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Theories of scientific and technological change view discovery and invention as endogenous processes 1,2 , wherein previous accumulated knowledge enables future progress by allowing researchers to, in Newton's words, 'stand on the shoulders of giants' 3-7 . Recent decades have witnessed exponential growth in the volume of new scientific and technological knowledge, thereby creating conditions that should be ripe for major advances 8,9 . Yet contrary to this view, studies suggest that progress is slowing in several major fields 10,11 . Here, we analyse these claims at scale across six decades, using data on 45 million papers and 3.9 million patents from six large-scale datasets, together with a new quantitative metric-the CD index 12 -that characterizes how papers and patents change networks of citations in science and technology. We find that papers and patents are increasingly less likely to break with the past in ways that push science and technology in new directions. This pattern holds universally across fields and is robust across multiple different citation- and text-based metrics 1,13-17 . Subsequently, we link this decline in disruptiveness to a narrowing in the use of previous knowledge, allowing us to reconcile the patterns we observe with the 'shoulders of giants' view. We find that the observed declines are unlikely to be driven by changes in the quality of published science, citation practices or field-specific factors. Overall, our results suggest that slowing rates of disruption may reflect a fundamental shift in the nature of science and technology., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

The 2019 13 th Workshop on Recent Issues in Bioanalysis (WRIB) took place in New Orleans, LA, USA on April 1-5, 2019 with an attendance of over 1000 representatives from pharmaceutical/biopharmaceutical companies, biotechnology companies, contract research organizations and regulatory agencies worldwide. WRIB was once again a 5-day, week-long event - a full immersion week of bioanalysis, biomarkers, immunogenicity and gene therapy. As usual, it was specifically designed to facilitate sharing, reviewing, discussing and agreeing on approaches to address the most current issues of interest including both small- and large-molecule bioanalysis involving LCMS, hybrid LBA/LCMS, LBA cell-based/flow cytometry assays and qPCR approaches. This 2019 White Paper encompasses recommendations emerging from the extensive discussions held during the workshop, and is aimed to provide the bioanalytical community with key information and practical solutions on topics and issues addressed, in an effort to enable advances in scientific excellence, improved quality and better regulatory compliance. Due to its length, the 2019 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication (Part 1) covers the recommendations on Innovation in Small Molecules and Oligonucleotides & Mass Spec Method Development Strategies for Large Molecules Bioanalysis. Part 2 (2018 FDA BMV Guidance, 2019 ICH M10 BMV Draft Guideline and regulatory agencies' input on bioanalysis, biomarkers, immunogenicity and gene therapy) and Part 3 (New Insights in Biomarkers Assays Validation, Current & Effective Strategies for Critical Reagent Management, Flow Cytometry Validation in drug discovery & development & CLSI H62, Interpretation of the 2019 FDA Immunogenicity Guidance and The Gene Therapy Bioanalytical Challenges) are published in volume 11 of Bioanalysis , issues 23 and 24 (2019), respectively.

We report the top ten papers published by the Journal ofInnovation in Health Informatics in 2017.

Theories of innovation emphasize the role of social networks and teams as facilitators of breakthrough discoveries 1-4 . Around the world, scientists and inventors are more plentiful and interconnected today than ever before 4 . However, although there are more people making discoveries, and more ideas that can be reconfigured in new ways, research suggests that new ideas are getting harder to find 5,6 -contradicting recombinant growth theory 7,8 . Here we shed light on this apparent puzzle. Analysing 20 million research articles and 4 million patent applications from across the globe over the past half-century, we begin by documenting the rise of remote collaboration across cities, underlining the growing interconnectedness of scientists and inventors globally. We further show that across all fields, periods and team sizes, researchers in these remote teams are consistently less likely to make breakthrough discoveries relative to their on-site counterparts. Creating a dataset that allows us to explore the division of labour in knowledge production within teams and across space, we find that among distributed team members, collaboration centres on late-stage, technical tasks involving more codified knowledge. Yet they are less likely to join forces in conceptual tasks-such as conceiving new ideas and designing research-when knowledge is tacit 9 . We conclude that despite striking improvements in digital technology in recent years, remote teams are less likely to integrate the knowledge of their members to produce new, disruptive ideas., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Continual development necessitates innovation. One must discover seeds of innovation and then concentrate resources on these seeds. To do so, one must recognize technology trends and then adopt and execute appropriate innovation strategies. This study used advanced change point detection method to investigate leading indicators that represent changes in technology trends. We examine patents, papers, and newspaper articles in Japan and US for 55 technologies. Results suggest that patents can be more appropriate as leading indicators than either papers or newspapers. This result can contribute to appropriate innovation strategies for planning and updating, and can provide tools that are useful to decision-makers. [ABSTRACT FROM AUTHOR]

The term incidentaloma, created in 1982, has spread throughout medical literature. However, there does not seem to be a precise definition to describe what an incidentaloma is. In the initial uses, the word incidentaloma systematically designated a mass that was detected during an imaging examination prescribed for diagnostic purposes unrelated to the reason for carrying out the examination. Naming this mass "incidentaloma" did not give any precision on its nature as it can be located in many anatomical zones, secreting or not, benign or malignant, etc. Today, the term "incidentaloma" carries a much broader dimension which seems to cover the notion of incidental discovery, whether radiological, biological or genetic. The evolution of the term "incidentaloma" demonstrates its heuristic nature. It is a sign of a change in modern medicine which hesitates between a patient clinic and a data clinic. Fortuitous discoveries are a phenomenon known and anticipated by radiologists. Thus, these discoveries are no longer fortuitous, or even unexpected, but secondary to the use of health technology., (© 2020 médecine/sciences – Inserm.)

China is at a critical moment of transforming high-speed development to high-quality development, and it is significant to improve the efficiency of green technological innovation. In this paper, under the perspective of two-stage innovation value chain, we construct the evaluation index system of green technology innovation efficiency, adopt the super efficiency SBM model to measure the green technology innovation efficiency of China's high-tech industries, and based on the results obtained, we assume the fuzzy set qualitative comparative analysis method (fs-QCA) based on the group theory to explore the complex causal mechanism and grouping paths of the interaction between enterprises, government and market that affects the green technology innovation efficiency Mechanism and group path. The study results show that (1) enterprise, government, and market are not necessary conditions to influence the efficiency of green technological innovation, and even if a particular party plays a central role, it needs the assistance of other parties. (2) The improvement of green technological innovation efficiency requires the interaction of enterprises, government, and market, and even if any party does not have the core conditions, it can still produce high green technological innovation efficiency. (3) The path of the "innovative compensation" effect is identified, which indicates that enterprises will generate a high level of green innovation efficiency under sufficient investment brought about by the enterprise scale effect and matched with a good level of economic development. (4) The market economy-led pathway suggests that when the market economy is highly developed, firms do not need environmental regulation and government support to generate efficient levels of green technological innovation., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Liu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

In numerous developing nations, challenges such as insufficient investment in innovation and limited capabilities for conversion impede the growth of the construction sector, thus affecting the overall economic well-being of these regions. This paper focuses on construction industry innovation (CII) and its correlation with region economic development (RED), providing valuable insights to overcome these challenges and promote sustainable economic advancement. This study references existing literature to devise an evaluation indicator system dedicated for CII and RED. It then proceeds with an empirical analysis of the integration and synergy between CII and the economic development across 31 Chinese provinces from 2012 to 2021. Furthermore, this paper employs ArcGIS and Geoda software to meticulously dissect the spatial distribution characteristics underlying this coordination. The main conclusions are succinctly summarized as follows: CII in China is intricately connected to RED, exhibiting a strong connection that diminishes from south to north. Nonetheless, the coordination level between these factors remains relatively low, with notable regional disparities, particularly from southeast to northwest. The primary obstacles to effective coordination are related to innovation input, output, and economic scale. Additionally, spatial correlation analysis demonstrates pronounced regional clustering, showing stability despite slight fluctuations over the study period. This research underscores the concept of coupling coordination between CII and RED, underpinned by scientific analytical methods. The outcomes provide a definitive guide for advancing the transformation and enhancement of the construction industry while promoting RED., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Xiang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This paper empirically investigates the impact of digital finance on the breakthrough innovation of enterprises with a sample of A-share listed companies in Shanghai and Shenzhen from 2011 to 2022. It is found that digital finance can promote corporate breakthrough innovation, and presents certain structural heterogeneity characteristics. The mechanism test shows that digital finance has the dual attributes of a financing platform and a social platform, which can promote breakthrough innovation by alleviating corporate financing constraints and expanding corporate social networks. Heterogeneity analysis reveals that the role of digital finance in promoting breakthrough innovation is characterized by regional heterogeneity, with digital finance playing a greater role in promoting breakthrough innovation in provinces with a low level of development of the banking sector, provinces with a high level of development of the capital market sector, and the central region. In addition, the degree of firms' external financing dependence and the degree of product market competition can strengthen the positive effect of digital finance on firms' breakthrough innovation. This paper enriches the related research on the impact of digital finance on enterprise innovation, and provides theoretical basis and policy insights on how digital finance can better assist the innovation-driven development strategy., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Yanmin Shi. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This paper examines the impact of the digital economy on sustainable development, using panel data from cities at the prefecture level and above in China from 2011 to 2019. The results indicate: (1) The digital economy is conducive to boosting growth, increasing employment, reducing energy consumption, and cutting emissions, thereby promoting sustainable development. These findings prove robust. (2) Mechanism test outcomes reveal that, from the perspective of technological innovation, the digital economy can promote sustainable development through increasing R&D input and enhancing innovation output. (3) An extended analysis of the risk of a digital "divide" demonstrates that "dividend" of the digital economy is primarily manifests in spurring economic growth, enhancing energy efficiency, and strengthening environmental protection in lagging regions, while the digital "divide" effect is manifested in the stronger employment stimulating effect of developed regions versus backward areas. The results of this study not only enrich the relevant research system, but also provide empirical evidence to support accelerating digital transformation, strengthening technological innovation governance, and advancing sustainable development., Competing Interests: The authors declare that they have no competing interests., (Copyright: © 2024 He et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The rapid evolution of the digital economy has significantly accelerated progress towards achieving green and sustainable processes, particularly in the field of green production. While existing research has delved into the effects of the digital economy on Green Innovation (GI) and the consequences of digital transformation on Corporate Value (CV), there remains a notable gap in the literature regarding the potential for synergistic enhancements in firms' GI&CV through the ongoing digital revolution. This study utilizes an evolutionary game model and employs system dynamics methods to simulate the dynamic evolution trajectory of the influence of the digital economy on the synergy between GI&CV. Subsequently, it empirically assesses the interconnected synergies between GI&CV using a dataset comprising information from Chinese listed firms spanning from 2011 to 2020, examining the impact of the digital economy on these synergies. Moreover, the study delves into the analysis of the transmission mechanism and conducts an extended investigation to further explore this phenomenon. The findings of this paper including: (1) The digital economy acts as a driving force behind the synergistic enhancement of firm GI&CV. Moreover, this effect is further augmented by governmental environmental regulation and green subsidy policies. (2) Drawing upon the information asymmetry theory and the resource-based theory, the regional marketization level and firms' digital transformation play intermediary roles. (3) The heterogeneity test indicate that firms situated in eastern regions and those classified as non-heavily polluted benefitted to a greater extent. This study sheds light on the incentive implications of digital economy for the synergistic upgrading of GI&CV, thereby extending the breadth of study on the consequences of digital economy. Moreover, it offers actionable suggestions for enterprises to leverage digital economy development towards achieving a synergistic improvement of GI&CV., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Song et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Currently, digital transformation is having various impacts on enterprises around the world, including the green innovation. However, the current literature on the relationship between digitalization and green innovation in enterprises is scarce. What is the relationship between them, and whether heterogeneous environmental regulation has mediating effects, are questions that are worth exploring. Using a sample of listed manufacturing enterprises in China, this paper empirically tests the impact of digital transformation on enterprise green innovation. The results show that: (1) Digital transformation has a significant positive impact on green innovation, including green innovation output and green innovation capability. (2) Diverse environmental regulation may have mediating effects of digital transformation's influence on green innovation. (3) After a number of robustness tests, the conclusions are still valid. This paper can provide a reference for developing green development strategies for manufacturing enterprises., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Sun et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The digital economy is now the expected norm for economic development, warranting strategic importance for enterprise digital transformation. Nonetheless, enterprises have a lengthy journey to embark upon for digital transformation. On the one hand, resource-based demands pose a significant challenge due to the development characteristics of the initiative; on the other hand, excessive emphasis on economic gains may result in severe environmental issues. Therefore, this paper examines whether green innovation, which combines environmental and economic benefits, can effectively address the above dilemma. The study includes all A-share listed companies from 2010 to 2020 as the research sample, and empirically investigates the impact of green innovation on enterprise digital transformation and its mechanism based on resource-based view. The study concluded that (i) green innovation has a significant positive impact on corporate digital transformation performance, exhibiting asymmetric effects. The robustness tests confirmed the validity of the findings. (ii) Enterprises that actively engage in green innovation can effectively reduce their financial constraints, enhance their operational capacity, and enable the efficient allocation of resources, thereby promoting digital transformation within the enterprise. (iii) There is a regional imbalance in the conversion of green innovation performance into economic performance. The aforementioned results offer fresh insights for investigating the connection between green innovation and digital transformation. Additionally, these findings hold significant implications for the discourse on the synergistic advancement of the environment and economy., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 She, Zhang. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The Baijiu industry is a significant contributor to both the food industry and the light industry. Its high tax characteristics effectively promote the sustainable development of the regional economy. First, the evaluation index system of scientific and technological innovation (STI) and high-quality development of Baijiu industry (HQDBI) were constructed. The entropy-improved CRITIC method was used to measure the weights. Second, the coordination relationship and evolution trend of STI and HQDBI were explored using the coupling coordination model and the Tapio decoupling model. Then, the transfer law and key influencing factors were further investigated using the Markov chain and grey correlation, respectively. The main contribution is the dynamic evolution of the coupling and decoupling relationships from the perspective of multiple Baijiu provinces, and deeply depicts the coordination relationship and evolutionary trends of STI and HQDBI. The results show that: the spatial distribution of the coupling coordination degree shows high values in the east-west and low values in the north-south characteristics. In 2021, a pattern of coordinated development in Baijiu provinces has emerged along the Yangtze River basin. The decoupling state is mainly strong decoupling, but it remains poor in Shanxi. The coordination process is unstable and difficult to achieve leapfrog development. Coordination, sustainability and innovation environment have a greater impact on the coordination of subsystems., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright: © 2024 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Improving corporate green technology innovation is a key link in achieving green transformation and development. Compared with formal environmental regulations that force companies to carry out green innovation passively, ESG ratings under soft environmental regulations can better stimulate the internal motivation of companies. This study uses the ESG ratings of listed companies published for the first time by SynTao Green Finance as an exogenous impact. Taking China's A-share listed companies from 2011 to 2022 as a research sample, the multi-period differences-in-differences model was used to empirically test the impact of ESG rating soft supervision on corporate green technology innovation. The results show that the impact of ESG rating events as a soft market regulation has a significant positive impact on the improvement of corporate green technology innovation. This conclusion still holds after a series of robustness tests. Meanwhile, enterprise digital transformation plays a positive regulatory role. The heterogeneity test shows that the green technology innovation of state-owned enterprises is more affected by ESG ratings. Mechanism research has found that ESG rating events promote corporate green technology innovation by easing corporate financing constraints and reducing managerial myopia. Further research found that under the influence of the external environment, intensified market competition and increased attention from the capital market are also conducive to the improvement of corporate green technology innovation. This study strengthens the corporate ESG concept under the guidance of green development and provides empirical evidence for promoting corporate green transformation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The goal of this study was to conduct a thorough investigation on understanding how infrastructure growth and technological innovation affect social mobility and the Sustainable Development Goals (SDGs). This study aimed to illuminate the underlying mechanisms by exploring the mediating function of psychological empowerment and the moderating impact of community satisfaction. The study carefully chose a sizeable sample of 370 connected to the mega project CPEC. Data collection was carried out using a questionnaire-based approach. Notably, the study confirmed the large and favorable influence of technical innovation and infrastructural development on both the SDGs-13 (climate change) and social mobility. Furthermore, this study provided light on the critical function of environmental impacts identifying it as an important mediating mechanism that magnifies the effects of innovation and infrastructure on long-term development outcomes. It gives decision-makers in government, business, international organizations, and local communities useful information by offering empirical data and insights. This study offers a novel perspective and explores the relationship between infrastructure growth, technological innovation, social mobility, and SDGs-13-climate change. It uncovers the pivotal roles of psychological empowerment and community satisfaction, offering fresh insights into global development strategies influencing SDGs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

In the era of rapid product iteration, companies need simple and effective methods to guide the entire process of product innovation design and enhance their product innovation capabilities. Most research focused on improving one or several steps in the product design process. Although some scholars have proposed methods that guided the entire process, they combined more than three different theories, which increased the difficulty of theoretical learning and the complexity of practical implementation. This paper proposed a product innovation design process composed of three theoretical methods: Kano, Axiomatic Design (AD), and Theory of the Solution of Inventive Problems (TRIZ). This new process guided the entire product design process with fewer theoretical methods, reducing the difficulty of learning and implementation. The paper demonstrated the effectiveness of this method through the design practice of a portable two-wheeled self-balancing vehicle. Additionally, the discussion section explored the method's potential from the design management perspective., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Rong et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

In almost every country, patents need to be renewed multiple times after they are granted. A patentee assesses the value of the patent and then pays a renewal fee to keep it active for another stipulated period. The factors that characterize the value of a patent is subjective. This paper aims to address the research gap of building an accurate model for predicting the renewal life (often considered as a substitute for the patent value) of Indian patents, and identification of significant factors that influence the renewal life. This study uses an extensive data set collected from the Indian Patent Office for all granted patents filed between 1995 and 2005. The popular statistical and machine learning algorithms do not result in accurate predictive models, because the patent renewal life distribution (at least for the Indian patents) shows unusual spikes at the two extreme values, which makes the modeling task more challenging. We propose a new two-stage hybrid model by combining an efficient multi-class classifier and a binomial regression model for predicting the complex renewal data distribution. We conducted a comparative analysis of the proposed model with several state-of-the-art machine learning and statistical models. The results show that the proposed hybrid model gives 90% accuracy as compared to the best competitor which gives only 40% accuracy. [ABSTRACT FROM AUTHOR]

The relationship between environmental regulation and innovation has long been a key issue of scholarly interest. The Porter hypothesis posits that environmental regulations can effectively promote innovation. However, with the rapid development of the Internet, the relationship between environmental regulation and innovation has changed. Through a theoretical analysis, this paper finds that the development of the Internet can not only directly promote innovation but also inhibit innovation through environmental regulations. This paper uses Chinese city-level data from 2014 to 2016 to empirically test the relationship among the Internet, environmental regulation, and innovation. The study finds that (1) the increase in the Internet level and in the intensity of environmental regulations promotes innovation, and the results remain stable after the replacement of the Internet level metrics, (2) the increase in the Internet level inhibits the positive effect of environmental regulations on innovation, but its inhibitory effect is lower than the promotion effect of the Internet on innovation, and (3) the Internet and environmental regulations have a significant promotion effect on the application and acquisition of three types of patents, including invention patents, utility model patents and design patents, with the application and acquisition of utility model patents having the greatest promotion effect, and (4) the analysis of heterogeneity shows that environmental regulation has a greater effect on innovation in eastern and provincial capital cities, and the Internet has a greater effect on innovation in western and nonprovincial capital cities. Finally, this article puts forward policy recommendations based on three aspects: strengthening Internet construction, implementing environmental regulations and policies based on local conditions, and increasing support for R&D and innovation. [ABSTRACT FROM AUTHOR]

This paper investigates the complex causal relationships between various types of environmental regulatory instruments (ERI) and agri-firms' technological innovation employing fuzzy set qualitative comparative analysis (fsQCA). The study finds a well-designed set of ERI can promote technological innovation in agribusiness; control-command ERI cannot promote technological innovation in agribusiness solely, market-incentivized ERI is indispensable in promoting firms' innovation performance, implicit ERI plays an important role in promoting firms' innovation and voluntary ERI does not play a significant role in promoting firms' technological innovation. The government should coordinate among various types of ERI and improve the design of ERI to achieve a win-win situation for both economic and environmental performance in the agriculture sector., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Xia et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Introduction: In March 2016, the Chinese government officially launched a nationwide consistency evaluation of the quality and efficacy of generic drugs., Methods: This paper conducted an empirical study using the Difference-in-Differences method to explore the effect of this policy on the innovation quality of China's pharmaceutical manufacturing industry and further analyzed the underlying mechanism of action., Results: The results of the study show that the generic consistency evaluation policy has a significant promotion effect on the innovation quality of China's pharmaceutical manufacturing industry, and the promotion effect is the largest for non-state-owned enterprises and enterprises in the central region; in addition, the intensity of R&D capital investment and R&D personnel investment which play a mediating role., Discussion: Therefore, we should fully recognize the positive effect of generic drug consistency evaluation policy on improving the innovation quality of the pharmaceutical manufacturing industry and pay attention to the necessity of regional coordination and unification in policy implementation and the formulation of supporting policy tools. This study provides empirical evidence for the implementation effect of the generic drug consistency evaluation policy, which can provide an essential reference for the further improvement of the procedure and the R&D decision-making of pharmaceutical enterprises., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Liu, Huang and Mao.)

Many science, technology and innovation (STI) resources are attached with several different labels. To assign automatically the resulting labels to an interested instance, many approaches with good performance on the benchmark datasets have been proposed for multilabel classification task in the literature. Furthermore, several open-source tools implementing these approaches have also been developed. However, the characteristics of real-world multilabel patent and publication datasets are not completely in line with those of benchmark ones. Therefore, the main purpose of this paper is to evaluate comprehensively seven multi-label classification methods on real-world datasets. Three real-world datasets (Biological-Sciences, Health-Sciences, and USPTO) from SciGraph and USPTO database are constructed. Seven multilabel classification methods with tuned parameters (dependency-LDA, MLkNN, LabelPowerset, RAkEL, TextCNN, TexRNN, and TextRCNN) are comprehensively compared on these three real-world datasets. To evaluate the performance, the study adopts three classification-based metrics: Macro-F1, Micro-F1, and Hamming Loss. The TextCNN and TextRCNN models show obvious superiority on small-scale datasets with more complex hierarchical structure of labels and more balanced documentlabel distribution in terms of macro-F1, micro-F1 and Hamming Loss. The MLkNN method works better on the larger-scale dataset with more unbalanced document-label distribution. Three real-world datasets differ in the following aspects: statement, data quality, and purposes. Additionally, open-source tools designed for multi-label classification also have intrinsic differences in their approaches for data processing and feature selection, which in turn impacts the performance of a multi-label classification approach. In the near future, we will enhance experimental precision and reinforce the validity of conclusions by employing more rigorous control over variables through introducing expanded parameter settings. The observed Macro F1 and Micro F1 scores on real-world datasets typically fall short of those achieved on benchmark datasets, underscoring the complexity of real-world multi-label classification tasks. Approaches leveraging deep learning techniques offer promising solutions by accommodating the hierarchical relationships and interdependencies among labels. With ongoing enhancements in deep learning algorithms and large-scale models, it is expected that the efficacy of multi-label classification tasks will be significantly improved, reaching a level of practical utility in the foreseeable future. (1) Seven multi-label classification methods are comprehensively compared on three real-world datasets. (2) The TextCNN and TextRCNN models perform better on small-scale datasets with more complex hierarchical structure of labels and more balanced document-label distribution. (3) The MLkNN method works better on the larger-scale dataset with more unbalanced document-label distribution. [ABSTRACT FROM AUTHOR]

Does international R&D collaboration produce patents of higher technological value? Applied to the case of Siemens, this paper utilizes the Patent Cooperation Treaty (PCT) and Google Patents statistics to identify patterns within invention and co-invention. For example, sole patenting by headquarters or subsidiaries is juxtaposed with co-invented patent filings, vertical versus horizontal co-patented applications and internal versus external. The paper compares the effect of different forms of co-invention on the technological value of patent filings, proxied by forward external citations. The results are based on 2013 and 2019 Siemens PCT data and confirm the positive effect of international co-invention, vis-à-vis sole patenting, on the technological value of patents. Patent applications co-invented by foreign subsidiaries, or vertically collaborated applications, create higher technological value, while headquarters or single subsidiaries generate fewer forward citations. Moreover, co-patenting by subsidiaries with external partners creates higher technological value than sole patenting by headquarters. Siemens has recognized the value of partnerships with outside inventors and leveraged these relationships in order to generate higher technological value. We contribute by building a unique and detailed classification of co-patenting patterns, and the paper develops a strong case for cross-country co-patenting, especially with external partners. From a managerial perspective, international co-patenting involving external partners has strategic value and must be fostered. [ABSTRACT FROM AUTHOR]

This paper introduces justice-centered reflective practice, an approach that emerged out of our practitioner research in the Independent School Teaching Residency program. This ongoing and imperfect praxis is simultaneously a stance, a lens, a pedagogy, an orientation, and a way of understanding and mobilizing our individual and collective identities as teacher educators. Mediated by joy, imagination, vulnerability, and uncertainty, six foundational principles guide our work: justice-centered reflective practice is (1) purposeful and systematic, (2) iterative and cyclical, (3), critically reflective, (4) agentive, (5) done in community, and (6) loving and hopeful. Here we detail these principles and illustrate how they manifest in our work as teacher educators in how we structure the program and enact our pedagogy. We seek to continue a scholarly conversation among critical teacher educators about how we enact liberatory values and aspirations in the context of institutions and policy environments that often constrain our collective work. [ABSTRACT FROM AUTHOR]

Scientists and inventors increasingly work in teams, raising fundamental questions about the nature of team production and making individual assessment increasingly difficult. Here we present a method for describing individual and team citation impact that both is computationally feasible and can be applied in standard, wide-scale databases. We track individuals across collaboration networks to define an individual citation index and examine outcomes when each individual works alone or in teams. Studying 24 million research articles and 3.9 million US patents, we find a substantial impact advantage of teamwork over solo work. However, this advantage declines as differences between the team members' individual citation indices grow. Team impact is predicted more by the lowercitation rather than the higher-citation team members, typically centering near the harmonic average of the individual citation indices. Consistent with this finding, teams tend to assemble among individuals with similar citation impact in all fields of science and patenting. In assessing individuals, our index, which accounts for each coauthor, is shown to have substantial advantages over existing measures. First, it more accurately predicts out-of-sample paper and patent outcomes. Second, it more accurately characterizes which scholars are elected to the National Academy of Sciences. Overall, the methodology uncovers universal regularities that inform team organization while also providing a tool for individual evaluation in the team production era. [ABSTRACT FROM AUTHOR]

Facing the problem of increasing waste, scientists, foundations, and companies around the globe resulted in ideas and invented technologies to slow down the process. Sources of waste range from industrial waste (e.g., construction and demolition materials, hazardous wastes, ashes) to municipal solid waste (e.g., food wastes, paper, cardboard, plastics, textiles). Modern solutions do not focus only on technological aspects of waste management but also on sociological ones. Thanks to the Internet and social media platforms, scientists can influence ecological consciousness and awareness on a much larger scale. This research was conducted using the search keywords related to modern technologies for waste management. This paper presents a spectrum of selected modern solutions that changed in recent years and how they have impacted waste management. It also discusses challenges and future directions of waste management in the context of the circular economy. The use of modern solutions in waste management allows to achieve selected goals of sustainable development. [ABSTRACT FROM AUTHOR]

This general review paper presents a condensed view of recent inventions in the Additive Manufacturing (AM) field. It outlines factors affecting the development and commercialization of inventions via research collaboration and discusses breakthroughs in materials and AM technologies and their integration with emerging technologies. The paper explores the impact of AM across various sectors, including the aerospace, automotive, healthcare, food, and construction industries, since the 1970s. It also addresses challenges and future directions, such as hybrid manufacturing and bio-printing, along with socio-economic and environmental implications. This collaborative study provides a concise understanding of the latest inventions in AM, offering valuable insights for researchers, practitioners, and decision makers in diverse industries and institutions. [ABSTRACT FROM AUTHOR]

The aim of this paper is to investigate the effects of information technology (IT) capability on firm growth in the context of open technological innovation. The paper utilized a logical deductive approach to develop hypotheses and analytical frameworks, and collected empirical data from 256 Chinese new ventures. Regression analysis and structural equation models were used to test the hypotheses and analyze the data. The results showed that IT capability, including flexibility and integration of information technology, significantly influenced firm growth, and open technological innovation partially mediated the relationship between IT flexibility and firm growth, and significantly mediated the relationship between IT integration and firm growth. The paper's limitations include the cross-sectional design, limited sample size, and potential unobserved variables such as organizational learning that could affect the relationship between IT capability and firm growth. The research is the first to investigate the effects of IT capability on firm growth based on the mediation of open technological innovation in China, contributing to the literature on IT capability and providing insights for managerial practice in the sharing economy era., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Yao, Li. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

With the continuous promotion of China's innovation-driven development strategy, the role of technological innovation on economic development has become increasingly important. In this context, the support of R&D capital investment for technological innovation also becomes non-negligible. This leads to the question of whether the allocation of R&D capital is reasonable and whether there is room for further improvement. This paper is based on inter-provincial panel data from 2009 to 2020, which are classified based on China's National Bureau of Statistics for R&D funding sources in high-tech industries and incorporated into an overall discussion framework. Using STATA16 statistical software, the R&D innovation output of high-tech industries is inves-tigated by building a PVAR model with the perspective of funding sources of R&D input intensity. The study results show that (1) the increase in the intensity of enterprises' own capital investment has a positive impact on innovation output because it can generate a financial "reservoir" effect to support technological innovation. (2) the increase in the intensity of government capital invest-ment has a positive impact on innovation output because it can alleviate the loss of income of en-terprises due to "R&D spillover" and will send a positive signal to the market. (3) the foreign in-vestment intensity has a positive impact on the innovation output of enterprises due to the com-bined effect of "spillover effect" and "crowding out effect". (4) the increase of other capital in-vestment intensity also has a neutral effect on the increase of innovation output under the current financial market environment. Finally, based on the above findings, corresponding policy impli-cations are drawn. This study will help to improve the understanding of R&D capital allocation imbalance and R&D input and output issues in developing countries and provide a reference for policy makers., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Jin, Li. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Most researchers consider CO 2 emissions to be the primary indicator of environmental degradation. Similarly, ecological footprint appears to be a significant proxy for environmental degradation in recent research due to its multifaceted impact on the natural environment. With this in mind, this study investigates fluctuations in CO 2 emissions and ecological footprint as indicators of environmental degradation in Bangladesh from 1980 to 2020, and how they are influenced by net savings, natural resource depletion, technological innovation, and democracy. The non-linear ARDL (NARDL)-based asymmetric analysis finds that positive changes in net savings, natural resource depletion, and democracy positively impact both parameters of environmental degradation in the long run. On the other hand, a positive change in technological innovation reduces these parameters in the long run. Likewise, negative changes in net savings and technological innovation reduce environmental degradation. In contrast, negative changes in natural resource depletion and democracy exacerbate these two parameters and degrade environmental quality in the long run. However, there are some variations in the short-run influence of the predictors on the predicted variable. Overall, the findings of this study suggest that policymakers must strategically exploit natural resources, net savings, technology diffusion, and democratic principles to preserve the natural environment in Bangladesh., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

To achieve the carbon peaking and neutrality targets in China, carbon price and technological innovation will play increasingly important roles in recent future. It is widely-known that carbon price and technological innovation can contribute significantly to emission reduction, respectively; but it is still unclear whether the cooperation effects of carbon price and technological innovation would be positive or negative. In this paper, we assume that there are 3 types of emission reduction measures in China's industrial enterprises, which are improvement of energy efficiency, adjustment of energy structure, and substitution of pollution inputs and non-pollution inputs; then we introduce carbon price and technological innovation respectively and simultaneously, and establish 12 scenarios based on the Data Envelopment Analysis models combined with material balance principal (DEA-MBP), and estimate the additional emission reductions and additional production costs of China's industrial enterprises when carbon price and technological innovation exist respectively or simultaneously. The counterfactually estimating results show that there would be significant regional and sectorial heterogeneities in carbon emission reduction characteristics for China's industrial enterprises. If low-carbon technologies in some sectors have the ability to reduce carbon emissions at the expense of high additional production cost, carbon pricing policies would encourage enterprises to adopt new mitigation technologies and increase additional emission reduction by more than 20%, especially technologies focusing on the adjustment of energy structure and the substitution of pollution inputs by non-pollution inputs. However, in some sectors which have already been covered by carbon pricing policies, the additional carbon pricing policy may not have a significant effect on emission reduction, and the emission reduction would decrease by 10%., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Ke Wang reports financial support was provided by National Natural Science Foundation of China. Ke Wang reports financial support was provided by Fok Ying Tung Education Foundation. Ke Wang reports financial support was provided by Joint Development Program of Beijing Municipal Commission of Education. Ke Wang reports financial support was provided by National Program for Support of Top-notch Young Professionals., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

In 1936 the Austrian geologist Paul Waitz published a seminal bibliographical, historical essay on Colima volcano, Mexico. His article exemplifies well the paths by which geology became what Lorraine Daston has termed sciences of the archive, that is, the manner in which scientific disciplines became concerned with archival work. Waitz's historical description of studies of Colima volcano built a genealogy of observations, ultimately constructing a history of the volcano itself. By bringing attention not only to Waitz's discourse but also to his treatment of visual objects, such as pictorial and photographic landscapes, my article points out how long-term aesthetics, such as the picturesque and the sublime, functioned as tropes which enabled a standardized perception, essential to visualize a clear history of scientific observations, from the landscape paintings of the nineteenth-century artist Johann Moritz Rugendas to Waitz's own photographs., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Featured Application: Technology trend analysis of connected vehicles. As official public records of inventions, patents provide an understanding of technological trends across the competitive landscape of various industries. However, traditional manual analysis methods have become increasingly inadequate due to the rapid expansion of patent information and its unstructured nature. This paper contributes an original approach to enhance the understanding of patent data, with connected vehicle (CV) patents serving as the case study. Using free, open-source natural language processing (NLP) libraries, the author introduces a novel metric to quantify the alignment of classifications by a subject matter expert (SME) and using machine learning (ML) methods. The metric is a composite index that includes a purity factor, evaluating the average ML conformity across SME classifications, and a dispersion factor, assessing the distribution of ML assigned topics across these classifications. This dual-factor approach, labeled the H-index, quantifies the alignment of ML models with SME understanding in the range of zero to unity. The workflow utilizes an exhaustive combination of state-of-the-art tokenizers, normalizers, vectorizers, and topic modelers to identify the best NLP pipeline for ML model optimization. The study offers manifold visualizations to provide an intuitive understanding of the areas where ML models align or diverge from SME classifications. The H-indices reveal that although ML models demonstrate considerable promise in patent analysis, the need for further advancements remain, especially in the domain of patent analysis. [ABSTRACT FROM AUTHOR]

In this essay, I first analyze the extension of hermeneutical interpretation in the Heideggerian sense to products of contemporary technology which are components of our "lifeworld". Products of technology, such as airplanes, laptops, cellular phones, washing machines, or vacuum cleaners might be compared with what Heidegger calls the "Ready-to-hand" (das Zuhandene) with regard to utilitarian objects such as a hammer, planer, needle and door handle in Being and Time. Our life with our equipment, which represents the "Ready-to-hand" in Heidegger's sense of the word, is determined by temporalization (Zeitigung) which cannot be separated and isolated from the wholeness of things in the world. In the second part of my paper, I explore the positive achievement of material hermeneutics (Don Ihde) with regard to its extension to technoscience and the discussion of how such hermeneutics can contribute to the preservation of our threatened lifeworld, but also to explore the possibilities of how technical inventions, medical innovations could improve our way of life. [ABSTRACT FROM AUTHOR]

As a typical representative of the public key cryptosystem, RSA has attracted a great deal of cryptanalysis since its invention, among which a famous attack is the small private exponent attack. It is well-known that the best theoretical upper bound for the private exponent d that can be attacked is d ≤ N 0.292 , where N is a RSA modulus. However, this bound may not be achieved in practical attacks since the lattice constructed by Coppersmith method may have a large enough dimension and the lattice-based reduction algorithms cannot work so well in both efficiency and quality. In this paper, we propose a new practical attack based on the binary search for the most significant bits (MSBs) of prime divisors of N and the Herrmann-May's attack in 2010. The idea of binary search is inspired by the discovery of phenomena called "multivalued-continuous phenomena", which can significantly accelerate our attack. Together with several carefully selected parameters according to our exact and effective numerical estimations, we can improve the upper bound of d that can be practically achieved. More specifically, without the binary search method, we successfully attack RSA with a 1024-bit-modulus N when d ≤ N 0.285 . Moreover, by our new method, we can implement a successful attack for a 1024-bit-modulus RSA when d ≤ N 0.292 and for a 2048-bit-modulus RSA when d ≤ N 0.287 in about a month. We believe our method can provide some inspiration to practical attacks on RSA with mainstream-size moduli. [ABSTRACT FROM AUTHOR]