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Bolt loosening evaluation method based on normalized screw root equivalent stress and loosening life curve
Ocean acidification induces changes in circadian alternative splicing profiles in a coral reef fish
Innovative deep learning classifiers for breast cancer detection through hybrid feature extraction techniques
Abstract Breast cancer remains a major cause of mortality among women, where early and accurate detection is critical to improving survival rates. This study presents a hybrid classification approach for mammogram analysis by combining handcrafted statistical features and deep learning techniques. The methodology involves preprocessing with the Shearlet Transform, segmentation using Improved Otsu thresholding and Canny edge detection, followed by feature extraction through Gray Level Co-occurrence Matrix (GLCM), Gray Level Run Length Matrix (GLRLM), and 1st-order statistical descriptors. These features are input into a 2D BiLSTM-CNN model designed to learn spatial and sequential patterns in mammogram images. Evaluated on the MIAS dataset, the proposed method achieved 97.14% accuracy, outperforming several benchmark models. The results indicate that this hybrid strategy offers improvements in classification performance and may assist radiologists in more effective breast cancer screening.
Effects of sport disciplines on offspring sex ratio in elite athletes: an observational study
Gpbar1-mediated SIRT1-PGC-1α axis maintains mitochondrial homeostasis and mitigates renal injury in obstructive jaundice
Treatment outcomes of ABVD in classical Hodgkin lymphoma patients from Thailand without procarbazine access
Physical activity enhances college students’ mental health through social adaptability and exercise behavior chain mediation
Empathy and mental health distress in informal caregivers of dementia and stroke patients: a cross-sectional study
FDA approves a c-MET-targeted ADC for lung cancer
Written in chromatin: The enduring legacy of C. David Allis
How does the institutional environment improve the entrepreneurial quality of returnees? A configuration analysis based on a complex system view
Enhancing high-quality entrepreneurship among returnees stands as a pivotal mechanism in driving the robust economic development of emerging economies. The inquiry into crafting an enabling institutional framework to bolster the excellence of returnee entrepreneurship has garnered significant interest within academia and pertinent industries. Existing research primarily explores the impact of single institutional elements on returnee entrepreneurship, overlooking the diverse pathways to improve its quality under institutional complexity. Building on these insights, the current study explores the complex relationship between institutional configurations and the quality of returnee entrepreneurship in China. It also employs Necessary Condition Analysis (NCA) and dynamic Qualitative Comparative Analysis (QCA) methods based on a complex systems perspective. The research samples include 30 provinces in China. The findings reveal that while individual institutional factors do not, on their own, drive high-quality entrepreneurship among returnees in Periods 1 and 2, the importance of market environment and digital infrastructure becomes pronounced by Period 3. In the initial period, resource-driven entrepreneurship paired with emerging opportunities fosters high-quality outcomes. By Period 2, two additional configurations take shape: legitimacy-driven entrepreneurship under opportunity emergence and a dual-driver model that integrates both opportunities and resources. This dual-driver approach remains the dominant pathway for returnees in Period 3. Additionally, the market environment remains a critical factor across all periods. Digital infrastructure has become increasingly crucial for returnee entrepreneurship. Initially, the market environment focused primarily on financial services, but its connection with digital infrastructure intensified over time. In that regard, differences in economic resources and development across provinces have also led to region-specific pathways for improving the quality of returnee entrepreneurship. The findings contribute to a nuanced comprehension of the disparate progress of returnee entrepreneurial endeavors across regions within emerging economies. Most importantly, they offer theoretical insights to enhance the institutional framework in diverse regions, fostering the attainment of high-quality returnee entrepreneurship.
Influence of bond strength in treated mixed recycled aggregate concrete incorporating olivine sand
Development of Cu-ZnO ZrO2 based polyacrylonitrile polymer composites for removing pharmaceutical pollutants and heavy metals from wastewater
ADCY4 inhibits cAMP-induced growth of breast cancer by inactivating FAK/AKT and ERK signaling but is frequently silenced by DNA methylation
A NoSQL document based eCRF system for study of vaccines with variable adverse events case study on COVID19 vaccines
Predict the degree of secondary structures of the encoding sequences in DNA storage by deep learning model
Oxyresveratrol suppressed melanogenesis, dendrite formation, and melanosome transport in melanocytes via regulation of the MC1R/cAMP/MITF pathway
Abstract Oxyresveratrol, a natural derivative of resveratrol, has been shown to possess antimelanogenic properties. However, the underlying mechanism and its effect on melanin transfer remain poorly understood. In this study, the effects and mechanisms of oxyresveratrol on melanogenesis, dendrite formation, and melanosome transport were investigated. In vitro assays indicated that oxyresveratrol is a potent inhibitor of human tyrosinase, with an IC50 value of 2.27 µg/mL. Treatment of B16F10 melanoma cells with oxyresveratrol suppressed melanogenesis through the down-regulation of the MC1R/cAMP/MITF signaling pathway. In a co-culture model of B16F10 and HaCaT cells, oxyresveratrol inhibited both melanin transfer and dendrite formation by down-regulating the expression of small GTPases (CDC42, RAB17, RAB11B, RAC1) and the kinesin KIF5B. These findings suggested that oxyresveratrol may serve as a promising therapeutic agent for pigment-related disorders by inhibiting melanogenesis, dendrite formation, and melanosome transport.