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Background/Aims: Recent studies indicate that therapies targeting the vasculature can significantly sensitize tumors to radiation. Ultrasound-stimulated microbubbles (USMBs) are regarded as a promising radiosensitizer. In this study, we investigated the effect of USMBs on the sensitivity of nasopharyngeal carcinoma (NPC) to radiation. Methods: Human NPC (CNE-2) cells and human umbilical vein endothelial cells (HUVECs) were exposed to radiation (0, 2, and 8 Gy) alone or in combination with USMBs. Cell viability and apoptosis were measured with the MTT assay and flow cytometry, respectively. The angiogenic activity of HUVECs was detected using matrigel tubule formation. The in vitro effects induced by these treatments were confirmed in vivo with xenograft models of CNE-2 cells in nude mice by examining vascular integrity using color Doppler flow imaging and cell survival using immunohistochemistry. Additionally, the in vivo and in vitro expressions of angiotensin II (ANG II) and its receptor (AT1R) were detected by immunohistochemistry and western blotting, respectively. With CNE-2 cells and HUVECs transfected with control, ANG II, or AT1R, perindopril (an inhibitor of angiotensin-converting enzyme) and candesartan (an inhibitor of AT1R) were used to verify the role of ANG II and AT1R in the radiosensitivity of tumor and endothelial cells by USMBs, by determining cell viability and apoptosis and angiogenic activity. Results: In the NPC xenografts, USMBs slightly reduced blood flow and CD34 expression, increased tumor cell death and ANG II and AT1R expression, and significantly enhanced the effects of radiation. With CNE-2 cells and HUVECs, the USMBs further enhanced the inhibition of tumor cell viability and endothelial tubule formation and further enhanced the increase in ANG II and AT1R due to radiation. Furthermore, perindopril and candesartan significantly enhanced the inhibitory effect of radiation and USMBs on tumor cell growth and angiogenesis in vitro. Conclusions: We have demonstrated for the first time that USMB exposure can significantly enhance the destructive effect on NPC of radiation, and this effect might be further increased by ANG II and AT1R inhibition. Our findings suggest that USMBs can be used as a promising sensitizer of radiotherapy to treat NPC, and the clinical effect might be increased by ANG II and AT1R inhibition. [ABSTRACT FROM AUTHOR]

This study constructs and investigates the non-fragile asynchronous H ∞ control for uncertain stochastic memory systems with Bernoulli distribution. The system not only contains the randomly occurring uncertainties of all parameters (ROUAPs) and stochastic disturbances in the system model, but also includes randomly gain perturbations in the controller. By introducing the stochastic variables, a new model structure is built obeying Bernoulli distribution to describe the system and the controller. Moreover, a modified Lyapunov–Krasovskii function (LKF) is constructed, combining Itô’s differential formula and free-weighting matrix method, less conservative results are presented in terms of the linear matrix inequality (LMI). Furthermore, an observer-based non-fragile asynchronous H ∞ controller is designed without any limits on the system parameters. Finally, three numerical examples are provided to demonstrate the effectiveness and feasibility of the proposed results. [ABSTRACT FROM AUTHOR]

Our paper considers the following fundamental scheduling problem. There are n deterministic jobs to be scheduled offline on multiple identical machines, which have bounded capacities. Each job is associated with a start-time, an end-time, a process time, and demand for machine capacity. The goal is to schedule all of the jobs non-preemptively in their start-time-end-time windows, subject to machine capacity constraints such that the total busy time of the machines is minimized. We refer to this problem as minimizing the total busy time for the scheduling of multiple identical machines (MinTBT). This problem has important applications in power-aware scheduling for Cloud computing, optical network design, customer service systems, and other related areas. Scheduling to minimize busy times is already NP-hard in the special case where all jobs have the same process time and can be scheduled in a fixed time interval. One best-known result for this problem is a 5-approximation algorithm for special instances using first-fit-decreasing algorithm. In this paper, we propose and prove a 3-approximation algorithm, modified first-fit-decreasing-earliest for the general case and obtain more results for special cases. We then show how our results are applied in cloud computing to improve the energy efficiency. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Resource scheduling in infrastructure as a service (IaaS) is one of the keys for large-scale Cloud applications. Extensive research on all issues in real environment is extremely difficult because it requires developers to consider network infrastructure and the environment, which may be beyond the control. In addition, the network conditions cannot be predicted or controlled. Therefore, performance evaluation of workload models and Cloud provisioning algorithms in a repeatable manner under different configurations and requirements is difficult. There is still lack of tools that enable developers to compare different resource scheduling algorithms in IaaS regarding both computing servers and user workloads. To fill this gap in tools for evaluation and modeling of Cloud environments and applications, we propose CloudSched. CloudSched can help developers identify and explore appropriate solutions considering different resource scheduling algorithms. Unlike traditional scheduling algorithms considering only one factor such as CPU, which can cause hotspots or bottlenecks in many cases, CloudSched treats multidimensional resource such as CPU, memory and network bandwidth integrated for both physical machines and virtual machines (VMs) for different scheduling objectives (algorithms). In this paper, two existing simulation systems at application level for Cloud computing are studied, a novel lightweight simulation system is proposed for real-time VM scheduling in Cloud data centers, and results by applying the proposed simulation system are analyzed and discussed. [ABSTRACT FROM PUBLISHER]