Dynamic properties of sand from dry to fully saturated states

By using bender and extender elements test, the velocities of the primary and shear waves, V(P) and V(s) respectively, were measured for a sandy material by gradually varying the degree of saturation, S(r), between the dry and fully saturated states. The effect on the results of varying the relative density and effective confining pressure was also studied. The measurements clearly reveal that for a certain optimum S(r), which is around 0.7-0.9% for the chosen sand, the value of the shear modulus G reaches a maximum value, whereas the corresponding Poisson's ratio nu attains a minimum value. The values of the shear modulus corresponding to S(r) approximate to 0% and S(r) = 100% tend towards the same value. For values of Skempton's B parameter greater than 0.99, the values of V(P) and nu rise very sharply to those of water. The predictions from Biot's theory with respect to the variation of V(P) with S(r) match well with the measured experimental data.

Trade determination in multi-attribute exchanges

Electronic exchanges are double-sided marketplaces that allow multiple buyers to trade with multiple sellers, with aggregation of demand and supply across the bids to maximize the revenue in the market. Two important issues in the design of exchanges are (1) trade determination (determining the number of goods traded between any buyer-seller pair) and (2) pricing. In this paper we address the trade determination issue for one-shot, multi-attribute exchanges that trade multiple units of the same good. The bids are configurable with separable additive price functions over the attributes and each function is continuous and piecewise linear. We model trade determination as mixed integer programming problems for different possible bid structures and show that even in two-attribute exchanges, trade determination is NP-hard for certain bid structures. We also make some observations on the pricing issues that are closely related to the mixed integer formulations.

Reinforcement learning applications in dynamic pricing of retail markets

In this paper, we investigate the use of reinforcement learning (RL) techniques to the problem of determining dynamic prices in an electronic retail market. As representative models, we consider a single seller market and a two seller market, and formulate the dynamic pricing problem in a setting that easily generalizes to markets with more than two sellers. We first formulate the single seller dynamic pricing problem in the RL framework and solve the problem using the Q-learning algorithm through simulation. Next we model the two seller dynamic pricing problem as a Markovian game and formulate the problem in the RL framework. We solve this problem using actor-critic algorithms through simulation. We believe our approach to solving these problems is a promising way of setting dynamic prices in multi-agent environments. We illustrate the methodology with two illustrative examples of typical retail markets.

High resolution facies record on late Holocene flood plain sediments from lower reaches of Narmada Valley, Western India

A high resolution quantitative granulometric record for site Uchediya 21A degrees 43'2.22aEuro(3) N, 73A degrees 6'26.22aEuro(3) E; 10 m a. s. l.] gives understanding towards accretion history of the late Holocene flood plain in the lower reaches of Narmada River. Two sediment facies (sandy and muddy) and seven subfacies (sandy subfacies: St(MS+FS+CS), SmFS+MS, Sl(FS+VFS), and St(MS + CS); muddy subfacies: FmSILT+VFS+FS, FmSILT+VFS (O) and FmSILT+VFS (T)) are identified based on cluster analysis supplemented with sedimentary structures observed in field and other laboratory data. Changes in hydrodynamics are further deduced based on various sedimentological parameters and their ratios leading to arrive at a depositional model.

Anomalous structural and dynamical phase transitions of soft colloidal binary mixtures

We report microscopic structural and dynamical measurements on binary mixtures of homopolymers and polymer grafted nanoparticles at high densities in good solvent. We find strong and unexpected anomalies in the structure and dynamics of these binary mixtures, including appearance of spontaneous orientational alignment, as a function of added homopolymers of different molecular weights. Our experiments point to the possibility of exploiting the phase space in density and homopolymer size, of such hybrid systems, to create new materials with novel structural and physical properties.