Variety Of Technologies Research Articles

Computational diplomacy: how 'hackathons for good' feed a participatory future for multilateralism in the digital age.

This article explores the role of hackathons for good in building a community of software and hardware developers focused on addressing global sustainable development goal (SDG) challenges. We theorize this movement as computational diplomacy: a decentralized, participatory process for digital governance that leverages collective intelligence to tackle major global issues. Analysing Devpost and GitHub data reveals that 30% of hackathons since 2010 have addressed SDG topics, employing diverse technologies to create innovative solutions. Hackathons serve as crucial kairos moments, sparking innovation bursts that drive both immediate project outcomes and long-term production. We propose that these events harness the neurobiological basis of human cooperation and empathy, fostering a collective sense of purpose and reducing interpersonal prejudice. This bottom-up approach to digital governance integrates software development, human collective intelligence and collective action, creating a dynamic model for transformative change. By leveraging kairos moments, computational diplomacy promotes a more inclusive and effective model for digital multilateral governance of the future. This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

Photocatalytic degradation of microcystins from a field-collected cyanobacterial assemblage by 3D printed TiO2 structures using artificial versus solar irradiation

Microcystins (MCs) from freshwater cyanobacteria cause adverse effects to humans and ecological receptors through multiple exposure routes requiring adaptable and diverse treatment technologies. Photocatalysis of MCs using TiO2 is a promising technology; however, TiO2 photocatalysts as unbound nanoparticles in suspension are impractical to deploy. 3D Printing (3DP) provides a means to immobilize TiO2, producing deployable photocatalyst structures with extensive geometric freedom. The objective of this proof-of-concept experiment was to incrementally increase the environmental complexity (e.g., broad-spectrum fluorescent lamps and outdoor solar; filtered cell lysate and algal assemblage as the source of MCs) while comparing photocatalysis rates of MCs by 3DP TiO2 structures using polylactic acid (PLA) as the binder. Degradation half-lives of MCs were shorter in TiO2 embedded in 3DP PLA relative to PLA-only controls with differences in half-lives ranging from 3.6 to 10h. The one exception was the outdoor solar and an algal assemblage, where significant differences could not be discerned due to the already rapid photolysis rates. Ultimately, photocatalysis rates (half-life = 1.9–11.6h) were comparable to those previously published for TiO2 3DP structures in a laboratory environment and TiO2 fixed-films (half-life = 2–13h) demonstrating feasibility of 3DP to immobilize TiO2 photocatalysts under a range of conditions. This is the first time that MC concentrations from a field-collected HAB were photocatalytically degraded in both solar simulated light and sunlight using a custom-made advanced photocatalytic nano-composite with enhanced performance through high surface area design enabled by 3D printing. These data inform future development of scalable, retrievable, and operationally flexible structures with immobilized TiO2.

Classifying Technologies during the Assessment, Treatment Planning, Documentation and Evaluation Phases of Music Therapy: A Survey of Board-Certified Practitioners

Music therapists (MT-BCs) use diverse technologies to provide evidence-based personalized interventions to a wide variety of people. Most studies on the technological practices of MT-BCs report a general overview of the tools they use in their daily work. This study offers an new way of understanding technologies used by MT-BCs, classified and situated in the phases of music therapy (MT) practice: Assessment, Treatment Planning, In-Session, Documentation and Evaluation. An online survey was sent to a mailing list of 1,951 board-certified music therapists (MT-BC), and we received 104 responses. Results support distinct functions in technological practices between each of the phases of MT, revealing categories of notetaking and data entry that characterize planning, documentation and evaluation tasks, and a wider diversity of technology configurations in assessment and in-session work. We end by discussing design implications for HCI researchers and designers of music technologies for health, as well as HCI-MT design collaboration to better support the work of the MT-BC community.

Determination of principal axes orientation in an ion trap using matter-wave interference

We have developed a method for determining the orientations of the principal axes of an ion trap using an ion matter-wave interferometer. By examining the ion matter-wave interference signal induced by spin-dependent momentum kicks originating from stimulated Raman transitions, we can accurately ascertain the angles between the directions of these momentum kicks and the trap principal axes. The application of direct–current voltage to the ground electrodes, a common method adopted to finely tune trap frequencies in ion traps, leads to the trap principal axes rotating, a phenomenon that is yet to be reported quantatively. Our measurements successfully captured the rotation of the trap axes depending on the applied offset voltages. The findings of this study offer valuable insights into the functioning of ion traps for diverse quantum science and technology applications.

Equity, Diversity, and Inclusion in STEM Academic Librarianship: Perspectives and Practices in Canada

This research explores the perspectives and practices of Equity, Diversity, and Inclusion (EDI) in Canadian Science, Technology, Engineering, and Mathematics (STEM) academic librarianship. Research data were collected from Canadian STEM librarians through an online survey and one-on-one interviews. Findings indicate that the majority of participants' libraries and institutions have integrated EDI into their strategic plans, policies, or guidelines. These STEM librarians shared their perspectives, experiences, opportunities, and challenges in achieving their EDI goals. Besides providing examples of practices, the research sheds light on potential improvements to encourage STEM academic librarians to effectively integrate EDI into their professional practices. Establishing a supportive organizational culture for EDI is identified as a crucial motivational factor.

Benchmarking Big Data Systems: Performance and Decision-Making Implications in Emerging Technologies

Systems for graph processing are a key enabler for insights from large-scale graphs that are critical to many new advanced technologies such as Artificial Intelligence, Internet of Things, and blockchain. In this study, we benchmark another two widely utilized graph processing systems, Apache Spark GraphX and Apache Fink, concerning the key performance criterion by means of response time, scalability, and computational complexity. We demonstrate our results which show the capability of each system for real-world graph applications, and hence, providing a quantitative understanding to select the system for our purpose. GraphX’s strength was in processing batch in-memory workloads typical of blockchain and machine learning model optimization, while Flink excelled in processing stream data, which is timely and important to the IoT world. These performance characteristics emphasize how the capabilities of graph processing systems can match the requirements for the performance of different emerging technology applications. Our findings ultimately inform practitioners about system efficiencies and limitations, but also the recent advances in hardware accelerators and algorithmic improvements aimed at shaping the new graph processing frontier in diverse technology domains.

Retriever: A view-based approach to reverse engineering software architecture models

Software systems, which have become an integral part of our daily lives, are constantly evolving and growing in complexity. The challenge of understanding and managing these systems has led to a shift towards automated extraction of models from software artifacts. However, extracting architectural models for web service or microservice systems is challenging due to the heterogeneity of formats, languages, and semantics. This challenge arises from the independent deployment and loose coupling of services, as well as the diverse technologies and platforms that comprise the heterogeneous artifacts. This paper addresses this issue with two key ideas: a knowledge representation model for diverse artifacts and a framework for integrating individual views into a unified architectural model. The former involves model-to-model transformations that consider technology-specific relationships and concepts. At the same time, the latter uses model transformation and composition techniques to create a unified model based on an existing metamodel. This work goes beyond the current state of the art by introducing an approach for reconstructing component-based software architectures and combining model-driven reverse engineering processes to capture information across multiple views. As empirical evidence of its applicability and accuracy, we report on its successful application in real projects of different sizes. Our evaluation shows scalability in generating architectural models and can reconstruct the components of a software system and their interactions with F1 values up to 0.94 for structural properties and up to 0.88 for behavioral properties.

Numerical Simulation of Solid Diverting Particles Transport and Plugging in Large-Scale Hydraulic Fracture

Diversion technology, also known as temporary plugging technology, has become an integral part of hydraulic fracturing in unconventional reservoirs. The solid diverting particles are a common type of chemical diverting agents used in horizontal well multistage fracturing. The transport and plugging of solid diverting particles within the fractures are crucial physical processes in the far-field diversion technology. In this study, in order to clarify the formation of the plugging layer by solid diverting particles in large-scale hydraulic fracture and to offer insights for the quantitative optimization of far-field diversion technology (FFD), an enhanced simplified two-fluid model within the Euler-Euler framework is employed to simulate the transport and plugging process of solid diverting particles within the fracture. And the numerical schemes of the front settlement region, the plugging layer formation region and the rear settlement region are also optimized. The proposed model is verified through comparison with experimental results from visual fracture test device. Based on the numerical results across various particle, pumping and fracture parameters, our findings indicate that: (1) The duration required to form a complete plugging layer can be reduced to 3% to 20% by increasing injection concentration, injection rate, and fracturing fluid viscosity; (2) Increasing the injection concentration (from 10kg/m3 to 30kg/m3) significantly enhances the length of the plugging layer by about 1 to 16 times, compensating for the inability to achieve a complete plugging layer with smaller particle sizes. Merely increasing the injection rate alone (from 0.35m3/min to 0.80m3/min) does not remedy the inability of small particles to form a complete plugging layer under identical plugging conditions. Excessive fracturing fluid viscosity (higher than 6mPa·s) impedes the formation of a complete plugging layer with smaller particles. High fracturing fluid leak-off rate (higher than 2.5×10-7m/s) markedly reduces the length of the plugging layer by about 37% to 44%; (3) Achieving a high close packing degree of particles within the plugging layer is facilitated by increasing injection concentration, increasing injection rate, and reducing fluid viscosity; (4) The abrupt variation in fracture width or height along the fracture length affects up to about 18% of the length of the plugging layer at the top of fracture. To ensure large length of the plugging layer at the top of fracture and high close packing degree of particles within the plugging layer, we recommend injection concentration above 10kg/m3, fracturing fluid viscosity below 6mPa·s, and injection rate exceeding 0.35m3/min. For particle size less than 1.8mm, we suggest injection concentration above 20kg/m3, and fracturing fluid viscosity not exceeding 3mPa·s.

Pathways to innovation: How city pilots leverage digital technology to reduce carbon emissions

Technological innovation through various pathways is crucial for achieving carbon neutrality and peak carbon emissions. The Innovative City Pilot (ICP) initiative, a key effort to promote national innovation, has garnered increasing attention. However, most studies have not examined the effects of ICP on carbon emissions through diverse digital technologies. Using city-level data from 2000 to 2022, we constructed a staggered difference-in-differences (DID) model to analyze changes in carbon emissions before and after the ICP period in both ICP and non-ICP areas. The carbon emission reduction pathway of the ICP influences various forms of digital technology, which then empower local green product innovation, market-oriented innovation, and industrial innovation. The impact of ICP emission reduction through digital technology is more significant in western, first- and second-tier, sub-provincial, populous, and coastal cities. In conclusion, policymakers should tailor policies according to the action pathways of digital technology and specific city characteristics. We outline the specific pathways of green product innovation, market-oriented innovation, and industrial innovation enabled by digital technologies and provide policy recommendations for the sustainable development of China.

Ocean energy enabling a sustainable energy-industry transition for Hawaiʻi

Global transitions to highly sustainable energy-industry systems imply shifts to high shares of variable renewable energy sources. While onshore solar photovoltaics and wind power can be expected to be the lowest cost electricity sources around the world, land-constrained regions and islands may have limited onshore renewable potential. Thus, offshore energy technologies, including floating solar photovoltaics, offshore wind turbines, and wave power, may become essential. Furthermore, for Hawaiʻi, offshore energy may provide increased supply diversity and avoid land conflicts as electricity generation is expected to increase. The LUT Energy System Transition Model was employed to investigate the techno-economic implications of high technological diversity through integration of offshore energy technologies compared to full cost-optimisation under both self-supply and electricity-based fuel import scenarios. Limiting solar electricity leads to 0-2.3 GW of offshore electricity and 0-4.1 GW of wave power by 2050, but at 3.5-28.0% increased system costs. Under self-supply conditions and an 80% solar photovoltaics limit, a novel interaction between the key offshore technologies was identified with 0.6-1.1 GW of offshore floating photovoltaics, which contribute 12.3% of all electricity generation by 2050. Due to the limited land availability in Hawaiʻi and island regions, ocean energy technologies may significantly contribute to energy-industry system defossilisation.

Clownselling: an in-depth narrative review on the therapeutic influence of clowning therapy in paediatric and adult cancer treatment and palliative care

Cancer and its treatments impose substantial physical and psychological burdens on patients, underscoring the need for innovative and holistic interventions. This narrative review explores the evolving role of clownselling in paediatric and adult cancer care, tracing its historical progression from entertainment to a therapeutic modality. Recognizing the potential of clowning therapy to address emotional, psychological, and existential challenges, the review systematically assesses its impact on treatment adherence, quality of life, and contributions in palliative care settings. By elucidating the therapeutic process, principles, and goals, it provides a comprehensive understanding of the foundations of clowning therapy. Given its positive influence on well-being, the integration of clowning therapy into interdisciplinary care teams and institutional policies is advocated. Future directions include diversified research, technology integration, standardized protocols and awareness campaigns, ensuring the sustained evolution of clowning therapy in fostering holistic well-being within the intricate tapestry of cancer care.

Balancing Innovation and Profitability: Technological Diversification in Iran’s Insurance Industry

Abstract This study explores how technological diversification affects financial performance in Iran’s insurance industry. Using semi-structured interviews with six experts, including CEOs and faculty members, key indicators of technological diversification were identified, such as new underwriting software and digital advertising platforms. A 33-item questionnaire was developed based on these insights and distributed to top managers of Iranian insurance companies, with secondary financial data sourced from the Central Insurance of Iran. The study employes regression analysis and Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the impact of technological diversification on financial performance, controlling for firm size, debt ratio, and company age. Findings indicate a significant negative relationship between technological diversification and both Return on Equity (ROE) and Return on Assets (ROA), suggesting that the costs of adopting new technologies may outweigh their short-term financial benefits. Additionally, high debt ratios were found to adversely affect ROA, highlighting the financial risks of excessive borrowing.

Enhancing cross-border contact tracing in Europe: Lessons learned from COVID-19 and future directions

Abstract Introduction Health systems in the EU operate at the national level, granting Member States autonomy for outbreak preparedness and response within their territories whilst coordinating at EU level to combat serious cross-border threats. The EU’s Early Warning and Response System (EWRS) provides the platform to exchange personal data for contact tracing across 30/EEA countries and was extensively utilized during COVID-19. This study examines insights from EU/EEA countries and assesses the feasibility of integrating national digital systems with EWRS to increase its effectiveness. Methods A comparative case study surveyed representatives from 24 countries and interviewed nine, analyzing contact tracing processes, actors, digital technologies, and challenges/facilitators during COVID-19. Thematic analysis was complemented by two webinars engaging EU/EEA countries to validate findings and gather additional perspectives. Results EWRS was valued for safety and efficiency but faced challenges during peak pandemic periods due to the heavy manual workload. Integrating national digital systems with EWRS could enhance data quality, timeliness, and coordination between countries. However, countries have varied and incompatible digital contact tracing systems, limiting the feasibility of their integration with EWRS. Moreover, most countries organize contact tracing at the subnational level, with regional entities developing and managing their own digital technologies under national guidance. Smaller countries excluded, subnational contact tracing case management systems were often not integrated with each other to exchange personal data in an automated way at a national level. Conclusions While integrating national digital systems with EWRS could bolster efficiency of contact tracing across EU/EEA, the presence of diverse technologies and decentralized governance poses feasibility challenges. Other improvements are needed to enhance cross-border contact tracing during outbreaks. Key messages • Integrating national digital systems with EWRS promises enhanced efficiency for contact tracing across EU/EEA in line with Regulation (EU) 2022/2371 on serious cross-border threats to health. • Diverse technologies and decentralized governance pose feasibility challenges, underscoring the need for further enhancements in cross-border contact tracing in EU/EEA during large outbreaks.

Revolutionising patient care: the role of AI-generated avatars in healthcare consultations

Abstract Background/Introduction The healthcare sector faces an unprecedented challenge with the surging demand in both public and private settings, pushing them towards the brink of overload. This scenario underscores a critical knowledge gap in leveraging technology to alleviate the burden on healthcare services. Our study introduces an innovative solution through the development of avatars generated with artificial intelligence (AI) technologies, that replicate the likeness and expertise of healthcare professionals. These AI-generated avatars aim to bridge the gap in patient consultations, offering a scalable and efficient alternative to traditional care models. Purpose The primary objective of our study was to design and implement a virtual assistant capable of conducting patient consultations with the same reliability and personal touch as a trusted human medical professional. This was carried out through the integration of diverse AI technologies including generative models, large language models (LLMs), speech-to-text, and text-to-speech algorithms. Methods Our methodology encompassed the creation of three-components, the visual and auditory representation of the healthcare professional (avatar), the capability to process and generate speech (brain functions), and a database of information sourced from medical repositories as well as expert inputs (compiled knowledge). The development process involved capturing and generating the likeness and voice of a medical expert, training LLMs with the compiled knowledge, and engineering the system to function in real-time. This multifaceted approach ensured the AI-generated avatars were not only personalised but also intelligent and interactive. Results The successful execution of each component confirmed its feasibility, with the AI-generated avatars resembling their human counterparts in appearance and voice, effectively processing spoken inputs, and providing medical advice based on the compiled knowledge. The primary challenge identified was the integration of these components to operate seamlessly in real-time, indicating the need for further refinement in synchronisation and response speed. Conclusion This study has laid a foundational step towards revolutionising patient care through AI technologies. Our results demonstrate the potential of AI-generated avatars to alleviate workloads by providing personalised and efficient patient consultation services. Future work will focus on enhancing the real-time integration of system components, improving the scalability of the solution, and further personalising the patient experience. This direction not only intends to expand the capabilities of healthcare providers but also opens new avenues for patient engagement and care delivery.

Advances in Plant Disease Diagnostics and Surveillance- A review

Plant diseases pose a significant threat to global food security, leading to substantial yield losses and economic impacts. Early detection and effective monitoring are crucial for managing plant diseases, yet traditional diagnostic methods such as visual inspections, serological tests, and molecular assays face limitations in sensitivity, specificity, and scalability. In recent years, advancements in diagnostic and surveillance technologies have revolutionized plant health management. Next-Generation Sequencing (NGS) enables comprehensive pathogen profiling, while CRISPR-based diagnostics offer rapid and highly specific detection. Similarly, biosensors and portable devices provide on-site diagnostics, and machine learning and AI applications enhance the analysis of complex datasets, supporting automated disease identification and predictive modeling. Concurrently, advances in disease surveillance through remote sensing technologies, including satellites and Unmanned Aerial Vehicles (UAVs), enable large-scale, real-time monitoring of crop health, detecting disease outbreaks and facilitating targeted interventions. Integrating these diverse technologies into multi-platform systems offers a holistic approach to plant disease management, combining molecular diagnostics, environmental monitoring, and digital platforms to support data-driven decision-making. Several challenges remain, including high costs, technical complexities, and the need for standardized data integration. Addressing these barriers is essential to ensure that these technologies are accessible and effective across various agricultural systems, particularly in resource-limited settings. Future research should focus on enhancing the robustness, affordability, and scalability of these tools while promoting interdisciplinary collaborations.

Flow Diversion for Intracranial Aneurysms With Incorporated Branch: A Subanalysis From the SEASE International Registry

BACKGROUND The presence of an incorporated branch as well as its anatomical relationship to the intracranial aneurysms (IAs) and the parent artery may affect the occlusion outcome following flow diversion. This study evaluated the safety and effectiveness of the cobalt‐chromium Surpass Evolve (Stryker), a 64‐wire flow diversion device for the treatment of IAs with incorporated branches. METHODS This subanalysis uses data from the SEASE (Safety and Effectiveness Assessment of Surpass Evolve) registry to retrieve data related to IAs with incorporated branches. Those IAs were classified by a core lab into 4 categories based on their anatomical relationship to the parent artery and branch: (A) sidewall anatomic, (B) sidewall hemodynamic, (C) neck branch, and (D) dome branch. We compared the outcomes based on their incorporated branch's relation to the dome (A–C versus D). RESULTS This study included 67 patients and IAs. Most IAs were in the posterior communicating artery (46.3%), with a median size of 4.35 mm. Age, sex, comorbidities, baseline functional‐status, and IA features were similar between the 2 groups. Among those, 53 (79.1%) had branches emerging from the dome, and 14 (20.9%) had branches originating from other locations (A = 7, B = 2, and C = 5). At a median imaging follow‐up of 10.5 months, complete occlusion was lower in IAs with a branch from the sac compared with those with the neck (60.8% versus 92.9%; P = 0.026), with an overall occlusion of 67.7%. Thromboembolic and hemorrhagic complications, as well as retreatment, were reported in 1.6% and 3.1% of cases, respectively, with no significant differences between groups. CONCLUSION Our analysis underscores the influence of branch origin on occlusion rates, with the neck‐originating branch demonstrating higher occlusion rates. These insights emphasize the role of anatomical considerations in treatment strategies, follow‐up timelines, and designing future clinical trials. Further studies are warranted to explore these variations across different flow diversion technologies.

Simple Smoothing of the Bottom Silicon Surface Using Wet Chemical Etching Methods for Epitaxial III‐V/Silicon Tandem Manufacturing

The implementation of diverse technologies has recently facilitated the production of cost‐effective and highly efficient solar cells. High‐efficiency solar cells with III‐V compounds tandem crystalline silicon cells have achieved photovoltaic efficiency of higher than 39%. Etching silicon wafers plays a vital role in the deposition of epitaxial layers, neutralizing dangling bonds, and surface passivation for tandem solar cells. The wafers are polished using a solution of HF–HNO3–CH3COOH (HNA) and 20% KOH to smoothen the wafer surface. When HNA wet etching is performed for 3.5 min and the 20% KOH etching lasts for 6 min, the microroughness of the wafer is 1.9 nm with a measurement area of 10 × 10 μm2 and 0.816 nm within an area of 1 × 1 μm2. Compared with the as‐cut wafer, the reflectance increases from 31.7% to 34.7%, and the effective minority carrier lifetime, with 30 nm Al2O3 passivation after 450 °C activated, increases from 1.4 to 1.8 ms in a carrier density of 1.0 × 1015 cm−3.

Technology Integration as a Spectrum: integrating technology in early childhood classrooms

ABSTRACT This study explores how early childhood preservice teachers use technology in PreK-3 classrooms, focusing on the alignment between their intentions and actual practices. Using the ‘Technology Integration as a Spectrum (TIS)’ model, the study identifies four types of technology use. Findings reveal that preservice teachers primarily use technology for adult- or software-driven goals, which often contradict their pedagogical beliefs. Although they advocate for child-centred learning approaches, their technology use predominantly reflects these more structured methods, resulting in misalignments between intended purposes and actual practices. This study highlights the need for diverse technology use, including Free Use, and recommends critical reflection on technology practices to ensure alignment with pedagogical goals for effective implementation.

Digital Twin-assisted anomaly detection for industrial scenarios

Industry 5.0 is the current industrial paradigm that inherits the technological diversity of its predecessor, Industry 4.0, but includes three priority goals: (i) resilience, (ii) sustainability and (iii) human-centeredness. Through these three goals, Industry 5.0 pursues a more far-reaching digital transformation in industrial ecosystems with high protection guarantees. However, the deployment of innovative information technologies for this new digital transformation also requires considering their implicit vulnerabilities and threats in order to avoid any negative impacts on the three Industry 5.0 goals, and to prioritize cybersecurity aspects so as to ensure acceptable protection levels. This paper, therefore, proposes a detection framework composed of a Digital Twin (DT) and machine learning algorithms for online protection, supporting the resilience that Industry 5.0 seeks. To validate the approach, this work includes several practical studies on a real industrial control testbed to demonstrate the feasibility and accuracy of the framework, taking into account a set of malicious perturbations in several critical sections of the system. The results highlight the effectiveness of the DT in complementing the anomaly detection processes, especially for advanced and stealthy threats.

Precision crop mapping: within plant canopy discrimination of crop and soil using multi-sensor hyperspectral imagery

Leveraging diverse optomechanical and imaging technologies for precision agriculture applications is gaining attention in emerging economies. The precise spatial detection of plant objects in farms is crucial for optimizing plant-level nutrition and managing pests and diseases. High-resolution remote sensors mounted on drones have been increasingly deployed for large-scale crop mapping and field variability characterization. While field-level crop identification and crop-soil discrimination have been studied extensively, within-plant canopy discrimination of crop and soil has not been explored in real agricultural farms. The objectives of this study are: (i) adoption and assessment of spectral unmixing for discriminating crop and soil at within-plant canopy level, and (ii) generation of benchmark terrestrial and drone-based hyperspectral datasets for plant or sub-plant level discrimination using various spectral mixture modelling approaches and sources of endmembers. We acquired hyperspectral imagery of vegetable crops using a frame-based sensor mounted on a drone flying at different heights. Further, several linear, non-linear, and sparse-based spectral unmixing methods were used to discriminate plant and soil based on spectral signatures (endmembers) extracted from different spectral libraries prepared using in situ or field, ground-based, and drone-based hyperspectral imagery. The results, validated against pixel-to-pixel ground truth data, indicate an overall crop-soil discrimination accuracy of 99–100%, subject to a combination of endmember source and flying height. The influences of different endmember sources, spatial resolution as indicated by flying height, and inversion algorithms on the quality of estimated abundances are assessed from a verifiable and functionally relevant perspective. The generated hyperspectral datasets and ground truth data can be used for developing and testing new methods for sub-canopy level soil-crop discrimination in various agricultural applications of remote sensing.