RESUMEN
BACKGROUND: The harvest of fruit can be significantly advanced with the thriving development of intelligent and automated robot technologies. Nevertheless, the picking success rate of tomato fruit still requires improvement as some fruits are unexpectedly damaged inside, which is imperceptible by machine vision. Herein, a modelling method based on modified Voronoi algorithm is proposed to reconstruct the cellular structure of tomato pericarp. RESULTS: Based on the reconstructed micro-model, the compression physical behaviour of the pericarp cells is simulated to observe internal local stress and potential damage. It is revealed that the simulation result for pericarps of tomatoes with different ripeness is highly consistent to the experimental tests, which has well validated the feasibility of this modelling and simulation method. CONCLUSION: A Voronoi-based modelling method is proposed for micro-reconstruction of tomato pericarp, and the corresponding compression simulation results agree well with the experimental tests. Such result can be utilized as reference to improve the grasping force control for harvesting robot to avoid invisible damage induced by accident overload issue. With the predicting result, superior success rate can be achieved to enhance robot performance. © 2024 Society of Chemical Industry.
RESUMEN
This paper studies an optimization problem of antenna placement for multiple heading angles of the target in a distributed multiple-input multiple-output (MIMO) radar system. An improved method to calculate the system's coverage area in light of the changing target heading is presented. The antenna placement optimization problem is mathematically modelled as a sequential decision problem for compatibility with reinforcement learning solutions. A reinforcement learning agent is established, which uses the long short-term memory (LSTM)-based proximal policy optimization (PPO) method as the core algorithm to solve the antenna placement problem. Finally, the experimental findings demonstrate that the method can enhance the coverage area of antenna placement and thus has reference value for providing new ideas for the antenna placement optimization of distributed MIMO radar.
RESUMEN
Photocurable 3D printing technology has outperformed extrusion-based 3D printing technology in material adaptability, resolution, and printing rate, yet is still limited by the insecure preparation and selection of photoinitiators and thus less reported. In this work, we developed a printable hydrogel that can effectively facilitate various solid or hollow structures and even lattice structures. The chemical and physical dual-crosslinking strategy combined with cellulose nanofibers (CNF) significantly improved the strength and toughness of photocurable 3D printed hydrogels. In this study, the tensile breaking strength, Young's modulus, and toughness of poly(acrylamide-co-acrylic acid)D/cellulose nanofiber (PAM-co-PAA)D/CNF hydrogels were 375 %, 203 % and 544 % higher than those of the traditional single chemical crosslinked (PAM-co-PAA)S hydrogels, respectively. Notably, its outstanding compressive elasticity enabled it to recover under 90 % strain compression (about 4.12 MPa). Resultantly, the proposed hydrogel can be utilized as a flexible strain sensor to monitor the motions of human movements, such as the bending of fingers, wrists, and arms, and even the vibration of a speaking throat. The output of electrical signals can still be collected through strain even under the condition of energy shortage. In addition, photocurable 3D printing technology can provide customized services for hydrogel-based e-skin, such as hydrogel-based bracelets, fingerstall, and finger joint sleeves.
RESUMEN
The present study aimed to explore the mechanisms underlying sepsis-induced acute lung injury (ALI) and identify more effective therapeutic strategies to treat it. The gene expression data set GSE10474 was downloaded and assessed to identify differentially expressed genes (DEGs). Principal component analysis, functional enrichment analysis and differential co-expression analysis of DEGs were performed. Furthermore, potential target drugs for key DEGs were assessed. A total of 209 DEGs, including 107 upregulated and 102 downregulated genes were screened. A number of DEGs, including zinc finger and BTB domain containing 17 (ZBTB17), heat shock protein 90 kDa ß, member 1 (HSP90B1) and major histocompatibility complex, class II, DR α were identified. Furthermore, gene ontology terms including antigen processing and presentation, glycerophospholipid metabolism, transcriptional misregulation in cancer, thyroid hormone synthesis and pathways associated with diseases, such as asthma were identified. In addition, a differential co-expression network containing ubiquitin-conjugating enzyme E2 D4, putative and tubulin, γ complex associated protein 3 was constructed. Furthermore, a number of gene-drug interactions, including between HSP90B1 and adenosine-5'-diphosphate and radicicol, were identified. Therefore, DEGs, including ZBTB17 and HSP90B1, may be important in the pathogenesis of sepsis-induced ALI. Furthermore, drugs including adenosine-5'-diphosphate may be novel drug candidates to treat patients with ALI.
