Innovative Concept Research Articles

Bio-Based Innovation and the Global Patent System: Exploring the WIPO Treaty on Intellectual Property, Genetic Resources and Associated Traditional Knowledge

Abstract This opinion critically examines the 2024 WIPO Treaty on Intellectual Property, Genetic Resources and Associated Traditional Knowledge, a new instrument addressing the use of genetic resources (GR), and traditional knowledge associated with GR (ATK) in the global patent system. Given the Treaty’s position at the intersection of intellectual property and environmental law, this article discusses its history and negotiation in the first part, including the Treaty’s links to the Convention on Biological Diversity (CBD) and the Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPS). It then discusses the concept of bio-based innovation and its role in the bioeconomy. Following this, the article assesses the Treaty’s contents, including its context and objectives, scope, the Patent Disclosure Requirement (PDR), sanctions and remedies for non-compliance with the PDR, information systems on GR and ATK, and its relationship with other international instruments. The article highlights the extensive diplomatic negotiations that shaped the final text and considers potential amendments that could be made during the Treaty’s review process. The Treaty is intended to improve the global patent system’s effectiveness, transparency, and quality concerning GR and ATK and to prevent Offices from granting patents erroneously. Its provisions present new challenges and complexities for stakeholders, and its long-term success will depend on ongoing international collaboration and engagement, both within and outside the Treaty’s framework, and ensuring equitable benefit-sharing from the use of GR and ATK as part of a global sustainable bioeconomy.

Frugal innovation and entrepreneurial university: a case study of African first development university in Africa

The concept of frugal innovation has gained significant traction in low middle-income countries due to its potential to contribute to sustainable development goals (SDGs). This study examines the role of universities in promoting frugal innovation and their capacity to drive socio-economic development through entrepreneurial initiatives. The objective is to explore how universities can serve as both entrepreneurial and development-focused institutions and to develop a conceptual framework to guide their efforts. The study utilizes an exploratory single case study methodology, focusing on the American University of Nigeria (AUN), a leading institution in Nigeria known for its development and entrepreneurship programs. Drawing on data from the AUN THE global impact ranking 2024, the results of the study indicate that the ability of a university to effectively manage technology and skills transfer in frugal innovations is influenced by six university capabilities, and the generation of frugal innovations is moderated by policy and innovation ecosystems involving government agencies, regulatory bodies, and policymakers. This study contributes to the existing body of knowledge by initiating a discussion on how development and entrepreneurship can support frugal innovation, and offers practical insights to inspire other universities to develop their own models for societal and economic impact. The study underscores the necessity of integrating “development” into the vision of universities, particularly in low middle-income and developing economies, and emphasizes the significance of universities embracing both entrepreneurial and development-focused roles. The findings highlight the potential of universities in advancing sustainable development goals, particularly in low middle-income and developing economies, as they work towards meeting the global SDGs by 2030.

To What Extent Can Digital Health Technologies Comply With the Principles of Responsible Innovation? Practice-and Policy-Oriented Research Insights Regarding an Organisational and Systemic Issue

Background: Digital health technologies (DHTs) have expanded exponentially since the COVID-19 crisis and have prompted questions about their impact across all levels of health systems. Because health organisations and systems play a central role in the success or failure of the transition to more equitable and sustainable societies, the concept of Responsible Innovation in Health (RIH), focused on aligning the processes and outcomes of innovation with societal values, is gaining interest in research, policy, and practice. This study aims to explore enablers and constraints to the development, procurement and/or utilisation of responsible DHTs in health organisations. Methods: Semi-structured interviews were conducted with 29 stakeholders concerned with the development, procurement, and/or utilisation of DHTs in a large Canadian academic health centre. Data were thematically analysed through a mixed deductive-inductive process using the RIH framework. Results: Our findings highlight that the consideration of RIH principles in the development, procurement, and/or utilisation of DHTs depends mainly on organisational and systemic factors and conditions, namely: (1) the presence of an organisational culture that promotes RIH in its innovation-related practices and processes; (2) availability of material and financial resources as well as expertise in certain fields (eg, environmental sustainability); (3) the evolution of health technology assessment (HTA) practices to include other dimensions beyond effectiveness, safety, and costs; (4) the scope of the regulatory and legal frameworks that govern the approval and use of DHTs; and (5) the role of the market (eg, venture capital) in the design of federal and provincial innovation policies. Conclusion: This study provides insights on practice, policy, and political issues that health organisations may face in the development, procurement, and/or utilisation of responsible DHTs. It can help scholars, practitioners, decision-makers, and industry to create the conditions for a better integration of RIH principles into health organisations and systems.

Irreversibility analysis of radiative TiO2+Al2O3+Cu/H2O ternary nanofluid flow over a bidirectional stretching sheet with cattaneo-christov heat flux: nanotechnology applications

Ternary nanofluids demonstrate better heat transfer characteristics in contrast to conventional liquids and typical hybrid nanofluids. These are applied in sophisticated cooling systems for electronics, heat exchangers, and automotive engines, along with renewable energy systems such as solar collectors, where efficient heat transfer plays a crucial role. The aim of this research is to investigate the movement of a Casson ternary nanofluid passing through a bidirectional exponential sheet by employing the innovative Cattaneo-Christov heat flux concept. The utilization of the energy equation considers thermal radiation, viscous dissipation, and heat source/sink effects, with the integration of chemical reaction effects into the concentration equation. An analysis of entropy generation is utilized to evaluate the thermodynamic irreversibility within the system. The conversion of transport equations involves a transformation from partial to ordinary differential equations, followed by a numerical solution utilizing the BVP4C solver embedded in the MATLAB package R2022b. The impacts of developed factors on thermal, concentration, and velocity behavior, as well as engineering quantities, are thoroughly explored graphically. The outcome reveals that the velocity gradients diminish as magnetic fields intensify, while it amplified by the Hall factor. The rise in temperature of ternary nanofluid correlates with elevated levels of radiation, and Brownian motion. Concentration intensifies with the rapid development of thermophoresis influences. Heightened values of the Reynolds and Brinkman numbers give rise to amplified entropy production but a decrease in the Bejan number. The ternary nanofluid displays a remarkable 8.92% increase in skin friction on the x-axis and y-axis, influenced by the potent Darcy-Forchheimer factor. The rates of mass and heat transfer in nanofluids undergo a decrease of 8.58% and 12.52%, respectively, due to the heightened influence of Brownian motion and Eckert number. The results could provide valuable insights into the performance of ternary nanofluids in various industrial environments under specific conditions.

Towards Self-Conscious AI Using Deep ImageNet Models: Application for Blood Cell Classification

The exceptional performance of ImageNet competition winners in image classification has led AI researchers to repurpose these models for a whole range of tasks using transfer learning (TL). TL has been hailed for boosting performance, shortening learning time and reducing computational effort. Despite these benefits, issues such as data sparsity and the misrepresentation of classes can diminish these gains, occasionally leading to misleading TL accuracy scores. This research explores the innovative concept of endowing ImageNet models with a self-awareness that enables them to recognize their own accumulated knowledge and experience. Such self-awareness is expected to improve their adaptability in various domains. We conduct a case study using two different datasets, PBC and BCCD, which focus on blood cell classification. The PBC dataset provides high-resolution images with abundant data, while the BCCD dataset is hindered by limited data and inferior image quality. To compensate for these discrepancies, we use data augmentation for BCCD and undersampling for both datasets to achieve balance. Subsequent pre-processing generates datasets of different size and quality, all geared towards blood cell classification. We extend conventional evaluation tools with novel metrics—“accuracy difference” and “loss difference”—to detect overfitting or underfitting and evaluate their utility as potential indicators for learning behavior and promoting the self-confidence of ImageNet models. Our results show that these metrics effectively track learning progress and improve the reliability and overall performance of ImageNet models in new applications. This study highlights the transformative potential of turning ImageNet models into self-aware entities that significantly improve their robustness and efficiency in various AI tasks. This groundbreaking approach opens new perspectives for increasing the effectiveness of transfer learning in real-world AI implementations.

Multi-targets cleavage of BmNPV genome through genome-wide repeat sequence using CRISPR/Cas9 antiviral system.

The escalating severity of Bombyx mori nuclear polyhedrosis virus (BmNPV) infections poses significant challenges to the silkworm industry, especially when massive production shifts occur from the eastern regions to western regions with lower labor costs. Education and experience levels are different and disease control is badly needed. To solve the problems, we have developed an innovative CRISPR/Cas9 system specifically targeting BmNPV to enhance viral resistance. For the system, we selected BmNPV genes linked to virus replication and proliferation as targets, designing 2 sites for each gene. Mutating the target sequence renders the system incapable of efficiently cleaving the virus genome, hence decreasing cleavage efficiency. We conducted a search for "NGG" or "CCN" target sequences in the BmNPV genome, excluding non-recurring and potential targets in the B.mori genome. We successfully identified 2 distinct target sequences in the BmNPV genome-one being repeated 12 times and the other three times. These sequences lead to fragmentation of virus genome into multiple large segments that are difficult to repair. Transgenic silkworms demonstrate robust resistance to viruses, significantly boosting their survival rates compared with wild-type silkworms under various virus infection concentrations. Our system efficiently targets dozens of viral genomes with just 2 sequences, minimizing transposable elements while ensuring cutting effectiveness. This marks a pioneering advancement by using repetitive elements within the virus genome for targeted CRISPR cleavage, aiming for antiviral effects through genome fragmentation rather than disrupting essential viral genes. Our research introduces innovative concepts to CRISPR antiviral investigations and shows promise for the practical application of gene editing in industrial silkworm strains.

Towards the Concept of Digital Grassroots Youth Innovation

In recent years, young people have acquired a more active role in different areas of public life, such as culture, politics and gender debates. However, the relevance of their role in innovation processes has remained largely undiscussed. Are young people, in particular those from working class backgrounds, a forgotten actor for innovation and technological change policies? This study aims to understand whether the youth population—who are widely connected to the Internet, who do not necessarily participate in formal educational spaces but are increasingly acquiring digital skills autonomously—can be considered as an agent of innovation. Specifically, this study aims to propose and define the concept of Digital Grassroots Youth Innovation. It is based on both empirical and theoretical sources. On the one hand, it relies on a compilation of experiences of innovative activities related to digital technologies led by young people in Argentina. On the other hand, it is supported by a theoretical discussion on (a) the different types of innovations and their subjects, (b) the specificities of the ‘marginal mass’ in informational capitalism and (c) the characterisation of the young population in Argentina as ‘NEET’ (not in education, employment or training). Finally, we ask about the role played by digital technologies and non-formal learning in these particular innovation processes.

Promoting motivation and reducing stress in medical students by utilizing self-determination theory - a randomized controlled trial in practical psychiatry courses.

Medical students experience high levels of stress and related mental health problems. Students' autonomous and controlled motivation and their mental well-being are interconnected. This study aimed to investigate whether an innovative teaching concept based on self-determination theory (SDT) could improve students' motivation and thereby reduce their stress levels, ultimately providing a healthier framework for learning. In a week-long practical psychiatry course for medical students, a new didactic concept was implemented in half the groups (n = 73) and compared with the preexisting concept (n = 75) as a randomized controlled trial (RCT). To promote the SDT-target factors of perceived autonomy, competence, and relatedness, the methods used included team building, exclusively positive feedback, group discussions, and choice in task distribution. Significant group differences in motivation, stress, performance, and their relationships were analyzed through t-tests, multiple linear regression analyses, mediation analyses, and hierarchical linear modeling (HLM) using questionnaires collected before (t0) and after (t1) the course, and students' exam results (t2). In the innovation group (n = 53), intrinsic motivation/interest (d = 0.41; p = .019) and perceived choice/autonomy (d = 0.33; p = .048) were greater than in the control group (n = 52). While autonomous regulation remained stable, the innovation group showed reduced controlled regulation (d = -0.36; p = .033) and reported significantly lower stress (d = -0.55; p = .003). The observed changes in motivation collectively mediated the stress reduction. However, students in the innovation group achieved lower exam scores, which seemed to result from the absence of critical feedback, but not from the observed differences in motivation or stress. This study demonstrated that enhancing intrinsic motivation through SDT-based teaching can effectively reduce stress in medical students. Exclusively strengths-based positive feedback may have hindered exam performance, but optimizing educational concepts to promote motivation and reduce stress will be a valuable step toward improving medical students' mental well-being.

RTINet: A Lightweight and High-Performance Railway Turnout Identification Network Based on Semantic Segmentation.

To lighten the workload of train drivers and enhance railway transportation safety, a novel and intelligent method for railway turnout identification is investigated based on semantic segmentation. More specifically, a railway turnout scene perception (RTSP) dataset is constructed and annotated manually in this paper, wherein the innovative concept of side rails is introduced as part of the labeling process. After that, based on the work of Deeplabv3+, combined with a lightweight design and an attention mechanism, a railway turnout identification network (RTINet) is proposed. Firstly, in consideration of the need for rapid response in the deployment of the identification model on high-speed trains, this paper selects the MobileNetV2 network, renowned for its suitability for lightweight deployment, as the backbone of the RTINet model. Secondly, to reduce the computational load of the model while ensuring accuracy, depth-separable convolutions are employed to replace the standard convolutions within the network architecture. Thirdly, the bottleneck attention module (BAM) is integrated into the model to enhance position and feature information perception, bolster the robustness and quality of the segmentation masks generated, and ensure that the outcomes are characterized by precision and reliability. Finally, to address the issue of foreground and background imbalance in turnout recognition, the Dice loss function is incorporated into the network training procedure. Both the quantitative and qualitative experimental results demonstrate that the proposed method is feasible for railway turnout identification, and it outperformed the compared baseline models. In particular, the RTINet was able to achieve a remarkable mIoU of 85.94%, coupled with an inference speed of 78 fps on the customized dataset. Furthermore, the effectiveness of each optimized component of the proposed RTINet is verified by an additional ablation study.

Fixed Point Results for Fuzzy Enriched Contraction in Fuzzy Banach Spaces with Applications to Fractals and Dynamic Market Equillibrium

We introduce fuzzy enriched contraction, which extends the classical notion of fuzzy Banach contraction and encompasses specific fuzzy non-expansive mappings. Our investigation establishes both the presence and uniqueness of fixed points considering this broad category of operators using a Krasnoselskij iterative scheme for their approximation. We also show the graphical representation of fuzzy enriched contraction and analyze its graph for different values of beta. The implications of these findings extend to significant results within fuzzy fixed-point theory, enriching the understanding of iterative processes in fuzzy metric spaces. To demonstrate the versatility of our innovative concepts and the associated fixed-point theorems, we provide illustrative examples that showcase their applicability across diverse domains, including the generation of fractals. This demonstrates the relevance of fuzzy enriched contraction to iterated function systems, enabling the study of fractal structures under various contractive conditions. Additionally, we explore practical applications of fuzzy enriched contraction in dynamic market equilibrium, offering new insights into stability and convergence in economic models. Through this unified framework, we open new avenues for both theoretical advancements and real world applications in fuzzy systems.

The role of universities in enabling open innovation through the development of digital competence of faculty

The concept of open innovation, which involves the intentional exchange of internal and external knowledge to accelerate innovation, has been widely discussed in business management but, in recent years, has also entered the academic community. This concept aligns closely with the university's mission to advance knowledge, foster creativity, and address real-world problems. The present study aims to examine the role of universities in promoting educational innovation as a form of open innovation through developing the digital competence of faculty and using external sources of knowledge. Accordingly, this study explores the following research questions: 1) What educational innovations are facilitated by developing faculty's digital competence? 2) To what extent are these educational innovations linked to external knowledge sources? The study is based on the following research methods: scientific literature review, focus group discussion with faculty members, and conceptual model development through data triangulation. The findings position digital competence as an enabler of educational innovations and highlight the university's role in creating a conducive environment for open innovation by enabling collaboration with various actors, accessing and sharing knowledge and empowering the participation of diverse stakeholders. Moreover, the study concludes that enhancing faculty digital competence, integrating external knowledge through collaborative spaces, fostering industry partnerships, and investing in digital infrastructure can create a dynamic ecosystem that supports open innovation as an educational innovation.

Vesalius and His Manikin: An Enduring Influence on Modern Anatomic Teaching.

Anatomic teaching has long informed surgical knowledge, experience, and skills. One tool for teaching that emerged during the Renaissance was the fugitive anatomic sheet, which used flap layers to reveal different levels of anatomy. In 1538, Vogtherr introduced the first fugitive sheets, which included illustrations of male and female figures with a torso paper flap that, when lifted, revealed the internal organs in a cartoonish style. The popularity of these anatomic fugitive sheets spurred an increase in small print-and-sale workshops. In 1543, Vesalius included fugitive anatomic sheets in his books Fabrica and Epitome, containing large paper flapped models that could be created by cutting out and gluing images of human internal anatomy onto a base layer. Students could tack these manikins up to a nearby wall during dissection. Significant collaboration between Vesalius and his publisher occurred to coordinate the integration of large foldable sheets featuring the cutout models into his works. Vesalius's groundbreaking discoveries, his use of the most advanced printing techniques, and his innovative teaching style are fundamental aspects of the legacy of medical education. This article shows these remarkable fugitive anatomic sheets from the original publications of Fabrica and Epitome together for the first time. It explores the innovative concepts and applications of Vesalius's unique printings.

Advanced optimization of elastic sheets for solar parabolic trough concentrators: integrating particle swarm optimization and genetic algorithms

Abstract The fabrication of solar parabolic trough concentrators using flat elastic sheets presents a straightforward and cost-effective method. This paper introduces an optimization technique centered on stiffness adjustment, harnessing elastic buckling to attain precise parabolic shapes in these concentrators. Through an enhanced Particle Swarm Optimization-Genetic Algorithm (PSO-GA), strategically punched holes are optimized on the flat sheet, allowing for the attainment of perfect parabolic shapes by controlling the chord length with a positional rod or cable. The efficacy of this approach is showcased not only through interactive finite element analysis and ray tracing software simulations but also via experimental sunlight concentration. A geometric concentration ratio of up to 145.16 is achieved, underscoring the effectiveness of this innovative concept. This approach facilitates the simple fabrication and transportation of flat mirror elements to field sites, where they can be assembled into parabolic trough concentrators, offering potential cost reductions and highly efficient solar energy solutions.

Providing a framework to optimize the sustainable construction material supply chain with the possibility of horizontal transfers

The application of Supply Chain Management (SCM) principles has gained considerable attention across various industries to enhance operational efficiency and business performance. In the construction sector, SCM can guide managers in strategic planning and foster collaboration with suppliers, leading to more effective project execution. Despite its importance, limited research has focused on designing sustainable supply chains for construction materials under uncertain conditions. This study aims to bridge this gap by introducing a robust optimization framework that incorporates sustainable development criteria, specifically the minimization of harmful environmental effects and the reduction of worker unemployment. Additionally, the research introduces an innovative concept of horizontal transfers between downstream members, which not only reduces supply deficiencies but also indirectly increases profitability for these members. This article is a part of a Doctoral dissertation. It follows a two-step approach. First, suppliers of construction materials are ranked based on sustainable development criteria using a multi-criteria decision-making method. The best-ranked supplier is then integrated into a mathematical model for optimizing the supply chain design. Given the NP-hard nature of the problem, the CPLEX 12.1 solver with the epsilon constraint method is used to solve small-scale models. For larger-scale problems, three meta-heuristic algorithms are developed: multi-objective ant-lion, multi-objective gray wolf, and multi-objective dragonfly. The results show that while both the ant-lion and gray wolf algorithms deliver comparable average performance, the gray wolf algorithm excels in terms of solution time, making it more effective for real-time problem-solving. This makes the gray wolf algorithm the most efficient choice for addressing large-scale, multi-objective supply chain challenges. This research introduces a novel framework for designing sustainable construction supply chains under uncertain conditions. By focusing on criteria such as minimizing harmful environmental effects and reducing worker unemployment, this study addresses key aspects of sustainable development. Additionally, the innovative horizontal transfer mechanism and the insights into algorithmic performance provide valuable contributions to the field, especially for real-world applications in the construction industry.

Bottom-up stripping of graphene with controlled oxidation behaviors towards supercapacitors energy storage

Due to its distinctive two-dimensional planar structure, room temperature quantum Hall effect, and high strength, graphene has garnered significant interest in the fields of energy storage and conversion. In order to achieve high efficiency in the production of graphene, electrochemical peeling has been extensively investigated. Nevertheless, the intermolecular forces between graphite layers are disrupted during ion intercalation in solution, leading to inconsistent bonding forces and low yields. In order to address the issues above, this study introduces a novel bottom-up electrochemical peeling method, wherein graphite expansion occurs above the electrolyte. By preventing contact between the peeled graphene and the electrolyte, the oxidation of graphene is significantly minimized, resulting in a substantial yield of 88 %. At the current density of 1.0 A g−1, the Go-QAS displayed 225.5 F g−1, and kept about 220.2 F g−1 after 500 cycles. The well-designed bottom-up peeling process leads to graphene nanosheets with reduced structural degradation, high purity, and excellent conductivity. This technique is expected to introduce innovative concepts for the field.

Highly Water‐Dispersible Spiropyran‐Octapeptide Supramolecules: Efficient, Multi‐processable, and Versatile Photoswitches for Time‐Dependent Dual‐Mode Encryption

AbstractWith exceptional photochromic and photoluminescent properties, spiropyrans have demonstrated significant potential for advanced information encryption and anti‐counterfeiting applications. However, its inherent water insolubility leads to incompatibility with aqueous polymers, and even more, its ease of leaching from the matrix hinders the formation of stable stimuli‐responsive platforms through direct blending with all polymers. Here, the fabrication of amphiphilic spiropyran‐octapeptide molecules is reported that can spontaneously self‐assemble into highly water‐dispersible supramolecular nanofibers in water. These assemblies exhibit universal polymer matrix compatibility while retaining the rapid photo‐responsiveness of spiropyrans. The formation of strong interactions between the supramolecular assembly and polymer chains ensures the long‐term stability of the resultant stimuli‐responsive materials in aqueous environments. These platforms fully preserve the base polymers’ processing properties, with silk fibroin as the matrix offering exceptional opportunities for constructing photo‐responsive platforms in various forms (e.g., films, gels, fibers, and coatings) with multiple functionalities using diverse solution processing techniques. Integrating distinct photochromic and photoluminescent responses within a single format without interference, combined with environmental stability and processing flexibility, enables the creation of dual‐mode, high‐security encryption devices for diverse application scenarios. The outlined strategy provides innovative concepts for developing high‐performance, versatile intelligent systems utilizing stimulus‐responsive molecules.

Proceedings of a membrane update symposium: advancements, scientific insights, and future trends for dialysis membranes for enhanced clinical outcomes in end stage kidney disease patients.

From September 6 - 8 2022, the Life/2022 Membrane Symposium was held in Frankfurt, Germany, and transmitted live to a worldwide internet audience. The event was part of the Life/Nephrology Campus initiative, a continuous educational platform for the nephrology community to expand knowledge and share expertise on contemporary topics in chronic kidney disease. We describe recent questions and advances in the field, and we underline challenges in the care of dialysis patients and opportunities for integration of new findings into clinical practice to improve patient outcomes in end stage kidney disease patients. Most patients with kidney failure are on maintenance hemodialysis (MHD). The scientific program of the symposium was developed around topics about the role, functional determinants, technical aspects, limitations, and clinical implications of membranes presently in use. International experts with clinical or technical expertise as well as scientific recognition within the nephrology community were asked to prepare their presentations based on their own experiences, perceptions, opinions, and sources of information. The symposium devoted a major portion to discussing novel approaches for improving membranes and treatment quality, including updates on innovative concepts that may could potentially transform the landscape of kidney replacement therapy for chronic kidney disease patients in the future. The intent was to provide insights into current attention points for healthcare professionals new to the field of MHD, and to test a unique forum for continuing medical education integrating physician and patient experiences to promote changes in clinical practice. Furthermore, the symposium premiered a specifically developed mixed reality holographic 3D model to demonstrate recent dialyzer innovation diminishing protein fouling on membrane surfaces. As a continuous online educational platform for scientific exchange, this Life/2022 event provided online learning opportunities with on-demand content, with all symposium lectures freely available on nephrologycampus.com.

Technological progress in central and eastern Europe: Digitalization and business innovation leaders and outsiders

Innovation and the associated digitization of the global economy are becoming the foundation of competitiveness and development. This state of affairs affects all regions and countries of the world, especially enterprises, which need to adapt to stay in the market. The situation is particularly challenging in developing countries, whose economic potential is lower than that of developed economies. Addressing this issue, the article presents the results of a study on the degree of digitization and innovation of enterprises in the countries of Central and Eastern Europe (CEE), which are among the group of developing economies. The research included independent assessments of innovation and digitization in these countries, as well as a combined assessment of both processes. It was based on a set of 17 selected indicators characterizing the processes of digitization (9) and innovation (8). The CRITIC method was used to calculate the weights of these indicators, and the TOPSIS method was used to determine the digitization and innovation indices, as well as the final digitization and innovation index. Using the results of this analysis, relationships were determined between the digitization and innovation indices, as well as between the final index (innovation and digitization) and selected economic parameters of the countries under study (CEE). The results show that companies in the studied countries are highly differentiated in terms of their digitization and innovation. The best results in both dimensions were obtained by the Czech Republic and Slovenia, while the weakest were by Latvia and Romania. In terms of business innovation, the Czech Republic and Slovenia are the best performers, while Latvia and Romania are the weakest. On the other hand, Slovenia and the Czech Republic are the leaders in business digitization, while Romania and Bulgaria are the worst performers. The remaining countries fell within the area of average development in these dimensions. The obtained results should be a valuable source of knowledge for assessing the measures taken to date in CEE countries in the field of innovation and digitization. It would also be advisable to use them in the development and implementation of economic policy and the targeting of investment activities in the EU. A major opportunity, especially for improving the innovativeness of CEE countries, could be the Open Innovation concept. Its wider implementation in these countries should improve their performance in this regard.

Study of Self-Locking Structure Based on Surface Microstructure of Dung Beetle Leg Joint.

Dung beetle leg joints exhibit a remarkable capacity to support substantial loads, which is a capability significantly influenced by their surface microstructure. The exploration of biomimetic designs inspired by the surface microstructure of these joints holds potential for the development of efficient self-locking structures. However, there is a notable absence of research focused on the surface microstructure of dung beetle leg joints. In this study, we investigated the structural characteristics of the surface microstructures present in dung beetle leg joints, identifying the presence of fish-scale-like, brush-like, and spike-like microstructures on the tibia and femur. Utilizing these surface microstructural characteristics, we designed a self-locking structure that successfully demonstrated functionality in both the rotational direction of the structure and self-locking in the reverse direction. At a temperature of 20 °C, the biomimetic closure featuring a self-locking mechanism was capable of generating a self-locking force of 18 N. The bionic intelligent joint, characterized by its unique surface microstructure, presents significant potential applications in aerospace and various engineering domains, particularly as a critical component in folding mechanisms. This research offers innovative design concepts for folding mechanisms, such as those utilized in satellite solar panels and solar panels for asteroid probes.

Expansion high payload imperceptible steganography using parameterized multilayer EMD with clock-adjustment model

Steganography is a widely used technique for protecting data privacy. In such research, the desired attributes always include undetectability, a high embedding payload, and excellent image quality for the stego-image. However, achieving both high image quality and substantial embedding payloads often involves a trade-off. The development of an algorithm that can achieve this balance remains a key focus of these studies. Although progress has been made, there is still room for improvement in optimizing this balance between embedding capacity and image quality in current research. To address this challenge, in this study, we propose a novel steganographic method called the parameterized multilayer EMD with clock adjustment model (PMEMD–CAM). In the proposed method, we generalize the embedding and extraction process, offering a more efficient and flexible way to conceal data via the innovative concept of a CAM. In CAM, the sender can predefine the parameters to determine the number of pointers on a clock and the weight of each pointer. The pixel values in a block subsequently result in an initial clock status, and the corresponding secret data yield a target clock status. The main idea of CAM is to adjust the pointers in the clock with a minimum number of cost steps to achieve the target status for hiding the secret data. Subsequently, the authorized receiver can extract the secret data based on the clock model. In addition, a multilayer embedding strategy is applied to improve the embedding payload. Experimental results demonstrate that the proposed method achieves a high capacity of 4.754 bits per pixel (bpp) with a peak signal-to-noise ratio (exceeding 30 decibels (dB), outperforming existing schemes. Furthermore, our method exhibits resilience against various steganalysis attacks.