Decomposition driven interface evolution for layers of binary mixtures: I. Model dirivation and base states

A dynamical model is proposed to describe the coupled decomposition and profile evolution of a free surfacefilm of a binary mixture. An example is a thin film of a polymer blend on a solid substrate undergoing simultaneous phase separation and dewetting. The model is based on model-H describing the coupled transport of the mass of one component (convective Cahn-Hilliard equation) and momentum (Navier-Stokes-Korteweg equations) supplemented by appropriate boundary conditions at the solid substrate and the free surface. General transport equations are derived using phenomenological nonequilibrium thermodynamics for a general nonisothermal setting taking into account Soret and Dufour effects and interfacial viscosity for the internal diffuse interface between the two components. Focusing on an isothermal setting the resulting model is compared to literature results and its base states corresponding to homogeneous or vertically stratified flat layers are analyzed.

El nuevo reto de relación con los clientes: Social CRM

La evolución de Internet al modelo Web 2.0, ha creado el nuevo sistema denominado Social Media, donde han proliferado un número ingente de redes sociales, que han cambiado las formas de relación y colaboración entre los usuarios, así como la relaciones de éstos y las empresas. En respuesta a estos dramáticos cambios sociales y tecnológicos, que actualmente están dando forma a las relaciones negocio-empresa, las empresas están descubriendo que es necesario modificar la estrategia de utilización del CRM (Customer Relationship Management) con sus clientes y desarrollar nuevas capacidades que permitan la creación de valor con los clientes. Y es aquí donde aparece el concepto de Social CRM, entendido como una estrategia centrada en entender, anticiparse y responder mejor a las necesidades de los clientes existentes o potenciales, aprovechando los datos sociales, para crear unas fuertes relaciones beneficiosas para ambas partes. En este trabajo se describe un modelo de adopción de Social CRM, aplicando un método de análisis “Top-Down”, y basado en el modelo de Gartner denominado “The Eight Building Blocks of CRM” [1]. El presente trabajo descompone el modelo de adopción descrito por Gartner, en los siguientes puntos. - Una decisión estratégica de la compañía - Asomarse a la realidad social - Analizar las redes sociales. - Metodología de adopción. - Despliegue y extensión en todos los departamentos de la compañía y la adaptación de los recursos humanos. - Selección e integración con las plataformas tradicionales de CRM - Análisis de herramientas de monitorización de Social CRM El modelo propuesto tiene dos objetivos, por un lado pretende proporcionar la visión de cómo CRM puede influir en los resultados empresariales en la era del cliente social, y por otro, proporcionar a los administradores cómo las inversiones y los recursos existentes de CRM puede ser integrados con las nuevas tecnologías y procesos para formar capacidades que pueden mejorar el rendimiento del negocio. ABSTRACT. “The Internet evolution to Web 2.0 model has created a new system called Social Media, where have proliferated a huge number of social networks which have changed the relationship and collaboration forms user-to-user and user-to-company. In response to these dramatic social and technological changes that are currently shaping the business-business relationships, companies are finding it necessary to modify the strategy for use of CRM (Customer Relationship Management) with customers and develop new capabilities to creating value with customers. And here is where the concept of Social CRM appears, understood as a focus on understanding, anticipating and responding to the needs of existing and potential customers strategy, leveraging social data to create a strong mutually beneficial relationships. In this paper describes an adoption model of Social CRM, using a "Top-Down" analysis method and based on the model of Gartner called "The Eight Building Blocks of CRM" [1]. This paper decomposes the adoption model described by Gartner in the following points. - A company strategic decision. - Look at social reality. - Analyze social networks. - Methodology adoption. - Deployment and extension in all departments of the company and the adaptation of human resources. - Selection and integration with traditional CRM platforms. - Analysis of monitoring tools for Social CRM. The proposed model has two objectives, firstly aims to provide insight into how CRM can influence business outcomes in the era of the social customer, and secondly, to provide administrators how investments and existing resources can be integrated CRM with new technologies and processes for developing capabilities that can increase business performance”.

Methodology based on registration techniques for representing subjects and their deformations acquired from general purpose 3D sensors

In this thesis a methodology for representing 3D subjects and their deformations in adverse situations is studied. The study is focused in providing methods based on registration techniques to improve the data in situations where the sensor is working in the limit of its sensitivity. In order to do this, it is proposed two methods to overcome the problems which can difficult the process in these conditions. First a rigid registration based on model registration is presented, where the model of 3D planar markers is used. This model is estimated using a proposed method which improves its quality by taking into account prior knowledge of the marker. To study the deformations, it is proposed a framework to combine multiple spaces in a non-rigid registration technique. This proposal improves the quality of the alignment with a more robust matching process that makes use of all available input data. Moreover, this framework allows the registration of multiple spaces simultaneously providing a more general technique. Concretely, it is instantiated using colour and location in the matching process for 3D location registration.

Murine Model for Preclinical Studies of Var2CSA-Mediated Pathology Associated with Malaria in Pregnancy

Plasmodium falciparum infection during pregnancy leads to abortions, stillbirth, low birth weight, and maternal mortality. Infected erythrocytes (IEs) accumulate in the placenta by adhering to chondroitin sulfate A (CSA) via var2CSA protein exposed on the P. falciparum IE membrane. Plasmodium berghei IE infection in pregnant BALB/c mice is a model for severe placental malaria (PM). Here, we describe a transgenic P. berghei parasite expressing the full-length var2CSA extracellular region (domains DBL1X to DBL6ε) fused to a P. berghei exported protein (EMAP1) and characterize a var2CSA-based mouse model of PM. BALB/c mice were infected at midgestation with different doses of P. berghei-var2CSA (P. berghei-VAR) or P. berghei wild-type IEs. Infection with 10(4) P. berghei-VAR IEs induced a higher incidence of stillbirth and lower fetal weight than P. berghei At doses of 10(5) and 10(6) IEs, P. berghei-VAR-infected mice showed increased maternal mortality during pregnancy and fetal loss, respectively. Parasite loads in infected placentas were similar between parasite lines despite differences in maternal outcomes. Fetal weight loss normalized for parasitemia was higher in P. berghei-VAR-infected mice than in P. berghei-infected mice. In vitro assays showed that higher numbers of P. berghei-VAR IEs than P. berghei IEs adhered to placental tissue. Immunization of mice with P. berghei-VAR elicited IgG antibodies reactive to DBL1-6 recombinant protein, indicating that the topology of immunogenic epitopes is maintained between DBL1-6-EMAP1 on P. berghei-VAR and recombinant DBL1-6 (recDBL1-6). Our data suggested that impairments in pregnancy caused by P. berghei-VAR infection were attributable to var2CSA expression. This model provides a tool for preclinical evaluation of protection against PM induced by approaches that target var2CSA.

Analysis of Lead-Acid batteries with a third-order dynamical model

Electrical energy storage is a really important issue nowadays. As electricity is not easy to be directly stored, it can be stored in other forms and converted back to electricity when needed. As a consequence, storage technologies for electricity can be classified by the form of storage, and in particular we focus on electrochemical energy storage systems, better known as electrochemical batteries. Largely the more widespread batteries are the Lead-Acid ones, in the two main types known as flooded and valve-regulated. Batteries need to be present in many important applications such as in renewable energy systems and in motor vehicles. Consequently, in order to simulate these complex electrical systems, reliable battery models are needed. Although there exist some models developed by experts of chemistry, they are too complex and not expressed in terms of electrical networks. Thus, they are not convenient for a practical use by electrical engineers, who need to interface these models with other electrical systems models, usually described by means of electrical circuits. There are many techniques available in literature by which a battery can be modeled. Starting from the Thevenin based electrical model, it can be adapted to be more reliable for Lead-Acid battery type, with the addition of a parasitic reaction branch and a parallel network. The third-order formulation of this model can be chosen, being a trustworthy general-purpose model, characterized by a good ratio between accuracy and complexity. Considering the equivalent circuit network, all the useful equations describing the battery model are discussed, and then implemented one by one in Matlab/Simulink. The model has been finally validated, and then used to simulate the battery behaviour in different typical conditions.

Portfolio Entrepreneurship in Family Firms: A Resource-based Perspective

The phenomenon of portfolio entrepreneurship has attracted considerable scholarly attention and is particularly relevant in the family fi rm context. However, there is a lack of knowledge of the process through which portfolio entrepreneurship develops in family firms. We address this gap by analyzing four in-depth, longitudinal family firm case studies from Europe and Latin America. Using a resource-based perspective, we identify six distinct resource categories that are relevant to the portfolio entrepreneurship process. Furthermore, we reveal that their importance varies across time. Our resulting resource-based process model of portfolio entrepreneurship in family firms makes valuable contributions to both theory and practice.

A quasi-chemical viscosity model for fully liquid slags in the Al2O3-CaO-'FeO'-SiO2 system

A structurally based viscosity model for fully liquid silicate slags has been proposed and applied to the Al2O3-CaO-'FeO'-SiO2 system at metallic iron saturation. The model links the slag viscosity to the internal structure of melts through the concentrations of various anion/cation structural units (SUs). The concentrations of structural units are equivalent to the second nearest neighbor bond concentrations calculated by the quasi-chemical thermodynamic model. This viscosity model describes experimental data over the entire temperature and composition range within the Al2O3-CaO-'FeO'-SiO2 system at metallic iron saturation and can be extended to other industrial slag systems.

Dynamic rupture in a 3-D particle-based simulation of a rough planar fault

An appreciation of the physical mechanisms which cause observed seismicity complexity is fundamental to the understanding of the temporal behaviour of faults and single slip events. Numerical simulation of fault slip can provide insights into fault processes by allowing exploration of parameter spaces which influence microscopic and macroscopic physics of processes which may lead towards an answer to those questions. Particle-based models such as the Lattice Solid Model have been used previously for the simulation of stick-slip dynamics of faults, although mainly in two dimensions. Recent increases in the power of computers and the ability to use the power of parallel computer systems have made it possible to extend particle-based fault simulations to three dimensions. In this paper a particle-based numerical model of a rough planar fault embedded between two elastic blocks in three dimensions is presented. A very simple friction law without any rate dependency and no spatial heterogeneity in the intrinsic coefficient of friction is used in the model. To simulate earthquake dynamics the model is sheared in a direction parallel to the fault plane with a constant velocity at the driving edges. Spontaneous slip occurs on the fault when the shear stress is large enough to overcome the frictional forces on the fault. Slip events with a wide range of event sizes are observed. Investigation of the temporal evolution and spatial distribution of slip during each event shows a high degree of variability between the events. In some of the larger events highly complex slip patterns are observed.

A scatterometer neural network sensor model with input noise

The ERS-1 satellite carries a scatterometer which measures the amount of radiation scattered back toward the satellite by the ocean's surface. These measurements can be used to infer wind vectors. The implementation of a neural network based forward model which maps wind vectors to radar backscatter is addressed. Input noise cannot be neglected. To account for this noise, a Bayesian framework is adopted. However, Markov Chain Monte Carlo sampling is too computationally expensive. Instead, gradient information is used with a non-linear optimisation algorithm to find the maximum em a posteriori probability values of the unknown variables. The resulting models are shown to compare well with the current operational model when visualised in the target space.

A scatterometer neural network sensor model with input noise

The ERS-1 satellite carries a scatterometer which measures the amount of radiation scattered back toward the satellite by the ocean's surface. These measurements can be used to infer wind vectors. The implementation of a neural network based forward model which maps wind vectors to radar backscatter is addressed. Input noise cannot be neglected. To account for this noise, a Bayesian framework is adopted. However, Markov Chain Monte Carlo sampling is too computationally expensive. Instead, gradient information is used with a non-linear optimisation algorithm to find the maximum em a posteriori probability values of the unknown variables. The resulting models are shown to compare well with the current operational model when visualised in the target space.

An accurate and scalable analytical model for IEEE 802.15.4 slotted CSMA/CA networks

In this paper a Markov chain based analytical model is proposed to evaluate the slotted CSMA/CA algorithm specified in the MAC layer of IEEE 802.15.4 standard. The analytical model consists of two two-dimensional Markov chains, used to model the state transition of an 802.15.4 device, during the periods of a transmission and between two consecutive frame transmissions, respectively. By introducing the two Markov chains a small number of Markov states are required and the scalability of the analytical model is improved. The analytical model is used to investigate the impact of the CSMA/CA parameters, the number of contending devices, and the data frame size on the network performance in terms of throughput and energy efficiency. It is shown by simulations that the proposed analytical model can accurately predict the performance of slotted CSMA/CA algorithm for uplink, downlink and bi-direction traffic, with both acknowledgement and non-acknowledgement modes.

Differentiating human NT2/D1 neurospheres as a versatile in vitro 3D model system for developmental neurotoxicity testing

Developmental neurotoxicity is a major issue in human health and may have lasting neurological implications. In this preliminary study we exposed differentiating Ntera2/clone D1 (NT2/D1) cell neurospheres to known human teratogens classed as non-embryotoxic (acrylamide), weakly embryotoxic (lithium, valproic acid) and strongly embryotoxic (hydroxyurea) as listed by European Centre for the Validation of Alternative Methods (ECVAM) and examined endpoints of cell viability and neuronal protein marker expression specific to the central nervous system, to identify developmental neurotoxins. Following induction of neuronal differentiation, valproic acid had the most significant effect on neurogenesis, in terms of reduced viability and decreased neuronal markers. Lithium had least effect on viability and did not significantly alter the expression of neuronal markers. Hydroxyurea significantly reduced cell viability but did not affect neuronal protein marker expression. Acrylamide reduced neurosphere viability but did not affect neuronal protein marker expression. Overall, this NT2/D1 -based neurosphere model of neurogenesis, may provide the basis for a model of developmental neurotoxicity in vitro.

Methodology for development of a physiological model incorporating CYP3A and P-glycoprotein for the prediction of intestinal drug absorption

The small intestine poses a major barrier to the efficient absorption of orally administered therapeutics. Intestinal epithelial cells are an extremely important site for extrahepatic clearance, primarily due to prominent P-glycoprotein-mediated active efflux and the presence of cytochrome P450s. We describe a physiologically based pharmacokinetic model which incorporates geometric variations, pH alterations and descriptions of the abundance and distribution of cytochrome 3A and P-glycoprotein along the length of the small intestine. Simulations using preclinical in vitro data for model drugs were performed to establish the influence of P-glycoprotein efflux, cytochrome 3A metabolism and passive permeability on drug available for absorption within the enterocytes. The fraction of drug escaping the enterocyte (F(G)) for 10 cytochrome 3A substrates with a range of intrinsic metabolic clearances were simulated. Following incorporation of P-glycoprotein in vitro efflux ratios all predicted F(G) values were within 20% of observed in vivo F(G). The presence of P-glycoprotein increased the level of cytochrome 3A drug metabolism by up to 12-fold in the distal intestine. F(G) was highly sensitive to changes in intrinsic metabolic clearance but less sensitive to changes in intestinal drug permeability. The model will be valuable for quantifying aspects of intestinal drug absorption and distribution.

An enhanced scalable probe-based multicast admission control scheme

To guarantee QoS for multicast transmission, admission control for multicast sessions is expected. Probe-based multicast admission control (PBMAC) scheme is a scalable and simple approach. However, PBMAC suffers from the subsequent request problem which can significantly reduce the maximum number of multicast sessions that a network can admit. In this letter, we describe the subsequent request problem and propose an enhanced PBMAC scheme to solve this problem. The enhanced scheme makes use of complementary probing and remarking which require only minor modification to the original scheme. By using a fluid-based analytical model, we are able to prove that the enhanced scheme can always admit a higher number of multicast sessions. Furthermore, we present validation of the analytical model using packet based simulation. Copyright © 2005 The Institute of Electronics, Information and Communication Engineers.

Knowledge Construction Technology through Hypermedia-Based Intelligent Conversational Channel

There have been multifarious approaches in building expert knowledge in medical or engineering field through expert system, case-based reasoning, model-based reasoning and also a large-scale knowledge-based system. The intriguing factors with these approaches are mainly the choices of reasoning mechanism, ontology, knowledge representation, elicitation and modeling. In our study, we argue that the knowledge construction through hypermedia-based community channel is an effective approach in constructing expert’s knowledge. We define that the knowledge can be represented as in the simplest form such as stories to the most complex ones such as on-the-job type of experiences. The current approaches of encoding experiences require expert’s knowledge to be acquired and represented in rules, cases or causal model. We differentiate the two types of knowledge which are the content knowledge and socially-derivable knowledge. The latter is described as knowledge that is earned through social interaction. Intelligent Conversational Channel is the system that supports the building and sharing on this type of knowledge.