A Vision-Based Underwater Formation Control System Design and Implementation on Small Underwater Spherical Robots

The ocean is a significant strategic resource, and the insufficient development and use of the ocean, as well as the increase in attention to the ocean, have led to the development of underwater robot technology. The need for in-depth marine exploration and the limitations of one underwater robot has sparked research on the underwater multi-robot system. In the underwater environment, weak communication is caused by the shielding effect of the seawater medium, which makes multi-robot systems difficult to form. Hence, we combine the robot’s vision system with the leader-follower structure to form a vision-based underwater formation method, in which the visual solution serves as the control system’s feedback. By using three small underwater robot platforms, the proposed method is proved to be effective and practicable through underwater formation experiments. Furthermore, the coordination period and error of the control system are analyzed

A Vision-Based Underwater Formation Control System Design and Implementation on Small Underwater Spherical Robots

The ocean is a significant strategic resource, and the insufficient development and use of the ocean, as well as the increase in attention to the ocean, have led to the development of underwater robot technology. The need for in-depth marine exploration and the limitations of one underwater robot has sparked research on the underwater multi-robot system. In the underwater environment, weak communication is caused by the shielding effect of the seawater medium, which makes multi-robot systems difficult to form. Hence, we combine the robot’s vision system with the leader-follower structure to form a vision-based underwater formation method, in which the visual solution serves as the control system’s feedback. By using three small underwater robot platforms, the proposed method is proved to be effective and practicable through underwater formation experiments. Furthermore, the coordination period and error of the control system are analyzed

A Laboratory Experimental Study: An FBG-PVC Tube Integrated Device for Monitoring the Slip Surface of Landslides

A new detection device was designed by integrating fiber Bragg grating (FBG) and polyvinyl chloride (PVC) tube in order to monitor the slip surface of a landslide. Using this new FBG-based device, a corresponding slope model with a pre-set slip surface was designed, and seven tests with different soil properties were carried out in laboratory conditions. The FBG sensing fibers were fixed on the PVC tube to measure strain distributions of PVC tube at different elevation. Test results indicated that the PVC tube could keep deformation compatible with soil mass. The new device was able to monitor slip surface location before sliding occurrence, and the location of monitored slip surface was about 1–2 cm above the pre-set slip surface, which basically agreed with presupposition results. The monitoring results are expected to be used to pre-estimate landslide volume and provide a beneficial option for evaluating the potential impact of landslides on shipping safety in the Three Gorges area

A Heat and Mass Transfer Model of Peanut Convective Drying Based on a Two-Component Structure

In order to optimize the convective drying process parameters of peanuts and to provide a theoretical basis for the scientific use of energy in the drying process, this study took single-particle peanuts as the research object and analyzed the heat and mass transfer process during convective drying. In addition, a 3D two-component moisture heat transfer model for peanuts was constructed based on the mass balance and heat balance theorem. Moreover, the changes in the internal temperature and concentration fields of peanut pods during the whole drying process were investigated by simulations using COMSOL Multiphysics. The model was validated by thin-layer drying experiments, compared with the one-component model, and combined with low-field NMR technology to further analyze the internal moisture distribution state of peanut kernel drying process. The results show that both models can effectively simulate the peanut thin-layer drying process, and consistency is found between the experimental and simulated values, with the maximum errors of 10.25%, 9.10%, and 7.60% between the simulated moisture content and the experimental values for the two-component model, peanut shell, and peanut kernel models, respectively. Free water and part of the weakly bound water was the main water lost by peanuts during the drying process, the change in oil content was small, and the bound water content was basically unchanged. The results of the study provide a theoretical basis to accurately predict the moisture content within different components of peanuts and reveal the mechanism of moisture and heat migration during the drying process of peanut pods

Prediction of Cholecystokinin-Secretory Peptides Using Bidirectional Long Short-term Memory Model Based on Transfer Learning and Hierarchical Attention Network Mechanism

Cholecystokinin (CCK) can make the human body feel full and has neurotrophic and anti-inflammatory effects. It is beneficial in treating obesity, Parkinson’s disease, pancreatic cancer, and cholangiocarcinoma. Traditional biological experiments are costly and time-consuming when it comes to finding and identifying novel CCK-secretory peptides, and there is an urgent need to develop a new computational method to predict new CCK-secretory peptides. This study combines the transfer learning method with the SMILES enumeration data augmentation strategy to solve the data scarcity problem. It establishes a fusion model of the hierarchical attention network (HAN) and bidirectional long short-term memory (BiLSTM), which fully extracts peptide chain features to predict CCK-secretory peptides efficiently. The average accuracy of the proposed method in this study is 95.99%, with an AUC of 98.07%. The experimental results show that the proposed method is significantly superior to other comparative methods in accuracy and robustness. Therefore, this method is expected to be applied to the preliminary screening of CCK-secretory peptides

Immune checkpoint inhibitor‐related molecular markers predict prognosis in extrahepatic cholangiocarcinoma

Abstract Background Therapeutic approaches for extrahepatic cholangiocarcinoma (EHCC) are limited, due to insufficient understanding to biomarkers related to prognosis and drug response. Here, we comprehensively assess the molecular characterization of EHCC with clinical implications. Methods Whole‐exome sequencing (WES) on 37 tissue samples of EHCC were performed to evaluate genomic alterations, tumor mutational burden (TMB) and microsatellite instability (MSI). Results Mutation of KRAS (16%) was significantly correlated to poor OS. ERBB2 mutation was associated with improved OS. ERBB2, KRAS, and ARID1A were three potentially actionable targets. TMB ≥10 mutations per megabase was detected in 13 (35.1%) cases. Six patients (16.2%) with MSIsensor scores ≥10 were found. In multivariate Cox analysis, patients with MSIsensor sore exceed a certain threshold (MSIsensor score ≥0.36, value approximately above the 20th percentile as thresholds) showed a significant association with the improved OS (HR = 0.16; 95% CI: 0.056–0.46, p < 0.001), as well as patients with both TMB ≥3.47 mutations per megabase (value approximately above the 20th percentile) and MSIsensor score ≥0.36. Conclusions TMB and MSI are potential biomarkers associated with better prognosis for EHCC patients. Furthermore, our study highlights important genetic alteration and potential therapeutic targets in EHCC

Growth, Enzymatic, and Transcriptomic Analysis of <i>xyr1</i> Deletion Reveals a Major Regulator of Plant Biomass-Degrading Enzymes in <i>Trichoderma harzianum</i>

The regulation of plant biomass degradation by fungi is critical to the carbon cycle, and applications in bioproducts and biocontrol. Trichoderma harzianum is an important plant biomass degrader, enzyme producer, and biocontrol agent, but few putative major transcriptional regulators have been deleted in this species. The T. harzianum ortholog of the transcriptional activator XYR1/XlnR/XLR-1 was deleted, and the mutant strains were analyzed through growth profiling, enzymatic activities, and transcriptomics on cellulose. From plate cultures, the Δxyr1 mutant had reduced growth on D-xylose, xylan, and cellulose, and from shake-flask cultures with cellulose, the Δxyr1 mutant had ~90% lower β-glucosidase activity, and no detectable β-xylosidase or cellulase activity. The comparison of the transcriptomes from 18 h shake-flask cultures on D-fructose, without a carbon source, and cellulose, showed major effects of XYR1 deletion whereby the Δxyr1 mutant on cellulose was transcriptionally most similar to the cultures without a carbon source. The cellulose induced 43 plant biomass-degrading CAZymes including xylanases as well as cellulases, and most of these had massively lower expression in the Δxyr1 mutant. The expression of a subset of carbon catabolic enzymes, other transcription factors, and sugar transporters was also lower in the Δxyr1 mutant on cellulose. In summary, T. harzianum XYR1 is the master regulator of cellulases and xylanases, as well as regulating carbon catabolic enzymes