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Synergistic effects of NiSe2 on S-doped g-C3N4 for efficient caffeine degradation and electrocatalysis
This work focuses on the synthesis and characterization of NiSe2 on S-doped g-C3N4 to enhance the degradation of caffeine and improve the electrocatalytic performance in both HER and OER. Through a controlled synthesis method, NiSe2 was successfully anchored onto the surface of S-doped g-C3N4, leading to a significant increase in active sites and improved charge transfer. From the PXRD analysis, the crystallite sizes for the planes (210) and (311) were found to be 26 and 21 nm. Morphological analysis confirmed the uniform distribution of NiSe2 nanorod-like structures on the S-g-C3N4 nanosheets. Additionally, the composite demonstrated superior photocatalytic degradation efficiency of 96 % for caffeine under visible light irradiation by the composite, highlighting its potential application in both environmental remediation and energy conversion technologies. After the addition of hydroxyl and singlet oxygen scavengers, the degradation has been decreased to 50.3 % and 47.36 %, highlighting the potential of these radicals in the removal of caffeine. The electrochemical measurements revealed a remarkable increase in HER and OER activities of the NiSe2 on S-doped g-C3N4 composite (?128 mV and 338 mV at 10 mA cm?2 and 50 mA cm?2 respectively) compared to S-doped g-C3N4 and NiSe2 alone. This study highlights the promising role of NiSe2-S-g-C3N4 composites as multifunctional materials in addressing pressing challenges in water treatment and sustainable energy. 2025 Elsevier B.V. -
Synergistic enhancement of bifunctionality in Ni-doped VO2 (B) nanostructures: A pathway for improved water electrocatalysis
The global energy demand led to the exploration of techniques to produce green hydrogen, such as water electrolysis, as a future fuel for energy management. However, the efficiency of hydrogen evolution (HER) during this electrocatalysis is usually regulated by the proficiency of the catalyst in generating a facile oxygen evolution reaction (OER). In this work, the robust bifunctionality of Ni-doped VO2(B) as an electrocatalyst for hydrogen and oxygen evolution reactions is investigated. The optical characterization uncovered the semiconducting nature of nanoflake-like VO2(B) nanostructures. Furthermore, optimizing Ni concentration resulted in significant reduction of overpotentials from 518 mV to 289 mV for HER and from 435 mV to 404 mV for OER under a current density of 10 mA/cm2. This excellent electrochemical efficiency of the Ni-doped VO2(B) nanostructures is further showcased by the low Tafel slope values of 129 mV/dec and 99 mV/dec for HER and OER, respectively. Consistent with these findings, the materials exhibited minimal charge transfer resistance of 57.1 ?, reinforcing the superior electrocatalytic activity. Additionally, the chronopotentiometric studies confirmed the long-term stability of the nanostructures. Altogether, Ni-doped VO2(B) nanostructures can be considered as a potential electrocatalyst for overall water electrolysis, laying the foundation for a sustainable energy future. 2025 Elsevier B.V. -
Synergistic fabrication, characterization, and prospective optoelectronic applications of DES grafted activated charcoal dispersed PVA films
This study investigates the synthesis, analysis, and utility of films comprising deep eutectic solvent (DES) grafted activated charcoal (AC) within a polyvinyl alcohol (PVA) matrix for optoelectronic device applications. The fabrication process involves the dispersion of DES functionalization AC into the PVA solution, followed by casting onto substrates with controlled drying. Comprehensive characterization encompassing X-ray diffraction (XRD), scanning electron microscopy (SEM), UVvis spectroscopy, Fourier-transform infrared spectroscopy (FTIR), and impedance spectroscopy which discerns the films microstructure, morphology, conductance, band-gap, and optical traits. The DES grafted AC infusion with variable concentration has significantly influenced optical absorbance and reduced the band gap indicating efficient charge mobility. Furthermore, the impedance analysis has revealed the electrical conduction of the film to be 1.8 10?6 ??1 m?1. In summary, the dispersion of DES modified AC in the PVA matrix have converted the insulating PVA to a semiconducting polymeric film with reduced band-gap and increased absorption, which present a propitious avenue for wide array of optoelectronic devices, such as thin film transistors, photovoltaics, LEDs, photodetectors, and many such applications. 2024 The Authors. Polymers for Advanced Technologies published by John Wiley & Sons Ltd. -
Synergistic g-c3n4/v2o5/pani composite for electrochemical energy storage
This work illustrates the synthesis of a ternary hybrid composite (g-C3N4/V2O5/PANI) from graphitic carbon nitride, vanadium pentoxide, and Polyaniline via hydrothermal method followed by in-situ polymerization. Morphological analysis confirms the integration of vanadium pentoxide (V2O5) and polyaniline (PANI) within the interlayer spaces of graphitic materials. The resultant hybrid composite structure facilitates rapid diffusion and ion movement at the electrode-electrolyte interface. Additionally, incorporating V2O5 within a polymer matrix alongside graphitic material generates diverse electrical profiles, enhancing electrochemical performance. The electrochemical characteristics of g-C3N4/V2O5/PANI composites were examined by Cyclic voltammetry (CV), Galvanostatic charge-discharge (GCD), and Electrochemical impedance spectroscopy (EIS). The GCD analysis shows that the g-C3N4/V2O5/PANI composite exhibits a specific capacitance of 880 Fg?1 at a current density of 1 Ag?1, retaining 78 % of its initial capacitance after executing 2000 cycles at 3 Ag?1. Furthermore, a symmetric supercapacitor was constructed using g-C3N4/V2O5/PANI composite material as the electrode, showing a capacitance of 246 Fg?1 when measured at an input current density of 1 Ag?1. This study demonstrates g-C3N4/V2O5/PANI is a potential electrode material for supercapacitor application. 2024 -
Synergistic g-c3n4/v2o5/pani composite for electrochemical energy storage
This work illustrates the synthesis of a ternary hybrid composite (g-C3N4/V2O5/PANI) from graphitic carbon nitride, vanadium pentoxide, and Polyaniline via hydrothermal method followed by in-situ polymerization. Morphological analysis confirms the integration of vanadium pentoxide (V2O5) and polyaniline (PANI) within the interlayer spaces of graphitic materials. The resultant hybrid composite structure facilitates rapid diffusion and ion movement at the electrode-electrolyte interface. Additionally, incorporating V2O5 within a polymer matrix alongside graphitic material generates diverse electrical profiles, enhancing electrochemical performance. The electrochemical characteristics of g-C3N4/V2O5/PANI composites were examined by Cyclic voltammetry (CV), Galvanostatic charge-discharge (GCD), and Electrochemical impedance spectroscopy (EIS). The GCD analysis shows that the g-C3N4/V2O5/PANI composite exhibits a specific capacitance of 880 Fg?1 at a current density of 1 Ag?1, retaining 78 % of its initial capacitance after executing 2000 cycles at 3 Ag?1. Furthermore, a symmetric supercapacitor was constructed using g-C3N4/V2O5/PANI composite material as the electrode, showing a capacitance of 246 Fg?1 when measured at an input current density of 1 Ag?1. This study demonstrates g-C3N4/V2O5/PANI is a potential electrode material for supercapacitor application. 2024 -
Synergistic Hybrid Segmentation for Handwritten Kannada Word Recognition Addressing Deep Learning Challenges
The handwritten Kannada script has an intricate aksharas that are formed by combining consonants, vowels, and ottus. These complex combinations pose significant hurdles for automated text segmentation. The inherent diversity in handwriting styles, coupled with prevalent character overlap, multi-touch connections, varied curve structures such as upper open curve(OC), upper closed curve (CC), and the highly condensed nature of Ottaksharas, routinely blurs character boundaries, leading to severe segmentation errors that propagate and compromise overall recognition accuracy. A hybrid approach that customizes adaptive traditional methods like vertical pixel count, to identify true character gaps in handwritten Kannada characters could effectively manage character overlap, or segment multi-touch characters or Ottaksharas. This pre-processing stage can allow subsequent deep learning models to recognize this segmented character. This will avoid significant hurdles: immense data requirements for pixel-level annotations, high computational costs for dense prediction, and significant architectural complexities for precise boundary delineation and handling connectivity. Given these constraints, particularly with less-resource language like Kannada, scaling deep learning models will lead to ever erroneous recognition. This paper argues that modified traditional approaches, by directly embedding customized knowledge and leveraging targeted feature engineering, can offer a computationally efficient and data-lean alternative. This strategy enables more robust segmentation for complex Kannada characters, providing a practical pathway for automated handwritten text processing in such linguistic domains. 2025 IEEE. -
Synergistic interfacial passivation of dye-sensitized solar cell photoanodes using Myristica fragrans pulp-derived carbon dots and Ag nanoparticles
Interfacial charge recombination at the photoanode remains a critical factor in limiting the performance of Dye-sensitized solar cells. The photoanodes play a crucial role in efficient electron injection and transport with minimised recombination reactions, directly influencing the efficiency of the cell. This work investigates the use of carbon dots (CDs) derived from Myristica fragrans fruit pulp via a one-step hydrothermal process as a component in photoanodes. The TiO2 photoanode is modified by in situ deposition of silver nanoparticles (ANP) and CDs directly onto the metal-oxide semiconductor matrix via photoreduction. The passivated cell exhibited ?28 % increase in efficiency over the pristine cell, attaining 6.39 0.20 %, with a current density of 14.74 0.28mAcm?2, and an open-circuit voltage of 0.76 0.02 V. Herein, the passivation of TiO2 has altered the optical bandgap of the photoanode from 3.23 eV to 1.75 eV, thereby enhancing light absorption towards the visible and near-IR region. Furthermore, the localized surface plasmon resonance (LSPR) effect of ANP and the charge-transfer mediator properties of CDs synergistically enhance charge mobility, thereby improving photoanode performance by reducing recombination. With a charge-transfer resistance of 6.87 ? and an electron lifetime of 47.19 s, the work explored here serves as an appropriate passivation layer, providing a clean interface between the layers. 2026 Elsevier B.V. -
Synergistic pseudocapacitive behavior of Cr2CTx MXene and Cu-PTC MOF in CM-II: an Electroactive composite
The increasing global energy demand and a shift towards sustainable energy solutions necessitate the development of advanced energy storage devices, with supercapacitors emerging as key candidates. Achieving high energy density without compromising power density remains a critical challenge, underscoring the need for novel materials with robust pseudocapacitive behavior. This study introduces a novel electroactive composite, CM-II, composed of Cr2CTx MXene and a Cu-based MOF, Cu-PTC. The synthesis, structural, and morphological characterization of CM-II is extensively detailed. Cr2CTx MXene provides a conductive scaffold, while Cu-PTC contributes redox-active sites and porosity, creating a synergistic combination that enhances charge storage. The pseudocapacitive performance of CM-II has been systematically evaluated, with a specific capacitance of 3035 F g?1 and a long cycle-life with a capacitance retention of 96% after 5000 cycles, showcasing its potential as a high-performance material for next-generation supercapacitors. 2025 The Author(s). Published by IOP Publishing Ltd. -
Synergistic utilisation of waste coconut fibers, sugarcane bagasse ash, and recycled aggregates in geopolymer paver blocks
The use of industrial and agricultural waste such as ground granulated blast furnace slag (GGBS), recycled coarse aggregates (RCA), sugarcane bagasse ash (SCBA), and waste coconut fibers (WCF) have great potential in development of sustainable construction materials. In this study, geopolymer paver blocks were prepared with GGBS and SCBA as precursors, natural coarse aggregates (NCA) partially replaced with RCA as filler material, and WCF used as an additive. To understand the synergy of these materials, SCBA and WCF was incorporated in a fixed dosage, with varying replacement rates of RCA. GGBS was replaced with 20% SCBA, NCA was replaced with 25% and 50% RCA, and a constant dose of 1% WCF was incorporated in the geopolymer mix. The developed paver blocks were tested for compressive strength, split tensile strength, flexural strength, resistance to abrasion, and water absorption. The results obtained demonstrate that addition of RCA, SCBA, and WCF do not benefit the compressive strength, split tensile strength, and water absorption of the paver blocks. However, the flexural strength and resistance to abrasion have shown significant improvement in the presence of RCA, WCF, and SCBA. This research also develops linear regression models to predict strength properties and water absorption of the paver blocks. The results indicate that linear regression model can be used to predict the compressive strength, split tensile strength, and flexural strength with an accuracy of 85%, 96%, and 71%, respectively. Overall, the developed geopolymer paver blocks with RCA, SCBA, and WCF meet the standard requirements of IS 15658: 2021 for pavement applications, and a significant improvement in the flexural strength and resistance to abrasion will enhance the durability and longevity of the paver blocks in service. 2026 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license. http://creativecommons.org/licenses/by-nc-nd/4.0/ -
Synergizing Artificial Intelligence and Sustainability for Sustainable Climate Action: Decoding the Digital Dilemma
The rapid development and use of artificial intelligence (AI) tools across a range of industries in recent years has spurred a revolution in the way that global issues like climate change and the improvement of sustainable energy solutions are addressed. These resources not only strengthen motivation but also radically alter how environmental and energy-related concerns are approached. It is essential to assess current practices in energy and climate change modeling in order to pinpoint areas for future application, given the growing worldwide reliance on efficient and sustainable energy solutions as well as the development of artificial intelligence and machine learning. Keeping this in mind, the authors of the chapter examine the interplay between AI, the sustainability approach, and its impact on climate change. The chapter examines the policy perspective on AI and climate action, balancing it with a sustainable development perspective. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026. -
Synergizing digital learning with customer engagement in digital era
Specifically concentrating on the junction of digital learning and customer engagement, this research investigates the dynamic interplay between technology, education, and consumer relationships. The research demonstrates a symbiotic link between advances in one field and their favourable influence on the other through a thorough literature review and case studies. The findings show that increasing learning outcomes and fostering meaningful customer involvement may be achieved by combining customer engagement tactics with digital learning methodologies. According to the study's conclusion, firms must take advantage of this convergence to gain a competitive advantage. It highlights that digital learning and consumer involvement offer a substantial channel for innovation and growth. According to the report, for a complete user experience, customer engagement tactics should include digital learning tools. By illuminating this creative amalgamation, this chapter provides a novel outlook on the dynamic digital terrain, providing discernments into restructuring pedagogical approaches and augmenting customer engagements. 2025 Samriddha D. P., Thirupathi Manickam, Devarajanayaka Kalenahalli and Ravi V.. All rights reserved. -
Synergizing Edge AI and Quantum Machine Learning for Real-Time Cyber Threat Mitigation
The escalation of the complexity of cyber threats must be countered by traditional signature- and rule- based security approaches. In this study, we propose a hybrid Edge AI-Quantum Machine Learning (QML) framework that employs variational quantum circuits and classical neural networks towards real-time per-device threat detection. Using three case studies, we validate the framework: (1) fraud detection in high frequency trading with 17% more true positives and 22% less false positives; (2) inference times under 100 ms for IoT anomaly detection; and (3) reduction of over 25% in deepfake misclassification. The built system is built end- to- end with an open- source stack. Finally, regulatory and ethical considerations (GDPR, data, privacy, international cybersecurity protocols, etc., Budapest Convention) are discussed. In presenting this work, we present a scalable and adaptive model for next- generation cybersecurity. 2026, IGI Global Scientific Publishing. All rights reserved. -
Synergizing Humanity and Technology: A Human-Machine Collaboration for Business Sustainability in Industry 5.0
In the context of Industry 5.0, this paper emphasizes the crucial role of human-machine collaboration for sustainable business practices. It explores the need for a people-centric approach, recognizing the significance of the human workforce alongside advanced technologies. The study investigates three influential theoriesActor-Network Theory (ANT), Activity Theory, and Socio-Technical Systems Theory (STS)proposing a novel Socio-Technical Interaction Network (STIN) model that synthesizes their strengths. The STIN model views systems as intricate networks of diverse actors, both human and non-human, acknowledging their agency and interactions within socio-technical environments. By incorporating elements from each theory, it prioritizes contextual analysis, considering socio-cultural and environmental influences on human-technology interactions. The STIN model aims to provide a holistic lens for interdisciplinary research and guide the design of technology-infused systems aligned with human needs and societal contexts. In conclusion, human-machine collaboration is deemed not just a technological necessity but a strategic imperative for organizations striving for long-term sustainability in Industry 5.0, fostering adaptability, innovation, and sustainable practices. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Synergizing Insights for Precise Rice Leaf Disease Diagnosis Via Multi-Modal Fusion
Rice holds a significant position in India, especially in the southern part of the country, where people tend to eat some rice at least once a day. Farmers are facing a huge loss due to diseases in leaf, which is the main problem of agriculture. By using techniques like machine learning, main problems detection can be done. This review, discusses common plant diseases that affect the leaf. Some include Leaf Spots, Rusts, Fusarium Wilt, Early Blight, Powdery Mildew and Downey Mildew. Our research found that machine learning techniques on rice plants make finding diseases on leaves easier. Finally, we concluded that the most accurate method is the Enhanced VGG16, with an accuracy of 99.60% because it is really good at spotting diseases on rice leaves because it's great at recognizing the small details and patterns in leaf pictures. This helps it to tell the diseases apart more accurately and make fewer mistakes in identifying them. 2024 IEEE. -
Synergizing Neutrosophy and Randomized Blocks Design: Development and Analytical Insights
The design of the experiment is a strategy for effectively examining the relationship between input design parameters and process output and developing a greater understanding. A randomized block design is an experimental design that has two primary factors and is widely used in agriculture, environment, biological, animal, and food sciences, where experimental material is heterogeneous and precise. In a randomised block design, one or more observations may lose their true significance due to an accident, poor handling, pest infestations in agricultural trials, or other factors. It is prudent to treat this value as missing and estimate it. In todays practical situations, uncertainty and inaccuracies are inevitable in most research areas. It is important to handle such data, which can lead to inaccurate and unreliable results. Neutrosophy is the branch of philosophy that provides an efficient method to study impreciseness among the data. Some of the common sources of Neutrosophy in randomised block design are incorrect blocking factor selection, measurement error, subjective factors, and natural variability. It is paramount to handle the Neutrosophy in a randomised block design; otherwise, it may lead to various problems, like a high risk of false positives. In this paper, the Neutrosophic Randomised Block Design (NRBD) is introduced to tackle data impreciseness. The study also, outlines a methodology for estimating missing observations in NRBD and presents its analysis. Additionally, the study compares the efficiency of NRBD to that of the Neutrosophic Completely Randomised Design (NCRD). 2024, American Scientific Publishing Group (ASPG). All rights reserved. -
Synergizing Senses: Advancing Multimodal Emotion Recognition in Human-Computer Interaction with MFF-CNN
Optimizing the authenticity and efficacy of interactions between humans and computers is largely dependent on emotion detection. The MFF-CNN framework is used in this work to present a unique method for multidimensional emotion identification. The MFF-CNN model is a combination of approaches that combines convolutional neural networks and multimodal fusion. It is intended to efficiently collect and integrate data from several modalities, including spoken words and human facial expressions. The first step in the suggested system's implementation is gathering a multimodal dataset with emotional labels added to it. The MFF-CNN receives input features in the form of retrieved facial landmarks and voice signal spectroscopy reconstructions. Convolutional layers are used by the model to understand hierarchies spatial and temporal structures, which improves its capacity to recognize complex emotional signals. Our experimental assessment shows that the MFF-CNN outperforms conventional unimodal emotion recognition algorithms. Improved preciseness, reliability, and adaptability across a range of emotional states are the outcomes of fusing the linguistic and face senses. Additionally, visualization methods improve the interpretability of the model and offer insights into the learnt representations. By providing a practical and understandable method for multimodal emotion identification, this study advances the field of human-computer interaction. The MFF-CNN architecture opens the door to more organic and psychologically understanding human-computer interactions by showcasing its possibilities for practical applications. The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. -
Synergy Unleashed: Smart Governance, Sustainable Tourism, and the Bioeconomy
This study investigates the transformational potential of smart Governance in the tourism sector to enhance the operational effectiveness, transparency, and efficacy of governmental actions. This research synthesises the body of knowledge regarding the use of technology and data-driven methods in Governance using a literature review methodology. A conceptual framework is suggested to highlight the complex effects of smart Governance on many stakeholders in the travel industry. The study uses a multidimensional paradigm that includes agile leadership, stakeholder alliances, network management, and adaptive Governance. It explains how these complementary components construct a revolutionary ecology that encourages creativity, adaptability, and inclusive growth. Organisations can acquire insights into visitor behaviours, preferences, and traffic patterns by utilising data analytics and digital platforms, which can improve resource allocation, infrastructure construction, and policy formation. Applications that use real-time data enable dynamic crowd control, traffic optimisation, and safety improvements. The report also highlights how local communities may be involved in smart Governance to promote inclusive decision-making. This framework helps promote deeper study into the actual application and outcomes of smart Governance, which has the potential to change the travel sector. This multidisciplinary approach fosters resilience, innovation, and responsible, inclusive development. This study promotes real-world applications that fully utilise this synergy to further the interconnected objectives of sustainable tourism, bioeconomic growth, and efficient Governance. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Synthesis and Biological Evaluation of Sr and Co Co-Doped TiO?Folic Acid Nanocomposites: Antibacterial, Antifungal (Candida albicans), Antioxidant (DPPH and Trolox), and In Vitro Anticancer Activity against HepG2 Cells
Liver cancer and multidrug-resistant bacterial infections pose significant health challenges, highlighting the urgent need for multifunctional therapeutics. In this study, a TiO? nanocomposite co-doped with strontium (Sr) and cobalt (Co) and surface-functionalized with folic acid (TiO?SrCoFA) nanocomposite was synthesized via a hydrothermal method followed by post-synthesis FA functionalization. XRD confirmed the anatase phase, with reduced crystallite size for TiO?SrCoFA, while TEM showed spherical, uniformly dispersed nanoparticles (~ 23nm) with no agglomeration. DLS revealed a hydrodynamic diameter of 138.6nm, and XPS/FTIR confirmed Sr, Co, and FA incorporation. Optical studies (UV-Vis and PL) indicated electronic modifications conducive to ROS generation. TiO?SrCoFA exhibited enhanced antimicrobial activity against Gram-positive bacteria (Staphylococcus aureus, Bacillus subtilis, Bacillus megaterium), Gram-negative bacteria (Klebsiella pneumoniae, Proteus vulgaris), and Candida albicans. Antioxidant assays demonstrated concentration-dependent scavenging (2883%) comparable to vitamin C. In HepG2 liver cancer cells, TiO?SrCoFA showed superior cytotoxicity with an IC?? of 6.5g/mL versus 9.8g/mL for TiO?, inducing apoptosis and oxidative stress. The enhanced bioactivity is attributed to nanoscale size, Sr/Co doping, FA-mediated targeting, and ROS generation. TiO?SrCoFA thus represents a promising multifunctional nanotherapeutic platform for simultaneous antimicrobial, antioxidant, and anticancer applications. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2026. -
Synthesis and catalytic applications of metal boride ceramics
Metal borides belong to the class of high-temperature ceramics and have conventionally been used for high-temperature applications. However, in the past few decades, new variants of metal borides have emerged, with high catalytic capabilities. Owing to their tuneable structural, compositional, and morphological properties, metal borides have huge potential for industrially relevant catalytic applications. This chapter compiles the existing knowledge on the ever-expanding family of metal borides. Various synthesis strategies that are commonly adopted for the fabrication of metal borides, both in crystalline and amorphous/nanocrystalline forms, are discussed in detail. The chapter also aims to explain the origin of catalysis in metal borides. Some of the most prominent catalytic applications of metal borides are vividly discussed in this chapter. At the end of this chapter, a brief outlook is provided for future research initiatives with metal borides. 2023 Elsevier Ltd. All rights reserved. -
Synthesis and Characterisation of SrAl2O4: Eu3+ Orange-Red Emitting Nanoparticles
The current study involves the synthesis and characterisation of europium doped strontium aluminate nanophosphors using the solid-state reaction method with varying concentrations of europium. The existence of the SrAl2O4 phase in all samples was verified using X-ray diffraction and FTIR analysis. The lattice parameters as well as phase fractions were determined using Rietveld refinement. Surface morphology was studied using field emission scanning electron microscope. Using the Tauc plot method acquired from the diffuse reflectance spectra, the band gaps of the samples were determined and it was found that the doped samples possess lower band gaps compared to the host. Our findings demonstrate that these nanophosphors exhibiting bright orange-red emission under UV excitation with quantum efficiency 70.68%, can be applied for display and fluorescence imaging. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.