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Agricultural socialized service is gradually emerging as a new stimulus for enhancing the agricultural production environment. However, their precise impact on improving the agricultural ecological environment and promoting the green development of agriculture remains incompletely understood. Therefore, leveraging panel data spanning from 2003 to 2020 across 31 provinces in China, this study utilizes the bidirectional fixed effect model, moderating effect model, and spatial Durbin model to systematically assess the influence of agricultural socialized services on agricultural green development and its spatial ramifications. The findings show that (I) agricultural socialized services significantly contribute to promoting agricultural green development, particularly in regions with lower aging demographics. (II) The application of the spatial Durbin model reveals that this promotional effect does not exhibit significant spatial spillover effect. (III) The role of agricultural socialized services in fostering agricultural green development can be significantly enhanced by advancements in land transfer, agricultural technological innovations, and the improvement of rural human capital. In conclusion, the study provides a set of policy recommendations that include government financial support, facilitating land transfer, improving rural education and technical training, and promoting green production technologies to effectively promote agricultural green development. [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]

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]

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]

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]

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]

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]

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]

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]

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]

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 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]

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]

This article discusses the institutional frameworks that guide research integrity and security in universities in Kenya, with a focus on the protection of intellectual property (IP) and the management of technology transfer. The expansion of Kenya's higher education system has led to an increased emphasis on universities contributing to solving social and environmental challenges and generating economically relevant knowledge. However, universities face challenges in ensuring research integrity and security, particularly in STEM subjects and commercially sensitive research areas. The article highlights the need for universities to establish research compliance structures and implement policies and guidelines to protect IP and manage technology transfer. Recommendations include sensitizing faculty and administration on potential risks, providing effective tools for research administrators, and implementing research integrity and security education and training programs. The study was approved by the Kenyatta University Ethics Review Committee and supported by CRDF Global and CNS. [Extracted from the article]

Literature on technology transfer to Africa is dominated by studies on agribusiness, military technology, information and communication technology, energy, climate change, health, and manufacturing, while it is scanty on others like transport infrastructure. In this article, we reviewed literature and carried out key informant interviews to collect data on technology transfer for Chinese-built roads in Kenya. Our objective was to examine the extent of technology transfer from Chinese multinational corporations to Kenyan institutions and organizations. We established that there was little technology transfer mostly because of Kenya's internal obstacles such as inadequate absorptive capacity, weak competition culture, and weak legal and institutional frameworks on technology transfer. Multinational corporations transferred technology primarily to fulfil their commercial objectives and to meet the domestic labour training requirements. The technology transferred was not sufficient to simulate innovation and technology development in Kenya. We recommend reviewing Kenya's legal and institutional frameworks on international technology transfer in order to improve the participation in and enforcement of technology transfer by government institutions. [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]

This article explores the extent to which the regional higher education system (HES) influences the location of foreign research and development (R&D). To do so, we use a dataset with information on the location choices of new foreign R&D establishments within Spain from 2005 to 2013. Similarly, we use a multiple measure of the three university missions, distinguishing between research capacity training, scientific research, and technology transfer. We find that the probability of a foreign R&D establishment being located in a region is positively affected by the strength of the region's HES missions, and more specifically by the quality of its scientific research, while its research training capacity and knowledge transfer activities do not seem to play a significant role. Moreover, the strength of the research mission has a positive influence on the location choice of foreign units conducting research activities but is weak to explain the location of those performing development activities. JEL CLASSIFICATION F21; F23; O32 [ABSTRACT FROM AUTHOR]

Infectious diseases (IDs) are a leading cause of death. The diversity and adaptability of microbes represent a continuing risk to health. Combining vision with passion, our transdisciplinary medical research team has been focussing its work on the better management of infectious diseases for saving human lives over the past five decades through medical discoveries and innovations that helped change the practice of medicine. The team used a multiple-faceted and integrated approach to control infectious diseases through fundamental discoveries and by developing innovative prevention tools and rapid molecular diagnostic tests to fulfill the various unmet needs of patients and health professionals in the field of ID. In this article, as objectives, we put in context two main research areas of ID management: innovative infection prevention that is woman-controlled, and the rapid molecular diagnosis of infection and resistance. We also explain how our transdisciplinary approach encompassing specialists from diverse fields ranging from biology to engineering was instrumental in achieving success. Furthermore, we discuss our vision of the future for translational research to better tackle IDs. [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]

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 investigates the challenges associated with constructing wireless chargers at the megawatt level using inductive power transfer (IPT) technology for marine energy storage systems. For marine applications, charging can only take place at a quay, meaning that only static charging is possible. In this paper, the specifications of the MF Ampere ferry have been used for the feasibility study. Through analytical calculations and PSIM simulation, it was determined that several low-power (100 kW) IPT systems need to be paralleled to achieve 1 MW power transfer. Building a single unit of 1 MW is not feasible due to the voltage and current stress across the components and limited space available onboard and onshore. However, a 100-kW power level can be implemented, despite the involved misalignments, if the primary system is kept stationary with respect to the secondary. Two proposed solutions for implementing a fast charger at the 1 MW level are presented in this paper: 10 units of 100 kW without mechanical mooring assistance or 5 units of 200 kW with mechanical mooring assistance. [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]

Diffusion bonding technology is widely used in the connection of precision components, yet accurately and reliably detecting contact-type defects on the bond interface still remains a significant problem. Nonlinear ultrasonic methods have been proven to be sensitive to contact-type defects; however, the use of continuous wave or tone burst wave excitation limits its wider application. In this paper, dual-probe nonlinear ultrasonic testing with pulse wave excitation is proposed to detect contact-type defects in diffusion-bonded joints. A titanium alloy diffusion-bonded specimen with artificial defects was fabricated, and the corresponding detection device was designed based on the existing ultrasonic C-scan testing system. A C-scan imaging program based on nonlinear parameters was developed by extracting the fundamental and second harmonic waves of the reflection echo on the bond interface. The results demonstrated that the proposed detection scheme can obtain the nonlinear parameters of diffusion-bonded interfaces, and the nonlinear ultrasonic C-scan image of the bond interface is also obtained. The nonlinear parameter in the contact-type defects areas calculated from the bond interface echo is about 10 times (20 dB) higher than that in macro defects areas, whose gap is about 10 μm. The results indicate that the nonlinear ultrasonic methods seem to be more sensitive to contact-type defects and have a great potential to complement the insufficient detection capability of linear ultrasound for diffusion-bonded joints. [ABSTRACT FROM AUTHOR]

Synthesizing various studies that follow technology beyond innovation and use, this article aims to continue widening the scope of history of technology toward this perspective. It argues that we must follow technology through time and—in addition to its use—its maintenance and repair, while also addressing its so-called afterlife, encompassing topics such as reuse, reconfiguration and/or restoration, decline or deliberate ruination, abandonment, and removal and/or remains. Recent studies of these issues underscore that the temporality of technology does not end with the end of its use, suggesting instead multilayered temporalities. History of technology is thus challenged to rethink some of its established and largely unquestioned approaches, such as the "innovation timeline", the model of "technology diffusion and substitution", and "lifecycle" metaphors borrowed from twentieth-century theories of economic growth and innovation. [ABSTRACT FROM AUTHOR]

With the increasing demand for efficient maritime logistic management, industries are striving to develop automation software. However, collecting data for analytics from diverse sources like shipping routes, weather conditions, historical incidents, and cargo specifications has become a challenging task in the distribution environment. This challenge gives rise to the possibility of faulty products and traditional testing techniques fall short of achieving optimal performance. To address this issue, we propose a novel decentralised software system based on Transfer Learning and blockchain technology named as BETL (Blockchain -Enabled Transfer Learning). Our proposed system aims to automatically detect and prevent vulnerabilities in maritime operational data by harnessing the power of transfer learning and smart contract-driven blockchain. The vulnerability detection process is automated and does not rely on manually written rules. We introduce a non-vulnerability score range map for the effective classification of operational factors. Additionally, to ensure efficient storage over the blockchain, we integrate an InterPlanetary File System (IPFS). To demonstrate the effectiveness of transfer learning and blockchain integration for secure logistic management, we conduct a testbed-based experiment. The results show that this approach can achieve high precision (98.00%), detection rate (98.98%), accuracy (97.90%), and F-score (98.98), which highlights its benefits in enhancing the safety and reliability of maritime logistics processes. Additionally, the computational time of BETL (the proposed approach) was improved by 18.9% compared to standard transfer learning. [ABSTRACT FROM AUTHOR]

Orchid is a type of plant that grows on land. It is highly valued for its beauty and is cherished by many because of its graceful flower shape, delicate fragrance, vibrant colors, and noble symbolism. Although there are various types of orchids, some of them look similar in appearance and color, making it challenging for people to distinguish them quickly and accurately. The existing methods for classifying orchid species face issues with accuracy due to the similarities between different species and the differences within the same species. This affects their practical use. To address these challenges, this paper introduces an efficient method for classifying orchid species using transfer learning. The main achievement of this study is the successful utilization of transfer learning to achieve accurate orchid species classification. This approach reduces the need for large datasets, minimizes overfitting, cuts down on training time and costs, and enhances classification accuracy. Specifically, the proposed approach involves four phases. First, we gathered a collection of 12 orchid image sets, totaling 12,227 images, through a combination of network sources and field photography. Next, we analyzed the distinctive features present in the collected orchid image sets. We identified certain connections between the acquired orchid datasets and other datasets. Finally, we employed transfer learning technology to create an efficient classification function for orchid species based on these relationships. As a result, our proposed method effectively addresses the challenges highlighted. Experimental results demonstrate that our classification algorithm, which utilizes transfer learning, achieves a classification accuracy rate of 96.16% compared to not using the transfer learning method. This substantial improvement in accuracy greatly enhances the efficiency of orchid classification. [ABSTRACT FROM AUTHOR]

The Canary Islands are considered a hotspot of biodiversity and have high levels of endemicity, including endemic reptile species. Nowadays, some invasive alien species of reptiles are proliferating with no control in different parts of the territory, creating a dangerous situation for the ecosystems of this archipelago. Despite the fact that the regional authorities have initiated actions to try to control the proliferation of invasive species, the problem has not been solved as it depends on sporadic sightings, and it is impossible to determine when these species appear. Since no studies for automatically identifying certain species of reptiles endemic to the Canary Islands have been found in the current state-of-the-art, from the Signals and Communications Department of the Las Palmas de Gran Canaria University (ULPGC), we consider the possibility of developing a detection system based on automatic species recognition using deep learning (DL) techniques. So this research conducts an initial identification study of some species of interest by implementing different neural network models based on transfer learning approaches. This study concludes with a comparison in which the best performance is achieved by integrating the EfficientNetV2B3 base model, which has a mean Accuracy of 98.75%. [ABSTRACT FROM AUTHOR]

This study is aimed at investigating the asymmetric and time-frequency co-movements and the hedge or safe-haven properties of carbon efficient indices, the MSCI ACWI Sustainable Impact, and MSCI World EGS indices, in relation to technology and innovation-themed investments. In doing so, the ADCC-GJR-GARCH and wavelet coherence techniques are applied to a daily return series ranging from January 2019 to January 2023. Findings of the ADCC-GJR-GARCH model show negative and insignificant asymmetric linkage among underlying indices during the sample period. The S&P 500 carbon efficient index (CEI) acts as a strong hedge or safe-haven for technology and innovation-themed indices during tranquil and tumultuous periods. The MSCI ACWI Sustainable Impact, MSCI World EGS, and carbon efficient indices except for S&P 500 CEI exhibit weak hedge or safe-haven attributes. Wavelet coherence reveals negative (positive) co-movements between the thematic and carbon efficient indices in short-term (medium-term and long-term) horizons with consistent leading behavior of thematic indices to carbon efficient indices outcomes. It justifies the presence of short-lived hedging or safe-haven characteristics in the thematic domain for investors. These strong and weak hedge or safe-haven characteristics of low carbon and sustainability indices reveal that adding low carbon efficient and sustainable investments to a portfolio result in considerable diversification benefits for investors who tend to take minimal risk in both tranquil and tumultuous periods. The current findings imply that financial institutions, thematic investing companies, and governments need to encourage carbon efficient technology transfer and innovation-themed investments by increasing the fund allocations in underlying asset classes. Policy-making and regulatory bodies can encourage investors to make carbon-efficient and thematic investments and companies to issue carbon-efficient stocks or investments to safeguard social and economic risks during fragile periods. These investments can offer greater opportunities to combat the intensity of economic shocks on portfolios for responsible or sustainable investors. [ABSTRACT FROM AUTHOR]

With the advancement of information technology and artificial intelligence, translation technologies have seen rapid development in language services and increasing integration in higher education. However, research on factors affecting students' acceptance of these technologies remains limited. This study intends to formulate and test an extended Technology Acceptance Model (TAM) incorporating computer self-efficacy and perceived enjoyment to investigate students' adoption of translation technologies. A questionnaire survey was conducted among 370 college students in China experienced with using translation technologies. The results from the structural equation modeling demonstrated a positive prediction on perceived ease of use and enjoyment from computer self-efficacy. Perceived enjoyment increased perceived ease of use and attitudes. Perceived ease of use positively influenced perceived usefulness and attitudes. Finally, attitudes positively predicted greater behavioral intentions to use translation technologies. However, computer self-efficacy was identified to have no significant effect on perceived usefulness. The study makes significant theoretical contributions by expanding TAM and offering practical guidance to improve students' acceptance of translation technologies in tertiary education. [ABSTRACT FROM AUTHOR]

Myopia control with new designs of spectacle lenses is a flourishing area of research. The present work reviews the effectiveness of new designs (DIMSs, defocus-incorporated multiple segments; CARE, cylindrical annular refractive element; HALs/SALs, highly/slightly aspherical lenslets; DOT, diffusion optics technology) aiming at slowing myopia progression. A search through the PubMed database was conducted for articles published between 1 January 2003 and 28 February 2023. Publications were included if they documented baseline central refraction (SER) and/or axial length (AL) data, and the change in these parameters, in myopic children wearing new designs of spectacle lenses (treatment group) compared to myopic children using single-vision lenses, SVLs (control group). The selection process revealed nine suitable articles. Comparing the mean and standard error values of the treatment and control groups, the highest differences in the change in the SER and AL were −0.80 (1.23) D [95% CI: −1.053 to −0.547; p < 0.001] and 0.35 (0.05) mm [95% CI: 0.252 to 0.448; p < 0.001], respectively; the effect of treatment provided by a HAL design, compared to SVLs, led to a deceleration of 54.8% in the SER and 50.7% in the AL. However, the heterogeneity of the results prevents reaching strong conclusions about the effectiveness of these new designs. [ABSTRACT FROM AUTHOR]

China is actively promoting the development of a robust trading nation. In this context, utilizing data from China's A-share listed companies spanning from 2003 to 2021, this study investigates the impact of foreign shareholders on enterprises in a scenario where overseas sales reduce the profit margin of Chinese firms. The findings reveal that overseas sales do indeed decrease the profit margin of Chinese enterprises; however, foreign shareholders mitigate this negative effect and various robustness tests support this conclusion. Mechanism analysis confirms that foreign shareholders primarily enhance enterprise productivity through improved production technology spillover effects, thereby alleviating the adverse impact of overseas sales on Chinese firms' profit margins. Heterogeneity analysis demonstrates that both longer holding periods for foreign shareholders and multiple foreign shareholders significantly alleviate the negative influence of overseas sales on Chinese firms' profit margins. Moreover, there is significant heterogeneity in how foreign shareholders alleviate these detrimental consequences based on property rights nature, institutional environment, overseas related party transactions and subsidiaries, as well as industry attributes. These findings have important reference value for China's efforts towards becoming a strong trading nation and can contribute to enhancing trade capacity in other countries. [ABSTRACT FROM AUTHOR]

Traditionally, extensive vehicle testing is applied to assure the robustness and safety of automotive systems. This approach is highly challenged by increasing system complexity. Formal verification lends a powerful framework for model-based safety assurance, but due to the mixed discrete–continuous behavior of automotive systems, traditional tools for discrete program verification are helpful but not sufficient. In academia, during the last two decades new approaches arose for the formal verification of such mixed discrete-continuous systems. However, the industry is not fully aware of this development, the tools are seldom tried and their applicability is not well examined. In a Ford–RWTH research alliance project, we aimed at evaluating the potential of knowledge and technology transfer in this area. This paper has two main objectives. Firstly, we want to report on the state-of-the-art in the above-mentioned academic development in a generally understandable form, targeted to interested potential users. Secondly, we want to share our observations after testing different available tools for their applicability and usability in the automotive sector and as a conclusion devise some recommendations. [ABSTRACT FROM AUTHOR]

The collaboration relationships between innovation actors at a geographic level may be considered as grouping two separate layers, the domestic and the foreign. At the level of each layer, the relationships and the actors involved constitute a Triple Helix game. The paper distinguished three levels of analysis: the global grouping together all actors, the domestic grouping together domestic actors, and the foreign related to only actors from partner countries. Bibliographic records data from the Web of Science for South Korea and West Africa breakdown per innovation actors and distinguishing domestic and international collaboration are analyzed with game theory. The core, the Shapley value, and the nucleolus are computed at the three levels to measure the synergy between actors. The synergy operates more in South Korea than in West Africa; the government is more present in West Africa than in South Korea; domestic actors create more synergy in South Korea, but foreign more in West Africa; South Korea can consume all the foreign synergy, which is not the case of West Africa. Research data are limited to publication records; techniques and methods used may be extended to other research outputs. West African governments should increase their investment in science, technology, and innovation to benefit more from the synergy their innovation actors contributed at the foreign level. However, the results of the current study may not be sufficient to prove that greater investment will yield benefits from foreign synergies. This paper uses game theory to assess innovation systems by computing the contribution of foreign actors to knowledge production at an area level. It proposes an indicator to this end. [ABSTRACT FROM AUTHOR]

With the rapid development of information transfer technology and the influence of complex electromagnetic environment, the signal components in communication systems are becoming more and more complex, and the spectrum congestion is further aggravated, which seriously affects the performance of communication systems. Single-channel blind source separation technology is an effective solution, but the existing algorithms are deficient in terms of estimation accuracy, time delay and computational complexity. Based on the powerful feature extraction capability and timing signal processing capability of deep learning, this paper proposes an end-to-end time-domain blind separation convolutional network structure, including three parts: encoder, separation module and decoder. The attention mechanism module is also introduced into the encoding layer of the network to enhance the deep feature extraction ability of the network, highlight the influence of important timing features of communication signals, further improve the separation performance and enhance the practicality of the network. The experimental results show that the algorithm has superior performance and can effectively separate the mixed communication signal of various modulation types, and it can also extract own-side communication signals from high-power masked signals. Compared with the existing algorithms, the network in this paper has high separation accuracy and low computational complexity, which breaks the bottleneck of traditional single-channel blind separation algorithms in complex communication electromagnetic environment. [ABSTRACT FROM AUTHOR]

The original extended mind theory propagated by Clark and Chalmers (Analysis 58:7–19, 1998) refers to the idea that our minds do not simply live within our brains or bodies but extend into the material world. In other words, the extended mind refers to the externalization of cognitive processes into technology. Through the case study of the artistic performance of the android Alter inspired by the Japanese Shintoist ritual of Kagura this paper reconceptualizes the extended mind from a technological act of transfer towards the relational, spatial, and performative ontologies of the intersubjective encounters between humans and non-humans. In an effort to decolonize performance and curatorial practice the paper draws upon indigenous scholarship, feminist STS, and performance studies to overcome preconceived conceptualizations of affect, perception, and relationality. The fundamental question the paper explores is how does intersubjective relationality unfold through performance in space? Based upon a critique of the android Alter's past performance the paper concludes with a re-envisioned event score that employs a reconceptualized theory of the extended mind and aimed at a different kind of intersubjective relationality to emerge. [ABSTRACT FROM AUTHOR]

There are various health issues associated with the different stages of long-distance pipeline transportation. These issues pose potential risks to environmental pollution, resource waste, and the safety of human life and property. It is essential to have real-time knowledge of the overall health status of pipelines throughout their entire lifecycle. This article investigates various health-monitoring technologies for long-distance pipelines, providing references for addressing potential safety issues that may arise during long-term transportation. This review summarizes the factors and characteristics that affect pipeline health from the perspective of pipeline structure health. It introduces the principles of major pipeline health-monitoring technologies and their respective advantages and disadvantages. The review also focuses on the application of Distributed Acoustic Sensing (DAS) technology, specifically time and space continuous monitoring technology, in the field of pipeline structure health monitoring. This paper discusses the process of commercialization development of DAS technology, the main research progress in the experimental field, and the open research issues. DAS technology has broad application prospects in the field of long-distance transportation pipeline health monitoring. [ABSTRACT FROM AUTHOR]

As the demand for diverse nanostructures in physical/chemical devices continues to rise, the development of nanotransfer printing (nTP) technology is receiving significant attention due to its exceptional throughput and ease of use. Over the past decade, researchers have attempted to enhance the diversity of materials and substrates used in transfer processes as well as to improve the resolution, reliability, and scalability of nTP. Recent research on nTP has made continuous progress, particularly using the control of the interfacial adhesion force between the donor mold, target material, and receiver substrate, and numerous practical nTP methods with niche applications have been demonstrated. This review article offers a comprehensive analysis of the chronological advancements in nTP technology and categorizes recent strategies targeted for high‐yield and versatile printing based on controlling the relative adhesion force depending on interfacial layers. In detail, the advantages and challenges of various nTP approaches are discussed based on their working mechanisms, and several promising solutions to improve morphological/material diversity are presented. Furthermore, this review provides a summary of potential applications of nanostructured devices, along with perspectives on the outlook and remaining challenges, which are expected to facilitate the continued progress of nTP technology and to inspire future innovations. [ABSTRACT FROM AUTHOR]

Social sustainability is a global necessity because of environmental and economic uncertainty. This issue needs the foremost solution, and for this purpose, researchers' and policymakers' emphasis is required. Thereby, the present paper investigates sustainable energy technologies such as solar and hydroelectric, eco-innovation and EG and their impact on social sustainability in China. The study also used industrialization and inflation as the control variables in the time span of 1981 to 2020. The present study also applied the Dynamic Auto-regressive Distributed Lags (DARDL) model to evaluate the association between the outlined variables. The results indicated that sustainable energy technologies such as solar and hydroelectric, eco-innovation, economic growth, industrialization and inflation are significantly associated with social sustainability in China. The present paper offers standard policies to regulators in making regulations related to maintaining social sustainability by using effective sustainable energy technologies and eco-innovation. [ABSTRACT FROM AUTHOR]

Open innovation is a concept of collaboration of ideas, knowledge, and resources that originates from within the organization and involves external organizations. University-industry collaboration is a factor driving innovation and competitiveness. Most research on interactions between universities and industry concentrated on the industrial side meanwhile, universities, as knowledge producers, play a vital role in creating an open innovation ecosystem that encourages realizing innovations that benefit society. Therefore, the problem raised in this research is how university collaboration can support open innovation. This research aims to identify research trends, the latest technologies, and inter-university collaboration frameworks that can support open innovation. The methodology used is Kitchenham's Systematic Literature Review (SLR) and bibliometric. SLR consists of Identification Study, Selection Studies, Quality Assessment, Data Extraction and Study Synthesis. From the SLR stages, 21 papers published between 2019 and 2023 were obtained. Synthesis and additional literature review were carried out to identify trends, technologies, and frameworks related to the topic comprehensively. In terms of trend, based on the application bibliometric, it was found that there was an increase in the number of publications and the top list of open innovation journals. University collaboration in open innovation more frequently takes place in the UK, and the industries mostly involved are small-medium enterprises. Quantitative research methodology and data analyses, comprising of hypothesis test, regression test, and descriptive statistics, are mostly preferred. Meanwhile, descriptive data analysis is the most common means of qualitative data analysis. Numerous suggestions on topics for future research were also identified. In addition, data analysis using machine learning survival data is identified as a novelty among data analysis methods. Technology transfer and the use of digital platforms may support open innovation processes, and the use of blockchain technology may promote digital platforms development. Seven domains form the framework for university collaboration in open innovation, namely Social Behavior, People, Process, Organization, Environment, Technology, and Performance. The findings of trends, technologies, and frameworks in this research may serve as a foundation for research on similar topics, and the identified framework domains could serve as framework components that might be used by universities to collaborate with partners in implementing open innovation processes. The research have contributes to knowledge management theoretically and practically. Theoretically, open innovation can expand the knowledge base by supporting the concept that knowledge and expertise can be found outside organizational boundaries. Practically, it can enrich knowledge management practices by emphasizing the importance of utilizing digital platform technology in supporting knowledge management sourced from external knowledge and collaboration services in the open innovation process. [ABSTRACT FROM AUTHOR]

This study examines the trade relationship between Turkey and Uzbekistan, particularly in sesame exports, with the aim of strengthening Uzbekistan's competitiveness. Based on the theory of comparative advantage and using key indicators such as the Revealed Comparative Advantage (RCA) Index, the Revealed Symmetric Comparative Advantage (RSCA) Index, and the Normal Revealed Comparative Advantage (NRCA) Index, this study highlights the robust competitiveness of Turkey in exporting agricultural machinery designed specifically for sesame production. Through a comprehensive analysis of these indices, the study highlights Turkey's particular strength in this sector, sheds light on its comparative advantage and emphasises the country's strategic position in the global market for sesame-related agricultural machinery. However, Uzbekistan currently lacks competitiveness in sesame exports. The study underlines the key role of effective technology transfer, especially in machinery exports from Turkey, in improving Uzbekistan's position. Econometric models show the significant impact of exchange rates and domestic demand on Uzbekistan's sesame exports. The study's findings highlight ways to improve the efficiency of agricultural machinery exports between the two countries. This provides policymakers with valuable insights to strengthen sustainable trade relations and increase the volume of agricultural exports. [ABSTRACT FROM AUTHOR]

Ciguatera, a global issue, lacks adequate capacity for ciguatoxin analysis in most affected countries. The Caribbean region, known for its endemic ciguatera and being home to a majority of the global small island developing states, particularly needs established methods for ciguatoxin detection in seafood and the environment. The radioligand receptor binding assay (r-RBA) is among the in vitro bioassays currently used for ciguatoxin analysis; however, similarly to the other chemical-based or bioassays that have been developed, it faces challenges due to limited standards and interlaboratory comparisons. This work presents a single laboratory validation of an r-RBA developed in a Cuban laboratory while characterizing the performance of the liquid scintillation counter instrument as a key external parameter. The results obtained show the assay is precise, accurate and robust, confirming its potential as a routine screening method for the detection and quantification of ciguatoxins. The new method will aid in identifying high-risk ciguatoxic fish in Cuba and the Caribbean region, supporting monitoring and scientific management of ciguatera and the development of early warning systems to enhance food safety and food security, and promote fair trade fisheries. [ABSTRACT FROM AUTHOR]

The local manufacture of advanced pharmaceutical products has been a long-standing objective of health and industry policy in many developing countries, including in Latin America. This strategy has been applied to fight epidemics such as HIV/AIDS, malaria, and the COVID-19 pandemic. However, we still know little about the politics and governance that enable such arrangements, especially when there is no consent from the originator company. This study focuses on the case of Brazil, a country that is well-known for its health-industry policy, which includes the local production of direct-acting antivirals (DAAs), a new treatment for hepatitis C. We seek to explain the factors that have contributed to Brazil’s successful production of generic versions of DAAs, and, later, to the decision by the Ministry of Health (MoH) to procure drugs from multinational pharmaceutical companies rather than from local laboratories. A lack of support for domestic production by important stakeholders, the patent holder’s attempt to block domestic production and the MoH’s adoption of more modern treatment guidelines under a different procurement logic all created an unfavourable environment for local production and procurement of DAAs. Our study draws implications for middle-income countries that wish to produce drugs domestically without voluntary license agreements. [ABSTRACT FROM AUTHOR]

The grand Chinese endeavour, the Belt and Road Initiative (BRI), is a Chinese attempt to carve out its own economic development model. Technology transfer is essential to economic development and therefore it plays a central role in the BRI. While the World Trade Organization (WTO) envisages a liberal trade model for development including transfer of technology, does the BRI offer a different/alternative technology transfer model? This article deals with this question by analysing Chinese technology transferrelated policies, namely Intellectual Property (IP) and Foreign Direct Investment (FDI) policies in the context of the BRI. This article contrasts inbound/outbound Chinese technology transfer-related policies/practices and tries to forecast the impact of integrating these policies in the BRI. [ABSTRACT FROM AUTHOR]

Enterprise digitalization and intellectualization (EDI) is a crucial aspect of China's modernization process. However, uncertainty in market and business decisions hinders the EDI diffusion process in China. Therefore, this research aims to solve the uncertainty problem of EDI diffusion by examining market demand and government policy coordination. First, we utilize complex network game theory and establish a technology–organization–environment framework for the factors that influence the elements of EDI transformation by combining evidence from existing studies. Second, the network game model is constructed to analyze and optimize the updating rules in the network as a diffusion strategy that enterprises under the uncertain market can adopt. Finally, the impact of adjusting government subsidies and different premiums on the diffusion of EDI transformation strategies is examined. The degree of market diffusion and average revenue of EDI are higher after the optimization of network node strategy updating rules compared to before optimization. Further analysis reveals that only the premium effect of product pricing and inverted U-shaped subsidy support from the government affect the degree of market diffusion and the average revenue of EDI, while the other premium effects are not significant. These findings enrich research related to complex networks and nonlinear dynamic strategies. They also indicate recommendations for government policies to enhance diffusion efficiency and reasonable pricing for enterprises to promote returns. [ABSTRACT FROM AUTHOR]

The energy blockchain is a platform based on blockchain technology, creating a secure, transparent, and decentralized system for peer-to-peer transactions and automated smart contracts. This platform has the ability to facilitate the exchange and management of energy resources, such as electricity or renewable energy certificates. Our research aims to clarify the growth trends of energy systems with blockchain technology throughout the world. The novelty of this study is to understand the main factor in energy blockchain patent granting using a patent decomposition analysis and log mean Divisia index analysis and discover the relative importance in the R&D shift from electricity to other technology. Additionally, the IPC for energy blockchain technology primarily focuses on configuring and managing energy systems, including electricity, gas, and water supply. We also present a comprehensive overview of how countries and companies engage with energy blockchain technology and find China leads with 59% of patents, followed by the U.S. with 20%, but their specific tech shares differ. Participants span beyond traditional energy sectors, including electric and electronic machinery, IT firms, transport manufacturers, startups, and universities dedicated to blockchain technology. [ABSTRACT FROM AUTHOR]

Technological innovation and preoccupation with new markets through technological innovation have become critical factors in achieving success in the global market. Currently, companies cannot develop and commercialize all technologies. Therefore, the importance of technology transfers is rapidly increasing. Technology transfer is a crucial strategy adopted by organizations to remain innovative and competitive. However, Korea's technology transfer rate is only 37.9%. In particular, the technology transfer rate from universities to companies is lower than that from government-funded research institutes in Korea. Although the fundamental approach for resolving barriers to technology transfer have been studied, previous research has been conducted from a narrow definition of technology transfer. Furthermore, previous research has focused on analyzing the success factors of technology transfer, presenting technology transfer processes, or conducting case studies. Therefore, it is necessary to develop a technology donor diagnosis framework based on CSFs (Critical Success Factors) to eliminate obstacles to technology transfers. To lower the barriers to technology transfers, it is necessary to develop a strategy for a successful technology transfer based on the diagnosis of technology donors. This study develops a diagnosis framework for universities from the perspective of technology donors, implements and tests the framework using case studies, and proposes strategies for each stage of technology transfer growth. The framework is able to assess multidimensional perspectives, because CSFs and PMs were extracted based on BSC. Furthermore, by comparing the perspectives score of technology donors in different universities, technology donors can identify the areas in which each university is lacking in its current situation. Multidimensional diagnosis and aggregation score of technology donors offer to extract optimal CSFs for technology transfer activation for each growth stage. [ABSTRACT FROM AUTHOR]

The special public funding policies, formulated and implemented by provincial governments, plays an important role in the development of private universities in China. However, there is a lack of scientific evaluation on the rationality and completeness of the provincial special public funding policy of China's private colleges and universities. Therefore, this paper uses PMC-index model and text mining technology to establish an evaluation index system for the provincial special public funding policy of private universities in China. Based on PMC-Index and PMC-Surface, 13 policy texts issued since 2010 were evaluated scientifically. The results show that the average PMC-Index of the 13 policies is 6.97, and the PMC-Surface map is smooth, which indicates that the overall structure of these policies is reasonable and the policy content has certain completeness. Only one policy is unacceptable. Through further analysis, we found that there is still much room for improvement in the content design of the sample policy, and its rationality and completeness are related to the publication time. This study is helpful to fully understand the advantages and disadvantages of the provincial special public funding policy of private universities in China. [ABSTRACT FROM AUTHOR]