Chemical mediation of egg capsule deposition by mud snails

Mud snails (Ilyanassa obsoleta = Nassarius obsoletus = Nassa obsoleta) deposit eggs in protective capsules on hard substrata in soft bottom environments. We studied sites of egg capsule deposition and snail movement responses to odors to determine if chemoreception plays a role in deposition site selection. From results of field surveys, laboratory experiments, and field experiments, we conclude that mud snails use chemoreception for capsule deposition. Attractive odors originate from mud snail and whelk egg capsules and from living bivalves. Evidence for attractive odors from conspecifics is equivocal. Capsules are deposited on living odor sources and nearby hard substrates. We hypothesize that deposition of capsules on living substrates increases the likelihood that embryos will survive by decreasing the chance of smothering of embryos by sediments.     

Application of polymeric flocculant for enhancing settling of the pond ash particles and water drainage from hydraulically stowed pond ash

Delayed settling of the ash particles and poor drainage of water from the pond ash are the major problems faced during the hydraulic stowing of pond ash. In this study the effect of polymeric flocculant on settling of the ash particles and drainage of water during pond ash stowing are investigated. In addition, the parameters, viz. drainage and absorption of water during pond ash stowing are quantified by stowing a mine goaf model with pond ash slurries of five different concentrations added with and without flocculant. The study revealed that addition of only 5 × 10^?6 of Sodium Carboxymethyl Cellulose (Na-CMC) flocculant with the pond ash slurries during stowing offers best result in terms of quicker settling of the ash particles and enhanced water drainage from the hydraulically stowed pond ash. Besides, it resulted in drainage of more than 85% of the total water used in the initial 45 min of stowing. The improvement in drainage is caused due to coagulation and flocculation of the pond ash particles because of charge neutralization and particle–particle bridging. This study may provide a basis for estimating the drainage and absorption of water during the real pond ash stowing operation in underground mines.     

Applications of 'TissueQuant'- a color intensity quantification tool for medical research

This paper demonstrates the use of TissueQuant - an image analysis tool for quantification of color intensities which was developed for use in medical research where the stained biological specimen such as tissue or antigen needs to be quantified. TissueQuant provides facilities for user interaction to choose and quantify the color of interest and its shades. Gaussian weighting functions are used to provide a color score which quantifies how close the shade is to the user specified reference color. We describe two studies in medical research which use TissueQuant for quantification. The first study evaluated the effect of petroleum-ether extract of Cissus quadrangularis (CQ) on osteoporotic rats. It was found that the analysis results correlated well with the manual evaluation, p < 0.001. The second study evaluated the nerve morphometry and it was found that the adipose and non adipose tissue content was maximum in radial nerve among the five nerves studied.     

Modeling of ammonothermal growth of gallium nitride single crystals

Ammonothermal growth of GaN crystals with a retrograde solubility has been modeled and simulated here using fluid dynamics, thermodynamics and heat transfer models. The nutrient is considered as a porous media bed and the flow in the porous charge is simulated using the Darcy-Brinkman-Forchheimer model. The resulting governing equations are solved using the finite volume method. For the case of retrograde solubility, the charge is put above the baffle. The temperature difference between the dissolving zone and growth zone is found smaller than that applied on the sidewall of autoclave. The baffle opening has a strong effect on the nutrient transport and supersaturation of GaN species in the growth zone.     

Artificial Neural Network Model for Predicting Stable and Unstable Regions in Cu-Zn Alloys

Processing maps are developed using the Dynamic Materials Model (DMM) and instability criterion, which help in choosing optimum process parameters for hot-working of materials. Certain high-level expertise is required to interpret and extract the information on instability regimes to be avoided during processing. In recent years, Artificial Neural Network (ANN) models have been developed to predict flow stress by using the input vector; namely, temperature, strain rate and strain. In this study, using the available Cu-Zn alloy data, ANN model has been developed to classify the hot-working process parameters, such as temperature, strain rate and flow stress for instability regime, directly from the corrected flow stress data without applying the DMM. This model uses 10 compositions of Cu-Zn system, ranging from 3% Zn to 51% Zn. The developed ANN model has been able to learn the nonlinear classifier, which separates unstable region from the stable region in the Cu-Zn alloy system with zinc content less than 40%.     

Rocking stiffness of mounting arrangements in electrical cabinets and control panels

Several studies have shown that the consideration of a rigid body-rocking mode in a cabinet is necessary to evaluate accurate incabinet spectra. Observations from finite element analyses are used to study cabinet rocking behavior and to show that accurate representation of the boundary conditions at the cabinet base is essential in the evaluation of correct rocking mode. Simple formulations for evaluating the rocking stiffness are developed by conducting detailed analytical studies for three different types of cabinet mounting arrangements. Availability of these formulations enables incorporation of a cabinet rocking mode in the Ritz vector approach [Nucl. Eng. Des. 190 (1990) 225] for evaluating the cabinet dynamic properties in significant mode and for generating the incabinet response spectra.     

Designing fault-tolerant real-time computer systems with diversified bus architecture for nuclear power plants

Fault-tolerant real-time computer (FT-RTC) systems are widely used to perform safe operation of nuclear power plants (NPP) and safe shutdown in the event of any untoward situation. Design requirements for such systems need high reliability, availability, computational ability for measurement via sensors, control action via actuators, data communication and human interface via keyboard or display. All these attributes of FT-RTC systems are required to be implemented using best known methods such as redundant system design using diversified bus architecture to avoid common cause failure, fail-safe design to avoid unsafe failure and diagnostic features to validate system operation. In this context, the system designer must select efficient as well as highly reliable diversified bus architecture in order to realize fault-tolerant system design. This paper presents a comparative study between CompactPCI bus and Versa Module Eurocard (VME) bus architecture for designing FT-RTC systems with switch over logic system (SOLS) for NPP.     

Groundwater Flow and Contaminant Transport Simulation with Imprecise Parameters

A methodology has been developed in this study wherein a genetic algorithm (GA) is used to find a global optimal solution to a groundwater flow and contaminant problem by incorporating an artificial neural network (ANN) to evaluate the objective function within the genetic algorithm. The study shows that an ANN-GA technique can be used to find the uncertainties in output parameters due to imprecision in input parameters. The ANN-GA methodology is applied to five case studies involving radial flow in a well, one-dimensional solute transport in steady uniform flow, a two-dimensional heterogeneous steady flow, a two-dimensional solute transport, and a two-dimensional unsteady groundwater flow to demonstrate the efficiency and effectiveness of the developed algorithm. The results show that, with this approach, one can successfully measure the uncertainty in groundwater flow and contaminant transport simulations and achieve a considerable reduction in computational effort when compared to the vertex method that has been widely used in the past.     

Feature Activated Molecular Dynamics: Parallelization and Application to Systems with Globally Varying Mechanical Fields

A recently developed hybrid molecular dynamics method (Feature Activated Molecular Dynamics, or FAMD), which was originally designed to extend the scope of certain types of molecular dynamics simulations, is extended here in two ways. First, the method is modified to execute on parallel computer architectures using the MPI communication interface. The parallel FAMD algorithm is demonstrated to be computationally efficient and to substantially increase the length scales accessible with molecular dynamics. The performance of the parallel algorithm is demonstrated using a crystalline system containing 1× 10⁶ atoms, in which 1000 supersaturated self-interstitials are introduced and allowed to aggregate for about 4 ns. In the second part of this paper, the FAMD method is applied to problems in which spatio-temporally varying stress fields are present throughout the simulation cell. In particular, we consider the evolution of a spherical void in a hydrostatically stressed silicon crystal and show that the method can capture the extremely rapid void cavitation dynamics following material failure. Once again, the FAMD approach is demonstrated to provide substantial computational advantages over standard molecular dynamics.