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  1. Book ; Online: Plasma Cash

    Konstantopoulos, Georgios

    Towards more efficient Plasma constructions

    2019  

    Abstract: Plasma is a framework for scalable off-chain computation. We describe and evaluate Plasma Cash, an improved Plasma construction which leverages non-fungible tokens and Sparse Merkle Trees to reduce the data storage and bandwidth requirements for users. ... ...

    Abstract Plasma is a framework for scalable off-chain computation. We describe and evaluate Plasma Cash, an improved Plasma construction which leverages non-fungible tokens and Sparse Merkle Trees to reduce the data storage and bandwidth requirements for users. We analyze the cryptoeconomic exit and challenge mechanisms used to keep user funds secured, even when the Plasma Cash chain's consensus algorithm is compromised. A reference implementation is provided for evaluation. Finally, we briefly discuss further improvements that can be made to the Plasma Cash protocol such as arbitrary denomination payments, less user data checking, fast and optimistic exits.
    Keywords Computer Science - Cryptography and Security
    Publishing date 2019-11-27
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article: Factors Influencing Functional Outcomes in Supracondylar Humerus Fractures: A Retrospective Study of Paediatric Patients in a Level One Trauma Centre.

    Poulios, Panagiotis / Serlis, Athanasios / Durand-Hill, Matthieu / Konstantopoulos, Georgios

    Cureus

    2023  Volume 15, Issue 4, Page(s) e37447

    Abstract: Background The outcomes after fixation of the supracondylar humerus fracture (SCHF) are not documented in the current literature. In our study, we endeavour to determine the factors that influence the functional outcome and gauge their respective impact. ...

    Abstract Background The outcomes after fixation of the supracondylar humerus fracture (SCHF) are not documented in the current literature. In our study, we endeavour to determine the factors that influence the functional outcome and gauge their respective impact. Methodology We retrospectively reviewed the outcomes of patients who presented to our tertiary care centre (Royal London Hospital) with SCHFs between September 2017 and February 2018. We analysed patient records to assess several clinical parameters, including age, Gartland's classification, comorbidities, time to treatment, and fixation configuration. We conducted a multiple linear regression analysis to determine each of the clinical parameter's impact on the functional and cosmetic outcome, as reflected in Flynn's criteria. Results We included 112 patients in our study. Pediatric SCHFs had good functional outcomes based on Flynn's criteria. There was no significant statistical difference in functional outcomes with respect to sex (p= 0.713), age (p= 0.96), fracture type (p= 0.14), K-wire configuration (p=0.83), and time elapsed since surgery (p= 0.240). Conclusions Our results demonstrate that good functional outcomes can be expected with paediatric SCHFs based on Flynn's criteria, regardless of age at injury, sex, or pin configuration, provided satisfactory reduction is achieved and maintained. The only variable with statistical significance was Gartland's grade; Grades III and IV were correlated with poorer outcomes.
    Language English
    Publishing date 2023-04-11
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2747273-5
    ISSN 2168-8184
    ISSN 2168-8184
    DOI 10.7759/cureus.37447
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: Digital Innovation Enabled Nanomaterial Manufacturing; Machine Learning Strategies and Green Perspectives.

    Konstantopoulos, Georgios / Koumoulos, Elias P / Charitidis, Costas A

    Nanomaterials (Basel, Switzerland)

    2022  Volume 12, Issue 15

    Abstract: Machine learning has been an emerging scientific field serving the modern multidisciplinary needs in the Materials Science and Manufacturing sector. The taxonomy and mapping of nanomaterial properties based on data analytics is going to ensure safe and ... ...

    Abstract Machine learning has been an emerging scientific field serving the modern multidisciplinary needs in the Materials Science and Manufacturing sector. The taxonomy and mapping of nanomaterial properties based on data analytics is going to ensure safe and green manufacturing with consciousness raised on effective resource management. The utilization of predictive modelling tools empowered with artificial intelligence (AI) has proposed novel paths in materials discovery and optimization, while it can further stimulate the cutting-edge and data-driven design of a tailored behavioral profile of nanomaterials to serve the special needs of application environments. The previous knowledge of the physics and mathematical representation of material behaviors, as well as the utilization of already generated testing data, received specific attention by scientists. However, the exploration of available information is not always manageable, and machine intelligence can efficiently (computational resources, time) meet this challenge via high-throughput multidimensional search exploration capabilities. Moreover, the modelling of bio-chemical interactions with the environment and living organisms has been demonstrated to connect chemical structure with acute or tolerable effects upon exposure. Thus, in this review, a summary of recent computational developments is provided with the aim to cover excelling research and present challenges towards unbiased, decentralized, and data-driven decision-making, in relation to increased impact in the field of advanced nanomaterials manufacturing and nanoinformatics, and to indicate the steps required to realize rapid, safe, and circular-by-design nanomaterials.
    Language English
    Publishing date 2022-08-01
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2662255-5
    ISSN 2079-4991
    ISSN 2079-4991
    DOI 10.3390/nano12152646
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  4. Book ; Online: Deep Learning Aided Beamforming for Downlink Non Orthogonal Multiple Access Systems

    Konstantopoulos, Georgios / Ropokis, Georgios A. / Louet, Yves

    2023  

    Abstract: We investigate the problem of optimal beamformer design for the downlink of Multi Input Single Output (MISO) Non-Orthogonal Multiple Access (NOMA). In more detail, focusing on the two-user scenario, we first derive a closed from expression for the Bit ... ...

    Abstract We investigate the problem of optimal beamformer design for the downlink of Multi Input Single Output (MISO) Non-Orthogonal Multiple Access (NOMA). In more detail, focusing on the two-user scenario, we first derive a closed from expression for the Bit Error Rate (BER) experienced by both user. Using the derived expression, in an effort to introduce fairness in our system design, we introduce the problem of optimal, with respect to minimizing the maximum of the BER values experienced by the two users, beamforming and propose a Machine Learning (ML) based solution for this problem. Finally, we conduct simulations which allow us to verify that our proposed algorithm outperforms other existing benchmarks as well as that in a variety of cases, it may result to BER performance close to the one obtained by the use of time consuming constrained optimization methods, such as to solve the given optimization problem.

    Comment: This paper was submitted and is under review by IEEE Transactions on Machine Learning in Communications and Networking Journal (TMLCN)
    Keywords Electrical Engineering and Systems Science - Signal Processing
    Subject code 006
    Publishing date 2023-05-04
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article: Testing Novel Portland Cement Formulations with Carbon Nanotubes and Intrinsic Properties Revelation: Nanoindentation Analysis with Machine Learning on Microstructure Identification.

    Konstantopoulos, Georgios / Koumoulos, Elias P / Charitidis, Costas A

    Nanomaterials (Basel, Switzerland)

    2020  Volume 10, Issue 4

    Abstract: Nanoindentation was utilized as a non-destructive technique to identify Portland Cement hydration phases. Artificial Intelligence (AI) and semi-supervised Machine Learning (ML) were used for knowledge gain on the effect of carbon nanotubes to ... ...

    Abstract Nanoindentation was utilized as a non-destructive technique to identify Portland Cement hydration phases. Artificial Intelligence (AI) and semi-supervised Machine Learning (ML) were used for knowledge gain on the effect of carbon nanotubes to nanomechanics in novel cement formulations. Data labelling is performed with unsupervised ML with k-means clustering. Supervised ML classification is used in order to predict the hydration products composition and 97.6% accuracy was achieved. Analysis included multiple nanoindentation raw data variables, and required less time to execute than conventional single component probability density analysis (PDA). Also, PDA was less informative than ML regarding information exchange and re-usability of input in design predictions. In principle, ML is the appropriate science for predictive modeling, such as cement phase identification and facilitates the acquisition of precise results. This study introduces unbiased structure-property relations with ML to monitor cement durability based on cement phases nanomechanics compared to PDA, which offers a solution based on local optima of a multidimensional space solution. Evaluation of nanomaterials inclusion in composite reinforcement using semi-supervised ML was proved feasible. This methodology is expected to contribute to design informatics due to the high prediction metrics, which holds promise for the transfer learning potential of these models for studying other novel cement formulations.
    Language English
    Publishing date 2020-03-30
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2662255-5
    ISSN 2079-4991
    ISSN 2079-4991
    DOI 10.3390/nano10040645
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Carbon Fiber Reinforced Composites: Study of Modification Effect on Weathering-Induced Ageing via Nanoindentation and Deep Learning.

    Konstantopoulos, Georgios / Semitekolos, Dionisis / Koumoulos, Elias P / Charitidis, Costas

    Nanomaterials (Basel, Switzerland)

    2021  Volume 11, Issue 10

    Abstract: The exposure of carbon-fiber-reinforced polymers (CFRPs) to open-field conditions was investigated. Establishment of structure-property relations with nanoindentation enabled the observation of modification effects on carbon-fiber interfaces, and impact ... ...

    Abstract The exposure of carbon-fiber-reinforced polymers (CFRPs) to open-field conditions was investigated. Establishment of structure-property relations with nanoindentation enabled the observation of modification effects on carbon-fiber interfaces, and impact resistance. Mapping of nanomechanical properties was performed using expectation-maximization optimization of Gaussian fitting for each CFRPs microstructure (matrix, interface, carbon fiber), while Weibull analysis connected the weathering effect to the statistically representative behavior of the produced composites. Plasma modification demonstrated reduced defect density and improved nanomechanical properties after weathering. Artificial intelligence for anomaly detection provided insights on condition monitoring of CFRPs. Deep-learning neural networks with three hidden layers were used to model the resistance to plastic deformation based on nanoindentation parameters. This study provides new assessment insights in composite engineering and quality assurance, especially during exposure under service conditions.
    Language English
    Publishing date 2021-10-06
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2662255-5
    ISSN 2079-4991
    ISSN 2079-4991
    DOI 10.3390/nano11102631
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  7. Book ; Thesis: Zusammenhangsuntersuchung zwischen psychomotorischer Entwicklung im zweiten Lebensjahr und neuromotorischen Befunden mit fünf Jahren

    Konstantopoulos, Georgios

    1985  

    Size 154, XXXVII S. : graph. Darst.
    Document type Book ; Thesis
    Thesis / German Habilitation thesis München, Univ., Diss., 1985
    HBZ-ID HT003213879
    Database Catalogue ZB MED Medicine, Health

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    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    87 D 1724 order for loan Magazin

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  8. Article ; Online: Remote Follow-up of Shoulder Arthroplasty Patients During COVID-19 Pandemic - Is This the way Forward?

    Mansukhani, Sameer A / Gopinath, Praveen / Chaturvedi, Amit / Konstantopoulos, Georgios / Leivadiotou, Dimitra

    Journal of shoulder and elbow arthroplasty

    2022  Volume 6, Page(s) 24715492221075460

    Abstract: Background: The COVID-19 Pandemic has affected the way health care systems function across the globe. Apart from eliminating the risk of being in a vulnerable environment during the pandemic such as a hospital setting, virtual arthroplasty follow-up ... ...

    Abstract Background: The COVID-19 Pandemic has affected the way health care systems function across the globe. Apart from eliminating the risk of being in a vulnerable environment during the pandemic such as a hospital setting, virtual arthroplasty follow-up reduces the demand on funding and resources on the National Health Services (NHS).
    Methods: We retrospectively reviewed our shoulder arthroplasty patients (55) operated between October 2018 to November 2020 at both our hospital sites. For remote follow-up, patients were contacted on a scheduled appointment date via telephone by an orthopaedic surgeon to enquire about their wound, pain and function. Patients were questioned as per questionnaire from the Oxford Shoulder Score (OSS) and American Shoulder and Elbow Surgeons (ASES) Standardised Assessment form.
    Results: 50 patients were included in the final data set after excluding those who had died (5 patients). All patients had had final x-rays with full Covid-19 precautions at the time of final follow-up. No patient had wound problems except one who had concerns of wound appearance. There were no cases of notching, impingement, deep infection, dislocation or nerve injury. Of the 50 patients, 40 (80%) patients were satisfied to have a remote follow-up. 36 (72%) patients said they wouldn't mind a remote follow-up appointment.
    Conclusion: Remote follow-up via audio consultation may be an effective alternative to in person visits after shoulder arthroplasty. Patients in this series demonstrated a high level of satisfaction with virtual visits and post-operative complications were effectively identified.
    Language English
    Publishing date 2022-02-14
    Publishing country United States
    Document type Journal Article
    ISSN 2471-5492
    ISSN (online) 2471-5492
    DOI 10.1177/24715492221075460
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  9. Article: Exploration of Methodologies for Developing Antimicrobial Fused Filament Fabrication Parts.

    Pemas, Sotirios / Xanthopoulou, Eleftheria / Terzopoulou, Zoi / Konstantopoulos, Georgios / Bikiaris, Dimitrios N / Kottaridi, Christine / Tzovaras, Dimitrios / Pechlivani, Eleftheria Maria

    Materials (Basel, Switzerland)

    2023  Volume 16, Issue 21

    Abstract: Composite 3D printing filaments integrating antimicrobial nanoparticles offer inherent microbial resistance, mitigating contamination and infections. Developing antimicrobial 3D-printed plastics is crucial for tailoring medical solutions, such as ... ...

    Abstract Composite 3D printing filaments integrating antimicrobial nanoparticles offer inherent microbial resistance, mitigating contamination and infections. Developing antimicrobial 3D-printed plastics is crucial for tailoring medical solutions, such as implants, and cutting costs when compared with metal options. Furthermore, hospital sustainability can be enhanced via on-demand 3D printing of medical tools. A PLA-based filament incorporating 5% TiO
    Language English
    Publishing date 2023-10-29
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2487261-1
    ISSN 1996-1944
    ISSN 1996-1944
    DOI 10.3390/ma16216937
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: HPV16

    Konstantopoulos, Georgios / Leventakou, Danai / Saltiel, Despoina-Rozi / Zervoudi, Efthalia / Logotheti, Eirini / Pettas, Spyros / Karagianni, Korina / Daiou, Angeliki / Hatzistergos, Konstantinos E / Dafou, Dimitra / Arsenakis, Minas / Kottaridi, Christine

    Viruses

    2024  Volume 16, Issue 1

    Abstract: Human Papillomaviruses have been associated with the occurrence of cervical cancer, the fourth most common cancer that affects women globally, while 70% of cases are caused by infection with the high-risk types HPV16 and HPV18. The integration of these ... ...

    Abstract Human Papillomaviruses have been associated with the occurrence of cervical cancer, the fourth most common cancer that affects women globally, while 70% of cases are caused by infection with the high-risk types HPV16 and HPV18. The integration of these viruses' oncogenes
    MeSH term(s) Female ; Humans ; B7-H1 Antigen/genetics ; Human papillomavirus 16/genetics ; Immune Evasion ; MicroRNAs/genetics ; Uterine Cervical Neoplasms/genetics ; Uterine Cervical Neoplasms/virology ; Oncogene Proteins, Viral/genetics
    Chemical Substances B7-H1 Antigen ; MicroRNAs ; MIRN143 microRNA, human ; E6 protein, Human papillomavirus type 16 ; Oncogene Proteins, Viral ; HIF1A protein, human
    Language English
    Publishing date 2024-01-12
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2516098-9
    ISSN 1999-4915 ; 1999-4915
    ISSN (online) 1999-4915
    ISSN 1999-4915
    DOI 10.3390/v16010113
    Database MEDical Literature Analysis and Retrieval System OnLINE

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