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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]

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]

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]

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]

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]

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]

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]

Research on the transfer of skill from the circumstances in which it was learned to partially or completely novel tasks or situations is a foundational topic in the study of learning, memory, education, and expertise. A long history of transfer research has led to the conclusion that skill learning is generally domain specific. One important transfer problem occurs when a domain of expertise undergoes a fundamental shift, as when experts must adapt to changes in technology, rules, or professional practice. Here we examine skill maintenance in StarCraft 2, a video game of skills which undergoes frequent changes due to updates and includes a variety of gameplay options. Of particular interest are two competing predictions about how transfer will interact with expertise in this domain. The first approach emphasizes perceived similarity of the domains and predicts that skilled individuals will exhibit more favourable transfer than novices as these people will know enough to avoid processes, methods, and strategies which no longer apply after a domain change. The second emphasizes maximal adaptation to task constraints and predicts that experts will suffer the most during a domain change because of the loss of exploitable affordances. Neither approach did a good job explaining behaviour after the major game update called 'StarCraft 2: Heart of the Swarm,' perhaps because transfer was generally strong across all players. However, when examining transfer in the context of larger changes to gameplay, transfer seemed slightly better in more experienced players. The theoretical implications of this apparent interaction effect, and of the apparent resilience of more experienced StarCraft 2 players to transfer costs, are discussed. [ABSTRACT FROM AUTHOR]

The evolution of virtual reality (VR) has created the opportunity for a relatively low-cost and accessible method to practice motor skills. Previous studies have demonstrated how motor skill practice in non-immersive virtual environments transfers to physical environments. Though minimal research has investigated motor learning and transfer within immersive VR, multiple experiments provide empirical evidence of positive transfer effects. Most studies have used software engines and modified hardware to enhance the similarities between virtual and physical environments. However, many learners and practitioners currently use commercially available VR intending to enhance real-world performance, though there is very little evidence to support the notion of positive transfer for these systems. Therefore, this experiment aimed to investigate how motor skill practice using a commercially available VR system improved real-world performance and how that compared to physical practice. Participants (n = 68) were randomly selected into one of two groups: virtual reality (VR) practice (n = 33) or real-world (RW) practice (n = 35). The experiment occurred over two consecutive days, with a pretest, posttest, and practice phase occurring each day. The pre- and post-testing phases were identical for both groups and consisted of putting a golf ball 10 times on a carpeted surface towards the center of a target. The practice phases consisted of 60 total putts per day in the respective environment (VR or RW). Participants continuously alternated golf putting holes from three different distances until they accrued 60 total putts. Participants in the RW group performed golf putts to three targets. Participants in the VR group also performed golf putts on three different miniature golf putting holes, using the commercially available Oculus Rift and the Cloudlands VR Minigolf game. The VR putting targets were designed to replicate the putting holes in the physical environment. Separate 2 (group) x 4 (test) repeated measures ANOVAs were used to assess accuracy and club head kinematics. The results revealed a significant main effect for test, but not for group. Post hoc analyses revealed that both groups significantly improved their putting accuracy and club head kinematics at similar rates. The results from this study indicate that the transfer of learning that occurred as a result of practicing in a commercially available VR environment was similarly effective when compared to RW practice. [ABSTRACT FROM AUTHOR]

Prior studies ignore the impact of infrastructure on university technology transfer. High-speed rail, China's most significant infrastructure, has played an essential role in the economy and society. Using high-speed railway construction as a quasi-experiment and a large sample of Chinese universities for the 2007–2017 period, we investigate the impact of high-speed rail on university technology transfer. We provide extensive evidence that high-speed rail has a positive effect on university technology transfer. The finding remains valid after a battery of robustness tests. Mechanism tests find that high-speed rail can improve university technology transfer by promoting the interaction between universities and enterprises and improving enterprises' technology demand for universities. Further analysis shows that better intellectual property protection strengthens the effect of high-speed rail on university technology transfer, and the relationship between high-speed rail and university technology transfer is more prominent in the regions with underdevelopment technology trading markets. Our study suggests that high-speed rail is an important variable that affects university technology transfer. [ABSTRACT FROM AUTHOR]

Within the university-industry ecosystem, improvement and innovation of technology transfer involve implementing appropriate dynamic capabilities. To answer the question—What are the micro-foundations of dynamic capabilities in university technology transfer?—this study investigates in-depth organizational-level dynamic capabilities in transferring university-based knowledge to business and society. Two qualitative case studies were deployed at organizational entities at Vrije Universiteit Amsterdam: the Industry Alliance Office, and the Demonstrator Lab. These two organizations stimulate science- and business-oriented university technology transfer. In this context, the micro-foundations of the dynamic capabilities "sensing", "seizing" and "reconfiguring" are identified and discussed. For "sensing", which is the university's ability to explore the opportunities in the ecosystem, the micro-foundations are "selecting internal competency" and "sensing external partners". For "seizing", which supports universities in managing complementarity with industry and society, micro-foundations include "resource co-allocation" and "collaborative business model". The micro-foundations of "reconfiguring", through which universities maintain evolutionary fitness in the innovation ecosystem, are "strategic renewal", "establishing a university technology transfer-friendly environment", and "asset orchestration". This study provides researchers with a better understanding of how dynamic capabilities facilitate university technology transfer. Industrial practitioners and policymakers can consider the suggestions of the present study when pursuing collaboration with universities. [ABSTRACT FROM AUTHOR]

With the Public–Private Partnership (PPP) mode playing an increasingly important role in the investment of infrastructure, promoting the diffusion of low-carbon technology innovation in PPP projects not only helps to reduce the carbon emissions of infrastructure, but also plays an important demonstration role in the low-carbon transformation of construction industry. In order to clarify the evolutionary mechanism of low-carbon technology innovation diffusion among stakeholders under the unique payment mechanism of PPP projects in China, the paper builds two different evolutionary game models respectively under government payment mechanism and consumer payment mechanism based on evolutionary game theory. The evolutionary relationship between the choice of behavior strategies and the change of influencing factors under different payment mechanisms are analyzed by numerical simulation. It is found that under government payment mechanism, the regulation cost of government to promote low-carbon technology innovation and the punishment of the superior regulatory authority for non-regulation behavior are the important factors affecting government's behavioral strategies. The low-carbon technology innovation cost of social capital and the intensity of government subsidy and punishment are the main factors affecting social capital's behavioral strategies; Under consumer payment mechanism, consumer becomes the ultimate payer of low-carbon products, and the income they get from purchasing low-carbon products and the subsidy provided by the government become the main factors determining consumer's behavioral strategies. Finally, from the perspective of government, social capital and consumer, countermeasures and management implications are put forward to effectively promote the diffusion of low-carbon technology innovation under different payment mechanism in PPP projects. [ABSTRACT FROM AUTHOR]

The recent era has witnessed exponential growth in the production of multimedia data which initiates exploration and expansion of certain domains that will have an overwhelming impact on human society in near future. One of the domains explored in this article is content-based image retrieval (CBIR), in which images are mostly encoded using hand-crafted approaches that employ different descriptors and their fusions. Although utilization of these approaches has yielded outstanding results, their performance in terms of a semantic gap, computational cost, and appropriate fusion based on problem domain is still debatable. In this article, a novel CBIR method is proposed which is based on the transfer learning-based visual geometry group (VGG-19) method, genetic algorithm (GA), and extreme learning machine (ELM) classifier. In the proposed method, instead of using hand-crafted features extraction approaches, features are extracted automatically using a transfer learning-based VGG-19 model to consider both local and global information of an image for robust image retrieval. As deep features are of high dimension, the proposed method reduces the computational expense by passing the extracted features through GA which returns a reduced set of optimal features. For image classification, an extreme learning machine classifier is incorporated which is much simpler in terms of parameter tuning and learning time as compared to other traditional classifiers. The performance of the proposed method is evaluated on five datasets which highlight the better performance in terms of evaluation metrics as compared with the state-of-the-art image retrieval methods. Its statistical analysis through a nonparametric Wilcoxon matched-pairs signed-rank test also exhibits significant performance. [ABSTRACT FROM AUTHOR]

Background: The SARS-CoV-2 pandemic is a global threat affecting 210 countries, with 2,177,469 confirmed cases and 6.67% case fatality rate as of April 16, 2020. In Africa, 17,243 cases have been confirmed, but many remain undiagnosed due to limited laboratory-capacity, suboptimal performance of used molecular-assays (~30% false negative, Yu et al. and Zhao et al., 2020) and limited WHO-recommended rapid-tests. Objectives: We aim to implement measures to minimize risks for COVID-19 in Cameroon, putting together multidisciplinary highly-experienced virologists, immunologists, bioinformaticians and clinicians, to achieve the following objectives: (a) to integrate/improve available-infrastructure, methodologies, and expertise on COVID-19. For this purpose, we will create a platform enabling researchers/clinicians to better integrate and translate evidence into the COVID-19 clinical-practice; (b) to enhance capacities in Cameroon for screening/detecting individuals with high-risks of COVID-19, by setting-up effective core-facilities on-site; (c) to validate point-of-care SARS-CoV-2 molecular assays allowing same-day result delivery, thus permitting timely diagnosis, treatment, and retention in care of COVID-19 patients; (d) to implement SARS-CoV-2 diagnosis with innovative/highly sensitive ddPCR-based assays and viral genetic characterization; (e) to validate serological assays to identify COVID-19-exposed persons and follow-up of convalescents. Methods: This is a prospective, observational study conducted among COVID-19 suspects/contacts during 24 months in Cameroon. Following consecutive sampling of 1,536 individuals, oro/nasopharyngeal swabs and sera will be collected. Well characterised biorepositories will be established locally; molecular testing will be performed on conventional real-time qPCR, point-of-care GeneXpert, antigen-tests and digital droplet PCR (ddPCR); SARS-CoV2 amplicons will be sequenced; serological testing will be performed using ELISA, and antibody-based kits. Sensitivity, specificity, positive- and negative-predictive values will be evaluated. Expected outcomes: These efforts will contribute in creating the technical and clinical environment to facilitate earlier detection of Sars-CoV-2 in Africa in general and in Cameroon in particular. Specifically, the goals will be: (a) to implement technology transfer for capacity-building on conventional and point-of-care molecular assays, achieving a desirable performance for clinical diagnosis of SARS-CoV2; (b) to integrate/improve the available infrastructure, methodologies, and expertise on Sars-CoV2 detection; (c) to improve the turn-around-time for diagnosing COVID-19 infection with obvious advantage for patients/clinical management thanks to low-cost assays, thus permitting timely treatment and retention in care; (d) to assess the epidemiology of COVID-19 and circulating-variants in Cameroon as compared to strains found in other countries. [ABSTRACT FROM AUTHOR]

In order to solve the problem of coal dust pollution at the transfer point, a three-dimensional numerical model of wind flow-coal dust at the loading point of underground rubber run was established by computational fluid dynamics (CFD) discrete particle model and finite element method and k-ε turbulence model, and the coal dust diffusion pollution phenomenon caused by the coal flow transfer under the intersection of wind flow in the cross tunnel was studied. Based on the simulation results of wind flow velocity contour, pressure contour and isochronous flow vector distribution, the influence mechanism of wind flow and coal dust characteristics on the distribution of wind flow and coal dust diffusion in the roadway is analysed, and a dust control and reduction system and treatment scheme with new pneumatic screw spray technology as the core is proposed to suppress coal dust pollution at the reloading point. The results of the study show that the wind flow distribution is mainly influenced by the intersection of tape traction and cross-roadway wind flow, showing a complex multi-layer distribution along the roadway and in the normal direction; the diffusion of coal dust of different particle sizes is influenced by the roadway wind flow, and coal dust with particle sizes in the range of 10μm~20μm is more easily diffused, and the dust with particle sizes in the range of 20μm~45μm is mainly collected and suspended near the vortex wind flow at the cross-roadway. The coal dust in the range of 20 μm~45 μm is more likely to gather in the vortex; the treatment system effectively controls the coal dust inside the dust cover, and the spiral-shaped transported droplet particle group formed by the pneumatic spiral spray combines with it efficiently, which verifies the dust control and reduction effect of the pneumatic spiral spray system at the transfer point, and the dust removal efficiency reaches 89.35%~93.06%, which provides relevant theoretical support for the treatment of dust pollution at the coal transfer point in underground coal mines It provides the theoretical support and means to control dust pollution at underground coal transfer points. [ABSTRACT FROM AUTHOR]

Universities are important parts of innovation ecosystems, and university technology transfer (UTT), which aims for the sustainable commercialization of sci-tech achievements, is closely related to other actors in the ecosystem. Based on the panel data of 31 provinces in mainland China, this paper empirically analyzes the spatiotemporal distribution characteristics of UTT levels from 2011 to 2019 and estimates the influencing factors using the spatial Durbin model (SDM) with an economic spatial weighting matrix from the perspective of innovation ecosystems. The results are presented as follows: (1) Although the overall level of UTT in China is low, it shows an upward trend in most provinces. In addition, the interprovincial gap is obvious, forming a ladder distribution of UTT levels increasing from west to east. (2) There is a significant spatial autocorrelation between UTT levels in the provinces. (3) Industry, economy, and informatization play significant roles in promoting UTT, while financial institutes and openness have significant inhibitory effects. The economy has a significant spatial spillover effect on UTT, while government, industry and informatization have a significant inhibitory effect on UTT in neighboring regions. (4) The direct and indirect effects of influencing factors in the Eastern Region and other regions show significant spatial heterogeneity. [ABSTRACT FROM AUTHOR]

Around the world, governments make substantial investments in public sector research and development (R&D) entities and activities to generate major scientific and technical advances that may catalyze long-term economic growth. Institutions ranging from the Chinese Academy of Sciences to the French National Centre for Scientific Research to the Helmholtz Association of German Research Centers conduct basic and applied R&D to create commercially valuable knowledge that supports the innovation goals of their respective government sponsors. Globally, the single largest public sector R&D sponsor is the U.S. federal government. In 2019 alone, the U.S. government allocated over $14.9 billion to federally funded research and development centers (FFRDCs), also known as national labs. However, little is known about how federal agencies' utilization of FFRDCs, their modes of R&D collaboration, and their adoption of non-patent intellectual property (IP) policies (copyright protection and materials transfer agreements) affect agency-level performance in technology transfer. In particular, the lack of standardized metrics for quantitatively evaluating government entities' effectiveness in managing innovation is a critical unresolved issue. We address this issue by conducting exploratory empirical analyses of federal agencies' innovation management activities using both supply-side (filing ratio, transfer rate, and licensing success rate) and demand-side (licensing income and portfolio exclusivity) outcome metrics. We find economically significant effects of external R&D collaborations and non-patent IP policies on the technology transfer performance of 10 major federal executive branch agencies (fiscal years 1999–2016). We discuss the scholarly, managerial, and policy implications for ongoing and future evaluations of technology transfer at federal labs. We offer new insights and guidance on how critical differences in federal agencies' interpretation and implementation of their R&D management practices in pursuit of their respective missions affect their technology transfer performance outcomes. We generalize key findings to address the broader innovation processes of public sector R&D entities worldwide. [ABSTRACT FROM AUTHOR]

Alzheimer's disease (AD) affects the quality of life as it causes; memory loss, difficulty in thinking, learning, and performing familiar tasks. Resting-state functional magnetic resonance imaging (rs-fMRI) has been widely used to investigate and analyze different brain regions for AD identification. This study investigates the effectiveness of using correlated transfer function (CorrTF) as a new biomarker to extract the essential features from rs-fMRI, along with support vector machine (SVM) ordered hierarchically, in order to distinguish between the different AD stages. Additionally, we explored the regions, showing significant changes based on the CorrTF extracted features' strength among different AD stages. First, the process was initialized by applying the preprocessing on rs-fMRI data samples to reduce noise and retain the essential information. Then, the automated anatomical labeling (AAL) atlas was employed to divide the brain into 116 regions, where the intensity time series was calculated, and the CorrTF features were extracted for each region. The proposed framework employed the SVM classifier in two different methodologies, hierarchical and flat multiclassification schemes, to differentiate between the different AD stages for early detection purposes. The ADNI rs-fMRI dataset, employed in this study, consists of 167, 102, 129, and 114 normal, early, late mild cognitive impairment (MCI), and AD subjects, respectively. The proposed schemes achieved an average accuracy of 98.2% and 95.5% for hierarchical and flat multi-classification tasks, respectively, calculated using ten folds cross-validation. Therefore, CorrTF is considered a promising biomarker for AD early-stage identification. Moreover, the significant changes in the strengths of CorrTF connections among the different AD stages can help us identify and explore the affected brain regions and their latent associations during the progression of AD. [ABSTRACT FROM AUTHOR]

Innovation is intrinsically dependent on the construction of local infrastructure. Using panel data on 285 cities in China, we empirically examined the impact of high-speed rails on urban innovation and the mechanism underlying this effect. We found that high-speed rails significantly increase urban innovation. In our analysis, high-speed rails were found to increase the agglomeration of innovation factors, including population and investment, which in turn increase urban technological innovation. The agglomeration of investment factors brought about by high-speed rails is the main source of the improvement in urban innovation. Through the use of a spatial panel model, we found that high-speed rails promote knowledge dissemination and technology spillovers among the cities along high-speed railways, thus improving their innovation levels. However, the existing effects of high-speed rails on innovation exhibit spatial heterogeneity. We confirmed the effect of high-speed rails on innovation and explored the mechanism underlying this effect by considering the effects of factor agglomeration and knowledge spillovers. Our conclusions can be used as a resource by policymakers to stimulate knowledge and technology diffusion, which in turn cultivates and stimulates urban innovation. [ABSTRACT FROM AUTHOR]

Quality control of biopharmaceuticals such as monoclonal antibodies (mAbs) has been evolving and becoming more challenging as the requirements of the regulatory agencies increase due to the demanding complexity of products under evaluation. Mass Spectrometry (MS)-based methods such as the multi-attribute method (MAM) are being explored to achieve a deeper understanding of the attributes critical for the safety, efficacy, and quality of these products. MAM uses high mass accuracy/high-resolution MS data that enables the direct and simultaneous monitoring of relevant product quality attributes (PQAs, in particular, chemical modifications) in a single workflow, replacing several orthogonal methods, reducing time and costs associated with these assays. Here we describe a MAM implementation process using a QTOF high resolution platform. Method implementation was accomplished using NIST (National Institute for Standards and Technology) mAb reference material and an in-process mAb sample. PQAs as glycosylation profiles, methionine oxidation, tryptophan dioxidation, asparagine deamidation, pyro-Glu at N-terminal and glycation were monitored. Focusing on applications that require batch analysis and high-throughput, sample preparation and LC-MS parameters troubleshooting are discussed. This MAM workflow was successfully explored as reference analytical tool for comprehensive characterization of a downstream processing (DSP) polishing platform and for a comparability study following technology transfer between different laboratories. [ABSTRACT FROM AUTHOR]

Background: Successful implementation of medical technologies applied in life-threatening conditions, including extracorporeal membrane oxygenation (ECMO) requires appropriate preparation and training of medical personnel. The pandemic has accelerated the creation of new ECMO centers and has highlighted continuous training in adapting to new pandemic standards. To reach high standards of patients' care, we created the first of its kind, National Education Centre for Artificial Life Support (NEC-ALS) in 40 million inhabitants' country in the Central and Eastern Europe (CEE). The role of the Center is to test and promote the novel or commonly used procedures as well as to develop staff skills on management of patients needing ECMO. Method: In 2020, nine approved and endorsed by ELSO courses of "Artificial Life Support with ECMO" were organized. Physicians participated in the three-day high-fidelity simulation-based training that was adapted to abide by the social distancing norms of the COVID-19 pandemic. Knowledge as well as crucial cognitive, behavioral and technical aspects (on a 5-point Likert scale) of management on ECMO were assessed before and after course completion. Moreover, the results of training in mechanical chest compression were also evaluated. Results: There were 115 participants (60% men) predominantly in the age of 30–40 years. Majority of them (63%) were anesthesiologists or intensivists with more than 5-year clinical experience, but 54% had no previous ECMO experience. There was significant improvement after the course in all cognitive, behavioral, and technical self-assessments. Among aspects of management with ECMO that all increased significantly following the course, the most pronounced was related to the technical one (from approximately 1.0 to more 4.0 points). Knowledge scores significantly increased post-course from 11.4 ± SD to 13 ± SD (out of 15 points). The quality of manual chest compression relatively poor before course improved significantly after training. Conclusions: Our course confirmed that simulation as an educational approach is invaluable not only in training and testing of novel or commonly used procedures, skills upgrading, but also in practicing very rare cases. The implementation of the education program during COVID-19 pandemic may be helpful in founding specialized Advanced Life Support centers and teams including mobile ones. The dedicated R&D Innovation Ecosystem established in the "ECMO for Greater Poland" program, with developed National Education Center can play a crucial role in the knowledge and know-how transfer but future research is needed. [ABSTRACT FROM AUTHOR]

This paper examines the effect of social trust on university technology transfer. A large sample of Chinese universities from the 2007–2017 period was used. We find that social trust facilitates university technology transfer. The finding remain valid after a series of robustness. The mechanism test shows that social trust facilitates university technology transfer by improving the level of university-industry cooperative innovation. Our study suggests that social trust is an important factor that affects university technology transfer. [ABSTRACT FROM AUTHOR]

Subcontractors depend heavily on their prime contractor and thus find it very risky to enter a new business on their own. This study proposes a framework for these subcontractors to develop blue ocean technologies related to their prime contractor. First, the primary technologies predicted to be promising are extracted from the business reports of the prime contractor. Sub-technologies are then selected through a patent-based search using keywords and International Patent Classification codes of the primary technologies. From them, blue ocean technologies are proposed by optimizing the weighted mean of the min-max normalized market value, degree of competition in the technology market, and subcontractors' potential technological capabilities for each sub-technology. This study shows that subcontractors can enhance their technology competitiveness by finding a low-risk blue ocean technology. Our empirical research on the subcontractors of a semiconductor firm identified technological patent fields for them to pursue. From our framework, subcontractors can identify blue ocean technologies by considering their prime contractor's future industrial areas and technologies of interest as well as their own technological capabilities. Furthermore, the prime contractors can gain the synergy effect of technology expansion through cooperation. [ABSTRACT FROM AUTHOR]

Studies of research policies and scientific production are essential for strengthening educational systems and achieving objectives such as quality improvement. The aim of this study was to evaluate the influence of research policies on the scientific production of public and private Peruvian universities. An observational, descriptive, secondary analysis study of the research policies of 92 universities and two graduate schools licensed by the National Superintendence of Higher Education of Peru (SUNEDU) was conducted for the period from 2016–2020. Scientific publications from educational institutions were collected from Scopus and Web of Science for the study period, and researchers certified by the National Council of Science and Technology of Peru (CONCYTEC) were divided by group and level. Multiple regression analysis was performed using two models. The analysis indicated that research policies did not influence scientific production in Scopus or Web of Science in either 2019 or 2020 (Model I) but that type of management (p < 0.01), number of National Scientific, Technological, and Technological Innovation Registry (RENACYT) researchers (p < 0.001) and 2016 scientific production (p < 0.001) did influence production when these variables were incorporated into the model (Model II). However, time of licensing and management type had no effects. The number of research policies implemented by Peruvian universities and licensed graduate schools was not large. Therefore, it is recommended that project funding policies, research training, and research collaboration be strengthened and that the management capacity of research centers and institutes be increased. [ABSTRACT FROM AUTHOR]

Prior research showed that there is a growing consensus among researchers, which point out a key role of external knowledge sources such as external R&D and technologies in enhancing firms´ innovation. However, firms´ from catching-up Central and Eastern European (CEE) countries have already shown in the past that their innovation models differ from those applied, for example, in Western Europe. This study therefore introduces a novel two-staged model combining artificial neural networks and random forests to reveal the importance of internal and external factors influencing firms´ innovation performance in the case of 3,361 firms from six catching-up CEE countries (Czech Republic, Slovakia, Poland, Estonia, Latvia and Lithuania), by using the World Banks´ Enterprise Survey data from 2019. We confirm the hypothesis that innovators in the catching-up CEE countries depend more on internal knowledge sources and, moreover, that participation in the firms groups represents an important factor of firms´ innovation. Surprisingly, we reject the hypothesis that foreign technologies are a crucial source of external knowledge. This study contributes to the theories of open innovation and absorptive capacity in the context of selected CEE countries and provides several practical implications for firms. [ABSTRACT FROM AUTHOR]

The innovation of a particular company benefits the whole industry when innovation technology transfers to others. Similarly, the development and innovation in internet companies influence the development and innovation of the industry. This investigation has applied a unique approach of meta-frontier analysis to estimate and analyze the innovation in internet companies in China. A unique dataset of Chinese internet companies from 2000 to 2017 has been utilized to estimate and compare the innovation over the period of study. The change in technology gap ratio (TGR) and a shift in production function have translated into innovation which was overlooked by previous studies. It is found that the production function of internet companies is moving upward in the presence of external factors such as smartphones invention, mobile internet, mobile payments, and artificial intelligence, etc. Consequently, a sudden increase in TGR is captured due to the innovation of some companies. Hence, the average TE of the industry falls caused by the increased distance of other companies form industry production function. However, the innovation advantage defused when other companies start imitating and the average TE elevates. A steady increase in the TGR index revealed that the continuous innovation-based growth of some companies lifting the production frontier upward. This provides the opportunity for other companies to imitate and provides continuous growth in the industry. This study provides a novel methodological approach to measure innovation and also provide practical implication by empirical estimation of innovation in Chinese internet companies. [ABSTRACT FROM AUTHOR]

The innovation value chain is an effective tool for analysing innovation activities and reflects the process of value creation and increase in innovation activities. From the perspective of innovation value chains, we divided patent innovation activities into three stages: knowledge innovation stage, applied research stage and patent commercialization stage. The panel data from 64 universities directly managed by the Ministry of Education from 2009 to 2017 were used and several conclusions were drawn: 1) In the initial stage of knowledge innovation, the fundamental research fund plays a crucial promoting role, and knowledge innovation achievements are mainly published academic papers. 2) In the applied research stage, the knowledge innovation in the early stage and the fund investment in R&D activities have a significant positive effect on the patent output of universities, but the personnel investment has a negative effect. 3) In the final stage of patent commercialization, preliminary research results have a positive impact on patent commercialization, whose marginal effect depends on the industry-university-research relationship, external competition and reputation of the university. The evidence showed that there is a feedback channel between university patent commercialization and knowledge innovation, and new knowledge generated by the interaction with the outside world in the process of patent commercialization was transmitted to the subject of knowledge innovation through this channel, forming a virtuous dynamic cycle. By analysing the driving factors of the value chain of patent innovation in colleges and universities, we provided empirical evidence for the operation mechanism and policy formulation of college patents in China. [ABSTRACT FROM AUTHOR]

University dropout is a growing problem with considerable academic, social and economic consequences. Conclusions and limitations of previous studies highlight the difficulty of analyzing the phenomenon from a broad perspective and with bigger data sets. This paper proposes a new, machine-learning based method, able to examine the problem using a holistic approach. Advantages of this method include the lack of strong distribution hypothesis, the capacity for handling bigger data sets and the interpretability of the results. Results are consistent with previous research, showing the influence of personal and contextual variables and the importance of academic performance in the first year, but other factors are also highlighted with this model, such as the importance of dedication (part or full time), and the vulnerability of the students with respect to their age. Additionally, a comprehensive graphic output is included to make it easier to interpret the discovered rules. [ABSTRACT FROM AUTHOR]

The paper introduces structural diversity as a new approach to quantify the complexity of technologies. By modeling technologies as combinatorial networks, a measure of technological complexity is derived that represents the diversity of (sub-)network topologies in these networks. It is further argued that this measure can be empirically approximated with the Network Diversity Score (NDS). The paper also presents an application of this approach to European patent data from 1980 to 2015. On this basis, the measure of structural diversity is shown to replicate a number of stylized facts commonly associated with technological complexity: Complexity increases over time and younger technologies are more complex than older technologies. Complex technologies are also associated to larger R&D efforts and require more collaborative R&D activities. Lastly, when controlling for technologies’ size, technologies scoring high on structural diversity are also shown to concentrate in space. [ABSTRACT FROM AUTHOR]

The rapid development and diffusion of new technologies such as automation and artificial intelligence makes life more convenient. At the same time, people may develop overdependence on technology to simplify everyday tasks or to reduce the level of effort required to accomplish them. We conduct a two-phase real-effort laboratory experiment to assess how external assistance affects subsequent revealed preferences for the convenience of a lower level of effort versus monetary rewards requiring greater effort. The results suggest that men treated with external help in the first phase tend to choose more difficult options with potentially higher monetary rewards. In contrast, after being treated with external help, women exhibit a stronger propensity to utilize the convenience of an easier task and are less likely to choose a more difficult option that carries higher potential earnings. [ABSTRACT FROM AUTHOR]

In homes, problems in daily functioning of older people often occur in the bathroom, especially in the transfers to the toilet and/or shower/bath. Assistive products have the potential to maximise functional independence (i.e. performance without assistance from another person) in everyday activities; however, more research is needed to better understand the impact of this technology on independence in the transfers in the bathroom. Additionally, little is known about the role of the environmental factors in the process of implementing bathroom adaptations. Therefore, this cross-sectional study aimed to examine the relationship between the use of assistive products and independence in the transfers in the bathroom. The secondary objective was to determine the role of the environmental factors in predicting the implementation of bathroom adaptations. 193 community-dwelling older adults with disabilities in the basic activities of daily life, who requested public long-term care services in Spain, were included. Data was collected in the participant´s homes using a standardised assessment procedure. There was no significant association between the number of categories of assistive products used in the toilet transfer and the independent performance of this task. In a multivariate model, the number of categories of assistive products used in the transfer to shower/bath was positively associated with the independent performance of this transfer (OR = 2.59, 95%CI = 1.48–4.53; p = 0.001). A multivariate analysis revealed that social functioning was significantly associated with the implementation of a bathroom adaptation; social risk was lower in participants who made an adaptation (OR = 0.76, 95%CI = 0.63–0.93; p = 0.006). Assistive products may play an important role in promoting independence in the bathroom. Assistive product needs should be addressed when planning community-based interventions aimed at improving daily life. Moreover, social functioning had a strong influence on the installation of bathroom adaptations, suggesting the importance of paying special attention to social factors in the home adaptations planning process. [ABSTRACT FROM AUTHOR]

Future impacts of climate change on marine fisheries have the potential to negatively influence a wide range of socio-economic factors, including food security, livelihoods and public health, and even to reshape development trajectories and spark transboundary conflict. Yet there is considerable variability in the vulnerability of countries around the world to these effects. We calculate a vulnerability index of 147 countries by drawing on the most recent data related to the impacts of climate change on marine fisheries. Building on the Intergovernmental Panel on Climate Change framework for vulnerability, we first construct aggregate indices for exposure, sensitivity and adaptive capacity using 12 primary variables. Seven out of the ten most vulnerable countries on the resulting index are Small Island Developing States, and the top quartile of the index includes countries located in Africa (17), Asia (7), North America and the Caribbean (4) and Oceania (8). More than 87% of least developed countries are found within the top half of the vulnerability index, while the bottom half includes all but one of the Organization for Economic Co-operation and Development member states. This is primarily due to the tremendous variation in countries’ adaptive capacity, as no such trends are evident from the exposure or sensitivity indices. A negative correlation exists between vulnerability and per capita carbon emissions, and the clustering of states at different levels of development across the vulnerability index suggests growing barriers to meeting global commitments to reducing inequality, promoting human well-being and ensuring sustainable cities and communities. The index provides a useful tool for prioritizing the allocation of climate finance, as well as activities aimed at capacity building and the transfer of marine technology. [ABSTRACT FROM AUTHOR]

Most studies on the response of socioeconomic systems to a sudden shift focus on long-term equilibria or end points. Such narrow focus forgoes many valuable insights. Here we examine the transient dynamics of regime shift on a divided population, exemplified by societies divided ideologically, politically, economically, or technologically. Replicator dynamics is used to investigate the complex transient dynamics of the population response. Though simple, our modeling approach exhibits a surprisingly rich and diverse array of dynamics. Our results highlight the critical roles played by diversity in strategies and the magnitude of the shift. Importantly, it allows for a variety of strategies to arise organically as an integral part of the transient dynamics—as opposed to an independent process—of population response to a regime shift, providing a link between the population's past and future diversity patterns. Several combinations of different populations' strategy distributions and shifts were systematically investigated. Such rich dynamics highlight the challenges of anticipating the response of a divided population to a change. The findings in this paper can potentially improve our understanding of a wide range of socio-ecological and technological transitions. [ABSTRACT FROM AUTHOR]