PLOD3 facilitated T cell activation in the colorectal tumor microenvironment and liver metastasis by the TNF-α/ NF-κB pathway.

BACKGROUND: Colorectal cancer (CRC) has been the third most prevalent cancer worldwide. Liver metastasis is the critical factor for the poor prognosis of CRC. Here, we investigated the expression and role of PLOD3 in CRC. METHODS: Different liver metastasis models were established by injecting PLOD3 stable knockdown or overexpression CT26 or MC38 mouse CRC cells into the spleen of mice to verify the tumorigenicity and metastasis ability in vivo. RESULTS: We identified PLOD3 is significantly overexpressed in liver metastasis samples of CRC. High expression of PLOD3 was significantly associated with poor survival of CRC patients. The knockdown of PLOD3 exhibited remarkable inhibition of proliferation, migration, and invasion in CRC cells, while the opposite results could be found in different PLOD3-overexpressed CRC cells. Stable knockdown of PLOD3 also significantly inhibited liver metastasis of CRC cells in different xenografts models, while stable overexpression of PLOD3 promotes liver metastasis and tumor progression. Further studies showed that PLOD3 facilitated the T cell activation in the tumor microenvironment and affected the TNF-α/ NF-κB pathway. CONCLUSIONS: This study revealed the essential biological functions of PLOD3 in colon cancer progression and metastasis, suggesting that PLOD3 is a promising translational medicine target and bioengineering targeting PLOD3 overcomes CRC liver metastasis.

KBMeasure: small sample in-situ damage automatic measurement method based on the combination of keypoints detection and binocular 3D reconstruction for aero-engine blades.

Size is one of the important bases for the level assessment of aero-engine blade damage and the disposal method selection for damaged blades. Therefore, research on in-situ damage measurement of aero-engine blades is conducted in this paper. We break the inherent pipeline of "3D reconstruction and manual annotation of keypoints" in traditional damage measurement methods, and propose an in-situ damage automatic measurement method (KBMeasure) based on the combination of damage keypoints intelligent detection and binocular 3D reconstruction. KBMeasure replaces the manual annotation of damage keypoints, improves the damage measurement efficiency, and reduces the dependence on professional inspectors. The proposed method also overcomes the problem of high computational cost and low efficiency caused by redundant 3D reconstruction of the entire damaged area. For the characteristics of large changes in damage scale, low image resolution, the requirement of high-precision keypoints positioning, limited annotated data, and lightweight deployment in aero-enginge blade damage measurement task, a novel blade damage keypoints detection model (DKeyDet) with top-down framework is designed by introducing coordinate classification, semi-supervised learning, and knowledge distillation. Then, intersecting optical axis binocular model is used to estimate the spatial coordinates of the detected keypoints and compute the size of damage. The keypoints detection average precision (AP) and average recall (AR) of our method are 87.6 and 91.3, and the damage measurement size error (SE) is 0.08, which is superior to existing methods. This research provides a new theoretical support for in-situ damage automatic measurement for aero-engine in service, and provides what we believe is a novel idea for damage measurement of industrial components in other fields.

Isorhamnetin Regulates Programmed Death Ligand-1 Expression by Suppressing the EGFR-STAT3 Signaling Pathway in Canine Mammary Tumors.

Programmed death ligand-1 (PD-L1) is highly expressed in a variety of cancer cells and suggests a poorer prognosis for patients. The natural compound isorhamnetin (ISO) shows promise in treating cancers and causing damage to canine mammary tumor (CMT) cells. We investigated the mechanism of ISO in reducing PD-L1 expression in CMT cells. Clustered, regularly interspaced short palindromic repeat-associated protein 9 (CRISPR/Cas9) was used to mediate CD274 knockout in U27 cells. Then, monoclonal cells were screened and cultured. Nucleotide sequencing and expression of PD-L1 were detected. Additionally, we examined cell migration, invasion, and damage. Immunofluorescent staining of PD-L1 was examined in U27 cells. The signaling pathways were measured by Western blotting. Murine xenotransplantation models and murine immunocompetent allograft mammary tumor models were established to evaluate the effect of ISO therapy. Expression of Ki-67, caspase3, and PD-L1 were analyzed by immunohistochemistry. A pull-down assay was used to explore which proteins could bind to ISO. Canine EGFR protein was purified and used to detect whether it directly binds to ISO using a surface plasmon resonance assay. ISO inhibited the EGFR-STAT3-PD-L1 signaling pathway and blocked cancer growth, significantly increasing the survival rate of healthy cells. The cell membrane receptor EGFR was identified as a direct target of ISO. ISO could be exploited as an antineoplastic treatment of CMT by targeting EGFR to suppress PD-L1 expression.

Identification and validation of a novel necroptosis-related molecular signature to evaluate prognosis and immune features in breast cancer.

Necroptosis has been shown to play an important role in the development of tumors. However, the characteristics of the necroptosis-related subtypes and the associated immune cell infiltration in the tumor microenvironment (TME) of breast cancer (BRCA) remain unclear. In this study, we identified three clusters related to necroptosis using the expression patterns of necroptosis-relevant genes (NRGs), and found that these three clusters had different clinicopathological features, prognosis and immune cell infiltration in the TME. Cluster 2 was characterized by less infiltration of immune cells in the TME and was associated with a worse prognosis. Then, a necroptosis risk score (NRS) composed of 14 NRGs was constructed using the least absolute shrinkage and selection operator regression (LASSO) Cox regression method. Based on NRS, all BRCA patients in the TCGA datasets were classified into a low-risk group and a high-risk group. Patients in the low-risk group were characterized by longer overall survival (OS), lower mutation burden, and higher infiltration level of immune cells in the TME. Moreover, the NRS was significantly associated with chemotherapeutic drug sensitivity. Finally, the knockdown of VDAC1 reduced the proliferation and migration of BRCA cells, and promoted cell death induced by necroptosis inducer. This study identified a novel necroptosis-related subtype of BRCA, and a comprehensive analysis of NRGs in BRCA revealed its potential roles in prognosis, clinicopathological features, TME, chemotherapy, tumor proliferation, and tumor necroptosis. These results may improve our understanding of NRGs in BRCA and provide a reference for developing individualized therapeutic strategies.

Application of Levosimendan in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection Patients with Myocardial Injury.

Objective: This study aims to investigate the effectiveness of levosimendan in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection complicated by cardiac insufficiency and myocardial injury. Methods: A total of 22 patients with SARS-CoV-2 infection and myocardial injury, admitted to the Cardiology Department of our hospital between December 2022 and February 2023, are randomly divided into two groups: a dobutamine general treatment group and a levosimendan observation treatment group. The treatment outcomes of the two groups are compared and analyzed. Results: The overall improvement rate in the general treatment group is 80%, while the levosimendan treatment group shows a 100% improvement rate. There is a statistically significant difference between the two groups (P < .05). Post-treatment, the left ventricular ejection fraction for the general treatment group and the levosimendan treatment group are (48 ± 7)% and (54 ± 6)%, respectively. Additionally, the left ventricular end-diastolic diameter is (55.0 ± 3.0) mm in the general treatment group and (51 ± 5.0) mm in the levosimendan group, with a statistically significant difference (P < .05). After active treatment, the plasma levels of B-type natriuretic peptide (Brain Natriuretic Peptide, NT-proBNP) are significantly lower in the levosimendan treatment group than in the general treatment group (P < .05). Moreover, the plasma levels of interleukin-6 (IL-6) and C-reactive protein (CRP) in the levosimendan group decrease slightly faster than those in the general treatment group, with a statistically significant difference (P < .05). The length of hospital stay in the levosimendan group is (12 ± 3) days, significantly lower than the general treatment group (16 ± 5) days, with a statistically different result (P < .05). Conclusions: Levosimendan demonstrates significant efficacy in patients with novel coronavirus infection complicated by myocardial injury, resulting in improved clinical symptoms, enhanced cardiac function, shorter hospital stays, early discharge, and cost savings.

Clinical Prognostic Factors and Integrated Multi-Omics Studies Identify Potential Novel Therapeutic Targets for Pediatric Desmoid Tumor.

BACKGROUND: Desmoid tumor (DT), also known as desmoid-type fibromatosis (DTF) or aggressive fibromatosis (AF) is a rare mesenchymal tumor affecting both children and adults. It is non-metastasis but infiltrative, growing with a high recurrence rate to even cause serious health problems. This study investigates the biology of desmoid tumors through integrated multi-omics studies. METHODS: We systematically investigated the clinical data of 98 extra-abdominal cases in our pediatric institute and identified some critical clinical prognostic factors. Moreover, our integrated multi-omics studies (Whole Exome Sequencing, RNA sequencing, and untargeted metabolomics profiling) in the paired PDT tumor/matched normal tissues identified more novel mutations, and potential prognostic markers and therapeutic targets for PDTs. RESULTS: The top mutation genes, such as CTNNB1 (p.T41A and p.S45F) and MUC4 (p.T3775T, p.S3450S, etc.), were observed with a mutation in more than 40% of PDT patients. We also identified a panel of genes that are classed as the FDA-approved drug targets or Wnt/ß-catenin signaling pathway-related genes. The integrated analysis identified pathways and key genes/metabolites that may be important for developing potential treatment of PDTs. We also successfully established six primary PDT cell lines for future studies. CONCLUSIONS: These studies may promote the development of novel drugs and therapeutic strategies for PDTs.

PKCι Is a Promising Prognosis Biomarker and Therapeutic Target for Pancreatic Cancer.

BACKGROUND: As the highest prevalent pancreatic cancer, pancreatic ductal adenocarcinoma (PDAC) ranks the 7th lethal malignancy worldwide. The late diagnosis, chemotherapeutic resistance, and high associated mortality make PDAC a dilemma facing the oncologists. Protein kinase C (PKC) enzymes have been shown to be important in different cancer progression. METHODS: To understand the pattern of PKC enzymes in PDAC, we examined all PKC family member genes expression in PDAC and matched normal tissues. The critical role of PKCι was further investigated in different PDAC cells using cellular and molecular technology. RESULTS: We found that PRKCI (PKCι) was the most significantly overexpressed PKCs in pancreatic cancer. However, little is known about its role and regulation of oncogenic signaling pathways in pancreatic cancer. In this study, we confirmed the overexpression of PKCι in PDAC, and this high expression was associated with poor prognosis of patients. We proved that knockdown of PKCι by small interfering RNA or shRNA significantly inhibited pancreatic cancer cell growth and migration or invasion. Conversely, PKCι overexpression promoted pancreatic cancer cell growth and migration. Moreover, bioinformatical and technical studies informed the participation of PKCι in regression of apoptosis in PDAC cells, which may be related to the regulation of both PI3K/AKT and Wnt/ß-catenin pathways. CONCLUSIONS: Therefore, our results are adding more insight into the importance of PKCι in pancreatic cancer. PKCι induces pancreatic cancer progression through activation of PI3K/AKT and Wnt/ß-catenin signaling pathways, which may provide a promising therapeutic target for pancreatic cancer.

KCNN4-mediated Ca2+/MET/AKT axis is promising for targeted therapy of pancreatic ductal adenocarcinoma.

As a member of the potassium calcium-activated channel subfamily, increasing evidence suggests that KCNN4 was associated with malignancies. However, the roles and regulatory mechanisms of KCNN4 in PDAC have been little explored. In this work, we demonstrated that the level of KCNN4 in PDAC was abnormally elevated, and the overexpression of KCNN4 was induced by transcription factor AP-1. KCNN4 was closely correlated with unfavorable clinicopathologic characteristics and poor survival. Functionally, we found that overexpression of KCNN4 promoted PDAC cell proliferation, migration and invasion. Conversely, the knockdown of KCNN4 attenuated the growth and motility of PDAC cells. In addition to these, knockdown of KCNN4 promoted PDAC cell apoptosis and led to cell cycle arrest in the S phase. In mechanistic investigations, RNA-sequence revealed that the MET-mediated AKT axis was essential for KCNN4, encouraging PDAC cell proliferation and migration. Collectively, these findings reveal a function of KCNN4 in PDAC and suggest it's an attractive therapeutic target and tumor marker. Our studies underscore a better understanding of the biological mechanism of KCNN4 in PDAC and suggest novel strategies for cancer therapy.

Centromere protein F is identified as a novel therapeutic target by genomics profile and contributing to the progression of pancreatic cancer.

Pancreatic cancer (PC) is the most severe and serious deadliest cancer type worldwide. Centromeric proteins (CENPs) family are involved in centromere formation and kinetochore organization during mitosis and play an important role in cancers. Here, we analyzed all CENPs in a panel of PC tissues and non-tumor tissues by genomics profile. We identified that CENPF is significantly upregulated in PC and correlated with poor prognosis of patients. Furthermore, silencing CENPF significantly inhibited PC cell proliferation, migration and epithelial-mesenchymal transition (EMT), and caused cell cycle arrest at the G2/M phase, meanwhile, in vivo growth of pancreatic cells. Moreover, the TNF pathway and longevity regulating pathways are two potential pathways, which were regulated by CENPF. These findings investigated the clinical and functional contribution of CENPF as a novel biomarker for PC.

VMFNet: visual-microwave dual-modality real-time target detection model for detecting damage to curved radar absorbing materials.

Damage to radar absorbing materials (RAMs) reduces the stealth capabilities and battlefield survivability of the equipment. Research on RAM damage detection technology is key to outfield equipment maintenance. In this paper, an intelligent RAM damage detection method based on visual and microwave modalities is proposed. A compressed sensing planar-scanning microwave imaging method based on a range migration algorithm (RMA) imaging operator and fast Gaussian gridding nonuniform fast Fourier transform (FGG-NUFFT) is proposed, achieving high imaging quality and speed. A dual-modality, curved RAM dataset (DCR dataset) is constructed, composed of visual images and microwave images showing two kinds of damage: round shedding and strip cracks. A new dual-modality target detection model, the visual-microwave fusion network (VMFNet), is designed to detect RAM damage. Its mean average precision (mAP) reaches 81.87%, and its inference speed reaches 35.91 fps. A visual network (VisNet) and microwave network (MicNet) are designed as the backbone of VMFNet for extracting the visual and microwave features of RAMs. A path aggregation network (PANet) unit is designed to fuse the multiscale features of the two modalities, resulting in good retention of shallow-level features and high detection accuracy. The head contains different receptive fields and outputs three scales of detection results, effectively detecting damage of different sizes.

Intelligent recognition of composite material damage based on deep learning and infrared testing.

Composite materials are commonly used in aircraft, and the integrity of these materials affects both flight and safety performance. Damage detection technology involving infrared nondestructive testing has played an important role in damage detection in aircraft composite materials. Traditional manual detection methods are inefficient, and the use of intelligent detection methods can effectively improve detection efficiency. Due to the diverse types of damage that can occur in composite materials, this damage is difficult to distinguish solely from infrared images. The introduction of infrared signals, which is temporal signals, provides the possibility of judging the type of damage. In this paper, a 1D-YOLOv4 network is established. The network is based on the YOLOv4 network and adds a changing neck and a 1D-CNN for improvement. Testing shows that the algorithm can identify infrared images and infrared signals in composite materials. Its recognition accuracy is 98.3%, with an AP of 91.9%, and a kappa of 0.997. Comparing the network in this paper with networks such as YOLOv3, YOLOv4 and YOLOv4+Neck, the results show that the proposed network is more effective. At the same time, the detection effects of the original data, the fitted data, the first derivative data and the second derivative data are studied, and the detection effect of the first derivative data has the best outcome.

S100A16 promotes metastasis and progression of pancreatic cancer through FGF19-mediated AKT and ERK1/2 pathways.

The S100 protein family genes play a crucial role in multiple stages of tumorigenesis and progression. Most of S100 genes are located at chromosome locus 1q21, which is a region frequently rearranged in cancers. Here, we examined the expression of the S100 family genes in paired pancreatic ductal adenocarcinoma (PDAC) samples and further validated the expression of S100A16 by immunohistochemistry staining. We found that S100A16 is significantly upregulated in clinical PDAC samples. However, its roles in PDAC are still unclear. We next demonstrated that S100A16 promotes PDAC cell proliferation, migration, invasion, and metastasis both in vitro and in vivo. Knockdown of S100A16 induces PDAC cell cycle arrest in the G2/M phase and apoptosis. Furthermore, we also demonstrated that S100A16 promotes PDAC cell proliferation, migration, and invasion via AKT and ERK1/2 signaling in a fibroblast growth factor 19 (FGF19)-dependent manner. Taken together, our results reveal that S100A16 is overexpressed in PDAC and promotes PDAC progression through FGF19-mediated AKT and ERK1/2 signaling, suggesting that S100A16 may be a promising therapeutic target for PDAC. S100A16 was upregulated in PDAC and associated with prognosis of PDAC patients. S100A16 regulates apoptosis and the cell cycle of pancreatic cancer cells. S100A16 promotes the progression of pancreatic cancer by AKT-ERK1/2 signaling. S100A16 may be a promising therapeutic target for PDAC.

Infrared and ultrasonic intelligent damage recognition of composite materials based on deep learning.

With the large-scale application of composite materials in military aircraft, various composite material detection technologies with infrared nondestructive and ultrasonic nondestructive testing as the core have played an important role in detecting composite material component damage in military aircraft. At present, the damage of composite materials is mostly recognized manually, which is time-consuming, laborious, and inefficient. It can effectively improve detection efficiency and accuracy by using intelligent detection methods to detect and recognize damage. Moreover, the effect of infrared detection is significantly reduced with increasing detection depth, while ultrasonic detection has shallow-blind areas. A cascade fusion R-CNN network is proposed in order to comprehensively identify composite material damage. This network realizes the intelligent fusion recognition of infrared and ultrasonic damage images of composite materials. The network is based on a cascade R-CNN network, using fusion modules and BiFPN for improvement. For the infrared image and ultrasonic C-scan image data set established in this paper, the algorithm can identify the type and location of damage detected by infrared and ultrasonic testing. Its recognition accuracy is 99.3% and mean average precision (mAP) is 90.4%. In the detection process, the characteristics of infrared and ultrasonic images are used to realize the recognition of damage depth. Compared to SSD, YOLOv4, faster R-CNN and cascade R-CNN, the network proposed in this paper is better and more effective.

The androgen receptor expression and association with patient's survival in different cancers.

To understand the androgen receptor (AR) in different human malignancies, we conducted a pan-cancer analysis of AR in different tumor tissues and association with patient survival and obtained AR expression data from The Cancer Genome Atlas. Pan-Cancer Analysis of AR indicated that 12 tumor types had decreased AR expression in the tumor, while glioblastoma multiforme has overexpressed AR. The survival analysis showed that high AR mRNA is associated with poor survival of stomach adenocarcinoma and low-grade glioma, but better survival of adrenocortical carcinoma, kidney renal clear cell carcinoma, acute myeloid leukemia, liver hepatocellular carcinoma, ovarian serous cystadenocarcinoma, and skin cutaneous melanoma based on AR mRNA, protein or AR-score. AR was associated with different clinical characteristics and AR correlated genes enriched in cancer-related pathways. These data indicate that AR signaling may be strongly associated with some cancer development and patients' survival, which is promising for potential treatment using antiandrogen therapies.

Genome-Wide Analysis of LncRNA in Bovine Mammary Epithelial Cell Injuries Induced by Escherichia Coli and Staphylococcus Aureus.

Escherichia coli and Staphylococcus aureus are two common pathogenic microorganisms that cause mastitis in dairy cows. They can cause clinical mastitis and subclinical mastitis. In recent studies, lncRNAs have been found to play an important role in the immune responses triggered by microbial inducers. However, the actions of lncRNAs in bovine mastitis remain unclear. The purpose of this study was to investigate the effects of bovine mammary epithelial cell injuries induced by treatment with E. coli and S. aureus, and to explore the lncRNA profile on cell injuries. The lncRNA transcriptome analysis showed a total of 2597 lncRNAs. There were 2234 lncRNAs differentially expressed in the E. coli group and 2334 in the S. aureus group. Moreover, we found that the E. coli and S. aureus groups of maternal genes targeted signaling pathways with similar functions according to KEGG and GO analyses. Two lncRNA-miRNA-mRNA interaction networks were constructed in order to predict the potential molecular mechanisms of regulation in the cell injuries. We believe that this is the first report demonstrating the dysregulation of lncRNAs in cells upon E. coli and S. aureus infections, suggesting that they have the potential to become important diagnostic markers and to provide novel insights into controlling and preventing mastitis.

Transcriptome Profiling of m6A mRNA Modification in Bovine Mammary Epithelial Cells Treated with Escherichia coli.

Mastitis is a common disease in dairy cows that is mostly caused by E. coli, and it brings massive losses to the dairy industry. N6-Methyladenosine (m6A), a methylation at the N6 position of RNA adenine, is a type of modification strongly associated with many diseases. However, the role of m6A in mastitis has not been investigated. In this study, we used MeRIP-seq to sequence the RNA of bovine mammary epithelial cells treated with inactivated E. coli for 24 h. In this in vitro infection model, there were 16,691 m6A peaks within 7066 mRNA transcripts in the Con group and 10,029 peaks within 4891 transcripts in the E. coli group. Compared with the Con group, 474 mRNAs were hypermethylated and 2101 mRNAs were hypomethylated in the E. coli group. Biological function analyses revealed differential m6A-modified genes mainly enriched in the MAPK, NF-κB, and TGF-ß signaling pathways. In order to explore the relationship between m6A and mRNA expression, combined MeRIP-seq and mRNA-seq analyses revealed 212 genes with concomitant changes in the mRNA expression and m6A modification. This study is the first to present a map of RNA m6A modification in mastitis treated with E. coli, providing a basis for future research.

Sufficiency for inducible Caspase-9 safety switch in human pluripotent stem cells and disease cells.

Embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) have promising potential for opening new avenues in regenerative medicine. However, since the tumorigenic potential of undifferentiated pluripotent stem cells (PSCs) is a major safety concern for clinical transplantation, inducible Caspase-9 (iC9) is under consideration for use as a fail-safe system. Here, we used targeted gene editing to introduce the iC9 system into human iPSCs, and then interrogated the efficiency of inducible apoptosis with normal iPSCs as well as diseased iPSCs derived from patients with acute myeloid leukemia (AML-iPSCs). The iC9 system induced quick and efficient apoptosis to iPSCs in vitro. More importantly, complete eradication of malignant cells without AML recurrence was shown in disease mouse models by using AML-iPSCs. In parallel, it shed light on several limitations of the iC9 system usage. Our results suggest that careful use of the iC9 system will serve as an important countermeasure against posttransplantation adverse events in stem cell transplantation therapies.

[Study on Form of Ar/Air ICP and A Microwave Diagnostics Based on the Hß Spectrum Broadening].

The ICP in closed quartz chamber is an effective solution to local stealth of aircraft. The attenuation of the electromagnetic wave is strongly affected by distribution of electron density in incidence direction. In this paper, an experiment that the planar ICP discharged in all-quartz chamber (30.8 cm×30.8 cm×5.8 cm) was conducted. The E-H mode transition of Ar/Air ICP was observed, and the width and the proportion of ICP area versus the RF power were measured. Such physical phenomena were explained rationally by ICP-source theoretical model. A new microwave diagnostics is presented based on the Hß spectrum broadening and the characteristics of planar-coil ICP. It is used to diagnose the spatial electron density distribution of Ar/Air in incidence direction. The parameters of electron density distribution function in the incident direction are separately solved by the fitting results of the Hß stack broadening and microwave interferometer. And the curves of electron density distribution versus RF power are obtained. We obtain a stable ring plasma source with electron density varying from 0.5×1011～3.2×1011 cm-3. The experiment demonstrates that electron density is prominently affected by the RF power and gas species. The peak value of electron density is positioned near the center of ICP. It is shown that the electron density of Ar ICP is higher than the air, but the area of air ICP is larger through comparing the curves of Ar/Air electron density.

[Experimental study on closed plasma discharging under low pressure and spectroscopic diagnosis].

Closed plasma can overcome difficulties of maintaining plasma and excessive energy consumption in open environment. For plasma stealth technology, a closed plasma generator was designed. Using microsecond pulse generator and argon as working gas, discharge experiments were carried out under low pressure environment. The emission spectrum of Ar at different position in discharge chamber was measured. By using collisional-radiative modal (CRM), the distribution of plasma parameters was studied. At a given electron temperature and density with specified discharge parameters, corresponding population distribution could be obtained by CRM. By comparing the line ratio of argon 2p levels acquired from CRM with the line ratio from spectrum measured, the plasma parameters were confirmed after obtaining the minimum difference value. Using the line ratio of argon 2p9 to 2p1 from CRM while the range of electron density was 1-5 eV, the calculating error was analyzed. The results reveal that, the electron density of the closed plasma reaches a magnitude of 10(11) cm(-3) and shows a gradient distribution with small variational amplitude, and the distribution is beneficial to the application of plasma stealth.

BPMTrack: Multi-Object Tracking With Detection Box Application Pattern Mining.

The key to multi-object tracking is its stability and the retention of identity information. A common problem with most detection-based approaches is trusting and using all the detector outputs for the association. However, some settings of detectors can affect stable long-range tracking. Based on the principle of reducing the association noise in the detection processing step, we propose a new framework, the Box application Pattern Mining Tracker (BPMTrack), to address this issue. Specifically, we worked on three main aspects: output threshold, association strategy, and motion model. Due to the problem of inconsistency between classification scores and localization accuracy, we propose the Box Quality Estimation Network (BQENet) to predict the localization quality scores of all detections in the current frame, reserving high-quality boxes for the tracker. In addition, based on observations of intensive scenarios, we propose a simple and effective data association method, the Non-Maximum Suppression Integration (NMSI) matching strategy. It recovers the Non-Maximum Suppression (NMS) detection, inputs them into BQENet, and then performs hierarchical matching with reasonable control of box priority to alleviate the problem of absent objects caused by occlusion. Finally, we propose an improved Measurement Correct and Noise Scale (MCNS) Kalman algorithm to improve the prediction accuracy of object positions and, thus, the association quality. We performed an extensive ablation evaluation of the proposed framework to prove its effectiveness. Moreover, the three tracking benchmarks show our method's accuracy and long-distance performance.