Novel Approaches to Plastic Pollution: Leveraging Machine Learning and Metaproteomics for Advanced Plastic Degradation
DOI:
https://doi.org/10.33102/mjosht.v11i1.451Keywords:
Plastic pollution, Machine learning, Metaproteomics, Plastic degradation, Environmental sustainabilityAbstract
This study addresses a pressing global issue—plastic waste—and explores technologies such as machine learning and metaproteomics as potential solutions. Current initiatives to reduce, recycle, and dispose of plastics in landfills are inadequate; plastic pollution is an issue that affects various ecosystems globally. This paper proposes a prospective solution that leverages machine learning algorithms and metaproteomics to improve the efficiency of plastic degradation. The prediction of environmental factors that facilitate bacteria-induced plastic degradation is performed using Random Forests and Convolutional Neural Networks (CNNs) models on extensive datasets. This enables the identification of specific microbes and enzymes capable of degrading plastics and other substances, including PETase, which acts on polyethylene terephthalate. Metaproteomics enhances this process by elucidating the proteins produced by microorganisms, thereby facilitating the identification of enzymes involved in plastic degradation. The amalgamation of these technologies facilitates the ongoing monitoring and regulation of degradation conditions, thereby improving scalability and performance metrics. Furthermore, the paper examines additional emerging technological innovations, including machine learning, nanotechnology, artificial intelligence, and robotics, that contribute to enhancing the degradation process and the comprehensive management of plastic waste. Collectively, these concepts have the potential to establish a circular economy where plastic waste is considered a valuable resource rather than waste. In conclusion, the integration of machine learning with metaproteomics presents a compelling narrative to tackle plastic pollution. These technologies improve the efficiency and ecological sustainability of plastic degradation processes, establishing a future in which humanity repurposes plastic waste as a valuable resource in industrial applications rather than discarding it.
Downloads
References
Sharifinia, Moslem, Zahra Afshari Bahmanbeigloo, Mehrzad Keshavarzifard, Mohammad Hossein Khanjani, and Brett P. Lyons. "Microplastic pollution as a grand challenge in marine research: a closer look at their adverse impacts on the immune and reproductive systems." Ecotoxicology and Environmental Safety 204 (2020): 111109. doi: 10.1016/J.ECOENV.2020.111109.
Auta, Helen Shnada, Chijioke U. Emenike, and Shahul Hamid Fauziah. "Distribution and importance of microplastics in the marine environment: a review of the sources, fate, effects, and potential solutions." Environment international 102 (2017): 165-176.
Haque, T. A., M. Tabassum, M. Jamilur Rahman, M. N. E. A. Siddique, M. Mostafa, M. Abdul Khalaque, Z. Abedine, and H. Hamidi. "Environmental analysis of arsenic in water, soil and Food materials from highly contaminated area of Alampur Village, Amjhupi union, Meherpur." Advanced Journal of Chemistry, Section A: Theoretical, Engineering and Applied Chemistry (2019): 181-91.
Chae, Yooeun, and Youn-Joo An. "Effects of micro-and nanoplastics on aquatic ecosystems: Current research trends and perspectives." Marine pollution bulletin 124, no. 2 (2017): 624-632. doi: 10.1016/J.MARPOLBUL.2017.01.070.
de Souza Machado, Anderson Abel, Werner Kloas, Christiane Zarfl, Stefan Hempel, and Matthias C. Rillig. "Microplastics as an emerging threat to terrestrial ecosystems." Global change biology 24, no. 4 (2018): 1405-1416. doi: 10.1111/GCB.14020.
Baho, Didier L., Mirco Bundschuh, and Martyn N. Futter. "Microplastics in terrestrial ecosystems: Moving beyond the state of the art to minimize the risk of ecological surprise." Global Change Biology 27, no. 17 (2021): 3969-3986. doi: 10.1111/GCB.15724.
Tosin, Maurizio, Miriam Weber, Michela Siotto, Christian Lott, and Francesco Degli Innocenti. "Laboratory test methods to determine the degradation of plastics in marine environmental conditions." Frontiers in microbiology 3 (2012): 225. doi: 10.3389/FMICB.2012.00225/PDF.
Gupta, Arjun, and Sangeeta Agrawal. "Machine learning-based enzyme engineering of PETase for improved efficiency in plastic degradation." J. Emerg. Investig 6 (2023): 1-10. doi: 10.59720/22-016.
Hemalatha, N., Akhil Wilson, and T. Akhil. "Prediction of Plastic Degrading Microbes." bioRxiv (2021): 2021-08. doi: 10.1101/2021.08.01.454681.
Naik, Richa Ramesh, Armi Tiihonen, Janak Thapa, Clio Batali, Zhe Liu, Shijing Sun, and Tonio Buonassisi. "Discovering equations that govern experimental materials stability under environmental stress using scientific machine learning." npj Computational Materials 8, no. 1 (2022): 72. doi: 10.1038/S41524-022-00751-5.
Nabi, Iqra, Kejian Li, Hanyun Cheng, Tao Wang, Yangyang Liu, Saira Ajmal, Yang Yang, Yiqing Feng, and Liwu Zhang. "Complete photocatalytic mineralization of microplastic on TiO2 nanoparticle film." Iscience 23, no. 7 (2020). doi: 10.1016/J.ISCI.2020.101326.
Maulana, Didit Ardi, and Muhammad Ibadurrohman. "Synthesis of nano-composite Ag/TiO2 for polyethylene microplastic degradation applications." In IOP conference series: materials science and engineering, vol. 1011, no. 1, p. 012054. IOP Publishing, 2021. doi: 10.1088/1757-899X/1011/1/012054.
Vogel, Kristina, Ren Wei, Lara Pfaff, Daniel Breite, Hassan Al-Fathi, Christian Ortmann, Irina Estrela-Lopis et al. "Enzymatic degradation of polyethylene terephthalate nanoplastics analyzed in real time by isothermal titration calorimetry." Science of the Total Environment 773 (2021): 145111. doi: 10.1016/J.SCITOTENV.2021.145111.
Tofa, Tajkia Syeed, Karthik Laxman Kunjali, Swaraj Paul, and Joydeep Dutta. "Visible light photocatalytic degradation of microplastic residues with zinc oxide nanorods." Environmental Chemistry Letters 17 (2019): 1341-1346. doi: 10.1007/S10311-019-00859-Z.
Yuwendi, Yuwendi, Muhammad Ibadurrohman, Setiadi Setiadi, and Slamet Slamet. "Photocatalytic degradation of polyethylene microplastics and disinfection of E. coli in water over Fe-and Ag-modified TiO2 nanotubes." Bulletin of Chemical Reaction Engineering & Catalysis 17, no. 2 (2022): 263-277. doi: 10.9767/BCREC.17.2.13400.263-277.
Ghatge, Sunil, Youri Yang, Yongseok Ko, Younggun Yoon, Jae-Hyung Ahn, Jeong Jun Kim, and Hor-Gil Hur. "Degradation of sulfonated polyethylene by a bio-photo-fenton approach using glucose oxidase immobilized on titanium dioxide." Journal of hazardous materials 423 (2022): 127067. doi: 10.1016/J.JHAZMAT.2021.127067.
Fadli, Muhamad Haris, Muhammad Ibadurrohman, and Slamet Slamet. "Microplastic pollutant degradation in water using modified TiO2 photocatalyst under UV-irradiation." In IOP conference series: materials science and engineering, vol. 1011, no. 1, p. 012055. IOP Publishing, 2021. doi: 10.1088/1757-899X/1011/1/012055.
Rahman, Naimur, and Sajib Kumar Das. "A Fusion of Three Custom-Tailored Deep Learning Architectures for Waste Classification." In 2022 4th International Conference on Sustainable Technologies for Industry 4.0 (STI), pp. 1-6. IEEE, 2022. doi: 10.1109/STI56238.2022.10103297.
Pandey, Ashish, Harshit Jain, Harshit Raj, and Prince Gupta. "Identification and classification of waste using cnn in waste management." In 2023 IEEE 8th International Conference for Convergence in Technology (I2CT), pp. 1-6. IEEE, 2023. doi: 10.1109/I2CT57861.2023.10126312.
Yang, Lei, Yong Xiang, Yinchuan Li, Wenyi Bao, Feng Ji, Jingtao Dong, Jingjing Chen, Mengjie Xu, and Rongsheng Lu. "Identification and classification of recyclable waste using laser-induced breakdown spectroscopy technology." AIP Advances 13, no. 7 (2023). doi: 10.1063/5.0149329/18056618/075024_1_5.0149329.PDF.
Gadre, V., S. Sashte, and A. Sarnaik. "Waste classification using resnet-152." Interantional journal of scientific research in engineering and management 7, no. 01 (2023). doi: 10.55041/IJSREM17421.
E. al. Nagaraj, “A Smart Management System For Garbage Classification Using Deep Learning,” International Journal on Recent and Innovation Trends in Computing and Communication, vol. 11, no. 10, pp. 1285–1289, Nov. 2023, doi: 10.17762/IJRITCC.V11I10.8671.
Nandhini, S., Sharma S. Mrinal, Naveen Balachandran, K. Suryanarayana, and DS Harish Ram. "Electronically assisted automatic waste segregation." In 2019 3rd International Conference on Trends in Electronics and Informatics (ICOEI), pp. 846-850. IEEE, 2019. doi: 10.1109/ICOEI.2019.8862666.
Sleem, Ahmed, and Ibrahim Elhenawy. "Intelligent waste management system for recycling and resource optimization." Full Length Article 1, no. 2 (2023): 102-02. doi: 10.54216/JISIOT.010205.
Sheng, Teoh Ji, Mohammad Shahidul Islam, Norbahiah Misran, Mohd Hafiz Baharuddin, Haslina Arshad, Md Rashedul Islam, Muhammad EH Chowdhury, Hatem Rmili, and Mohammad Tariqul Islam. "An internet of things based smart waste management system using LoRa and tensorflow deep learning model." IEEE Access 8 (2020): 148793-148811. doi: 10.1109/ACCESS.2020.3016255.
Jiménez Barriga, Nadia, and Belen Hernández Villalba. "ROBOTE: Interactive Educational Tool to Teach Basic Education Children to Classify and Collect Waste in their School Environment." In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, pp. 1-8. 2023. doi: 10.1145/3544549.3583847.
Zia, Huma, Muhammad Uzair Jawaid, Hafiza Sundus Fatima, Imtiaz Ul Hassan, Azmat Hussain, Sheryar Shahzad, and Muhammad Khurram. "Plastic waste management through the development of a low cost and light weight deep learning based reverse vending machine." Recycling 7, no. 5 (2022): 70. doi: 10.3390/RECYCLING7050070.
Al-Shareeda, Sarah, Hamza Hasan, and Ali Alkhayyat. "SmartyBin: A Tangible AI-Based Waste Classification Prototype." In 2023 International Symposium on Networks, Computers and Communications (ISNCC), pp. 1-6. IEEE, 2023. doi: 10.1109/ISNCC58260.2023.10323940.
Sami, Khan Nasik, Zian Md Afique Amin, and Raini Hassan. "Waste management using machine learning and deep learning algorithms." International Journal on Perceptive and Cognitive Computing 6, no. 2 (2020): 97-106. doi: 10.31436/IJPCC.V6I2.165.
Dong, Luofan, Huaqiang Du, Fangjie Mao, Ning Han, Xuejian Li, Guomo Zhou, Junlong Zheng, Meng Zhang, Luqi Xing, and Tengyan Liu. "Very high resolution remote sensing imagery classification using a fusion of random forest and deep learning technique—Subtropical area for example." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13 (2019): 113-128. doi: 10.1109/JSTARS.2019.2953234.
Wu, Jun, Pengfei Guo, Yiwei Cheng, Haiping Zhu, Xian-Bo Wang, and Xinyu Shao. "Ensemble generalized multiclass support-vector-machine-based health evaluation of complex degradation systems." IEEE/ASME Transactions on Mechatronics 25, no. 5 (2020): 2230-2240. doi: 10.1109/TMECH.2020.3009449.
West, Gregory, Tareq Assaf, and Uriel Martinez-Hernandez. "Towards Low-cost Plastic Recognition using Machine Learning and Multi-spectra Near-infrared Sensor." In 2023 IEEE SENSORS, pp. 1-4. IEEE, 2023. doi: 10.1109/SENSORS56945.2023.10325140.
J. Kim, H. S. Lee, J. Jang, Y. Ahn, S. J. Ki, and H.-G. Park, “Comparing the Performance of Machine Learning and Deep Learning Algorithms in Wastewater Treatment Process,” Journal of Korean Society of Environmental Engineers, vol. 45, no. 12, pp. 587–593, Dec. 2023, doi: 10.4491/KSEE.2023.45.12.587.
Karimi, Ahmad Maroof, Justin S. Fada, Mohammad Akram Hossain, Shuying Yang, Timothy J. Peshek, Jennifer L. Braid, and Roger H. French. "Automated pipeline for photovoltaic module electroluminescence image processing and degradation feature classification." IEEE Journal of Photovoltaics 9, no. 5 (2019): 1324-1335. doi: 10.1109/JPHOTOV.2019.2920732.
Xu, Yanwei, Weiwei Cai, Liuyang Wang, and Tancheng Xie. "Intelligent diagnosis of rolling bearing fault based on improved convolutional neural network and LightGBM." Shock and Vibration 2021, no. 1 (2021): 1205473. doi: 10.1155/2021/1205473.
Ren, Zi-Ang, Yi-Peng Chen, Jing-Yang Liu, Hua-Jian Ding, and Qin Wang. "Implementation of machine learning in quantum key distributions." IEEE Communications Letters 25, no. 3 (2020): 940-944. doi: 10.1109/LCOMM.2020.3040212.
Astray, Gonzalo, Anton Soria-Lopez, Enrique Barreiro, Juan Carlos Mejuto, and Antonio Cid-Samamed. "Machine learning to predict the adsorption capacity of microplastics." Nanomaterials 13, no. 6 (2023): 1061. doi: 10.3390/NANO13061061.
Shravani, Nandikante, and S. Vigneshwari. "Optimizing Waste Management through Intelligent Machine Learning Systems: A Comparative Study." In 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), pp. 1-6. IEEE, 2023. doi: 10.1109/ICCCNT56998.2023.10308278.
Gambarini, Victor, Olga Pantos, Joanne M. Kingsbury, Louise Weaver, Kim M. Handley, and Gavin Lear. "Phylogenetic distribution of plastic-degrading microorganisms." Msystems 6, no. 1 (2021): 10-1128. doi: 10.1128/MSYSTEMS.01112-20.
Hemalatha, N., Akhil Wilson, and T. Akhil. "Prediction of Plastic Degrading Microbes." bioRxiv (2021): 2021-08. doi: 10.1101/2021.08.01.454681.
Purohit, Jyotika, Anirudha Chattopadhyay, and Basavaraj Teli. "Metagenomic exploration of plastic degrading microbes for biotechnological application." Current Genomics 21, no. 4 (2020): 253-270. doi: 10.2174/1389202921999200525155711.
Edwards, Sabrina, Rosa León-Zayas, Riyaz Ditter, Helen Laster, Grace Sheehan, Oliver Anderson, Toby Beattie, and Jay L. Mellies. "Microbial consortia and mixed plastic waste: pangenomic analysis reveals potential for degradation of multiple plastic types via previously identified PET degrading bacteria." International journal of molecular sciences 23, no. 10 (2022): 5612. doi: 10.3390/IJMS23105612/S1.
Zrimec, Jan, Mariia Kokina, Sara Jonasson, Francisco Zorrilla, and Aleksej Zelezniak. "Plastic-degrading potential across the global microbiome correlates with recent pollution trends." MBio 12, no. 5 (2021): 10-1128. doi: 10.1128/MBIO.02155-21.
Son, Hyeoncheol Francis, Seongjoon Joo, Hogyun Seo, Hye-Young Sagong, Seul Hoo Lee, Hwaseok Hong, and Kyung-Jin Kim. "Structural bioinformatics-based protein engineering of thermo-stable PETase from Ideonella sakaiensis." Enzyme and Microbial Technology 141 (2020): 109656. doi: 10.1016/J.ENZMICTEC.2020.109656.
Wright, Robyn J., Rafael Bosch, Morgan GI Langille, Matthew I. Gibson, and Joseph A. Christie-Oleza. "A multi-OMIC characterisation of biodegradation and microbial community succession within the PET plastisphere." Microbiome 9 (2021): 1-22. doi: 10.1186/S40168-021-01054-5.
Carr, Clodagh M., David J. Clarke, and Alan DW Dobson. "Microbial polyethylene terephthalate hydrolases: current and future perspectives." Frontiers in Microbiology 11 (2020): 571265. doi: 10.3389/FMICB.2020.571265/PDF.
Heyer, Robert, Kay Schallert, Anja Büdel, Roman Zoun, Sebastian Dorl, Alexander Behne, Fabian Kohrs et al. "A robust and universal metaproteomics workflow for research studies and routine diagnostics within 24 h using phenol extraction, FASP digest, and the MetaProteomeAnalyzer." Frontiers in Microbiology 10 (2019): 1883. doi: 10.3389/FMICB.2019.01883/PDF.
doi: 10.3389/FMICB.2020.00442/PDF.
Ballerstedt, Hendrik, Till Tiso, Nick Wierckx, Ren Wei, Luc Averous, Uwe Bornscheuer, Kevin O’Connor et al. "MIXed plastics biodegradation and UPcycling using microbial communities: EU Horizon 2020 project MIX-UP started January 2020." Environmental Sciences Europe 33, no. 1 (2021): 99. doi: 10.1186/S12302-021-00536-5.
Ju, Feng, Yubo Wang, and Tong Zhang. "Bioreactor microbial ecosystems with differentiated methanogenic phenol biodegradation and competitive metabolic pathways unraveled with genome-resolved metagenomics." Biotechnology for biofuels 11 (2018): 1-16. doi: 10.1186/S13068-018-1136-6.
Skariyachan, Sinosh, Amulya A. Patil, Apoorva Shankar, Meghna Manjunath, Nikhil Bachappanavar, and S. Kiran. "Enhanced polymer degradation of polyethylene and polypropylene by novel thermophilic consortia of Brevibacillus sps. and Aneurinibacillus sp. screened from waste management landfills and sewage treatment plants." Polymer Degradation and Stability 149 (2018): 52-68. doi: 10.1016/J.POLYMDEGRADSTAB.2018.01.018.
Zampolli, Jessica, Alessandro Orro, Daniele Vezzini, and Patrizia Di Gennaro. "Genome-based exploration of Rhodococcus species for plastic-degrading genetic determinants using bioinformatic analysis." Microorganisms 10, no. 9 (2022): 1846. doi: 10.3390/MICROORGANISMS10091846.
Zhu, Baotong, Dong Wang, and Na Wei. "Enzyme discovery and engineering for sustainable plastic recycling." Trends in biotechnology 40, no. 1 (2022): 22-37. doi: 10.1016/J.TIBTECH.2021.02.008.
Nyika, Joan Mwihaki. "The Plastic Waste Menace and Approaches to Its Management Through Biodegradation." In Handbook of Research on Waste Diversion and Minimization Technologies for the Industrial Sector, pp. 218-235. IGI Global, 2021. doi: 10.4018/978-1-7998-4921-6.CH010.
Datta, Saptashwa, K. Narayanan Rajnish, Melvin S. Samuel, Arivalagan Pugazlendhi, and Ethiraj Selvarajan. "Metagenomic applications in microbial diversity, bioremediation, pollution monitoring, enzyme and drug discovery. A review." Environmental Chemistry Letters 18 (2020): 1229-1241. doi: 10.1007/S10311-020-01010-Z.
Liebal, Ulf W., An NT Phan, Malvika Sudhakar, Karthik Raman, and Lars M. Blank. "Machine learning applications for mass spectrometry-based metabolomics." Metabolites 10, no. 6 (2020): 243. doi: 10.3390/METABO10060243.
Reel, Parminder S., Smarti Reel, Ewan Pearson, Emanuele Trucco, and Emily Jefferson. "Using machine learning approaches for multi-omics data analysis: A review." Biotechnology advances 49 (2021): 107739. doi: 10.1016/J.BIOTECHADV.2021.107739.
Soueidan, Hayssam, and Macha Nikolski. "Machine learning for metagenomics: methods and tools." arXiv preprint arXiv:1510.06621 (2015). doi: 10.1515/METGEN-2016-0001.
Nikolaivits, Efstratios, Brana Pantelic, Muhammad Azeem, George Taxeidis, Ramesh Babu, Evangelos Topakas, Margaret Brennan Fournet, and Jasmina Nikodinovic-Runic. "Progressing plastics circularity: A review of mechano-biocatalytic approaches for waste plastic (re) valorization." Frontiers in Bioengineering and Biotechnology 9 (2021): 696040. doi: 10.3389/FBIOE.2021.696040/PDF.
Tabassum, Mujahid, H. A. D. I. NABIPOUR Nabipour, Abdul Kashem, Saad Bin, Manas Kumar Haldar, Ateeb Hassan, Mobin Siddique, and M. D. Bazlul. "A Feasibility Study of Renewable Energy Generation from Palm Oil Waste in Malaysia." Saad Bin and Haldar, Manas Kumar and Hassan, Ateeb and Mobin Siddique, MD Bazlul, A Feasibility Study of Renewable Energy Generation from Palm Oil Waste in Malaysia. doi: 10.2139/SSRN.4263589.
Tamin, Owen, Ervin Gubin Moung, Jamal Ahmad Dargham, Farashazillah Yahya, Sigeru Omatu, and Lorita Angeline. "Machine learning for plastic waste detection: State-of-the-art, challenges, and solutions." In 2022 International Conference on Communications, Information, Electronic and Energy Systems (CIEES), pp. 1-6. IEEE, 2022. doi: 10.1109/CIEES55704.2022.9990703.
Jaiswal, Shweta, Babita Sharma, and Pratyoosh Shukla. "Integrated approaches in microbial degradation of plastics." Environmental Technology & Innovation 17 (2020): 100567. doi: 10.1016/J.ETI.2019.100567.
Lu, Hongyuan, Daniel J. Diaz, Natalie J. Czarnecki, Congzhi Zhu, Wantae Kim, Raghav Shroff, Daniel J. Acosta et al. "Deep learning redesign of PETase for practical PET degrading applications." Biorxiv (2021): 2021-10. doi: 10.1101/2021.10.10.463845.
Kumar, Saurav, Drishti Yadav, Himanshu Gupta, Om Prakash Verma, Irshad Ahmad Ansari, and Chang Wook Ahn. "A novel yolov3 algorithm-based deep learning approach for waste segregation: Towards smart waste management." Electronics 10, no. 1 (2020): 14. doi: 10.3390/ELECTRONICS10010014.
Manikandan, V., S. Arjun, Athira Visweswaran, and N. Sruthi. "Automated Waste Segregation using Machine Learning." AIJR Proceedings (2023): 264-268. doi: 10.21467/PROCEEDINGS.160.33.
Nguyen, Thanh Nha, and Duc Thien Tran. "Designing of A Plastic Garbage Robot With Vision-Based Deep Learning Applications." In 2023 International Conference on System Science and Engineering (ICSSE), pp. 306-311. IEEE, 2023. doi: 10.1109/ICSSE58758.2023.10227251.
Prabawati, Anindita, Evi Frimawaty, and Joko T. Haryanto. "Strengthening stakeholder partnership in plastics waste management based on circular economy paradigm." Sustainability 15, no. 5 (2023): 4278. doi: 10.3390/SU15054278.
Polushkina, Tatyana Mikhailovna, Yulia Alekseevna Akimova, Tatyana Petrovna Koroleva, Svetlana Andreevna Kochetkova, and Lyubov Ivanovna Zinina. "Development of organic agriculture in the European Union member states: The role of public-private partnership." Journal of Environmental Management and Tourism 11, no. 5 (2020): 1081-1094. doi: 10.14505//JEMT.V11.5(45).06.
Qi, Qingsheng. "Plastics biodegradation and recycling-the introduction of China-Europe cooperation project" Synthetic microorganism communities for plastic degradation and transformation"." Sheng wu Gong Cheng xue bao= Chinese Journal of Biotechnology 37, no. 10 (2021): 3411-3413. doi: 10.13345/J.CJB.210400.
Sharma, Hemlata, and Deepesh K. Neelam. "Understanding challenges associated with plastic and bacterial approach toward plastic degradation." Journal of Basic Microbiology 63, no. 3-4 (2023): 292-307. doi: 10.1002/JOBM.202200428.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Arooj Fatima Tul Zahra, Mujahid Tabassum, Sundresan Perumal
This work is licensed under a Creative Commons Attribution 4.0 International License.
The copyright of this article will be vested to author(s) and granted the journal right of first publication with the work simultaneously licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license, unless otherwise stated.
