EACOFT: an energy-aware correlation filter for visual tracking.

Correlation filter based trackers attribute to its calculation in the frequency domain can efficiently locate targets in a relatively fast speed. This characteristic however also limits its generalization in some specific scenarios. The reasons that they still fail to achieve superior performance to state-of-the-art (SOTA) trackers are possibly due to two main aspects. The first is that while tracking the objects whose energy is lower than the background, the tracker may occur drift or even lose the target. The second is that the biased samples may be inevitably selected for model training, which can easily lead to inaccurate tracking. To tackle these shortcomings, a novel energy-aware correlation filter (EACOFT) based tracking method is proposed, in our approach the energy between the foreground and the background is adaptively balanced, which enables the target of interest always having a higher energy than its background. The samples’ qualities are also evaluated in real time, which ensures that the samples used for template training are always helpful with tracking. In addition, we also propose an optimal bottom-up and top-down combined strategy for template training, which plays an important role in improving both the effectiveness and robustness of tracking. As a result, our approach achieves a great improvement on the basis of the baseline tracker, especially under the background clutter and fast motion challenges. Extensive experiments over multiple tracking benchmarks demonstrate the superior performance of our proposed methodology in comparison to a number of the SOTA trackers

Fusion of infrared and visible images for remote detection of low-altitude slow-speed small targets.

Detection of the low-altitude and slow-speed small (LSS) targets is one of the most popular research topics in remote sensing. Despite of a few existing approaches, there is still an accuracy gap for satisfying the practical needs. As the LSS targets are too small to extract useful features, deep learning based algorithms can hardly be used. To this end, we propose in this article an effective strategy for determining the region of interest, using a multiscale layered image fusion method to extract the most representative information for LSS-target detection. In addition, an improved self-balanced sensitivity segment model is proposed to detect the fused LSS target, which can further improve both the detection accuracy and the computational efficiency. We conduct extensive ablation studies to validate the efficacy of the proposed LSS-target detection method on three public datasets and three self-collected datasets. The superior performance over the state of the arts has fully demonstrated the efficacy of the proposed approach

Therapeutic potential of dihydroartemisinin in mitigating radiation‐induced lung injury: Inhibition of ferroptosis through Nrf2/HO‐1 pathways in mice

Abstract Background Radiation‐induced lung injury (RILI) is a common consequence of thoracic radiation therapy that lacks effective preventative and treatment strategies. Dihydroartemisinin (DHA), a derivative of artemisinin, affects oxidative stress, immunomodulation, and inflammation. It is uncertain whether DHA reduces RILI. In this work, we investigated the specific mechanisms of action of DHA in RILI. Methods Twenty‐four C57BL/6J mice were randomly divided into four groups of six mice each: Control group, irradiation (IR) group, IR + DHA group, and IR + DHA + Brusatol group. The IR group received no interventions along with radiation treatment. Mice were killed 30 days after the irradiation. Morphologic and pathologic changes in lung tissue were observed with hematoxylin and eosin staining. Detection of hydroxyproline levels for assessing the extent of pulmonary fibrosis. Tumor necrosis factor α (TNF‐α), transforming growth factor‐β (TGF‐β), glutathione peroxidase (GPX4), Nuclear factor erythroid 2‐related factor 2 (Nrf2), and heme oxygenase‐1 (HO‐1) expression in lung tissues were detected. In addition, mitochondrial ultrastructural changes in lung tissues were also observed, and the glutathione (GSH) content in lung tissues was assessed. Results DHA attenuated radiation‐induced pathological lung injury and hydroxyproline levels. Additionally, it decreased TNF‐α and TGF‐β after irradiation. DHA may additionally stimulate the Nrf2/HO‐1 pathway. DHA upregulated GPX4 and GSH levels and inhibited cellular ferroptosis. Brusatol reversed the inhibitory effect of DHA on ferroptosis and its protective effect on RILI. Conclusion DHA modulated the Nrf2/HO‐1 pathway to prevent cellular ferroptosis, which reduced RILI. Therefore, DHA could be a potential drug for the treatment of RILI

HRMOT: two-step association based multi-object tracking in satellite videos enhanced by high-resolution feature fusion.

Multi-object tracking in satellite videos (SV-MOT) is one of the most challenging tasks in remote sensing, its difficulty mainly comes from the low spatial resolution, small target and extremely complex background. The widely studied multi-object tracking (MOT) approaches for general images can hardly be directly introduced to the remote sensing scenarios. The main reason can be attributed to: 1) the existing MOT approaches would cause a significant missed detection of the small targets in satellite videos; 2) it is difficult for the general MOT approaches to generate complete trajectories in complex satellite scenarios. To address these problems, a novel SV-MOT approach enhanced by high-resolution feature fusion (HRMOT) is proposed. It is comprised of a high-resolution detection network and a two-step based association strategy. In the high-resolution detection network, a high-resolution feature fusion module is designed to assist the detection by maintaining small object features in forward propagation. Based on high-quality detection, the densely-packed weak objects can be effectively tracked by associating almost every detection box instead of only the high score ones. Comprehensive experiment results on the representative satellite video datasets (VISO) demonstrate that the proposed HRMOT can achieve a competitive performance on the tracking accuracy and the frequency of ID conversion with the state-of-the-art (SOTA) methods

The Role and Mechanism of Borneol to Open the Blood-Brain Barrier

Background: The blood-brain barrier (BBB) is the greatest challenge in the treatment of intracranial malignant tumors. Objective: The aim of this study is to determine the role of borneol in opening the BBB and elucidate the underlying mechanisms. Materials and Methods: Twenty Sprague-Dawley (SD) rats were randomized into borneol group intragastrically administered with 10% borneol corn oil (2 mL/kg) and control group. After 30 minutes, 2% Evans blue (4 mL/kg) was injected. Thirty minutes later, brain tissue was analyzed using the Evans blue standard curve. Another 40 SD rats were randomized into high-, medium-, and low-dose borneol groups and a control group. Each rat in the experimental groups was intragastrically administered with 10% borneol corn oil (2 mL/kg, 1.25 mL/kg, and 0.5 mL/kg, respectively). The control group was injected with corn oil of 1.25 mL/kg. After 30 minutes, the rats were killed, and the brain tissues were collected. The expression of occludin, occludens-1, nitric oxide synthase, P-glycoprotein, and intercellular cell adhesion molecule-1 (ICAM-1) was detected by immunohistochemy. Results: The concentration of Evans blue in the borneol group was higher than in the control group ( P < .05). The mean density of ICAM-1 expression was higher in the experimental group than in the control group ( P < .05). In contrast, significant differences of positive area and total density of ICAM-1 were shown only between the high-dose group and the control group ( P < .05). Conclusion: Borneol can open the BBB, which might be related with the increased expression of ICAM-1

Spatio-Temporal Analysis of Cultivated Land from 2010 to 2020 in Long’an County, Karst Region, China

Spatio-temporal changes in cultivated land have a profound impact on food security and sustainable development. However, existing studies on spatio-temporal changes in cultivated land mostly focus on single factors, for instance quantity, quality and ecology, that cannot comprehensively reflect the changes in total production capacity and the sustainability of cultivated land. This study aims to construct a comprehensive analysis approach and to provide a reference basis for a comprehensive analysis of the extent of changes in overall cultivated land food-production capacity and the formulation of cultivated land conservation-related policies. This comprehensive analysis method constructed from three dimensions: quantity, production capacity and ecology, fully reflects the changes in the total amount, structure, rate of change, spatial distribution, quality, total production capacity and sustainability of cultivated land. The results from the application of this approach to Long’an County, Guangxi Province, China demonstrate that: (a) from 2010 to 2020, the total amount of cultivated land in Long’an County decreased sharply by 30.83%, accounted for mainly by the conversion into orchards, forest land and other garden land; (b) the quality of cultivated land improved by 2.71% on average, mostly in relation to natural factors; (c) the total food-production capacity of cultivated land decreased by 28.96% on average, mainly due to the decrease in the area of cultivated land; (d) both the ecological grade and the sustainability of cultivated land decreased slightly; (e) the barycenter of cultivated land migrated 3.3 km to the ecologically sensitive areas in the west, and the patch size of cultivated land decreased from an average of 2.60 hectares/pc in 2010 to that of 1.34 hectares/pc in 2020, suggesting increased fragmentation of cultivated land; and (f) the patch regularity of cultivated land decreased from 2.08 in 2010 to 1.76 in 2020, showing improved patch regularity and slightly better adaptability to mechanization. There were two main reasons for the lower, total food production capacity in Long’an County: first, the low comparative income of grain cultivation, because of which farmers spontaneously adjusted the agricultural cultivation structure to pursue high returns; and second, the lack of targeted government policies to protect cultivated land. In general, this comprehensive analysis method is applicable to other provinces in China or other regions abroad to provide a reference basis for a comprehensive understanding of changes in the food production capacity of cultivated land and the formulation of policies on cultivated land protection

Deregulation of Serum MicroRNA Expression Is Associated with Cigarette Smoking and Lung Cancer

Lung cancer is the leading cause of cancer-related death and cigarette smoking is the main risk factor for lung cancer. Circulating microRNAs (miRNAs) are considered potential biomarkers of various cancers, including lung cancer. However, it is unclear whether changes in circulating miRNAs are associated with smoking and smoking-related lung cancer. In this study, we determined the serum miRNA profiles of 10 nonsmokers, 10 smokers, and 10 lung-cancer patients with miRCURY LNA microRNA arrays. The differentially expressed miRNAs were then confirmed in a larger sample. We found that let-7i-3p and miR-154-5p were significantly downregulated in the sera of smokers and lung-cancer patients, so the serum levels of let-7i-3p and miR-154-5p are associated with smoking and smoking-related lung cancer. The areas under receiver operating characteristic curves for let-7i-3p and miR-154-5p were approximately 0.892 and 0.957, respectively. In conclusion, our results indicate that changes in serum miRNAs are associated with cigarette smoking and lung cancer and that let-7i-3p and miR-154-5p are potential biomarkers of smoking-related lung cancer

Deregulation of Serum MicroRNA Expression Is Associated with Cigarette Smoking and Lung Cancer

Lung cancer is the leading cause of cancer-related death and cigarette smoking is the main risk factor for lung cancer. Circulating microRNAs (miRNAs) are considered potential biomarkers of various cancers, including lung cancer. However, it is unclear whether changes in circulating miRNAs are associated with smoking and smoking-related lung cancer. In this study, we determined the serum miRNA profiles of 10 nonsmokers, 10 smokers, and 10 lung-cancer patients with miRCURY LNA microRNA arrays. The differentially expressed miRNAs were then confirmed in a larger sample. We found that let-7i-3p and miR-154-5p were significantly downregulated in the sera of smokers and lung-cancer patients, so the serum levels of let-7i-3p and miR-154-5p are associated with smoking and smoking-related lung cancer. The areas under receiver operating characteristic curves for let-7i-3p and miR-154-5p were approximately 0.892 and 0.957, respectively. In conclusion, our results indicate that changes in serum miRNAs are associated with cigarette smoking and lung cancer and that let-7i-3p and miR-154-5p are potential biomarkers of smoking-related lung cancer

LSM3, NDUFB3, and PTGS2 may be potential biomarkers for BRCA1-mutation positive breast cancer

Purpose: We aimed to find critical biomakers associated with BRCA1-mutation positive breast cancer