High-performance time-series quantitative retrieval from satellite images on a GPU cluster

The quality and accuracy of remote sensing instruments continue to increase, allowing geoscientists to perform various quantitative retrieval applications to observe the geophysical variables of land, atmosphere, ocean, etc. The explosive growth of time-series remote sensing (RS) data over large-scales poses great challenges on managing, processing, and interpreting RS ‘‘Big Data.’’ To explore these time-series RS data efficiently, in this paper, we design and implement a high-performance framework to address the time-consuming time-series quantitative retrieval issue on a graphics processing unit cluster, taking the aerosol optical depth (AOD) retrieval from satellite images as a study case. The presented framework exploits the multilevel parallelism for time-series quantitative RS retrieval to promote efficiency. At the coarse-grained level of parallelism, the AOD time-series retrieval is represented as multidirected acyclic graph workflows and scheduled based on a list-based heuristic algorithm, heterogeneous earliest finish time, taking the idle slot and priorities of retrieval jobs into account. At the fine-grained level, the parallel strategies for the major remote sensing image processing algorithms divided into three categories, i.e., the point or pixel-based operations, the local operations, and the global or irregular operations have been summarized. The parallel framework was implemented with message passing interface and compute unified device architecture, and experimental results with the AOD retrieval case verify the effectiveness of the presented framework.N/

The Eighteenth Data Release of the Sloan Digital Sky Surveys: Targeting and First Spectra from SDSS-V

The eighteenth data release of the Sloan Digital Sky Surveys (SDSS) is the first one for SDSS-V, the fifth generation of the survey. SDSS-V comprises three primary scientific programs, or "Mappers": Milky Way Mapper (MWM), Black Hole Mapper (BHM), and Local Volume Mapper (LVM). This data release contains extensive targeting information for the two multi-object spectroscopy programs (MWM and BHM), including input catalogs and selection functions for their numerous scientific objectives. We describe the production of the targeting databases and their calibration- and scientifically-focused components. DR18 also includes ~25,000 new SDSS spectra and supplemental information for X-ray sources identified by eROSITA in its eFEDS field. We present updates to some of the SDSS software pipelines and preview changes anticipated for DR19. We also describe three value-added catalogs (VACs) based on SDSS-IV data that have been published since DR17, and one VAC based on the SDSS-V data in the eFEDS field.Comment: Accepted to ApJ

The eighteenth data release of the Sloan Digital Sky Surveys : targeting and first spectra from SDSS-V

The eighteenth data release of the Sloan Digital Sky Surveys (SDSS) is the first one for SDSS-V, the fifth generation of the survey. SDSS-V comprises three primary scientific programs, or "Mappers": Milky Way Mapper (MWM), Black Hole Mapper (BHM), and Local Volume Mapper (LVM). This data release contains extensive targeting information for the two multi-object spectroscopy programs (MWM and BHM), including input catalogs and selection functions for their numerous scientific objectives. We describe the production of the targeting databases and their calibration- and scientifically-focused components. DR18 also includes ~25,000 new SDSS spectra and supplemental information for X-ray sources identified by eROSITA in its eFEDS field. We present updates to some of the SDSS software pipelines and preview changes anticipated for DR19. We also describe three value-added catalogs (VACs) based on SDSS-IV data that have been published since DR17, and one VAC based on the SDSS-V data in the eFEDS field.Publisher PDFPeer reviewe

Non-coding RNA-mediated modulation of ferroptosis in cardiovascular diseases

Cardiovascular disease (CVD) is a major contributor to increasing morbidity and mortality worldwide and seriously threatens human health and life. Cardiomyocyte death is considered the pathological basis of various CVDs, including myocardial infarction, heart failure, and aortic dissection. Multiple mechanisms, such as ferroptosis, necrosis, and apoptosis, contribute to cardiomyocyte death. Among them, ferroptosis is an iron-dependent form of programmed cell death that plays a vital role in various physiological and pathological processes, from development and aging to immunity and CVD. The dysregulation of ferroptosis has been shown to be closely associated with CVD progression, yet its underlying mechanisms are still not fully understood. In recent years, a growing amount of evidence suggests that non-coding RNAs (ncRNAs), particularly microRNAs, long non-coding RNAs, and circular RNAs, are involved in the regulation of ferroptosis, thus affecting CVD progression. Some ncRNAs also exhibit potential value as biomarker and/or therapeutic target for patients with CVD. In this review, we systematically summarize recent findings on the underlying mechanisms of ncRNAs involved in ferroptosis regulation and their role in CVD progression. We also focus on their clinical applications as diagnostic and prognostic biomarkers as well as therapeutic targets in CVD treatment. Data availability: No new data were created or analyzed in this study. Data sharing is not applicable to this article

Construction of sea surface current vectors using a single HF radar: A theoretical study

Summary: A technique called the stream and potential function method (SPFM) is presented to retrieve the sea surface current vector field from the radial-component measurements of only one high-frequency (HF) radar. SPFM estimates the surface current vector field jointly based on hydrodynamic constraints and a two-dimensional (2D) ocean current model. The current vector field is assumed to comprise two parts: nondivergent vortex flow and irrotational divergent flow; this guarantees that both the stream function and the potential function are considered. Physically, SPFM is embedded in a more physically consistent hydrodynamic framework that enables the spatiotemporal distribution characteristics of the current vector field at the sea surface to be effectively captured by a single HF radar. The evaluation of SPFM with HYCOM surface current dataset verifies that this approach is more reliable than the stream function method (SFM)

Designing the composition and optimizing the mechanical properties of non-equiatomic FeCoNiTi high-entropy alloys

Research into new high-entropy alloys (HEAs) holds significant promise for advancing aerospace materials. Nevertheless, the complexity of their composition presents formidable challenges in designing HEAs with both high strength and plasticity. In this study, molecular dynamics (MD) simulation was used to explore the optimal composition combination of FeCoNiTi high-entropy alloys with non-equiatomic ratios. Shear modulus (G) characterizes strength, while stacking fault energy (SFE) characterizes plasticity and ductility. Through molecular dynamics (MD) simulations, elastic constants (C11, C12, and C44) and generalized stacking fault energies (GSFEs) for 18 alloy variants were computed. Additionally, the elastic modulus (G, E, and B) for all components was estimated using the Voigt–Reuss–Hill (VRH) averaging method. Following standard guidelines, the composition for the FeCoNiTi alloy was predicted as Ni: 30%–60 %, Co: 30%–50 %, Fe: 5%–10 %, and Ti: 5%–10 %. Subsequently, five optimized variants underwent tensile calculations to identify the most suitable composition. The results indicate that the Fe0.05Co0.4Ni0.5Ti0.05 HEA exhibits the best combination of strength and plasticity. Microscopically, its enhanced plasticity is attributed to the twinning-induced plasticity (TWIP) effect. While Fe0.1Co0.4Ni0.4Ti0.1 HEA does not outperform the other variants, it displays a martensitic transformation and deformation twins with increased strain, which are mechanisms not observed in other components. The study of non-equiatomic FeCoNiTi HEAs offers a theoretical foundation for future alloy development. This innovative alloy design method fosters the rapid development of high-performance HEAs, facilitating their rapid development and application

GSDME in Endothelial Cells: Inducing Vascular Inflammation and Atherosclerosis via Mitochondrial Damage and STING Pathway Activation

The initiation of atherosclerotic plaque is characterized by endothelial cell inflammation. In light of gasdermin E’s (GSDME) role in pyroptosis and inflammation, this study elucidates its function in atherosclerosis onset. Employing Gsdme- and apolipoprotein E-deficient (Gsdme−/−/ApoE−/−) and ApoE−/− mice, an atherosclerosis model was created on a Western diet (WD). In vitro examinations with human umbilical vein endothelial cells (HUVECs) included oxidized low-density lipoprotein (ox-LDL) exposure. To explore the downstream mechanisms linked to GSDME, we utilized an agonist targeting the stimulator of the interferon genes (STING) pathway. The results showed significant GSDME activation in ApoE−/− mice arterial tissues, corresponding with atherogenesis. Gsdme−/−/ApoE−/− mice displayed fewer plaques and decreased vascular inflammation. Meanwhile, GSDME’s presence was confirmed in endothelial cells. GSDME inhibition reduced the endothelial inflammation induced by ox-LDL. GSDME was linked to mitochondrial damage in endothelial cells, leading to an increase in cytoplasmic double-stranded DNA (dsDNA). Notably, STING activation partially offset the effects of GSDME inhibition in both in vivo and in vitro settings. Our findings underscore the pivotal role of GSDME in endothelial cells during atherogenesis and vascular inflammation, highlighting its influence on mitochondrial damage and the STING pathway, suggesting a potential therapeutic target for vascular pathologies

Variations in the Intestinal Microbiota of the Chinese Soft-Shelled Turtle (<i>Trionyx sinensis</i>) between Greenhouse and Pond Aquaculture

The microbial community structure in aquaculture water plays an important role in the intestinal microbial diversity of aquatic animals. The Chinese soft-shelled turtle (SST) (Trionyx sinensis) is an important aquaculture species of high economic value in the Asia-Pacific region. An intuitive understanding of the microbial diversity and abundances of SST aquaculture is crucial for comprehending these ecosystems. Herein, the evolutionary characteristics of the bacterial communities in the SST and its aquaculture water systems were investigated using Illumina MiSeq sequencing. This experiment sampled nine SSTs from a pond outside a greenhouse and was repeated three times. The sequencing results revealed significant differences in the microflora composition at the phylum and genus levels in both the intestine and aquaculture water of the SSTs in the greenhouse and pond aquaculture environments. A total of 1039 genera belonging to 65 phyla were identified. At the phylum level, the relative abundances of Chloroflexi (24%), Acidobacteria (5%), and Nitrospira (3%) were higher in the greenhouse water than in the pond water. The relative abundances of Bacteroidetes (35%), Actinobacteria (8%), and Cyanobacteria (4%) were higher in the pond water than in the greenhouse water. The intestinal microorganisms in the SSTs experienced significant changes after the SSTs were transferred from a greenhouse culture to a pond culture environment for 28 days. After the SSTs were cultured in the ponds, we observed decreases in the relative abundances of Actinobacteria (39% to 25%), Cyanobacteria (24% to 0.8%), Chlorobacteria (9% to 3%), and Firmicutes (5.5% to 0.8%. However, we observed increases in the relative abundances of Bacteroidetes (2% to 35%) and Acidobacteria (0.3% to 25%). These results showed that the bacterial diversity and richness compositions in the intestinal tract and aquaculture water were the same. However, the relative abundances of bacterial communities varied. The results of this study are of great significance in understanding how the environment affects SST cultures. These data may provide valuable instructions for Chinese soft-shelled turtle aquaculture management

The Identification and Validation of Hub Genes Associated with Acute Myocardial Infarction Using Weighted Gene Co-Expression Network Analysis

Acute myocardial infarction (AMI), one of the most severe and fatal cardiovascular diseases, remains the main cause of mortality and morbidity worldwide. The objective of this study is to investigate the potential biomarkers for AMI based on bioinformatics analysis. A total of 2102 differentially expressed genes (DEGs) were screened out from the data obtained from the gene expression omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) explored the co-expression network of DEGs and determined the key module. The brown module was selected as the key one correlated with AMI. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses demonstrated that genes in the brown module were mainly enriched in ‘ribosomal subunit’ and ‘Ribosome’. Gene Set Enrichment Analysis revealed that ‘TNFA_SIGNALING_VIA_NFKB’ was remarkably enriched in AMI. Based on the protein–protein interaction network, ribosomal protein L9 (RPL9) and ribosomal protein L26 (RPL26) were identified as the hub genes. Additionally, the polymerase chain reaction (PCR) results indicated that the expression levels of RPL9 and RPL26 were both downregulated in AMI patients compared with controls, in accordance with the bioinformatics analysis. In summary, the identified DEGs, modules, pathways, and hub genes provide clues and shed light on the potential molecular mechanisms of AMI