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AbstractDrawing on the driving mechanism of biological muscles and combining the nonlinear hyperelastic characteristics of silicone rubber, a multi-degree-of-freedom pneumatic soft bionic actuator is designed, which can be used as the executing mechanism for soft robots and robotic arms. Using response surface analysis and numerical simulation algorithms, the optimal combination of structural dimensions parameters is determined with the maximum bending and torsion angles output by the actuator as the optimization objectives. Based on the idea of flexible mechanism Piecewise Constant Curvature (PCC) modeling, the kinematics equation of the actuator is derived. Analyze the equivalent motion structure of the actuator and establish a dynamic model of the actuator based on the Lagrange method. The physical model of the actuator is manufactured using rapid prototyping technology. Finally, experimental testing and analysis are conducted on the physical model to obtain the motion and dynamic characteristics curves and empirical formulas of the actuator, which are compared with theoretical and simulation results to verify that the pneumatic soft bionic actuator is feasible and effective. The above research methods, processes, and results can provide reference and inspiration for the research and implementation of pneumatic and hydraulic soft robots and gripping actuators for soft robotic arms. [ABSTRACT FROM AUTHOR]

To achieve the accuracy and anti-interference of the motion control of the soft robot more effectively, the motion control strategy of the pneumatic soft bionic robot based on the improved Central Pattern Generator (CPG) is proposed. According to the structure and motion characteristics of the robot, a two-layer neural network topology model for the robot is constructed by coupling 22 Hopfield neuron nonlinear oscillators. Then, based on the Adaptive Neuro-Fuzzy Inference System (ANFIS), the membership functions are offline learned and trained to construct the CPG-ANFIS-PID motion control strategy for the robot. Through simulation research on the impact of CPG-ANFIS-PID input parameters on the swimming performance of the robot, it is verified that the control strategy can quickly respond to input parameter changes between different swimming modes, and stably output smooth and continuous dynamic position signals, which has certain advantages. Then, the motion performance of the robot prototype is analyzed experimentally and compared with the simulation results. The results show that the CPG-ANFIS-PID motion control strategy can output coupled waveform signals stably, and control the executing mechanisms of the pneumatic soft bionic robot to achieve biological rhythms motion propulsion waveforms, confirming that the control strategy has accuracy and anti-interference characteristics, and enable the robot have certain maneuverability, flexibility, and environmental adaptability. The significance of this work lies in establishing a CPG-ANFIS-PID control strategy applicable to pneumatic soft bionic robot and proposing a rhythmic motion control method applicable to pneumatic soft bionic robot. [ABSTRACT FROM AUTHOR]

Identifying drug-target interactions (DTIs) holds significant importance in drug discovery and development, playing a crucial role in various areas such as virtual screening, drug repurposing and identification of potential drug side effects. However, existing methods commonly exploit only a single type of feature from drugs and targets, suffering from miscellaneous challenges such as high sparsity and cold-start problems. We propose a novel framework called MSI-DTI (M ulti- S ource I nformation-based D rug- T arget I nteraction Prediction) to enhance prediction performance, which obtains feature representations from different views by integrating biometric features and knowledge graph representations from multi-source information. Our approach involves constructing a D rug- T arget K nowledge G raph (DTKG), obtaining multiple feature representations from diverse information sources for SMILES sequences and amino acid sequences, incorporating network features from DTKG and performing an effective multi-source information fusion. Subsequently, we employ a multi-head self-attention mechanism coupled with residual connections to capture higher-order interaction information between sparse features while preserving lower-order information. Experimental results on DTKG and two benchmark datasets demonstrate that our MSI-DTI outperforms several state-of-the-art DTIs prediction methods, yielding more accurate and robust predictions. The source codes and datasets are publicly accessible at https://github.com/KEAML-JLU/MSI-DTI. [ABSTRACT FROM AUTHOR]

Two silicon carbide (SiC) lightweight off-axis aspheric mirrors were fabricated by using robot polishing technology. One is a primary mirror with dimension 380mm×328mm, the other is a tertiary mirror with dimension 294mm×238mm. The robot polishing technology is the combination of CCOS technology and a 6-axises industrial robot. The setup of robot polishing system is discussed, and the mirror aspheric grinding, surface polishing and figuring process are reported in this paper. The final surface shape error of primary mirror is 11.4nm RMS, and the tertiary is 12.1nm RMS. The capability of off-axis aspheric mirror fabricating on robot polishing system is verified.

The soft robot is a kind of continuum robot, which is mainly made of soft elastic material or malleable material. It can be continuously deformed in a limited space, and can obtain energy in large bending or high curvature distortion. It has obvious advantages such as high security of human-computer interaction, strong adaptability of unstructured environment, high driving efficiency, low maintenance cost, etc. It has wide application prospects in the fields of industrial production, defense military, medical rehabilitation, exploration, and so on. From the perspective of the bionic mechanism, this paper introduces the soft robots corresponding to insect crawling, snake crawling, fish swimming, elephant trunk, arm, etc. According to different driving modes, the soft robots can be classified into pneumatic-hydraulic driven, intelligent material driven, chemical reaction driven, and so on. The mechanical modeling, control strategy, material, and manufacturing methods of soft robot are summarized, and the application fields of soft robot are introduced. This paper analyzes the main challenges faced by the research on the key technologies of soft robots, summarizes and analyzes them, and puts forward the prospects for the future research of soft robots. The development trend of the future is to develop the soft robot with the characteristics of micro-scale, rigid-flexible coupling, variable stiffness, multi-functional, high integration, and intelligence of driving sensor control. [ABSTRACT FROM AUTHOR]

A variety of factors have been linked to the occurrence of anterior cruciate ligament injury (ACLI), including sex, familial factors, and genetic variations. To find the genetic loci associated with ACLI and explore the genetic mechanism of ACLI in order to provide a genetic basis for the diagnosis, prognosis, and treatment of patients with ACLI. Cross-sectional study. Hospital. Data from 101 Chinese Yunnan Han patients with ACLI and 110 Yunnan Han individuals without ACLI (control group) were collected. The single nucleotide polymorphisms of COL1A1 rs1800012, COL5A1 rs12722 and rs13946, COL12A1 rs970547 and rs240736 and the rs1800787, rs1800788, rs1800789, rs1800790, rs1800791, and rs2227389 in the β-fibrinogen (β-fib) promoter region were analyzed using restriction fragment length polymorphism and DNA sequencing detection, and their genetic associations with ACLI were assessed. Single nucleotide polymorphisms of COL1A1 rs1800012, COL5A1 rs12722 and rs13946, and the rs1800789 and rs1800791 in the β-fib promoter region showed no difference between patients with ACLI and control participants, but the changes of COL12A1 rs970547 and rs240736 and the rs1800787, rs1800788, rs1800790, and rs2227389 genotypes in the β-fib promoter region were associated with ACLI. Furthermore, the rs970547 allele and genotype frequencies in male ACLI patients were different from the control group (P <.05): the frequencies of the rs970547 A and G alleles in the patients were 71.9% and 28.1%, respectively, and in the control group were 58.8% and 41.2%, respectively. The frequencies of AA, AG, and GG genotypes in the patients were 49.3%, 45.2%, and 5.5%, respectively, and in the control group were 27.5%, 62.7%, and 9.8%, respectively, suggesting that male carriers of rs970547 A and rs970547 AA were at high risk of ACLI. Males with the rs970547 A allele and rs970547 AA genotype of COL12A1 may be at high risk for ACLI. Low rs1800787 TT and high rs1800788 CT, rs1800790 AG, and rs2227389 CT frequencies as well as high TGA* of rs1800790, rs1800791, and rs2227389 in the β-fib promoter region may be genetic risk factors related to ACLI. [ABSTRACT FROM AUTHOR]