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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: H. Byju; K. A. Rubeena; C. T. Shifa; T. R. Athira; +20 Authors

    Habitat fragmentation and degradation in natural wetlands has resulted in declines in the populations of shorebirds in the Indian subcontinent. Shorebirds rely on these wetlands as wintering or stop-over sites along the southern extent of the Central Asian Flyway. Shorebirds are known to utilize agroecosystems as alternate foraging habitats. The suitability of agroecosystems as foraging areas for overwintering migratory shorebirds has not been well studied in the Indian subcontinent. We conducted a comprehensive assessment of published literature and compiled field observations to investigate the importance of inland and coastal agroecosystems for shorebirds in India. We assessed the shorebird populations at natural wetlands: mudflats and mangroves of Kadalundi Vallikkunnu Community Reserve (KVCR) and Puthuvypu sand beach, as well as adjacent agroecosystems on the west coast of India, including Sanketham Wetlands, Manthalakkadavu, Vazhakkad, Elamaram, Kodinhi, and Kooriyad. On the east coast, we assessed the natural wetland habitats of Valinokkam, Point Calimere, and Pichavaram and evaluated inland agroecosystems in regions, such as Jammu and Kashmir, Punjab, Rajasthan, Gujarat, Uttar Pradesh, Tamil Nadu, and Kerala. Fifty-three shorebird species utilize diverse agroecosystems from various parts of India. While studies on the use of agroecosystems by shorebirds are limited on the east coast, evidence suggests that major wintering sites are adjacent to paddy fields, fostering substantial shorebird diversity. In Pichavaram, Point Calimere, and Gulf of Mannar regions, 22 shorebird species utilize agroecosystems, including the notable near-threatened Eurasian Curlew. Seventeen of these species are winter arrivals, highlighting the crucial role agroecosystems play as stopover areas. On the west coast, 19 shorebird species appear to utilize agroecosystems in Kooriyad, Manthalakkadavu, Vazhakkad, Sanketham Wetlands, Elamaram, and Kodinhi. Few species use agricultural fields in the north (Jammu and Kashmir). Paddy fields, that are flooded as part of the cropping cycle, support diverse prey species, such as macroinvertebrates, amphibians, and small fish, that could attract and support migratory shorebirds. Agricultural practices like fallowing, flooding, and ploughing could further increase the abundance and accessibility of prey for shorebirds, drawing them in greater numbers. It is crucial to recognize that unsustainable and unethical agricultural methods could detrimentally affect shorebird numbers. The accumulation of pesticide residues and the contamination from heavy metals could also threaten shorebirds. As a result, there is an urgent need for detailed research to better evaluate the importance of agroecosystems in supporting resident or migratory shorebirds. Systematic studies that explain the population dynamics, habitat selection trends, habitat utilization, and the over-summering behavior of the migratory birds at agroecosystems are needed. Implementing sustainable conservation strategies and adopting environmentally friendly agricultural practices are essential to support the rich biodiversity of the region.

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    Article . 2023 . Peer-reviewed
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    Article . 2023
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Diversityarrow_drop_down
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      Diversity
      Article . 2023 . Peer-reviewed
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      Article . 2023
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Zaiga Jansone; Zigmārs Rendenieks; Andris Lapāns; Ilmar Tamm; +9 Authors

    Accurate and robust methods are needed to monitor crop growth and predict grain yield and quality in breeding programs, particularly under variable agrometeorological conditions. Field experiments were conducted during two successive cropping seasons (2021, 2022) at four trial locations (Estonia, Latvia, Lithuania, Norway). The focus was on assessment of the grain yield (GY), grain protein content (GPC), and UAV-derived NDVI measured at different plant growth stages. The performance and stability of 16 selected spring wheat genotypes were assessed under two N application rates (75, 150 kg N ha−1) and across different agrometeorological conditions. Quantitative relationships between agronomic traits and UAV-derived variables were determined. None of the traits exhibited a significant (p < 0.05) genotype-by-nitrogen interaction. High-yielding and high-protein genotypes were detected with a high WAASB stability, specifically under high and low N rates. This study highlights the significant effect of an NDVI analysis at GS55 and GS75 as key linear predictors, especially concerning spring wheat GYs. However, the effectiveness of these indices depends on the specific growing conditions in different, geospatially distant locations, limiting their universal utility.

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    Agronomy
    Article . 2023
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    Agronomy
    Article . 2023 . Peer-reviewed
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      Agronomy
      Article . 2023
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      Agronomy
      Article . 2023 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Tareefa S. Alsumaiti; Khalid A. Hussein; Dawit T. Ghebreyesus; Pakorn Petchprayoon; +2 Authors

    The recent flooding events in the UAE have emphasized the need for a reassessment of flood frequencies to mitigate risks. The exponential urbanization and climatic changes in the UAE require a reform for developing and updating intensity–duration–frequency (IDF) curves. This study introduces a methodology to develop and update IDF curves for the UAE at a high spatial resolution using CHIRPS (Climate Hazards Group InfraRed Precipitation with Station) data. A bias correction was applied to the CHIRPS data, resulting in an improved capture of extreme events across the country. The Gumbel distribution was the most suitable theoretical distribution for the UAE, exhibiting a strong fit to the observed data. The study also revealed that the CHIRPS-derived IDF curves matched the shape of IDF curves generated using rain gauges. Due to orographic rainfall in the northeastern region, the IDF intensities were at their highest there, while the aridity of inland regions resulted in the lowest intensities. These findings enhance our understanding of rainfall patterns in the UAE and support effective water resource management and infrastructure planning. This study demonstrates the potential of the CHIRPS dataset for IDF curve development, emphasizes the importance of performing bias corrections, and recommends tailoring adjustments to the intended application.

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    Remote Sensing
    Article . 2023
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    Remote Sensing
    Article . 2023 . Peer-reviewed
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Remote Sensingarrow_drop_down
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      Article . 2023
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      Article . 2023 . Peer-reviewed
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Kai Li; Billy Pik Lik Lau; Xin Yuan; Wei Ni; +2 Authors

    In recent years, ubiquitous semantic Metaverse has been studied to revolutionize immersive cyber-virtual experiences for augmented reality (AR) and virtual reality (VR) users, which leverages advanced semantic understanding and representation to enable seamless, context-aware interactions within mixed-reality environments. This survey focuses on the intelligence and spatio-temporal characteristics of four fundamental system components in ubiquitous semantic Metaverse, i.e., artificial intelligence (AI), spatio-temporal data representation (STDR), semantic Internet of Things (SIoT), and semantic-enhanced digital twin (SDT). We thoroughly survey the representative techniques of the four fundamental system components that enable intelligent, personalized, and context-aware interactions with typical use cases of the ubiquitous semantic Metaverse, such as remote education, work and collaboration, entertainment and socialization, healthcare, and e-commerce marketing. Furthermore, we outline the opportunities for constructing the future ubiquitous semantic Metaverse, including scalability and interoperability, privacy and security, performance measurement and standardization, as well as ethical considerations and responsible AI. Addressing those challenges is important for creating a robust, secure, and ethically sound system environment that offers engaging immersive experiences for the users and AR/VR applications. This work was supported by the CISTER Research Unit (UIDP/UIDB/04234/2020), project ADANET (PTDC/EEICOM/3362/2021) and project IBEX (PTDC/CCI-COM/4280/2021), financed by National Funds through FCT/MCTES (Portuguese Foundation for Science and Technology).

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    arXiv.org e-Print Archive
    Other literature type . Preprint . 2023
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    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    https://doi.org/10.1109/jiot.2...
    Article . 2023 . Peer-reviewed
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    https://doi.org/10.48550/arxiv...
    Article . 2023
    License: arXiv Non-Exclusive Distribution
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ arXiv.org e-Print Ar...arrow_drop_down
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      arXiv.org e-Print Archive
      Other literature type . Preprint . 2023
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      https://doi.org/10.1109/jiot.2...
      Article . 2023 . Peer-reviewed
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      https://doi.org/10.48550/arxiv...
      Article . 2023
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    Authors: Alaa Awad Abdellatif; Naram Mhaisen; Amr Mohamed; Aiman Erbad; +1 Authors

    The rise of chronic disease patients and the pandemic pose immediate threats to healthcare expenditure and mortality rates. This calls for transforming healthcare systems away from one-on-one patient treatment into intelligent health systems, leveraging the recent advances of Internet of Things and smart sensors. Meanwhile, reinforcement learning (RL) has witnessed an intrinsic breakthrough in solving a variety of complex problems for distinct applications and services. Thus, this article presents a comprehensive survey of the recent models and techniques of RL that have been developed/used for supporting Intelligent-healthcare (I-health) systems. It can guide the readers to deeply understand the state-of-the-art regarding the use of RL in the context of I-health. Specifically, we first present an overview of the I-health systems' challenges, architecture, and how RL can benefit these systems. We then review the background and mathematical modeling of different RL, deep RL (DRL), and multiagent RL models. We highlight important guidelines on how to select the appropriate RL model for a given problem, and provide quantitative comparisons, showing the results of deploying key RL models in two scenarios that can be followed in monitoring applications. After that, we conduct an in-depth literature review on RL's applications in I-health systems, covering edge intelligence, smart core network, and dynamic treatment regimes. Finally, we highlight emerging challenges and future research directions to enhance RL's success in I-health systems, which opens the door for exploring some interesting and unsolved problems. Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Networked Systems

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    https://doi.org/10.1109/jiot.2...
    Article . 2023 . Peer-reviewed
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      https://doi.org/10.1109/jiot.2...
      Article . 2023 . Peer-reviewed
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    Authors: Aamir Sajjad Nasir; Muhammad Usman; Muhammad Ali Ijaz Malik; Asad Naeem Shah; +6 Authors

    Mineral oil resources are depleting rapidly, and the slower conventional oil biodegradation process results in environmental pollution. To resolve this issue, cupric oxide (CuO) nanoparticles (1% wt) were introduced into a base oil to improve the lubricating capability of castor oil. In addition, 1% wt. sodium dodecyl sulfate was also blended with the base oil in order to attain the maximum dispersion stability of CuO nanoparticles in the castor oil. Afterward, thermophysical property, atomic absorption spectroscopy, and Fourier transform infrared radiation (FTIR) testing of the lubricant oil sample were performed before and after 100 h of engine operations at 75% throttle and 2200 rpm for each lubricant sample in order to check the capability of the novel oil with mineral oil. Compared with the natural mineral oil, the behavior of the CuO-based lubricant has essentially the same physical features, as measured according to ASTM standard methods. The physicochemical properties like (KV)40 °C, (KV)100 °C, FP, ash, and TBN decrease more in the case of the synthetic oil by 1.15, 1.11, 0.46, 1.1, and 1.2% than in the conventional oil, respectively. FTIR testing shows that the maximum peaks lie in the region of 500 to 1750 cm−1, which shows the presence of C=O, C-N, and C-Br to a maximum extent in the lubricant oil sample. AAS testing shows that the synthetic oil has 21.64, 3.23, 21.44, and 1.23% higher chromium, iron, aluminum, and zinc content. However, the copper and calcium content in the synthetic oil is 14.72 and 17.68%, respectively. It can be concluded that novel bio-lubricants can be utilized as an alternative to those applications that are powered by naturally produced mineral oil after adding suitable additives that further enhance their performance.

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    Authors: Yazeed Yasin Ghadi; Tehseen Mazhar; Syed Faisal Abbas Shah; Inayatul Haq; +3 Authors

    In the past few years, privacy concerns have grown, making the financial models of businesses more vulnerable to attack. In many cases, it is hard to emphasize the importance of monitoring things in real-time with data from Internet of Things (IoT) devices. The people who make the IoT devices and those who use them face big problems when they try to use Artificial Intelligence (AI) techniques in real-world applications, where data must be collected and processed at a central location. Federated learning (FL) has made a decentralized, cooperative AI system that can be used by many IoT apps that use AI. It is possible because it can train AI on IoT devices that are spread out and do not need to share data. FL allows local models to be trained on local data and share their knowledge to improve a global model. Also, shared learning allows models from all over the world to be trained using data from all over the world. This article looks at the IoT in all of its forms, including “smart” businesses, “smart” cities, “smart” transportation, and “smart” healthcare. This study looks at the safety problems that the federated learning with IoT (FL-IoT) area has brought to market. This research is needed to explore because federated learning is a new technique, and a small amount of work is done on challenges faced during integration with IoT. This research also helps in the real world in such applications where encrypted data must be sent from one place to another. Researchers and graduate students are the audience of our article.

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    Authors: Affia, Abasi-amefon Obot;

    Võrgutoega seadmete ja nende haavatavuste kasvuga on hakatud rohkem tähelepanu pöörama asjade interneti (IoT) turvariskide haldamisele (SRM). Võimalik ründepind laieneb asjade Interneti ökosüsteemi kasvades, tuues esile vajadust tugevate turvameetmete järele arenevate ohtude vastu. Olemasolevad uuringud toovad siiski välja lünki asjade Interneti arhitektuuri täielikul integreerimisel turvariskide haldamisse. Rakendamise praktilised väljakutsed tõstavad niigi keerukate asjade interneti süsteemide keerukust ja teevad turvariskide haldamise ülesannet veelgi keerulisemaks. Seega õõnestab teooria ja praktika vaheline ebavõrdsus turvaraamistike eduka rakendamise tõenäosust reaalsetes asjade interneti süsteemides, muutes need vastuvõtlikuks pidevalt arenevale ohumaastikule. Nende väljakutsete lahendamiseks tutvustame IoT-arhitektuuril põhinevat turvariskide haldamise (IoTA-SRM) raamistikku, mis pakub terviklikku ja integreeritavat lähenemist tuvariskide haldamisele asjade interneti süsteemides. Integreerides IoT arhitektuuri turvariskide haldamisse, saavad sidusrühmad tagada oma IoT süsteemi komponentide ja interaktsioonide igakülgse katvuse. Raamistikku hinnati autonoomsete sõidukisüsteemide ekspertide poolt läbiviidud juhtumiuuringute abil, et teha kindlaks selle praktilisus, kohanemisvõime ja eelised. Kuigi antud juhtumite analüüsis nähakse raamistiku praktilisust, võib selle teoreetiline rikkus jääda praktikutele rakendamise ajal abstraktseks. Arvestades asjade interneti süsteemide keerukust ja ohtude dünaamilist olemust, ei piisa üksi traditsioonilistest õpetamisviisidest, et hõlbustada raamistiku üleminekut teoreetiliselt arusaamiselt praktilisele rakendusele, mistõttu on vaja tavapärasest õpetamisviisidest edasi ulatuvaid haridusmeetodeid. Seega töötati välja sekkumispõhine häkatoni lähenemine. See lähenemisviis, mida täiustatakse kohandatud sekkumistega, soodustab kogemuslikku õppimist. Antud sekkumised on hoolikalt välja töötatud, kohandatavad erinevate häkatoni kontekstide ja turvalisuse aspektide õpetamise sisuga ning täiustatud tegevusuuringute tsüklite kaudu, et võimaldada osalejatel navigeerida ja rakendada IoTA-SRM raamistikku. Meie integreeritud raamistik ja häkatoni lähenemisviis täitsid kahte rolli: haridusmudel, mis on suunatud turvariskide haldamisele asjade interneti süsteemides, ja IoTA-SRM-i raamistiku hindamismehhanism häkatoni iteratsioonide kaudu, võimaldades selliselt selle iteratiivset täiustamist. See doktoritöö aitab kaasa IoT SRMi teoreetilisele mõistmisele ja IoT turvariskide juhtimise praktilistele lähenemisviisidele. Lisaks pakub see meetodit tulevaste spetsialistide koolitamiseks selles kiiresti arenevas valdkonnas. Siin esitatud leiud ja metoodikad loovad aluse tulevastele püüdlustele IoT SRM-i rakendamisel ja õpetamisel, näitlikustades sünergilist seost teoreetiliste turvakontseptsioonide ja nende praktilise rakendamise vahel. With the rise of network-capable devices and their vulnerabilities, attention has focused on security risk management (SRM) in the internet of things (IoT). The potential attack surface expands as the IoT ecosystem grows, underscoring the need for robust security measures against evolving threats. Yet, existing research reveals gaps in fully integrating the IoT architecture into SRM activities. Practical implementation challenges further complicate the intricate nature of IoT systems and the daunting task of SRM. Consequently, the disparity between theory and practice undermines the likelihood of successfully implementing security frameworks in real-world IoT systems, leaving them susceptible to an ever-evolving threat landscape. To address these challenges, we introduce the IoT Architecture-based Security Risk Management (IoTA-SRM) framework, offering a comprehensive and integrative approach to SRM in IoT systems. By integrating the IoT architecture into security risk management, stakeholders can ensure comprehensive coverage of their IoT system components and interactions. The framework was evaluated involving expert-validated case studies in autonomous vehicle systems to ascertain its practicality, adaptability, and benefits. However, though the practicality of the framework is seen in this case analysis, its theoretical richness may remain abstract for practitioners during application. Given the intricacy of IoT systems and the dynamic nature of threats, traditional instructional approaches alone prove insufficient to facilitate the framework's transition from theoretical understanding to practical application, necessitating educational methods that transcend conventional instruction. Thus, an intervention-based hackathon approach was developed. Enhanced with tailored interventions, this approach fosters an experiential learning approach. These interventions are carefully crafted, adaptable to diverse hackathon contexts and security learning content, and refined through action research cycles to enable participants to navigate and apply the IoTA-SRM framework. Our integrated framework and hackathon approach served dual roles: an educational model targeting SRM in IoT systems and an evaluation mechanism for the IoTA-SRM framework through hackathon iterations, thus allowing for its iterative refinement. This thesis contributes to the theoretical understanding of IoT SRM and practical approaches for IoT security risk management. It further offers a method for educating future professionals in this rapidly evolving field. The findings and methodologies presented herein provide a basis for future endeavours in applying and teaching IoT SRM, exemplifying the synergistic relationship between theoretical security concepts and their practical application. https://www.ester.ee/record=b5645350

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    Authors: Aziz Nurbekov; Muhammadjon Kosimov; Makhmud Shaumarov; Botir Khaitov; +3 Authors

    Soil productivity and crop yield were examined in response to legume-based short crop rotation under conventional (CT) and no-till (NT) tillage practices in saline meadow-alluvial soils of the arid region in Bukhara, Uzbekistan. Compared with the CT treatment, crop yield was consistently higher under NT, i.e., winter wheat 9.63%, millet 9.9%, chickpea 3.8%, and maize 10.7% at the first experiment cycle during 2019–2021. A further crop productivity increase was observed at the second experiment cycle during 2021–2023 under NT when compared to CT, i.e., winter wheat 17.7%, millet 31.2%, chickpea 19.6%, and maize 19.1%. An increase in total phyto residue by 20.9% and root residue by 25% under NT compared to CT contributed to the improvement in soil structure and played a vital role in the sustained improvement of crop yields. In turn, the increased residue retention under NT facilitated soil porosity, structural stability, and water retention, thereby improving soil quality and organic matter content. Soil salinity more significantly decreased under NT than in CT, reducing salinity buildup by 18.9% at the 0–25 cm and 32.9% at the 75–100 cm soil profiles compared to CT. The total forms N and P were significantly increased under NT when compared to CT, while the efficiency of the applied crop rotation was essential. This study showed the essential role of the NT method with legume-based intensive cropping in the maintenance of soil health and crop yield, thereby touching on recent advances in agro-biotechnology and the sustainable land management of drylands.

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    Authors: Enock Siankwilimba; Jacqueline Hiddlestone-Mumford; Md Enamul Hoque; Bernard Mudenda Hang'ombe; +10 Authors

    AbstractIn the fourth industrial revolution, achieving sustainable agricultural development while feeding a growing world population and maintaining a balanced interrelationship between the economy, society, and the environment has been a significant challenge. However, COVID-19 disrupted agricultural extension and advisory systems, affecting all market participants. The complexity of the pandemic has impacted the private sector, public sector, extension staff, donor funding, education, and research systems, subsequently affecting human nutrition. This paper aims to expertly review COVID-19’s effects on the sustainability of gender-specific agricultural extension service systems. Demand and supply market stakeholders in the extension system are thematically discussed. The findings reveal various consequences of COVID-19 for market actors on both the demand and supply sides of the extension system. Private-sector players often support expansion directly or indirectly, with multi-sectorial support and funding strategies existing for sustainability. In many developing nations, the comprehensive extension system was disrupted by COVID-19, impacting household incomes and nutrition. The pandemic accelerated the adoption of digital technologies in many developing nations, transitioning from a centralized to a decentralized and pluralistic extension model. Multi-sector coordination and execution, especially from health and other sectors, are crucial in managing complex crises that disrupt the market system.

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      Cogent Food &amp; Agriculture
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      Cogent Food &amp; Agriculture
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: H. Byju; K. A. Rubeena; C. T. Shifa; T. R. Athira; +20 Authors

    Habitat fragmentation and degradation in natural wetlands has resulted in declines in the populations of shorebirds in the Indian subcontinent. Shorebirds rely on these wetlands as wintering or stop-over sites along the southern extent of the Central Asian Flyway. Shorebirds are known to utilize agroecosystems as alternate foraging habitats. The suitability of agroecosystems as foraging areas for overwintering migratory shorebirds has not been well studied in the Indian subcontinent. We conducted a comprehensive assessment of published literature and compiled field observations to investigate the importance of inland and coastal agroecosystems for shorebirds in India. We assessed the shorebird populations at natural wetlands: mudflats and mangroves of Kadalundi Vallikkunnu Community Reserve (KVCR) and Puthuvypu sand beach, as well as adjacent agroecosystems on the west coast of India, including Sanketham Wetlands, Manthalakkadavu, Vazhakkad, Elamaram, Kodinhi, and Kooriyad. On the east coast, we assessed the natural wetland habitats of Valinokkam, Point Calimere, and Pichavaram and evaluated inland agroecosystems in regions, such as Jammu and Kashmir, Punjab, Rajasthan, Gujarat, Uttar Pradesh, Tamil Nadu, and Kerala. Fifty-three shorebird species utilize diverse agroecosystems from various parts of India. While studies on the use of agroecosystems by shorebirds are limited on the east coast, evidence suggests that major wintering sites are adjacent to paddy fields, fostering substantial shorebird diversity. In Pichavaram, Point Calimere, and Gulf of Mannar regions, 22 shorebird species utilize agroecosystems, including the notable near-threatened Eurasian Curlew. Seventeen of these species are winter arrivals, highlighting the crucial role agroecosystems play as stopover areas. On the west coast, 19 shorebird species appear to utilize agroecosystems in Kooriyad, Manthalakkadavu, Vazhakkad, Sanketham Wetlands, Elamaram, and Kodinhi. Few species use agricultural fields in the north (Jammu and Kashmir). Paddy fields, that are flooded as part of the cropping cycle, support diverse prey species, such as macroinvertebrates, amphibians, and small fish, that could attract and support migratory shorebirds. Agricultural practices like fallowing, flooding, and ploughing could further increase the abundance and accessibility of prey for shorebirds, drawing them in greater numbers. It is crucial to recognize that unsustainable and unethical agricultural methods could detrimentally affect shorebird numbers. The accumulation of pesticide residues and the contamination from heavy metals could also threaten shorebirds. As a result, there is an urgent need for detailed research to better evaluate the importance of agroecosystems in supporting resident or migratory shorebirds. Systematic studies that explain the population dynamics, habitat selection trends, habitat utilization, and the over-summering behavior of the migratory birds at agroecosystems are needed. Implementing sustainable conservation strategies and adopting environmentally friendly agricultural practices are essential to support the rich biodiversity of the region.

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    Authors: Zaiga Jansone; Zigmārs Rendenieks; Andris Lapāns; Ilmar Tamm; +9 Authors

    Accurate and robust methods are needed to monitor crop growth and predict grain yield and quality in breeding programs, particularly under variable agrometeorological conditions. Field experiments were conducted during two successive cropping seasons (2021, 2022) at four trial locations (Estonia, Latvia, Lithuania, Norway). The focus was on assessment of the grain yield (GY), grain protein content (GPC), and UAV-derived NDVI measured at different plant growth stages. The performance and stability of 16 selected spring wheat genotypes were assessed under two N application rates (75, 150 kg N ha−1) and across different agrometeorological conditions. Quantitative relationships between agronomic traits and UAV-derived variables were determined. None of the traits exhibited a significant (p < 0.05) genotype-by-nitrogen interaction. High-yielding and high-protein genotypes were detected with a high WAASB stability, specifically under high and low N rates. This study highlights the significant effect of an NDVI analysis at GS55 and GS75 as key linear predictors, especially concerning spring wheat GYs. However, the effectiveness of these indices depends on the specific growing conditions in different, geospatially distant locations, limiting their universal utility.

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    Agronomy
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    Authors: Tareefa S. Alsumaiti; Khalid A. Hussein; Dawit T. Ghebreyesus; Pakorn Petchprayoon; +2 Authors

    The recent flooding events in the UAE have emphasized the need for a reassessment of flood frequencies to mitigate risks. The exponential urbanization and climatic changes in the UAE require a reform for developing and updating intensity–duration–frequency (IDF) curves. This study introduces a methodology to develop and update IDF curves for the UAE at a high spatial resolution using CHIRPS (Climate Hazards Group InfraRed Precipitation with Station) data. A bias correction was applied to the CHIRPS data, resulting in an improved capture of extreme events across the country. The Gumbel distribution was the most suitable theoretical distribution for the UAE, exhibiting a strong fit to the observed data. The study also revealed that the CHIRPS-derived IDF curves matched the shape of IDF curves generated using rain gauges. Due to orographic rainfall in the northeastern region, the IDF intensities were at their highest there, while the aridity of inland regions resulted in the lowest intensities. These findings enhance our understanding of rainfall patterns in the UAE and support effective water resource management and infrastructure planning. This study demonstrates the potential of the CHIRPS dataset for IDF curve development, emphasizes the importance of performing bias corrections, and recommends tailoring adjustments to the intended application.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Kai Li; Billy Pik Lik Lau; Xin Yuan; Wei Ni; +2 Authors

    In recent years, ubiquitous semantic Metaverse has been studied to revolutionize immersive cyber-virtual experiences for augmented reality (AR) and virtual reality (VR) users, which leverages advanced semantic understanding and representation to enable seamless, context-aware interactions within mixed-reality environments. This survey focuses on the intelligence and spatio-temporal characteristics of four fundamental system components in ubiquitous semantic Metaverse, i.e., artificial intelligence (AI), spatio-temporal data representation (STDR), semantic Internet of Things (SIoT), and semantic-enhanced digital twin (SDT). We thoroughly survey the representative techniques of the four fundamental system components that enable intelligent, personalized, and context-aware interactions with typical use cases of the ubiquitous semantic Metaverse, such as remote education, work and collaboration, entertainment and socialization, healthcare, and e-commerce marketing. Furthermore, we outline the opportunities for constructing the future ubiquitous semantic Metaverse, including scalability and interoperability, privacy and security, performance measurement and standardization, as well as ethical considerations and responsible AI. Addressing those challenges is important for creating a robust, secure, and ethically sound system environment that offers engaging immersive experiences for the users and AR/VR applications. This work was supported by the CISTER Research Unit (UIDP/UIDB/04234/2020), project ADANET (PTDC/EEICOM/3362/2021) and project IBEX (PTDC/CCI-COM/4280/2021), financed by National Funds through FCT/MCTES (Portuguese Foundation for Science and Technology).

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    Other literature type . Preprint . 2023
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    https://doi.org/10.1109/jiot.2...
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      https://doi.org/10.1109/jiot.2...
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    Authors: Alaa Awad Abdellatif; Naram Mhaisen; Amr Mohamed; Aiman Erbad; +1 Authors

    The rise of chronic disease patients and the pandemic pose immediate threats to healthcare expenditure and mortality rates. This calls for transforming healthcare systems away from one-on-one patient treatment into intelligent health systems, leveraging the recent advances of Internet of Things and smart sensors. Meanwhile, reinforcement learning (RL) has witnessed an intrinsic breakthrough in solving a variety of complex problems for distinct applications and services. Thus, this article presents a comprehensive survey of the recent models and techniques of RL that have been developed/used for supporting Intelligent-healthcare (I-health) systems. It can guide the readers to deeply understand the state-of-the-art regarding the use of RL in the context of I-health. Specifically, we first present an overview of the I-health systems' challenges, architecture, and how RL can benefit these systems. We then review the background and mathematical modeling of different RL, deep RL (DRL), and multiagent RL models. We highlight important guidelines on how to select the appropriate RL model for a given problem, and provide quantitative comparisons, showing the results of deploying key RL models in two scenarios that can be followed in monitoring applications. After that, we conduct an in-depth literature review on RL's applications in I-health systems, covering edge intelligence, smart core network, and dynamic treatment regimes. Finally, we highlight emerging challenges and future research directions to enhance RL's success in I-health systems, which opens the door for exploring some interesting and unsolved problems. Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Networked Systems

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    https://doi.org/10.1109/jiot.2...
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      https://doi.org/10.1109/jiot.2...
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    Authors: Aamir Sajjad Nasir; Muhammad Usman; Muhammad Ali Ijaz Malik; Asad Naeem Shah; +6 Authors

    Mineral oil resources are depleting rapidly, and the slower conventional oil biodegradation process results in environmental pollution. To resolve this issue, cupric oxide (CuO) nanoparticles (1% wt) were introduced into a base oil to improve the lubricating capability of castor oil. In addition, 1% wt. sodium dodecyl sulfate was also blended with the base oil in order to attain the maximum dispersion stability of CuO nanoparticles in the castor oil. Afterward, thermophysical property, atomic absorption spectroscopy, and Fourier transform infrared radiation (FTIR) testing of the lubricant oil sample were performed before and after 100 h of engine operations at 75% throttle and 2200 rpm for each lubricant sample in order to check the capability of the novel oil with mineral oil. Compared with the natural mineral oil, the behavior of the CuO-based lubricant has essentially the same physical features, as measured according to ASTM standard methods. The physicochemical properties like (KV)40 °C, (KV)100 °C, FP, ash, and TBN decrease more in the case of the synthetic oil by 1.15, 1.11, 0.46, 1.1, and 1.2% than in the conventional oil, respectively. FTIR testing shows that the maximum peaks lie in the region of 500 to 1750 cm−1, which shows the presence of C=O, C-N, and C-Br to a maximum extent in the lubricant oil sample. AAS testing shows that the synthetic oil has 21.64, 3.23, 21.44, and 1.23% higher chromium, iron, aluminum, and zinc content. However, the copper and calcium content in the synthetic oil is 14.72 and 17.68%, respectively. It can be concluded that novel bio-lubricants can be utilized as an alternative to those applications that are powered by naturally produced mineral oil after adding suitable additives that further enhance their performance.

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    Authors: Yazeed Yasin Ghadi; Tehseen Mazhar; Syed Faisal Abbas Shah; Inayatul Haq; +3 Authors

    In the past few years, privacy concerns have grown, making the financial models of businesses more vulnerable to attack. In many cases, it is hard to emphasize the importance of monitoring things in real-time with data from Internet of Things (IoT) devices. The people who make the IoT devices and those who use them face big problems when they try to use Artificial Intelligence (AI) techniques in real-world applications, where data must be collected and processed at a central location. Federated learning (FL) has made a decentralized, cooperative AI system that can be used by many IoT apps that use AI. It is possible because it can train AI on IoT devices that are spread out and do not need to share data. FL allows local models to be trained on local data and share their knowledge to improve a global model. Also, shared learning allows models from all over the world to be trained using data from all over the world. This article looks at the IoT in all of its forms, including “smart” businesses, “smart” cities, “smart” transportation, and “smart” healthcare. This study looks at the safety problems that the federated learning with IoT (FL-IoT) area has brought to market. This research is needed to explore because federated learning is a new technique, and a small amount of work is done on challenges faced during integration with IoT. This research also helps in the real world in such applications where encrypted data must be sent from one place to another. Researchers and graduate students are the audience of our article.

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    Authors: Affia, Abasi-amefon Obot;

    Võrgutoega seadmete ja nende haavatavuste kasvuga on hakatud rohkem tähelepanu pöörama asjade interneti (IoT) turvariskide haldamisele (SRM). Võimalik ründepind laieneb asjade Interneti ökosüsteemi kasvades, tuues esile vajadust tugevate turvameetmete järele arenevate ohtude vastu. Olemasolevad uuringud toovad siiski välja lünki asjade Interneti arhitektuuri täielikul integreerimisel turvariskide haldamisse. Rakendamise praktilised väljakutsed tõstavad niigi keerukate asjade interneti süsteemide keerukust ja teevad turvariskide haldamise ülesannet veelgi keerulisemaks. Seega õõnestab teooria ja praktika vaheline ebavõrdsus turvaraamistike eduka rakendamise tõenäosust reaalsetes asjade interneti süsteemides, muutes need vastuvõtlikuks pidevalt arenevale ohumaastikule. Nende väljakutsete lahendamiseks tutvustame IoT-arhitektuuril põhinevat turvariskide haldamise (IoTA-SRM) raamistikku, mis pakub terviklikku ja integreeritavat lähenemist tuvariskide haldamisele asjade interneti süsteemides. Integreerides IoT arhitektuuri turvariskide haldamisse, saavad sidusrühmad tagada oma IoT süsteemi komponentide ja interaktsioonide igakülgse katvuse. Raamistikku hinnati autonoomsete sõidukisüsteemide ekspertide poolt läbiviidud juhtumiuuringute abil, et teha kindlaks selle praktilisus, kohanemisvõime ja eelised. Kuigi antud juhtumite analüüsis nähakse raamistiku praktilisust, võib selle teoreetiline rikkus jääda praktikutele rakendamise ajal abstraktseks. Arvestades asjade interneti süsteemide keerukust ja ohtude dünaamilist olemust, ei piisa üksi traditsioonilistest õpetamisviisidest, et hõlbustada raamistiku üleminekut teoreetiliselt arusaamiselt praktilisele rakendusele, mistõttu on vaja tavapärasest õpetamisviisidest edasi ulatuvaid haridusmeetodeid. Seega töötati välja sekkumispõhine häkatoni lähenemine. See lähenemisviis, mida täiustatakse kohandatud sekkumistega, soodustab kogemuslikku õppimist. Antud sekkumised on hoolikalt välja töötatud, kohandatavad erinevate häkatoni kontekstide ja turvalisuse aspektide õpetamise sisuga ning täiustatud tegevusuuringute tsüklite kaudu, et võimaldada osalejatel navigeerida ja rakendada IoTA-SRM raamistikku. Meie integreeritud raamistik ja häkatoni lähenemisviis täitsid kahte rolli: haridusmudel, mis on suunatud turvariskide haldamisele asjade interneti süsteemides, ja IoTA-SRM-i raamistiku hindamismehhanism häkatoni iteratsioonide kaudu, võimaldades selliselt selle iteratiivset täiustamist. See doktoritöö aitab kaasa IoT SRMi teoreetilisele mõistmisele ja IoT turvariskide juhtimise praktilistele lähenemisviisidele. Lisaks pakub see meetodit tulevaste spetsialistide koolitamiseks selles kiiresti arenevas valdkonnas. Siin esitatud leiud ja metoodikad loovad aluse tulevastele püüdlustele IoT SRM-i rakendamisel ja õpetamisel, näitlikustades sünergilist seost teoreetiliste turvakontseptsioonide ja nende praktilise rakendamise vahel. With the rise of network-capable devices and their vulnerabilities, attention has focused on security risk management (SRM) in the internet of things (IoT). The potential attack surface expands as the IoT ecosystem grows, underscoring the need for robust security measures against evolving threats. Yet, existing research reveals gaps in fully integrating the IoT architecture into SRM activities. Practical implementation challenges further complicate the intricate nature of IoT systems and the daunting task of SRM. Consequently, the disparity between theory and practice undermines the likelihood of successfully implementing security frameworks in real-world IoT systems, leaving them susceptible to an ever-evolving threat landscape. To address these challenges, we introduce the IoT Architecture-based Security Risk Management (IoTA-SRM) framework, offering a comprehensive and integrative approach to SRM in IoT systems. By integrating the IoT architecture into security risk management, stakeholders can ensure comprehensive coverage of their IoT system components and interactions. The framework was evaluated involving expert-validated case studies in autonomous vehicle systems to ascertain its practicality, adaptability, and benefits. However, though the practicality of the framework is seen in this case analysis, its theoretical richness may remain abstract for practitioners during application. Given the intricacy of IoT systems and the dynamic nature of threats, traditional instructional approaches alone prove insufficient to facilitate the framework's transition from theoretical understanding to practical application, necessitating educational methods that transcend conventional instruction. Thus, an intervention-based hackathon approach was developed. Enhanced with tailored interventions, this approach fosters an experiential learning approach. These interventions are carefully crafted, adaptable to diverse hackathon contexts and security learning content, and refined through action research cycles to enable participants to navigate and apply the IoTA-SRM framework. Our integrated framework and hackathon approach served dual roles: an educational model targeting SRM in IoT systems and an evaluation mechanism for the IoTA-SRM framework through hackathon iterations, thus allowing for its iterative refinement. This thesis contributes to the theoretical understanding of IoT SRM and practical approaches for IoT security risk management. It further offers a method for educating future professionals in this rapidly evolving field. The findings and methodologies presented herein provide a basis for future endeavours in applying and teaching IoT SRM, exemplifying the synergistic relationship between theoretical security concepts and their practical application. https://www.ester.ee/record=b5645350

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    Authors: Aziz Nurbekov; Muhammadjon Kosimov; Makhmud Shaumarov; Botir Khaitov; +3 Authors

    Soil productivity and crop yield were examined in response to legume-based short crop rotation under conventional (CT) and no-till (NT) tillage practices in saline meadow-alluvial soils of the arid region in Bukhara, Uzbekistan. Compared with the CT treatment, crop yield was consistently higher under NT, i.e., winter wheat 9.63%, millet 9.9%, chickpea 3.8%, and maize 10.7% at the first experiment cycle during 2019–2021. A further crop productivity increase was observed at the second experiment cycle during 2021–2023 under NT when compared to CT, i.e., winter wheat 17.7%, millet 31.2%, chickpea 19.6%, and maize 19.1%. An increase in total phyto residue by 20.9% and root residue by 25% under NT compared to CT contributed to the improvement in soil structure and played a vital role in the sustained improvement of crop yields. In turn, the increased residue retention under NT facilitated soil porosity, structural stability, and water retention, thereby improving soil quality and organic matter content. Soil salinity more significantly decreased under NT than in CT, reducing salinity buildup by 18.9% at the 0–25 cm and 32.9% at the 75–100 cm soil profiles compared to CT. The total forms N and P were significantly increased under NT when compared to CT, while the efficiency of the applied crop rotation was essential. This study showed the essential role of the NT method with legume-based intensive cropping in the maintenance of soil health and crop yield, thereby touching on recent advances in agro-biotechnology and the sustainable land management of drylands.

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    Authors: Enock Siankwilimba; Jacqueline Hiddlestone-Mumford; Md Enamul Hoque; Bernard Mudenda Hang'ombe; +10 Authors

    AbstractIn the fourth industrial revolution, achieving sustainable agricultural development while feeding a growing world population and maintaining a balanced interrelationship between the economy, society, and the environment has been a significant challenge. However, COVID-19 disrupted agricultural extension and advisory systems, affecting all market participants. The complexity of the pandemic has impacted the private sector, public sector, extension staff, donor funding, education, and research systems, subsequently affecting human nutrition. This paper aims to expertly review COVID-19’s effects on the sustainability of gender-specific agricultural extension service systems. Demand and supply market stakeholders in the extension system are thematically discussed. The findings reveal various consequences of COVID-19 for market actors on both the demand and supply sides of the extension system. Private-sector players often support expansion directly or indirectly, with multi-sectorial support and funding strategies existing for sustainability. In many developing nations, the comprehensive extension system was disrupted by COVID-19, impacting household incomes and nutrition. The pandemic accelerated the adoption of digital technologies in many developing nations, transitioning from a centralized to a decentralized and pluralistic extension model. Multi-sector coordination and execution, especially from health and other sectors, are crucial in managing complex crises that disrupt the market system.

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      Other literature type . 2023
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      Data sources: Datacite
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      Cogent Food &amp; Agriculture
      Article . 2023
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      Cogent Food &amp; Agriculture
      Article . 2023 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
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