Vesicle formation from dimeric surfactants through ion-pairing. Adjustment of polar headgroup separation leads to control over vesicular thermotropic properties

Eight new vesicle-forming dimeric surfactants are synthesized: the polar headgroup separation in such dimeric amphiphiles strongly influences their vesicular thermotropic phase-transition behaviour.

On the role of cloud adjustment time scale in simulating precipitation with Relaxed Arakawa-Schubert convection scheme

The precipitation by Relaxed Arakawa-Schubert cumulus parameterization in a General Circulation Model (GCM) is sensitive to the choice of relaxation parameter or specified cloud adjustment time scale. In the present study, we examine sensitivity of simulated precipitation to the choice of cloud adjustment time scale (tau(adj)) over different parts of the tropics using National Center for Environmental Prediction (NCEP) Seasonal Forecast Model (SFM) during June-September. The results show that a single specified value of tau(adj) performs best only over a particular region and different values are preferred over different parts of the world. To find a relation between tau(adj) and cloud depth (convective activity) we choose six regions over the tropics. Based on the observed relation between outgoing long-wave radiation and tau(adj), we propose a linear cloud-type dependent relaxation parameter to be used in the model. The simulations over most parts of the tropics show improved results due to this newly formulated cloud-type dependent relaxation parameter.

Role of the cloud adjustment time scale in simulation of the interannual variability of Indian summer monsoon

The simulation of precipitation in a general circulation model relying on relaxed mass flux cumulus parameterization scheme is sensitive to cloud adjustment time scale (CATS). In this study, the frequency of the dominant intra-seasonal mode and interannual variability of Indian summer monsoon rainfall (ISMR) simulated by an atmospheric general circulation model is shown to be sensitive to the CATS. It has been shown that a longer CATS of about 5 h simulates the spatial distribution of the ISMR better. El Nio Southern Oscillation-ISMR relationship is also sensitive to CATS. The equatorial Indian Ocean rainfall and ISMR coupling is sensitive to CATS. Our study suggests that a careful choice of CATS is necessary for adequate simulation of spatial pattern as well as interannual variation of Indian summer monsoon precipitation.

Identification of a class of non-linear systems

This paper considers the on-line identification of a non-linear system in terms of a Hammerstein model, with a zero-memory non-linear gain followed by a linear system. The linear part is represented by a Laguerre expansion of its impulse response and the non-linear part by a polynomial. The identification procedure involves determination of the coefficients of the Laguerre expansion of correlation functions and an iterative adjustment of the parameters of the non-linear gain by gradient methods. The method is applicable to situations involving a wide class of input signals. Even in the presence of additive correlated noise, satisfactory performance is achieved with the variance of the error converging to a value close to the variance of the noise. Digital computer simulation establishes the practicability of the scheme in different situations.

The nonequilibrium region of a mixing layer

Experiments were conducted in the nonequilibrium region of a free mixing layer with unequal freestream velocities. Four velocity ratios U(1)/U(2) of 0.32, 0.46, 0.74, and 0.96 were used in this investigation. The growth of the shear layer as well as the velocity adjustment in the near wake were examined. There was reasonable agreement between the measured mean velocity profiles and those computed using the K-epsilon turbulence model. Some periodic turbulence velocity fluctuations were observed in the mixing layer, but their frequency remained the same along the flow.

Selection of intrusion detection system threshold bounds for effective sensor fusion

The motivation behind the fusion of Intrusion Detection Systems was the realization that with the increasing traffic and increasing complexity of attacks, none of the present day stand-alone Intrusion Detection Systems can meet the high demand for a very high detection rate and an extremely low false positive rate. Multi-sensor fusion can be used to meet these requirements by a refinement of the combined response of different Intrusion Detection Systems. In this paper, we show the design technique of sensor fusion to best utilize the useful response from multiple sensors by an appropriate adjustment of the fusion threshold. The threshold is generally chosen according to the past experiences or by an expert system. In this paper, we show that the choice of the threshold bounds according to the Chebyshev inequality principle performs better. This approach also helps to solve the problem of scalability and has the advantage of failsafe capability. This paper theoretically models the fusion of Intrusion Detection Systems for the purpose of proving the improvement in performance, supplemented with the empirical evaluation. The combination of complementary sensors is shown to detect more attacks than the individual components. Since the individual sensors chosen detect sufficiently different attacks, their result can be merged for improved performance. The combination is done in different ways like (i) taking all the alarms from each system and avoiding duplications, (ii) taking alarms from each system by fixing threshold bounds, and (iii) rule-based fusion with a priori knowledge of the individual sensor performance. A number of evaluation metrics are used, and the results indicate that there is an overall enhancement in the performance of the combined detector using sensor fusion incorporating the threshold bounds and significantly better performance using simple rule-based fusion.

Handling sectional views in volume-based approach to automatically construct 3D solid from 2D views

This paper presents an algorithm for solid model reconstruction from 2D sectional views based on volume-based approach. None of the existing work in automatic reconstruction from 2D orthographic views have addressed sectional views in detail. It is believed that the volume-based approach is better suited to handle different types of sectional views. The volume-based approach constructs the 3D solid by a boolean combination of elementary solids. The elementary solids are formed by sweep operation on loops identified in the input views. The only adjustment to be made for the presence of sectional views is in the identification of loops that would form the elemental solids. In the algorithm, the conventions of engineering drawing for sectional views, are used to identify the loops correctly. The algorithm is simple and intuitive in nature. Results have been obtained for full sections, offset sections and half sections. Future work will address other types of sectional views such as removed and revolved sections and broken-out sections. (C) 2004 Elsevier Ltd. All rights reserved.

Hybrid moving block bootstrap for stochastic simulation of multi-site multi-season streamflows

The Hybrid approach introduced by the authors for at-site modeling of annual and periodic streamflows in earlier works is extended to simulate multi-site multi-season streamflows. It bears significance in integrated river basin planning studies. This hybrid model involves: (i) partial pre-whitening of standardized multi-season streamflows at each site using a parsimonious linear periodic model; (ii) contemporaneous resampling of the resulting residuals with an appropriate block size, using moving block bootstrap (non-parametric, NP) technique; and (iii) post-blackening the bootstrapped innovation series at each site, by adding the corresponding parametric model component for the site, to obtain generated streamflows at each of the sites. It gains significantly by effectively utilizing the merits of both parametric and NP models. It is able to reproduce various statistics, including the dependence relationships at both spatial and temporal levels without using any normalizing transformations and/or adjustment procedures. The potential of the hybrid model in reproducing a wide variety of statistics including the run characteristics, is demonstrated through an application for multi-site streamflow generation in the Upper Cauvery river basin, Southern India. (C) 2004 Elsevier B.V. All rights reserved.

Noise minimization in RC-active filters using generalized impedance converters

A procedure has been given for minimizing the total output noise of a Generalized Impedance Converter (GIC), subject to constraints dictated by signal handling capability of the Operational Amplifiers and ease of microcircuit fabrication. The noise reduction is achieved only by the adjustment of RC elements of the GIC, and the total output noise after optimization in the example cited is close to the theoretical lower limit. The output noise of a higher-order filter can be reduced by RC-optimizing the individual GIC's of the active realization. Experimental results on a 20–24 kHz channel bank band-pass filter demonstrate the effectiveness of the above procedure.

An unsteady flow due to eccentrically rotating porous disk and a fluid at infinity

An exact solution of the unsteady Navier-Stokes equations is obtained for the flow due to non-coaxial rotations of a porous disk, executing non-torsional oscillations in its own plane, and a fluid at infinity. It is shown that the infinite number of solutions existing for a flow confined between two disks reduce to a single unique solution in the case of a single disk. The adjustment of the unsteady flow near the rotating disk to the flow at infinity rotating about a different axis is explained.

A structural principle for a class of adaptive systems

A feature common to many adaptive systems for identification and control is the adjustment.of gain parameters in a manner ensuring the stability of the overall system. This paper puts forward a principle which assures such a result for arbitrary systems which are linear and time invariant except for the adjustable parameters. The principle only demands that a transfer function be positive real. This transfer function dependent on the structure of the system with respect to the parameters. Several examples from adaptive identification, control and observer schemes are given as illustrations of the conceptual simplification provided by the structural principle.

Impaired conflict monitoring in Parkinson's disease patients during an oculomotor redirect task

Fallibility is inherent in human cognition and so a system that will monitor performance is indispensable. While behavioral evidence for such a system derives from the finding that subjects slow down after trials that are likely to produce errors, the neural and behavioral characterization that enables such control is incomplete. Here, we report a specific role for dopamine/basal ganglia in response conflict by accessing deficits in performance monitoring in patients with Parkinson's disease. To characterize such a deficit, we used a modification of the oculomotor countermanding task to show that slowing down of responses that generate robust response conflict, and not post-error per se, is deficient in Parkinson's disease patients. Poor performance adjustment could be either due to impaired ability to slow RT subsequent to conflicts or due to impaired response conflict recognition. If the latter hypothesis was true, then PD subjects should show evidence of impaired error detection/correction, which was found to be the case. These results make a strong case for impaired performance monitoring in Parkinson's patients.

Why is there a short-term increase in global precipitation in response to diminished CO2 forcing?

Recently, it was found that a reduction in atmospheric CO2 concentration leads to a temporary increase in global precipitation. We use the Hadley Center coupled atmosphere-ocean model, HadCM3L, to demonstrate that this precipitation increase is a consequence of precipitation sensitivity to changes in atmospheric CO2 concentrations through fast tropospheric adjustment processes. Slow ocean cooling explains the longer-term decrease in precipitation. Increased CO2 tends to suppress evaporation/precipitation whereas increased temperatures tend to increase evaporation/precipitation. When the enhanced CO2 forcing is removed, global precipitation increases temporarily, but this increase is not observed when a similar negative radiative forcing is applied as a reduction of solar intensity. Therefore, transient precipitation increase following a reduction in CO2-radiative forcing is a consequence of the specific character of CO2 forcing and is not a general feature associated with decreases in radiative forcing. Citation: Cao, L., G. Bala, and K. Caldeira (2011), Why is there a short-term increase in global precipitation in response to diminished CO2 forcing?, Geophys. Res. Lett., 38, L06703, doi:10.1029/2011GL046713.

Carrier density-dependent transport in poly(3-methylthiophene): from injection-limited to space-charge-limited current

Current-voltage (I-V) and impedance measurements were carried out in doped poly(3-methylthiophene) devices by varying the carrier density. As the carrier concentration reduces the I-V characteristics indicate that the conduction mechanism is limited by metal-polymer interface, as also observed in impedance data. The temperature dependence of I-V in moderately doped samples shows a trap-controlled space-charge-limited conduction (SCLC); whereas in lightly doped devices injection-limited conduction is observed at lower bias and SCLC at higher voltages. The carrier density-dependent quasi-Fermi level adjustment and trap-limited transport could explain this variation in conduction mechanism. Capacitance measurements at lower frequencies and higher bias voltages show a sign change in values due to the significant variations in the relaxation behaviour for lightly and moderately doped samples. The electrical hysteresis increases as carrier density is reduced due to the time scales involved in the de-trapping of carriers.

Diffuse optical tomographic imager using a single light source

Near-infrared diffuse optical tomography (DOT) technique has the capability of providing good quantitative reconstruction of tissue absorption and scattering properties with additional inputs such as input and output modulation depths and correction for the photon leakage. We have calculated the two-dimensional (2D) input modulation depth from three-dimensional (3D) diffusion to model the 2D diffusion of photons. The photon leakage when light traverses from phantom to the fiber tip is estimated using a solid angle model. The experiments are carried for single (5 and 6 mm) as well as multiple inhomogeneities (6 and 8 mm) with higher absorption coefficient in a homogeneous phantom. Diffusion equation for photon transport is solved using finite element method and Jacobian is modeled for reconstructing the optical parameters. We study the development and performance of DOT system using modulated single light source and multiple detectors. The dual source methods are reported to have better reconstruction capabilities to resolve and localize single as well as multiple inhomogeneities because of its superior noise rejection capability. However, an experimental setup with dual sources is much more difficult to implement because of adjustment of two out of phase identical light probes symmetrically on either side of the detector during scanning time. Our work shows that with a relatively simpler system with a single source, the results are better in terms of resolution and localization. The experiments are carried out with 5 and 6 mm inhomogeneities separately and 6 and 8 mm inhomogeneities both together with absorption coefficient almost three times as that of the background. The results show that our experimental single source system with additional inputs such as 2D input/output modulation depth and air fiber interface correction is capable of detecting 5 and 6 mm inhomogeneities separately and can identify the size difference of multiple inhomogeneities such as 6 and 8 mm. The localization error is zero. The recovered absorption coefficient is 93% of inhomogeneity that we have embedded in experimental phantom.