Hyperspectral Attention Network for Object Tracking.

Hyperspectral video provides rich spatial and spectral information, which is crucial for object tracking in complex scenarios. Despite extensive research, existing methods often face an inherent trade-off between rich spectral information and redundant noisy information. This dilemma arises from the efficient utilization of hyperspectral image data channels. To alleviate this problem, this paper introduces a hierarchical spectral attention network for hyperspectral object tracking. We employ a spectral band attention mechanism with adaptive soft threshold to examine the correlations across spectral bands, which integrates the information available in various spectral bands and eliminates redundant information. Moreover, we integrate spectral attention into a hierarchical tracking network to improve the integration of spectral and spatial information. The experimental results on entire public hyperspectral competition dataset WHISPER2020 show the superior performance of our proposed method compared with that of several related methods in visual effects and objective evaluation.

Synergistic Catalysis of Water-Soluble Exogenous Catalysts and Reservoir Minerals during the Aquathermolysis of Heavy Oil.

Oil serves as the essential fuel and economic foundation of contemporary industry. However, the use of traditional light crude oil has exceeded its supply, making it challenging to meet the energy needs of humanity. Consequently, the extraction of heavy oil has become crucial in addressing this demand. This research focuses on the synthesis of several water-soluble catalysts that can work along with reservoir minerals to catalyze the hydrothermal cracking process of heavy oil. The goal is to effectively reduce the viscosity of heavy oil and lower the cost of its extraction. Based on the experimental findings, it was observed that when oil sample 1 underwent hydrothermal cracking at a temperature of 180 °C for a duration of 4 h, the amount of water added and catalyst used were 30% and 0.2% of the oil sample dosage, respectively. It was further discovered that the synthesized Mn(II)C was able to reduce the viscosity of oil sample 1 by 50.38%. The investigation revealed that the combination of Mn(II)C + K exhibited a significant synergistic catalytic impact on reducing viscosity. Initially, the viscosity reduction rate was 50.38%, which climbed to 61.02%. Subsequently, when catalyzed by the hydrogen supply agent isopropanol, the rate of viscosity reduction rose further to 91.22%. Several methods, such as freezing point analysis, thermogravimetric analysis, DSC analysis, component analysis, gas chromatography, wax crystal morphology analysis, and GC-MS analysis, were conducted on aqueous organic matter derived from heavy oil after undergoing different reaction systems. These analyses confirmed that the viscosity of the heavy oil was decreased. By studying the reaction mechanism of the model compound and analyzing the aqueous phase, the reaction largely involves depolymerization between macromolecules, breakdown of heteroatom chains, hydrogenation, ring opening, and other related consequences. These actions diminish the strength of the van der Waals force and hydrogen bond in the recombinant interval, impede the creation of a grid-like structure in heavy oil, and efficiently decrease its viscosity.

Liposome-Encapsulated Zoledronate Favors Tumor Vascular Normalization and Enhances Anticancer Efficacy of Cisplatin.

The aim of this study was to examine the effectiveness of alanine-proline-arginine-proline-glycine (APRPG) peptide-conjugated PEGylated cationic liposomes-encapsulated zoledronic acid (ZOL) (APRPG-PEG-ZOL-CLPs) in achieving vascular normalization. Cisplatin (diamminedichloroplatinum, DDP) was used to improve anticancer efficacy. The present study showed that APRPG-PEG-ZOL-CLPs increased anticancer efficacy, which was regarded as vascular normalization. Our results demonstrated that the viability, migration, and tube formation of human umbilical vein endothelial cells (HUVECs) were evidently repressed by APRPG-PEG-ZOL-CLPs. Moreover, APRPG-PEG-ZOL-CLPs could decrease vessel density, as well as hypoxia-inducible factor 1α (HIF-1α), and increase thrombospondin 1 (TSP-1) expression of tumors. Therefore, the anticancer efficacy of APRPG-PEG-ZOL-CLPs combined with DDP was superior to that of PEG-ZOL-CLP or ZOL treatment combined with DDP schemes, as demonstrated by the obviously evident reduction in tumor volume. These results indicated that APRPG-PEG-ZOL-CLPs were most effective in normalizing tumor vasculature to elevate the therapeutic effect of antitumor drugs.

Clinical Value of Metagenomic Next-Generation Sequencing Using Spinal Tissue in the Rapid Diagnosis of Spinal Tuberculosis.

Purpose: To evaluate the accuracy of metagenomic next-generation sequencing (mNGS) for rapid diagnosis of spinal tuberculosis using spinal tissue specimens. Methods: Medical data regarding suspected spinal tuberculosis were retrospectively analyzed. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the curve (AUC) of mNGS were calculated to determine its diagnostic efficacy, and these values were compared with culture and composite reference standard (CRS). Results: Two hundred and three cases of spinal tuberculosis were included for analysis. The sensitivity, specificity, PPV, NPV, and AUC of mNGS compared with culture were all very good. When CRS was used for the comparison, the sensitivity of mNGS and culture were 71.2% and 73.0%; the specificity and PPV were 100% in all cases; the NPV were 74.2% and 75.4%; the AUCs were all 0.86. The sensitivity and NPV of culture were slightly higher than that of mNGS; however, the diagnostic efficacy of mNGS and culture was consistent (P > 0.05). Conclusion: Spinal tissue specimens for mNGS testing had very good accuracy for diagnosing spinal tuberculosis.

A Variable Radius Side Window Direct SLAM Method Based on Semantic Information.

Simultaneous Localization and Mapping (SLAM) is a challenging and key issue in the mobile robotic fields. In terms of the visual SLAM problem, the direct methods are more suitable for more expansive scenes with many repetitive features or less texture in contrast with the feature-based methods. However, the robustness of the direct methods is weaker than that of the feature-based methods. To deal with this problem, an improved direct sparse odometry with loop closure (LDSO) is proposed, where the performance of the SLAM system under the influence of different imaging disturbances of the camera is focused on. In the proposed method, a method based on the side window strategy is proposed for preprocessing the input images with a multilayer stacked pixel blender. Then, a variable radius side window strategy based on semantic information is proposed to reduce the weight of selected points on semistatic objects, which can reduce the computation and improve the accuracy of the SLAM system based on the direct method. Various experiments are conducted on the KITTI dataset and TUM RGB-D dataset to test the performance of the proposed method under different camera imaging disturbances. The quantitative and qualitative evaluations show that the proposed method has better robustness than the state-of-the-art direct methods in the literature. Finally, a real-world experiment is conducted, and the results prove the effectiveness of the proposed method.

Chloride intracellular channel 5 modulates adipocyte accumulation in skeletal muscle by inhibiting preadipocyte differentiation.

Intramuscular fat, the total lipid deposited within skeletal muscle, has been regarded as a potential factor responsible for meat quality in animal production and insulin resistance in humans. The objective of present study was to identify candidate genes which control intramuscular fat accumulation through using animal models. PIC pigs (lean-type) and Rongchang pigs (obese-type) were used. By scanning the mRNA samples of longissimus dorsi muscle with Affymetrix Gene-Chip microarray technology, sus scrofa chloride intracellular channel 5 (CLIC5) was isolated, and its mRNA abundance and protein expression level were reversely related with the intramuscular fat content of pigs. Furthermore, over-expression of CLIC5 dramatically increased the proliferation of 3T3-L1 preadipocytes, while inhibited adipocytic differentiation accompanied by the down-regulation of c/EBPalpha, LPL, and PPARgamma protein. Our results suggest that CLIC5 might be a crucial regulator of adipose accumulation in skeletal muscle of pigs.

An Improved Deep Residual Network-Based Semantic Simultaneous Localization and Mapping Method for Monocular Vision Robot.

The robot simultaneous localization and mapping (SLAM) is a very important and useful technology in the robotic field. However, the environmental map constructed by the traditional visual SLAM method contains little semantic information, which cannot satisfy the needs of complex applications. The semantic map can deal with this problem efficiently, which has become a research hot spot. This paper proposed an improved deep residual network- (ResNet-) based semantic SLAM method for monocular vision robots. In the proposed approach, an improved image matching algorithm based on feature points is presented, to enhance the anti-interference ability of the algorithm. Then, the robust feature point extraction method is adopted in the front-end module of the SLAM system, which can effectively reduce the probability of camera tracking loss. In addition, the improved key frame insertion method is introduced in the visual SLAM system to enhance the stability of the system during the turning and moving of the robot. Furthermore, an improved ResNet model is proposed to extract the semantic information of the environment to complete the construction of the semantic map of the environment. Finally, various experiments are conducted and the results show that the proposed method is effective.

Combination of metronomic administration and target delivery strategies to improve the anti-angiogenic and anti-tumor effects of triptolide.

The metronomic administration of a low-dose cytotoxic agent with no prolonged drug-free breaks is an anti-angiogenic cancer treatment method. The use of nano-formulations in this manner enhances anti-tumor efficacy and reduces toxicity by inhibiting angiogenic activity, reduces adverse effects, and changes the biodistribution of TP in the body, steering TP away from potentially endangering healthy tissues. The present study uses liposomes and Asn-Gly-Arg (NGR) peptide conjugated aminopeptidase N(APN)-targeted liposomes for triptolide (TP), as a model for the investigation of targeted metronomic administration and subsequent effects on the toxicity profile and efficacy of the chemotherapeutic agent. Metronomic NGR-PEG-TP-LPs have been found to have enhanced anti-tumor activity, a phenomenon that is attributed to an increase in angiogenic inhibition properties. In vitro experiments demonstrate that the viability, migration, and tube formation of human umbilical vein endothelial cells (HUVECs) are obviously suppressed in comparison with that of other treatment groups. In vivo experiments also demonstrate that the anti-tumor efficacy of targeted metronomic administration is superior to that of liposome-administered treatments given at maximum tolerated dose (MTD) schemes, as is evidenced by markedly decreased tumor volume, vessel density, and the volume of circulating endothelial progenitor cells (CEPCs) in serum. Moreover, we observed that the metronomic administration of NGR-PEG-TP-LPs could elevate thrombospondin-1 (TSP-1) expression in tumors, a finding that is consistent with the promotion of TSP-1 secretion specifically from HUVECs. Additionally, metronomic NGR-PEG-TP-LPs have minimal drug-associated toxicity (weight loss, hepatotoxicity and nephrotoxicity in mice). Our research demonstrates the significance of targeted metronomic administration using liposomes for anti-angiogenic cancer therapy.

An Improved DSA-Based Approach for Multi-AUV Cooperative Search.

Multi-AUV cooperative target search problem in unknown 3D underwater environment is not only a research hot spot but also a challenging task. To complete this task, each autonomous underwater vehicle (AUV) needs to move quickly without collision and cooperate with other AUVs to find the target. In this paper, an improved dolphin swarm algorithm- (DSA-) based approach is proposed, and the search problem is divided into three stages, namely, random cruise, dynamic alliance, and team search. In the proposed approach, the Levy flight method is used to provide a random walk for AUV to detect the target information in the random cruise stage. Then the self-organizing map (SOM) neural network is used to build dynamic alliances in real time. Finally, an improved DSA algorithm is presented to realize the team search. Furthermore, some simulations are conducted, and the results show that the proposed approach is capable of guiding multi-AUVs to achieve the target search task in unknown 3D underwater environment efficiently.

A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles.

Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.

A novel underwater dam crack detection and classification approach based on sonar images.

Underwater dam crack detection and classification based on sonar images is a challenging task because underwater environments are complex and because cracks are quite random and diverse in nature. Furthermore, obtainable sonar images are of low resolution. To address these problems, a novel underwater dam crack detection and classification approach based on sonar imagery is proposed. First, the sonar images are divided into image blocks. Second, a clustering analysis of a 3-D feature space is used to obtain the crack fragments. Third, the crack fragments are connected using an improved tensor voting method. Fourth, a minimum spanning tree is used to obtain the crack curve. Finally, an improved evidence theory combined with fuzzy rule reasoning is proposed to classify the cracks. Experimental results show that the proposed approach is able to detect underwater dam cracks and classify them accurately and effectively under complex underwater environments.

Anti-angiogenic and anti-tumor effects of metronomic use of novel liposomal zoledronic acid depletes tumor-associated macrophages in triple negative breast cancer.

Zoledronic acid (ZOL) has been used as an adjuvant therapy for breast cancer. It is suggested that ZOL might be associated with inhibition of macrophages, which in turn reduces tumor growth, metastasis and tumor angiogenesis. Moreover, metronomic therapy can inhibit tumor angiogenesis and tumor immune cells. Previously we developed ZOL based cationic liposomes that allowed a higher intratumor delivery of drug compared with free ZOL in vivo. Therefore, in this study, Asn-Gly-Arg (NGR) and PEG2000 were used as ligands to modify the surface of liposomes (NGR-PEG-LP-ZOL) in metronomic therapy to clear the tumor-associated macrophages (TAMs) and inhibit the formation of tumor angiogenesis, achieving the purpose of anti-tumor growth. Our data showed that NGR-PEG-LP-ZOL metronomic therapy has the strongest inhibitory effect on tumor growth. Further, NGR-PEG-LP-ZOL metronomic therapy could significantly impair TAMs by inhibiting the expression of CD206 antibody in tumor tissues, decreasing the expression of cytokine related gene expression of TAMs, as well as reducing the percentage of TAMs in tumor tissues. In addition, NGR-PEG-LP-ZOL metronomic therapy could significantly inhibit the expression of tumor neovascular specific antibody CD31 and reduce the microvessel density. In conclusion, our study demonstrated that NGR-PEG-LP-ZOL metronomic therapy could impair TAMs by inhibiting tumor angiogenesis and enhance the antitumor effect of ZOL.

Bioinspired Intelligent Algorithm and Its Applications for Mobile Robot Control: A Survey.

Bioinspired intelligent algorithm (BIA) is a kind of intelligent computing method, which is with a more lifelike biological working mechanism than other types. BIAs have made significant progress in both understanding of the neuroscience and biological systems and applying to various fields. Mobile robot control is one of the main application fields of BIAs which has attracted more and more attention, because mobile robots can be used widely and general artificial intelligent algorithms meet a development bottleneck in this field, such as complex computing and the dependence on high-precision sensors. This paper presents a survey of recent research in BIAs, which focuses on the research in the realization of various BIAs based on different working mechanisms and the applications for mobile robot control, to help in understanding BIAs comprehensively and clearly. The survey has four primary parts: a classification of BIAs from the biomimetic mechanism, a summary of several typical BIAs from different levels, an overview of current applications of BIAs in mobile robot control, and a description of some possible future directions for research.

The traditional Chinese medicine formulation Ruanjian Sanjie Decoction regulates the tumor matrix and improves the anti-tumor efficacy of TP-PEG-LPs

The Ruanjian Sanjie Decoction (RSD) is a traditional Chinese medicine (TCM) formulation consisting of Spica Prunellae, Pseudobulbus Cremastrae Seu Pleiones, Concha Ostreae and Semen Coicis, and widely used as an adjuvant in anti-cancer therapy. The aim of this study was to determine the effects of RSD on the extracellular matrix (ECM) of tumors, and on the efficacy of anti-cancer nano-formulations in a tumor-bearing mouse model. The mice were treated with triptolide encapsulated in PEG-modified liposomes (TP-PEG-LPs), either alone or in combination with RSD. The combination treatment significantly retarded tumor growth relative to the untreated controls, indicating the potent adjuvant effect of RSD in targeted anti-cancer therapy. In addition, RSD also reduced the amount of total collagen and collagen I and increased that of collagen III in the tumor ECM, along with decreasing the expression of the pro-angiogenic VEGF. Finally, even high doses of RSD did not significantly affect the liver and kidney function or body weight, indicating low toxicity.

Bioinspired neural network for real-time cooperative hunting by multirobots in unknown environments.

Multiple robot cooperation is a challenging and critical issue in robotics. To conduct the cooperative hunting by multirobots in unknown and dynamic environments, the robots not only need to take into account basic problems (such as searching, path planning, and collision avoidance), but also need to cooperate in order to pursue and catch the evaders efficiently. In this paper, a novel approach based on a bioinspired neural network is proposed for the real-time cooperative hunting by multirobots, where the locations of evaders and the environment are unknown and changing. The bioinspired neural network is used for cooperative pursuing by the multirobot team. Some other algorithms are used to enable the robots to catch the evaders efficiently, such as the dynamic alliance and formation construction algorithm. In the proposed approach, the pursuing alliances can dynamically change and the robot motion can be adjusted in real-time to pursue the evader cooperatively, to guarantee that all the evaders can be caught efficiently. The proposed approach can deal with various situations such as when some robots break down, the environment has different boundary shapes, or the obstacles are linked with different shapes. The simulation results show that the proposed approach is capable of guiding the robots to achieve the hunting of multiple evaders in real-time efficiently.

Dietary supplementation with zinc oxide stimulates ghrelin secretion from the stomach of young pigs.

Dietary supplementation with zinc is known to enhance food intake and growth in young children. However, the underlying mechanisms remain largely unknown. Ghrelin, a peptide derived mainly from stomach, plays an important role in food-intake regulation. The present study was conducted with the piglet model to test the hypothesis that zinc may increase gastric ghrelin secretion. In Experiment 1 (Exp. 1) , thirty-six 28-day-old weaned pigs were assigned to two groups (18 pigs/group), receiving four-week supplementation of 0 or 2000 mg/kg Zn (as ZnO) to the basal diet containing 100 mg/kg Zn. In Experiment (Exp. 2), sixteen 28-day-old piglets were assigned to the same treatments (n=8/group) as in Exp. 1, except that they were pair-fed an equal amount of diet. At the end of the experiments, blood, stomach and duodenum samples were obtained for biochemical analysis, including assays of ghrelin protein and insulin-like growth factor-I (IGF-I) in plasma, as well as quantification of ghrelin and IGF-I mRNA levels in the duodenum and gastric mucosa. Further, gastric mucosal cells from unsupplemented piglets were cultured with 0-0.5 mM ZnO for 2-24 h for assays of ghrelin production and gene expression. Dietary Zn supplementation increased plasma concentrations of ghrelin, IGF-I and cholecystokinin; IGF-I gene expression in the duodenum as well as food intake and piglet growth (Exp. 1). The effects of ZnO on plasma levels of ghrelin, intestinal IGF-I expression and piglet growth were independent of food intake. Addition of ZnO to culture medium enhanced ghrelin production from gastric mucosal cells without affecting ghrelin mRNA levels. Collectively, our results indicate that ZnO stimulates ghrelin secretion from the stomach at the post-transcriptional level. This novel finding aids in elucidating the cellular and molecular mechanism for a role of zinc in promoting food intake and growth of young children.

CLA differently regulates adipogenesis in stromal vascular cells from porcine subcutaneous adipose and skeletal muscle.

Conjugated linoleic acid (CLA), a mixture of isomers of linoleic acid, has previously been shown to be able to decrease porcine subcutaneous (SC) adipose tissue levels while increasing the count of intramuscular (IM) adipose tissue in vivo. However, the underlying mechanisms through which it acts are poorly understood. The objective of this study was to investigate the different effects of CLA on adipogenesis in cultured SC adipose tissue and IM stromal vascular cells obtained from neonatal pigs. As shown here, trans-10, cis-12 CLA decreased the expression of adipocyte-specific genes as well as adipose precursor cell numbers and the accumulation of lipid in cultured SC adipose tissue stromal vascular cells. However, the cis-9, trans-11 CLA did not alter adipogenesis in SC cultures. On the other hand, both CLA isomers increased the expression of adipocyte-specific genes in IM cultures, together with the increasing accumulation of lipid and Oil Red O-stained cells. Collectively, these data show that CLA decreases SC adipose tissue but increases IM adipose tissue by different regulation of adipocyte-specific gene expression. These results suggest that adipogenesis in IM adipocytes differs from that in SC adipocytes.

Coal-derived boron and phosphorus co-doped activated carbon with expanded interlayer space for high performance sodium ion capacitor anode.

Aiming at the key problem of Na+ insertion difficulty and low charge transfer efficiency of activated carbon materials. It is an effective strategy to increase the lattice spacing and defect concentration by doping to reduce the ion diffusion resistance and improve the kinetics. Hence, anthracitic coal is used to prepare activated carbon (AC) and B,P-doped activated carbon (B,P-AC) as the cathode and anode materials for high-performance all-carbon SICs, respectively. AC cathode material has high specific surface area and reasonable micropore structure, which shows excellent capacitance performance. B,P-AC anode material has the advantages of extremely high specific surface area (1856.1 m2/g), expanded interlayer spacing (0.40 nm) and uniform distribution of B and P heteroatoms. Hence, B,P-AC anode achieves a highly reversible Na+ storage capacity of 243 mAh/g at a current density of 0.05 A/g. Density functional theory (DFT) calculations further verify that B,P-AC has stronger Na+ storage performance. The final assembled B,P-AC//AC SIC offers a high energy density of 109.78 Wh kg-1 and a high-power density of 10.03 kW kg-1. The high-performance coal-derived activated carbon of this work provides a variety of options for industrial production of electrode materials for sodium ion capacitors.