Thermal Field Analysis and Simulation of an Infrared Belt Furnace Used for Solar Cells

During solar cell firing, volatile organic compounds (VOC) and a small number of metal particles were removed using the gas flow. When the gas flow was disturbed by the thermal field of infrared belt furnace and structure, the metal particles in the discharging gas flow randomly adhered to the surface of solar cell, possibly causing contamination. Meanwhile, the gas flow also affected the thermal uniformity of the solar cell. In this paper, the heating mechanism of the solar cell caused by radiation, convection, and conduction during firing was analyzed. Afterward, four 2-dimensional (2D) models of the furnace were proposed. The transient thermal fields with different gas inlets, outlets, and internal structures were simulated. The thermal fields and the temperature of the solar cell could remain stable and uniform when the gas outlets were installed at the ends and in the middle of the furnace, with the gas inlets being distributed evenly. To verify the results, we produced four types of furnaces according to the four simulated results. The experimental results indicated that the thermal distribution of the furnace and the characteristics of the solar cells were consistent with the simulation. These experiments improved the efficiency of the solar cells while optimizing the solar cell manufacturing equipment

TFDet: Target-aware Fusion for RGB-T Pedestrian Detection

Pedestrian detection plays a critical role in computer vision as it contributes to ensuring traffic safety. Existing methods that rely solely on RGB images suffer from performance degradation under low-light conditions due to the lack of useful information. To address this issue, recent multispectral detection approaches have combined thermal images to provide complementary information and have obtained enhanced performances. Nevertheless, few approaches focus on the negative effects of false positives caused by noisy fused feature maps. Different from them, we comprehensively analyze the impacts of false positives on the detection performance and find that enhancing feature contrast can significantly reduce these false positives. In this paper, we propose a novel target-aware fusion strategy for multispectral pedestrian detection, named TFDet. Our fusion strategy highlights the pedestrian-related features while suppressing unrelated ones, resulting in more discriminative fused features. TFDet achieves state-of-the-art performance on both KAIST and LLVIP benchmarks, with an efficiency comparable to the previous state-of-the-art counterpart. Importantly, TFDet performs remarkably well even under low-light conditions, which is a significant advancement for ensuring road safety. The code will be made publicly available at \url{https://github.com/XueZ-phd/TFDet.git}

Dynamic match kernel with deep convolutional features for image retrieval

For image retrieval methods based on bag of visual words, much attention has been paid to enhancing the discriminative powers of the local features. Although retrieved images are usually similar to a query in minutiae, they may be significantly different from a semantic perspective, which can be effectively distinguished by convolutional neural networks (CNN). Such images should not be considered as relevant pairs. To tackle this problem, we propose to construct a dynamic match kernel by adaptively calculating the matching thresholds between query and candidate images based on the pairwise distance among deep CNN features. In contrast to the typical static match kernel which is independent to the global appearance of retrieved images, the dynamic one leverages the semantical similarity as a constraint for determining the matches. Accordingly, we propose a semantic-constrained retrieval framework by incorporating the dynamic match kernel, which focuses on matched patches between relevant images and filters out the ones for irrelevant pairs. Furthermore, we demonstrate that the proposed kernel complements recent methods, such as hamming embedding, multiple assignment, local descriptors aggregation, and graph-based re-ranking, while it outperforms the static one under various settings on off-the-shelf evaluation metrics. We also propose to evaluate the matched patches both quantitatively and qualitatively. Extensive experiments on five benchmark data sets and large-scale distractors validate the merits of the proposed method against the state-of-the-art methods for image retrieval

QCD sum rule studies on the sssˉsˉs s \bar s \bar s tetraquark states with JPC=1+−J^{PC} = 1^{+-}

We apply the method of QCD sum rules to study the structure $X$ newly observed by the BESIII Collaboration in the $\phi \eta^\prime$ mass spectrum in 2.0-2.1 GeV region in the $J/\psi \rightarrow \phi \eta \eta^\prime$ decay. We construct all the $s s \bar s \bar s$ tetraquark currents with $J^{PC} = 1^{+-}$, and use them to perform QCD sum rule analyses. One current leads to reliable QCD sum rule results and the mass is extracted to be $2.00^{+0.10}_{-0.09}$ GeV, suggesting that the structure $X$ can be interpreted as an $s s \bar s \bar s$ tetraquark state with $J^{PC} = 1^{+-}$. The $Y(2175)$ can be interpreted as its $s s \bar s \bar s$ partner having $J^{PC} = 1^{--}$, and we propose to search for the other two partners, the $s s \bar s \bar s$ tetraquark states with $J^{PC} = 1^{++}$ and $1^{-+}$, in the $\eta^\prime f_0(980)$, $\eta^\prime K \bar K$, and $\eta^\prime K \bar K^*$ mass spectra.Comment: 8 pages, 5 figures, 1 table, suggestions and comments are welcom

Induction of lncRNA MALAT1 by hypoxia promotes bone formation by regulating the miR-22-3p/CEBPD axis

Adaptation to hypoxia promotes fracture healing. However, the underlying molecular mechanism remains unknown. Increasing evidence has indicated that long non-coding RNAs (lncRNAs) play crucial roles in several diseases, including fracture healing. In the present study, lncRNA microarray analysis was performed to assess the expression levels of different lncRNAs in MC3T3-E1 cells cultured under hypoxic conditions. A total of 42 lncRNAs exhibited significant differences in their expression, including metastasis associated lung adenocarcinoma transcript 1 (MALAT1), maternally expressed 3, AK046686, AK033442, small nucleolar RNA host gene 2 and distal-less homeobox 1 splice variant 2. Furthermore, overexpression of MALAT1 promoted osteoblast differentiation, alkaline phosphatase (ALP) activity and matrix mineralization of MC3T3-E1 cells, whereas its knockdown diminished hypoxia-induced cell differentiation, ALP activity and matrix mineralization in these cells. Moreover, functional analysis indicated that MALAT1 regulated the mRNA and protein expression levels of CCAAT/ enhancer binding protein δ by competitively binding to microRNA-22-3p. Adenoviral-mediated MALAT1 knockdown inhibited fracture healing in a mouse model. Taken together, the results indicated that MALAT1 may serve a role in hypoxia-mediated osteogenesis and bone formation