889 resultados para Marca-passo artificial
Resumo:
调查了人工湿地水生植物根区理化特性,根系扩展的深度和位置,微生物和酶的分布状况;比较了不同深度人工湿地污水净化效果;探讨了人工湿地污水处理系统最佳净化空间位点。通过对香蒲、灯心草人工湿地的研究,发现植物的根系主要分布在基质上层25cm区域内,在5到10cm区域内,微生物数量最多,25cm区域次之,35cm以下较少。系统表层磷酸酶,葡聚糖脱水酶和蛋白酶的活性较20cm区域内各酶活性强。对于废水的净化而言,系统20cm和60cm处的净化效果差别很小。结果表明,人工湿地废水处理系统上部区域为较佳净化空间。
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Shearing rate is among the most important factors affecting the undrained shear strength of clays. In particular, for seismic or storm-wave loading conditions, the shearing rate is much higher than that used in many common laboratory or field tests. The testing program described here evaluates the effect of peripheral velocity on the undrained strength inferred from the shear vane test. The study was conducted on a lightly cemented bentonite-kaolinite mixture manufactured in the laboratory, which possesses many characteristics similar to those of natural materials. Results show that the shear strength increases with increasing peripheral velocity, while the residual shear strength seems to be nearly independent of rotation rate.
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We study magnetic artificial flagella whose swimming speed and direction can be controlled using light and magnetic field as external triggers. The dependence of the swimming velocity on the system parameters (e.g., length, stiffness, fluid viscosity, and magnetic field) is explored using a computational framework in which the magnetostatic, fluid dynamic, and solid mechanics equations are solved simultaneously. A dimensionless analysis is carried out to obtain an optimal combination of system parameters for which the swimming velocity is maximal. The swimming direction reversal is addressed by incorporating photoresponsive materials, which in the photoactuated state can mimic natural mastigonemes. © 2013 American Physical Society.
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This paper presents ongoing work on data collection and collation from a large number of laboratory cement-stabilization projects worldwide. The aim is to employ Artificial Neural Networks (ANN) to establish relationships between variables, which define the properties of cement-stabilized soils, and the two parameters determined by the Unconfined Compression Test, the Unconfined Compressive Strength (UCS), and stiffness, using E50 calculated from UCS results. Bayesian predictive neural network models are developed to predict the UCS values of cement-stabilized inorganic clays/silts, as well as sands as a function of selected soil mix variables, such as grain size distribution, water content, cement content and curing time. A model which can predict the stiffness values of cement-stabilized clays/silts is also developed and compared to the UCS model. The UCS model results emulate known trends better and provide more accurate estimates than the results from the E50 stiffness model. © 2013 American Society of Civil Engineers.
Resumo:
We study magnetic artificial flagella whose swimming speed and direction can be controlled using light and magnetic field as external triggers. The dependence of the swimming velocity on the system parameters (e.g., length, stiffness, fluid viscosity, and magnetic field) is explored using a computational framework in which the magnetostatic, fluid dynamic, and solid mechanics equations are solved simultaneously. A dimensionless analysis is carried out to obtain an optimal combination of system parameters for which the swimming velocity is maximal. The swimming direction reversal is addressed by incorporating photoresponsive materials, which in the photoactuated state can mimic natural mastigonemes.
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Biomimetic micro-swimmers can be used for various medical applications, such as targeted drug delivery and micro-object (e.g. biological cells) manipulation, in lab-on-a-chip devices. Bacteria swim using a bundle of flagella (flexible hair-like structures) that form a rotating cork-screw of chiral shape. To mimic bacterial swimming, we employ a computational approach to design a bacterial (chirality-induced) swimmer whose chiral shape and rotational velocity can be controlled by an external magnetic field. In our model, we numerically solve the coupled governing equations that describe the system dynamics (i.e. solid mechanics, fluid dynamics and magnetostatics). We explore the swimming response as a function of the characteristic dimensionless parameters and put special emphasis on controlling the swimming direction. Our results provide fundamental physical insight on the chirality-induced propulsion, and it provides guidelines for the design of magnetic bi-directional micro-swimmers. © 2013 The Author(s) Published by the Royal Society. All rights reserved.
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A recurrent artificial neural network was used for 0-and 7-days-ahead forecasting of daily spring phytoplankton bloom dynamics in Xiangxi Bay of Three-Gorges Reservoir with meteorological, hydrological, and limnological parameters as input variables. Daily data from the depth of 0.5 m was used to train the model, and data from the depth of 2.0 m was used to validate the calibrated model. The trained model achieved reasonable accuracy in predicting the daily dynamics of chlorophyll a both in 0-and 7-days-ahead forecasting. In 0-day-ahead forecasting, the R-2 values of observed and predicted data were 0.85 for training and 0.89 for validating. In 7-days-ahead forecasting, the R-2 values of training and validating were 0.68 and 0.66, respectively. Sensitivity analysis indicated that most ecological relationships between chlorophyll a and input environmental variables in 0-and 7-days-ahead models were reasonable. In the 0-day model, Secchi depth, water temperature, and dissolved silicate were the most important factors influencing the daily dynamics of chlorophyll a. And in 7-days-ahead predicting model, chlorophyll a was sensitive to most environmental variables except water level, DO, and NH3N.
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Highly sensitive biosensor for detection of acetylcholine (ACh) and competitive acetylcholinesterase (AChE) inhibitor, eserine, is investigated. Peculiar microelectronic configuration of an ion-sensitive field-effect transistor (ISFET) in addition to a right choice of the pH-transducing nanolayers allows recording a response of the enzyme-modified ISFET (EnFET) to a wide range of ACh concentrations. We demonstrate a remarkable improvement of at least three orders of magnitude in dose response to ACh. Described bioelectronic system reveals clear response, when the catalytic activity of the immobilized AChE is inhibited in a reversible manner by eserine, competitive inhibitor of AChE. ©2007 IEEE.
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Microsatellite markers and D-loop sequences of mtDNA from a female allotetraploid parent carp and her progenies of generations 1 and 2 induced by sperm of five distant fish species were analyzed. Eleven microsatellite markers were used to identify 48 alleles from the allotetraploid female. The same number of alleles (48) appeared in the first and second generations of the gynogenetic offspring, regardless of the source of the sperm used as an activator. The mtDNA D-loop analysis was performed on the female tetraploid parent, 25 gynogenetic offspring, and 5 sperm-donor species. Fourteen variable sites from the 1,018 bp sequences were observed in the offspring as compared to the female tetraploid parent. Results from D-loop sequence and microsatellite marker analysis showed exclusive maternal transmission, and no genetic information was derived from the father. Our study suggests that progenies of artificial tetraploid carp are genetically stable, which is important for genetic breeding of this tetraploid fish.
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Using artificial systems to simulate natural lake environments with cyanobacterial blooms, we investigated plankton community succession by polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) fingerprinting and morphological method. With this approach, we explored potential ecological effects of a newly developed cyanobacterial blooms removal method using chitosan-modified soils. Results of PCR-DGGE and morphological identification showed that plankton communities in the four test systems were nearly identical at the beginning of the experiment. After applying the newly developed and standard removal methods, there was a shift in community composition, but neither chemical conditions nor plankton succession were significantly affected by the cyanobacteria removal process. The planted Vallisneria natans successfully recovered after cyanobacteria removal, whereas that in the box without removal process did not. Additionally, canonical correspondence analysis indicated that other than for zooplankton abundance, total phosphorus was the most important environmental predictor of planktonic composition. The present study and others suggest that dealing with cyanobacteria removal using chitosan-modified soils can play an important role in controlling cyanobacterial blooms in eutrophicated freshwater systems.
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Studies on the colonization of environmentally extreme ground surfaces were conducted in a Mars-like desert area of Inner Mongolia, People's Republic of China, with microalgae and cyanobacteria. We collected and mass-cultured cyanobacterial strains from these regions and investigated their ability to form desert crusts artificially. These crusts had the capacity to resist sand wind erosion after just 15 days of growth. Similar to the surface of some Chinese deserts, the surface of Mars is characterized by a layer of fine dust, which will challenge future human exploration activities, particularly in confined spaces that will include greenhouses and habitats. We discuss the use of such crusts for the local control of desert sands in enclosed spaces on Mars. These experiments suggest innovative new directions in the applied use of microbe-mineral interactions to advance the human exploration and settlement of space.
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Lake Dianchi is a shallow and turbid lake, located in Southwest China. Since 1985, Lake Dianchi has experienced severe cyanabacterial blooms (dominated by Microcystis spp.). In extreme cases, the algal cell densities have exceeded three billion cells per liter. To predict and elucidate the population dynamics ofMicrocystis spp. in Lake Dianchi, a neural network based model was developed. The correlation coefficient (R 2) between the predicted algal concentrations by the model and the observed values was 0.911. Sensitivity analysis was performed to clarify the algal dynamics to the changes of environmental factors. The results of a sensitivity analysis of the neural network model suggested that small increases in pH could cause significantly reduced algal abundance. Further investigations on raw data showed that the response of Microcystis spp. concentration to pH increase was dependent on algal biomass and pH level. When Microcystis spp. population and pH were moderate or low, the response of Microcystis spp. population would be more likely to be positive in Lake Dianchi; contrarily, Microcystis spp. population in Lake Dianchi would be more likely to show negative response to pH increase when Microcystis spp. population and pH were high. The paper concluded that the extremely high concentration of algal population and high pH could explain the distinctive response of Microcystis spp. population to +1 SD (standard deviation) pH increase in Lake Dianchi. And the paper also elucidated the algal dynamics to changes of other environmental factors. One SD increase of water temperature (WT) had strongest positive relationship with Microcystis spp. biomass. Chemical oxygen demand (COD) and total phosphorus (TP) had strong positive effect on Microcystis spp. abundance while total nitrogen (TN), biological oxygen demand in five days (BOD5), and dissolved oxygen had only weak relationship with Microcystis spp. concentration. And transparency (Tr) had moderate positive relationship with Microcystis spp. concentration.
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This book is devoted to the rapidly growing highly interdisciplinary field of embodied artificial intelligence involving researchers from areas as diverse as computer science, engineering, cognitive science, neuroscience, biology, ...
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The field of Artificial Intelligence, which started roughly half a century ago, has a turbulent history. In the 1980s there has been a major paradigm shift towards embodiment. While embodied artificial intelligence is still highly diverse, changing, and far from "theoretically stable", a certain consensus about the important issues and methods has been achieved or is rapidly emerging. In this non-technical paper we briefly characterize the field, summarize its achievements, and identify important issues for future research. One of the fundamental unresolved problems has been and still is how thinking emerges from an embodied system. Provocatively speaking, the central issue could be captured by the question "How does walking relate to thinking?" © Springer-Verlag Berlin Heidelberg 2004.
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Viable F-1 hybrids were obtained from crosses of female Macrobrachium nipponense and male Macrobrachium hainanense involving spermatophore transfer and artificial insemination. This represents the first successful known case of hybridization of two Macrobrachium species by means of artificial insemination. The hatching rate was over 90%. About 20-60% of newly hatched larvae metamorphosed to postlarvae. The morphological characteristics of the hybrids resembled a combination of features of both parents. Malate dehydrogenase (MDH) and esterase (EST) isozyme electrophoresis indicated parents and F-1 hybrids showed co-dominant expression of the paternal and maternal alleles controlling the isozymes and confirmed the hybridization. (C) 2004 Elsevier B.V. All rights reserved.