185 research outputs found

    Evolving Optical Networks for Latency-Sensitive Smart-Grid Communications via Optical Time Slice Switching (OTSS) Technologies

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    In this paper, we proposed a novel OTSS-assisted optical network architecture for smart-grid communication networks, which has unique requirements for low-latency connections. Illustrative results show that, OTSS can provide extremely better performance in latency and blocking probability than conventional flexi-grid optical networks.Comment: IEEE Photonics Society 1st Place Best Poster Award, on CLEO-PR/OECC/PGC 201

    GLISP: A Scalable GNN Learning System by Exploiting Inherent Structural Properties of Graphs

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    As a powerful tool for modeling graph data, Graph Neural Networks (GNNs) have received increasing attention in both academia and industry. Nevertheless, it is notoriously difficult to deploy GNNs on industrial scale graphs, due to their huge data size and complex topological structures. In this paper, we propose GLISP, a sampling based GNN learning system for industrial scale graphs. By exploiting the inherent structural properties of graphs, such as power law distribution and data locality, GLISP addresses the scalability and performance issues that arise at different stages of the graph learning process. GLISP consists of three core components: graph partitioner, graph sampling service and graph inference engine. The graph partitioner adopts the proposed vertex-cut graph partitioning algorithm AdaDNE to produce balanced partitioning for power law graphs, which is essential for sampling based GNN systems. The graph sampling service employs a load balancing design that allows the one hop sampling request of high degree vertices to be handled by multiple servers. In conjunction with the memory efficient data structure, the efficiency and scalability are effectively improved. The graph inference engine splits the KK-layer GNN into KK slices and caches the vertex embeddings produced by each slice in the data locality aware hybrid caching system for reuse, thus completely eliminating redundant computation caused by the data dependency of graph. Extensive experiments show that GLISP achieves up to 6.53×6.53\times and 70.77×70.77\times speedups over existing GNN systems for training and inference tasks, respectively, and can scale to the graph with over 10 billion vertices and 40 billion edges with limited resources

    Short-term safety or long-term failure? Empirical evidence of the impact of securitization on bank risk

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    Based on a sample of U.S. commercial banks from 2002 to 2012, this paper shows that bank loan securitization has a significant and positive impact on both Z-scores and the likelihood of bank failure, indicating a short-term risk reduction and a long-term risk increase effect. We also find disparate impacts between mortgage and non-mortgage securitization. Loan sale activities are found to have a similar impact to securitization

    Deformation and damage properties of rock-like materials subjected to multi-level loading-unloading cycles

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    In the process of engineering construction such as tunnels and slopes, rock mass is frequently subjected to multiple levels of loading and unloading, while previous research ignores the impact of unloading rate on the stability of rock mass. A number of uniaxial multi-level cyclic loading-unloading experiments were conducted to better understand the effect of unloading rate on the deformation behavior, energy evolution, and damage properties of rock-like material. The experimental results demonstrated that the unloading rate and relative cyclic number clearly influence the deformation behavior and energy evolution of rock-like samples. In particular, as the relative cyclic number rises, the total strain and reversible strain both increase linearly, while the total energy density, elastic energy density, and dissipated energy density all rise nonlinearly. In contrast, the irreversible strain first decreases quickly, then stabilizes, and finally rises slowly. As the unloading rate increases, the total strain and reversible strain both increase, while the irreversible strain decreases. The dissipated energy damage was examined in light of the aforementioned experimental findings. The accuracy of the proposed damage model, which takes into account the impact of the unloading rate and relative cyclic number, is then confirmed by examining the consistency between the model predicted and the experimental results. The proposed damage model will make it easier to foresee how the multi-level loading-unloading cycles will affect the rock-like materials

    Traditional Chinese Medicine syndrome-related herbal prescriptions in treatment of malignant tumors

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    AbstractObjectiveTo investigate the distribution characteristics of TCM syndromes and the related herbal prescriptions for malignant tumors (MT).MethodsA clinical database of the TCM syndromes and the herbal prescriptions in treatment of 136 MT patients were established. The data were then analyzed using cluster and frequency analysis.ResultsAccording to the cluster analysis, the TCM syndromes in MT patients mainly included two patterns: deficiency of both Qi and Yin and internal accumulation of toxic heat. The commonly-prescribed herbs were Huangqi (Astraglus), Nüzhenzi (Fructus Ligustri Lucidi), Lingzhi (Ganoderma Lucidum), Huaishan (Dioscorea Opposita), Xiakucao (Prunella Vulgaris), and Baihuasheshecao (Herba Hedyotidis).ConclusionDeficiency of Qi and Yin is the primary syndrome of MT, and internal accumulation of toxic heat is the secondary syndrome. The herbs for Qi supplementation and Yin nourishment are mainly used, with the assistance of herbs for heat-clearance and detoxification

    Progress in biological and medical research in the deep underground: an update

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    As the growing population of individuals residing or working in deep underground spaces for prolonged periods, it has become imperative to understand the influence of factors in the deep underground environment (DUGE) on living systems. Heping Xie has conceptualized the concept of deep underground medicine to identify factors in the DUGE that can have either detrimental or beneficial effects on human health. Over the past few years, an increasing number of studies have explored the molecular mechanisms that underlie the biological impacts of factors in the DUGE on model organisms and humans. Here, we present a summary of the present landscape of biological and medical research conducted in deep underground laboratories and propose promising avenues for future investigations in this field. Most research demonstrates that low background radiation can trigger a stress response and affect the growth, organelles, oxidative stress, defense capacity, and metabolism of cells. Studies show that residing and/or working in the DUGE has detrimental effects on human health. Employees working in deep mines suffer from intense discomfort caused by high temperature and humidity, which increase with depth, and experience fatigue and sleep disturbance. The negative impacts of the DUGE on human health may be induced by changes in the metabolism of specific amino acids; however, the cellular pathways remain to be elucidated. Biological and medical research must continue in deep underground laboratories and mines to guarantee the safe probing of uncharted depths as humans utilize the deep underground space
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