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  1. Artikel ; Online: It starts at home: non-economic factors influencing consumer acceptance of battery storage in Australia.

    McCarthy, Breda / Liu, Hongbo

    Environmental science and pollution research international

    2024  

    Abstract: Homeowners play a critical role in the uptake of low-carbon technologies, yet little is known about the factors that underlie market acceptance of residential battery storage. This research integrates social-psychological, demographic and behavioural ... ...

    Abstract Homeowners play a critical role in the uptake of low-carbon technologies, yet little is known about the factors that underlie market acceptance of residential battery storage. This research integrates social-psychological, demographic and behavioural factors into a holistic model that predicts market acceptance. Previous research has indicated that social factors play a crucial role in the adoption of rooftop solar. Still, the influence of subjective norms on battery storage, a relatively invisible technology, has yet to be fully understood. An online survey from homeowners in Australia, a mature renewable energy market, is used to provide insights into market acceptance that are relevant to international energy markets. A two-step econometric model, using factor analysis and ordered logistic regression, was used for data analysis. The results show that subjective norms, moral emotions and an environmental self-identity are positively associated with market acceptance. Demographic factors, such as younger age and higher levels of education, predict market acceptance. Motives such as technical interest, autarky and load-shifting behaviours are also relevant. Several recommendations for policymakers and practitioners are offered to improve the acceptance of battery storage, including interventions that exploit social parameters and appeal to consumer psychology.
    Sprache Englisch
    Erscheinungsdatum 2024-02-27
    Erscheinungsland Germany
    Dokumenttyp Journal Article
    ZDB-ID 1178791-0
    ISSN 1614-7499 ; 0944-1344
    ISSN (online) 1614-7499
    ISSN 0944-1344
    DOI 10.1007/s11356-024-32614-5
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  2. Artikel ; Online: Topology-based multi-jammer localization in wireless networks

    Liu Hongbo / Chen Yingying / Xu Wenyuan / Liu Zhenhua / Su Yuchen

    Security and Safety, Vol 3, p

    2024  Band 2023025

    Abstract: Jamming attacks and unintentional radio interference are some of the most urgent threats harming the dependability of wireless communication and endangering the successful deployment of pervasive applications built on top of wireless networks. Unlike the ...

    Abstract Jamming attacks and unintentional radio interference are some of the most urgent threats harming the dependability of wireless communication and endangering the successful deployment of pervasive applications built on top of wireless networks. Unlike the traditional approaches focusing on developing jamming defense techniques without considering the location of jammers, we take a different viewpoint that the jammers’ position should be identified and exploited for building a wide range of defense strategies to alleviate jamming. In this paper, we address the problem of localizing multiple jamming attackers coexisting in wireless networks by leveraging the network topology changes caused by jamming. We systematically analyze the jamming effects and develop a framework that can partition network topology into clusters and can successfully estimate the positions of multiple jammers even when their jamming areas are overlapping. Our experiments on a multi-hop network setup using MicaZ sensor nodes validate the feasibility of real-time collection of network topology changes under jamming and our extensive simulation results demonstrate that our approach is highly effective in localizing multiple attackers with or without the prior knowledge of the order that the jammers are turned on.
    Schlagwörter jammer localization ; wireless networks ; topology ; Electronic computers. Computer science ; QA75.5-76.95
    Thema/Rubrik (Code) 000
    Sprache Englisch
    Erscheinungsdatum 2024-01-01T00:00:00Z
    Verlag EDP Sciences
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  3. Artikel ; Online: Improve-RRBS: a novel tool to correct the 3' trimming of reduced representation sequencing reads.

    Fóthi, Ábel / Liu, Hongbo / Susztak, Katalin / Aranyi, Tamas

    Bioinformatics advances

    2024  Band 4, Heft 1, Seite(n) vbae076

    Abstract: Motivation: Reduced Representation Bisulfite Sequencing (RRBS) is a popular approach to determine DNA methylation of the CpG-rich regions of the genome. However, we observed that false positive differentially methylated sites (DMS) are also identified ... ...

    Abstract Motivation: Reduced Representation Bisulfite Sequencing (RRBS) is a popular approach to determine DNA methylation of the CpG-rich regions of the genome. However, we observed that false positive differentially methylated sites (DMS) are also identified using the standard computational analysis.
    Results: During RRBS library preparation the MspI digested DNA undergo end-repair by a cytosine at the 3' end of the fragments. After sequencing, Trim Galore cuts these end-repaired nucleotides. However, Trim Galore fails to detect end-repair when it overlaps with the 3' end of the sequencing reads. We found that these non-trimmed cytosines bias methylation calling, thus, can identify DMS erroneously. To circumvent this problem, we developed improve-RRBS, which efficiently identifies and hides these cytosines from methylation calling with a false positive rate of maximum 0.5%. To test improve-RRBS, we investigated four datasets from four laboratories and two different species. We found non-trimmed 3' cytosines in all datasets analyzed and as much as >50% of false positive DMS under certain conditions. By applying improve-RRBS, these DMS completely disappeared from all comparisons.
    Availability and implementation: Improve-RRBS is a freely available python package https://pypi.org/project/iRRBS/ or https://github.com/fothia/improve-RRBS to be implemented in RRBS pipelines.
    Sprache Englisch
    Erscheinungsdatum 2024-05-24
    Erscheinungsland England
    Dokumenttyp Journal Article
    ISSN 2635-0041
    ISSN (online) 2635-0041
    DOI 10.1093/bioadv/vbae076
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  4. Artikel ; Online: Pathogenic bacteria and treatment resistance in older cardiovascular disease patients with lung infection and risk prediction model

    Liu Hongbo / Xie Liyan / Xing Cong

    Open Life Sciences, Vol 18, Iss 1, Pp 753-

    2023  Band 60

    Abstract: This study analyzes the distribution of pathogenic bacteria and their antimicrobial susceptibilities in elderly patients with cardiovascular diseases to identify risk factors for pulmonary infections. A risk prediction model is established, aiming to ... ...

    Abstract This study analyzes the distribution of pathogenic bacteria and their antimicrobial susceptibilities in elderly patients with cardiovascular diseases to identify risk factors for pulmonary infections. A risk prediction model is established, aiming to serve as a clinical tool for early prevention and management of pulmonary infections in this vulnerable population. A total of 600 patients were categorized into infected and uninfected groups. Independent risk factors such as older age, diabetes history, hypoproteinemia, invasive procedures, high cardiac function grade, and a hospital stay of ≥10 days were identified through logistic regression. A predictive model was constructed, with a Hosmer–Lemeshow goodness of fit (P = 0.236) and an area under the receiver operating characteristic curve of 0.795, demonstrating good discriminative ability. The model had 63.40% sensitivity and 82.80% specificity, with a cut-off value of 0.13. Our findings indicate that the risk score model is valid for identifying high-risk groups for pulmonary infection among elderly cardiovascular patients. The study contributes to the early prevention and control of pulmonary infections, potentially reducing infection rates in this vulnerable population.
    Schlagwörter cardiovascular disease ; pulmonary infection ; pathogenic bacteria ; drug resistance ; risk prediction model ; Biology (General) ; QH301-705.5
    Thema/Rubrik (Code) 610
    Sprache Englisch
    Erscheinungsdatum 2023-12-01T00:00:00Z
    Verlag De Gruyter
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  5. Artikel ; Online: Study on catalytic removal of toluene by metal oxides derived from hydrotalcite

    Liu Hongbo / Huang Zhiyong

    E3S Web of Conferences, Vol 272, p

    2021  Band 01008

    Abstract: Hydrotalcite (HT) precursor was synthesized by coprecipitation method, and the surface of HT precursor was modified. The mixed metal oxide (MO) catalyst was prepared by calcination of HT precursor, which was used to remove toluene from VOCs assisted by ... ...

    Abstract Hydrotalcite (HT) precursor was synthesized by coprecipitation method, and the surface of HT precursor was modified. The mixed metal oxide (MO) catalyst was prepared by calcination of HT precursor, which was used to remove toluene from VOCs assisted by NTP technology. The catalytic performance of MO catalyst was investigated. The results show that the MO catalyst with good structure can be obtained after calcination of HT precursor before and after modification. The results of catalytic performance test showed that the initial concentration of toluene was 700 ppm, the gas flow rate was 600 mL/min, and the reaction time was 30 min, SIE of NTP was above 3.0 kJ/L, the toluene conversion rate reached above 90%. MO assisted NTP had better catalytic performance with lower energy consumption. The toluene treatment capacity per unit energy consumption increased from 15.3% to 20.6%, which had an increase of 34.6%.
    Schlagwörter Environmental sciences ; GE1-350
    Thema/Rubrik (Code) 660
    Sprache Englisch
    Erscheinungsdatum 2021-01-01T00:00:00Z
    Verlag EDP Sciences
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  6. Artikel ; Online: Discussion on the Rise of Healthy Chinese Sports Industry and the Training Mode of Compound Sports Talents.

    Liu, Hongbo / Li, Ming

    Journal of healthcare engineering

    2022  Band 2022, Seite(n) 6943285

    Abstract: With the improvement of people's living standards and quality, sports charm stimulates people's awareness of sports consumption and makes sports industry develop rapidly into one of the important industries for the sustainable development of national ... ...

    Abstract With the improvement of people's living standards and quality, sports charm stimulates people's awareness of sports consumption and makes sports industry develop rapidly into one of the important industries for the sustainable development of national economy. In modern society, sports industry has become a new industry with huge business opportunities. Especially, when the social economy develops to a certain level and sports form a certain scale, the interdependence, mutual support, and mutual promotion between sports and economy become more inseparable. This paper studies and discusses the training strategy of "compound" talents in sports industry under the background of healthy China strategy, in order to promote the development and innovation of China's sports industry. In terms of training sports talents, we should not only pay attention to personal technical, professional, practical, and understanding contents but also introduce some humanistic contents and social hot contents to improve the comprehensive quality of talents.
    Mesh-Begriff(e) China ; Health Status ; Humans ; Industry ; Sports
    Sprache Englisch
    Erscheinungsdatum 2022-03-07
    Erscheinungsland England
    Dokumenttyp Journal Article ; Review
    ZDB-ID 2545054-2
    ISSN 2040-2309 ; 2040-2295
    ISSN (online) 2040-2309
    ISSN 2040-2295
    DOI 10.1155/2022/6943285
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  7. Artikel ; Online: Identification of potential immune/diagnosis related gene-immunocyte subtype networks in extracellular immune response to respiratory syncytial virus infection.

    Wang, Baohong / Liu, Hongbo

    Virus research

    2022  Band 321, Seite(n) 198906

    Abstract: Introduction: Respiratory syncytial virus (RSV) is one of the important pathogenic agents of pediatric respiratory tract infection. Weighted gene co-expression network analysis (WGCNA) is used to study autoimmune diseases, which can find potential hub ... ...

    Abstract Introduction: Respiratory syncytial virus (RSV) is one of the important pathogenic agents of pediatric respiratory tract infection. Weighted gene co-expression network analysis (WGCNA) is used to study autoimmune diseases, which can find potential hub genes. The diagnostic model based on hub genes and machine learning makes it possible to diagnose the extracellular immune response to RSV infection early.
    Objective: The aim of the present study was to identify potential immune, diagnose and treatment related genes expressed in RSV-infected cells.
    Methods: Firstly, gene expression data were downloaded from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). Secondly, WGCNA was performed based on DEGs to obtain hub genes related to immunity score. Thirdly, protein-protein interaction (PPI) and the immune infiltration analysis of hub immune related genes were performed. Finally, diagnostic and immune related genes were identified by machine learning, followed by functional analysis.
    Results: Totally, 2063 DEGs were identified in the extracellular immune response to RSV infection. Among which, 10 key immune and diagnosis related genes were identified, including ITGA2B, GP9, ITGB3, SELP, PPBP, MPL, CXCL8, NFE2, PTGS1 and LY6G6F. Several immune/diagnosis related gene-immunocyte subtype networks were identified, such as CXCL8-Type 17 T helper cell, LY6G6F-CD56 bright natural killer cell, PPBP-activated CD4 T cell/T follicular helper cell, NFE2/PTGS1/SELP-activated dendritic cell, GP9/ITGA2B/MPL-activated CD8 T cell. ITGB3, MPL and PTGS1 could be considered as therapeutic targets. Some significantly enriched signaling pathways were identified, including hematopoietic cell lineage (involving GP9 and ITGA2B), cytokine-cytokine receptor interaction (involving MPL), chemokine signaling pathway (involving PPBP) and arachidonic acid metabolism (involving PTGS1).
    Conclusions: The 10-immune related gene signature may be used as potential diagnostic markers for the extracellular immune response to RSV infection, which may provide a new field in searching for diagnostic and therapeutic molecules in the extracellular immune response to RSV infection.
    Mesh-Begriff(e) Arachidonic Acid ; Chemokines ; Child ; Computational Biology ; Cytokines/genetics ; Gene Expression Profiling ; Gene Regulatory Networks ; Humans ; Immunity ; Receptors, Cytokine ; Respiratory Syncytial Virus Infections/diagnosis ; Respiratory Syncytial Virus Infections/genetics ; Respiratory Syncytial Virus, Human/genetics
    Chemische Substanzen Chemokines ; Cytokines ; Receptors, Cytokine ; Arachidonic Acid (27YG812J1I)
    Sprache Englisch
    Erscheinungsdatum 2022-08-28
    Erscheinungsland Netherlands
    Dokumenttyp Journal Article
    ZDB-ID 605780-9
    ISSN 1872-7492 ; 0168-1702
    ISSN (online) 1872-7492
    ISSN 0168-1702
    DOI 10.1016/j.virusres.2022.198906
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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    Jg. 1995 - 2021: Lesesall (1.OG)
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  8. Artikel ; Online: Research on Monitoring of Gymnastics Facilities and Intelligent Optimal Distribution of Gymnastics Venues Based on Internet of Things.

    Liu, Hongbo / Wang, Yuzhen

    Computational intelligence and neuroscience

    2022  Band 2022, Seite(n) 6164448

    Abstract: In view of the low level of gymnastics facilities monitoring and intelligent management of gymnastics venues, which cannot effectively manage gymnastics venues in real time, this paper proposes a method of gymnastics facilities monitoring and intelligent ...

    Abstract In view of the low level of gymnastics facilities monitoring and intelligent management of gymnastics venues, which cannot effectively manage gymnastics venues in real time, this paper proposes a method of gymnastics facilities monitoring and intelligent optimization distribution of gymnastics venues in the Internet of Things. This paper will build an information monitoring model, introduce a particle swarm optimization algorithm to participate in the location layout, and explore the actual effect of gymnastics and the Internet of Things. The research results show that (1) the system can measure the mechanical error of facilities and ensure that the controllable fault tolerance rate is less than 1%. (2) The quality of system monitoring is evaluated in accuracy, time, delay, and satisfaction, and the results are basically satisfactory, but the accuracy and time still need to be improved. (3) Using the evaluation system of sports facilities to test the temperature, humidity, facility pressure, and energy consumption suitable for gymnastics and to verify the injury tendency of athletes. When the damage tendency is between 70% and 100%, the actual damage rate is 1. (4) The speed of the PSO algorithm is faster than other methods, which is used to optimize the layout of gymnastics venues and has a certain role in promoting the construction of gymnastics venues. The system model designed in this paper performs well in gymnastics and needs to be further improved and optimized.
    Mesh-Begriff(e) Algorithms ; Gymnastics ; Humans ; Internet ; Internet of Things
    Sprache Englisch
    Erscheinungsdatum 2022-09-09
    Erscheinungsland United States
    Dokumenttyp Journal Article
    ZDB-ID 2388208-6
    ISSN 1687-5273 ; 1687-5273
    ISSN (online) 1687-5273
    ISSN 1687-5273
    DOI 10.1155/2022/6164448
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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  9. Artikel: Identification of potential immune/diagnosis related gene-immunocyte subtype networks in extracellular immune response to respiratory syncytial virus infection

    Wang, Baohong / Liu, Hongbo

    Virus research. 2022 Aug. 27,

    2022  

    Abstract: Respiratory syncytial virus (RSV) is one of the important pathogenic agents of pediatric respiratory tract infection. Weighted gene co-expression network analysis (WGCNA) is used to study autoimmune diseases, which can find potential hub genes. The ... ...

    Abstract Respiratory syncytial virus (RSV) is one of the important pathogenic agents of pediatric respiratory tract infection. Weighted gene co-expression network analysis (WGCNA) is used to study autoimmune diseases, which can find potential hub genes. The diagnostic model based on hub genes and machine learning makes it possible to diagnose the extracellular immune response to RSV infection early. The aim of the present study was to identify potential immune, diagnose and treatment related genes expressed in RSV-infected cells. Firstly, gene expression data were downloaded from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). Secondly, WGCNA was performed based on DEGs to obtain hub genes related to immunity score. Thirdly, protein-protein interaction (PPI) and the immune infiltration analysis of hub immune related genes were performed. Finally, diagnostic and immune related genes were identified by machine learning, followed by functional analysis. Totally, 2063 DEGs were identified in the extracellular immune response to RSV infection. Among which, 10 key immune and diagnosis related genes were identified, including ITGA2B, GP9, ITGB3, SELP, PPBP, MPL, CXCL8, NFE2, PTGS1 and LY6G6F. Several immune/diagnosis related gene-immunocyte subtype networks were identified, such as CXCL8-Type 17 T helper cell, LY6G6F-CD56 bright natural killer cell, PPBP-activated CD4 T cell/T follicular helper cell, NFE2/PTGS1/SELP-activated dendritic cell, GP9/ITGA2B/MPL-activated CD8 T cell. ITGB3, MPL and PTGS1 could be considered as therapeutic targets. Some significantly enriched signaling pathways were identified, including hematopoietic cell lineage (involving GP9 and ITGA2B), cytokine-cytokine receptor interaction (involving MPL), chemokine signaling pathway (involving PPBP) and arachidonic acid metabolism (involving PTGS1). The 10-immune related gene signature may be used as potential diagnostic markers for the extracellular immune response to RSV infection, which may provide a new field in searching for diagnostic and therapeutic molecules in the extracellular immune response to RSV infection.
    Schlagwörter CD4-positive T-lymphocytes ; CD8-positive T-lymphocytes ; Respiratory syncytial virus ; arachidonic acid ; chemokines ; dendritic cells ; gene expression ; gene expression regulation ; genes ; immune response ; metabolism ; models ; natural killer cells ; protein-protein interactions ; research ; respiratory tract diseases ; therapeutics ; viruses
    Sprache Englisch
    Erscheinungsverlauf 2022-0827
    Erscheinungsort Elsevier B.V.
    Dokumenttyp Artikel
    Anmerkung Pre-press version
    ZDB-ID 605780-9
    ISSN 1872-7492 ; 0168-1702
    ISSN (online) 1872-7492
    ISSN 0168-1702
    DOI 10.1016/j.virusres.2022.198906
    Datenquelle NAL Katalog (AGRICOLA)

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  10. Artikel: An optimal method for diagnosing heart disease using combination of grasshopper evalutionary algorithm and support vector machines.

    Zhou, Wei / Liu, Hongbo / Zhou, Rui / Li, Jiafu / Ahmadi, Sina

    Heliyon

    2024  Band 10, Heft 9, Seite(n) e30363

    Abstract: Due to the importance of accurate diagnosis and prompt treatment of this condition, the medical world is searching for a solution for its early detection and efficient treatment. Heart disease is one of the leading causes of death in modern society. With ...

    Abstract Due to the importance of accurate diagnosis and prompt treatment of this condition, the medical world is searching for a solution for its early detection and efficient treatment. Heart disease is one of the leading causes of death in modern society. With the development of computer science today, this issue can be resolved using computers. Data mining is one of the solutions for diagnosing this illness. One of the cutting-edge disciplines, data mining, can aid in better decision-making in many areas of medicine, including disease diagnosis and treatment. In order to improve diagnosis accuracy, a combination method using the evolutionary algorithms locust and support vector machine has been tested in this study. Use should be made of heart disease. Because of the hybrid nature of this approach, normalization is actually carried out in three steps: first, by using pre-processing operations to remove unknown and outlier data from the data set; second, by using the locust evolutionary algorithm to choose the best features from the available features; and third, by classifying the data set using a support vector machine. The accuracy criterion for the proposed method compared to Niobizin methods, neural networks, and J48 trees improved by 18 %, 30 %, and 24 %, respectively, after implementing it on the data set and comparing it with other algorithms used in the field of heart disease diagnosis.
    Sprache Englisch
    Erscheinungsdatum 2024-04-25
    Erscheinungsland England
    Dokumenttyp Journal Article
    ZDB-ID 2835763-2
    ISSN 2405-8440
    ISSN 2405-8440
    DOI 10.1016/j.heliyon.2024.e30363
    Datenquelle MEDical Literature Analysis and Retrieval System OnLINE

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