The Tibetan Plateau (TP) has a variety of vegetation types that range from alpine tundra to tropic evergreen forest, which play an important role in the global carbon (C) cycle and is extremely vulnerable to climate change. The vegetation C uptake is crucial to the ecosystem C sequestration. Moreover, net reduction in vegetation C uptake (NRVCU) will strongly affect the C balance of terrestrial ecosystem. Until now, there is limited knowledge on the recovery process of vegetation net C uptake and the spatial-temporal patterns of NRVCU after the disturbance that caused by climate change and human activities. Here, we used the MODIS-derived net primary production to characterize the spatial-temporal patterns of NRVCU. We further explored the influence factors of the net reduction rate in vegetation C uptake (NRRVCU) and recovery processes of vegetation net C uptake across a unique gradient zone on the TP. Results showed that the total net reduction amount of vegetation C uptake gradually decreased from 2000 to 2015 on the TP (Slope = -0.002, P < 0.05). Specifically, an increasing gradient zone of multi-year average of net reduction rate in vegetation carbon uptake (MYANRRVCU) from east to west was observed. In addition, we found that the recovery of vegetation net C uptake after the disturbance caused by climate change and anthropogenic disturbance in the gradient zone were primarily dominated by precipitation and temperature. The findings revealed that the effects of climate change on MYANRRVCU and vegetation net C uptake recovery differed significantly across geographical space and vegetation types. Our results highlight that the biogeographic characteristics of the TP should be considered for combating future climate change.
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http://dx.doi.org/10.1016/j.envres.2021.111894 | DOI Listing |
J Bone Oncol
February 2025
School of Mathematics and Computer Science, Quanzhou Normal University, Quanzhou, 362001, China.
Objective: Segmenting and reconstructing 3D models of bone tumors from 2D image data is of great significance for assisting disease diagnosis and treatment. However, due to the low distinguishability of tumors and surrounding tissues in images, existing methods lack accuracy and stability. This study proposes a U-Net model based on double dimensionality reduction and channel attention gating mechanism, namely the DCU-Net model for oncological image segmentation.
View Article and Find Full Text PDFQuant Imaging Med Surg
January 2025
Department of Information Management, National Yunlin University of Science & Technology, Yunlin.
Background: Image segmentation is crucial in medical diagnosis, helping to identify diseased areas in images for more accurate diagnoses. The U-Net model, a convolutional neural network (CNN) widely used for medical image segmentation, has limitations in extracting global features and handling multi-scale pathological information. This study aims to address these challenges by proposing a novel model that enhances segmentation performance while reducing computational demands.
View Article and Find Full Text PDFBMC Public Health
January 2025
Centro de Investigação Em Saúde de Manhiça (CISM), Rua 12, Maputo, Vila da Manhiça, PO Box 1929, Mozambique.
Background: Monitoring HIV infection estimates is critical to guide health interventions and assess their impact, especially in highly vulnerable groups to the infection such as African pregnant women. This study describes the trends of HIV infection over eleven years in women attending selected antenatal care (ANC) clinics from southern Mozambique.
Methods: We performed a secondary analysis of data registered at the ANC clinic of the Manhiça District Hospital and from the Ministry of Health's HIV National Program Registry between 2010 and 2021.
Physical exercise has been demonstrated to effectively mitigate repetitive behaviors in children with autism spectrum disorder (ASD), but the underlying dynamic brain network mechanisms are poorly understood. The triple network model consists of three brain networks that jointly regulate cognitive and emotional processes and is considered to be the core network underlying the aberrant manifestations of ASD. This study investigated whether a mini-basketball training program (MBTP) could alter repetitive behaviors and the dynamic connectivity of the triple network.
View Article and Find Full Text PDFJ Ovarian Res
January 2025
LongHua Hospital Shanghai University of Traditional Chinese Medicine, No.725 Wanping South Road, Xuhui District, Shanghai, 200032, China.
Objective: To systematically evaluate the effectiveness of non-pharmacological interventions (NPIs), including electroacupuncture, exercise, diet, and lifestyle changes, in reducing androgen levels in women with polycystic ovary syndrome (PCOS) through a systematic review and network meta-analysis.
Methods: Comprehensive searches were conducted in PubMed, Embase, Cochrane Library, Web of Science, CNKI, and Wanfang up to June 2024. Randomized controlled trials (RCTs) comparing NPIs with other NPIs or placebo treatments in adult women with PCOS were included.
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