Stochastic gravitational wave background from the collisions of dark matter halos

We investigate the effect of the dark matter (DM) halos collisions, namely collisions of galaxies and galaxy clusters, through gravitational bremsstrahlung, on the stochastic gravitational wave background. We first calculate the gravitational wave signal of a single collision event, assuming point masses and linear perturbation theory. Then we proceed to the calculation of the energy spectrum of the collective effect of all dark matter collisions in the Universe. Concerning the DM halo collision rate, we show that it is given by the product of the number density of DM halos, which is calculated by the extended Press-Schechter (EPS) theory, with the collision rate of a single DM halo, which is given by simulation results, with a function of the linear growth rate of matter density through cosmological evolution. Hence, integrating over all mass and distance ranges, we finally extract the spectrum of the stochastic gravitational wave background created by DM halos collisions. As we show, the resulting contribution to the stochastic gravitational wave background is of the order of $h_{c} \approx 10^{-29}$ in the band of $f \approx 10^{-15} Hz$. However, in very low frequency band, it is larger. With current observational sensitivity it cannot be detected.Comment: 11 pages,4 figure

Integrating scRNA and bulk-RNA sequencing develops a cell senescence signature for analyzing tumor heterogeneity in clear cell renal cell carcinoma

IntroductionCellular senescence (CS) plays a critical role in cancer development, including clear cell renal cell carcinoma (ccRCC). Traditional RNA sequencing cannot detect precise molecular composition changes within tumors. This study aimed to analyze cellular senescence’s biochemical characteristics in ccRCC using single RNA sequencing (ScRNA-seq) and traditional RNA sequencing (Bulk RNA-seq).MethodsResearchers analyzed the biochemical characteristics of cellular senescence in ccRCC using ScRNA-seq and Bulk RNA-seq. They combined these approaches to identify differences between malignant and non-malignant phenotypes in ccRCC across three senescence-related pathways. Genes from these pathways were used to identify molecular subtypes associated with senescence, and a new risk model was constructed. The function of the gene DUSP1 in ccRCC was validated through biological experiments.ResultsThe combined analysis of ScRNA-seq and Bulk RNA-seq revealed significant differences between malignant and non-malignant phenotypes in ccRCC across three senescence-related pathways. Researchers identified genes from these pathways to identify molecular subtypes associated with senescence, constructing a new risk model. Different subgroups showed significant differences in prognosis level, clinical stage and grade, immune infiltration, immunotherapy, and drug sensitivity.DiscussionSenescence signature markers are practical biomarkers and predictors of molecular typing in ccRCC. Differences in prognosis level, clinical stage and grade, immune infiltration, immunotherapy, and drug sensitivity between different subgroups indicate that this approach could provide valuable insights into senescence-related treatment options and prognostic assessment for patients with ccRCC. The function of the gene DUSP1 in ccRCC was validated through biological experiments, confirming its feasibility as a novel biomarker for ccRCC. These findings suggest that targeted therapies based on senescence-related mechanisms could be an effective treatment option for ccRCC

An immersogeometric formulation for free-surface flows with application to marine engineering problems

An immersogeometric formulation is proposed to simulate free-surface flows around structures with complex geometry. The fluid–fluid interface (air–water interface) is handled by the level set method, while the fluid–structure interface is handled through an immersogeometric approach by immersing structures into non-boundary-fitted meshes and enforcing Dirichlet boundary conditions weakly. Residual-based variational multiscale method (RBVMS) is employed to stabilize the coupled Navier–Stokes equations of incompressible flows and level set convection equation. Other level set techniques, including re-distancing and mass balancing, are also incorporated into the immersed formulation. Adaptive quadrature rule is used to better capture the geometry of the immersed structure boundary by accurately integrating the intersected background elements. Generalized-α role= presentation style= box-sizing: border-box; margin: 0px; padding: 0px; display: inline-block; line-height: normal; font-size: 16.2px; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; max-height: none; min-width: 0px; min-height: 0px; border: 0px; position: relative; \u3eα method is adopted for time integration, which results in a two-stage predictor multi-corrector algorithm. GMRES solver preconditioned with block Jacobian matrices of individual fluid and level set subproblems is used for solving the coupled linear systems arising from the multi-corrector stage. The capability and accuracy of the proposed method are assessed by simulating three challenging marine engineering problems, which are a solitary wave impacting a stationary platform, dam break with an obstacle, and planing of a DTMB 5415 ship model. A refinement study is performed. The predictions of key quantities of interest by the proposed formulation are in good agreement with experimental results and boundary-fitted simulation results from others. The proposed formulation has great potential for wide applications in marine engineering problems

Normative Analysis of Individual Brain Differences Based on a Population MRI-Based Atlas of Cynomolgus Macaques

The developmental trajectory of the primate brain varies substantially with aging across subjects. However, this ubiquitous variability between individuals in brain structure is difficult to quantify and has thus essentially been ignored. Based on a large-scale structural magnetic resonance imaging dataset acquired from 162 cynomolgus macaques, we create a species-specific 3D template atlas of the macaque brain, and deploy normative modeling to characterize individual variations of cortical thickness (CT) and regional gray matter volume (GMV). We observed an overall decrease in total GMV and mean CT, and an increase in white matter volume from juvenile to early adult. Specifically, CT and regional GMV were greater in prefrontal and temporal cortices relative to early unimodal areas. Age-dependent trajectories of thickness and volume for each cortical region revealed an increase in the medial temporal lobe, and decreases in all other regions. A low percentage of highly individualized deviations of CT and GMV were identified (0.0021%, 0.0043%, respectively, P \u3c 0.05, false discovery rate [FDR]-corrected). Our approach provides a natural framework to parse individual neuroanatomical differences for use as a reference standard in macaque brain research, potentially enabling inferences regarding the degree to which behavioral or symptomatic variables map onto brain structure in future disease studies