43 resultados para Error of measurement

em Indian Institute of Science - Bangalore - Índia


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We propose a molecular mechanism for the intra-cellular measurement of the ratio of the number of X chromosomes to the number of sets of autosomes, a process central to both sex determination and dosage compensation in Drosophila melanogaster. In addition to the two loci, da and Sxl, which have been shown by Cline (Genetics, 90, 683, 1978)and others to be involved in these processes, we postulate two other loci, one autosomal (ω) and the other, X-linked (π). The product of the autosomal locus da stimulates ω and initiates synthesis of a limited quantity of repressor. Sxl and π ,both of which are X-linked, compete for this repressor as well as for RNA polymerase. It is assumed that Sxl has lower affinity than π for repressor as well as polymerase and that the binding of polymerase to one of these sites modulates the binding affinity of the other site for the enzyme. It can be shown that as a result of these postulated interactions transcription from the Sxl site is proportional to the X/A ratio such that the levels of Sxl+ product are low in males, high in females and intermediate in the intersexes. If, as proposed by Cline, the Sxl- product is an inhibitor of X chromosome activity, this would result in dosage compensation. The model leads to the conclusion that high levels of Sxl+ product promote a female phenotype and low levels, a male phenotype. One interesting consequence of the assumptions on which the model is based is that the level of Sxl+ product in the cell, when examined as a function of increasing repressor concentration, first goes up and then decreases, yielding a bell-shaped curve. This feature of the model provides an explanation for some of the remarkable interactions among mutants at the Sxl, da and mle loci and leads to several predictions. The proposed mechanism may also have relevance to certain other problems, such as size regulation during development, which seem to involve measurement of ratios at the cellular level.

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Infrared Earth sensors are used in spacecraft for attitude sensing. Their accuracy is limited by systematic and random errors. Dominant sources of systematic errors are analyzed for a typical scanning infrared Earth sensor used in a remote-sensing satellite in a 900-km sun-synchronous orbit. The errors considered arise from 1) seasonable variation of infrared radiation, 2) oblate shape of the Earth, 3) ambient temperature of sensors, 4) changes in spin/scan period, and 5) misalignment of the axis of the sensors. Simple relations are derived using least-squares curve fitting for onboard correction of these errors. With these, it is possible to improve the accuracy of attitude determination by eight fold and achieve performance comparable to ground-based post-facto attitude computation.

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Most of the signals recorded in experiments are inevitably contaminated by measurement noise. Hence, it is important to understand the effect of such noise on estimating causal relations between such signals. A primary tool for estimating causality is Granger causality. Granger causality can be computed by modeling the signal using a bivariate autoregressive (AR) process. In this paper, we greatly extend the previous analysis of the effect of noise by considering a bivariate AR process of general order p. From this analysis, we analytically obtain the dependence of Granger causality on various noise-dependent system parameters. In particular, we show that measurement noise can lead to spurious Granger causality and can suppress true Granger causality. These results are verified numerically. Finally, we show how true causality can be recovered numerically using the Kalman expectation maximization algorithm.

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Quantitative use of satellite-derived rainfall products for various scientific applications often requires them to be accompanied with an error estimate. Rainfall estimates inferred from low earth orbiting satellites like the Tropical Rainfall Measuring Mission (TRMM) will be subjected to sampling errors of nonnegligible proportions owing to the narrow swath of satellite sensors coupled with a lack of continuous coverage due to infrequent satellite visits. The authors investigate sampling uncertainty of seasonal rainfall estimates from the active sensor of TRMM, namely, Precipitation Radar (PR), based on 11 years of PR 2A25 data product over the Indian subcontinent. In this paper, a statistical bootstrap technique is investigated to estimate the relative sampling errors using the PR data themselves. Results verify power law scaling characteristics of relative sampling errors with respect to space-time scale of measurement. Sampling uncertainty estimates for mean seasonal rainfall were found to exhibit seasonal variations. To give a practical example of the implications of the bootstrap technique, PR relative sampling errors over a subtropical river basin of Mahanadi, India, are examined. Results reveal that the bootstrap technique incurs relative sampling errors < 33% (for the 2 degrees grid), < 36% (for the 1 degrees grid), < 45% (for the 0.5 degrees grid), and < 57% (for the 0.25 degrees grid). With respect to rainfall type, overall sampling uncertainty was found to be dominated by sampling uncertainty due to stratiform rainfall over the basin. The study compares resulting error estimates to those obtained from latin hypercube sampling. Based on this study, the authors conclude that the bootstrap approach can be successfully used for ascertaining relative sampling errors offered by TRMM-like satellites over gauged or ungauged basins lacking in situ validation data. This technique has wider implications for decision making before incorporating microwave orbital data products in basin-scale hydrologic modeling.

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The reduction in natural frequencies,however small, of a civil engineering structure, is the first and the easiest method of estimating its impending damage. As a first level screening for health-monitoring, information on the frequency reduction of a few fundamentalmodes can be used to estimate the positions and the magnitude of damage in a smeared fashion. The paper presents the Eigen value sensitivity equations, derived from first-order perturbation technique, for typical infra-structural systems like a simply supported bridge girder, modelled as a beam, an endbearing pile, modelled as an axial rod and a simply supported plate as a continuum dynamic system. A discrete structure, like a building frame is solved for damage using Eigen-sensitivity derived by a computationalmodel. Lastly, neural network based damage identification is also demonstrated for a simply supported bridge beam, where the known-pairs of damage-frequency vector is used to train a neural network. The performance of these methods under the influence of measurement error is outlined. It is hoped that the developed method could be integrated in a typical infra-structural management program, such that magnitudes of damage and their positions can be obtained using acquired natural frequencies, synthesized from the excited/ambient vibration signatures.

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Based on the measurements of Alcock and Zador, Grundy et al. estimated an uncertainty of the order of +/- 5 kJ mol(-1) for the standard Gibbs energy of formation of MnO in a recent assessment. Since the evaluation of thermodynamic data for the higher oxides Mn3O4, Mn2O3, and MnO2 depends on values for MnO, a redetermination of its Gibbs energy of formation was undertaken in the temperature range from 875 to 1300 K using a solid-state electrochemical cell incorporating yttria-doped thoria (YDT) as the solid electrolyte and Fe + Fe1-delta O as the reference electrode. The cell can be presented as Pt, Mn + MnO/YDT/Fe + Fe1+delta O, Pt Since the metals Fe and Mn undergo phase transitions in the temperature range of measurement, the reversible emf of the cell is represented by the three linear segments. Combining the emf with the oxygen potential for the reference electrode, the standard Gibbs energy of formation of MnO from alpha-Mn and gaseous diatomic oxygen in the temperature range from 875 to 980 K is obtained as: Delta G(f)(o)/Jmol(-1)(+/- 250) = -385624 + 73.071T From 980 to 1300 K the Gibbs energy of formation of MnO from beta-Mn and oxygen gas is given by: Delta G(f)(o)/Jmol(-1)(+/- 250) = -387850 + 75.36T The new data are in excellent agreement with the earlier measurements of Alcock and Zador. Grundy et al. incorrectly analyzed the data of Alcock and Zador showing relatively large difference (+/- 5 kJ mol(-1)) in Gibbs energies of MnO from their two cells with Fe + Fe1-delta O and Ni + NiO as reference electrodes. Thermodynamic data for MnO is reassessed in the light of the new measurements. A table of refined thermodynamic data for MnO from 298.15 to 2000 K is presented.

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16-electrode phantoms are developed and studied with a simple instrumentation developed for Electrical Impedance Tomography. An analog instrumentation is developed with a sinusoidal current generator and signal conditioner circuit. Current generator is developed withmodified Howland constant current source fed by a voltage controlled oscillator and the signal conditioner circuit consisting of an instrumentation amplifier and a narrow band pass filter. Electronic hardware is connected to the electrodes through a DIP switch based multiplexer module. Phantoms with different electrode size and position are developed and the EIT forward problem is studied using the forward solver. A low frequency low magnitude sinusoidal current is injected to the surface electrodes surrounding the phantom boundary and the differential potential is measured by a digital multimeter. Comparing measured potential with the simulated data it is intended to reduce the measurement error and an optimum phantom geometry is suggested. Result shows that the common mode electrode reduces the common mode error of the EIT electronics and reduces the error potential in the measured data. Differential potential is reduced up to 67 mV at the voltage electrode pair opposite to the current electrodes. Offset potential is measured and subtracted from the measured data for further correction. It is noticed that the potential data pattern depends on the electrode width and the optimum electrode width is suggested. It is also observed that measured potential becomes acceptable with a 20 mm solution column above and below the electrode array level.

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A method is described for monitoring the concentration of endogenous receptor-bound gonadotropin in the ovarian tissue. This involved development of a radioimmunoassay procedure, the validity of which for measuring all of the tissue-bound hormone has been established. The specificity of the method of measurement was indicated by the fact that high levels of FSH could be measured only in target tissue such as follicles, while non-target organs showed little FSH. Using this method, the amount of FSH in the non-luteal ovarian tissue of the hamster at different stages of the estrous cycle was quantitated and compared with serum FSH levels found at these times. No correlation could be found between serum and tissue FSH levels at all times. On the morning of estrus, for example, when the serum level of FSH was high, the ovarian concentration was low, and on the evening of diestrus-2 the ovary exhibited high concentration of FSH, despite the serum FSH concentration being low at this time. The highest concentration of FSH in the ovary during the cycle was found on the evening of proestrus. Although a large amount of this was found in the Graafian follicles, a considerable amount could still be found in the �growing� follicles. Ovarian FSH concentration could be considered to be a reflection of FSH receptor content, since preventing the development of FSH receptors by blocking initiation of follicular development during the cycle resulted in a decrease in the concentration of FSH in the ovary. The high concentration of FSH in the ovary seen on the evening of diestrus-2 was not influenced either by varying the concentration of estrogen or by neutralization of LH. Neutralization of FSH on diestrus-2, on the other hand, caused a drastic reduction in the ovarian LH concentration on the next day (i.e. at proestrus), thus suggesting the importance of FSH in the induction of LH receptors.

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This paper is concerned with the dual head-discharge characteristics of a modified chimney weir. It is shown by an optimization procedure that the modified chimney weir having an inward trapezoidal weir over an inverted V-notch can produce discharges proportional to both the logarithm of the head as well as the linear power of the head reckoned independently over two different reference planes, within a prefixed maximum allowable percentage error from the theoretical discharge. A new technique is adopted to optimize the weir parameters, in order to obtain the maximum ranges of measurement under logarithmic, linear as well as combined characteristics. In the case of linear weir it is shown that it is possible to enhance the linearity range of the chimney weir by more than 540% and for a weir with constant indication accuracy by more than 350%. In addition, about 86% of the overall depth of the designed linear weir and over 90% of the logarithmic weir is converted as the corresponding measurable ranges. Experiments with four typical weirs give consistent constant average coefficient of discharge for each weir confirming the theory. The practical application of the weir in minor irrigation, hydraulic and other engineering fields is highlighted.

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A comparative study of strain response and mechanical properties of rammed earth prisms, has been made using Fiber Bragg Grating (FBG) sensors (optical) and clip-on extensometer (electro-mechanical). The aim of this study is to address the merits and demerits of traditional extensometer vis-à-vis FBG sensor; a uni-axial compression test has been performed on a rammed earth prism to validate its structural properties from the stress - strain curves obtained by two different methods of measurement. An array of FBG sensors on a single fiber with varying Bragg wavelengths (..B), has been used to spatially resolve the strains along the height of the specimen. It is interesting to note from the obtained stress-strain curves that the initial tangent modulus obtained using the FBG sensor is lower compared to that obtained using clip-on extensometer. The results also indicate that the strains measured by both FBG and extensometer sensor follow the same trend and both the sensors register the maximum strain value at the same time.

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The activity coefficients of oxygen in copper-tin alloys at 1 1 00°C have been measured by two different equilibrium methodsthe cell Pt, Ni + NiO I ZrOz solid electrolyte I O[Cu + Sn], cermet. Pt and the equilibrium between Cu + Sn alloys and SnO + SiO, slags established via SnO vapour. The results from both types of measurement confirm the work of Block and co-workers and show that other data are in error. The deoxidation equilibria for Sn in liquid copper, with solid SnO, as deoxidation product, have been evaluated at temperatures of interest in copper smelting.

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An all-digital on-chip clock skew measurement system via subsampling is presented. The clock nodes are sub-sampled with a near-frequency asynchronous sampling clock to result in beat signals which are themselves skewed in the same proportion but on a larger time scale. The beat signals are then suitably masked to extract only the skews of the rising edges of the clock signals. We propose a histogram of the arithmetic difference of the beat signals which decouples the relationship of clock jitter to the minimum measurable skew, and allows skews arbitrarily close to zero to be measured with a precision limited largely by measurement time, unlike the conventional XOR based histogram approach. We also analytically show that the proposed approach leads to an unbiased estimate of skew. The measured results from a 65 nm delay measurement front-end indicate that for an input skew range of +/- 1 fan-out-of-4 (FO4) delay, +/- 3 sigma resolution of 0.84 ps can be obtained with an integral error of 0.65 ps. We also experimentally demonstrate that a frequency modulation on a sampling clock maintains precision, indicating the robustness of the technique to jitter. We also show how FM modulation helps in restoring precision in case of rationally related clocks.

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The thermal expansion of magnesium oxide has been measured below room temperature from 140°K to 284.5°K, using an interferometric method. The accuracy of measurement is better than 3% in the temperature range studied. The agreement of these results with Durand's is quite good, but consistently higher over most of the range by 2 or 3%, for the most part within the estimated experimental error. The Grüneisen parameter remains constant at about 1.51 over the present experimental range; but an isolated measurement of Durand at 85°K suggests that at lower temperatures it rises quite sharply above this value. This possibility is therefore investigated theoretically. With a non-central force model to represent MgO, γ(−3) and γ(2) are calculated and it is found that γ(−3) > γ(2), again suggesting that the Grüneisen parameter increases with falling temperature. Of the two reported experimental values for the infra-red absorption frequency, correlation with the heat capacity strongly indicates a wavelength of 25.26μm rather than 17.3μm. Thermal expansion measurements at still lower temperatures must be carried out to confirm definitely the rise in the Grüneisen parameter.

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Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.