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Accurate boundaries of smallholder farm fields are important and indispensable geo-information that benefits farmers, managers, and policymakers in terms of better managing and utilizing their agricultural resources. Due to their small size, irregular shape, and the use of mixed-cropping techniques, the farm fields of smallholder can be difficult to delineate automatically. In recent years, numerous studies on field contour extraction using a deep Convolutional Neural Network (CNN) have been proposed. However, there is a relative shortage of labeled data for filed boundaries, thus affecting the training effect of CNN. Traditional methods mostly use image flipping, and random rotation for data augmentation. In this paper, we propose to apply Generative Adversarial Network (GAN) for the data augmentation of farm fields label to increase the diversity of samples. Specifically, we propose an automated method featured by Fully Convolutional Neural networks (FCN) in combination with GAN to improve the delineation accuracy of smallholder farms from Very High Resolution (VHR) images. We first investigate four State-Of-The-Art (SOTA) FCN architectures, i.e., U-Net, PSPNet, SegNet and OCRNet, to find the optimal architecture in the contour detection task of smallholder farm fields. Second, we apply the identified optimal FCN architecture in combination with Contour GAN and pixel2pixel GAN to improve the accuracy of contour detection. We test our method on the study area in the Sudano-Sahelian savanna region of northern Nigeria. The best combination achieved F1 scores of 0.686 on Test Set 1 (TS1), 0.684 on Test Set 2 (TS2), and 0.691 on Test Set 3 (TS3). Results indicate that our architecture adapts to a variety of advanced networks and proves its effectiveness in this task. The conceptual, theoretical, and experimental knowledge from this study is expected to seed many GAN-based farm delineation methods in the future.

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The influence of SGLT-1 on perivascular preadipocytes (PVPACs) and vascular remodeling is not well understood. This study aimed to elucidate the role and mechanism of SGLT-1-mediated PVPACs bioactivity. PVPACs were cultured in vitro and applied ex vivo to the carotid arteries of mice using a lentivirus-based thermosensitive in situ gel (TISG). The groups were treated with Lv-SGLT1 (lentiviral vector, overexpression), Lv-siSGLT1 (RNA interference, knockdown), or specific signaling pathway inhibitors. Assays were conducted to assess changes in cell proliferation, apoptosis, glucose uptake, adipogenic differentiation, and vascular remodeling in the PVPACs. Protein expression was analyzed by Western blotting, immunocytochemistry, and/or immunohistochemistry. The methyl thiazolyl tetrazolium (MTT) assay and Hoechst 33342 staining indicated that SGLT-1 overexpression significantly promoted PVPACs proliferation and inhibited apoptosis in vitro. Conversely, SGLT-1 knockdown exerted the opposite effect. Oil Red O staining revealed that SGLT-1 overexpression facilitated adipogenic differentiation, while its inhibition mitigated these effects. 3H-labeled glucose uptake experiments demonstrated that SGLT-1 overexpression enhanced glucose uptake by PVPACs, whereas RNA interference-mediated SGLT-1 inhibition had no significant effect on glucose uptake. Moreover, RT-qPCR, Western blotting, and immunofluorescence analyses revealed that SGLT-1 overexpression upregulated FABP4 and VEGF-A levels and activated the Akt/mTOR/p70S6K signaling pathway, whereas SGLT-1 knockdown produced the opposite effects. In vivo studies corroborated these findings and indicated that SGLT-1 overexpression facilitated carotid artery remodeling. Our study demonstrates that SGLT-1 activation of the Akt/mTOR/p70S6K signaling pathway promotes PVPACs proliferation, adipogenesis, glucose uptake, glucolipid metabolism, and vascular remodeling. NEW & NOTEWORTHY: SGLT-1 is expressed in PVPACs and can affect preadipocyte glucolipid metabolism and vascular remodeling. SGLT-1 promotes the biofunctions of PVPACs mediated by Akt/mTOR/p70S6K signaling pathway. Compared with caudal vein or intraperitoneal injection, the external application of lentivirus-based thermal gel around the carotid artery is an innovative attempt at vascular remodeling model, it may effectively avoid the transfection of lentiviral vector into the whole body of mice and the adverse effect on experimental results. [ABSTRACT FROM AUTHOR]