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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11536098 | PMC |
| http://dx.doi.org/10.1017/S0033291724002137 | DOI Listing |
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Evolutionary game analysis on the regulation of medical devices used in health services delivery.
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December 2024
School of Management, Hefei University of Technology, Hefei, People's Republic of China.
Medical devices (MDs) play a critical role in healthcare delivery while also bringing potential medical risks and unintended harms to patients. Although government regulation is well recognized as a critical and essential function for ensuring the safety of MDs in many countries, the supplementary role that hospitals play is often neglected. This paper constructs a tripartite evolutionary game model involving the government, hospitals, and MDs enterprises to explore their strategic behaviors of MDs regulation in healthcare delivery.
View Article and Find Full Text PDFIntegrated analysis of physiological and metabolic data uncovers essential dynamic mechanisms involved in the maturation of cigar tobacco leaves.
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December 2024
Microelement Research Center, College of Resources and Environment, Huazhong Agricultural University, No. 1 Shizishan Road, Wuhan, 430070, China.
The quality of cigar tobacco leaves is profoundly affected by the timing of their harvest, with both early and late collections resulting in inferior characteristics. While the relationship between maturity and physiological metabolic processes is acknowledged, a comprehensive understanding of the physiological behavior of cigar leaves harvested at different stages remains elusive. This research investigated the physiological and metabolomic profiles of the cigar tobacco variety CX-014, grown in Danjiangkou City, Hubei Province, with leaves sampled at 35 (T1), 42 (T2), 49 (T3), and 56 (T4) days post-inflorescence removal.
View Article and Find Full Text PDFAn African vulture optimization algorithm based energy efficient clustering scheme in wireless sensor networks.
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December 2024
Department of Computer Science and Engineering, Chennai Institute of Technology, Chennai, India.
Energy efficiency plays a major role in sustaining lifespan and stability of the network, being one of most critical factors in wireless sensor networks (WSNs). To overcome the problem of energy depletion in WSN, this paper proposes a new Energy Efficient Clustering Scheme named African Vulture Optimization Algorithm based EECS (AVOACS) using AVOA. The proposed AVOACS method improves clustering by including four critical terms: communication mode decider, distance of sink and nodes, residual energy and intra-cluster distance.
View Article and Find Full Text PDFA stable combination of non-stable genes outperforms standard reference genes for RT-qPCR data normalization.
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December 2024
Laboratoire de Recherche en Sciences Végétales, Equipe Génomique et Biotechnologie des Fruits, UMR 5546, CNRS, UPS, Toulouse INP, Université de Toulouse, Toulouse, France.
Gene expression profiling is of key importance in all domains of life sciences, as medicine, environment, and plants, for both basic and applied research. Despite the emergence of microarrays and high-throughput sequencing, qPCR remains a standard method for gene expression analyses, with its data normalization step being crucial for ensuring accuracy. Currently, the most widely used normalization method is based on the use of reference genes, assumed to be stably expressed across all experimental conditions.
View Article and Find Full Text PDFOptimizing adult-oriented artificial intelligence for pediatric chest radiographs by adjusting operating points.
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December 2024
Department of Radiology, Stanford University, Lucile Packard Children's Hospital, 725 Welch Road, Palo Alto, CA, 94304, USA.
The purpose of this study was to evaluate whether the optimal operating points of adult-oriented artificial intelligence (AI) software differ for pediatric chest radiographs and to assess its diagnostic performance. Chest radiographs from patients under 19 years old, collected between March and November 2021, were divided into test and exploring sets. A commercial adult-oriented AI software was utilized to detect lung lesions, including pneumothorax, consolidation, nodule, and pleural effusion, using a standard operating point of 15%.
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