Based on the construction of digital technology evaluation index system, this paper builds a dynamic threshold regression model to explore the complex impact of digital technology on Chinese-style industrial modernization under the threshold of R&D human resources, taking 30 provinces as research objects. It has been found that China's digital technology index is continuously improving, but there is a digital gap among regions. The beneficial impact of digital technology on Chinese-style industrial modernization has been thoroughly validated. Considering the threshold effect of R&D human resources, the influence of digital technology on Chinese-style industrial modernization exhibits nonlinear characteristics. With R&D human resources crossing the first threshold, it has shown a significant positive effect on Chinese-style industrial modernization, and the middle range of R&D human resources presents the optimal interval of the relationship between the two. The research findings offer a theoretical framework for advancing the construction of Chinese-style modernization.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11584949 | PMC |
| http://dx.doi.org/10.1016/j.heliyon.2024.e38484 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Characterization of 3,3'-iminodipropionitrile (IDPN) damaged utricle transcriptome in the adult mouse utricle.
Front Mol Neurosci
December 2024
State Key Laboratory of Digital Medical Engineering, Department of Otolaryngology Head and Neck Surgery, Zhongda Hospital, School of Life Sciences and Technology, Advanced Institute for Life and Health, Jiangsu Province High-Tech Key Laboratory for Bio-Medical Research, Southeast University, Nanjing, China.
Utricle is an important vestibular sensory organ for maintaining balance. 3,3'-iminodipropionitrile (IDPN), a prototype nitrile toxin, has been reported to be neurotoxic and vestibulotoxic, and can be used to establish an damage model of vestibular dysfunction. However, the mechanism of utricular HCs damage caused by IDPN is unclear.
View Article and Find Full Text PDFMedication non-adherence: reflecting on two decades since WHO adherence report and setting goals for the next twenty years.
Front Pharmacol
December 2024
Syreon Research Institute, Budapest, Hungary.
Background: Non-adherence to medication remains a persistent and significant challenge, with profound implications for patient outcomes and the long-term sustainability of healthcare systems. Two decades ago, the World Health Organization (WHO) dedicated its seminal report to adherence to long-term therapies, catalysing notable changes that advanced both research and practice in medication adherence. The aim of this paper was to identify the most important progress made over the last 2 decades in medication adherence management and to initiate a discussion on future objectives, suggesting priority targets for the next 20 years.
View Article and Find Full Text PDFDigital health interventions in adult intensive care and recovery after critical illness to promote survivorship care.
J Intensive Care Soc
January 2025
Department of Physiotherapy, Faculty of Medicine, Dentistry and Health Sciences, School of Health Sciences, The University of Melbourne, Melbourne, VIC, Australia.
Digital health refers to the field of using and developing technology to improve health outcomes. Digital health and digital health interventions (DHIs) within the area of intensive care and critical illness survivorship are rapidly evolving. Digital health interventions refer to technologies in clinical interventional format.
View Article and Find Full Text PDFImaging-based spatial transcriptomics (ST) is evolving rapidly as a pivotal technology in studying the biology of tumors and their associated microenvironments. However, the strengths of the commercially available ST platforms in studying spatial biology have not been systematically evaluated using rigorously controlled experiments. In this study, we used serial 5-m sections of formalin-fixed, paraffin-embedded surgically resected lung adenocarcinoma and pleural mesothelioma tumor samples in tissue microarrays to compare the performance of the single cell ST platforms CosMx, MERFISH, and Xenium (uni/multi-modal) platforms in reference to bulk RNA sequencing, multiplex immunofluorescence, GeoMx Digital Spatial Profiler, and hematoxylin and eosin staining data for the same samples.
View Article and Find Full Text PDFThe application of deep learning in early enamel demineralization detection.
PeerJ
January 2025
State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China.
Objective: The study aims to develop a diagnostic model using intraoral photographs to accurately detect and classify early detection of enamel demineralization on tooth surfaces.
Methods: A retrospective analysis was conducted with 208 patients aged 14 to 44. A total of 624 high-quality digital images captured under standardized conditions were used to construct a deep learning model based on the Mask region-based convolutional neural network (Mask R-CNN).
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!