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Tracheostomy is a vital therapy for juvenile-onset recurrent respiratory papillomatosis (JORRP) to maintain an adequate airway in an emergency, yet the relationship between cannulation duration and prognosis has not been extensively explored.To investigate the predictive influence of the duration of tracheostomy dependence on JORRP remission.A retrospective review of JORRP patients (The rate of decannulation was 72.7%. After decannulation for one year, the percentage of distal spread fell from 42.9 to 30.4%. Twenty-six of 77 patients (33.8%) had remission of their disease, 40 (51.9%) continued to have active disease while 11 (14.3%) died during follow-up. The cannulation duration was positively correlated with the overall duration of this disease (The study demonstrates that the time span before decannulation indicates the severity of disease and cannulation aggravates the distal spread. Patients with cannulation duration ≤ 34.9 months after tracheostomy are prone to possess a relatively pleasant prognosis.

Appropriate vibration parameters can improve the efficiency of vibration harvesting, so the selection of vibration harvesting parameters is very important. In this paper, the stress of olive fruit is analyzed, and the vibration of olive tree is tested and simulated. Design-Expert 12.0 is used for experimental design, The diameter, height and angle of main branches were selected as the test factors, and the optimal vibration frequency and force were selected as the evaluation indexes. determines the optimal vibration frequency through modal analysis; the optimum vibration force is determined by harmonic response analysis and test. The quadratic polynomial response regression model of optimal vibration frequency and optimal vibration force is obtained. The research results can provide reference for the design of Vibrating harvester.

The pros and cons of tracheotomy, as a classic treatment of juvenile-onset recurrent respiratory papillomatosis (JORRP), have gradually been recognized, but the exact impact of tracheotomy on remission and demise is not clear.To investigate the predicting influence of tracheotomy on prognosis for JORRP.Three hundred forty two patients with JORRP treated in Beijing Tongren Hospital were retrospectively reviewed. The clinical characteristics and prognosis parameters were compared in the group of tracheotomy and non-tracheotomy.The rate of tracheotomy was 24.6% (84/342). Among these patients, 68 (81.0%) developed the tracheal papillomatosis. The onset age of RRP occurred earlier in tracheostomized group, and patients performed tracheotomy needed a greater number of surgeries and developed distal spread more easily (The age at diagnosis, the surgical frequency and the medical level of hospital are important factors affecting the occurrence of tracheotomy. Patients who had undergone tracheotomy are prone to possess the low remission rate and high mortality.

Assessment of pronunciation has long been established as an integral component of speakingassessment, usually combined with other dimensions such as fluency, lexico-grammatical resourcesand topic development to generate an overall score for the speaking section in major English tests. Fewstudies have focused on assessment of pronunciation per se, which plays a critical role in pedagogicalcontext such as pre-service teacher training. This study attempts to develop a diagnostic rating scaleof pronunciation for the purpose of pronunciation instruction in a pedagogical practice and providesupporting evidence for the construct validity of the scale by many-facet Rasch analysis. Results fromstatistical analysis suggest overall satisfactory construct validity of the scale. The statistical findings arefurther corroborated by focus group interviews with raters and examinees. This study has implicationsfor second language pronunciation instruction,assessmentand self-learning, as well as the developmentand validation of diagnostic rating scale of other aspects of organizational competence.

Purpose The purpose of this study is to test a chassis robot on rugged road cargo handling. Design/methodology/approach Attitude solution of D-H series robot gyroscope speed and acceleration sensor. Findings In identical experimental environments, hexapodal robots experience smaller deviations when using a four-footed propulsive gait from a typical three-footed gait for forward motion; for the same distance but at different speeds, the deviation basically keeps itself within the same range when the robot advances forward with four-foot propulsive gait; because the foot slide in the three-footed gait sometimes experiences frictions, the robot exhibits a large gap in directional deviations in different courses during motion; for motion using a four-footed propulsive gait, there are minor directional deviations of hexapodal robots resulting from experimental errors, which can be reduced through optimizing mechanical structures. Originality/value Planning different gaits can solve problems existing in some typical gaits. This article has put forward a gait planning method for hexapodal robots moving forward with diverse gaits as a redundant multifreedom structure. Subsequent research can combine a multiparallel-legged structure to analyze kinematics, optimize the robot’s mechanical structure and carry out in-depth research of hexapod robot gaits.

To identify the recurrence rate and risk factors for recurrence in patients with juvenile-onset recurrent respiratory papillomatosis (JORRP).A retrospective review was performed for all JORRP patients who underwent surgery between 2002 and 2019 at our institution. The demographic characteristics and clinical parameters were recorded. Kaplan-Meier estimates and Cox proportional hazards models were used to analyze the rate of recurrence and its risk factors.Our study included 721 patients. The cumulative recurrence rates at 1, 5, and 10 postoperative years following initial surgery were 74.2%, 90.0%, and 94.3%, respectively. Age at diagnosis younger than 4.5 years (HR = 2.380, 95% CI [1.169-4.846], P = 0.017), high Derkay anatomical score (HR = 1.136, 95% CI [1.043-1.236], P = 0.003) and HPV type 11 infection (HR = 2.947, 95% CI [1.326-6.551], P = 0.008) were independent risk factors for recurrence. Adjuvant therapy with interferon was less likely to recur (HR = 0.237, 95% CI [0.091-0.616], P = 0.003). Additionally, gender, tracheotomy, mode of delivery, parity, expression of Ki-67, HPV vaccination, and surgical treatment method were not independently associated with recurrence (P 0.05).Age at diagnosis younger than 4.5 years, high Derkay anatomical score and HPV type 11 infection were associated with an increased risk for recurrence in patients with JORRP. Adjuvant therapy with interferon may reduce the risk of recurrence.

Extraction and segmentation of kiwifruit vine range is an important part of precision agriculture in kiwifruit orchard. In this paper, depth semantic segmentation and traditional machine learning are used to segment and extract kiwifruit vines from orthophoto images, and the accuracy and image quality of vine segmentation based on pspnet, SVM and random forest classification in another test set are compared. Experimental results show that although the mean pixel accuracy of deep semantic segmentation is slightly lower than that of traditional machine learning segmentation, the segmentation image quality of deep semantic segmentation is better and the pixels are more continuous. The deep learning method effectively developed UAV remote sensing image data, improved the usability of remote sensing image, and provided necessary plant information for orchard precision agriculture.

An apple pluck port based on negative pressure suction force can realize contactless apple plucking and also reduce possible damage to the apple. Accordingly, in this study, a strength type pneumatic pluck port was designed on the basis of a Tesla valve. First, a low air pressure block for mechanization of the Tesla valve structure at the intersection between the main and curved air passageway was theoretically modelled and analyzed. Then, the air pressure and the flow speed distribution were analyzed for three different types of structure parameters under various distances of the Tesla pluck port from the apple; on the basis of a fluent simulation, the maximum pressure difference at both sides of the apple was also simulated. Finally, the structure parameters under an optimal negative pressure field according to the simulation analysis were proposed, and a manufactured experimental test was conducted to compare the results with the simulation. The simulation and experimental data prove that when the included angle between the main and curved air passageway of the Tesla pluck port is lower than 45°, the low air pressure block at the intersection between the main and curved air passageway of the Tesla valve affects the flow of the pluck port and extends the length of the low air pressure block. The Tesla pluck port guarantees a flow in the pipe when the pipe port diameter is 10–15 mm larger than the apple diameter, ensuring the negative strengthening effect of the Tesla pluck port. The experiment proves that the Tesla pluck port designed in this study exhibits a better negative pressure strengthening effect than that achieved via previously existing methods, which can strengthen the plucking effect.

China is a one of the largest countries producing kiwifruit, and there are many kinds of kiwifruit in China. The identification of kiwifruit varieties has important application value in kiwifruit automatic picking robots and kiwifruit sorting factories. The paper studies the classification of kiwifruit varieties based on deep learning, and studies the deployment and application of kiwifruit classification model on the Jetson Nano artificial intelligence development board. A portable device used for classification of kiwifruit varieties was designed and developed. This paper studied the selection of various parts of the portable device of kiwifruit classification and designed the portable device shell. The portable device shell was obtained through the 3D printer, assembled the parts, and obtained the portable kiwi variety classification equipment. The construction of the kiwifruit dataset of “Cuixiang”, “Qinmei”, “Xuxiang” and “Hayward” kiwis was studied and using data augmentation to introduce variations into the data. According to the characteristics of the problem of 4 types of kiwifruit classification, the methods and advantages of transfer learning are discussed. Using transfer learning based on three pre-training models Xception, ResNet50, DenseNet121. Comparative analysis of the model size, training speed, convergence, and recognition accuracy of the transfer learning model based on Xception, ResNet50, and DenseNet121, and concluded that in Xception, ResNet50, and DenseNet121, the transfer learning model based on DenseNet121 pre-trained model has the best effect on the classification of four kiwifruit varieties, with fast convergence speed, smallest model, and high recognition accuracy of 97.79%. This paper studied the deployment and experiment of the deep learning model on the Jetson Nano development board. Using the PyTorch to perform transfer learning based on the DenseNet121 pre-training model. After using the TensorRT acceleration engine, it took an average of 0.035s to classify each image, and the real-time classification FPS reached an average of 30, the accuracy rate of the model on the validation set is 93.63%, achieving fast and accurate classification of kiwi varieties.

In order to realize the establishment of the unknown terrain map in the indoor environment of the ROS wheeled mobile robot, this article uses Lidar, Raspberry Pi and other hardware to build the wheeled mobile robot, in the ROS environment, the robot is built by the URDF model, and the robot model is configured. Differential controller, keyboard control node, etc. Establish the simulation environment, use different simulation environments to visually simulate the robot, and simulate the two optimization algorithms in the SLAM algorithm to simulate the construction of the map. In order to explore the effect of SLAM’s different optimization algorithms on the construction of graphics, the SLAM algorithm based on filter and the SLAM algorithm based on graph optimization are introduced respectively. The robot is selected. After the robot is built, three different experimental environments are selected. A variety of map-building algorithms are used to experiment, comparing the effects of G-mapping algorithm and Cartographer algorithm to build maps in a small-scale, large-scale and multi-obstacle environment. Use the image processing software under the Linux system to analyse the map created by the robot in the experimental environment, measure the coordinates of the robot feature points in the created map by the number of pixels, and compare the actual coordinates of the location of the special point in the actual environment to evaluate Construction effect. By comparing the effects of the two algorithms on the contours of various obstacles when building a map, the effect of mapping in a multi-obstacle environment is evaluated. The results show that the SLAM graph-building algorithm based on graph optimization has a more stable graph-building effect.