Effect of Groundwater Seepage on Uplift Resistance of Buried Pipelines

The uplift resistance of pipelines buried in sands, in the presence of inclined groundwater flow, considering both upward and downward flow directions, has been determined by using the lower bound finite elements limit analysis in conjunction with nonlinear optimization. A correction factor (f (gamma) ), which needs to be multiplied with the uplift factor (F (gamma) ), has been computed to account for groundwater seepage. The variation of f (gamma) has been obtained as a function of i(gamma (w) /gamma (sub) ) for different horizontal inclinations (theta) of groundwater flow; where i = absolute magnitude of hydraulic gradient along the direction of flow, gamma (w) is the unit weight of water and gamma (sub) is the submerged unit weight of soil mass. For a given magnitude of i, there exists a certain critical value of theta for which the magnitude of f (gamma) becomes the minimum. An example has also been presented to illustrate the application of the results obtained for designing pipelines in presence of groundwater seepage.

LOWER BOUNDS FOR BOXICITY

An axis-parallel b-dimensional box is a Cartesian product R-1 x R-2 x ... x R-b where R-i is a closed interval of the form a(i),b(i)] on the real line. For a graph G, its boxicity box(G) is the minimum dimension b, such that G is representable as the intersection graph of boxes in b-dimensional space. Although boxicity was introduced in 1969 and studied extensively, there are no significant results on lower bounds for boxicity. In this paper, we develop two general methods for deriving lower bounds. Applying these methods we give several results, some of which are listed below: 1. The boxicity of a graph on n vertices with no universal vertices and minimum degree delta is at least n/2(n-delta-1). 2. Consider the g(n,p) model of random graphs. Let p <= 1 - 40logn/n(2.) Then with high `` probability, box(G) = Omega(np(1 - p)). On setting p = 1/2 we immediately infer that almost all graphs have boxicity Omega(n). Another consequence of this result is as follows: For any positive constant c < 1, almost all graphs on n vertices and m <= c((n)(2)) edges have boxicity Omega(m/n). 3. Let G be a connected k-regular graph on n vertices. Let lambda be the second largest eigenvalue in absolute value of the adjacency matrix of G. Then, the boxicity of G is a least (kappa(2)/lambda(2)/log(1+kappa(2)/lambda(2))) (n-kappa-1/2n). 4. For any positive constant c 1, almost all balanced bipartite graphs on 2n vertices and m <= cn(2) edges have boxicity Omega(m/n).

On Whitespace Identification Using Randomly Deployed Sensors

This work considers the identification of the available whitespace, i.e., the regions that do not contain any existing transmitter within a given geographical area. To this end, n sensors are deployed at random locations within the area. These sensors detect for the presence of a transmitter within their radio range r(s) using a binary sensing model, and their individual decisions are combined to estimate the available whitespace. The limiting behavior of the recovered whitespace as a function of n and r(s) is analyzed. It is shown that both the fraction of the available whitespace that the nodes fail to recover as well as their radio range optimally scale as log(n)/n as n gets large. The problem of minimizing the sum absolute error in transmitter localization is also analyzed, and the corresponding optimal scaling of the radio range and the necessary minimum transmitter separation is determined.

SARAS MEASUREMENT OF THE RADIO BACKGROUND AT LONG WAVELENGTHS

SARAS is a correlation spectrometer connected to a frequency independent antenna that is purpose-designed for precision measurements of the radio background at long wavelengths. The design, calibration, and observing strategies admit solutions for the internal additive contributions to the radiometer response, and hence a separation of these contaminants from the antenna temperature. We present here a wideband measurement of the radio sky spectrum by SARAS that provides an accurate measurement of the absolute brightness and spectral index between 110 and 175MHz. Accuracy in the measurement of absolute sky brightness is limited by systematic errors of magnitude 1.2%; errors in calibration and in the joint estimation of sky and system model parameters are relatively smaller. We use this wide-angle measurement of the sky brightness using the precision wide-band dipole antenna to provide an improved absolute calibration for the 150 MHz all-sky map of Landecker and Wielebinski: subtracting an offset of 21.4 K and scaling by a factor of 1.05 will reduce the overall offset error to 8 K (from 50 K) and scale error to 0.8% (from 5%). The SARAS measurement of the temperature spectral index is in the range -2.3 to -2.45 in the 110-175MHz band and indicates that the region toward the Galactic bulge has a relatively flatter index.

Coding of relative size in monkey inferotemporal cortex

We seldom mistake a closer object as being larger, even though its retinal image is bigger. One underlying mechanism could be to calculate the size of the retinal image relative to that of another nearby object. Here we set out to investigate whether single neurons in the monkey inferotemporal cortex (IT) are sensitive to the relative size of parts in a display. Each neuron was tested on shapes containing two parts that could be conjoined or spatially separated. Each shape was presented in four versions created by combining the two parts at each of two possible sizes. In this design, neurons sensitive to the absolute size of parts would show the greatest response modulation when both parts are scaled up, whereas neurons encoding relative size would show similar responses. Our main findings are that 1) IT neurons responded similarly to all four versions of a shape, but tuning tended to be more consistent between versions with proportionately scaled parts; 2) in a subpopulation of cells, we observed interactions that resulted in similar responses to proportionately scaled parts; 3) these interactions developed together with sensitivity to absolute size for objects with conjoined parts but developed slightly later for objects with spatially separate parts. Taken together, our results demonstrate for the first time that there is a subpopulation of neurons in IT that encodes the relative size of parts in a display, forming a potential neural substrate for size constancy.

Voice source characterization using pitch synchronous discrete cosine transform for speaker identification

A characterization of the voice source (VS) signal by the pitch synchronous (PS) discrete cosine transform (DCT) is proposed. With the integrated linear prediction residual (ILPR) as the VS estimate, the PS DCT of the ILPR is evaluated as a feature vector for speaker identification (SID). On TIMIT and YOHO databases, using a Gaussian mixture model (GMM)-based classifier, it performs on par with existing VS-based features. On the NIST 2003 database, fusion with a GMM-based classifier using MFCC features improves the identification accuracy by 12% in absolute terms, proving that the proposed characterization has good promise as a feature for SID studies. (C) 2015 Acoustical Society of America

Retrieval and Multi-scale Validation of Soil Moisture from Multi-temporal SAR Data in a Semi-Arid Tropical Region

The current study presents an algorithm to retrieve surface Soil Moisture (SM) from multi-temporal Synthetic Aperture Radar (SAR) data. The developed algorithm is based on the Cumulative Density Function (CDF) transformation of multi-temporal RADARSAT-2 backscatter coefficient (BC) to obtain relative SM values, and then converts relative SM values into absolute SM values using soil information. The algorithm is tested in a semi-arid tropical region in South India using 30 satellite images of RADARSAT-2, SMOS L2 SM products, and 1262 SM field measurements in 50 plots spanning over 4 years. The validation with the field data showed the ability of the developed algorithm to retrieve SM with RMSE ranging from 0.02 to 0.06 m(3)/m(3) for the majority of plots. Comparison with the SMOS SM showed a good temporal behaviour with RMSE of approximately 0.05 m(3)/m(3) and a correlation coefficient of approximately 0.9. The developed model is compared and found to be better than the change detection and delta index model. The approach does not require calibration of any parameter to obtain relative SM and hence can easily be extended to any region having time series of SAR data available.

Energy Harvesting WSNs for Accurately Estimating the Maximum Sensor Reading: Trade-Offs and Optimal Design

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.

Optimum Parameter Selection in Sparse Reconstruction of Frequency-Domain Optical-Coherence Tomography Signals

For a multilayered specimen, the back-scattered signal in frequency-domain optical-coherence tomography (FDOCT) is expressible as a sum of cosines, each corresponding to a change of refractive index in the specimen. Each of the cosines represent a peak in the reconstructed tomogram. We consider a truncated cosine series representation of the signal, with the constraint that the coefficients in the basis expansion be sparse. An l(2) (sum of squared errors) data error is considered with an l(1) (summation of absolute values) constraint on the coefficients. The optimization problem is solved using Weiszfeld's iteratively reweighted least squares (IRLS) algorithm. On real FDOCT data, improved results are obtained over the standard reconstruction technique with lower levels of background measurement noise and artifacts due to a strong l(1) penalty. The previous sparse tomogram reconstruction techniques in the literature proposed collecting sparse samples, necessitating a change in the data capturing process conventionally used in FDOCT. The IRLS-based method proposed in this paper does not suffer from this drawback.

Multiple Spectral Peak Tracking for Heart Rate Monitoring from Photoplethysmography Signal During Intensive Physical Exercise

We propose a multiple initialization based spectral peak tracking (MISPT) technique for heart rate monitoring from photoplethysmography (PPG) signal. MISPT is applied on the PPG signal after removing the motion artifact using an adaptive noise cancellation filter. MISPT yields several estimates of the heart rate trajectory from the spectrogram of the denoised PPG signal which are finally combined using a novel measure called trajectory strength. Multiple initializations help in correcting erroneous heart rate trajectories unlike the typical SPT which uses only single initialization. Experiments on the PPG data from 12 subjects recorded during intensive physical exercise show that the MISPT based heart rate monitoring indeed yields a better heart rate estimate compared to the SPT with single initialization. On the 12 datasets MISPT results in an average absolute error of 1.11 BPM which is lower than 1.28 BPM obtained by the state-of-the-art online heart rate monitoring algorithm.

Asparagine requirement in Plasmodium berghei as a target to prevent malaria transmission and liver infections

The proteins of Plasmodium, the malaria parasite, are strikingly rich in asparagine. Plasmodium depends primarily on host haemoglobin degradation for amino acids and has a rudimentary pathway for amino acid biosynthesis, but retains a gene encoding asparagine synthetase (AS). Here we show that deletion of AS in Plasmodium berghei (Pb) delays the asexual-and liver-stage development with substantial reduction in the formation of ookinetes, oocysts and sporozoites in mosquitoes. In the absence of asparagine synthesis, extracellular asparagine supports suboptimal survival of PbAS knockout (KO) parasites. Depletion of blood asparagine levels by treating PbASKO-infected mice with asparaginase completely prevents the development of liver stages, exflagellation of male gametocytes and the subsequent formation of sexual stages. In vivo supplementation of asparagine in mice restores the exflagellation of PbASKO parasites. Thus, the parasite life cycle has an absolute requirement for asparagine, which we propose could be targeted to prevent malaria transmission and liver infections.

Temperature-Dependent Photoluminescence of g-C3N4: Implication for Temperature Sensing

We report the temperature-dependent photoluminescence (PL) properties of polymeric graphite-like carbon nitride (g-C3N4) and a methodology for the determination of quantum efficiency along with the activation energy. The PL is shown to originate from three different pathways of transitions: sigma*-LP, pi*-LP, and pi*-pi, respectively. The overall activation energy is found to be similar to 73.58 meV which is much lower than the exciton binding energy reported theoretically but ideal for highly sensitive wide-range temperature sensing. The quantum yield derived from the PL data is 23.3%, whereas the absolute quantum yield is 5.3%. We propose that the temperature-dependent PL can be exploited for the evaluation of the temperature dependency of quantum yield as well as for temperature sensing. Our analysis further indicates that g-C3N4 is well-suited for wide-range temperature sensing.

Raman and infra-red microspectroscopy: towards quantitative evaluation for clinical research by ratiometric analysis

Biomolecular structure elucidation is one of the major techniques for studying the basic processes of life. These processes get modulated, hindered or altered due to various causes like diseases, which is why biomolecular analysis and imaging play an important role in diagnosis, treatment prognosis and monitoring. Vibrational spectroscopy (IR and Raman), which is a molecular bond specific technique, can assist the researcher in chemical structure interpretation. Based on the combination with microscopy, vibrational microspectroscopy is currently emerging as an important tool for biomedical research, with a spatial resolution at the cellular and sub-cellular level. These techniques offer various advantages, enabling label-free, biomolecular fingerprinting in the native state. However, the complexity involved in deciphering the required information from a spectrum hampered their entry into the clinic. Today with the advent of automated algorithms, vibrational microspectroscopy excels in the field of spectropathology. However, researchers should be aware of how quantification based on absolute band intensities may be affected by instrumental parameters, sample thickness, water content, substrate backgrounds and other possible artefacts. In this review these practical issues and their effects on the quantification of biomolecules will be discussed in detail. In many cases ratiometric analysis can help to circumvent these problems and enable the quantitative study of biological samples, including ratiometric imaging in 1D, 2D and 3D. We provide an extensive overview from the recent scientific literature on IR and Raman band ratios used for studying biological systems and for disease diagnosis and treatment prognosis.

Numerical Investigation of Richtmyer-Meshkov Instability Driven by Cylindrical Shocks

In this paper, a numerical method with high order accuracy and high resolution was developed to simulate the Richtmyer-Meshkov(RM) instability driven by cylindrical shock waves. Compressible Euler equations in cylindrical coordinate were adopted for the cylindrical geometry and a third order accurate group control scheme was adopted to discretize the equations. Moreover, an adaptive grid technique was developed to refine the grid near the moving interface to improve the resolution of numerical solutions. The results of simulation exhibited the evolution process of RM instability, and the effect of Atwood number was studied. The larger the absolute value of Atwood number, the larger the perturbation amplitude. The nonlinear effect manifests more evidently in cylindrical geometry. The shock reflected from the pole center accelerates the interface for the second time, considerably complicating the interface evolution process, and such phenomena of reshock and secondary shock were studied.