Particle bonding mechanism in CGDS-a three-dimensional approach

Abstract: Cold gas dynamics spray (CGDS) is a surface coating process using highly accelerated particles to form the surface coating by high speed impact of the particles. In the CGDS process, metal particles of generally 1-50 μm diameter is carried by a gas stream in high pressure (typically 20-30 atm) through a DE Laval type nozzle to achieve supersonic flying so as to impact on the substrate. Typically, the impact velocity ranges between 300 and 1200 m/s in the CGDS process. When the particle gains its critical velocity, the minimum in-flight speed at which it can deposit, adiabatic shear instabilities will occur. Herein, to ascertain the critical velocities of different particle sizes on the bonding efficiency in CGDS process, three-dimensional numerical simulations of single particle deposition process were performed. In the CGDS process, one of the most important parameters which determine the bonding strength with the substrate is particle impact temperature. Bonding will occur when the particle’s impacting velocity surpass the critical velocity, at which the interface can achieve 60 % of melting temperature of particle material (Ref 1). Therefore, critical velocity should be a main parameter on the coating quality. The particle critical velocity is determined not only by its size, but also by its material properties. This study numerically investigate the critical velocity for the particle deposition process in CGDS. In the present numerical analysis, copper (Cu) was chosen as particle material and aluminum (Al) as substrate material for this study. The impacting velocities were selected between 300 m/s and 800 m/s increasing in steps of 100 m/s. The simulation result reveals temporal and spatial interfacial temperature distribution and deformation between particle(s) and substrate. Finally, comparison is carried out between the computed results and experimental data

Sampling Neural Radiance Fields for Refractive Objects

Recently, differentiable volume rendering in neural radiance fields (NeRF) has gained a lot of popularity, and its variants have attained many impressive results. However, existing methods usually assume the scene is a homogeneous volume so that a ray is cast along the straight path. In this work, the scene is instead a heterogeneous volume with a piecewise-constant refractive index, where the path will be curved if it intersects the different refractive indices. For novel view synthesis of refractive objects, our NeRF-based framework aims to optimize the radiance fields of bounded volume and boundary from multi-view posed images with refractive object silhouettes. To tackle this challenging problem, the refractive index of a scene is reconstructed from silhouettes. Given the refractive index, we extend the stratified and hierarchical sampling techniques in NeRF to allow drawing samples along a curved path tracked by the Eikonal equation. The results indicate that our framework outperforms the state-of-the-art method both quantitatively and qualitatively, demonstrating better performance on the perceptual similarity metric and an apparent improvement in the rendering quality on several synthetic and real scenes.Comment: SIGGRAPH Asia 2022 Technical Communications. 4 pages, 4 figures, 1 table. Project: https://alexkeroro86.github.io/SampleNeRFRO/ Code: https://github.com/alexkeroro86/SampleNeRFR

SDSS-IV MaNGA: Cannibalism Caught in the Act - On the Frequency of Occurrence of Multiple Cores in Brightest Cluster Galaxies

Although it is generally accepted that massive galaxies form in a two-phased fashion, beginning with a rapid mass buildup through intense starburst activities followed by primarily dry mergers that mainly deposit stellar mass at outskirts, the late time stellar mass growth of brightest cluster galaxies (BCGs), the most massive galaxies in the universe, is still not well understood. Several independent measurements have indicated a slower mass growth rate than predictions from theoretical models. We attempt to resolve the discrepancy by measuring the frequency of BCGs with multiple cores, which serve as a proxy of the merger rates in the central region and facilitate a more direct comparison with theoretical predictions. Using 79 BCGs at z = 0.06-0.15 with integral field spectroscopic data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) project, we obtain a multiple-core fraction of 0.11 ± 0.04 at z ≈ 0.1 within an 18 kpc radius from the center, which is comparable to the value of 0.08 ± 0.04 derived from mock observations of 218 simulated BCGs from the cosmological hydrodynamical simulation IllustrisTNG. We find that most cores that appear close to the BCGs from imaging data turn out to be physically associated systems. Anchoring on the similarity in the multiple-core frequency between the MaNGA and IllustrisTNG, we discuss the mass growth rate of BCGs over the past 4.5 Gyr

HypertenGene: extracting key hypertension genes from biomedical literature with position and automatically-generated template features

<p>Abstract</p> <p>Background</p> <p>The genetic factors leading to hypertension have been extensively studied, and large numbers of research papers have been published on the subject. One of hypertension researchers' primary research tasks is to locate key hypertension-related genes in abstracts. However, gathering such information with existing tools is not easy: (1) Searching for articles often returns far too many hits to browse through. (2) The search results do not highlight the hypertension-related genes discovered in the abstract. (3) Even though some text mining services mark up gene names in the abstract, the key genes investigated in a paper are still not distinguished from other genes. To facilitate the information gathering process for hypertension researchers, one solution would be to extract the key hypertension-related genes in each abstract. Three major tasks are involved in the construction of this system: (1) gene and hypertension named entity recognition, (2) section categorization, and (3) gene-hypertension relation extraction.</p> <p>Results</p> <p>We first compare the retrieval performance achieved by individually adding template features and position features to the baseline system. Then, the combination of both is examined. We found that using position features can almost double the original AUC score (0.8140vs.0.4936) of the baseline system. However, adding template features only results in marginal improvement (0.0197). Including both improves AUC to 0.8184, indicating that these two sets of features are complementary, and do not have overlapping effects. We then examine the performance in a different domain--diabetes, and the result shows a satisfactory AUC of 0.83.</p> <p>Conclusion</p> <p>Our approach successfully exploits template features to recognize true hypertension-related gene mentions and position features to distinguish key genes from other related genes. Templates are automatically generated and checked by biologists to minimize labor costs. Our approach integrates the advantages of machine learning models and pattern matching. To the best of our knowledge, this the first systematic study of extracting hypertension-related genes and the first attempt to create a hypertension-gene relation corpus based on the GAD database. Furthermore, our paper proposes and tests novel features for extracting key hypertension genes, such as relative position, section, and template features, which could also be applied to key-gene extraction for other diseases.</p

Neurotrophic Effect of Citrus 5-Hydroxy-3,6,7,8,3′,4′-Hexamethoxyflavone: Promotion of Neurite Outgrowth via cAMP/PKA/CREB Pathway in PC12 Cells

5-Hydroxy-3,6,7,8,3′,4′-hexamethoxyflavone (5-OH-HxMF), a hydroxylated polymethoxyflavone, is found exclusively in the Citrus genus, particularly in the peels of sweet orange. In this research, we report the first investigation of the neurotrophic effects and mechanism of 5-OH-HxMF in PC12 pheochromocytoma cells. We found that 5-OH-HxMF can effectively induce PC12 neurite outgrowth accompanied with the expression of neuronal differentiation marker protein growth-associated protein-43(GAP-43). 5-OH-HxMF caused the enhancement of cyclic AMP response element binding protein (CREB) phosphorylation, c-fos gene expression and CRE-mediated transcription, which was inhibited by 2-naphthol AS-E phosphate (KG-501), a specific antagonist for the CREB-CBP complex formation. Moreover, 5-OH-HxMF-induced both CRE transcription activity and neurite outgrowth were inhibited by adenylate cyclase and protein kinase A (PKA) inhibitor, but not MEK1/2, protein kinase C (PKC), phosphatidylinositol 3-kinase (PI3K) or calcium/calmodulin-dependent protein kinase (CaMK) inhibitor. Consistently, 5-OH-HxMF treatment increased the intracellular cAMP level and downstream component, PKA activity. We also found that addition of K252a, a TrKA antagonist, significantly inhibited NGF- but not 5-OH-HxMF-induced neurite outgrowth. These results reveal for the first time that 5-OH-HxMF is an effective neurotrophic agent and its effect is mainly through a cAMP/PKA-dependent, but TrKA-independent, signaling pathway coupling with CRE-mediated gene transcription. A PKC-dependent and CREB-independent pathway was also involved in its neurotrophic action