245 research outputs found
Improvement of LCM model and determination of model parameters at watershed scale for flood events in Hongde Basin of China
No full textConsidering the fact that the original two-parameter LCM model can only be used to investigate rainfall losses during the runoff period because the initial abstraction is not included, the LCM model was redefined as a three-parameter model, including the initial abstraction coefficient λ, the initial abstraction Ia, and the rainfall loss coefficient R. The improved LCM model is superior to the original two-parameter model, which only includes r and R, where r is the initial rainfall loss index and can be calculated with λ using the Soil Conservation Service curve number (SCS-CN) method, with r=1/(1+λ). The trial method was used to determine the parameter values of the improved LCM model at the watershed scale for 15 flood events in the Hongde Basin in China. The results show that larger r values are associated with smaller R values, and the parameter R ranges widely from 0.5 to 2.0. In order to improve the practicability of the LCM model, r=0.833 with λ=0.2 is reasonable for simplifying calculation. When the LCM model is applied to arid and semi-arid regions, rainfall without yielding runoff should be deducted from the total rainfall for more accurate estimation of rainfall-runoff
locus appears to play a pivotal role in a variety of cancers
No full textDeutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/50110000165
An ocean wave simulation method using Ansys Fluent
No full textOcean wave has been a hot topic of research since the nineteenth century. CFD became a powerful tool in the recent years in understanding the wave behavior and helped researchers to conduct preliminary study. Although a lot of work has been done on oceanic application using wave simulation method, some of these applications are already in the commercial stage, but little work can be found detailing a standard, accurate and yet not too complicated way to simulate wave with a reasonable generality. In this study the author proposed a method using Ansys Fluent to simulate ocean waves at full range of water depth, wave length and wave amplitude, utilizing Airy linear wave, Stokes 2nd order wave and Cnoidal wave. The method enables researchers to simulate waves with expected characteristics efficiently.Bachelor of Engineering (Aerospace Engineering
Identification of Prognostic Genes Related to Cell Senescence and Lipid Metabolism in Glioblastoma Based on Transcriptome and Single-Cell RNA-Seq Data
No full textGlioblastoma (GBM) is the most aggressive primary brain cancer, with poor prognosis due to its aggressive behavior and high heterogeneity. This study aimed to identify cellular senescence (CS) and lipid metabolism (LM)-related prognostic genes to improve GBM prognosis and treatment. Transcriptome and scRNA-seq data, CS-associated genes (CSAGs), and LM-related genes (LMRGs) were acquired from public databases. Prognostic genes were identified by intersecting CSAGs, LMRGs, and differentially expressed genes (DEGs), followed by WGCNA and univariate Cox regression. A risk model and nomogram were constructed. Analyses covered clinicopathological features, immune microenvironment, somatic mutations, and drug sensitivity. GBM scRNA-seq data identified key cells and prognostic gene expression. SOCS1 and PHB2 were identified as prognostic markers, contributing to the construction of a robust risk model with excellent predictive ability. High-risk group (HRG) patients had poorer survival, higher immune and stromal scores, and distinct somatic mutation profiles. Drug sensitivity analysis revealed significant differences in IC50 values. In microglia differentiation, SOCS1 and PHB2 showed dynamic expression patterns. These findings provide new strategies for GBM prognosis and treatment
Investigating the Prognostic Role of Telomerase-Related Cellular Senescence Gene Signatures in Breast Cancer Using Machine Learning
No full textBackground: Telomeres and cellular senescence are critical biological processes implicated in cancer development and progression, including breast cancer, through their influence on genomic stability and modulation of the tumor microenvironment. Methods: This study integrated bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) data to establish a gene signature associated with telomere maintenance and cellular senescence for prognostic prediction in breast cancer. Telomere-related genes (TEGs) and senescence-associated genes were curated from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A comprehensive machine learning framework incorporating 101 algorithmic combinations across 10 survival modeling approaches, including random survival forests and ridge regression, was employed to develop a robust prognostic model. Results: A set of 19 key telomere- and senescence-related genes was identified as the optimal prognostic signature. The model demonstrated strong predictive accuracy and was successfully validated in multiple independent cohorts. Functional enrichment analyses indicated significant associations with immune responses and aging-related pathways. Single-cell transcriptomic analysis revealed marked cellular heterogeneity, identifying distinct subpopulations (fibroblasts and immune cells) with divergent risk scores and biological pathway activity. Additionally, pseudo-time trajectory analysis and intercellular communication mapping provided insights into the dynamic evolution of the tumor microenvironment. Immunohistochemical (IHC) validation using data from the Human Protein Atlas confirmed differential protein expression between normal and tumor tissues for several of the selected genes, reinforcing their biological relevance and clinical utility. Conclusions: This study presents a novel 19-gene telomere- and senescence-associated signature with strong prognostic value in breast cancer. These findings enhance our understanding of tumor heterogeneity and may inform precision oncology approaches and future therapeutic strategies
Algebraic Anisotropic Eddy Viscosity Model for Separated Flows of Internal Cooling Channels
No full textA new algebraic anisotropic eddy viscosity model (AEVM) is developed to account for the anisotropic characteristics of flow fields for internal cooling channels in a gas turbine. The model consist of two parts: k and å near wall modeling are improved to obtain precise near wall turbulent characteristics and eddy viscosity; anisotropic ratios are derived to account for anisotropy and further modify the normal Reynolds stresses by combining implicit algebraic stress model and isotropic eddy viscosity model. The new algebraic anisotropic eddy viscosity model is validated in two cases: 1) flow prediction of backward facing step, better results are obtained especially turbulent quantities, 2) flow and heat transfer predictions of internal channels with ribs, numerical reattachment length after each rib is more close to the measured value after anisotropic modification, and heat transfer prediction accuracy is increased by 6-10%. Results indicate the present model can be applied to flow and heat transfer prediction of separated flows in internal cooling channels efficiently.</p
Preparation of <em>Drosophila</em> Larval Samples for Gas Chromatography-Mass Spectrometry (GC-MS)-based Metabolomics
No full textQuantification of d- and l-2-Hydroxyglutarate in Drosophila melanogaster Tissue Samples Using Gas Chromatography-Mass Spectrometry
No full textLarge eddy simulation of compound angle hole film cooling with hole length-to-diameter ratio and internal crossflow orientation effects
No full textCompound angle hole film cooling with varying length-to-diameter ratio and internal crossflow orientations is investigated by large eddy simulation (LES). The film density ratio is 1.5, and the blowing ratio ranges from 0.4 to 1.2. The compound angle of 45° and three length-to-diameter ratios (L/D) from 0.5 to 5 are chosen for the simulations. In addition to the vertical inflow through the plenum, internal crossflow orientations that are perpendicular to and parallel to the mainstream flow are investigated. The prediction accuracy is validated by the reported hydrodynamic data and present film effectiveness data measured by pressure sensitive paint (PSP). Results show that compound angle hole film effectiveness generally shows a decreasing trend as length-to-diameter ratio increases, which is contrary to the cylindrical hole. This is associated with the fact that length-to-diameter ratio influences the in-tube flow behavior, formation of Kelvin-Helmholtz (K-H) structures, and development of single asymmetric main vortex (SAMV). The internal crossflow orientation is demonstrated to have a significant effect on the in-tube flow behavior and the film cooling effectiveness. The perpendicular-counter flow and parallel-inline flow cases are found to provide more uniform hole exit velocity distributions than other internal crossflow orientations and vertical inflow case. Also found is that uniform hole exit velocity distribution provides favorable influence on the film effectiveness.</p
- …
