S2^2MAT: Simultaneous and Self-Reinforced Mapping and Tracking in Dynamic Urban Scenariosorcing Framework for Simultaneous Mapping and Tracking in Unbounded Urban Environments

Despite the increasing prevalence of robots in daily life, their navigation capabilities are still limited to environments with prior knowledge, such as a global map. To fully unlock the potential of robots, it is crucial to enable them to navigate in large-scale unknown and changing unstructured scenarios. This requires the robot to construct an accurate static map in real-time as it explores, while filtering out moving objects to ensure mapping accuracy and, if possible, achieving high-quality pedestrian tracking and collision avoidance. While existing methods can achieve individual goals of spatial mapping or dynamic object detection and tracking, there has been limited research on effectively integrating these two tasks, which are actually coupled and reciprocal. In this work, we propose a solution called S$^2$MAT (Simultaneous and Self-Reinforced Mapping and Tracking) that integrates a front-end dynamic object detection and tracking module with a back-end static mapping module. S$^2$MAT leverages the close and reciprocal interplay between these two modules to efficiently and effectively solve the open problem of simultaneous tracking and mapping in highly dynamic scenarios. We conducted extensive experiments using widely-used datasets and simulations, providing both qualitative and quantitative results to demonstrate S$^2$MAT's state-of-the-art performance in dynamic object detection, tracking, and high-quality static structure mapping. Additionally, we performed long-range robotic navigation in real-world urban scenarios spanning over 7 km, which included challenging obstacles like pedestrians and other traffic agents. The successful navigation provides a comprehensive test of S$^2$MAT's robustness, scalability, efficiency, quality, and its ability to benefit autonomous robots in wild scenarios without pre-built maps.Comment: homepage: https://sites.google.com/view/smat-na

Synergistic Effects of Apigenin and Paclitaxel on Apoptosis of Cancer Cells

BACKGROUND: It was well known that the clinical use of chemotherapeutic drugs is restricted by severe adverse reactions and drug resistances. Thus it is necessary to figure out a strategy to increase the specific anti-tumor efficiency of chemotherapeutic drugs. Apigenin, a kind of flavonoids, has been reported to possess anticancer activities with very low cytotoxicity to normal tissue. METHODOLOGY/PRINCIPAL FINDINGS: Our results from cell viability assay, western-blots and TdT-mediated dUTP-biotin nick end labeling (TUNEL) assay demonstrated the synergistic pro-apoptotic effects of a low dose of apigenin and paclitaxel in human cancer cell lines. To analyze the underlying mechanism, we examined reactive oxygen species (ROS) staining after cells were treated with a combination of apigenin and paclitaxel, or each of them alone. Data from flow-cytometry showed that superoxides but not reduction of peroxides accumulated in HeLa cells treated with apigenin or a combination of apigenin and paclitaxel. Apigenin and paclitaxel-induced HeLa cell apoptosis was related to the level of ROS in cells. We further evaluated activity and protein level of superoxide dismutase (SOD). Apigenin significantly inhibited SOD activity but did not alter the SOD protein level suggesting that apigenin promoted ROS accumulation through suppressing enzyme activity of SOD. Addition of Zn(2+), Cu(2+) and Mn(2+) to cell lysates inhibited apigenin's effects on SOD activity. At the same time, data from caspase-2 over-expression and knocked-down experiments demonstrated that caspase-2 participated in apigenin and paclitaxel-induced HeLa cell apoptosis. CONCLUSIONS/SIGNIFICANCE: Taken together, our study demonstrated that apigenin can sensitize cancer cells to paclitaxel induced apoptosis through suppressing SOD activity, which then led to accumulation of ROS and cleavage of caspase-2, suggesting that the combined use of apigenin and paclitaxel was an effective way to decrease the dose of paclitaxel taken

T Cell Exhaustion and CAR-T Immunotherapy in Hematological Malignancies

T cell exhaustion has been recognized to play an immunosuppressive role in malignant diseases. Persistent tumor antigen stimulation, the presence of inhibitory immune cells and cytokines in tumor microenvironment (TME), upregulated expression of inhibitory receptors, changes in T cell-related transcription factors, and metabolic factors can all result in T cell exhaustion. Strategies dedicated to preventing or reversing T cell exhaustion are required to reduce the morbidity from cancer and enhance the effectiveness of adoptive cellular immunotherapy. Here, we summarize the current findings of T cell exhaustion in hematological malignancies and chimeric antigen receptor T (CAR-T) immunotherapy, as well as the value of novel technologies, to inverse such dysfunction. Our emerging understanding of T cell exhaustion may be utilized to develop personalized strategies to restore antitumor immunity

A Novel Anti-Drift Visual Object Tracking Algorithm Based on Sparse Response and Adaptive Spatial-Temporal Context-Aware

Correlation filter (CF) based trackers have gained significant attention in the field of visual single-object tracking, owing to their favorable performance and high efficiency; however, existing trackers still suffer from model drift caused by boundary effects and filter degradation. In visual tracking, long-term occlusion and large appearance variations easily cause model degradation. To remedy these drawbacks, we propose a sparse adaptive spatial-temporal context-aware method that effectively avoids model drift. Specifically, a global context is explicitly incorporated into the correlation filter to mitigate boundary effects. Subsequently, an adaptive temporal regularization constraint is adopted in the filter training stage to avoid model degradation. Meanwhile, a sparse response constraint is introduced to reduce the risk of further model drift. Furthermore, we apply the alternating direction multiplier method (ADMM) to derive a closed-solution of the object function with a low computational cost. In addition, an updating scheme based on the APCE-pool and Peak-pool is proposed to reveal the tracking condition and ensure updates of the target’s appearance model with high-confidence. The Kalam filter is adopted to track the target when the appearance model is persistently unreliable and abnormality occurs. Finally, extensive experimental results on OTB-2013, OTB-2015 and VOT2018 datasets show that our proposed tracker performs favorably against several state-of-the-art trackers

A Novel Anti-Drift Visual Object Tracking Algorithm Based on Sparse Response and Adaptive Spatial-Temporal Context-Aware

Correlation filter (CF) based trackers have gained significant attention in the field of visual single-object tracking, owing to their favorable performance and high efficiency; however, existing trackers still suffer from model drift caused by boundary effects and filter degradation. In visual tracking, long-term occlusion and large appearance variations easily cause model degradation. To remedy these drawbacks, we propose a sparse adaptive spatial-temporal context-aware method that effectively avoids model drift. Specifically, a global context is explicitly incorporated into the correlation filter to mitigate boundary effects. Subsequently, an adaptive temporal regularization constraint is adopted in the filter training stage to avoid model degradation. Meanwhile, a sparse response constraint is introduced to reduce the risk of further model drift. Furthermore, we apply the alternating direction multiplier method (ADMM) to derive a closed-solution of the object function with a low computational cost. In addition, an updating scheme based on the APCE-pool and Peak-pool is proposed to reveal the tracking condition and ensure updates of the target’s appearance model with high-confidence. The Kalam filter is adopted to track the target when the appearance model is persistently unreliable and abnormality occurs. Finally, extensive experimental results on OTB-2013, OTB-2015 and VOT2018 datasets show that our proposed tracker performs favorably against several state-of-the-art trackers

A novel mutation in exon 11 of COMP gene in a Chinese family with pseudoachondroplasia

Pseudoachondroplasia (PSACH) is a relatively common skeletal dysplasia characterized by disproportionate short stature, joint laxity, early-onset osteoarthrosis, and dysplasia of the spine, epiphysis, and metaphysis. It is known as an autosomal dominant disease which results exclusively from mutations in the gene for Cartilage Oligomeric Matrix Protein (COMP). We have identified a five year old Chinese boy who was diagnosed as pseudoachondroplasia according to clinical manifestations and X-ray symptoms. His mother seems like another effected individual because of the apparent short stature. Genomic DNA was extracted from peripheral blood lymphocytes. DNA sequencing analysis of the COMP gene revealed a heterozygous mutation (c.1219 T > C,p.Cys407Arg) in the patient. His mother was also affected with the same genetic change. Mutations in COMP gene is proved to change the Cartilage Oligomeric Matrix Protein. This missense mutation (c.1219 T > C) has not been reported before and it is not belongs to polymorphism sites. Our results extend the spectrum of mutations in COMP gene leading to pseudoachondroplasia. Keywords: COMP, Novel mutation, Skeletal dysplasia, Pseudoachondroplasia, Therap

Review of CFD-DEM Modeling of Wet Fluidized Bed Granulation and Coating Processes

Wet fluidized bed granulation and coating processes have been widely used in the pharmaceutical and food industries. The complex gas–solid flow coupled with heat and mass transfer in such processes made it hard to form complete control over the apparatuses. To serve better design, scaling-up, and optimization of granulators and coaters, the underlying micro-scale mechanisms must be clarified. Computational fluid dynamics coupled with the discrete element method (CFD-DEM) provides a useful tool to study in-depth the gas-solid hydrodynamics of the granulation and coating processes. This review firstly introduced the fundamental theory of CFD-DEM from governing equations, force calculation, and coupling schemes. Then the application of CFD-DEM in simulating wet fluidized bed granulation and coating was presented. Specifically, the research focus and the role of CFD-DEM in resolving issues were discussed. Finally, the outlook on the development of CFD-DEM in the context of granulation and coating was given

Effects of Music and White Noise Exposure on the Gut Microbiota, Oxidative Stress, and Immune-Related Gene Expression of Mice

The microbiota in gastrointestinal tracts is recognized to play a pivotal role in the health of their hosts. Music and noise are prevalent environmental factors in human society and animal production and are reported to impact their welfare and physiological conditions; however, the information on the relationship between the microbiota, physiological status, and sound is limited. This study investigated the impact of music and white noise exposure in mice through 16s rRNA gene sequencing, enzyme assay, and qPCR. The results demonstrate that white noise induced oxidative stress in animals by decreasing serum SOD and GSH-PX activity while increasing LDH activity and MDA levels (p Bacteroidetes, Firmicutes, Verrucomicrobia, and Proteobacteria were dominant among all the groups. Furthermore, the proportion of Firmicutes increased in the music treatment group but decreased in the white noise treatment group compared to the control group. In conclusion, white noise has detrimental impacts on the gut microbiota, antioxidant activity, and immunity of mice, while music is potentially beneficial