Flow Dynamic Analysis of Core Shooting Process through Experiment and Multiphase Modeling

Core shooting process is the most widely used technique to make sand cores and it plays an important role in the quality of sand cores as well as the manufacture of complicated castings in metal casting industry. In this paper, the flow behavior of sand particles in the core box was investigated synchronously with transparent core box, high-speed camera, and pressure measuring system. The flow pattern of sand particles in the shooting head of the core shooting machine was reproduced with various colored core sand layers. Taking both kinetic and frictional stress into account, a kinetic-frictional constitutive correlation was established to describe the internal momentum transfer in the solid phase. Two-fluid model (TFM) simulations with turbulence model were then performed and good agreement was achieved between the experimental and simulation results on the flow behavior of sand particles in both the shooting head and the core box. Based on the experimental and simulation results, the flow behavior of sand particles in the core box, the formation of “dead zone” in the shooting head, and the effect of drag force were analyzed in terms of sand volume fraction (αs), sand velocity (Vs), and pressure variation (P)

Integrating microfluidics and biosensing on a single flexible acoustic device using hybrid modes

Integration of microfluidics and biosensing functionalities on a single device holds promise in continuous health monitoring and disease diagnosis for point-of-care applications. However, the required functions of fluid handling and biomolecular sensing usually arise from different actuation mechanisms. In this work, we demonstrate that a single acoustofluidic device, based on a flexible thin film platform, is able to generate hybrid waves modes, which can be used for fluidic actuation (Lamb waves) and biosensing (thickness shear waves). On this integrated platform, we show multiple and sequential functions of mixing, transport and disposal of liquid volumes using Lamb waves, whilst the thickness bulk shear waves allow us to sense the chemotherapeutic Imatinib, using an aptamer-based strategy, as would be required for therapy monitoring. Upon binding, the conformation of the aptamer results in a change in coupled mass, which has been detected. This platform architecture has the potential to generate a wide range of simple sample-to-answer biosensing acoustofluidic devices

Resonance instability of primordial gravitational waves during inflation in Chern-Simons gravity

We investigate axion inflation where the gravitational Chern-Simons term is coupled to a periodic function of the inflaton. We find that tensor perturbations with different polarizations are amplified in different ways by the Chern-Simons coupling. Depending on the model parameters, the resonance amplification results in a parity-violating peak or a board plateau in the energy spectrum of gravitational waves, and the sharp cutoff in the infrared region constitutes a characteristic distinguishable from stochastic gravitational wave backgrounds produced by matter fields in Einstein gravity.Comment: 16 pages, 4 figure

DA-STC: Domain Adaptive Video Semantic Segmentation via Spatio-Temporal Consistency

Video semantic segmentation is a pivotal aspect of video representation learning. However, significant domain shifts present a challenge in effectively learning invariant spatio-temporal features across the labeled source domain and unlabeled target domain for video semantic segmentation. To solve the challenge, we propose a novel DA-STC method for domain adaptive video semantic segmentation, which incorporates a bidirectional multi-level spatio-temporal fusion module and a category-aware spatio-temporal feature alignment module to facilitate consistent learning for domain-invariant features. Firstly, we perform bidirectional spatio-temporal fusion at the image sequence level and shallow feature level, leading to the construction of two fused intermediate video domains. This prompts the video semantic segmentation model to consistently learn spatio-temporal features of shared patch sequences which are influenced by domain-specific contexts, thereby mitigating the feature gap between the source and target domain. Secondly, we propose a category-aware feature alignment module to promote the consistency of spatio-temporal features, facilitating adaptation to the target domain. Specifically, we adaptively aggregate the domain-specific deep features of each category along spatio-temporal dimensions, which are further constrained to achieve cross-domain intra-class feature alignment and inter-class feature separation. Extensive experiments demonstrate the effectiveness of our method, which achieves state-of-the-art mIOUs on multiple challenging benchmarks. Furthermore, we extend the proposed DA-STC to the image domain, where it also exhibits superior performance for domain adaptive semantic segmentation. The source code and models will be made available at \url{https://github.com/ZHE-SAPI/DA-STC}.Comment: 18 pages,9 figure

DF-GAN: Deep Fusion Generative Adversarial Networks for Text-to-Image Synthesis

Synthesizing high-quality realistic images from text descriptions is a challenging task. Almost all existing text-to-image Generative Adversarial Networks employ stacked architecture as the backbone. They utilize cross-modal attention mechanisms to fuse text and image features, and introduce extra networks to ensure text-image semantic consistency. In this work, we propose a much simpler, but more effective text-to-image model than previous works. Corresponding to the above three limitations, we propose: 1) a novel one-stage text-to-image backbone which is able to synthesize high-quality images directly by one pair of generator and discriminator, 2) a novel fusion module called deep text-image fusion block which deepens the text-image fusion process in generator, 3) a novel target-aware discriminator composed of matching-aware gradient penalty and one-way output which promotes the generator to synthesize more realistic and text-image semantic consistent images without introducing extra networks. Compared with existing text-to-image models, our proposed method (i.e., DF-GAN) is simpler but more efficient to synthesize realistic and text-matching images and achieves better performance. Extensive experiments on both Caltech-UCSD Birds 200 and COCO datasets demonstrate the superiority of the proposed model in comparison to state-of-the-art models

Mir-23b down-regulates the expression of target gene of acetaldehyde dehydrogenase 1a1 and increases the sensitivity of cervical cancer stem cells to cisplatin

Purpose: To study the effect of miR-23b on the expression of the target gene of acetaldehyde dehydrogenase 1A1 (ALDH1A1), and cisplatin (CDDP) susceptibility of cervical carcinoma stem cells. Methods: Human cervical cancer cell line Hela cells were cultured in vitro, and miR-23b mimic and negative control were transfected into the cells using lipofectamine method. The growth of the two groups of cells was determined using growth curve method, and their proliferation measured using plate clone formation. The influence of treatments on the sensitivity of the cells to CDDP was assayed using MTT method. The mRNA expression of ALDH1A1 in Hela cells was assayed using real-time quantitative polymerase hain reation (PCR), while its protein expression was assayed by Western blot. Results: The levels of expressions of ALDH1A1 protein and mRNA in the miR-23b overexpression group were significantly lower than those in the control group (p < 0.05). The sensitivities of Hela cells to CDDP in the ALDH1A1 inhibition group and the control group were dose-dependent to some extent, but cell inhibition in ALDH1A1 inhibition group markedly increased, relative to control when the CDDP dose was 0.1 ppc (p < 0.01). Conclusion: Up-regulating the expression of miR-23b significantly inhibits the growth and proliferation of cervical cancer cells, and increases their sensitivity to CDDP via down-regulation of the expression of the target gene for ALDH1A1. Therefore, during cervical carcinoma treatment, increasing the level of miR-23b may produce a chemotherapeutic effect. Keywords: MiR-23b, Acetaldehyde dehydrogenase 1A1, Cervical cancer, Cisplatin, Sensitivit