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Numerous researchers and institutions have been developing in ovo sexing technologies to improve animal welfare by identifying male embryos in an early embryonic stage and disposing of them before pain perception. This review gives a complete overview of the technological approaches reported in papers and patents by performing a thorough search using Web of Science and Patstat/Espacenet databases for papers and patents, respectively. Based on a total of 49 papers and 115 patent families reported until May 2023 worldwide, 11 technology categories were defined: 6 non-optical and 5 optical techniques. Every category was described for its characteristics while assessing its potential for application. Next, the dynamics of the publications of in ovo sexing techniques in both paper and patent fields were described through growth curves, and the interest or actual status was visualized using the number of paper citations and the actual legal status of the patents. When comparing the reported technologies in papers to those in patents, scientific gaps were observed, as some of the patented technologies were not reported in the scientific literature, e.g., ion mobility and mass spectrometry approaches. Generally, more diverse approaches in all categories were found in patents, although they do require more scientific evidence through papers or industrial adoption to prove their robustness. Moreover, although there is a recent trend for non-invasive techniques, invasive methods like analyzing DNA through PCR or hormones through immunosensing are still being reported (and might continue to be) in papers and patents. It was also observed that none of the technologies complies with all the industry requirements, although 5 companies already entered the market. On the one hand, more research and harmony between consumers, industry, and governments is necessary. On the other hand, close monitoring of the market performance of the currently available techniques will offer valuable insights into the potential and expectations of in ovo sexing techniques in the poultry industry. [ABSTRACT FROM AUTHOR]

This study employs a bibliometric approach to analyze the landscape of artificial intelligence (AI) components used in performance measurement. As organizations increasingly leverage AI for optimizing processes and decision-making, understanding the trends in AI components becomes imperative. The identified AI components are classified based on their roles in enhancing performance measurement, offering insights into the prevalent methodologies and emerging technologies. The bibliometric analysis encompasses a comprehensive review of scholarly articles, conference papers, and patents, systematically exploring the evolving field. In this research, the methodology involves data extraction from reputable academic databases and patent repositories, followed by applying bibliometric techniques to quantify and visualize key aspects. The findings of this study contribute to the existing knowledge by mapping the intellectual structure of AI components for performance measurement. [ABSTRACT FROM AUTHOR]

The study utilizes bibliometrics to explore papers and patents in the field of fuel cell to examine the scientific and technical development in the area. The research data were retrieved from the WOS database and USPTO patent data from the period between 1991 and 2010, which consists of 20,758 papers and 8,112 patents. The authors analyzed numbers of papers and patents to examine the trends in the papers and patents in different countries, organizations and individuals. The results indicate upward growth in both papers and patents in fuel cell, with a higher growth rate for papers. The study shows that major paper and patent output are concentrated in a small number of countries. An imbalance exists between the number of papers published and the patents granted in organizations. The organizations that published papers and patents vary in type and category. Very few individual researchers are able to produce high numbers of both papers and patents. [ABSTRACT FROM AUTHOR]

Deep neural networks are exposed to the risk of adversarial attacks via the fast gradient sign method (FGSM), projected gradient descent (PGD) attacks, and other attack algorithms. Adversarial training is one of the methods used to defend against the threat of adversarial attacks. It is a training schema that utilizes an alternative objective function to provide model generalization for both adversarial data and clean data. In this systematic review, we focus particularly on adversarial training as a method of improving the defensive capacities and robustness of machine learning models. Specifically, we focus on adversarial sample accessibility through adversarial sample generation methods. The purpose of this systematic review is to survey state-of-the-art adversarial training and robust optimization methods to identify the research gaps within this field of applications. The literature search was conducted using Engineering Village (Engineering Village is an engineering literature search tool, which provides access to 14 engineering literature and patent databases), where we collected 238 related papers. The papers were filtered according to defined inclusion and exclusion criteria, and information was extracted from these papers according to a defined strategy. A total of 78 papers published between 2016 and 2021 were selected. Data were extracted and categorized using a defined strategy, and bar plots and comparison tables were used to show the data distribution. The findings of this review indicate that there are limitations to adversarial training methods and robust optimization. The most common problems are related to data generalization and overfitting. [ABSTRACT FROM AUTHOR]

This study provides a comprehensive analysis of global patent trends in battery recycling, focusing on secondary batteries and related technologies across Korea, China, and the United States. The methodology involved collecting data from various patent databases, followed by quantitative analysis to identify technology trends and guide future development. The research employed statistical tools to analyze patent activities, including the frequency and scope of patent filings, and comparative analysis to highlight differences between countries. This study reveals distinct emphases on technologies such as lithium-ion and waste battery recycling, highlighting notable differences in patent activities among key companies and countries. China's large number of patents in battery manufacturing processes contrasts with the USA's focus on electrochemical cell construction and storage systems, while Korea shows significant activity in waste battery technology. The novelty of this paper lies in its detailed comparative analysis of patent trends across these three major economies, providing insights into the technological focuses and priorities of each country. The study also identifies key challenges, such as the need for consistent innovation and broader geographic coverage in Korea, enhancing patent influence and international presence in China, and ensuring high patent quality and fostering innovation in lagging sectors in the United States. Addressing these challenges through enhanced collaboration, increased R&D investments, and supportive policies is crucial for strengthening the global position and driving further innovation in the battery recycling sector. [ABSTRACT FROM AUTHOR]

This paper examines the impact of environmental decentralization on the export domestic value-added rate of enterprises using combined data from 2000–2014 from China Industrial Enterprise Database, China Customs Database, WIOD, China Environment Yearbook and China Enterprise Patent Database. The research findings show that the overall environmental decentralization has an inverted U-shaped impact on enterprises' export DVAR, with 94.4% of the sample in the promotion interval. 73.2% of ordinary trade enterprises and 85.7% of processing trade enterprises are in the suppressive interval of the U-shaped impact of administrative decentralization; 69.2% of ordinary trade enterprises are in the suppressive interval of the U-shaped impact of monitoring decentralization, and 85.7% of processing trade enterprises are in the promotion range of the inverted U-shaped impact; 66.0% of ordinary trade enterprises and 86.7% of processing trade enterprises are in the suppression range of the U-shaped impact of monitoring decentralization. In addition, cost markup and R&D innovation as mediating variables are important transmission channels for environmental decentralization to influence enterprises' export DVAR. [ABSTRACT FROM AUTHOR]

While the benefits of land-use mix have been widely analyzed with regard to transportation, public health, and economic development, relatively little attention has been paid to empirically investigating the impact of land-use mix on technological innovation at the intra-urban level. Drawing upon a database of geo-coded patents that are used to reflect the capacity of technological innovation, this paper takes Shanghai as a case study and analyzes how the intra-urban distribution of technological innovation has been associated with land-use mix at the 1 km × 1 km grid cell level. Empirical results, which are robust when the grids are divided at the 2 km × 2 km level, show that the degree of land-use mix is positively associated with the number of patents for a given grid, suggesting that grids with a higher level of land-use mix are likely to have more patents, ceteris paribus. Moreover, the results demonstrate an inverted U-curve relationship between land-use mix and technological innovation, indicating that a too much higher level of land-use mix could lead to a smaller number of patents for a certain grid. In addition, the empirical results suggest the existence of spatial dependence in the effect of land-use mix on technological innovation. [ABSTRACT FROM AUTHOR]

High-quality innovation is an inevitable requirement for high-quality economic development, and an accurate grasp of the regional distribution characteristics of the level of highquality innovation development (HQID) can better understand and simulate high-quality innovation. This paper constructs a dataset of high-value inventions based on the Chinese patent database using textual analysis methods and the criteria for High-Quality Inventions proposed by the State Intellectual Property Office, and explores inter-provincial variability and convergence by using the Theil index, α convergence, and β convergence. This paper finds that High-Quality Inventions are significantly and positively correlated with various indicators measuring the quality and value of patents. In general, the overall level of HQID is on an upward trend with clear differences among provinces, which shows a regional unbalanced but overall rapid development. From the regional differences of HQID, the regional differences of HQID have been narrowed, mainly within the region. In terms of the convergence of HQID, α convergence, absolute β convergence, conditional β convergence, and club convergence exist nationally and within each region, which indicates that the gap between the national and regional levels of HQID has been narrowing over time. HQID has a positive promotion effect on the relationship between HQID and economic growth, economic growth rate, and total factor productivity. High-quality innovation can improve the quality of input factors, cultivate new dynamic energy for economic development, and then promote high-quality economic development. In the context of the shift of IP work from pursuing quantity to improving quality, the scientific understanding of high-quality innovation, the development status, and the differences of regional innovation high-quality development is of great significance for improving innovation quality and efficiency, and effectively supporting high-quality economic development. [ABSTRACT FROM AUTHOR]

Based on the database of green patents of China's A-share listed enterprises from 2001 to 2018, this paper identifies the impact of the province-managing-county (PMC) fiscal reform on the green innovation performance of enterprises by using staggered DID method. The results show that the PMC fiscal reform significantly promotes enterprises' green innovation performance, and this impact is not only reflected in the quantity of green patents but also in the quality. The mechanism test finds that the policy effect of PMC fiscal reform comes from the attraction of environmental investment and optimization of human capital structure. The PMC fiscal reform expands the financial autonomy of county governments, facilitating the compensation and allocation mechanism. Moreover, the paper incorporates the county-power-expansion (CPE) reform into the robustness test to exclude the interference of other policies in the same period. [ABSTRACT FROM AUTHOR]

Patents and citations are powerful tools increasingly used in financial economics (and management research more broadly) to understand innovation. Biases may result, however, from the interactions between the truncation of patents and citations and the changing composition of inventors. When aggregated at the firm level, these patent and citation biases can survive popular adjustment methods and are correlated with firm characteristics. These issues can lead to problematic inferences. We provide an actionable checklist to avoid biased inferences and also suggest machine learning as a potential new way to address these problems. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online [ABSTRACT FROM AUTHOR]

Purpose: With the global economic slowdown in 2023, most universities in the central and western regions of China may face the problem of shortage of government financial funding, which is directly related to the development of science and technology of the universities. With the support of the local government, most of the ordinary universities have shifted attention to the transfer and transformation of intellectual property based on school-enterprise cooperation, hoping to seek more commercialization income as an extra source of income. Therefore, this paper aimed to study the current situation of university intellectual property, i.e. the reserve and distribution of transferable patents, discipline distribution of patents, and regional cooperation of university patents. Design/methodology/approach: A patent database of 10 key universities in Henan Province of China from 2012 to 2021 was established. The evaluation indicator model by the Entropy method was conducted to reveal the interaction mechanism between quantity indicators, quality indicators, and value indicators. Based on the data analysis, the development direction of the discipline construction and school-enterprise cooperation for local universities was clear. Findings: The findings indicated that the number of patent applications from ten key universities in Henan Province has been increasing rapidly over the years. The trend for authorized invention patents has remained relatively stable. Compared with the patent applications and authorizations, the growth of transferable patents was notably slow. The significance of strategic layout of dominant disciplines and related high-value patents was not appreciated enough by Chinese government and universities. There was a large difference of dominant disciplines between 10 key universities, and the patent level of each university was directly proportional to the number of dominant disciplines. The university patent level heavily relied on the researchers' contributions and the distribution mechanism of scientific research resources within the university. Guangdong Province and the Yangtze River Delta of China, being economically developed regions, exhibited the most active engagement in patent technology cooperation. Conversely, the central and western regions displayed relatively lower participation in high-value patent research and development. Research limitations/implications: This study can provide a unique perspective to understand and solve the financial bottleneck problem of ordinary universities in the central and western regions of China. The discipline construction and school-enterprise cooperation are just one of the existing schemes, but it still cannot solve the financial problems faced by local universities in China towards the government. Practical implications: The findings of this study can serve as a foundation for further investigation into policies aimed at improving the financial problems of ordinary universities in the central and western regions of China. Originality/value: As an important attempt, the study tried to focus the financial problem of universities in the central and western regions of China based on the evaluation of the current situation of university intellectual property. This research findings are of great value in finding optimal layout between university patents, disciplines and school-enterprise cooperation. [ABSTRACT FROM AUTHOR]

A large part of big data consists of text documents such as papers, patents or articles. To analyze text data, we have to preprocess the text documents and build a structured data based on a document-word matrix using various text mining techniques. This is because statistics and machine learning algorithms used in text analysis require structured train data. The row and column of the matrix are document and word, respectively. The element of the matrix represents the frequency value of the word occurring in each document. In general, because the number of words is much larger than the number of documents, most elements have zero values. Due to the sparsity problem caused by inflated zeros, the performance of the predictive model has decreased. In this paper, we propose a method to solve the sparsity problem and improve the model performance in text data analysis. We perform compound Poisson linear modeling to make the proposed method. To show the performance of our proposed method, we collect and analyze the patent documents from patent databases. In our experimental results, we compared the value of the Akaike information criterion (AIC) of the proposed model with traditional models, such as linear model, generalized linear model and zero-inflated Poisson model. Additionally, we illustrated that the AIC value of our proposed model is smaller than others. Therefore, we verify the validity of this paper. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Management & Business Research (2521-4306) is the property of Chinese Management Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Periodontal disease is an inflammatory condition characterized by an aberrant immune response against a dysbiotic dental biofilm, with oxidative stress performing an essential role in its pathogenesis. This paper presents a patent mining, performed in the Orbit Intelligence patent database, related to antioxidant phytochemicals in the technological developments that are working to prevent and treat periodontal disease. To access the documents, the descriptors "PERIODONTAL" and "ANTIOXIDANT" were typed in the title, abstract, and claim search fields. A total of 322 patents demonstrate the growing interest in researching natural antioxidants for scientific and technological purposes. The top ten countries regarding the number of family patents produced were the United States, the European Office, Japan, South Korea, China, India, Mexico, Denmark, Canada, and Great Britain. The most cited compounds were vitamin C, green tea, quercetin, melatonin, lycopene, resveratrol, and curcumin. These compounds have been used for the technological development of gels, membranes, dentifrices, chewing gum, orally disintegrating film, mouthwash, mouth spray, and mouth massage cream and exhibit the ability to neutralize free radicals and reduce oxidative stress, a critical factor in the development and progression of periodontal diseases. The patent documents have shown that using antioxidant compounds in conjunction with traditional periodontal treatments is a promising area of interest in periodontal therapy. [ABSTRACT FROM AUTHOR]

Patent monetisation is an important source of revenues worldwide. This activity is increasingly carried out by patent assertion entities (PAE), which are at the origin of about 40% of infringement actions filed in the United States. This paper uses an original database of US patents reporting PAE patent acquisitions. We document two key empirical facts about the presence of PAEs in the market for patents. First, PAEs build large patent portfolios and contribute significantly to patent transfers in the US. Second, their impact on follow-on innovation is, on average, negative. With a series of dynamic diff-in-diffs analyses, we estimate a significant post-transfer drop in forward citations received by patents acquired by PAEs. This drop is not immediate but takes some years to materialise. Heterogeneity tests show that our results are driven by acquisitions of old and highly cited patents, as well as by patent acquisitions by large patent aggregators. [ABSTRACT FROM AUTHOR]

There is currently a great deal of confusion about the impact of robotisation, mainly due to the lack of clarity in research on timeframes and technologies. To overcome this, we distinguish between two basic narratives. The first - 'robots in the cages' - is an old story of automation which means that the industrial robots are pre-programmed high-precision machines that are used on a large scale but only in a few industries. In contrast, the emerging story - 'robots are moving out of the cages' - is about the more flexible and autonomous robots at present used on a small scale in the service sector, albeit the application areas are expanding rapidly.The objectives of this paper are first to analyse these two stories in terms of their technological, industrial and organisational characteristics, second, to examine the geographical pattern of global competition for robotisation in these narratives, and third, to discuss briefly the policy challenges involved. For the analysis, we use information from the International Federation of Robotics, the EPO Worldwide Patent Statistical Database (PATSTAT) and the Dealroom.co start-up database. [ABSTRACT FROM AUTHOR]

Purpose: How does university-firm collaboration affect the performance of both universities and firms? The purpose of this paper is to evaluate university-firm collaborations aimed at expanding the treatment effects of collaboration ambition on university academic performance as well as collaboration ambition focused on the firm's production of innovation and financial performance for the top 110 US universities and the top 200 US R&D performing firms. Design/methodology/approach: "Two studies, based on the three archival data sets (National Bureau of Economic Research-Rensselaer Scientific Papers Database and the Harvard Dataverse Network (DVN) US Patent Citations database and Compustat database), are undertaken in the top 110 US universities and the top 200 US R&D performing firms." The study introduces a theoretical model that explicitly addresses collaboration diversity, number of collaborations, knowledge stock and the endogeneity problem that is generated by self-selection of collaboration ambition in university and firm's performance. Findings: The results suggest that the effects of adopting proactive collaboration decision on academic performance are insignificant in the firm subsample. However, more interestingly, the authors find supporting evidence of the negative impact of collaboration on university groups. The authors also find that collaboration diversity, knowledge stock and collaboration ambition lead to stronger firm performance but the number of collaborations is smaller on firm performance. Furthermore, the authors find that collaboration ambition moderates the positive effect of the number of collaborations on firm performance. Practical implications: University-firm collaboration is a multifaceted relationship, suggesting that the empirical analysis can be interpreted through the university and the firm view to enhance the understanding of the collaboration for performance creation. This study articulates the positive role of collaboration diversity, knowledge stock and collaboration ambition and the negative role of the number of collaborations on university-firm collaboration in terms of university and firm performance. Moreover, proactive collaboration ambition has the positive effect of a higher number of collaborations on firm performance. The authors conclude that policy should refrain from overly focusing on collaboration diversity, number of collaborations, knowledge stock and collaboration ambition, and the authors consider the interactions between the number of collaborations and collaboration ambition on university-firm collaboration when discussing their effects on mutual performance. Originality/value: This study demonstrates the effects of university-firm collaboration on academic performance. In addition, the authors discuss the factors that influence collaboration to help the firm to increase its innovation and financial performance. Therefore, it would be interesting to see simultaneously how university-firm collaboration affects the performance of both partners. [ABSTRACT FROM AUTHOR]

Technology prediction is an important technique to help new energy vehicle (NEV) firms keep market advantage and sustainable development. Under fierce competition in the new energy industry, there is an urgent necessity for innovative technology prediction method to effectively identify core and frontier technologies for NEV firms. Among the various methods of technology prediction, one of the most frequently used methods is to make technology prediction from patent data. This paper synthesizes the frequent pattern growth (FP-growth) algorithm and input-output analysis to construct a new technology prediction method based on the knowledge flow perspective, takes the data of NEV patent family in 1989–2018 the Derwent patent database as a sample, divides the data according to the 5-year standard, and uses the method to identify the core and frontier technologies in the NEV field during different periods. Furthermore, the multiple co-occurrence method applies to analyze the technology layout and evolution patterns in China's NEV field. The results show that the technology prediction method proposed in this paper can effectively identify core and frontier technologies to achieve NEV technology prediction. [ABSTRACT FROM AUTHOR]

Plastic pollution is one of the major problems being faced by the world today. The lack of proper recycling and insufficient waste management practices; leaves more than 55% of plastic waste unattended resulting in open dumping of plastic waste. Microplastic pollution is one of the niche areas of study addressed by a few researchers and inventors. Researchers are working on various aspects concerned with the microplastic impact on marine, freshwater, and soil environment. The paper covers a detailed patent landscape for analysis, extraction, identification, and separation techniques for microplastics in marine, freshwater, and soil ecosystem. The patent analysis is performed through the IP classification, applicants, and inventor's details, citation analysis, patent grant, kind codes, country codes, document types, and jurisdictions. The paper also includes relevant bibliometric analysis of the research publications in the area of microplastics identification, separation, and analysis techniques supporting the patent landscape to understand the overall research scenario in the area of microplastic pollution. The patent landscape is done by using the Lens patent database, Espacenet, and applications such as MS excel and origin. The objective of this study is to provide an overview of the research trends and the need for research and innovation in the field of microplastics pollution, considering the patenting activity and publications as an indicator of innovation. [ABSTRACT FROM AUTHOR]

In situ gelling systems represent a burgeoning paradigm in ocular drug administration, addressing intrinsic challenges posed by extant ocular formulations, such as compromised bioavailability and constraints in traversing the corneal barrier. This systematic review endeavours to comprehensively examine the contemporary landscape of research in this domain, focusing on the nuanced capabilities of in situ gelling systems to optimize drug delivery and enhance therapeutic outcomes, without much technological complexity. Employing a meticulous search strategy across diverse databases for publications and patents spanning the years 2015 to 2023 a total of 26 research papers and 14 patents meeting stringent inclusion criteria were identified. Synthesizing the collective insights derived from these investigations, it becomes evident that in situ gelling systems confer an ability to protract the residence time of formulations or active pharmaceutical ingredients (APIs) within the ocular milieu. This sustained presence engenders extended drug release kinetics, thereby fostering improved patient compliance and mitigating the proclivity for side effects attendant to frequent dosing. These salutary effects extend to diminished systemic drug absorption, augmented ocular bioavailability, and the prospect of reduced dosing frequencies, thereby amplifying patient adherence to therapeutic regimens. Intriguingly, the protective attributes of in situ gelling systems extend to the establishment of an ocular surface barrier, thereby abating the susceptibility to infections and inflammatory responses. In summation, this review underscores the auspicious potential of in situ gelling systems as a transformative approach to advancing ocular drug delivery, warranting sustained research endeavours and developmental initiatives for the betterment of global patient outcomes. [Display omitted] • In situ gels for ocular delivery offer simple alternative to conventional low performing drops • Various polymer and polymer combinations are used for in situ gelling, each with distinct mechanism and advantages. • Gelling upon application enhances drug retention and improves ocular bioavailability. • In situ gel-forming systems represent advanced ocular drug delivery, with enhanced therapeutic outcomes for eye disorders. • This review covers recent research and patents, focusing on ophthalmic applications of in situ gels. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to examine how financial technology (FinTech) knowledge from foreign firms flows into and among elite commercial banks in Hong Kong's financial sector to drive innovation. Design/methodology/approach: Using social network analysis and regression analysis on a novel database of patents held by Hong Kong's elite commercial banks, this paper examines the relationships between network position and FinTech knowledge flow. Findings: This paper finds four untold patterns of innovation and inequality in Hong Kong's financial sector: only three banks are responsible for all the FinTech knowledge entering Hong Kong; most foreign FinTech comes from the USA through Hong Kong and Shanghai Banking Corporation, whereas most FinTech from China enters through Fubon Bank and Development Bank of Singapore; older banks and banks with more connections to firms inside Asia are more likely to import FinTech; the most beneficial sources of FinTech for a bank's network position are firms from outside Asia. Originality/value: Despite the well-documented volumes of cross-border and cross-continental movement of financial institutions in Hong Kong, there is little work on the knowledge flows that underwrite this mobility. This paper addresses this gap by using FinTech knowledge flows to map the distribution of innovation, network position and competitive advantage in Hong Kong's financial sector. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to understand to what extent open innovation (OI) is utilized in R&D departments by using patents as a main source. The paper adopts the "designation of the inventor" as a new method for detecting open or closed innovation, a method which examines the type of relationship that exists between the inventor(s) and the patent applicant(s). Since the openness or closedness of an invention is mainly measured by analyzing a firm's co-applicants, the patent's designation of the inventor indicates whether or not inventors are employees of the applicant. The paper offers new empirical evidence about whether a patent is open or not without surveying inventors and it complements previous studies that failed to describe whether a patent is based on open or closed innovation. After studying a collection of 231 patents in the wind energy sector obtained from the European Patent database, descriptive statistics show that OI Patents (OIPs) where the inventor is under agreement represent approximately 90% of the total number of OIPs, which in turn account for more than 23% of the total number of closed and open types of patent. Additionally, the designation of inventor method is also able to identify closed innovation-based patents. The results also show that a minority of companies utilize a hybrid type of OI, in which the inventors are composed of a mix of external individuals and employees. The results suggest that the method proposed yields a better understanding of how OI as well as other innovation strategies are utilized by firms in a particular industry or technological field. [ABSTRACT FROM AUTHOR]

Purpose: This work presents a study on the female involvement in patent applications in all 23 Ibero-American countries that are WIPO members, in order to measure gender inequalities in institutional collaborations and technological fields, across time. Design/methodology/approach: The data used in this paper come from EPO Worldwide Patent Statistical Database (PATSTAT). PATSTAT contains bibliographical data relating to more than 100 million patent documents from leading industrialized and developing countries, as well as legal event data from more than 40 patent authorities contained in the EPO worldwide legal event data (INPADOC). The extracted subset is composed of 150,863 patent applications with priority years between 2007 and 2016. Findings: Our observations indicate that even in more dynamic economies such as Portugal and Spain, the participation of women per patent applications does not exceed 30%. Additionally, the distribution of female participation among institutional sectors and technological fields is consistent with previous studies in other regions and indicate a socio-cultural divide. Research limitations: Unisex names were not considered and were counted as gender unknown, and patent applications for which no inventor information was available were discarded, but further effort of data analysis may provide more information about gender inequalities. Practical implications: While patents are imperfect variables of inventive step and therefore should be considered as a variable proxy of innovation, our findings may help to guide the implementation of policies for balancing gender participation in innovative activities, as well as instigating research into the issues causing divisive participation along gender lines. Originality/value: While there is a widespread effort into evaluating and improving the participation of groups recognized as minorities within state-of-the-art activities, research about women participation in the innovation sector is fragmented due to differing regional characteristics: industrial and academic segmentation, socio-economic disparities, and cultural factors. Thus, localized studies present an opportunity of filling the gaps of knowledge on societal participation in innovation activities. [ABSTRACT FROM AUTHOR]

The Internet of Things technology has entered a stage of rapid development, and the development trends and innovative features of it are worth exploring in depth. The purpose of this paper is to provide a comprehensive analysis of the current research focus and innovation characteristics of the Internet of Things technology, and it puts forward policy recommendations for countries in the future development. In this paper, the Internet of Things technology based on Scopus database is divided into five technical sub-fields by means of bibliometric. Patentometrics is used to make the systematic analysis of Internet of Things Technology and its various technical sub-fields based on Derwent Patent Database, and the analysis explores the innovative features of Internet of Things technology and its various technical sub-fields. Research shows that the research focus and innovation characteristics of countries in the Internet of Things technology are not the same. [ABSTRACT FROM AUTHOR]

As new energy vehicle (NEV) is the future of automobile development, it is of great significance to dig deeper into the technical topics and development trends of new energy vehicles for accurately understanding the technical trends of the new energy vehicle industry, grasping development opportunities, and scientifically formulating strategic plans. This paper takes the patent texts in the field of new energy vehicles from 2000 to 2020 in the patent database of CNKI as the data source, identifies 25 technical topics implied in the patent texts by using the LDA (Latent Dirichlet Allocation) topic model, analyzes the evolution trend of the 25 technical topics in terms of importance and popularity, and predicts the popularity and development trend of each technical topic in new energy vehicles from 2021 to 2025 by constructing the ARIMA model. The popularity and development trend of each technology topic of new energy vehicles in China from 2021 to 2025 are predicted by constructing ARIMA model. Drawing on quantitative evidence, the study found that there are top five technical topics in terms of importance in this field, namely, Topic 8 (Installation and Fixation), Topic 5 (Heat Dissipation), Topic 14 (Vehicle Data Monitoring), Topic 9 (Charging Pile), and Topic 15 (Damping). From 2014 to 2020, the importances of Topic 5 (Heat Dissipation), Topic 8 (Installation and Fixation), Topic 6 (Electric Drive System), Topic 9 (Charging Pile), and Topic 15 (Damping) are gradually rising. In terms of popularity of technical topics, from 2014 to 2020, the first to fifth topics are Topic 20 (Safety), Topic 8 (Installation and Fixation), Topic 3 (Cable Insulation Materials), Topic 15 (Damping), and Topic 10 (Pump Cooling). Based on the prediction of ARIMA model, it is found that the popularity of these five technical topics is steadily increasing from 2021 to 2025, among which the popularity of Topic 20 (Safety) will increase from 63.58 to 113.07, the largest increase in popularity among all technical topics. The paper provides implications for countries dedicated to developing the new energy vehicle industry. [ABSTRACT FROM AUTHOR]

Copyright of Papers in Regional Science is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, we investigate the phenomenon of patent collateralization by empirically focusing on the factors that affect the outcome of the collateralization process. In particular, we want to examine to what extent patent quality, lenders' characteristics, as well as lenders' selection capabilities (i.e. in identifying high-quality patents) affect the likelihood of observing a security interest release. We identify the patents recorded in security agreements and their release from the USPTO Patent Assignment database. The final dataset is made up of a total of 8818 security interest agreement records, involving 133,110 patents pledged as collateral for debt between 2007 and 2010. We find evidence that a security interest is more likely to be released for patents with a higher technical merit and when the lenders are more experienced and are specialty finance companies. When considering other types of lenders (i.e. banks in particular) or less experienced lenders, the positive association between the security interest release and the technical merit of the pledged patent is lower. The evidence suggests that IP-backed loans represent an effective financial channel for those firms that control valuable intangible assets and that experience and specialization allow lenders to develop better selection capabilities. [ABSTRACT FROM AUTHOR]

Understanding NLP patents provides valuable insights into innovation trends and competitive dynamics in artificial intelligence. This study uses the Lens patent database to investigate the landscape of NLP patents. The overall patent output in the NLP field on a global scale has exhibited a rapid growth over the past decade, indicating rising research and commercial interests in applying NLP techniques. By analyzing patent assignees, technology categories, and geographic distribution, we identify leading innovators as well as research hotspots in applying NLP. The patent landscape reflects intensifying competition between technology giants and research institutions. This research aims to synthesize key patterns and developments in NLP innovation revealed through patent data analysis, highlighting implications for firms and policymakers. A detailed understanding of NLP patenting activity can inform intellectual property strategy and technology investment decisions in this burgeoning AI domain. [ABSTRACT FROM AUTHOR]

Fast and effective forecasting of the new generation of products is key to enhancing the competitiveness of a company in the market. Although the technological evolution laws in the theory of the solution of inventive problems (TRIZ) have been used to predict the potential states of products for innovation, there is a lack of effective methods to select the best technological evolution law consistently with product replacement and update, and acquiring potentially new technologies and solutions, which relies heavily on designers' experience and makes it impossible for designers to efficiently use the technological evolution laws to stimulate product innovation. Aimed to bridge this gap, this paper proposes an integrated method consisting of three main steps, combining the technological evolution laws with back propagation neural network (BPNN), international patent classification (IPC) knowledge and company's technological distance. The best technical evolution law is first searched by a BPNN. The functional verbs and effects in the IPC are then extracted and searched for potential technologies in the Spyder-integrated development environment. Finally, the company's technological distance is used to select analogous sources of potential solutions in the patent database. The final innovative design is determined based on the ideality. The proposed method is applied in the development of a steel pipe-cutting machine to verify its feasibility. The proposed method reduces the dependence on designers' experience and provides a way to access cross-domain technologies, providing a systematic approach for the technological evolution laws to motivate innovative product design. [ABSTRACT FROM AUTHOR]

Due to the particularity of biomedical industry, it has become necessary for biomedical enterprises to seek innovative research and development (R&D) cooperation to maintain advanced technologies and products in multiple fields. Under such circumstance, the biomedical industry has gradually formed a certain cluster to promote the development of the industry. So far, the biomedical industry cluster has formed in China, mainly within the Yangtze River Delta, Pearl River Delta, and Beijing-Tianjin-Hebei three urban agglomerations. Within the industrial clusters, the frequency of innovation cooperation among enterprises, universities, research institutions, and other relevant organizations in the biomedical area is high, and the capacity for innovation cooperation is strong as well. This paper used the representative cross-section data of cooperative patents from the medical science and technology patent database of China National Knowledge Infrastructure (CNKI), researching the R&D cooperation within the three major urban agglomerations in China from 2008 to 2016 (Yangtze River Delta Urban Agglomeration, Pearl River Delta Urban Agglomeration, Beijing-Tianjin-Hebei Urban Agglomeration) on total 36 cities' spatial pattern characteristics of biomedical cooperation and the influencing factors. The spatial interaction model was used to study the spatial, economic, political, and R&D influencing factors of cross-city cooperation. The degree of aggregation showed that cross-city R&D cooperation mainly occurred in well-developed and central cities of urban agglomerations. Econometric results revealed that spatial, economic, political, and R&D bias factors did have a significant impact on the frequency of biomedical R&D cooperation across cities. [ABSTRACT FROM AUTHOR]

Previous papers have approached direct and indirect self-citations at a firm-level considering that firms that internalize more self-knowledge are also those with a more accumulated stock of knowledge, which translates into greater absorptive capacity. When these firms internalize their own knowledge, they are appropriating the returns of their own previous investments in R&D. This paper applies an indirect self-citation measure as a proxy for absorptive capacity of knowledge spillovers in regions to test whether specialization in more basic knowledge technologies facilitates or hampers the internalization of knowledge spillovers. Based on patent citation information from the Organization for Economic Co-operation and Development patent database and other control variables, we estimate a zero-inflated negative binomial model encompassing 645 NUTS-2 regions from 44 countries. The main results show that regions with a higher level of basic technological knowledge are more likely to internalize knowledge spillovers. [ABSTRACT FROM AUTHOR]

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Technology forecasting is an important and critical issue that determines the starting point of planning and is considered as a management tool directly related to the future. In the previous research items, the development of renewable energy technologies was of concern. Moreover, due to the increasing need of countries to produce electricity and facing the lack of resources, this research focuses on forecasting photovoltaic technology. Accordingly, in this paper, for technological research in the field of solar energy, the patents extracted from one of the most famous renewable energy databases in the United States (US patent database) between 200 and 2020 were examined. Next, research gaps were analyzed by using the artificial neural network clustering method and also by analyzing covered and uncovered compounds. The results show that in the future, photovoltaic technology research will move towards the third generation of technology (organic materials) as well as focus on environmental parameters and their effects on the performance of photovoltaic systems. [ABSTRACT FROM AUTHOR]

This study contributes to existing literature on the innovative activity of firms, examining how migration can be a channel for knowledge spillover. Indeed, the aim of the paper is to introduce a new variable, which is computed on the basis of the distribution of inventors across countries, according to patent data. The paper consists of a theoretical model and an empirical analysis, which is a cross-national analysis of the United States, Japan and Europe, based upon a new dataset of worldwide R&D-intensive manufacturing firms. We use data from all EU R&D investment scoreboard editions, which were issued every year from 2002 to 2010 by the JRC-IPTS. The empirical results suggest that the migration of inventors might enhance local innovation levels, by confirming the theoretical analysis propositions. [ABSTRACT FROM AUTHOR]

Copyright of Shipin Kexue/ Food Science is the property of Food Science Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Experts recommend support to patents for stimulating innovation. Also, the South African government supports patents, in particular, international patents. In this paper it is examined how this strategy can be designed to successfully trigger economic progress. Aim: The present South African activities in patents are investigated in this paper and areas identified where an intensification of patenting looks promising for economic progress. Setting: The patent activities since 1985 are analysed and compared to the annual export– import balance from 2009 to 2018, in order to identify starting points for improving economic structures. The data are linked to current suggestions to the National Advisory Council on Innovation (NACI) for future technologies. Methods: The analysis of patents is performed, using the international patent database PATSTAT, as well as the analysis of the export–import balance at the WITS database of the World Bank. Results: The patent analysis reveals a low level of South African domestic patents, with a focus on less complex goods and a stagnation period of 35 years. The data on the export – import balance show negative figures for consumer goods and even more so for capital goods. Conclusion: Economic progress can be accelerated by stimulating patent and economic activities to produce more complex consumer and capital goods. However, it may be necessary to focus on certain areas at the beginning in order to achieve a sufficient critical mass of competence and international competitiveness. In any case, the support of patents is only successful when it is closely linked to a strategy regarding technology. [ABSTRACT FROM AUTHOR]

Abstract: This paper discusses the construction of a new longitudinal database tracking inventors and patent‐owning firms over time. We match granted patents between 2000 and 2011 to administrative databases of firms and workers housed at the U.S. Census Bureau. We use inventor information in addition to the patent assignee firm name to improve on previous efforts linking patents to firms. The triangulated database allows us to maximize match rates and provide validation for a large fraction of matches. In this paper, we describe the construction of the database and explore basic features of the data. We find patenting firms, particularly young patenting firms, disproportionally contribute jobs to the U.S. economy. We find that patenting is a relatively rare event among small firms but that most patenting firms are nevertheless small, and that patenting is not as rare an event for the youngest firms compared to the oldest firms. Although manufacturing firms are more likely to patent than firms in other sectors, we find that most patenting firms are in the services and wholesale sectors. These new data are a product of collaboration within the U.S. Department of Commerce, between the U.S. Census Bureau and the U.S. Patent and Trademark Office. [ABSTRACT FROM AUTHOR]

Patent landscaping is the process of finding patents related to a particular topic. It is important for companies, investors, governments, and academics seeking to gauge innovation and assess risk. However, there is no broadly recognized best approach to landscaping. Frequently, patent landscaping is a bespoke human-driven process that relies heavily on complex queries over bibliographic patent databases. In this paper, we present Automated Patent Landscaping, an approach that jointly leverages human domain expertise, heuristics based on patent metadata, and machine learning to generate high-quality patent landscapes with minimal effort. In particular, this paper describes a flexible automated methodology to construct a patent landscape for a topic based on an initial seed set of patents. This approach takes human-selected seed patents that are representative of a topic, such as operating systems, and uses structure inherent in patent data such as references and class codes to “expand” the seed set to a set of “probably-related” patents and anti-seed “probably-unrelated” patents. The expanded set of patents is then pruned with a semi-supervised machine learning model trained on seed and anti-seed patents. This removes patents from the expanded set that are unrelated to the topic and ensures a comprehensive and accurate landscape. [ABSTRACT FROM AUTHOR]

This paper examines whether technological advances benefit more from path-dependent or path-creating capabilities. Consistently with recent advances in the literature, we argue that multiple technological trajectories can coexist in a field; therefore, firms may contribute to technological development by recombining in novel ways the capabilities that are widespread in the field, or by building novel and rare capabilities. The paper also conceptualises how technological uncertainty affects the value of such capabilities. Using patent data from 1977 to 2007 for firms developing the hydrocracking technology, the paper finds that both rare and widespread capabilities are valuable to the invention process, thereby suggesting that both path-dependent and path-creating strategies are beneficial for technological development. The paper shows that uncertainty has an inverted U-shaped effect on invention value. In particular, under conditions of low uncertainty, path-dependent capabilities tend to be more valuable. [ABSTRACT FROM AUTHOR]

Background: The patent literature contains a large amount of information on the internal state of current industrial technologies that are not available in other literature studies. Scientific articles are the direct achievements of theoretical research in this field and can reveal how current theories in basic research have developed. In this study, the progress and status of natural anticancer products in this field were summarized, and the research hotspots were explored through the analysis of the relevant patent literature and scientific articles. Methods: Patent data were retrieved from the incoPat patent retrieval database, and paper data were retrieved from the Web of Science core set and PubMed. GraphPad Prism 8, Microsoft Excel 2010, and CiteSpace 5.8.R3 were used to perform visual processing. The analyzed patent literature includes the patent applicant type, country (or region), and technical subject. The analyzed scientific article includes academic groups, subject areas, keyword clustering, and burst detection. Results: A total of 20,435 patent families and 38,746 articles were collected by 4 January 2022. At present, antitumor drugs derived from natural products mainly include 1) apoptosis inducers such as curcumin, gallic acid, resveratrol, Theranekron D6, and gaillardin; 2) topoisomerase inhibitors such as camptothecins, scaffold-hopped flavones, podophyllotoxin, oxocrebanine, and evodiamine derivatives; 3) telomerase inhibitors such as camptothecin and isoquinoline alkaloids of Chelidonium majus , amentoflavone, and emodin; 4) microtubule inhibitors such as kolaflavanone, tanshinone IIA analog, eugenol, and millepachine; 5) immunomodulators such as fucoidan, myricetin, bergapten, and atractylenolide I; 6) tumor microenvironment regulators such as beta-escin and icaritin; 7) multidrug resistance reversal agents such as berberine, quercetin, and dihydromyricetin; and 8) antiangiogenic and antimetastatic agents such as epigallocatechin-3-gallate, lupeol, ononin, and saikosaponin A. Conclusion: Anticancer natural product technology was introduced earlier, but the later development momentum was insufficient. In addition, scientific research activities are relatively closed, and technical exchanges need to be strengthened. Currently, the development of medicinal plants and the research on the anticancer mechanism of natural active products are still research hotspots, especially those related to immune checkpoints, essential oils, and metastatic cancer. Theories of traditional Chinese medicine (TCM), such as "restraining excessiveness to acquire harmony," "same treatment for different diseases," "Meridian induction theory," and "Fuzheng Quxie," have important guiding significance to the research of anticancer mechanisms and the development of new drugs and can provide new ideas for this process. Systematic Review Registration : [https://sourceforge.net/projects/citespace/], identifier [000755430500001]. [ABSTRACT FROM AUTHOR]

Patent is a very important and valuable type of scientific and technical big data. This paper presents how to mine patent text to obtain valuable information/knowledge from large-scale candidates obtained from these patents based on massive patent texts. We firstly propose a patent term extraction method using co-occurrence in the abstract and first-claim sections of patent records. There are three steps: (1) we extract candidate strings according to our definition of a term; (2) we propose an assumption to verify whether a candidate string is a qualified term or not by using the co-occurrence of terms in the abstract and first claim; and (3) we use term frequency-inverse document frequencyAUTHOR: TF-IDF has been defined as 'term frequency-inverse document frequency'. Please check if correct. or mutual information to rank and select candidate terms. Secondly, we propose a new method to obtain valuable long tail term from patents. To fulfill the purpose, (1) we firstly build long tail term-common term pair as candidate set; (2) then we evaluate each candidate pair's value; and finally, (3) to demonstrate our method, we give an example on our result. This study provides a new perspective in extracting terms from free texts of patent records and also proposes a new method to obtain valuable long term to aid information analysis with massive patent texts. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The increasing complexity of patented mechanical designs means that their novelty and inventive steps increasingly rely on interacting geometric features and how they contribute to device functions. These features and interactions are normally incorporated in patents through clear patent claims. However, patents can be difficult to interpret and understand for designers due to their legal terminologies. This suggests there is a need for greater awareness of relevant prior art amongst designers in terms of avoiding potential conflict. This paper presents a framework that helps designers obtain insight on relevant prior art and enables emerging design-prior art comparison. The framework mainly contains development of a patent graphical functional representation, a domain-specific ontology and a semantic database. The graphical representation presenting the functional reasoning of patents in terms of interacting geometric features. A domain-specific ontology enables knowledge sharing and conceptualisation, providing a standardised vocabulary for describing patented designs. By formulating patent data into a semantic database, commonality of working principles between an emerging design and prior art can be identified. This enables early identification of potential conflict and thereby could help designers steer their emerging designs away from protected solutions. A computer tool being developed based on this approach is also described. [ABSTRACT FROM AUTHOR]

ICT/IS management plays an important role within the framework of innovation management, and one of the key elements of this role is the support of Competitive Intelligence in the context of innovation processes. The strategic information needs of innovation management are also directed towards different kinds of intellectual property (IP) information entities and commercialization. The purpose of this paper is to define these entities and IP information systems as an important part of a company's Competitive Intelligence Unit for competitor analysis and technology trends. The open access IP information systems will be analyzed together with commercial solutions. The aim of this paper is to underline the importance of open access IP systems compared to added value commercial solutions for competitive intelligence purposes for SMEs. The comparison will be carried out using examples of patent searches within a concrete dataset. [ABSTRACT FROM AUTHOR]

Trade and the environment are two grave concerns of sustainable development in the new development pattern of the Chinese economy. Reducing corporate pollution intensity (CPI) is an essential means of securing economic sustainability, energy conservation, and emissions reduction, and participating in global value chains (GVCs) is a key driver of CPI reduction. Based on the elucidation of the mechanism by which GVC position affects CPI through technological innovation, this paper used the matching data of the enterprise pollution discharge database, the customs import and export database, the enterprise patent database, and the industrial enterprise database from 2000 to 2014 to empirically test the impact of GVC position on CPI. Furthermore, the robustness of the core conclusions was further verified by using the data of listed companies and manufacturing sub-sectors from 2010 to 2019. The main conclusions were as follows: ① GVC position generally showed a positive environmental effect. GVC position could reduce the pollution emissions per unit of output value of enterprises. This core conclusion still held after robustness tests such as replacement of measurement indicators, replacement of sample data, and endogenous discussions. ② The results of the analysis of the mechanism of action showed that GVC position would reduce CPI through the output effect and technological innovation effect. ③ The results of the heterogeneity analysis showed that, under different corporate ownership types, technical levels, and regional characteristics, GVC position had a more obvious impact on improving the environmental effects of foreign-funded enterprises, high-tech enterprises, and enterprises in China’ s eastern region. ④ The research perspective of the article shifted from the micro-enterprise level to the meso-level industry level. The results of the dynamic decomposition of pollutant emission intensity at the industry level showed that the contribution of the resource reallocation effect to the reduction of industry pollution emission intensity was 55.39%, and it was an important channel for GVC position to pollution intensity. To this end, the study puts forward relevant policy suggestions from the aspects of implementing a more active opening strategy, enhancing the technological innovation capabilities of enterprises, and encouraging the coordinated development of multi-type enterprises and regional coordinated development, providing theoretical support and empirical evidence for promoting high-quality economic development in China. [ABSTRACT FROM AUTHOR]

301 DIW Wochenbericht Nr. 17/2021 VERÖFFENTLICHUNGEN DES DIW BERLIN Discussion Papers Nr. 1942 2021 | Heike Belitz, Anna Lejpras R&D Internationalization Strategies of the World's Top Corporate R&D Investors This paper contributes to the debate on the internationalization of the R&D activity of multinational enterprises (MNEs). Based on the final dataset, covering about 1,700 world's top corporate R&D investors and their patenting activity, we find that about one-fifth focus their patent-relevant R&D activity in their home country only. R&D Internationalization Strategies of the World's Top Corporate R&D Investors. [Extracted from the article]

Residues from wine and juice processing still contain about 70% of the phenolic compounds in grapes. These compounds are valued for having several bioactive properties that are explored in the pharmaceutical and food sectors. This paper aims to summarize the most recent advances in the use of enzymatic techniques for the recovery of bioactive compounds from GP for industrial application. For this, we analyzed scientific articles and patent applications from the last 20 years in the main indexed and patent databases. Among the most used enzymes in the recovery of bioactive compounds in wastes, cellulases, pectinases, tannases, glucoamylases, and proteases such as trypsin and chymotrypsin, are the most important. As a result, extracts are obtained with greater retrieval of compounds such as anthocyanins, gallic acid, catechins, epicatechins, and trans‐resveratrol and the improvement of coloring, anti‐inflammatory, antioxidant and vasoprotective properties. Although the use of enzymes for the recovery of phenolics is an old strategy, the number of studies focusing on the functional characteristics and industrial applicability of the extracts obtained has been recently growing. Practical applications: Phenolic compounds have acted as anti‐inflammatories, antioxidants, anticarcinogens, and antimicrobials, being additives or relevant ingredients for various products in the food and pharmaceutical industry. Although there are several techniques for extracting/recovering phenolics from grape pomace, there is still no agreement on which method is ideal. In recent years, several extractions methods have been applied in seeking optimized conditions to recover phenolics from grape residues. Among them, the use of enzymes has been gaining attention for being considered a green and promising technology. The present study aims to carry out a review that would bring a new perspective to the recovery of bioactive compounds from grape residues by enzymatic techniques, with a view to industrial purpose. [ABSTRACT FROM AUTHOR]