Is production the core competence for the internationalization of emerging country firms?

The rise of new multinationals in countries like Brazil provides an opportunity to revisit and carefully construct theories of how firms internationalize, a topic on which extant theory is weak. Brazilian firms are "infant multinationals", unlike developed country firms that are "mature multinationals". They are also internationalizing in a very different global context, and can do so on the basis of different competitive advantages than multinationals that came before. Therefore, this study aims at creating subsidies for theory building about early-stage internationalization. Emerging country firms have Production competences as main competitive asset to internationalize, what reflects their competitive positioning in home markets and their entry strategy in international markets. In the case of early-entrants - Western multinationals in the 1950s and Japanese in the 1980s - the Production competence played a key role for successful internationalization. Thus, the focus of the study is the role that the Production competence plays in the internationalization of late-entrants, the emerging country multinationals. The research design considers not only the position of the headquarters but also the initiatives of the subsidiaries and the dynamic interplay between both. The paper allows a better understanding of internationalization processes and the role of Production, when firms start building their own international networks. It brings relevant insights about the paths that are being followed by emerging country multinationals, the difficulties they find, the solutions they develop. These are important inputs not only for new theory building but also for managerial practice. (C) 2012 Elsevier B.V. All rights reserved.

Low-Resolution Molecular Models Reveal the Oligomeric State of the PPAR and the Conformational Organization of Its Domains in Solution

The peroxisome proliferator-activated receptors (PPARs) regulate genes involved in lipid and carbohydrate metabolism, and are targets of drugs approved for human use. Whereas the crystallographic structure of the complex of full length PPAR gamma and RXR alpha is known, structural alterations induced by heterodimer formation and DNA contacts are not well understood. Herein, we report a small-angle X-ray scattering analysis of the oligomeric state of hPPAR gamma alone and in the presence of retinoid X receptor (RXR). The results reveal that, in contrast with other studied nuclear receptors, which predominantly form dimers in solution, hPPAR gamma remains in the monomeric form by itself but forms heterodimers with hRXR alpha. The low-resolution models of hPPAR gamma/RXR alpha complexes predict significant changes in opening angle between heterodimerization partners (LBD) and extended and asymmetric shape of the dimer (LBD-DBD) as compared with X-ray structure of the full-length receptor bound to DNA. These differences between our SAXS models and the high-resolution crystallographic structure might suggest that there are different conformations of functional heterodimer complex in solution. Accordingly, hydrogen/deuterium exchange experiments reveal that the heterodimer binding to DNA promotes more compact and less solvent-accessible conformation of the receptor complex.

Development of musculoskeletal models for the design and the pre-clinical validation of hip resurfacing prosthesis

Background. The surgical treatment of dysfunctional hips is a severe condition for the patient and a costly therapy for the public health. Hip resurfacing techniques seem to hold the promise of various advantages over traditional THR, with particular attention to young and active patients. Although the lesson provided in the past by many branches of engineering is that success in designing competitive products can be achieved only by predicting the possible scenario of failure, to date the understanding of the implant quality is poorly pre-clinically addressed. Thus revision is the only delayed and reliable end point for assessment. The aim of the present work was to model the musculoskeletal system so as to develop a protocol for predicting failure of hip resurfacing prosthesis. Methods. Preliminary studies validated the technique for the generation of subject specific finite element (FE) models of long bones from Computed Thomography data. The proposed protocol consisted in the numerical analysis of the prosthesis biomechanics by deterministic and statistic studies so as to assess the risk of biomechanical failure on the different operative conditions the implant might face in a population of interest during various activities of daily living. Physiological conditions were defined including the variability of the anatomy, bone densitometry, surgery uncertainties and published boundary conditions at the hip. The protocol was tested by analysing a successful design on the market and a new prototype of a resurfacing prosthesis. Results. The intrinsic accuracy of models on bone stress predictions (RMSE < 10%) was aligned to the current state of the art in this field. The accuracy of prediction on the bone-prosthesis contact mechanics was also excellent (< 0.001 mm). The sensitivity of models prediction to uncertainties on modelling parameter was found below 8.4%. The analysis of the successful design resulted in a very good agreement with published retrospective studies. The geometry optimisation of the new prototype lead to a final design with a low risk of failure. The statistical analysis confirmed the minimal risk of the optimised design over the entire population of interest. The performances of the optimised design showed a significant improvement with respect to the first prototype (+35%). Limitations. On the authors opinion the major limitation of this study is on boundary conditions. The muscular forces and the hip joint reaction were derived from the few data available in the literature, which can be considered significant but hardly representative of the entire variability of boundary conditions the implant might face over the patients population. This moved the focus of the research on modelling the musculoskeletal system; the ongoing activity is to develop subject-specific musculoskeletal models of the lower limb from medical images. Conclusions. The developed protocol was able to accurately predict known clinical outcomes when applied to a well-established device and, to support the design optimisation phase providing important information on critical characteristics of the patients when applied to a new prosthesis. The presented approach does have a relevant generality that would allow the extension of the protocol to a large set of orthopaedic scenarios with minor changes. Hence, a failure mode analysis criterion can be considered a suitable tool in developing new orthopaedic devices.

Models for the Study of Cortical Activity During Cognitive ans Motor Tasks

This thesis is mainly devoted to show how EEG data and related phenomena can be reproduced and analyzed using mathematical models of neural masses (NMM). The aim is to describe some of these phenomena, to show in which ways the design of the models architecture is influenced by such phenomena, point out the difficulties of tuning the dozens of parameters of the models in order to reproduce the activity recorded with EEG systems during different kinds of experiments, and suggest some strategies to cope with these problems. In particular the chapters are organized as follows: chapter I gives a brief overview of the aims and issues addressed in the thesis; in chapter II the main characteristics of the cortical column, of the EEG signal and of the neural mass models will be presented, in order to show the relationships that hold between these entities; chapter III describes a study in which a NMM from the literature has been used to assess brain connectivity changes in tetraplegic patients; in chapter IV a modified version of the NMM is presented, which has been developed to overcomes some of the previous version’s intrinsic limitations; chapter V describes a study in which the new NMM has been used to reproduce the electrical activity evoked in the cortex by the transcranial magnetic stimulation (TMS); chapter VI presents some preliminary results obtained in the simulation of the neural rhythms associated with memory recall; finally, some general conclusions are drawn in chapter VII.

Micro-FEM models based on micro-CT reconstructions for the in vitro characterization of the elastic properties of trabecular bone tissue.

This master’s thesis describes the research done at the Medical Technology Laboratory (LTM) of the Rizzoli Orthopedic Institute (IOR, Bologna, Italy), which focused on the characterization of the elastic properties of the trabecular bone tissue, starting from october 2012 to present. The approach uses computed microtomography to characterize the architecture of trabecular bone specimens. With the information obtained from the scanner, specimen-specific models of trabecular bone are generated for the solution with the Finite Element Method (FEM). Along with the FEM modelling, mechanical tests are performed over the same reconstructed bone portions. From the linear-elastic stage of mechanical tests presented by experimental results, it is possible to estimate the mechanical properties of the trabecular bone tissue. After a brief introduction on the biomechanics of the trabecular bone (chapter 1) and on the characterization of the mechanics of its tissue using FEM models (chapter 2), the reliability analysis of an experimental procedure is explained (chapter 3), based on the high-scalable numerical solver ParFE. In chapter 4, the sensitivity analyses on two different parameters for micro-FEM model’s reconstruction are presented. Once the reliability of the modeling strategy has been shown, a recent layout for experimental test, developed in LTM, is presented (chapter 5). Moreover, the results of the application of the new layout are discussed, with a stress on the difficulties connected to it and observed during the tests. Finally, a prototype experimental layout for the measure of deformations in trabecular bone specimens is presented (chapter 6). This procedure is based on the Digital Image Correlation method and is currently under development in LTM.

"Influence of lower-limb joint models on subject-specific musculoskeletal model predictions during gait" ( "modelli muscoloscheletrici personalizzati dell'arto inferiore: Analisi dell'effetto della modellazione dei giunti sulla predizione dei carichi agenti sul sistema scheletrico durante il cammino").

The aim of the present thesis was to investigate the influence of lower-limb joint models on musculoskeletal model predictions during gait. We started our analysis by using a baseline model, i.e., the state-of-the-art lower-limb model (spherical joint at the hip and hinge joints at the knee and ankle) created from MRI of a healthy subject in the Medical Technology Laboratory of the Rizzoli Orthopaedic Institute. We varied the models of knee and ankle joints, including: knee- and ankle joints with mean instantaneous axis of rotation, universal joint at the ankle, scaled-generic-derived planar knee, subject-specific planar knee model, subject-specific planar ankle model, spherical knee, spherical ankle. The joint model combinations corresponding to 10 musculoskeletal models were implemented into a typical inverse dynamics problem, including inverse kinematics, inverse dynamics, static optimization and joint reaction analysis algorithms solved using the OpenSim software to calculate joint angles, joint moments, muscle forces and activations, joint reaction forces during 5 walking trials. The predicted muscle activations were qualitatively compared to experimental EMG, to evaluate the accuracy of model predictions. Planar joint at the knee, universal joint at the ankle and spherical joints at the knee and at the ankle produced appreciable variations in model predictions during gait trials. The planar knee joint model reduced the discrepancy between the predicted activation of the Rectus Femoris and the EMG (with respect to the baseline model), and the reduced peak knee reaction force was considered more accurate. The use of the universal joint, with the introduction of the subtalar joint, worsened the muscle activation agreement with the EMG, and increased ankle and knee reaction forces were predicted. The spherical joints, in particular at the knee, worsened the muscle activation agreement with the EMG. A substantial increase of joint reaction forces at all joints was predicted despite of the good agreement in joint kinematics with those of the baseline model. The introduction of the universal joint had a negative effect on the model predictions. The cause of this discrepancy is likely to be found in the definition of the subtalar joint and thus, in the particular subject’s anthropometry, used to create the model and define the joint pose. We concluded that the implementation of complex joint models do not have marked effects on the joint reaction forces during gait. Computed results were similar in magnitude and in pattern to those reported in literature. Nonetheless, the introduction of planar joint model at the knee had positive effect upon the predictions, while the use of spherical joint at the knee and/or at the ankle is absolutely unadvisable, because it predicted unrealistic joint reaction forces.

Novel insights into mechanisms of food allergy and allergic airway inflammation using experimental mouse models

Over the last decades, considerable efforts have been undertaken in the development of animal models mimicking the pathogenesis of allergic diseases occurring in humans. The mouse has rapidly emerged as the animal model of choice, due to considerations of handling and costs and, importantly, due to the availability of a large and increasing arsenal of genetically modified mouse strains and molecular tools facilitating the analysis of complex disease models. Here, we review latest developments in allergy research that have arisen from in vivo experimentation in the mouse, with a focus on models of food allergy and allergic asthma, which constitute major health problems with increasing incidence in industrialized countries. We highlight recent novel findings and controversies in the field, most of which were obtained through the use of gene-deficient or germ-free mice, and discuss new potential therapeutic approaches that have emerged from animal studies and that aim at attenuating allergic reactions in human patients.

Gauss-Seidel Estimation of Generalized Linear Mixed Models with Application to Poisson Modeling of Spatially Varying Disease Rates

Generalized linear mixed models (GLMMs) provide an elegant framework for the analysis of correlated data. Due to the non-closed form of the likelihood, GLMMs are often fit by computational procedures like penalized quasi-likelihood (PQL). Special cases of these models are generalized linear models (GLMs), which are often fit using algorithms like iterative weighted least squares (IWLS). High computational costs and memory space constraints often make it difficult to apply these iterative procedures to data sets with very large number of cases. This paper proposes a computationally efficient strategy based on the Gauss-Seidel algorithm that iteratively fits sub-models of the GLMM to subsetted versions of the data. Additional gains in efficiency are achieved for Poisson models, commonly used in disease mapping problems, because of their special collapsibility property which allows data reduction through summaries. Convergence of the proposed iterative procedure is guaranteed for canonical link functions. The strategy is applied to investigate the relationship between ischemic heart disease, socioeconomic status and age/gender category in New South Wales, Australia, based on outcome data consisting of approximately 33 million records. A simulation study demonstrates the algorithm's reliability in analyzing a data set with 12 million records for a (non-collapsible) logistic regression model.

Pathogenesis of bacterial meningitis: contributions by experimental models in rabbits

Rabbits models of bacterial meningitis have contributed substantially to our understanding of the disease, although the technical characteristics of these models only allow the study of specific aspects of the disease. Bacterial multiplication in the subarachnoidal space is not substantially influenced by host defense mechanisms, mainly because of the lack of sufficient amounts of specific antibodies and functional complement in infected CSF. The multiplying bacteria induce profound changes in the blood-brain barrier, an influx of serum proteins into the CSF and the invasion of polymorphonuclear leukocytes at the site of the infection. The presence of polymorphonuclear leukocytes in CSF not only appears to be of limited value in combating the infection, but also seems to produce deleterious effects on the central nervous system. Components of the leukocytes, such as unsaturated fatty acids, arachidonic metabolites and free oxygen radicals, may contribute to the profound hydrodynamic, structural and metabolic changes that are currently under study in experimental models of the disease. A better understanding of the pathophysiology of bacterial meningitis may allow us to design more effective therapeutic strategies and improve the outcome of this disease.

Index of Complexity, Outcome and Need scored on plaster and digital models

The aim of this study was to compare standard plaster models with their digital counterparts for the applicability of the Index of Complexity, Outcome, and Need (ICON). Generated study models of 30 randomly selected patients: 30 pre- (T(0)) and 30 post- (T(1)) treatment. Two examiners, calibrated in the ICON, scored the digital and plaster models. The overall ICON scores were evaluated for reliability and reproducibility using kappa statistics and reliability coefficients. The values for reliability of the total and weighted ICON scores were generally high for the T(0) sample (range 0.83-0.95) but less high for the T(1) sample (range 0.55-0.85). Differences in total ICON score between plaster and digital models resulted in mostly statistically insignificant values (P values ranging from 0.07 to 0.19), except for observer 1 in the T(1) sample. No statistically different values were found for the total ICON score on either plaster or digital models. ICON scores performed on computer-based models appear to be as accurate and reliable as ICON scores on plaster models.

Ontologies and Methods for Interoperability of Engineering Analysis Models (EAMS) in an E-Design Environment

ABSTRACT ONTOLOGIES AND METHODS FOR INTEROPERABILITY OF ENGINEERING ANALYSIS MODELS (EAMS) IN AN E-DESIGN ENVIRONMENT SEPTEMBER 2007 NEELIMA KANURI, B.S., BIRLA INSTITUTE OF TECHNOLOGY AND SCIENCES PILANI INDIA M.S., UNIVERSITY OF MASSACHUSETTS AMHERST Directed by: Professor Ian Grosse Interoperability is the ability of two or more systems to exchange and reuse information efficiently. This thesis presents new techniques for interoperating engineering tools using ontologies as the basis for representing, visualizing, reasoning about, and securely exchanging abstract engineering knowledge between software systems. The specific engineering domain that is the primary focus of this report is the modeling knowledge associated with the development of engineering analysis models (EAMs). This abstract modeling knowledge has been used to support integration of analysis and optimization tools in iSIGHT FD , a commercial engineering environment. ANSYS , a commercial FEA tool, has been wrapped as an analysis service available inside of iSIGHT-FD. Engineering analysis modeling (EAM) ontology has been developed and instantiated to form a knowledge base for representing analysis modeling knowledge. The instances of the knowledge base are the analysis models of real world applications. To illustrate how abstract modeling knowledge can be exploited for useful purposes, a cantilever I-Beam design optimization problem has been used as a test bed proof-of-concept application. Two distinct finite element models of the I-beam are available to analyze a given beam design- a beam-element finite element model with potentially lower accuracy but significantly reduced computational costs and a high fidelity, high cost, shell-element finite element model. The goal is to obtain an optimized I-beam design at minimum computational expense. An intelligent KB tool was developed and implemented in FiPER . This tool reasons about the modeling knowledge to intelligently shift between the beam and the shell element models during an optimization process to select the best analysis model for a given optimization design state. In addition to improved interoperability and design optimization, methods are developed and presented that demonstrate the ability to operate on ontological knowledge bases to perform important engineering tasks. One such method is the automatic technical report generation method which converts the modeling knowledge associated with an analysis model to a flat technical report. The second method is a secure knowledge sharing method which allocates permissions to portions of knowledge to control knowledge access and sharing. Both the methods acting together enable recipient specific fine grain controlled knowledge viewing and sharing in an engineering workflow integration environment, such as iSIGHT-FD. These methods together play a very efficient role in reducing the large scale inefficiencies existing in current product design and development cycles due to poor knowledge sharing and reuse between people and software engineering tools. This work is a significant advance in both understanding and application of integration of knowledge in a distributed engineering design framework.

EFFECTS OF INFORMATION DISPLAY ON THE CONSTRUCTION OF CLINICIAN MENTAL MODELS

Objective: To determine how a clinician’s background knowledge, their tasks, and displays of information interact to affect the clinician’s mental model. Design: Repeated Measure Nested Experimental Design Population, Sample, Setting: Populations were gastrointestinal/internal medicine physicians and nurses within the greater Houston area. A purposeful sample of 24 physicians and 24 nurses were studied in 2003. Methods: Subjects were randomized to two different displays of two different mock medical records; one that contained highlighted patient information and one that contained non-highlighted patient information. They were asked to read and summarize their understanding of the patients aloud. Propositional analysis was used to understand their comprehension of the patients. Findings: Different mental models were found between physicians and nurses given the same display of information. The information they shared was very minor compared to the variance in their mental models. There was additionally more variance within the nursing mental models than the physician mental models given different displays of the same information. Statistically, there was no interaction effect between the display of information and clinician type. Only clinician type could account for the differences in the clinician comprehension and thus their mental models of the cases. Conclusion: The factors that may explain the variance within and between the clinician models are clinician type, and only in the nursing group, the use of highlighting.

Finite element analyses of human vertebral bodies embedded in polymethylmethalcrylate or loaded via the hyperelastic intervertebral disc models provide equivalent predictions of experimental strength

Quantitative computer tomography (QCT)-based finite element (FE) models of vertebral body provide better prediction of vertebral strength than dual energy X-ray absorptiometry. However, most models were validated against compression of vertebral bodies with endplates embedded in polymethylmethalcrylate (PMMA). Yet, loading being as important as bone density, the absence of intervertebral disc (IVD) affects the strength. Accordingly, the aim was to assess the strength predictions of the classic FE models (vertebral body embedded) against the in vitro and in silico strengths of vertebral bodies loaded via IVDs. High resolution peripheral QCT (HR-pQCT) were performed on 13 segments (T11/T12/L1). T11 and L1 were augmented with PMMA and the samples were tested under a 4° wedge compression until failure of T12. Specimen-specific model was generated for each T12 from the HR-pQCT data. Two FE sets were created: FE-PMMA refers to the classical vertebral body embedded model under axial compression; FE-IVD to their loading via hyperelastic IVD model under the wedge compression as conducted experimentally. Results showed that FE-PMMA models overestimated the experimental strength and their strength prediction was satisfactory considering the different experimental set-up. On the other hand, the FE-IVD models did not prove significantly better (Exp/FE-PMMA: R²=0.68; Exp/FE-IVD: R²=0.71, p=0.84). In conclusion, FE-PMMA correlates well with in vitro strength of human vertebral bodies loaded via real IVDs and FE-IVD with hyperelastic IVDs do not significantly improve this correlation. Therefore, it seems not worth adding the IVDs to vertebral body models until fully validated patient-specific IVD models become available.

Apoptosis of hippocampal neurons in organotypic slice culture models: direct effect of bacteria revisited

Neurons of the hippocampal dentate gyrus selectively undergo programmed cell death in patients suffering from bacterial meningitis and in experimental models of pneumococcal meningitis in infant rats. In the present study, a membrane-based organotypic slice culture system of rat hippocampus was used to test whether this selective vulnerability of neurons of the dentate gyrus could be reproduced in vitro. Apoptosis was assessed by nuclear morphology (condensed and fragmented nuclei), by immunochemistry for active caspase-3 and deltaC-APP, and by proteolytic caspase-3 activity. Co-incubation of the cultures with live pneumococci did not induce neuronal apoptosis unless cultures were kept in partially nutrient-deprived medium. Complete nutrient deprivation alone and staurosporine independently induced significant apoptosis, the latter in a dose-response way. In all experimental settings, apoptosis occurred preferentially in the dentate gyrus. Our data demonstrate that factors released by pneumococci per se failed to induce significant apoptosis in vitro. Thus, these factors appear to contribute to a multifactorial pathway, which ultimately leads to neuronal apoptosis in bacterial meningitis.

Assessment of Skill and Portability in Regional Marine Biogeochemical Models: Role of Multiple Planktonic Groups

Application of biogeochemical models to the study of marine ecosystems is pervasive, yet objective quantification of these models' performance is rare. Here, 12 lower trophic level models of varying complexity are objectively assessed in two distinct regions (equatorial Pacific and Arabian Sea). Each model was run within an identical one-dimensional physical framework. A consistent variational adjoint implementation assimilating chlorophyll-a, nitrate, export, and primary productivity was applied and the same metrics were used to assess model skill. Experiments were performed in which data were assimilated from each site individually and from both sites simultaneously. A cross-validation experiment was also conducted whereby data were assimilated from one site and the resulting optimal parameters were used to generate a simulation for the second site. When a single pelagic regime is considered, the simplest models fit the data as well as those with multiple phytoplankton functional groups. However, those with multiple phytoplankton functional groups produced lower misfits when the models are required to simulate both regimes using identical parameter values. The cross-validation experiments revealed that as long as only a few key biogeochemical parameters were optimized, the models with greater phytoplankton complexity were generally more portable. Furthermore, models with multiple zooplankton compartments did not necessarily outperform models with single zooplankton compartments, even when zooplankton biomass data are assimilated. Finally, even when different models produced similar least squares model-data misfits, they often did so via very different element flow pathways, highlighting the need for more comprehensive data sets that uniquely constrain these pathways.