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Almusaed, A. & Yitmen, I. (2023). Architectural Reply for Smart Building Design Concepts Based on Artificial Intelligence Simulation Models and Digital Twins. Sustainability, 15(6), Article ID 4955.
Open this publication in new window or tab >>Architectural Reply for Smart Building Design Concepts Based on Artificial Intelligence Simulation Models and Digital Twins
2023 (English)In: Sustainability, E-ISSN 2071-1050, Vol. 15, no 6, article id 4955Article in journal (Refereed) Published
Abstract [en]

Artificial Intelligence (AI) simulation models and digital twins (DT) are used in designingand treating the activities, layout, and functions for the new generation of buildings to enhanceuser experience and optimize building performance. These models use data about a building’s use,configuration, functions, and environment to simulate different design options and predict theireffects on house function efficiency, comfort, and safety. On the one hand, AI algorithms are usedto analyze this data and find patterns and trends that can guide the design process. On the otherhand, DTs are digital recreations of actual structures that can replicate building performance in realtime. These models would evaluate alternative design options, the performance of the building, andways to improve user comfort and building efficiency. This study examined the important role ofintelligent building design aspects, such as activities using multi-layout and the creation of particularfunctions based on AI simulation models, in developing DT-based smart building systems. Theempirical data came from a study of architecture and engineering firms throughout the globe usinga CSAQ (computer-administered, self-completed survey). For this purpose, the study employedstructural equation modeling (SEM) to examine the hypotheses and build the relationship model. Theresearch verifies the relevance of AI-based simulation models supporting the creation of intelligentbuilding design features (activities, layout, functionalities), enabling the construction of DT-basedsmart building systems. Furthermore, this study highlights the need for further exploration ofAI-based simulation models’ role and integration with DT in smart building design.

Place, publisher, year, edition, pages
MDPI, 2023
Keywords
smart building design; artificial intelligence; AI simulations models; digital twins
National Category
Building Technologies Computer Sciences
Identifiers
urn:nbn:se:hj:diva-59987 (URN)10.3390/su15064955 (DOI)000958891200001 ()2-s2.0-85151519691 (Scopus ID)GOA;;1743137 (Local ID)GOA;;1743137 (Archive number)GOA;;1743137 (OAI)
Available from: 2023-03-14 Created: 2023-03-14 Last updated: 2023-04-17Bibliographically approved
Almusaed, A., Almssad, A., Alasadi, A., Yitmen, I. & Al-Samaraee, S. (2023). Assessing the Role and Efficiency of Thermal Insulation by the "BIO-GREEN PANEL" in Enhancing Sustainability in a Built Environment. Sustainability, 15(13), Article ID 10418.
Open this publication in new window or tab >>Assessing the Role and Efficiency of Thermal Insulation by the "BIO-GREEN PANEL" in Enhancing Sustainability in a Built Environment
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2023 (English)In: Sustainability, E-ISSN 2071-1050, Vol. 15, no 13, article id 10418Article in journal (Refereed) Published
Abstract [en]

The pressing concern of climate change and the imperative to mitigate CO2 emissions have significantly influenced the selection of outdoor plant species. Consequently, evaluating CO2's environmental effects on plants has become integral to the decision-making process. Notably, reducing greenhouse gas (GHG) emissions from buildings is significant in tackling the consequences of climate change and addressing energy deficiencies. This article presents a novel approach by introducing plant panels as an integral component in future building designs, epitomizing the next generation of sustainable structures and offering a new and sustainable building solution. The integration of environmentally friendly building materials enhances buildings' indoor environments. Consequently, it becomes crucial to analyze manufacturing processes in order to reduce energy consumption, minimize waste generation, and incorporate green technologies. In this context, experimentation was conducted on six distinct plant species, revealing that the energy-saving potential of different plant types on buildings varies significantly. This finding contributes to the economy's improvement and fosters enhanced health-related and environmental responsibility. The proposed plant panels harmonize various building components and embody a strategic approach to promote health and well-being through bio-innovation. Furthermore, this innovative solution seeks to provide a sustainable alternative by addressing the challenges of unsustainable practices, outdated standards, limited implementation of new technologies, and excessive administrative barriers in the construction industry. The obtained outcomes will provide stakeholders within the building sector with pertinent data concerning performance and durability. Furthermore, these results will enable producers to acquire essential information, facilitating product improvement.

Place, publisher, year, edition, pages
MDPI, 2023
Keywords
climate change, biophilic design, bio-basis product, passport materials, built environment, thermal insulations
National Category
Construction Management
Identifiers
urn:nbn:se:hj:diva-62207 (URN)10.3390/su151310418 (DOI)001028210800001 ()2-s2.0-85165064791 (Scopus ID)GOA;intsam;897653 (Local ID)GOA;intsam;897653 (Archive number)GOA;intsam;897653 (OAI)
Available from: 2023-08-18 Created: 2023-08-18 Last updated: 2023-08-18Bibliographically approved
Homod, R. Z., Saad Jreou, G. N., Mohammed, H. I., Almusaed, A., Hussein, A. K., Al-Kouz, W., . . . Yaseen, Z. M. (2023). Crude oil production prediction based on an intelligent hybrid modelling structure generated by using the clustering algorithm in big data. Geoenergy Science and Engineering, 225, Article ID 211703.
Open this publication in new window or tab >>Crude oil production prediction based on an intelligent hybrid modelling structure generated by using the clustering algorithm in big data
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2023 (English)In: Geoenergy Science and Engineering, ISSN 2949-8910, Vol. 225, article id 211703Article in journal (Refereed) Published
Abstract [en]

Since the behavior of a complex dynamic system for a large oil field in Iraq is significantly influenced by many nonlinearities, its dependent parameters exhibit non-stationary with a very high delay time. Developing white-box modelling approaches for such dynamic oil well production cannot handle these large data sets with all dependent dimensions and their non-linear effects. Therefore, this study adopts the hybrid model that combines white-box and black-box to address such problems because the model outputs require various variable types to achieve optimal fitness to measured values. The hybrid model structure needs to evolve with changes in the physical parameters (white-box part) and Neural Networks' Weights (black-box part). The model structure of the proposed hybrid network relied on converting fuzzy rules in a Takagi–Sugeno–Kang Fuzzy System (TSK-FS) into a multilayer perceptron network (MLP). The hybrid parameters are formulated concerning six-dimensional dependent variables to describe them in matrix form or layer and by which can quantify total model outputs. After mapping categorical variables to tuples of MLP, the Gauss-Newton regression (GNR) provides an optimal update of the hybrid parameters to get the best fitting of the model outputs with the target of the dataset. The clustering technique and GNR promote predictive performance due to reducing uncertainties in the hybrid parameters. Due to time being the most effective of the independent variables for predicting oil production, datasets are classified into different clusters based on time. The actual field dataset for training and validation is collected from Zubair Oil Field (9 oil wells), which is implemented to build the proposed model. The results of the hybrid model indicate that the development of the proposed structure has achieved the high capability to represent such big data which is the most imperative feature of the proposed model. Furthermore, obtained results show its accuracy far outpacing competitors and achieving a significant improvement in predictive performance.

Place, publisher, year, edition, pages
Elsevier, 2023
Keywords
Fuzzy clustering, Hybrid modelling, Non-linear system identification, Production forecasting, Sugeno inference system, Iraq, Big data, Cluster analysis, Clustering algorithms, Forecasting, Fuzzy inference, Fuzzy neural networks, Linear systems, Oil wells, Hybrid model, Hybrid model structures, Hybrid parameters, Inference systems, Model outputs, Sugeno inference, White box, algorithm, crude oil, forecasting method, fuzzy mathematics, nonlinearity, oil field, oil production, oil well, prediction
National Category
Environmental Engineering
Identifiers
urn:nbn:se:hj:diva-60790 (URN)10.1016/j.geoen.2023.211703 (DOI)001044266600001 ()2-s2.0-85159768937 (Scopus ID)
Available from: 2023-06-07 Created: 2023-06-07 Last updated: 2023-08-29Bibliographically approved
Homod, R. Z., Yaseen, Z. M., Hussein, A. K., Almusaed, A., Alawi, O. A., Falah, M. W., . . . Eltaweel, M. (2023). Deep clustering of cooperative multi-agent reinforcement learning to optimize multi chiller HVAC systems for smart buildings energy management. Journal of Building Engineering, 65, Article ID 105689.
Open this publication in new window or tab >>Deep clustering of cooperative multi-agent reinforcement learning to optimize multi chiller HVAC systems for smart buildings energy management
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2023 (English)In: Journal of Building Engineering, E-ISSN 2352-7102, Vol. 65, article id 105689Article in journal (Refereed) Published
Abstract [en]

Chillers are responsible for almost half of the total energy demand in buildings. Hence, the obligation of control systems of multi-chiller due to changes indoor environments is one of the most significant parts of a smart building. Such a controller is described as a nonlinear and multi-objective algorithm, and its fabrication is crucial to achieving the optimal balance between indoor thermal comfort and running a minimum number of chillers. This work proposes deep clustering of cooperative multi-agent reinforcement learning (DCCMARL) as well-suited to such system control, which supports centralized control by learning of agents. In MARL, since the learning of agents is based on discrete sets of actions and stats, this drawback significantly affects the model of agents for representing their actions with efficient performance. This drawback becomes considerably worse when increasing the number of agents, due to the increased complexity of solving MARL, which makes modeling policy very challenging. Therefore, the DCCMARL of multi-objective reinforcement learning is leveraging powerful frameworks of a hybrid clustering algorithm to deal with complexity and uncertainty, which is a critical factor that influences to the achievement of high levels of a performance action. The results showed that the ability of agents to manipulate the behavior of the smart building could improve indoor thermal conditions, as well as save energy up to 44.5% compared to conventional methods. It seems reasonable to conclude that agents' performance is influenced by what type of model structure.

Place, publisher, year, edition, pages
Elsevier, 2023
Keywords
Clustering of multi-agent reinforcement learning (MARL) policy, Hybrid layer model, Multi-objective reinforcement learning (MORL), Multi-unit residential buildings, Optimal chiller sequencing control (OCSC), Takagi–sugeno fuzzy (TSF) identification, Climate control, Clustering algorithms, Deep learning, Energy management, Energy management systems, Fertilizers, Intelligent buildings, Learning systems, Multi agent systems, Clustering of multi-agent reinforcement learning policy, Clusterings, Fuzzy identification, Hybrid layer, Layer model, Learning policy, Multi objective, Multi-agent reinforcement learning, Multi-objective reinforcement learning, Multi-unit, Multi-unit residential building, Optimal chiller sequencing, Optimal chiller sequencing control, Reinforcement learnings, Residential building, Takagi-sugeno, Takagi–sugeno fuzzy identification, Reinforcement learning
National Category
Construction Management
Identifiers
urn:nbn:se:hj:diva-59280 (URN)10.1016/j.jobe.2022.105689 (DOI)000997053000001 ()2-s2.0-85144449447 (Scopus ID);intsam;851396 (Local ID);intsam;851396 (Archive number);intsam;851396 (OAI)
Available from: 2023-01-03 Created: 2023-01-03 Last updated: 2023-06-16Bibliographically approved
Almusaed, A., Yitmen, I. & Almssad, A. (2023). Enhancing Smart Home Design with AI Models: A Case Study of Living Spaces Implementation Review. Energies, 16(6), Article ID 2636.
Open this publication in new window or tab >>Enhancing Smart Home Design with AI Models: A Case Study of Living Spaces Implementation Review
2023 (English)In: Energies, E-ISSN 1996-1073, Vol. 16, no 6, article id 2636Article in journal (Refereed) Published
Abstract [en]

The normal development of “smart buildings,” which calls for integrating sensors, rich data, and artificial intelligence (AI) simulation models, promises to usher in a new era of architectural concepts. AI simulation models can improve home functions and users’ comfort and significantly cut energy consumption through better control, increased reliability, and automation. This article highlights the potential of using artificial intelligence (AI) models to improve the design and functionality of smart houses, especially in implementing living spaces. This case study provides examples of how artificial intelligence can be embedded in smart homes to improve user experience and optimize energy efficiency. Next, the article will explore and thoroughly analyze the thorough analysis of current research on the use of artificial intelligence (AI) technology in smart homes using a variety of innovative ideas, including smart interior design and a Smart Building System Framework based on digital twins (DT). Finally, the article explores the advantages of using AI models in smart homes, emphasizing living spaces. Through the case study, the theme seeks to provide ideas on how AI can be effectively embedded in smart homes to improve functionality, convenience, and energy efficiency. The overarching goal is to harness the potential of artificial intelligence by transforming how we live in our homes and improving our quality of life. The article concludes by discussing the unresolved issues and potential future research areas on the usage of AI in smart houses. Incorporating AI technology into smart homes benefits homeowners, providing excellent safety and convenience and increased energy efficiency.

Place, publisher, year, edition, pages
MDPI, 2023
Keywords
smart home design, AI technology, human environment, living space, ubiquitous computing
National Category
Building Technologies Computer Sciences
Identifiers
urn:nbn:se:hj:diva-59979 (URN)10.3390/en16062636 (DOI)000955593700001 ()2-s2.0-85151623302 (Scopus ID)GOA;;864706 (Local ID)GOA;;864706 (Archive number)GOA;;864706 (OAI)
Available from: 2023-03-13 Created: 2023-03-13 Last updated: 2023-08-28Bibliographically approved
Almusaed, A., Almssad, A., Yitmen, I. & Homod, R. Z. Z. (2023). Enhancing Student Engagement: Harnessing "AIED"'s Power in Hybrid Education - A Review Analysis. Education Sciences, 13(7), Article ID 632.
Open this publication in new window or tab >>Enhancing Student Engagement: Harnessing "AIED"'s Power in Hybrid Education - A Review Analysis
2023 (English)In: Education Sciences, E-ISSN 2227-7102, Vol. 13, no 7, article id 632Article, review/survey (Refereed) Published
Abstract [en]

Hybrid learning is a complex combination of face-to-face and online learning. This model combines the use of multimedia materials with traditional classroom work. Virtual hybrid learning is employed alongside face-to-face methods. That aims to investigate using Artificial Intelligence (AI) to increase student engagement in hybrid learning settings. Educators are confronted with contemporary issues in maintaining their students' interest and motivation as the popularity of online and hybrid education continues to grow, where many educational institutions are adopting this model due to its flexibility, student-teacher engagement, and peer-to-peer interaction. AI will help students communicate, collaborate, and receive real-time feedback, all of which are challenges in education. This article examines the advantages and disadvantages of hybrid education and the optimal approaches for incorporating Artificial Intelligence (AI) in educational settings. The research findings suggest that using AI can revolutionize hybrid education, as it enhances both student and instructor autonomy while fostering a more engaging and interactive learning environment.

Place, publisher, year, edition, pages
MDPI, 2023
Keywords
AIED, interactive learning, hybrid education, online teaching, student engagement
National Category
Pedagogy
Identifiers
urn:nbn:se:hj:diva-62234 (URN)10.3390/educsci13070632 (DOI)001035070900001 ()GOA;intsam;897923 (Local ID)GOA;intsam;897923 (Archive number)GOA;intsam;897923 (OAI)
Available from: 2023-08-22 Created: 2023-08-22 Last updated: 2023-08-22Bibliographically approved
Adlemo, A., Almusaed, A., Conway, P. L. J., Hansen, Å. & Rico-Cortez, M. (2023). Hybrid education: A critical review into challenges and opportunities. In: Proceedings of the International CDIO Conference: . Paper presented at 19th CDIO International Conference, CDIO 2023 Trondheim 26 June 2023 through 29 June 2023 (pp. 857-865). Norges teknisk-naturvitenskapelige universitet
Open this publication in new window or tab >>Hybrid education: A critical review into challenges and opportunities
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2023 (English)In: Proceedings of the International CDIO Conference, Norges teknisk-naturvitenskapelige universitet , 2023, p. 857-865Conference paper, Published paper (Refereed)
Abstract [en]

Hybrid education is a complex combination of simultaneous face-to-face and online teaching. This model of teaching comes with a wide range of benefits, primarily being able to offer the same content to a wider audience. Hybrid education became an effective form of teaching during the COVID-19 pandemic. In these post pandemic years, the benefit of hybrid education can still be utilized, allowing for improved flexibility in teaching schedules, engaging students in interactive learning, bringing online students closer to the teacher and face-to-face students, and offering education to students who could not otherwise participate. However, with all the benefits of hybrid education, there are some significant challenges which restrict the implementation or hinder the full potential of hybrid education. Some key challenges are student engagement from the online students with the teacher as well as with other students, technological requirements, physical classroom set-up, education of the teachers, and time investment in re-structuring courses. In this article, we review the challenges of hybrid education, strategies to address these challenges focusing on implementation and effectiveness, as well as evaluating student feedback from students at Jönköping University that have been a part of hybrid education. 

Place, publisher, year, edition, pages
Norges teknisk-naturvitenskapelige universitet, 2023
Series
Proceedings of the International CDIO Conference
Keywords
CDIO Standards: 8, 10, Hybrid education, Student engagement
National Category
Pedagogy
Identifiers
urn:nbn:se:hj:diva-62987 (URN)2-s2.0-85177080772 (Scopus ID)978-82-303-6186-3 (ISBN)
Conference
19th CDIO International Conference, CDIO 2023 Trondheim 26 June 2023 through 29 June 2023
Available from: 2023-12-04 Created: 2023-12-04 Last updated: 2024-01-09Bibliographically approved
Yitmen, I., Almusaed, A. & Alizadehsalehi, S. (2023). Investigating the Causal Relationships among Enablers of the Construction 5.0 Paradigm: Integration of Operator 5.0 and Society 5.0 with Human-Centricity, Sustainability, and Resilience. Sustainability, 15(11), Article ID 9105.
Open this publication in new window or tab >>Investigating the Causal Relationships among Enablers of the Construction 5.0 Paradigm: Integration of Operator 5.0 and Society 5.0 with Human-Centricity, Sustainability, and Resilience
2023 (English)In: Sustainability, E-ISSN 2071-1050, Vol. 15, no 11, article id 9105Article in journal (Refereed) Published
Abstract [en]

The Construction 5.0 paradigm is the next phase in industrial development that aims to combine the skills of human experts in partnership with efficient and precise machines to achieve production solutions that are resource-efficient and preferred by clients. This study reviewed the evolution of the Construction 5.0 paradigm by defining its features and diverse nature. It introduced the architecture, model, and system of Construction 5.0 and its key enablers: Operator 5.0, Society 5.0, human-centricity, sustainability, and resilience. The study used the SEM method to evaluate the research model and investigate the causal relationships among the key enablers of the Construction 5.0 paradigm. Nine vital hypotheses were proposed and assessed comprehensively. The critical enablers' variables were measured to examine the constructs' reliability and validity. The key findings showed that Construction 5.0 prioritizes collaboration between humans and machines, merges cyberspace with physical space, and balances the three pillars of sustainability (economy, environment, and society), creating a relationship among Operator 5.0, Society 5.0, human-Ccentricity, sustainability, and resilience. The study also discussed the limitations and challenges and offered suggestions for future research. Overall, Construction 5.0 aims to achieve sustainable development and become a robust and resilient provider of prosperity in an industrial community of a shared future. The study expects to spark debate and promote pioneering research toward the Construction 5.0 paradigm.

Place, publisher, year, edition, pages
MDPI, 2023
Keywords
Construction 5.0, Operator 5.0, Society 5.0, human-centricity, sustainability, resilience, SEM, industrial growth
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:hj:diva-61780 (URN)10.3390/su15119105 (DOI)001006097200001 ()2-s2.0-85161665630 (Scopus ID)GOA;intsam;888695 (Local ID)GOA;intsam;888695 (Archive number)GOA;intsam;888695 (OAI)
Available from: 2023-06-30 Created: 2023-06-30 Last updated: 2023-06-30Bibliographically approved
Almusaed, A., Alasadi, A. & Almssad, A. (2022). A Research on the Biophilic Concept upon School's Design from Hot Climate: A Case Study from Iraq. Advances in Materials Science and Engineering, Article ID 7994999.
Open this publication in new window or tab >>A Research on the Biophilic Concept upon School's Design from Hot Climate: A Case Study from Iraq
2022 (English)In: Advances in Materials Science and Engineering, ISSN 1687-8434, E-ISSN 1687-8442, article id 7994999Article in journal (Refereed) Published
Abstract [en]

In recent years, there have been solid global trends and severe attempts by ministries of education in the world to improve the reality of educational institutions and schools through the design and construction of schools and educational systems that meet the requirements of the age by applying the concepts of sustainable and effective systems to the new generation. They called for a promising future and hence the need to activate the applications of the biophilic schools. The theme of the biophilic schools is closely related to the concept of sustainable environmental structures that deal with the surrounding natural environment with intimacy, which is one of the most important new methods of design and construction at present, where ecological challenges are powerfully evoked in the making of their design decisions. Biophilic schools are an essential part of a new concept that wants to design revolutionary educational systems with new economic outputs that are valuable but do not depart from the idea of sustainable schools in general. It represents an expression given to schools designed to be environmentally sensitive and healthy for their occupants and educational systems based on experience, humanity, and attraction. Indeed, many architects have begun to explore and develop new architectural designs linked with the concepts of biophilic schools. Through the researchers' awareness of the negative circumstance experienced by school buildings in Iraq and by investing in the recommendations of an applied field research, it was reached to crystallize the research problem represented in the obstacles that schools suffer from, which calls for the search for developmental solutions for an efficient educational environment, and in order to reach this goal, by informing researchers about new global experiences in this field, the research presented its hypothesis in choosing the model of biophilic schools that exist in many countries in the world, because of what it can provide from successful and fruitful educational and urban components. The researchers reached many conclusions and recommendations aimed at applying the research hypothesis and achieving its goals.

Place, publisher, year, edition, pages
Hindawi Publishing Corporation, 2022
Keywords
Design, Case-studies, Design and construction, Educational institutions, Educational systems, Global trends, Hot climate, Ministry of Education, School design, School systems, Sustainable systems, Sustainable development
National Category
Architectural Engineering
Identifiers
urn:nbn:se:hj:diva-56374 (URN)10.1155/2022/7994999 (DOI)000793474000001 ()2-s2.0-85128323697 (Scopus ID)GOA;intsam;810731 (Local ID)GOA;intsam;810731 (Archive number)GOA;intsam;810731 (OAI)
Available from: 2022-05-04 Created: 2022-05-04 Last updated: 2022-05-30Bibliographically approved
Almusaed, A., Almssad, A. & Najar, K. (2022). An Innovative School Design Based on a Biophilic Approach Using the Appreciative Inquiry Model: Case Study Scandinavia. Advances in Civil Engineering / Hindawi, Article ID 8545787.
Open this publication in new window or tab >>An Innovative School Design Based on a Biophilic Approach Using the Appreciative Inquiry Model: Case Study Scandinavia
2022 (English)In: Advances in Civil Engineering / Hindawi, ISSN 1687-8086, E-ISSN 1687-8094, article id 8545787Article in journal (Refereed) Published
Abstract [en]

To understand the school’s role in society and its works, it became essential to reevaluate its functions and importance for society after the aggressive attack of the COVID-19 pandemic. Thus, a new educational space design represents a powerful and required tool for stimulating creativity and increasing concentration, motivation, and assimilation of knowledge for future generations. The article will use appreciative inquiry as a method that works with perspective ideas readings doted by high positive human sensitivity. It also represents a powerful tool for the students’ opinions about the teaching spaces and environments. To improve the performance of educational institutions and schools, considering the sustainability concepts and biophilic designs has become an urgent necessity within the Scandinavian countries and in the world in general. The scientific research and theoretical analysis within the biophilic theory have been conducted to see how the designer can integrate the nature components holistically in the educational environment based on spatial, visual, and ecological integration concepts. The study aims to develop knowledge about applying biophilia as a phenomenon in educational institutes of Scandinavia where the students among others are the main decision-maker. The article’s main finding is that students dream of free open teaching spaces integrated with nature, where the biophilic theory frameworks are suitable to form this sustainable model that enables educational institutions and schools to improve their performance within different stages of the study.

Place, publisher, year, edition, pages
Hindawi Publishing Corporation, 2022
Keywords
Appreciative inquiry approach; Environmental buildings; Biophilic schools; Educational process
National Category
Engineering and Technology
Identifiers
urn:nbn:se:hj:diva-57764 (URN)10.1155/2022/8545787 (DOI)000831949300001 ()2-s2.0-85135081233 (Scopus ID)GOA;;1678613 (Local ID)GOA;;1678613 (Archive number)GOA;;1678613 (OAI)
Available from: 2022-06-29 Created: 2022-06-29 Last updated: 2022-08-11Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-5814-2667

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