68 resultados para Continuous progression


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In this paper, the design of a new solar operated adsorption cooling system with two identical small and one large adsorber beds, which is capable of producing cold continuously, has been proposed. In this system, cold energy is stored in the form of refrigerant in a separate refrigerant storage tank at ambient temperature. Silica gel water is used as a working pair and system is driven by solar energy. The operating principle is described in details and its thermodynamic transient analysis is presented. Effect of COP and SCE for different adsorbent mass and adsorption/desorption time of smaller beds are discussed. Recommended mass and number of cycles of operation for smaller beds to attain continuous cooling with average COP and SCE of 0.63 and 337.5 kJ/kg, respectively are also discussed, at a generation, condenser and evaporator temperatures of 368 K, 303 K and 283 K, respectively. (C) 2015 Elsevier Ltd. All rights reserved.

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Polycyclic aromatic molecules such as ellipticine intercalate into double-stranded DNA and interfere with physiological functions. In the present study, we evaluate the chemotherapeutic potential of MPTQ on animal models and its mode of action. In order to test the antitumor activity, monohydrochloride of MPTQ was orally administered in mice bearing tumor. Results showed a significant inhibition of tumor growth compared to that of untreated controls. More importantly, mean lifespan of tumor bearing animals treated with MPTQ was significantly higher as compared to that of untreated tumor bearing mice suggesting that the treatment affected viability of cancerous cells, but not of normal cells. Consistent with this, we find that administration of MPTQ to normal mice did not cause any major side effects as observed upon hematological and serum profiling. We also found that MPTQ induces cytotoxicity in cancer cell lines, by activating apoptosis both by intrinsic and extrinsic pathways. Thus, MPTQ could be used as a potential cancer therapeutic agent. (c) 2011 Wiley Periodicals, Inc.

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We demonstrate in here a powerful scalable technology to synthesize continuously high quality CdSe quantum dots (QDs) in supercritical hexane. Using a low cost, highly thermally stable Cd-precursor, cadmium deoxycholate, the continuous synthesis is performed in 400 mu m ID stainless steel capillaries resulting in CdSe QDs having sharp full-width-at-half-maxima (23 nm) and high photoluminescence quantum yields (45-55%). Transmission electron microscopy images show narrow particles sizes distribution (sigma <= 5%) with well-defined crystal lattices. Using two different synthesis temperatures (250 degrees C and 310 degrees C), it was possible to obtain zinc blende and wurtzite crystal structures of CdSe QDs, respectively. This synthetic approach allows achieving substantial production rates up to 200 mg of QDs per hour depending on the targeted size, and could be easily scaled to gram per hour.

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In this article, we study risk-sensitive control problem with controlled continuous time Markov chain state dynamics. Using multiplicative dynamic programming principle along with the atomic structure of the state dynamics, we prove the existence and a characterization of optimal risk-sensitive control under geometric ergodicity of the state dynamics along with a smallness condition on the running cost.

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The current day networks use Proactive networks for adaption to the dynamic scenarios. The use of cognition technique based on the Observe, Orient, Decide and Act loop (OODA) is proposed to construct proactive networks. The network performance degradation in knowledge acquisition and malicious node presence is a problem that exists. The use of continuous time dynamic neural network is considered to achieve cognition. The variance in service rates of user nodes is used to detect malicious activity in heterogeneous networks. The improved malicious node detection rates are proved through the experimental results presented in this paper. (C) 2015 The Authors. Published by Elsevier B.V.

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Scalable stream processing and continuous dataflow systems are gaining traction with the rise of big data due to the need for processing high velocity data in near real time. Unlike batch processing systems such as MapReduce and workflows, static scheduling strategies fall short for continuous dataflows due to the variations in the input data rates and the need for sustained throughput. The elastic resource provisioning of cloud infrastructure is valuable to meet the changing resource needs of such continuous applications. However, multi-tenant cloud resources introduce yet another dimension of performance variability that impacts the application's throughput. In this paper we propose PLAStiCC, an adaptive scheduling algorithm that balances resource cost and application throughput using a prediction-based lookahead approach. It not only addresses variations in the input data rates but also the underlying cloud infrastructure. In addition, we also propose several simpler static scheduling heuristics that operate in the absence of accurate performance prediction model. These static and adaptive heuristics are evaluated through extensive simulations using performance traces obtained from Amazon AWS IaaS public cloud. Our results show an improvement of up to 20% in the overall profit as compared to the reactive adaptation algorithm.

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This paper discusses dynamic modeling of non-isolated DC-DC converters (buck, boost and buck-boost) under continuous and discontinuous modes of operation. Three types of models are presented for each converter, namely, switching model, average model and harmonic model. These models include significant non-idealities of the converters. The switching model gives the instantaneous currents and voltages of the converter. The average model provides the ripple-free currents and voltages, averaged over a switching cycle. The harmonic model gives the peak to peak values of ripple in currents and voltages. The validity of all these models is established by comparing the simulation results with the experimental results from laboratory prototypes, at different steady state and transient conditions. Simulation based on a combination of average and harmonic models is shown to provide all relevant information as obtained from the switching model, while consuming less computation time than the latter.

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Medicinal plants are considered as one of the ideal sources for cancer therapy due to their bioactive contents and low toxicity to humans. Vernonia genus is one of the common medicinal plants, which has wide spread usage in food and medicine. However, there are limited studies to explore its anticancer properties. In the current study, we have used Vernonia condensata, to explore its anticancer activity using various approaches. Here, we show that extract prepared from Vernonia condensata (VCE) exhibits cytotoxic properties against various cancer cells in a dose- and time-dependent manner. Interestingly, when treated with VCE, there was no significant cytotoxicity in peripheral blood mononuclear cells (PBMCs). Flow cytometry analysis revealed that although VCE induced cell death, arrest was not observed. VCE treatment led to disruption of mitochondrial membrane potential in a concentration dependent manner resulting in activation of apoptosis culminating in cell death. Immunoblotting studies revealed that VCE activated intrinsic pathway of apoptosis. More importantly, VCE treatment resulted in tumor regression leading to significant enhancement in life span in treated mice, without showing any detectable side effects. Therefore, for the first time our study reveals the potential of extract from Vernonia condensata to be used as an anticancer agent.