This study examines the role of intellectual property protection (IPP) in enhancing radical technological innovation (RTI) within national research project teams, using an innovation-driven theory and an ability-motivation-opportunity (AMO) perspective. This study utilizes a sample of 336 national research project team members from various Chinese universities, research institutes, and corporations to analyze the theoretical model. Additionally, a two-stage hybrid partial least squares structural equation modeling (PLS-SEM) approach, combined with artificial neural network techniques (ANN), is employed to evaluate the hypotheses. The empirical findings of this study reveal a positive association between the intensity of IPP and RTI within national research project teams. Research and development investment intensity (R&DII) is identified as the primary predictor, while integrated leadership (IL) and group potential (GP) play crucial moderating roles. These groundbreaking findings extend the scope of innovation-driven and AMO theories, providing a proactive model for national research project teams to propose improvements to the IPP system, ultimately enhancing the realization of RTI.

China\'s high-quality development cannot be achieved without high-quality research. As the university is an indispensable source of advanced research, analyzing the impact of university-industry collaboration (UIC) on firm performance helps us understand the significance of universities for China\'s economic development and innovation activities. As existing research does not pay attention to the impact of UIC on the productivity of Chinese firms, we examine the impact of such collaboration on firm productivity using natural language processing and by matching China\'s intellectual property and listed firms\' operations databases. The empirical results show that UIC can promote firm productivity by improving the quality of their innovations, strengthening internalization efficiency, and broadening their research horizons. Moreover, the UIC process has a pronounced effect on promoting firm productivity in technology- and intellectual property-intensive industries. From the UIC perspective, we interpret China\'s economic development and provide new insights for developing countries regarding using universities to alleviate the insufficiency of private R&D investments.

This paper presents new evidence on knowledge flows in the Beijing-Tianjin-Hebei region of China, involving 43 cities (districts) in the Beijing-Tianjin-Hebei region, based on the invention patent transfer data from the State Intellectual Property Office of China. First, the characteristics of technology flows in the Beijing-Tianjin-Hebei region are analyzed in terms of changes in the number of flows, types of flowing subjects and spatial distribution characteristics. Then, a multi-level patent technology flow network in the Beijing-Tianjin-Hebei region was constructed, and the structural characteristics and node characteristics of each level network were explored separately. The key findings of the study are as follows. (1) The number of patented technology flows has been growing over time, showing obvious phase characteristics during the study period. As a whole, the intra-city (district) technology flow in the Beijing-Tianjin-Hebei region is higher than the inter-city (district). (2) The multi-level patent technology flow network in the Beijing-Tianjin-Hebei region shows dynamic characteristics, with more and more mobile subjects participating in the patent technology flow network, some network nodes becoming closer to each other, and the trend of small group technology flow increasing significantly. (3) Enterprises are the core hub of the patent technology flow network in Beijing-Tianjin-Hebei region. Individual invention patent technology transfer also occupies a high proportion and the participation of universities and colleges in the patent technology flow network in the Beijing-Tianjin-Hebei region is gradually increasing. (4) Over time, the flow of patent technology in the 43 cities (districts) in the Beijing-Tianjin-Hebei region has gradually become active and no longer relies excessively on a particular city (district) for patent technology transfer.

Intellectual property is crucial for the development of firms. At the micro level, firm comprehensive intellectual property ability involves abilities about intellectual property creation, utilization, protection, and management. In order to develop the comprehensive intellectual property ability of firms, the China National Intellectual Property Administration began to implement the national intellectual property demonstration advantage firm (NIPDAF) policy in 2013. Based on this exogenous policy shock, using data from listed companies from 2011 to 2020 as the research sample, the time-varying DID method is used to test the impact of the NIPDAF policy intended to cultivate comprehensive intellectual property ability on firm productivity. The results show that after policy implementation, the total factor productivity of NIPDAFs increased by about 3.3% compared to the control group. This finding is robust after a series of tests. Furthermore, the NIPDAF policy promotes firm productivity through stimulating technology innovation, improving investment efficiency, and enhancing competitive advantage. In addition, the NIPDAF policy has a more significant incentive effect on the total factor productivity of non-state-owned enterprises, firms in the eastern region, and firms in patent intensive industries.

With the widespread application of deep neural networks (DNNs), the risk of privacy breaches against DNN models is constantly on the rise, resulting in an increasing need for intellectual property (IP) protection for such models. Although neural network watermarking techniques are widely used to safeguard the IP of DNNs, they can only achieve passive protection and cannot actively prevent unauthorized users from illicit use or embezzlement of the trained DNN models. Therefore, the development of proactive protection techniques to prevent IP infringement is imperative. To this end, we propose SecureNet, a key-based access license framework for DNN models. The proposed approach involves injecting license keys into the model through backdoor learning, enabling correct model functionality only when the appropriate license key is included in the input. To ensure the reusability of DNN models, we also propose a license key replacement algorithm. In addition, based on SecureNet, we designed defense mechanisms against adversarial attacks and backdoor attacks, respectively. Furthermore, we introduce a fine-grained authorization method that enables flexible granting of model permissions to different users. We have designed four license-key schemes with different privileges, tailored to various scenarios. We evaluated SecureNet on five benchmark datasets including MNIST, Cifar10, Cifar100, FaceScrub, and CelebA, and assessed its performance on six classic DNN models: LeNet-5, VGG16, ResNet18, ResNet101, NFNet-F5, and MobileNetV3. The results demonstrate that our approach outperforms the state-of-the-art model parameter encryption methods by at least 95% in terms of computational efficiency. Additionally, it provides effective defense against adversarial attacks and backdoor attacks without compromising the model\'s overall performance.

This article aims to propose practical solutions that coordinate the conflicting interests between the global community and the pharmaceutical industry on the intellectual property (IP) waiver for COVID-19 vaccines and facilitate a more equitable vaccine supply chain in the post-COVID-19 world. We critically conducted a narrative literature review to identify procedural and practical issues in the current vaccine supply chain. The search was conducted across various academic disciplines, including biomedical science, life science, law and social science, using resources such as PubMed, Web of Science, Scopus and Westlaw. After screening 731 articles, 55 studies were selected for review. The narrative review revealed several critical barriers that hinder vaccine supply in less-developed countries (LDCs) as follows: (1) WTO Trade-Related Aspects of Intellectual Property Rights (TRIPs) waiver requests may not be granted due to its stringent consensus rule; (2) the current compulsory license system may not work due to the complexity of IP rights covering COVID-19 vaccine technologies; (3) only a few LDCs have domestic companies capable of manufacturing vaccines, and (4) political and economic tensions among countries exacerbate existing barriers to vaccine distribution in LDCs. Based on these findings, we proposed a comprehensive compulsory license system, which combines TRIPS\'s compulsory license system with the third-party beneficiary mechanism under Common Law. This integrated approach offers a balanced solution that ensures fair compensation for vaccine developers while facilitating broader vaccine access.

As China emerges as a synthetic biology (synbio) global leader, it faces distinct science-society challenges. Our series offers a snapshot of China\'s synbio state, emphasizing the intersection and its policy implications. The debut piece elucidates the intellectual property rights (IPR)-funding interplay in China\'s expanding synbio territory, underlining its key role in driving innovation and commercialization.

Institutions are the fundamental determinants of carbon emission performance. However, the environmental impact of intellectual property institution, especially its impact on carbon emissions, has been paid little attention. Therefore, the main purpose of this study is to assess the effect of intellectual property institution on carbon emission reduction, revealing a new solution to control carbon emissions. To achieve the goal, this study regards the National Intellectual Property Demonstration City (NIPDC) policy in China as a quasi-natural experiment of intellectual property institution construction and exploits the difference in difference approach to objectively evaluate the impact of intellectual property institution on carbon emission reduction based on the panel data of China\'s cities. The study draws the following important conclusions. First, compared with non-pilot cities, the NIPDC policy has reduced urban carbon emissions by 8.64% in pilot cities. In particular, the \"carbon emission reduction dividend\" of the NIPDC policy is in the long term but not in the short term. Second, the influence mechanism analysis shows that the NIPDC policy can promote carbon emission reduction by stimulating technology innovation, especially breakthrough innovation. Third, the space overflow analysis reveals that the NIPDC policy can mitigate carbon emissions in adjacent areas, resulting in obvious spatial radiation effect. Fourth, the heterogeneity analysis confirms that the carbon emission reduction effect of the NIPDC policy is more obvious in low administrative hierarchic cities, small and medium-sized cities, and western cities. As a result, Chinese policymakers should orderly promote the construction of NIPDCs, strengthen technology innovation, give full play to the spatial radiation role of NIPDCs, and optimize the role of government, so as to better release the carbon emission abatement effect of intellectual property institution.

Research Purpose. In order to study the evolution mechanism of intellectual property operation platform, value analysis in the modern digital technology-driven environment, and how to better develop the operation of intellectual property platform in the current digital technology environment; Research Methods. This paper analyzes the relationship between the development of digital economy and intellectual property operation platform, analyzes, and compares the different stages of intellectual property platform operation in the digital technology-driven environment, and compares the coupling degree of platform operation services in different environments. Research Results. From the research and analysis results, it can be seen that the operation of intellectual property rights under digital technology is of positive significance in the development of social-ecological environment, combined with the development of the industrial ecosystem, and plays a positive role in transforming intellectual property rights into market value, promoting the development of small and medium-sized enterprises and economic construction. It is of great significance to create a perfect chain of intellectual property protection and legal protection of property rights, copyrights, and transfer rights. Research Conclusion. It provides new ideas and research value for the future operation mode of intellectual property platform, provides a better guarantee platform and legal environment for China to improve the level of digital economy, creates a suitable ecological environment, and stimulates people\'s thinking potential.

Many IP (intellectual property) will also be infringed, and it will become more and more serious, causing huge economic losses to people or groups who own IP. If punitive damages can be made for intentional but intentional infringement of IP, it will help to stop intentional infringement of IP, and it can also give due compensation to the obligee\'s loss. Based on this, this paper analyzes the introduction and implementation of punitive damages in IP law. In this paper, a relatively efficient text classification method is realized by using the method of deep learning and model design. Similar texts in the training set are grouped into a group, and each group is considered as a common text vector. Then, a threshold is set to deal with clusters higher than the threshold, and the training set is reformed. Through the experimental results, the feature extraction effect of this model is improved, the classification accuracy is constantly improved, and the final convergence rate of this model reaches 95%. It has been verified that the system can realize the automatic classification of basic Chinese patent texts.