981 resultados para Marker assisted selection


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In a system with energy harvesting (EH) nodes, the design focus shifts from minimizing energy consumption by infrequently transmitting less information to making the best use of available energy to efficiently deliver data while adhering to the fundamental energy neutrality constraint. We address the problem of maximizing the throughput of a system consisting of rate-adaptive EH nodes that transmit to a destination. Unlike related literature, we focus on the practically important discrete-rate adaptation model. First, for a single EH node, we propose a discrete-rate adaptation rule and prove its optimality for a general class of stationary and ergodic EH and fading processes. We then study a general system with multiple EH nodes in which one is opportunistically selected to transmit. We first derive a novel and throughput-optimal joint selection and rate adaptation rule (TOJSRA) when the nodes are subject to a weaker average power constraint. We then propose a novel rule for a multi-EH node system that is based on TOJSRA, and we prove its optimality for stationary and ergodic EH and fading processes. We also model the various energy overheads of the EH nodes and characterize their effect on the adaptation policy and the system throughput.

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The selective formation of a single isomer of a 3+2] self-assembled organic cage from a reaction mixture of an unsymmetrical aldehyde and a flexible amine is discussed. The experimental and theoretical findings suggest that in such a process, the geometric features of the aldehyde play a key role.

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In several wireless sensor networks, it is of interest to determine the maximum of the sensor readings and identify the sensor responsible for it. We propose a novel, decentralized, scalable, energy-efficient, timer-based, one-shot max function computation (TMC) algorithm. In it, the sensor nodes do not transmit their readings in a centrally pre-defined sequence. Instead, the nodes are grouped into clusters, and computation occurs over two contention stages. First, the nodes in each cluster contend with each other using the timer scheme to transmit their reading to their cluster-heads. Thereafter, the cluster-heads use the timer scheme to transmit the highest sensor reading in their cluster to the fusion node. One new challenge is that the use of the timer scheme leads to collisions, which can make the algorithm fail. We optimize the algorithm to minimize the average time required to determine the maximum subject to a constraint on the probability that it fails to find the maximum. TMC significantly lowers average function computation time, average number of transmissions, and average energy consumption compared to approaches proposed in the literature.

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Opportunistic selection in multi-node wireless systems improves system performance by selecting the ``best'' node and by using it for data transmission. In these systems, each node has a real-valued local metric, which is a measure of its ability to improve system performance. Our goal is to identify the best node, which has the largest metric. We propose, analyze, and optimize a new distributed, yet simple, node selection scheme that combines the timer scheme with power control. In it, each node sets a timer and transmit power level as a function of its metric. The power control is designed such that the best node is captured even if. other nodes simultaneously transmit with it. We develop several structural properties about the optimal metric-to-timer-and-power mapping, which maximizes the probability of selecting the best node. These significantly reduce the computational complexity of finding the optimal mapping and yield valuable insights about it. We show that the proposed scheme is scalable and significantly outperforms the conventional timer scheme. We investigate the effect of. and the number of receive power levels. Furthermore, we find that the practical peak power constraint has a negligible impact on the performance of the scheme.

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Among the multiple modulatory physical cues explored to regulate cellular processes, the potential of magneto-responsive substrates in magnetic field stimulated stem cell differentiation is still unperceived. In this regard, the present work demonstrates how an external magnetic field can be applied to direct stem cell differentiation towards osteogenic commitment. A new culture methodology involving periodic delivery of 100 mT static magnetic field (SMF) in combination with HA-Fe3O4 magnetic substrates possessing a varying degree of substrate magnetization was designed for the study. The results demonstrate that an appropriate combination of weakly ferromagnetic substrates and SMF exposure enhanced cell viability, DNA synthesis and caused an early switchover to osteogenic lineage as supported by Runx2 immunocytochemistry and ALP expression. However, the mRNA expression profile of early osteogenic markers (Runx2, ALP, Col IA) was comparable despite varying substrate magnetic properties (diamagnetic to ferromagnetic). On the contrary, a remarkable upregulation of late bone development markers (OCN and OPN) was explicitly detected on weak and strongly ferromagnetic substrates. Furthermore, SMF induced matrix mineralization with elevated calcium deposition on similar substrates, even in the absence of osteogenic supplements. More specifically, the role of SMF in increasing intracellular calcium levels and in inducing cell cycle arrest at G0/G1 phase was elucidated as the major molecular event triggering osteogenic differentiation. Taken together, the above results demonstrate the competence of magnetic stimuli in combination with magneto-responsive biomaterials as a potential strategy for stem cell based bone tissue engineering.

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Hypoxia-inducible factor 1 alpha (HIF-1 alpha) is an important transcription factor that regulates different cellular responses to hypoxia. HIF-1 alpha is rapidly degraded by von Hippel-Lindau (VHL) protein under normoxic conditions and stabilized under hypoxia. A common variant of HIF-1 alpha (1772C > T) (rs 11549465) polymorphism, corresponding to an amino acid change from proline to serine at 582 position within the oxygen-dependent degradation domain, results in increased stability of the protein and altered transactivation of its target genes. The present study was aimed to find the association between HIF-1 alpha (1772C > T) (rs 11549465) polymorphism and breast cancer development. For this purpose, 348 primary breast cancer patients and 320 healthy and age-matched controls were genotyped through PCR-RFLP method. The genotype frequencies were compared between patients and controls, and their influence on clinical characteristics of breast cancer patients was analyzed. Our study revealed a significant increase of TT genotype in breast cancer patients compared to controls (p = 0.038). Further, TT genotype and T allele were found to be associated with progesterone receptor (PR)-negative status (p < 0.09). None of the clinical variables revealed significant association with HIF-1 alpha (1772C > T) (rs 11549465) polymorphism.

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Cooperative relaying combined with selection has been extensively studied in the literature to improve the performance of interference-constrained secondary users in underlay cognitive radio (CR). We present a novel symbol error probability (SEP)-optimal amplify-and-forward relay selection rule for an average interference-constrained underlay CR system. A fundamental principle, which is unique to average interference-constrained underlay CR, that the proposed rule brings out is that the choice of the optimal relay is affected not just by the source-to-relay, relay-to-destination, and relay-to-primary receiver links, which are local to the relay, but also by the direct source-to-destination (SD) link, even though it is not local to any relay. We also propose a simpler, practically amenable variant of the optimal rule called the 1-bit rule, which requires just one bit of feedback about the SD link gain to the relays, and incurs a marginal performance loss relative to the optimal rule. We analyze its SEP and develop an insightful asymptotic SEP analysis. The proposed rules markedly outperform several ad hoc SD link-unaware rules proposed in the literature. They also generalize the interference-unconstrained and SD link-unaware optimal rules considered in the literature.

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In geographical forwarding of packets in a large wireless sensor network (WSN) with sleep-wake cycling nodes, we are interested in the local decision problem faced by a node that has ``custody'' of a packet and has to choose one among a set of next-hop relay nodes to forward the packet toward the sink. Each relay is associated with a ``reward'' that summarizes the benefit of forwarding the packet through that relay. We seek a solution to this local problem, the idea being that such a solution, if adopted by every node, could provide a reasonable heuristic for the end-to-end forwarding problem. Toward this end, we propose a local relay selection problem consisting of a forwarding node and a collection of relay nodes, with the relays waking up sequentially at random times. At each relay wake-up instant, the forwarder can choose to probe a relay to learn its reward value, based on which the forwarder can then decide whether to stop (and forward its packet to the chosen relay) or to continue to wait for further relays to wake up. The forwarder's objective is to select a relay so as to minimize a combination of waiting delay, reward, and probing cost. The local decision problem can be considered as a variant of the asset selling problem studied in the operations research literature. We formulate the local problem as a Markov decision process (MDP) and characterize the solution in terms of stopping sets and probing sets. We provide results illustrating the structure of the stopping sets, namely, the (lower bound) threshold and the stage independence properties. Regarding the probing sets, we make an interesting conjecture that these sets are characterized by upper bounds. Through simulation experiments, we provide valuable insights into the performance of the optimal local forwarding and its use as an end-to-end forwarding heuristic.

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The present study focuses on exploring air-assisted atomization strategies for effective atomization of high-viscosity biofuels, such as pure plant oils (PPOs). The first part of the study concerns application of a novel air-assisted impinging jet atomization for continuous spray applications, and the second part concerns transient spray applications. The particle/droplet imaging analysis (PDIA) technique along with direct imaging methods are used for the purpose of spray characterization. In the first part, effective atomization of Jatropha PPO is demonstrated at gas-to-liquid ratios (GLRs) on the order 0.1. The effect of liquid and gas flow rates on the spray characteristics is evaluated, and results indicate a Sauter mean diameter (SMD) of 50 mu m is achieved with GLRs as low as 0.05. In the second part of the study, a commercially available air-assisted transient atomizer is evaluated using Jatropha PPO. The effect of the pressure difference across the air injector and ambient gas pressure on liquid spray characteristics is studied. The results indicate that it is possible to achieve the same level of atomization of Jatropha as diesel fuel by operating the atomizer at a higher pressure difference. Specifically, a SMD of 44 mu m is obtained for the Jatropha oil using injection pressures of <1 MPa. A further interesting observation associated with this injector is the near constancy of a nondimensional spray penetration rate for the Jatropha oil spray.

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Discovering new drugs to treat tuberculosis more efficiently and to overcome multidrug resistance is a world health priority. To find novel antitubercular agents several approaches have been used in various institutions worldwide, including target-based approaches against several validated mycobacterial enzymes and phenotypic screens. We screened more than 17,000 compounds from Vichem's Nested Chemical Library(TM) using an integrated strategy involving whole cell-based assays with Corynebacterium glutamicum and Mycobacterium tuberculosis, and target-based assays with protein kinases PknA, PknB and PknG as well as other targets such as PimA and bacterial topoisomerases simultaneously. With the help of the target-based approach we have found very potent hits inhibiting the selected target enzymes, but good minimal inhibitory concentrations (MIC) against M. tuberculosis were not achieved. Focussing on the whole cell-based approach several potent hits were found which displayed minimal inhibitory concentrations (MIC) against M. tuberculosis below 10 mu M and were non-mutagenic, non-cytotoxic and the targets of some of the hits were also identified. The most active hits represented various scaffolds. Medicinal chemistry-based lead optimization was performed applying various strategies and, as a consequence, a series of novel potent compounds were synthesized. These efforts resulted in some effective potential antitubercular lead compounds which were confirmed in phenotypic assays. (C) 2015 Elsevier Ltd. All rights reserved.

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In this letter, we quantify the transmit diversity order of the SM system operating in a closed-loop scenario. Specifically, the SM system relying on Euclidean distance based antenna subset selection (EDAS) is considered and the achievable diversity gain is evaluated. Furthermore, the resultant trade-off between the achievable diversity gain and switching gain is studied. Simulation results confirm our theoretical results. Specifically, at a symbol error rate of about 10(-4) the signal-to-noise ratio gain achieved by EDAS is about 7 dB in case of 16-QAM and about 5 dB in case of 64-QAM.

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Cooperative relaying combined with selection exploits spatial diversity to significantly improve the performance of interference-constrained secondary users in an underlay cognitive radio (CR) network. However, unlike conventional relaying, the state of the links between the relay and the primary receiver affects the choice of the relay. Further, while the optimal amplify-and-forward (AF) relay selection rule for underlay CR is well understood for the peak interference-constraint, this is not so for the less conservative average interference constraint. For the latter, we present three novel AF relay selection (RS) rules, namely, symbol error probability (SEP)-optimal, inverse-of-affine (IOA), and linear rules. We analyze the SEPs of the IOA and linear rules and also develop a novel, accurate approximation technique for analyzing the performance of AF relays. Extensive numerical results show that all the three rules outperform several RS rules proposed in the literature and generalize the conventional AF RS rule.

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The crystallization of 28 binary and ternary cocrystals of quercetin with dibasic coformers is analyzed in terms of a combinatorial selection from a solution of preferred molecular conformations and supramolecular synthons. The crystal structures are characterized by distinctive O-H center dot center dot center dot N and O-H center dot center dot center dot O based synthons and are classified as nonporous, porous and helical. Variability in molecular conformation and synthon structure led to an increase in the energetic and structural space around the crystallization event. This space is the crystal structure landscape of the compound and is explored by fine-tuning the experimental conditions of crystallization. In the landscape context, we develop a strategy for the isolation of ternary cocrystals with the use of auxiliary template molecules to reduce the molecular and supramolecular `confusion' that is inherent in a molecule like quercetin. The absence of concomitant polymorphism in this study highlights the selectivity in conformation and synthon choice from the virtual combinatorial library in solution.

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Flexray is a high speed communication protocol designed for distributive control in automotive control applications. Control performance not only depends on the control algorithm but also on the scheduling constraints in communication. A balance between the control performance and communication constraints must required for the choice of the sampling rates of the control loops in a node. In this paper, an optimum sampling period of control loops to minimize the cost function, satisfying the scheduling constraints is obtained. An algorithm to obtain the delay in service of each task in a node of the control loop in the hyper period has been also developed. (C) 2015 The Authors. Published by Elsevier B.V.

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A new, phenoxo-bridged Cu-II dinuclear complex Cu-2(L)(2)(DMF)(2)] (1) has been obtained by employing the coumarin-assisted tridentate precursor, H2L, benzoic acid(7-hydroxy-4-methyl-2-oxo-2H-chromen-8-ylmethylene)-hydrazide]. Complex 1 has been systematically characterized by FTIR, UV-Vis, fluorescence and PR spectrometry. The single crystal X-ray diffraction analysis of 1 shows that the geometry around each copper ion is square pyramidal, comprising two enolato oxygen atoms belonging to different ligands (which assemble the dimer bridging the two metal centers), one imine-N and one phenolic-O atoms of the Schiff base and one oxygen atom from the DMF molecule. The temperature dependent magnetic interpretation agrees with the existence of weak ferromagnetic interactions between the bridging dinuclear Cu(II) ions. Both the ligand and complex 1 exhibit anti-mycobacterial activity and considerable efficacy towards M. tuberculosis H37Rv ATCC 27294 and M. tuberculosis H37Ra ATCC 25177 strains. The cytotoxicity study on human adenocarcinoma cell lines (MCF7) suggests that the ligand and complex 1 have potential anticancer properties. Molecular docking of H2L with the enoyl acyl carrier protein reductase of M. tuberculosis H37R(v) (PDB ID: 4U0K) is examined and the best docked pose of H2L shows one hydrogen bond with Thr196 (1.99 angstrom).