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Rural tourism is an important way to promote sustainable economic development and boost the comprehensive revitalization of the countryside. The key to promoting rural tourism development lies in solving the development path problem. In this paper, we extracted high-frequency keywords from the text of 2021 World Tourism Alliance—Case of Tourism Contributing to Rural Revitalization through the text mining tool ROST-CM6, generated a common word matrix, and then used Stata17 for cluster analysis, combined with the case in a deep analysis of similar keywords. The results show that the tourism path to realizing rural revitalization is diversified, and there are four paths: ecological development type, industry-driven type, cultural integration type and multiple governance type. [ABSTRACT FROM AUTHOR]

In this work, the CeO2 nanoparticles were dispersed onto the surface of graphene oxide (GO), followed by electrodeposition of Pt–Pd alloy nanoparticles on the CeO2 surface to fabricate Pt–Pd@CeO2/graphene oxide composites (Pt–Pd@CeO2/GO). Morphological investigation was conducted using X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM). The results of morphological characterization revealed that CeO2 nanoparticles acted as cores, while Pt–Pd alloy nanoparticles formed shells. The electrocatalytic oxidation performance of Pt–Pd@CeO2/GO composites for methanol electro-oxidation reaction (MOR) was systematically investigated. The mass activity for MOR on Pt1Pd1.3@CeO2/GO electrocatalyst was 1128 mA·mgPt+Pd−1, which was 5.0-fold higher than that of Pt/C catalysts. The synergistic effect between Pt and Pd, along with the active oxygen-containing species of CeO2 effectively enhanced catalytic activity. This work presents a novel approach to developing catalysts with high catalytic performance for MOR. [ABSTRACT FROM AUTHOR]

Key message: The application of flagellin 22 (flg22), the most widely studied PAMP, enhance crop cold tolerance. ICE1-CBF pathway and SA signaling is involved in the alleviation of cold injury by flg22 treatment. Pathogen infection cross-activates cold response and increase cold tolerance of host plants. However, it is not possible to use the infection to increase cold tolerance of field plants. Here flagellin 22 (flg22), the most widely studied PAMP (pathogen-associated molecular patterns), was used to mimic the pathogen infection to cross-activate cold response. Flg22 treatment alleviated the injury caused by freezing in Arabidopsis, oilseed and tobacco. In Arabidopsis, flg22 activated the expression of immunity and cold-related genes. Moreover, the flg22 induced alleviation of cold injury was lost in NahG transgenic line (SA-deficient), sid2-2 and npr1-1 mutant plants, and flg22-induced expression of cold tolerance-related genes, which indicating that salicylic acid signaling pathway is required for the alleviation of cold injury by flg22 treatment. In short flg22 application can be used to enhance cold tolerance in field via a salicylic acid-depended pathway. [ABSTRACT FROM AUTHOR]

Substance use disorders are a significant public health issue. Options to dispose of controlled medications are limited, increasing the risk of diversion. Providing an alternative for disposal, a chemical denaturant, SafeMedWaste, was designed to destroy controlled substances irreversibly and safely be placed in non-hazardous landfills. Via HPLC–MS, four formulations of SafeMedWaste were tested with 34 different liquid controlled medications from DEA schedules I–V. Beta testing assessed the efficacy of SafeMedWaste in a clinical setting and on waste generated in a manufacturing setting. Furthermore, a formulation of SafeMedWaste was tested on solid controlled medications. All 34 of the liquid medications tested (e.g., amphetamine, diazepam, fentanyl, ketamine) were fully destroyed in SafeMedWaste within 2–24 h. Analysis of a beta test sample of SafeMedWaste containing fentanyl, midazolam, and morphine waste collected in a hospital showed full denaturation of these drugs in 24 h. Variants of SafeMedWaste were optimized to denature six different controlled substance waste samples from a manufacturing facility. In contrast to side-by-side studies with a charcoal disposal system using the same drugs, SafeMedWaste fully inactivated and destroyed the controlled substances in the waste streams. Another formulation of SafeMedWaste was tested on solid medications, which were fully denatured in 48–72 h. In conclusion, SafeMedWaste irreversibly denatures controlled medications that present a problem in our society. [ABSTRACT FROM AUTHOR]

Diabetic encephalopathy (DE) is one of the chronic complications of diabetes. Even then, the molecular mechanism underlying DE remains unexplored. In this study, we have made an attempt to investigate the metabolic changes associated with the streptozocin (STZ)-induced cognitive dysfunction in the hippocampus of the rat model, a classical rodent model for DE, with the help of Gas Chromatography-Mass Spectrometry-based method. The STZ injections led to the rise of mean blood glucose levels in the diabetes mellitus (DM) group of rats as compared to the control (CON) group of rats throughout the experiment. However, we did not find any significant difference between the blood glucose levels of the DM & the CON groups of rats before the STZ injection. The results indicated a behavioral and morphological cognitive dysfunction in the DM groups of rats. The metabolomic investigation of these DE rats demonstrated a lower level of N-acetylaspartate and dihydroxyacetone phosphate accompanied by a higher level of homocysteine and glutamate as against the CON group of rats. The outcome of this study may unravel the underlying pathophysiological mechanism of DE. Also, the metabolomic data from this study may provide a platform for the development of DE biomarkers. [ABSTRACT FROM AUTHOR]

Epigenetic modifications, including chromatin modifications and DNA methylation, have a central role in the regulation of gene expression in plants and animals. The transmission of epigenetic marks is crucial for certain genes to retain cell lineage-specific expression patterns and maintain cell fate. However, the marks that have accumulated at regulatory loci during growth and development or in response to environmental stimuli need to be deleted in gametes or embryos, particularly in organisms such as plants that do not set aside a germ line, to ensure the proper development of offspring. In Arabidopsis thaliana, prolonged exposure to cold temperatures (winter cold), in a process known as vernalization, triggers the mitotically stable epigenetic silencing of the potent floral repressor FLOWERING LOCUS C (FLC), and renders plants competent to flower in the spring; however, this silencing is reset during each generation. Here we show that the seed-specific transcription factor LEAFY COTYLEDON1 (LEC1) promotes the initial establishment of an active chromatin state at FLC and activates its expression de novo in the pro-embryo, thus reversing the silenced state inherited from gametes. This active chromatin state is passed on from the pro-embryo to post-embryonic life, and leads to transmission of the embryonic memory of FLC activation to post-embryonic stages. Our findings reveal a mechanism for the reprogramming of embryonic chromatin states in plants, and provide insights into the epigenetic memory of embryonic active gene expression in post-embryonic phases, through which an embryonic factor acts to 'control' post-embryonic development processes that are distinct from embryogenesis in plants. [ABSTRACT FROM AUTHOR]

Cyclodextrin has been found to be an attractive novel solubilizer due to its unique material properties. Absidia coerulea is widely used in steroid bioconversion. The effects of hydroxypropyl-β-cyclodextrin (HP-β-CD) on the growth, morphology, and steroid-converting activity of A. coerulea CICC 40302 were systematically studied. HP-β-CD affected A. coerulea growth, resulting in changes in its spore morphology and mycelial morphology. It induced an increase in the spore germination rate and a decrease in cell biomass at the stationary phase. Optical microscopy revealed that HP-β-CD altered the mycelial morphology and reduced the pellet compactness of A. coerulea. A convenient and feasible computing method was used to measure pellet compactness, and it demonstrated that the compactness degree of the pellet decreased as HP-β-CD increased, which could be attributed to the modification of the physical properties of the fermentation medium. Moreover, the changing of mycelial morphology influenced steroid-converting activity. The results showed that HP-β-CD had multiple concentration-dependent effects on A. coerulea cells. HP-β-CD in the proper concentration range holds great potential as a biocompatible solubilizer. [ABSTRACT FROM AUTHOR]

This paper focuses on the robust adaptive control problems for a class of interval time-delay systems and a class of large-scale interconnected systems. The nonlinear uncertainties of the systems under study are bounded by high-order polynomial functions with unknown gains. Firstly, the adaptive feedback controller which can guarantee the stability of the closed-loop system in the sense of uniform ultimate boundedness is proposed. Then the proposed adaptive idea is extended to robust stabilizing designing method for a class of large-scale interconnected systems. Here, another problem we address is to design a decentralized feedback adaptive controller such that the closed-loop system is stable in the sense of uniform ultimate boundedness for all admissible uncertainties and time-delay. Finally, an illustrative example is given to show the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

The implementation of Smart Airport and Airport 4.0 visions relies on the integration of automation, artificial intelligence, data science, and aviation technology to enhance passenger experiences and operational efficiency. One essential factor in the integration is the semantic segmentation of the aircraft main components (AMC) perception, which is essential to maintenance, repair, and operations in aircraft and airport operations. However, AMC segmentation has challenges from low data availability, high-quality annotation scarcity, and categorical imbalance, which are common in practical applications, including aviation. This study proposes a novel AMC segmentation solution, employing a transfer learning framework based on a sophisticated DeepLabV3 architecture optimized with a custom-designed Focal Dice Loss function. The proposed solution remarkably suppresses the categorical imbalance challenge and increases the dataset variability with manually annotated images and dynamic augmentation strategies to train a robust AMC segmentation model. The model achieved a notable intersection over union of 84.002% and an accuracy of 91.466%, significantly advancing the AMC segmentation performance. These results demonstrate the effectiveness of the proposed AMC segmentation solution in aircraft and airport operation scenarios. This study provides a pioneering solution to the AMC semantic perception problem and contributes a valuable dataset to the community, which is fundamental to future research on aircraft and airport semantic perception.Graphical abstract: The implementation of Smart Airport and Airport 4.0 visions relies on the integration of automation, artificial intelligence, data science, and aviation technology to enhance passenger experiences and operational efficiency. One essential factor in the integration is the semantic segmentation of the aircraft main components (AMC) perception, which is essential to maintenance, repair, and operations in aircraft and airport operations. However, AMC segmentation has challenges from low data availability, high-quality annotation scarcity, and categorical imbalance, which are common in practical applications, including aviation. This study proposes a novel AMC segmentation solution, employing a transfer learning framework based on a sophisticated DeepLabV3 architecture optimized with a custom-designed Focal Dice Loss function. The proposed solution remarkably suppresses the categorical imbalance challenge and increases the dataset variability with manually annotated images and dynamic augmentation strategies to train a robust AMC segmentation model. The model achieved a notable intersection over union of 84.002% and an accuracy of 91.466%, significantly advancing the AMC segmentation performance. These results demonstrate the effectiveness of the proposed AMC segmentation solution in aircraft and airport operation scenarios. This study provides a pioneering solution to the AMC semantic perception problem and contributes a valuable dataset to the community, which is fundamental to future research on aircraft and airport semantic perception. [ABSTRACT FROM AUTHOR]