indicators according to the division of labour, adopt different working methods according to the groups to which the learning bjects belong, and establish a long-term evaluation mechanism in the process.
    MeSH term(s) Communication ; Deep Learning ; Humans
    Language English
    Publishing date 2022-06-15
    Publishing country United States
    Document type Journal Article ; Retracted Publication
    ZDB-ID 2252430-7
    ISSN 1748-6718 ; 1748-670X ; 1027-3662
    ISSN (online) 1748-6718
    ISSN 1748-670X ; 1027-3662
    DOI 10.1155/2022/4654153
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 6373: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  6. Article ; Online: Forecasting COVID-19 pandemic in Alberta, Canada using modified ARIMA models.

    Sun, Jian

    Computer methods and programs in biomedicine update

    2021  Volume 1, Page(s) 100029

    Abstract: Background and objectives: Auto regressive integrated moving average (ARIMA) model is a popular model to forecast future values of a time series using the past values of the same series. However, if the variance of the time series varies with time, the ... ...

    Abstract Background and objectives: Auto regressive integrated moving average (ARIMA) model is a popular model to forecast future values of a time series using the past values of the same series. However, if the variance of the time series varies with time, the 95% confidence interval estimated by the ARIMA will not be accurate. This study proposes a method to revise the ARIMA model to suit time series with heteroscedasticity.
    Methods: Multiple historical ARIMA models were constructed with publicly available COVID-19 data in Alberta, Canada. The time series between different time periods were applied for these models. The means and their 95% confidence intervals of the differences between the forecasted values and the corresponding actual values were computed. The forecasted values of the general ARIMA models were modified by adding these differences.
    Results: The average incident cases forecasted with the proposed method are lower than those with a general ARIMA model during the forecasted period. The 95% confidence intervals of the forecasted incidence with the proposed method are narrower. During the forecasted period (13 weeks) the average incidence was predicted to increase first and then decrease exponentially.
    Conclusion: The proposed method can be used to automatically specify the best ARIMA model, to fit time series with heteroscedasticity and to forecast longer period of the trends in the future. In the next 13 weeks, the Covid-19 incidence may decrease but not eliminate. To stop the transmission of infections eventually, persistent effects complying with accurate forecasts are necessary.
    Language English
    Publishing date 2021-09-26
    Publishing country Netherlands
    Document type Journal Article
    ISSN 2666-9900
    ISSN (online) 2666-9900
    DOI 10.1016/j.cmpbup.2021.100029
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Optimizing the Multimerization Properties of Quinoline-Based Allosteric HIV-1 Integrase Inhibitors.

    Sun, Jian / Kessl, Jacques J

    Viruses

    2024  Volume 16, Issue 2

    Abstract: Allosteric HIV-1 Integrase (IN) Inhibitors or ALLINIs bind at the dimer interface of the IN, away from the enzymatic catalytic site, and disable viral replication by inducing over-multimerization of IN. Interestingly, these inhibitors are capable of ... ...

    Abstract Allosteric HIV-1 Integrase (IN) Inhibitors or ALLINIs bind at the dimer interface of the IN, away from the enzymatic catalytic site, and disable viral replication by inducing over-multimerization of IN. Interestingly, these inhibitors are capable of impacting both the early and late stages of viral replication. To better understand the important binding features of multi-substituted quinoline-based ALLINIs, we have surveyed published studies on IN multimerization and antiviral properties of various substituted quinolines at the 4, 6, 7, and 8 positions. Here we show how the efficacy of these inhibitors can be modulated by the nature of the substitutions at those positions. These features not only improve the overall antiviral potencies of these compounds but also significantly shift the selectivity toward the viral maturation stage. Thus, to fully maximize the potency of ALLINIs, the interactions between the inhibitor and multiple IN subunits need to be simultaneously optimized.
    MeSH term(s) HIV-1/metabolism ; Allosteric Regulation ; HIV Integrase Inhibitors/pharmacology ; HIV Integrase Inhibitors/chemistry ; HIV Integrase/metabolism ; Quinolines/pharmacology ; Protein Multimerization
    Chemical Substances p31 integrase protein, Human immunodeficiency virus 1 (YY6481J2FF) ; quinoline (E66400VT9R) ; HIV Integrase Inhibitors ; HIV Integrase (EC 2.7.7.-) ; Quinolines
    Language English
    Publishing date 2024-01-28
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2516098-9
    ISSN 1999-4915 ; 1999-4915
    ISSN (online) 1999-4915
    ISSN 1999-4915
    DOI 10.3390/v16020200
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Persistent Left Superior Vena Cava with Hemiazygos Continuation of Left Inferior Vena Cava.

    Lin, Shuang-Xiang / Sun, Jian-Zhong

    Radiology

    2023  Volume 310, Issue 1, Page(s) e232050

    MeSH term(s) Humans ; Persistent Left Superior Vena Cava ; Vena Cava, Inferior/diagnostic imaging ; Vena Cava, Superior/diagnostic imaging ; Longitudinal Studies
    Language English
    Publishing date 2023-12-14
    Publishing country United States
    Document type Journal Article
    ZDB-ID 80324-8
    ISSN 1527-1315 ; 0033-8419
    ISSN (online) 1527-1315
    ISSN 0033-8419
    DOI 10.1148/radiol.232050
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Ue I Zs.106: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  9. Article: DIC-Transformer: interpretation of plant disease classification results using image caption generation technology.

    Zeng, Qingtian / Sun, Jian / Wang, Shansong

    Frontiers in plant science

    2024  Volume 14, Page(s) 1273029

    Abstract: Disease image classification systems play a crucial role in identifying disease categories in the field of agricultural diseases. However, current plant disease image classification methods can only predict the disease category and do not offer ... ...

    Abstract Disease image classification systems play a crucial role in identifying disease categories in the field of agricultural diseases. However, current plant disease image classification methods can only predict the disease category and do not offer explanations for the characteristics of the predicted disease images. Due to the current situation, this paper employed image description generation technology to produce distinct descriptions for different plant disease categories. A two-stage model called DIC-Transformer, which encompasses three tasks (detection, interpretation, and classification), was proposed. In the first stage, Faster R-CNN was utilized to detect the diseased area and generate the feature vector of the diseased image, with the Swin Transformer as the backbone. In the second stage, the model utilized the Transformer to generate image captions. It then generated the image feature vector, which is weighted by text features, to improve the performance of image classification in the subsequent classification decoder. Additionally, a dataset containing text and visualizations for agricultural diseases (ADCG-18) was compiled. The dataset contains images of 18 diseases and descriptive information about their characteristics. Then, using the ADCG-18, the DIC-Transformer was compared to 11 existing classical caption generation methods and 10 image classification models. The evaluation indicators for captions include Bleu1-4, CiderD, and Rouge. The values of BLEU-1, CIDEr-D, and ROUGE were 0.756, 450.51, and 0.721. The results of DIC-Transformer were 0.01, 29.55, and 0.014 higher than those of the highest-performing comparison model, Fc. The classification evaluation metrics include accuracy, recall, and F1 score, with accuracy at 0.854, recall at 0.854, and F1 score at 0.853. The results of DIC-Transformer were 0.024, 0.078, and 0.075 higher than those of the highest-performing comparison model, MobileNetV2. The results indicate that the DIC-Transformer outperforms other comparison models in classification and caption generation.
    Language English
    Publishing date 2024-01-25
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2613694-6
    ISSN 1664-462X
    ISSN 1664-462X
    DOI 10.3389/fpls.2023.1273029
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Strong Non-Zeno Mixed Adaptive Dynamic Event-Triggered Control for Distributed Consensus.

    Yuan, Shuo / Yu, Chengpu / Sun, Jian

    IEEE transactions on cybernetics

    2024  Volume PP

    Abstract: This article studies the distributed adaptive event-triggered consensus control problem of linear multiagent systems. A strong non-Zeno mixed adaptive dynamic event-triggering scheme is proposed, which guarantees a strictly positive minimum interevent ... ...

    Abstract This article studies the distributed adaptive event-triggered consensus control problem of linear multiagent systems. A strong non-Zeno mixed adaptive dynamic event-triggering scheme is proposed, which guarantees a strictly positive minimum interevent time (MIET) between any two consecutive events. A model-based event-triggered fully distributed adaptive control law is presented without using prior global information about the communication topology. Moreover, a hybrid system model is constructed to facilitate the stability analysis of the closed-loop system. It is shown that the proposed control strategy can achieve asymptotic consensus of all agents via intermittent communication in a fully distributed way, while guaranteeing the strictly positive MIET property. Finally, the effectiveness of the designed control method is illustrated by a simulation example.
    Language English
    Publishing date 2024-01-24
    Publishing country United States
    Document type Journal Article
    ISSN 2168-2275
    ISSN (online) 2168-2275
    DOI 10.1109/TCYB.2024.3349676
    Database MEDical Literature Analysis and Retrieval System OnLINE

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