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Driven by the increasing global population and rapid urbanization, aircraft noise pollution has emerged as a significant environmental challenge, impeding the sustainable development of the aviation industry. Traditional noise prediction methods are limited by incomplete datasets, insufficient spatiotemporal consistency, and poor adaptability to complex meteorological conditions, making it difficult to achieve precise noise management. To address these limitations, this study proposes a novel noise prediction framework based on a hybrid Convolutional Neural Network–Bidirectional Long Short-Term Memory–Attention (CNN–BiLSTM–Attention) model. By integrating multi-source data, including meteorological parameters (e.g., temperature, humidity, wind speed) and aircraft trajectory data (e.g., altitude, longitude, latitude), the framework achieves high-precision prediction of aircraft noise. The Haversine formula and inverse distance weighting (IDW) interpolation are employed to effectively supplement missing data, while spatiotemporal alignment techniques ensure data consistency. The CNN–BiLSTM–Attention model leverages the spatial feature extraction capabilities of CNNs, the bidirectional temporal sequence processing capabilities of BiLSTMs, and the context-enhancing properties of the attention mechanism to capture the spatiotemporal characteristics of noise. The experimental results indicate that the model’s predicted mean value of 68.66 closely approximates the actual value of 68.16, with a minimal difference of 0.5 and a mean absolute error of 0.89%. Notably, the error remained below 2% in 91.4% of the prediction rounds. Furthermore, ablation studies revealed that the complete CNN–BiLSTM–AM model significantly outperformed single-structure models. The incorporation of the attention mechanism was found to markedly enhance both the accuracy and generalization capability of the model. These findings highlight the model’s robust performance and reliability in predicting aviation noise. This study provides a scientific basis for effective aviation noise management and offers an innovative solution for addressing noise prediction problems under data-scarce conditions.

The northern permafrost regions are increasingly experiencing frequent and intense extreme events, with a rise in the occurrence of compound extreme events. Many climate-related hazards in these areas are driven by such compound events, significantly affecting the stability and functionality of vegetation ecosystems. However, the cumulative and lagged effects of compound extreme events on vegetation remain unclear, which may lead to an underestimation of their actual impacts. This study provides a comprehensive analysis of the spatiotemporal variations in compound extreme events and the vegetation response to these events in the northern permafrost regions from 1982 to 2022. The primary focus of this study is on examining the cumulative and lagged effects of compound extreme climate events on the Kernel Normalized Difference Vegetation Index (kNDVI) during the growing seasons. The results indicate that in high-latitude regions, the frequency of extreme high temperature–precipitation compound events and high temperature–drought compound events have increased in 58.0% and 67.0% of the areas, respectively. Conversely, the frequency of extreme low temperature–drought compound events and extreme low temperature–precipitation compound events has decreased in 70.6% and 57.2% of the areas, with the high temperature–drought compound events showing the fastest increase. The temporal effects of compound extreme events on kNDVI vary with vegetation type; they produce more cumulative and lagged effects compared with single extreme high-temperature events and fewer effects compared with single extreme precipitation events, with compound events significantly affecting forest and grassland ecosystems. Notably, extreme high temperature–precipitation compound events exhibit the strongest cumulative and lagged effects on vegetation, while extreme low temperature–drought compound events influence wetland and shrubland areas within the same month. This study underscores the importance of a multivariable perspective in understanding vegetation dynamics in permafrost regions.

To date, the non-viral vector Chimeric Antigen Receptor (CAR) T cell preparation platform, exemplified by transposons, has demonstrated significant potential in tumor immunotherapy and yielded positive results in multiple clinical trials. Nonetheless, non-methylated CpG sequences within plasmid DNA can elicit an inflammatory response via Toll-like receptor 9 (TLR9) during CAR-T cell preparation, adversely affecting transgene expression. Additionally, de novo DNA methylation programs promote T cell exhaustion, which poses a significant limitation for CAR-T cell therapy applications. High-throughput liquid protein chip and CBA analyses were utilized to determine the expression levels of inflammatory factors. Flow cytometry and luciferase reporter assays were employed for mutation screening. BALB/c mice and M-NSG mice were used to evaluate the inflammatory response and efficacy of LCG CAR-T , with TIL grouping detected via immunohistochemistry. In this study, we modified the newly discovered Passer (JL) transposon to construct a low-CpG content transposon for CAR-T cell (LCG CAR-T cell) preparation. experiments demonstrated that LCG CAR-T cells prepared using this new transposon exhibited stronger cytotoxicity. In animal models, LCG CAR-T cells significantly inhibited tumor growth and increased the populations of CD4+CAR-T cells and tumor-infiltrating lymphocytes. Furthermore, LCG CAR-T cells modulated pro-inflammatory cytokine release, thereby reducing inflammatory responses and surpassing the effects observed with unmodified CAR-T cells. Collectively, our results demonstrate the high safety and efficacy of non-viral, low CpG Passer transposon CAR-T cells, offering new avenues for improving CAR-T cell efficacy while minimizing inflammation.

Chemodynamic therapy (CDT) alone cannot achieve sufficient therapeutic effects due to the excessive glutathione (GSH) and hypoxia in the tumor microenvironment (TME). Developing a novel strategy to improve efficiency is urgently needed. Herein, we prepared a copper silicate nanoplatform (CSNP) derived from colloidal silica. The Cu(II) in CSNP can be reduced to Cu(I), which cascades to induce a subsequent CDT process. Additionally, benefiting from GSH depletion and oxygen (O2) generation under 660 nm laser irradiation, CSNP exhibits both Fenton-like and hypoxia-alleviating activities, contributing to the effective generation of superoxide anion radical (•O2−) and hydroxyl radical (•OH) in the TME. Furthermore, given the suitable band-gap characteristic and excellent photochemical properties, CSNP can also serve as an efficient type-I photosensitizer for photodynamic therapy (PDT). The synergistic CDT/PDT activity of CSNP presents an efficient antitumor effect and biosecurity in both in vitro and in vivo experiments. The development of an all-in-one nanoplatform that integrates Fenton-like and photosensing properties could improve ROS production within tumors. This study highlights the potential of silicate nanomaterials in cancer treatment.

Siberia occupies vast areas underlain by permafrost, and understanding its land cover changes is important for ecological environmental protection in a warming climate. Based on the land cover and climate datasets, we analyzed the land cover changes and their drivers in Siberia from 1992 to 2020. The results show that ① From 1992 to 2020, the areas of evergreen needleleaf trees and deciduous needleleaf trees in Siberia decreased by 9% and 2.5%, and the areas of grassland, shrub, cropland, and construction land increased by 1.5%, 14.2%, 2.8%, and 39.2%, respectively. Cropland expansion had the fastest rate of 1.85% in the continuous permafrost zone, and construction land expansion had the fastest rate of 3.07% in the non-permafrost zone. ② The center of gravity of agricultural land continues to migrate to the northeast, and the center of gravity of construction land continues to migrate to the southwest. ③ The primary drivers for the land cover changes were temperature and precipitation, and active layer thickness also affected grassland, cropland, and deciduous needleleaf trees. The correlation coefficient between active layer thickness and cropland area is 0.74 in the continuous permafrost zone. The interaction between factors is mostly manifested as a two-factor enhancement, with the highest q -value of the interaction of temperature and precipitation for explanatory power. Our results suggest that climate change and permafrost degradation significantly changed land cover in Siberia. This finding deepens our understanding of the mechanisms of land cover change under the influence of permafrost degradation and provides a new perspective on the land cover changes in permafrost regions.

According to the recent practice in Laopingzi Village, Jiaopingdu Town, Luquan Yi and Miao Autonomous County (Luquan County hereinafter) in dry and hot valley of Jinsha River, the development of Zanthoxylum schinifolium Sieb. et Zucc planting industry can help farmers gradually get rid of poverty and achieve a virtuous cycle of ecological environment. It is a sustainable poverty alleviation way. Based on the three aspects of soil properties, climatic conditions, and topographical conditions influencing the growth of Z. schinifolium, this paper selected eight evaluation factors to establish a suitability evaluation system for Z. schinifolium, used the analytic hierarchy process to determine the indicator, and determined the weight of the evaluation indicators. Besides, it calculated the comprehensive suitability index of land suitability of Z. schinifolium and evaluated the suitability of Z. schinifolium land in Jiaopingdu Town of Luquan County. The results showed that the suitable area for the cultivation of Z. schinifolium in Jiaopingdu Town reached 7 270.78 ha, accounting for 88.69 % of the study area; the area of unsuitable land was 922.07 ha, accounting for 11.31% of the study area. Among the suitable land areas, the high suitability area reached 562.99 ha, accounting for 7.79%; the moderate suitability area was 2 206.76 ha, accounting for 28.61%; the low suitability area was 4 599.03 ha, accounting for 63.6%. Based on the results of suitability evaluation, it came up with pertinent recommendations for the development of Z. schinifolium industry in Jiaopingdu Town.

The present work had the purpose of developing a class of terpolymer plugging microspheres for petroleum engineering. The terpolymer microspheres were prepared by dispersion copolymerization of acrylamide (AM), sodium 4-styrenesulfonate (SSS) and 2-acrylamido-2- methyl propane sulfonic acid (AMPS), using ethanol/deionized water as dispersion medium, polyvinyl pyrrolidone (PVP) as dispersant, N,N-methylenebisacrylamide (MBA) as crosslinking agent and potassium persulfate (KPS) as initiator. The influences of dispersion medium volume ratio, concentration of dispersant, pH value and stirring speed on the stability of dispersion system were investigated. The results showed that the stable dispersion system was obtained when ethanol-water ratio was 50:50 (v: v), the dispersant content was 15 wt. % (total mass of monomers), pH value was 7 and stirring speed was 200 r/min, which was suitable for ternary dispersion polymerization. FTIR spectrum and SEM images indicated the structure and surface morphology of microspheres.

Industrial poverty alleviation is the core of poverty alleviation in rural areas of China, and it is the fundamental way for the rural poor to achieve stable income and poverty alleviation. Laopingzi Village, Jiaopingdu Town, Luquan County, Kunming County, Yunnan Province, located in the dry-hot valley area of Jinsha River, has become a typical deep poverty-stricken village due to its special natural conditions. In recent years, in the battle to win the fight against poverty, the people of Laopingzi Village have achieved a virtuous cycle of the ecological environment and an access to get rid of poverty and get rich through vigorously developing green prickleyash planting industry. By the end of 2018, the incidence of poverty in Laopingzi Village Committee dropped from 45.62% in 2014 to 1.11%, and the green prickleyash planting industry had achieved remarkable results in poverty alleviation. This article summarizes the specific practices of developing the green prickleyash planting industry in the village, analyzes the main results and successful experiences of the mode and discusses the inspiration of the implementation of green prickleyash cultivation on industrial poverty alleviation, so as to provide an effective practical example for the development and poverty alleviation of poverty-stricken areas.

According to the mode of \" company ( Luquan Keyu Agricultural Science and Technology Products Development Co. , Ltd.$ + branch ( Laopingzi Village Committee $+ cooperative ( Laopingzi Green Prickleyash Plantng Farmer Specialized Cooperative$ + farmer ( 327 plantng households $ \" , the management mode of \" Jiaopingdu Brand Green Prickleyash\" + Internet management has gradually been formed to share Internet resources and build a platform for production and marketing of green prickleyash in Luquan County. 52% of the net household income of 34 386. [...]the income from green pėckleyash cultivation accounted for a large proportion of the household income of the poverty-stricken households, suggesting that the development of green pėckleyash planting industry plays an important role in poverty alleviation in Laopingzi Village, Jiaopingdu Town. [...]a single variety, without the suppoo of industrial chain, will cause many poverty alleviation project aborted%8&. [...]in order to develop industries in mountainous areas, it is necessary to take the market as the leading factor, integrate the effective resources, construct an integrated industrial chain of farming, feeding, processing and marketing and strengthen the integration of the primary, secondary and tertiary industries to complement each other, complement each other's functions, link up with each other, constantly create value and deliver benefits, which not only enhance the market's ability to resist risks but also create new jobs, increase employment opportunities and enrich the methods and channels of gaining profits. [...]we should improve the skills of the main body of poverty alleviation, be good at grasping the numerous opportunities brought by the current economic, social and ecological environment changes to the poverty alleviation model of \"Internet + agriculture\" and excavate potential opportunities %10 ] .