Designing Network Design Strategies Through Gradient Path Analysis

Designing a high-efficiency and high-quality expressive network architecture has always been the most important research topic in the field of deep learning. Most of today's network design strategies focus on how to integrate features extracted from different layers, and how to design computing units to effectively extract these features, thereby enhancing the expressiveness of the network. This paper proposes a new network design strategy, i.e., to design the network architecture based on gradient path analysis. On the whole, most of today's mainstream network design strategies are based on feed forward path, that is, the network architecture is designed based on the data path. In this paper, we hope to enhance the expressive ability of the trained model by improving the network learning ability. Due to the mechanism driving the network parameter learning is the backward propagation algorithm, we design network design strategies based on back propagation path. We propose the gradient path design strategies for the layer-level, the stage-level, and the network-level, and the design strategies are proved to be superior and feasible from theoretical analysis and experiments.Comment: 12 pages, 9 figure

LUX-ZEPLIN (LZ) Technical Design Report

In this Technical Design Report (TDR) we describe the LZ detector to be built at the Sanford Underground Research Facility (SURF). The LZ dark matter experiment is designed to achieve sensitivity to a WIMP-nucleon spin-independent cross section of three times ten to the negative forty-eighth square centimeters

Prediction of Queue Dissipation Time for Mixed Traffic Flows With Deep Learning

Queue dissipation has been extensively studied about traffic signalization, work zone operations, and ramp metering. Various methods for estimating the intersection’s queue length and dissipation time have been reported in the literature, including the use of car-following models with simulation, vehicle trajectories from GPS, shock-wave theory, statistical estimation from traffic flow patterns, and artificial neural networks (ANN). However, most of such methods cannot account for the impacts of interactions between different vehicle types and their spatial distributions in the queue length on the initial discharge time and the resulting total dissipation duration. As such, this study presents a system, named TrafficTalk, that applies a deep learning-based method to reliably capture the queue characteristics of mixed traffic flows, and produce a robust estimate of the dissipating duration for the design of the optimal signal plan. The proposed TrafficTalk, featuring the effectiveness in transforming video-imaged traffic conditions into vehicle density maps, has proved its performance under extensive field evaluations. For instance, compared with the benchmark model, XGBoost in the literature, it has reduced the MAPE from 25.8% to 10.4%., and from 31.3% to 10.4% if the queue discharging stream comprises motorcycles

Xanthine derivative KMUP-1 ameliorates retinopathy

Retinal neovascularization (RNV) and cell apoptosis observed in retinopathy are the most common cause of vision loss worldwide. Increasing vascular endothelial growth factor (VEGF), which was driven by hypoxia or inflammation, would result in RNV. This study investigated the anti-inflammatory and anti-apoptotic xanthine-based derivative KMUP-1 on hypoxia-induced conditions in vitro and in vivo. In the oxygen-induced retinopathy animal model, KMUP-1 mitigated vaso-obliteration and neovascularization. In the cell model of hypoxic endothelium cultured at 1% O2, KMUP-1 inhibited endothelial migration and tube formation and had no cytotoxic effect on cell growth. Upregulation of pro-angiogenic factors, HIF-1α and VEGF, and pro-inflammatory cytokines, IL-1β and TNF-α, expression in the retinal-derived endothelial cells, RF/6 A cells, upon hypoxia stimulation, was suppressed by KMUP-1 treatment. RF/6 A cells treated with KMUP-1 showed a reduction of PI3K/Akt, ERK, and RhoA/ROCKs signaling pathways and induction of protective pathways such as eNOS and soluble guanylyl cyclase at 1% O2. Furthermore, KMUP-1 decreased the expression of VEGF, ICAM-1, TNF-α, and IL-1β and increased the BCL-2/BAX ratio in the oxygen-induced retinopathy mouse retina samples. In conclusion, the results of this study suggest that KMUP-1 has potential therapeutic value in retinopathy due to its triple effects on anti-angiogenesis, anti-inflammation, and anti-apoptosis in hypoxic endothelium

Proteasome Inhibitors Decrease the Viability of Pulmonary Arterial Smooth Muscle Cells by Restoring Mitofusin-2 Expression under Hypoxic Conditions

Pulmonary hypertension (PH) is a severe progressive disease, and the uncontrolled proliferation of pulmonary artery smooth muscle cells (PASMCs) is one of the main causes. Mitofusin-2 (MFN2) profoundly inhibits cell growth and proliferation in a variety of tumor cell lines and rat vascular smooth muscle cells. Down-regulation of MFN2 is known to contribute to PH. Proteasome inhibitors have been shown to inhibit the proliferation of PASMCs; however, there is no study on the regulation of proteasome inhibitors through MFN-2 in the proliferation of PASMCs, a main pathophysiology of PH. In this study, PASMCs were exposed to hypoxic conditions and the expression of MFN2 and cleaved-PARP1 were detected by Western blotting. The effects of hypoxia and proteasome inhibitors on the cell viability of PASMC cells were detected by CCK8 assay. The results indicated that hypoxia increases the viability and reduces the expression of MFN2 in a PASMCs model. MFN2 overexpression inhibits the hypoxia-induced proliferation of PASMCs. In addition, proteasome inhibitors, bortezomib and marizomib, restored the decreased expression of MFN2 under hypoxic conditions, inhibited hypoxia-induced proliferation and induced the expression of cleaved-PARP1. These results suggest that bortezomib and marizomib have the potential to improve the hypoxia-induced proliferation of PASMCs by restoring MFN2 expression

KMUP-1 Suppresses RANKL-Induced Osteoclastogenesis and Prevents Ovariectomy-Induced Bone Loss: Roles of MAPKs, Akt, NF-κB and Calcium/Calcineurin/NFATc1 Pathways

<div><p>Background</p><p>KMUP-1 is a xanthine derivative with inhibitory activities on the phosphodiesterase (PDE) 3,4 and 5 isoenzymes to suppress the degradation of cyclic AMP and cyclic GMP. However, the effects of KMUP-1 on osteoclast differentiation are still unclear. In this study, we investigated whether KMUP-1 inhibits osteoclastogenesis induced by RANKL in RAW 264.7 cells and bone loss induced by ovariectomy in mice, and the underlying mechanisms.</p><p>Principal Findings</p><p><i>In vitro</i>, KMUP-1 inhibited RANKL-induced TRAP activity, the formation of multinucleated osteoclasts and resorption-pit formation. It also inhibited key mediators of osteoclastogenesis including IL-1β, IL-6, TNF-α and HMGB1. In addition, KMUP-1 inhibited RANKL-induced activation of signaling molecules (Akt, MAPKs, calcium and NF-κB), mRNA expression of osteoclastogensis-associated genes (TRAP, MMP-9, Fra-1, and cathepsin K) and transcription factors (c-Fos and NFATc1). Furthermore, most inhibitory effects of KMUP-1 on RANKL-mediated signal activations were reversed by a protein kinase A inhibitor (H89) and a protein kinase G inhibitor (KT5823). <i>In vivo</i>, KMUP-1 prevented loss of bone mineral content, preserved serum alkaline phosphate and reduced serum osteocalcin in ovariectomized mice.</p><p>Conclusions</p><p>KMUP-1 inhibits RANKL-induced osteoclastogenesis <i>in vitro</i> and protects against ovariectomy-induced bone loss <i>in vivo</i>. These effects are mediated, at least in part, by cAMP and cGMP pathways. Therefore, KMUP-1 may have a role in pharmacologic therapy of osteoporosis.</p></div

Effects of KMUP-1 on bone loss in ovariectomized (OVX) mice.

<p>(<b>A</b>) OVX mice were sacrificed after 30 days of KMUP-1 treatment. Images of the longitudinal and transverse sections of the proximal tibia were obtained with a µCT. (<b>B</b>, <b>C</b>) Tibial trabecular bone mineral content (BMC) and bone volume/tissue volume (BV/TV, %) were quantified from data obtained by the µCT. All values are expressed as mean ± S.E.M. ^#<i>P</i><0.05 compared with the Sham group;^*<i>P</i><0.05 compared with the OVX group.</p