Characterization of groundwater chemistry under the influence of lithologic and anthropogenic factors along a climatic gradient in Upper Cauvery basin, South India

Hydrogeological and climatic effect on chemical behavior of groundwater along a climatic gradient is studied along a river basin. `Semi-arid' (500-800 mm of mean annual rainfall), `sub-humid' (800-1,200 mm/year) and `humid' (1,200-1,500 mm/year) are the climatic zones chosen along the granito-gneissic plains of Kabini basin in South India for the present analysis. Data on groundwater chemistry is initially checked for its quality using NICB ratio (<+/- 5 %), EC versus TZ+ (similar to 0.85 correlation), EC versus TDS and EC versus TH analysis. Groundwater in the three climatic zones is `hard' to `very hard' in terms of Ca-Mg hardness. Polluted wells are identified (> 40 % of pollution) and eliminated for the characterization. Piper's diagram with mean concentrations indicates the evolution of CaNaHCO3 (semi-arid) from CaHCO3 (humid zone) along the climatic gradient. Carbonates dominate other anions and strong acids exceeded weak acids in the region. Mule Hole SEW, an experimental watershed in sub-humid zone, is characterized initially using hydrogeochemistry and is observed to be a replica of entire sub-humid zone (with 25 wells). Extension of the studies for the entire basin (120 wells) showed a chemical gradient along the climatic gradient with sub-humid zone bridging semi-arid and humid zones. Ca/Na molar ratio varies by more than 100 times from semi-arid to humid zones. Semi-arid zone is more silicaceous than sub-humid while humid zone is more carbonaceous (Ca/Cl similar to 14). Along the climatic gradient, groundwater is undersaturated (humid), saturated (sub-humid) and slightly supersaturated (semi-arid) with calcite and dolomite. Concentration-depth profiles are in support of the geological stratification i.e., not approximate to 18 m of saprolite and similar to 25 m of fracture rock with parent gneiss beneath. All the wells are classified into four groups based on groundwater fluctuations and further into `deep' and `shallow' based on the depth to groundwater. Higher the fluctuations, larger is its impact on groundwater chemistry. Actual seasonal patterns are identified using `recharge-discharge' concept based on rainfall intensity instead of traditional monsoon-non-monsoon concept. Non-pumped wells have low Na/Cl and Ca/Cl ratios in recharge period than in discharge period (Dilution). Few other wells, which are subjected to pumping, still exhibit dilution chemistry though water level fluctuations are high due to annual recharge. Other wells which do not receive sufficient rainfall and are constantly pumped showed high concentrations in recharge period rather than in discharge period (Anti-dilution). In summary, recharge-discharge concept demarcates the pumped wells from natural deep wells thus, characterizing the basin.

ON POLYTOPAL UPPER BOUND SPHERES

Generalizing a result (the case k = 1) due to M. A. Perles, we show that any polytopal upper bound sphere of odd dimension 2k + 1 belongs to the generalized Walkup class K-k(2k + 1), i.e., all its vertex links are k-stacked spheres. This is surprising since it is far from obvious that the vertex links of polytopal upper bound spheres should have any special combinatorial structure. It has been conjectured that for d not equal 2k + 1, all (k + 1)-neighborly members of the class K-k(d) are tight. The result of this paper shows that the hypothesis d not equal 2k + 1 is essential for every value of k >= 1.

The upper Bay of Bengal salinity structure in a high-resolution model

Salinity in the Bay of Bengal is highly heterogeneous, with extremely fresh waters found at the surface in the Northern part of the basin, and saltier waters at subsurface as well as to the south. This paper investigates the seasonal structure of sea surface salinity of the Bay in a regional high-resolution model forced by ERA-Interim reanalysis and various precipitation products. Surface circulation is believed to drive the spreading of northern Bay of Bengal fresh waters to the rest of the Indian Ocean. We first present a series of experiments to infer the sensitivity of modeled circulation to various numerical choices. Surface circulation is found to be sensitive to the horizontal resolution of the model, with the 1/12 degrees version appearing much more realistic than the 1/4 degrees version. The sidewall boundary condition is also drastically influencing the characteristics of the western boundary current simulated. We then investigate the sensitivity of the salinity response to the various precipitation products. We observe that ERA-Interim excess precipitation induces a fresh bias in the surface salinity response. Spaceborne precipitation products are more satisfactory. We then identify the pathways of the northern Bay freshwater mass, based on passive tracers experiments. Our model suggests that over timescales of a few months, vertical exchanges between the upper fresh layer and the underlying saltier layer appear to be the main export pathway for the freshwater. The horizontal circulation within the mixed layer also acts to convey fresh waters out of the Bay at these timescales, but in a lesser quantity compared to the vertical export. Beyond its intrinsic interest for the understanding of Bay of Bengal physics, this study highlights the need for a careful design of any realistic numerical model, in three key aspects: the choice of the resolution of the model, the choice of the sub-grid scale parameterizations, and the choice of the forcing fluxes. (C) 2013 Elsevier Ltd. All rights reserved.

Upper bound solution for pullout capacity of vertical anchors in sand using finite elements and limit analysis

The horizontal pullout capacity of vertical anchors embedded in sand has been determined by using an upper bound theorem of the limit analysis in combination with finite elements. The numerical results are presented in nondimensional form to determine the pullout resistance for various combinations of embedment ratio of the anchor (H/B), internal friction angle (ϕ) of sand, and the anchor-soil interface friction angle (δ). The pullout resistance increases with increases in the values of embedment ratio, friction angle of sand and anchor-soil interface friction angle. As compared to earlier reported solutions in literature, the present solution provides a better upper bound on the ultimate collapse load.

REDUCING COMPUTATIONAL EFFORT IN SOLVING GEOMECHANICS PROBLEMS WITH UPPER BOUND FINITE ELEMENTS LIMIT ANALYSIS AND LINEAR OPTIMIZATION

This paper presents a simple technique for reducing the computational effort while solving any geotechnical stability problem by using the upper bound finite element limit analysis and linear optimization. In the proposed method, the problem domain is discretized into a number of different regions in which a particular order (number of sides) of the polygon is chosen to linearize the Mohr-Coulomb yield criterion. A greater order of the polygon needs to be selected only in that region wherein the rate of the plastic strains becomes higher. The computational effort required to solve the problem with this implementation reduces considerably. By using the proposed method, the bearing capacity has been computed for smooth and rough strip footings and the results are found to be quite satisfactory.

Solving Axisymmetric Stability Problems by Using Upper Bound Finite Elements, Limit Analysis, and Linear Optimization

A numerical formulation has been proposed for solving an axisymmetric stability problem in geomechanics with upper bound limit analysis, finite elements, and linear optimization. The Drucker-Prager yield criterion is linearized by simulating a sphere with a circumscribed truncated icosahedron. The analysis considers only the velocities and plastic multiplier rates, not the stresses, as the basic unknowns. The formulation is simple to implement, and it has been employed for finding the collapse loads of a circular footing placed over the surface of a cohesive-frictional material. The formulation can be used to solve any general axisymmetric geomechanics stability problem.

Effect of the Flow Rule on the Bearing Capacity of Strip Foundations on Sand by the Upper-Bound Limit Analysis and Slip Lines

The influence of the flow rule on the bearing capacity of strip foundations placed on sand was investigated using a new kinematic approach of upper-bound limit analysis. The method of stress characteristics was first used to find the mechanism of the failure and to compute the stress field by using the Mohr-Coulomb yield criterion. Once the failure mechanism had been established, the kinematics of the plastic deformation was established, based on the requirements of the upper-bound limit theorem. Both associated and nonassociated plastic flows were considered, and the bearing capacity was obtained by equating the rate of external plastic work to the rate of the internal energy dissipation for both smooth and rough base foundations. The results obtained from the analysis were compared with those available from the literature. (C) 2014 American Society of Civil Engineers.

Upper Bounds on the Size of Grain-Correcting Codes

In this paper, we revisit the combinatorial error model of Mazumdar et al. that models errors in high-density magnetic recording caused by lack of knowledge of grain boundaries in the recording medium. We present new upper bounds on the cardinality/rate of binary block codes that correct errors within this model. All our bounds, except for one, are obtained using combinatorial arguments based on hypergraph fractional coverings. The exception is a bound derived via an information-theoretic argument. Our bounds significantly improve upon existing bounds from the prior literature.

Texture discriminability in monkey inferotemporal cortex predicts human texture perception

Shape and texture are both important properties of visual objects, but texture is relatively less understood. Here, we characterized neuronal responses to discrete textures in monkey inferotemporal (IT) cortex and asked whether they can explain classic findings in human texture perception. We focused on three classic findings on texture discrimination: 1) it can be easy or hard depending on the constituent elements; 2) it can have asymmetries, and 3) it is reduced for textures with randomly oriented elements. We recorded neuronal activity from monkey inferotemporal (IT) cortex and measured texture perception in humans for a variety of textures. Our main findings are as follows: 1) IT neurons show congruent selectivity for textures across array size; 2) textures that were easy for humans to discriminate also elicited distinct patterns of neuronal activity in monkey IT; 3) texture pairs with asymmetries in humans also exhibited asymmetric variation in firing rate across monkey IT; and 4) neuronal responses to randomly oriented textures were explained by an average of responses to homogeneous textures, which rendered them less discriminable. The reduction in discriminability of monkey IT neurons predicted the reduced discriminability in humans during texture discrimination. Taken together, our results suggest that texture perception in humans is likely based on neuronal representations similar to those in monkey IT.

A Comparison of Machine Learning Techniques for Modeling River Flow Time Series: The Case of Upper Cauvery River Basin

Models of river flow time series are essential in efficient management of a river basin. It helps policy makers in developing efficient water utilization strategies to maximize the utility of scarce water resource. Time series analysis has been used extensively for modeling river flow data. The use of machine learning techniques such as support-vector regression and neural network models is gaining increasing popularity. In this paper we compare the performance of these techniques by applying it to a long-term time-series data of the inflows into the Krishnaraja Sagar reservoir (KRS) from three tributaries of the river Cauvery. In this study flow data over a period of 30 years from three different observation points established in upper Cauvery river sub-basin is analyzed to estimate their contribution to KRS. Specifically, ANN model uses a multi-layer feed forward network trained with a back-propagation algorithm and support vector regression with epsilon intensive-loss function is used. Auto-regressive moving average models are also applied to the same data. The performance of different techniques is compared using performance metrics such as root mean squared error (RMSE), correlation, normalized root mean squared error (NRMSE) and Nash-Sutcliffe Efficiency (NSE).

Interpreting the upper level structure of the Madden-Julian oscillation

The nonlinear response of a spherical shallow water model to an imposed heat source in the presence of realistic zonal mean zonal winds is investigated numerically. The solutions exhibit elongated, meridionally tilted ridges and troughs indicative of a poleward dispersion of wave activity. As the speed of the jets is increased, the equatorial Kelvin wave is unaffected but the global Rossby wave train coalesces to form a compact, amplified quadrupole structure that bears a striking resemblance to the observed upper level structure of the Madden-Julian oscillation. In the presence of strong subtropical westerly jets, the advection of planetary vorticity by the meridional flow and relative vorticity by the zonally averaged background flow conspire to create the distinctive quadrupole configuration of flanking Rossby waves.

Do gamma oscillations play a role in cerebral cortex?

Gamma rhythm (which has a center frequency between 30 and 80 Hz) is modulated by cognitive mechanisms such as attention and memory, and has been hypothesized to play a role in mediating these processes by supporting communication channels between cortical areas or encoding information in its phase. We highlight several issues related to gamma rhythms, such as low and inconsistent power, its dependence on low-level stimulus features, problems due to conduction delays, and contamination due to spike-related activity that makes accurate estimation of gamma phase difficult. Gamma rhythm could be a potentially useful signature of excitation-inhibition interactions in the brain, but whether it also provides a mechanism for information processing or coding remains an open question.

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.

Dynamics of 3D view invariance in monkey inferotemporal cortex

Rotations in depth are challenging for object vision because features can appear, disappear, be stretched or compressed. Yet we easily recognize objects across views. Are the underlying representations view invariant or dependent? This question has been intensely debated in human vision, but the neuronal representations remain poorly understood. Here, we show that for naturalistic objects, neurons in the monkey inferotemporal (IT) cortex undergo a dynamic transition in time, whereby they are initially sensitive to viewpoint and later encode view-invariant object identity. This transition depended on two aspects of object structure: it was strongest when objects foreshortened strongly across views and were similar to each other. View invariance in IT neurons was present even when objects were reduced to silhouettes, suggesting that it can arise through similarity between external contours of objects across views. Our results elucidate the viewpoint debate by showing that view invariance arises dynamically in IT neurons out of a representation that is initially view dependent.