Design optimization of acoustic metamaterials and phononic crystals with a time domain method

A time-dependent adjoint approach for obtaining sensitivity derivatives for shape optimizations of acoustic metamaterials and phononic crystals is presented. The gradient-based design procedure is suitable for large numbers of design variables, and results are shown on achieving effective material properties with a unit cell and the broadband noise reduction with periodic arrays of cylinders. The acoustic wave propagation problem is solved in the time-domain using a Streamline Upwind/Petrov Galerkin formulation. Topology parameterization is accomplished using the homogenization method, and shape optimization is subsequently used afterwards to refine the geometries. Surface parameterization is accomplished using control grids, which are based on a Laplace equation. The combined strategy is compared with penalty-based topology optimization. Furthermore, the proposed topology optimization is also conducted on the design of a broadband acoustic cloaking device

Computational investigation of the effects of casing treatments on the performance of a turbofan

A computational survey focused on modifications to the casing near the rotor blade tip is carried out for the purpose of enhancing the performance and increasing the stall margin of a model turbofan stage in transonic operating conditions. The study is divided into three phases. During the first phase two types of casing treatments, inward protruding rings and circumferential grooves, were tested with relatively coarse grids. In the second phase, a grid resolution study is carried out with the results from this phase influencing the choices for the third stage. In the third phase, a comprehensive study is performed to examine the near-stall effects and stall-related behavior of the baseline case and a series of circumferential groove configurations

A Novel Evolution-Based Method for Detecting Gene-Gene Interactions

BACKGROUND: The rapid advance in large-scale SNP-chip technologies offers us great opportunities in elucidating the genetic basis of complex diseases. Methods for large-scale interactions analysis have been under development from several sources. Due to several difficult issues (e.g., sparseness of data in high dimensions and low replication or validation rate), development of fast, powerful and robust methods for detecting various forms of gene-gene interactions continues to be a challenging task. METHODOLOGY/PRINCIPAL FINDINGS: In this article, we have developed an evolution-based method to search for genome-wide epistasis in a case-control design. From an evolutionary perspective, we view that human diseases originate from ancient mutations and consider that the underlying genetic variants play a role in differentiating human population into the healthy and the diseased. Based on this concept, traditional evolutionary measure, fixation index (Fst) for two unlinked loci, which measures the genetic distance between populations, should be able to reveal the responsible genetic interplays for disease traits. To validate our proposal, we first investigated the theoretical distribution of Fst by using extensive simulations. Then, we explored its power for detecting gene-gene interactions via SNP markers, and compared it with the conventional Pearson Chi-square test, mutual information based test and linkage disequilibrium based test under several disease models. The proposed evolution-based method outperformed these compared methods in dominant and additive models, no matter what the disease allele frequencies were. However, its performance was relatively poor in a recessive model. Finally, we applied the proposed evolution-based method to analysis of a published dataset. Our results showed that the P value of the Fst -based statistic is smaller than those obtained by the LD-based statistic or Poisson regression models. CONCLUSIONS/SIGNIFICANCE: With rapidly growing large-scale genetic association studies, the proposed evolution-based method can be a promising tool in the identification of epistatic effects

One-shot Implicit Animatable Avatars with Model-based Priors

Existing neural rendering methods for creating human avatars typically either require dense input signals such as video or multi-view images, or leverage a learned prior from large-scale specific 3D human datasets such that reconstruction can be performed with sparse-view inputs. Most of these methods fail to achieve realistic reconstruction when only a single image is available. To enable the data-efficient creation of realistic animatable 3D humans, we propose ELICIT, a novel method for learning human-specific neural radiance fields from a single image. Inspired by the fact that humans can effortlessly estimate the body geometry and imagine full-body clothing from a single image, we leverage two priors in ELICIT: 3D geometry prior and visual semantic prior. Specifically, ELICIT utilizes the 3D body shape geometry prior from a skinned vertex-based template model (i.e., SMPL) and implements the visual clothing semantic prior with the CLIP-based pretrained models. Both priors are used to jointly guide the optimization for creating plausible content in the invisible areas. Taking advantage of the CLIP models, ELICIT can use text descriptions to generate text-conditioned unseen regions. In order to further improve visual details, we propose a segmentation-based sampling strategy that locally refines different parts of the avatar. Comprehensive evaluations on multiple popular benchmarks, including ZJU-MoCAP, Human3.6M, and DeepFashion, show that ELICIT has outperformed strong baseline methods of avatar creation when only a single image is available. The code is public for research purposes at https://huangyangyi.github.io/ELICIT/.Comment: To appear at ICCV 2023. Project website: https://huangyangyi.github.io/ELICIT

15-Deoxy-Δ 12,14

It has been reported that bone marrow-derived mesenchymal stem cells (BMSCs) have capacity to migrate to the damaged liver and contribute to fibrogenesis in chronic liver diseases. 15-Deoxy-Δ12,14-prostaglandin J2 (15d-PGJ2), an endogenous ligand for peroxisome proliferator-activated receptor gamma (PPARγ), is considered a new inhibitor of cell migration. However, the actions of 15d-PGJ2 on BMSC migration remain unknown. In this study, we investigated the effects of 15d-PGJ2 on the migration of BMSCs using a mouse model of chronic liver fibrosis and primary mouse BMSCs. Our results demonstrated that in vivo, 15d-PGJ2 administration inhibited the homing of BMSCs to injured liver by flow cytometric analysis and, in vitro, 15d-PGJ2 suppressed primary BMSC migration in a dose-dependent manner determined by Boyden chamber assay. Furthermore, the repressive effect of 15d-PGJ2 was blocked by reactive oxygen species (ROS) inhibitor, but not PPARγ antagonist, and action of 15d-PGJ2 was not reproduced by PPARγ synthetic ligands. In addition, 15d-PGJ2 triggered a significant ROS production and cytoskeletal remodeling in BMSCs. In conclusion, our results suggest that 15d-PGJ2 plays a crucial role in homing of BMSCs to the injured liver dependent on ROS production, independently of PPARγ, which may represent a new strategy in the treatment of liver fibrosis