Internet of Things (IoT) aims to bring every object (eg, smart cameras, wearable, environmental sensors, home appliances, and vehicles) online, hence generating massive volume of data that can overwhelm storage systems and data analytics applications. Cloud computing offers services at the infrastructure level that can scale to IoT storage and processing requirements. However, there are applications such as health monitoring and emergency response that require low latency, and delay that is caused by transferring data to the cloud and then back to the application can seriously impact their performances. To overcome this limitation, Fog computing paradigm has been proposed, where cloud services are extended to the edge of the network to decrease the latency and network congestion. To realize the full potential of Fog and IoT paradigms for real‐time analytics, several challenges need to be addressed. The first and most critical problem is designing resource management techniques that determine which modules of analytics applications are pushed to each edge device to minimize the latency and maximize the throughput. To this end, we need an evaluation platform that enables the quantification of performance of resource management policies on an IoT or Fog computing infrastructure in a repeatable manner. In this paper we propose a simulator, called iFogSim, to model IoT and Fog environments and measure the impact of resource management techniques in latency, network congestion, energy consumption, and cost. We describe two case studies to demonstrate modeling of an IoT environment and comparison of resource management policies. Moreover, scalability of the simulation toolkit of RAM consumption and execution time is verified under different circumstances.
While a number of studies have documented the importance of microglia in central nervous system (CNS) response to injury, infection and disease, little is known regarding its role in viral encephalitis. We therefore, exploited an experimental model of Japanese Encephalitis, to better understand the role played by microglia in Japanese Encephalitis Virus (JEV) infection. Lectin staining performed to assess microglial activation indicated a robust increase in reactive microglia following infection. A difference in the topographic distribution of activated, resting, and phagocytic microglia was also observed. The levels of various proinflammatory mediators, such as inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (Cox-2), IL-6, IL-1beta, TNF-alpha, and MCP-1 that have been implicated in microglial response to an activational state was significantly elevated following infection. These cytokines exhibited region selective expression in the brains of infected animals, with the highest expression observed in the hippocampus. Moreover, the expression of neuronal specific nuclear protein NeuN was markedly downregulated during progressive infection indicating neuronal loss. In vitro studies further confirmed that microglial activation and subsequent release of various proinflammatory mediators induces neuronal death following JEV infection. Although initiation of immune responses by microglial cells is an important protective mechanism in the CNS, unrestrained inflammatory responses may result in irreparable brain damage. Our findings suggest that the increased microglial activation following JEV infection influences the outcome of viral pathogenesis. It is likely that the increased microglial activation triggers bystander damage, as the animals eventually succumb to infection.
Abstract-The Internet of Everything (IoE) solutions gradually bring every object online, and processing data in centralized cloud does not scale to requirements of such environment. This is because, there are applications such as health monitoring and emergency response that require low latency and delay caused by transferring data to the cloud and then back to the application can seriously impact the performance. To this end, Fog computing has emerged, where cloud computing is extended to the edge of the network to decrease the latency and network congestion. Fog computing is a paradigm for managing a highly distributed and possibly virtualized environment that provides compute and network services between sensors and cloud data centers. This chapter provides background and motivations on emergence of Fog computing and defines its key characteristics. In addition, a reference architecture for Fog computing is presented and recent related development and applications are discussed.
The ability to identify directional interactions that occur among multiple neurons in the brain is crucial to an understanding of how groups of neurons cooperate in order to generate specific brain functions. However, an optimal method of assessing these interactions has not been established. Granger causality has proven to be an effective method for the analysis of the directional interactions between multiple sets of continuous-valued data, but cannot be applied to neural spike train recordings due to their discrete nature. This paper proposes a point process framework that enables Granger causality to be applied to point process data such as neural spike trains. The proposed framework uses the point process likelihood function to relate a neuron's spiking probability to possible covariates, such as its own spiking history and the concurrent activity of simultaneously recorded neurons. Granger causality is assessed based on the relative reduction of the point process likelihood of one neuron obtained excluding one of its covariates compared to the likelihood obtained using all of its covariates. The method was tested on simulated data, and then applied to neural activity recorded from the primary motor cortex (MI) of a Felis catus subject. The interactions present in the simulated data were predicted with a high degree of accuracy, and when applied to the real neural data, the proposed method identified causal relationships between many of the recorded neurons. This paper proposes a novel method that successfully applies Granger causality to point process data, and has the potential to provide unique physiological insights when applied to neural spike trains.
Despite recent advances in understanding molecular mechanisms involved in glioblastoma progression, the prognosis of the most malignant brain tumor continues to be dismal. Because the flavonoid kaempferol is known to suppress growth of a number of human malignancies, we investigated the effect of kaempferol on human glioblastoma cells. Kaempferol induced apoptosis in glioma cells by elevating intracellular oxidative stress. Heightened oxidative stress was characterized by an increased generation of reactive oxygen species (ROS) accompanied by a decrease in oxidant-scavenging agents such as superoxide dismutase (SOD-1) and thioredoxin (TRX-1). Knockdown of SOD-1 and TRX-1 expression by small interfering RNA (siRNA) increased ROS generation and sensitivity of glioma cells to kaempferol-induced apoptosis. Signs of apoptosis included decreased expression of Bcl-2 and altered mitochondrial membrane potential with elevated active caspase-3 and cleaved poly(ADP-ribose) polymerase expression. Plasma membrane potential and membrane fluidity were altered in kaempferol-treated cells. Kaempferol suppressed the expression of proinflammatory cytokine interleukin-6 and chemokines interleukin-8, monocyte chemoattractant protein-1, and regulated on activation, normal T-cell expressed and secreted. Kaempferol inhibited glioma cell migration in a ROS-dependent manner. Importantly, kaempferol potentiated the toxic effect of chemotherapeutic agent doxorubicin by amplifying ROS toxicity and decreasing the efflux of doxorubicin. Because the toxic effect of both kaempferol and doxorubicin was amplified when used in combination, this study raises the possibility of combinatorial therapy whose basis constitutes enhancing redox perturbation as a strategy to kill glioma cells. [Mol Cancer Ther 2007;6(9):2544 -53]
Charge carrier transport in organic semiconductors is at the heart of many revolutionary technologies ranging from organic transistors, light-emitting diodes, flexible displays and photovoltaic cells. Yet, the nature of charge carriers and their transport mechanism in these materials is still unclear. Here we show that by solving the time-dependent electronic Schrödinger equation coupled to nuclear motion for eight organic molecular crystals, the excess charge carrier forms a polaron delocalized over up to 10–20 molecules in the most conductive crystals. The polaron propagates through the crystal by diffusive jumps over several lattice spacings at a time during which it expands more than twice its size. Computed values for polaron size and charge mobility are in excellent agreement with experimental estimates and correlate very well with the recently proposed transient localization theory.
Rosmarinic acid (RA) reduced the mortality of mice infected with Japanese encephalitis virus (JEV). Significant decreases in viral loads (P < 0.001) and proinflammatory cytokine levels (P < 0.001) were observed in JEV-infected animals treated with RA compared to levels in infected mice without treatment, at 8 to 9 days postinfection.
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