Preparation and characterization of stable aqueous suspensions of up-converting Er3+/Yb3+-doped LiNbO3 nanocrystals

The preparation of LiNbO3:Er3+/Yb3+ nanocrystals and their up-conversion properties have been studied. It is demonstrated that polyethyleneimine- (PEI) assisted dispersion procedures allow obtaining stable aqueous LiNbO3:Er3+/Yb3+ powder suspensions, with average size particles well below the micron range (100–200 nm) and the isoelectric point of the suspension reaching values well above pH 7. After excitation of Yb3+ ions at a wavelength of 980 nm, the suspensions exhibit efficient, and stable, IR-to-visible (green and red) up-conversion properties, easily observed by the naked eye, very similar to those of the starting crystalline bulk material.

Service needs forecasting: an approach for the automotive industry using analogies with medical ER management models.

During the past years, the industry has shifted position and moved towards “the luxury universe” whose customers are demanding, treating individuals as unique and valued customer for the business, offering vehicles produced with the state of the art technologies and implementing the highest finishing standards. Due to the competitive level in the market, car makers enable processes which equalizes customer services to E.R. management, being dealt with the maximum urgency that allows the comparison between both, car workshops and emergency rooms, where workshop bays or ramps will be equal to emergency boxes and skilled technicians are equivalent to the health care specialist, who will carry out tests and checks prior to afford any final operation, keeping the “patient” under control before it is back to normal utilization. This paper establishes a valid model for the automotive industry to estimate customer service demand forecasting under variable demand conditions using analogies with patient demand models used for the medical ER.

SERVICE NEEDS FORECASTING: An Approach for the Motor Industry Using Analogies with Medical ER Management Models.

During the past years, the industry has shifted position and moved towards “the luxury universe” whose customers are demanding, treating individuals as unique and valued customer for the business, offering vehicles produced with the state of the art technologies and implementing the highest finishing standards. Due to the competitive level in the market, motor makers enable processes which equalizes customer services to E.R. management, being dealt with the maximum urgency that allows the comparison between both, car workshops and emergency rooms, where workshop bays or ramps will be equal to emergency boxes and skilled technicians are equivalent to the health care specialist, who will carry out tests and checks prior to afford any final operation, keeping the “patient” under control before it is back to normal utilization. This paper ratify a valid model for the automotive industry to estimate customer service demand forecasting under variable demand conditions using analogies with patient demand models used for the medical ER

Analysis and optimization of propagation losses in LiNbO3 optical waveguides produced by swift heavy-ion irradiation

The propagation losses (PL) of lithium niobate optical planar waveguides fabricated by swift heavy-ion irradiation (SHI), an alternative to conventional ion implantation, have been investigated and optimized. For waveguide fabrication, congruently melting LiNbO3 substrates were irradiated with F ions at 20 MeV or 30 MeV and fluences in the range 1013–1014 cm−2. The influence of the temperature and time of post-irradiation annealing treatments has been systematically studied. Optimum propagation losses lower than 0.5 dB/cm have been obtained for both TE and TM modes, after a two-stage annealing treatment at 350 and 375∘C. Possible loss mechanisms are discussed.

Single - and double energy swift and slow heavy ion irradiated optical waveguides in Er: Tungstene-Tellurite glass and BGO for telecom applications

The fabrication of broadband amplifiers in wavelength division multiplexing (WDM) around 1.55 m, as they exhibit large stimulated cross sections and broad emission bandwidth. Bi4Ge3O12 (eultine type BGO) - well known scintillator material, also a rare-earth host material, photorefractive waveguides produced in it only using light ions in the past. Recently: MeV N+ ions and swift O5+ and C5+ ions, too*. Bi12GeO20 (sillenite type BGO) - high photoconductivity and photorefractive sensitivity in the visible and NIR good candidate for real-time holography and optical phase conjugation, photorefractive waveguides produced in it only using light ions. No previous attempts of ion beam fabrication of waveguides in it.

Calculation of the spatial distribution of photovoltaic field by arbitrary 2D ilumination patterns en LiNbO3; application to photovoltaic particle trapping.

Patterns of evanescent photovoltaic field induced by illumination on a surface of lithium niobate (LN) have been calculated and compared with the experimental patterns of nano- and microparticles trapped by dielectrophoretic forces. A tool for this calculation has been developed. Calculo de distribución espacial de campo por efecto fotovoltaico con patrones arbitrarios de iluminación, en LiNbO3

Calculation of dielectrophoretic potential generated under illumination patterns on x- and z-cut LiNbO3 : application to photovoltaic particle trapping

The dielectrophoretic potential generated near the surface of a z-cut LiNbO3 by photovoltaic charge transport has been calculated for first time. The procedure and results are compared with the ones corresponding to x-cut. Diferences in the position, sharpness and time evolution are reported, and their implication on particle trapping are discussed.

1D and 2D neutral particle patterning by dielectrophoretic forces on z-cut Fe:LiNbO3 crystals

1D and 2D patterning of uncharged micro- and nanoparticles via dielectrophoretic forces on photovoltaic z-cut Fe:LiNbO3 have been investigated for the first time. The technique has been successfully applied with dielectric micro-particles of CaCO3 (diameter d = 1-3 μm) and metal nanoparticles of Al (d = 70 nm). At difference with previous experiments in x- and y-cut, the obtained patterns locally reproduce the light distribution with high fidelity. A simple model is provided to analyse the trapping process. The results show the remarkably good capabilities of this geometry for high quality 2D light-induced dielectrophoretic patterning overcoming the important limitations presented by previous configurations.

Service Capacity Reserve under Uncertainty by Hospital’s ER Analogies: A Practical Model for Car Services

We define a capacity reserve model to dimension passenger car service installations according to the demographic distribution of the area to be serviced by using hospital?s emergency room analogies. Usually, service facilities are designed applying empirical methods, but customers arrive under uncertain conditions not included in the original estimations, and there is a gap between customer?s real demand and the service?s capacity. Our research establishes a valid methodology and covers the absence of recent researches and the lack of statistical techniques implementation, integrating demand uncertainty in a unique model built in stages by implementing ARIMA forecasting, queuing theory, and Monte Carlo simulation to optimize the service capacity and occupancy, minimizing the implicit cost of the capacity that must be reserved to service unexpected customers. Our model has proved to be a useful tool for optimal decision making under uncertainty integrating the prediction of the cost implicit in the reserve capacity to serve unexpected demand and defining a set of new process indicators, such us capacity, occupancy, and cost of capacity reserve never studied before. The new indicators are intended to optimize the service operation. This set of new indicators could be implemented in the information systems used in the passenger car services.

Service capacity reserve under uncertainty by hospital's ER's analogies: a practical model for car services

El objetivo de esta investigación consiste en definir un modelo de reserva de capacidad, por analogías con emergencias hospitalarias, que pueda ser implementado en el sector de servicios. Este está específicamente enfocado a su aplicación en talleres de servicio de automóviles. Nuestra investigación incorpora la incertidumbre de la demanda en un modelo singular diseñado en etapas que agrupa técnicas ARIMA, teoría de colas y simulación Monte Carlo para definir los conceptos de capacidad y ocupación de servicio, que serán utilizados para minimizar el coste implícito de la reserva capacidad necesaria para atender a clientes que carecen de cita previa. Habitualmente, las compañías automovilísticas estiman la capacidad de sus instalaciones de servicio empíricamente, pero los clientes pueden llegar bajo condiciones de incertidumbre que no se tienen en cuenta en dichas estimaciones, por lo que existe una diferencia entre lo que el cliente realmente demanda y la capacidad que ofrece el servicio. Nuestro enfoque define una metodología válida para el sector automovilístico que cubre la ausencia genérica de investigaciones recientes y la habitual falta de aplicación de técnicas estadísticas en el sector. La equivalencia con la gestión de urgencias hospitalarias se ha validado a lo largo de la investigación en la se definen nuevos indicadores de proceso (KPIs) Tal y como hacen los hospitales, aplicamos modelos estocásticos para dimensionar las instalaciones de servicio de acuerdo con la distribución demográfica del área de influencia. El modelo final propuesto integra la predicción del coste implícito en la reserva de capacidad para atender la demanda no prevista. Asimismo, se ha desarrollado un código en Matlab que puede integrarse como un módulo adicional a los sistemas de información (DMS) que se usan actualmente en el sector, con el fin de emplear los nuevos indicadores de proceso definidos en el modelo. Los resultados principales del modelo son nuevos indicadores de servicio, tales como la capacidad, ocupación y coste de reserva de capacidad, que nunca antes han sido objeto de estudio en la industria automovilística, y que están orientados a gestionar la operativa del servicio. ABSTRACT Our aim is to define a Capacity Reserve model to be implemented in the service sector by hospital's emergency room (ER) analogies, with a practical approach to passenger car services. A stochastic model has been implemented using R and a Monte Carlo simulation code written in Matlab and has proved a very useful tool for optimal decision making under uncertainty. The research integrates demand uncertainty in a unique model which is built in stages by implementing ARIMA forecasting, Queuing Theory and a Monte Carlo simulation to define the concepts of service capacity and occupancy, minimizing the implicit cost of the capacity that must be reserved to service unexpected customers. Usually, passenger car companies estimate their service facilities capacity using empirical methods, but customers arrive under uncertain conditions not included in the estimations. Thus, there is a gap between customer’s real demand and the dealer’s capacity. This research sets a valid methodology for the passenger car industry to cover the generic absence of recent researches and the generic lack of statistical techniques implementation. The hospital’s emergency room (ER) equalization has been confirmed to be valid for the passenger car industry and new process indicators have been defined to support the study. As hospitals do, we aim to apply stochastic models to dimension installations according to the demographic distribution of the area to be serviced. The proposed model integrates the prediction of the cost implicit in the reserve capacity to serve unexpected demand. The Matlab code could be implemented as part of the existing information technology systems (ITs) to support the existing service management tools, creating a set of new process indicators. Main model outputs are new indicators, such us Capacity, Occupancy and Cost of Capacity Reserve, never studied in the passenger car service industry before, and intended to manage the service operation.

Efficient photo-induced dielectrophoretic particle trapping on Fe:LiNbO3 for arbitrary two dimensional patterning

1D and 2D patterning of uncharged micro- and nanoparticles via dielectrophoretic forces on photovoltaic z-cut Fe:LiNbO3 have been investigated for the first time. The technique has been successfully applied with dielectric micro-particles of CaCO3 (diameter d = 1-3 ?m) and metal nanoparticles of Al (d = 70 nm). At difference with previous experiments in x- and y-cut, the obtained patterns locally reproduce the light distribution with high fidelity. A simple model is provided to analyse the trapping process. The results show the remarkably good capabilities of this geometry for high quality 2D light-induced dielectrophoretic patterning overcoming the important limitations presented by previous configurations.