Fast 2D Bicephalous Convolutional Autoencoder for Compressing 3D Time Projection Chamber Data

High-energy large-scale particle colliders produce data at high speed in the order of 1 terabytes per second in nuclear physics and petabytes per second in high-energy physics. Developing real-time data compression algorithms to reduce such data at high throughput to fit permanent storage has drawn increasing attention. Specifically, at the newly constructed sPHENIX experiment at the Relativistic Heavy Ion Collider (RHIC), a time projection chamber is used as the main tracking detector, which records particle trajectories in a volume of a three-dimensional (3D) cylinder. The resulting data are usually very sparse with occupancy around 10.8%. Such sparsity presents a challenge to conventional learning-free lossy compression algorithms, such as SZ, ZFP, and MGARD. The 3D convolutional neural network (CNN)-based approach, Bicephalous Convolutional Autoencoder (BCAE), outperforms traditional methods both in compression rate and reconstruction accuracy. BCAE can also utilize the computation power of graphical processing units suitable for deployment in a modern heterogeneous high-performance computing environment. This work introduces two BCAE variants: BCAE++ and BCAE-2D. BCAE++ achieves a 15% better compression ratio and a 77% better reconstruction accuracy measured in mean absolute error compared with BCAE. BCAE-2D treats the radial direction as the channel dimension of an image, resulting in a 3x speedup in compression throughput. In addition, we demonstrate an unbalanced autoencoder with a larger decoder can improve reconstruction accuracy without significantly sacrificing throughput. Lastly, we observe both the BCAE++ and BCAE-2D can benefit more from using half-precision mode in throughput (76-79% increase) without loss in reconstruction accuracy. The source code and links to data and pretrained models can be found at https://github.com/BNL-DAQ-LDRD/NeuralCompression_v2

Rethinking CycleGAN: Improving Quality of GANs for Unpaired Image-to-Image Translation

An unpaired image-to-image (I2I) translation technique seeks to find a mapping between two domains of data in a fully unsupervised manner. While the initial solutions to the I2I problem were provided by the generative adversarial neural networks (GANs), currently, diffusion models (DM) hold the state-of-the-art status on the I2I translation benchmarks in terms of FID. Yet, they suffer from some limitations, such as not using data from the source domain during the training, or maintaining consistency of the source and translated images only via simple pixel-wise errors. This work revisits the classic CycleGAN model and equips it with recent advancements in model architectures and model training procedures. The revised model is shown to significantly outperform other advanced GAN- and DM-based competitors on a variety of benchmarks. In the case of Male2Female translation of CelebA, the model achieves over 40% improvement in FID score compared to the state-of-the-art results. This work also demonstrates the ineffectiveness of the pixel-wise I2I translation faithfulness metrics and suggests their revision. The code and trained models are available at https://github.com/LS4GAN/uvcgan

Effect of APOE ɛ4 Status on Brain Amyloid-β and Cognitive Function in Amnestic and Nonamnestic Mild Cognitive Impairment: A 18F Florbetapir PET-CT Study

Mild cognitive impairment (MCI) is recognized as a predementia syndrome caused by multiple etiologies and nonmemory symptoms in MCI have recently gained increasing attention. However, the pattern of Aβ deposition and the effect of APOE (apolipoprotein E, APOE) ε4 on cognitive impairment in amnestic MCI (aMCI) and nonamnestic MCI (naMCI) patients has not been demonstrated. In this work, the amyloid-β (Aβ) load by [$^{18}$F]florbetapir PET imaging and cognitive performance is compared by comprehensive neuropsychological scales in participants with different MCI types or different APOE ε4 carriage status. According to the Aβ positivity and results of voxel-wise analysis, higher Aβ loads are observed in aMCI patients than naMCI patients, especially aMCI patients with APOE ε4. Additionally, it is observed that memory domain Z scores show a strong negative correlation with global florbetapir SUVR in the aMCI group (r = – 0.352, p < 0.001) but not in the naMCI group (r = –0.016, p = 0.924). Moreover, this correlation is independent of APOE e4 carriage status. This study aims to identify high-risk groups at an early stage of AD(Alzheimer's Disease, AD) through cognitive performance and APOE ε4 carrier status, which can be important for guiding clinical intervention trials

Mechanics Design for Stretchable, High Areal Coverage GaAs Solar Module on an Ultrathin Substrate,”

The trench design of substrate together with curvy interconnect formed from buckling provides a solution to stretchable electronics with high areal coverage on an ultrathin substrate, which are critically important for stretchable photovoltaics. In this paper, an improved trench design is proposed and verified by finite element analysis (FEA), through use of a heterogeneous design, to facilitate strain isolation and avoid possible fracture/delamination issue. A serpentine design of interconnect is also devised to offer $440$90%

Astragaloside IV improves slow transit constipation by regulating gut microbiota and enterochromaffin cells

Purpose: Slow transit constipation (STC) is a common gastrointestinal disorder characterized by altered gut microbiota and reduced number of enterochromaffin cells (ECs). Astragaloside IV (AS-IV), a low drug permeability saponin, has showed beneficial effects on patients with STC. However, the specific mechanism by which AS-IV regulates STC remains unclear. In this study, we aimed to investigate the effect of AS-IV on STC and its associated mechanisms involving gut microbiota.Methods: The effect of AS-IV on STC was evaluated on STC mice induced with loperamide. We measured defecation frequency, intestinal mobility, ECs loss, and colonic lesions in STC mice treated with AS-IV. We also analyzed the changes in gut microbiota and metabolites after AS-IV treatment. Moreover, we investigated the relationship between specific gut microbes and altered fecal metabolites, such as 3-bromotyrosine (3-BrY). We also conducted in vitro experiments to investigate the effect of 3-BrY on caspase-dependent apoptosis of ECs and the activation of the p38 MAPK and ERK signaling pathways induced by loperamide.Results: AS-IV treatment promoted defecation, improved intestinal mobility, suppressed ECs loss, and alleviated colonic lesions in STC mice. AS-IV treatment also affected gut microbiota and metabolites, with a significant correlation between specific gut microbes and altered fecal metabolites such as 3-BrY. Furthermore, 3-BrY may potentially reduce caspase-dependent apoptosis of ECs and protect cell survival by inhibiting the activation of the p38 MAPK and ERK signaling pathways induced by loperamide.Conclusion: Our findings suggest that changes in gut microbiota and ECs mediated the therapeutic effect of STC by AS-IV. These results provide a basis for the use of AS-IV as a prebiotic agent for treating STC. The specific mechanism by which AS-IV regulates gut microbiota and ECs warrants further investigation

Single-cell RNA sequencing reveals cellular dynamics and therapeutic effects of astragaloside IV in slow transit constipation

The cellular characteristics of intestinal cells involved in the therapeutic effects of astragaloside IV (AS-IV) for treating slow transit constipation (STC) remain unclear. This study aimed to determine the dynamics of colon tissue cells in the STC model and investigate the effects of AS-IV treatment by single-cell RNA sequencing (scRNA-seq). STC mouse models were developed using loperamide, with subsequent treatment using AS-IV. Colon tissues and feces were collected for scRNA-seq and targeted short-chain fatty acid quantification. We integrated scRNA-seq data with network pharmacology to analyze the effect of AS-IV on constipation. AS-IV showed improvement in defecation for STC mice induced by loperamide. Notably, in STC mice, epithelial cells, T cells, B cells, and fibroblasts demonstrated alterations in cell proportions and aberrant functions, which AS-IV partially rectified. AS-IV has the potential to modulate the metabolic pathway of epithelial cells through its interaction with peroxisome proliferator-activated receptor gamma (PPARγ). AS-IV reinstated fecal butyrate levels and improved energy metabolism in epithelial cells. The proportion of naïve CD4+T cells is elevated in STC, and the differentiation of these cells into regulatory T cells (Treg) is regulated by B cells and fibroblasts through the interaction of ligand-receptor pairs. AS-IV treatment can partially alleviate this trend. The status of fibroblasts in STC undergoes alterations, and the FB_C4_Adamdec1 subset, associated with angiogenesis and the Wingless-related integration (Wnt) pathway, emerges. Our comprehensive analysis identifies perturbations of epithelial cells and tissue microenvironment cells in STC and elucidates mechanisms underlying the therapeutic efficacy of AS-IV