Graph Reasoning Transformer for Image Parsing

Capturing the long-range dependencies has empirically proven to be effective on a wide range of computer vision tasks. The progressive advances on this topic have been made through the employment of the transformer framework with the help of the multi-head attention mechanism. However, the attention-based image patch interaction potentially suffers from problems of redundant interactions of intra-class patches and unoriented interactions of inter-class patches. In this paper, we propose a novel Graph Reasoning Transformer (GReaT) for image parsing to enable image patches to interact following a relation reasoning pattern. Specifically, the linearly embedded image patches are first projected into the graph space, where each node represents the implicit visual center for a cluster of image patches and each edge reflects the relation weight between two adjacent nodes. After that, global relation reasoning is performed on this graph accordingly. Finally, all nodes including the relation information are mapped back into the original space for subsequent processes. Compared to the conventional transformer, GReaT has higher interaction efficiency and a more purposeful interaction pattern. Experiments are carried out on the challenging Cityscapes and ADE20K datasets. Results show that GReaT achieves consistent performance gains with slight computational overheads on the state-of-the-art transformer baselines.Comment: Accepted in ACM MM202

Analyzing the Hardware-Software Implications of Multi-modal DNN Workloads using MMBench

The explosive growth of various types of big data and advances in AI technologies have catalyzed a new type of applications called multi-modal DNNs. Multi-modal DNNs are capable of interpreting and reasoning about information from multiple modalities, making them more applicable to real-world AI scenarios. In recent research, multi-modal DNNs have outperformed the best uni-modal DNN in a wide range of applications from traditional multimedia to emerging autonomous systems. However, despite their importance and superiority, very limited research attention has been devoted to understand the characteristics of multi-modal DNNs and their implications on current computing software/hardware platforms. To facilitate research and advance the understanding of these multi-modal DNN workloads, we first present MMbench, an open-source benchmark suite consisting of a set of real-world multi-modal DNN workloads with relevant performance metrics for evaluation. Then we use MMbench to conduct an in-depth analysis on the characteristics of multi-modal DNNs. We study their implications on application and programming framework, operating and scheduling system, as well as execution hardware. Finally, we conduct a case study and extend our benchmark to edge devices. We hope that our work can provide guidance for future software/hardware design and optimization to underpin multi-modal DNNs on both cloud and edge computing platforms

Activation of β-Adrenoceptors by Dobutamine May Induce a Higher Expression of Peroxisome Proliferator-Activated Receptors δ (PPARδ) in Neonatal Rat Cardiomyocytes

Recent evidence showed the role of peroxisome proliferator-activated receptors (PPARs) in cardiac function. Cardiac contraction induced by various agents is critical in restoring the activity of peroxisome proliferator-activated receptors δ (PPARδ) in cardiac myopathy. Because dobutamine is an agent widely used to treat heart failure in emergency setting, this study is aimed to investigate the change of PPARδ in response to dobutamine. Neonatal rat cardiomyocytes were used to examine the effects of dobutamine on PPARδ expression levels and cardiac troponin I (cTnI) phosphorylation via Western blotting analysis. We show that treatment with dobutamine increased PPARδ expression and cTnI phosphorylation in a time- and dose-dependent manner in neonatal rat cardiomyocytes. These increases were blocked by the antagonist of β1-adrenoceptors. Also, the action of dobutamine was related to the increase of calcium ions and diminished by chelating intracellular calcium. Additionally, dobutamine-induced action was reduced by the inhibition of downstream messengers involved in this calcium-related pathway. Moreover, deletion of PPARδ using siRNA generated the reduction of cTnI phosphorylation in cardiomyocytes treated with dobutamine. Thus, we concluded that PPARδ is increased by dobutamine in cardiac cells

Cascaded deep monocular 3D human pose estimation with evolutionary training data

End-to-end deep representation learning has achieved remarkable accuracy for monocular 3D human pose estimation, yet these models may fail for unseen poses with limited and fixed training data. This paper proposes a novel data augmentation method that: (1) is scalable for synthesizing massive amount of training data (over 8 million valid 3D human poses with corresponding 2D projections) for training 2D-to-3D networks, (2) can effectively reduce dataset bias. Our method evolves a limited dataset to synthesize unseen 3D human skeletons based on a hierarchical human representation and heuristics inspired by prior knowledge. Extensive experiments show that our approach not only achieves state-of-the-art accuracy on the largest public benchmark, but also generalizes significantly better to unseen and rare poses. Code, pre-trained models and tools are available at this HTTPS URL.Comment: Accepted to CVPR 2020 as Oral Presentatio

SORTING NEXIN 1 Functions in Plant Salt Stress Tolerance Through Changes of NO Accumulation by Regulating NO Synthase-Like Activity

Nitric oxide (NO) production via NO synthase (NOS) plays a vital role in plant tolerance to salt stress. However, the factor(s) regulating NOS-like activity in plant salt stress tolerance remains elusive. Here, we show that Arabidopsis SORTING NEXIN 1 (SNX1), which can restore H2O2-induced NO accumulation in yeast Δsnx4 mutant, functions in plant salt stress tolerance. Salt stress induced NO accumulation through promoted NOS-like activity in the wild type, but this induction was repressed in salt-stressed snx1-2 mutant with the mutation of SNX1 because NOS-like activity was inhibited in the mutant. Consistently, snx1-2 displayed reduced tolerance to high salinity with decreased survival rate compared with the wild type, and exogenous treatment with NO donor significantly rescued the hypersensitivity of the mutant to salt stress. In addition, the snx1-2 mutant with reduced NOS-like activity repressed the expression of stress-responsive genes, decreased proline accumulation and anti-oxidant ability compared with wild-type plants when subjected to salt stress. Taken together with our finding that salt induces the expression of SNX1, our results reveal that SNX1 plays a crucial role in plant salt stress tolerance by regulating NOS-like activity and thus NO accumulation

Navigated intramedullary nailing for patients with intertrochanteric hip fractures is cost-effective at high-volume hospitals in mainland China: A markov decision analysis

ObjectivePrevious studies have reported that navigation systems can improve clinical outcomes of intramedullary nailing (IMN) for patients with intertrochanteric fractures. However, information is lacking regarding the relationship between the costs of navigated systems and clinical outcomes. The present research aimed to evaluate the cost-effectiveness of navigated IMN as compared with traditional freehand IMN for patients with intertrochanteric fractures.MethodsA Markov decision model with a 5-year time horizon was constructed to investigate the costs, clinical outcomes and incremental cost-effectiveness ratio (ICER) of navigated IMN for a 70-year-old patient with an intertrochanteric fracture in mainland China. The costs [Chinese Yuan (¥)], health utilities (quality-adjusted life-years, QALYs) and transition probabilities were obtained from published studies. The willingness-to-pay threshold for ICER was set at ¥1,40,000/QALY following the Chinese gross domestic product in 2020. Three institutional surgical volumes were used to determine the average navigation-related costs per patient: low volume (100 cases), medium volume (200 cases) and high volume (300 cases).ResultsInstitutes at which 300, 200 and 100 cases of navigated IMN were performed per year showed an ICER of ¥43,149/QALY, ¥76,132.5/QALY and ¥1,75,083/QALY, respectively. Navigated IMN would achieve cost-effectiveness at institutes with an annual volume of more than 125 cases.ConclusionsOur analysis demonstrated that the navigated IMN could be cost-effective for patients with inter-trochanteric fracture as compared to traditional freehand IMN. However, the cost-effectiveness was more likely to be achieved at institutes with a higher surgical volume