Research on the impact mechanism of scientific and technological innovation on the high-quality development of the marine economy

Promoting the high-quality development of the marine economy is an inevitable choice for building a maritime power, and technological innovation can provide strong impetus for the high-quality development of the marine economy. Therefore, it is urgent to clarify the impact mechanism of technological innovation on the high-quality development of the marine economy, and promote the high-quality development of the marine economy. This study employs panel data from 11 coastal provinces and municipalities (autonomous regions) in China, spanning the years 2006 to 2020. The objective is to empirically evaluate the mechanism through which scientific and technical innovation impacts the high-quality development of the marine economy. This is achieved by utilizing the PVAR model and the mediation effect model. The research findings indicate that there is a noteworthy impact of enhancing scientific and technological innovation on the marine economy of China. Moreover, there exists a significant reciprocal relationship between scientific and technological innovation and the pursuit of high-quality development in the marine economy. It is observed that scientific and technological innovation not only has a positive influence on the high-quality development of the marine economy by enhancing green total factor productivity and optimizing the industrial structure, but it also facilitates the advancement of the marine economy through the chain mediation path of “improving green total factor productivity and optimizing industrial structure”

Neutrosophic soft sets forecasting model for multi-attribute time series

Traditional time series forecasting models mainly assume a clear and definite functional relationship between historical values and current/future values of a dataset. In this paper, we extended current model by generating multi-attribute forecasting rules based on consideration of combining multiple related variables. In this model, neutrosophic soft sets (NSSs) are employed to represent historical statues of several closely related attributes in stock market such as volumes, stock market index and daily amplitudes

Spatial differences, distribution dynamics and driving factors of the synergy between marine ecological security and high-quality development in three major marine economic circles of China

IntroductionIn China, the sustainable development of the marine is facing a prominent contradiction between ecological security and economic development, as well as unbalanced and non-coordinated regional development. Exploring the regional differences in the synergy between marine ecological security (MES) and high-quality development of the marine economy (MHQD) and its driving mechanism is the key to optimizing the spatial distribution of marine development, promoting the synergistic and balanced development of the regional marine composite system during the “14th Five-Year Plan” period.MethodsIn this article, we employed the Dagum Gini coefficient decomposition model and Kernel density estimation methods to reveal the evolution of regional differences, sources, and distributional dynamics of synergistic development of the composite system from 2009 to 2020. Meanwhile, spatial econometric analyses were applied to identify the influencing factors and spatial spillover effects.ResultsThe level of synergistic development of composite system has a fluctuating upward trend, with a significant positive spatial correlation and a significant “polarization effect”. Inter-regional differences in the synergistic development of the composite system are the main source of the overall differences. Factors such as innovation-driven, human capital, and opening up to the outside world are important driving factors for the synergistic development of the composite system.DiscussionThe MES-MHQD composite system exhibits a low level of synergistic development, with significant differences in the level of synergy both among the 3MMECs and within each circle. We infer that the expansion trend of overall difference will constrain the exploration of a sustainable development path for China’s coastal regions in the future. It is necessary to optimize the spatial layout of the composite system, establish robust mechanisms for regional cooperation and communication, accurately identify the development bottlenecks of the regional composite systems. This study provides a theoretical basis and decision-making reference for the promotion of the synergistic development of the composite system of the Three Major Marine Economic Circles (3MMECs) in China

Research on the evolution of innovation behavior of new generation entrepreneurs in different scenarios

Innovation of new generation entrepreneurs is crucial to the development of a country. Empirical research method can analyze the history and current situation, but it is difficult to reflect the dynamic process and evolution trend under different scenarios. In this paper, we adopt computational experiment method to model the decision-making process of new generation entrepreneurs. Multi-agent evolution model is constructed to simulate individual behavior of different types of new generation entrepreneurs under different scenarios. By the comparison of different results, it analyses the evolutionary rules of innovation behaviors and explores guidance policies to promote entrepreneurs’ innovation behavior and achieve better innovation performance. The experimental results show that although internal elements such as individual’s innovative spirit, innovative ability and cognition of social capital determine the innovation intention, the capital, technology and talent conditions are also very important for innovation implementation. New generation entrepreneurs with different risk preferences should objectively evaluate and treat innovation risks according to their own characteristics. This helps to reduce the negative impact of innovation risk on continuous innovation. Meanwhile, government should pay attention to establishing risk guarantee mechanism such as innovation insurance fund to promote the innovation of new generation entrepreneurs. First published online 17 April 202

A real-world clinicopathological model for predicting pathological complete response to neoadjuvant chemotherapy in breast cancer

PurposeThis study aimed to develop and validate a clinicopathological model to predict pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer patients and identify key prognostic factors.MethodsThis retrospective study analyzed data from 279 breast cancer patients who received NAC at Zhejiang Provincial People’s Hospital from 2011 to 2021. Additionally, an external validation dataset, comprising 50 patients from Lanxi People’s Hospital and Second Affiliated Hospital, Zhejiang University School of Medicine from 2022 to 2023 was utilized for model verification. A multivariate logistic regression model was established incorporating clinical, ultrasound features, circulating tumor cells (CTCs), and pathology variables at baseline and post-NAC. Model performance for predicting pCR was evaluated. Prognostic factors were identified using survival analysis.ResultsIn the 279 patients enrolled, a pathologic complete response (pCR) rate of 27.96% (78 out of 279) was achieved. The predictive model incorporated independent predictors such as stromal tumor-infiltrating lymphocyte (sTIL) levels, Ki-67 expression, molecular subtype, and ultrasound echo features. The model demonstrated strong predictive accuracy for pCR (C-statistics/AUC 0.874), especially in human epidermal growth factor receptor 2 (HER2)-enriched (C-statistics/AUC 0.878) and triple-negative (C-statistics/AUC 0.870) subtypes, and the model performed well in external validation data set (C-statistics/AUC 0.836). Incorporating circulating tumor cell (CTC) changes post-NAC and tumor size changes further improved predictive performance (C-statistics/AUC 0.945) in the CTC detection subgroup. Key prognostic factors included tumor size >5cm, lymph node metastasis, sTIL levels, estrogen receptor (ER) status and pCR. Despite varied pCR rates, overall prognosis after standard systemic therapy was consistent across molecular subtypes.ConclusionThe developed predictive model showcases robust performance in forecasting pCR in NAC-treated breast cancer patients, marking a step toward more personalized therapeutic strategies in breast cancer

Metastatic patterns and prognosis of patients with primary malignant cardiac tumor

BackgroundDistant metastases are independent negative prognostic factors for patients with primary malignant cardiac tumors (PMCT). This study aims to further investigate metastatic patterns and their prognostic effects in patients with PMCT.Materials and methodsThis multicenter retrospective study included 218 patients with PMCT diagnosed between 2010 and 2017 from Surveillance, Epidemiology, and End Results (SEER) database. Logistic regression was utilized to identify metastatic risk factors. A Chi-square test was performed to assess the metastatic rate. Kaplan–Meier methods and Cox regression analysis were used to analyze the prognostic effects of metastatic patterns.ResultsSarcoma (p = 0.002) and tumor size¿4 cm (p = 0.006) were independent risk factors of distant metastases in patients with PMCT. Single lung metastasis (about 34%) was the most common of all metastatic patterns, and lung metastases occurred more frequently (17.9%) than bone, liver, and brain. Brain metastases had worst overall survival (OS) and cancer-specific survival (CSS) among other metastases, like lung, bone, liver, and brain (OS: HR = 3.20, 95% CI: 1.02–10.00, p = 0.046; CSS: HR = 3.53, 95% CI: 1.09–11.47, p = 0.036).ConclusionPatients with PMCT who had sarcoma or a tumor larger than 4 cm had a higher risk of distant metastases. Lung was the most common metastatic site, and brain metastases had worst survival among others, such as lung, bone, liver, and brain. The results of this study provide insight for early detection, diagnosis, and treatment of distant metastases associated with PMCT

The Prevalence of Metabolically Healthy and Unhealthy Obesity according to Different Criteria

Objective: Obesity-related disease risks may vary depending on whether the subject has metabolically healthy obesity (MHO) or metabolically unhealthy obesity (MUO). At least 5 definitions/criteria of obesity and metabolic disorders have been documented in the literature, yielding uncertainties in a reliable international comparison of obesity phenotype prevalence. This report aims to compare differences in MHO and MUO prevalence according to the 5 most frequently used definitions. Methods: A random sample of 4,757 adults aged 35 years and older (male 51.1%) was enrolled. Obesity was defined either according to body mass index or waist circumference, and the definitions of metabolic abnormalities were derived from 5 different criteria. Results: In MHO, the highest prevalence was obtained when using the homeostasis model assessment (HOMA) criteria (13.6%), followed by the Chinese Diabetes Society (11.4%), Adult Treatment Panel III (10.3%), Wildman (5.2%), and Karelis (4.2%) criteria; however, the MUO prevalence had an opposite trend to MHO prevalence. The magnitude of differences in the age-specific prevalence of MHO and MUO varied greatly and ranked in different orders. The proportion of insulin resistance for MHO and MUO individuals differed significantly regardless of which metabolic criterion was used. Conclusion: The prevalence of MHO and MUO in the Chinese population varies according to different definitions of obesity and metabolic disorders