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The digital economy, as a new economic form with high information density, provides a new driving force for the realization of high-quality agricultural development. Panel data of 31 provinces in China from 2011 to 2020 were selected for analysis. The static panel data interaction effect model and panel threshold model were used to verify the nonlinear influence mechanism and heterogeneity of financial development in the process of the digital economy affecting high-quality agricultural development. The findings are as follows. (1) During the study period, the high-quality development of China's agriculture showed a steady upward trend; however, the regional differences were significant, and the eastern part was larger than the central and western part. (2) The digital economy can promote high-quality agricultural development. (3) The digital economy has a double threshold effect in the process of affecting high-quality agricultural development, which depends on the level of financial development. When the threshold is exceeded, the digital economy has a more significant promoting effect on high-quality agricultural development. (4) The impact of the digital economy on high-quality agricultural development is heterogeneous. From the perspective of different regions, the impact effect is greatest in the eastern region, while the effect is smaller in the central and western regions. From different resource endowments, the positive impact effect is greatest in the major grain-selling areas, followed by the major grain producing areas, but the positive digital economy driving effect is not significant in the balance of production and sales areas. Finally, three policy suggestions are proposed. First, the Chinese government should increase investments in and support for digital technology to promote the integration of the digital economy and agriculture. Second, the Chinese government should promote the development of digital inclusive finance in areas with financial development below the threshold. Third, different regions should implement differentiated digital economies to promote high-quality agricultural development. [ABSTRACT FROM AUTHOR]

Seasonal frozen soil is widely distributed in China. The seasonal freeze-thaw (F-T) process of soil will adversely affect the safety and service life of the engineering structures in these areas. Therefore, it is necessary to thoroughly study the main factors affecting the F-T process of soil and prevent or control F-T damage. This study first briefly introduces the distribution of seasonal frozen soil in China and the damage of soil after F-T. Then, on the one hand, it discusses the influencing trends of soil properties after freeze-thaw cycles (FTC) based on the different soil structure, compaction degree, moisture content, freezing temperature, and FTC times. On the other hand, it analyzes the present major project prevention and control measures to the damage of soils subjected to the F-T. This study highlights the positive effect of soil reinforcement on improving soil mechanical properties and reducing F-T destruction to the soil construction. Finally, it prospects the optimal reinforcement methods for all kinds of soils during different F-T conditions based on further theoretical research and practical experience. [ABSTRACT FROM AUTHOR]

Background: Early diagnosis and treatment effectiveness of early-onset coronary artery disease (EOCAD) are crucial, and non-invasive predictive biomarkers are needed for young adults. We aimed to evaluate the usefulness of the triglyceride-glucose (TyG) index, a novel marker of insulin resistance, in identifying young CAD patients and predicting their risk of developing target lesion failure (TLF). Methods: We recruited EOCAD patients (luminal narrowing ≥ 70%) and controls free from CAD (luminal narrowing < 30%), both aged 45 years or younger, from 38 hospitals in China between 2017 and 2020. EOCAD patients who underwent successful percutaneous coronary intervention were followed for incident TLF. TyG index was defined as Ln [fasting triglyceride (mg/dL) × fasting blood glucose (mg/dL)/2]. We used logistic regression and Cox proportional hazards modeling to evaluate the association of TyG index with prevalent EOCAD and incident TLF, respectively. The discriminatory ability of TyG index was assessed by the area under the receiver-operating characteristic curve (AUC). Results: Among the included 1513 EOCAD patients (39.6 ± 4.4 years, 95.4% male) and 1513 age-matched controls (39.0 ± 4.4 years, 46.4% male), TyG index was positively associated with the prevalence of EOCAD (adjusted odds ratio: 1.40, 95% confidence interval [CI] 1.23–1.60, per standard deviation [SD] increase in TyG index). The addition of TyG index to an empirical risk model provided an improvement in diagnostic ability for EOCAD, with a net reclassification improvement of 0.10 (95% CI 0.03–0.17, p = 0.005). During a medium of 33 month (IQR: 31–34 months) follow-up, 43 (3.3%) patients experienced TLF. Multivariate Cox regression model revealed that TyG index was an independent risk factor for TLF (adjusted hazard ratio [HR]: 2.410, 95% CI 1.07–5.42 comparing the top to bottom TyG index tertile groups; HR: 1.30, 95% CI 1.01–1.73, per SD increase in TyG index). Compared with a model of conventional risk factors alone, the addition of the TyG index modestly improved the AUC (0.722–0.734, p = 0.04) to predict TLF. Conclusions: TyG index is positively associated with prevalent EOCAD and incident TLF. TyG index appeared to be a valuable component of future efforts to improve CAD risk stratification and TLF outcome prediction among young adults. [ABSTRACT FROM AUTHOR]

Land surface reflectance (LSR) data form the basis of quantitatively remotely sensed applications. For accurate LSR retrieval, atmospheric correction has been investigated by many researchers and implemented in typical processing systems, including common atmospheric correction software for various types of datasets and automatic operating systems for application to certain individual data sources. In recent years, China has launched multiple medium–high-resolution satellites but has not provided standard LSR products partly because of the lack of an appropriate operational system. In this paper, a multi-source remote sensing LSR product system for medium- and high-resolution data is proposed, called the "Operational Atmospheric Correction Framework for multi-source Medium-high-resolution Remote Sensing data of China" (ACFrC). The AC algorithm, processing flow, and design of the multi-source LSR system were described in detail. A practical atmospheric correction algorithm was proposed specially for data in only the visible and near-infrared (VNIR) bands. The entire processing chain was divided into modules for multi-source data ingestion, apparent reflectance calculation, cloud and water identification, atmospheric correction, and standard LSR product generation. To date, most types of multi-source data have been tested using the ACFrC system, with reasonable results being obtained. From the preliminary results, the 313 scenes of LSR products from the GaoFen-2 (GF-2) satellite over China for the period from 2015 to 2018 were cross-compared with Landsat-8 LSR acquired on the same day, showing an overall uncertainty less than 0.112 × LSR + 0.0112. Further, the ACFrC data processing efficiency was found to be suitable for automatic operation. System improvement is ongoing and future refinements will include online cloud parallel computing functionality and services, more robust algorithms, and other radiometric processing functions. [ABSTRACT FROM AUTHOR]

Background: Prunus pedunculata Pall, the deciduous shrub of Amygdalus subgenus in Rosaceae, is a new kind of desert oil-bearing tree. It has a long story of being planted in the West and North of China for sand fixation and desert control. In addition, the seeds of P. pedunculata are rich of oil, especially the monounsaturated fatty acid and polyunsaturated fatty acid. However, little is known about the molecular mechanisms of oil accumulation during the seed development of P. pedunculata. Results: The seeds of P. pedunculata from three independent plants at 10, 18, 24, 31, 39, 45, 59 and 73 days after flowering (DAF) were obtained and the oil compositions were evaluated. It showed that oleic acid was the dominant type of oil content in the mature seeds (from 32.724% at 10DAF to 72.06% at 73DAF). Next, transcriptome sequencing for the developing seeds produced 988.795 million high quality reads and TRINITY assembled 326,271 genes for the first transcriptome for P. pedunculata. After the assembled transcriptome was evaluated by BUSCO with 85.9% completeness, we identified 195,342, 109,850 and 121,897 P. pedunculata genes aligned to NR, GO and KEGG pathway databases, respectively. Then, we predicted 23,229 likely proteins from the assembled transcriptome and identified 1917 signal peptides and 5512 transmembrane related proteins. In the developing seeds we detected 91,362 genes (average FPKM > 5) and correlation analysis indicated three possible development stages – early (10 ~ 24DAF), middle (31 ~ 45DAF) and late (59 ~ 73DAF). We next analyzed the differentially expressed genes (DEGs) in the developing seeds. Interestingly, compared to 10DAF the number of DEGs was increased from 4406 in 18DAF to 27,623 in 73DAF. Based on the gene annotation, we identified 753, 33, 8 and 645 DEGs related to the fatty acid biosynthesis, lipid biosynthesis, oil body and transcription factors. Notably, GPAT, DGD1, LACS2, UBC and RINO were highly expressed at the early development stage, ω6-FAD, SAD, ACP, ACCA and AHG1 were highly expressed at the middle development stage, and LACS6, DGD1, ACAT1, AGPAT, WSD1, EGY2 and oleosin genes were highly expressed at the late development stage. Conclusions: This is the first time to study the developing seed transcriptome of P. pedunculata and our findings will provide a valuable resource for future studies. More importantly, it will improve our understanding of molecular mechanisms of oil accumulation in P. pedunculata. [ABSTRACT FROM AUTHOR]