Proof of the deadlock-freeness of ALD routing algorithm

This is the appendix to the paper Load-Balanced Adaptive Routing for Torus Networks to provide a detailed, formal proof of the deadlock-freeness of the routing algorithm proposed in the paper. The paper is submitted to Electronics Letters, and the abstract of which is as follows: A new routing algorithm for torus interconnection networks to achieve high throughput on various traffic patterns, Adaptive Load-balanced routing with cycle Detection (ALD), is presented. Instead of the -channels scheme adopted in a few recently proposed algorithms of the same category, a cycle detection scheme is employed in ALD to handle deadlock, which leads to higher routing adaptability. Simulation results demonstrate that ALD achieves higher throughput than the recently proposed algorithms on both benign and adversarial traffic patterns

A Submodular Optimization Framework for Outage-Aware Cell Association in Heterogeneous Cellular Networks

In cellular heterogeneous networks (HetNets), offloading users to small cell base stations (SBSs) leads to a degradation in signal to interference plus noise ratio (SINR) and results in high outage probabilities for offloaded users. In this paper, we propose a novel framework to solve the cell association problem with the intention of improving user outage performance while achieving load balancing across different tiers of BSs. We formulate a combinatorial utility maximization problem with weighted BS loads that achieves proportional fairness among users and also takes into account user outage performance. A formulation of the weighting parameters is proposed to discourage assigning users to BSs with high outage probabilities. In addition, we show that the combinatorial optimization problem can be reformulated as a monotone submodular maximization problem and it can be readily solved via a greedy algorithm with lazy evaluations. The obtained solution offers a constant performance guarantee to the cell association problem. Simulation results show that our proposed approach leads to over 30% reduction in outage probabilities for offloaded users and achieves load balancing across macrocell and small cell BSs

Outlier-Robust Gromov-Wasserstein for Graph Data

Gromov-Wasserstein (GW) distance is a powerful tool for comparing and aligning probability distributions supported on different metric spaces. Recently, GW has become the main modeling technique for aligning heterogeneous data for a wide range of graph learning tasks. However, the GW distance is known to be highly sensitive to outliers, which can result in large inaccuracies if the outliers are given the same weight as other samples in the objective function. To mitigate this issue, we introduce a new and robust version of the GW distance called RGW. RGW features optimistically perturbed marginal constraints within a Kullback-Leibler divergence-based ambiguity set. To make the benefits of RGW more accessible in practice, we develop a computationally efficient and theoretically provable procedure using Bregman proximal alternating linearized minimization algorithm. Through extensive experimentation, we validate our theoretical results and demonstrate the effectiveness of RGW on real-world graph learning tasks, such as subgraph matching and partial shape correspondence

Fast and Provably Convergent Algorithms for Gromov-Wasserstein in Graph Data

In this paper, we study the design and analysis of a class of efficient algorithms for computing the Gromov-Wasserstein (GW) distance tailored to large-scale graph learning tasks. Armed with the Luo-Tseng error bound condition~\citep{luo1992error}, two proposed algorithms, called Bregman Alternating Projected Gradient (BAPG) and hybrid Bregman Proximal Gradient (hBPG) enjoy the convergence guarantees. Upon task-specific properties, our analysis further provides novel theoretical insights to guide how to select the best-fit method. As a result, we are able to provide comprehensive experiments to validate the effectiveness of our methods on a host of tasks, including graph alignment, graph partition, and shape matching. In terms of both wall-clock time and modeling performance, the proposed methods achieve state-of-the-art results

Insufficient Radiofrequency Ablation Promotes Angiogenesis of Residual Hepatocellular Carcinoma Via HIF-1α/VEGFA

Background: The mechanism of rapid growth of the residual tumor after radiofrequency (RF) ablation is poorly understood. In this study, we investigated the effect of hyperthermia on HepG2 cells and generated a subline with enhanced viability and dys-regulated angiogenesis in vivo, which was used as a model to further determine the molecular mechanism of the rapid growth of residual HCC after RF ablation. Methodology/Principal Findings: Heat treatment was used to establish sublines of HepG2 cells. A subline (HepG2 k) with a relatively higher viability and significant heat tolerance was selected. The cellular protein levels of VEGFA, HIF-1α and p-Akt, VEGFA mRNA and secreted VEGFA were measured, and all of these were up-regulated in this subline compared to parental HepG2 cells. HIF-1α inhibitor YC-1 and VEGFA siRNA inhibited the high viability of the subline. The conditioned media from the subline exerted stronger pro-angiogenic effects. Bevacizumab, VEGFA siRNA and YC-1 inhibited proangiogenic effects of the conditioned media of HepG2 k cells and abolished the difference between parental HepG2 cells and HepG2 k cells. For in vivo studies, a nude mouse model was used, and the efficacy of bavacizumab was determined. HepG2 k tumor had stronger pro-angiogenic effects than parental HepG2 tumor. Bevacizumab could inhibit the tumor growth and angiogenesis, and also eliminate the difference in tumor growth and angiogenesis between parental HepG2 tumor and HepG2 k tumor in vivo. Conclusions/Significance: The angiogenesis induced by HIF1α/VEGFA produced by altered cells after hyperthermia treatment may play an important role in the rapid growth of residual HCC after RF ablation. Bevacizumab may be a good candidate drug for preventing and treating the process

High density lipoprotein promotes proliferation of adipose-derived stem cells via S1P1 receptor and Akt, ERK1/2 signal pathways

Introduction: Adipose-derived stem cells (ADSC) are non-hematopoietic mesenchymal stem cells that have shown great promise in their ability to differentiate into multiple cell lineages. Their ubiquitous nature and the ease of harvesting have attracted the attention of many researchers, and they pose as an ideal candidate for applications in regenerative medicine. Several reports have demonstrated that transplanting ADSC can promote repair of injured tissue and angiogenesis in animal models. Survival of these cells after transplant remains a key limiting factor for the success of ADSC transplantation. Circulating factors like High Density Lipoprotein (HDL) has been known to promote survival of other stems cells like bone marrow derived stem cells and endothelial progenitor cells, both by proliferation and by inhibiting cell apoptosis. The effect of HDL on transplanted adipose-derived stem cells in vivo is largely unknown. Methods: This study focused on exploring the effects of plasma HDL on ADSC and delineating the mechanisms involved in their proliferation after entering the bloodstream. Using the MTT and BrdU assays, we tested the effects of HDL on ADSC proliferation. We probed the downstream intracellular Akt and ERK1/2 signaling pathways and expression of cyclin proteins in ADSC using western blot. Results: Our study found that HDL promotes proliferation of ADSC, by binding to sphingosine-1-phosphate receptor-1(S1P1) on the cell membrane. This interaction led to activation of intracellular Akt and ERK1/2 signaling pathways, resulting in increased expression of cyclin D1 and cyclin E, and simultaneous reduction in expression of cyclin-dependent kinase inhibitors p21 and p27, therefore promoting cell cycle progression and cell proliferation. Conclusions: These studies raise the possibility that HDL may be a physiologic regulator of stem cells and increasing HDL concentrations may be valuable strategy to promote ADSC transplantation.'973' National ST Major Project [2011CB503900]; National Natural Science Foundation of China [81270321, 81170101, 81370235]; Natural Science Foundation of Beijing, China [7122106]SCI(E)[email protected]; [email protected]

Mobility influences on the capacity of wireless cellular networks

Capacity has always been a major concern in wireless networks. This letter studies the impact of mobility on the overall system capacity in wireless cellular networks. In this letter we present a simple system model which we developed to capture the inherent relationships among system capacity, new call blocking probability, handoff dropping probability, call terminating probability, and bandwidth utilization rate. We investigate the complex relationship between mobility and capacity-related parameters. Through simulation, we demonstrate that mobility has a significant impact on capacity and is reversely proportional to the bandwidth reserved for handoff traffic

Performance Bounds for P2P Streaming System with

Abstract: In this paper, we develop a fluid model that seeks to expose the fundamental characteristics and mathematical theory of peerto-peer streaming system with transcoding. We find out and prove that, to provide peers receiving data above some flow rate, there is a lower bound of server upload bandwidth in this kind of system. We give a flow rate allocation algorithm to achieve the minimal server upload bandwidth in the proof. We compare this lower bound with the minimal demand of server upload bandwidth of no transcoding system. And, we prove that, the demand of server upload bandwidth in transcoding peer-to-peer streaming system using the proposed algorithm is the necessary (not sufficient) condition for the no transcoding one. At last, we give the simulations experiment to show the difference of server load in transcoding and no transcoding systems