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  1. AU="Ziming Zhang"
  2. AU="Mensah, Derrick"
  3. AU="Albacker, L"
  4. AU="Rupp, Adam"
  5. AU=Chia Helena N
  6. AU="Agostini, Ludovico"
  7. AU="Vieira, Dorice"
  8. AU="Sharma, Arya M"
  9. AU="Lieve E. H. van der Donk"
  10. AU="Großer, Matthias"
  11. AU="Ong, Edison"
  12. AU=Lavery James V
  13. AU=Moss Arthur J
  14. AU="Ni, Dongchun"
  15. AU="Yang, Yanfan"
  16. AU="Shona Manning"
  17. AU=Charters Pia F P AU=Charters Pia F P
  18. AU="Adumuah, Naa N"
  19. AU="Rodrigues, Jonathan Carl Luis"
  20. AU=Seidel Bastian M
  21. AU="Duan Weimin"
  22. AU=Ioanas M
  23. AU="Nancy Zambon"
  24. AU="Kumawat, Sunita"
  25. AU=Bogliacino Francesco
  26. AU="Setter, Peter"
  27. AU=Shikata Chihiro
  28. AU="Jordan P. Metcalf"
  29. AU=Peri?i? Nanut Milica AU=Peri?i? Nanut Milica
  30. AU="Pramod, Ganapathiraju"
  31. AU="Fu, Chu-Jun"
  32. AU="Nejad, Harry G."
  33. AU="Zhang, Q E"
  34. AU="Oppenheim, Madeline"

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  1. Artikel ; Online: Evolutionary Game Analysis of Shared Manufacturing Quality Innovation Synergetic Behavior Considering a Subject’s Heterogeneous Emotions

    Ziming Zhang / Xinping Wang / Chang Su / Linhui Sun

    Processes, Vol 10, Iss 1233, p

    2022  Band 1233

    Abstract: Shared manufacturing provides a new path for the transformation and development of the manufacturing industry, but challenges such as low quality and poor positivity for quality improvement limit the positive role of shared manufacturing. Considering the ...

    Abstract Shared manufacturing provides a new path for the transformation and development of the manufacturing industry, but challenges such as low quality and poor positivity for quality improvement limit the positive role of shared manufacturing. Considering the influences of heterogeneous emotions of subjects on quality decision making, the theory of rank-dependent expected utility (RDEU) and evolutionary game theory were integrated to establish an evolutionary game model of shared manufacturing quality innovation synergy with multi-agent participation and analyze how sentiment affects motivation for quality improvement. The study showed that: (1) emotions, an irrational factor, can significantly change the stable state of the evolution of the shared manufacturing quality innovation synergetic system by influencing the decision-making behavior of decision makers; (2) in terms of the specific microscopic influence mechanism, rationality is the key to ensuring that the behavioral decisions of decision makers do not enshrine large systemic deviations. (3) In terms of the mechanism of heterogeneous emotions, when one party is optimistic, the deepening of the other party’s pessimism tends to bring positive effects; when one party is pessimistic, the deepening of the other party’s optimism tends to bring negative effects. The main management insights are as follows: (1) correctly recognizing and treating heterogeneous emotions of decision makers and regulating the formation and role of heterogeneous emotions of decision makers; (2) appropriately creating an atmosphere of pessimistic emotions, and guiding shared manufacturing to pay attention to manufacturing quality innovation synergy; (3) appropriately releasing favorable information about quality innovation synergy, and continuously promoting high-quality development of shared manufacturing. This study broadens the path of quality improvement in shared manufacturing and the scope of application of emotion theory in a certain sense.
    Schlagwörter shared manufacturing ; quality innovation synergy ; RDEU ; evolutionary game ; heterogeneous emotions ; Chemical technology ; TP1-1185 ; Chemistry ; QD1-999
    Thema/Rubrik (Code) 629
    Sprache Englisch
    Erscheinungsdatum 2022-06-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  2. Artikel ; Online: An Edge Cloud Data Integrity Protection Scheme Based on Blockchain

    Weihua Duan / Yu Jiang / Xiaolong Xu / Ziming Zhang / Guanpei Liu

    Security and Communication Networks, Vol

    2022  Band 2022

    Abstract: The publicly accessible feature of edge servers leads to the threat of malicious access to the data stored on the server and a series of security problems such as the leakage of user data privacy and the destruction of integrity. Data custody causes the ... ...

    Abstract The publicly accessible feature of edge servers leads to the threat of malicious access to the data stored on the server and a series of security problems such as the leakage of user data privacy and the destruction of integrity. Data custody causes the separation of user ownership and management rights and brings potential security risks of data theft and destruction. Among them, for the integrity of the data uploaded by the terminal, the current protection mechanism mostly verifies the identity of the visitor or encrypts the data, but the role of verification is mostly assumed by the server, and it is impossible to avoid the collusion of edge servers with malicious intruders. In this paper, a distributed virtual machine agent (VMA) is designed and implemented, an edge cloud data integrity monitoring framework is built, and the verification protocol based on blockchain is proposed, which achieves trusted verification without relying on a trusted third party. Also, a prototype system of edge cloud data integrity protection based on blockchain is constructed to prevent data corruption. The results of security proof and experimental verification show that the mechanism based on blockchain technology can defend against three attacks of cloud service providers, has superior computation, and reduces the storage costs to protect the integrity of user data.
    Schlagwörter Technology (General) ; T1-995 ; Science (General) ; Q1-390
    Thema/Rubrik (Code) 303
    Sprache Englisch
    Erscheinungsdatum 2022-01-01T00:00:00Z
    Verlag Hindawi-Wiley
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  3. Artikel ; Online: A Pulmonary Vascular Extraction Algorithm from Chest CT/CTA Images

    Shihui Xu / Ziming Zhang / Qinghua Zhou / Wei Shao / Wenjun Tan

    Journal of Healthcare Engineering, Vol

    2021  Band 2021

    Abstract: Segmentation of pulmonary vessels in CT/CTA images can help physicians better determine the patient’s condition and treatment. However, due to the complexity of CT images, existing methods have limitations in the segmentation of pulmonary vessels. In ... ...

    Abstract Segmentation of pulmonary vessels in CT/CTA images can help physicians better determine the patient’s condition and treatment. However, due to the complexity of CT images, existing methods have limitations in the segmentation of pulmonary vessels. In this paper, a method based on the separation of pulmonary vessels in CT/CTA images is investigated. The method is divided into two steps: in the first step, the lung parenchyma is extracted using the Unet++ algorithm, which can effectively reduce the oversegmentation rate; in the second step, the pulmonary vessels in the lung parenchyma are extracted using nnUnet. According to the obtained lung parenchyma segmentation results, the “AND” operation is performed on the original image and the lung parenchyma segmentation results, and only the blood vessels within the lung parenchyma are segmented, which reduces the interference of external tissues and improves the segmentation accuracy. The experimental data source used CT/CTA images acquired from the partner hospital. After the experiments were performed on a total of 67 sets of images, the accuracy of CT and CTA images reached 85.1% and 87.7%, respectively. The comparison of whether to segment the lung parenchyma and with other conventional methods was also performed, and the experimental results showed that the algorithm in this paper has high accuracy.
    Schlagwörter Medicine (General) ; R5-920 ; Medical technology ; R855-855.5
    Thema/Rubrik (Code) 000
    Sprache Englisch
    Erscheinungsdatum 2021-01-01T00:00:00Z
    Verlag Hindawi Limited
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  4. Artikel ; Online: Game Analysis of the Evolution of Energy Structure Transition Considering Low-Carbon Sentiment of the Decision-Makers in the Context of Carbon Neutrality

    Xinping Wang / Zhenghao Guo / Ziming Zhang / Boying Li / Chang Su / Linhui Sun / Shihui Wang

    Processes, Vol 10, Iss 8, p

    2022  Band 1650

    Abstract: Countries have started to aggressively undertake energy structure transformation strategies in order to reach the objective of carbon neutrality. Both clean and efficient coal energy use and clean energy use will be crucial to the process of changing the ...

    Abstract Countries have started to aggressively undertake energy structure transformation strategies in order to reach the objective of carbon neutrality. Both clean and efficient coal energy use and clean energy use will be crucial to the process of changing the energy structure since the two cannot be totally replaced within a short period of time. In this study, we quantify emotions as an irrational factor, combine them with an evolutionary game using RDEU theory, and build an evolutionary game model between government regulators and energy consumers. We then analyze how low-carbon emotions of decision-makers affect their choice of strategy and the transformation of the energy structure. The findings support that by affecting the relative importance of each strategic choice, emotions have a profound impact on the evolutionary steady state of the system. Appropriate stress and anxiety can increase decision-makers’ feelings of responsibility, while pleasant emotions frequently support strategic conduct. The main countermeasures are as follows: Allow government regulators and energy consumers to properly release positive information, with government regulators forming subsidies and energy consumers actively cooperating and promoting low-carbon activities. This will properly guide the low-carbon sentiment of game subjects to keep them realistically pessimistic.
    Schlagwörter carbon neutrality ; energy structure transition ; low-carbon sentiment ; RDEU ; evolutionary game ; Chemical technology ; TP1-1185 ; Chemistry ; QD1-999
    Thema/Rubrik (Code) 320
    Sprache Englisch
    Erscheinungsdatum 2022-08-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  5. Artikel ; Online: A Pulmonary Artery-Vein Separation Algorithm Based on the Relationship between Subtrees Information

    Kun Yu / Ziming Zhang / Xiaoshuo Li / Pan Liu / Qinghua Zhou / Wenjun Tan

    Journal of Healthcare Engineering, Vol

    2021  Band 2021

    Abstract: Physicians need to distinguish between pulmonary arteries and veins when diagnosing diseases such as chronic obstructive pulmonary disease (COPD) and lung tumors. However, manual differentiation is difficult due to various factors such as equipment and ... ...

    Abstract Physicians need to distinguish between pulmonary arteries and veins when diagnosing diseases such as chronic obstructive pulmonary disease (COPD) and lung tumors. However, manual differentiation is difficult due to various factors such as equipment and body structure. Unlike previous geometric methods of manually selecting the points of seeds and using neural networks for separation, this paper proposes a combined algorithm for pulmonary artery-vein separation based on subtree relationship by implementing a completely new idea and combining global and local information, anatomical knowledge, and two-dimensional region growing method. The algorithm completes the reconstruction of the whole vascular structure and the separation of adhesion points from the tree-like structure characteristics of blood vessels, after which the automatic classification of arteries and veins is achieved by using anatomical knowledge, and the whole process is free from human intervention. After comparing all the experimental results with the gold standard, we obtained an average separation accuracy of 85%, which achieved effective separation. Meanwhile, the time range could be controlled between 40 s and 50 s, indicating that the algorithm has good stability.
    Schlagwörter Medicine (General) ; R5-920 ; Medical technology ; R855-855.5
    Thema/Rubrik (Code) 006
    Sprache Englisch
    Erscheinungsdatum 2021-01-01T00:00:00Z
    Verlag Hindawi Limited
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  6. Artikel ; Online: Application of a Neural Network Classifier to Radiofrequency-Based Osteopenia/Osteoporosis Screening

    Johnathan W. Adams / Ziming Zhang / Gregory M. Noetscher / Ara Nazarian / Sergey N. Makarov

    IEEE Journal of Translational Engineering in Health and Medicine, Vol 9, Pp 1-

    2021  Band 7

    Abstract: Objective: There is an unmet need for quick, physically small, and cost-effective office-based techniques that can measure bone properties without the use of ionizing radiation. Methods: The present study reports the application of a neural network ... ...

    Abstract Objective: There is an unmet need for quick, physically small, and cost-effective office-based techniques that can measure bone properties without the use of ionizing radiation. Methods: The present study reports the application of a neural network classifier to the processing of previously collected data on very-low-power radiofrequency propagation through the wrist to detect osteoporotic/osteopenic conditions. Our approach categorizes the data obtained for two dichotomic groups. Group 1 included 27 osteoporotic/osteopenic subjects with low Bone Mineral Density (BMD), characterized by a Dual X-Ray Absorptiometry (DXA) T-score below – 1, measured within one year. Group 2 included 40 healthy and mostly young subjects without major clinical risk factors such as a (family) history of bone fracture. We process the complex radiofrequency spectrum from 30 kHz to 2 GHz. Instead of averaging data for both wrists, we process them independently along with the wrist circumference and then combine the results, which greatly increases the sensitivity. Measurements along with data processing require less than 1 min. Results: For the two dichotomic groups identified above, the neural network classifier of the radiofrequency spectrum reports a sensitivity of 83% and a specificity of 94%. Significance: These results are obtained without including any additional clinical risk factors. They justify that the radio transmission data are usable on their own as a predictor of bone density. This approach has the potential for screening patients at risk for fragility fractures in the office, given the ease of implementation, small device size, and low costs associated with both the technique and the equipment.
    Schlagwörter Artificial intelligence ; neural networks ; osteopenia ; osteoporosis ; radiofrequency measurements ; signal processing ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Medical technology ; R855-855.5
    Thema/Rubrik (Code) 310
    Sprache Englisch
    Erscheinungsdatum 2021-01-01T00:00:00Z
    Verlag IEEE
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    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  7. Artikel ; Online: Identification of the Key Pathways and Genes in Hypoxia Pulmonary Arterial Hypertension Following Intrauterine Growth Retardation

    Weifen Zhu / Ziming Zhang / Weiwei Gui / Zheng Shen / Yixin Chen / Xueyao Yin / Li Liang / Lin Li

    Frontiers in Molecular Biosciences, Vol

    2022  Band 9

    Abstract: High-throughput sequencing and weighted gene co-expression network analysis (WGCNA) were used to identify susceptibility modules and genes in liver tissue for the hypoxic pulmonary arterial hypertension (PAH) animal model following intrauterine growth ... ...

    Abstract High-throughput sequencing and weighted gene co-expression network analysis (WGCNA) were used to identify susceptibility modules and genes in liver tissue for the hypoxic pulmonary arterial hypertension (PAH) animal model following intrauterine growth retardation (IUGR). A total of 5,000 genes were clustered into eight co-expression modules via WGCNA. Module blue was mostly significantly correlated with the IUGR–hypoxia group. Gene Ontology analysis showed that genes in the module blue were mainly enriched in the fatty acid metabolic process, lipid modification, and fatty acid catabolic process. The Kyoto Encyclopedia of Genes and Genomes enrichment analyses showed that the genes in module blue were mainly associated with fatty acid metabolism, PPAR signaling pathway, and biosynthesis of unsaturated fatty acids. In addition, the maximal clique centrality method was used to identify the hub genes in the subnetworks, and the obtained results were verified using real-time quantitative PCR. Finally, we identified that four genes including Cyp2f4, Lipc, Acadl, and Hacl1 were significantly associated with IUGR-hypoxia. Our study identified a module and several key genes that acted as essential components in the etiology of the long-term metabolic consequences in hypoxia PAH following IUGR.
    Schlagwörter pulmonary arterial hypertension ; intrauterine growth retardation ; hypoxia ; weighted gene co-expression network analysis ; metabolic dysfunction ; Biology (General) ; QH301-705.5
    Thema/Rubrik (Code) 610
    Sprache Englisch
    Erscheinungsdatum 2022-03-01T00:00:00Z
    Verlag Frontiers Media S.A.
    Dokumenttyp Artikel ; Online
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  8. Artikel ; Online: Differed Adaptive Strategies to Nutrient Status between Native and Exotic Mangrove Species

    Ying Wang / Ziming Zhang / Kehong He / Zhangcai Qin / Luhua Xie / Yihan Liu / Yaobei Lin / Jing Wei / Fan Wang

    Forests, Vol 13, Iss 804, p

    2022  Band 804

    Abstract: To rapidly rehabilitate mangrove forests, exotic mangrove species characterized by high growth rates have been introduced in China, which would undoubtedly affect the nutrient status, nutrient acquisition and utilization strategies of mangrove plants, ... ...

    Abstract To rapidly rehabilitate mangrove forests, exotic mangrove species characterized by high growth rates have been introduced in China, which would undoubtedly affect the nutrient status, nutrient acquisition and utilization strategies of mangrove plants, but the mechanism remains unclear. Qi’ao Island (a suburb of Zhuhai City) has the largest continuous exotic mangrove forests in China, where a mass collection of mangrove soils, plant tissues and tidewater was conducted. Ecological stoichiometric ratios and isotopic compositions were then analyzed to evaluate the ecosystem-scale nutrient status and compare the nutrient acquisition and utilization strategies of native Kandelia obovata (KO) and exotic Sonneratia apetala (SA) species. Soil and foliar C:N:P stoichiometries indicated that there is high P availability but N limitations, while further isotopic evidence indicated that native KO and exotic SA responded differently to the N limitation status. First, native KO seemed to prefer NO 3 − , while exotic SA preferred NH 4 + , according to the Δ 15 N leaf–root (leaf–root δ 15 N difference) as well as the relationships between foliar δ 15 N and soil-extracted NH 4 + δ 15 N, and between N and heavy metal contents. This suggested possible inter-specific competition between native KO and exotic SA, leading to different N species’ preferences to maximize resource utilization. Next, native KO likely adopted the “conservative” strategy to ensure survival with reduced investment in N-rich growth components but root systems leading to lower growth rates and higher N use efficiency (NUE) and intrinsic water use efficiency (iWUE), while exotic SA adopted the “aggressive” strategy to ensure fast growth with heavy investment in N-rich growth components, leading to rapid growth and lower NUE and iWUE, and showing signs of invasiveness. Further, native KO is more responsive to aggravated N limitation by enhancing NUE. This study will provide insights into the adaptation of different mangrove species to nutrient limitations and the ...
    Schlagwörter mangrove ; exotic species ; nutrient status ; nitrogen use efficiency ; intrinsic water use efficiency ; Plant ecology ; QK900-989
    Thema/Rubrik (Code) 333 ; 580
    Sprache Englisch
    Erscheinungsdatum 2022-05-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  9. Artikel ; Online: Artificial Intelligence-Enhanced Echocardiography for Systolic Function Assessment

    Zisang Zhang / Ye Zhu / Manwei Liu / Ziming Zhang / Yang Zhao / Xin Yang / Mingxing Xie / Li Zhang

    Journal of Clinical Medicine, Vol 11, Iss 2893, p

    2022  Band 2893

    Abstract: The accurate assessment of left ventricular systolic function is crucial in the diagnosis and treatment of cardiovascular diseases. Left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS) are the most critical indexes of cardiac ... ...

    Abstract The accurate assessment of left ventricular systolic function is crucial in the diagnosis and treatment of cardiovascular diseases. Left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS) are the most critical indexes of cardiac systolic function. Echocardiography has become the mainstay of cardiac imaging for measuring LVEF and GLS because it is non-invasive, radiation-free, and allows for bedside operation and real-time processing. However, the human assessment of cardiac function depends on the sonographer’s experience, and despite their years of training, inter-observer variability exists. In addition, GLS requires post-processing, which is time consuming and shows variability across different devices. Researchers have turned to artificial intelligence (AI) to address these challenges. The powerful learning capabilities of AI enable feature extraction, which helps to achieve accurate identification of cardiac structures and reliable estimation of the ventricular volume and myocardial motion. Hence, the automatic output of systolic function indexes can be achieved based on echocardiographic images. This review attempts to thoroughly explain the latest progress of AI in assessing left ventricular systolic function and differential diagnosis of heart diseases by echocardiography and discusses the challenges and promises of this new field.
    Schlagwörter echocardiography ; artificial intelligence ; left ventricular systolic function ; machine learning ; deep learning ; Medicine ; R
    Thema/Rubrik (Code) 610
    Sprache Englisch
    Erscheinungsdatum 2022-05-01T00:00:00Z
    Verlag MDPI AG
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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  10. Artikel ; Online: Artificial Intelligence-assisted Medical Imaging in Interventional Management of Valvular Heart Disease

    Wenwen Chen / BS / Yuji Xie / MD / Zisang Zhang / Ye Zhu / MS / Yiwei Zhang / Shuangshuang Zhu / PhD / Chun Wu / Ziming Zhang / Xin Yang / Man wei Liu / Mingxing Xie / Li Zhang

    Advanced Ultrasound in Diagnosis and Therapy, Vol 7, Iss 3, Pp 217-

    2023  Band 227

    Abstract: The integration of medical imaging and artificial intelligence (AI) has revolutionized interventional therapy of valvular heart diseases (VHD), owing to rapid development in multimodality imaging and healthcare big data. Medical imaging techniques, such ... ...

    Abstract The integration of medical imaging and artificial intelligence (AI) has revolutionized interventional therapy of valvular heart diseases (VHD), owing to rapid development in multimodality imaging and healthcare big data. Medical imaging techniques, such as echocardiography, cardiovascular magnetic resonance (CMR) and computed tomography (CT), play an irreplaceable role in the whole process of pre-, intra- and post-procedural intervention of VHD. Different imaging techniques have unique advantages in different stages of interventional therapy. Therefore, single imaging technique can’t fully meet the requirements of complicated clinical scenarios. More importantly, a single intraoperative image provides only limited vision of the surgical field, which could be a potential source for unsatisfactory prognosis. Besides, the non-negligible inter- and intra-observer variability limits the precise quantification of heart valve structure and function in daily clinical practice. With the help of analysis clustered and regressed by big data and exponential growth in computing power, AI broken grounds in the interventional therapy of VHD, including preoperative planning, intraoperative navigation, and postoperative follow-up. This article reviews the state-of-the-art progress and directions in the application of AI for medical imaging in the interventional therapy of VHD.
    Schlagwörter |vhd|ai|machine learning|medical imaging ; Medical technology ; R855-855.5 ; Medicine ; R
    Thema/Rubrik (Code) 610
    Sprache Englisch
    Erscheinungsdatum 2023-09-01T00:00:00Z
    Verlag Editorial Office of Advanced Ultrasound in Diagnosis and Therapy
    Dokumenttyp Artikel ; Online
    Datenquelle BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl)

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