DataCI: A Platform for Data-Centric AI on Streaming Data

We introduce DataCI, a comprehensive open-source platform designed specifically for data-centric AI in dynamic streaming data settings. DataCI provides 1) an infrastructure with rich APIs for seamless streaming dataset management, data-centric pipeline development and evaluation on streaming scenarios, 2) an carefully designed versioning control function to track the pipeline lineage, and 3) an intuitive graphical interface for a better interactive user experience. Preliminary studies and demonstrations attest to the easy-to-use and effectiveness of DataCI, highlighting its potential to revolutionize the practice of data-centric AI in streaming data contexts.Comment: 3 pages, 4 figure

Active-Learning-as-a-Service: An Efficient MLOps System for Data-Centric AI

The success of today's AI applications requires not only model training (Model-centric) but also data engineering (Data-centric). In data-centric AI, active learning (AL) plays a vital role, but current AL tools can not perform AL tasks efficiently. To this end, this paper presents an efficient MLOps system for AL, named ALaaS (Active-Learning-as-a-Service). Specifically, ALaaS adopts a server-client architecture to support an AL pipeline and implements stage-level parallelism for high efficiency. Meanwhile, caching and batching techniques are employed to further accelerate the AL process. In addition to efficiency, ALaaS ensures accessibility with the help of the design philosophy of configuration-as-a-service. It also abstracts an AL process to several components and provides rich APIs for advanced users to extend the system to new scenarios. Extensive experiments show that ALaaS outperforms all other baselines in terms of latency and throughput. Further ablation studies demonstrate the effectiveness of our design as well as ALaaS's ease to use. Our code is available at \url{https://github.com/MLSysOps/alaas}.Comment: 8 pages, 7 figure

DIFAI: Diverse Facial Inpainting using StyleGAN Inversion

Image inpainting is an old problem in computer vision that restores occluded regions and completes damaged images. In the case of facial image inpainting, most of the methods generate only one result for each masked image, even though there are other reasonable possibilities. To prevent any potential biases and unnatural constraints stemming from generating only one image, we propose a novel framework for diverse facial inpainting exploiting the embedding space of StyleGAN. Our framework employs pSp encoder and SeFa algorithm to identify semantic components of the StyleGAN embeddings and feed them into our proposed SPARN decoder that adopts region normalization for plausible inpainting. We demonstrate that our proposed method outperforms several state-of-the-art methods.Comment: ICIP 202

Integrated Sensing-Communication-Computation for Edge Artificial Intelligence

Edge artificial intelligence (AI) has been a promising solution towards 6G to empower a series of advanced techniques such as digital twin, holographic projection, semantic communications, and auto-driving, for achieving intelligence of everything. The performance of edge AI tasks, including edge learning and edge AI inference, depends on the quality of three highly coupled processes, i.e., sensing for data acquisition, computation for information extraction, and communication for information transmission. However, these three modules need to compete for network resources for enhancing their own quality-of-services. To this end, integrated sensing-communication-computation (ISCC) is of paramount significance for improving resource utilization as well as achieving the customized goals of edge AI tasks. By investigating the interplay among the three modules, this article presents various kinds of ISCC schemes for federated edge learning tasks and edge AI inference tasks in both application and physical layers

Methionine Restriction Increases Insulin Sensitivity in Type-2 Diabetes via miRNA Activation

Methionine Restriction (MR) causes a higher level of circulating and hepatic fibroblastic growth factor 21 (FGF21). This leads to metabolic phenotypes, including increased energy expenditure, insulin sensitivity, and extended lifespan. Previous studies on obese mice have concluded that dietary MR in a high-fat regimen prevents hyperglycemia and improves glucose homeostasis, thus preventing type-2 diabetes, a multifactorial metabolic disease characterized by high blood glucose levels and cell insulin resistance. Recent experiments have shown that cells’ response to dietary MR includes changes in methylation of DNA promoters that activate or repress microRNAs (miRNAs), which are small endogenous nucleotide sequences and contain 18-22 base pairs that control gene expression for lipid metabolism. Considering that the disruption of miRNA levels affects insulin resistance, miRNA potentially plays a role in MR to increase insulin sensitivity for type-2 diabetes. In this paper, we investigate the mechanism of MR influencing the expression level of miRNA-15b to promote insulin sensitivity in obese organisms. Using our in-vitro model, we measured the expression of miRNA-15b in adipocytes cultured in MR and control conditions. Additionally, we compared insulin sensitivity and free fatty acid (FFA) metabolite levels between obese mice on control and MR diets. Taken together, we were able to verify the positive effects of MR in reducing hepatic fatty acid production, decreasing blood glucose levels, and increasing insulin sensitivity. However, miRNA-15b downregulates cells’ insulin signaling pathway and insulin sensitivity. Therefore, we proposed potential influences of MR on other miRNAs in reducing lipid cell differentiation and enhancing insulin sensitivity for future investigation

TAT-Modified Gold Nanoparticles Enhance the Antitumor Activity of PAD4 Inhibitors

Purpose: Histone citrullination by peptidylarginine deiminases 4 (PAD4) regulates the gene expression of tumor suppressor. In our previously study, YW3-56 (356) was developed as a potent PAD4 inhibitor for cancer therapy with novel function in the autophagy pathway. To enhance the antitumor activity, the PAD4 inhibitor 356 was modified by the well-established cationic penetrating peptide RKKRRQRRR (peptide TAT) and gold nanoparticles to obtain 356-TAT-AuNPs which could enhance the permeability of chemical drug in solid tumor. Methods: 356-TAT-AuNPs were prepared, and their morphology were characterized. The antitumor activity of 356-TAT-AuNPs was evaluated in vitro and in vivo. Results: 356-TAT-AuNPs exhibited higher anticancer activity against HCT-116, MCF-7 and A549 cells than 356 and 356-AuNPs. Compared with 356 and 356-AuNPs, 356-TAT-AuNPs entered the cytoplasm and nuclear, exhibited stronger anticancer activity by increasing apoptosis, inducing autophagy and inhibiting of histone H3 citrullination, and in HCT-116 xenograft mouse model, 356-TAT-AuNPs could improve the antitumor activity. Conclusion: The modified AuNPs with peptide TAT as drug delivery system are potent in delaying tumor growth and could be a powerful vehicle for profitable anticancer drug development. We believe that peptide TAT modification strategy may provide a simple and valuable method for improving antitumor activity of PAD4 inhibitors for clinical use.publishedVersio

Electroacupuncture ameliorates peptic ulcer disease in association with gastroduodenal microbiota modulation in mice

Peptic ulcer disease (PUD) is a common disease and frequently encountered in the clinic. Accumulating evidence suggests that PUD is associated with the gastrointestinal microbiota. Electroacupuncture (EA) is an improved version of acupuncture, which can improve the clinical effect by increasing the stimulation and delivering appropriate electrical pulses to needles. This method has been widely used in the treatment of peptic ulcer disease. However, its effect on gastrointestinal microbiota remains unclear. Therefore, in the present study, the ameliorative effect of EA was evaluated on the gastroduodenal mucosa, and the regulatory effect of the gastroduodenal microbiota was assessed in PUD mice. A total of 48 male Kun Ming mice were randomly divided into the following groups: normal control group (NC), PUD model group (PUD), Shousanli group (LI10), and Zusanli group (ST36) (n=12). The mice in groups LI10 and ST36 were treated with EA at LI10 and ST36, respectively. This intervention was continued for 7 days. Subsequently, we evaluated the morphological changes in the gastric and duodenal mucosa, and specific indices were measured, including the contents of serum dopamine (DA), the trefoil factor (TFF), and the vasoactive intestinal peptide (VIP). In addition, the gastric and duodenal microbiota were assessed via 16S ribosomal DNA sequencing. The results indicated that EA at LI10 or ST36 significantly reduced the injury of the gastroduodenal mucosa in PUD mice. The gastric microbial community structure of the groups LI10 and ST36 was similar to that of the NC group following comparison with the microbial community structure of the PUD model group. Moreover, the abundance of Firmicutes in the stomach was decreased, whereas that of Bacteroidetes was increased, and the abundance of Firmicutes in the duodenum was decreased. Furthermore, the microbial diversity and richness of the gastric microbiota in group LI10 were also significantly increased, and the serum dopamine and trefoil factor levels in group ST36 were significantly increased. Therefore, it is suggested that EA ameliorating PUD is in association with improving the levels of DA and TFF and regulating the relative abundances of Firmicutes and Bacteroidetes in the gastric microbiota

Turbulent scaling in fluids

This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The project was a study of turbulence in fluids that are subject to different body forces and to external temperature gradients. Our focus was on the recent theoretical prediction that the Kolomogorov picture of turbulence may need to be modified for turbulent flows driven by buoyancy and subject to body forces such as rotational accelerations. Models arising from this research are important in global climate modeling, in turbulent transport problems, and in the fundamental understanding of fluid turbulence. Experimentally, we use (1) precision measurements of heat transport and local temperature; (2) flow visualization using digitally- enhanced optical shadowgraphs, particle-image velocimetry, thermochromic liquid-crystal imaging, laser-doppler velocimetry, and photochromic dye imaging; and (3) advanced image- processing techniques. Our numerical simulations employ standard spectral and novel lattice Boltzmann algorithms implemented on parallel Connection Machine computers to simulate turbulent fluid flow. In laboratory experiments on incompressible fluids, we measure probability distribution functions and two-point spatial correlations of temperature T and velocity V (both T-T and V-T correlations) and determine scaling relations for global heat transport with Rayleigh number. We also explore the mechanism for turbulence in thermal convection and the stability of the thermal boundary layer