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The plasma equilibrium plays a crucial role in nuclear fusion studies, serving as the foundation for various aspects of fusion research, including plasma stability, transport, and current drive. In this paper, a new Grad–Shafranov equation solver is developed for the fixed-boundary plasma equilibria with toroidal flow. This solver utilizes the pressure profile, safety factor profile (not current profile), and any two profiles of the toroidal angular velocity, plasma temperature, and square of the Mach number as inputs. The numerical results obtained by this solver exhibit good agreement with known analytic solution under identical parameters, and the potential applications of the solver are demonstrated through several numerical equilibria with toroidal flow. It is very convenient to apply this code to simulate the tokamak equilibrium with a smooth plasma shape. In addition, the effect of toroidal flow on the plasma equilibria is investigated as a simple application. The results reveal a notable outward shift in the contour profiles of magnetic flux surface, density, pressure, and temperature induced by toroidal flow. [ABSTRACT FROM AUTHOR]

Real-time detection of fabric defects is a fairly critical part of industrial production. However, there are still some key issues to be solved in practical detection production, such as low detection speed and delays in traditional cloud detection. To address these issues, in this paper, a new detection network architecture, called YOLOV4-TinyS, is proposed. Firstly, the k -medoids clustering algorithm is used to improve the matching of anchor points and ground truths for datasets with great differences. Secondly, the residual structure is changed to reduce the complexity of the network structure, and a depth-separable convolution is used instead of partial convolution to improve the detection speed. Thirdly, the output feature layer is designed with shallow feature fusion to improve the location information extraction capability and use spatial attention and channel attention to improve the network efficiency. Finally, the whole network is trained and tested on four different datasets and extensive experiments show that the network has higher detection accuracy and faster detection speed compared to existing methods. Compared to the original network, YOLOV4-Tiny, the model complexity is reduced by 67.86% and the highest detection accuracy of 99.91% is achieved. Furthermore, the establishment of an efficient fabric inspection system and the validation of the method allows for the fast detection of fabric defects on conveyor belts. Thus, the proposed method has the potential to lay the foundation for the real-time detection of fabric defects and their application in industry. [ABSTRACT FROM AUTHOR]

Climate change and land use/land cover (LULC) change have received widespread attention as the two main factors contributing to the shrinking of plant habitats. However, the different effects of these factors on understory economic tree species are not clear. This is not conducive to the conservation and exploitation of forest resources. Here, we used species distribution modeling to predict the extent to which climate change and LULC change will affect changes in suitable habitats for A. elata under different scenarios in the future. The results showed the suitable habitat to be located in the Changbai Mountain Range in northeast China. The current area is 110,962 km2. The main variables that affect the suitable habitat are annual precipitation, LULC, slope, and mean diurnal range. The percentage contributions are 31.2%, 16.8%, 12.8%, and 12.3%, respectively. In the 2070s, the area of high-quality (moderately and highly) suitable habitat was reduced by an average of 6.05% when climate alone changed, and by an average of 10.21% when land use alone changed. When both factors changed together, there was an average decrease of 9.69%. When climate change and land use change acted together, the shrinking area of suitable habitat did not suddenly increase. These findings help to identify potentially suitable habitats for A. elata and to carry out conservation and exploitation efforts to ensure sustainability. [ABSTRACT FROM AUTHOR]

Purpose: LncRNA-Atherosclerotic plaque pathogenesis-associated transcript (APPAT) could be detected in circulating blood and has been demonstrated to correlate with the development of atherosclerosis in our previous work. It could be a potential noninvasive biomarker for earlier diagnoses of clinical cardiovascular disease. Moreover, the expression of miR-647 increased in ox-LDL-treated vascular smooth muscle cells and peripheral blood of patients with coronary heart disease. A negative correlation between APPAT and miR-647 was confirmed, and FGF5 was screened as molecular target of miR-647. However, it is largely unclear how APPAT, miR-647, and FGF5 interact and function in disease development. Here, we aim to explore the underlying molecular mechanism in this progression. Materials and Methods: APPAT, miR-647, and FGF5 expression levels were detected by quantitative reverse transcription polymerase chain reaction; cell proliferation was detected by EdU incorporation assay; cell migration was detected by wound-healing assay; the molecular interaction of APPAT/ FGF5 with miR-647 was verified by dual-luciferase reporter assay; the western blot was performed to determine the gene expression at protein levels; subcellular localizations of APPAT and miR-647 were observed by fluorescence in situ hybridization; cytosolic and nucleus fractionation assay was performed to further detect the distribution of miR-647. Results: APPAT and miR-647 have inverse effects on human aortic smooth muscle cells' (HASMCs) proliferation and migration. APPAT negatively regulated the cell activity, whereas miR-647 did it in a positive way (p<0.05). Three pairs of molecular interplay were found: mutual negative regulation between APPAT and miR-647, APPAT downregulated FGF5, miR-647 regulation on FGF5 (p<0.05). Subcellular location assay confirmed the molecular interaction of APPAT and miR-647. Conclusions: APPAT could suppress the migration and proliferation of ox-LDL-treated HASMCs via interacting with miR-647 and FGF5. We revealed a nontypical competing endogenous RNA mechanism of long noncoding RNA in the progression of atherosclerosis. [ABSTRACT FROM AUTHOR]