996 resultados para automated meter reading (AMR)
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The ribosomal P-site hosts the peptidyl-tRNAs during translation elongation. Which P-site elements support these tRNA species to maintain codon-anticodon interactions has remained unclear. We investigated the effects of P-site features of methylations of G966, C967, and the conserved C-terminal tail sequence of Ser, Lys, and Arg (SKR) of the S9 ribosomal protein in maintenance of the translational reading frame of an mRNA. We generated Escherichia coli strains deleted for the SKR sequence in S9 ribosomal protein, RsmB (which methylates C967), and RsmD (which methylates G966) and used them to translate LacZ from its +1 and -1 out-of-frame constructs. We show that the S9 SKR tail prevents both the +1 and -1 frameshifts and plays a general role in holding the P-site tRNA/peptidyl-tRNA in place. In contrast, the G966 and C967 methylations did not make a direct contribution to the maintenance of the translational frame of an mRNA. However, deletion of rsmB in the S9 Delta 3 background caused significantly increased -1 frameshifting at 37 degrees C. Interestingly, the effects of the deficiency of C967 methylation were annulled when the E. coli strain was grown at 30 degrees C, supporting its context-dependent role.
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Network theory applied to protein structures provides insights into numerous problems of biological relevance. The explosion in structural data available from PDB and simulations establishes a need to introduce a standalone-efficient program that assembles network concepts/parameters under one hood in an automated manner. Herein, we discuss the development/application of an exhaustive, user-friendly, standalone program package named PSN-Ensemble, which can handle structural ensembles generated through molecular dynamics (MD) simulation/NMR studies or from multiple X-ray structures. The novelty in network construction lies in the explicit consideration of side-chain interactions among amino acids. The program evaluates network parameters dealing with topological organization and long-range allosteric communication. The introduction of a flexible weighing scheme in terms of residue pairwise cross-correlation/interaction energy in PSN-Ensemble brings in dynamical/chemical knowledge into the network representation. Also, the results are mapped on a graphical display of the structure, allowing an easy access of network analysis to a general biological community. The potential of PSN-Ensemble toward examining structural ensemble is exemplified using MD trajectories of an ubiquitin-conjugating enzyme (UbcH5b). Furthermore, insights derived from network parameters evaluated using PSN-Ensemble for single-static structures of active/inactive states of 2-adrenergic receptor and the ternary tRNA complexes of tyrosyl tRNA synthetases (from organisms across kingdoms) are discussed. PSN-Ensemble is freely available from http://vishgraph.mbu.iisc.ernet.in/PSN-Ensemble/psn_index.html.
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Objective identification and description of mimicked calls is a primary component of any study on avian vocal mimicry but few studies have adopted a quantitative approach. We used spectral feature representations commonly used in human speech analysis in combination with various distance metrics to distinguish between mimicked and non-mimicked calls of the greater racket-tailed drongo, Dicrurus paradiseus and cross-validated the results with human assessment of spectral similarity. We found that the automated method and human subjects performed similarly in terms of the overall number of correct matches of mimicked calls to putative model calls. However, the two methods also misclassified different subsets of calls and we achieved a maximum accuracy of ninety five per cent only when we combined the results of both the methods. This study is the first to use Mel-frequency Cepstral Coefficients and Relative Spectral Amplitude - filtered Linear Predictive Coding coefficients to quantify vocal mimicry. Our findings also suggest that in spite of several advances in automated methods of song analysis, corresponding cross-validation by humans remains essential.
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Glass micropipettes are versatile probing tools for performing micro-and nano-manipulation tasks. This paper presents the design and development of an automated pipette puller system for fabrication of glass micropipettes. The pipette puller employs a new strategy for fabrication of micropipettes that enables achieving independent control of their taper, tip diameter, and bend-angle, and also facilitates theoretical derivation of simple, approximate relationships between the pipette shape and the pulling parameters. Subsequently, the design and fabrication of the pipette puller is described, which include that of the pipette heating system, the mechanical motion stages, and the control electronics of the pipette puller. The fabricated pipette puller is experimentally evaluated to demonstrate control of the taper, tip diameter, and the bend-angle of the micropipette. Further, the dependence of the taper and tip diameter on the pulling parameters is evaluated and is shown to be in alignment with the proposed theoretical relationships. (C) 2014 AIP Publishing LLC.
Resumo:
The goal of the work reported in this paper is to use automated, combinatorial synthesis to generate alternative solutions to be used as stimuli by designers for ideation. FuncSION, a computational synthesis tool that can automatically synthesize solution concepts for mechanical devices by combining building blocks from a library, is used for this purpose. The objectives of FuncSION are to help generate a variety of functional requirements for a given problem and a variety of concepts to fulfill these functions. A distinctive feature of FuncSION is its focus on automated generation of spatial configurations, an aspect rarely addressed by other computational synthesis programs. This paper provides an overview of FuncSION in terms of representation of design problems, representation of building blocks, and rules with which building blocks are combined to generate concepts at three levels of abstraction: topological, spatial, and physical. The paper then provides a detailed account of evaluating FuncSION for its effectiveness in providing stimuli for enhanced ideation.
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Story understanding involves many perceptual and cognitive subprocesses, from perceiving individual words, to parsing sentences, to understanding the relationships among the story characters. We present an integrated computational model of reading that incorporates these and additional subprocesses, simultaneously discovering their fMRI signatures. Our model predicts the fMRI activity associated with reading arbitrary text passages, well enough to distinguish which of two story segments is being read with 74% accuracy. This approach is the first to simultaneously track diverse reading subprocesses during complex story processing and predict the detailed neural representation of diverse story features, ranging from visual word properties to the mention of different story characters and different actions they perform. We construct brain representation maps that replicate many results from a wide range of classical studies that focus each on one aspect of language processing and offer new insights on which type of information is processed by different areas involved in language processing. Additionally, this approach is promising for studying individual differences: it can be used to create single subject maps that may potentially be used to measure reading comprehension and diagnose reading disorders.
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This paper presents our work on developing an automated micro positioner and a low cost disposable dispenser module having a disposable dispenser core. The dispenser core is made up of Polydimethylsiloxane (PDMS). Once the user specifies the dispensing location in the Graphical User Interface (GUI), the movement of the micropositioner is automatic. The design, fabrication and characterization results of the dispenser module are also presented. The dispensing experiments are performed with Di-Ethanol Amine as the working reagent. The minimum dispensed volume achieved is about 4 nL.
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A block-structured adaptive mesh refinement (AMR) technique has been used to obtain numerical solutions for many scientific applications. Some block-structured AMR approaches have focused on forming patches of non-uniform sizes where the size of a patch can be tuned to the geometry of a region of interest. In this paper, we develop strategies for adaptive execution of block-structured AMR applications on GPUs, for hyperbolic directionally split solvers. While effective hybrid execution strategies exist for applications with uniform patches, our work considers efficient execution of non-uniform patches with different workloads. Our techniques include bin-packing work units to load balance GPU computations, adaptive asynchronism between CPU and GPU executions using a knapsack formulation, and scheduling communications for multi-GPU executions. Our experiments with synthetic and real data, for single-GPU and multi-GPU executions, on Tesla S1070 and Fermi C2070 clusters, show that our strategies result in up to a 3.23 speedup in performance over existing strategies.
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In this work, we report a system-level integration of portable microscopy and microfluidics for the realization of optofluidic imaging flow analyzer with a throughput of 450 cells/s. With the use of a cellphone augmented with off-the-shelf optical components and custom designed microfluidics, we demonstrate a portable optofluidic imaging flow analyzer. A multiple microfluidic channel geometry was employed to demonstrate the enhancement of throughput in the context of low frame-rate imaging systems. Using the cell-phone based digital imaging flow analyzer, we have imaged yeast cells present in a suspension. By digitally processing the recorded videos of the flow stream on the cellphone, we demonstrated an automated cell viability assessment of the yeast cell population. In addition, we also demonstrate the suitability of the system for blood cell counting. (C) 2015 AIP Publishing LLC.
Resumo:
Computing the maximum of sensor readings arises in several environmental, health, and industrial monitoring applications of wireless sensor networks (WSNs). We characterize the several novel design trade-offs that arise when green energy harvesting (EH) WSNs, which promise perpetual lifetimes, are deployed for this purpose. The nodes harvest renewable energy from the environment for communicating their readings to a fusion node, which then periodically estimates the maximum. For a randomized transmission schedule in which a pre-specified number of randomly selected nodes transmit in a sensor data collection round, we analyze the mean absolute error (MAE), which is defined as the mean of the absolute difference between the maximum and that estimated by the fusion node in each round. We optimize the transmit power and the number of scheduled nodes to minimize the MAE, both when the nodes have channel state information (CSI) and when they do not. Our results highlight how the optimal system operation depends on the EH rate, availability and cost of acquiring CSI, quantization, and size of the scheduled subset. Our analysis applies to a general class of sensor reading and EH random processes.
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Clinical microscopy is a versatile diagnostic platform used for diagnosis of a multitude of diseases. In the recent past, many microfluidics based point-of-care diagnostic devices have been developed, which serve as alternatives to microscopy. However, these point-of-care devices are not as multi-functional and versatile as clinical microscopy. With the use of custom designed optics and microfluidics, we have developed a versatile microscopy-based cellular diagnostic platform, which can be used at the point of care. The microscopy platform presented here is capable of detecting infections of very low parasitemia level (in a very small quantity of sample), without the use of any additional computational hardware. Such a cost-effective and portable diagnostic device, would greatly impact the quality of health care available to people living in rural locations of the world. Apart from clinical diagnostics, it's applicability to field research in environmental microbiology has also been outlined. (C) 2015 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.
Development of an automated ultrasonic spray pyrolysis system and the growth of Cu2ZnSnS4 thin films
Resumo:
An automated ultrasonic spray pyrolysis system is fabricated for the growth of thin films. The system is equipped with x-y movement and enables film deposition in different patterns and spray rates. Cu-2(Zn,Sn)S-4 (CZTS) films are deposited using this setup. The substrate temperature (T-s) is varied from 240 to 490 degrees C. Kesterite CZTS phase is observed in all the films together with binary phases. The films prepared at T-s <340 degrees C showed SnxSy phase and those at T-s >340 degrees C showed Cu2S phase. Sulfur incorporation is maximum (40%) at 440 degrees C and the films showed better morphology. The Cu and S concentrations are varied to remove binary phases. Depth wise elemental analysis confirmed the existence of single phase CZTS. p-Type CZTS films of resistivity in the range of 10(2)-10(3) Omega cm are obtained. (C) 2015 Elsevier B.V. All rights reserved.
Resumo:
对涡轮流量传感器进行了理论分析,给出了涡轮流量计仪表常数的计算方法,讨论了获得较大固有仪表常数K_0时涡轮传感器结构参数(如叶片数、涡轮半径、口径等)的优化组合问题,通过多相流动实验,总结出K_0与流动密度之间的实验关系,由此给出用涡轮流量计测量多相流的半理论半经验公式,并在油井多相流量测量中得到了实际应用,符合较好。