Collaborative Planning for Catching and Transporting Objects in Unstructured Environments

Multi-robot teams have attracted attention from industry and academia for their ability to perform collaborative tasks in unstructured environments, such as wilderness rescue and collaborative transportation.In this paper, we propose a trajectory planning method for a non-holonomic robotic team with collaboration in unstructured environments.For the adaptive state collaboration of a robot team to catch and transport targets to be rescued using a net, we model the process of catching the falling target with a net in a continuous and differentiable form.This enables the robot team to fully exploit the kinematic potential, thereby adaptively catching the target in an appropriate state.Furthermore, the size safety and topological safety of the net, resulting from the collaborative support of the robots, are guaranteed through geometric constraints.We integrate our algorithm on a car-like robot team and test it in simulations and real-world experiments to validate our performance.Our method is compared to state-of-the-art multi-vehicle trajectory planning methods, demonstrating significant performance in efficiency and trajectory quality

Expression of the phosphorylated MEK5 protein is associated with TNM staging of colorectal cancer

<p>Abstract</p> <p>Background</p> <p>Activation of MEK5 in many cancers is associated with carcinogenesis through aberrant cell proliferation. In this study, we determined the level of phosphorylated MEK5 (pMEK5) expression in human colorectal cancer (CRC) tissues and correlated it with clinicopathologic data.</p> <p>Methods</p> <p>pMEK5 expression was examined by immunohistochemistry in a tissue microarray (TMA) containing 335 clinicopathologic characterized CRC cases and 80 cases of nontumor colorectal tissues. pMEK5 expression of 19 cases of primary CRC lesions and paired with normal mucosa was examined by Western blotting. The relationship between pMEK5 expression in CRC and clinicopathologic parameters, and the association of pMEK5 expression with CRC survival were analyzed respectively.</p> <p>Results</p> <p>pMEK5 expression was significantly higher in CRC tissues (185 out of 335, 55.2%) than in normal tissues (6 out of 80, 7.5%; <it>P </it>< 0.001). Western blotting demonstrated that pMEK5 expression was upregulated in 12 of 19 CRC tissues (62.1%) compared to the corresponding adjacent nontumor colorectal tissues. Overexpression of pMEK5 in CRC tissues was significantly correlated to the depth of invasion (<it>P </it>= 0.001), lymph node metastasis (<it>P </it>< 0.001), distant metastasis (<it>P </it>< 0.001) and high preoperative CEA level (<it>P </it>< 0.001). Consistently, the pMEK5 level in CRC tissues was increased following stage progression of the disease (<it>P </it>< 0.001). Analysis of the survival curves showed a significantly worse 5-year disease-free (<it>P </it>= 0.002) and 5-year overall survival rate (<it>P </it>< 0.001) for patients whose tumors overexpressed pMEK5. However, in multivariate analysis, pMEK5 was not an independent prognostic factor for CRC (DFS: <it>P </it>= 0.139; OS: <it>P </it>= 0.071).</p> <p>Conclusions</p> <p>pMEK5 expression is correlated with the staging of CRC and its expression might be helpful to the TNM staging system of CRC.</p

HIV-1 subtypes and drug-resistance mutation sites in HIV/AIDS patients with antiretroviral-therapy failure

ObjectiveTo analyze the characteristics of HIV-1 subtypes and drug-resistance mutation sites among HIV-infected patients who received high-efficiency antiretroviral therapy but failed.MethodsA total of 130 plasma samples were collected from the patients who received antiviral treatment for 6 months in Taizhou City of Zhejiang Province in 2021 but failed the treatment and the viral load was ≥1 000 copies·mL-1. Nucleic acid in the samples was extracted， and the pol gene was amplified by nested reverse transcription PCR. After next-generation sequencing， online tools were used to compare and analyze the subtypes and drug-resistant mutation sites.ResultsA total of 110 samples were successfully sequenced. The main HIV-1 subtype was CRF01_AE， accounting for 42.72% （47 cases）， followed by CRF07_BC， 35.45% （39 cases）； CRF08_BC， 10.00% （11 cases）； CRF85_BC ， 8.18% （9）； and a small number of B subtype， 1.81% （2 cases） and C subtype， 1.81% （2 cases）. The online tool comparison showed that there were 67 cases with mutations of drug-resistance sites and 61 cases with drug-resistance. The mutation sites were mainly M184V， K103N， K65R and V181C， and the mutation rates were 20.00% （22 cases）， 10.91% （12 cases）， 8.18% （9 cases） and 8.18% （9 cases）， respectively. These mutation sites caused different degrees of resistance to nucleoside reverse transcriptase inhibitors （NRTI）， non- nucleoside reverse transcriptase inhibitors （NNRTI） and protease inhibitors （PI）， including 45 cases of NRTI， 61 cases of NNRTI and 2 cases of PI resistance.ConclusionThe HIV infected people who fail the treatment in Taizhou are mainly with the subtypes CRF01_AE and CRF07_BC. The rate of drug-resistance mutation is at a moderate level， mainly due to the mutation of NRTI and NNRTI drug-resistance sites， and a small number of PI drug-resistance sites. Therefore， the antiviral treatment plan for HIV infected people should be reasonably adjusted， and the detection of drug-resistance mutation sites should be strengthened to avoid the generation of transmissible drug-resistance strains

Gene expression and promoter methylation of porcine uncoupling protein 3 gene

Objective Uncoupling protein 3 gene (UCP3) is a candidate gene associated with the meat quality of pigs. The aim of this study was to explore the regulation mechanism of UCP3 expression and provide a theoretical basis for the research of the function of porcine UCP3 gene in meat quality. Methods Bisulfite sequencing polymerase chain reaction (PCR) and quantitative real-time PCR (Q-PCR) were used to analyze the methylation of UCP3 5′-flanking region and UCP3 mRNA expression in the adipose tissue or skeletal muscle of three pig breeds at different ages (1, 90, 210-day-old Putian Black pig; 90-day-old Duroc; and 90-day-old Dupu). Results Results showed that two cytosine-guanine dinucleotide (CpG) islands are present in the promoter region of porcine UCP3 gene. The second CpG island located in the core promoter region contained 9 CpG sites. The methylation level of CpG island 2 was lower in the adipose tissue and skeletal muscle of 90-day-old Putian Black pigs compared with 1-day-old and 210-day-old Putian Black pigs, and the difference also existed in the skeletal muscle among the three 90-day-old pig breeds. Furthermore, the obvious changing difference of UCP3 mRNA expression was observed in the skeletal muscle of different groups. However, the difference of methylation status and expression level of UCP3 gene was not significant in the adipose tissue. Conclusion Our data indicate that UCP3 mRNA expression level was associated with the methylation status of UCP3 promoter in the skeletal muscle of pigs

The construction of personalized virtual landslide disaster environments based on knowledge graphs and deep neural networks

Virtual Landslide Disaster environments are important for multilevel simulation, analysis and decision-making about Landslide Disasters. However, in the existing related studies, complex disaster scene objects and relationships are not deeply analyzed, and the scene contents are fixed, which is not conducive to meeting multilevel visualization task requirements for diverse users. To resolve the above issues, a construction method for Personalized Virtual Landslide Disaster Environments Based on Knowledge Graphs and Deep Neural networks is proposed in this paper. The characteristics of relationships among users, scenes and data were first discussed in detail; then, a knowledge graph of virtual Landslide Disaster environments was established to clarify the complex relationships among disaster scene objects, and a Deep Neural network was introduced to mine the user history information and the relationships among object entities in the knowledge graph. Therefore, a personalized Landslide Disaster scene data recommendation mechanism was proposed. Finally, a prototype system was developed, and an experimental analysis was conducted. The experimental results show that the method can be used to recommend intelligently appropriate disaster information and scene data to diverse users. The recommendation accuracy stabilizes above 80% – a level able to effectively support The Construction of Personalized Virtual Landslide Disaster environments

Adaptive Construction of the Virtual Debris Flow Disaster Environments Driven by Multilevel Visualization Task

The construction of a virtual debris flow disaster environment is of great significance in debris flow disaster prevention, risk assessment, accurate simulation, and disaster emergency response. However, existing research on virtual disaster environments mainly focus on the specific visualization task requirements of single-type users, and the multilevel visualization task requirements of multitype users are generally not met. In this paper, an adaptive construction method for virtual debris flow disaster environments driven by multilevel visualization task is proposed based on the characteristics of users with different professional knowledge backgrounds and requirements in disaster emergency response scenarios. The on-demand construction of virtual debris flow disaster environments and the corresponding diverse organization and dynamic scheduling technologies are discussed in detail. Finally, the Qipan Gully debris flow disaster is selected for experimental analysis, and a prototype system is developed. The experimental results show that the proposed method can adaptively construct virtual debris flow disaster environments according to the multilevel visualization task requirements of multitype users in debris flow disaster emergency response scenarios. This approach can provide efficient rendering of disaster scenes and appropriate disaster information to multitype users who are involved in debris flow disaster emergency response scenarios