Rheological Behavior of Al-7Si-0.3Mg Alloy at Mushy State

In recent years, semisolid manufacturing has emerged as an attractive option for near net shape forming of components with aluminum alloys. In this class of processes, the key to success lies mainly in the understanding of rheological behavior of the semi-solid slurry in the temperature range between liquidus and solidus. The present study focuses on the non-Newtonian flow behavior of the pseudo plastic slurry of Al-7Si-0.3Mg alloy for a wide shear range using a high-temperature Searle-type rheometer. The rheological behavior of the slurry is studied with respect to relevant process variables and microstructural features such as shear rate, shear duration, temperature history, primary particle size, shape, and their distribution. The experiments performed are isothermal tests, continuous cooling tests, shear jump tests, and shear time tests. The continuous cooling experiments are aimed toward studying the viscosity and shear stress evolution within the slurry matrix with increasing solid fraction at a constant shear rate. Three different cooling rates are considered and their effect on flow behavior of the slurry was studied under iso-shear condition. Descending shear jump experiments are performed to understand the viscous instability of the slurry.

Continuous synthesis of high quality CdSe quantum dots in supercritical fluids

We demonstrate in here a powerful scalable technology to synthesize continuously high quality CdSe quantum dots (QDs) in supercritical hexane. Using a low cost, highly thermally stable Cd-precursor, cadmium deoxycholate, the continuous synthesis is performed in 400 mu m ID stainless steel capillaries resulting in CdSe QDs having sharp full-width-at-half-maxima (23 nm) and high photoluminescence quantum yields (45-55%). Transmission electron microscopy images show narrow particles sizes distribution (sigma <= 5%) with well-defined crystal lattices. Using two different synthesis temperatures (250 degrees C and 310 degrees C), it was possible to obtain zinc blende and wurtzite crystal structures of CdSe QDs, respectively. This synthetic approach allows achieving substantial production rates up to 200 mg of QDs per hour depending on the targeted size, and could be easily scaled to gram per hour.

Risk-Sensitive Ergodic Control of Continuous Time Markov Processes With Denumerable State Space

In this article, we study risk-sensitive control problem with controlled continuous time Markov chain state dynamics. Using multiplicative dynamic programming principle along with the atomic structure of the state dynamics, we prove the existence and a characterization of optimal risk-sensitive control under geometric ergodicity of the state dynamics along with a smallness condition on the running cost.

A Perspective to Adopt Continuous Dynamic Cognition for Malicious Node Detection in Heterogeneous Networks

The current day networks use Proactive networks for adaption to the dynamic scenarios. The use of cognition technique based on the Observe, Orient, Decide and Act loop (OODA) is proposed to construct proactive networks. The network performance degradation in knowledge acquisition and malicious node presence is a problem that exists. The use of continuous time dynamic neural network is considered to achieve cognition. The variance in service rates of user nodes is used to detect malicious activity in heterogeneous networks. The improved malicious node detection rates are proved through the experimental results presented in this paper. (C) 2015 The Authors. Published by Elsevier B.V.

PLAStiCC: Predictive Look-Ahead Scheduling for Continuous dataflows on Clouds

Scalable stream processing and continuous dataflow systems are gaining traction with the rise of big data due to the need for processing high velocity data in near real time. Unlike batch processing systems such as MapReduce and workflows, static scheduling strategies fall short for continuous dataflows due to the variations in the input data rates and the need for sustained throughput. The elastic resource provisioning of cloud infrastructure is valuable to meet the changing resource needs of such continuous applications. However, multi-tenant cloud resources introduce yet another dimension of performance variability that impacts the application's throughput. In this paper we propose PLAStiCC, an adaptive scheduling algorithm that balances resource cost and application throughput using a prediction-based lookahead approach. It not only addresses variations in the input data rates but also the underlying cloud infrastructure. In addition, we also propose several simpler static scheduling heuristics that operate in the absence of accurate performance prediction model. These static and adaptive heuristics are evaluated through extensive simulations using performance traces obtained from Amazon AWS IaaS public cloud. Our results show an improvement of up to 20% in the overall profit as compared to the reactive adaptation algorithm.

Reservoir Operation with Fuzzy State Variables for Irrigation of Multiple Crops

This paper presents the development and application of a stochastic dynamic programming model with fuzzy state variables for irrigation of multiple crops. A fuzzy stochastic dynamic programming (FSDP) model is developed in which the reservoir storage and soil moisture of the crops are considered as fuzzy numbers, and the reservoir inflow is considered as a stochastic variable. The model is formulated with an objective of minimizing crop yield deficits, resulting in optimal water allocations to the crops by maintaining storage continuity and soil moisture balance. The standard fuzzy arithmetic method is used to solve all arithmetic equations with fuzzy numbers, and the fuzzy ranking method is used to compare two or more fuzzy numbers. The reservoir operation model is integrated with a daily-based water allocation model, which results in daily temporal variations of allocated water, soil moisture, and crop deficits. A case study of an existing Bhadra reservoir in Karnataka, India, is chosen for the model application. The FSDP is a more realistic model because it considers the uncertainty in discretization of state variables. The results obtained using the FSDP model are found to be more acceptable for the case study than those of the classical stochastic dynamic model and the standard operating model, in terms of 10-day releases from the reservoir and evapotranspiration deficit. (C) 2015 American Society of Civil Engineers.

Cybernetic Modeling Revisited: A Method for Inferring the Cybernetic Variables u(i) from Experimental Data

The cybernetic modeling framework for the growth of microorganisms provides for an elegant methodology to account for the unknown regulatory phenomena through the use of cybernetic variables for enzyme induction and activity. In this paper, we revisit the assumption of limited resources for enzyme induction (Sigma u(i) = 1) used in the cybernetic modeling framework by presenting a methodology for inferring the individual cybernetic variables u(i) from experimental data. We use this methodology to infer u(i) during the simultaneous consumption of glycerol and lactose by Escherichia coli and then model the fitness trade-offs involved in the recently discovered predictive regulation strategy of microorganisms.

Computationally efficient models for simulation of non-ideal DC-DC converters operating in continuous and discontinuous conduction modes

This paper discusses dynamic modeling of non-isolated DC-DC converters (buck, boost and buck-boost) under continuous and discontinuous modes of operation. Three types of models are presented for each converter, namely, switching model, average model and harmonic model. These models include significant non-idealities of the converters. The switching model gives the instantaneous currents and voltages of the converter. The average model provides the ripple-free currents and voltages, averaged over a switching cycle. The harmonic model gives the peak to peak values of ripple in currents and voltages. The validity of all these models is established by comparing the simulation results with the experimental results from laboratory prototypes, at different steady state and transient conditions. Simulation based on a combination of average and harmonic models is shown to provide all relevant information as obtained from the switching model, while consuming less computation time than the latter.

Diagnostico de prevalencia a leptospirosis canina con respecto a las variables edad, sexo y raza, en ocho barrios del distrito 2 de la ciudad de Managua Septiembre 2007 - Enero 2008

La leptospirosis es considerada una de las zoonosis más difundidas en el mundo entero. El perro actúa como un potencial diseminador de esta enfermedad ya que mantiene una estrecha relación con el hombre, y al mismo tiempo con otros animales tanto domésticos como salvajes. Con el objetivo de conocer la presencia de leptospirosis canina, se realizó estudio en ocho barrios del distrito dos de la cuidad de Managua entre 8 de septiembre al 9 de diciembre 2007. Se realizó un muestreo de 76 canes, correspondiente al 5% del total de canes en los ocho barrios. Se extrajo 3ml de sangre de la vena safena externa, luego de procesarlas para separar el suero sanguíneo del plasma mediante centrifugación, fueron trasladadas al laboratorio del Centro Veterinario de Diagnóstico e Investigación CEVEDI, UNAN-León, para su análisis mediante los métodos ELISA y MAT. De acuerdo con los resultados obtenidos mediante la prueba ELISA un 93.4%, 71 canes, son negativos y un 6.6%, o bien 5 especímenes, son seropositivos a Leptospira spp. Según los resultados de la prueba de micro aglutinación MAT, el 96.1% de la población muestreada es negativa y el 3.9% es positiva a leptospirosis encontrándose los siguientes serovares canico/a, icterohemorragiae, pyrogenes.

Liquid crystal based continuous phase retarder: From optically neutral to a quarter waveplate in 200 microseconds

Liquid crystal variable phase retarders have been incorporated into prototype devices for optical communications system applications, both as endless polarization controllers 1,2,3, and as holographic beam steerers 4. Nematic liquid crystals allow continuous control of the degree of retardation induced at relatively slow switching speeds, while ferroelectric liquid crystal based devices allow fast (sub millisecond) switching, but only between two bistable states. The flexoelectro-optic effect 5,6 in short-pitch chiral nematic liquid crystals allows both fast switching of the optic axis and continuous, electric field dependent control of the degree of rotation of the optic axis. A novel geometry for the flexoelectro-optic effect is presented here, in which the helical axis of the chiral nematic is perpendicular to the cell walls (grandjean texture) and the electric field is applied in the plane of the cell. This facilitates deflection of the optic axis of the uniaxial negatively birefringent material from lying along the direction of propagation to having some component in the polarization plane of the light. The device is therefore optically neutral at zero field for telecommunications wavelengths (1550nm), and allows a continuously variable degree of phase excursion to be induced, up to 2π/3 radians achieved so far in a 40μm thick cell. The retardation has been shown both to appear, on application of the field, and disappear on removal, at speeds of 100-500 μs. The direction of deflection of the optic axis is also dependent on the direction of the field, allowing the possibility, in a converging electrode "cartwheel cell", of endless rotation of the liquid crystal waveplate at a higher rate than achievable through dielectric coupling to plain nematic materials.