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The high computational cost, complex external environment, and limited computing resources of embedded system are some major problems in traditional autonomous robot navigation methods. To overcome these problems, a mobile robot path planning navigation system based on panoramic vision was proposed. This method first describes the structure and functions of the navigation system. It explains how to use the environment to explore and map in order to create a panoramic vision sensor. Finally, it elaborates on the breadth-first search based on regression neural network (RNN) method, the Voronoi skeleton diagram method, the algorithm principle, and how to navigate by the planning path implementation of practical strategies. The simulation results illustrate that the breadth-first search method and the Voronoi skeleton graph method based on panoramic view have a high speed. The accessibility of RNN planning algorithm can effectively solve the difficult problems such as high computing overhead, complex navigation environment, and limited computing resources. In the actual robot navigation experiment, the difference in real-time performance and optimality performance that exists between the two algorithms is reflected in the length and duration of the course taken by the robot. When applied to a variety of site environments, the breadth-first search method requires between 23.2 and 45.3% more time to calculate the planned path than the Voronoi skeleton graph method, despite the fact that the planned path length is between 20.7 and 35.9% shorter using the breadth-first search method. It serves as a guide for choosing the appropriate algorithm to implement in practical applications.

Objective: The purpose of the current study was to determine the difference in intestinal microbiota after delivery between healthy fetuses and fetuses with hyperechogenic bowel during the second trimester and the relationship between fetal echogenic bowel and microbiota. Methods: Fourteen healthy fetuses (control group), 13 fetuses with echogenic bowel (EB group), and seven fetuses with echogenic bowel and other abnormalities (C‐EB group) were selected. The first meconium after delivery was collected for 16S rRNA sequencing. Results: A total of 1 222 131 high‐quality sequences were generated after sequencing optimization of all samples. Each sample contained an average of 35 945 high‐quality sequences and 2036 operational taxonomic units (OTUs). There was no significant difference in the Shannon, Simpson index among the three groups. At the genus level, the abundance of Escherichia coli/Shigella in the EB and C‐EB groups was significantly lower than the control group, while the abundance of Staphylococcus, Methylobactrium, and Curvibacter in the EB group was significantly higher than the other groups. There was a difference in abundance of Gammaproteobacteria, Fusobacteria, Enterobacteriaceae, and E. coli in the EB and C‐EB groups. Conclusions: The formation of echogenic bowel may be related to the microbiota. [ABSTRACT FROM AUTHOR]

Ferroan brucite with different Fe2+ doping amounts (Mg1-XFeX(OH)2, x = 0.3, 0.4, 0.5, 0.6, 0.7 and 0.8) was synthesized for the removal of Congo red (CR) from wastewater. As the Fe2+ content increased, the removal efficiency initially increased and then decreased, and Mg0.6Fe0.4(OH)2 exhibited the maximum removal amount which was 2745.96 mg/g. The high removal ability of Mg0.6Fe0.4(OH)2 was derived from the combined removal mechanism. The removal amount of CR was highly related to the amount of Fe2+ in MgFe(OH)2 and its existed state. The removal behaviors of M0.7Fe0.3(OH)2 (M = Zn, Ni, Co) were also conducted to verify the function and university of Fe2+ in the degradation process. The influence of M2+ in M0.7Fe0.3(OH)2 (M = Zn, Ni, Co) on the removal efficiency was explored by experimental study and calculation of the system energy and bond length change based on molecular simulation. This work provided an outstanding approach for preparation of high efficiency materials to purify organic wastewater. [ABSTRACT FROM AUTHOR]

Background: Painful temporomandibular disorder (TMD) is the common cause of chronic oro‐facial pain, which may interfere with sleep. Previous studies have documented an association between sleep and TMD. Objectives: This study aimed to further explore the association of night‐time sleep and daytime napping with painful TMD. Methods: A total of 419 patients (aged 31.88 ± 11.54 years with women forming 85.4%) from a TMD/Orofacial Pain center were enrolled. Patients' sleep conditions were evaluated with the Pittsburgh Sleep Quality Index (PSQI) questionnaire, and information on night‐time sleep duration, napping duration and napping frequency was interviewed. TMD was diagnosed according to the Diagnostic Criteria for TMD protocol and stratified into myalgia (muscle pain), arthralgia (joint pain) and combined (muscle and joint pain) subgroups. The severity of TMD was measured with the Fonseca Anamnestic Index (FAI) questionnaire. Restricted cubic spline (RCS) regression models were established to explore relationships between sleep and painful TMD subgroups. Results: Patients with poor sleep quality (PSQI≥6) had higher FAI scores (median 60, p <.001) and higher proportions of painful TMDs. The myalgia subgroup had higher PSQI scores (median 8, p <.001) than the arthralgia subgroup. The RCS models indicated a non‐linear relationship between night‐time sleep duration and myalgia (p <.001), which was not observed in arthralgia. However, there were no significant findings concerning napping and painful TMD subgroups. Conclusion: This study found that the association between sleep and TMD is mainly related to painful TMD conditions, which are associated with night‐time sleep duration. [ABSTRACT FROM AUTHOR]