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The atmospheric weighted mean temperature (Tm) is a key parameter in global navigation satellite system (GNSS) water vapor retrieval and can convert the zenith wet delay (ZWD) into precipitable water vapor (PWV). However, there are some shortcomings in the existing Tm models, such as the detailed time-varying lapse rate not being considered. Additionally, the spatiotemporal characteristics of Tm need to be further refined. Therefore, we developed a new global high-precision and high-spatiotemporal-resolution Tm model considering time-varying lapse rate using the latest European Centre for Medium-Range Weather Forecasts ReAnalysis 5 (ERA5) atmospheric reanalysis data. Firstly, a global multidimensional Tm lapse rate model (NGGTm-H model) was developed using the sliding window algorithm. Secondly, the daily variation characteristics of Tm and its relationships with geographical situation were investigated. Finally, a hybrid-grid global Tm model considering time-varying lapse rate (NGGTm model) was developed. To verify the effectiveness of the proposed model, the NGGTm model was compared with the Bevis and GPT3 models using the Tm data recorded at 378 radiosonde stations in 2017 and the surface grid Tm data calculated from the ERA5 reanalysis data. The results show that taking the surface grid Tm data of ERA5 as reference values, the average root mean square error (RMSE) value predicted by the NGGTm model was 2.84 K, which was higher with 0.50 K, 0.18 K and 0.06 K than those of the Bevis, GPT3-5 and GPT3-1 models, respectively. Meanwhile, taking the Tm data from the radiosonde stations as the reference values, the mean bias and RMSE of the NGGTm model were 0.10 K and 3.30 K, respectively, which exhibit the best accuracy and stability among the Bevis, GPT3-5 and GPT3-1 models. [ABSTRACT FROM AUTHOR]

Cotton holds a significant position among cash crops in China, with Xinjiang serving as the primary cotton‐growing region within the country. Agricultural practices involving plastic mulching have gained importance. However, the presence of residual plastic film affects the growth of cotton seedlings as well as the soil environment. Our study aimed to explore the impact of residual plastic film accumulation on the growth of cotton seedlings and the associated soil water‐salt environment. This was done through a barrel planting experiment, utilizing soil from cotton fields with varying durations of mulching. The study showed that when the mulching period exceeded 12 years (residual plastic film content of 260.77 kg hm−2), residual plastic film had a significant impact on cotton seedling growth and the soil environment. Residual plastic film reduces the seedling germination rate of cotton by up to 11.11% (7 days after irrigation, 15 years of film mulching, residual plastic film content of 309.88 kg hm−2). It also impedes the growth of cotton seedlings; plant height, stem thickness, and leaf area were reduced by 34.52%, 10.73%, and 37.18%, respectively (19 days after irrigation, 15 years of film mulching, residual plastic film content of 309.88 kg·hm−2). Compared with the treatment without residual plastic film, the shallow soil water content in the T5 treatment decreased by 1.19% (10 days after irrigation, 15 years of film mulching, residual plastic film content of 309.88 kg·hm−2). Residual plastic film in cotton fields subjected to long‐term mulching obstructs the normal growth and development of cotton seedlings while also impacting the transport of soil water and salt. Therefore, we recommend adopting biodegradable mulch or regularly recycling residual plastic film within mulched areas to prevent its accumulation and subsequent negative impacts. [ABSTRACT FROM AUTHOR]

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SUMMARY: As a maternal tissue, the pericarp supports and protects for other components of seed, such as embryo and endosperm. Despite the importance of maize pericarp in seed, the genome‐wide transcriptome pattern throughout maize pericarp development has not been well characterized. Here, we developed RNA‐seq transcriptome atlas of B73 maize pericarp development based on 21 samples from 5 days before fertilization (DBP5) to 32 days after fertilization (DAP32). A total of 25 346 genes were detected in programming pericarp development, including 1887 transcription factors (TFs). Together with pericarp morphological changes, the global clustering of gene expression revealed four developmental stages: undeveloped, thickening, expansion and strengthening. Coexpression analysis provided further insights on key regulators in functional transition of four developmental stages. Combined with non‐seed, embryo, endosperm, and nucellus transcriptome data, we identified 598 pericarp‐specific genes, including 75 TFs, which could elucidate key mechanisms and regulatory networks of pericarp development. Cell wall related genes were identified that reflected their crucial role in the maize pericarp structure building. In addition, key maternal proteases or TFs related with programmed cell death (PCD) were proposed, suggesting PCD in the maize pericarp was mediated by vacuolar processing enzymes (VPE), and jasmonic acid (JA) and ethylene‐related pathways. The dynamic transcriptome atlas provides a valuable resource for unraveling the genetic control of maize pericarp development. Significance Statement: This study provides a high temporal resolution transcriptome atlas for unraveling the genetic control of maize pericarp development. [ABSTRACT FROM AUTHOR]

Flywheel energy storage technology has attracted more and more attention in the energy storage industry due to its high energy density, fast charge and discharge speed, long service life, clean and pollution-free characteristics. It is wwidely used in uninterruptible power system, grid frequency modulation, energy recovery and reuse and other fields. With the development of flywheel rotor materials, motors, bearings and control technology, flywheel energy storage technology has been greatly developed. Introducing the basic structure of the flywheel energy storage system in the above three applications. Typical charge-discharge control strategies are given for the three sensor-less algorithms of model reference adaptive control, sliding mode observer andextended Kalman filter, which are suitable for flywheel energy storage devices.