A scaling analysis of momentum and heat transport in laser surface melting

In this paper, we outline a systematic procedure for scaling analysis of momentum and heat transfer in laser melted pools. With suitable choices of non-dimensionalising parameters, the governing equations coupled with appropriate boundary conditions are first scaled, and the relative significance of various terms appearing in them are accordingly analysed. The analysis is then utilised to predict the orders of magnitude of some important quantities, such as the velocity scale at the top surface, velocity boundary layer thickness, maximum temperature rise in the pool, fully developed pool-depth, and time required for initiation of melting. Using the scaling predictions, the influence of various processing parameters on the system variables can be well recognised, which enables us to develop a deeper insight into the physical problem of interest. Moreover, some of the quantities predicted from the scaling analysis can be utilised for optimised selection of appropriate grid-size and time-steps for full numerical simulation of the process. The scaling predictions are finally assessed by comparison with experimental and numerical results quoted in the literature, and an excellent qualitative agreement is observed.

Role of Management Decision Variables in Determining Technology Progress and Technical Efficiency in Indian Electronic Industry

This paper analyses the influence of management on Technical Efficiency Change (TEC) and Technological Progress (TP) in the communication equipment and consumer electronics sub-sectors of Indian hardware electronics industry. Each sub-sector comprises 13 sample firms for two time periods.The primary objective is to determine the relative contribution of TP and TEC to TFP Growth (TFPG) and to establish the influence of firm specific operational management decision variables on these two components. The study finds that both the sub-sectors have strived and achieved steady TP but not TEC in the period of economic liberalisation to cope with the intensifying competition. The management decisions with respect to asset and profit utilization, vertical integration, among others, improved TP and TE in the sub-sectors. However, R&D investments and technology imports proved costly for TFP indicating inadequate efforts and/or poor resource utilisation by the management. Management was found to be complacent in terms of improving or developing their own technology as indicated by their higher dependence on import of raw materials and no influence of R&D on TP.

Regionalization of precipitation in data sparse areas using large scale atmospheric variables - A fuzzy clustering approach

Delineation of homogeneous precipitation regions (regionalization) is necessary for investigating frequency and spatial distribution of meteorological droughts. The conventional methods of regionalization use statistics of precipitation as attributes to establish homogeneous regions. Therefore they cannot be used to form regions in ungauged areas, and they may not be useful to form meaningful regions in areas having sparse rain gauge density. Further, validation of the regions for homogeneity in precipitation is not possible, since the use of the precipitation statistics to form regions and subsequently to test the regional homogeneity is not appropriate. To alleviate this problem, an approach based on fuzzy cluster analysis is presented. It allows delineation of homogeneous precipitation regions in data sparse areas using large scale atmospheric variables (LSAV), which influence precipitation in the study area, as attributes. The LSAV, location parameters (latitude, longitude and altitude) and seasonality of precipitation are suggested as features for regionalization. The approach allows independent validation of the identified regions for homogeneity using statistics computed from the observed precipitation. Further it has the ability to form regions even in ungauged areas, owing to the use of attributes that can be reliably estimated even when no at-site precipitation data are available. The approach was applied to delineate homogeneous annual rainfall regions in India, and its effectiveness is illustrated by comparing the results with those obtained using rainfall statistics, regionalization based on hard cluster analysis, and meteorological sub-divisions in India. (C) 2011 Elsevier B.V. All rights reserved.

Dynamics between patent latent variables and patent price

This paper focuses on studying the relationship between patent latent variables and patent price. From the existing literature, seven patent latent variables, namely age, generality, originality, foreign filings, technology field, forward citations, and backward citations were identified as having an influence on patent value. We used Ocean Tomo's patent auction price data in this study. We transformed the price and the predictor variables (excluding the dummy variables) to its logarithmic value. The OLS estimates revealed that forward citations and foreign filings were positively correlated to price. Both the variables jointly explained 14.79% of the variance in patent pricing. We did not find sufficient evidence to come up with any definite conclusions on the relationship between price and the variables such as age, technology field, generality, backward citations and originality. The Heckman two-stage sample selection model was used to test for selection bias. (C) 2011 Elsevier Ltd. All rights reserved.

A neural network based automatic generation control design through reinforcement learning

This paper presents the design and implementation of a learning controller for the Automatic Generation Control (AGC) in power systems based on a reinforcement learning (RL) framework. In contrast to the recent RL scheme for AGC proposed by us, the present method permits handling of power system variables such as Area Control Error (ACE) and deviations from scheduled frequency and tie-line flows as continuous variables. (In the earlier scheme, these variables have to be quantized into finitely many levels). The optimal control law is arrived at in the RL framework by making use of Q-learning strategy. Since the state variables are continuous, we propose the use of Radial Basis Function (RBF) neural networks to compute the Q-values for a given input state. Since, in this application we cannot provide training data appropriate for the standard supervised learning framework, a reinforcement learning algorithm is employed to train the RBF network. We also employ a novel exploration strategy, based on a Learning Automata algorithm,for generating training samples during Q-learning. The proposed scheme, in addition to being simple to implement, inherits all the attractive features of an RL scheme such as model independent design, flexibility in control objective specification, robustness etc. Two implementations of the proposed approach are presented. Through simulation studies the attractiveness of this approach is demonstrated.

Ultrasound Assisted Optical Tomography: Estimation of phase Shift experienced by photon on transit through US insonified region for detection of breast tumor

A Monte Carlo model of ultrasound modulation of multiply scattered coherent light in a highly scattering media has been carried out for estimating the phase shift experienced by a photon beam on its transit through US insonified region. The phase shift is related to the tissue stiffness, thereby opening an avenue for possible breast tumor detection. When the scattering centers in the tissue medium is exposed to a deterministic forcing with the help of a focused ultrasound (US) beam, due to the fact that US-induced oscillation is almost along particular direction, the direction defined by the transducer axis, the scattering events increase, thereby increasing the phase shift experienced by light that traverses through the medium. The phase shift is found to increase with increase in anisotropy g of the medium. However, as the size of the focused region which is the region of interest (ROI) increases, a large number of scattering events take place within the ROI, the ensemble average of the phase shift (Delta phi) becomes very close to zero. The phase of the individual photon is randomly distributed over 2 pi when the scattered photon path crosses a large number of ultrasound wavelengths in the focused region. This is true at high ultrasound frequency (1 MHz) when mean free path length of photon l(s) is comparable to wavelength of US beam. However, at much lower US frequencies (100 Hz), the wavelength of sound is orders of magnitude larger than l(s), and with a high value of g (g 0.9), there is a distinct measurable phase difference for the photon that traverses through the insonified region. Experiments are carried out for validation of simulation results.

Functional analysis of ultra high information rates conveyed by rat vibrissal primary afferents

Sensory receptors determine the type and the quantity of information available for perception. Here, we quantified and characterized the information transferred by primary afferents in the rat whisker system using neural system identification. Quantification of ``how much'' information is conveyed by primary afferents, using the direct method (DM), a classical information theoretic tool, revealed that primary afferents transfer huge amounts of information (up to 529 bits/s). Information theoretic analysis of instantaneous spike-triggered kinematic stimulus features was used to gain functional insight on ``what'' is coded by primary afferents. Amongst the kinematic variables tested-position, velocity, and acceleration-primary afferent spikes encoded velocity best. The other two variables contributed to information transfer, but only if combined with velocity. We further revealed three additional characteristics that play a role in information transfer by primary afferents. Firstly, primary afferent spikes show preference for well separated multiple stimuli (i.e., well separated sets of combinations of the three instantaneous kinematic variables). Secondly, neurons are sensitive to short strips of the stimulus trajectory (up to 10 ms pre-spike time), and thirdly, they show spike patterns (precise doublet and triplet spiking). In order to deal with these complexities, we used a flexible probabilistic neuron model fitting mixtures of Gaussians to the spike triggered stimulus distributions, which quantitatively captured the contribution of the mentioned features and allowed us to achieve a full functional analysis of the total information rate indicated by the DM. We found that instantaneous position, velocity, and acceleration explained about 50% of the total information rate. Adding a 10 ms pre-spike interval of stimulus trajectory achieved 80-90%. The final 10-20% were found to be due to non-linear coding by spike bursts.

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.

Efecto de la dosis y el momento de aplicación del nitrógeno sobre la producción y calidad de semilla de pasto gamba (Andropogon gayanus Kunth)

El presente trabajo tuvo como objetivo, evaluar en términos biológicos y económicos, el efecto de la dosis y el momento de aplicación de nitrógeno, sobre la producción y calidad de semillas de Androppgon gayanus CIAT 621. El estudio se llevó a cabo en la finca "Santa Rosa", ubicada al Oeste de la ciudad de Managua. El análisis de calidad de semilla se realizó empleándose la metodología utilizada por el CIAT, para el análisis de calidad de semillas brozosas. Se utilizó un diseño de bloques completos al azar, para un arreglo bifactorial de cuatro dosis y tres momentos de aplicación de nitrógeno. Se incluyó un tratamiento testigo, sin fertilización, para un total de 13 tratamientos y tres repeticiones por tratamiento. Los resultados evidencian que las dosis de nitrógeno y los momentos de aplicación, tuvieron efecto estadísticamente significativo (P<0.01) sobre el Número de Tallos Reproductivos Totales por Hectárea y el rendimiento de semilla Cruda por Hectárea. El incremento en el rendimiento de Semilla Cruda por Hectárea, estuvo asociado con el incremento del Número de Tallos Reproductivos Totales por Hectárea (r=.82) (Pvariables: Número de Racimos por Inflorescencia, Tamaño de Racimos y Peso de Racimos. Para el análisis estadístico de las variables de calidad de semilla, se realizó la prueba de "Z", para la diferencia de X proporciones. El porcentaje de Semilla Pura presentó su máximo valor con la dosis de 25 kg N/ha, aplicados a los 40 días después del corte de uniformidad (55.43%), presentando diferencias no significativas (P>0.05), respecto de la dosis de 75 kg N/ha, aplicados a los 20 días después del corte de uniformidad (55.31%). Para el porcentaje de Germinación, el valor más alto resultó cuando se aplicaron 100 kg N/ha, a los 40 días después del corte de uniformidad (46%), presentando diferencias no significativas (P>0.05), con la dosis de 25 kg N/ha, aplicados a los 40 días después del corte de uniformidad (45%). El Valor Cultural presentó una tendencia similar a las dos variables anteriores, (Semilla Pura y Germinación).Este resultado se debió a que el Valor Cultural es un índice compuesto producto de ambas variables. Su mayor valor se obtuvo con la dosis de 25 kg N/ha, aplicados a los 40 días después del corte de uniformidad (25%), siendo estadísticamente igual (P>0.05), cuando se aplicaron 75 kg N/ha, 20 días después del corte de uniformidad (23.78%).Este comportamiento irregular, en el efecto del nitrógeno sobre los parámetros de calidad de la semilla (Semilla Pura, Germinación y Valor Cultural), coincide con lo reportado por Ferguson (1991), quien afirma que los efectos del nitrógeno en la calidad de la semilla son variables, pero normalmente no tiene efecto. Otros autores; Cameron y Mullaly (1969) y Grof (1969), citados por Humphreys (1975}, reportan que no encontraron una relación consistente entre la calidad de la semilla y el nivel de nitrógeno, en la producción de semilla de pastos tropicales. De todos los tratamientos evaluados, el mayor beneficio monetario se obtuvo con la dosis de 75 kg N/ha aplicados a los 40 días después del corte de uniformidad (US $ 1,111.10/ha). No obstante, la dosis de 25 kg N/ha aplicados a los 40 días después del corte de uniformidad fue el tratamiento con el que se obtuvo el mayor margen de ingreso bruto (96.5% del ingreso total), en comparación con el resto de tratamientos en que se aplicó nitrógeno.

A Viscoelastic Constitutive Model with Nonlinear Evolutionary Internal Variables

Based on the internal variable theory, a viscoelastic constitutive model of a highly deformable continuous medium is proposed. A set of second rank tensorial internal state variables corresponding to Biot's strain is introduced, and a nonlinear evolution

Intracellular demography and the dynamics of Salmonella enterica infections.

An understanding of within-host dynamics of pathogen interactions with eukaryotic cells can shape the development of effective preventive measures and drug regimes. Such investigations have been hampered by the difficulty of identifying and observing directly, within live tissues, the multiple key variables that underlay infection processes. Fluorescence microscopy data on intracellular distributions of Salmonella enterica serovar Typhimurium (S. Typhimurium) show that, while the number of infected cells increases with time, the distribution of bacteria between cells is stationary (though highly skewed). Here, we report a simple model framework for the intensity of intracellular infection that links the quasi-stationary distribution of bacteria to bacterial and cellular demography. This enables us to reject the hypothesis that the skewed distribution is generated by intrinsic cellular heterogeneities, and to derive specific predictions on the within-cell dynamics of Salmonella division and host-cell lysis. For within-cell pathogens in general, we show that within-cell dynamics have implications across pathogen dynamics, evolution, and control, and we develop novel generic guidelines for the design of antibacterial combination therapies and the management of antibiotic resistance.

Evaluación de los parámetros productivos de pollos de engorde sometidos a tres fases de alimentación

El trabajo experimental "Evaluación de los parámetros pro­ ductivos de pollos de engorde sometidos a tres ases de alimentación", se llevó a efecto en la granja avícola "La Flota”, ubicada en el Km. 17 carretera Managua-Masaya, 800 mts. al Este, comarca "Los Madrigales”, jurisdicción de Nindirí, Departamento de Masaya. El ensayo fue realizado con ciento ochenta pollos de un día de edad, perteneciente a la línea Cubana E-23, divididos en dos tratamientos con tres réplicas cada uno, fueron distribuidos en un Diseño completo al azar y sometidos a una prueba de DUNCAN para determinar la superioridad por tratamiento; a los que a vez se les efectuó un estudio económico de costos de producción evaluados a través de un balance general. El tratamiento T1 consistió en la aplicación de dos fases de alimentación (Testigo) y el tratamiento T2 con tres fases de alimentación (Experimental), contando cada tratamiento con 90 pollos. Los pollos criados bajo el tratamiento T2 tuvieron una mejor conversión alimenticia (2.33), en relación a los pollos del T1 (2.42) y obtuvieron un peso vivo a los 49 días de 3.77 libras y 3.59 libras respectivamente. El rendimiento en canal fue satisfactorio para los dos tratamientos (para el T1 fue de 70.38• y para el T2 de 72.01%) en relación a los resultados obtenidos a nivel nacional. No se encontró diferencias significativas (P< 0.05) para las variables rendimiento en canal, calidad de la canal y mortalidad. En la crianza de pollos de engorde con tres fases de alimentación (T2), se obtuvo una disminución en los costos de producción de US * 0.21, por cada libra de carne producida.

Evaluación de diferentes niveles de ofrecimiento de concentrado comercial adicionando forraje verde ad libitum en conejos durante el período de ceba

El ensayo estudió el efecto de cuatro niveles de ofrecimiento de concentrado comercial, adicionando forraje verde ad libitum en conejos durante el período de ceba. El forraje verde suministrado, consistió en una mezcla pi­cada, que contenía en base a peso fresco el 75% de hojas de musa. sp (plátano), 15% de hojas cajanus cajan (gandul) y 15% de hojas de pennisetum purpureum (taiwán). En el tratamiento utilizado como testigo T1, se suministró pienso comercial en cantidades en gramos por día por gazapo de 96, 129, 145, 158 y 162 para las semanas uno, dos, tres y cuatro respectivamente, para el tratamiento T2, se suministró el 75% del concentrado comercial ofrecido en T1, para el trata­ miento T3, se suministró el 50% del concentrado comercial ofre­cido en T1 y para el tratamiento T4, se suministró el 25% del concentrado comercial ofrecido en T1. Se utilizó un D C A (Diseño completamente aleatorio), incluyendo la covariable peso inicial. El período de evaluación fue de 35 días, con un tiempo de adaptación al alimento de 5 días. Las unidades experimentales fueron 22 gazapos al destete de 34 y 35 días de edad, nacidos en la granja, presentado caracteristicas entre las razas: Neozelandis, California, Pardo, Mariposa y Chinchilla. Se encontró efecto significativo al 0.05 para los tratamientos y no significativo al 0.05 para la covariable peso inicial, siendo las variables respuestas: Consumo de concentrado, consumo de forraje, ganancia media diaria, relación consumo de concentrado entre incremento de peso y relación consumo de forraje entre incremento de peso. Se obtuvieron ganancias medias promedios en gramos por día de 32.2, 28.57, 25.03 y 12.82. Los costos de alimentación en córdobas por gazapo en los 35 días de evaluación fueron 8.23, 6.29, 4.33 y 2.39, que se determinaron en base al análisis de presupuestos parciales, obteniendo un beneficio neto en córdobas de 32.95, 31.66, 30.28 y 21.619 para los tratamientos T1, T2, T3 y T4 respectivamente, a una taza de cambio de C$8.05: US$ 1.