Green innovation and enterprise digital transformation: Escape from the "dilemma" of development and governance choices.

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.

The impact of technological innovation on the green digital economy and development strategies.

To investigate the interplay among technological innovation, industrial structure, production methodologies, economic growth, and environmental consequences within the paradigm of a green economy and to put forth strategies for sustainable development, this study scrutinizes the limitations inherent in conventional deep learning networks. Firstly, this study analyzes the limitations and optimization strategies of multi-layer perceptron (MLP) networks under the background of the green economy. Secondly, the MLP network model is optimized, and the dynamic analysis of the impact of technological innovation on the digital economy is discussed. Finally, the effectiveness of the optimization model is verified by experiments. Moreover, a sustainable development strategy based on dynamic analysis is also proposed. The experimental results reveal that, in comparison to traditional Linear Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Naive Bayes (NB) models, the optimized model in this study demonstrates improved performance across various metrics. With a sample size of 500, the optimized model achieves a prediction accuracy of 97.2% for forecasting future trends, representing an average increase of 14.6%. Precision reaches 95.4%, reflecting an average enhancement of 19.2%, while sensitivity attains 84.1%, with an average improvement of 11.8%. The mean absolute error is only 1.16, exhibiting a 1.4 reduction compared to traditional models and confirming the effectiveness of the optimized model in prediction. In the examination of changes in industrial structure using 2020 data to forecast the output value of traditional and green industries in 2030, it is observed that the output value of traditional industries is anticipated to decrease, with an average decline of 11.4 billion yuan. Conversely, propelled by the development of the digital economy, the output value of green industries is expected to increase, with an average growth of 23.4 billion yuan. This shift in industrial structure aligns with the principles and trends of the green economy, further promoting sustainable development. In the study of innovative production methods, the green industry has achieved an increase in output and significantly enhanced production efficiency, showing an average growth of 2.135 million tons compared to the average in 2020. Consequently, this study highlights the dynamic impact of technological innovation on the digital economy and its crucial role within the context of a green economy. It holds certain reference significance for research on the dynamic effects of the digital economy under technological innovation.

Analysis of the spatial and temporal evolution process and development trend of innovation capability of Chinese sports industry.

The paper uses spatial panel data on the number of patents in the field of sports in each province from 2017-2022 to explore the spatial and temporal evolution process of the innovation capacity of China's sports industry and analyze its development trend based on theories related to economic geography, using exploratory spatial data analysis (ESDA) and Spatial-temporal correlation analysis research methods. The study shows that: 1. there is a large spatial regional disparity in the innovation capacity of China's sports industry, showing an obvious pattern of strength in the east and weakness in the west. 2. there is an obvious phenomenon of spatial agglomeration in the innovation capacity of China's sports industry and the agglomeration phenomenon in space is gradually increasing. 3. there is a spatial spillover effect in the innovation capacity of China's sports industry, and the inward spillover continues to strengthen mainly into Zhejiang, Fujian and Jiangsu provinces, while the outward spillover mainly goes to Guangdong, Hubei, Hebei, Hunan, Sichuan. Sports industry innovation capacity development put forward three suggestions: to promote the development of sports industry in the northwest region; to play the advantages of regional characteristics of sports industry; to accelerate the integration of neighboring regions to build the process. in order to help the high-quality development of sports industry.

Papers and patents are becoming less disruptive over time.

Theories of scientific and technological change view discovery and invention as endogenous processes1,2, 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 advances8,9. Yet contrary to this view, studies suggest that progress is slowing in several major fields10,11. 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 index12-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 metrics1,13-17. 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.

Thyroid cancer under the scope of emerging technologies.

The vast majority of thyroid cancers originate from follicular cells. We outline outstanding issues at each step along the path of cancer patient care, from prevention to post-treatment follow-up and highlight how emerging technologies will help address them in the coming years. Three directions will dominate the coming technological landscape. Genomics will reveal tumoral evolutionary history and shed light on how these cancers arise from the normal epithelium and the genomics alteration driving their progression. Transcriptomics will gain cellular and spatial resolution providing a full account of intra-tumor heterogeneity and opening a window on the microenvironment supporting thyroid tumor growth. Artificial intelligence will set morphological analysis on an objective quantitative ground laying the foundations of a systematic thyroid tumor classification system. It will also integrate into unified representations the molecular and morphological perspectives on thyroid cancer.

Teaming: learning, competing, and innovating in the world of reproductive medicine.

Healthcare teams must be deliberately cultivated to reach their full potential. Shifting focus from individual performance to a team's collective competence allows for targeted and evidence-based interventions that support teamwork and improve patient outcomes. We reviewed essential concepts drawn from team science and explored the practical applications of teaming. Reproductive endocrinology and infertility healthcare providers play a pivotal role by teaching, modeling, and fostering teaming attitudes and behaviors. Through teaming, we can maximize our teams' ability to learn, innovate, compete with other teams, and thrive in today's healthcare environment.

Recommending blue ocean technologies for subcontractors: A framework based on business reports of prime contractors and patents.

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

2021 Update on Safety of Magnetic Resonance Imaging: Joint Statement From Canadian Cardiovascular Society/Canadian Society for Cardiovascular Magnetic Resonance/Canadian Heart Rhythm Society.

Magnetic resonance imaging (MRI) is often considered the gold-standard test for characterizing cardiac as well as noncardiac structure and function. However, many patients with cardiac implantable electronic devices (CIEDs) and/or severe renal dysfunction are unable to undergo this test because of safety concerns. In the past 10 years, newer-generation CIEDs and gadolinium-based contrast agents (GBCAs) as well as coordinated care between imaging and heart rhythm device teams have mitigated risk to patients and improved access to MRI at many hospitals. The purpose of this statement is to review published data on safety of MRI in patients with conditional and nonconditional CIEDs in addition to patient risks from older and newer GBCAs. This statement was developed through multidisciplinary collaboration of pan-Canadian experts after a relevant and independent literature search by the Canadian Agency for Drugs and Technologies in Health. All recommendations align with the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. Key recommendations include: (1) the development of standardized protocols for patients with a CIED undergoing MRI; (2) patients with MRI nonconditional pacemakers and pacemaker dependency should be programmed to asynchronous mode and those with MRI nonconditional transvenous defibrillators should have tachycardia therapies turned off during the scan; and (3) macrocyclic or newer linear GBCAs should be used in preference to older GBCAs because of their better safety profile in patients at higher risk of nephrogenic systemic fibrosis.

Impact of innovation in oncology: more questions than answers.

Oncology is going through the fastest innovation period in the history of medicine and a growing number of patients improve or experience increased chances of survival. The declining death rate, starting from 1991, resulted in 2.9 million deaths avoided in the United States so far. A growing prevalence of patients is observed in all Western countries. New cancer drug approvals between 2000 and 2016, linked to other diagnostic, surgical, and health care improvements, were significantly associated with death reduction for the most common cancers. Alongside many positive aspects, other effects of innovations in oncology also deserve attention, especially challenges associated with the substantial increase of knowledge volume, the sharp growth of prevalence, and a concomitant or consequent increase in clinical, social, and organizational complexity. We analyse some of the consequences of oncology innovation on healthcare systems and professionals and present some suggestions on how these could be addressed by healthcare systems.

Science shines in a new virtual SY-Stem.

The third 'Symposium for the Next Generation of Stem Cell Research' (SY-Stem) was held virtually on 3-5 March 2021, having been cancelled in 2020 due to the COVID-19 pandemic. As in previous years, the meeting highlighted the work of early career researchers, ranging from postgraduate students to young group leaders working in developmental and stem cell biology. Here, we summarize the excellent work presented at the Symposium, which covered topics ranging from pluripotency, species-specific aspects of development and emerging technologies, through to organoids, single-cell technology and clinical applications.