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To improve the mechanization levels of red cluster pepper harvesting in hilly and mountainous regions of southwest China, a crawler-type harvester is developed to suit the local planting and growth characteristics of red cluster pepper and to facilitate mechanized picking, conveying, and collecting processes. The design, supported by theoretical calculations and structural analysis, includes detailed studies of the picking, conveying, and collecting mechanisms, as well as the hydraulic system. Factors affecting picking efficiency were identified. ADAMS simulation was used to determine the optimum rotational speed range for the spring-tooth roller by analyzing its trajectory. A prototype was then built and field tested with forward speed and the spring-tooth roller's rotational speed as variables to assess impurity, damage, loss, and hanging rates. Data from these tests were analyzed using Design Expert software, which created a mathematical model relating the test indices to the two variables. Optimum parameters were identified, resulting in a harvester configuration that achieved an average productivity of 0.21 ha·h−1 at a forward speed of 1.75 m·s−1 and a roller rotational speed of 181 r·min−1. The impurity rate was 26.7%, the loss rate was 6.1%, the damage rate was 2.3%, and the hanging rate was 4.2%, conforming to the industry standard DG/T 114-2019. This research provides a viable solution for mechanized harvesting of red cluster pepper in hilly and mountainous regions with small planting plots. [ABSTRACT FROM AUTHOR]

Objective To describe the cross-cultural adaptation of the document of advance care planning (ACP) Voicing My CHOiCESTM in Chinese, and provide the basis for the practice of ACP in China. Methods The process of cross-cultural adaptation involved document translation and synthesis, evaluation of healthcare providers, evaluation of patients, back translation, author revision of the original document, and finalization. The participants were all kinds of healthcare providers involved in ACP practice, including doctors, nurses, social workers, psychologists, hospice volunteers, anesthesiologists, nutritionists, and pharmacists. The heathcare providers were invited to answer a questionnaire about the document's structure, importance, appropriateness, and level of language localization. The evaluation of healthcare providers included three rounds of the process. We revised the document based on the feedback and developed the first draft. The first draft of the document was reviewed by young patients with fatal diseases and their families. They read each page of the document and rated the perceived appropriateness, helpfulness, and stressfulness of each item. After further revision, the final document was formed. Results Due to the differences in language, culture, health, and legal system between China and the United States, the cross-cultural adaptations were made in some topics of the document. The Chinese version of the document included 13 topics, involving medical and nursing decision-making, daily life planning, funeral planning, and spiritual support, etc. In total, 91.67% of the patients and 80% of their parents considered all topics covered to be appropriate for age and culture. In total, 75% of patients and 70% of their parents found all the topics to be helpful. In the evaluation of stress, death-related topics brought pressure on patients. Conclusions The Chinese version of Voicing My CHOiCESTM is the first ACP document applicable to adolescents and young adults in China. This document can help young Chinese patients to think and express their wishes and preferences, and guide patients, family members, and healthcare providers to fully and deeply communicate with each other about future planning.

The operational complexities of the elastic tooth drum pepper harvester (ETDPH), characterized by variable drum loads that are challenging to recognize due to varying pepper densities, significantly impact pepper loss rates and mechanical damage. This study proposes a novel method integrating complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), kernel principal component analysis (KPCA), and a support vector machine (SVM) to enhance drum load recognition. The method consists of three principal steps: the initial experiments with ETDPHs to identify the critical factors affecting drum load and to formulate classification criteria; the development of a CEEMDAN-KPCA-SVM model for ETDPH drum load recognition, where drum spindle torque signals are processed by CEEMDAN for decomposition and reconstruction, followed by feature extraction and dimensionality reduction via KPCA to refine the model's accuracy and training efficiency; and evaluation of the model's performance on real datasets, highlighting the improvements brought by CEEMDAN and KPCA, as well as comparative analysis with other machine learning models. The results describe four load conditions—no load (mass of pepper intake (MOPI) = 0 kg/s), low load (0 < MOPI ≤ 0.658 kg/s), normal load (0.658 < MOPI ≤ 1.725 kg/s), and high load (MOPI > 1.725 kg/s)—with the CEEMDAN-KPCA-SVM model achieving 100% accuracy on both training and test sets, outperforming the standalone SVM by 6% and 12.5%, respectively. Additionally, it reduced the training time to 2.88 s, a 10.9% decrease, and reduced the prediction time to 0.0001 s, a 63.6% decrease. Comparative evaluations confirmed the superiority of the CEEMDAN-KPCA-SVM model over random forest (RF) and gradient boosting machine (GBM) in classification tasks. The synergistic application of CEEMDAN and KPCA significantly improved the accuracy and operational efficiency of the SVM model, providing valuable insights for load recognition and adaptive control of ETDPH drum parameters. [ABSTRACT FROM AUTHOR]

To address the fuzzy reconstruction effect on distant objects in unbounded scenes and the difficulty in feature matching caused by the thin structure of power lines in images, this paper proposes a novel image-based method for the reconstruction of power transmission lines (PTLs). The dataset used in this paper comprises PTL progressive motion sequence datasets, constructed by a visual acquisition system carried by a developed Flying–walking Power Line Inspection Robot (FPLIR). This system captures close-distance and continuous images of power lines. The study introduces PL-NeRF, that is, an enhanced method based on the Neural Radiance Fields (NeRF) method for reconstructing PTLs. The highlights of PL-NeRF include (1) compressing the unbounded scene of PTLs by exploiting the spatial compression of normal L ∞ ; (2) encoding the direction and position of the sample points through Integrated Position Encoding (IPE) and Hash Encoding (HE), respectively. Compared to existing methods, the proposed method demonstrates good performance in 3D reconstruction, with fidelity indicators of PSNR = 29, SSIM = 0.871, and LPIPS = 0.087. Experimental results highlight that the combination of PL-NeRF with progressive motion sequence images ensures the integrity and continuity of PTLs, improving the efficiency and accuracy of image-based reconstructions. In the future, this method could be widely applied for efficient and accurate 3D reconstruction and inspection of PTLs, providing a strong foundation for automated monitoring of transmission corridors and digital power engineering. [ABSTRACT FROM AUTHOR]

In this article, statistical inference is taken into account about two-parameter Lomax distribution under adaptive progressive Type-II hybrid censored data in combination with competing risks model. Frequency and Bayesian estimators under both symmetric and asymmetric loss functions are obtained for unknown parameters as well as cause-special reliability and hazard functions. Furthermore, the existence and uniqueness of maximum likelihood estimators are given. The corresponding confidence and credible intervals are also constructed based on asymptotic theory, delta method and MCMC technique. According to the simulation results, the performance of all the proposed point and interval estimates is evaluated. Finally, an example by analyzing real experimental data is given to illustrate all the deductive process established in this article. [ABSTRACT FROM AUTHOR]

The Flying–Walking Power Line Inspection Robot (FPLIR) faces challenges in maintaining stability and reliability when operating in harsh transmission line environments with complex conditions. The robot often switches modes frequently to land accurately on the line, resulting in increasing following errors and premature or delayed switching caused by reference path switching. To address these issues, a path-following control method based on improved line of sight (LOS) is proposed. The method features an adaptive acceptance circle strategy that adjusts the radius of the acceptance circle of the path point based on the angle of the path segment and the flight speed at the time of switching, improving path-following accuracy during reference trajectory switching. Also, an adaptive heading control with vertical distance feedback is designed to prioritize different path-following methods in real time based on variations in vertical distance, achieving rapid convergence along the following path. The state feedback following control law, based on the improved LOS, achieves the stable following of the reference path, which was validated by simulations. The simulation results show that the improved LOS reduces the convergence time by 0.8 s under controllable error conditions for path angles of θ ∈ (0, π⁄2). For path angles of θ ∈ (π⁄2, π), the following error is reduced by 0.3 m, and the convergence time is reduced by 0.4 s. These results validate the feasibility and effectiveness of the proposed method. This method demonstrates advantages over the traditional LOS in terms of following accuracy and convergence speed, providing theoretical references for future 3D path following for path-following robots and aerial vehicles. [ABSTRACT FROM AUTHOR]

There have been numerous tests proposed to determine whether or not the exponential model is suitable for a given data set. In this article, we propose a new test statistic based on spacings to test whether the general progressive Type-II censored samples are from exponential distribution. The null distribution of the test statistic is discussed and it could be approximated by the standard normal distribution. Meanwhile, we propose an approximate method for calculating the expectation and variance of samples under null hypothesis and corresponding power function is also given. Then, a simulation study is conducted. We calculate the approximation of the power based on normality and compare the results with those obtained by Monte Carlo simulation under different alternatives with distinct types of hazard function. Results of simulation study disclose that the power properties of this statistic by using Monte Carlo simulation are better for the alternatives with monotone increasing hazard function, and otherwise, normal approximation simulation results are relatively better. Finally, two illustrative examples are presented. [ABSTRACT FROM AUTHOR]

The impact of general anesthetics on brain function development is one of the top frontier issues of public concern. However, little bibliometric analysis has investigated this territory systematically. Our study aimed to visualize the publications between 2000 and 2023 to inspire the trends and hotspots in anesthetic neurodevelopmental toxicity research. Publications from 2000 to 2023 were collected from the Web of Science Core Collection. CiteSpace was utilized to plot and analyze the network maps of countries, institutions, authors, journals, and keywords associated with these publications. A total of 864 publications, consisting of 786 original articles and 78 reviews, were extracted from 2000 to 2023. The annual publications have increased constantly over the past two decades. The USA and the People's Republic of China were the leading driving forces in this field. Harvard University was the most productive institution. Zhang Y published the most related articles, and Jevtovic-Todorovic V was mostly cited in this field. The most prolific journal was Pediatric Anesthesia, and the most frequently co-cited journal was Anesthesiology. Keywords were divided into nine clusters: "apoptosis", "propofol", "developing brain", "cognitive dysfunction", "neuronal cell degeneration", "brain", "neuroinflammation", "local anesthesia", and "oxygen therapy". The strongest citation bursts in earlier years were "learning disability", "cell death", and "cognitive function". The emerging trends in the coming years were "awake regional anesthesia", "behavioral outcome", and "infancy general anesthesia compared to spinal anesthesia". We conclude that anesthetic-induced neurotoxicity has received growing attention in the past two decades. Our findings evaluated the present status and research trends in this area, which may provide help for exploring further potential prospects on hot topics and frontiers., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2024, Li et al.)