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Fuel cell electric buses (FCBs) have proven to be a technically viable solution for transportation, owing to various advantages, such as reliability, simplicity, better energy efficiency, and quietness of operation. However, large-scale adoption of FCBs is hindered by the lack of extensive and structured infrastructure and the high cost of clean hydrogen. Many studies agree that one of the significant contributors to the lack of competitiveness of green hydrogen is the cost of electricity for its production, followed by transportation costs. On the one hand, to reduce the investment cost of the electrolyzer, high operating hours should be achieved; on the other, as the number of operating hours decreases, the impact of the electricity costs declines. This paper presents an innovative algorithm for a scalable hydrogen refuelling station (HRS) capable of successfully matching and identifying the most cost-efficient levelized cost of hydrogen (LCOH) produced via electrolysis and connected to the grid, based on the HRS components' cost curves and the hourly average electricity price profile. The objective is to identify the least-cost range of LCOH by considering both the electric energy and the investment costs associated with a hydrogen demand given by different FCB sizes and electrolyzer rated powers. In addition, sensitivity analyses have been conducted to quantify the technology cost margins, and a cost comparison between the refuelling of an FCB fleet and the recharging infrastructure required for an equivalent fleet of Battery Electric Buse (BEB) has been performed. An LCOH of around 10.5 €/kg varying from 12 €/kg (2 FCB) to 10.2 €/kg (30 FCB) has been found for the best-optimized configurations. The final major conclusion of this paper is that FCB technology is currently not economically competitive. Still, a cost contraction of the electric energy price and the electrolyzer capital investment would lead to a 50% decrease in the LCOH. Furthermore, increasing renewable energies into the grid may shift the electricity cost curve, resulting in higher prices when the BEB recharging demand is more significant. This impact, in addition to the peak power load and longer recharging times, might contribute to bridging the gap with FCBs. • Techno-economic model for the sizing of an HRS with grid-connected electrolyzer. • The widespread diffusion of H2 technology in mobility needs both reliability and cost-effectiveness. • Investigation of various electrolysers rated powers and fuel cell buses fleet size. • An action on both CAPEX and OPEX would lead to potential cost margins improvement. • It is found that the best configuration that balances the CAPEX and OPEX coincides with an LCOH ranging from 12 to 10 €/kg. [ABSTRACT FROM AUTHOR]

The positive relationship between knowledge transfer and knowledge innovation is recognized by most scholars, while knowledge heterogeneity, as a knowledge situation of the enterprise organization, affects knowledge transfer within enterprise organizations. Therefore, as a state, knowledge transfer can be regarded as a result of knowledge heterogeneity, and it becomes the intermediary state between knowledge heterogeneity and knowledge innovation. The organizational structure of individuals within an enterprise organization may affect these three elements and their interrelationships. In this paper, data are collected by means of on-the-spot investigation and a network questionnaire for analysis. The results show that the microstructure state of the individual in the enterprise organization plays a moderating role for the first three elements. The lower that the micro-restriction of the individual is, the more favorable the knowledge heterogeneity is for the inverted U-shaped impact of knowledge transfer and knowledge innovation and the more favorable the occurrence of knowledge innovation. [ABSTRACT FROM AUTHOR]

Blockchain cross-chaining is about interconnectivity and interoperability between chains and involves both physical to virtual digital aspects and cross-chaining between digital networks. During the process, the liquidity transfer of information or assets can increase the use of items with other chains, so it is worth noting that the enhancement of cross-chain liquidity is of great practical importance to cross-chain technology. In this model, Layerzero is used as the primary secure cross-chain facility to build a full-chain identity by unifying NFT-distributed autonomous cross-chain identity IDs; applying super-contract pairs to enhance cross-chain liquidity; and initiating a dynamic transaction node creditworthiness model to increase the security of the cross-chain model and its risk management. Finally, by verifying three important property metrics timeliness is improved by at least 18%, robustness is increased by at least 50.9%, and radius of convergence is reduced by at least 25%. It is verified that the liquidity cross-chain model can eliminate the authentication transition between hierarchies while saving the cross-chain time cost, as a way to truly realize the liquid interoperability between multiple chains of blockchain. [ABSTRACT FROM AUTHOR]

In order to reveal the current status and future trends of lubricant additives, this study analyzes the structured and unstructured data of 77701 lubricant additive patents recorded by Patsnap. The results show that China is the country with the largest number of patents in this field, and the United States is the main exporting country of international technology flow; the current research and development of lubricant additives is dominated by multifunctional composite additives; environmentally friendly additive compositions are the current research hotspot; and more environmentally friendly and economically degradable additives have more development potential in the future. Overall, this study provides a comprehensive understanding of the research and application of lubricant additives and contributes to the future development of the lubricant industry. [ABSTRACT FROM AUTHOR]

Multi beam forward looking sonar plays an important role in underwater detection. However, due to the complex underwater environment, unclear features, and susceptibility to noise interference, most forward looking sonar systems have poor recognition performance. The research on MFLS for underwater target detection faces some challenges. Therefore, this study proposes innovative improvements to the YOLOv5 algorithm to address the above issues. On the basis of maintaining the original YOLOv5 architecture, this improved model introduces transfer learning technology to overcome the limitation of scarce sonar image data. At the same time, by incorporating the concept of coordinate convolution, the improved model can extract features with rich positional information, significantly enhancing the model's detection ability for small underwater targets. Furthermore, in order to solve the problem of feature extraction in forward looking sonar images, this study integrates attention mechanisms. This mechanism expands the receptive field of the model and optimizes the feature learning process by highlighting key details while suppressing irrelevant information. These improvements not only enhance the recognition accuracy of the model for sonar images, but also enhance its applicability and generalization performance in different underwater environments. In response to the common problem of uneven training sample quality in forward looking sonar imaging technology, this study made a key improvement to the classic YOLOv5 algorithm. By adjusting the bounding box loss function of YOLOv5, the model's over sensitivity to low-quality samples was reduced, thereby reducing the punishment on these samples. After a series of comparative experiments, the newly proposed CCW-YOLOv5 algorithm has achieved detection accuracy in object detection mAP@0.5 Reached 85.3%, and the fastest inference speed tested on the local machine was 54 FPS, showing significant improvement and performance improvement compared to existing advanced algorithms. [ABSTRACT FROM AUTHOR]

How do technological revolutions affect the rise and fall of great powers? Scholars have long observed that major technological breakthroughs disrupt economic power balances, yet they rarely investigate how this process occurs. Existing studies establish that a nation's success in adapting to revolutionary technologies is determined by the fit between its institutions and the demands of these technologies. The standard explanation emphasizes institutions suited for monopolizing innovation in new, fast-growing industries (leading sectors). I outline an alternative pathway based on general-purpose technologies (GPTs), foundational advances that boost productivity only after an extended diffusion process across many sectors. Specifically, GPT diffusion demands institutional adaptations that widen the base of engineering skills associated with a GPT. To test this argument, I set the GPT mechanism against the leading-sector mechanism across three cases, which correspond to past industrial revolutions: Britain's rise to preeminence in the early nineteenth century; the United States's overtaking of Britain before World War I; Japan's challenge to US technological dominance in the late twentieth century. The findings support a novel explanation for technology-driven power transitions, directly bearing on how emerging technologies like AI, which some regard as driving a fourth industrial revolution, could influence a possible US–China power transition. [ABSTRACT FROM AUTHOR]

Electrochemistry has been one of the important tools in determining or evaluating vital conditions with the help of powerful and influential electrode designs. The fundamentals of electrochemical determination are simply based on direct or indirect electron transfer that occurs during the process such as the recognition of target molecules by biorecognition elements. Therefore, electrochemical biosensors have been a significant development for promising analytical applications, particularly in the field of biomedicine. In this context, electrochemical immunosensors, which can detect important biomarkers, provide many advantages with their good analytical performance and practicability. Innovation in electrochemical immunosensors continues rapidly, and non‐invasive wearable sensor technologies, especially personal equipment, come to the fore. Developments in the field of nanotechnology can easily be cited as an important driving force of these advances. Therefore, in this review, the design technology of non‐invasive immunosensors used for electrochemical biomarker detection is briefly reviewed and the contribution of nanoparticles to the efficiency of the process is examined to provide a basis for future applications. [ABSTRACT FROM AUTHOR]

This manuscript presents the use of three novel technologies for the implementation of wireless green battery-less sensors that can be used in agriculture. The three technologies, namely, additive manufacturing, energy harvesting, and wireless power transfer from airborne transmitters carried from UAVs, are considered for smart agriculture applications, and their combined use is demonstrated in a case study experiment. Additive manufacturing is exploited for the implementation of both RFID-based sensors and passive sensors based on humidity-sensitive materials. A number of energy-harvesting systems at UHF and ISM frequencies are presented, which are in the position to power platforms of wireless sensors, including humidity and temperature IC sensors used as agriculture sensors. Finally, in order to provide wireless energy to the soil-based sensors with energy harvesting features, wireless power transfer (WPT) from UAV carried transmitters is utilized. The use of these technologies can facilitate the extensive use and exploitation of battery-less wireless sensors, which are environmentally friendly and, thus, "green". Additionally, it can potentially drive precision agriculture in the next era through the implementation of a vast network of wireless green sensors which can collect and communicate data to airborne readers so as to support, the Artificial Intelligence and Machine Learning-based decision-making with data. [ABSTRACT FROM AUTHOR]

Global Navigation Satellite Systems (GNSS) offer comprehensive position, navigation, and timing (PNT) estimates worldwide. Given the growing demand for reliable location awareness in both indoor and outdoor contexts, the advent of fifth-generation mobile communication technology (5G) has enabled expansive coverage and precise positioning services. However, the power received by the signal of interest (SOI) at terminals is notably low. This can lead to significant jamming, whether intentional or unintentional, which can adversely affect positioning receivers. The diagnosis of jamming types, such as classification, assists receivers in spectrum sensing and choosing effective mitigation strategies. Traditional jamming diagnosis methodologies predominantly depend on the expertise of classification experts, often demonstrating a lack of adaptability for diverse tasks. Recently, researchers have begun utilizing convolutional neural networks to re-conceptualize a jamming diagnosis as an image classification issue, thereby augmenting recognition performance. However, in real-world scenarios, the assumptions of independent and homogeneous distributions are frequently violated. This discrepancy between the source and target distributions frequently leads to subpar model performance on the test set or an inability to procure usable evaluation samples during training. In this paper, we introduce LJCD-Net, a deep adversarial migration-based cross-domain jamming generalization diagnostic network. LJCD-Net capitalizes on a fully labeled source domain and multiple unlabeled auxiliary domains to generate shared feature representations with generalization capabilities. Initially, our paper proposes an uncertainty-guided auxiliary domain labeling weighting strategy, which estimates the multi-domain sample uncertainty to re-weight the classification loss and specify the gradient optimization direction. Subsequently, from a probabilistic distribution standpoint, the spatial constraint imposed on the cross-domain global jamming time-frequency feature distribution facilitates the optimization of collaborative objectives. These objectives include minimizing both the source domain classification loss and auxiliary domain classification loss, as well as optimizing the inter-domain marginal probability and conditional probability distribution. Experimental results demonstrate that LJCD-Net enhances the recognition accuracy and confidence compared to five other diagnostic methods. [ABSTRACT FROM AUTHOR]

To reduce the occurrence of information loss and distortion in image style transfer, a method is proposed for researching and designing image style transfer technology based on multi‐scale convolutional neural networks (CNNs) feature fusion. Initially, the VGG19 model is designed for coarse and fine‐scale networks to achieve multi‐scale CNN feature extraction of target image information. Subsequently, while setting the corresponding feature loss function, an additional least‐squares penalty parameter is introduced to balance the optimal total loss function. Finally, leveraging the characteristics of stochastic gradient descent iteration, image features are fused and reconstructed to obtain better style transfer images. Experimental evaluations utilize peak signal‐to‐noise ratio (PSNR), structural similarity index (SSIM), information entropy (IE), and mean squared error (MSE) as metrics for assessing the transferred images, comparing them with three typical image style transfer methods. Results demonstrate that the proposed method achieves optimal performance across all metrics, realizing superior image style transfer effects. [ABSTRACT FROM AUTHOR]

Early industrialization of the developed countries has enabled their leadership in technological innovation, including environmentally sound technologies. ESTs are technologies that help prevent, control, or reduce greenhouse gas emissions. Endorsed as an integral part of climate action, a binding obligation to ensure access for global south to these technologies remains missing from international environment law and international intellectual property rights law. Transfer of technology also faces certain economic barriers such as lack of infrastructure and human resources that enable adoption and absorption of ESTs. Moreover, there exists ideological differences between developed countries and developing and least developed countries regarding mechanism of technology transfer, creating an impasse in international negotiations to achieve EST transfer. In this paper the author has attempted to reframe the discussion on transfer of ESTs through a climate justice perspective. An incorporation of the practical aspects of the common but differentiated responsibilities of the developed countries into the TRIPS regime, in the form of binding obligations to technology transfer and financial assistance, or relaxations in patent protections, may provide adequate resolution. A balanced and rational approach to EST transfer, beyond the exigencies of global politics, is necessary for the continued prosperity of the Earth. [ABSTRACT FROM AUTHOR]

This research sought to develop a structured methodology for transferring resilience resources and safety innovation across industrial sectors, specifically, from aviation to maritime. As transportation sectors struggle to adapt to new economic realities and seek to prosper in new operational contexts there is a need to preserve resources and invest in change initiatives which will derive meaningful impact. A structured methodology to guide a principled transfer of safety solutions across sectors would be a sustainable method of improving the resilience of the sector. An action research approach was adopted. A five-step methodology was developed in cooperation with three maritime organisations to identify challenges and resilience resources from aviation which could be feasibly transferred and implemented. Five steps were identified as being key to a principled transfer of resilience resources from aviation to maritime. They were as follows: (1) industry comparison and database of aviation resilience resources; (2) maritime user needs and gap analysis, and resilience resources evaluation and selection; (3) scenarios production and resources mapping onto scenarios; (4) feasibility analysis; and (5) implementation plan. The results highlight the utility of combining bottom-up (identifying problems) and top-down (identifying a database of resources) approaches at the outset. A comprehensive workshop-based feasibility analysis is also key to ensuring the identified resources can be effectively implemented in the destination sector. [ABSTRACT FROM AUTHOR]

This paper studies the diffusion of battery electric vehicle (BEV) technology in Japan. The diffusion process in this study refers to both the innovation and adoption of BEV technology. While previous studies on BEV technological diffusion focus on policy selection, especially domestic policy, little is known about the connectedness between international and domestic factors in the BEV technological diffusion process. This paper aims to enrich the discussion of technology diffusion by expanding the argument that technology diffusion is not only a domestic problem but also an international relations problem using a case study of BEV technology diffusion in Japan. The findings indicate that two international factors push Japan to diffuse BEV technology: Japanese commitment to the global environmental regime and global competition in BEV manufacturing. However, the domestic institution factor hinders the BEV technology diffusion. The production structures of automobile industries and political economy relations between the automobile industry and the government further complicate the diffusion process of BEV technology. [ABSTRACT FROM AUTHOR]

This study identifies and discusses strategies for enhancing the efficiency of technology transferring from university to the industrial sector, concerning activities carried out by Technology Transfer Offices (TTOs). The study answers two research questions: (i) What barriers hamper academic research transferring to industry? (ii) What are the inbound and outbound strategies for transferring academic research results to industry? Our findings show that the main barriers that hamper technology transfer are related to organisational, technical, human, and cultural factors comprising the academic and industrial environments. Regarding strategies, our findings reveal a comprehensive list of inbound and outbound strategies that might be implemented to cope with the ambidextrous nature of the TTOs and increase technology transfer. Finally, we discuss our findings and the relationship between the main barriers and the boundary-spanning strategies to support a more effective Technology Transfer process. [ABSTRACT FROM AUTHOR]

It is important to use evidence-based programs and practices (EBPs) to address major public health issues. However, those who use EBPs in real-world settings often require support in bridging the research-to-practice gap. In the US, one of the largest systems that provides such support is the Substance Abuse and Mental Health Services Administration's (SAMHSA's) Technology Transfer Center (TTC) Network. As part of a large external evaluation of the Network, this study examined how TTCs determine which EBPs to promote and how to promote them. Using semi-structured interviews and pre-testing, we developed a "Determinants of Technology Transfer" survey that was completed by 100% of TTCs in the Network. Because the study period overlapped with the onset of the COVID-19 pandemic, we also conducted a retrospective pre/post-pandemic comparison of determinants. TTCs reported relying on a broad group of factors when selecting EBPs to disseminate and the methods to do so. Stakeholder and target audience input and needs were consistently the most important determinant (both before and during COVID-19), while some other determinants fluctuated around the pandemic (e.g., public health mandates, instructions in the funding opportunity announcements). We discuss implications of the findings for technology transfer and frame the analyses in terms of the Interactive Systems Framework for Dissemination and Implementation. [ABSTRACT FROM AUTHOR]

The global community, with coordination from the United Nations, is energized to pursue the Sustainable Development Goals (SDGs), a list of 17 important aspirations that summarize the key challenges of our era. The SDGs apply to every nation and represent an international effort to eliminate extreme poverty, ensure access to safe drinking water, strengthen food security, and produce clean and reliable energy, among other pursuits. Space technology is already being used around the world to advance progress toward the SDGs and monitor their related Indicators. This paper explores how six technologies related to space—satellite Earth observation, satellite communication, satellite navigation and positioning, human spaceflight and microgravity research, space technology transfer, and basic scientific research—are being used to realize the vision that the SDGs represent. The paper also discusses the obstacles that limit the application of these technologies for the SDGs and provides an overview of potential paths to overcome these barriers. The paper finally studies the historical and potential roles that four distinct types of entities involved in global sustainable development—governments, non- and inter-governmental organizations, entrepreneurial companies, and universities— have played or may play in the application of space technologies towards the SDGs. • Six space technology areas are shown to support the U.N. Sustainable Development Goals. • Examples of space projects that support the SDGs are found in many sectors. • New designs for technology are needed to improve effectiveness of space applications for the SDGS. [ABSTRACT FROM AUTHOR]

Our concern in this paper is the environmental 'footprinting' of food and its role as a source of technopolitical power in global food governance. Our case is the highly industrialised farmed salmon sector which currently generates metrics and carefully curated visualisations to promote this fish as a more sustainable and 'climate friendly' protein relative to animal protein produced on land. We show how these metrics and visualisations depend on an industrial production and measurement infrastructure. Significantly, this infrastructure and the metrics that it generates is being promoted as a 'climate smart' solution to small‐scale and extensive aquaculture in the Global South. Salmon aquaculture industry proposals for the transfer of technology from salmon farming to global aquaculture are explicitly articulated in global food governance and other institutional spaces. While there may be frictions in the transfer of salmon aquaculture's infrastructure of measurement to aquaculture in the Global South, our analysis suggests that environmental footprinting of food—and its associated measurement infrastructure—may be an emerging source of technopolitical power in increasingly corporatised global food governance systems. [ABSTRACT FROM AUTHOR]

Concept drift is one of the most prominent issues in streaming data that machine learning models need to address. Most of the research in the field of concept drift targets updating the prediction model for recovery from concept drift. A little effort has been put into the development of a learning system that can learn drifting concepts with minimal overhead. In this paper, a dynamic ensemble classifier is designed to detect and adapt the concept drifts in streaming data. Thereupon, a novel approach- Selective Ensemble using Transfer Learning (SETL) is proposed that has the ability to adapt the new concept of data. It employs a transfer learning and a weighted majority voting scheme to enable resource optimization. It also overcomes the issues, such as negative transfer and overfitting that may occur during the process of transfer learning. The experiments are performed using real-world open-source datasets. The results indicate that SETL outperforms existing state-of-the-art algorithms for most of the datasets in terms of performance metrics such as Accuracy, F1-score, Kappa measure, precision and recall. [ABSTRACT FROM AUTHOR]

In the wave of the digital era, Building Information Modelling (BIM) has emerged as the primary tool for intelligent construction and digital transformation in the Architecture, Engineering, and Construction (AEC) industry. China's focus on policy guidance for the dissemination and application of BIM technology has promoted high-quality development and technological innovation in the AEC industry. However, few studies have described the multi-dimensional evolution picture of BIM technology policy in China, and lack of effective grasp and prediction of policy evolution law and future direction. An improved policy quantitative analysis framework is built using natural language processing (NLP) based on deep learning in this paper. The dynamic characteristics of 242 Chinese BIM technology policy documents from 1998 to 2022 in the PKULAW database are quantitatively analyzed by the framework, and the four-stage integrated evolution of Chinese BIM technology policy is quantitatively mapped in a visual form through network analysis and dynamic topic model (DTM). Furthermore, this research conducts a comprehensive discussion from three dimensions, providing valuable insights for policy makers and industry participants in China. The findings contribute to the deep integration of policy optimization and the construction industry, while also aiming to share China's experience in BIM technology governance with other countries and regions. Ultimately, this study seeks to support the global AEC industry in its digital transformation and development by offering valuable knowledge and perspectives. [ABSTRACT FROM AUTHOR]

The push towards research commercialisation at universities has highlighted the importance of intellectual property (IP) policies in fostering innovation and guiding and managing research commercialisation activities. This paper undertakes a content analysis of intellectual property policies of all (37) Australian public universities, focusing on policy objectives, definition of IP, ownership of IP created by different creators, and distribution of net commercialisation revenues. It is found that all universities assert ownership over staff-created IP, particularly when related to employment or utilisation of university resources. For students, policies tend to balance their rights with university interests, with nuanced approaches for different types of student participation, but the focus of most policies was on postgraduate students engaging in research activities. While some policies had clear arrangements for IP created by visitors and affiliates and Indigenous cultural and intellectual property (ICIP), about a quarter of policies did not specify arrangements for these groups. Revenue sharing arrangements vary but generally award something between a third to a half of net revenue to creators, to both acknowledge their contribution and incentivise further innovation. Policies included a broad spectrum of objectives, from protecting and commercialising IP to fostering innovation and societal benefit, reflecting varying strategies across the higher education sector. Policies could benefit from further clarity in certain areas such as the rights of students or other creator groups. Research is needed to assess the effectiveness of these policies and their influence on innovation and commercialisation activities. [ABSTRACT FROM AUTHOR]

This contribution discusses salient aspects of the development of ceramics technology from its invention to the present, and the role ceramics have played during the cultural development and technological progress of ancient and modern societies. The conjecture is being advanced that the transformation of ceramic production modes from holistic, that is, individualistic processes to prescriptive, that is, cooperative industrially determined technologies had a profound and lasting impact on the social, economic, and cultural fabric of all societies. In addition, the chaotic and thus, nondeterministic interaction of ceramic technology and society, and the transfer of information among potters will be described in terms of the concept of strange attractors as well as sets of self‐normalizing ‘memes’ (ideas) in a Lamarckian and/or Darwinian mode. Such specific ideas drive cultural and, by inference, technological evolution of societies. [ABSTRACT FROM AUTHOR]

The article reappraises nature of technology transfer in a colonial context by underlining how the colonised mediated and shaped what was ostensibly an imposition by the imperial administration. This wider point is illustrated by demonstrating the ways in which in the late nineteenth and early twentieth centuries, different groups of Indians used newly introduced railways to reconceptualise meanings of travel by adding new categories of travel while significantly modifying the extant ones. Crucially deviating from both ‘technology as imperialism’ and ‘technology as subversion’ historiographical paradigms, this article argues for a more nuanced appraisal of technology transfer, especially emphasising the role of users in shaping the impact of technology. Examining a diverse range of sources, viz., railway records (Annual Railway Reports and railway passenger statistics), newspaper reports and travelogues and pamphlets written by Indian railway travellers, the article claims Indians not only mediated the impact of trains on travel in late colonial India; but they shaped the outcome of this technology transfer in ways that reveals agency and remarkable involvement with a new mode of transit. In short, the article demonstrates dynamic interaction between imperial policies and responses of the colonised through the lens of technology transfer. [ABSTRACT FROM AUTHOR]

Mass transfer technology for large quantities of tiny substances, such as electronic chips and drug particles, plays a crucial role in many industries. This study proposes a transferring system for large quantities of small objects based on the synergism of triboelectric nanogenerators (TENGs) and photo‐responsive dielectric materials. TENG device can provide an output voltage of over 8 kV within a rotation time of 40 ms and the titanium oxide phthalocyanine (TiOPc) photoconductive films are fabricated as the photo‐responsive interface, in order to match the output impedance of TENG. The transfer system enables a maximum adsorption load of 98 mg mm−2, which is enough for handling all common electronics chips/wafers. Under the stimulation of laser light, the conductivity of the TiOPc interface can be increased by two orders of magnitude within 1 ms, which leads to the vanish of the surface potential on the laser spot and the release of patterned or pointed object. This photo‐responsive strategy can achieve both large quantity transfer of tiny objects and highly selective release of the element at designed position. This collaborative mechanism of electrostatic force and photoconductivity provides a different approach for realizing efficient and precise Mass transfer system of semiconductor and chip industry. [ABSTRACT FROM AUTHOR]

The capitalisation on and transfer of technological, engineering and scientific knowledge associated with empirical know-how is an important issue for the sustainability and development of manufacturing. Indeed, certain sectors of industry are facing the increasing ageing of the labour force, recruitment difficulties and high staff turnover, leading to a loss of knowledge and know-how. In a context of numerical and digital transition and the migration of processes to industry 4.0, one of major challenges manufacturers face today is their capacity to build intelligent platforms for acquiring, storing and transferring their know-how and knowledge. It is crucial to create new media and tools for staff training and development capable of capturing knowledge and reusing it to create a project history through expertise and data collection. This paper presents the methodology and guidelines for implementing electronic knowledge books (eK-Books), along with their uses. The eK-Book is a semantic web-based hypertext medium (channel) allowing stakeholders to capitalise on, structure and transfer knowledge by using concept maps, process maps, influence graphs, downloadable documents, web pages and hypermedia knowledge sheets. They are intended for engineers, expert or novice technicians, manufacturers, sector coordinators and plant managers, as well as trainers and learners. They are usable and manageable in all types of environments and with different levels of accessibility. This paper highlights (1) the transfer knowledge capacity of eK-Books and (2) their usability in two agri-food sectors namely (1) the cheese sector with protected designation of origin (PDO) and protected geographical indication (PGI), and (2) the butchery and cold meat sectors. [ABSTRACT FROM AUTHOR]

Unmanned underwater vehicles (UUVs) are key technologies to conduct preventive inspection and maintenance tasks in offshore renewable energy plants. Making such vehicles autonomous would lead to benefits such as improved availability, cost reduction and carbon emission minimization. However, some technological aspects, including the powering of these devices, remain with a long way to go. In this context, underwater wireless power transfer (UWPT) solutions have potential to overcome UUV powering drawbacks. Considering the relevance of this topic for offshore renewable plants, this work aims to provide a comprehensive summary of the state of the art regarding UPWT technologies. A technology intelligence study is conducted by means of a bibliographical survey. Regarding underwater wireless power transfer, the main methods are reviewed, and it is concluded that inductive wireless power transfer (IWPT) technologies have the most potential. These inductive systems are described, and their challenges in underwater environments are presented. A review of the underwater IWPT experiments and applications is conducted, and innovative solutions are listed. Achieving efficient and reliable UWPT technologies is not trivial, but significant progress is identified. Generally, the latest solutions exhibit efficiencies between 88% and 93% in laboratory settings, with power ratings reaching up to 1–3 kW. Based on the assessment, a power transfer within the range of 1 kW appears to be feasible and may be sufficient to operate small UUVs. However, work-class UUVs require at least a tenfold power increase. Thus, although UPWT has advanced significantly, further research is required to industrially establish these technologies. [ABSTRACT FROM AUTHOR]

Narrowband afterglow materials display interesting functions in high-quality anti-counterfeiting and multiplexed bioimaging. However, there is still a limited exploration of these afterglow materials, especially for those with a full width at half maxima (FWHM) around 30 nm. Here, we report the fabrication of narrowband organic/inorganic hybrid afterglow materials via energy transfer technology. Coronene (Cor) with a long phosphorescence feature and broad phosphorescence band is selected as the donor for energy transfer, and inorganic quantum dots (QDs) of CdSe/ZnS with a narrowband emission are used as acceptors. Upon doping into the organic matrix, the resultant three-component materials exhibit a narrowband afterglow with an afterglow lifetime of approximately 3.4 s and an FWHM of 31 nm. The afterglow wavelength of the afterglow materials can be controlled by the QDs. This work based on organic/inorganic hybrids provides a facile approach for developing multicolor and narrowband afterglow materials, as well as opens a new way for expanding the features of organic afterglow for multifunctional applications. It is expected to rely on narrowband afterglow emitters to solve the "spectrum congestion" problem of high-density information storage in optical anti-counterfeiting and information encryption. [ABSTRACT FROM AUTHOR]

BACKGROUND: Exosomes have become one of the frontiers of biomedical research in recent years because of their promising applications in clinical diagnosis and therapy. OBJECTIVE: To reveal the basic research and technology development trend of exosomes at home and abroad, and provide suggestions for related scientific and technological research and development in China. METHODS: This paper presented a quantitative analysis of the overall research and development situation, the frontier hotspots and future development trends in this research area by means of bibliometric methods and tools. RESULTS AND CONCLUSION: The research and development hotspots in this area have entered a high growth phase with the application of new tools and methods. Many new technologies and products are facing clinical applications and markets with the development of a large number of clinical translation experiments. Comparative analysis at home and abroad reveals that China has made more remarkable achievements in basic research in this field, but there are still weaknesses in the possession of independent intellectual property rights, clinical technology translation, and regulatory system standardization and management, which need to be further strengthened in the future. [ABSTRACT FROM AUTHOR]

The development of urbanization has brought new challenges to the ecological environment, and the promotion of green technology innovation and development is widely recognized as an essential method to achieve cities' economic benefits and environmental protection. This paper examines whether the new urbanization pilot policies (NUP) increase green technology innovation (GTI) from both theoretical and empirical perspectives. This paper examines the impact of new urbanization on GTI by analyzing data from 285 cities in China between 2010 and 2021, using the multi-period DID model with the implementation of NUP as an exogenous policy shock. The study results indicate that NUP significantly affects GTI, and the conclusion still holds after the parallel trend test, placebo test, and other robustness tests. Heterogeneity analysis shows that the NUP significantly enhances GTI in low environmental pollution, non-resource-based, Medium-sized, and Central Region cities. The test of moderating effect shows that NUP has a "linkage effect" with the government's environmental attention, financial investment in innovation, and regional talent pooling. The findings of this paper provide empirical evidence and decision-making reference for promoting NUP and sustainable development of cities. [ABSTRACT FROM AUTHOR]

Assistive Technologies encompass a wide array of products, services, healthcare standards, and the systems that support them. Product/market fit is necessary for a technology to be transferred successfully. Current tools lack variables that are key to technology transfer, and current trainings do not have a validated tool to assess the effectiveness of a training, increasing innovators' readiness for technology transfer. The goal was to develop a tool to evaluate the readiness of a technology by incorporating other models and focusing beyond just commercialization. The development involved five stages: 1. Review of current tools used in technology transfer in academic, government, and industry settings; 2. Development of the draft version of the tool with internal review; 3. Alpha version review and refinement, 4. Content validation of the tool's beta version; 5. Assessment of the readiness tool for reliability and preparedness for wide-use dissemination. The tool was revised and validated to 6 subscales and 25 items. The assistive technology subscale was removed from the final version to eliminate repetitive questions and taking into consideration that the tool could be used across technologies. We developed a flexible assessment tool that looked beyond just commercial success and considered the problem being solved, implications on or input from stakeholders, and sustainability of a technology. The resulting product, the Technology Translation Readiness Assessment Tool (TTRAT)TM, has the potential to be used to evaluate a broad range of technologies and assess the success of training programs. Quality of life can be substantially impacted when an assistive technology does not meet the needs of an end-user. Thus, effective Assistive Technology Tech Transfer (ATTT) is needed. The use of the TTRAT may help to inform NIDILRR and other funding agencies that invest in rehabilitation technology development on the overall readiness of a technology, but also the impact of the funding on technology readiness. The TTRAT may help to educate novice rehabilitation technology innovators on appropriate considerations for not only technology readiness, but also general translation best practices like assembling a diverse team with appropriate skillsets, understanding of the market and its size, and sustainability strategies. [ABSTRACT FROM AUTHOR]

In recent years, as China experiences economic expansion and its corporations become more global, it has notably become a central hub for cross-border mergers and acquisitions (M&A) on the world stage. The Chinese government, in tandem, leverages these international M&A operations to drive industrial transformation and progress in technology. This research investigates the role of China's industrial policies in shaping cross-border M&A activities by examining recent instances. Findings indicate that relaxing financial barriers and applying specific industrial tactics bolster companies' abilities to secure funding, consequently energizing cross-border M&A initiatives. Several firms in these international mergers and acquisitions are intricately connected to political strategies, markedly affecting the formulation of industrial policies. This assertion is corroborated through the analysis of relevant statistical evidence. The study methodically collects and scrutinizes data to quantitatively depict the current landscape and influencing elements of cross-border M&A, thus providing concrete evidence for policy and business strategy formulation. [ABSTRACT FROM AUTHOR]

The 2030 Agenda for Sustainable Development Goals of the United Nations puts forward a transformational vision to cope with food security, nutrition, and health challenges, in which sweet potato can play an important role. Globally, sweet potato production is valued at $53.83 billion. The Agricultural Research Council of South Africa (ARC) sweet potato research and development (R&D) program over the past seven decades delivered 31 genetically improved cultivars via demand‐led breeding, managed the collection and maintenance of 375 accessions, contributed toward the optimization of cultivation practices, developed crop protection and diagnostic services, and provided streamlined seed systems and technology transfer in processing and enterprise development. The ARC's work is part of a large number of interdependent global programs committed to improving livelihoods and nutrition through sweet potato. This review shares and analyses major achievements, highlights unique research contributions achieved through partnerships, and discusses bottlenecks on funding and uptake of technologies. New research imperatives will involve root phenotyping, employing marker‐based technologies, and genome‐wide association studies through new funding received recently. Exploration of the commercialization potential of processed products made from orange‐fleshed sweet potato will be a major focus of the R&D program. Expansion of partnerships, marketing, and financing will be important for future contribution of sweet potato to the economy. Core Ideas: Sweet potato has great potential to address several Sustainable Development Goals of the United Nations.A comprehensive sweet potato research and development program described herein provided technology across the full value chain.Screening methods for wilt disease, nematodes, protein content, virus, and crop development are highlighted.Expansion of partnerships and financing is essential to retain research momentum.Modern technologies must be key in new research imperatives.This article provides important lessons for public breeding efforts. [ABSTRACT FROM AUTHOR]

The 'Common but Differentiated Responsibilities and Respective Capabilities' ('CBDRC') is a traditional yet rather controversial principle of International Law. It stems from the need to establish an equitable approach to global concerns through non-reciprocal obligations. Despite the quasi-universal acceptance of the principle since its first appearance in the 1992 Rio Declaration on Environment and Development, certain legal challenges persist regarding its formal status, the rationale for the differentiation of legal obligations, and its implementation. The CBDRCs principle continues to play a crucial role in the ongoing post-pandemic negotiations aimed at reshaping the international health legal architecture. This article argues that translating the principle of CBDRCs into operational tools for a comprehensive system of pandemic prevention, preparedness and response, could address inequalities between the Global North and the Global South, thus changing the narrative on fairness in international health law. [ABSTRACT FROM AUTHOR]

The authors present the design, fabrication and testing of a W‐band monopulse antenna. This antenna consists of three main building blocks: an array with 48 × 48 slots, a tapered corporate‐feed network and a comparator. The comparator has four input ports to generate sum and difference patterns in orthogonal cardinal planes for monopulse operation. A novel octuple excitation is adopted for the corporate network to achieve a side lobe level lower than −20 dB for the sum patterns and simultaneously reduce drastically the manufacturing complexity. Diffusion bonding technology is used for fabrication. Twenty‐four etched copper sheets with a thickness of 0.2 mm are stacked to realise the prototype. The total size of the antenna is 40.76×40.76×1.51λ03 $40.76\times 40.76\times 1.51{\lambda }_{0}^{3}$, with λ0 being the wavelength at the centre frequency (94 GHz). The antenna presents an isolation better than 12 dB among the input ports in the 84–100 GHz band. The realised measured gain is 40.7 dBi at 94 GHz. The measured 3‐dB gain bandwidth is 17.4%. The difference patterns at 94.0 GHz present null depths of −24.0, −18.0, −17.5, and −17.4 dB, in the E‐, H‐, 45°‐, and 135°‐planes, respectively. [ABSTRACT FROM AUTHOR]

A slew of economic, environmental, and social concerns has pushed policymakers and governments to embrace renewable energy (RE) technologies in order to ensure a sustainable energy future. RE technologies have a beneficial effect on the environment and social well-being. Therefore, this study presents a method for systematically determining and ranking the benefits of adopting RE technologies in remote areas and possible solutions. The present analysis is structured into four distinct levels. The benefits of RE technologies were identified through a comprehensive review of relevant literature. The Delphi technique was employed to reach a consensus and classify the advantages. Fourteen benefits were determined and classified according to seven primary criteria. Furthermore, the Fuzzy Analytic Hierarchy Process was employed to determine the weights and rankings. The Fuzzy VIekriterijumsko KOmpromisno Rangiranje method was ultimately used to evaluate the potential alternatives. The integrated method result significantly reveals that the environmental criteria are the most critical factor, with a weight of (0.1727), and are followed by the quality of energy aspect, with a weight of (0.1617). Moreover, the global weights show that Sustainability is ranked highest, followed by Skill development, then the other sub-benefits within different categories. These two benefits have relative weights of (9.9164%) and (9.4924%), respectively. Furthermore, the most effective solution facilitating local and foreign investors was the most promising among the four recommended alternatives. The quote has proven that it benefits the government and policymakers in deploying RE technologies and resolving energy challenges in remote areas of developing nations like Pakistan. [ABSTRACT FROM AUTHOR]

Mechanical bruise is one of the most crucial factors affecting the quality of pears, which has a huge influence on postharvest transportation, storage, and sale of pears. To rapidly detect early bruises of pears across different bruise types, hyperspectral imaging technology coupled with transfer learning methods was performed in this study. Two transfer learning methods, that is, transfer component analysis (TCA) and manifold embedded distribution alignment (MEDA), were applied for two tasks (impact bruise → crush bruise, crush bruise → impact bruise). Supporting vector machine (SVM) was set as a baseline to conduct analysis and comparison of the transferability of the models. The result showed that, for task 1 (impact bruise → crush bruise), MEDA and TCA‐SVM model achieved a classification accuracy of 93.33% and 91.11% in target domain, individually. For task 2 (crush bruise →impact bruise), MEDA and TCA‐SVM model achieved an accuracy of 88.89% and 85.19% in target domain, respectively. Both the two models improved the accuracy compared with SVM models (84.44% for task 1; 77.04% for task 2). Overall, the results indicated that transfer learning approaches could perform pear bruise detection across different bruise types. Hyperspectral imaging in combination with transfer learning methods is a promising possibility for the efficient and cost‐saving field detection of fruit bruises among different bruise types. Practical Application: The production and export of pears are faced with problems of mechanical damage due to vibration, collision, impact, and other factors, which cause chemical changes in color, odor, and taste. Sometimes the bruise was too slight to be ignored which would infect with other fruits in the future. In this study, we used hyperspectral imaging combined with transfer learning method could detect these slight bruises caused by different factors. Distinguishing different types of damage can provide a reference for quick judgment of the process causing damage and take prompt measures to reduce economic losses. [ABSTRACT FROM AUTHOR]

With the proliferation of electronic devices and electricity-based mobility solutions, the significance of wireless power transfer technology has increased substantially. However, ensuring secure and reliable power transmission to authorized users remains a significant challenge. Addressing this complex issue requires an integrated approach that balances efficiency, stability, and security considerations. While current efforts primarily focus on improving charging efficiency and user convenience, integrating robust security measures into wireless charging infrastructure is challenging due to its inherently open nature and susceptibility to external interference. Technical advancements are required to strengthen the security of the wireless charging infrastructure; however, these should be balanced with power loss management. This study tackles two core issues: the increasing hardware requirements for billing system authentication protocols and the interception of wireless charging signals by unauthorized users, leading to power theft and subsequent losses. To address these challenges, we propose a mechanism termed "LazyFrog". This mechanism dynamically adjusts the frequency hopping schedule, activating frequency changes only in response to detected threats during remote charging or upon identifying unauthorized access attempts. The proposed mechanism compares the expected power reception at the device with the actual power supplied by the charging station, enabling the detection of abnormal power losses. By minimizing unnecessary frequency changes and optimizing energy consumption, LazyFrog reduces hardware requirements. Moreover, we have implemented a relative distance estimation mechanism to facilitate efficient power transfer as wireless devices move within the charging environment. With these features, LazyFrog demonstrates a secure, flexible, and energy-efficient wireless charging system ready for practical application. [ABSTRACT FROM AUTHOR]

A field study with varying nitrogen (N) rates (0-150 kg N ha-1) was conducted in Ludhiana (Punjab, India) in a randomized complete block design in three consecutive baby corn seasons to quantify and mitigate N losses to the environment. The nitrous oxide (N2O) flux emissions were measured at 2, 4, 8, 16, and 24 days after each fertilizer N split application. The leachate N losses were estimated by analyzing ammonium and nitrate ion content. Fertilizer N surplus to crop requirement explained 94.1% (spring), 95.9% (summer), and 95.5% (winter) variation in the area-scaled N losses (N2O, leachate). Lower fertilizer N usage by plants at early growth stages (upto V6 stage) resulted in higher N losses within ten days after the first fertilizer application. Carbon equivalent emissions followed the trend summer> spring>winter. Temporal variations during the monitoring seasons influenced the cob and stover yield in response to fertilizer N. On average, 67.9% of the applied fertilizer N was taken up by plants, 4.7% was lost via N leaching, 2.7% escaped as N2O, 3.2% accumulated in the soil profile, and 21.5% remained unaccounted. Sensing-based N application significantly improved N recovery efficiency by 51.2%, mitigated N emissions by 45.4%, and N leaching by 69.3% in comparison with fixed-time blanket fertilizer N topdressings. Fertilizer N management using PAU-LCC provided an economical and farmer-friendly solution to achieve a significant reduction in N losses while sustaining productivity. Further validation and transfer of technology to on-farm locations are needed to benefit from this work. [ABSTRACT FROM AUTHOR]

Following the West, China exhibits a proactive attitude and conservative actions to developing entrepreneurial universities. This article deconstructs such a paradoxical approach by analysing the scholarly literature, policy discourses, and empirical data and their various perceptions of entrepreneurial universities in the Greater Bay Area (GBA). We conducted 71 interviews in four case universities to obtain empirical data for triangulation with the literature and policies. Our main research findings include the following: (1) there is a desire to introduce the concept of entrepreneurial universities from the West, along with their characteristics and aims; (2) China's policy discourse of excellence and pragmatism affects entrepreneurship education and technology transfer; and (3) an emerging identity of entrepreneurial universities is constrained by attitudes and barriers at the institutional level. China's perceptions and practices reflect a lack of sustainability of and fragmented approach to developing entrepreneurial universities, with strong implications for establishing entrepreneurial universities elsewhere. [ABSTRACT FROM AUTHOR]

At the end of the 1970s, the People's Republic of China (PRC) promoted policies to attract investments from the developed capitalist world, aiming for technological transfer and offering a profitable environment in exchange. Although the TNC capital, know-how, and technology have been key factors for Chinese development, the State has planned and regulated those investments, so they can be aligned with an autonomous project of development, avoiding the classic centre-periphery dependency relationship. This paper analysis focuses on the Five-Year Plans, and the regulation policy laws for inward investment. At the end we analyse the FDI data, which allowed us to identify the main changes and distinct phases of the development of FDI and the State policy. [ABSTRACT FROM AUTHOR]

The surge in economic and human development has led to increasing concerns about environmental degradation, thus necessitating effective strategies to enhance sustainability and environmental quality. Therefore, this study empirically examines the impact of environmental fiscal policies, environmental technologies, and research and development (R&D) expenditures on achieving environmental sustainability in the G7 countries. Using advanced econometric techniques, including the Cross-Sectionally Augmented Autoregressive Distributed Lags (CS-ARDL) model and the Dynamic Common Correlated Effects (DCCE) approach, the study identifies both short-run and long-run correlations between the aforementioned variables and their impact on greenhouse gas (GHG) emissions. Our findings confirm the inverted U-shaped Kuznets Curve relationship and reinforce the previous literature on the complex dynamics between economic growth and GHG emissions specific to developed countries. The research also supports the effectiveness of well-designed environmental taxes in reducing environmental degradation and GHG emissions, consistent with and extending existing studies in this area. In addition, the study provides empirical evidence of the critical role of environmental technologies and targeted R&D expenditures in improving environmental quality. In terms of policy implications, our research underscores the urgency for policymakers in the G7 countries to fine-tune environmental taxation mechanisms and increase investment in sustainable technological solutions. Specific recommendations include the development of more efficient tax systems that adhere to the polluter-pays principle, as well as financial incentives such as tax credits and subsidies aimed at accelerating green technology adoption and innovation. In doing so, the study seeks to contribute to the broader discourse on environmental policy and sustainable development, providing valuable perspectives for both the academic community and policy actors. [ABSTRACT FROM AUTHOR]

This paper presents a Fuzzy-QFD model to support the selection of startups to participate in acceleration programs. It proposes to model the selection process by Startup Selection relating the technology transfer and the innovative business modelling. The study provides a quantitative analysis to identify the best startups for participation in accelerated programs. To achieve such a goal, the model uses a multi-criteria decision-making based on QFD (Quality Function Deployment). This study is a pioneer in presenting a model that prioritises the selection of startups by using technology transfer criteria and business modelling components. The model was applied in an acceleration program in Brazilian, and the results indicate that the model is able to rank the companies by presenting which startups stand out. Therefore, the method can be used in prioritisation problems or in the selection of companies to participate in acceleration programs that hold technology transfer in their activities. [ABSTRACT FROM AUTHOR]

The objectives of this mixed-methods study were to gather survey and interview data about the barriers and facilitators from grantees funded by the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR) and to extract themes that could inform program changes that would increase technology translation (TT) success in assistive technology (AT). We developed a TT Barriers and Facilitators survey consisting of Likert scale and multiple-choice questions about barriers and facilitators to TT. With survey respondents who were willing, we conducting a semi-structured interview and asked pointed questions to expand upon survey response rankings and perceived barriers and facilitators. The questions were framed to explore the grantee's personal experience with ATTT and what helped and hindered their individualised processes. Across survey and interview respondents, the three most common themes when exploring the barriers and facilitators of TT were funding, incentives, and collaboration. Results indicate that there is a need for increased collaboration and access to additional resources such as funding for pilot grants, support to assess technology marketability, help to navigate regulatory and legal aspects, and assistance in establishing goals to help grantees successfully transfer assistive technologies to consumers. A large amount of research and development into assistive technology does not lead to tech transfer which means that these technologies are not getting to the people that need them. Educating tech transfer offices at universities about how to transfer AT would improve outcomes greatly. Creating a community of practice where grantees can find academic or industry partners would also increase the likelihood of tech transfer. Some tools to catalyse these improvements are: mentoring, access to consultants, podcasts, and online training. [ABSTRACT FROM AUTHOR]

This work deals with the investigation and characterization of Ti6Al4V parts produced with an intriguing manufacturing process belonging to the Wire Arc Additive Manufacturing (WAAM) family: the Cold Metal Transfer technology (CMT). Wall‐shaped parts were produced according to different process parameters, namely the wire feed speed and voltage–current combinations, leading to different energy inputs. The parts were characterized in terms of surface morphology, microhardness, microstructure, tensile properties, and fatigue crack growth. The results suggested that the investigated deposition parameters led to similar results. Moreover, the mechanical and fatigue crack growth behavior was in line with parts of the same alloy produced through other manufacturing routes, whereas the microstructure type was the result of the fast cooling of the molten material. Finally, considering the simple system adopted to avoid oxidation during the deposition stage, the results suggested that CMT is a promising manufacturing technique for titanium alloy semifinished parts. Highlights: Wall‐like parts made of Ti6Al4V alloy were produced through WAAM‐CMT technologySound parts with minimum oxidation were produced through a simple enveloping systemThe parts had properties similar to those of more traditional manufacturing routesThe microstructure, tensile, and fatigue crack growth behavior were quite isotropic [ABSTRACT FROM AUTHOR]

This paper examines how latecomer firms manage to achieve industrial upgrading through strategic coupling with global lead firms in automotive production networks. Drawing upon the example of the Guangzhou Automotive Corporation in southern China, this paper theorizes 'cross‐scalar tension' as a key factor to explain why the four cases of strategic coupling between lead firms, the same domestic firm and state ended in different results, from decoupling to a sustainable coupling with local upgrading. This paper contributes to the pertinent literature by demonstrating that cross‐scalar tension is inherent to the nature of global production networks, and unreconciled tension concerning different corporate strategies on technological transfer, localization and product development could lead to decoupling. Importantly, good coordination and matching on corporate strategies between lead and domestic firms could relieve cross‐scalar tensions, thus fostering local industrial upgrading and sustainable strategic coupling. [ABSTRACT FROM AUTHOR]

The brain‐computer interface (BCI) enables individuals with impairments to interact with the real world without relying on the neuromuscular pathway. BCI leverages artificial intelligence (AI) models for control. It can capture brain activity patterns associated with mental processes and convert them into commands for actuators. One promising application of BCI is in rehabilitation centres. When compared to traditional methods integrated with machine learning (ML) approaches that were initially explored in the past decade, there is a relatively limited number of studies utilizing deep learning (DL) approaches in BCI applications. A novel approach has been developed for the automatic recognition of motor imagery (MI) tasks. This article introduces the improved sparrow search algorithm with deep transfer learning‐based EEG motor imagery classification (ISSADTL‐EEGMIC) algorithm for BCIs. The presented ISSADTL‐EEGMIC algorithm primarily focuses on the automated classification of motor imagery tasks. To achieve this, the ISSADTL‐EEGMIC method first preprocesses EEG signals using the wavelet packet decomposition (WPD) technique. Additionally, it employs the neural architecture search network (NASNet) technique for feature extraction. Moreover, the ISSADTL‐EEGMIC model performs the classification process using the stacked sparse autoencoder (SSAE) model. Furthermore, hyperparameter optimization of the SSAE model is performed using the ISSA technique, which helps achieve maximum classification performance. The results from the simulation of the ISSADTL‐EEGMIC algorithm have been examined using two benchmark datasets. The experimental findings suggest that it outperforms recent approaches in terms of performance. [ABSTRACT FROM AUTHOR]

Single Image Super-Resolution (SISR) for image enhancement enables the generation of high spatial resolution in Remote Sensing (RS) images without incurring additional costs. This approach offers a practical solution to obtain high-resolution RS images, addressing challenges posed by the expense of acquisition equipment and unpredictable weather conditions. To address the over-smoothing of the previous SISR models, the diffusion model has been incorporated into RS SISR to generate Super-Resolution (SR) images with enhanced textural details. In this paper, we propose a Diffusion model with Adversarial Learning Strategy (DiffALS) to refine the generative capability of the diffusion model. DiffALS integrates an additional Noise Discriminator (ND) into the training process, employing an adversarial learning strategy on the data distribution learning. This ND guides noise prediction by considering the general correspondence between the noisy image in each step, thereby enhancing the diversity of generated data and the detailed texture prediction of the diffusion model. Furthermore, considering that the diffusion model may exhibit suboptimal performance on traditional pixel-level metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM), we showcase the effectiveness of DiffALS through downstream semantic segmentation applications. Extensive experiments demonstrate that the proposed model achieves remarkable accuracy and notable visual enhancements. Compared to other state-of-the-art methods, our model establishes an improvement of 189 for Fréchet Inception Distance (FID) and 0.002 for Learned Perceptual Image Patch Similarity (LPIPS) in a SR dataset, namely Alsat, and achieves improvements of 0.4%, 0.3%, and 0.2% for F1 score, MIoU, and Accuracy, respectively, in a segmentation dataset, namely Vaihingen. [ABSTRACT FROM AUTHOR]