SIMD Everywhere Optimization from ARM NEON to RISC-V Vector Extensions

Many libraries, such as OpenCV, FFmpeg, XNNPACK, and Eigen, utilize Arm or x86 SIMD Intrinsics to optimize programs for performance. With the emergence of RISC-V Vector Extensions (RVV), there is a need to migrate these performance legacy codes for RVV. Currently, the migration of NEON code to RVV code requires manual rewriting, which is a time-consuming and error-prone process. In this work, we use the open source tool, "SIMD Everywhere" (SIMDe), to automate the migration. Our primary task is to enhance SIMDe to enable the conversion of ARM NEON Intrinsics types and functions to their corresponding RVV Intrinsics types and functions. For type conversion, we devise strategies to convert Neon Intrinsics types to RVV Intrinsics by considering the vector length agnostic (vla) architectures. With function conversions, we analyze commonly used conversion methods in SIMDe and develop customized conversions for each function based on the results of RVV code generations. In our experiments with Google XNNPACK library, our enhanced SIMDe achieves speedup ranging from 1.51x to 5.13x compared to the original SIMDe, which does not utilize customized RVV implementations for the conversions

Hepcidin Regulation by BMP Signaling in Macrophages Is Lipopolysaccharide Dependent

Hepcidin is an antimicrobial peptide, which also negatively regulates iron in circulation by controlling iron absorption from dietary sources and iron release from macrophages. Hepcidin is synthesized mainly in the liver, where hepcidin is regulated by iron loading, inflammation and hypoxia. Recently, we have demonstrated that bone morphogenetic protein (BMP)-hemojuvelin (HJV)-SMAD signaling is central for hepcidin regulation in hepatocytes. Hepcidin is also expressed by macrophages. Studies have shown that hepcidin expression by macrophages increases following bacterial infection, and that hepcidin decreases iron release from macrophages in an autocrine and/or paracrine manner. Although previous studies have shown that lipopolysaccharide (LPS) can induce hepcidin expression in macrophages, whether hepcidin is also regulated by BMPs in macrophages is still unknown. Therefore, we examined the effects of BMP signaling on hepcidin expression in RAW 264.7 and J774 macrophage cell lines, and in primary peritoneal macrophages. We found that BMP4 or BMP6 alone did not have any effect on hepcidin expression in macrophages although they stimulated Smad1/5/8 phosphorylation and Id1 expression. In the presence of LPS, however, BMP4 and BMP6 were able to stimulate hepcidin expression in macrophages, and this stimulation was abolished by the NF-κB inhibitor Ro1069920. These results suggest that hepcidin expression is regulated differently in macrophages than in hepatocytes, and that BMPs regulate hepcidin expression in macrophages in a LPS-NF-κB dependent manner

Two-stage assembly system with imperfect items for a coordinated two-level integrated supply chain under carbon emission constraints

This paper may provide an alternative to the problem of a two-stage assembly system with imperfect processes in a single manufacturer-retailer and two-level integrated supply chain. A mathematical model is developed based on the following scenarios: (a) the manufacturer and the retailer are in different countries where the exchange rate is uncertain; (b) the fixed and variable carbon emission costs are incorporated into current environmental issues; (c) shortage is allowed, and the unsatisfied demand is completely backlogged. In the light of these concerns, our model is to determine the production run time, the shortage time period and defective rate of manual stage. The optimal solutions are computed by our proposed algorithm. Finally, a numerical example and sensitivity analysis are carried out to illustrate the model

Deltex1 Is a Target of the Transcription Factor NFAT that Promotes T Cell Anergy

SummaryThe molecular process underlying T cell anergy is incompletely understood. Deltex1 (DTX1) is a Notch target with unknown physiological function. Here we show that Dtx1 was a transcription target of nuclear factor of activated T cells (NFAT) and participated in T cell anergy. DTX1 protein was upregulated during T cell anergy, and transgenic expression of Dtx1 attenuated T cell activation. DTX1 inhibited T cell activation by both E3-dependent and E3-independent mechanisms. In addition, DTX1 suppressed T cell activation in the absence of its Notch-binding domain. Importantly, DTX1 regulated the expression of two anergy-associated molecules, growth arrest and DNA-damage-inducible 45 β (Gadd45β) and Cbl-b. DTX1 interacted with early growth response 2 (Egr-2) for optimum expression of Cbl-b. Furthermore, deficiency of DTX1 augmented T cell activation, conferred resistance to anergy induction, enhanced autoantibody generation, and increased inflammation. DTX1 therefore represents a component downstream of calcium-NFAT signaling that regulates T cell anergy

Single-Image HDR Reconstruction by Learning to Reverse the Camera Pipeline

Recovering a high dynamic range (HDR) image from a single low dynamic range (LDR) input image is challenging due to missing details in under-/over-exposed regions caused by quantization and saturation of camera sensors. In contrast to existing learning-based methods, our core idea is to incorporate the domain knowledge of the LDR image formation pipeline into our model. We model the HDRto-LDR image formation pipeline as the (1) dynamic range clipping, (2) non-linear mapping from a camera response function, and (3) quantization. We then propose to learn three specialized CNNs to reverse these steps. By decomposing the problem into specific sub-tasks, we impose effective physical constraints to facilitate the training of individual sub-networks. Finally, we jointly fine-tune the entire model end-to-end to reduce error accumulation. With extensive quantitative and qualitative experiments on diverse image datasets, we demonstrate that the proposed method performs favorably against state-of-the-art single-image HDR reconstruction algorithms.Comment: CVPR 2020. Project page: https://www.cmlab.csie.ntu.edu.tw/~yulunliu/SingleHDR Code: https://github.com/alex04072000/SingleHD

Human Fetal Scalp Dermal Papilla Enriched Genes and the Role of R-Spondin-1 in the Restoration of Hair Neogenesis in Adult Mouse Cells

Much remains unknown about the regulatory networks which govern the dermal papilla’s (DP) ability to induce hair follicle neogenesis, a capacity which decreases greatly with age. To further define the core genes which characterize the DP cell and to identify pathways prominent in DP cells with greater hair inductive capacity, comparative transcriptome analyses of human fetal and adult dermal follicular cells were performed. 121 genes were significantly upregulated in fetal DP cells in comparison to both fetal dermal sheath cup (DSC) cells and interfollicular dermal (IFD) populations. Comparison of the set of enriched human fetal DP genes with human adult DP, newborn mouse DP, and embryonic mouse dermal condensation (DC) cells revealed differences in the expression of Wnt/β-catenin, Shh, FGF, BMP, and Notch signaling pathways. We chose R-spondin-1, a Wnt agonist, for functional verification and show that exogenous administration restores hair follicle neogenesis from adult mouse cells in skin reconstitution assays. To explore upstream regulators of fetal DP gene expression, we identified twenty-nine transcription factors which are upregulated in human fetal DP cells compared to adult DP cells. Of these, seven transcription factor binding motifs were significantly enriched in the candidate promoter regions of genes differentially expressed between fetal and adult DP cells, suggesting a potential role in the regulatory network which confers the fetal DP phenotype and a possible relationship to the induction of follicle neogenesis

Association between use of non–vitamin k oral anticoagulants with and without concurrent medications and risk of major bleeding in nonvalvular atrial fibrillation

Importance:  Non–vitamin K oral anticoagulants (NOACs) are commonly prescribed with other medications that share metabolic pathways that may increase major bleeding risk. Objective:  To assess the association between use of NOACs with and without concurrent medications and risk of major bleeding in patients with nonvalvular atrial fibrillation. Design, Setting, and Participants:  Retrospective cohort study using data from the Taiwan National Health Insurance database and including 91 330 patients with nonvalvular atrial fibrillation who received at least 1 NOAC prescription of dabigatran, rivaroxaban, or apixaban from January 1, 2012, through December 31, 2016, with final follow-up on December 31, 2016. Exposures:  NOAC with or without concurrent use of atorvastatin; digoxin; verapamil; diltiazem; amiodarone; fluconazole; ketoconazole, itraconazole, voriconazole, or posaconazole; cyclosporine; erythromycin or clarithromycin; dronedarone; rifampin; or phenytoin. Main Outcomes and Measures:  Major bleeding, defined as hospitalization or emergency department visit with a primary diagnosis of intracranial hemorrhage or gastrointestinal, urogenital, or other bleeding. Adjusted incidence rate differences between person-quarters (exposure time for each person during each quarter of the calendar year) of NOAC with or without concurrent medications were estimated using Poisson regression and inverse probability of treatment weighting using the propensity score. Results:  Among 91 330 patients with nonvalvular atrial fibrillation (mean age, 74.7 years [SD, 10.8]; men, 55.8%; NOAC exposure: dabigatran, 45 347 patients; rivaroxaban, 54 006 patients; and apixaban, 12 886 patients), 4770 major bleeding events occurred during 447 037 person-quarters with NOAC prescriptions. The most common medications co-prescribed with NOACs over all person-quarters were atorvastatin (27.6%), diltiazem (22.7%), digoxin (22.5%), and amiodarone (21.1%). Concurrent use of amiodarone, fluconazole, rifampin, and phenytoin with NOACs had a significant increase in adjusted incidence rates per 1000 person-years of major bleeding than NOACs alone: 38.09 for NOAC use alone vs 52.04 for amiodarone (difference, 13.94 [99% CI, 9.76-18.13]); 102.77 for NOAC use alone vs 241.92 for fluconazole (difference, 138.46 [99% CI, 80.96-195.97]); 65.66 for NOAC use alone vs 103.14 for rifampin (difference, 36.90 [99% CI, 1.59-72.22); and 56.07 for NOAC use alone vs 108.52 for phenytoin (difference, 52.31 [99% CI, 32.18-72.44]; P < .01 for all comparisons). Compared with NOAC use alone, the adjusted incidence rate for major bleeding was significantly lower for concurrent use of atorvastatin, digoxin, and erythromycin or clarithromycin and was not significantly different for concurrent use of verapamil; diltiazem; cyclosporine; ketoconazole, itraconazole, voriconazole, or posaconazole; and dronedarone. Conclusions and Relevance:  Among patients taking NOACs for nonvalvular atrial fibrillation, concurrent use of amiodarone, fluconazole, rifampin, and phenytoin compared with the use of NOACs alone, was associated with increased risk of major bleeding. Physicians prescribing NOAC medications should consider the potential risks associated with concomitant use of other drugs